Riverbank Erosion in the Bengal Delta: An Integrated Perspective 3031470095, 9783031470097

Table of contents :
Foreword
Preface
Scientific Notations
Conversion Table
Length
Area
Volume
Weight
About the Book
Contents
About the Authors
Abbreviations
List of Figures
List of Tables
PartPart10005730123
Chapter 1: Riverbank Erosion: Basic Concepts and Approaches
1.1 Conceptual Outlook of Riverbank Erosion
1.2 Historical Perspective of Bank Erosion Hazard Studies
1.2.1 Trajectory of Bank Erosion Research
1.2.2 Approaches to Bank Erosion Study
1.3 Dimensions of Riverbank Erosion Research
1.4 Interdisciplinary Nature of Riverbank Erosion
1.5 Scales in Riverbank Erosion Study
References
Chapter 2: Context of Riverbank Erosion
2.1 Backdrop
2.2 Global Perspective on Riverbank Erosion
2.3 Regional Perspective on River Bank Erosion in the Bengal Delta
2.4 The State of the Art of Bank Erosion Research in the Bengal Delta
2.5 Present Study: Needs and Focus
References
PartPart20005730124
Chapter 3: Riverbank Erosion: A Natural Process
3.1 Riverbank Erosion: A Natural Geoecological Process
3.2 Types and Mechanisms of Bank Erosion
3.2.1 Mechanism of Bank Erosion: World Scenario
3.2.2 Bank Erosion Scenario of Bengal Delta
3.3 Riverbank Erosion Factors
3.3.1 Erodibility Factors
3.3.2 Erosivity Factors
3.3.2.1 Erosivity Under Monsoon Regime
3.3.2.2 Tidal Upsurge and Storm Surge
3.3.2.3 Variable River Regime
3.4 Measurement of Riverbank Erosion
3.4.1 Field Techniques
3.4.1.1 Erosion Pin
3.4.1.2 Photo Electronic Erosion Pin (PEEP) and PEET-3T
3.4.1.3 Total Station and Terrestrial Laser Scanner
3.4.2 Existing Models on River Bank Erosion
3.4.2.1 Bank Assessment of Non-point Source Consequence of Sediment (BANCS)
3.4.2.2 The Bank Stability and Toe Erosion Model (BSTEM)
3.4.2.3 The Bank Stability Model (BSM)
3.4.2.4 Toe Erosion Model (TEM)
3.4.2.5 Dynamic SedNet Stream Bank Erosion Model
3.4.2.6 Numerical Modelling Using DSAS Model
3.4.2.7 Generalized Model of Quantitative Assessment of River Bank Erosion Across the Cross-Sections
3.4.3 Empirical Measurements of Bank Erosion
3.4.3.1 Bankline Shifting Using DSAS Model in the Bengal Delta
3.4.3.2 Quantitative Assessment of Bank Erosion Along the Cross Sections of Bhagirathi River
References
Chapter 4: Riverbank Erosion: A Human-Induced Process
4.1 Regulated River Regime and Bank Erosion
4.1.1 Farakka Barrage Project: A Mega-scale Intervention
4.1.2 Decrease of Lean Period Discharge in the Post-Farakka Period and Bank Erosion in Bangladesh
4.1.3 Increase of Lean Period Discharge in the Post-Farakka Period and Bank Erosion in India
4.1.4 Fluctuation in River Regime Through Controlled Hydrology
4.2 Land Use and Cover Changes and Bank Erosion
4.2.1 Impact of Bank Erosion on Land Use and Cover Changes
4.2.1.1 Basin-Scale Analysis
4.2.1.2 Site-Specific Analysis
4.2.2 Impact of Land Use on Channel Instability and Bank Erosion
4.3 Other Anthropogenic Drivers of Bank Erosion
4.3.1 Brickfields and Sediment Flux
4.3.2 Road Stream Crossing and Channel Changes
4.3.3 Guide Bank and Sedimentation
4.3.4 Vessel Movements and Bank Failure
References
PartPart30005730125
Chapter 5: Riverbank Erosion and Channel Morphology
5.1 Channel Planform Changes
5.1.1 Channel Oscillation and Meandering in Bengal Basin
5.1.1.1 Oscillatory Behaviour and Meander Deformation
5.1.1.2 Stream Meandering and Sinuosity
5.1.2 Stream Meandering and Meander Geometry for the Bhagirathi River
5.1.2.1 Pattern of Meandering
5.1.2.2 Geometry of Stream Meandering
5.1.3 Channel Braiding in the Bengal Basin
5.1.3.1 General Nature of Braiding Indices
5.1.3.2 Case Studies from Bengal Basin
5.2 Channel Cross-sectional Changes
5.2.1 Channel Geometry
5.2.1.1 Width-Depth Ratio
5.2.1.2 Width Index
5.2.1.3 Depth Index
5.2.1.4 Channel Efficiency Index
5.2.2 Analysis of Channel Asymmetry
5.2.2.1 Measuring Channel Asymmetry
5.2.2.2 Pattern of Asymmetry Indices
References
Chapter 6: Economic Vulnerabilities Induced by Riverbank Erosion
6.1 Introduction
6.2 Conceptual Framework on Resource Base, Economy, and Livelihood
6.2.1 Resource Base and Economy
6.2.2 Shifting of Economic Activity
6.2.3 Rural Livelihood and Its Change
6.3 Change in the Asset Profile
6.3.1 Nature of Land Loss
6.3.2 Loss of Agricultural and Settlement Land
6.3.3 Bank Erosion and Displacement
6.3.4 Selling of Properties and Assets
6.4 Change in Income Portfolio
6.4.1 Sources of Income
6.4.2 Distribution of Income
6.5 Poverty Assessment
6.5.1 Techniques for Measuring Poverty
6.5.1.1 Head Count Index
6.5.1.2 Poverty Gap Index
6.5.1.3 Poverty Severity Index
6.5.2 Analysis of Poverty
6.6 Occupational Change and Livelihood Diversification
6.6.1 Nature of Diversification
6.6.2 Measurement of Diversification
6.6.2.1 Inverse Herfindahl-Hirschman Index
6.6.2.2 Individual Occupational Diversification Index
6.6.3 Assessment of Factors
6.7 Multivariate Analysis of Livelihood Vulnerability
6.7.1 Variable-Wise Analysis (R- mode Analysis)
6.7.2 Region-Wise Analysis (Q-mode Analysis)
6.7.3 Livelihood Vulnerability Among Various Income Groups
6.8 Impact on Agricultural Activities
6.8.1 Agriculture in West Bengal
6.8.1.1 Cropping Intensity
6.8.1.2 Crop Diversity
6.8.1.3 Agricultural Productivity
6.8.1.4 Commercialization of Agriculture
6.8.1.5 Critical Appreciation of Mainland and Charland Agriculture in West Bengal and Bangladesh
6.9 Recent Changes in the Economic Landscape
References
Chapter 7: Social Instabilities Induced by Riverbank Erosion
7.1 Backdrop
7.2 Changes in Social Institutions
7.2.1 Family
7.2.2 Kinship
7.2.3 Education
7.2.4 Healthcare
7.2.5 Government
7.3 Social Processes and Social Relation in Hazardous Space
7.3.1 Measuring the Social Processes
7.3.2 Pattern of Social Processes
7.3.2.1 Intraindividual Processes
7.3.2.2 Interpersonal Processes
7.3.2.3 Intergroup Processes
7.3.2.4 Group Processes
7.3.3 Association of Social Processes
7.4 Social Psychological Effects of Bank Erosion Hazard
7.5 Social Psychology of Desire
7.6 Emic and Etic Perspectives of Bank Erosion
7.6.1 Perception of Women
7.6.2 Perception of Economic Migrants
7.6.3 Perception of Permanent Migrants
7.6.4 Perception of School Teachers Coming from Outside (Etic Perspective)
7.6.5 Perception of Outside People and Relatives (Etic Perspective)
7.7 Emergence of Charland and Critical Social Process
7.7.1 Backdrop and Rationale
7.7.2 Study Design
7.7.3 Study Findings and Analysis
7.7.3.1 Evolution of Mid-Channel Bar into the Bank-Attached Bar
7.7.3.2 Evolution of Char and Social Instability
References
PartPart40005730126
Chapter 8: Coping Strategies: Towards a Resilient Society
8.1 Swimming Against the Tide
8.2 Existing Strategies at the Individual and Community Level
8.2.1 Individual and Community Initiatives in West Bengal
8.2.2 Individual and Community Initiatives in Bangladesh
8.3 Controlling Measures (Engineering)
8.3.1 Civil Engineering Measures
8.3.1.1 Major Civil Engineering Structures
8.3.1.2 Civil Engineering in West Bengal
8.3.1.3 Civil Engineering in Bangladesh
8.3.2 Bio-engineering/Bio-technical Measures
8.4 Alternative Mitigation Measures (Social Engineering): Examples from West Bengal and Bangladesh
8.4.1 In-Situ Models
8.4.1.1 Matiari Model - Non-land-Based Household Manufacturing
8.4.1.2 Common Property Resource Management
8.4.1.3 Development of Indigenous Small-Scale and Cottage Industry
8.4.2 Ex-Situ Models
8.4.2.1 Model of Labour Migration
8.4.2.2 Densification of Settlement
8.5 Concluding Notes
References
Chapter 9: Future Speculations and Challenges
9.1 Perspectives of Future Speculations and Challenges
9.2 Climate Change, Sea Level Rise, and Bank Erosion
9.3 Sociocultural Changes and Bank Erosion
9.4 Future Speculation About the Livelihood Strategies
9.5 Concluding Notes
References
Glossary
Index

Citation preview

Springer Geography

Aznarul Islam Sanat Kumar Guchhait

Riverbank Erosion in the Bengal Delta An Integrated Perspective

Springer Geography Advisory Editors Mitja Brilly, Faculty of Civil and Geodetic Engineering, University of Ljubljana, Ljubljana, Slovenia Richard A. Davis, Department of Geology, School of Geosciences, University of South Florida, Tampa, FL, USA Nancy Hoalst-Pullen, Department of Geography and Anthropology, Kennesaw State University, Kennesaw, GA, USA Michael Leitner, Department of Geography and Anthropology, Louisiana State University, Baton Rouge, LA, USA Mark W. Patterson, Department of Geography and Anthropology, Kennesaw State University, Kennesaw, GA, USA Márton Veress, Department of Physical Geography, University of West Hungary, Szombathely, Hungary

The Springer Geography series seeks to publish a broad portfolio of scientific books, aiming at researchers, students, and everyone interested in geographical research. The series includes peer-reviewed monographs, edited volumes, textbooks, and conference proceedings. It covers the major topics in geography and geographical sciences including, but not limited to: Economic Geography, Landscape and Urban Planning, Urban Geography, Physical Geography and Environmental Geography. Springer Geography — now indexed in Scopus

Aznarul Islam • Sanat Kumar Guchhait

Riverbank Erosion in the Bengal Delta An Integrated Perspective

Aznarul Islam Department of Geography Aliah University Kolkata, West Bengal, India

Sanat Kumar Guchhait Department of Geography The University of Burdwan Purba Bardhaman, West Bengal, India

ISSN 2194-3168 (electronic) ISSN 2194-315X Springer Geography ISBN 978-3-031-47009-7 ISBN 978-3-031-47010-3 (eBook) https://doi.org/10.1007/978-3-031-47010-3 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Paper in this product is recyclable.

Panoramic view of bank erosion along the left bank of the Bhagirathi River, West Bengal, India (Field Photograph, 2013)

This book is dedicated to the victims of bank erosion hazards of the Ganga-BrahmaputraMeghna delta in the Indo-Bangladesh region whose pains and tears are reflected with the insightful investigation.

Foreword

It was my immense pleasure to get an invitation from Dr. Aznarul Islam and Prof. Sanat Kumar Guchhait to write a foreword for the book Riverbank Erosion in the Bengal Delta: An Integrated Perspective. Riverbank erosion, though a natural fluvial process, sometimes becomes hazardous to the people and society of the active fluvial corridors of the world. The issue of bank erosion is very severe in the Ganga-Brahmaputra-Meghna Delta. Therefore, the present book authored by Dr. Aznarul Islam and Prof. Sanat Kumar Guchhait is a very timely and appropriate attempt to reveal the dynamics of riverbank erosion as a process and its effects on society and the economy. The systematic attempt to explore all those issues from the Bengal Delta (West Bengal and Bangladesh) is really a pioneering attempt in the concerned field. This book is composed of nine chapters including introduction and future speculations. The holistic and integrated treatment adopted in this book really uncovers many significant facts of the bank erosion research in both India and Bangladesh The lucid treatment of the subject and pictorial description of the complex issues are really amazing for the readers. Though bank erosion of the Bengal Delta is given due emphasis, the piece of the work will serve the geographers, earth scientists, regional planners, hydrologists, social scientists, and various stakeholders of the concerned regions. This book will also be helpful for all types of readers and researchers who need to know the river bank erosion from a systematic approach. The processes associated with riverbank erosions are substantial with good case studies, field, and geo-spatial data in an integrated GIS environment. There are many important approaches, such as the “desirable aspect of riverbank erosion” and “social fusion and fission model” in the wake of bank erosion and char development that will certainly attract a wider audience from diverse disciplines.

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Foreword

I am pretty sure that this kind of authoritative book on the subject will make a significant contribution to river bank erosion research and future researchers will be keen to pursue their own research in many dimensions of the books. Chairman, Department of Geography & Environment, Director, Disaster Research Training and Management Centre, University of Dhaka, Dhaka, Bangladesh Secretary, Bangladesh Geographical Society (BGS), Dhaka, Bangladesh

M. Shahidul Islam

Preface

Riverbank erosion is commonly found in the floodplains and deltas of the world. However, the issue of bank erosion and its related risk often expressed as the agrarian decline is vital in the Bengal Delta because this region contains a huge population that continually exerts pressure on natural systems. Thus, on the one hand, the people settling along the river banks for life and livelihood disrupt the natural processes of fluvial systems, and on the other, they often suffer from land loss and the state of being environmental refugees. Bank erosion is linked to channel accretion and bar growth which also becomes the ostensible source of social and pathological issues, especially around the ownership of newly elevated land. Thus, social transformation regarding bank erosion is addressed in the context of tropical countries like India and Bangladesh. Moreover, to save from bank erosion people have adopted some hard engineering measures which not only require huge costs but also often become futile in the face of furious nature. Hence, the book composed of four parts and nine chapters has addressed riverbank erosion as a process and the impact of riverbank erosion on fluvial, economic, and social landscapes with a keen intention to provide some meaningful insights on management strategies and future bank erosion scenarios. The Bengal Delta, the most populated region of the world, exerts huge pressure on land. However, there is no single book produced to date on the bank erosion of the Bengal Delta for a holistic purpose. This book intends to fill out the long-felt gap in this region. Therefore, the book will not only cater to the need of the students at the undergraduate and graduate levels in earth sciences, geography, and environmental sciences but also fill up the gap of the regional planners and decision-makers in comprehending the complexity of the Bengal Delta. We are very much thankful to the respondents during the field survey and other stakeholders directly and indirectly associated with the data collection process. We kindly acknowledge the active and overwhelming cooperation of our laboratory members and students like Dr. Biplab Sarkar, Susmita Ghosh, Suman Deb Barman, Abdur Rahman, Md. Mofizul Hoque, Dr. Sadik Mahammad, and Sekh Mohinuddin for preparing some maps and diagrams. We are also equally thankful to our family xi

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Preface

members for their support and sacrifice throughout the entire journey. Moreover, as a larger part of the book is from the MPhil and PhD thesis of Dr Aznarul Islam, all the concerned persons and institutions from Burdwan University, Aliah University, and Barasat Government College are duly acknowledged. We also show our deep gratitude to all the other persons who promptly replied to our request for study materials and data support. We sincerely acknowledge those international and national publishers (e.g. Springer Nature, Elsevier, Taylor and Francis, and the University Press Limited of Bangladesh), organizations and individuals who were kind enough to grant our request for permission to reuse/reproduce several figures and tables in this present book. We are grateful to Dieter Merkle Vice President, Dr Guido Zosimo-Landolfo, Editorial Director/ Asset Manager of Springer Nature Switzerland AG, Aaron Schiller, Associate Editor Earth Sciences, Geography and Environment for signing the agreement on this project and for providing the opportunity of using their prestigious pages for manuscripts of our eminent authors. We are also grateful to the production team for their meticulous efforts to publish the book as correctly as possible. We hope the outcomes of this volume will flood the thoughts of scholars, faculties, planners, and stakeholders returning us the apt worth. Kolkata, West Bengal, India Purba Bardhaman, West Bengal, India

Aznarul Islam Sanat Kumar Guchhait

Scientific Notations

A′ A A* A1 A2 am Am Aw BI Cl d max d′ d D50 FmI Gi Id Iw Lc Lm P P0 P1 P2 Q Qm r R R2

Area between Lc and Lm Cross-sectional area First measure of Knighton Second measure of Knighton Third measure of Knighton Amplitude Peak amplitude First measure of Das and Islam Braiding index Channel length Maximum depth Expected depth Mean channel depth Median diameter Meander form index Gini coefficient Depth index Width index Channel centre line Median area line Wetted perimeter Head count index Poverty gap index Poverty severity index Discharge Maximum discharge Co-efficient of correlation Hydraulic radius Co-efficient of determination xiii

xiv

rc Re SmI v w w′ z ϴa ϴd λ ν ψ ω

Scientific Notations

Radius of curvature Reynolds number Meander shape index Average velocity Channel width Expected width Poverty line Arc angle Direction angle Wavelength Kinematic viscosity of fluid Annual rate of shifting Net annual rate of erosion/accretion

Conversion Table

Length 1 Kilometer= 0.6214 Mile 1 Centimeter= 0.3937 Inch

Area 1 Hectare = 2.4711 Acre 1 Acre = 0.4047 Hectare 1 Acre = 3.025 Bigha 1 Hectare = 7.4751 Bigha 1 Acre = 4047 Sq. Meter 1 Acre = 100 Satak 1 Acre = 43560 Sq. Feet 1 Bigha = 20 Katha

Volume 1 Cumec=35.235 Cusecs 1 Acre-foot = 1233.48 Cubic Meter

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Weight 1 Quintal = 100 Kilogram 1 Maund = 40 Kilogram

Conversion Table

About the Book

The severity of riverbank erosion and concern of the people in Nadia District along the left bank of the Bhagirathi River, India (Field photo, 2012)

In the light of present academic discourse, researches on contemporary global environmental problems are not only explored from hazard perspective, rather books and valuable research articles are often conceptualized and contextualized with an integrated perspective. This book, therefore, not only examines the river bank erosion dynamics and related hazard perspective or not only it grasps the social perspective of bank erosion hazards in the context of the Ganga-BrahmaputraMeghna delta, rather a reciprocity between physical dynamics and social process. Hence, this book intends to portray the concept and dynamics of riverbank erosion and its rationale in the realm of environmental and social problems along with the strategies for managing the hazards. xvii

Contents

Part I

Riverbank Erosion: Concepts, Approaches, and Context

1

Riverbank Erosion: Basic Concepts and Approaches . . . . . . . . . . . . 1.1 Conceptual Outlook of Riverbank Erosion . . . . . . . . . . . . . . . . . . 1.2 Historical Perspective of Bank Erosion Hazard Studies . . . . . . . . . 1.2.1 Trajectory of Bank Erosion Research . . . . . . . . . . . . . . . . 1.2.2 Approaches to Bank Erosion Study . . . . . . . . . . . . . . . . . . 1.3 Dimensions of Riverbank Erosion Research . . . . . . . . . . . . . . . . . 1.4 Interdisciplinary Nature of Riverbank Erosion . . . . . . . . . . . . . . . 1.5 Scales in Riverbank Erosion Study . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3 3 6 6 7 11 13 13 17

2

Context of Riverbank Erosion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Backdrop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Global Perspective on Riverbank Erosion . . . . . . . . . . . . . . . . . . . 2.3 Regional Perspective on River Bank Erosion in the Bengal Delta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 The State of the Art of Bank Erosion Research in the Bengal Delta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Present Study: Needs and Focus . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

23 23 24

Part II 3

26 31 32 35

Riverbank Erosion: Process Approach

Riverbank Erosion: A Natural Process . . . . . . . . . . . . . . . . . . . . . . . 3.1 Riverbank Erosion: A Natural Geoecological Process . . . . . . . . . . 3.2 Types and Mechanisms of Bank Erosion . . . . . . . . . . . . . . . . . . . 3.2.1 Mechanism of Bank Erosion: World Scenario . . . . . . . . . . 3.2.2 Bank Erosion Scenario of Bengal Delta . . . . . . . . . . . . . . .

43 43 45 49 49

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Contents

3.3

4

Riverbank Erosion Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.1 Erodibility Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.2 Erosivity Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Measurement of Riverbank Erosion . . . . . . . . . . . . . . . . . . . . . . . 3.4.1 Field Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4.2 Existing Models on River Bank Erosion . . . . . . . . . . . . . . 3.4.3 Empirical Measurements of Bank Erosion . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

54 55 56 64 66 68 76 93

Riverbank Erosion: A Human-Induced Process . . . . . . . . . . . . . . . . 4.1 Regulated River Regime and Bank Erosion . . . . . . . . . . . . . . . . . 4.1.1 Farakka Barrage Project: A Mega-scale Intervention . . . . . 4.1.2 Decrease of Lean Period Discharge in the Post-Farakka Period and Bank Erosion in Bangladesh . . . . . . . . . . . . . . 4.1.3 Increase of Lean Period Discharge in the Post-Farakka Period and Bank Erosion in India . . . . . . . . . . . . . . . . . . . 4.1.4 Fluctuation in River Regime Through Controlled Hydrology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Land Use and Cover Changes and Bank Erosion . . . . . . . . . . . . . 4.2.1 Impact of Bank Erosion on Land Use and Cover Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Impact of Land Use on Channel Instability and Bank Erosion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Other Anthropogenic Drivers of Bank Erosion . . . . . . . . . . . . . . . 4.3.1 Brickfields and Sediment Flux . . . . . . . . . . . . . . . . . . . . . 4.3.2 Road Stream Crossing and Channel Changes . . . . . . . . . . . 4.3.3 Guide Bank and Sedimentation . . . . . . . . . . . . . . . . . . . . . 4.3.4 Vessel Movements and Bank Failure . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

99 99 100

Part III 5

103 104 106 109 109 127 130 130 133 135 136 140

Riverbank Erosion: Form and Vulnerability Approach

Riverbank Erosion and Channel Morphology . . . . . . . . . . . . . . . . . . 5.1 Channel Planform Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.1 Channel Oscillation and Meandering in Bengal Basin . . . . 5.1.2 Stream Meandering and Meander Geometry for the Bhagirathi River . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.3 Channel Braiding in the Bengal Basin . . . . . . . . . . . . . . . . 5.2 Channel Cross-sectional Changes . . . . . . . . . . . . . . . . . . . . . . . . 5.2.1 Channel Geometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.2 Analysis of Channel Asymmetry . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

147 147 147 157 180 188 188 193 197

Contents

6

7

Economic Vulnerabilities Induced by Riverbank Erosion . . . . . . . . . 6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Conceptual Framework on Resource Base, Economy, and Livelihood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.1 Resource Base and Economy . . . . . . . . . . . . . . . . . . . . . . 6.2.2 Shifting of Economic Activity . . . . . . . . . . . . . . . . . . . . . 6.2.3 Rural Livelihood and Its Change . . . . . . . . . . . . . . . . . . . . 6.3 Change in the Asset Profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.1 Nature of Land Loss . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.2 Loss of Agricultural and Settlement Land . . . . . . . . . . . . . 6.3.3 Bank Erosion and Displacement . . . . . . . . . . . . . . . . . . . . 6.3.4 Selling of Properties and Assets . . . . . . . . . . . . . . . . . . . . 6.4 Change in Income Portfolio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4.1 Sources of Income . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4.2 Distribution of Income . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5 Poverty Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5.1 Techniques for Measuring Poverty . . . . . . . . . . . . . . . . . . 6.5.2 Analysis of Poverty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6 Occupational Change and Livelihood Diversification . . . . . . . . . . 6.6.1 Nature of Diversification . . . . . . . . . . . . . . . . . . . . . . . . . 6.6.2 Measurement of Diversification . . . . . . . . . . . . . . . . . . . . 6.6.3 Assessment of Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.7 Multivariate Analysis of Livelihood Vulnerability . . . . . . . . . . . . . 6.7.1 Variable-Wise Analysis (R- mode Analysis) . . . . . . . . . . . 6.7.2 Region-Wise Analysis (Q-mode Analysis) . . . . . . . . . . . . . 6.7.3 Livelihood Vulnerability Among Various Income Groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.8 Impact on Agricultural Activities . . . . . . . . . . . . . . . . . . . . . . . . . 6.8.1 Agriculture in West Bengal . . . . . . . . . . . . . . . . . . . . . . . 6.9 Recent Changes in the Economic Landscape . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Social Instabilities Induced by Riverbank Erosion . . . . . . . . . . . . . . 7.1 Backdrop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Changes in Social Institutions . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.1 Family . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.2 Kinship . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.3 Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.4 Healthcare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.5 Government . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 Social Processes and Social Relation in Hazardous Space . . . . . . . 7.3.1 Measuring the Social Processes . . . . . . . . . . . . . . . . . . . . 7.3.2 Pattern of Social Processes . . . . . . . . . . . . . . . . . . . . . . . . 7.3.3 Association of Social Processes . . . . . . . . . . . . . . . . . . . .

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201 201 201 202 202 203 204 204 206 209 213 214 215 218 221 222 223 223 225 227 229 230 230 232 233 235 235 245 246 249 249 249 250 250 252 253 254 255 255 257 262

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Contents

7.4 7.5 7.6

Social Psychological Effects of Bank Erosion Hazard . . . . . . . . . . Social Psychology of Desire . . . . . . . . . . . . . . . . . . . . . . . . . . . . Emic and Etic Perspectives of Bank Erosion . . . . . . . . . . . . . . . . . 7.6.1 Perception of Women . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.6.2 Perception of Economic Migrants . . . . . . . . . . . . . . . . . . . 7.6.3 Perception of Permanent Migrants . . . . . . . . . . . . . . . . . . 7.6.4 Perception of School Teachers Coming from Outside (Etic Perspective) . . . . . . . . . . . . . . . . . . . . . . . . 7.6.5 Perception of Outside People and Relatives (Etic Perspective) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.7 Emergence of Charland and Critical Social Process . . . . . . . . . . . . 7.7.1 Backdrop and Rationale . . . . . . . . . . . . . . . . . . . . . . . . . . 7.7.2 Study Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.7.3 Study Findings and Analysis . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Part IV 8

9

264 266 268 269 271 272 273 274 276 276 277 277 282

Riverbank Erosion: Management and Futuristic Approach

Coping Strategies: Towards a Resilient Society . . . . . . . . . . . . . . . . . 8.1 Swimming Against the Tide . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 Existing Strategies at the Individual and Community Level . . . . . . 8.2.1 Individual and Community Initiatives in West Bengal . . . . 8.2.2 Individual and Community Initiatives in Bangladesh . . . . . 8.3 Controlling Measures (Engineering) . . . . . . . . . . . . . . . . . . . . . . . 8.3.1 Civil Engineering Measures . . . . . . . . . . . . . . . . . . . . . . . 8.3.2 Bio-engineering/Bio-technical Measures . . . . . . . . . . . . . . 8.4 Alternative Mitigation Measures (Social Engineering): Examples from West Bengal and Bangladesh . . . . . . . . . . . . . . . . 8.4.1 In-Situ Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.2 Ex-Situ Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5 Concluding Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

287 287 288 288 290 292 293 297

Future Speculations and Challenges . . . . . . . . . . . . . . . . . . . . . . . . . 9.1 Perspectives of Future Speculations and Challenges . . . . . . . . . . . 9.2 Climate Change, Sea Level Rise, and Bank Erosion . . . . . . . . . . . 9.3 Sociocultural Changes and Bank Erosion . . . . . . . . . . . . . . . . . . . 9.4 Future Speculation About the Livelihood Strategies . . . . . . . . . . . 9.5 Concluding Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

317 317 318 319 321 322 323

299 300 308 313 313

Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325 Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337

About the Authors

Aznarul Islam (b. 1987) completed Master of Science in Geography from Kalyani University, West Bengal, and MPhil and PhD in Geography from the University of Burdwan, West Bengal, India. He is currently an Assistant Professor in the Department of Geography, Aliah University, Kolkata, India. Previously he was an Assistant Professor (West Bengal Education Service) in the Department of Geography, Barasat Government College, West Bengal. He has already published more than 60 research papers in different journals of national and international repute. He has already edited nine books and contributed more than 20 book chapters in edited volumes and conference proceedings. He has presented papers in more than 25 national and international seminar and conferences. He has been performing the role of editor and reviewer in various national and international journals. He is a life member of the Indian Geographical Foundation (IGF), Kolkata, and the National Association of Geographers, India (NAGI), New Delhi. To date, he has successfully supervised more than 40 dissertations on various topics of geomorphology at the Master’s level. He has already supervised two PhD students in Geomorphology and Hydrology and another three are pursuing their research under his guidance. He has completed one ICSSR (Govt. of India) Major research Project on Assessment of Socio- Economic Vulnerability of Flood Victims and Preparation of CommunityBased Disaster Management Plan Using Social Engineering: A Study of Murshidabad District, West Bengal. He is acting as the Principal Investigator in the DST-SERB SURE (Govt. of India) research Project on Spatial Mapping and Modelling of Soil and Groundwater Pollution by Nitrate from Agricultural Fields in the Lower Ganga Delta of West Bengal. His principal area of research includes floods, channel shifting, river bank erosion, river pollution, and water resource management. Sanat Kumar Guchhait (b. 1968) completed his MSc (Geography) in 1993 and PhD in 2005 from the Department of Geography, the University of Burdwan. Prof. Guchhait is currently engaged in teaching in the Department of Geography, the University of Burdwan, West Bengal, India, since 2001. His area of interest is xxiii

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About the Authors

environmental geography, social geography, and philosophy of geography. In conducting research and publication of books, he prefers to enquire in the tune of the environment, society and livelihood. Environment and Forest, Ecourbanism, Enclave exchange, Traditional Livelihood, and ecological knowledge of tribal society have occupied the domain of his research in the last 10 years. He has completed UGC Major Research Project on soil erosion, conservation, and forest ecology in laterite landscape. He has successfully supervised 14 doctoral students and published 97 research papers in different peer-reviewed national and international journals and edited books. His recent publication includes Laterites of the Bengal Basin Characterization, Geochronology and Evolution (jointly with S. Ghosh) ISBN 978-3-030-22937-5 (eBook): https://doi.org/10.1007/978-3-03022937-5 from Springer Nature Switzerland AG.

Abbreviations

AER ALOS APL ASTER BANCS BE BEHI BH BPL BSM BSTEM CEGIS CFF COVID-19 CPR CS CST CV CWC DEM DF DL&RO DPS DRIFT DSAS EIA ENSO EPR FBA FBP

Accumulated Excess Run-off Advanced Land Observing Satellite Above Poverty Line Advanced Spaceborne Thermal Emission and Reflection Radiometer Bank Assessment of Non-point Source Consequence of Sediment Bank Erodibility Bank Erosion Hazard Index Bore Hole Below Poverty Line Bank Stability Model The Bank Stability and Toe Erosion Model Centre for Effective Governance of Indian States Chhotanagpur Foot-Hill Fault Coronavirus Disease 2019 Common Property Resource Cross Section Cumulative Successive Total Co-efficient of Variation Central Water Commission Digital Elevation Model Damodar Fault District Land and Land Revenue Office Degree of Phosphorus Saturation Diffuse Reflectance Infrared Fourier Transform Digital Shoreline Analysis System Environmental Impact Assessment El Nino-Southern Oscillation End Point Rate Farakka Barrage Authority Farakka Barrage Project xxv

xxvi

FCC FoS FSTPP GB GBD GBM GIS HHI HSI IMD IOD IWAI KoPT LB LDC LDF LIDAR LMR LPG LRR LULC MABE MC MDC MFF MGNREGA MoU NBS NBSS & LUP NGO NSM OLI PC1 PC2 PCA PDS PRIN RB RRI SD SHG SI SID SRTM

Abbreviations

False Colour Composite Factor of Safety Farakka Super Thermal Power Project Ganga-Brahmaputra Ganga-Brahmaputra Delta Ganga-Brahmaputra-Meghna Geographical Information System Herfindahl-Hirschman Index Hydraulic Sinuosity Index Indian Meteorology Department Indian Ocean Dipole Inland Waterways Authority of India Kolkata Port Trust Left Bank Least Developed Countries Link Discharge Factor Light Detection and Ranging Lower Mekong River Liquefied Petroleum Gas Linear Regression Rate Land Use and Land Cover Mean Annual Bank Erosion Mass Conversion Moderately Developed Countries Medinipur Farakka Fault Mahatma Gandhi National Rural Employment Guarantee Act Memoranda of Understanding Near Bank Stress National Bureau of Soil Survey and Land Use Planning Non-Government Organization Net Shoreline Movement Operational Land Imager First Principal Component Second Principal Component Principal Component Analysis Public Distribution System Principal Right Bank River Research Institute Standard Deviation Self-Help Group Sinuosity Index State Irrigation Department Shuttle Radar Topographic Mission

Abbreviations

SSI STP SWID TC TEM TIRS TLS TM TSI UAV WBI

xxvii

Standard Sinuosity Index Soil Test Phosphorus State Water Investigation Directorate Tropical Cyclone Toe Erosion Model Thermal Infrared Sensor Terrestrial Laser Scanning Sensor Thematic Mapper Topographic Sinuosity Index Unmanned Aerial Vehicles World Bank Institute

List of Figures

Fig. 1.1 Fig. 1.2 Fig. 1.3

Fig. 1.4

Fig. 1.5

Flow of energy for different kinds of erosional processes. (Source: Summerfield, 1991) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Time frame diagram to trace out the trajectory of bank erosion research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Approaches to studying riverbank erosion. (a) Sankey diagram showing the approaches to studying riverbank erosion during 1970–2020. Note: the red band represents the natural approach, the blue band for anthropogenic, the yellow for hazard, and the green for the rational approach which is shown on the left vertical axis. The figure clearly shows the interrelationship among the various approaches portrayed in the previous works. (b) Spatiotemporal development of riverbank erosion research in different continents in different decades using major approaches. (Based on Table S1.1) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Riverbank erosion as a naturally induced process. The chord diagram indicates the share of the different natural trigger factors to induce bank erosion across the world based on the study findings (1970–2020). Note: there are five broad categories of factors inducing riverbank erosion. For example, for flow hydrology, there are 63 works shown using the blue ring. Out of these 63 works, 26 works are concerned with only flow hydrology in relation to riverbank erosion while 15 works are concerned with riverbank erosion in relation to the interplay of flow hydrology and cohesive and non-cohesive riverbank; 11 works focus on flow hydrology and riparian vegetation for bank erosion; 9 works have shown riverbank erosion as an interplay between flow hydrology and storm surges and floods; 2 relates to riverbank erosion in the context of flow hydrology and tectonic movements. (Based on Table S1.2) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Interdisciplinary nature of erosion research . . . . . . . . . . . . . . . . . . . . . . . . .

4 7

8

9 14

xxix

xxx

Fig. 2.1

Fig. 2.2

Fig. 2.3 Fig. 2.4

Fig. 2.5

Fig. 3.1

Fig. 3.2

Fig. 3.3

List of Figures

Locational attributes with major river system and important places of the Ganga-Brahmaputra-Meghna delta (also called as Bengal Delta) . .. . . .. . .. . .. . .. . .. . .. . .. . .. . . .. . .. . .. . .. . .. . .. . .. . .. . . .. . .. . .. . .. . Digital elevation model of the Ganga-Brahmaputra-Meghna delta showing low-lying relief surrounded by highlands on the three sides (Shillong Plateau and Barind tract on the north, Rajmahal hills and Chhotonagpur Plateau on the west and Indo-Burma fold belt on the east) and Bay of Bengal on the south. (Based on SRTM DEM 30 m & USGS Earth Explorer) . . . . . . . . . . Major reference works produced in West Bengal indicating the concentrated nature of works on the Ganga River . . . . . . . . . . . . . Major reference works produced in Bangladesh indicating the concentrated nature of works on the Jamuna River. (Based on Rahman et al., 2022) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Location of the in-depth field investigation in the Bengal Delta. The location of study villages in different zones in selected C.D. blocks in Nadia District, West Bengal, India has been shown . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Framework for alternatives to channel bank infrastructure. Dynamic-process conservation areas protect the linkage between river channels and adjacent landscapes, and provide the highest ecological benefit to riparian ecosystems. The other alternatives provide ecological benefits to the degree that they accommodate the geomorphic processes that sustain them. (Florsheim et al., 2008) . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . Mechanisms of riverbank erosion through diagrams: (a) Shallow slide (from Environment Agency, 1999), (b) Rotational slip (from Environment Agency, 1999), (c) Slab failure (from Environment Agency, 1999), (d) Cantilever failure (from Environment Agency, 1999), (e) Earth flow (from Environment Agency, 1999), (f) Mechanisms of cantilever failure (Ashbridge, 1995), (g) Popout failure (from O’Neill and Kuhns, 1994), (h) Hydraulic failure mechanisms. (From O’Neill & Kuhns, 1994) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lithological composition of the sediments along the Bhagirathi River, (a) location of the boreholes (BH), (b) western and (c) eastern bank lithologs (Note: BH-1 at Ghola, BH-2 at Kobla, BH-3 at Islampur, BH-4 at Vidyanagar, BH-5 at Madhupur, BH-6 at Gotra, BH-7 at Narayanpur, BH-8 at Tatla, and BH-9 at Mayapur; BH-1 to BH-5 from Purba Barddhaman district and BH-6 to BH-9 from Nadia district) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

27

28 29

30

33

46

48

51

List of Figures

Fig. 3.4

Fig. 3.5

Fig. 3.6

Fig. 3.7

Fig. 3.8 Fig. 3.9

Fig. 3.10

Fig. 3.11

Fig. 3.12

Rating curve of the Bhagirathi River, (a) treaty period, (b) normal period (computed from hydrologic data, 2005–2009, CWC, India). Note: GTS stands for Great Trigonometrical Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bank erosion in response to material composition, (a) Bank erosion due to piping (based on Hagerty, 1991b), (b) Stratified stream banks and combination failures along the banks of river Bhagirathi. (Based on Johnson & Stypula, 1993) . . . . . . . . . . . .. . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . Lithological composition along the left bank of Bhagirathi river. (Source: Parua, 1992) (Note: Location of selected study sites – Matiari, Akandanga, Rukunpur, and Char-Kashthasali is shown in Fig. 2.5 in Chap. 2; areas with clayey silt are located in few pockets marked by solid tilted line while other areas are dominated mainly by fine sand shown with dotted tilted lines; vertical pipes with solid lines are the location of the boreholes; offtake is the point where Bhagirathi River bifurcates near Jangipur; Si for silt (%), Sa for sand (%), C for clay (%), and N for Standard Penetration Test value for relative density of soil (N 0–4 very loose, 5–10 loose, 11–30 medium, and 31–50 for dense) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Riverbank composition and nature of erosion. (a) Mixed bank composition, formation of tunnel or piping, cracks and undermining, (b) Soil profile dominated by loose unconsolidated sand in its lower portion often induces combinational failure, (c) Mixed soil profile with clay and silty dominance in the upper portion, (d) Bank erosion by sliding on the bare surface. (Source: Field Photographs, 2013–2015) . . . . . . . . . . . . . . . . . . . . . . . . . . . Discharge hydrograph of river Ajay at Natunhat gauge station, 2000. (Source: River Research Institute, Kolkata, 2000) . . . . . . . . . . Variation in flow and water level at Pateswari of Dudhkumar River, Bangladesh (Note Q for discharge and WL for water level, PWD for public works datum, Bangladesh). (Pal et al. 2017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Typical hydrograph of Bhagirathi-Hooghly system. Note: the arrow indicates the synchronization of the peaks between the Ajay and Bhagirathi Rivers. (Source: Central Water Commission, India) . . . . . . . . . . . . . . . . . . . . . . . . Hjulström curve to indicate the nature of erosion, deposition, and transportation (Source: Hjulström, 1935). Erosion is maximum for medium-grade sediment (0.01 to 1 mm) because beyond the scale sediment will be more finer, i.e., cohesive or coarser, i.e., heavier resisting bank erosion . . . . . . . . . . . D50 of bed materials between Feeder canal to Baladanga. (Source: KoPT, 2003–2009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

xxxi

52

53

56

57 59

59

62

63 66

xxxii

Fig. 3.13

Fig. 3.14

Fig. 3.15 Fig. 3.16

Fig. 3.17

Fig. 3.18

Fig. 3.19

Fig. 3.20

Fig. 3.21

Fig. 3.22

List of Figures

Typical coarse sandy river bed of Ajay, (a) Ramudih, Jharkhand, (b) Natunhat, Mongolkote, West Bengal, 2012. (Source: field photograph, 2012) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Development of instruments for measuring the vertical profile of stream bank. (a) Erosion pins, (b) Total Station, (c) Terrestrial laser scanning. (Source: Myers et al., 2019) . . . . . . . Inputs and output in the BESTEM model and its sequential steps. (Source: Midgley et al., 2012) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Computation of net annual rate of erosion/accretion (ω) and the annual rate of shifting (ψ). (Drawn by the authors, 2015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Channel oscillation along the left bank of the Ganga-Padma River. Sub-captions (a–d) indicate positions of the left bank in 1990, 2000, 2010, and 2020; (e) indicates the superimposed bank lines; (f) EPR along the left bank; (g–i) show the nature of the bank erosion in the upper, middle, and lower stretches of the river . . . . Channel oscillation along the right bank of the Ganga-Padma River. Sub-captions (a–d) indicate positions of the right bank in 1990, 2000, 2010, and 2020; (e) indicates the superimposed bank lines; (f) EPR along the right bank; (g–i) show the nature of the bank erosion in the upper, middle, and lower stretches of the river . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . EPR and LRR along the left and right bank of the River Ganga-Padma, (a) Transect-wise distribution of EPR and LRR, (b) Correlation between EPR and LRR for the studied transects . . . . . .. . . . . . .. . . . . . .. . . . . .. . . . . . .. . . . . . .. . . . . .. . . . . . .. . . . . . .. . . . Channel oscillation along the left bank of the Bhagirathi-Hooghly River. Sub-captions (a–d) indicate positions of the left bank in 1990, 2000, 2010, and 2020; (e) indicates the superimposed bank lines; (f) EPR along the left bank; (g–i) show the nature of the bank erosion in the upper, middle, and lower stretches of the river . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Channel oscillation along the right bank of the BhagirathiHooghly River. Sub-captions (a–d) indicate positions of the right bank in 1990, 2000, 2010, and 2020; (e) indicates the superimposed bank lines; (f) EPR along the right bank; (g–i) show the nature of the bank erosion in the upper, middle, and lower stretches of the river . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . EPR and LRR along the left and right bank of the River Bhagirathi-Hooghly, (a) Transect-wise distribution of EPR and LRR, (b) Correlation between EPR and LRR for the studied transects . . . . . .. . . . . . .. . . . . . .. . . . . .. . . . . . .. . . . . . .. . . . . .. . . . . . .. . . . . . .. . . .

66

67 71

75

77

77

78

80

81

82

List of Figures

Fig. 3.23

Fig. 3.24

Fig. 3.25

Fig. 3.26

Fig. 3.27

Fig. 3.28

Fig. 3.29

Fig. 3.30

Fig. 3.31

Fig. 4.1 Fig. 4.2 Fig. 4.3

Channel oscillation along the left bank of the Brahmaputra River. Sub-captions (a–d) indicate positions of the left bank in 1990, 2000, 2010, and 2020; (e) indicates the superimposed bank lines; (f) EPR along the left bank; (g–i). show the nature of the bank erosion in the upper, middle, and lower stretches of the river . . . . Channel oscillation along the right bank of the Brahmaputra River. Sub-captions (a–d) indicate positions of the right bank in 1990, 2000, 2010, and 2020; (e) indicates the superimposed bank lines; (f) EPR along the right bank; (g–i) show the nature of the bank erosion in the upper, middle, and lower stretches of the river . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . EPR and LRR along the left and right bank of the Brahmaputra River, (a) Transect-wise distribution of EPR and LRR, (b) Correlation between EPR and LRR for the studied transects . . . . . Channel oscillation along the left bank of the Meghna River. Sub-captions (a–d) indicate positions of the left bank in 1990, 2000, 2010, and 2020; (e) indicates the superimposed bank lines; (f) EPR along the left bank; (g–i) show the nature of the bank erosion in the upper, middle, and lower stretches of the river . . . . Channel oscillation along the right bank of the Meghna River. Sub-captions (a–d) indicate positions of the right bank in 1990, 2000, 2010, and 2020; (e) indicates the superimposed bank lines; (f) EPR along the right bank; (g–i) show the nature of the bank erosion in the upper, middle, and lower stretches of the river . . . . EPR and LRR along the left and right bank of the Meghna River, (a) Transect-wise distribution of EPR and LRR, (b) Correlation between EPR and LRR for the studied transects . . . . . . . . . . . . . . . . . . . Bankline shifting analysis. (a) Location of cross section on River Bhagirathi (Source: Hydrographic sheets, KoPT, 1972), (b) Representative cross-sectional profiles for CS 335 to demonstrate the minimum, maximum banking, and range of shifting . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . The U-shaped 2nd-degree polynomial curve showing the relation between rate of erosion and rate of shifting (Computed from hydrographic sheets, KoPT: 1972–2012) . . . . . . . Nature of bankline shifting, (a) Distribution of bank line registering minimum and maximum value. (b) Cumulative successive total indicating the nature of bank oscillation . . . . . . . . . .

xxxiii

83

84

85

86

87

88

89

91

92

Farakka Barrage Project and surroundings . . . . . . . . . . . . . . . . . . . . . . . . . 101 Photographs (a) and (b) showing Rail cum Road Bridge across the river Ganga. (Source: Todaytimesnews.com) . . . . . . . . . . 102 Flow fluctuations in Hardinge bridge. (a) Average, maximum, and minimum discharge and (b) Pre-dam and post-dam variations in the flow regime . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . 103

xxxiv

Fig. 4.4

Fig. 4.5

Fig. 4.6

Fig. 4.7

Fig. 4.8 Fig. 4.9 Fig. 4.10 Fig. 4.11 Fig. 4.12 Fig. 4.13 Fig. 4.14 Fig. 4.15 Fig. 4.16

Fig. 4.17

Fig. 4.18 Fig. 4.19

Fig. 4.20

List of Figures

Discharge at Jangipur, Berhampore, and Purbasthali in pre- and post-FBP periods, (a) maximum, (b) average. (Based on Parua, 1992) . . . . . . . .. . . . . . . .. . . . . . . . .. . . . . . . . .. . . . . . . .. . . . . Discharge hydrograph of Bhagirathi at Treaty period. (a) Actual, (b) 10-day moving average. (Source: Average discharge (2005–2009), CWC, India) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Discharge hydrograph of Bhagirathi at normal period. (a) Actual, (b) 10-day moving average. (Source: Average discharge during 2005–2009, CWC, India) . . . . . . . . . . . . . . . . . . . . . . . . . Average annual discharge at Feeder Canal, Berhampore, and Katwa during the treaty period and normal period; (a) Actual, (b) Coefficient of variation. (Computed from CWC data 2008–2009) . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . .. . . . . . Workflow for land use and land cover map preparation using satellite images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LULC changes in America – a case of the Mississippi River, (a) 1992, (b) 2022 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LULC changes in the Asian countries – a case of the Mekong River. (a) 1992 and (b) 2022 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LULC changes in the Ganga-Padma region. (a) 1992 and (b) 2022 . . . .. . . . . . . .. . . . . . . . .. . . . . . . . .. . . . . . . .. . . . . . . . .. . . . . . . . .. . . LULC changes in the Bhagirathi region. (a) 1992 and (b) 2022 . . . .. . . . . . . .. . . . . . . . .. . . . . . . . .. . . . . . . .. . . . . . . . .. . . . . . . . .. . . LULC changes in the Hooghly River basin. (a) 1992 and (b) 2020 . . . .. . . . . . . .. . . . . . . . .. . . . . . . . .. . . . . . . .. . . . . . . . .. . . . . . . . .. . . LULC changes in the Brahmaputra region. (a) 1992 and (b) 2022 . . . .. . . . . . . .. . . . . . . . .. . . . . . . . .. . . . . . . .. . . . . . . . .. . . . . . . . .. . . LULC changes in the Padma and Meghna region. (a) 1992 and (b) 2022 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LULC changes in the Matiari and Akandanga mouza. (a) Matiari-1920, (b) Matiari-2020, (c) Akandanga-1920, (d) Akandanga-2020 . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . LULC changes in the Rukunpur and Char-Kashthasali mouza. (a) Rukunpur-1920, (b) Rukunpur-2020, (c) Char-Kashthasali1920, (d) Char-Kashthasali-2020 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Growth of various land use during the 1920s and 2020 . . . . . . . . . . . Severity of bank erosion along the Padma River, (a) Riverbank erosion in different unions along the Padma River at Harirampur Upazila. (Based on Rahman et al., 2016), (b) Erosion-accretion dynamics along the left bank of the Padma River at Harirampur (Note: Blue colour arrow indicates the direction of the Padma River while other arrows indicate direction of bankline shifting from time to time) . . . . . . . . . . . . . . . . . . . Land use change, channel condition, and sediment yield over time, Piedmont region, USA. (After Wolman, 1967) . . . . . . . .

106

108

109

110 112 114 115 116 117 118 119 120

123

124 125

126 127

List of Figures

Fig. 4.21 Fig. 4.22 Fig. 4.23 Fig. 4.24

Fig. 4.25

Fig. 4.26

Fig. 4.27

Fig. 4.28 Fig. 4.29 Fig. 4.30 Fig. 5.1

Fig. 5.2

Fig. 5.3 Fig. 5.4

Fig. 5.5

Schematic representation of the influence of riparian flora on the riverbank stability. (Based on Barua et al., 2011, 2019) . . . Erosion susceptibility of various land uses along the left bank of Bhagirathi River. (Islam & Guchhait, 2013) . . . . . . . . . . . . . . Location of brick field and road-stream crossing . . . . . .. . . . .. . . . . .. . Riverbank erosion in relation to brick kiln industry, (a) Shallow depression in the brick kiln area for entrapping sediment during flood along the left bank of Bhagirathi River, near Beldanga; (b) Bank failure due to cutting of soil from the upper horizons near Nabadwip. (Source: Field photograph, 2011) . . . . . . . . . . . . . . . . . Alteration of topographic expression due to brick kiln industries, (a) Formation of the artificial valley due to silt excavation, (b) artificial spur-like feature . . . .. . . .. . . . .. . . .. . . .. . . . .. . . .. . . .. . . . .. . Bed scouring due to the presence of road piers of Berhampore bridge. (a) Pier location, (b) Changing cross-sectional morphology. (Source: Ghosh, 2000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Road stream crossing and bank erosion, (a) Nasipur Railway Bridge near Hazarduari, Murshidabad, (b) New Bhagirathi bridge near Balarampur under construction. (Field photograph, 2019) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bamboo-made guide bank inducing sedimentation near Nabadwip. (Field Photograph, 2011) . . . . . . . . . . . . . . . . . . . . . . . . . . Pattern of Kelvin wave and wave propagation angle towards the riverbank. (Based on Kurdistani et al., 2019) . . . . . . . . Bank failure due to ship movement near Beldanga. (a) Movement of the vessel, (b) Fall of cohesive bank . . . . . . . . . . . . Types of meander modifications. + stands for increasing; for decreasing; u for upstream; d for downstream. (Based on García-Martínez & Rinaldi, 2022) . . . . . . . . . . . . . . . . . . . . . . Channel oscillation of major rivers of the Bengal Delta. (a) River Bhagirathi (Upper and Middle), (b) River Bhagirathi (Lower) and River Hooghly (Upper), (c) River Brahmaputra, (d) River Meghna, (e) River Ganga-Padma . . . . . . . . . . . . . . . . . . . . . . . . Relation between CI and VI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (a–e) Channel oscillation of river Bhagirathi in the lower reach during 1927–2020, (f) Space-time specificity in channel cut-off. (Computed from topographical maps and satellite images) . . . . . . . Morphology of meander geometry. (a) Ideal river meander and morphometric variables. (Williams, 1986); (b) Meander axis and direction angle with the sine-generated curve (Note: am stands for amplitude) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

xxxv

128 129 131

132

133

134

136 137 138 139

148

151 157

158

160

xxxvi

Fig. 5.6

Fig. 5.7

Fig. 5.8

Fig. 5.9

Fig. 5.10

Fig. 5.11

Fig. 5.12

Fig. 5.13

Fig. 5.14

Fig. 5.15

Fig. 5.16

Fig. 5.17 Fig. 5.18

List of Figures

Location of meander loops. (a) pre-Farakka (1927, 1954, 1974), (b) post-Farakka (1990, 2000, 2010, and 2020) (Note: The maps of different times are intended for locating the meander loops only and these side-by-side locations are not to be confused with shifting analysis. Topographical maps and satellite images treated separately for their different datum) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spatio-temporal variations in radius of curvature during (a) pre-Farakka (1927, 1954, and 1974) and (b) post-Farakka period (1990, 2000, 2010, and 2020) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spatio-temporal variations in amplitude during (a) pre-Farakka (1927, 1954, and 1974) and (b) post-Farakka period (1990, 2000, 2010 and 2020) . .. . .. . .. .. . .. . .. . .. . .. . .. . .. . .. . .. . .. .. . .. . .. . .. . .. . .. . Spatio-temporal variations in wavelength during (a) pre-Farakka (1927, 1954, and 1974) and (b) post-Farakka period (1990, 2000, 2010, and 2020) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . (a) Spatio-temporal variations in channel length during a. pre-Farakka (1927, 1954, and 1974) and (b) post-Farakka period (1990, 2000, 2010, and 2020) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spatio-temporal variations in arc angle during (a) pre-Farakka (1927, 1954, and 1974) and (b) post-Farakka period (1990, 2000, 2010, and 2020) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . Spatio-temporal variations in direction angle during (a) pre-Farakka (1927, 1954, and 1974) and (b) post-Farakka period (1990, 2000, 2010, and 2020) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spatio-temporal variation in sinuosity index (Note: green line indicates the peak points while red line shows the average sinuosity index in the pre-Farakka period from 1927 to 1974 (first 32 meander loops on x-axis) and post-Farakka from 1990 to 2020 (33–77 loops) period) . .. . . . . . . .. . . . . . .. . . . . . .. . . . . . .. . . . . . .. . . . . . .. . . . Spatio-temporal variation in radius/wavelength ratio (Note: red line shows the average r/w ratio in the pre-Farakka and postFarakka period) . . .. .. . .. . .. . .. . .. . .. . .. .. . .. . .. . .. . .. . .. . .. .. . .. . .. . .. . Spatio-temporal variation in meander shape index (Note: red line shows the average meander shape index in the pre-Farakka and post-Farakka period) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spatio-temporal variation in mender form index (Note: red line shows the average meander form index in the pre-Farakka and post-Farakka period) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Relation between meander shape index and meander form index (1927–2020) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Morphological dynamics of channel bars of Bhagirathi-Hooghly River, India during 1990–2020, (a) Char Balidanga, Bhagirathi River, (b) Rukunpur char, Bhagirathi River, (c) Chak Bholadanga, Hooghly River, (d) Gournaganar Char, Hooghly River . . . . . . . . . . .

162

165

166

167

170

171

173

174

176

177

179 180

183

List of Figures

Fig. 5.19

Fig. 5.20

Fig. 5.21

Fig. 5.22

Fig. 5.23

Fig. 5.24

Fig. 5.25

Fig. 5.26

Fig. 5.27

Fig. 5.28

Morphological dynamics of channel bars of Ganga-Padma River during 1990–2020, (a) Rostampur Char, Ganga River, India. (b) Radhakantapur Char, Ganga River, Bangladesh, (c) Char Bhabananda Diar, Padma River, Bangladesh, (d) North Char Janajat, Padma River, Bangladesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Morphological dynamics of channel bars of Brahmaputra and Meghna Rivers in Bangladesh during 1990–2020, (a) Nischintapur Char, Brahmaputra River, (b) Char Kodalia, Brahmaputra River, Bangladesh, (c) Charmodhu, Meghna River, (d) Kalitola Char, Meghna River . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Location of cross-section on the Bhagirathi River (Source: Hydrographic sheets, KoPT, 1972). (Note CS 249 denotes the first cross-section (Sl. No. 1) and CS 364 denotes the terminal cross-section of this study (Sl. No. 39)) . . . . .. . . . .. . . . . .. . . . .. . . . .. . . Spatio-temporal variation in width-depth ratio indicating a decreasing trend in the middle of the study stretch and increasing trend at the lower and the upper end of the distance . . . . . . . . . . . . . . . Spatio-temporal variation in width index indicating a decreasing trend in the middle of the study stretch and an increasing trend at the lower and the upper end of the distance . . . . . . . . . . . . . . . . . . . . . . . . Spatio-temporal variation in depth index indicating an increasing trend in the middle of the study stretch and decreasing trend at the lower and the upper end of the distance . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spatio-temporal variation in channel form index showing the decreasing trend in the middle part of the study region and bulging in the upper and lower parts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Parameters of an asymmetrical channel after Knighton, 1981 (Note: Ar and Al indicate right bank and left bank cross-sectional areas, A stands for the total area of the channel (A = Ar + Al), x for the distance from the channel centreline (Lc) (measured positive to the right and negative to the left) to the centroid of maximum depth, dmax is maximum depth, and d is mean depth) . . . . . . . . . . . . . An example (CS 315) of changing cross-sectional shape. (a) Pre-Farakka period-1972 and (b) post-Farakka period-1984 (Computed from hydrographic sheets, KoPT-1972–2012; Note: Datum reduced to MSL) . .. . . .. . .. . . .. . .. . . .. . .. . . .. . .. . . .. . .. . . .. . .. . Spatio-temporal variation in channel asymmetry. (a) A* index, (b) A1 index, (c) A2 index. The indices indicate that asymmetry has increased in the post-Farakka period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

xxxvii

184

185

188

189

190

191

192

193

195

196

xxxviii

Fig. 6.1

Fig. 6.2 Fig. 6.3

Fig. 6.4

Fig. 6.5

Fig. 6.6

Fig. 6.7

Fig. 6.8

Fig. 6.9

List of Figures

Dynamics of land loss in the study villages located along the Bhagirathi River, (a). Nature of land loss. (Data Source: Field Survey, 2012–2013; Sample size Matiari 597; Akandanga 127; Rukunpur 183; Ganjadanga 78; Char-Kashthasali 144; Sujanpur 57), (b). Types of land loss in the study area. (Data Source: Field Survey, 2012–2013; Sample size: Matiari, 362; Akandanga 88; Rukunpur 152; Ganjadanga 78; Char-Kashthasali 51; Sujanpur 0) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bank erosion-prone areas of Bangladesh. (Based on Bangladesh Water Development Board, 2017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Loss of properties by bank erosion, (a) Agricultural land in Matiari, (b) Agricultural land in Rukunpur, (c) Banana orchard in Rukunpur, (d) Loss of crops by bank erosion induced flood in Akandanga. (Source: Field survey, 2012–2013) . . . . . . . . . . . . . . . . . . . Dynamics of agricultural land loss, (a). Amount of agricultural land loss, (b). Percentage of agricultural land loss in the study area. (Data Source: Field Survey, 2012–2013; Sample size: Matiari, 362; Akandanga 88; Rukunpur 152; Ganjadanga 72; Char-Kashthasali 48; Sujanpur 0) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Riverbank erosion, relocation of settlement and homelessness in the study villages, (a). Shifting of settlement by bank erosion, (b). Homelessness induced by bank erosion (Data Source: Field Survey, 2012–2013; Sample size: Matiari,362; Akandanga 88; Rukunpur 152; Ganjadanga 78; Char-Kashthasali 51; Sujanpur 57) . . . . . . .. . . . . . . . . .. . . . . . . . .. . . . . . . . . .. . . . . . . . .. . . . . . . . . .. . . . . . . . . .. . . . . Bank erosion and displacement. (a). Cyclic displacement of Omar Ali’s family around char Janajat in Bangladesh. (Based on Islam, 2021), (b). Model of the linear movement of the people due to riverbank erosion along the Bhagirathi River. (Proposed by the authors, 2022) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Forced selling of properties and assets for the survival of victims. (Data Source: Field Survey, 2012–2013; Matiari 362; Akandanga 88; Rukunpur 152; Ganjadanga 78; Char-Kashthasali 51; Sujanpur 57) . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . .. . . . . Changes in income portfolio due to riverbank erosion, (a). Spatiotemporal variation in production of income, (b). Spatio-temporal variations in general income level. (Data Source: Field Survey, 2012–2013 Sample size: Matiari 362; Akandanga 88; Rukunpur 152; Ganjadanga 78; Char-Kashthasali 51; Sujanpur 57) . . . . . . . . . Changes in farming and non-farming income due to riverbank erosion, (a). Spatio-temporal variations in agricultural income level, (b). Spatio-temporal variations in non-agricultural income level. (Data Source: Field Survey, 2012–2013 Sample size: Matiari 362; Akandanga 88; Rukunpur 152; Ganjadanga 78; Char-Kashthasali 51; Sujanpur 57) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

205 207

208

209

211

212

214

216

217

List of Figures

Fig. 6.10

Fig. 6.11

Fig. 6.12

Fig. 6.13

Fig. 6.14

Fig. 6.15

Fig. 6.16

Fig. 6.17 Fig. 6.18 Fig. 6.19 Fig. 6.20

Fig. 6.21

Relation between agricultural land loss and income level. (Data Source: Field Survey, 2012–2013 Sample size: Matiari 362; Akandanga 88; Rukunpur 152; Ganjadanga 78; Char-Kashthasali 51; Sujanpur 57) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spatio-temporal variations in the distribution of income. (Data Source: Field Survey, 2012–2013 Sample size: Matiari 597; Akandanga 127; Rukunpur 183; Ganjadanga 78; CharKashthasali 144; Sujanpur 57) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Trend of Gini Coefficient in income with Generation. (Data Source: Field Survey, 2012–2013 Sample size: Matiari 362; Akandanga 88; Rukunpur 152; Ganjadanga 78; Char-Kashthasali 51; Sujanpur 57) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spatio-temporal change in Poverty indices: (a) Head Count ratio, (b) Poverty Gap Index, (c) Poverty Severity Index. (Data Source: Field Survey, 2012–2014 Sample size: Matiari 362; Akandanga 88; Rukunpur 152; Ganjadanga 78; Char-Kashthasali 51; Sujanpur 57) . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . .. . . . . Spatio-temporal variations in Occupational Index. (Data Source: Field Survey, 2012–2014 Sample size: Matiari,362; Akandanga 88; Rukunpur 152; Ganjadanga 78; Char-Kashthasali 51; Sujanpur 57) . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . .. . . . . Spatio-temporal variations in the diversification of income and occupation: (a) Inverse Herfindahl-Hirschman Index, (b) Individual Occupational Diversification Index. (Sample size Matiari,362; Akandanga 88; Rukunpur 152; Ganjadanga 78; Char-Kashthasali 51; Sujanpur 57) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Factors leading occupational diversification of the present generation. (Data Source: Field Survey, 2012–2013) Sample size Matiari 138; Akandanga 57; Rukunpur 104; Ganjadanga 45; Char-Kashthasali 30; Sujanpur 32; N.B sample size includes only those workers experienced diversification of occupation) . . . . . . . . . Association among different variables of livelihood vulnerability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Regional association among the villages regarding livelihood vulnerability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Interrelationship among various income groups regarding livelihood vulnerability, (a) Matiari, (b) Rukunpur . . . . . . . . . . . . . . . . Dynamics in the cropping intensity and diversity of the mainland and charland in the study area, (a). Nature of cropping intensity, (b). Crop Diversification Index after Gibbs-Martin. (Source: Field Survey, 2012) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Crop productivity. (a). Matiari Mouza, (b). Akandanga Mouza, (c). Rukunpur Mouza, (d). Char-Kashthasali and Ganjadanga villages. Note: Charland productivity is only in case of Ganjadanga. (Source: Field Survey, 2012) . . . . . . . . . . . . . . . . . . . . . . . . .

xxxix

218

220

221

224

225

228

229 231 232 234

236

241

xl

List of Figures

Fig. 6.22

Selling of crops by farmers. (a). for 1980 and (b). for 2012. (Source: Field Survey, 2012) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243

Fig. 7.1

Study area location and demographic dynamics, (a). Location of the study villages, (b). Family size in relation to bank erosion. (Computed from District Census Handbook, Nadia (1991–2011) Note: Blue colour bars denote the villages along the banks of the river and the red colour away from the river) . . . . . . . . . . . . . . . . . . . . . . Literacy rate of the study villages based on field survey, 2015. (Sample size: Matiari 122, Akandanga 19, Rukunpur 62, and Ganjadanga 20) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Major health problems related to bank erosion revealed through the field survey, 2015. (Sample size: Matiari 122, Akandanga 19, Rukunpur 62, and Ganjadanga 20) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Effectiveness of the government schemes to mitigate the hazards of bank erosion. (Sample size: Matiari 122, Akandanga 19, Rukunpur 62, and Ganjadanga 20) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nature of intraindividual processes, (a) Mean rating of respondents, (b) Mean-CV differential. (Computed from the field data, 2015: Sample size: Matiari 122, Akandanga 19, Rukunpur 62, and Ganjadanga 20) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nature of interpersonal processes, (a) Mean rating of respondents, (b) Mean-CV differential. (Computed from the field data, 2015: Sample size: Matiari 122, Akandanga 19, Rukunpur 62, and Ganjadanga 20) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nature of intergroup processes, (a) Mean rating of respondents, (b) Mean-CV differential. (Computed from the field data, 2015: Sample size: Matiari 122, Akandanga 19, Rukunpur 62, and Ganjadanga 20) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nature of group processes, (a) Mean rating of respondents, (b) Mean-CV differential. (Computed from the field data, 2015: Sample size: Matiari 122, Akandanga 19, Rukunpur 62, and Ganjadanga 20) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Discrimination of social processes through 2-stage PCA . . . . . . . . . . Social psychology of hazard, (a) Perception of male, (b) Perception of female in percentage. (Sample Size: Matiari 122, Akandanga 19, Rukunpur 62, and Ganjadanga 20) . . . . . . . . . . . . . . . . Relative consistency of males and females in the perception of different variables of social psychology. (Sample Size: Matiari 122, Akandanga 19, Rukunpur 62, and Ganjadanga 20) . . . . . . . . . .

Fig. 7.2

Fig. 7.3

Fig. 7.4

Fig. 7.5

Fig. 7.6

Fig. 7.7

Fig. 7.8

Fig. 7.9 Fig. 7.10

Fig. 7.11

251

252

253

254

257

259

260

261 263

265

266

List of Figures

Fig. 7.12

Fig. 7.13

Fig. 7.14

Fig. 7.15

Fig. 7.16

Fig. 7.17

Fig. 7.18

Fig. 7.19 Fig. 7.20 Fig. 8.1

Fig. 8.2

Fig. 8.3 Fig. 8.4

Fig. 8.5

Tajfel Matrix showing the psychology of social desire vis-à-vis distribution of resources in the society, (a) Matiari- a normal society, (b) Rukunpur – a hazard-dominated society Note: numeric values adjacent to Scatter points are the percentage figure of the number of respondents. (Computed from the field data 2015, Sample size 122 for Matiari and 62 for Rukunpur) . . . . . . . . . Perception of the women in relation to crisis and options in the context of bank erosion in percentage. (Sample size: Matiari 122, Rukunpur 62) . .. . . .. . . .. . .. . . .. . . .. . . .. . . .. . . .. . . .. . .. . . .. . . .. . . .. . . .. . Perception of the economic migrant in relation to crisis and options in the context of bank erosion in percentage. (Sample Size: Matiari 41, Rukunpur 62) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Perception of the permanent migrant in relation to crisis and options in the context of bank erosion in percentages. (Sample Size: Matiari 10, Rukunpur 17) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Perception of the teachers in relation to crisis and options in the context of bank erosion in percentage. (Sample Size: Matiari 21, Rukunpur 10) . .. . . .. . . .. . .. . . .. . . .. . . .. . . .. . . .. . . .. . .. . . .. . . .. . . .. . . .. . Perception of the outside people in relation to crisis and options in the context of bank erosion in percentage. (Sample Size: Matiari 40, Rukunpur 40) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Perception of the relatives in relation to crisis and options in the context of bank erosion in percentage. (Sample Size: Matiari 21, Rukunpur 21) . .. . . .. . . .. . .. . . .. . . .. . . .. . . .. . . .. . . .. . .. . . .. . . .. . . .. . . .. . Location of the study chars of the Bhagirathi River . . . . . . . . . . . . . . . Transformation of chars in the study area in different time frame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Satisfaction level of the respondents about Government schemes, (a) mean rating of 100 points, (b) mean-CV differential (Computed from the field data, 2015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Individual and community initiatives to better live with bank erosion, (a) Bank protection works along the left bank of Bhagirathi near Rukunpur, (b) Mulberry plantations along the left bank of Bhagirathi in Rukunpur. (Source: Field photograph, 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Structural and non-structural measures of bank erosion. (Based on Parua, 2010) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Various structural and non-structural techniques used to protect riverbanks from erosion (a) Revetment, (b) Brick mattressing, (c) Groynes, (d) Permeable spur, (e) Dumping geo-bags, (f) Flow area increases by dredging, (g) Wooden piling, (h) Crisscross porcupines. (Based on Islam, 2008) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Futility of bank protection works, (a) near ISKCON Temple, Nabadwip, (b) near Rukunpur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

xli

268

269

271

273

274

275

275 278 280

289

291 293

294 296

xlii

Fig. 8.6

Fig. 8.7

Fig. 8.8

Fig. 8.9 Fig. 8.10

Fig. 8.11 Fig. 8.12 Fig. 8.13

Fig. 8.14

Fig. 9.1

List of Figures

Comparative effectiveness of bio-engineering and civil engineering practices over time (Based on Howell, 1999). It proves that bio-engineering structures are increasing at the expense of civil engineering structures .. . . . .. . . . . .. . . . .. . . . . .. . . . .. . Evaluation of bio-engineering measures. (a) Natural bank protection with kans grass along the left bank of the Bhagirathi River, (b) Bamboo root penetration deeper into the soil reduces the rate of riverbank erosion along the Bhagirathi near Rukunpur village. It is observed that places without bamboo root penetration have an accelerated rate of bank line shifting. (Source: Field survey, 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Brass metal industry in Matiari. (a) Sheet making; (b) shaping brass sheet in finished products. (Source: Field photograph, 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Flow diagram of Matiari model for the operation of brass metal industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hypothesized palaeochannel fishing for Akandanga, (a) Waterbody falling under the jurisdiction of Akandanga, (b) Present situation of the palaeochannel (Note: Channel cut-off area has been considered as palaeochannel area because it has already been neck cut-off and being gradually sedimented. (Source: Field photograph, 2014) . . .. .. . .. .. . .. .. . .. . .. .. . .. .. . .. .. . .. . .. .. . .. .. . .. .. . Small scale and cottage industry, (a) Tant, (b) Bidi-binding in Rukunpur. (Source: Field photograph, 2014) . . . . . . . . . . .. . . . . . . . . . . . Nature of labour migration in the study area. (Based on Islam & Guchhait, 2021) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Densification of settlements as an adaptational strategy to better live in erosion-prone areas of Bangladesh, (a) Location of Hizla Thana with safer and vulnerable location, (b) Directional geometry of the densification process. The pinkish arrows indicate the movement of settlements to safer locations from the vulnerable zone. (Based on Mamun & Amin, 1999) . . . . . . . . . . . . . . . . . . . . . . . . . . . Densification model and its framework. (a) Conceptual framework of the densification model, (b) Pathways to implementing the model. Note: Colour arrows do not convey any special meaning. This is only for graphical visualization. (Based on Mamun & Amin, 1999) . .. . . . . . . . .. . . . . . . . . .. . . . . . . . .. . . . . . . . . .. . .

298

298

300 301

304 307 309

311

312

Framework integrating climate change, flood, and bank erosion in a loop manner. The figure demonstrates that floods will increase in the wake of climate change which tends to increase the riverbank erosion and socioeconomic instabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319

List of Tables

Table 1.1 Table 1.2

Erosional agents and their relevant erosional processes . . . . . . . . . Space–time in river bank erosion research . . . . . . . . . . . . . . . . . . . . . . . .

4 15

Table 3.1 Table 3.2 Table 3.3 Table 3.4

Effects of channel bank infrastructure to control bank erosion . Bank erosion mechanisms . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . Factors triggering bank erosion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Suspended sediment load through Bhagirathi and its tributaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reynolds number downstream of Berhampore and Katwa in the pre-Farakka and post-Farakka period . . . . . . . . . . . . . . . . . . . . . . Description of the BEHI model input parameters. (Rosgen, 2001) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Criteria selected for converting stream bank erodibility variables to BEHI ratings. (Rosgen, 2001) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Description of methods, input parameters, and data sources of NBS. (Rosgen, 2001) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NBS ratings based on Rosgen (2009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Minimum, maximum, and range of shifting . . . . . . . . . . . . . . . . . . . . . . Detection of erosion and accretion over time . . . . . . . . . . . . . . . . . . . . .

44 47 54

Table 3.5 Table 3.6 Table 3.7 Table 3.8 Table 3.9 Table 3.10 Table 3.11 Table 4.1 Table 4.2 Table 4.3

Table 4.4 Table 4.5 Table 4.6

Average discharge (m3s-1) in the pre-Farakka period at various gauge stations of the Bhagirathi River . . . . . . . . . . . . . . . . . . . . . . . . . . . . Water level and discharge at Jangipur of Bhagirathi River . . . . . . Indo-Bangladesh water sharing treaties of 1977a and 1996b showing the theoretical distribution of Ganga water at Farakka (in Cusecs) . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . .. . . . . LULC dynamics of Mississippi, Mekong, and Ganga Rivers (in km2) during 1992–2022 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LULC dynamics of Bhagirathi, Hooghly, Brahmaputra, and Meghna Rivers (in km2) during 1992–2022 . . . . . . . . . . . . . . . . . . . . . . Changes in the major land use and land cover during the 1920s and 2020 in the study area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

63 65 69 70 70 71 90 93 105 105

107 121 122 124 xliii

xliv

Table 4.7

Table 5.1 Table 5.2 Table 5.3 Table 5.4 Table 5.5 Table 5.6 Table 5.7 Table 5.8 Table 5.9 Table 5.10 Table 5.11 Table 5.12 Table 5.13 Table 5.14 Table 5.15 Table 5.16 Table 6.1 Table 6.2 Table 6.3 Table 6.4 Table 6.5 Table 6.6 Table 6.7 Table 6.8 Table 6.9 Table 6.10

List of Tables

Changes in the major land use and land cover (land under water, sand bar, and others) during the 1920s and 2020 in the study area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Meander deformations of the major rivers of the GBM delta during 1990–2020 .. . . .. . . .. . .. . . .. . . .. . .. . . .. . . .. . . .. . .. . . .. . . .. . .. . Nature of sinuosity of the major rivers of the Bengal Basin in 1990 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nature of sinuosity of the major rivers of the Bengal Basin in 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nature of sinuosity of the major rivers of the Bengal Basin in 2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nature of sinuosity of the major rivers of the Bengal Basin in 2020 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Selected meander loops for meander geometry analysis . . . . . . . . . Spatio-temporal variations in radius of curvature, amplitude, and wavelength . . .. . . . . .. . . . . .. . . . . .. . . . . . .. . . . . .. . . . . .. . . . . .. . . . . .. . Spatio-temporal variations in channel length, arc angle, and direction angle .. . . . . . .. . . . . .. . . . . .. . . . . . .. . . . . .. . . . . . .. . . . . .. . . . . . .. . Spatio-temporal variation in sinuosity index . . .. .. . .. .. . .. . .. .. . .. Temporal variation in radius/wavelength ratio . . . . . . . . . . . . . . . . . . . Temporal variation in meander shape index . . . . . . . . . . . . . . . . . . . . . . Temporal variation in meander form index . . . . . . . . . . . . . . . . . . . . . . . Braiding index (BI) of the different rivers of Bengal Basin after Brice (1964) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Braiding index (Pt) of the different rivers of Bengal Basin after Hong and Davies (1979) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Growth of char area (km2) at selected places of the Major Rivers of the Bengal Delta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Descriptive statistics of Knighton’s (1981) Indices . . . . . . . . . . . . . . Land loss in the Brahmaputra River in Assam, India . . . . . . . . . . . . Inequality in land loss among the farmers of the selected villages through the chi-square test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Partial correlation between average income and particular income groupsa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cropping intensity of the selected villages . . .. . . .. . .. . .. . .. . .. . .. . Cropping diversity index of the selected villages . . . . . . . . . . . . . . . . Crop productivity (kilogram/hectare) of Matiari and Akandanga villages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Crop productivity (kilogram/hectare) of Rukunpur, Ganjadanga, and Char-Kashthasali villages . . .. . .. .. . .. . .. .. . .. . .. Village-level selling of agricultural products, 1980 . . . . . . . . . . . . . . Village-level selling of agricultural production, 2012 . . . . . . . . . . . Land accretion and erosion in the major rivers of Bangladesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

125 150 152 153 154 155 156 164 169 175 176 177 178 181 182 186 194 206 210 235 236 238 239 240 242 243 244

List of Tables

xlv

Table 6.11

Percentage distribution of cropping patterns by zone in Kazipur .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . . .. 245

Table 7.1 Table 7.2

School dropout (2007–2012) . .. . . . .. . . . . .. . . . . .. . . . . .. . . . . .. . . . . .. . Social processes and their measuring variables in relation to riverbank erosion . . .. . . . . .. . . . . . .. . . . . . .. . . . . .. . . . . . .. . . . . . .. . . . . .. . . Nature of social transformation in relation to char dynamics . . . Proposed brass metal industry for Rukunpur . . . . . . . . . . . . . . . . . . . . . Annual income, expenditure, and savings of the fisherman household unit . . . . .. . . . . . . . . . .. . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . .. . . . . Hypothesized palaeochannel fishing at Akandanga . . . . . . . . . . . . . . Number of households to be supported by tant industry in the study area . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .. . . . . . . . Number of households to be supported by bidi binding in the study area . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .. . . . . . . .

Table 7.3 Table 8.1 Table 8.2 Table 8.3 Table 8.4 Table 8.5

253 256 281 303 305 306 308 308

Part I

Riverbank Erosion: Concepts, Approaches, and Context

Riverbank erosion is a fundamental fluvial, geo-mechanical, and chemical process in a river basin. Some fundamental concepts, historical approaches, and context of riverbank erosion research worldwide need to be explored. Riverbank erosion: basic concepts and approaches (Chap. 1) glean out the very basic perspectives of bank erosion in terms of the conceptual framework, dimensions, historical approaches, and spatial and temporal scales. Context of riverbank erosion (Chap. 2) discusses the nature of riverbank erosion at the global and regional (Bengal Delta) scale to create the backdrop of the present investigation with particular emphasis on the state of the art of bank erosion research in the Bengal Delta. This chapter also outlines the needs and focus of carrying out this research.

333

Chapter 1

Riverbank Erosion: Basic Concepts and Approaches

1.1

Conceptual Outlook of Riverbank Erosion

Since the very beginning of Earth, some fundamental laws and processes that governed the terrestrial system operated at different paces over the world. Erosionaccretion dynamics is such a fundamental process that is widely familiar as the natural agency to impact the terrestrial and marine systems. Erosion is simply the mechanical dissipation of any matter and substances or chemical process where substances are dissolved and transported. Besides, accretion or deposition is the accumulation of matter/substance by physical and chemical processes. According to the Encyclopaedia of Geomorphology, erosion indicates the exogenetic processes of the removal of materials from elevated areas to the lowlands (Lupia-Palmieri, 2006). Thus, it excludes the processes of weathering and mass wasting and includes the mobile agents mainly running water, glaciers, wind, and sea waves that draw their energy from solar radiation (Fig. 1.1). The most common processes are by erosional agents in various mechanical and chemical ways (Table 1.1). In the fluvial system, erosion, transportation, and deposition are widely explored as interrelated processes and their responses over terrestrial and marine surfaces. Thus, the evolution of the planation surfaces requires the performance of erosion and sedimentation over space and time. In classical geomorphology, the Davisian cycle of erosion also implies the overriding role of the erosion process to complete the cycle (Davis, 1899). In this context, the two basic modalities – vertical incision and lateral erosion – are observed with different proportions in various stages of the cycle of erosion. For example, the maturity and the early old stage are characterized by

Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/978-3-031-47010-3_1. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Islam, S. K. Guchhait, Riverbank Erosion in the Bengal Delta, Springer Geography, https://doi.org/10.1007/978-3-031-47010-3_1

3

333

4

1 Riverbank Erosion: Basic Concepts and Approaches

Solar radiation intercepted by the earth 17.8 ×1016 W

Solar energy to atmosphere

Hydrological cycle

Fluvial erosion

12.3× 1016 W

4× 1016 W

Glacial erosion

Kinetic energy (wind) Aeolian erosion

7× 1014 W Coastal waves and currents

Coastal erosion

5×1012 W

Fig. 1.1 Flow of energy for different kinds of erosional processes. (Source: Summerfield, 1991) Table 1.1 Erosional agents and their relevant erosional processes Erosional process Erosional agent Running water

Entrainment of rocky materials Hydraulic action (corrosion)

Glacier Wind

Plucking or quarrying Deflation

Wave and currents

Hydraulic action (corrosion)

Erosion by transported materials Abrasion

Wear of transported materials Attrition

Abrasion

Attrition

Corrosion or abrasion Abrasion

Attrition Attrition

Methods of transportation Traction Suspension Solution Traction Traction Suspension Traction Suspension (solution)

Source: Thornbury (1954) Note: Less effective processes are indicated within brackets

more lateral erosion and less vertical incision. However, the process of erosion has drawn the attention of planners and stakeholders in the wake of the so-called hazard perspective of bank erosion mainly in densely populated areas of the world. Therefore, though riverbank erosion is defined as a natural geomorphic process that implies the separation and entrainment of bank materials in the form of grains,

333

1.1

Conceptual Outlook of Riverbank Erosion

5

aggregates, or blocks by fluvial, sub-aerial, and/or geomechanical processes, it has now become a multidimensional concept with the ultimate objective of the impact of erosion on society and the measures to avoid it. It is a common form of geomorphic hazard associated with floodplain and meandering or braided river systems (Lawler, 2004; Bandyopadhyay, 2007). Naturally, some other processes related to riverbank erosion also deserve separate attention, for example, geologic erosion and accelerated soil erosion. However, the perspective of geologic erosion and soil erosion is quite different from the riverbank erosion. Geologic erosion is natural and slowly occurring since the very inception of the earth while accelerated soil erosion is often viewed in the context of the human interventions and intensive agricultural practices that induce accelerated soil erosion. Hence, geologic erosion is an essential process by which the sediment dispersal mechanism, sediment budgeting, and delta-building process are maintained (Brady & Weil, 2013). Moreover, the role of differential (neo)tectonic activities in river basins, especially in Bangladesh, is of utmost importance to understand the interaction between geological, geomorphological, and hydrological river behaviour. However, in the era of the “Anthropocene”, a proposed geological epoch with significant human impact on the earth system (Zalasiewicz et al., 2019), various forms of human interventions mainly in the form of intensive agriculture, deforestation, and urbanization put intensive pressure on the land. This induces accelerated soil erosion through the process of sheet erosion, rill erosion, and gully erosion. Thus, the accelerated nature of soil erosion has put pressure on the natural ecosystem services and land management practices. The process of soil erosion involves the activity of rainwater and wind by the forces of erodibility and erosivity. However, bank erosion involves the role of fluvial hydrodynamics to erode the river bank. Thus, bank erosion like geologic erosion is also a natural process that occurs through a hydrodynamic energy function that is more profoundly found for meandering or braiding river. Riverbank erosion is predominantly studied in physical sciences, but this process has far-reaching consequences on social behaviour and the economic system. For example, riverbank erosion induces land loss (loss of fertile agricultural land), job loss, and demolition of houses. People with sufficient landholding residing by the side of the river with the active bank erosion are transformed into beggars or landless overnight. Being marginalized, they are exposed to socioeconomic instability and psychological shocks. Bank erosion at one point and the formation of char downstream by the transportation of eroded material leads to community conflicts and political turmoil regarding the occupancy of charlands. Hence, the process of riverbank erosion is now discussed in eco-geomorphology (integration of hydrology, geomorphology, and ecology) instead of traditional pure geomorphology. Similarly, this process is also gradually incorporated into the socio-hydrology and political economy instead of pure sociological or geopolitical approaches. Thus, the approaches towards riverbank erosion have become more integrated that need system thinking and complex interrelated physical and social processes than the earlier concepts.

333

6

1.2 1.2.1

1

Riverbank Erosion: Basic Concepts and Approaches

Historical Perspective of Bank Erosion Hazard Studies Trajectory of Bank Erosion Research

The journey of riverbank erosion research started with a focus on the natural process approach. Though it is very difficult to consider any scientific study as the first work on riverbank erosion, few renowned scholars attempted to investigate riverbank erosion from a natural process approach (Table S1.1). In their studies, few of them focused purely on open channel hydraulics where the dissipation of energy for making the river dynamic has been explored to its fullest extent. In this hydraulics domain, they also tried to explore the influence of discharge, near bank velocity, and stream power shear stress, on bank failure. Another group of researchers, for getting a clear understanding of the process of bank erosion, attempted to link hydraulics geometry to the properties of the riverbank, i.e., stratification of the riverbank and cohesiveness of the bank materials. A little annexure to the existing research during that time was to measure the rate of riverbank erosion. In this regard, the erosion pin was the oldest technique for measuring the rate and volume of erosion. With time, many other techniques have been developed for increasing the accuracy of measurement (Table S3.3). Thereafter, the total station (an electronic theodolite measuring angles and distances between stations) and PEEP (Photo-Electronic Erosion Pin used for automatic detection of erosion and deposition) technologies were dominantly employed. Additionally, the evolution of laser technology has made a revolutionary change in the study of river bank erosion research. Therefore, the natural process approach broadly includes the study of hydraulic geometry, bank stratigraphy, and measurement of erosion rate. The scholarly discussion on the factors and mechanism of river bank erosion has highly attracted the significant role of anthropogenic activities on river bank erosion. Flow alteration through the construction of dams, near bank deforestation, sand mining, artificial channel modification, land use, and land cover change are dominantly discussed as anthropogenic activities for river bank erosion in the era of the “Anthropocene” (Das et al., 2020). Apart from the anthropogenic approach, river bank erosion has also been studied from a hazard perspective because it has a direct and indirect relation with the social, economic, and psychological fabric of the affected community (Fig. 1.2). Therefore, studies in this direction have explored various dimensions of hazards, i.e., severity, spatiality, community’s exposure, sensitivity and vulnerability, and hazard prediction. Therefore, all of the aforementioned methods collectively create a solid foundation that enables researchers to approach their work from a logical or risk-management perspective. In this strategy, structural engineering modifications were largely implemented before 2010. Afterwards, risk mitigation via raising the community’s ability for adaptation has gained widespread recognition. However, the rational method places a stronger focus on collaborative engineering and community-based risk mitigation (Table S1.1).

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Fig. 1.2 Time frame diagram to trace out the trajectory of bank erosion research

1.2.2

Approaches to Bank Erosion Study

To study bank erosion, there are four different approaches, i.e., (1) Natural approach, (2) Anthropogenic approach, (3) Hazard approach, and (4) Rational approach. The nature of all the approaches has been studied based on 419 previous research works executed across the world. The inclusion of the literature is based on a systematic search strategy, i.e., identification of keywords (“riverbank erosion”, “approaches to riverbank erosion”, “channel instability”, “lateral erosion”, “bank erosion hazard”, “controlled hydrology”, “hard engineering”, and “climate change and riverbank erosion”) and selection of research articles, reports, thesis, etc., using academic databases such as Google Scholar, Scopus, and Web of Science from 1970 to 2020. More particularly, among all the reviewed literature 68 are purely related to the natural process of river bank erosion while many other scholastic research works attempted to combine the natural process with the anthropogenic approach (64), hazard approach (58), and rational approach (32) (Fig. 1.3a and Table S1.1). Besides, 51 pieces of literature were considered and studied as purely anthropogenic approaches, and much other literature reflecting the anthropogenic approach attempted to combine the hazard approach (44) and rational approach (23). Moreover, 26 pieces of literature purely focusing on the hazard approach and 23 on the rational approach have been taken into consideration. Therefore, based on the abovementioned pieces of literature an attempt has been made to truly represent the existing approaches and their combinational nature (Fig. 1.3a and Table S1.1). Moreover, to glean the perspective of the bank erosion research across the continents in different decades (1970–2020), an attempt has been made where it is observed that bank erosion study has magnified in the recent decade (2010–2020) in the Asian

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(a)

20 15

Natural approach

Anthopogenic approach

Hazard approach

Rational approach

(b)

10 5 0 1970-1980 1980-1990 1990-2000 2000-2010 2010-2020 1970-1980 1980-1990 1990-2000 2000-2010 2010-2020 1970-1980 1980-1990 1990-2000 2000-2010 2010-2020 1970-1980 1980-1990 1990-2000 2000-2010 2010-2020 1970-1980 1980-1990 1990-2000 2000-2010 2010-2020 1970-1980 1980-1990 1990-2000 2000-2010 2010-2020

Major Works (1970-2020)

25

Asia

Europe

North America

South America

Australia

Africa

Continents

Fig. 1.3 Approaches to studying riverbank erosion. (a) Sankey diagram showing the approaches to studying riverbank erosion during 1970–2020. Note: the red band represents the natural approach, the blue band for anthropogenic, the yellow for hazard, and the green for the rational approach which is shown on the left vertical axis. The figure clearly shows the interrelationship among the various approaches portrayed in the previous works. (b) Spatio-temporal development of riverbank erosion research in different continents in different decades using major approaches. (Based on Table S1.1)

countries compared to the Europe and North American countries (Fig. 1.3b). In Europe and America, the bank erosion study started much earlier resulting in a larger number of works till 2010, after that there has been a decrease in the bank erosion study. This contrasting scenario is prevalent due to the severity of riverbank erosion and the need to increase community resilience in Asian countries while a relative slackening in the severity of the bank erosion due to the taming of the rivers in

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Fig. 1.4 Riverbank erosion as a naturally induced process. The chord diagram indicates the share of the different natural trigger factors to induce bank erosion across the world based on the study findings (1970–2020). Note: there are five broad categories of factors inducing riverbank erosion. For example, for flow hydrology, there are 63 works shown using the blue ring. Out of these 63 works, 26 works are concerned with only flow hydrology in relation to riverbank erosion while 15 works are concerned with riverbank erosion in relation to the interplay of flow hydrology and cohesive and non-cohesive riverbank; 11 works focus on flow hydrology and riparian vegetation for bank erosion; 9 works have shown riverbank erosion as an interplay between flow hydrology and storm surges and floods; 2 relates to riverbank erosion in the context of flow hydrology and tectonic movements. (Based on Table S1.2)

Europe and North America by structural interventions. However, in some cases, due to the growing awareness about the ecological flow, rivers are allowed to flow unimpeded resulting in bank erosion in recent times (Vietz et al., 2018). Riverbank erosion is a natural outcome of the meandering streams that induces channel shifting and oscillation in one place and avulsion in another place. The processes of erosion, avulsion, meandering, and braiding are closely integrated into a natural process-form system. All those processes lead to erosion of the bank at one point and deposition of material mainly in the river bed away from the point of bank erosion. Therefore, this process of channel adjustment is purely a perspective of the natural phenomena (Fig. 1.4 and Table S1.2).

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An alternative to the natural process approach is more concerned with the anthropogenic approach which is quite complex bearing multiple spatio-temporal dimensions induced by human interventions (Dang et al., 2022). It integrates the structural changes (e.g., dams, and land use and land cover) and modification in the social system due to bank erosion in a two-way process, i.e., society is affected by bank erosion and vice versa. For example, since the very dawn of human civilization, humans started settling along the river for its agro-ecological and hydrological advantages (Tejwani, 1993). The river-centric civilizations of Mesopotamia, the Indus Valley, and the Tigress River characterize this legacy. However, these people were sometimes affected due to the riverbank erosion hazard. The second anthropogenic aspect is related to river damming. Human constructs dams to minimize flood hazards and also to maximize economic profit through irrigation-based agriculture. However, this kind of damming has severe consequences of bank erosion upstream and downstream of the river. The third anthropogenic perspective is related to environmental refugees. Due to the riverbank erosion and loss of settlement, people residing adjacent to the river are forced to migrate and are transformed into environmental refugees. Even a single generation may have experienced land losses and relocation of settlements for several times. These people in the long run face the problem of finding suitable land for settlement. Thus, ultimately, they are pushed to the disadvantaged location of the riverbank. Bhatia is a perfect example of bank erosion-induced migrated people of Indo-Bangladesh. In other words, these people living in the tidal areas of coastal Bangladesh frequently face geo-climatic hazards such as storm surges and cyclone-induced riverbank erosion and embankment breaching. As a result, adversely affected hazard victims are forced to migrate permanently into the interior areas. Inland people codify those environmental refugees as Bhatia with a sense of negligence (Chakraborty, 2017). The last perspective of the anthropogenic process is related to fertile agricultural land loss in the highly active bank erosion zone that paralyses an economic system. The hazard approach has gained popularity with time for contemporary environmental issues both in the physical and cultural landscape. The study contemplated in this research started with the geo-environmental setup of the study area from which regional problems and hazards have become tell-tale. The study area is well-known to both physical and social scientists due to its marked bank erosion of the major rivers of the Bengal Delta. Rivers are always oscillating in this area causing huge socioeconomic problems for the villagers very close to the river bank. With time, land mainly agricultural land has been engulfed by the rivers. Agriculture is the backbone of the economy of the villages in the floodplains of India and Bangladesh. But severe riverbank erosion along the major rivers in the flood plains of the Indo-Bangladesh region has disrupted the economy frequently for a long time. Throughout the entire research work, the nature and mechanism of bank erosion and its impact on the village economy and society are assessed in different chapters, where it is clear that bank erosion is undeniable but adjustment and mitigation strategies can reduce the vulnerability of hazards.

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Dimensions of Riverbank Erosion Research

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A rational approach is the combined form of the above three approaches. This approach aims to reduce human vulnerability and increase the coping capacity of the people because it believes that bank erosion is inevitable along with the active courses of the river. People by hook or by crook are forced to adjust to hazards. This approach is familiar with a catchy notion “to live with hazard”.

1.3

Dimensions of Riverbank Erosion Research

Dimensions of riverbank erosion are manifested through (1) natural dimensions and (2) socioeconomic dimensions. Riverbank erosion is popularly regarded as a natural process because whenever there is lateral erosion of a river, bank erosion is inevitable. Hooke (1979) portrayed that riverbank erosion is the only process in the fluvial system that is subsequently associated with sediment transport and deposition activity. Moreover, he identified riverbank erosion as principally a natural process controlled by the discharge characteristics, rainfall characteristics, soil moisture characteristics (antecedent precipitation index), geology, and bank material characteristics. However, with the massive human interventions, riverbank erosion and its dimensions have been intensified proportionately. In Asia, riverbank erosion is largely governed by the monsoon climatic regime, tropical cyclones, and snowmelt (Darby et al., 2013). Physical environmental dimension common in the domain of academics and research is concerned with natural hazards and catastrophes. In this regard, bank erosion plays an important role in the control of channel width and adjustments of the fluvial systems; it makes a significant contribution to the river’s sediment load and destruction of the floodplain land, and reduction in the resource value of the river (Thorne, 1991). Bank erosion greatly controls both the rate and direction of channel migration and so alters the overall pattern of channel evolution which has been observed in the Red and the Mississippi Rivers of the USA (Thorne, 1991). Moreover, environmental processes related to riverine ecosystem processes are also closely linked to riverbank erosion. The supply of sediment to the fluvial system provides nutrients through the aquatic ecosystem to the nature of riverbank erosion (Florsheim et al., 2008). Though previously bank erosion was treated as a purely natural process, nowadays riverbank erosion has a socioeconomic dimension. The rapid increase in population, encroachment of riverbanks by humans, increasing shipping, and controlled hydrologic regime through dams have exacerbated the problems in the fluvial system in general and riverbank erosion in particular. Emberson (2017), however, has outlined that deforestation of the tropical forests for expansion of agricultural land led to an increase of erosion of river meander by about 23% between 1984 and 2014 than the natural system. Similarly, Horton et al. (2017) have documented a relationship between the deforestation of tropical areas and riverbank erosion. Therefore, there is a need to make a wider contemporary riverbank erosion discourse from the natural process-related perspective to explore the complexity of the social dynamics.

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Socioeconomic dimensions are traditionally treated from a hazard perspective. This is due to the land loss by bank erosion and agrarian distress. Furthermore, economic marginalization pushes back societal processes in an integrated distortion of normal social relations with the outcome of social distress. Bank erosion induces socioeconomic instabilities from various aspects. This basic notion has been explored by various scholars worldwide from the standpoint of population displacement and migration, agriculture loss, feebling of household economy, stressed women-scape, property loss and damage, and other social instabilities. Population displacement is the foremost consequence of bank erosion. The erosion victims are forced to migrate to a nearby city and live in urban slums (Schmuck-Widmann, 2001; Hutton & Haque, 2004; Iqbal, 2010) and get their identity as environmental refugees. In Bangladesh, millions of people migrate annually for this reason (Rahman, 1991; Deshingkar & Grimm, 2004) inducing the growth of the urban population through rural-to-urban migration. Since 1971, there has been a 60% increase in urbanization per decade in Bangladesh (Elahi, 1972; Islam, 1976). Migration of victim workers outside the local area sometimes may help families in distress by sending the remittances to their place of origin. Remittances sent by migrant workers play an important role in strengthening the economy of the source regions (Puri & Ritzema, 2001; Azad, 2003). If the remittances are invested in farmland, those can contribute to output growth, and if consumed for daily livelihood, those will generate positive multiplier effects (Stahl & Arnold, 1986). However, losing land such an option is diluted. Agriculture in developing countries is severely affected by bank erosion (Schmuck-Widmann, 2001; Uddin & Rahman, 2011). Generally, it has been noted that bank erosion induces a change in cropping pattern, a decline in crop production, changes in crop diversity, a change in cropping intensity, and outstanding damage to crops (Uddin & Rahman, 2011). In Bangladesh, it has been noted that due to sand deposition cultivation of rice is not possible and in place of rice, maize, pulses, oilseeds, groundnut, etc., are grown on the char (Uddin & Rahman, 2011). There is also the problem of in-situ displacement of peasant holdings (Feldman & Geisler, 2011). The declining agricultural productivity scenario (Baboule et al., 1994; Roose, 1996; Van Rompaey et al., 2002; Dragicevic & Stepic, 2006) has led to the decline of the agricultural population. During 1961–2002, there was a 60% decline in the agricultural population of the Kolubara River basin in Siberia. Not only the agricultural decline but the general decline of the economy is noticed in the erosion-prone area also. Poverty, unemployment, job shifting, and indebtedness are the common scenarios in this belt of erosion (Uddin & Rahman, 2011). Bank erosion severely impacts vulnerable groups of society and especially women (Rogge & Elahi, 1989; Haque, 1997). It has been noted that displaced women have a higher level of perceived stress than their non-displaced counterparts (Taylor et al., 1976; Logue et al., 1979; Shore, 1986; Canino et al., 1990; Lima et al., 1991; Rubonis & Bickman, 1991; Keya & Harun, 2007). Bank erosion also affects property

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Scales in Riverbank Erosion Study

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belongings. When disaster strikes, poor people survive by selling off their belongings like land, livestock, housing materials, and other personal belongings (Haque, 1997; Hutton & Haque, 2004; Uddin & Rahman, 2011). Besides these socioeconomic impacts, some other social vulnerabilities found in the erosion-prone areas lead to the breaking of the social bond, family relations, disruption of social services, degradation of social status, and also increased social injustice created by the powerful group (Islam & Rashid, 2011).

1.4

Interdisciplinary Nature of Riverbank Erosion

Natural science is more objective and precise than social science because natural science deals with the nature and properties of living organisms and non-living things under the dictum of nature while social science disciplines concern the socioeconomic aspects of human life conditioned by subjective will, desire, emotion, and judgement. Riverbank erosion is studied from both the natural and social science perspectives because of its integrative nature. The science of riverbank erosion needs to apply the basic principles of fluvial dynamics to understand the nature of the riverbank erosion process. On the other hand, measuring the consequences of bank erosion from the socioeconomic perspective attracts social scientists. Physical scientists principally study natural phenomena (natural mechanism and its quantitative dimensions) and try to relocate people from erosion-prone areas to safe locations. Otherwise, they try to tame the river by some river training works like bunding with geotextile. Social scientists on the other hand have a notion to live with the problem through restructured social relations and resettlements. They don’t intend to tame the river courses by civil or hard engineering measures but rather try to find out a solution that can save the people from socioeconomic vulnerability. However, in the context of riverbank erosion, both perspectives are required for a better understanding of the erosion sciences (Fig. 1.5) because both perspectives have some validity against hazard management. Therefore, an integrative understanding is of utmost necessity considering the site, situation, integrity, and temporality of the phenomena.

1.5

Scales in Riverbank Erosion Study

For its interdisciplinary approach, all the previous scholars dealing with the issue of riverbank erosion have considered certain spatial and temporal connotations. From the perspective of spatial scale, scientists have been concerned with “site”, “reach”, and “catchment” and the combination of these. Most of the researchers have

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Fig. 1.5 Interdisciplinary nature of erosion research

addressed this issue from the perspective of reach as the most intriguing point of investigation while the works related to catchment are very meagre (Table 1.2). From the perspective of temporal scale, ahistorical, short, medium, and long periods have been used in this context. Following Lawler (1993), the definition of short-term encompasses a few months to a few years, medium 1–30 years, and long for 10,000–20,000 years. Most researchers around the world have focused on the ahistorical and short-term scale while long-term focus on the temporal scale is conspicuous by the relative absence. A detailed list of scholars is tabulated here to perceive the different contexts of spatio-temporal dimensions of bank erosion research across the world (Table 1.2). In the above categorization, a reach-related study on spatial scale and short-term investigation on temporal scale have outnumbered other contexts. The utmost effort has been made to illuminate the aspects of the major researchers since that time to date, though it is not a complete list of all the previous works since 1959. The nature of riverbank erosion varies as per the spatial and temporal scales. Actually, the spatial scale cannot be separated from the temporal scale. There is a close correspondence between space and time that constitutes the regional mosaics of bank erosion worldwide. Thus, the global and regional perspectives on the nature of bank erosion studies are discussed in the next chapter with an outlook on the context of the bank erosion studies in the Bengal Delta.

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Table 1.2 Space–time in river bank erosion research

Wolman (1959) Twidale (1964) La Marche (1966) Hill (1973) Goss (1973) Ponce (1978) Hooke (1979) Blacknell (1981) Kesel and Baummanh (1981) Guy (1981) Thorne and Tovey (1981) Pizzutto (1984a) Pizzutto (1984b) Nanson and Hean (1985) Lawler (1986) Odgaard (1987) Walker (1987) Osman and Thorne (1988) Thorne and Osman (1988) Pizzutto and Mackelnburg (1989) Lawler (1991) Hooke and Redmond (1992) Thorne and Abt (1993) Thorne et al.( 1993) Darby and Thorne (1994) Nanson et al.(1994) Lawler (1994) Ashbridge (1995) Mosselman (1995) Bradbury et al.(1995) Leys (1995) Bull (1997) Brierley and Murn (1997) Stott (1997) Gurnell (1997) Piegay et al. (1997) Abam (1997) Brewer and Lewin (1998) Abernethey and Rutherfurd (1998) Mosselman (1995) Meentemeyer et al.(1998) Huang and Nanson (1998) Lawler et al.(1999) Rowntree and Dollar (1999) Green et al.(1999) Harmel et al.(1999) Stott (1999) Casagli et al. (1999) Thorne (1999) Simon et al.(1999) Nicholas et al. (1999) Laubel et al. (2000) Prosser et al.(2000) Abernethey and Rutherfurd (2000) Nagata et al.(2000)

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Scholars

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(continued)

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Table 1.2 (continued)

Darby et al.(2000) Simon et al.(2000) Gilvear et al. (2000) Wood at al.(2001) Couper and Maddock (2001) Couper et al. (2002) Darby and Delbono (2002) Darby at al.(2002) Simon and Collison (2002) Hooke (2003) Fonstad and Marcus (2003) Couper (2004) Piegay et al. (2005) Bandyapadhyay (2007) Parua (2010) Rudra (2011) Karmaker and Dutta (2013) Henshaw et al. (2013) Kessler et al. (2013) Rudra (2014) Dewan et al. (2016) Guchhait et al. (2016) Islam and Guchhait (2017) Abidin et al. (2017) Hemmelder et al. (2018) Jugie et al. (2018) Deng et al. (2019) Das et al. (2019) Sarif et al. (2021) Bernier et al. (2021) Li et al. (2021) Saadon et al. (2021)

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Reach

Scholars

Site

Spatial Scale

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Note: Green bullets are used to identify publication that considers more than one scale but gives prominence to that dotted with a red star. The definition of temporal scale is taken from Lawler (1993), i.e., short (few months to a few years), intermediate (1–30 years), and long (10,000–20,000 years). The definition of site, reach, and catchment is somewhat arbitrary, however, taken to portray the hierarchical nature of the study – site is the lowest unit and catchment is the highest spatial unit. Also, there is a close correspondence between spatial units and temporal units. Care has been taken to prepare this table, especially after 2005, however, indeliberate missing of works may be found. (Based on Couper, 2004 and recent literature 2005–2021)

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Couper, P., Stott, T. I. M., & Maddock, I. A. N. (2002). Insights into river bank erosion processes derived from analysis of negative erosion-pin recordings: Observations from three recent UK studies. Earth Surface Processes and Landforms: The Journal of the British Geomorphological Research Group, 27(1), 59–79. Dang, D. H., Ma, L., Ha, Q. K., & Wang, W. (2022). A multi-tracer approach to disentangle anthropogenic emissions from natural processes in the St. Lawrence river and estuary. Water Research, 219, 118588. Darby, S. E., & Delbono, I. (2002). A model of equilibrium bed topography for meander bends with erodible banks. Earth Surface Processes and Landforms, 27, 1057–1085. Darby, S. E., & Thorne, C. R. (1994). Prediction of tension crack location and riverbank erosion along destabilised channels. Earth Surface Processes and Landforms, 19, 233–245. Darby, S. E., et al. (2000). Technical communication: Computer program for stability analysis of steep, cohesive river banks. Earth Surface Processes and Landforms, 25, 175–190. Darby, S. E., et al. (2002). Numerical studies of bank erosion and channel migration in meandering. Rivers Water Resources Research, 38, 1163. Darby, S. E., Leyland, J., Kummu, M., Räsänen, T. A., & Lauri, H. (2013). Decoding the drivers of bank erosion on the Mekong river: The roles of the Asian monsoon, tropical storms, and snowmelt. Water Resources Research, 49(4), 2146–2163. Das, V. K., Roy, S., Barman, K., Debnath, K., Chaudhuri, S., & Mazumder, B. S. (2019). Investigations on undercutting processes of cohesive river bank. Engineering Geology, 252, 110–124. Das, B. C., Ghosh, S., Islam, A., & Roy, S. (2020). An Appraisal to Anthropogeomorphology of the Bhagirathi-Hooghly River System: Concepts, Ideas and Issues. In Anthropogeomorphology of Bhagirathi-Hooghly River System in India (pp. 1–40). CRC Press. Davis, W. M. (1899). The geomorphic cycle. Geomorphic Journal, 14, 481–504. Deng, S., Xia, J., & Zhou, M. (2019). Coupled two-dimensional modeling of bed evolution and bank erosion in the Upper JingJiang Reach of Middle Yangtze River. Geomorphology, 344, 10–24. Deshingkar, P., & Grimm, S. (2004). Voluntary internal migration – An update (p. 23). Overseas Development Institute. Dewan, A., Corner, R., Saleem, A., Rahman, M. M., Haider, M. R., Rahman, M. M., & Sarker, M. H. (2017). Assessing channel changes of the Ganges-Padma River system in Bangladesh using Landsat and hydrological data. Geomorphology, 276, 257–279. Dragicevic, S., & Stepic, M. (2006). Changes of the erosion intensity in the Ljig River basin – The influence of the antropogenic factor. Bulletin of the Serbian Geographical Society, 85(2), 37–44. Elahi, K. M. (1972). Urbanization in Bangladesh – A geodemographic study. Oriental Geographer, 16(1), 39–48. Emberson, R. (2017). Accelerating riverbank erosion. Nature Geoscience, 10(5), 328–328. Feldman, S., & Geisler, C. (2011, April). Land grabbing in Bangladesh: In-situ displacement of peasant holdings. In International conference on global land grabbing (pp. 6–8). Institute of Development Studies, University of Sussex. Florsheim, J. L., Mount, J. F., & Chin, A. (2008). Bank erosion as a desirable attribute of rivers. Bioscience, 58(6), 519–529. Fonstad, M., & Marcus, W. A. (2003). Self-organised criticality in riverbank systems. Annals of the Association of American Geographers, 93, 281–296. Gilvear, D., et al. (2000). Character of channel planform change and meander development: Luangwa River, Zambia. Earth Surface Processes and Landforms, 25, 421–436. Goss, D. W. (1973). Relation of physical and mineralogical properties to stream bank stability. Water Resources Bulletin, 9, 140. Green, T. R., Beavis, S. G., Dietrich, C. R., & Jakeman, A. J. (1999). Relating stream-bank erosion to in-stream transport of suspended sediment. Hydrological Processes, 13(5), 777–787.

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Chapter 2

Context of Riverbank Erosion

2.1

Backdrop

Are we gradually entering into a risk society? This question frequently blinks in the minds of academicians and also among the common people due to the increasing intensity of both physical and social hazards of the present time. The idea was for the first time well explained by Beck (1992) who claimed that rampant technocentric development has deranged the rhythm of the natural system leading to the increasing intensity of physical hazards. The unwieldiness of these risks challenges institutional control and disaster management, “evoking the terrifying experience of being part of a vulnerable society that is overwhelmed by forces that are neither controlled nor fully understandable” (Beck, 1992), making the society unstable where the development is blurred and social hazards have become frequent. It is inarguably true that more use of automated technology begets more use of resources at the cost of the environment. Under such a technocentric praxis, the natural rhythm of the environment is obstructed halting the normal course of cybernetics. Environment under such circumstances has two options – either the normal rhythm of the environment is lost (decaying of the system) or it tries to overcome the barrier(s) and wants to regain the normal rhythm through homeostasis. The second action is being expressed as the increasing intensity and frequency of hazards due to this human intervention. Apart from this general perspective, another point of concern is that natural hazards are inevitable. Humans with their rapidly increasing numbers from the very beginning of the twentieth century are gradually encroaching the areas which are more prone to natural hazards. This is more pronounced for the cyclonic coastal areas, flood-prone areas of the large rivers, and also bank erosion-prone areas of the middle and lower course of the large rivers. Most of the large rivers of the world require an optimum area for their flow variability, directional change of flow, and

Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/978-3-031-47010-3_2. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Islam, S. K. Guchhait, Riverbank Erosion in the Bengal Delta, Springer Geography, https://doi.org/10.1007/978-3-031-47010-3_2

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also shifting of their course. This is technically known as Constant of Channel Maintenance (Schumm, 1954). However, humans from the early stage of civilization have preferred to settle in the flood-prone areas of the river valley and close to the river bank for freshwater access and other resources of the river. Therefore, they were the victims of flood and bank erosion hazards. Now, the problems have been intensified with the growing population along the banks of major rivers and their flood plains. The phenomena are the common parlance for the densely populated flood plains and bank areas of south-east Asia and south-east China. The situation is more intense for the Ganga-Brahmaputra-Meghna (GBM) Delta because of its high density of population, higher frequency of flood, and high intensity of bank erosion. The GBM delta the largest riverine delta of the world, and the most densely populated region of the world after North-West Europe experiences severe bank erosion every year during the monsoon and post-monsoon seasons mainly by Ganga, Bhagirathi, Hooghly, Padma, Brahmaputra, Jamuna, and Meghna. Thus, this book attempts to uphold the bank erosion of the GBM delta from the perspective of physical and social hazards.

2.2

Global Perspective on Riverbank Erosion

Most rivers across the world are following the meandering path through the erosion and accretion processes. Therefore, meandering along with bank erosion is a common phenomenon in almost every river. Few rivers across the world have become familiar with devastating bank erosion primarily due to meander dynamics. For example, Ganga (Singha et al., 2020), Meghna (Gazi et al., 2020), Brahmaputra (Akhtar et al., 2011), Padma (Bhuiyan et al., 2017), Yangtze (Deng et al., 2019), and Mekong (Kummu et al., 2008) rivers in Asia; the Mississippi-Missouri river (National Research Council, 2008), Ohio river and Colorado river (Hagerty et al., 1981) of North America; Amazon (Anthony et al., 2019), Rhine and São Francisco rivers (Maillard et al., 2022) in South America; Nile (Wong et al., 2007), Niger and Congo rivers (Gbadegesin et al., 1994) in Africa; Gordon (Bradbury et al., 1995), Murray and Darling rivers (Hughes & Prosser, 2003) in Australia are most important. The channel dynamics due to lateral erosion in Australia are evident in the rivers of Murray and Darling of the Murray-Darling River basin and Gordon River in the Tasmania River basin. Hughes and Prosser (2003) illustrated that over the entire Murray-Darling River basin the average annual rate of erosion varied from 1 to 2 cm/ year. Moreover, they predicted the annual rate of sediment production due to river bank erosion to be 8.6 Mt/year. Infrequent flood events are found to be the key factor in bank erosion. Moreover, the river bank having poor riparian vegetation was found to be very prone to river bank erosion in the Darling River. The lower reach of the Gordon River is also found to be susceptible to river bank erosion in response to

2.2

Global Perspective on Riverbank Erosion

25

wakes produced from large boats (Nanson et al., 1994). Parnell et al. (2007) observed that the large boats used as industrial ferries are mainly responsible for river bank erosion due to their high speeds and capability of producing larger wakes. Many European rivers, especially in urban areas, are not allowed to follow the meandering path due to the flow regulation by the modification of river channels. The process of straightening river channels and other engineering works are found to exist to protect the settlements and agricultural land against flood and river bank erosion. However, the process of river bank erosion is evident for a few rivers, for example, Rhône River, River Buëch, Merantaise River, Cher Rivers in France (Hemmelder et al., 2018); Upper Severn Basin, river banks in Devon, River Arrow (Couper & Maddock, 2001), River Severn rivers in the UK (Bull, 1997); Sieve and Cecina rivers in Italy, etc. (Rinaldi & Casagli, 1999). Channel migration due to river bank erosion and their significant contribution to the sediment load of various rivers in the USA are well documented. For example, in the midwestern USA, the contribution of river bank erosion on the stream sediment load varies from 23% to 79% in Minnesota (Kelley & Nater, 2000; Kessler et al., 2013), from 0% to 81% in Wisconsin (Lamba et al., 2015), and 23% to 64% in Iowa (Palmer et al., 2014; Schilling et al., 2011). Zaimes et al. (2021) studied the spatiotemporal variation of stream bank erosion of 30 selected reaches in three different regions of Iowa, USA (first and second order stream in northeast region and second and third order streams in central and southeast regions) during 2002–2008 applying erosion pins method. The mean stream bank erosion rates they estimated for central, northeast, and southeast regions were 155, 134, and 94 mm year-1 respectively. Konsoer et al. (2016) studied the river bank erosion of two bends, i.e., Maier bend (5 km) and Horseshoe bend (4 km) of Wabash River of the Ohio River Basin, based on BSTEM. They estimated the total volumetric rate of erosion as 53,290 m3year-1 during 2011–2012 and increased to 98,694 m3year-1 (1.85 times) during 2012–2013 at Maier bend. They also found that maximum erosion has occurred at the apex of the Meander bend. Similarly, for the Horseshoe bend total volumetric rate of erosion was estimated as 1820 m3year-1 during 2011–2012 and 3954 m3year-1 during 2012–2013. In contrast to the Maier bend, the maximum erosion was observed at 0.4 km upstream of the apex. Rhoades et al. (2009) quantified the bank erosion of the South River, Virginia from 1937 and 2005. The lateral erosion rate they observed ranges from 2.50 × 106 m3 in the years 1999, 2000, 2001, 2003, and 2004. The nature and severity of riverbank erosion of the major rivers of the Bengal Delta area are discussed in the following sections. The severity of river bank erosion is evident in the Brahmaputra River. The investigation of Akhtar et al. (2011) for a stretch of 622.73 km extending from

2.3

Regional Perspective on River Bank Erosion in the Bengal Delta

29

Fig. 2.3 Major reference works produced in West Bengal indicating the concentrated nature of works on the Ganga River

Dhubri to Kobo in Assam revealed that 538.80 km2 of the right and 914.62 km2 of the left bank land area was lost by the river bank erosion during 1990–2007. According to Sarma (2005), the 630 km stretch in Assam was identified as erosion prone area. As per their estimated data 2358.57 km2 and 1490.76 km2 of land were found as eroded and accreted areas respectively during 1912–1996 and therefore 867.81 km2 area was estimated as net loss due to river bank erosion during the same period. The erosion phenomenon is also severe in the Bangladesh part of the Brahmaputra River. For example, Khan and Islam (2003) estimated the erosion rate as 160 m per year during 1973–1992. The bank erosion and channel migration in the Padma and the Jamuna Rivers in Bangladesh are well documented. As per the estimate of Dewan et al. (2017), the total amount of erosion on the left and right

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Context of Riverbank Erosion

banks of the Padma River was 189.40 km2 (4.98 m year-1) and 166.53 km2 (4.38 m year-1) respectively during 1973–2011. The maximum erosion on the left bank was observed as 58.82 km2 (11.76 m year-1) during 1977–1980 and on the right bank 98 km2 (19.60 m year-1) during the same period. Besides, Ophra et al. (2018) studied the erosion nature of the Padma River in the 3 selected districts (Munshiganj, Madaripur, and Shariatpur) between 1988 and 2017 and estimated a land loss of 42,689.59 ha due to erosion (1472.056 ha/year). The maximum erosion was observed during 1988–1993 (10,448.47 ha, 2089.693 ha per year). It is pertinent to mention here that the majority of the works produced on riverbank erosion are concerned with the Jamuna River because of its severity of erosion and creating a huge loss in Bangladesh. Rahman et al. (2022) reviewed the major works on riverbank erosion and found that 12 out of the 20 reference works are concerned with the Jamuna River (Fig. 2.4).

Fig. 2.4 Major reference works produced in Bangladesh indicating the concentrated nature of works on the Jamuna River. (Based on Rahman et al., 2022)

2.4

2.4

The State of the Art of Bank Erosion Research in the Bengal Delta

31

The State of the Art of Bank Erosion Research in the Bengal Delta

Physical geography mostly studies earth surface phenomena as natural processes. However, human geography seeks to explain the surface phenomena as the interaction of the physical and socioeconomic processes. There are clear differences between these two types of processes. Although most physical phenomena are easily understood by physical laws, complex, fuzzy, often non-linear processes at multiple spatio-temporal scales are also prevalent in the physical world (Richards, 2002). However, the complexity of social phenomena is quite different and strikingly present in human society and often interpreted as the processes of social interaction in relation to physical processes (Grundmann & Stehr, 2007). Considering these differences, the state of art of bank erosion research in the Bengal Delta is focused on the physical processes with a universal notion and social interactions with the particularistic form. There is indeed a considerable difference between the study of riverbank erosion of the western and eastern worlds (Wantzen, 2022). In the Western world, more than 90% population lives in cities, where riverbank erosion is no more a risk. Rivers within or at the periphery of the cities are tamed. It is also found in the larger cities of the Eastern world, but most of the people of Asia and Africa are settled along the river course. The agrarian economy is at the base of such people. Therefore, bank erosion and related hazards scape are integral parts of the state of the art of erosion research for the rivers of Asia and Africa including the Bengal Delta (Paul et al., 2020). Bank erosion in the Bengal Delta is thus an ideal consideration in exploring bank erosion-related dynamics from a humanistic approach. Therefore, the present investigation has a specific focus on bank erosion and its impact on the economy and society within the study area. The study area is marked by the channel oscillation of the Ganga, Bhagirathi-Hooghly, Padma, Meghna, Jamuna, and Brahmaputra river systems. For example, the Bhagirathi River in West Bengal oscillates within a belt of 5–15 km with a revisit period of around 200–250 years as per historical records (Islam, 2016). In the study area, agriculture, fishing, and animal husbandry have faced an extreme level of marginalization due to channel shifting and bank erosion. In a nutshell, the economy of the study area has been drastically affected due to the severity of bank erosion as well as dismantling other sociocultural processes. In this regard, thousands of extremely marginalized people have been investigated intensively to bring out an alternative solution to this problem. In the study area, palaeochannels, pastures, or chars can be used as common property resources (CPRs) which have a higher potential to support the economy against bank erosion hazards (Islam, 2016). This CPRs management may act as the immediate substitution for a land-based economy. At the same time, a non-land-based economy has a high potential to absorb the shock of hazards which is deeply investigated in this research work. Apart from in-situ adjustment, ex-situ adjustment very common in the study area in terms of migration has been analysed through process and outcomes in the sequel to stabilize the economy against the hazard.

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Present Study: Needs and Focus

The study of environmental hazards is important from the very inception of civilization. Humans prefer to settle in those areas which are less hazardous. Development of settlement in safe locations is not only found in ancient, medieval periods but also in modern days. In recent decades, hazard study is becoming more and more important due to the increase in population and built-up environment in the hazard-prone areas which are intensifying hazards. Prosperous human civilization has developed on the riverside because of hydrological and agroecological perspectives (Adedeji, 2011). Ancient civilizations like Indus Valley Civilization, and Mesopotamia, are examples of river-based civilizations (Zhang et al., 2015). Nowadays more than 70% population lives in flood plains and the deltas of the rivers (Global Centre on Adaptation, 2021). Rivers by nature oscillate and swing across the flood plains and deltas from one position to another. This channel oscillation induces hazardous conditions by eroding land, and settlement and thus destabilizes the livelihood of the people around the intensive bank erosion sites. In an urban area, a river is bound by engineering structures and hence channel migration is forcefully stopped to secure the urban livelihood. But in a rural set-up river is relatively unbound and so likely oscillation of rivers damages livelihood. Therefore, rural people are the most victims of channel migration and bank erosion. The mighty river system in the Bengal Delta with huge monsoon spells and a large population pressure altogether makes this unique. Though some researchers (e.g., Haque, 1998; Hutton & Haque, 2004; Islam, 2016) have uttered a few specific issues related to riverbank erosion problems in the states of West Bengal and Bangladesh, a comprehensive understanding of the present erosion scenario, management strategies, and future risk estimation is the need of the hour. The analysis undertaken in this book is attempted at two levels: (1) intensive field-based investigation carried out mainly in the eastern part of the Bengal Delta (i.e., West Bengal) and (2) general portrayal of the bank erosion scenario carried out for the eastern part of the Bengal Delta (i.e., Bangladesh) mainly based on the literature, secondary data, maps, and images. For intensive field-based investigation, severe bank erosion-prone area, i.e., lower stretch of the Bhagirathi River located in the inter-confluence zone formed by the river Ajay marking the northern limit of the study area and the river Jalangi marking the southern limit where the river Bhagirathi gives a way to the river Hooghly (Fig. 2.5) is particularly focused. Furthermore, to portray the riverbank erosion as a socio-spatial process, a typical study area design is figured out. With the increase of distance from the river bank, the impact of bank erosion becomes gradually feeble. To assess this spatial variability of bank erosion hazard, three tiers around the left bank of the river have been taken into consideration. Tier-1 villages are located adjacent to the river Bhagirathi, i.e., up to 1.5 km from the left bank of the river, tier-2 lies in the middle strip between 1.5–3.0 km and tier-3 is located far away from the bank, i.e., beyond 3 km (Fig. 2.5). It is observed that there are both intra-zonal variation and inter-zonal variation while correlating bank erosion with society. Generally, it can be said that there is a strong correlation

2.5 Present Study: Needs and Focus

33

Fig. 2.5 Location of the in-depth field investigation in the Bengal Delta. The location of study villages in different zones in selected C.D. blocks in Nadia District, West Bengal, India has been shown

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between bank erosion and society for the mouzas adjacent to the river Bhagirathi (tier-1), feeble correlation for the farthest villages (tier-3), and moderate for the middle strip (tier-2). Therefore, a socio-spatial symbiosis is clearly depicted. Hence in tier-1 or in the active erosion-prone areas, four representative villages from four C.D. Blocks of Nadia district adjacent to the river Bhagirathi have been selected. These four villages are (1) Matiari of C.D. Block Kaliganj, (2) Akandanga of C.D. Block Nakashipara, (3) Rukunpur of C.D. Block Krishnagar II, and (4) Ganjadanga of C.D. Block Nabadwip. The intensity of erosion for Akandanga is moderate, Ganjadanga is characterized by high erosion and Rukunpur and Matiari are conspicuous by their severity of erosion. In the very high erosion (severe) belt two villages, i.e., Rukunpur and Matiari have been taken to assess whether the severity of erosion is the only cause of the degree of victimization. Rukunpur is basically an agricultural area whereas Matiari once had a dual economy through agriculture and the brass metal industry has now deviated from a land-based economy to a brass metal industry. In tier-2, another one village, i.e., CharKashthasali adjacent to Ganjadanga has been taken. Char-Kashthasali is showing a feeble correlation between bank erosion and social vulnerability because it has a minimum land loss. In tier-3, virtually no village has experienced bank erosion at all. But for the interlinking of the rural economy, some villages in this belt have had an indirect impact on their life and livelihood by the severity of bank erosion for the nearby villages. Sujanpur is a representative village of this kind located near Rukunpur. The primary data for carrying out the work have been collected from a field survey taking 782 sample households on a random basis from the six selected villages viz. Matiari, Akandanga, Rukunpur, Ganjadanga, Char-Kashthasali, and Sujanpur. For the collection of household data, random sampling has been applied for its inherent virtue of being unbiased because of more or less homogeneity of the population. For determining sample size, first, a pilot survey was conducted to ascertain the target population, i.e., the erosion victims of the villages. The results derived through the pilot survey establish that there are 61%, 69%, 83%, 100%, and 35% land-losing households of the total households in Matiari, Akandanga, Rukunpur, Ganjadanga, and Char-Kashthasali respectively while no land-loss is reported in Sujanpur village. The sample size has been determined according to the formula (Eq. 2.1) propounded by the Department of Economic and Social Affairs (2005): nh = z2 ðr Þ ð1 - r Þ ðf Þ ðkÞ=ðpÞ ðnÞ e2

ð2:1Þ

where nh is the sample size to be selected; z is the level of confidence desired (95% here); r is an estimate of a key indicator to be measured by the survey; f is the sample design effect assumed to be 2.0 (default value); k is a multiplier of non-response (1.1 here); p is the proportion of the total population accounted for by the target population and upon which the parameter r is based; n is the average household size (number of persons per household); and e is the margin of error (0.01 here) to be attained.

References

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Using the above formula a statistically significant sample size of 725 erosion victim households (362 households in Matiari, 88 in Akandanga, 152 Rukunpur, 72 in Ganjadanga, and 51 in Char-Kashthasali) while another 57 non-erosion victim households from Sujanpur were chosen for final interview in the study area to ascertain the economic change and livelihood vulnerability as discussed in Chap. 6. However, to unfold bank erosion-induced social hazards, tier-1 villages viz. Matiari, Akandanga, Rukunpur, and Ganjadanga have been taken into consideration. Sample households have been chosen according to two criteria of land loss – (a) households greater than 90% land loss and (b) households greater than 6 bighas land loss. In the study villages, almost all the households are victims of bank erosion but the families who have lost their lion’s share of agricultural land are not only economically exhausted but socially and psychologically ruined also. So those families are taken as samples to study the impact of bank erosion on society. Following this method the number of respondents interviewed for social analysis (Chap. 7) from Matiari, Akandanga, Rukunpur, and Ganjadanga is 122, 19, 62, and 20 respectively out of the total erosion victim households of 362, 88, 152, and 78 (Table S2.1) chosen according to Eq. 2.1. Therefore, this book will unearth various perspectives of bank erosion research: (1) bank erosion as a natural process, (2) bank erosion as a human-induced process, (3) dynamics of geomorphic landscapes in relation to riverbank erosion, (4) economic and (5) social impacts of river bank erosion and (6) the management of bank erosion with an indication of (7) future bank erosion scenario. This integrated attempt will establish a discourse on riverbank erosion as a science that will help the academician, researchers, planners, and stakeholders of the Bengal Delta in particular and other areas of the world in general.

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Rudra, K. (2006). Shifting of the Ganga and land erosion in West Bengal: A socio-ecological viewpoint. CDEP occasional paper, 8, 1–20. Rudra, K. (2010). Dynamics of the Ganga in West Bengal, India (1764–2007): Implications for science–policy interaction. Quaternary International, 227(2), 161–169. Rudra, K. (2014). Changing river courses in the western part of the Ganga–Brahmaputra delta. Geomorphology, 227, 87–100. Rudra, K. (2018a). The Bhagirathi-Hugli River system. In Rivers of the Ganga-BrahmaputraMeghna Delta (pp. 77–93). Springer. Rudra, K. (2018b). Rivers of the Ganga-Brahmaputra-Meghna Delta. Springer. Rudra, K. (2020). Combating flood and erosion in the lower ganga plain in India: Some unexplored issues. In Disaster Studies (pp. 173–186). Springer. Rudra, K. (2022). Changing River Courses in Bengal (1780 to 2020). In Riverine systems (pp. 403–422). Springer. Sarif, M. N., Siddiqui, L., Islam, M. S., Parveen, N., & Saha, M. (2021). Evolution of river course and morphometric features of the River Ganga: A case study of up and downstream of Farakka Barrage. International Soil and Water Conservation Research, 9(4), 578–590. Sarif, M. N., Siddiqui, L., Siddiqui, M. A., Parveen, N., Islam, M., Khan, S., et al. (2022). Household-based approach to assess the impact of river bank erosion on the socio-economic condition of people: A case study of Lower Ganga Plain. In Challenges of disasters in Asia (pp. 73–101). Springer. Sarma, J. N. (2005). Fluvial process and morphology of the Brahmaputra River in Assam, India. Geomorphology, 70(3–4), 226–256. Schilling, K. E., Isenhart, T. M., Palmer, J. A., Wolter, C. F., & Spooner, J. (2011). Impacts of landcover change on suspended sediment transport in two agricultural watersheds 1. JAWRA Journal of the American Water Resources Association, 47(4), 672–686. Schumm, S. A. (1954). The relation of drainage basin relief to sediment loss. International Association of Scientific Hydrology, 36(1), 216–219. Singha, P., Das, P., Talukdar, S., & Pal, S. (2020). Modeling livelihood vulnerability in erosion and flooding induced river Island in Ganges riparian corridor, India. Ecological Indicators, 119, 106825. Sinha, R., & Ghosh, S. (2012). Understanding dynamics of large rivers aided by satellite remote sensing: A case study from Lower Ganga plains, India. Geocarto International, 27(3), 207–219. Sultana, P., Thompson, P. M., & Wesselink, A. (2020). Coping and resilience in riverine Bangladesh. Environmental Hazards, 19, 70–89. https://doi.org/10.1080/17477891.2019. 1665981 Tanvir Rahman, M. A. T. M., Islam, S., & Rahman, S. H. (2015). Coping with flood and riverbank erosion caused by climate change using livelihood resources: A case study of Bangladesh. Climate and Development, 7, 185–191. https://doi.org/10.1080/17565529.2014.910163 Thakur, P. K., Laha, C., & Aggarwal, S. P. (2012). River bank erosion hazard study of river Ganga, upstream of Farakka barrage using remote sensing and GIS. Natural Hazards, 61(3), 967–987. Wantzen, K. M. (2022). River culture–life as a dance the rhythm of the waters. https://unesdoc. unesco.org/ark:/48223/pf0000382775 . Accessed 24 July 2023. Wong, C. M., Williams, C. E., Pittock, J., Collier, U., & Schelle, P. (2007). World’s top 10 rivers at risk. (WWF International). Online version. http://wwf.panda.org/?108620/Worlds-Top-10Rivers-at-Risk. Accessed 18 Sept 2014. Yao, Z., Ta, W., Jia, X., & Xiao, J. (2011). Bank erosion and accretion along the Ningxia–Inner Mongolia reaches of the Yellow River from 1958 to 2008. Geomorphology, 127(1–2), 99–106. Zaimes, G. Ν., Tamparopoulos, A. E., Tufekcioglu, M., & Schultz, R. C. (2021). Understanding stream bank erosion and deposition in Iowa, USA: A seven year study along streams in different regions with different riparian land-uses. Journal of Environmental Management, 287, 112352. Zaman, M. Q. (1989). The social and political context of adjustment of riverbank erosion hazard and population resettlement in Bangladesh. Human Organization, 48(3), 196–205. Zhang, J., et al. (2015). River-human harmony model to evaluate the relationship between humans and water in River Basin. Current Science, 109(6), 1130–1139.

Part II

Riverbank Erosion: Process Approach

A systematic treatment of riverbank erosion to reveal the complexity of a system requires a process approach. Riverbank erosion though primarily a natural process gets intensified through anthropogenic activities. Thus, riverbank erosion: a natural process (Chap. 3) is analysed with the natural geo-ecological perspective coupled with types, mechanisms, factors, and measurements. However, riverbank erosion: a human-induced process (Chap. 4) entails the dimensions of the megascale dams and barrages, along with changing land use and land cover with other small-scale basin interventions such as the erection of brickfields, and ship movement. Prosperous civilizations of the past had extensively used the major rivers and their basins with huge modifications for the development of agriculture and settlement. After the industrial revolution, river basins and channels are widely modified, altered, and tamed for industrialization and urbanization. These interventions often exacerbate the pace of bank erosion worldwide.

Chapter 3

Riverbank Erosion: A Natural Process

3.1

Riverbank Erosion: A Natural Geoecological Process

River bank erosion is a fundamental fluvial action existent in any fluvial system to support the sediment supply and ecological functionality. However, this process is often condemned as the most common hazard in the world, especially in the Bengal Delta for its widespread loss of the community infrastructure and livelihood options in the agrarian system. This traditional approach to development in the context of bank erosion has been thought of in a narrower sense. Florsheim et al. (2008) probably first pointed out the desirable aspects of bank erosion. They treated riverbank erosion as a natural fluvial process that is required for creating and maintaining the eco-geomorphological behaviour and response of a fluvial system. They mentioned that in the wake of the riverbank stabilization with different measures like the civil engineering structures (tube, geotextiles, etc.), a fluvial system loses many things including loss of sediment sources, loss of geomorphic processes, loss of bank substrate, and loss of riparian forest. The pathways through which these losses are exacerbated are clearly outlined in the scheme of Florsheim et al. (2008) which is produced in Table 3.1. In brief, riverbank erosion induces diversity in the geomorphic landscape, like the creation of erosional landforms through scouring and the deposition of landforms through sediment deposit. This natural dynamic is going on since the creation of riverine surface. However, in the era of the Anthropocene, the construction of dams and barrages over the major river systems of the world has entrapped sediment loads in the reservoirs that restrict the source to sink sediment movement reducing the sediment supply for the delta-building mechanism (Alexander et al., 2012). This process of dwarfing the delta-building mechanism is accelerated by the dams in the upstream basin areas. Blum and Roberts (2009) demonstrated how the cut-off of

Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/978-3-031-47010-3_3. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Islam, S. K. Guchhait, Riverbank Erosion in the Bengal Delta, Springer Geography, https://doi.org/10.1007/978-3-031-47010-3_3

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Table 3.1 Effects of channel bank infrastructure to control bank erosion Geomorphic and ecological attribute Loss of sediment source Supply Grain size

Habitat or ecosystem service influenced Downstream sandbars as resting habitat for migrating birds. Coarse - subscribe for attachment and interstitial space for hiding from predators.

Loss of geomorphic processes Migration Widening

Newly scoured or deposited surfaces. Adjustment necessary for incised channel to evolve towards equilibrium with floodplain at elevation to support riparian plants. Vertical banks for wildlife burrowing and nesting fitter and retention of nutrients, pollutants, and water quality. Shoreline microhabitat: Soft sediment or burrows, emergent vegetation to cling to; underwater plants, snags, roots protruding from bank. Variation in nearbank flow velocity, refugia during storm flows. Protection from predators. Complex riparian vegetation, areas for wildlife: Bird breeding, nesting, safety from predators: Probing for insects under tree bark; wildlife: Food, migration corridor, and/or dispersal route; plants: Structure for vines. Shade, organic material, fish food reduction in pool complexity and depth, loss of attachment sites.

Loss of bank substrate Unconsolidated sediments Natural biotic and abiotic components of land water margin. Undercut banks

Loss of riparian forest Stream-side riparian ecosystem willow and cottonwood forests. Overhanging branches, leaves large woody debris.

Example of organism affected Whooping crane (Grus Americana). Macroinvertebrates (e.g., mayflies [Ephemeroptera], caddisflies [Trichoptera], and stoneflies [Plecoptera]). Riparian trees (e.g., cottonwood [Populus], willow [Salix], alder [Alnus]). Riparian trees (see above).

Bank swallow (Riparia riparia). Macroinvertebrates (see above). Shore – Dwelling insects (e.g., Neocurtilla); macro-invertebrates. Overwintering fish, macroinvertebrates (see above). Calfornia shrimp (Syncaris pacifica), juvenile fish (e.g., Coho salmon [Oncorhynchus kisutch]).

Birds (e.g., willow flycatcher [Empidonax traillii extimus], gila woodpecker [Melanerpes uropygialis], western yellowbilled cuckoo [Coccyzus americanus occidentalis]), reptiles (e.g., riparian lizard [Sceloporus occidentalis]), semiaquatic mammals (e.g., river otter [Lontra canadensis]), macroinvertebrates, climbing vines (e.g., river-bank grape [Vitis riparia]). Fish, macroinvertebrates (nymph and adult stages). Fish, macroinvertebrates (see above).

Source: Florsheim et al. (2008)

sediment supply from the catchment areas due to human interventions may lead to delta-building processes of the Mississippi River in the USA. They also have shown that stopping the delta-building process coupled with the sea level rise may lead to the drowning of the delta underwater. The Bengal delta is also facing a similar scenario due to the lowering of the sediment supply from the upstream basin area due

3.2

Types and Mechanisms of Bank Erosion

45

to different types of anthropogenic interventions. The major rivers of the Bengal Delta (Ganga, Brahmaputra, Tista, and Meghna) are obstructed by the anthropogenic intervention that restricts the free flow of the river and sediments. In downstream of the dams of those rivers contain minimum sediments causing the water to be sediment deficient and hence water becomes hungry for securing sediment. This causes river bank erosion in the downstream segment of the dams (Hupp et al., 2009). However, due to the longitudinal disconnection of the river due to dams, the sediment loads are carried within the channels and are deposited in the form of bars and thus the major volume of the sediments cannot enter the estuarine front for the delta buildings. By such anthropogenic interventions, the supply of sediment from riverbank erosion if entrapped by the dams may induce dwarfing of the delta building process on the one hand and river erosion below the dammed reach on the other. Thus, stopping river bank erosion is not a solution for the long-term. Rather alternative approaches need to be worked out considering the dynamic processes of conservation areas, erosion easement, elimination stressors, and non-structural approaches (Fig. 3.1). Towards achieving this, assessment of riverbank erosion as a natural process in terms of types and mechanisms, controlling factors and measurements are essential.

3.2

Types and Mechanisms of Bank Erosion

The types and mechanism of riverbank erosion is complex and hence several classification schemes are available. For example, (1) classification based on triggering forces, i.e., sub-aerial, fluvial, and mass movement is given by few scholars (e.g., Grove, 2001), (2) classification based on typical sediment and moisture conditions, i.e., gravitational failure and hydraulic failure is produced by Watson and Basher (2006), (3) classification based on the erodility and erosivity factors as produced by few scholars (e.g., Coleman, 1969; Torry & Weaver, 1984), (4) classification based on the role of vegetation on erosion process – riparian induced bank erosion and riparian inhibited bank erosion is sketched by Grove (2000). According to the first scheme, sub-aerial processes are classified as: (1) Cryergic processes (needle ice growth; ice lens growth; thermo-erosional niching; and snow-melt), (2) Pore water-associated processes (desiccation; slaking; piping and sapping; and gravel lens washout) and (3) Rainsplash processes (raindrop impact; rilling; and gullying); fluvial processes are examined mainly in the context of fluvial entrainment mechanism while mass movement as determined by the factor of safety (soil strength/soil stress) includes cantilever, planar, pop-out/draw-down, and rotational failures. Regarding the second classification scheme, gravitational failure also called mass movements is triggered by gravitational forces on an elevated river bank under low flow conditions while hydraulic failure also called fluvial erosion is caused by the riverine forces (entrainment and erosion) operating on the river bank and bed under high flow conditions. There are 12 broad categories of bank erosion mechanism of which nine mechanisms are mainly related to gravitational failure while

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Fig. 3.1 Framework for alternatives to channel bank infrastructure. Dynamic-process conservation areas protect the linkage between river channels and adjacent landscapes, and provide the highest ecological benefit to riparian ecosystems. The other alternatives provide ecological benefits to the degree that they accommodate the geomorphic processes that sustain them. (Florsheim et al., 2008)

three are to hydraulic failure or direct fluvial erosional process (O’Neill and Kuhns 1994, Thorne, 1998, Environment Agency, 1999). Regarding the third classification scheme, there are (i) erosional failure (depending on the tractive force of the river current exceeding the critical value of bank material), (ii) flow slides (depending on water level and seepage action), (iii) shear failure depending upon the shearing resistance of soil along a surface, initiated by internal erosion or over steepening of bank or pressure given by the human settlement at the edge of the bank (Parua, 1992). As per the fourth classification scheme, riparian vegetation induces Piping,

3.2

Types and Mechanisms of Bank Erosion

47

Cantilever Failure, and Windthrow while Frost Action, Desiccation, and Mass Failure are restricted by vegetation. As these classification schemes are overlapping in several cases, one scheme based on typical sediment and moisture conditions is elaborated in Table 3.2 and Fig. 3.2a–h. Table 3.2 Bank erosion mechanisms

Mechanisms Shallow slides

Classification Gravitational

Typical flow conditions Low

Rotational slip

Gravitational

Slab failure

Sediment characteristics Fine-grained, low cohesion

Bank moisture Saturated

Low

Fine-grained, cohesive

Saturated

Gravitational

Low

Fine-grained cohesive

Varies

Cantilever failure

Gravitational

Low

Composite fine/coarse

Varies

Wet earth flow Popout failure

Gravitational

Low

Saturated

Hydraulic/ gravitational

Low

Fine-grained cohesive Fine-grained cohesive

Dry granular flow

Gravitational

Low

Non-cohesive

Dry

Soil/rock fall

Gravitational

Low

Weakly cohesive

Dry

Piping failure

Hydraulic/ gravitational

Low

Interbedded fine/coarse

Saturated

Bank undercutting

Hydraulic

High

Generally non-cohesive

N/A

Bed degradation

Hydraulic

High

Relatively erodible bed

N/A

Basal cleanout

Hydraulic

Varies

All types

N/A

Saturated

Description Layer of bank material displaced along a plane parallel to bank surface Deep-seated movement along the curved slip surface Block of bank falls forwards into the channel Collapse of the overhanging block of sediment Saturated flow, often on low-angled banks Small blocks forced out of bank due to excessive pore pressure and overburden Movement of individual grains in banks close to the angle of repose Individual grains or blocks fall into the channel from very steep banks Loss of strength due to preferential flow in areas of high porewater pressure Removal of cohesive material from the toe of bank, causing bank to overhang Removal of material from the bed of the stream. Removal of (often) non-cohesive material at the base of bank

Source: After O’Neill and Kuhns (1994), Thorne (1998), and Environment Agency (1999)

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Fig. 3.2 Mechanisms of riverbank erosion through diagrams: (a) Shallow slide (from Environment Agency, 1999), (b) Rotational slip (from Environment Agency, 1999), (c) Slab failure (from Environment Agency, 1999), (d) Cantilever failure (from Environment Agency, 1999), (e) Earth flow (from Environment Agency, 1999), (f) Mechanisms of cantilever failure (Ashbridge, 1995), (g) Popout failure (from O’Neill and Kuhns, 1994), (h) Hydraulic failure mechanisms. (From O’Neill & Kuhns, 1994)

3.2

Types and Mechanisms of Bank Erosion

3.2.1

49

Mechanism of Bank Erosion: World Scenario

River bank erosion is a complex process controlled by the factors of bank material composition, bank stratigraphy, bank geometry, and more importantly the dynamics in the flow regime (Thorne, 1991). Based on the bank material composition and stratigraphy the river bank can broadly be classified as a non-cohesive, cohesive, and mixed bank. The natural river banks completely composed of cohesive or non-cohesive materials are less commonly observed while the mixed bank is common for the large rivers. For example, the study of Hooke (1979) on seven rivers of Great Britain revealed that ~50% of bank materials are cohesive in nature. The bank materials of the Mississippi River, USA exhibit cohesive materials located at the upper layer of the bank and non-cohesive materials at the bottom (Thorne, 1991; Simon et al., 2000). Besides, the Sesayap River (Indonesia) portrays that the layers of cohesive bank materials are sandwiched by the layers of non-cohesive materials (Harsanto, 2012). The different mechanical properties of the cohesive and non-cohesive river banks lead to the diversification in the types and mechanisms of river bank erosion. Non-cohesive bank materials are composed of a mixture of gravel, sand, and silt and therefore there is an absence of electrical or mechanical bonding among the particles. Consequently, non-cohesive bank materials are eroded when discrete particles are entrained (measured by shear stress and particle size). Contrastingly, in case of cohesive bank entrainment of aggregates leads to bank failure. The electrochemical forces that act within the aggregates have made the erosion process more complex. Therefore, to comprehend the complex behaviour of the cohesive bank and bank erosion, a group of geomorphologists has investigated the subaerial erosion process (Lawler, 1993; Couper & Maddock, 2001; Prosser et al., 2001) and others have focused on the hydraulic erosion process (Wolman, 1959; Hooke, 1979). Cohesive banks are found as poorly drained due to the dominance of silt and clay particles and therefore excess pore water pressure is observed as the principal agent of the subaerial erosion process. Besides, the hydraulic erosion on the cohesive bank is determined by lift and drag forces. Arulanandan et al. (1980) defined hydraulic erosion as the function of the magnitude of excess shear stress that can be expressed as (τ - τc), where τ is applied shear stress by flow while τc denotes the critical shear stress. Moreover, the force-resistance relationship, flow variability, and diversified effects of vegetation have increased the complexity of the hydraulic erosion process on the cohesive bank.

3.2.2

Bank Erosion Scenario of Bengal Delta

(a) Bhagirathi River The sedimentological characteristics on either side of the Bhagirathi River are pronounced in the previous studies. For example, Mukherjee and Fryar (2008)

50

3 Riverbank Erosion: A Natural Process

demonstrated that the sediments deposited on the western side of the river are old (Precambrian) and Cratonic in nature dominated by hard clay, whereas, the sediments of the eastern side are of Himalayan origin, younger (early CretaceousHolocene) dominated by soft-silt. Sarkar and Islam (2021) studied the sub-surface stratigraphic records of both sides of the Bhagirathi River. The sediment samples collected from the boreholes located in the western part of the study area are enriched by different types of clay such as sticky clay, grey soft clayey silt, and clay with carbonaceous matter. Contrastingly, the east bank shows the domination of sands of different sizes (Sarkar & Islam, 2021) (Fig. 3.3a, b, c). Change in river discharge leads to changes in water level. Discharge is always positively correlated with the water level, though having a different magnitude of correlation depending on local geomorphological and geohydrological characteristics. From the rating curve of the stage-discharge relationship, it is observed that Berhampore is showing a stronger correlation in the treaty period while relatively weak in the non-treaty period – a clear indication of controlled hydrology. A reverse scenario is observed for Katwa triggered by the Ajay-Mayurakshi system (Fig. 3.4a, b). This stage-discharge relationship frequently oscillates tuning with the controlled river regime during the lean period and peak river regime during the freshet period contributed by the Ajay-Mayurakshi system. Thereby, if the water level is changed frequently, there will be corresponding changes in river bank erosion through seepage effects. If the water level changes frequently, seepage effects will produce equivalent changes in river bank erosion. The movement of the pore-water within the bank is the most exciting aspect of a high-flow occurrence. As flood water rises, increased hydraulic head allows water to enter into the river banks and helps in the groundwater recharge. When the bank-full stage is over, the hydraulic gradient is changed causing flow reversal, i.e., water seeps from the banks into the river. Hagerty refers to this process as “piping”, in which outflowing water can entrain and extract grain from a layer of sand (Hagerty, 1991a, b). Piping erosion leads to the undermining of overlying, less pervious layers causing distortion and deflation (Bernatek-Jakiel & Poesen, 2018). The most typical outcome of this undermining is the development of fractures in the undermined layer when the soil is unable to withstand the tensile strains brought on by deflation (Hagetry et al., 1995; Thorne, 1998) (Fig. 3.5a). Mass wasting occurs as the cracking reduces the operational strength of the bank (Thorne, 1998). The gully development is a different type of bank collapse with significant seepage (Istanbulluoglu et al., 2005). While the creation of gullies is typically thought to be the consequence of surface erosion, the piping may cause subsurface erosion that causes the pipe to collapse and create gullies along stream banks (Harvey & Watson, 1985; Bernatek-Jakiel & Poesen, 2018). Besides this piping, another type of mechanism responsible for erosion along the banks is cantilevered slumping – a slight variation from the piping erosion. This type of erosion is mainly observed in the bank where it is mainly constituted by two layers: the upper being constituted by the cohesive materials and the lower by the unconsolidated materials. Removal of the lower non-cohesive layer leads to the

3.2

Types and Mechanisms of Bank Erosion

51

Fig. 3.3 Lithological composition of the sediments along the Bhagirathi River, (a) location of the boreholes (BH), (b) western and (c) eastern bank lithologs (Note: BH-1 at Ghola, BH-2 at Kobla, BH-3 at Islampur, BH-4 at Vidyanagar, BH-5 at Madhupur, BH-6 at Gotra, BH-7 at Narayanpur, BH-8 at Tatla, and BH-9 at Mayapur; BH-1 to BH-5 from Purba Barddhaman district and BH-6 to BH-9 from Nadia district)

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15 y = 0.0032x + 11.006 R² = 0.9547

Water Level in mGTS

14

a

13 12

Berhampore Katwa

11

Linear (Berhampore) Linear (Katwa)

10 y = 0.0026x + 6.5618 R² = 0.8289

9 8 600

17

700

800

900 1000 Discharge in Cumecs

1100

y = 0.0035x + 10.678 R² = 0.874

16

1300

b

15

Berhampore Katwa Linear ( Berhampore) Linear (Katwa)

14 Water Level in mGTS

1200

13 12 11 10

y = 0.0013x + 8.2764 R² = 0.9113

9 8

900

1200

1500

1800

2100

2400

2700

3000

3300

3600

Discahrge in Cumecs

Fig. 3.4 Rating curve of the Bhagirathi River, (a) treaty period, (b) normal period (computed from hydrologic data, 2005–2009, CWC, India). Note: GTS stands for Great Trigonometrical Survey

slumping of the upper consolidated layer by hydraulic forces (Johnson & Stypula, 1993) (Fig. 3.5b). Fluctuation in water level leads to piping action and slumping erosion along the banks of the river Bhagirathi. In the post-Farakka period, erosion has become recurrent due to regulated flow as well as discharge in the freshet period. Thus, Farakka Barrage Project (FBP) has survived Kolkata port at the cost of river bank erosion year-round, especially at the lower reach of Bhagirathi (Islam & Guchhait, 2017a, b). (b) Padma-Meghna River The Bengal basin is a large sink of sediments drained by the rivers of Ganga and Brahmaputra. A number of studies on sub-surface stratigraphic records unveil an intriguing history of Quaternary sediment deposition controlled by the combined

3.2

Types and Mechanisms of Bank Erosion

53

Fig. 3.5 Bank erosion in response to material composition, (a) Bank erosion due to piping (based on Hagerty, 1991b), (b) Stratified stream banks and combination failures along the banks of river Bhagirathi. (Based on Johnson & Stypula, 1993)

effect of tectonic and fluvial activities (Banerjee & Sen, 1987; Goodbred Jr. & Kuehl, 2000; Goodbred Jr. et al., 2003; Allison et al., 2003). Goodbred Jr. and Kuehl (2000) observed fining upward sand layers along the Jamuna River, especially, the fine sandy layer up to 15 m underlying the medium sandy layer (15–40 m) and coarse sandy layer (45–100 m). The sub-surface stratigraphy also observed by Goodbred Jr. and Kuehl (2000) along the Padma River exhibits a fine silty upper layer extending up to 5 m followed by a deeper (up to 90 m) fine sandy layer. Sinha et al. (2005) demonstrated that the sub-surface stratigraphy in the lower Ganga plains is dominated by sand of different sizes which also reflected the findings of Goodbred

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Jr. and Kuehl (2000) and Allison et al. (2003). Moreover, Nawfee et al. (2018) studied the erosion–accretion process of the selected channel bars developed on the Padma River, integrating sub-surface stratigraphic records and satellite images. They observed a thin layer of uniform mud layer at the bottom (>20 m) overlayed by a massive sandy layer (the determining layer of bank stability). Williams (2014) found that mud is preserved up to a few meters thick in the surficial Meghna River bank stratigraphy. The overbank muds are separated by sand layers that range from a few meters to 10 m. In all the cases, variable river regime leads to erosion of sandy bank, the main reason for bank erosion in the late monsoon period.

3.3

Riverbank Erosion Factors

In plain eyes, it is easy to observe and understand the bank erosion phenomena, especially for the people who are residing by the side of the middle or lower course of the larger rivers, but to explain the factors and their critical role requires a deep investigation. The factors triggering riverbank erosion have been identified by various scientists across the world. Knighton (1999) and Bandyopadhyay (2007) have shown various factors of bank erosion viz. flow characteristics (variability of stream discharge, degree of turbulence, flow velocity, etc.), bank material composition (particle size, gradation, the cohesiveness of the materials, etc.), climate (dry and wet cycle, amount and intensity of rainfall, temperature fluctuation, etc.), subsurface conditions (seepage force, pore water pressure, etc.), channel geometry (width, depth, the slope of the channel, bend curvature, etc.), biology (presence or absence of vegetal cover, etc.), and anthropogenic factors (urbanization, bank protection measures, etc.) (Table 3.3). Besides these general causal views of bank erosion,

Table 3.3 Factors triggering bank erosion Factors Flow properties Bank material composition Climate Subsurface conditions Channel geometry Biology Man induced factors

Relevant characteristics Magnitude frequency and variability of stream discharge; magnitude and distribution of velocity and shear stress; degree of turbulence Size, gradation, cohesivity, and stratification of bank sediments Amount, intensity, and duration of rainfall; frequency and duration of freezing Seepage forces, piping; soil moisture levels, porewater pressures Width, depth, and slope of the channel; height and angle of bank; bend curvature Type, density, and root system of vegetation; animal borrows and trampling Urbanization, land drainage, reservoir development, boating, bank protection measures

Source: Knighton (1999)

3.3

Riverbank Erosion Factors

55

several eminent scientists have assigned some factors more important than others. Lacey (1939, 1958) and Leopold and Maddock (1953) have found that bankfull discharge is of critical importance to determine the stable channel geometry in relation to the width, depth, and velocity of rivers varied with their mean annual discharge. Parua (2010) placed a high value on engineering aspects like faulty design and construction. In general bank, erosion is triggered by several factors. In the context of the river Bhagirathi, bank erosion has been analysed from two basic perspectives: erodibilty of soil and erosivity of water. Erodibility is conditioned by soil characteristics along the banks, while erosivity relates to variable flow characteristics of the river (Wallick et al., 2006; Naimah & Roslan, 2015). So, these two aspects deserve a special explanation before going into the ins and outs of river bank erosion hazards.

3.3.1

Erodibility Factors

Erodibility factors are related to the bed and bank material compositions. It is noticed that the banks of the river Bhagirathi (especially in the lower reach from Katwa to Nabadwip of West Bengal, India) are constituted by the soil having an upper silty layer and a lower sandy layer (Parua, 1992) or sandy layer across the whole profile (Figs. 3.6 and 3.7). At Akandanga and Char-Kashthasali soil is constituted by upper stiff dark grey clayey silt layer up to a maximum of 10 m and a lower sandy layer up to 16 m (Fig. 3.6). At Matiari and Rukunpur mouzas, virtually the whole soil profile is constituted by a loose fine sand layer with grey silt up to 16 m (Fig. 3.6). The very weak texture of soil of this area makes the river bank vulnerable to erosion in terms of fluvial hydro-dynamics. Therefore, the undercutting of subsurface sandy banks by the river water leads to the slumping of banks. Again if the silty surface layer, a relatively cemented layer, is removed by the cutting of surface soil, bank erosion is expedited. Intensive field-based investigation and analysis of the left bank of Bhagirathi are portrayed to grasp the erosivity and erodibility. This removal of surface soil is noticed along the sample sites of the river Bhagirathi for the brickfield industry and other construction works very close to the riverbank. Bank line shifting and severity of bank erosion is the common parlance along the tail reach of Bhagirathi in general and selected mouzas in particular. The shifting of the river Bhagirathi is confined to a certain limit. Though the river follows a cycle of revisit period of 200–250 years (Islam, 2012), at present left bank towards the east is more oscillating (shifting from one position to another) for two basic reasons viz. eastward tilting of the Bengal basin and lithological composition of the basement layer.

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Riverbank Erosion: A Natural Process

Fig. 3.6 Lithological composition along the left bank of Bhagirathi river. (Source: Parua, 1992) (Note: Location of selected study sites – Matiari, Akandanga, Rukunpur, and Char-Kashthasali is shown in Fig. 2.5 in Chap. 2; areas with clayey silt are located in few pockets marked by solid tilted line while other areas are dominated mainly by fine sand shown with dotted tilted lines; vertical pipes with solid lines are the location of the boreholes; offtake is the point where Bhagirathi River bifurcates near Jangipur; Si for silt (%), Sa for sand (%), C for clay (%), and N for Standard Penetration Test value for relative density of soil (N 0–4 very loose, 5–10 loose, 11–30 medium, and 31–50 for dense)

3.3.2

Erosivity Factors

The erosivity of water refers to the capacity of water to erode the soil or land (Brady et al., 2008). The capacity of water depends upon various fluid dynamics in relation to velocity, density, viscosity of water, and water level. Density and velocity, being the other factors, tend to enhance the probability of erosion while viscosity attempts to retard this. The hydrodynamics of a river depends on its discharge and sediment load. On the one hand, with the increasing discharge, there may be a corresponding

3.3

Riverbank Erosion Factors

57

Fig. 3.7 Riverbank composition and nature of erosion. (a) Mixed bank composition, formation of tunnel or piping, cracks and undermining, (b) Soil profile dominated by loose unconsolidated sand in its lower portion often induces combinational failure, (c) Mixed soil profile with clay and silty dominance in the upper portion, (d) Bank erosion by sliding on the bare surface. (Source: Field Photographs, 2013–2015)

increase in the magnitude of scouring and bank erosion. Fluctuation in discharge and the water level may intensify bank erosion processes also (Knighton, 1999). The erosivity of water in the river Bhagirathi is affected by the amount of discharge and fluctuation in the river regime, which causes bank erosion via numerous mechanisms. The following section will focus on the variable river regime of Bhagirathi and the associated mechanism of bank erosion, especially the impact of variable discharge upon bank erosion.

58

3.3.2.1

3

Riverbank Erosion: A Natural Process

Erosivity Under Monsoon Regime

Climate plays a pivotal role in riverbank erosion. The precipitation and temperature regime principally control the nature and intensity of riverbank erosion in any climatic region. The annual fluctuations in the temperature and precipitation regimes control the higher rates of erosion compared to the uniform distribution of temperature and precipitation. For example, in the monsoon regime, 80% of rainfall is concentrated within three-four months (July–October) triggering an intensified erosion after a long dry spell. Thus, 80% of the annual total discharge volume occurs during the monsoon season, i.e., July–October (Kale, 2003). All the rivers of the GBM delta, thus, typically show high flood peaks during the monsoon months causing annual floods and riverbank erosion. Darby et al. (2013) indicated the role of monsoon run-off on riverbank erosion; however, it is yet unknown how high flows affect morphological changes, such as riverbank erosion. In recent decades, few researchers have tried to measure bank erosion and the morphological changes vis-à-vis the peak water level (e.g., Bertoldi et al., 2010). Moreover, another group of scholars focusing on the relationship between river discharge and changing river width (Baki & Gan, 2012, Ashraf et al., 2016) has demonstrated that high flows during the monsoon season are found to introduce the morphological changes and bank erosion of a sand-bed braided channel like the Chenab River, Pakistan. They found that the maximum shifting of the channel was 208 m along the left bank of the Chenab River due to the monsoon spell. Similarly, the annual discharge hydrograph of the Ajay River in India (Fig. 3.8) depicts an extremely high peak during the monsoon months; however, the rest of the period becomes dry (Guchhait et al., 2016). Ghosh (2011) also mentioned the monsoon-induced river bank erosion and channel oscillating along the Mundeshwari River in the Damodar River Basin. Additionally, during the dry season (November to May), flows in the Dudhkumar River at Pateswari (Fig. 3.9), Bangladesh, drop to an average of 159 m3s-1, whereas the average flow during the monsoon season (June to October) is roughly 897 m3s-1 (Pal et al., 2017). In Bangladesh, extensive overbank spills and riverbank erosion are common. The major rivers in Bangladesh show channel oscillation from 60 m to 1600 m annually (Rahman, 2010). The unpredictable shifting behaviour of the rivers is principally controlled by the vagaries of the monsoon. Aktar (2013) also found that flood and riverbank erosion are concurrent in the monsoon season or flood is followed by riverbank erosion. This study also denotes that riverbank erosion is positively correlated with the peak discharge of the rivers. Due to global warming and an increase in precipitation, annual flood discharge of the rivers is also expected to increase by 15% and 20% for the years 2050 and 2100 with a corresponding increase in the riverbank erosion rates by 13% and 18% (Aktar, 2013). Moreover, Darby et al. (2013) pioneered a study to show the proportion of the snow melt water, tropical monsoon precipitation, and tropical cyclones to trigger river bank erosion of the Mekong River using accumulated excess run-off (AER), Indian Ocean Dipole (IOD), and El-Nino Southern Oscillation (ENSO) factors. The study demonstrates

3.3

Riverbank Erosion Factors

59

450 404

400 350 Discharge (m3/s)

Actual Discharge 300 Mean Discharge 250

248

200 165

150

104

100 50 0

9.6

4.8

0.9

0.76

45

13

11.02

0.54

Fig. 3.8 Discharge hydrograph of river Ajay at Natunhat gauge station, 2000. (Source: River Research Institute, Kolkata, 2000)

Fig. 3.9 Variation in flow and water level at Pateswari of Dudhkumar River, Bangladesh (Note Q for discharge and WL for water level, PWD for public works datum, Bangladesh). (Pal et al. 2017)

that the lower Mekong River basin experiences river bank erosion due to the tropical monsoon precipitation coupled with the tropical cyclone (MRC, 2005).

3.3.2.2

Tidal Upsurge and Storm Surge

Tidal upsurges and tropical cyclones have a significant impact on the nature and intensity of riverbank erosion in coastal regions. Tidal upsurge-induced river and

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3 Riverbank Erosion: A Natural Process

coastal erosion are mainly concentrated in the lower stretches of the rivers (tidally active) such as the Hooghly River, Padma, and Meghna. Hooghly River (India) exhibits a pronounced tidal prism due to the upsurge of the tidal waves and downstream flow of the river discharge inducing turbulence on the riverbank that results in bank erosion (Das et al., 2021). Moreover, tidal amplification is augmented by some human activities. For example, the development of the polder land in Bangladesh led to rising high water, channel capture, and riverbank erosion (van Maren et al., 2022). Besides, the role of tropical cyclones (TC) in bank erosion is also documented worldwide. The Bay of Bengal observes TCs regularly, especially in Bangladesh, India, and Myanmar with great storm surges and river bank erosion (Mandal et al., 2021). Moreover, increased rainfall following a TC is also a contributing factor to bank erosion. For example, Darby et al. (2011) show that during 1981–2005 tropical cyclones (TCs) contribute an average of ~7% of the total annual precipitation, but since the TCs-derived rainfall is received within the monsoon season, this is hydrologically effective for riverbank erosion. Thus, on average, TCs are found to contribute between 9% (upstream study site) and 21% (downstream study site) of the Lower Mekong River (LMR) runoff above the threshold for bank erosion. Consequently, Darby et al. (2011) have proved that TCs contribute on average 18% (upstream study site) and 26% (downstream study site) of the total simulated bank erosion during the 1981–2005 period. Using a hydrological model, he demonstrated that tropical cyclones contributed to the development of riverbank erosion at the rate of 17.5% and 26.4% in the upstream and downstream areas of the Mekong River respectively.

3.3.2.3

Variable River Regime

Variable river regime is one of the most triggering factors for bank erosion of the rivers of the tropical and subtropical climate because of their variable river regime owing to highly concentrated seasonal rainfall that leads to peak discharge at the end of the wet period and very low discharge at the end of the dry period. In both tropical and subtropical monsoons, more than 70% of rainfall occurs within 3 months of the wet period. Interestingly, in the study area banks of the larger rivers in many locations are sequenced with alternate sand or silt layer or course and fine sand. Under variable river regimes, sand layers of the banks are susceptible to erosion during peak periods as the turbulence of flow is intensified frequently during peak discharge having a scouring effect leading to the dislocation of sand material from banks. (a) Variable River Regime Through the Ajay-Mayurakshi System The Ajay-Mayurakshi system provides huge momentum to the Bhagirathi-Hooghly system, especially in its lower reach in the form of huge discharge and sediment load in the monsoon period, which has a significant impact on channel instability in this tail reach. The impact of such a variable river regime is discussed in the following sections.

3.3

Riverbank Erosion Factors

61

(i) Instability Through Discharge Discharge, an important indicator of river dynamics, is perhaps the most determining factor in the lower course of a river. The higher the discharge, the greater the power to work for a river. The strong channel instability in the lower reach of the Bhagirathi (from Katwa to Nabadwip) may be caused by the significant discharge generated by the Ajay-Mayurakshi System. On average, flood discharge contributed by the river Ajay and Mayurakshi (through Babla) to Bhagirathi is 1800 cusec and 1500 cusec respectively (Parua, 1992). O’Malley (1910) through his work Bengal District Gazetteers of Birbhum mentioned some of the historically important floods of these rivers for the years 1787, 1806, and 1902. Such devastating floods washed away most of the villages around the river during the monsoon period. Therefore, the maximum proportion of discharge is coming through Ajay and Mayurakshi (Babla) in the monsoon months (July to mid-October) (Parua, 1992). Major tributaries contributing to the river Bhagirathi are Bansloi, Pagla, Babla, Ajay, and Jalangi. Ajay-Mayurakshi and Jalangi rivers override the contribution of Bansloi and Pagla in respect of maximum discharge (Table S3.1). Apart from the monsoon discharge, the lean period (January to May) river discharge also fluctuates at the gauge stations of the Feeder canal, Berhampore, and Katwa on a 10-day scale in the sequel to the Indo-Bangladesh water sharing treaty. However, the hydrograph at Katwa station, immediately below the confluence of Ajay and Mayurakshi with Bhagirathi, portrays a different picture. It clarifies that discharge is more variable in the freshet period (monsoon months), not in the lean period. This conclusively proves the contribution of Ajay and Mayurakshi to the discharge of the river Bhagirathi in the freshet period. It is interesting to note that the maximum discharge recorded in the Ajay-Mayurakshi system occurs in July– August, for which coefficient of variation (CV) of annual discharge is also maximum in the freshet period as well. The peak discharge of Bhagirathi is mostly synchronized with the discharge peak of the river Ajay which is undoubtedly an outcome of monsoon rainfall from July to October (Fig. 3.10). Thus in the upper and middle reaches of Bhagirathi, frequent river bank erosion has been observed from 1978 to 2000 due to disequilibrium of the river regime induced by Indo-Bangladesh water sharing treaty (1977, 1996). This disequilibrium has decreased after 25–30 years. However. this erosion had no such seasonal bias as the variation of discharge occurs at a 10-day scale. The eastern bank of the upper and middle reaches of Bhagirathi was more prone to erosion and the residents nearby the bank (Under Murshidabad district) were mostly affected by such anthropogenic disturbance. In another context, the lower reach of Bhagirathi has a distinctly seasonal bias of bank erosion as Mayurakshi and Ajay contribute a huge amount of discharge and load during the monsoon leading to severe bank erosion during the late monsoon period (Islam & Guchhait, 2017a). (ii) Instability by Sediment Supply The negentropy of a river is disturbed by the supply of sediment and its deposition under varying discharge (Leopold & Langbein, 1962; Bandyopadhyay et al., 2014)

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Fig. 3.10 Typical hydrograph of Bhagirathi-Hooghly system. Note: the arrow indicates the synchronization of the peaks between the Ajay and Bhagirathi Rivers. (Source: Central Water Commission, India)

bringing out instability by maximizing entropy. Totally clear water devoid of any sediment and high sediment-laden water both have the minimum power to erode. Hence, a river optimally sediment-loaded may enhance the turbulence of the flow by increasing the particle Reynolds number to destabilize the riverbank. Tributaries of the river from both the left bank and right bank control the sediment budget of the river Bhagirathi. Hence in the downward direction, the sediment load of the river increases (Table 3.4). It has been observed that Ajay and Mayurakshi contribute 1.39 million tons and 2.52 million tons of sediment load annually to the river Bhagirathi respectively (Rudra, 2011) most of which is contributed during the monsoon period. Besides the quantity, the particle size of the sediment may influence flow characteristics and the nature of erosion. Abrasion, attrition, and hydraulic action will be more effective for the flow containing sediment having a D50 value within the range of 0.20–0.50 mm. As per the rule of the Hjulström curve (Fig. 3.11), entraining velocity will be required minimum for bed material having a D50 range from 0.2 to 0.5 mm. Below 0.2 mm it will be cohesive and above 0.5 mm it will be heavier. So, scouring and consequent bank erosion will be the maximum for bed material having D50 ranging from 0.2 to 0.5 mm. From feeder canal outfall to Katwa and from Katwa to Baladanga D50 of the bed material is in the ideal range (KoPT, 2008) for entraining with minimum velocity.

3.3

Riverbank Erosion Factors

63

Table 3.4 Suspended sediment load through Bhagirathi and its tributaries

River and gauge station Bhagirathi at Jangipur Bhagirathi at Berhampore Bhagirathi at Purbasthali Ajay at Natunhat Jalangi at Chapra Hooghly at Kalna

1973 Sediment load (106 T)/ million tons 6.29

Total run-off (106 Acre-Ft) 4.93

1978 Sediment load (106 T) 8.53

Total run-off (106 Acre-Ft) 18.98

1983 Sediment load (106 T) 7.05

Total run-off (106 Acre-Ft) 27.12

9.16

7.02

12.76

32.02

13.98

29.11

9.43

8.74

8.42

38.93

12.17

45.07

1.44 5.11 7.36

1.74 5.49 15.46

0.89 6.12 19.13

1.35 4.86 65.3

1.35 3.82 22.7

3.63 4.03 31.38

Source: Parua (1992) 1000

Erosion

Flow speed [cm/s]

100

10

Transport

1

Deposition

1000

100

10

1

0.1

0.01

0.001

0.1

Grain size [mm]

Fig. 3.11 Hjulström curve to indicate the nature of erosion, deposition, and transportation (Source: Hjulström, 1935). Erosion is maximum for medium-grade sediment (0.01 to 1 mm) because beyond the scale sediment will be more finer, i.e., cohesive or coarser, i.e., heavier resisting bank erosion

To study the turbulence of the flow of Bhagirathi below Berhampore and Katwa, Reynolds numbers have been computed using the formula of Chattopadhyay (2011) using Eq. 3.1: Re =

vR u

ð3:1Þ

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Riverbank Erosion: A Natural Process

where Re for Reynolds number, v mean flow velocity, R hydraulic radius, and u kinematic viscosity. The computed value of Re shows that in the lower reach of Bhagirathi below Katwa, turbulence becomes more than in Berhampore in the freshet period with a higher Reynolds number (Table 3.5). But Reynolds number at downstream of Berhampore shows a higher value than Katwa during the treaty period. Thus Table 3.4 clearly shows the reversal of Reynolds number from the freshet period to the treaty period as measured in Berhampore and Katwa during the assessment period. This exhibits the higher role of controlled hydrology (FBP influenced) for upper and middle reaches compared to the lower reach of the Bhagirathi River. The higher the Re, the greater the turbulence. The river Bhagirathi, being a large river, always records turbulent flow in the stretch below Berhampore and Katwa both in lean and freshet periods even in the pre-Farakka stage (before 1975 when Farakka barrage project was not installed) when a space-time averaged approach is embraced (Table 3.5). A higher Reynolds number in this reach below Katwa is triggered by higher velocity and discharge which are responsible for the higher rate of bank erosion than that of the stretch above Katwa. It has been observed that upstream of the Ajay-Bhagirathi confluence (from the Feeder canal outfall to Katwa) contains lower D50 (of bed sediment) in comparison to the downstream of Ajay-Bhagirathi confluence (Katwa to Baladanga) (Fig. 3.12). River Ajay and Mayurakshi both are coming from the Chhotonagpur plateau. Their D50 is higher than that of (sediments of upper reaches are mainly from the Himalayan region) Bhagirathi as sediment of the plateau tract is relatively coarser (Fig. 3.13). Higher D50 below Katwa (due to the supply of coarse sediment by Ajay-Mayurakshi) induces more scouring and erosion by higher particle Reynolds numbers.

3.4

Measurement of Riverbank Erosion

Measuring riverbank erosion in quantitative terms is important in bank erosion research to better comprehend the dynamics of riverbank erosion (Table S3.3). Linjuan et al. (2019) stated that before the year 1970, the research on riverbank erosion was relatively less. Researchers faced difficulties to study the mechanism of riverbanks due to the lack of advanced tools, techniques, and mathematical models. Abdul-Kadir and Ariffin (2012) found significant progress in the methods and techniques of measurement and monitoring of river bank erosion between 1992 and 2008. During this period, Diffuse Reflectance Infrared Fourier Transform (DRIFT) (Poulenard et al., 2009), Planimetric resurvey with the use of LIDAR remote sensing (Thoma et al., 2005), Photo Electronic Erosion Pin (PEEP) (Lawler & Leeks, 1992; Lawler, 1993), and PEEP-3 T (Lawler, 2008) were developed. However, in the recent decade, various tools and techniques have emerged as the most efficient and user-friendly providing the highest level of measurement accuracy.

a

Time Treaty period (April) Normal period (July) Treaty period (April) Normal period (July) 9.35226E-07 8.73744E-07

23

25.9

8.93565E-07

25

2218

874

1336

Discharge (cumecs) 878

0.913

0.784

0.882

Velocity (m/s) 0.853

6.127

4.873

5.092

Hydraulic mean radius (m) 4.986

Kinematic viscosity has been calculated from temperature (Computed from the hydrologic data of KoPT: 2011–2015)

D/S of Katwa

Location D/S of Berhampore

Kinematic Viscositya (m s) 9.57048E-07

Temperature (°C) 22

Table 3.5 Reynolds number downstream of Berhampore and Katwa in the pre-Farakka and post-Farakka period

6260695

4206266

5140584

Reynolds Number (VR/u) 4621904

3.4 Measurement of Riverbank Erosion 65

66

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Riverbank Erosion: A Natural Process

D50 (mm) of bed sediment

0.3 0.25 0.2 0.15 Feeder canal out fall to Katwa 0.1

Katwa to Baladanga

0.05 0 2002-03

2003-04

2004-05 2005-06 2006-07 Observation year

2007-08

2008-09

Fig. 3.12 D50 of bed materials between Feeder canal to Baladanga. (Source: KoPT, 2003–2009)

Fig. 3.13 Typical coarse sandy river bed of Ajay, (a) Ramudih, Jharkhand, (b) Natunhat, Mongolkote, West Bengal, 2012. (Source: field photograph, 2012)

3.4.1

Field Techniques

3.4.1.1

Erosion Pin

The use of erosion pins is a traditional, simple, robust, and relatively cheap technique in geomorphology for estimating the rates of erosion at a fine scale. Though the technique is widely used in badland environments, it is also effective for river bank erosion research as appeared first in the work of Wolman (1959) and was later popularized by its wide application in the 1970s by subsequent researchers (Bergman & Sullivan, 1963; Slaymaker, 1972; Knighton, 1973). In recent decades, advanced techniques are available in bank erosion research but the erosion pin method is still existing with the other methods (Fig. 3.14).

3.4

Measurement of Riverbank Erosion

67

Fig. 3.14 Development of instruments for measuring the vertical profile of stream bank. (a) Erosion pins, (b) Total Station, (c) Terrestrial laser scanning. (Source: Myers et al., 2019)

3.4.1.2

Photo Electronic Erosion Pin (PEEP) and PEET-3T

Photo-Electronic Erosion Pin (PEEP) is an improved system used in geomorphology to gather data on the occurrence, frequency, and lateral dimension and volume of erosional and depositional processes. The technique was first introduced by Lawler and Leeks in 1992. The PEEP sensor is a common example of a basic optoelectronic device. It consists of a row of parallel solar cells linked in series, each with an overlapped photovoltaic cell, and is housed inside a waterproof, clear acrylic tube with dimensions of 12 mm ID and 16 mm OD. In proportion to how long the PEEP tube has been exposed to light overall, the sensor produces an analogue voltage. It provides high accuracy on measurements (standard error or SE for estimated length ranges from 2 to 4 mm). One of the major limitations of this technique is that it can only measure events above the water level. The PEET-3T resolution system, which Lawler and Leeks (1992) introduced, is an upgraded technique that can more precisely identify changes in bank erosion events.

3.4.1.3

Total Station and Terrestrial Laser Scanner

The application of laser technology in the field of erosion science has made a revolutionary change in the way of investigation, measurement, and monitoring of erosion processes of natural phenomena such as sea cliffs, streambank dynamics, and gully erosion. Light Detection and Ranging (LiDAR), an advanced data acquisition technique related to landform dynamics, provides a useful opportunity to quantify river bank erosion with unprecedented resolution (mm to cm) and a high level of accuracy. One of the significant advantages of LiDAR is its ability to penetrate through vegetation cover. The laser pulses emitted by the LiDAR system can reach the ground surface by passing through gaps between leaves and branches. This capability allows for the detection and modelling of the underlying terrain, even in densely vegetated areas. Therefore, hand-held LiDAR systems have significant applications in the measurement and monitoring of river bank erosion, particularly in vegetated riverbank environments. LiDAR uses an airborne sensor (ALS) and a terrestrial laser scanning sensor (TLS) for data acquisition. ALS is generally applied

68

3 Riverbank Erosion: A Natural Process

for surveying a large area while TLS is best suited for efficiently measuring the microtopographic changes with high horizontal and vertical resolution. TLS is generally applied in engineering and structural science but in recent times it has gained the attention of scientists working in the field of geological and geomorphological science and the application of TLS in erosion science has become more common among geologists and geomorphologists. For example, Perroy et al. (2010) applied both the ALS and TLS for measuring the gully erosion on Santa Cruz Island in California. Young et al. (2010) also quantified the changes in the sea cliff of DelMar in California. Li et al. (2020) quantified the short-term changes in erosion and deposition of the active gully of Meeman-Shelby Forest State Park, USA using TLS technology. Heritage and Hetherington (2007) mentioned a few protocols regarding the use of TLS in fluvial morphology such as positioning of TLS for minimizing shadow obstruction, placing a target for a three-dimensional view, and repeating TLS scanning from a fixed point. Moreover, the TLS is also used for measuring the volume and rate of river bank erosion. For example, Myers et al. (2019) applied three measuring techniques: (a) erosion pins, (b) total station, and (c) TLS for measuring the volumetric changes in stream bank of Indian Mill Creek watershed, USA and finally they compared the results of the three selected measuring techniques. Moreover, the limitation of TLS application in estimating river bank erosion include (a) the incapability to scan the underwater river bank topography, and (b) difficulty when the river bank is covered with highly thick vegetation (Longoni et al., 2016).

3.4.2

Existing Models on River Bank Erosion

3.4.2.1

Bank Assessment of Non-point Source Consequence of Sediment (BANCS)

BANCS is the reach-scale model for the prediction of river bank erosion. The model combines two tools of bank erodibility, i.e., bank erosion hazard index (BEHI) and near bank stress (NBS) (Bigham et al., 2018). In BEHI, ten variables are included as predictors of river bank erodibility (Table 3.6). All the variables are transformed into risk ratings from 1 as very low to 10 as extreme risk and then to achieve the overall BEHI rating, they all are summed up (Table 3.7). Finally, the overall BEHI rating indicates the erosion potentiality where 45 as extremely high erosion potential. Near Bank Stress (NBS) estimates the level of shear stress acting upon the river bank due to channel hydraulic conditions. The rating of NBS follows seven methods however one or more methods can be considered depending on the bank condition and availability of data. The parameters of the model inputs are dependent on the selection of the methods (Table 3.8). Finally, the ratings, ranging from 1 as very low to 7 as extremely high, are provided for all the selected parameters (Table 3.9).

3.4

Measurement of Riverbank Erosion

69

Table 3.6 Description of the BEHI model input parameters. (Rosgen, 2001) BEHI variables Ratio of bank height/bankfull height Bank height Bankfull height

Ratio of root depth/bank height Root depth Weighted root density Root density Bank angle Surface protection Bank material adjustment

Stratification of bank material

3.4.2.2

Description Incision measurement, which suggests that a non-incised river has better access to the floodplain for energy dissipation during high flows. The ratio closer to 1 suggests a lesser risk of bank erosion. The height is calculated from the bottom of the bank to the top. It is calculated by measuring the distance from the toe to a bankfull indicator which might be a change in slope or particle size distribution. It calculates the structural reinforcing given by roots. It is calculated by measuring the distance from the top of the bank to the extent of the dominating roots. It is calculated by multiplying the root density by the root depth/bank height ratio. It refers to the proportion of the stream bank that is made up of roots. Measured in degrees A measure of how much of the streambank is covered in vegetation, dead wood, rocky outcrops, etc. The BEHI score total should be adjusted (parameters 1–5). If bedrock, the total BEHI is very low. Boulder results in a BEHI score of low overall. If not, according to the bank material, subtract up to 20 points or add up to 10 points. If cobble, subtract 10 points. Silt/clay: If mostly clay, subtract 20 points; otherwise, make no adjustments. Add 5–10 points (depending on % of sand) to the gravel or composite matrix. Sand (add 10 points). Based on the existence and characteristics of bank strata that might be prone to piping or entrainment, adjust the total BEHI score (parameters 1–6) (add 5–10 points).

Unit –

Data source Field measurement

m

Field measurement Field measurement

m

– m % %

% –

–

Field measurement Field measurement Field measurement Field observation Field measurement Field observation Stand measures

Stand measures

The Bank Stability and Toe Erosion Model (BSTEM)

The model was developed to predict the bank stability and toe erosion of river banks at a selected section. Two models, i.e., the bank stability model or BSM for simulating mass failure based on hydraulic and geotechnical processes and the toe erosion model or TEM for fluvial scouring in riverbanks are included in BSTEM (Midgley et al., 2012) (Fig. 3.15). In this model, the user needs to have different kinds of data as model inputs. The inputs are (1) geometric parameters of the river bank (bank geometry, reach length, reach slope), (2) flow condition (flow

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Riverbank Erosion: A Natural Process

Table 3.7 Criteria selected for converting stream bank erodibility variables to BEHI ratings. (Rosgen, 2001) Adjective hazard or Risk rating categories Very low Low Moderate High Very high Extreme

Value/ score Value Score Value Score Value Score Value Score Value Score Value Score

Bank height/ bankfull height 1.0–1.1 1.0–1.9 1.11–1.19 2.0–3.9 1.2–1.59 4.0–5.9 1.6–2.0 6.0–7.9 2.1–2.8 8.0–9.0 >2.8 10

Root depth/ bank height 1.0–0.9 1.0–1.9 0.89–0.5 2.0–3.9 0.49–0.3 4.0–5.9 0.29–0.15 6.0–7.9 0.14–0.05 8.0–9.0 2 m/year) (Mandal et al., 2021).

3.4

Measurement of Riverbank Erosion

3.4.2.7

75

Generalized Model of Quantitative Assessment of River Bank Erosion Across the Cross-Sections

This model attempts to compare the scenario of bank line shifting on a quantitative basis in terms of the annual rate of shifting and erosion, temporal bank line position, continuity, and recurring nature of erosion. The net annual rate of erosion/accretion (ω) and the annual rate of shifting(ψ) have been calculated using Eqs. 3.15 and 3.16, as described by Walker (1999) and Parua (1992). ω = Σbl=n

ð3:15Þ

ψ = ΣIblI=n

ð3:16Þ

In computing each bl, “+” stands for the sequence of erosion, and “-” stands for the sequence of accretion. Here, bl is the length of the bank that has been affected by erosion and accretion during a certain period of time (year), and “n” is the number of years. Now, the methodology for computation of the rate of erosion/accretion and the rate of shifting is very simple (Fig. 3.16). For example, if the right bank for the present case erodes 20 m a decade, a length of 40 m can estimated to be eroded during 1970–1990 but if again bank position of 1990 receded back to the initial position in 2010, a length of 40 m can be measured to be accreted during 1990–2010. Hence net erosion/accretion becomes zero while the annual rate of shifting becomes 2 m (80 m /40 years). The analysis of the above-mentioned methods suggests that for assessing streambanks erosion, each method has benefits and drawbacks. However, the choice of them depends on many factors such as the characteristics of the riverbank, the scale of the study area, desired level of detail, accuracy requirements, and available resources. For example, for high-precision measurements in a smaller area, laser scanning might be more suitable while to cover larger areas quickly and consistently, airborne or satellite LiDAR might be a better choice. Moreover, DSAS methods provide the opportunity to analyse the nature of erosion for long duration and large spatial scale. Fig. 3.16 Computation of net annual rate of erosion/ accretion (ω) and the annual rate of shifting (ψ). (Drawn by the authors, 2015)

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Riverbank Erosion: A Natural Process

3.4.3

Empirical Measurements of Bank Erosion

3.4.3.1

Bankline Shifting Using DSAS Model in the Bengal Delta

The application of the DSAS tool also helped to quantify the shifting nature of the river banks. The river Ganga from Manikchak to Arzai Dharampur shows a truly oscillatory character. The upper part is more oscillatory than the lower part. Similarly, the left bank is more oscillating than the right bank. According to Singha et al. (2020) ~85 km of the Ganga River between Rajmahal and the Farakka barrage is particularly susceptible to river bank erosion because of the flow dynamics and the existence of fragile fine silt layers at the toe of the river bank. Similarly, Rudra (2010) argued that a large structural intervention in Farakka (FBP) completed in 1971 over the Ganga River has risen the water level by about 6.71 m due to the 87 million m3 of water that has accumulated above the barrage since that time. To allow this, the river widened, and backflow continued past Bhagalpur. The river was shown to have carved out an eastward meander bend in existing sediments as confirmed by the maps of the Survey of India from 1970 to 1971. Therefore, the previous studies have confirmed that the upstream of the Farakka barrage extending to Rajmahal hill is dynamic due to both the natural factors (e.g., nature of flow and bank material) as well as anthropogenic interventions, primarily the FBP. The empirical study based on EPR and LRR of the left bank of the river from 1990 to 2020 shows that the high erosion rate – (66 to -160 m/year) with a mean - 83 m/ year. has been observed for 462 transects (Table S3.4). However, medium (-66 to 31 m/year) and low erosion ((-31 to 0 m/year) transects are found at 835 and 1139 locations respectively (Table S3.4). Contrastingly, 150 transects recorded high accretion rates (111–485 m/year) while 351 and 2031 transects recorded medium (38–111 m/year) and low accretion (0–38 m/year) along the left bank of the Ganga River (Table S3.4). Regarding the erosion and accretion scenario of the right bank of the Ganga river, it has been observed that there are 127, 284, and 2298 transects have portrayed high (-269 to -117 m/year), medium (-117 to -31 m/year), and low (31 to -0 m/year) erosion rate (Table S3.5) respectively while 593, 929, and 642 transects show high (130–524 m/year), medium (70–130 m/year), and low (0–70 m/year) accretion rates (Figs. 3.17 and 3.18) respectively as per the EPR and LRR findings (Fig. 3.19a, b). This shows that high erosion and high accretion transects are comparatively less. The river Padma from Guhu to Sagar Kandi indicates that the middle portion of the river swings more frequently during 1990–2020. Similarly, the left bank is more oscillating than the right bank. With the same erosion and accretion classes (as mentioned above), the high erosion rate has been observed at 264 transects while the medium and low erosion has been observed at 673, and 1167 transects respectively along the left bank of the Padma River (Table S3.6). Similarly, 339, 723, and 1066 transects portray high, medium, and low accretion rates respectively (Table S3.6). Regarding the right bank of the Padma River, the high erosion bearing transects are observed at 178 places while the medium and the low erosion

3.4

Measurement of Riverbank Erosion

77

Fig. 3.17 Channel oscillation along the left bank of the Ganga-Padma River. Sub-captions (a–d) indicate positions of the left bank in 1990, 2000, 2010, and 2020; (e) indicates the superimposed bank lines; (f) EPR along the left bank; (g–i) show the nature of the bank erosion in the upper, middle, and lower stretches of the river

Fig. 3.18 Channel oscillation along the right bank of the Ganga-Padma River. Sub-captions (a–d) indicate positions of the right bank in 1990, 2000, 2010, and 2020; (e) indicates the superimposed bank lines; (f) EPR along the right bank; (g–i) show the nature of the bank erosion in the upper, middle, and lower stretches of the river

78

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Riverbank Erosion: A Natural Process

Fig. 3.19 EPR and LRR along the left and right bank of the River Ganga-Padma, (a) Transect-wise distribution of EPR and LRR, (b) Correlation between EPR and LRR for the studied transects

transects are located at 1240, and 1822 locations (Table S3.7). Moreover, a high accretion rate (m/year) has been observed for the 205 transects. However, comparatively medium and low accretion rates are located at 372 and 909 transects (Table S3.7, Figs. 3.16 and 3.17) as per the EPR and LRR findings (Fig. 3.19a, b). The river Bhagirathi-Hooghly from the feeder canal outfall at Ahiron to Ganga Sagar has been studied which indicates that the middle portion of the river swings more frequently from 1990 to 2020. The stretch from Katwa and Kalyani oscillates more frequently. Rudra (2010) strongly argued that this stretch of the river has been significantly impacted by hydraulic control via FBP. However, considering the role of FBP, Islam and Guchhait (2017b) have also discussed this erosion phenomenon with special emphasis on neo-tectonic movement and the nature of bank stratigraphy

3.4

Measurement of Riverbank Erosion

79

in this floodplain region. On the left bank, the high erosion rate (-144 to -57 m/ year) has been observed at 99 transects while the medium (-57 to -23 m/year) and low (-23 to 0 m/year) erosion rates are found for 167 and 847 transects (Table S3.8). However, transect No.69, 999, and 4418 recorded the high (26 to 88 m/year), medium (5 to 26 m/year), and low (0 to 5 m/year) accretions respectively. Considering the same erosion and accretion classes for the right bank of the BhagirathiHooghly River, a high erosion rate has been observed for the 31 transects. However, comparatively medium and low erosion rates are located at 718 and 4636 transects (Table S3.9, Figs. 3.20 and 3.21) as per the EPR and LRR findings (Fig. 3.22a, b). Similarly, 84, 372, and 909 transects show high, medium, and low accretion rates of the Bhagirathi-Hooghly River on its right bank (Table S3.9). The river Brahmaputra from Guhu to Sagar Kandi has been studied which indicates that the middle portion of the river swings more frequently from 1990 to 2020. As evident in the observation of Sarma (2005), the entire amount of bank area lost to erosion over the twentieth century was 868 km2. Maximum rates of the shift from the north bank to the south that resulted in erosion were 227.5 m/year while the opposite phenomena, i.e., shift from the south bank to the north was 331.56 m/year due to accretion. Similarly, the present investigation based on the values of EPR and LRR observes that the left bank is more oscillating than the right bank. For example, on the left bank, the maximum erosion rate (-217 to – 97 m/year) has been observed for 258 transects while the maximum accretion rate (95–350 m/year) has been observed for 819 transects (Table S3.10). However, comparatively medium to low erosion (-97 to 0 m/year) and accretion rates (0 to 95 m/year) or the stable zones are located for 1030 and 1286 transects respectively (Figs. 3.23 and 3.24) as per the EPR and LRR findings (Fig. 3.25a, b). Similarly, on the right bank maximum erosion rate (-126 to – 66 m/year) has been observed for 547 transects while the maximum accretion rate (146–437 m/year) has been observed for 236 transects (Table S3.11). However, comparatively medium to low erosion (-66 to 0 m/year) and accretion rates (0 to 146 m/year) or the stable zones are located for 1442 and 487 transects respectively. The stretch of river Meghna extending from Brahmanbaria to Noakhali has been studied from an erosion and accretion perspective which indicates that the lower portion of the river swings more frequently from 1990 to 2020. Similarly, the right bank experiencing the high erosion rate is observed more oscillating than the left bank (Tables S3.12 and S3.13). On the right bank, according to the results of the EPR and LRR, the highest reported accretion rate (74–146 m/year) is seen in the 379 transects, whereas the maximum erosion rate (-436 to -332 m/year) is recorded in 169 transects. However, stable zones with low rates of erosion (-35 to 0 m/year) and accretion (0–18 m/year), respectively, are found at 1131 and 3038 transects (Figs. 3.26 and 3.27) (Fig. 3.28a, b). Similar to the right bank, the maximum erosion rate (-209 to -115 m/year) is found at 259 transects, while the maximum accretion rate (193–438 m/year) is found at 83 transects. However, the stable zones, which have relatively modest erosion rates (-15 to 0 m/year) and accretion rates (0–43 m/year), are found at 459 and 3218 transects, respectively.

80

3 Riverbank Erosion: A Natural Process

Fig. 3.20 Channel oscillation along the left bank of the Bhagirathi-Hooghly River. Sub-captions (a–d) indicate positions of the left bank in 1990, 2000, 2010, and 2020; (e) indicates the superimposed bank lines; (f) EPR along the left bank; (g–i) show the nature of the bank erosion in the upper, middle, and lower stretches of the river

3.4 Measurement of Riverbank Erosion

81

Fig. 3.21 Channel oscillation along the right bank of the Bhagirathi-Hooghly River. Sub-captions (a–d) indicate positions of the right bank in 1990, 2000, 2010, and 2020; (e) indicates the superimposed bank lines; (f) EPR along the right bank; (g–i) show the nature of the bank erosion in the upper, middle, and lower stretches of the river

82

3

250

(a)

Riverbank Erosion: A Natural Process

EPR ( Bhagirathi-Hooghly RB)

LRR (Bhagirathi-Hooghly RB)

EPR ( Bhagirathi-Hooghly LB)

LRR (Bhagirathi-Hooghly LB)

200 150

EPR & LRR (m/y)

100 50 0 0

1000

2000

3000

4000

5000

6000

7000

8000

-50 -100 -150 -200

Transect number 250

(b) 200

R²RB = 0.8263

150

LRR (m/y)

100 R²LB = 0.978

50 0 -200

-150

-100

-50

0

50

100

150

200

250

-50 Bhagirathi-Hooghly RB -100

Bhagirathi-Hooghly LB

-150

Linear (Bhagirathi-Hooghly RB) Linear (Bhagirathi-Hooghly LB)

-200

EPR (y/m)

Fig. 3.22 EPR and LRR along the left and right bank of the River Bhagirathi-Hooghly, (a) Transect-wise distribution of EPR and LRR, (b) Correlation between EPR and LRR for the studied transects

3.4

Measurement of Riverbank Erosion

83

Fig. 3.23 Channel oscillation along the left bank of the Brahmaputra River. Sub-captions (a–d) indicate positions of the left bank in 1990, 2000, 2010, and 2020; (e) indicates the superimposed bank lines; (f) EPR along the left bank; (g–i) show the nature of the bank erosion in the upper, middle, and lower stretches of the river

84

3

Riverbank Erosion: A Natural Process

Fig. 3.24 Channel oscillation along the right bank of the Brahmaputra River. Sub-captions (a–d) indicate positions of the right bank in 1990, 2000, 2010, and 2020; (e) indicates the superimposed bank lines; (f) EPR along the right bank; (g–i) show the nature of the bank erosion in the upper, middle, and lower stretches of the river

3.4

Measurement of Riverbank Erosion

85

500

(a) 400

EPR (Brahmaputra RB)

LRR ( Brahmaputra RB)

EPR ( Brahmaputra LB)

LRR ( Brahmaputra LB)

EPR & LRR (m/y)

300

200

100

0 0

500

1000

1500

2000

2500

3000

-100

-200

-300

Transect number 300

(b) 250 R²LB = 0.7727 200 R²RB = 0.367

150

LRR (m/y)

100 50 0 -300

-200

-100

0

100

200

300

400

500

-50 Brahmaputra RB

-100

Brahmaputra LB -150 Linear (Brahmaputra RB) -200

Linear (Brahmaputra LB)

-250

EPR (m/y)

Fig. 3.25 EPR and LRR along the left and right bank of the Brahmaputra River, (a) Transect-wise distribution of EPR and LRR, (b) Correlation between EPR and LRR for the studied transects

86

3

Riverbank Erosion: A Natural Process

Fig. 3.26 Channel oscillation along the left bank of the Meghna River. Sub-captions (a–d) indicate positions of the left bank in 1990, 2000, 2010, and 2020; (e) indicates the superimposed bank lines; (f) EPR along the left bank; (g–i) show the nature of the bank erosion in the upper, middle, and lower stretches of the river

3.4

Measurement of Riverbank Erosion

87

Fig. 3.27 Channel oscillation along the right bank of the Meghna River. Sub-captions (a–d) indicate positions of the right bank in 1990, 2000, 2010, and 2020; (e) indicates the superimposed bank lines; (f) EPR along the right bank; (g–i) show the nature of the bank erosion in the upper, middle, and lower stretches of the river

88

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Riverbank Erosion: A Natural Process

500

(a) 400

300

EPR (Meghna LB)

LRR (Meghna LB)

EPR (Meghna RB)

LRR (Meghna RB)

EPR & LRR (/y)

200

100

0 0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

5500

6000

6500

-100

-200

-300

-400

-500

Transect number 300

(b)

R²LB = 0.5671 200

LRR (m/y)

100 R²RB = 0.4216 0 -500

-400

-300

-200

-100

0

-100

100

200

300

400

500

Meghna LB Meghna RB

-200

Linear (Meghna LB) Linear (Meghna RB)

-300

EPR ( m/y)

Fig. 3.28 EPR and LRR along the left and right bank of the Meghna River, (a) Transect-wise distribution of EPR and LRR, (b) Correlation between EPR and LRR for the studied transects

3.4

Measurement of Riverbank Erosion

3.4.3.2

89

Quantitative Assessment of Bank Erosion Along the Cross Sections of Bhagirathi River

Bank line shifting analysis has been analysed for 12 cross sections for a period of 40 years (1972–2012). Profiles of the same location have been taken in 5 different time points viz. 1972, 1984, 1993, 2004, and 2012 (Fig. 3.29a).

(a)

12

Maximum left bankline position

Minimum left bankline position

(b)

Reduced level (metre)

10 8

1972 1984

6

1993

4

2004

2 0 -2

2012

Range of shifting (right bank)

0

100

200

300

400

500

600

700

800

900

1000 1100

Distance from Right Bank (metre)

Fig. 3.29 Bankline shifting analysis. (a) Location of cross section on River Bhagirathi (Source: Hydrographic sheets, KoPT, 1972), (b) Representative cross-sectional profiles for CS 335 to demonstrate the minimum, maximum banking, and range of shifting

90

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Riverbank Erosion: A Natural Process

Table 3.10 Minimum, maximum, and range of shifting

CS No. 249 252 255 283 286 289 332 335 337 347 350 352

Bank LB RB LB RB LB RB LB RB LB RB LB RB LB RB LB RB LB RB LB RB LB RB LB RB

Minimum bankline position Value (m) year 473.90 2012 100.00 1972 615.30 1972 130.00 1972 338.68 2012 120.00 1972 362.14 1993 36.00 1972 332.96 2001 32.00 2001 318.44 1984 69.00 2012 388.56 1984 58.00 1993 548.58 1972 210.00 1972 634.80 1972 120.00 1972 272.13 2012 60.00 1972 732.42 1972 140.00 1972 645.12 1972 360.00 1972

Maximum bankline position Value (m) year 559.76 1972 4.00 1993 1115.67 2012 10.00 2001 789.56 1984 2.00 2001 392.40 1972 20.00 1993 390.16 1972 10.00 1972 362.64 1972 30.00 1972 474.00 2012 38.00 2011 1061.43 2012 35.00 2012 630.00 1984 30.00 2004 421.15 1972 8.00 2011 1063.00 2012 50.00 2004 781.81 1984 50.00 1984

Range of shifting (max-min) (m) 85.86 -96.00 500.37 -120.00 450.88 -118.00 30.26 -16.00 57.20 -22.00 44.20 -39.00 85.44 -20.00 512.85 -175.00 -4.80 -90.00 149.02 -52.00 330.58 -90.00 136.69 -310.00

Computed from hydrographic sheets, KoPT (1972–2012). Note: 1972 is taken to show the pre-Farakka barrage condition and 2012 (most recent data available to us) to show the post-Farakka condition

Bank line shifting analysis has been accomplished using the concepts of minimum and maximum bankline position during the observation period (1972–2012) measured from the right bank (Fig. 3.29b). The range of shifting is the difference between the minimum and maximum bankline positions (Fig. 3.29b). The annual rate of shifting and erosion (Table 3.10) depicts the higher rate of erosion along the left bank for CS 252,335,350 while the annual rate of accretion is remarkable on the right bank for CS 252 and 350. Here, the range of shifting is greater where there is uniform shifting and smaller for the areas experiencing bi-polar shifting (Table 3.10). The range of shifting (greater than 150 m) has been observed for the CS 252, 335, and 350 along the left bank. Along these sections, constant unidirectional shifting has been observed. It proves that the left bank is more oscillating than the right bank in the study area (Table S3.2).

3.4

Measurement of Riverbank Erosion

91

35

Annual rate of shifting in metre

30

y = 0.0467x2 - 0.174x + 3.9183 R² = 0.7842

25 20 15 10 5

0 -20

-10

0 10 Annual rate of erosion in metre

20

30

Fig. 3.30 The U-shaped 2nd-degree polynomial curve showing the relation between rate of erosion and rate of shifting (Computed from hydrographic sheets, KoPT: 1972–2012)

The shifting of the channel is marked by the erosion-deposition sequence of the river. Erosion in one place and deposition in others keep the channel always dynamic as well as oscillating. Analysis of the total 12 cross-sections establishes that there is a strong correlation between the annual rate of shifting and the annual rate of erosion with the help of a 2nd-degree polynomial equation (Fig. 3.30). With the increase in either erosion or deposition, there has been a corresponding increase in channel shifting, while for the minimum value of erosion and deposition, the channel remains almost stationary. This is a quite natural and normal trend in fluvial hydraulics. The stable reach of a river shows very low erosion while unstable reach is marked by an erosion-accretion sequence. The regression curve appears as a parabola for a longer stretch of a river with stable and unstable reaches. From the curve (Fig. 3.30) drawn with the help of the database collected from KoPT, it can clearly be explained that if the rate of erosion is close to zero, the annual rate of shifting is minimum, but the rate of erosion if it diverges from zero point, the annual rate of shifting is accelerated. If it moves towards land (positive value) it indicates bank erosion otherwise bank deposition (for negative value). Bank line shifting has a definite trend of temporal variation regarding the minimum and maximum position of the bank line perceived through superimposition. In 1972, most of the cross sections have a minimum bank line position

92

3

(a)

Frequency of banks (%)

50 40

Minimum value of bank line

30 20

Maximum valueof bank line

10 0 1972

1984

1993 Year

2001

2012

Cumulative Successive Total (%)

250 60

Riverbank Erosion: A Natural Process

(b)

200 150 Left Bank Right Bank

100 50 0 249 252 255 283 286 289 332 335 337 347 350 352 CS Number

Fig. 3.31 Nature of bankline shifting, (a) Distribution of bank line registering minimum and maximum value. (b) Cumulative successive total indicating the nature of bank oscillation

(Table 3.10). This year right bank minimum position is far greater than the left bank minimum position. Out of 12 points of the right bank (from 12 cross sections), nine right banks have registered minimum positions while 5 points out of 12 points of the left bank have secured the minimum position. This proves that shifting bank lines are more for the left bank than the right. In the post-Farakka period, the river gradually widened its channel towards the east and west, especially where the river is impregnated with mid-channel bars. With the consequent growth of the mid-channel bar, a substantial rise is observed in the number of banks registering maximum bank line positions. Results obtained from “cumulative successive total” [bankline shifting measured in % for a specific assessment period, e.g., 1972–1984 with respect to total channel shifting during the entire assessment period (1972–2012) (Fig. 3.31a) and then individual shifting (%) is successively added] show the continuous nature of erosion along the left bank for CS 252, 335, and 350. Virtually all these cross-sections fall adjacent to the study mouzas. Relative continuity in erosion is indeed expected along the right bank for the rest of the cross sections (Fig. 3.31b). The erosion, accretion sequence portrays the continuous nature of erosion along the left bank of CS 252,335,350 and along the right bank of CS 335 during the assessment period of 1972–2012. The right bank of CS 255,337,350 depicts continuous erosion up to 2011 but accretion has started recently (Table 3.11). Riverbank erosion is though fundamentally natural process understood in terms of types, mechanisms, factors, and measurements, in recent times especially due to the accelerated rate of human interventions the process of riverbank erosion will be better understood when the human-induced process of bank erosion will be considered. Therefore, the next chapter is focused on the nature and magnitude of changes in response to the increasing rate of human intervention at the basin scale.

References

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Table 3.11 Detection of erosion and accretion over time CS No. 249 252 255 283 286 289 332 335 337 347 350 352

Bank LB RB LB RB LB RB LB RB LB RB LB RB LB RB LB RB LB RB LB RB LB RB LB RB

1972–1984 + + + + + + + + + + + + + +

1984–1993 + + + + + + + + + + + +

+ +

1993–2001 + + + + -

2001–2012 + 0 0 0 0

+ + + + + + + + +

+ + + + + + -

Computed from hydrographic sheets, KoPT (1972–2012). Note + stands for erosion, - for deposition, and 0 for no change in the bankline position

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Johnson, A. W., & Stypula, J. M. (1993). Guidelines for bank stabilization projects in the riverine environments of King County. King County Department of Public Works, Surface Water Management Division. Kale, V. S. (2003). Geomorphic effects of monsoon floods in Indian rivers. Natural Hazards, 28, 65–84. Knighton, A. D. (1973). Riverbank erosion in relation to streamflow conditions, River Bollin-Dean, Cheshire. East Midland Geographer, 5(8), 416–426. Knighton, A. D. (1999). Downstream variation in stream power. Geomorphology, 29(3–4), 293–306. KoPT. (1975). Hydrographic sheets on River Bhagirathi. Berhampore: Hydraulic Study Department, Kolkata Port Trust, Govt. of India. KoPT. (2008). Annual reports on River Bhagirathi (2007–2008). HSD. Lacey, G. (1939). Regime flow in incoherent alluvium. CBIP. (Publication No. 20). Lacey, G. (1958). Flow in alluvial channels with sandy mobile beds (Publication No. 20). The Institution of Civil Engineering. CBIP. Lawler, D. M. (1993). The measurement of river bank erosion and lateral channel change: A review. Earth Surface Processes and Landforms, 18(9), 777–821. Lawler, D. M. (2008). Advances in the continuous monitoring of erosion and deposition dynamics: Developments and applications of the new PEEP-3T system. Geomorphology, 93(1–2), 17–39. Lawler, D. M., & Leeks, G. J. L. (1992). River bank erosion events on the Upper Severn detected by the Photo-Electronic Erosion Pin (PEEP) system. In Erosion and Sediment Transport Monitoring Programmes in River Basins, 200, pp 95–105. Leopold, L. B., & Langbein, W. B. (1962). The concept of entropy in landscape evolution (Vol. 500). US Government Printing Office. Leopold, L. B., & Maddock, T. (1953). The hydraulic geometry of stream channels and some physiographic implications (Vol. 252). US Government Printing Office. Li, Y., McNelis, J. J., & Washington-Allen, R. A. (2020). Quantifying short-term erosion and deposition in an active gully using terrestrial laser scanning: A case study from West Tennessee, USA. Frontiers in Earth Science, 8, 587999. Linjuan, X., Junhua, L., Wanjie, Z., Yuanjian, W., & Enhui, J. (2019, August). Experimental study on starting shear stress of cohesive soil in the lower Yellow River. In 2019 international conference on smart grid and electrical automation (ICSGEA) (pp. 448–451). IEEE. Longoni, L., Papini, M., Brambilla, D., Barazzetti, L., Roncoroni, F., Scaioni, M., & Ivanov, V. I. (2016). Monitoring riverbank erosion in mountain catchments using terrestrial laser scanning. Remote Sensing, 8(3), 241. Mandal, B. K., Islam, A., Sarkar, B., & Rahman, A. (2021). Evaluating the spatio-temporal development of coastal aquaculture: An example from the coastal plains of West Bengal, India. Ocean & Coastal Management, 214, 105922. Mekong River Commission. (2005). Overview of the hydrology of the Mekong Basin (p. 82). Mekong River Commission. Midgley, T. L., Fox, G. A., & Heeren, D. M. (2012). Evaluation of the bank stability and toe erosion model (BSTEM) for predicting lateral retreat on composite streambanks. Geomorphology, 145, 107–114. Mukherjee, A., & Fryar, A. E. (2008). Deeper groundwater chemistry and geochemical modeling of the arsenic affected western Bengal basin, West Bengal, India. Applied Geochemistry, 23(4), 863–894. Mullick, M. R. A., Islam, K. A., & Tanim, A. H. (2020). Shoreline change assessment using geospatial tools: a study on the Ganges deltaic coast of Bangladesh. Earth Science Informatics, 13, 299–316. Muskananfola, M. R., & Febrianto, S. (2020). Spatio-temporal analysis of shoreline change along the coast of Sayung Demak, Indonesia using Digital Shoreline Analysis System. Regional Studies in Marine Science, 34, 101060. https://doi.org/10.1016/j.rsma.2020.101060

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Slaymaker, H. O. (1972). Patterns of present sub-aerial erosion and landforms in mid-Wales. Transactions of the Institute of British Geographers, 55, 47–68. Thoma, D. P., Gupta, S. C., Bauer, M. E., & Kirchoff, C. E. (2005). Airborne laser scanning for riverbank erosion assessment. Remote Sensing of Environment, 95(4), 493–501. Thorne, C. R. (1991). Bank erosion and meander migration of the Red and Mississippi Rivers, USA. In Hydrology for the Water Management of Large River Basins (Proceedings of the Vienna Symposium, August 1991). IAHS Fubl. no. 201, 1991, pp. 301–313. Thorne, C. R. (1998). Stream reconnaissance handbook: Geomorphological investigation and analysis of river channels. Wiley. Torry, V. H., & Weaver, F. J. (1984). Flow failures in Mississippi River banks. In 4th international symposium on landslides. van Maren, D. S., Beemster, J. G. W., Wang, Z. B., Khan, Z. H., Schrijvershof, R. A., & Hoitink, A. J. F. (2022). Tidal amplification and river capture in response to asynchronous land reclamation in the Ganges-Brahmaputra delta. Available at SSRN 4064791. Walker, J. (1999). The application of geomorphology to the management of river-bank erosion. Water and Environment Journal, 13(4), 297–300. Walker, J., Arnborg, L., & Peippo, J. (1987). Riverbank erosion in the Colville delta, Alaska. Geografiska Annaler: Series A, Physical Geography, 69(1), 61–70. Wallick, J. R., Lancaster, S. T., & Bolte, J. P. (2006). Determination of bank erodibility for natural and anthropogenic bank materials using a model of lateral migration and observed erosion along the Willamette River, Oregon, USA. River Research and Applications, 22(6), 631–649. Watson, A. J., & Basher, L. R. (2006). Stream bank erosion: a review of processes of bank failure, measurement and assessment techniques, and modelling approaches. A report prepared for stakeholders of the Motueka Integrated Catchment Management Programme and the Raglan Fine Sediment Study. Landcare Research, Hamilton, New Zealand. https://icm.landcareresearch. co.nz/knowledgebase/publications/public/ICM_report_bank_erosion.pdf Wilkinson, S., Henderson, A., Chen, Y., & Sherman, B. (2004). SedNet User Guide. Client Report, CSIRO Land and Water; Canberra. Williams, L. A. (2014). Late quaternary stratigraphy and infilling of the Meghna River valley along the tectonically active eastern margin of the Ganges-Brahmaputra-Meghna Delta. Doctoral dissertation. Wolman, M. G. (1959). Factors influencing erosion of a cohesive river bank. American Journal of Science, 257(3), 204–216. Young, A. P., Olsen, M. J., Driscoll, N., Flick, R. E., Gutierrez, R., Guza, R. T., et al. (2010). Comparison of airborne and terrestrial lidar estimates of seacliff erosion in southern California. Photogrammetric Engineering & Remote Sensing, 76(4), 421–427.

Chapter 4

Riverbank Erosion: A Human-Induced Process

4.1

Regulated River Regime and Bank Erosion

The regulated river regime in the era of the “Anthropocene” (Ogden, 2016) is a remarkable trend across the world in the form of controlling discharge predominantly through the construction of dams and barrages. In the Anglo-European tradition, damming of the rivers is a long tradition that started in the eighteenth century. The trends of dam construction peaked in the twentieth century. However, observing the clear traits in the drastic modification of the ecosystem behaviour, the deconstruction of dams has started in the USA and Europe. However, to date, the majority of the rivers are dammed and the flow fluctuation is held responsible for the erosion in the upper part of the basin and its eventual deposition in the lower part. Although the anthropogenic flow fluctuations in the wake of the environmental consciousness have reduced to some extent, bank protection and river training works are popularly embraced in those nations. This ultimately has reduced the bank erosion tendency of the river through bank stabilizations. For example, the Thames in Great Britain is largely controlled and erosion tendency is managed. However, in England, bank erosion is stimulated again within limited areas (Treasury, 2005). Straight and diked rivers are helped to start meandering again, favouring water buffering, and wetland creation to stimulate biodiversity and geodiversity (Addy et al., 2016). In the context of Asian countries like India and Bangladesh, dams are mushrooming day by day. Exponential growth in the dam construction has virtually made the river of the GBM delta anthropic and urban rivers in some cases. However, the majority of the rivers like Ganga, Brahmaputra, and Bhagirath-Hooghly are controlled by dams and barrages that regulate the fluvial regime of the rivers, especially in the lean months. For example, the anthropic fluctuations are responsible

Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/978-3-031-47010-3_4. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Islam, S. K. Guchhait, Riverbank Erosion in the Bengal Delta, Springer Geography, https://doi.org/10.1007/978-3-031-47010-3_4

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for riverbank erosion along the Bhagirathi-Hooghly River, India due to piping actions. Thus, it is vital to note the changes in the flow fluctuations of the river and their impact on the riverbank erosion. In the Bengal Delta on the one hand flow fluctuation is there and on the other hand, rivers are not much trained or embanked like the European rivers. Naturally, flow fluctuation induces major changes in the erosion and sedimentation scenario. The following section will thus present an analysis of the flow variations in the context of the FBP which is a mega-scale human intervention on the Ganga River that has enormous fluvio-hydrological and related riverine processes on both the Bhagirathi-Hooghly and Padma Rivers of the GBM delta.

4.1.1

Farakka Barrage Project: A Mega-scale Intervention

The Farakka Barrage Project (FBP), a massive engineering project built by the Govt. of India over the Ganga River in the Murshidabad and Malda districts of West Bengal, was made operational in 1975 with two main targets. The first goal aimed at rejuvenating the Kolkata Port (now Dr Syama Prasad Mookerjee Port) diverting 40,000 cusecs of water from the Ganga River into the Bhagirathi-Hooghly River through constructing the ~38 km long feeder canal. The second target was to save Kolkata’s urban agglomeration through the supply of fresh water and a salinityreduced environment (Rudra, 2011; Islam & Guchhait, 2017). To execute the plan of the FBP an authority was set up in 1961 that materialized the plan in 1975. This project comprised three major components – the Farakka Barrage (2245 m long), Jangipur Barrage (213 m long), and 38-km long feeder canal (Fig. 4.1). Furthermore, the engineering construction of the FBP is complex and constituted of 112 gates including 108 main gates and 4 fish lock gates along with 11 head regulator gates for diversion of about 40,000 cusecs of discharge into the feeder canal (Parua, 2010). The Jangipur Barrage was constructed for maintaining the steady flow from the feeder canal outfall at Ahiran to Bhagirathi by retraining it from returning the flow into the Padma through Bhagirathi. Besides, the road and rail bridge (Fig. 4.2a, b) across the river Ganga at Farakka connected North Bengal with South Bengal. Moreover, national waterway number 1, i.e., Haldia-Allahabad Inland Waterway is maintained through this feeder canal. The Feeder Canal also supplies water to 2100 MW required for the Farakka Super Thermal Power Project (FSTPP) of NTPC Ltd. at Farakka (Parua, 2009). The FBP has a profound impact on the channel morphology and hydraulic behaviour of the Ganges River system both upstream and downstream of the barrage (Parua, 2009; Mirza, 2004). The problem of inundation and riverbank erosion is a common fluvial hazard associated with this project in the Malda, Murshidabad, and Nadia Districts of West Bengal (Rudra, 2011; Islam, 2016). It can aptly be mentioned that the hydro-dynamics of the Lower Ganga system are greatly determined

4.1

Regulated River Regime and Bank Erosion

101

Fig. 4.1 Farakka Barrage Project and surroundings

by the anthropogenic modification of the hydraulic behaviour by the construction of the barrage since 1975. This chapter, therefore, unfolds the role of the FBP in controlling the channel dynamics of Bhagirathi in West Bengal, especially the meander geometry of the river in the following sections. The FBP was commissioned in 1975 to make the river Bhagirath-Hooghly navigable throughout the year allowing more discharge for the revival of Kolkata port (Islam, 2012). For testing purposes, India first diverted 310–450 m3s-1 of the Ganga water between April

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Fig. 4.2 Photographs (a) and (b) showing Rail cum Road Bridge across the river Ganga. (Source: Todaytimesnews.com)

21 and May 31, 1975. Subsequently, in 1977 India and Bangladesh signed a 5-year mutual agreement for distributing Ganga River water followed by two memoranda of understanding (MoUs) which were signed in 1983 and 1985. In 1996, both countries signed an agreement for 30 years. As per the provisions of the agreement, India achieved the right to withdraw 40,000 cusecs of Ganga water from the FBP in the lean months (January to May). However, an equal share of Ganga water will result when FBP receives a lower amount of water (1000 m3s-1) in all the gauge stations viz. Jangipur, Berhampore, and Katwa (Table 4.1). The discharge and water level of the Bhagirathi River at Jangipur gradually scaled down with time. Parua (1992) mentioned that the average minimum and maximum discharge during 1915–1972 were 9.24 m3s-1 and 1718 m3s-1 respectively. Moreover, the minimum discharge was reduced to 1.1 m3s-1 in 1965 however, the annual maximum was 952 m3s-1 (Table 4.2). Similarly, the average water level also gradually decreased with time. It is mentioned that in 1972, the number of significant flow days was reduced to 84 (Table 4.2).

4.1

Regulated River Regime and Bank Erosion

105

Table 4.1 Average discharge (m3s-1) in the pre-Farakka period at various gauge stations of the Bhagirathi River Year 1905 1906 1907 1908 1909 1910 1911 1912 1913

Date & month 1st–15th February 16th–31st August 10th–15th February 16th–30th September 1st–15th February 1st–15th September 1st–15th March August 16th–28th February 16th–31th August 1st–15th March August 1st–15th February 16th–31st August 1st–15th February 16th–31st August 16th–23rd February August

Jangipur (Entrance) – 3952.75 – 518.85 – 1071.65 2.49 – 2.07 – 2.41 – 117.94 1617.85 8.13 1236.40 4.64 –

Berhampore 30.98 – – – – – – – 11.36 2791.39 7.65 – 44.83 – – – 9.51 30.98

Katwa 58.62 4607.29 54.57 1933.22 22.68 1088.98 556.43 – 25.40 – 26.82 – – 4320.44 13.25 – 18.01 58.62

Source: Hirst (1915)

Table 4.2 Water level and discharge at Jangipur of Bhagirathi River

Year 1915 1920 1926 1930 1935 1940 1945 1950 1955 1960 1965 1970 1972 Average

Water Level (WL) and Discharge (Q) Minimum Maximum WL (m) Q min (m3s-1) WL (m) 15.05 3.1 21.4 16.86 5.8 20.7 14.42 3.6 19.96 14.92 13.3 21.26 14.94 1.6 21.43 14.88 4.6 20.69 15.1 25 21.22 15 20.1 20.86 14.39 18.2 20.97 14.73 17.1 20.85 13.52 1.1 19.18 14.48 3.7 19.45 14.63 2.9 18.91 14.83 9.24 20.53

Based on Parua (1992)

QM (m3s-1) 2554 1892 1317 2109 2053 2006 1572 1927 1472 1773 1409 1306 952 1718.62

Time span (days) of significant flow 190 150 175 170 138 165 178 136 191 156 142 122 84 154

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Maximum Discharge in Cumec

5000

a

4000 3000

Jangipur 2000

Berhamore Purbasthali

1000 0

1973

1975

1977

1979

1981

1983

1985

Year

Average Discharge in Cumec

2500

b

2000 1500 Jangipur 1000

Berhamore Purbasthali

500 0 1973

1975

1977

1979 Year

1981

1983

1985

Fig. 4.4 Discharge at Jangipur, Berhampore, and Purbasthali in pre- and post-FBP periods, (a) maximum, (b) average. (Based on Parua, 1992)

The distressed condition of discharge prevailed until FBP came into being in 1975 to supply the water through the feeder canal. It is observed that maximum discharge remained almost the same in the pre-FBP and post-FBP periods; however, an increase was recorded in average discharge in the post-FBP period for Jangipur, Berhampore, and Purbasthali gauge stations (Fig. 4.4a, b). This regulated increase in discharge (10-day peak and 10-day off-peak) in the lean months induced the rate of riverbank erosion due to the attainment of the higher stage of the river.

4.1.4

Fluctuation in River Regime Through Controlled Hydrology

Before the FBP was installed, the flow variability of the Bhagirathi River was dependent on the vagaries of the monsoon rainfall. The river carries a significant discharge in the monsoon and late monsoon periods; however, there is little or negligible flow for the rest of the year (Islam 2011). However, the FBP conceived

4.1

Regulated River Regime and Bank Erosion

107

Table 4.3 Indo-Bangladesh water sharing treaties of 1977a and 1996b showing the theoretical distribution of Ganga water at Farakka (in Cusecs) Bangladesh Period January 1–10 January 11–20 January 21–31 February 1–10 February 11–20 February 21–28/29 March 1–10 March 11–20 March 21–31 April 1–10 April 11–20 April 21–30 May 1–10 May 11–20 May 21–31

1977 58,500 51,250 47,500 46,250 42,500 39,250 38,500 38,000 36,000 35,000 34,750 34,500 35,000 35,250 38,750

1996 67,516 57,673 50,154 46,323 42,859 39,106 35,000 35,000 29,688 35,000 27,633 35,000 32,351 35,000 41,854

India Increase/ Decrease 9016 6423 2654 73 -359 -144 -3500 -3000 -6312 0 -7117 500 -2649 -250 3104

1977 40,000 38,500 35,000 33,000 31,500 30,750 26,750 25,500 25,000 24,000 20,750 20,500 21,500 24,000 26,750

1996 40,000 40,000 40,000 40,000 40,000 40,000 39,419 33,931 35,000 28,180 35,000 25,992 35,000 38,590 40,000

Increase/ Decrease 0 1500 5000 7000 8500 9250 12,669 8431 10,000 4180 14,250 5492 13,500 14,590 13,250

The flow was estimated based on 75% dependable flow from 1948 to 1973 (pre-FBP condition). The flow was estimated based on average flow (50% dependable) during the period from 1948 to 1988 (25 years pre-FBP & 15 years post-FBP conditions) under mutual agreement. For the 8 years (1988–1996), unilateral withdrawal was not taken into consideration. (Based on Islam & Guchhait, 2017)

a

b

on the consideration of the arithmetic hydrology drastically altered the hydraulic regime of the river. This resulted in the variability of the flow even in the lean months because the Indo-Bangladesh treaty was mainly focused on the lean period flow sharing on a 10-day scale from January to May of a year (Parua, 2010). As per the provisions of the water-sharing treaty in 1996, the river regime tends to highly fluctuate from March to May (Table 4.3). Actual discharge was more variable than the theoretical distribution in the treaty because of the uncertain availability of water in the reservoirs of the FBP. Under the threats of climate change, flow fluctuations have aggravated in recent times and tend to increase in the future as the hydrological extremes (floods and droughts) are closely tied with global warming and intensified hydrological cycle (Douville et al., 2021; Ficklin et al., 2022). Therefore, the discharge of the Bhagirathi River becomes ostensible all throughout the year. One interesting facet of this analysis is that more variability in the lean months (March to May) and relatively less variability for the rest of the year becomes clear from the discharge hydrograph of the river at Feeder canal (Farakka), and Berhampore gauge stations (Fig. 4.5a, b).

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Discharge in Cumecs

1300

Riverbank Erosion: A Human-Induced Process

a

Feeder Canal

1200

Berhampore

1100

Katwa

1000 900 800 700 600

Discharge in Cumecs

500 1-Jan

21-Jan

10-Feb

2-Mar

22-Mar Date

11-Apr

1-May

1300

10 per. Mov. Avg. (Feeder Canal)

1200

10 per. Mov. Avg. (Berhampore )

1100

10 per. Mov. Avg. ( Katwa)

21-May

b

1000 900 800 700 600 500 1-Jan

21-Jan

10-Feb

2-Mar

22-Mar Date

11-Apr

1-May

21-May

Fig. 4.5 Discharge hydrograph of Bhagirathi at Treaty period. (a) Actual, (b) 10-day moving average. (Source: Average discharge (2005–2009), CWC, India)

The discharge hydrograph exhibits peak and valley configuration during the treaty period (January to May) for the gauge stations at Feeder canal (Farakka), Berhampore, and Katwa. However, in the normal period (June to December), the hydrograph shows a less oscillatory nature at the Feeder canal and Berhampore while more fluctuating at Katwa. This is clearly depicted in the moving average on the 10-day scale on actual data and moving average curves (Fig. 4.6a, b). It is observed that all the gauge stations on the Bhagirathi River record almost similar natures of average annual discharge in the treaty period. This is due to the controlled hydrology from the FBP and the lesser supply of water from the tributaries of the Bhagirathi. On the contrary, gauge stations exhibit variable discharge depending upon the supply of the tributaries in the monsoon period (Fig. 4.7a, b). It is observed that a higher discharge variability is measured by the higher coefficient of variation (CV) at the Feeder canal in the lean period due to an alternate 10-day scale of water distribution from the FBP, i.e., a symptom of controlled hydrology by FBP. However, a higher discharge variability of Katwa in the normal period is induced by the fluctuating river regime of the Ajay-Mayurakshi system in the monsoon period (Fig. 4.7a, b). In brief, the lean period flow fluctuation in the Bhagirathi River especially in the upper part (feeder canal and Berhampore) has escalated due to controlled hydrology of the FBP

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3500

a

Discharge in Cumecs

3000 2500

Feeder Canal Berhampore Katwa

2000 1500 1000

500 1-Jun 21-Jun 11-Jul 31-Jul 20-Aug 9-Sep 29-Sep 19-Oct 8-Nov 28-Nov 18-Dec Date 3500

Discharge in Cumecs

3000

10 per. Mov. Avg. (Feeder Canal) 10 per. Mov. Avg. (Berhampore ) 10 per. Mov. Avg. ( Katwa)

b

2500 2000 1500 1000 500 1-Jun 21-Jun 11-Jul 31-Jul 20-Aug 9-Sep 29-Sep 19-Oct 8-Nov 28-Nov 18-Dec Date

Fig. 4.6 Discharge hydrograph of Bhagirathi at normal period. (a) Actual, (b) 10-day moving average. (Source: Average discharge during 2005–2009, CWC, India)

4.2 4.2.1

Land Use and Cover Changes and Bank Erosion Impact of Bank Erosion on Land Use and Cover Changes

Riverbank erosion brings a significant change in society at both the reach and basin scale through human adaption and riverbank protection management against erosion. Many studies (e.g., James et al., 2022; Chakraborty & Saha, 2022; Islam & Guchhait, 2013) have integrated riverbank erosion and social change emphasizing land use and land cover change. Though land use and land cover change is a

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Average Annual Discharge in Cumecs (2005-2009)

2000

a

1800 1600 1400 1200

Treaty Period (January-May)

1000 800

Normal Period (June-December)

600 400

Differential

200 0 Feeder Canal

Berhampore

Katwa

C.V. in Avearge Annual Discharge (%)

40

b

35 30 25 20

Treaty Period (January-May)

15 10

Normal Period (JuneDecember)

5 0 Feeder Canal

Berhampore

Katwa

Fig. 4.7 Average annual discharge at Feeder Canal, Berhampore, and Katwa during the treaty period and normal period; (a) Actual, (b) Coefficient of variation. (Computed from CWC data 2008–2009)

complex process and is controlled by multiple factors, numerous researchers (e.g., Guite & Bora, 2016; Das et al., 2021) have discussed the direct relationship between riverbank erosion and land use and land cover change. Riverbank erosion has become an increasing threat due to the loss of agricultural land, settlement displacement, and also infrastructural loss. The socioeconomic consequence due to this loss is not the same across the world. In Asian countries, bank erosion has become devastating as the marginal or the poor people living by the side of the riverbanks face the tragedy. Thus, the major objective of this section is to portray land use and land cover changes at the basin and site scale that have some relation with the riverbank erosion process.

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4.2.1.1

111

Basin-Scale Analysis

(a) Backdrop The shifting of the river courses across the world is well documented in Chap. 3. By nature, the river tends to oscillate over space and time to adjust to changing morphogenic variables since the evolutionary history of the earth (Islam & Guchhait, 2017). This fundamental nature has been perturbed through different human interventions. It indicates the training and taming of the river courses to keep the civilization in a safer place without frequent relocation. This tendency is well observed in Anglo-European context because of innovations in architecture and planning and relatively less mighty courses (Gurnell et al., 2007). However, in the context of tropical countries training for the river is not so easy for rivers like Ganga, Brahmaputra, and Padma influenced by monsoonal spell and tropical storm surges (Rudra, 2014; Guchhait et al., 2016). Moreover, infrastructure lacunae coupled with insufficient technological adaption restrict river training work to a limited extent. (b) Study Design and Methods The land use land cover (LULC) for the present study was detected using a systematic methodology involving a few steps: (1) data collection, (2) pre-processing, (3) LULC classification scheme, (4) selection of training data samples, (5) image classification and accuracy assessment (Fig. 4.8). The image process was performed in ERDAS Imagine (v. 14) and mapping was done using ArcGIS (v. 10.3). The satellite data were used to assess the spatio-temporal changes and prepare thematic maps of the different rivers and surrounding regions for the present investigation (Table S4.1). The satellite images of 1992 and 2022 were used to compute the LULC maps (Table S4.1). Landsat 5 TM (30 m) and Landsat 8 OLI data (30 m) sets were downloaded from the USGS Global Visualization Viewer (GloVis) online archive (https://glovis.usgs.gov/). The Landsat TM and OLI data sets have six and nine spectral bands. The data sets were downloaded in GeoTiff format and each band contained certain wavelength values (Table S4.2) in the form of a greyscale image. The accuracy assessment of the LULC may reduce due to the cloud cover and undesired shade. Therefore, high-quality and cloud-free images were used in this study. Erdas Imagine is a powerful tool for the analysis of satellite images and acquiring information from the data sets. The first and foremost step for LULC is creating a single image using the layer stacking tool of Erdas Imagine (a single image prepared by stacking multiple bands). Due to this process, a single image of the False Colour Composition (FCC) was generated (Erdas Imagine Tour Guides, 2014). The study area was clipped using ‘subsetting tool’ of the software, and histogram equalization method was used to enhance the spectral responses of the images. To analyse changes near the river within a 10 km buffer zone, overlaying the LULC data as the background provides a visual reference for the land use and land cover (LULC) classes and their distribution within the image. This helps in identifying and analyzing specific changes of features within the image in relation to the

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Fig. 4.8 Workflow for land use and land cover map preparation using satellite images

existing LULC classes. This enhances the overall interpretation and understanding of the observed data. The National Remote Sensing Centre (NRSC) classification scheme was used to classify the images. The study area is broadly classified by different classes depending upon the study area features. The classification was applied depending on colour, texture, and tone (Radhakrishnan et al., 2014). The data was trained using band combination and Google Earth. The band combination of 4-3-2 (1992) and 5-4-3 (2022) was used for creating FCC and identifying the LULC classes such as agricultural land, vegetation, water bodies, fallow land, built-up area, and sand bar using eye visualization. Moreover, Google Earth images of the respective years have also been used to confirm the identified LULC features. Finally, training sites were

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created using the drawing polygon tool of Erdas imagine in the Area of Interest (AOI) of the image. The signature editor tool of the software is used to store each specific AoI to generate specific classes and each class contains as much as possible AoI, which is merged into one single class. Therefore, the signature editor file was saved as a signature file (.sig format) and a total of 8 signature files were generated in this study to train the data set in the supervised classification process. The common remote sensing techniques used to classify the image are pixel-based classification, objectbased, supervised, and unsupervised classification. In this study, we used the Maximum Likelihood Classifier (MLC) algorithm of supervised classification widely applied for medium-resolution satellite images for classification (Zubair & Javed, 2018; Ratnaparkhi et al., 2016; Anil et al., 2011). MLC technique is based on Bayes’ classification and the algorithm (Eq. 4.1) classifies the image by computing the weight distance (Dw) of an unknown vector (x) belonging to the known class “i” (Erener, 2013). Dw = ln(ai) - [0:5 ln(|Cov(i)|] - [0:5(x - M c )T (Cov(i) - 1(x - M c )]

(4:1)

where c is a particular class, ai is the percent probability of any pixel in a member of class i. The datasets downloaded from the GloVis portal, according to date, contain error known as ‘salt and pepper effect’. Therefore, a majority filter with a 4 × 4 size kernel was applied to minimize the error in these images (Kantakumar et al., 2016). The images were classified after the majority filter was applied and generated the LULC map to compare with each other to determine the variation in the LULC pattern. (c) Results and Discussion The tell-tale binary in river training between the European and tropical nations has been demonstrated taking some case studies across the world. In the context of the Mississippi River (USA), agricultural land has declined from 1992 km2 to 731 km2 (Fig. 4.9a, b). It is quite interesting to note that there has been a spurt in the vegetation cover, i.e., 1130 km2 has increased during 1992–2022. Settlement in this river basin has increased in some way and the majority of the settlement has evolved along the riverbanks resulting in the embankment of the river courses. Thus, river courses here are less oscillatory and stable (Harmar et al., 2005; Smith & Winkley, 1996). Similarly in the context of Europe, a river portraying a higher rate of erosion has been stabilized by concrete as well as bioengineered embankments (Lachat, 1999; Faber, 2004). For example, Evette et al. (2009) mentioned vegetative engineering for river stabilization, particularly the Wattle fence to protect the Drôme River of southeastern France. Thus, riverbank erosion is not a major issue in landscape planning in recent times in Europe and America. However, riverbank erosion has become a serious issue posing threats to both the natural and human resources in floodplain regions of many countries of Asia like

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Fig. 4.9 LULC changes in America – a case of the Mississippi River, (a) 1992, (b) 2022

India, Bangladesh, and China (Das et al., 2014). For example, the frequent and intense nature of bank erosion of the Padma, Jamuna, and Meghna rivers in Bangladesh significantly has changed the pattern of land use and land cover due to bank erosion which has been portrayed in studies since the twentieth century. Arefin et al. (2021), for example, prominently observed that the vegetation, cultivated land, and rural settlements show very unstable land use and land cover due to riverbank erosion. Mamun et al. (2022) illustrated that about 8700 ha of land consisting of settlement and cultivated area is lost every year as a consequence of riverbank erosion in Bangladesh displacing ~200,000 people. Sarker et al. (2022) observed that ~25% of people living in the charlands of Bangladesh are compelled to migrate three times in the last decade due to riverbank erosion. In India riverbank erosion as a fluvial hazard has been studied from several perspectives where many researchers are concerned with establishing links between riverbank erosion and different socioenvironmental issues – land use and land cover change; livelihood vulnerability; psychological distress, etc. Talukdar et al. (2020) integrated land use and land cover

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115

change due to the Ganga Riverbank erosion with the livelihood vulnerability of the people. Islam and Guchhait (2018) measured the severity of land loss (agricultural and settlement) due to bank erosion on the left bank of the Bhagirathi River and investigated the social and psychological changes of the erosion victims. Guite and Bora (2016) measured that Subansiri riverbank erosion (Assam) caused the loss of agricultural lands (461.49 km2) and forest areas (134.05 km2) during the year 1956–2010. Regarding agricultural land, the picture opposite to the Mississippi River was observed during 1975–2022, i.e., an increase in agricultural land is remarkable for the Mekong, Ganga, and Bhagirathi River basin area (Figs. 4.10, 4.11, 4.12, 4.13, 4.14, and 4.15). However, the Hooghly River resembles the Mississippi River in this regard because the intensifying urbanizing force has been present in the Hooghly River basin in recent times (Table 4.4). This is mainly due to the expansion of urbanization in and around Kolkata city (Mondal et al., 2017; Chakraborty et al., 2021). However, the nature of urbanization between the Mississippi and Hooghly Rivers largely differs. In case of the Hooghly River basin, an urban built-up area emerged. In this regard, the nature of urbanization resembles the other countries of

Fig. 4.10 LULC changes in the Asian countries – a case of the Mekong River. (a) 1992 and (b) 2022

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Fig. 4.11 LULC changes in the Ganga-Padma region. (a) 1992 and (b) 2022

Asia because the loss of forest cover giving way to urbanization is a common scenario in developing nations owing to the huge population pressure and intensive use of land. In the context of Bhagirathi Hooghly and the Ganga River nature of the

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117

Fig. 4.12 LULC changes in the Bhagirathi region. (a) 1992 and (b) 2022

bank, erosion is comparatively higher (Table 4.5). Maldah district along the Ganga River and Murshidabad, Nadia and Purba Bardhaman along the Bhagirathi river suffer a lot due to frequent changes in the river channel. Here, relocation of settlement and shifting of the agricultural land development of chars are quite common and often oscillatory. Therefore, sandbar areas and waterbodies fluctuate from time to time because of the profuse nature of erosion and accretion sequence. In both the eastern and western parts of the Bengal Delta, the severity of bank erosion is recorded in past because of the oscillation of major rivers like Ganga, Padma, Meghna, and Brahmaputra. However, relocation of LULC type induced by bank erosion in many cases does not reflect in an absolute areal change of specific

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Fig. 4.13 LULC changes in the Hooghly River basin. (a) 1992 and (b) 2020

land use category. Thus, it is imperative to study the LULC changes in the wake of riverbank erosion. It needs to be studied in the context of micro-level analysis at a short time span. Therefore, the following section will be devoted to exploring LULC changes in the mouzas (smallest administrative units for revenue collection in India and Bangladesh) located along the river courses.

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119

Fig. 4.14 LULC changes in the Brahmaputra region. (a) 1992 and (b) 2022

4.2.1.2

Site-Specific Analysis

(a) Mouza-scale Analysis in India The immediate impact of bank erosion has been investigated through intense field observation. The present investigation will focus on the changing land use pattern within the period of 1920–2020 in all four mouzas viz. Matiari, Akandanga,

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Fig. 4.15 LULC changes in the Padma and Meghna region. (a) 1992 and (b) 2022

Rukunpur, and Char-Kashthasali. In the 1920s all the mouzas registered more than 85% of agricultural land. Except for Matiari other three mouzas had the figure of agricultural land well above 89% (Figs. 4.16a, c and 4.17a, c). But in 2020, there is a significant fall in agricultural land use. In 2020, it is observed that for Matiari and Rukunpur mouzas, the share of agricultural land has come down to ~60% (Figs. 4.16b, d and 4.17b, d). The loss is vehemently due to bank erosion. In other areas, there is a substantial fall in agricultural land use. This fall in agricultural land use is triggered by both the absolute and relative loss of agricultural land induced by riverbank erosion. In all the mouzas a significant proportion of agricultural land has been engulfed by the Bhagirathi River. It ranges from 3% to 111% in the different mouzas. Barring erosion, accretion is found. Eroded bank materials are transported downstream and are deposited under suitable channel morphological and hydrological conditions in the form of bars or charland. Again a portion of agricultural land has been converted into sand bars or charland formed by the deposition of bankside materials downstream. These two types of land loss constitute the absolute loss of agricultural land in the mouzas. The relative loss of agricultural land has been detected from non-agricultural activities and also by orchard farming, i.e., the expansion of settlements, communication lines, and orchards. Between 1920 and 2020, the settlement area increased for all the selected mouzas. It is observed that in all the cases, the residential area has become doubled or more. The main reason for

Class name Agricultural land Vegetation Built up Waterbodies Sand bar

Mississippi River 1992 2022 1992.73 731.06 1667.58 2225.03 131.68 429.26 340.60 457.01 23.95 314.16 Change -1261.67 557.46 297.58 116.42 290.22

Mekong River 1992 2022 759.11 1472.93 1284.28 343.74 164.13 381.63 292.73 284.90 49.60 66.65

Table 4.4 LULC dynamics of Mississippi, Mekong, and Ganga Rivers (in km2) during 1992–2022 Change 713.82 -940.54 217.50 -7.82 17.04

Ganga River 1992 2022 4370.51 3201.95 617.15 614.19 508.29 1167.31 486.88 846.18 515.12 668.33

Change -1168.56 -2.97 659.01 359.30 153.22

4.2 Land Use and Cover Changes and Bank Erosion 121

Class name Agricultural land Vegetation Built up Waterbodies Sand bar

Bhagirathi River 1992 2022 2510.35 2412.19 460.31 140.16 399.38 727.59 177.49 201.99 6.61 72.21

Change -98.16 -320.15 328.21 24.50 65.60

Hooghly River 1992 2022 2204.69 1968.37 1324.43 415.55 767.39 1892.95 1359.65 1334.41 26.24 71.10 Change -236.32 -908.88 1125.57 -25.23 44.86

Brahmaputra River 1992 2022 1994.16 1939.35 504.02 166.76 148.28 685.57 1499.72 1203.22 1583.80 1852.98

Change -54.81 -337.27 537.29 -296.50 269.18

Table 4.5 LULC dynamics of Bhagirathi, Hooghly, Brahmaputra, and Meghna Rivers (in km2) during 1992–2022 Meghna River 1992 2022 2076.47 1428.22 307.72 479.32 103.38 341.07 1460.16 1828.88 499.89 370.39

Change -648.25 171.60 237.68 368.72 -129.50

122 4 Riverbank Erosion: A Human-Induced Process

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123

Fig. 4.16 LULC changes in the Matiari and Akandanga mouza. (a) Matiari-1920, (b) Matiari2020, (c) Akandanga-1920, (d) Akandanga-2020

the expansion of the residential area in Matiari Mouza is the pull force of the brass metal industry. In the case of Char-Kashthasali, the expansion of settlement is due to the in-migration of the population from other severely eroded mouzas for survival reasons. In Rukunpur and Akandanga the growth of settlement is out and out natural rather than by migration. An increase in orchard area may be attributable to the substitution of traditional agriculture because traditional agriculture is no more

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Fig. 4.17 LULC changes in the Rukunpur and Char-Kashthasali mouza. (a) Rukunpur-1920, (b) Rukunpur-2020, (c) Char-Kashthasali-1920, (d) Char-Kashthasali-2020 Table 4.6 Changes in the major land use and land cover during the 1920s and 2020 in the study area Mouza Matiari Akandanga Rukunpur Char-Kashthasali

Agriculture (%) 1920 2020 85.7 59.78 96.2 61.36 89.74 43.87 97.43 70.99

Settlement (%) 1920 2020 7.25 16.36 1.16 8.82 4.97 8.18 2.02 7.99

Waterbodies (%) 1920 2020 3.4 0.97 2.2 5.49 3.92 6.73 0.4 1.32

Orchard (%) 1920 2020 1.7 6.89 0.44 15.67 1.37 15.4 0.15 14.07

remunerative and orchard farming is relatively more profitable than traditional crop farming. Therefore, it is observed that the major land uses viz. agricultural land, settlement, and orchard underwater land and sand bars (Charland) exhibit various scenarios (Tables 4.6 and 4.7). It is to be observed that the share of agricultural land has registered negative growth for all the cases while the settlement area has registered

4.2

Land Use and Cover Changes and Bank Erosion

Table 4.7 Changes in the major land use and land cover (land under water, sand bar, and others) during the 1920s and 2020 in the study area

Mouza Matiari Akandanga Rukunpur Char-Kashthasali

125 Land under river (%) 1920 2020 1.95 11.56 0 4.5 0 12.12 0 3.64

Charland (%) 1920 2020 0 4.44 0 4.16 0 13.7 0 1.99

Source: Field Survey, 2020 (Note: The above two tables depict the percentage figure of land uses and total mouza area for Matiari-619.2 Hectare, Akandanga-321.7 Hectare, Rukunpur-273.57 Hectare, and Char-Kashthasali-764 Hectare)

Change in LULC (%) during 1920 and 2020

Agricultural land

Settlements

Waterbodies

Orchard

Land under river

Rukunpur

Char-Kashthasali

Charland

20 10 0 -10 -20 -30

Matiari

Akandanga

-40 -50

Mouza

Fig. 4.18 Growth of various land use during the 1920s and 2020

positive growth during the period between the 1920s and 2020s (Fig. 4.18). Share of orchard, charland, and land within the channel have increased substantially for all the cases. (b) Bangladesh-upazila/Village-level Analysis The scenario of riverbank erosion is really critical and demands a micro-level analysis in some areas of the eastern part of the Bengal Delta (Bangladesh) to glean out the grim nature of the locality. To this end, it is intended to analyse the microlevel bank erosion in Bangladesh with reference to union (rural areas located between mouza and sub-district or upazila) and mouza (lowest demonstrative unit for revenue collection). Contrary to the West Bengal part, many mouzas in Bangladesh are completely devoured by some rivers like Padma and Jamuna. Naturally, there are several attempts in this region to quantify riverbank erosion. The works of Rahman et al. (2016) and Ghosh (2022) are notable in this regard. Rahman et al. (2016) portrayed the severe nature of bank erosion of the Padma River in Harirampuram upazila (Table S4.3). There are 3 unions (Lesraganj, Sutalary, and Azimnagar) out of 13 unions in Harirampur that are completely engulfed by the

Fig. 4.19 Severity of bank erosion along the Padma River, (a) Riverbank erosion in different unions along the Padma River at Harirampur Upazila. (Based on Rahman et al., 2016), (b) Erosionaccretion dynamics along the left bank of the Padma River at Harirampur (Note: Blue colour arrow indicates the direction of the Padma River while other arrows indicate direction of bankline shifting from time to time)

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127

Fig. 4.20 Land use change, channel condition, and sediment yield over time, Piedmont region, USA. (After Wolman, 1967)

Padma River (Fig. 4.19a, b). In Sulatray union, Sutalary, Baliaghop, Hajipur, Nischintapur, Char Nischintapur, Dubail, and Pubakanda mouzas comprising 3878 acres have been completely washed away by the Padma River (Table S4.4). Similarly, 22 mouzas under Lesraganj union having a total area of 8310 acres have been eroded by the Padma River (Table S4.5). Besides, in the Harukandi union, 10 Mouzas suffered critically due to bank erosion (Table S4.6). About 90% of the total area (3928 acres) in this union is also eroded.

4.2.2

Impact of Land Use on Channel Instability and Bank Erosion

Land use around the riverbank has an impact on fluvial hydrodynamics. Various scholars have addressed this issue for various spatial and temporal scales from different aspects. Thorne (1991) has shown the impacts of catchment land use change on channel instability through techniques of channel evolution model and bank stability model in the areas of Bluff-line hills of north-central Mississippi. Jacobson et al. (2001) have shown the effects of land use change on the instability of physical habitat of the stream. Booth (1990), Bledsoe and Watson (2001) and Doyle et al. (2000) have shown the impacts of drainage basin urbanization on channel instability. Wolman (1967) has shown the impact of land use change on sediment yield and channel condition for the Piedmont region of the USA for the period 1780– present (Fig. 4.20).

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Fig. 4.21 Schematic representation of the influence of riparian flora on the riverbank stability. (Based on Barua et al., 2011, 2019)

(A) General In the era of the Anthropocene, floodplain regions of most of the major rivers of the world have experienced a few common trends in LULC change, for example, clearance of vegetation, expansion of agriculture and urbanization at a large and rapid scale. Besides, in-channel modification in the forms of channelization, construction of dams and bridges, artificial levees, and bank protection, are also observed. Therefore, the anthropogenic land use change has a strong repercussion on the river system significantly changing the water quality, nutrients, sediment discharge, and flow hydraulics. Besides, riverbank erosion strongly controlled by the changing pattern of land use and land cover has received considerable attention from researchers across the world. (B) Bhagirathi In the study area, it has been observed that there is a gradation in the susceptibility level of erosion (Fig. 4.21). Nearly bare ground experiences maximum erosion because it is easily attacked by hydraulic force-driven bank erosion and surface run-off-induced soil erosion. Riparian vegetation protects banks from erosion through their root cover, plant cover, and soil modification capacity (Fig. 4.22). The significance of riparian vegetation as a control of channel form and process is increasingly being recognized in fluvial research (Rowntree & Nowak 1991; Gregory et al., 1992). Vegetation operates in a variety of ways: in some

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129

Fig. 4.22 Erosion susceptibility of various land uses along the left bank of Bhagirathi River. (Islam & Guchhait, 2013)

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4 Riverbank Erosion: A Human-Induced Process

circumstances, it increases bank stability; in others, it may affect hydraulic action as the root network binds up soil and retards soil erosion. Reduced soil erosion impacts the turbidity of water with subsequent effects on hydraulic forces. However, the nature of bank erosion varies according to plant type and species. One interesting observation is that orchards especially mango or banana orchards are more susceptible to bank erosion than grass cover because tree cover increases the erosive impact of raindrops contrary to the current belief that “incident rainfall is deprived most of its erosive force by tree cover” (Dohrenwend, 1977). Tsukamoto (1966) observed that canopies cause an increase in the kinetic energy of falling rain that increases the erosion of forest (Table S4.8) compared to the bushy trees and grass covers. Dutta et al. (2011) have worked out the conservational values of several common species in the Ganga Brahmaputra region (Table S4.9). Ambasht (1963) has shown that C. dactylon, S. spontaneum, and V. zizanoides have tremendous soil binding capacity by their root system when planted in an eroded riverbank of the Brahmaputra River system in Majuli of North East India. Saccharum species exhibited the highest conservation value and were effective in checking erosion in the Ganga River (Ambasht, 1970). Similar findings have been observed in the present study. In the study area kans (S. spontaneum) are the most efficient species to bind the soil and protect the land from bank erosion. The river stretches covered by kans grass have been observed to be the least erosion-prone than the other land uses. Kans grass is a grass native to South Asia. It is a perennial grass, growing up to three meters in height, with spreading rhizomatous roots. Leaves are harsh and linear, 0.5–1 m long; 6–15 mm wide. Because of this cover and root characteristics, this species proved most suitable for checking bank erosion.

4.3 4.3.1

Other Anthropogenic Drivers of Bank Erosion Brickfields and Sediment Flux

Brickfield industries and road-stream crossings are the other aspects of the human interventions over the Bhagirathi River Basin (BRB). Mushrooming of the brick fields along the banks of the river is notable (Fig. 4.23). At present, there are 41 brickfields in the head reach (Left Bank: 16 and Right Bank: 25), 61 in the middle reach (Left Bank: 32 and Right Bank: 29), and 52 in the tail reach (Left Bank: 18 and Right Bank: 34). Brickfield generally induces riverbank erosion (Das, 2016). The higher the number of brick fields along a river the greater the area of bank failure because of the cutting of earth materials from the riverbank (Fig. 4.24a, b). The ideal materials for the brick kiln industries are silt or clay silt materials along the bank. The brick kilners extract the silty materials from the upper horizons of the soils and destabilize the sandy layer at the bottom by the fluvial actions that expedite the bank failure along the Bhagirathi River. Moreover, they often create shallow depressions along

4.3

Other Anthropogenic Drivers of Bank Erosion

131

Fig. 4.23 Location of brick field and road-stream crossing

the riverbank to trap the silt during the flood stage and extract those afterwards for the industries (Fig. 4.25a, b). This way a brick kiln may increase the channel width with time. According to an estimate done by the District Land & Land Reforms Office (DL&LRO) of Nadia District in 2009, a kiln can move earth materials of about 3770 m3 in a year. This much material is extracted from within that river basin. If this figure is multiplied by the number of brick kilns located adjacent to the Bhagirathi

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Fig. 4.24 Riverbank erosion in relation to brick kiln industry, (a) Shallow depression in the brick kiln area for entrapping sediment during flood along the left bank of Bhagirathi River, near Beldanga; (b) Bank failure due to cutting of soil from the upper horizons near Nabadwip. (Source: Field photograph, 2011)

River it is equal to about 580,465 m3 of materials movements in 2019 which has increased from 184,694 m3 in 2000. This earth material movement by the anthropogenic processes is a real concern when comparing this figure with the annual sediment budget (0.5 to 1.0 × 106 m3 per year) by natural river transport of the Bhagirathi River. This estimate outlines the influence of humans on the sediment transfer process of the Bhagirathi River belt. Moreover, the morphological change

4.3

Other Anthropogenic Drivers of Bank Erosion

Reduced level (m)

17.5

LB of river

133

Agricultural land

(a)

17 16.5

Area of silt extraction for

16 15.5 15 14.5 0

10 20 30 40 50 60 70 Distance from the left bank of the river to brick field (m)

Reduced level (m)

19

80

(b)

18 17 16 15 14 0

10

20 30 40 50 Distance from left bank of the river to land (m)

60

70

Fig. 4.25 Alteration of topographic expression due to brick kiln industries, (a) Formation of the artificial valley due to silt excavation, (b) artificial spur-like feature

along a bank dotted with the location of the kilns is also remarkable. To address the impact of the brick kiln industry on the morphological changes along the Bhagirathi River, a few cross-sections were drawn. Generally, it is observed that from the bank of the river, elevation increases towards land or sometimes decreases after the natural levee is encountered (Fig. 4.25b). The natural landscaping is disrupted by the excavation of shallow depressions to entrap the sediment during the flood. The nature of the cross-sections portrays that from the bank of the Bhagirathi, there is a sharp fall in elevation and then rise abruptly where sediment cutting is not present (Fig. 4.25b).

4.3.2

Road Stream Crossing and Channel Changes

Over the Bhagirathi there are four road crossings (head reach: 2; middle reach: 2). Besides, human activities like bamboo fencing across the river, and ship movements along the river also control the hydro-geomorphological aspects. Road crossing

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(a)

19

(b)

17 1994

Elevation (m)

15

1976

13 11 9 7 5 0

50

100 150 Distance (m) from left bank

200

250

Fig. 4.26 Bed scouring due to the presence of road piers of Berhampore bridge. (a) Pier location, (b) Changing cross-sectional morphology. (Source: Ghosh, 2000)

across a river regulates the flow characteristics of a channel thereby inducing morphological changes (Gregory & Brookes, 1983). There are generally two types of structure: a. suspension bridge, b. cantilever bridge. The former generally constricts the channel while the latter directly modifies flow characteristics. Over the Bhagirathi River majority of the crossings are cantilevers having piers in between the two ends of the bridge. The piers play a vital role to modify the flow pattern by obstructing the flow and thereby scouring one side and deposition in between two piers. Morphological changes are observed below the Berhampur Bridge (Fig. 4.26a). During 1976 and 1994 reversal thalweg is more striking. Thalweg was oriented towards the left bank in 1976 while the right bank orientation of thalweg is found in 1994 (Fig. 4.26b). The alternate pattern of bed scouring and bed deposition during 1976 is suspected to be a consequence of the bridge piers.

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Other Anthropogenic Drivers of Bank Erosion

135

However, the hydraulic impulse from the FBP has increased bed scouring at a much faster rate and increased the cross-sectional area which has masked the effects of the road-stream crossing on channel morphology. Besides, the bridge near Azimganj was completed in the year 2010 with the recent technology to carry the increased loads. In this bridge, two piers are directly within the channel which has an impact on the local water level upstream of the piers. The typical geometry of these piers is that they have larger pier width at the bottom which has narrowed up. Over the past few decades, numerous researchers have looked into road-stream crossings as an important cause of riverbank erosion and channel shifting in Bangladesh. Researchers have, therefore, made significant progress in their investigation into how bridges affect rivers’ shifting. By implementing better management strategies, they have given suggestions to limit the detrimental effects on channel morphology. For example, Islam et al. (2017) and Uddin et al. (2022) examined the effects of the bridge on the dynamics of the morphological characteristics of the Jamuna and Dharla Rivers in Bangladesh and discovered notable morphological changes on the river after the bridge construction. The rise in the bar area, bar migration, bar change in shape, increase in bank erosion rate, enormous sediment deposition, river widening process, change in river discharge capacity, the occurrence of disasters, etc., were the main physical effects of the bridge found in their study. The bridge piers, according to studies by Biswas (2010), restrict the river’s access, which ultimately causes riverbank shifting. Ibitoye (2021) identified that the construction of the bridge over the river had clearly caused the bank line to move in both the east and west directions. These piers have reduced the effective water area and hence an increase in the upstream water level called afflux. Besides, the river training works on both banks also obstruct the flow during the high stage in the monsoon period. Actually, this boulder-strewn surface is prepared to restrict the channel oscillation and to save the bridge from the future probable collapse of the bridge. The artificially created boulder bed offers flow resistance and hence modification of the hydraulic behaviour of the Bhagirathi River. Another bridge at Balarampur near Berhampore (Fig. 4.27a, b) is under construction with three piers amid the channel beside another pier for additional services.

4.3.3

Guide Bank and Sedimentation

A guide bank is built to flow a river through a narrow channel without causing damage to the structure. Near Prachin (old) Mayapur, Nabadwip a bamboo-made guide bank was installed across the Bhagirathi river in 2011. This structure is mainly intended to divert the flow of the Bhagirathi River through a narrow passage on the right bank in order to pass the Inland Waterway Authority of India (IWAI) vessels. The width of the river in this area is ~1 km and the flow during the dry seasons is meagre (~25,000 cusecs). As the dispersed flow is unable to move the vessel, maintenance of a minimum water depth of about 2–3 m becomes essential.

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Fig. 4.27 Road stream crossing and bank erosion, (a) Nasipur Railway Bridge near Hazarduari, Murshidabad, (b) New Bhagirathi bridge near Balarampur under construction. (Field photograph, 2019)

Therefore, anthropogenically-induced sedimentation is encouraged for flow obstruction in a part of the channel in an attempt to increase the depth of the channel in other parts. In the context of the lower Bhagirathi River, the oblique pattern of the bamboo fencing induces the growth of a mid-channel bar through sedimentation (Fig. 4.28).

4.3.4

Vessel Movements and Bank Failure

The last but not least anthropogenic factor of riverbank failure is the movements of the vessel within the river channel that induces the bank instability and ultimately collapse of the riverbank (Rahman et al., 2022). The mechanism of bank failure is

4.3

Other Anthropogenic Drivers of Bank Erosion

137

Fig. 4.28 Bamboo-made guide bank inducing sedimentation near Nabadwip. (Field Photograph, 2011)

due to the creation of centrifugal force at the meander bends of the river. If the ship travels upstream the wave angle is positive and becomes equal to θ′. However, the wave angle is negative and is equal to -θ′ if the ship travels downstream of the river (Fig. 4.29). Bank failure due to the movements of vessels, ships, or boats is widely noted across the world. For example, Nguyen et al. (2021) have demonstrated through their intensive field studies of Hau River’s entrance navigation of South Vietnam that the riverbanks are capable of resisting the external shear stress by maximum wave height ranging from 40 to 60 cm. Similarly, McConchie and Toleman (2003) showed that the maximum wake waves generated by jet boats, outboard powered boats, and jet skis ranged in height from 6 to 133 mm for the Waikato River, New Zealand. These vessels-generated waves were 2–80 times larger than background wind-generated waves that are vital for creating the loss by bank erosion. In the context of the Bengal Delta, bank erosion by the ship movement is quite common because, in West Bengal and Bangladesh, the major rivers are used as navigable routes for freight and goods. In India, Bhagirathi River is a national waterway no. 1 since the pre-independent period and it was used for the movements of goods and passengers. However, in due course, the navigability has reduced resulting in the stopping of the movement of passengers through the Ganga River from the Bay of Bengal to Uttar Pradesh (Islam et al., 2020). Nowadays, the Inland

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Fig. 4.29 Pattern of Kelvin wave and wave propagation angle towards the riverbank. (Based on Kurdistani et al., 2019)

waterway authority of India (IWAI) is trying to keep a minimum navigability of 3 m width for all-year ship movement. Therefore, on the Bhagirathi-Hooghly River system, episodic movement of the ship makes the riverbank unstable due to shipinduced high amplitude waves (Fig. 4.30a). Nanson et al. (1994) also noted that there is a significant positive correlation between the maximum wave height in a train caused by the ship movement and the rate of bank failure in the Gordon River, Tasmania. Similarly, Kurdistani et al. (2019) also found that wave height, wave period, and wave obliquity are directly correlated with bank instability. Interestingly, the typical soil profile along the banks of Bhagirathi River is mainly constituted by coarse sand that will become fragile when a wave appears due to ship movements. Thus, large ships’ movement with an increase of 30–50 cm wave height increases the propensity of the undermining of the bottom layers of the river eventually leading to the collapse of the upper portion of the bank (Fig. 4.30b).

4.3

Other Anthropogenic Drivers of Bank Erosion

139

Fig. 4.30 Bank failure due to ship movement near Beldanga. (a) Movement of the vessel, (b) Fall of cohesive bank

In the context of Bangladesh, the ship movement-induced riverbank erosion is notable. A study conducted by Rahman et al. (2022) through a field survey and found that the average velocity of most of the launches for the Kirtankhola River in Barishal, Bangladesh is above 30 km h-1 which is above the critical velocity of 20 km h-1 (Table S4.7). Therefore, the bank erosion is triggered by the high amplitude waves. Riverbank erosion as a process is thus explained in terms of anthropogenic (this chapter) and natural drivers (Chap. 3). However, it would be fascinating to observe the major changes that occurred in a fluvial system due to riverbank erosion. The next chapter would be devoted to exploring channel morphology in terms of bank erosion.

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Part III

Riverbank Erosion: Form and Vulnerability Approach

Every process is linked to the causation of a particular form. The processes of riverbank erosion manifest their impact on the fluvial, economic, and social landscape. Riverbank erosion and channel morphology (Chap. 5) are concerned with the planform features such as spatiotemporal growth of the channel sinuosity and braiding of the major rivers of the Bengal Delta and cross-sectional forms such as channel geometry and asymmetry of the Bhagirathi River, West Bengal. Economic vulnerabilities induced by riverbank erosion (Chap. 6) depict the adverse effect of riverbank erosion on occupational structure, income, and agricultural practices. The social dimensions of riverbank erosion in most cases are targeted to chalk out reasons, problems, and mitigations from a humanistic outlook. Social instabilities induced by riverbank erosion (Chap. 7) portray the dilapidating conditions of the family institution like family, education, health, and marriage. Social processes, social psychology of hazards, etic and emic perspectives of bank erosion, and social turmoil in relation to the charland ownership are the important dimensions of discussion.

Chapter 5

Riverbank Erosion and Channel Morphology

5.1

Channel Planform Changes

5.1.1

Channel Oscillation and Meandering in Bengal Basin

Stream meandering is a natural tendency of a river. It induces the hydrodynamic flow of water in a sinuous pattern resulting in slope modification, bed deposition, bank erosion, etc. As a result, the straight channel is rare in nature (Leopold & Langbein, 1966). Channel oscillation and meandering are common occurrences in deltaic regions and flood plains. Oscillation and meandering of the channel is a major indicator of channel instability and bank erosion here occurs as a response to changing morphometric variables through its adjustment mechanism. Fluvial hydraulics triggers channel oscillation in natural ways, though it may be intensified by anthropogenic processes. Thus, channel oscillation and meandering are measured in the following sections to comprehend the river channel evolution.

5.1.1.1

Oscillatory Behaviour and Meander Deformation

The rivers of the Bengal Delta are frequently oscillating as evidenced in history (Islam, 2016). The major rivers like the Ganga, Brahmaputra, Meghna, Padma, and Bhagirathi-Hooghly have shifted their positions from time to time because of hydrogeomorphic and anthropogenic reasons over the decades. The pattern of channel changes continues for the active rivers of the Delta. However, the rivers like Jalangi, and Mathabhanga-Churni, of South Bengal are now disconnected from their parents due to the eastward tilting of the Bengal Basin caused by neotectonic movements and the anthropogenic trigger factors are now decaying channels with minimum flow

Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/978-3-031-47010-3_5. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Islam, S. K. Guchhait, Riverbank Erosion in the Bengal Delta, Springer Geography, https://doi.org/10.1007/978-3-031-47010-3_5

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Riverbank Erosion and Channel Morphology

Fig. 5.1 Types of meander modifications. + stands for increasing; - for decreasing; u for upstream; d for downstream. (Based on García-Martínez & Rinaldi, 2022)

only during the monsoon months. Thus, these decayed channels are almost stable in recent times. However, the major courses of the GBM delta still oscillate in different ways. The nature of the river oscillation is thus given due consideration with respect to the Ganga, Brahmaputra, Meghna, Padma, and Bhagirathi-Hooghly Rivers. The readily available high-resolution satellite images from 1990 helped in understanding the oscillatory behaviour of the rivers during the last three decades (1990–2020). Deformations in the channel meander denote the instability of a channel over time and space. Meander deformations are measured using probable seven types of transformations (García-Martínez & Rinaldi, 2022): (1) extension where meander amplitude either increases or decreases, (2) rotation where two successive loop heads approach each other, however, their bases do not rotate, (3) expansion where a loop may either expand sidewards or contract, (4) cut-off where a loop is disjointed from the parent river either by neck cut-off or chute cut-off, (5) translation where two loops with their complete morphology (one upstream and another downstream) move towards each other, (6) secondary bends where multi-headed meander is formed, and (7) irregular changes where other definite changes are not noted. These typical deformations are explained in Fig. 5.1. From 1990 to 2020 the pattern of meander deformation for the major rivers of the GBM delta is really fascinating. Out of the seven types of deformation as indicated earlier virtually all types of deformation are distinctly located. The maximum positive extension (~58%) is found to be located on the right bank of the GangaPadma River while the minimum (20%) is found on the left bank of the Hooghly River. However, the negative extension is comparatively lesser in the fluvial system. The loops located on the right bank of the Ganga-Padma River showed a maximum of ~15% loops in the negative extension category for the right bank of the Bhagirathi River, left and right bank of the Hooghly River and left bank of the Ganga-Padma River. Another typical deformation in meander geometry is the rotation of the loops that can appear both in the downstream or the upstream direction in the GBM delta. In the present context, the highest (~38%) upstream rotation has been observed on the left bank of the Bhagirathi River while the highest (~58%) downstream rotation has been found on the left bank of the Ganga-Padma River (Table 5.1). Furthermore, the maximum positive expansion (20%) of the meander loop is noted for the left

5.1

Channel Planform Changes

149

bank of the Hooghly River while the right bank of the same river portrays the maximum negative expansion (50%). The most significant changes in the meander geometry are often detected through the neck and chute cut-off. In the GBM delta, a maximum (~5%) neck cut-off is observed for the right bank of the Bhagirathi River while the maximum chute cut-off (20%) is found for the left bank of the Hooghly River. Interestingly, the trend of loop translation is striking for the rivers of the GBM delta with the maximum downstream translation (~67%) found to be located on the right side of the Hooghly River. However, the upstream translation is quite lower, i.e., maximum (only around 10%) being located on the right bank of the Bhagirathi River. Moreover, the complexity of the meander geometry is also detected through the growth of the secondary bends during the last 30 years (1990–2020). It is observed that around 86% of the loops are found to portray the secondary bends for the Ganga-Padma River implying the increasing level of meander complexity. However, the growth of the secondary loops for the Bhagirathi River is quite low which is indicative of the simple loop evolution. Similar observations are registered regarding the irregular changes in the meander geometry (Table 5.1). One interesting finding is that cut-off meander loops are vividly portrayed by some rivers, e.g., a cut-off near the char Chakundi area was recorded for the year 1994 reducing the length of 11.85 km in the same area. Another neck cut-off was observed for 2008 reducing a length of 3.6 km. Moreover, a vivid chute cut-off (Purbasthali cut-off) was noted near the Purbasthali area (Pakhiralaya) which happened in the year 1989 reducing the length to 9 km (Islam & Guchhait, 2017). This typical cut-off in the lower stretch of the Bhagirathi River indicates hydrogeomorphic instability in recent times. However, the other river of the GBM delta does not show such types of channel cut-offs during this particular tenure (1990–2000). However, rivers like Brahmaputra, Padma, and Meghna portray huge oscillations of the channel on either bank of the respective rivers (Fig. 5.2) which has been discussed with respect to EPR and LRR in Chap. 3.

5.1.1.2

Stream Meandering and Sinuosity

River meandering is easily detected through the changes in the sinuosity index which has been computed for the major rivers of the GBM delta using satellite images from 1990 to 2020 (Table S5.1). Mueller’s sinuosity index is used here to portray the dynamics of the meander through the topographic sinuosity index (TSI), hydraulic sinuosity index (HSI), and standard sinuosity index (SSI). For the river Ganga, it has been observed that the upper part (Rajmahal to Malda) shows that TSI has decreased from 1990 to 2000 while the TSI has increased from 2000 to 2010 and again decreased in 2020 (Tables 5.2, 5.3, 5.4, and 5.5). However, the middle part (Malda-Jalangi) shows that TSI increased from 1990 to 2000 and in 2010, but slightly decreased in 2020 (Tables 5.2, 5.3, 5.4, and 5.5). However, the lower part (Jalangi-Bangladesh) exhibits an increase in 2000 from 1990 and again a decrease in 2010 and further increase in 2020 (Tables 5.2, 5.3, 5.4, and 5.5).

Extension + 9 1 12 0 1 0 2 0 2 1 4 0 39.13 4.35 54.55 0.00 20.00 0.00 33.33 0.00 28.57 14.29 57.14 0.00 57.14 14.29 20.00 0.00

Rotation u d 8 6 5 8 0 2 2 1 0 4 0 2 34.78 26.09 22.73 36.36 0.00 40.00 33.33 16.67 0.00 57.14 0.00 28.57 34.78 57.14 0.00 16.67

Expansion + 1 8 4 7 1 2 1 3 1 3 0 2 4.35 34.78 18.18 31.82 20.00 40.00 16.67 50.00 14.29 42.86 0.00 28.57 20.00 50.00 4.35 31.82

Cut-off neck chute 1 0 1 2 0 1 0 0 0 0 0 0 4.35 0.00 4.55 9.09 0.00 20.00 0.00 0.00 0.00 0.00 0.00 0.00 4.55 20.00 0.00 0.00

Translation u d 0 11 2 5 0 1 0 4 0 0 0 0 0.00 47.83 9.09 22.73 0.00 20.00 0.00 66.67 0.00 0.00 0.00 0.00 9.09 66.67 0.00 0.00 Secondary bends 6 3 1 1 3 6 26.09 13.64 20.00 16.67 42.86 85.71 85.71 13.64

Irregular changes 4 4 1 2 4 6 17.39 18.18 20.00 33.33 57.14 85.71 85.71 17.39

Note: Brahmaputra and Meghna rivers are excluded from this analysis because they do not show such meander loops having sinuosity index (SI) > 1.05. Actually, two rivers profusely braided; “+” stands for positive change, “-” for negative change, “u” upstream loop, “d” downstream loop

GangaPadma

Hooghly

Bhagirathi

GangaPadma

Hooghly

Total loop L 23 R 22 L 5 R 6 L 7 R 7 L 100 R 100 L 100 R 100 L 100 R 100

5

Max Min

Number (%)

Actual number

River Bhagirathi

Table 5.1 Meander deformations of the major rivers of the GBM delta during 1990–2020

150 Riverbank Erosion and Channel Morphology

5.1

Channel Planform Changes

151

Fig. 5.2 Channel oscillation of major rivers of the Bengal Delta. (a) River Bhagirathi (Upper and Middle), (b) River Bhagirathi (Lower) and River Hooghly (Upper), (c) River Brahmaputra, (d) River Meghna, (e) River Ganga-Padma

Valley length (km) 155.684 146.446 153.755 109.973 81.092 94.026 128.616 130.809 42.718 52.260 33.430 90.112 89.599 112.395 101.494 39.931 39.344

Channel length (km) 165.287 165.507 165.808 110.140 81.520 95.101 129.117 132.722 46.545 52.443 36.657 90.352

90.008 113.737 105.353 43.308 41.108

81.126 69.546 77.164 33.772 43.766

Air length (km) 127.698 120.521 134.310 78.710 59.312 43.733 84.210 101.962 38.390 46.279 28.492 66.006 1.109 1.635 1.388 0.267 19.222

CI (CL/Ai) 1.294 1.373 1.235 1.399 1.374 2.175 1.533 1.302 1.212 1.133 1.287 1.369 1.104 1.616 1.343 0.281 20.883

VI (VL/Air) 1.219 1.215 1.145 1.397 1.367 2.150 1.527 1.283 1.113 1.129 1.173 1.365 0.954 0.970 0.846 0.185 21.827

TSI 0.745 0.576 0.617 0.995 0.981 0.979 0.989 0.938 0.531 0.970 0.605 0.990

0.046 0.030 0.154 0.185 119.567

HSI 0.255 0.424 0.383 0.005 0.019 0.021 0.011 0.062 0.469 0.030 0.395 0.010

1.005 1.012 1.037 0.045 4.297

SSI (CI/VI) 1.062 1.130 1.078 1.002 1.005 1.011 1.004 1.015 1.090 1.003 1.097 1.003

5

Note: Air length is the shortest distance between two points of a river reach; valley length is the length of a line which is everywhere midway between the base of the valley walls; channel length is the length of the channel (thalweg) in the stream under study

River stretch Ganga (Dilarpur – Godagari) Ganga (Godagari – Ambaria) Ganga (Ambaria – Chandpur) Bhagirathi (Farakka – Berhampur) Bhagirathi (Berhampur – Katwa) Bhagirathi (Katwa – Mrijapur) Hooghly (Mrijapur – Sankrail) Hooghly (Sankrail – Gangasagar) Brahmputra (Pakuria – Bahuka) Brahmputra (Bahuka – Sonatani) Bramputra (Sonatani – Daulatdia) Meghna (Parmanandapur – Sonargaon) Meghna (Sonargaon – Goal Bhaor) Meghna (Goal Bhaor – Hatia) Average SD CV

Table 5.2 Nature of sinuosity of the major rivers of the Bengal Basin in 1990

152 Riverbank Erosion and Channel Morphology

River stretch Ganga (Dilarpur – Godagari) Ganga (Godagari – Ambaria) Ganga (Ambaria – Chandpur) Bhagirathi (Farakka – Berhampur) Bhagirathi (Berhampur – Katwa) Bhagirathi (Katwa – Mrijapur) Hooghly (Mrijapur – Sankrail) Hooghly (Sankrail – Gangasagar) Brahmputra (Pakuria – Bahuka) Brahmputra (Bahuka – Sonatani) Bramputra (Sonatani – Daulatdia) Meghna (Parmanandapur – Sonargaon) Meghna (Sonargaon – Goal Bhaor) Meghna (Goal Bhaor – Hatia) Average SD CV

Valley length (km) 157.665 151.858 155.152 110.279 82.408 82.417 128.391 128.500 43.166 51.103 38.844 90.214 92.220 110.496 101.622 40.182 39.540

Channel length (km) 168.904 171.617 162.035 110.294 82.448 86.684 129.701 128.948 43.188 55.158 39.195 90.569

95.916 112.973 105.545 43.691 41.396

Table 5.3 Nature of sinuosity of the major rivers of the Bengal Basin in 2000

82.410 97.456 79.890 33.847 42.366

Air length (km) 127.698 120.783 136.011 78.708 59.283 43.770 84.192 103.558 38.357 46.425 33.811 66.006 1.164 1.159 1.333 0.225 16.907

CI (CL/Air) 1.323 1.421 1.191 1.401 1.391 1.980 1.541 1.245 1.126 1.188 1.159 1.372 1.119 1.134 1.291 0.215 16.652

VI (VL/Air) 1.235 1.257 1.141 1.401 1.390 1.883 1.525 1.241 1.125 1.101 1.149 1.367 0.726 0.840 0.853 0.158 18.534

TSI 0.727 0.611 0.736 1.000 0.998 0.901 0.971 0.982 0.996 0.536 0.935 0.986

0.274 0.160 0.147 0.158 107.701

HSI 0.273 0.389 0.264 0.000 0.002 0.099 0.029 0.018 0.004 0.464 0.065 0.014

1.040 1.022 1.033 0.039 3.766

SSI (CI/VI) 1.071 1.130 1.044 1.000 1.000 1.052 1.010 1.003 1.000 1.079 1.009 1.004

5.1 Channel Planform Changes 153

River stretch Ganga (Dilarpur – Godagari) Ganga (Godagari – Ambaria) Ganga (Ambaria – Chandpur) Bhagirathi (Farakka – Berhampur) Bhagirathi (Berhampur – Katwa) Bhagirathi (Katwa – Mrijapur) Hooghly (Mrijapur – Sankrail) Hooghly (Sankrail – Gangasagar) Brahmputra (Pakuria – Bahuka) Brahmputra (Bahuka – Sonatani) Bramputra (Sonatani – Daulatdia) Meghna (Parmanandapur – Sonargaon) Meghna (Sonargaon – Goal Bhaor) Meghna (Goal Bhaor – Hatia) Average SD CV

Valley length (km) 165.410 155.888 154.252 109.778 82.535 84.745 127.744 129.476 43.469 51.631 40.903 90.231 89.610 83.139 100.629 41.256 40.998

Channel length (km) 168.574 157.340 160.379 110.035 82.557 86.059 129.014 131.033 44.574 53.574 46.630 90.278

90.662 86.834 102.682 41.482 40.399

Table 5.4 Nature of sinuosity of the major rivers of the Bengal Basin in 2010

1.095 1.085 1.304 0.233 17.879

CI (CL/Air) 1.314 1.235 1.115 1.398 1.392 1.969 1.532 1.241 1.146 1.154 1.211 1.368 1.082 1.038 1.274 0.244 19.116

VI (VL/Air) 1.290 1.224 1.073 1.395 1.392 1.939 1.517 1.227 1.118 1.112 1.062 1.367 0.866 0.455 0.823 0.221 26.882

TSI 0.922 0.952 0.631 0.992 0.999 0.969 0.972 0.939 0.806 0.729 0.294 0.998

0.134 0.545 0.177 0.221 124.968

HSI 0.078 0.048 0.369 0.008 0.001 0.031 0.028 0.061 0.194 0.271 0.706 0.002

1.012 1.044 1.026 0.036 3.485

SSI (CI/VI) 1.019 1.009 1.040 1.002 1.000 1.016 1.010 1.012 1.025 1.038 1.140 1.001

5

82.826 80.060 80.259 34.865 43.440

Air length (km) 128.272 127.363 143.783 78.699 59.306 43.714 84.233 105.558 38.884 46.414 38.513 66.006

154 Riverbank Erosion and Channel Morphology

River stretch Ganga (Dilarpur – Godagari) Ganga (Godagari – Ambaria) Ganga (Ambaria – Chandpur) Bhagirathi (Farakka – Berhampur) Bhagirathi (Berhampur – Katwa) Bhagirathi (Katwa – Mrijapur) Hooghly (Mrijapur – Sankrail) Hooghly (Sankrail – Gangasagar) Brahmputra (Pakuria – Bahuka) Brahmputra (Bahuka – Sonatani) Bramputra (Sonatani – Daulatdia) Meghna (Parmanandapur – Sonargaon) Meghna (Sonargaon – Goal Bhaor) Meghna (Goal Bhaor – Hatia) Average SD CV

Valley length (km) 165.898 145.506 163.752 110.019 83.027 85.890 127.449 127.143 44.972 52.028 41.260 89.886 88.720 76.669 100.158 41.239 41.174

Channel length (km) 170.439 152.910 167.586 110.223 83.549 86.714 128.502 128.948 47.127 58.607 45.949 90.208

89.490 81.040 102.950 41.515 40.326

Table 5.5 Nature of sinuosity of the major rivers of the Bengal Basin in 2020

82.688 73.263 79.736 34.926 43.802

Air length (km) 128.186 120.999 150.021 78.791 59.199 43.690 84.233 103.558 39.500 45.620 40.543 66.006 1.082 1.106 1.317 0.233 17.682

CI (CL/Air) 1.330 1.264 1.117 1.399 1.411 1.985 1.526 1.245 1.193 1.285 1.133 1.367 1.073 1.046 1.277 0.250 19.553

VI (VL/Air) 1.294 1.203 1.092 1.396 1.403 1.966 1.513 1.228 1.139 1.140 1.018 1.362 0.887 0.438 0.782 0.259 33.156

TSI 0.893 0.768 0.782 0.994 0.979 0.981 0.976 0.929 0.717 0.493 0.133 0.987

0.113 0.562 0.218 0.259 119.284

HSI 0.107 0.232 0.218 0.006 0.021 0.019 0.024 0.071 0.283 0.507 0.867 0.013

1.009 1.057 1.036 0.040 3.884

SSI (CI/VI) 1.027 1.051 1.023 1.002 1.006 1.010 1.008 1.014 1.048 1.126 1.114 1.004

5.1 Channel Planform Changes 155

156 Table 5.6 Selected meander loops for meander geometry analysis

5 Year 1927 1954 1974 1990 2000 2010 2020 Total

Riverbank Erosion and Channel Morphology Left bank loops 6 5 5 6 5 5 5 37

Right bank loops 6 5 5 6 6 6 6 40

Total 12 10 10 12 11 11 11 77

This depicts that critical dynamics of meander geometry induced by fluvial hydraulics that is making cut-offs as well as extensions of meanders in different time points. Though the evolution of the meandering behaviour is principally controlled by the topographic factors (elevation, slope, and litho-structural diversity), fluctuations in the fluvial hydraulics are found to play a variable role in the control of the stream meandering. It is pertinent to mention that all the major river stretches portray a higher TSI in 1990, although the upper and lower Brahmaputra were substantially controlled by the forces of the fluvial hydraulics. In 2000, it was observed that Upper Bhagirathi registered a TSI of 1 implying a total topographic control over the upper Bhagirathi River. Similar findings were also noted for the middle and lower Bhagirathi River. However, the Middle Brahmaputra showed substantial control of hydraulic forces as evidenced by the HSI of about 0.5. In 2010, Lower Brahmaputra and Lower Meghna similarly portrayed a higher control of hydraulic forces on the meandering behaviour of the rivers. However, other stretches of another river are still predominantly controlled by topographic forces (Tables 5.3, 5.4, 5.5, and 5.6). This trend was followed in 2020. It was observed that Lower & Middle Brahmaputra and Lower Meghna registered a higher HSI >0.5 denoting the control by the fluvial hydraulics. Regarding the SSI, the highest figure was recorded for Middle Ganga (Malda-Jalangi) for the years 1990 and 2000; however, Lower Brahmaputra recorded a higher SSI for the years 2010 and 2020 (Tables 5.3, 5.4, 5.5, and 5.6). It is noteworthy that the channel index (CI) and valley index (VI) for the reaches of the different rivers show that all reaches for different observation years (1990, 2000, 2010, 2020) are either sinuous or meandering. For 1990, Bhagirathi Lower, Hooghly Upper, and Lower Meghna having CI and VI> 1.5 indicate a meandering pattern. Similarly, for 2000 Bhagirathi Lower and Hooghly Upper also registered the CI and VI>1.5. The same picture prevails for the years 2010 and 2020 (Tables 5.3, 5.4, 5.5, and 5.6). All other stretches of the rivers depicted an oscillatory pattern of CI and VI over time and space which actually signify the channel dynamicity of the major rivers of the Bengal Basin. It is also notable that CI and VI for different observation years are directly correlated (Fig. 5.3).

5.1

Channel Planform Changes

157

2.4 2.2

y1990 = 1.0335x - 0.0913 R² = 0.9669

1990 2000

2

y2000 = 0.9304x + 0.0503 R² = 0.952

1.8

y2010 = 1.0326x - 0.0726 R² = 0.9773

2010

VI

2020 y2020 = 1.0571x - 0.116 R² = 0.9731

1.6

Linear (1990) Linear (2000)

1.4

Linear (2010) Linear (2020)

1.2 1 1

1.2

1.4

1.6

1.8

2

2.2

2.4

CI

Fig. 5.3 Relation between CI and VI

5.1.2

Stream Meandering and Meander Geometry for the Bhagirathi River

5.1.2.1

Pattern of Meandering

The oscillation and meandering behaviour of the river Bhagirathi within the study area has been assessed with the help of maps and images of different times (Table S5.2) where topographical maps and satellite images are superimposed separately for their differential datum. With these maps and images, channel oscillation is depicted with the help of ArcGIS (v. 10.4) software. It has been depicted from the map that in the year 1927, the length of the channel of the river Bhagirathi in between Katwa and Nabadwip was 78.95 km and sinuosity was 2.13 strongly indicating a meandering channel. However, the 1954 topographical map clearly depicts that the stream length is reduced to 11.2 km making the channel straighter due to stream avulsion in the middle portion of the stretch between Katwa and Nabdwip (Fig. 5.4a). Superimposition of maps at the two different periods (1954 and 1974) depicts a major change in channel alignment than that of the previous superimposition (1927, 1954) (Fig. 5.4b). This may be due to the effect of the Farakka Barrage (Parua, 1992). It is clearly observed that in the year 1974, meander loops have been more accentuated and intensified with increasing sinuosity and channel length. There was a chute cut-off in the lower reach of the channel that dates back to 1989. This is popularly known as the Mayapur-Sankhapur cut-off. It occurred all of a sudden. Since the time of Rennell (1788), the neck distance for this acute meander

158

5

Riverbank Erosion and Channel Morphology

Fig. 5.4 (a–e) Channel oscillation of river Bhagirathi in the lower reach during 1927–2020, (f) Space-time specificity in channel cut-off. (Computed from topographical maps and satellite images)

5.1

Channel Planform Changes

159

was maintained at 5.62 km in 1788 and 2.20 km in 1975 just before the operation of FBP. Due to the construction of the FBP, it got a new hydraulic impulse at a recurrent interval throughout the year and due to the huge monsoon influx in 1989, it rendered huge forces to straighten the channel. Hence actually this cut-off was a chute cut-off triggered by the flood impulse of 1989 (Basu et al. 2005). As a result, a reduced length of 9 km has made the channel more straightened. In the year 1994, another cut-off occurred nearby the Bishnupur Char-Chakundi area reducing channel length by 11.85 km (Fig. 5.4c). Once again, in 2008 the same area experienced another cut-off, called Char Chakundi cut-off- II (Fig. 5.4d), reducing channel length by 3.6 km. Frequent cut-off in the same area proves the channel dynamics reached by hydro-fluvial control and subsurface geology as explained in the following section. Superimposition of river courses (Fig. 5.4e) depicts that channel is shifting in the recent decade (2010–2020), however the rate of oscillation has dwindled after the 30 years of the construction of FBP. Remarkably, there is space-time specificity in the channel cut-off. Spatially, three out of four cut-offs are confined to the lower reach of Bhagirathi (Katwa-Nabadwip) while temporally, all four cut-offs occurred in the post-Farakka period by the supply of discharge of FBP as well as flood impulse (Fig. 5.4f). It is clearly evident that FBP has initiated a new hydrologic regime that has augmented the instability of the Bhagirathi with a new dimension leading to the new regime of flood impulse in the form of cut-off. Apart from the role of the new hydrological regime of FBP, the role of lithofacies cannot be ignored for intense oscillation and meandering on the left side of the Bhagirathi floodplain.

5.1.2.2

Geometry of Stream Meandering

(a) Measuring Meander Geometry Meander geometry includes several important variables viz. radius of curvature, wavelength, amplitude, arc angle, direction angle, channel length, channel width, belt width, channel depth, etc., that give insights into the nature of channel evolution and also hydro-geomorphic dynamism. In a nutshell, an appreciable change in channel geometry definitely indicates channel instability. In the present context, some selected meander geometry parameters are taken into consideration to assess the nature of channel instability. Here chosen variables are analysed with a formula, followed by the collection of data and analysis subsequently. To assess the instability, six basic variables viz. radius of curvature (rc), amplitude (am), wavelength (ˠ), channel length (Cl), arc angle (ɵa), direction angle (ɵd), and four compound units viz. sinuosity index (SI), radius/wavelength ratio (rc/λ), meander shape index (SmI), and meander form index (FmI) are analysed taking 66 loops at different time points within the study area. The radius of curvature (rc) of a curve at a point is measured by the radius of the circular arc which best approximates the curve at that point (Fig. 5.5a). It is calculated as the straight line distance from the arc formed by the mid-channel line

160

5

Riverbank Erosion and Channel Morphology

Fig. 5.5 Morphology of meander geometry. (a) Ideal river meander and morphometric variables. (Williams, 1986); (b) Meander axis and direction angle with the sine-generated curve (Note: am stands for amplitude)

of a meandering reach to the imaginary centre of that arc forming a circle (Das, 2014). A regular meander in the form of a sine curve is easy to measure, but it is difficult for an irregular meander. For the study area, most of the menders are irregular and rc is calculated following the “principle of best fit circular arc”, i.e., arc limit should be up to that point to which the median line of the channel coincides with the arc. Peak amplitude (Am) is the vertical distance between the crest and the trough. River scientists often use this variable simply as amplitude. However, physical scientists use the term “amplitude” (am) to mean half of the peak amplitude (Das, 2014). Wavelength is the distance, over which the shape of the waves repeats (Hecht, 1987). It is usually determined considering the straight line distance between two consecutive crests, or troughs, or zero crossings. It is a characteristic of both traveling waves and standing waves, as well as other spatial wave patterns (Sonin, 1995). The curvilinear distance along the median channel line between two successive points of same the phase, taking a crest, and the subsequent trough denotes the channel length for a meander loop. The channel length is generally considered as the double bend length which is determined as the curvilinear distance along the median channel line between the inflection points of a specific meander loop. Therefore, the channel length (Cl) measures twice the bend length. Arc angle (Fig. 5.5a) is the angle in between lines radiating from the centre of the meandering arc up to the point of deflection point of the meander direction (Das, 2014). The direction angle is the angular distance measured in degrees between the lines of mean down-valley direction and path of the channel (Leopold & Langbein, 1966). The direction angle between the path and the down valley direction represents an imbalance between the slope and volume relation (Fig. 5.5b). The sinuosity index (SI) may be computed using different algorithms. In the present study, SI is computed for the individual meander loop using the methodology of Leopold and Langbein (1966) using Eq. 5.1.

5.1

Channel Planform Changes

161

S:I: =

Channel length Wave length

ð5:1Þ

The radius-wavelength ratio is simply a ratio between the radius of the meander loop (rc) and the wavelength (λ) of that loop. The ratio for a sine-generated curve of a single line is 1:4 (Das, 2014). The meander shape index (SmI) is measured as a ratio between the radius of curvature (rc) and amplitude (am) of a particular meander to indicate the nature of loop tightness. This is computed after Das (2014) using Eq. 5.2. Meander form index (FmI) is measured as a ratio between the amplitude (am) and wavelength (λ) of a meander to denote the intensity of the meandering pattern. This is computed after Das (2014) using Eq. 5.3. Sm I = rc =am

ð5:2Þ

Fm I = am =λ

ð5:3Þ

(b) Data Sources These basic geometric parameters have been used in the present context either directly or in ratio form using some indices. For the present study, meander geometry analysis intends to portray the unstable nature of river meandering with space and time as far as possible. Though the maps of river Bhagirathi with scale were done by Rennell (1788) and later by Tassin (1854), some cartographic constraints like scale and projection systems have limited the previous maps for detailed geometric analysis. As a result, a large-scale map with proper projection was done by the Survey of India in 1927 through topographical maps. This has necessitated us to trace the historical analysis of the meander geometry from 1927 to the present time (2020) for Bhagirathi in between the Ajay-Bhagirathi confluence at Katwa and Jalangi-Bhagirathi confluence at Nabadwip (the most oscillating reach) for six different time periods viz. 1927, 1954, 1974, 1990, 2000, 2010, and 2020. This reach is characterized by numerous meander loops of different magnitudes. Thus, to select the loops for the present study, the sinuosity index (SI) of the individual loop has been computed using Eq. 5.1. Only those loops having SI values greater than 1.10 have been considered for a detailed analysis of meander geometry. Thus, the following loops have been taken into consideration (Table 5.6, Fig. 5.6a, b). (c) Spatial and Temporal Variation in Fundamental Meander Geometry Parameters Taking the concept of the above-mentioned indices, the study reach of the river Bhagirathi is analysed with a view whether FBP has any impact on the spatiotemporal variations of meander geometry. The stretch within the Katwa to Nabdwip is taken into consideration. Different index measures within the study reach show fluctuation in the form of a sine-curve. Such a sine curve is best fitted with higherorder (5th or 6th order). However, by such polynomial curves, it is difficult to assess the trend behaviour.

162

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Riverbank Erosion and Channel Morphology

Fig. 5.6 Location of meander loops. (a) pre-Farakka (1927, 1954, 1974), (b) post-Farakka (1990, 2000, 2010, and 2020) (Note: The maps of different times are intended for locating the meander loops only and these side-by-side locations are not to be confused with shifting analysis. Topographical maps and satellite images treated separately for their different datum)

Therefore, 2nd order polynomial is applied for all the measures to make comparisons between the pre- and post-Farakka episode of meander geometry. Trends obtained through 2nd degree polynomials over different time points are explained to get a distinct idea about the nature of change in the channel geometry. Different

5.1

Channel Planform Changes

163

geometric indices are used to detect the impact of FBP on meander geometry of the river Bhagirathi in pre-Farakka period (1927, 1954 & 1974) and post-Farakka period (1990, 2000, 2010, and 2020) (Fig. 5.6a, b). (i) Radius of Curvature (rc) Considering a sine-generated curve (Fig. 5.5b), the radius of curvature is measured as half of the peak amplitude (Am) and equal to the amplitude (am). It alone does not reveal any qualitative or quantitative measure of the intensity of a meander (Im). Only there is a direct relation between the radius of curvature and the magnitude of channel width. However, if wavelength (λ) is constant, rc becomes smaller, signifying more intense the meander (Leopold & Langbein, 1966). In this study, it has been observed that the radius of curvature ranges from 0.29 to 1.89 km for 77 observed loops across space and time (Table 5.7). The measurements of the radius of curvature (rc) depict that the maximum value is greater than four times the minimum. The mean and median values are 1.07 km and 1.11 km respectively considering the whole distribution, signifying very close to each other. The coefficient of variation is about 40% denoting fluctuation of the radius of curvature. Barring these space-time averaged conditions, there are spatial and temporal variations too in rc. Spatial fluctuation reveals changes in rc of the loops in the downstream direction. For the observed temporal data from 1927 to 2020, there is a spatial oscillation in rc (Fig. 5.7a). A clear-cut spatial oscillation is reflected through rc observing temporal data from 1927 to 2020. Spatial rhythmicity is of common occurrence through time but there is no such linear trend of either increase or decrease observed downstream. Outstandingly, temporal variation is also remarkable where the mean value ranges from 1.02 to 1.12 km during 1927–2020 and C.V. ranges from 26% to 52% for the same period (Table 5.7). In the pre-Farakka period (1927, 1954, and 1974), a greater number of study points have a higher radius of curvature and there was an increasing trend over time as the curve of 1974 is laid above 1927 and 1954 and similarly curve of 1954 is located over 1927 (Fig. 5.7b). R2 values do not significantly support this generalization but the general tendency can be explained in this line of inquiry. However, low R2 values appear as 2nd degree polynomials have been assigned instead of higher-order polynomials. Almost the reverse scenario is found in the post-Farakka episode. Under controlled hydrology, the river is gradually adjusted with the steadystate channel hydrology, limiting the extension of the loops; rather, during high flood time meander loops are gradually cut off and the channel is straightened. This straightening has become more prominent over time as a higher number of study points are showing a lower amount of radius of curvature. For example, only 3 loops had rc < 0.6 km in the pre-Farakka period while 8 loops are now having rc < 0.6 km (Fig. 5.7a, b). Here also, even with the low R2 values, observations of study points over four successive time periods conclusively generalize the straightening of the channel gradually. Therefore, channel stabilization is the experienced reality of recent times.

1927 1954 1974 1990 2000 2010 2020 1927–2020

Radius of curvature Mean (km) SD (km) 1.06 0.39 1.12 0.40 1.10 0.29 1.08 0.37 1.05 0.44 1.02 0.54 1.05 0.55 1.07 0.42

SE (km) 0.11 0.13 0.09 0.11 0.13 0.16 0.17 0.05

CV (%) 36.59 35.34 26.40 34.81 42.42 52.81 52.65 39.33

Amplitude Mean (km) 1.96 1.63 2.02 1.55 1.24 1.22 1.24 1.55 SD (km) 1.17 0.53 0.68 1.00 0.71 0.67 0.66 0.84

Table 5.7 Spatio-temporal variations in radius of curvature, amplitude, and wavelength SE (km) 0.34 0.17 0.22 0.29 0.21 0.20 0.20 0.10

CV (%) 59.68 32.26 33.60 64.11 57.43 55.00 53.38 54.49

Wavelength Mean (km) 4.85 5.04 4.99 4.30 4.25 4.24 4.23 4.54

SD (km) 1.66 1.52 2.00 1.28 1.76 1.88 1.90 1.70

SE (km) 0.48 0.48 0.63 0.37 0.53 0.57 0.57 0.19

CV (%) 34.26 30.16 40.08 29.78 41.40 44.36 44.94 37.35

164 5 Riverbank Erosion and Channel Morphology

5.1

Channel Planform Changes

165

2

y1927 = 0.018x2 - 0.2386x + 1.6341 R² = 0.2642

Radius of curvature (km)

1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2

(a)

0

y1954 = 0.0187x2 - 0.2366x + 1.6997 R² = 0.1867

y1974 = 0.0175x2 - 0.1791x + 1.4118 R² = 0.2339

0

2

4

1927

1954

6 8 Meander loops 1974

Poly. (1927)

10

Poly. (1954)

14

Poly. (1974)

y1990 = 0.0002x2 - 0.023x + 1.213 R² = 0.0372

2 1.8 Radius of cuvature (km)

12

1.6

y2000 = -0.0221x2 + 0.2516x + 0.5536 R² = 0.2209

1.4 1.2 1 0.8 0.6 0.4 0.2 0 0

y2010 = -0.0276x2 + 0.323x + 0.3552 R² = 0.2278

y2020 = -0.0258x2 + 0.2851x + 0.5236 R² = 0.2077

(b) 2

4

6 8 Meander loops

1990

2000

Poly. (1990)

Poly. (2000)

10

12

2010

2020

Poly. (2010)

Poly. (2020)

14

Fig. 5.7 Spatio-temporal variations in radius of curvature during (a) pre-Farakka (1927, 1954, and 1974) and (b) post-Farakka period (1990, 2000, 2010, and 2020)

(ii) Amplitude (am) Amplitude singularly speaks very little about channel instability, but in combination with the other variables, it denotes the nature of channel insatiability. It is predicted that if am increases with constant λ, the intensity of meanders increases and vice versa. Here, amplitude ranges from 0.41 to 4.39 km for 77 observed loops. Noticeably, the maximum value is 10 times greater than the minimum value. The mean and median values are 1.43 km and 1.55 km respectively with CV near about 54% signifying variability of more than 50%. This definitely indicates a lack of consistency over time. This is a space-time average picture of the study. With the minute investigation in respect of space and time, variability of the amplitude becomes more prominent and pattern behaviour of amplitude shows a definite trend, i.e., amplitude decreases downstream. The decreasing trend is more prominent after 1974 (Fig. 5.8a).

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Riverbank Erosion and Channel Morphology

5 y1954 = 0.0322x2 - 0.4102x + 2.6457 R² = 0.3245

4.5

y1927 = -0.0304x2 + 0.3887x + 1.0775 R² = 0.0826

4 Amplitude (km)

3.5 3 2.5 2 1.5 1 0.5

y1974 = 0.048x2 - 0.6373x + 3.68 R² = 0.5279

(a)

0 0

2 1927

4 1954

4

1974

6 8 Meander loops Poly. (1927)

y2010 = -0.0277x2 + 0.2108x + 1.1728 R² = 0.2701

3.5 Amplitude (km)

3

10

14

12

Poly. (1954)

Poly. (1974)

y1990 = 0.0279x2 - 0.5698x + 3.7493 R² = 0.6598 y2000 = 0.0047x2 - 0.1898x + 2.1584 R² = 0.3912

2.5

y2020 = -0.0161x2 + 0.0924x + 1.4251 R² = 0.3049

2 1.5 1 0.5

(b)

0 0 1990

2 2000

4 2010

6 8 Meander loops 2020

Poly. (1990)

Poly. (2000)

10

12 Poly. (2010)

14 Poly. (2020)

Fig. 5.8 Spatio-temporal variations in amplitude during (a) pre-Farakka (1927, 1954, and 1974) and (b) post-Farakka period (1990, 2000, 2010 and 2020)

However, the curve of 1927 shows a radical departure from the others. In 1927, the Bhagirathi River in the middle position of the inter-confluence zone, between Katwa and Nabadwip had a bifurcated channel. At the same time, the dominant channel was highly meandering with higher values of amplitude. Barring this spatial pattern of 1927, a decrease in amplitude especially after 1974 is due to the combined effects of the flood impulse of Ajay and the hydraulic control of FBP. Mean amplitude over time varies from 1.22 to 2.02 km with CV ranging from 32% to 64% (Table 5.7). This is a clear indication of variability over time. This temporal variation is due to variable changes in the meandering pattern and of course, the meander cut-off especially from 1989. The gradual decrease in the mean and SD values of amplitude especially after 1974 denotes the straightening of channels. Figure 5.8a, b depicts the same. Here, 77 study points are plotted with 2nd degree parabola over different time points where the curve of 1927 is showing a different picture than the other. During this time, the number of study points with higher

Wavelength (km)

5.1

Channel Planform Changes

10 9 8 7 6 5 4 3 2 1 0

167

y1974 = 0.0958x2 - 0.8857x + 6.1753 R² = 0.1992

y1954 = 0.032x2 - 0.0895x + 4.3008 R² = 0.2995

y1927 = 0.0476x2 - 0.4844x + 5.423 R² = 0.1847

(a) 0

2 1927

4 1954

6 8 Meander loops Poly. (1927)

1974

10

14

12

Poly. (1954)

Poly. (1974)

8 y2020 = -0.0187x2 + 0.1364x + 4.2733 R² = 0.032

7

y1990 = -0.0078x2 + 0.059x + 4.335 R² = 0.019

Wavelength (km)

6 5 4 3 2 1

(b)

y2000 = -0.0341x2 + 0.3455x + 3.7119 R² = 0.0449

y2010 = -0.0308x2 + 0.3008x + 3.8475 R² = 0.0378

0 0

2

4

6

8

10

12

14

Meander loops 1990

2000

2010

2020

Poly. (1990)

Poly. (2000)

Poly. (2010)

Poly. (2020)

Fig. 5.9 Spatio-temporal variations in wavelength during (a) pre-Farakka (1927, 1954, and 1974) and (b) post-Farakka period (1990, 2000, 2010, and 2020)

amplitude is low. On the other hand, the curves of 1954 and 1974 are dissimilar from the curve of 1927. U-shaped parabola of 1954 and 1974 are showing higher amplitude in number. This trend continued up to 1990. However, appreciably from 2000, the lower amplitudes are more in number (Fig. 5.8b) and continuously it is decreasing afterwards (2000, 2010, 2020). Another notable fact is that the drastic fall of the 1990 curve signifies more study points with low amplitude. Therefore, it can be inferred that under controlled hydrology in post-Farakka episodes, straightening of the channel has led to a lowering of amplitude in most of the study points. At the first stage of the post-Farakka episode, the rate was high as shown by the steep slope of the 1990-curve, thereafter, a steady decline. The impulse of controlled hydrology just after the post-FBP episode exerted huge force in the earlier channel hydraulics for which a new equilibrium was established rendering the straightening of the channel and lowering of amplitude.

168

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(iii) Wavelength (λ) Needless to say, that wavelength is one of the fundamental meander geometry parameters which in association with other variables signifies channel alignment and geometry. Considering the meandering pattern, inconsistent structure in wavelength of different spaces and times is a symptom of variability. In the present study, this wavy pattern is a common feature (Fig. 5.9a, b). Out of 77 observed loops within a span of 93 years, wavelength ranges from 2.11 to 8.93 km. Here, maximum value is four times greater than the minimum value. Mean and median values are 4.54 km and 4.25 km respectively with CV at nearly 37% (Table 5.7). In the study reach, not only does the space-time combination denote variability, but it also shows variability over space and time separately. The variable spatial pattern of wavelength is clearly observed for the years 1954 and 1974. Considering spatial pattern, wavelength maintains a close symmetry for the years 2010 and 2020. Here, the wavelength pattern is just like the stationary waves. Very little spatial variation is observed in these two-time points of the twentieth century indicating the stability of wavelength for the present time. This conclusively denotes that the channel within Katwa and Nabadwip has now attained stability that was lost due to the oscillation triggered by FBP with the regulated flow at a 10-day scale at the initial period of 20–25 years. The graphical representation of wavelength for 77 study points shows almost the same trends as it was observed for the radius of curvature. It is obvious because an increase in amplitude leads to an increase in wavelength and vice versa. Interestingly, during 1927 the channel was relatively straighter than in 1954 and 1974 as evident by the 1927 curve because more study points have a low wavelength (Fig. 5.9a). But this is a misnomer in the sense that high and low values of the study points have forced the 2nd-degree polynomial to run an average trend. In the post-Farakka periods, the wavelength has decreased successively as the right half of the curves of the successive years are placed below the previous year’s trend (Fig. 5.9b). (iv) Channel Length (Cl) The channel length of the river is likely to increase due to channel oscillation. Therefore, variability in channel length over space and time signifies the trend of channel oscillation. The 77 observed points are taken within the period of 1927–2020 where the minimum and maximum values are 3.11 km and 18.26 km respectively (Table 5.8). Of the recoded data, mean and median values are 8.32 km and 8.1 km with a CV of 37%. CV here is an indicator to prove the variability of the channel over space and time. Fluctuation in channel length indicates frequent channel lengthening in some stretches due to meandering and frequent channel shortening in others due to meandering cut-off. This is clearly an indication of unstable fluvial dynamics. It also shows that the range of variation of channel length has decreased over time (highest in 1927 and 1990, 1990 is the post-Farakka period) indicating stabilization of the channel (Fig. 5.10). Besides this spatial pattern, the temporal pattern also shows channel oscillation. The mean channel length is the

1927 1954 1974 1990 2000 2010 2020 1927–2020

Channel length Mean SD (km) (km) 9.96 3.51 9.12 2.06 10.22 2.65 8.20 3.46 7.03 2.78 6.90 2.70 6.85 2.69 8.32 3.08

SE (km) 1.01 0.65 0.84 1.00 0.84 0.81 0.81 0.35

CV (%) 35.22 22.63 25.93 42.25 39.59 39.11 39.25 37.08

Arc angle Mean (Degree) 169.67 151.70 166.50 151.08 161.00 159.82 169.27 161.32 SD (Degree) 24.89 31.27 36.90 49.48 60.26 53.52 59.15 45.70

SE (Degree) 7.19 9.89 11.67 14.28 18.17 16.14 17.83 5.21

Table 5.8 Spatio-temporal variations in channel length, arc angle, and direction angle CV (%) 14.67 20.61 22.16 32.75 37.43 33.49 34.94 28.33

Direction angle Mean SD (Degree) (Degree) 70.58 25.91 69.70 26.00 71.60 20.66 67.50 19.57 68.82 26.05 64.64 26.63 65.18 26.38 68.25 23.74

SE (Degree) 7.48 8.22 6.53 5.65 7.85 8.03 7.96 2.70

CV (%) 36.71 37.30 28.86 28.99 37.85 41.20 40.48 34.78

5.1 Channel Planform Changes 169

170

5

Riverbank Erosion and Channel Morphology

20 y1954 = 0.1258x2 - 1.3222x + 11.555 R² = 0.2257

y1974 = 0.2007x2 - 2.3515x + 15.42 R² = 0.3638

18 Channel length (km)

16 14 12 10 8 6 4 y1927 = -0.0525x2 + 0.6921x + 8.3111 R² = 0.0273

(a)

2 0 0

2 1927

4 1954

6 8 Meander loops 1974

Poly. (1927)

10 Poly. (1954)

12

14

Poly. (1974)

18

Channel length (km)

16

y2000 = -0.0258x2 - 0.2378x + 9.7165 R² = 0.4678

14 12

y1990 = 0.0726x2 - 1.7125x + 15.398 R² = 0.6946 y2010 = -0.0784x2 + 0.4976x + 7.514 R² = 0.3689

10 8 6 4

(b)

2 0 0

y2020 = -0.0836x2 + 0.5819x + 7.2021 R² = 0.3543 2

4

6

8

10

12

14

Meander loops 1990

2000

2010

2020

Poly. (1990)

Poly. (2000)

Poly. (2010)

Poly. (2020)

Fig. 5.10 (a) Spatio-temporal variations in channel length during a. pre-Farakka (1927, 1954, and 1974) and (b) post-Farakka period (1990, 2000, 2010, and 2020)

minimum (of 6.85 km) for the year 2020 while the maximum (of 10.22 km) for the year 1974 clearly shows channel lengthening due to meandering in 1974 and minimum in 2020 by meander cut-off during this period. Barring this space-time-averaged condition, there lies a spatial and temporal variation in the length scenario. Trend behaviour of channel length over different time point observations of the same 77 loops shows dissimilar nature from the pre-Farakka to post-Farakka period. While the pre-Farakka episode is marked by parabolic trends, the post-Farakka episode is denoted by feeble parabolic trends at different time point observations. Under pre-Farakka episode 1927 curve is quite different from 1954 and 1974. More study points from 1954 and 1974 had high channel lengths. Thus, the extension of the loops occurs with the progress of time– a common behaviour of lower reach a river (Fig. 5.10a). But in the post-Farakka episode, more study points are showing low channel length indicating straightening

5.1

Channel Planform Changes

171

250

y1974 = -0.4621x2 + 4.6409x + 158.77 R² = 0.0105

Arc angle (degree)

200

150

100

50 y1954 = 1.2424x2 - 15.467x + 188.93 R² = 0.123

(a)

y1927 = -0.5465x2 + 2.95x + 180.09 R² = 0.4206

0 0

2 1927

4 1954

300

6 8 Meander loops Poly. (1927)

1974

10 Poly. (1954)

y2000 = 0.9068x2 - 19.899x + 238.68 R² = 0.2658

14

Poly. (1974)

y1990 = 1.3144x2 - 18.504x + 200.16 R² = 0.0963

250

Arc angle (degree)

12

200 150 100 50

(b) 0 0

y2020 = -0.2692x2 - 3.4692x + 202.47 R² = 0.1429

y2010 = -1.1247x2 + 8.6874x + 159.43 R² = 0.1267 2

4

6

8

10

12

14

Meander loops 1990

2000

2010

2020

Poly. (1990)

Poly. (2000)

Poly. (2010)

Poly. (2020)

Fig. 5.11 Spatio-temporal variations in arc angle during (a) pre-Farakka (1927, 1954, and 1974) and (b) post-Farakka period (1990, 2000, 2010, and 2020)

of the channel due to the meander cut-off by the flood episode as well as controlled hydrological behaviour. Here, successive straightening is observed over time as the right side of the curve of previous time points is laid over the next time points (the right side of the 1990 curve is lying over the curve of 2000 and similarly the curve of 2000 is lying over 2010 and so on) (Fig. 5.10b). (v) Arc Angle The higher the arc angle greater the probability of meander cut-off. There is a clear variation of arc angle ranging from 65° to 260° as evident from 77 observed loops. Mean and median values are 161° and 164° respectively with CV at 28%. These descriptive statistical figures indicate variation in arc angle. Besides this whole distribution, there are also variations in arc angle both in a spatial and

172

5 Riverbank Erosion and Channel Morphology

temporal framework. The curve for the year 1927 deviates from the curves of 1954 and 1974 (Fig. 5.11). For the temporal average, it has been observed that arc angle values range from 151° for the year 1990 to 170° for the year 1927 (Table 5.8). This shows that in 1990 on average the loops became more open. Here CV value is the maximum (37.43) for the year 2020 and the minimum (14.67) for the year 1927. This variation in space and time indicates more instability before 1990 and a condition of relative stability from the 1990s. The curves of the pre-Farakka period are distinctly different from post-Farakka. The three curves of the pre-Farakka episode have a parabolic shape denoting higher arc angles at some points while lower at the other points. PostFarakka episode on the other hand shows a linear trend reflecting more or less symmetric change of arc angle an indication of straightening of the channel. Interestingly during the pre-Farakka episode, the curves of 1927 and 1954 are positioned in the reverse pattern denoting alternation of arc angle due to meandering (Fig. 5.11a). However, from 1990 onwards the curves are depicting liberality with increasing slope as the successive curves (curve of 2000 and 2020) are running with steeper slopes than the previous one. After the successive meander cut off the 1980s and 1990s, the channel is maintaining a symmetric change of arc angle in the downstream (Fig. 5.11b). (vi) Direction Angle Direction angle portrays channel orientation in respect of mean down valley channel direction. A direction angle below 90° conforms to the down-valley direction; an angle equal to 90° denotes perpendicular channel orientation to the downvalley direction and an angle above 90° denotes the reversal of channel direction (Leopold & Langbein, 1966). For the present study of 77 loops observed within the time span of 1927–2020, the minimum and maximum values recorded are 24° and 121° respectively (Table 5.8). Mean and median values are 68° and 67° respectively with CV at 35%. The above data indicate a frequent change in the direction of the channel in the study area. If a spatial dimension is taken into consideration fluctuation in direction angle is also clear. With distance from Katwa, a clear-cut fluctuation is observed in the direction angle of different loops (Fig. 5.12). For the temporal dimension, fluctuation in direction angle is also common. The mean direction angle ranges from 64.64° in 2010 to 71.60° in 1974. Year-wise variation in the direction angle is observed with the minimum CV of 28.86% found for the year 1974 and a maximum of 41.20% for the year 2010. Bhagirathi taking a sharp bend from the main channel towards the south initially shows a direction angle of more than 90°. Direction angles downstream are less than 90° in most cases with some exceptions for some meander loops. Meander loops were more frequent in 1954 and 1974. Therefore, symmetric variations of direction angle are pronounced by the parabolic curve of 1954 and 1974 (Fig. 5.12a). In the post-Farakka episode, on the other hand, symmetric variations of direction angle is found as all three curves are showing linearity. Gradually, the channel is showing more symmetric variation of direction angle as the trend lines (1990, 2000, 2010, 2020) are successively showing linearity with a steeper slope (Fig. 5.12b).

5.1

Channel Planform Changes

173

140

y1927 = -0.0117x2 - 0.3684x + 73.614 R² = 0.0053

Directiona angle (degree)

120 100 80 60 40 20

(a)

y1954 = -0.8902x2 + 4.8644x + 77.217 R² = 0.3981

0 0

2 1927

4 1954

1974

y1974 = 0.4811x2 - 6.625x + 89.517 R² = 0.07

6 8 Meander loops

10

Poly. (1927)

Poly. (1954)

12

14

Poly. (1974)

140 y2010 = 0.0455x2 - 5.4091x + 96.455 R² = 0.3571 y2020 = -0.141x2 - 2.8622x + 90.388 R² = 0.3146

Direction angle (degree)

120 100 80 60 40 20

(b)

y2000 = 0.1072x2 - 5.5776x + 98.17 R² = 0.2958

y1990 = 0.0749x2 - 2.7153x + 81.091 R² = 0.1047

0 0

2

4

1990

2000

Poly. (1990)

Poly. (2000)

6 8 Meander loops 2010 Poly. (2010)

10

12

14

2020 Poly. (2020)

Fig. 5.12 Spatio-temporal variations in direction angle during (a) pre-Farakka (1927, 1954, and 1974) and (b) post-Farakka period (1990, 2000, 2010, and 2020)

(d) Spatial and Temporal Variation in Ratio Parameters of Meander Geometry (i) Sinuosity Index Geomorphologists have advocated several classification schemes of the alluvial channel based on the sinuosity index and channel instability. Most notable works are contributed by Leopold and Wolman (1957), Schumm (1963), Mueller (1968), Miall (1978), Rust (1978), and Ferguson and Werrity (1983). The foregoing analysis adopts the scheme of Miall (1978). In this scheme of classification sinuous, meandering, braided, and anastomosing are defined using the threshold values of

174

5

Riverbank Erosion and Channel Morphology

7

6

Sinuosity index

5

4

3

2

1

0 0

10

20

30 40 50 Meander loops (1927-2020)

60

70

80

Fig. 5.13 Spatio-temporal variation in sinuosity index (Note: green line indicates the peak points while red line shows the average sinuosity index in the pre-Farakka period from 1927 to 1974 (first 32 meander loops on x-axis) and post-Farakka from 1990 to 2020 (33–77 loops) period)

the SI: (1) Sinuous > 1.05, (2) Meandering > 1.5, (3) Braided > 1.3, and (4) Anastomosing > 2.0. Of the 77 observed loops, the maximum value of sinuosity index (6.12) was recorded for Loop R1 in 1990. The study shows mean and median values as 2.05 and 1.66 respectively with a CV of 56% signifying a higher spatio-temporal fluctuation in-stream meandering (Fig. 5.13). The studied loops have SI > 1.10 confirming the sinuous river course. More than 57% of loops have SI > 1.5 showing the meandering nature of most of the loops. However, temporal fluctuation in SI is notable for the present study. The period 2000–2020 shows the mean minimum SI (1.86) while the year 1974 depicts the maximum (2.35) denoting wider meandering after FBP and low meandering (stabilized channel) at present (2020). Thus, a rise-fall in SI is notable in SI from 1927 to 2020 with the CV ranging from a minimum of 47.22% in 1927 to a maximum of 68.78% in 1990 (Table 5.9). Gradual rise and fall in SI indicate frequent channel lengthening by meandering and shortening by meander cut-off. So, analysis of SI is to some extent different from other geometry as there is a wider lacking in the gradual change of SI over the period of time due to major cut-offs between 1989 and 2008 induced by flood impulse for which sinuosity has drastically changed. It is clear from Fig. 5.13 that the Farakka barrage episode has clearly altered the increasing trend into a decreasing one. The average SI was high before 1990. Meander cut-off for three times within a decade of the 1990s lowered the value of SI. Most of the acute meanders are now existing as oxbow lakes. Therefore, FBP cannot solely be considered as the reason for decreasing SI, rather flood phenomena with high discharge are more responsible.

5.1

Channel Planform Changes

175

Table 5.9 Spatio-temporal variation in sinuosity index

Year

Number of loops in different Sinuosity categories SI (1.10–1.50) SI (1.51–2.00) SI ( > 2.00) Total

Average and deviation in Sinuosity Mean SD SE CV (%)

1927 1954 1974 1990 2000 2010 2020 Total

4 3 1 6 6 6 7 33 (42.85)

2.27 1.98 2.35 2.15 1.86 1.86 1.86 2.05

3 5 6 3 1 2 1 21 (27.27)

5 2 3 3 4 3 3 23 (29.87)

12 10 10 12 11 11 11 77 (100)

1.07 0.95 1.28 1.48 0.97 1.21 1.18 1.15

0.31 0.30 0.41 0.43 0.29 0.37 0.36 0.13

47.22 47.85 54.68 68.78 52.06 65.15 63.69 56.17

Source: Islam & Guchhait (2017) (N.B within parentheses figures indicate the percentage of the total)

(ii) Radius/Wavelength Ratio (rc/λ) The nature and the magnitude of meander geometry can be understood in terms of the radius-wavelength ratio. The sine-generated curve confers a value of 1:4 (Williams, 1986). This ratio measures the intensity of a meander. The greater the ratio, the more intense the meander when other variables remain constant. However, the relationship between rc/λ changes with variation in amplitude (am) (Das, 2014). These relationships are mentioned as: (1) (rc/λ) = 1/4, if meander is regular (where am = rc), (2(rc/λ) = 1/4, if meander is intense (where am = 2rc), (3) (rc/λ) = 1, if meander is more intense towards neck cut-off (where am > 2rc), and (4) (rc/λ) = 1/ 4, if meander is open (where am < rc). The empirical observations from the field for 77 observed loops indicate that the lowest and the highest rc/λ are 0.09 and 0.64 respectively with an average of 0.25 which exactly coincides with the ratio for a perfect sine-generated curve. However, this space-time average condition largely varies spatially and temporally (e.g., 0.23 in the year 1927 to 0.27 in 2000 (Table 5.10). About 45% of the loops are falling above rc/λ ratio of 0.25 (Fig. 5.14). The average CV over time is 44% varying from a temporal minimum of 38% in 1927 and a temporal maximum of 57% in 2010. These fluctuations about the mean and the ideal value of 0.25 imply channel dynamics where the highest value of the sine curve is recorded after 1974, denoting a new instability induced by the altered hydrologic regime of the FBP (iii) Meander Shape Index The meander shape index (ratio between radius and amplitude) is used here to reveal the spatio-temporal dynamics of the meander shape. After Das (2014), the intensity of a meander is detected using the thresholds of the index as: (1) SmI > 1 for wide meander, (2) SmI = 1 for open meander, (3) SmI = 0.5 for regular meander, and (4) SmI = 1 signifying

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177

Table 5.11 Temporal variation in meander shape index Number of loops in different SmI categories SmI (< 0.5) SmI (0.5–1.0) SmI (> 1) 3 6 3 2 4 4 3 6 1 2 6 4 3 4 4 3 5 3 3 5 3 19 (24.67) 35 (45.45) 23 (29.87)

Year 1927 1954 1974 1990 2000 2010 2020 Total

Total 12 10 10 12 11 11 11 77 (100)

Average and deviation in SmI Mean SD SE CV (%) 0.69 0.36 0.10 52.92 0.74 0.30 0.10 40.90 0.60 0.29 0.09 47.75 1.02 0.83 0.24 81.94 1.19 0.96 0.29 81.15 1.13 0.99 0.30 87.58 1.10 0.90 0.27 81.59 0.93 0.74 0.08 79.75

N.B within parentheses figures indicate the percentage of the total (Computed from topographical maps and satellite images) 3.5 3

Meander shape index

2.5 2 1.5 1 0.5 0 0

10

20

30 40 50 Meander loops (1927-2020)

60

70

80

Fig. 5.15 Spatio-temporal variation in meander shape index (Note: red line shows the average meander shape index in the pre-Farakka and post-Farakka period)

the acuteness in the meandering behaviour. However, maximum openness in the loop character was observed in 2000 (Table 5.11). Moreover, the minimum value (0.60) was recorded in 1974 while the maximum (1.19) in 2000. Similarly, the maximum CV (88%) is recorded in 2010 while the minimum (41%) was in 1954. Therefore, hydraulic input through FBP has modified the majority of the loops from intense to open. Joining the highest peak value of SmI (Fig. 5.15) relationship is more strongly established between pre-Farakka (before 1974) and post-Farakka (after 1974) periods. Before 1974, SmI < 1.5 signifies intense meandering while after 1974 SmI > 2.0 for most of the peak values, signifying openness of meandering. Therefore, extra discharge contributed by the FBP at a regular interval has induced the meanders to become more open.

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The number of loops over time is almost the same within the study area but the shape of the meander is gradually becoming open over time. The mean values have a steady increase over time (Table 5.11) with the exception of 1974. This clearly prompts openness of meander over time. However, the striking point in this river is the significant change in the SmI value in the post-Farakka episode (1974) where the mean SmI changed more than 1.5 times from 1974 to 1990. This is also conspicuous by Fig. 5.15 where low SmI and high SmI are separated by a break of slope in the figure. SD values of SmI over different time periods have registered an increasing trend denoting fluctuation of SmI values with the increasing mean value. Therefore, it may generalize that acute meanders of earlier were more symmetric while meanders in the later phases are showing variability, i.e., in some portions it is acute while in some other portions, it is open. (iv) Meander Form Index Meander Shape Index (rc/am) quantifies meander intensity by assessing the degree of curvature in relation to the meander’s size, focusing on transverse deviation from the mean channel axis. On the other hand, the Meander Form Index (am/wavelength) gauges meander intensity by examining the amplitude of transverse deviation relative to the meander wavelength, emphasizing the relationship between deviation magnitude and longitudinal distance. Thus, the meander form index is a good measure for assessing the intensity or tightness of the meander loop by the ratio of amplitude and wavelength that helps us to decide about the meander cut-off. Das (2014) defined meander intensity as: (1) (am/λ) = 1/4, if meander is regular (where am = rc), (2) (am/λ) = 1/2, if meander is intense (where am = 2rc), (3) (am/λ) ≥ 1, if meander is more intense towards neck cut-off (where am ≥ 2rc), and (4) (am/λ) ≤ 1/4, if meander is open (where am < rc). Here, the mean value of SmI for 77 observed loops is 0.41 implying a tendency towards intense meander. The study also finds a high deviation (CV 77%) in the whole distribution. Furthermore, it is noted that the first three temporal sets of observations (1927, 1954, and 1974) show a higher fluctuation (Table 5.12). Table 5.12 Temporal variation in meander form index

Year 1927 1954 1974 1990 2000 2010 2020 Total

Number of loops in different FmI categories FmI FmI (1) Total 3 8 1 12 3 6 1 10 1 8 1 10 5 6 1 12 5 5 1 11 5 5 1 11 5 5 1 11 27 (35.06) 43 (55.54) 7 (9.09) 77 (100)

Average and deviation in FmI Mean 0.46 0.38 0.48 0.43 0.37 0.38 0.39 0.41

SD 0.33 0.29 0.32 0.38 0.31 0.34 0.34 0.32

SE 0.09 0.09 0.10 0.11 0.09 0.10 0.10 0.04

CV (%) 71.46 77.01 66.24 88.84 83.10 88.35 85.68 77.46

N.B within parentheses figures indicate the percentage of the total (Computed from topographical maps and satellite images)

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179

1.5

1.25

Meander form index

1

0.75

0.5

0.25

0 0

10

20

30 40 50 Meander loops (1927-2020)

60

70

80

Fig. 5.16 Spatio-temporal variation in mender form index (Note: red line shows the average meander form index in the pre-Farakka and post-Farakka period)

After 1974 fluctuation has been minimized compared to the previous episodes because of the controlled river regime of the FBP operationalized in 1975. The study also shows high temporal variations for the average value of FmI ranging from 0.37 (2000) to 0.48 (1974) (Table 5.12). Moreover, CV ranges from 66% (1974) to 89% (1990), implying a more regular meandering before 1974. This is a symptom of alteration of natural hydrology after FBP while irregular meandering after 1974 is induced by the FBP (Fig. 5.16). The river is now adjusted with the regulated flow controlled by FBP but the monsoon peak discharge of Ajay and Mayurakshi overtakes the regulated flow leading to a meander cut-off. But regulated flow for most of the year favours open meander while flood impulse favour meander cut off. The meander cut-off is not contributed by FBP. However, by several cut-offs due to flood impulse, the rest of the meanders appear as open menders, therefore the mean value is decreased. A firm exponential relation is established in Fig. 5.17 where the threshold value of the meander form index is 0.242 with an exponent value of -0.845. An exponent value close to ±1 is a stringent value, depicting stronger relation between x and y variables. Here, the meander form index is drastically decreased with an increase of the meander shape index value and R2 is highly satisfactory which is significant at a 95% level. This is quite obvious according to the normal rule of channel morphology which is established for the Bhagirathi River. Interestingly, such a relation has been intensified due to the FBP in which regulated flow has somehow obstructed the intensification of meandering and thereby forms of meander have become open

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1.5

Meander form index

1.25

1

y = 0.2421x-0.845 R² = 0.4387

0.75

0.5

0.25

0 0

0.5

1

1.5 2 Meander shape index

2.5

3

3.5

Fig. 5.17 Relation between meander shape index and meander form index (1927–2020)

afterwards. Such a generalized statement may not be conclusively be said as the direct impact of the FBP, however the role of the FBP cannot be ignored. The analysis contained in this section clearly depicts the channel behaviour over space and time where FBP is a critical point of turn. In the post-Farakka period, erosion and channel, cut-offs have straightened the channel on one hand and tend to form new meander loops as well as making some of the loops with the abolition of the acute meander. The post-FBP episode has established a new hydrological equilibrium. After the meander cut-off, the new channel under-regulated flow for lean months of the year (January to May) does not encourage so much to form acute meanders as before. It can be rigidly claimed that changes in the FmI and SmI are not the direct effect of the FBP but the regulated hydrology has some indirect effect for which FmI and SmI have changed especially after the 1990s.

5.1.3

Channel Braiding in the Bengal Basin

5.1.3.1

General Nature of Braiding Indices

Channel braiding is a response to the sediment-energy nexus of the fluvial system and is directly related to riverbank erosion in few ways. For example, riverbank erosion contributes to the sediment load of the river which gets deposited on the riverbed and initiates channel braiding when a river cannot carry its load due to either dissipation of stream energy relative to stream load (Ashworth & Ferguson, 1986; Ashmore, 1991; Ashworth, 1996). Moreover, the mid-channel bar amidst the river course also exerts pressure on the riverbank erosion (Islam & Guchhait, 2021). In the context of the Bengal Delta, channel braiding is one of the most prominent traits of

5.1

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181

large fluvial systems. To detect the changes like channel braiding, a temporal study (1990, 2000, 2010, and 2020) was executed over the major rivers: Ganga, Bhagirathi, Hooghly, Brahmaputra, and Meghna. The satellite images used in this study are mentioned in Table S5.1. The collected data was processed using the most widely used methodology of Brice (1964) for BI and Hong Davies (1979) for Pt using Eqs. 5.4 and 5.5. BI = 2ΣLb =Lr

ð5:4Þ

Pt = ΣLL =Lr

ð5:5Þ

where BI is the braiding index; Pt is the channel length index; Lb is the length of islands and (or) bars, Lr is the reach length, and LL is the length of the links or river channels. The pattern of channel braiding in the Bengal basin is really fascinating. The upper Ganga River (Dilarpur – Godagari) shows a fluctuating trend of the BI from 5.07 (1990) to 3.82 (2020). The trend of middle Ganga (Godagari – Ambaria) depicts a gradual decrease in the BI from 4.36 (1990) to 3.71 (2010). However, an increase has been observed in 2020 (Table 5.14). However, the lower part of the Ganga (Ambaria – Chandpur) shows a truly declining trend of the BI from 5.69 (1990) to 4.43 (2020). Like the Ganga River, the Bhagirathi River also portrays a similar picture of the braiding, i.e., the lower reach shows a higher tendency of braiding. However, the upper, middle, and lower reaches portray an escalation in the BI for the year 2000 compared to the other years like 1990, 2010, and 2020 (Table 5.13). On average, the upper Bhagirathi (Farakka – Berhampur) registers a Table 5.13 Braiding index (BI) of the different rivers of Bengal Basin after Brice (1964) River stretch Ganga (Dilarpur – Godagari) Ganga (Godagari – Ambaria) Ganga (Ambaria – Chandpur) Bhagirathi (Farakka – Berhampur) Bhagirathi (Berhampur – Katwa) Bhagirathi (Katwa – Mrijapur) Hooghly (Mrijapur – Sankrail) Hooghly (Sankrail – Gangasagar) Brahmputra (Pakuria – Bahuka) Brahmputra (Bahuka – Sonatani) Bramputra (Sonatani – Daulatdia) Meghna (Parmanandapur – Sonargaon) Meghna (Sonargaon – Goal Bhaor) Meghna (Goal Bhaor – Hatia) Average SD CV (%)

1990 5.07 4.36 5.69 0.10 0.52 1.17 0.73 0.82 8.90 7.81 7.04 0.68 1.64 3.56 3.43 3.04 88.58

2000 4.39 4.07 4.66 0.23 0.68 1.48 1.13 0.70 8.11 8.82 8.22 0.62 1.68 3.33 3.44 3.06 89.19

2010 5.35 3.71 4.57 0.06 0.24 1.14 0.91 0.70 9.00 5.40 7.77 0.56 2.53 5.02 3.35 2.92 87.09

2020 3.82 3.25 4.43 0.13 0.41 1.17 0.47 0.74 7.21 5.70 7.07 0.57 1.70 4.37 2.93 2.53 86.45

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Table 5.14 Braiding index (Pt) of the different rivers of Bengal Basin after Hong and Davies (1979) River stretch Ganga (Dilarpur – Godagari) Ganga (Godagari – Ambaria) Ganga (Ambaria – Chandpur) Bhagirathi (Farakka – Berhampur) Bhagirathi (Berhampur – Katwa) Bhagirathi (Katwa – Mrijapur) Hooghly (Mrijapur – Sankrail) Hooghly (Sankrail – Gangasagar) Brahmputra (Pakuria – Bahuka) Brahmputra (Bahuka – Sonatani) Bramputra (Sonatani – Daulatdia) Meghna (Parmanandapur – Sonargaon) Meghna (Sonargaon – Goal Bhaor) Meghna (Goal Bhaor – Hatia) Average SD CV (%)

1990 3.73 2.61 4.06 1.05 1.16 1.42 1.17 2.32 4.77 7.21 7.43 1.25 2.67 8.10 3.50 2.61 74.54

2000 3.30 2.74 3.06 1.01 1.13 1.31 1.22 1.71 6.11 7.02 5.78 1.23 2.45 4.83 3.06 2.15 70.18

2010 3.85 2.13 3.49 1.04 1.13 1.38 1.72 1.69 6.90 4.47 7.40 1.23 3.60 6.59 3.33 2.35 70.61

2020 2.74 2.20 3.70 1.04 1.22 1.31 1.31 1.50 6.46 5.72 6.47 1.06 2.81 5.88 3.10 2.22 71.72

braiding around 0.1 while the middle Bhagirathi (Berhampur – Katwa) shows BI around 0.5. However, the lower part of the Bhagirathi (Katwa – Mrijapur) registers a relatively higher BI (1.15). Besides, the river Hooghly also shows that the upper part (Mrijapur – Sankrail) depicts a relatively less braiding tendency (0.4–1.13) while the lower part (Sankrail – Gangasagar) oscillates around 0.7 (2000) to 0.82 (1990). In the Bengal Delta, the most braiding river is the Brahmaputra, one of the finest examples of a braided river in the world. All three reaches of the Brahmaputra show high-level braiding, however, the upper reach (Pakuria – Bahuka) in contrast to the other rivers in the study region shows a relatively higher BI ranging from 9 (2010) to 7.21 (2020) while the middle reach (Bahuka – Sonatani) and the tail reach (Sonatani – Daulatdia) depict a relatively low braiding ranging from 5.40 to 8.82 (Table 5.13). Furthermore, the river Meghna also shows that the lower stretch of Meghna (Goal Bhaor – Hatia) has a relatively higher BI (3.33–5.02) compared to the upper (Parmanandapur – Sonargaon) and the middle stretch (Parmanandapur – Sonargaon). A similar picture of the braiding was recorded for the rivers under consideration using the method of Hong and Davies (1979) (Table 5.14).

5.1.3.2

Case Studies from Bengal Basin

A few case studies from the braiding channels have been showcased to depict the nature of the dynamics of the bar growth over time (1990–2020). For this purpose, a few bars from the two most braiding rivers (Ganga and Brahmaputra) are selected.

5.1

Channel Planform Changes

183

Fig. 5.18 Morphological dynamics of channel bars of Bhagirathi-Hooghly River, India during 1990–2020, (a) Char Balidanga, Bhagirathi River, (b) Rukunpur char, Bhagirathi River, (c) Chak Bholadanga, Hooghly River, (d) Gournaganar Char, Hooghly River

The present investigation regarding the development of channel bars (chars) has been explored with reference to 12 chars selected randomly across the major rivers of the GBM delta (Figs. 5.18, 5.19, and 5.20). Two chars, considering the location (upper and lower) along with their size (larger ones are prioritized), have been selected from each of the six major rivers of the GBM delta, i.e., Bhagirathi River, India; Hooghly River, India; Ganga-Padma, India-Bangladesh; Padma, Bangladesh; Meghna, Bangladesh; Brahmaputra, Bangladesh. The development of chars has been tracked through the areal expansion and contraction of these selected bars. For the year 1990 average char area was found to be 203.67 km2. The average char area increased in 2010 (228.05 km2). In 2020 a significant fall in char area (206.86 km2) was noted. This temporal oscillation of the chars indicates the dynamic

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Fig. 5.19 Morphological dynamics of channel bars of Ganga-Padma River during 1990–2020, (a) Rostampur Char, Ganga River, India. (b) Radhakantapur Char, Ganga River, Bangladesh, (c) Char Bhabananda Diar, Padma River, Bangladesh, (d) North Char Janajat, Padma River, Bangladesh

nature of the fluvial hydraulics sedimentology and anthropogenic influx. When char specific outlook was embraced a more detailed picture sparks before us, e.g., Bhagirathi1 char (Char Baliadanga) has an average area of 0.57 km2 with a fluctuation from 0.35 km2 in 2010 to 0.90 km2, in 2000 with a CV of around 42%. Similarly, the other char of Bhagirathi and Hooghly Rivers also portray small areas of expansion (around 1 km2) with a CV ranging from 15% to 68% (Table 5.15). Besides, the areal expansion for the other rivers (Ganga, Padma, Meghna, and Brahmaputra) covers a large area. Char Bhabananda Diar for Padma Rivers covers an area of 258 km2. Similarly, the char of the Ganga River ranges from 262 to 395 km2. Moreover, Meghna also portrays a similar picture but the highest

5.1

Channel Planform Changes

185

Fig. 5.20 Morphological dynamics of channel bars of Brahmaputra and Meghna Rivers in Bangladesh during 1990–2020, (a) Nischintapur Char, Brahmaputra River, (b) Char Kodalia, Brahmaputra River, Bangladesh, (c) Charmodhu, Meghna River, (d) Kalitola Char, Meghna River

expansion of char is found for the Brahmaputra River, e.g., Brahmaputra 1 and Brahmaputra 2 cover an area of 490 and 445 km2 respectively. One very interesting thing is that the chars of Bhagirathi Hooghly are unstable which is reflected in their higher CV. However, the chars of the other major rivers are relatively stable island types with lower CV ranging from 1% to 20% only. Although the char area remains almost stationary from one year to another. The internal reorientation of the char area within the valley is noticeable for the river Brahmaputra. The temporal variation in size can easily be explained following the riverine dynamics of the respective rivers. It is found that bank erosion highly promotes char

Sl. No. 1 2 3 4 5 6 7 8 9 10 11 12 Average SD CV (%)

Char (River, Location) Bhagirathi 1 Bhagirathi 2 Hooghly 1 Hooghly 2 Ganga (upper) Ganga (lower) Padma 1 Padma 2 Meghna 1 Meghna 2 Brahmputra 1 Brahmputra 2

Name of the char Char Balidanga Char Rukunpur Char Gournagar Chak Bholadanga Rostampur Char Radhakantapur Char Char Bhabananda Diar North Char Janajat Kalitola Char Charmodhu Nischintapur Char Char Kodalia

1990 0.47 0.29 4.13 0.42 255.64 454.20 215.06 225.90 245.00 171.65 484.58 386.65 203.67 177.10 86.95

2000 0.90 0.38 4.96 0.55 257.03 454.73 256.53 344.46 241.94 172.32 525.55 480.40 228.31 197.03 86.30

Table 5.15 Growth of char area (km2) at selected places of the Major Rivers of the Bengal Delta 2010 0.35 0.79 5.46 0.40 269.79 408.60 284.67 424.73 242.27 172.20 487.63 439.73 228.05 189.88 83.26

2020 0.56 1.32 5.84 0.64 267.96 265.37 275.04 313.45 243.36 172.43 461.69 474.70 206.86 173.23 83.74

Average 0.57 0.69 5.10 0.50 262.61 395.73 257.83 327.14 243.14 172.15 489.86 445.37

SD 0.24 0.47 0.74 0.11 7.30 89.55 30.81 82.18 1.38 0.35 26.46 43.08

CV 41.44 67.49 14.49 22.47 2.78 22.63 11.95 25.12 0.57 0.20 5.40 9.67

186 5 Riverbank Erosion and Channel Morphology

5.1

Channel Planform Changes

187

development in the middle and lower course of a large river. The materials needed for the development of char not only come through bank erosion, but it is also an outcome of deposition of load with the decrease of velocity of river and also channel bed configuration, the curvature of thalweg and riverside slopes (Ashworth, 1996; Knighton, 2014). However, the middle or lower course of a river if it is meandering or braided (braiding normally occurs at the last segment of the lower course or due to the drastic fall of slope at the foothills) (Islam & Das, 2015; Jiongxin, 1997). From the earlier discussion, it is clear that under GBM delta, the charland in terms of the size, erosion, and accretion and also shifting behaviour, the rivers act differently. The upper part of the Meghna is now sluggish and therefore discharge and load are not so much effective for the char development. Therefore, stable chars are likely to be found. For Padma, the carried load throughout the long course of Ganga and Brahmaputra is likely to promote accretion. This accretion once again accelerates bank erosion that subsequently leads to further accretion of charland downstream. For the Brahmaputra, its relatively high channel gradient with moderate velocity will logically erode the charland in the peak period while accretion in the lean period (Alam et al., 2022; Kleinhans & Berg, 2011). Therefore, the presence of erosion and accretion leads to little change of char area but erosion at one point and accretion at another. Bhagirathi on the other hand for its regulated timescale hydrology neither promotes erosion nor accretion. Therefore, char areas though small are almost static in size with some little shifting. For the chars of Ganga, the upper and lower part depicts contrasting scenario. The local base level set by the barrage promotes settling for the upper part while the barrage disallows water and erosion. It is also true for the post-barrage site. Therefore, erosion-accretion depends on controlled hydrology but the high rate of flow in post barrage site will likely erode charland and relatively more accretion in the pre-barrage site. The temporal size variation of the studied char of the different rivers under the GBM delta shows a diversified picture. The study considers the time length of 30 years starting from 1990 up to 2020 at an interval of 10 years. The average size is very low for Bhagirathi and Hooghly (less than 6 km2) while it is high for high enough for Ganga, Padma, Meghna, and Brahmaputra (more than 200 km2). The very small size of Bhagirathi and Hooghly can be explained as the reach is controlled by regulated hydrology and the geometry of branching depicting sharp bend from the mainstream with an obtuse angle (Basu et al., 2005). Basically, the Mayurakshi and Ajay contribute sediment load which is deposited at the confluence zone, and slightly downstream. Materials for char development also come from bank erosion to some extent. SD for such charland is lowest among the study points, indicating a stable size over time. The size of the Char of Meghna is large with low SD, indicating stable size over time. The pre-barrage site of Ganga increases in size over time and is very slow indicating a relatively stable size, configured by low SD (7.30). For the post-barrage site, it shows a decreasing tendency due to erosion owing to the high velocity of water while the barrage gates are opened. Chars of Padma are showing a steady increase due to the deposition of materials coming through Ganga, Tista, and Brahmaputra. Chars of Brahmaputra show an increase and decrease sequence, and thereby SD is moderate.

188

5.2

5

Riverbank Erosion and Channel Morphology

Channel Cross-sectional Changes

The channel cross-sectional changes correlate the minute changes in the microvariation in the cross-sectional parameters. Cross-sectional changes have been depicted here in terms of channel geometry and cross-sectional asymmetry.

5.2.1

Channel Geometry

Channel geometry explains the nature of lateral and vertical erosion of the river. Here, the width-depth ratio (Schumm, 1960), width index, and depth index (Das, 2015) have been analysed with a detailed database to portray pre-Farakka (1972) and post-Farakka (1984) conditions of channel width and channel depth. Regarding channel width-depth analysis and channel asymmetry, 39 altogether cross-sections have been investigated (Fig. 5.21).

Fig. 5.21 Location of cross-section on the Bhagirathi River (Source: Hydrographic sheets, KoPT, 1972). (Note CS 249 denotes the first cross-section (Sl. No. 1) and CS 364 denotes the terminal cross-section of this study (Sl. No. 39))

5.2

Channel Cross-sectional Changes

5.2.1.1

189

Width-Depth Ratio

Width-depth ratio is generally considered as a balance against the discharge of a river at a point. Therefore, if the depth is high, the width of the river will be low to adjust the volume and vice versa. This ratio can clearly explain hydro-geomorphic adjustment to the channel in respect of fluvial dynamics, channel configuration, and composition of the bed and bank (Charlton, 2008; Das, 2015). The diagrammatic representation of the 39 cross-sections of the Bhagirathi River in the pre-Farakka and post-Farakka stages shows a significant difference. Most of the cross-sections have recorded an increase in the value of the width/depth ratio (Fig. 5.22) in the postFarakka condition. An increase in discharge induces an increase in active channel width (Kolberg & Howard, 1995). It ascertains that after inducing water by the Feeder canal in the Bhagirathi lateral erosion has been exacerbated whereas vertical erosion has not increased proportionately due to a lower channel gradient. However, the increase in the width-depth ratio for all 39 cross-sections has not been proportional to the differences in the lithologic composition of the bank and the bed materials that strongly control the degree of correlation between the discharge and channel width (Schumm, 1960; Miller & Onesti, 1979; Howard, 1980; Nanson & Hickin, 1986). All the selected cross-sections between 249 and 261, located immediately below Katwa, show a very high positive deviation in channel width during 1972–1984 due to the contribution of Ajay, while beyond cross-section (CS) 261, nearly 60% of cross-sections between 261 and 364 have shown a high to moderate positive deviation in active channel width that clearly indicates a general trend of increase in width/depth ratio in the post-Farakka period. The regulated river regime is the root of such change in the post-Farakka period but Ajay has a critical role in this scenario.

250

y1993 = 3E-07x5 - 0.0002x4 + 0.0197x3 - 0.5808x2 + 2.0651x + 122 R² = 0.4148 y1984 = 2E-06x5 - 0.0004x4 + 0.0263x3 - 0.6941x2 + 3.8767x + 119.92 R² = 0.1972

Width/Depth Ratio

200

y1972 = 2E-06x5 - 0.0003x4 + 0.0231x3 - 0.5989x2 + 4.2249x + 81.722 R² = 0.1389

1972

150

1984 1993

100

Decrease

Increase

Poly. (1972) Poly. (1984)

50 Poly. (1993) 0 0

10

20

30 40 50 Distance from Katwa (km)

60

70

80

Fig. 5.22 Spatio-temporal variation in width-depth ratio indicating a decreasing trend in the middle of the study stretch and increasing trend at the lower and the upper end of the distance

190

5

5.2.1.2

Riverbank Erosion and Channel Morphology

Width Index

The width index is the simple ratio between observed width (w) and expected width (w′) (Das, 2014). It can be formulated in Eq. 5.6. Iw =

w w p = w0 1:595 A

ð5:6Þ

where A denotes the cross-sectional area of the channel. In the lower course of a river, the width index is very significant in assessing the efficiency of a channel shape as it compares the ideal width or expected width for the most efficient channel with respect to the actual width. When the value of Iw becomes exactly one, the channel is perfectly efficient and a value greater than or less than the ideal value denotes an inefficient channel (Das, 2015). In the postFarakka period all the selected cross sections between 249 and 261 have virtually recorded an increase in width with a high positive deviation for the contribution of Ajay while for the remaining cross sections between 261 and 364, nearly 65% cross sections have registered an increase in width index for lateral movement of the channel by bank erosion in the post-Farakka period (Fig. 5.23). The waning tendency of expected width for Bhagirathi may be due to a sudden increase of discharge and the presence of a wider unconfined channel with negligible slope and non-cohesive substrate as well as a lack of riparian vegetation (Charlton, 2008; Das, 2015). This indicates the occurrence of bank erosion of a higher magnitude immediately after the post-Farakka situation, which is continuing with a lower magnitude. The width Index has a positive correlation with the width-depth ratio. The difference in w/d ratio between 1972 and 1984 and the difference in width index between 1972 and 1984 shows a strong positive correlation (Fig. 5.23) which is 10 y1993 = -3E-08x5 - 8E-07x4 + 0.0003x3 - 0.0124x2 + 0.0038x + 6.9949 R² = 0.3868

8

1972

Increase Width Index

1984 6

Decrease

Increase

1993 Poly. (1972)

4

Poly. (1984) Poly. (1993) y1984 = 5E-08x5 - 1E-05x4 + 0.0008x3 - 0.0201x2 + 0.086x + 6.8766 R² = 0.2064

2

y1972 = 6E-08x5 - 1E-05x4 + 0.0008x3 - 0.0215x2 + 0.1418x + 5.6475 R² = 0.1695

0 0

10

20

30 40 50 Distance from Katwa (km)

60

70

80

Fig. 5.23 Spatio-temporal variation in width index indicating a decreasing trend in the middle of the study stretch and an increasing trend at the lower and the upper end of the distance

5.2

Channel Cross-sectional Changes

191

significant at the 99% level. This difference in width index for the pre-Farakka and post-Farakka episodes and the difference in width-depth ratio for the same period depicts a symmetrical pattern of change in pre-Farakka and post-Farakka situations, indicating a very slight departure from perfection.

5.2.1.3

Depth Index

The depth index (Id) compares the ideal depth (d′) of a channel for being most efficient with the actual depth (d ). Following Das (2015), it can be derived using Eq. 5.7. Id =

d d p 0 = d 0:627 A

ð5:7Þ

where A is the cross-sectional area of the channel. The depth index (Id) portrays the vertical incision of the bed by hydrogeomorphic forces. The value of Id with exactly 1 indicates the most efficient channel depth and the value above or below it directs towards the relative inefficiency of the channel. In the post-Farakka period, a notable decrease in Id has been observed unlike the width index (Fig. 5.24) due to the inefficiency of the channel triggered by huge sediment load from the basin supply along with gentle gradient in a non-confined channel (Charlton, 2008). The study from the selected cross sections indicates exactly the reverse pattern of change in 1984. In other words, the same percentage of the cross sections with the increase in Iw have shown a decrease in Id in the post-Farakka period. Theoretically, a perfect inverse correlation exists between the width index and depth index. 0.5 y1993 = 4E-09x5 - 4E-07x4 + 1E-05x3 - 0.0002x2 + 0.0049x + 0.1361 R² = 0.3056

Depth Index

0.4

1972

y1984 = -2E-09x5 + 5E-07x4 - 3E-05x3 + 0.0009x2 - 0.0055x + 0.1801 R² = 0.2285

1984 0.3

1993

Decrease

Poly. (1972)

Proximate

Decrease

0.2

Poly. (1984) Poly. (1993) 0.1 y1972 = -2E-09x5 + 4E-07x4 - 2E-05x3 + 0.0006x2 - 0.0005x + 0.142 R² = 0.1837

0 0

10

20

30 40 50 Distance from Katwa (km)

60

70

80

Fig. 5.24 Spatio-temporal variation in depth index indicating an increasing trend in the middle of the study stretch and decreasing trend at the lower and the upper end of the distance

192

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Riverbank Erosion and Channel Morphology

Empirical analysis of data using power regression grounds the soundness of theory, i.e., a perfect and statistically significant correlation exists between the variables under consideration in both the pre-Farakka and post-Farakka period. But when linear regression is embraced, results differ from the pre-Farakka stage to the postFarakka. This mild decrease in the value of “r” may be due to disturbance in longadjusted river regimes by the construction of FBP (Parua, 1992).

5.2.1.4

Channel Efficiency Index

The channel form index (CFI) claims that 24 cross-sections out of 39 have lost their channel efficiency as a result of channel aggradation during the post-Farakka period. During 1972–1984, the absolute change in the CFI has been divided into four distinct groups. The category exhibiting minimally enhanced efficiency (-5 to 0) has encountered a total of 8 CS, while the total of 7 CS is exhibiting moderately increased channel efficiency (5) whereas 6 CS represents a minimal fall in channel efficiency. The middle section of the lower Bhagirathi (17–35 km) is notable since it reveals that 70% of the CS in this reach have increased their efficiency. Despite this, 60% of the CS in the lower reach, which is located between 35 and 71 km, and all CS in the upper part, which extends up to 17 km, have seen a drop in efficiency. The entire length typically exhibits larger decreases at either end, with the exception of one that has a slight decline in the middle that appears to be preserving steady-state equilibrium as suggested by the fifth-order polynomial (Fig. 5.25).

y 1993 = 1E-07x5 - 8E-05x4 + 0.0077x3 - 0.2283x2 + 0.8118x + 47.955 R² = 0.4148

90

Channel Form Index

80

1972

y1984 = 7E-07x5 - 0.0001x4 + 0.0103x3 - 0.2729x2 + 1.5238x + 47.138 R² = 0.1972

70

1984

y1972 = 7E-07x5 - 0.0001x4 + 0.0091x3 - 0.2354x2 + 1.6607x + 32.124 R² = 0.1389

60

1993

Increase

50

Poly. (1972)

40

Increase

Poly. (1984)

Decrease

30

Poly. (1993)

20 10 0 0

10

20

30 40 50 Distance from Katwa (km)

60

70

80

Fig. 5.25 Spatio-temporal variation in channel form index showing the decreasing trend in the middle part of the study region and bulging in the upper and lower parts

5.2

Channel Cross-sectional Changes

193

5.2.2

Analysis of Channel Asymmetry

5.2.2.1

Measuring Channel Asymmetry

Cross-sectional asymmetry is an important tool in assessing channel dynamics and riverbank erosion. Frequent change in cross-sectional asymmetry indicates channel dynamism. The higher the value of channel asymmetry, the higher the bank erosion due to the pool of water in a particular direction. In other words, if water flows principally along one bank there will be more erosion on that side and the other bank will virtually be unaffected by erosion. The concept of asymmetry in geomorphologic literature was first applied by Sharp (1963) and Tanner (1968) to assess sand dune morphology. But in fluvial geomorphology perhaps Knighton (1981) first introduced cross-sectional asymmetry of the channel to assess channel dynamics and development. Before Knighton, a group of geomorphologists pointed out the asymmetric nature of the channel. About 90% of the channels are indeed asymmetric (Leopold & Wolman, 1960). Cross-sectional forms are asymmetric even in the straight channel (Majumder, 2011) with successive bars of alternating pitch (Einstein & Shen, 1964; Keller, 1972). For the present analysis, 39 cross-sections have been selected (Fig. 5.26 and Table 5.16) within Katwa and Nabadwip for the Bhagirathi River of the study area. In this work, four techniques on channel asymmetry have been applied. The first three measures viz. A*, A1, and A2 are contributed by Knighton (1981) using Eqs. 5.8, 5.9, and 5.10. A = ðAr - Al Þ=A

ð5:8Þ



ð5:9Þ

A1 = ð2x dmax Þ=A A2 = 2x ðdmax - dÞ=A

ð5:10Þ

Fig. 5.26 Parameters of an asymmetrical channel after Knighton, 1981 (Note: Ar and Al indicate right bank and left bank cross-sectional areas, A stands for the total area of the channel (A = Ar + Al), x for the distance from the channel centreline (Lc) (measured positive to the right and negative to the left) to the centroid of maximum depth, dmax is maximum depth, and d is mean depth)

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Table 5.16 Descriptive statistics of Knighton’s (1981) Indices

Mean Standard error Median Standard deviation Sample variance Kurtosis Skewness Range Minimum Maximum Sum Count Largest(1) Smallest(1) Confidence level (95%)

A* 1972 0.0156 0.0457 0.0269 0.2856 0.0816 -0.9102 0.0227 1.1258 -0.5595 0.5664 0.6098 39.0000 0.5664 -0.5595 0.0926

1984 0.0604 0.0558 0.0921 0.3488 0.1216 -0.2851 -0.0791 1.5400 -0.7017 0.8383 2.3559 39.0000 0.8383 -0.7017 0.1131

A1 1972 0.1813 0.1847 0.3148 1.1532 1.3298 -1.0137 -0.2665 4.1640 -2.2735 1.8904 7.0698 39.0000 1.8904 -2.2735 0.3738

1984 0.2806 0.2199 0.0000 1.3733 1.8859 -1.0547 0.0992 5.0565 -1.9778 3.0787 10.9452 39.0000 3.0787 -1.9778 0.4452

A2 1972 0.0716 0.0916 0.1059 0.5717 0.3269 0.3433 -0.4302 2.4797 -1.4181 1.0616 2.7909 39.0000 1.0616 -1.4181 0.1853

1984 0.1926 0.1276 0.0883 0.7967 0.6348 -0.1272 0.5164 3.3267 -1.1694 2.1572 7.5099 39.0000 2.1572 -1.1694 0.2583

where Ar and Al are the cross-sectional areas respectively to the right and left (looking downstream) of the channel centreline, A is the total area of the channel (A = Ar + Al), x is the distance from the channel centreline (Lc) (measured positive to the right and negative to the left) to the centroid of maximum depth, dmax is maximum depth, and d is mean depth (Fig. 5.26). The channel centreline is a vertical line from the channel bed. Of these indices, the first one (A*) is very easy and most scientific to measure the degree of asymmetry of channel cross-sectional form. However, the second index (A1) and third index (A2) have measured asymmetry in both directions, i.e., horizontal and vertical (Knighton, 1981) forming a different perspective taking the consideration of depth.

5.2.2.2

Pattern of Asymmetry Indices

Applying three indices of Knighton (1981), the asymmetric nature of the cross sections has been analysed for the study area. In the pre-Farakka period, the crosssectional area was more symmetric compared to the post-Farakka situation. By inducing discharge in the lean period by controlled hydrology, channel shape and area have experienced significant change. The typical cross-sectional shape of the channel in pre-Farakka is nearly semi-circular with thalweg at the median point of cross section while triangular with thalweg in post-Farakka episode at one side of the bank (Fig. 5.27a, b). It proves sudden as well as rapid changes in the hydrodynamic characteristics of the channel. This scenario has been assessed by the three indices of Knighton (1981) and Das and Islam (2015). From the A* index it has been observed that there is a divergence between the curves of 1972 and 1984. In the post-Farakka period, areal asymmetry has increased for most of the CS (Fig. 5.28a).

5.2

Channel Cross-sectional Changes

195

10

Reduced level (m)

8 6 4 2 0 -2

0

50

100

150

200

250

300

350

-4

400

a

-6

Distance from Right Bank (m)

14 12 Reduced Level (m)

10 8 6 4 2 0 -2

0

50

100

150

-4 -6

200

250

b Distance from Right Bank (m)

Fig. 5.27 An example (CS 315) of changing cross-sectional shape. (a) Pre-Farakka period-1972 and (b) post-Farakka period-1984 (Computed from hydrographic sheets, KoPT-1972–2012; Note: Datum reduced to MSL)

Regarding A*, bimodal distribution of CS has been observed in the pre-Farakka period (Fig. 5.28b). Maximum frequency has been observed in the classes of 0.1 to 0.3 and -0.1 to -0.3. But in the post-Farakka period, uni-modal nature is found in the class of 0.1 to 0.3 (Fig. 5.28c). One important thing observed here is that in 1972 nineteen CS had more areal extent towards the left bank while in 1984 the number of cross sections having left bank areal orientation was 16. Thus, some of the cross sections have shifted their position from left to right bank in respect of the crosssectional area. However, most of the cross sections have more CS area towards the left bank indicating more scouring and bank erosion (Fig. 5.28c). Index A* has secured a higher value of the mean, range, and change of skewness from almost zero to the negative direction (Table 5.16). Regarding A1, it has been observed that areal asymmetry in terms of maximum depth (dmax) has increased in the post-Farakka period. It is quite natural because in the post-Farakka period due to

196

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Riverbank Erosion and Channel Morphology

1.0 y 1972 = -5E-10x6 + 1E-07x5 - 8E-06x4 + 0.0003x3 - 0.0036x2 + 0.0101x + 0.0155 R² = 0.0548 y 1984 = -2E-09x6 + 4E-07x5 - 3E-05x4 + 0.0014x3 - 0.0244x2 + 0.1533x - 0 .0935 R² = 0.1211 1972

0.8 0.6 0.4

1984

A*

0.2 1993

0.0 -0.2

Poly. (1972)

-0.4

Poly. (1984)

-0.6

Poly. (1993)

y1993 = 1E-09x6 - 2E-07x5 + 2E-05x4 - 0.0006x3 + 0.0084x2 - 0.0146x - 0.1 62 R² = 0.2002

-0.8 0

10

20

30 40 50 Distance from Katwa (km)

60

70

4.0

y1993 = -9E-09x6 + 2E-06x5 - 0.0001x4 + 0.0038x3 - 0.0484x2 + 0.1189x + 1.0901 R² = 0.2558

3.0

y 1984 = -4E-09x6 + 9E-07x5 - 8E-05x4 + 0.0031x3 - 0.0579x2 + 0.4287x - 0.534 R² = 0.0343

80

(a)

1972 1984 1993

2.0

Poly. (1972)

1.0 A1

Poly. (1984) Poly. (1993)

0.0 0

10

20

30

40

50

60

70

80

-1.0 -2.0 y 1972 = -2E-10x6 + 6E-08x5 - 7E-06x4 + 0.0003x3 - 0.0054x2 + 0.0237x + 0.0477 R² = 0.0641

-3.0

(b)

Distance from Katwa (km) 2.5

y 1993 = -6E-09x6 + 1E-06x5 - 8E-05x4 + 0.0025x3 - 0.0341x2 + 0.1225x + 0.4398 R² = 0.2536

1972

2.0 y 1984 =

-3E-09x6

+

7E-07x5

1.5

-

6E-05x4

0.0024x3

+ R² = 0.0573

-

0.0458x2

1984

+ 0.3458x - 0.4616

1993 Poly. (1972)

A2

1.0

Poly. (1984)

0.5

Poly. (1993)

0.0 -0.5

0

10

20

30

40

50

60

70

80

-1.0 -1.5 -2.0

y 1972 = -2E-10x6 + 6E-08x5 - 5E-06x4 + 0.0002x3 - 0.0025x2 + 0.0036x + 0.0467 R² = 0.0432

(c)

Distance from Katwa (km)

Fig. 5.28 Spatio-temporal variation in channel asymmetry. (a) A* index, (b) A1 index, (c) A2 index. The indices indicate that asymmetry has increased in the post-Farakka period

the availability of discharge from the Farakka Barrage Project, scouring in the bed on one side has become more intensified. Hence concentrated flow on one side of the river results from the creation of thalweg at one side of the banks for most of the cross sections and thereby increase the distance between the dmax point and channel centreline. An increase in the number of cross-sections having left bank orientation of the cross-sectional area has been observed. In the histogram plot of the index value, it has been observed that higher frequency in “+” sign classes at a higher range has been replaced by higher frequency in the “-” sign classes in the higher range value of the said index. This observation is consonant with that of A* in respect of areal asymmetry. A1 index has secured a higher value of mean, range, and change of skewness from negative to positive direction (Table 5.16).

References

197

An increase in the A2 index denotes channel asymmetry making a difference between maximum depth and average depth. This Index proves that the higher the value, the higher the maximum depth (dmax) compared to the mean depth (d). For the A2 index, it can be mentioned that the mean value has increased substantially in the post-Farakka period (Table 5.16). The range in the distribution has increased in the post-Farakka period. The negatively skewed distribution of the pre-Farakka stage has been converted into a positively skewed distribution in the post-Farakka condition reflecting the tailing of the curve towards the left bank. Therefore, it is perceived that riverbank erosion is intricately integrated with the various cross-sectional and planform morphological attributes as discussed above. However, riverbank erosion is a major driver of the socio-economic landscape change over various spatial and temporal dimensions that have been discussed in the next chapters.

References Alam, S., Jahan, S., & Noor, F. (2022). The surface water system, flood and water resources management of Bangladesh. Bangladesh Geosciences and Resources Potential, 467–546. Ashmore, P. (1991). Channel morphology and bed load pulses in braided, gravel-bed streams. Geografiska Annaler: Series A, Physical Geography, 73(1), 37–52. Ashworth, P. J. (1996). Mid-channel bar growth and its relationship to local flow strength and direction. Earth Surface Processes and Landforms, 21(2), 103–123. Ashworth, P. J., & Ferguson, R. I. (1986). Interrelationships of channel processes, changes and sediments in a proglacial braided river. Geografiska Annaler: Series A, Physical Geography, 68(4), 361–371. Basu, S. R., et al. (2005). Meandering and cut-off of the river Bhagirathi. In S. C. Kalwar (Ed.), Geomorphology and environmental sustainability (pp. 20–37). Concept Publishing Company. Brice, J. C. (1964). Channel patterns and terraces of the Loup Rivers in Nebraska. US Government Printing Office. Charlton, R. (2008). Fundamentals of fluvial geomorphology. Routledge. Das, B. C. (2014). Two indices to measure the intensity of meander. In Landscape ecology and water management: Proceedings of IGU Rohtak conference, Vol. 2 (pp. 233–245). Springer. Das, B. C. (2015). Modeling of most efficient channel form: A quantitative approach. Modeling Earth Systems and Environment, 1(3), 1–9. Das, B. C., & Islam, A. (2015). Channel asymmetry of an Ox-Bow lake: A different perspective. International Journal of Ecosystem, 5(3A), 69–74. Einstein, H. A., & Shen, H. W. (1964). A study of meandering in straight alluvial channels. Journal of Geophysical Research, 69, 5239–5247. Ferguson, R., & Werritty, A. (1983). Bar development and channel changes in the gravelly river Feshie. In J. D. Collinson & J. Lewin (Eds.), Modern and ancient fluvial systems (pp. 133–143). International Association of Sedimentologists. Sp. Publ. 6. García-Martínez, B., & Rinaldi, M. (2022). Changes in meander geometry over the last 250 years along the lower Guadalquivir River (southern Spain) in response to hydrological and human factors. Geomorphology, 410, 108284. Hecht, E. (1987). Optics (2nd ed.). Addison Wesley. Hong, L. B., & Davies, T. R. (1979). A study of stream braiding. Geological Society of America Bulletin, 90(12_Part_II), 1839–1859. https://doi.org/10.1130/GSAB-P2-90-1839

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Howard, A. D. (1980). Threshold in river regime. In V. R. Coates & J. D. Vitek (Eds.), Thresholds in geomoephology. Allen and Unwin. Islam, A. (2016). River bank erosion and its impact on economy and society: A study along the left bank of river Bhagirathi in Nadia District West Bengal. An unpublished PhD thesis. The University of Burdwan. Islam, A., & Das, B. C. (2015). Quantitative indices to measure unit channel bar location: A theoretical and empirical study. Ethiopian Journal of Environmental Studies and Management, 8(6), 628–634. Islam, A., & Guchhait, S. K. (2017). Analysing the influence of Farakka Barrage Project on channel dynamics and meander geometry of Bhagirathi river of West Bengal, India. Arabian Journal of Geosciences, 10(11), 1–18. Islam, A., & Guchhait, S. K. (2021). Social engineering as shock absorbing mechanism against bank erosion: A study along Bhagirathi river, West Bengal, India. International Journal of River Basin Management, 19(3), 379–392. Jiongxin, X. (1997). Evolution of mid-channel bars in a braided river and complex response to reservoir construction: An example from the middle Hanjiang River, China. Earth Surface Processes and Landforms: The Journal of the British Geomorphological Group, 22(10), 953–965. Keller, E. A. (1972). Development of alluvial stream channels: A five-stage model. Geological Society of America Bulletin, 83, 1531–1536. Kleinhans, M. G., & van den Berg, J. H. (2011). River channel and bar patterns explained and predicted by an empirical and a physics-based method. Earth Surface Processes and Landforms, 36(6), 721–738. Knighton, A. D. (1981). Asymmetry of river channel cross-sections: Part I. Quantitative indices. Earth Surface Processes and Landforms, 6(6), 581–588. Knighton, D. (2014). Fluvial forms and processes: A new perspective. Routledge. Kolberg, F. J., & Howard, A. D. (1995). Active channel geometry and discharge relation of US Piedmont and Midwestern streams: The variable exponent model revisited. Water Resources Research, 31(9), 2356–2365. Leopold, L. B. & Wolman, M. G. (1957). River Channel Patterns, Braided, Meandering and Straight. U.S. Geol. Surv. Paper. 282-B. https://doi.org/10.3133/pp282B Leopold, L. B., & Langbein, W. B. (1966). River meanders. Scientific American, 214(6), 60–70. Leopold, L. B., & Wolman, M. G. (1960). River meanders. Geological Society of America Bulletin, 71(6), 769–793. Majumder, T. (2011). Rajpat (in Bengali). Ananda. Miall, A. D. (1978). Fluvial sedimentology: A historical review. In A. D. Miall (Ed.), Fluvial sedimentology (pp. 1–47). Canadian Society of Petroleum Geologists. Miller, T. K., & Onesti, L. J. (1979). The relationship between channel shape and sedimentary characteristics in the channel perimeter. Bulletin of the Geological Society of America Part I, 90, 301–304. Mueller. (1968, June). An introduction to the hydraulic and topographic sinuosity indexes. Annals of the Association of American Geographers, 372. Nanson, G. C., & Hickin, E. J. (1986). A statistical analysis of bank erosion and channel migration in western America. Bulletin of the Geological Society of America, 97, 497–504. Parua, P. K. (1992). Stability of the banks of Bhagirathi-Hooghly river system. Ph.D thesis. Jadavpur University. Rennell, J. (1788). Memoir of a map of Hindoostan or the Mughal empire. M. Brown. Rust, B. R. (1978). A classification of alluvial channel systems. In I. A. D. Miall (Ed.), Fluvial sedimentology (Vol. 5, pp. 187–198). Ch. Memoirs of the Canadian Society of Petroleum Geologists.

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Schumm, S. A. (1960). The shape of alluvial channels in relation to sediment type. Professional Paper. U S Geological Survey, 352B, 17–30. Schumm, S. A. (1963). Sinuosity of alluvial rivers in the great plains. Geological Society of America Bulletin, 74, 1089–1100. Sharp, R. P. (1963). Wind ripples. The Journal of Geology, 71(5), 617–636. Sonin, A. A. (1995). The surface physics of liquid crystals. Taylor & Francis. Tanner, W. F. (1968). Shallow lake deposits, lower part of Morrison Formation (late Jurassic), northern New Mexico. The Mountain Geologist. Williams, G. P. (1986). River meanders and channel size. Journal of Hydrology, 88, 147–164.

Chapter 6

Economic Vulnerabilities Induced by Riverbank Erosion

6.1

Introduction

The economic base of the study area is mainly agriculture. Agriculture nowadays is not at all a profit-making activity due to the steady increase in labour cost and also the cost of fertilizer. Rather agrarian economy is gradually dwindling mainly due to market force (Sharma, 2007). Naturally, farmers are becoming socio-economically marginalized day by day. Such a scenario is most common in developing countries like India, Bangladesh, and Nepal. Adversities in the agrarian economy have trapped people in crisis even the suicides of farmers (National Crime Reports Bureau, 2014). If such a stressed economy faces frequent hazards, whether physical or social, the degree of socio-economic marginalization is intensified. The present focus, therefore, crops up the rapid economic decline of the study area triggered by the severity of river bank erosion. Here, stressed economy of the study area has been analysed in the context of erosion hazards and the livelihood crisis of the people thereof. A crisis in the economy always puts severe stress on livelihood. Therefore, economy and livelihood are critically analysed side by side.

6.2

Conceptual Framework on Resource Base, Economy, and Livelihood

Human existence cannot be thought of without resources for which the life and livelihood of society are fabricated. Availability of resources in rural areas is conditioned by the resource base of the surrounding area which is vehemently

Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/978-3-031-47010-3_6. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Islam, S. K. Guchhait, Riverbank Erosion in the Bengal Delta, Springer Geography, https://doi.org/10.1007/978-3-031-47010-3_6

201

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6 Economic Vulnerabilities Induced by Riverbank Erosion

controlled by nature. In the study area, therefore, interlinking the resource base, economy and livelihood is of prime importance in elaborating social dynamics threatened by hazards.

6.2.1

Resource Base and Economy

The economic landscape, like the spatial economy, mostly reflects three forms of economic activities in relation to production, distribution, and consumption. Resource base more specifically natural resource base plays a vital role in material life, especially in rural areas. In agrarian economy land, soil and climate are the key physical factors for agricultural production. For the present inquiry, all those physical factors are highly prevalent in the Nadia district (Fig. 2.5). Therefore, the agrarian economy in the study area has few limitations in promoting life and livelihood. However, the study area faces severe bank erosion with a drastic loss of land and soil that affects the food security of the agrarian community. The economy of the study area thus has experienced a continuous decline at least for the last 40 years due to severe land loss. Resource base, i.e., land is not able to support sufficient production for the survival of the household economy causing a severe crisis in livelihood.

6.2.2

Shifting of Economic Activity

The physical environment is the gift of nature whereas the economic environment is the outcome of human activity. All the different forms of economic activity like gathering and hunting, agriculture, mining, industry, transport and storage, trade and commerce, communication, etc., have evolved in different stages of civilization. In the study area agriculture is the backbone of the rural economy. But threatened by bank erosion hazards, the agriculture of the study villages is at stake. Both farmers and labourers being uprooted from agriculture are now shifted to the non-agricultural economy wherever available like a cottage industry, weaving, mulberry plantation, casual workers in the urban and semi-urban setup, construction workers, and are forced to adopt migration outside the state and the nation. This diversity of occupation is not the natural choice; rather environmental refugees are bound to take these options under stressed conditions. This shifting has a specific trend depending upon the opportunities whenever and wherever available. More importantly, most of the able-bodied members of the family including adults, women and even older people are engaged in different types of activities to the stabilize household economy.

6.2

Conceptual Framework on Resource Base, Economy, and Livelihood

6.2.3

203

Rural Livelihood and Its Change

Rural livelihood is gaining importance in the study of economic and socio-cultural landscapes as it is the most important aspect of human survival. Livelihood analysis tuned with the change of livelihood in the study area is not only an integral part of this work, but it is also of utmost relevance in the present context, as the physical hazard has induced strategic change in livelihood patterns. Livelihood study, either in a rural area or in an urban setup, concerns the way of living which significantly denotes the struggle for existence. In the present context, causes for livelihood change, the stress in livelihood, and livelihood diversity are critically analysed in terms of the adoption and adaptation of strategy to cope with the shock, and risk induced by bank erosion hazard. Adoption and adaptation of livelihood strategy indeed determine the quality of life of a family or a community, at the same time it also signifies the well-being of a family or a community. Besides this, social interaction, social relation, and social change are also conditioned by the adoption and adaptation of livelihood strategies. In the study area apart from the people of Matiari, other victims are forced to adopt and adapt livelihood diversity at an individual as well as household level. Being almost uprooted from farm operations even an individual adopts different occupations at different times of the year for the survival of his/her family. At the household level, women in some families are engaged in weaving, mulberry plantations, and bidi binding at different hours of the day. Such diversity is not the natural outcome, but rather a forced condition imposed by the hazard of that area. In understanding livelihood patterns and changes of livelihood due to bank erosion, a theoretical consideration of livelihood is the basic foundation in unfolding the livelihood dynamics and also finding out the solution to the problems. The expressive idea of the term livelihood becomes more meaningful when the means of living of people are threatened, damaged, and destroyed (UNDP, 1992). Chambers and Conway (1992) have defined – “A livelihood comprises the capabilities, assets, and activities required for a means of living.” Considering the capabilities of asset generation in relation to survival, Ellis (2000) has defined – “A livelihood comprises the assets and activities and access to resource mediated by institutions and social relations that are required for a means of living.” Considering the theoretical framework of rural livelihood, Ellis (2000) has pointed out four-point sequences in the form of livelihood assets, livelihood context, livelihood strategy, and livelihood vulnerability. In the context of livelihood assets, the term capital is frequently used under the following heads: (a) Natural capital is more familiar with the land, soil, water bodies, forest, rivers, etc., that are helpful to generate means of survival. (b) Physical capital includes basic infrastructures like roads, canals, buildings, machines for performing occupations, etc. (c) Financial capital indicates stocks of money in the form of savings, access to credits, income, surplus agricultural income, gems and jewellry, etc.

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(d) Human capital implies skill, labour, ability to work, education, health, etc. (e) Social capital considers social integrity, cohesiveness, network relation, etc. All those capitals or assets are necessary preconditions for maintaining sustainable livelihood as well as avoiding the risks and vulnerability of livelihood. A livelihood becomes vulnerable when asset generation becomes critical due to hazard, shock, seasonality, or poverty. For the present study, livelihood vulnerability appears due to critical consideration of natural assets (land loss), physical assets (damage of roads and settlement), financial assets (surplus farm income), and human capital (inability to work in farm practices). Ellis (1998, 1999) therefore emphasizes the adjustment to livelihood in relation to the crisis. Under such a crisis, livelihood adjustment occurs in two ways – in situ adjustments with the local substitution through the shifting of occupation and diversification and ex-situ adjustment through remittances. The present chapter thoroughly investigates the impact of bank erosion on the economy and livelihood. It, therefore, necessarily analyses livelihood vulnerability.

6.3

Change in the Asset Profile

An asset is “any resource owned or controlled by a business or an economic entity” (O’sullivan et al., 2003). It can be tangible (e.g., cash and building) and intangible (trademark, copyright, and patents) that are used to produce positive economic values in monetary terms (Siegel et al., 2011). Massive bank erosion induces severe loss of properties and assets in two main ways viz. direct loss of properties like land, settlement, and other household properties and selling of properties and assets for survival.

6.3.1

Nature of Land Loss

The first and foremost important shock that immediately comes through bank erosion is the loss of landed property (Haque, 1997) which is revealed through intensive field investigation using a questionnaire (Table S6.1) with a robust sampling design as mentioned in Chap. 2. In the surveyed villages in tier-I adjacent to the river as explained in Chap. 2 (Fig. 2.5), it is revealed that more than 60% of households have lost their land. Char-Kashthasali, located in tier-II, is an exception to this scenario. Here, only 35% of households have lost their land (Fig. 6.1). Villages beyond tier-II have no land loss at all. Sujanpur also is a representative of this zone. It is observed that the lion’s share of the households has experienced a huge loss of agricultural land in all the villages with the highest figure in Ganjadanga and the lowest in Char-Kashthasali. In Ganjadanga more than 92% of households have lost their agricultural land and in Char-Kashthasali only 33% of households have lost the same while Sujanpur is an exception to this (Islam & Guchhait, 2017).

6.3

Change in the Asset Profile

205 Household losing land ( agricultural and/or settlement) Household losing agricultural land Households not losing land

% of Households

100 90 80 70 60 50 40 30 20 10 (a) 0

Matiari

Akandanga

Rukunpur

Ganjadanga

Char-Kashthasali

Sujanpur

100 90

Matiari

Land loss (%)

80

Akandanga

70 Rukunpur

60 50

Ganjadanga

40

Char-Kashthasali

30

Sujanpur

20 10 0

(b)

settlement

agricultural land Types of Land Lost

others

Fig. 6.1 Dynamics of land loss in the study villages located along the Bhagirathi River, (a). Nature of land loss. (Data Source: Field Survey, 2012–2013; Sample size Matiari 597; Akandanga 127; Rukunpur 183; Ganjadanga 78; Char-Kashthasali 144; Sujanpur 57), (b). Types of land loss in the study area. (Data Source: Field Survey, 2012–2013; Sample size: Matiari, 362; Akandanga 88; Rukunpur 152; Ganjadanga 78; Char-Kashthasali 51; Sujanpur 0)

Village level survey shows that among the loss of landed properties agricultural land loss overtakes others. In all the villages having land loss, the loss of agricultural land is more than 75%. It is quite natural because the surrounding areas of a village are used for agriculture. It is pertinent to mention here that in Ganjadanga village, the relative loss of agricultural land is least in comparison to the other villages because in this village more than 44% of households have lost their settlements since the 1920s (Fig. 6.1) which is also reflected in the LULC transformation from 1920 to 2020 (Figs. 4.16, 4.17 in Chap. 4). Naturally, the loss of settlement land is quite high for them compared to the other villages. It accounts for nearly 13% of the total land area. Other types of land loss include orchards, pastures, roads, playgrounds, etc. All these types of land loss are also maximum in the case of Ganjadanga and so almost the entire village has been shifted from west to east. It is overwhelmingly true that in the study area agricultural economy has become fragile by the loss of agricultural land. That is why agricultural land loss deserves special treatment.

206

6.3.2

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Economic Vulnerabilities Induced by Riverbank Erosion

Loss of Agricultural and Settlement Land

Agricultural land loss is common parlance in the context of bank erosion all over the world. A handful of research works are also available on bank erosion and agricultural land loss (e.g., Schumuck-Widmann, 2001; Hutton & Haque, 2004; Uddin & Rahman, 2011). Most of the works concern economic and social perspectives. This work also intends to delve deeper into the issue of bank erosion and its impact on the agrarian economy. For example, bank erosion along the Brahmaputra River in Assam (India) is crucial in the context of land loss and striking loss of property and assets (Dekaraja & Mahanta, 2022). The Department of Water Resources, Government of Assam (Revenue Dept.) has estimated the loss during 2001–2006 where it is observed that in 2004, about 21, 000 Ha of land was eroded in 1245 villages with 62,258 households. The loss of property was estimated to be ~ INR 10,000 lakh (1USD = 45.23 INR during 2004) (Table 6.1). During the last 10 years (2003–2013), 16,552 bighas (1 acre = 3.025 bigha) of agricultural land were lost due to bank erosion (Kalitha, 2018). This scenario figures out the grim reality of the bank erosion in Assam. Similarly, another part of the Bengal Delta (Bangladesh) is a major hotspot of riverbank erosion. All the major rivers of Bangladesh like Brahmaputra, Jamuna, Padma, and Meghna exhibit huge riverbank erosion (Fig. 6.2). Bangladesh Water Development Board (2017) estimated the rate of bank erosion during 1973–2013 and found about 1770 ha year-1 for the Jamuna, 1298 ha year-1 for the Padma, and 2900 ha year-1 for the lower Meghna (Mojid, 2020). Survey results reveal that farmers in the Matiari and Rukunpur villages are most threatened by agricultural land loss, orchard loss, and crop damages (Fig. 6.3a–d). More than 40% of farmers have lost 5 bighas or more land in the concerned mouzas (Fig. 6.4a). For Rukunpur more than 13% of farmers have lost 16 bighas or more land. This is surely a depressive scenario from the perspective of the village economy of India. Char-Kashthasali, on the other hand, is less affected because here only 33% of farmers have lost their land and that’s too meagre in amount. Most of the farmers in Char-Kashthasali village have lost 5 bighas or less while Sujanpur has no land loss at all (Fig. 6.4a). In respect of the proportion of the land loss, farmers of Matiari and Rukunpur are most victimized. More than 69% of farmers have lost Table 6.1 Land loss in the Brahmaputra River in Assam, India Year 2001 2002 2003 2004 2005 2006

Area eroded (Ha) 5348 6803 12589.6 20,724 1984.27 821.83

No. of villages affected 227 625 424 1245 274 44

No. of families affected 7395 17,985 18,202 62,258 10,531 2832

Value of property including land loss (INR in Lakh) 377.72 2748.34 9885.83 8337.97 1534 106.93

Source: Assam State Portal (https://assam.gov.in/web/department-of-water-resource/flood-anderosion-problem)

6.3

Change in the Asset Profile

207

Fig. 6.2 Bank erosion-prone areas of Bangladesh. (Based on Bangladesh Water Development Board, 2017)

more than 90% of their agricultural land in Matiari village (Fig. 6.4b). For Rukunpur village nearly 47% of farmers have lost more than 90%. Char-Kashthasali village is also the least victimized in respect of the proportion of the land loss. Nearly 78% of farmers have lost less than 30% of their holdings. Akandanga and Ganjadanga are similar in respect of the proportion of agricultural land loss (Fig.6.4b). Both of these villages are moderately victimized in this regard. To glean the significant difference among villages related to the percentages of agricultural land loss, a chi-square test has been employed. The computed value of chi-square is 327 (Table 6.2) which is higher than the tabulated value (32.91 for 12 degrees of freedom at a 99.99% significance level). As the computed value far exceeds the tabulated value, it implies a significant difference among the villages

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Fig. 6.3 Loss of properties by bank erosion, (a) Agricultural land in Matiari, (b) Agricultural land in Rukunpur, (c) Banana orchard in Rukunpur, (d) Loss of crops by bank erosion induced flood in Akandanga. (Source: Field survey, 2012–2013)

related to agricultural land loss. Truly, two villages (Matiari and Rukunpur) have experienced a huge loss of agricultural land due to bank erosion while others are not. Barring the loss of agricultural land, loss of habitable land (settlement area) has also been observed in Matiari, Rukunpur, and Ganjadanga. People have become environmental refugees (Islam & Rashid, 2011), especially in Rukunpur and Ganjadanga due to massive bank erosion during the last 40 years and are forced to shift their settlements more than two times. In Rukunpur, more than 2% of households have experienced frequent shifting of their settlement, i.e., 3–4 times during

6.3

Change in the Asset Profile

16 or above

209

11.0-15.0

6.0-10.0

5 bighas or below

Farmers losing land (%)

100

(a)

80 60 40 20 0 Matiari

Akandanga

>90%

Rukunpur

60-90%

Ganjadanga

30-60%

Char-Kashthasali

Sujanpur

90%

Observed frequency in % (O) 2.76 10.70 6.65 10.26 77.08

Villages Matiari Akandanga Rukunpur Ganjadanga CharKashthasali Matiari 5.80 Akandanga 39.25 Rukunpur 11.09 Ganjadanga 39.74 Char10.42 Kashthasali Matiari 21.93 Akandanga 24.98 Rukunpur 35.47 Ganjadanga 24.36 Char12.50 Kashthasali Matiari 69.44 Akandanga 24.98 Rukunpur 46.56 Ganjadanga 25.64 Char0.00 Kashthasali ∑ (O-E)2/E = 327

Expected frequency in % (E) 21.49 21.49 21.49 21.49 21.49

(O-E) -18.73 -10.79 -14.84 -11.23 55.59

(O-E)2 350.72 116.33 220.19 126.19 3090.62

21.26 21.26 21.26 21.26 21.26

-15.46 17.99 -10.17 18.48 -10.84

238.98 323.64 103.52 341.64 117.58

11.24 15.22 4.87 16.07 5.53

23.85 23.85 23.85 23.85 23.85

-1.92 1.13 11.62 0.51 -11.35

3.69 1.27 135.11 0.26 128.82

0.15 0.05 5.66 0.01 5.40

33.32 33.32 33.32 33.32 33.32

36.12 -8.34 13.24 -7.68 -33.32

1304.60 69.60 175.28 58.97 1110.22

39.15 2.09 5.26 1.77 33.32

(O-E)2 /E 16.32 5.41 10.25 5.87 143.82

Computed from field data (2012–2013)

erosion on both sides of the char. However, if the char is located away from the mid-channel, bank side closure to the char becomes more erosion-prone. Both are equal for Padma. Moreover, bank erosion also occurs for the two sides of the char. In Padma, chars are larger in size and stable. The chars are the preferable sites for fishermen and bank erosion victims. Soils of those chars are so fertile that those are highly suitable for agriculture. Therefore, unlike the chars of Bhagirathi and Hooghly, the chars of Padma are crowded with population. Therefore, river bank erosion and char side erosion offer interesting dynamics of migration of households. Islam (2021) studied the shifting of households within the chars of Padma as circular, i.e., rotating within the char from one location to another due to bank erosion and flooding. In an empirical study, he has pictorially depicted the cyclical displacement of the house of Omar Ali Sheikh and his offsprings within the period of 1945 to 2008. The family of Omar Ali Sheikh returned to the original position in 2008 after 16 times dislocation. If not cyclical, the rotational displacement is found to occur in

6.3

Change in the Asset Profile

211

Households experiencing shifting of settlement by erosion (%)

>30 Days

15-30 days

40% mean rating in all villages barring Akandanga). For some villages like Rukunpur, bank protection work has been prioritized to minimize bank erosion which is also reflected in the higher positive rating of respondents for the government-undertaken bank protection works during the last 3–4 years (Fig. 7.4).

70

Mean Rating (%)

60 50 Bank Protection Work

40 30

Mulberry Plantation

20 10 0 Matiari

Akanadanga

Rukunpur

Ganjadanga

Fig. 7.4 Effectiveness of the government schemes to mitigate the hazards of bank erosion. (Sample size: Matiari 122, Akandanga 19, Rukunpur 62, and Ganjadanga 20)

7.3

Social Processes and Social Relation in Hazardous Space

7.3

255

Social Processes and Social Relation in Hazardous Space

Social processes are observable and recurring patterns of social interaction that have a consistent direction or quality (Bardis, 1979). Peter Kropotkin, the Russian geographer, for the first time applied the concept of conflict and cooperation in the domain of geography. Thereafter, it has become a popular notion in the domain of social geography. Broadly, four groups of social interactive processes viz. intraindividual, interpersonal, intergroup, and group process are analysed in the context of community interaction. In the hazardous space, all those four social interactive processes are mapped to figure out the disruption of social life during and after the hazard appears. Intraindividual processes refer to the interactions within an individual. Contrarily, interpersonal processes indicate the interaction between two or more individuals. Similarly, intergroup processes focus on the interactions between two or more groups, whereas group processes imply interactions among the group members (Islam & Guchhait, 2018).

7.3.1

Measuring the Social Processes

Some selected variables are used here to make comprehensive outcomes of the four broad groups of social processes using a systematic sampling design for the selected villages as mentioned in Chap. 2 (Table S2.1). For assessing intraindividual processes six criteria have been considered following Tesser and Schwarz (2001) such as “social unconscious, self-regulation, goal setting and goal striving, nature of emotion, values and ideologies, self-esteem” respectively. In the context of the interpersonal processes, four criteria are taken after Fletcher and Clark (2003), such as “helping and altruism, death and rebirth of social psychology of negotiation, affect/ emotion of self and identity” (Table 7.2). Similarly, for intergroup processes five parameters are considered following Brown and Gaertner (2003), such as “intergroup bias/prejudice, social justice, majority-minority relation, cultural mix and acculturation, trust and intergroup negotiation”. Finally, for group processes, another six variables are selected according to Hogg and Tindale (2001), such as “collective choice, judgement, and problem-solving, social categorization, depersonalization, and group behaviour, group socialization, and newcomer innovation, mood, and emotion in the group, social status and group structure, collective identity”. Selecting the variables, respondents were asked to answer the questions on a 100-point rating scale with a minimum of zero and a maximum of hundred.

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Social Instabilities Induced by Riverbank Erosion

Table 7.2 Social processes and their measuring variables in relation to riverbank erosion Types Intraindividual

Social process 1.1 Social unconscious 1.2 Self-regulation 1.3 Goal setting and goal striving 1.4 Nature of emotion 1.5 Value and ideologies

Interpersonal processes

1.6 Self-esteem 2.1 Helping and altruism 2.2 Death and rebirth of social psychology of negotiation 2.3 Affect/emotion 2.4 Self and identity

Intergroup Processes

3.1 Intergroup bias/prejudice

3.2 Social justice 3.3 Majority-minority relation

Group Processes

3.4 Cultural mix and acculturation 3.5 Trust and intergroup negotiation 4.1 Collective choice, judgement, and problem solving 4.2 Social categorization, depersonalization, and group behaviour 4.3 Group socialization and newcomer innovation 4.4 Mood and emotion in the group 4.5 Social status and group structure 4. 6 Collective identity

Examples How much love, craze, anger, and violence are repressed during disaster? How much can you control yourself to repress love, craze, and anger during this period? How much have you faced problems to fix a goal? How much is your emotion repressed by this event? How much can the kids understand your economic and psychological distress aftermath hazard? How much is your self-esteem dwarfed? Do you think that your close relatives are sympathetic to you in distress? Do you think some social rituals and cults have died away or some new rituals have appeared? How much do you get affected by the distressed conditions of others? Are you, victims of erosion, united irrespective of caste, creed, and religion? Do you think whether social and psychological gap among the victim groups has increased? Do the common people (non-victim) think or air voice in favour of you? Do you think the social and psychological gap between the victim and non-victim groups has increased? Have you taken any united measures against bank erosion and how much is it effective? Do the non-victims trust you in distress? Have you taken joint initiative regarding the arrangement of food and health facilities? Do you move united (irrespective of caste, creed, or religion) while in erosion danger? Are you careful about the families from where the heads of the families are outside for work? Do any emotions or nostalgic situations appear from the group discussion? Do you think that rich-poor gap has reduced and they have come closer? Do the victimized families work together during and after the erosion hazards?

7.3

Social Processes and Social Relation in Hazardous Space

7.3.2

257

Pattern of Social Processes

The pattern of social interaction has been evaluated by the average rating of the respondents and mean-CV differential in rating thereafter which is subsequently employed through graphical analysis.

7.3.2.1

Intraindividual Processes

Indicators of intraindividual processes show the maximum hazardscape for Rukunpur, the most victim village of the studied villages. Regarding the social unconscious, the victims have opined that people’s expressions of the unconscious mind like love, and anger are overlooked under stress. Similarly, control over the self is the minimum (Fig. 7.5a). Survival becomes so crucial that control over the self is lost especially in family interaction. Under such a strenuous condition, one can’t fix a definite goal be it an arrangement of offspring marriage or educating them, or a crucial decision of the family on any kind of long-term planning. Survey results

Self Esteem

Social Unconscious 100 80 60 40 20 0

Value and Ideologies

a Self-regulation

Matiari Akandanga Rukunpur Ganjadanga

Goal Setting and Goal Striving

Mean- C.V Differential of Respondents' Rating (%)

Nature of Emotion 100

b

80

Controlled by Event

60

Matiari

40

Akandanga

20 Rukunpur 0 Ganjadanga

-20 -40 -60

Controlled by Perception Social Self-regulation Goal Setting Unconscious and Goal Striving

Nature of Emotion

Value and Ideologies

Self Esteem

Intra-Individual Processes

Fig. 7.5 Nature of intraindividual processes, (a) Mean rating of respondents, (b) Mean-CV differential. (Computed from the field data, 2015: Sample size: Matiari 122, Akandanga 19, Rukunpur 62, and Ganjadanga 20)

258

7 Social Instabilities Induced by Riverbank Erosion

indicate that emotion is highly repressed by the bank erosion hazard, especially for Rukunpur. They can rarely think about the normal rhythm of family life apart from twice a meal a day. Being psychologically disturbed by the shock of bank erosion, Amanat Sk. (male, 55 years) have expressed, “I have lost 7 bigha of land during last 6 years. Now I am a landless labour. In our society land is not only property but a symbol of prestige. My social position is wiped out losing all my holdings. People do not respect me anymore. I have also forgotten to respect myself.” The consistency of the opinion was measured by the Mean-CV differential (Fig. 7.5b) which shows subjectivity of opinion for Akandanga, due to minimum land loss by bank erosion, while objectivity and consistency in opinion are more conspicuous for Rukunpur as land loss has occurred for each and every villager.

7.3.2.2

Interpersonal Processes

Indicators of interpersonal processes, operating between individuals, reveal the maximum intensity of hazard for Rukunpur, succeeded by Matiari, Ganjadanga, and Akandanga. In the context of helping and altruism, a convergence of opinion between Matiari and Rukunpur is found. Close relatives of Rukunpur help the victims selflessly almost without any hesitation but for Matiari, the well-off people extend help to the victims of “Nichupara”, the peripheral part of the village inhabited by poor people mostly refugees (Fig. 7.6a). However, the consistency of the opinion in Matiari regarding this variable is weak for variable individual response. For other variables, Rukunpur overrides the scores of other villages. Asena Bewa (female, 68 years) voices “when I came to this village in 1994 after my marriage, Muhuram (Muslim festival) was celebrated with pomps and pride. Gradually this ceremonial occasion has lost its glory due to the land loss of the villagers on a massive scale. At present only a few families celebrate this on their own; the cumulative social effort to organize this programme is almost absent now.” Such a voice is very common for Rukunpur but not for Akandanga which indicates the event-controlled mechanism for Rukunpur and the perception-controlled mechanism for Akandanga (Fig. 7.6b). Bank erosion in this region has led to variability in emotion and identity crisis due to actual phenomena as well as the socio-economic structure of the villages and economic conditions of the families. Almost all the respondents unequivocally agreed to assess self and identity with a high rating.

7.3.2.3

Intergroup Processes

Intergroup processes are rather complex than the earlier ones at an individual level. It is observed that intergroup bias and prejudice are the maxima for Matiari for increasing the psychological gap among the villagers due to income inequality by dint of manufacturing (Fig. 7.7a). Regarding this variable, only Matiari has recorded a positive mean-CV differential indicating objectivity of the phenomenon while the

7.3

Social Processes and Social Relation in Hazardous Space

259

Matiari Helping and Altruism 100

a

Akandanga

80 Rukunpur

60 40 20 Self and Identity

0

Ganjadanga Death and Rebirth of Social Psychology of Negotiation

Affect/Emotion 80

b

Mean -C.V. Differential (%)

60 40 20 0

Matiari

-20

Akandanga

-40

Rukunpur

-60

Ganjadanga

-80 -100 Helping and Altruism

Death and Rebirth of Affect/Emotion Social Psychology of Negotiation Interpersonal Processes

Self and Identity

Fig. 7.6 Nature of interpersonal processes, (a) Mean rating of respondents, (b) Mean-CV differential. (Computed from the field data, 2015: Sample size: Matiari 122, Akandanga 19, Rukunpur 62, and Ganjadanga 20)

responses from other villages are very much fragmentary. For social justice mean rating is not satisfactory and not consistent as well (Fig. 7.7b). This may be due to the predominance of group differences existing in the area. A gap in majority-minority relations (in terms of social and psychological gap) between the victims and non-victims has increased highly in Rukunpur because victims are the sufferers and are now in stressed conditions which are not fully perceived by non-victims. The rating in this variable is very inconsistent for Akandanga and Ganjadanga while more consistent for Matiari and Rukunpur. This certainly proves spatial variation in perception triggered by bank erosion. Cultural mix and acculturation (united measure against bank erosion) is observed maximum for Rukunpur as it is the most threatened village by bank erosion. Therefore, this response reflects the unitedness of people irrespective of caste, creed, and colour to save the village against the hazard and to survive the community ultimately. In Matiari and Rukunpur, the non-victims trust the victims in distress. This is the only

260

7

Social Instabilities Induced by Riverbank Erosion

Intergroup Bias/Prejudice 70 60 50 40 30 20 10 0

Trust and Intergroup Negotiation

a

Social Justice

Matiari Akandanga Rukunpur Ganjadanga

Cultural Mix and Acculturation

Majority-Minority Relation

40

Mean-CV Differential (%)

b 20

0 Matiari Akandanga -20

Rukunpur Ganjadanga

-40

-60 Intergroup Bias/Prejudice

Social Justice

Majority-Minority Cultural Mix and Relation Acculturation

Trust and Intergroup Negotiation

Inter-group Processes

Fig. 7.7 Nature of intergroup processes, (a) Mean rating of respondents, (b) Mean-CV differential. (Computed from the field data, 2015: Sample size: Matiari 122, Akandanga 19, Rukunpur 62, and Ganjadanga 20)

parameter in intergroup processes that have registered a positive mean-CV differential in all the villages. In other words, this parameter shows an event-controlled response.

7.3.2.4

Group Processes

In most of the socio-economic aspects, the scenario of Rukunpur is different from others. It is also found for group processes. For group processes, i.e., operating within the group, Rukunpur is standing apart with a higher mean rating except for mood and emotion in the group (Fig. 7.8a). For the severity of bank erosion in Rukunpur, victims are united and practice collective work during a hazard, while for

7.3

Social Processes and Social Relation in Hazardous Space

Collective Identity

Collective Choice, Judgement and Problem Solving 100 80 60 40 20 0

261

a Social Categorization, Depersonalization, and Group Behaviour

Akandanga Group Socialization and Newcomer Innovation

social status and group structure

Matiari

Rukunpur Ganjadanga

Mood and Emotion in the Group

80

Mean-CV differential (%)

60 40 20 0 Matiari

-20

Akandanga

-40

Rukunpur

-60

Ganjadanga

-80 -100 Collective Choice, Social Group Mood and Judgement and Categorization, Socialization and Emotion in the Problem Solving Depersonalization, Newcomer Group and Group Innovation Group Processes Behaviour

social status and Collective Identity group structure

b

Fig. 7.8 Nature of group processes, (a) Mean rating of respondents, (b) Mean-CV differential. (Computed from the field data, 2015: Sample size: Matiari 122, Akandanga 19, Rukunpur 62, and Ganjadanga 20)

Akandanga and Ganjadanga rating is rather low due to less severity and inconsistency of erosion and inconsistent for the lesser severity of erosion (Fig. 7.8a, b). Group cohesion is very clear in Rukunpur village. People move united against any issue related to bank erosion. During the period of crisis, they forget the enmity between the individuals within the same group. Regarding group socialization, Rukunpur has again secured the first position because of its intense social bond. Among the study villages, Rukunpur has a long tradition to face bank erosion as the regularity and severity is high. Practically, they have a separate identity as environmental refugees from the surrounding villagers. This identity has made them united. Apart from this, most of the adult people of Rukunpurs work outside the district as a coping strategy to sustain the family. In the absence of a family head, other people (elderly) in the villages take care of those families. Though the rating is positive, the intensity is not so high. Mood and emotion are psychological considerations.

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7 Social Instabilities Induced by Riverbank Erosion

Ganjadanga ranks first due to their nostalgia due to recent time land loss (prior to the 1990s). People of Rukunpur on the other hand have no time to get involved with nostalgia. That has faded away long before and they are now busy surviving their families. In response to this question Kadbanu Bibi (female, 43 years) states that “Even on empty stomach we have to work day in and day out for the survival of our families. We have practically no time for leisure. We are so much overburdened with our family and work that nostalgia relating to previous time, society, and activitythough appears in our mind persists for a very short period. We have no time to think about such nostalgic images.” Taking social status, Rukunpur again occupies the top position in hazardscape. The then landlords are the marginal farmers now. Hazards have established equity in terms of ownership of resources, only within a span of 20–25 years. For Matiari, on the other hand, the gap between the rich and poor has increased substantially by dint of the brass metal industry. Collective identity is also the maximum for Rukunpur. Shared senses of belonging to a group have developed appreciably under stressed conditions here. Madan Pramanik (male, 49 years) puts the view that “during the time of erosion, we cooperate with each other in household work and farm operation. When my neighbor was about to lose mature crops (oil seeds, paddy) due to erosion, I was busy with my family’s work at that time. Listening news, I rush to the field to save his crops instantly.” Thus a collective identity has developed gradually in Rukunpur because of the frequent hazard.

7.3.3

Association of Social Processes

The nature of social interaction discussed so far is viewed on a specific framework. However, all the separate frameworks are not segregated. Rather one is interlinked with the other. Therefore, two-stage PCA is employed to make it an interrelated system framework. Here, there are four broad categories of social processes: (a) intra-individual containing seven sub-variables, (b) interpersonal having five sub-variables, (c) intergroup concerned with six sub-variables, and (d) group processes consisting of seven sub-variables totaling 25 sub-variables. To reduce the dimensionality first standard PCA is run for each broad four categories individually. PRIN score of each village (Matiari, Akandanga, Rukunpur, and Ganjadanga) is defined under a broad variable using Eq. 7.1 ðIndividual score of the variable × PC1 ScoreÞ=PC1 Eigenvalue

ð7:1Þ

Taking these PRIN scores second-stage PCA is accomplished to discriminate the social processes, with dimensionality. From the above PCA, it becomes clear that the relationship is strong for intraindividual and interpersonal processes while relatively weak for intergroup and moderates for group processes (Tables S7.1–S7.4). This is due to the prevalence

7.3

Social Processes and Social Relation in Hazardous Space

263

of group differences existing in the concerned area. For intraindividual processes, the total variance explained in PC1 is 95% and all the components have very high positive loadings. Self-regulation, having the maximum positive score, is directing the system towards positive loading. For interpersonal processes, the total variance explained in PC1 is maximum (>97%) in comparison to others and all the components have high positive loading in PC1. The social psychology of rituals has achieved 100% loading in PC1 signifying a uniform rating among the respondents. This variable is dominating the system in a positive direction. For intergroup processes, the total variance explained in PC1 is relatively weak (79%) compared to the other categories where all the components have high positive loading in PC1 except intergroup bias and prejudice (0.53). This low loading of intergroup bias and prejudice in PC1 is due to the wide divergence of opinion. Trust and intergroup negotiation is showing the highest positive loading (0.995). For group processes, the total variance explained in PC1 is 83% and all the components have very high positive loading in PC1. Collective identities having the maximum positive loading have a dominant influence on this variable. However, the results obtained from the second stage of PCA (based on Table S7.5) clearly indicate discrimination of social processes. It proves the close association between intergroup and interpersonal processes and between intraindividual and intragroup (Table S7.6). The total variance explained at PC1 is more than 90% (Table S7.7) indicating the strength of association among the social processes. Interpersonal and intraindividual processes are dominating within the social system (Fig. 7.9) while group processes are feeble due to existing group

Component Plot

0.9

Component 2

0.6

Intergroup

0.3

Interpersonal

0.0

Intraindividual

-0.3 Group -0.6 -0.9 -0.9

-0.6

-0.3

0.0

0.3

Component 1

Fig. 7.9 Discrimination of social processes through 2-stage PCA

0.6

0.9

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7 Social Instabilities Induced by Riverbank Erosion

differences. It is clear from Fig. 7.9 that a wider difference is found for group and intergroup processes in the PC2 and thus they are located apart signifying contrast.

7.4

Social Psychological Effects of Bank Erosion Hazard

Social psychology inherently considers the feelings, thoughts, and behaviour of individuals influenced by the actual, imagined and implied presence of others (Allport, 1985). In a more realistic idea, it is the generalized thoughts, feelings, psyche, and behaviour of the individuals or a group developed due to ingroup or outgroup or society-environment interactions that are expressed during social, economic, and political action(s). It is a broad area of psychology where it is the combination of group ego and cognito. In the context of bank erosion hazard, group feelings of “body” space and “mind” space influenced by the perceived and or imagined image of bank erosion victims are intervened with special reference to fear/phobia, stress, and shock. The immediate social psychology that develops at the beginning stage of bank erosion is fear and phobia. Stress and shock also develop but stress and shock persist for a long time even after the bank erosion episode is over. It is difficult to segregate fear from a phobia as they are interlinked. “Phobia involves the experience of persistent fear that is excessive and unreasonable” (Wilson, 2015). The persistence of fear and phobia is very common in the study area. People who have experienced a fear of bank erosion are prone to phobia. When there is a sudden increase in the water level of the river, local people apprehend that bank erosion will occur. In the strict sense, fear/phobia is a pre-erosion phase event while physical and psychological stress is the in-phase event and shock develops in the post-erosion phase. Database gleaned through primary survey grounds that psychological stress and shock dominate in the post-bank period due to the destabilization of society and economy. During hazardous times, people are busy saving their agricultural and household assets. They cannot spare time to think about the future. It is practically wartime vigilance. Apart from this generalized picture, spatial perspective (land loss close to the river bank), and psychological terrain under the gender lens are crucial aspects in the vein of social psychology. In the spatial context, fear/phobia, stress, and shock are the maximum for Rukunpur followed by Ganjadanga (Fig. 7.10). This is obvious due to intense bank erosion in the concerned area. Matiari shows minimum fear, shock, and stress as the households are mainly dependent on a more sustainable non-agricultural economy which has no connection with bank erosion hazards. Gender space is a crucial inquisitive in this regard. The database reveals that fear and phobia are higher for male members than for females. This is due to the direct experience of the males in the field whereas the females can rarely perceive the images because of their busy schedule in household work. It is seldom visited by rural Muslim women for the social barrier. Male members are involved in wartime vigilance of crop harvesting and dumping the crops in household yards even relocating household infrastructure demolishing the earlier one. Physical stress is

7.4

Social Psychological Effects of Bank Erosion Hazard

265

Fear/Phobia 100 80

Shock

a Physical Stress (Pre Bank)

60 40 20 Psychological Stress (PostBank)

0

Physical Stress (Bank) Matiari Akandanga

Psychological Stress (Bank)

Physical Stress (Post-Bank)

Rukunpur Ganjadanga

Psychological Stress (PreBank)

b Fear/Phobia 100 Shock

80 60

Physical Stress (Pre Bank)

40 20 Psychological Stress (Post-Bank)

0

Physical Stress (Bank)

Matiari Psychological Stress (Bank)

Physical Stress (PostBank)

Akandanga Rukunpur

Psychological Stress (Pre- Bank)

Ganjadanga

Fig. 7.10 Social psychology of hazard, (a) Perception of male, (b) Perception of female in percentage. (Sample Size: Matiari 122, Akandanga 19, Rukunpur 62, and Ganjadanga 20)

too much for males before and during bank erosion. However, females have to shoulder the responsibility of in-house property and asset management during the pre-event as well as the post-event phase. Cooking or caring child during this jeopardized social life is too critical. They have to cook under the open sky. Moreover, to avoid this uncertainty and hazard of cooking, females of several households cook unitedly for a week or more. In the post-erosion phase, male members have to work hard for the survival of their families. It has been voiced by the erosion victims that physical stress is much higher in the post-bank erosion phase as they lose regular income from farm operation and hence immediately they do work whatever is available in the nearby areas. At that time they are practically

266

7

Social Instabilities Induced by Riverbank Erosion

Female-Male Differential in CV (%)

10 Relative consistency in perception of Male

8 6

Matiari Akandanga

4

Rukunpur

2

Ganjadanga

0 -2 -4

Relative Consistency in Perception of Female

-6 -8 -10 Fear/Phobia Physical Stress Physical Stress Physical Stress Psychological Psychological Psychological (Pre Bank) (Bank) (Post-Bank) Stress (Pre- Stress (Bank) Stress (PostBank) Bank)

Shock

Fig. 7.11 Relative consistency of males and females in the perception of different variables of social psychology. (Sample Size: Matiari 122, Akandanga 19, Rukunpur 62, and Ganjadanga 20)

beggars and so they cannot be choosers for selected works or familiar works. However, fear is the immediate effect of a horrible event while phobia persists even after the event is over. Psychological stress in the pre-bank erosion phase is much higher for males. Practically, they pass through sleepless nights due to the fear psychology of bank erosion. However, in the post-erosion phase psychological stress is much higher for females. They are always in tension – what to cook, how to feed the family members. Female members have voiced that they have to opt for starvation on one meal a day. The psychological stress of the males is relatively lower because males work outside and do not directly face the severity of the household crisis, especially food preparation and fodder for animals; rather they share their distress with other village mates during the evening time. Concerning shock, both categories experience highlevel trauma due to distress of bank erosion. Primary data reveals that the average rating for both males and females is above 90% (Fig. 7.10). This is due to the absence of shock and an absorbing economy in all the villages except Matiari. Though males and females are comparable in this scenario the score of females often overtakes the scores of the males due to emotional involvement regarding in-house resource management. Survey results depict that perceptions of the males are relatively more persistent than the females regarding fear/phobia and physical stress whereas females exhibit higher consistency in regard to psychological stress and shock (Fig. 7.11).

7.5

Social Psychology of Desire

Desire is a common attribute of every man. It is a state of mind to avail better opportunities, conditions, luxury, etc. Desire is a sense of hope for a person or an object or an outcome of an event. Psychologists often view it as the outcome of a

7.5

Social Psychology of Desire

267

function (Anderson et al., 2015). In the present context, the psychology of desire has been assessed through ingroup or outgroup mentality for interaction vis-à-vis the allocation of resources. The psychology of desire of a normal society greatly differs from a hazard-prone society. A hazard-prone society will behave quite differently from a normal society. Therefore, to carve out the psychological desire of a hazardprone society, a perception survey has been conducted in Rukunpur – a representative of an intense hazard-prone society, and Matiari – a representative of a more or less normal society. Respondents were given 13 pure allocations following the Tajfel matrix (Tables S7.8 and S7.9). Here, there are five broad categories of allocation such as “Ingroup favouritism, maximum joint benefit, outgroup favouritism, minimum joint benefit, and parity.” Ingroup favouritism consists of (a) minimum outgroup benefit, (b) maximum differentiation pro-ingroup, and (c) maximum ingroup profit. Maximum joint benefit considers (a) maximum joint profit pro-ingroup, (b) maximum joint profit pro-parity, and (c) maximum joint profit pro-outgroup. Outgroup favouritism comprised of (a) maximum outgroup profit, (b) maximum differentiation pro-outgroup, (c) minimum ingroup benefit; minimum joint benefit consisted of (a) minimum joint benefit pro-outgroup, (b) minimum joint benefit pro-parity, (c) minimum joint benefit pro-ingroup; and the parity” (Bourhis & Gagnon, 2003). Results show very high ingroup favouritism in general (Fig. 7.12). Maximum differentiation pro-ingroup is found for Matiari whereas an overwhelming response has been observed for the respondents of Rukunpur in favour of maximum joint profit in general and maximum joint profit pro-ingroup in particular. It is inarguably true that the psychology of a normal society is widely different from a hazarded society. Here, ingroup favouritism is a distinctive feature of normal psychology whereas maximum joint profit is the outcome of hazard psychology. It can easily be explained by social psychology. In a normal society, individualism is more profound for survival in a better way maintaining a “superiority gap” but hazard equalizes rich and poor in a distressed condition where maximum joint-profit and ingroup favouritism develop the strength to avoid crisis which is found for Rukunpur. For Rukunpur most of the respondents believe in maximum joint profit pro-ingroup indicating a struggle for existence. Fakir Sk. (male, 91 years) stated that “erosion has wiped out all our belongings. Now fulfilling basic needs is the prime factor for all of us. If we are allocated resources to meet the basic needs, we will never oppose an equal share of resources among the victims. We need justice for all and we have reposed our faith in maximum joint benefit.” This statement clearly proves the principles of sharing and “removal of gap” in a hazardous society. At the end stage of this discussion, it is revealed that the social processes, social psychology, and social behaviour of a society frequented by hazards are widely different from that of a normal society. A fragile economy and stressed livelihood are important markers of a hazard-prone society. Against this obstacle of material life, ingroup social ties, values, and morals become right and associated with social cohesiveness and intense bonds which are not the desire of normal psychology marked with individualism and favouritism.

268

7

36

Social Instabilities Induced by Riverbank Erosion

Points to Ingroup 84

60

108

36

132

11

Points to Outgroup

43

a

60

1

Ingroup Favouritism

Minimum Joint Benefit 84

27

6

Outgroup Favouritism

108

7

Maximum Joint Profit 3 2

1

132

36

36

60

Points to Ingroup 84

108

132

Points to Outgroup

b

2

60 Minimum Joint Benefit 84

Ingroup Favouritism 6

Outgroup Favouritism

3

Maximum Joint Profit

108

47 26

15 132

2

Fig. 7.12 Tajfel Matrix showing the psychology of social desire vis-à-vis distribution of resources in the society, (a) Matiari- a normal society, (b) Rukunpur – a hazard-dominated society Note: numeric values adjacent to Scatter points are the percentage figure of the number of respondents. (Computed from the field data 2015, Sample size 122 for Matiari and 62 for Rukunpur)

7.6

Emic and Etic Perspectives of Bank Erosion

Emic and etic perspectives are of crucial importance in the context of bank erosion of the study area. Emic is the insight of the people from the inside whereas etic is from the outside. Emic perspective is popularly studied in the tradition of the

7.6

Emic and Etic Perspectives of Bank Erosion

269

psychological study of folk beliefs (Morris et al., 1999) in cultural anthropology to understand the culture from the native point of view (Malinowski, 1922) whereas the etic perspective considers the tradition of behavioural psychology (Skinner, 1938). It emphasizes cultural practices in relation to antecedent factors such as economic or ecological conditions that are not under the purview of cultural insiders (Harris, 1979). Here it concerns the view of the victims and non-victims of the surrounding areas or relatives of the victims who are not victimized. Being affected by hazards, the way the victims perceive themselves and the perceptions of non-victims (outsiders) about the victims are scrutinized here. Emic perspectives have been depicted by the responses of the women, economic migrants, and permanent migrants of the study areas while etic perspectives have been exemplified in terms of the views of the teachers who are engaged in teaching in schools in the hazard-prone areas but coming from outside as well as outside people and the relatives of the victims residing outside hazard affected zone.

7.6.1

Perception of Women

The psychology of the women victims (emic) has been assessed with the help of the mean rating of some selected parameters using a questionnaire (Table S7.10). When asked about the shifting of their residence, most of the women are in favour of staying at their native places (present household) and not eager to go to their parent’s home because in a patriarchal society it goes against the norms. Regarding marriage, women in Matiari are satisfied with the economic conditions of in-laws’ houses, while most of the women in Rukunpur opined that it would have been better if not married here (Fig. 7.13). Such a response is natural due to the prevalence of hazards

Involvement in works other than household Joint cooking

100

Matiari Involvement in agriculture

Rukunpur

80 Reloacting towards parents home

60

Member of SHG

40 Change of residence

20

Discussion about erosion in spare time

0 Discussion the issue of resettleing elsewhere

Reduction of enjoyment during festivals

Study of the children from maternal uncles home

Happy with location of in- laws

Facing problems in searching grooms

Scaring of a new bride Facing problems in searching bride

Fig. 7.13 Perception of the women in relation to crisis and options in the context of bank erosion in percentage. (Sample size: Matiari 122, Rukunpur 62)

270

7 Social Instabilities Induced by Riverbank Erosion

in the study area which was not experienced by them in their parent’s houses. Even in searching for a bride or a groom for their kids, the parents of Rukunpur face severe problems. People outside the erosion-prone areas rarely opt to arrange matrimonial relations with the families of hazard-prone areas, with an apprehension that they have to shoulder extra responsibilities of the relatives. Females who have come to this area from outside after marriage are more worried about bank erosion. In most cases, wives believe that by ill fate they are facing the hazard and hence advise their husbands to leave this hazard-prone area to get rid of bank erosion. This is the real scenario in Rukunpur which is not found in Matiari for its more sustainable non-agricultural economy. Regarding enjoyment during the festive time, most of the women of Rukunpur have voiced that enjoyment has been reduced drastically. However, people of the Nichupara, a more victimized group in Matiari, have raised their voices diametrically opposite to the mainstream people of Matiari. In Rukunpur the so-called festivals have almost been withered away by the shock of bank erosion. Manju Bibi (female, 36) voiced: “Male members of the family can enjoy throughout the year in different spheres of life outside the family boundary. We (females) used to enjoy the festive mood only 2 or 3 times before land loss due to bank erosion. But now due to depressed economic conditions, enjoyment has been blurred due to the almost complete absence of those festivals. Now we are virtually devoid of the festive mood of any kind.” In relation to the study of the children residing at maternal uncle’s house, women both in the Matiari and Rukunpur have assigned a very poor rating because in Matiari they do not want to go to maternal uncle’s house as most of the families are flourishing compared to their relatives; for Rukunpur maternal uncle’s household economy is not in a state to accommodate those children. Regarding the involvement of women in wage-earning, the score of Rukunpur overrides Matiari. Most of the female members in Rukunpur are involved either in tant (cottage weaving) or bidi (cigar) binding works for the survival of their families while in Matiari only a few have to shoulder the responsibility of wage earnings; most of the families are well off. In Rukunpur nearly 60% of women are engaged in self-help groups (SHGs). This is an opportunity for sustaining their families by taking a loan from cooperatives for some household developing activities whereas in Matiari only 30% of women are attached within SHGs. Barring the wage-earning and SHG involvement, they often cooperate with their families regarding farm operations in the field sometimes. Due to the severity of bank erosion in Rukunpur joint cooking mostly occurs during peak events. Being almost penniless, they are forced to pile up their cooking items and share the food. During their spare time, most of the women in Rukunpur discuss the issue of bank erosion while in Matiari it is no more significant.

7.6

Emic and Etic Perspectives of Bank Erosion

7.6.2

271

Perception of Economic Migrants

Perception of economic migrants has been assessed with nine different aspects of the vulnerability using a questionnaire (Table S7.11). Out of the total economic migrants, more than 80% of respondents have moved outside West Bengal. This indicates that the work environment and opportunities outside West Bengal are far better than within West Bengal. Economic migrants who once had a typical agrarian attachment are now mostly involved in the informal non-agricultural sectors, especially industry and construction works. In Matiari some economic migrants are involved in different government jobs across India. People often move outside Bengal for two main reasons – first is the sustainability of income, while perenniality of income is the other one. Survey results indicate that more than 90% of respondents in Rukunpur go outside West Bengal for sustainable, remunerative income while the response in Matiari in this regard is slightly lower for its own economic magnet. Regarding the perenniality of income respondents in Rukunpur have overwhelmingly positive responses while it is low for Matiari as the in-situ working environment of the two places is different (Fig. 7.14). In this section an attempt has been made to analyse the psychological outlook of the economic migrants, staying far away from their permanent residence. Regarding bank erosion, nearly 80% of respondents in Rukunpur are anxious about the impending danger of bank erosion, while a significant number of respondents in Matiari have revealed very little or no anxiety about the erosion due to their non-land-based economy. Response regarding coming home all of a sudden after a huge erosion episode is poor for both Rukunpur and Matiari as only a few people can be able to return home. Few workers have lost

Work place outside West Bengal

100 Loss of job due to sudden visit to home after erosion

80

Working outside for survival of the family

60 40 Sudden come to home after huge erosion

20

Working in industrial or business firm

0

Planning to shift your family to a better location

Concern about erosion while staying outside

Sustainability of outside income compared to local

Working throughout the year

Matiari Rukunpur

Fig. 7.14 Perception of the economic migrant in relation to crisis and options in the context of bank erosion in percentage. (Sample Size: Matiari 41, Rukunpur 62)

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7 Social Instabilities Induced by Riverbank Erosion

their jobs under such circumstances as they did it without the consent of the authority. Finally, it has been observed that most of the migrants in Rukunpur go outside for the survival of their families, while it is very low in Matiari.

7.6.3

Perception of Permanent Migrants

Relatively landed family with little bit better economic conditions in these bank erosion-prone areas has shifted permanently to nearby village areas close to the road, rural service centres, or in some cities being afraid of recurrent bank erosion. They have both emic and etic perspectives. Therefore, those people are taken into consideration to judge the hazardous space and present normal social life. Perception of these permanent migrants has been explored with the help of nine variables in relation to the crisis faced by the migrants in the new location using a questionnaire (Table S7.12). Practically, migrants community from Matiari and Rukunpur (those two extremes are taken into consideration) have explicitly faced more expensive livelihoods in new locations because in a new location they have to buy every bit of their livelihood requirement. Earlier they would cultivate cereal crops, vegetables, and fruits in and around their household, and fish from the adjacent river and water bodies. Nearly 230 households in Matiari have shifted permanently to a new location. In the very recent past, all those households were located in Nichupara (Bablari Para) of Matiari mouza close to the river bank. Similarly, nearly 120 households from Bangalpara of Rukunpur have shifted their permanent residence to the nearby rurban and urban locations of Muragachha, Dhubulia, Tatla, Belpukur, and Krishnanagar city. In the new locations, emigrants from Rukunpur are relatively experiencing a better quality of livelihood than that of the Matiari mouza. For Matiari relocation is confined to the same mouza. But for Rukunpur permanent migrants have had their destination outside the mouza where environmental refugees enjoy better facilities for two reasons- in urban and semi-urban set-ups, the native and non-native identity is diluted for which migrants can easily adjust to the new locations, and secondly, due to the demand of labour they can earn almost regularly. Local people never refuse environmental refugees. Both for financial and psychological considerations, migrants from Rukunpur are well-adjusted in the new locations. Kith and kin bond between the relatives have been affected to some extent due to this migration. Permanent migrants often visit their relatives in erosion-prone areas, and similarly, the relatives from the erosion-prone areas come to the displaced families. But the urge for permanent migrants is more. Nearly 80% of migrants opined in favour of visiting relatives in erosion-prone areas due to their place attachment (Fig. 7.15). Disaster has united families for which mutual bond has increased. All the migrants agreed that they prefer to move in groups in search of better alternatives. In the new location, one of the major problems is securing land for habitation. The

7.6

Emic and Etic Perspectives of Bank Erosion

273

Expensiveness of Livelihood in new location 100 Residence on your own land

80

Treatment of the local people to you

60 40 Problem in finding land here

20

Finacial help from the local people

0

Coming in new location in group Visit of the relatives from erosion area to you

Psychological help from the local people

Visit to relatives in erosion prone area

Matiari Rukunpur

Fig. 7.15 Perception of the permanent migrant in relation to crisis and options in the context of bank erosion in percentages. (Sample Size: Matiari 10, Rukunpur 17)

problem is more intense for the migrants from Matiari as the land value in the new location is high enough compared to their earlier residence. Hence they used to settle along the banks of river Bhagirathi in relatively better locations that are not affected by bank erosion.

7.6.4

Perception of School Teachers Coming from Outside (Etic Perspective)

Teachers are the builders of the nations and possess profound ethical values and morality that are transmitted to the students. For such qualities, they extend help to people in distress either in cash or in kind or suitable advice. The subsequent focus explores gleaning the etic perspective of the school teachers (from outside) to the erosion victims using a questionnaire (Table S7.13). Regarding the village infrastructure of Rukunpur, nearly all the teachers have opined in favour of the very poor village infrastructure including roads, schools, and health services. However, for Matiari most of the teachers are satisfied with the present infrastructure. The majority of the teachers serving Rukunpur have plans to take transfer from this area to another area due to the prevalence of poorer infrastructure; it is not the reality for Matiari for better condition (Fig. 7.16). The issue of bank erosion is very significant for both villages, but the perception of teachers differs due to variable impact. It is quite natural as the issue of bank erosion is a life and death question for Rukunpur while for Matiari the issue is not so severe due to the prosperity of the economy and society by dint of the brass metal industry. Considering the mitigation programme against

274

7

Advising children not to disturb parents for their personal demands

Social Instabilities Induced by Riverbank Erosion

Dissatisfaction with villge Infrastructure 100 80

Matiari Planning to move outside for poor infrastructure

Rukunpur

60 Fall of attendance during erosion episode

40 20

Concern about bank erosion problems of the village

0 Undertaking any erosion mitigation programme

Interest to know about the erosion condition

Help the students of the victimized family by cash or kind

Help the villagers psychologically Help the villagers

Fig. 7.16 Perception of the teachers in relation to crisis and options in the context of bank erosion in percentage. (Sample Size: Matiari 21, Rukunpur 10)

bank erosion, teachers rarely care for it in Matiari while prompt initiatives among the teachers have been observed for Rukunpur. Interestingly, cooperation of the teachers either in cash or kind for students of the victim families is observed significantly both in Matiari and Rukunpur. This is certainly due to their ethical and moral consideration. In their opinion, if a student seeks help from them, they extend kind cooperation either psychologically or financially. More often teachers extend help to the poor villagers, especially in Rukunpur either by cash or in kind. They are very enthusiastic to know about the present status of the bank erosion. They always are in touch with the villagers and extend psychological support. They advise the kids not to disturb their parents for their own personal demands. Another interesting scenario marked by the teachers is that the attendance rate falls significantly during the hazard time. This has been distinctly observed for Rukunpur in 1994, 1996, and 2004 from the attendance register.

7.6.5

Perception of Outside People and Relatives (Etic Perspective)

As the outsiders have no such wide direct experience with the hazard, the perceptions of the outsiders have been evaluated with the help of seven important indicators using a questionnaire (Table S7.14). The same indicators are considered to evaluate the impacts of the kith and kin’s feeling about the victims. This is surely a typical type of the etic perspective. The question was asked whether the outside people welcome the victims after erosion. Most of the outside people responded in a

7.6

Emic and Etic Perspectives of Bank Erosion

275

Welcoming the people coming in your area after erosion 100 Trust about victims like your other neighbours

80

Matiari Rukunpur

Helping the victims financially

60 40 20 0

Respecting the victims like your other neighbours

Helping the victims psychologically

Beneficial effects in your area after coming of the people from outside

Adverse effects in your area after coming of the people from outside

Fig. 7.17 Perception of the outside people in relation to crisis and options in the context of bank erosion in percentage. (Sample Size: Matiari 40, Rukunpur 40)

Welcoming the people coming in your area after erosion 100 Trust about victims like your other neighbours

80 60

Matiari Rukunpur Helping the victims financially

40 20 0 Respecting the victims like your other neighbours

Adverse effects in your area after coming of the people from outside

Helping the victims psychologically

Beneficial effects in your area after coming of the people from outside

Fig. 7.18 Perception of the relatives in relation to crisis and options in the context of bank erosion in percentage. (Sample Size: Matiari 21, Rukunpur 21)

negative sense both for Matiari and Rukunpur but the rating of a few parameters is quite high for the relatives due to their kith and kin bond (Figs. 7.17 and 7.18). Outside people are eager to help more psychologically than financially while the relatives help the victims both financially and psychologically for the same reason. The strength of financial help is relatively higher for Matiari than Rukunpur for the economic soundness of Matiari. Considering the perspective of the beneficial effects

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7 Social Instabilities Induced by Riverbank Erosion

of immigrants in the destination area, both the outside people and the relatives have welcomed them. Outside people think that migrants can easily be employed as labourers in the brass metal industry of Matiari while migrants from Rukunpur prefer the weaving sector. In other words, migrants provide a pool of active and energetic labour for different works. Relatives always help them to get work due to social bonds. However, outside people consider them as cheap and guaranteed labour sources as they always are keen on wage-earning to sustain their families. They have the image that immigrants are seldom a liability to the economy. But some outside people, though few in numbers, consider them as baneful to their economy because they are grabbing their jobs and snatching their daily income. Considering respect and trust, a higher rating is observed for relatives than for outside people. But a significant proportion of outside people do not have either respect or trust and consider them as refugees who cannot be trusted for their conditional crisis. It is crucial to mention that riverbank erosion is directly related to social processes and etic and emic perspectives. However, another aspect of riverbank erosion is closely associated with the development of the chars in the fluvial systems and its impact on social processes which is discussed in the following section.

7.7 7.7.1

Emergence of Charland and Critical Social Process Backdrop and Rationale

Erosion-deposition sequence or the pool-riffle sequence within a channel is the natural process due to changing morphogenic variables of a fluvial system. Char (initially mid-channel bar) is the response to the deposition of sediment on the river bed. The evolution of chars amidst the river Bhagirathi has a relation with the social fabric of the villagers on the two opposite banks of the river. Survey results indicate that there is operating social fission (bipolar society) between the two groups residing on the opposite banks of the river and social fusion (agglomerated society) within the respective group members after the emergence of char within the river. The terms fusion and fission are derived from nuclear physics. In social and behavioural sciences, these terms are not at all new. After surfacing the quantitative revolution in the 1960s, the terms have become popular and well-known in social physics. However, in modern human society, the nature of fusion-fission is quite different from those of primate animals (Ramos-Fernández et al., 2006; Archie et al., 2006; Smith et al., 2007). They merge together for their common interest and split for the conflict of interest. If nature strikes human society or a society faces a hazard, there appear two types of relationship – the first one is social fusion among similar interest groups and or individuals and the other is the social fission among the conflicting interest groups and or individuals. Here, critical social dynamics are explored in the context of the emergence of char (mid-channel bar) as a factor of social fusion and or fission between the groups residing on the two opposite banks of the river Bhagirathi.

7.7

Emergence of Charland and Critical Social Process

7.7.2

277

Study Design

To explore the perspectives of social fusion and fission, four major chars near (1) Matiari, (2) Char Chakundi, (3) Dampal and (4) Rukunpur located amidst the Bhagirathi River were selected (Fig. 7.19). For each char, 50 respondents dependent on the char were chosen purposively from both banks of the river. Out of the four chars, three (Matiari, Char Chakundi and Dampal ) had the point bar location while the another char (Rukunpur) had the mid-channel bar condition. Moreover, another minor char near Rukunpur had point bar condition. This typical design helped us to assess the social turmoil situation and peaceful co-existence indicating a stage based on evolution in the wake of the transformation of the chars from mid-location to the bank attached. The shifting of channel bars was detected using Maps (Survey of India Topographical Map, 1927, 1974), Google Earth Image, 2020. Following Islam and Das (2015), unit channel bar location is measured using Eq. 7.2: Lb1 =

wd ðW l - W r Þ ± W b þ W W

ð7:2Þ

This measure is the ratio of the width difference of the channel and bar (Wd) and total channel width (W ). For defining Wd, the width of the left channel with reference to the bar centroid (Wl) and the width of the right channel with reference to the bar centroid (Wr) and total bar width (Wb) are calculated. For this index, value “0” indicates the perfect mid-channel bar, value “1” indicates the perfect bank-attached bar, and values in between >0 and < 1 indicate the transitional types. The “+” signs indicate the right bank orientation of the unit channel bar and the “–” sign indicates the left bank orientation of the bar. To measure the social fusion and fission, a questionnaire (Table S7.15) survey was conducted in 2020 based on 13 standardized socio-economic parameters (1. caste, 2. religion, 3. language, 4. education, 5. health, 6. age, 7. sex, 8. marriage, 9. mutual adjustment and trust, 10. economic status/occupation, 11. party politics, 12. kin and kith relation, and 13. ethnicity) during three phases of bar formation (1. Before char formation, 2. Mid-channel bar condition, 3. Side attached bar condition) following Sarkar et al. (2017). The measurement of the nature of fusion and fission was done between two conditions of groupings – 1. within the group members residing on the same side of the river, 2. between the group members residing on the opposite side of the river based on the 10-point rating scale (Table S7.10).

7.7.3

Study Findings and Analysis

7.7.3.1

Evolution of Mid-Channel Bar into the Bank-Attached Bar

In a meandering river, mid-channel bars are very unstable and change their position due to the deflection of hydrological flow over time. Mid-channel bars that began as

278

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Social Instabilities Induced by Riverbank Erosion

Fig. 7.19 Location of the study chars of the Bhagirathi River

7.7

Emergence of Charland and Critical Social Process

279

bar amidst the river channel gradually come closer to the either left bank or right bank and are ultimately attached to a bank. So, the episode of the evolution of mid-channel bars is not just growth and elongation but the conversion of mid-channel bars into point bars. This conversion process is attributable to the shifting locations of the primary and secondary flow of the river. The bank along which lesser current or secondary flow dominates gets the attached bar or point bar at the end of the evolutionary process. In the context of the study bars, for the 1927 toposheets, it is clear that Matiari char (Lb1 -0.49), and Dampal char (Lb1 -0.71) depict mid-channel bars and no bar for Char Chakundi and Rukunpur. In 1974, Matiari char (Lb1 of 1) exhibits right bank attached condition and Dampal char (Lb1 of 0.82) tends to be right bank oriented. However, Char Chakundi (Lb1 of -0.47) appears as a mid-channel bar with inclination towards left bank. Interestingly, Rukunpur char still did not appear in 1974, however, Bhagirathi River was impregnated with an embroynic char during that period and Rukunpur char appeared for the first time in 1991 (Fig. 7.20). In 2020, main Matiari char (Lb1 of 1) is right bank attached with 4 minor mid-channel bars developed in group (Fig. 7.20). Char Chakundi (Lb1 of -1) and Dampal char (Lb1 of -1) are left bank attached during 2020. However, major char of Rukunpur depicts mid-channel condition (Lb1of -0.60) with left bank inclination and one minor char of Rukunpur (Lb1 of -1) is left bank attached (Fig. 7.20).

7.7.3.2

Evolution of Char and Social Instability

When a mid-channel bar emerges from the river bed, social relation gets deviated from the existing one. Those who were enmatic to each other on a particular side of the river earlier now become united to occupy the land on the mid-channel bar. This situation is analogous to nuclear fusion where two or more atomic nuclei collide at a very high speed and join to form a new type of heavier atomic nucleus. The people on the right bank are united irrespective of caste, creed, and religion. Similarly, the people on the left bank are united. Social fission operates in two stages. First, when the mid-channel bar appears, the long-established social relation between the left-bank people and right-bank people gets disturbed. For occupying the char the people on the left bank and right bank are polarized. Consequently, a “bi-polar society” gradually develops and the social distance increases between those people. This creates a fissure in social processes and ultimately social structure. Second, when the mid-channel bar is transformed into a point bar (bank attached bar), those people who are adjacent to the char will have supremacy over the char and the other bank people will leave their demands and voices because it is difficult for those people to occupy the char crossing the whole river. In this stage, inter-group social fission is weakened, however, intragroup fission appears among the individuals of the owner group (having supremacy over the char). Now each and everybody wants his individual supremacy over the land. This process continues for a long and ultimately social conflict within the same

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Social Instabilities Induced by Riverbank Erosion

Fig. 7.20 Transformation of chars in the study area in different time frame

group once consolidated becomes contentious issue for occupying the side-attached bar (Table 7.3). The above theoretical perception regarding social fission, and fusion arising from the conflict of ownership of charland can easily be established for the study area of

7.7

Emergence of Charland and Critical Social Process

281

Table 7.3 Nature of social transformation in relation to char dynamics Stage of evolution I II III

Nature of char Before char formation Emergence of mid-channel bar Conversion of mid-channel bar into bank-attached bar

Between the groups on the opposite banks of the river Normal (standard) Fission Regaining normality

Within the respective group Normal (standard) Fusion Fission

Bhagirathi through primary information. Although the size of the chars is small (less than 6 km2 and even less than 1 km2), the bank erosion victims have lost their land and houses due to severe erosion. Initially, the chars in Bhagirathi appear as midchannel bar. However, most of the chars are away from eroded bank sites due to the presence of primary flow. For the study of Rukunpur (the most vulnerable mouza), the villages of the two sides are Rukunpur (left bank) and Kamalnagar (right bank). Rukunpur is colonized by Muslim people engaged in agriculture whereas Kamalnagar is a Hindu village practicing herding buffaloes and cows. For the religious difference, there is an apparent antagonism between these two villages separated by the river barrier. While the char is developed close to Kamalnagar during 1980s (Fig. 7.20), the Kamalnagar people intended to occupy it because the sand-dominated soil of the mid-channel bars offers grassland lucrative for buffalo herding. On the other hand, the people of Rukunpur attempted to capture it during 1980 and 1990 as most of the people had lost their productive cropping land by bank erosion. They opined that eroded material had formed the char (basically those eroded materials promote char development downstream). People of Kamalnagar put the opinion that as it is close to their bank site they have the right to occupy the char. Both the intra-village people are united to command over char keeping aside their personal or family and caste-related ego and/or conflict. Thus, fusion develops within each village leading to conflict between the two villages. When the Kamalnagar char becomes right bank attached, Rukunpur people left their demand. However, another major char that developed during 1990s as a mid-channel bar (Fig. 7.20), conflict occurred several times within the chars between 1990 and 2010 with violence and attack on each other with traditional arms like bamboo parts, iron rods, cutters, and choppers resulting in the shedding of blood. In this conflict, majority of the land has been occupied by the people of Rukunpur. When, this mid-channel bar approaches towards left bank and one small char is attached to left bank, the inter-village conflict is over. Then, the intra-village conflict has arisen about the demarcation of land within the village. Now the conflict occurs about the boundary of the individual plot as those are readily washed out by peak discharge in monsoon and post-monsoon and erosion of some plots by the primary and secondary flow. Therefore, land demarcation is a critical issue almost every year leading to the fission of village communities. Now, the char is extending towards Rukunpur with accretion on left side while erosion to the site nearby Kamalnagar. Under this consideration, villagers of Kamalnagar are no more interested to occupy it as their

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logic of proximity of char to their bank site is no more valid. Intra-village conflict is not found in Kamalnagar, as they have no intention to divide it (Kamalnagar char) into individual plots, rather they use it as the pasture ground as the common property resource. Similar findings are reported for other chars (Matiari char, Char Chakundi, and Dampal char). Therefore, the study pointed out the social instabilities in this chapter coupled with economic vulnerabilities as depicted in Chap. 6 in the wake of riverbank erosion. The grim socio-economic picture needs attention from the bank planners and stakeholders for appropriate management measures. Coping strategies are thus uttered in the next chapter.

References Allport, G. W. (1985). The historical background of social psychology. In G. Lindzey & E. Aronson (Eds.), The handbook of social psychology. McGraw Hill. Anderson, W. A., & Parker, F. B. (1966). Society. Van Nostrand Co. Anderson, C., et al. (2015). Is the desire for status a fundamental human motive? A review of the empirical literature. Psychological Bulletin., 141, 574. Archie, E. A., Moss, C. J., & Alberts, S. C. (2006). The ties that bind: Genetic relatedness predicts the fission and fusion of social groups in wild African elephants. Proceedings of the Royal Society B: Biological Sciences, 273(1586), 513–522. https://doi.org/10.1098/rspb.2005.3361 Bardis, P. D. (1979). Social interaction and social processes. Social Science, 54(3), 147–167. Bourhis, R., & Gagnon, A. (2003). Social orientations in the minimal group paradigm. In R. Brown & S. Gaertner (Eds.), Blackwell handbook of social psychology: Intergroup processes. Blackwell Publishers Ltd. Brown, R., & Gaertner, S. (2003). Blackwell handbook of social psychology: Intergroup processes. Blackwell Publishers Ltd. Fletcher, G., & Clark, M. (2003). Blackwell handbook of social psychology: Interpersonal processes. Blackwell Publishers Ltd. Harris, M. (1979). Cultural materialism: The struggle for a science of culture. Vintage. Hogg, M. A., & Tindale, S. (2001). Blackwell handbook of social psychology: Group processes. Blackwell Publishers Ltd. Islam, A., & Das, B. C. (2015). Quantitative indices to measure unit channel bar location: A theoretical and empirical study. Ethiopian Journal of Environmental Studies and Management, 8(6), 628–634. Islam, A., & Guchhait, S. K. (2017). Search for social justice for the victims of erosion hazard along the banks of river Bhagirathi by hydraulic control: A case study of West Bengal, India. Environment, Development and Sustainability, 19(2), 433–459. Islam, A., & Guchhait, S. K. (2018). Analysis of social and psychological terrain of bank erosion victims: A study along the Bhagirathi river, West Bengal, India. Chinese Geographical Science, 28(6), 1009–1026. Islam, A., Laskar, N., & Ghosh, P. (2012). An areal variation of fluvial hazard perceptions of various social groups-a perspective from rural West Bengal, India. Indian Streams Research Journal, 2(9), 1–9. Komac, B. (2010, June 7–8). Risk education and natural hazards. CapHaz-Net Risk Communication and Risk Education Workshop. Malinowski, B. (1922). Argonauts of the Western Pacific. Rutledge. Morris, M. W., et al. (1999). View from inside and outside: Integrating emic and etic insights about culture and justice judgment. Academy of Management Review, 24(4), 781–796.

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Ramos-Fernández, G., Boyer, D., & Gómez, V. P. (2006). A complex social structure with fission– fusion properties can emerge from a simple foraging model. Behavioral Ecology and Sociobiology, 60(4), 536–549. Rose, N. (2000). Government and control. The British Journal of Criminology, 40, 321–339. https://doi.org/10.1093/bjc/40.2.321 Sarkar, B., Islam, A., Deb, B. S., & Khatoon, S. (2017). Evolution of mid-channel bars and emergence of social conflicts – A case study of the selected chars of Hooghly River, West Bengal. In Problems and sustainability of surface and groundwater resources in deltaic West Bengal (pp. 181–192). Shivers, L. G. (1949). Gillin and Gillin. Cultural sociology (a revision of an introduction to sociology) (book review). Social Forces, 28(1), 95. Skinner, B. F. (1938). The behaviour of organisms: An experimental analysis. Prentice Hall. Smith, J. E., Memenis, S. K., & Holekamp, K. E. (2007). Rank-related partner choice in the fission– fusion society of the spotted hyena (Crocuta crocuta). Behavioral Ecology and Sociobiology, 61(5), 753–765. https://doi.org/10.1007/s00265-006-0305-y Tesser, A., & Schwarz, N. (2001). Blackwell handbook of social psychology: Intraindividual processes. Blackwell Publishers Ltd. Wilson, F. P. (2015). Never fear – Phobias: Everyone fears something. 13thirty Books.

Part IV

Riverbank Erosion: Management and Futuristic Approach

The last part is the management and future speculation. Here attempts are made to reduce the intensity of bank erosion hazards through structural measures and coping strategies and ultimately future speculation of bank erosion. The vulnerability of the economic and social structure of the bank erosion victims necessitates management. Coping strategies: Towards a resilient society (Chap. 8) elucidates the traditional and alternative approaches for shock absorption. Civil engineering and bio-engineering are frequently used to stabilize river bank erosion. However, for increasing community resilience, social engineering measures such as in-situ and ex-situ processes are prioritized. Future speculation and challenges (Chap. 9) are nothing but the future worrying factors like climate change, sea level rise, and population explosion. These issues are focused on in the context of the Bengal Delta in the final chapter.

Chapter 8

Coping Strategies: Towards a Resilient Society

8.1

Swimming Against the Tide

Before portraying the dimensions of coping strategies, the essence of this attempt to cope can be termed as “swimming against the tide”. In an estuarine area, it is easy to drive the boat along the tide, but it is really difficult to drive against the tide and more often during stormy situations. In a hazard-prone area, people have to struggle during hazards and also in the post-hazard period. It is a struggle for existence initially. But if the hazard is recurrent, people face the struggle but at the same time, they feel that they have to live with the hazard. It is experienced in the recurrent flood in Bangladesh or in the Goghat–Arambag area of the Hooghly district, West Bengal, India. People have learned how to withstand a flood. They gain some experience in how to store food for several days or a month, where to relocate, how to build a house to avoid displacement during flood time, etc. Unless and until the havoc flood ruins the area. The same knowledge is found for the Japanese people in the frequently occurring intense seismic zone of Japan. The almost same logic can be built up for bank erosion people in the GangaBrahmaputra Deltaic zone. If intensive bank erosion occurs in an area, people without such experience face the tragedy more. The situation is swimming against the tide in the stormy situation. The whole community is destabilized losing their land, households, and assets. The threatening aspects of river bank erosion, landslide, and seismic events are different from floods or cyclones due to permanent damage to productive land and residential setup. Initially, bank erosion victims are perplexed, about what to do, and how to survive family, which are common for the other types of hazards. But while it is the question of relocation of settlement and permanent loss of cropping land they face a crisis afterwards. They have to shift their residence, they have to search for alternative occupations in an agrarian economy.

Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/978-3-031-47010-3_8. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Islam, S. K. Guchhait, Riverbank Erosion in the Bengal Delta, Springer Geography, https://doi.org/10.1007/978-3-031-47010-3_8

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This is nothing but swimming against the tide for long hours. If it is recurrent, they perceive that they have to leave this place permanently, and they have to search for an alternative occupation that is not affected by the hazard. And if not possible to relocate at all, alternative economy is the only option to safeguard the family through alternative occupations, and a forceful migration for job opportunities. They not only search for this option individually, but rather they invite village mates to join them to reduce the security and loneliness in a new setup and most profoundly to help others for remittances that will not safeguard individual families but also upgrade the economy of the victims. While such a mental setup is developed, they relocate nearby with a mindset that bank erosion will occur but we have to survive the family by the remittances. This was the experience gained from Rukunpur, Gangadanga, and Akandanga, where they clearly said, “we are now adjusted to this situation, we feel anxiety for a few days, but it is no more distress psychology. We now believe that these are part and parcel of life and livelihood. We have to safeguard the livelihood through in situ and ex-situ income sources.” This was voiced by Nizamuddin Sekh. Now they have acquired the skill and knowledge to swim against the tide. These coping strategies, technical knowledge, along with structural engineering are portrayed to conclude that bank erosion is inevitable, and to live with bank erosion is the better reality.

8.2 8.2.1

Existing Strategies at the Individual and Community Level Individual and Community Initiatives in West Bengal

The Government of India has launched several welfare schemes for which the people of hazard-prone areas along the Bhagirathi River are also benefitted. Under the rural development scheme, the Government of India has initiated various formal programmes like 100-day work through MGNREGA, Indira Awas Yojana, Public Distribution System (Rationing), Credit scheme (Kisan credit card), and agricultural insurance which is common to all needy village people. Some special assistance programmes in the form of bank protection work, provision of temporary shelter, funds for mulberry plantation, and provision of food subsidies have been adopted by the provincial government. Now the effectiveness of the government schemes for mitigating the hazards of bank erosion is analysed. Survey results show a very gloomy picture as all the government schemes except bank protection work contrarily mulberry plantation stumbles to meet the needs of the erosion victims. After the introduction of the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) in 2005, it achieved satisfactory results for rural employment though Nair et al. (2013), Khera (2013), and Saha and Makwana (2011) pointed out the limitations of this project. Primary data suggested that through MGNREGA, respondents’ satisfaction level ranges from 25% to 40% in different study villages and the satisfaction is highly variable as indicated by the

8.2

Existing Strategies at the Individual and Community Level

289

MGNREGA 100 Days Work 100

(a)

80 Mulberry Plantation

60

Indira Awas Yojna

40 20 0 Bank Protection Work

Rationing and Food Subsidy

Matiari Akanadanga Rukunpur

Temporary Shelter

Kisan Credit Ganjadanga

60

(b)

Mean-CV Differential (%)

40 20

Matiari

0 -20

Akanadanga

-40

Rukunpur

-60

Ganjadanga

-80 -100 MGNREGA Indira Awas Rationing Kisan Credit Temporary Bank 100 Days Yojna and Food Shelter Protection Work Subsidy Work

Mulberry Plantation

Fig. 8.1 Satisfaction level of the respondents about Government schemes, (a) mean rating of 100 points, (b) mean-CV differential (Computed from the field data, 2015)

higher coefficient of variation (CV) than mean (Fig. 8.1b). In their opinion, the beneficiaries have never been given 100 days in a year for a five-member family. Employment days vary from 40 to 60 a year in different spatial units. A considerable number of the respondents have raised their voices against transparency. The satisfaction level for Indira Awas Yojna ranges from 20% to 30% only in different villages. Moreover, respondents have put the questions against the implementation of the project for vested interests. For the public distribution system (PDS), the respondents are not at all satisfied. The level of satisfaction ranges from 15% to 30% from one area to another (Fig. 8.1a). However, erosion-induced refugees do not get extra facilities from the PDS which only considers the essential needs of the people as per the above poverty line (APL), below poverty line (BPL), and Antyodaya (people at the bottom of the pyramid) categorization. Unfortunately, real target groups in the erosion-prone area often are deprived of politico-administrative lacking, and several APL families are enjoying Antyodaya Yojna (more rationing

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for the underprivileged people) under PDS. Credit to the farmers for agricultural development is important. That’s why the government has initiated a Kisan credit card. But till now this scheme has not received any significant success and small and marginal farmers face difficulty if agricultural land is not recorded by their names. For so many farmers, it is recorded for their late predecessors. For the homeless people triggered by the bank erosion, government has provided them temporary shelter in a very rare situation. With an eye to vote bank flood victims are generally given shelter in flood camps where flood becomes a hazard in an area. For Akandanga the issue of temporary shelter during erosion is not assessed as there is no erosion-induced homeless. The village-level survey indicates the relative success of the bank protection work and provision of funds for mulberry plantations (Fig. 8.2b). In recent times (2013), bank protection work has got some success along the banks of Bhagirathi near Rukunpur and Matiari (Fig. 8.2a) for which the villagers are not experiencing bank erosion in the respective villages for the last 7 years. Therefore, it is pertinent to mention here that for such villages rather than the expenditure for village road construction under the panchayat system (village-level administration and development in India), it can be diverted to bank protection works. Another scheme gaining importance day by day is the mulberry plantation due to the provision of a room for the nurturing of the cocoon which is normally used for family members. In the Rukunpur village, the respondent’s rating is relatively consistent for bank protection work and mulberry plantation.

8.2.2

Individual and Community Initiatives in Bangladesh

Riverbank erosion is a life and death question for the common people of Bangladesh for centuries. Consequently, land loss, livelihood vulnerability, and crisis are also the obvious outcome of this process as outlined above. Naturally, human has embraced various techniques to protect humans and their welfare from the severity of bank erosion from the very inception of our civilization. Naturally, to better live with the bank erosion they have developed their own mechanism of mitigation at individual and community levels apart from the structural and physical measures. Going through the previous works it is apparent that several techniques are widely adopted by erosion victims to cope with erosion scenarios. First, taking loans (credit) from various NGOs is a commonly observed picture. A study conducted by Hossain (2021) showed that the amount of loan ranges from tk 10,000 to 1,20,000 with an average of Tk 34,500 (Table S8.1). These loans back up the economy for further functioning in the same location without changing their original habitat. Moreover, income diversification from different sources is another dominant trend in Bangladesh. Besides, the agricultural practice, they are engaged in the rearing of some household animals for supporting the family income, especially while the erosion-stricken economy stumbles. The rearing of cows and goats is reported by the Asian Development Bank (2012).

8.2

Existing Strategies at the Individual and Community Level

291

Fig. 8.2 Individual and community initiatives to better live with bank erosion, (a) Bank protection works along the left bank of Bhagirathi near Rukunpur, (b) Mulberry plantations along the left bank of Bhagirathi in Rukunpur. (Source: Field photograph, 2014)

Furthermore, the crisis situation due to bank erosion also leads to school dropouts (Hossain, 2022). By this mechanism, many families shed their economic burden for the time being (Hossain, 2021). Similarly, Chowdhury et al. (2022) demonstrated that most of the victims rely upon less expensive food to curtail their family expenditures. These measures are mostly some kind of in-situ adjustments. However, the severity of erosion results in the ex-situ adjustment of the individual and

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communities. They are of two forms: (1) change of habitat by permanent migration and (2) labour migration. Migration to urban areas by a relatively well-off group is widely noted, however, those who cannot afford to buy land/house are relocated to the disadvantageous chars of the rivers (Mortreux et al., 2018). It has been observed that post-relocation support for settlements is diversified (Table S8.2). However, Paul et al. (2021) found that the major types of locations include land purchased after the most recent relocation (30%) followed by land of relatives (26%) (Table S8.2). Moreover, Ahmed et al. (2021) demonstrated that the victims of the vulnerable chars in Bangladesh have adopted some community-based strategies for combating climate change-related shocks and vulnerability (Table S8.3). Major changes are observed in farming practices. Some of those techniques such as livestock rearing, and off-farm works may also be applicable for the river bank erosion victims. These practices have certainly played a crucial role in the elevation of the victims’ profiles.

8.3

Controlling Measures (Engineering)

Bank erosion as a natural hazard in a complex fluvial system intensified by human activities unfolds complex riverine processes with diversified social impact. The immediate impact is the loss of fertile agricultural land and destruction of residential set-up which subsequently destabilizes the land-based economy mainly agriculture; thus bank erosion transform victims into refugees. The impact is more severe for the GBM delta than in other parts of the world due to the severity of erosion and the high density of the population. To reduce the disaster risk of bank erosion man has embraced various measures starting from very traditional and rudimentary techniques to modern applications of geotextiles (Fig. 8.3). All together strategies can be classified into three types: – (1) structural measures using civil structures like dyking with geotextile (Choudhury & Sanyal, 2013), (2) bio-physical engineering with plants (ICIMOD, 2012), and (3) social engineering through the alternative economy. Community people and government initially undertake structural measures by engineering techniques to stabilize the bank. Such an engineering technique has several problems like extensive cost, alternation of bank ecology, negative process response downstream, etc. (SEPA, 2008). However, presently, bio-physical engineering measures are preferred more from the perspective of riverine ecology and bank stability but the persistency of bio-physical engineering against severe bank erosion is questionable. Keeping in mind about the above limitations, social engineering is considered as the most preferred one as it absorbs the shock of the economy and also strengthens the livelihood of the people adversely affected by bank erosion. Here, a basic understanding is to live with hazards. Social engineering measures the intensities that rivers will oscillate and bank erosion is inevitable but the adjustment to the hazards by the introduction of the alternative economy can reduce the vulnerability to a greater extent; here denying riverine actions and ecology is negated. It welcomes strategy in the form of densification of people and their settlements to safer zones has been adopted by Mamun and Amin (1999) for

8.3

Controlling Measures (Engineering)

293

Fig. 8.3 Structural and non-structural measures of bank erosion. (Based on Parua, 2010)

mitigating river bank erosion disasters in Bangladesh. In this chapter, the pros and cons of all those strategies are revealed collecting primary data from the erosion victims of the sample space along the course of Bhagirathi.

8.3.1

Civil Engineering Measures

8.3.1.1

Major Civil Engineering Structures

Major civil structural measures are taken to mitigate the effects of the river bank erosion. They have been broadly classified into three types of civil measures:(a) hard material protection, (b) barrier across the river, and (c) flow area increase by dredging (Fig. 8.4). (a) Hard material protection: These techniques involve hard materials to protect the bank of the river from erosion events. There are several ways to protect the bank. Two common ways are (1) revetment and (2) brick mattressing. Revetment aims

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Fig. 8.4 Various structural and non-structural techniques used to protect riverbanks from erosion (a) Revetment, (b) Brick mattressing, (c) Groynes, (d) Permeable spur, (e) Dumping geo-bags, (f) Flow area increases by dredging, (g) Wooden piling, (h) Crisscross porcupines. (Based on Islam, 2008)

to protect the eroding or concave bank with erosion-resistant materials such as stone, concrete, etc. Brick mattressing is also a similar technique to revetement with the basic difference that bank protection will be done using bricks (Islam, 2008). (b) Barrier across the river: The bank can also be protected using the barriers across the rivers. Groynes are constructed across the eroding riverbank. Here, the protecting materials (wood, concrete, and stone) are placed transverse to the flow of the rivers. Another popular technique is the permeable spur that is placed perpendicular to the river flow from one bank to another. This type of spur is made of permeable materials like bellies, bamboo, timber, brush, steel, or wire

8.3

Controlling Measures (Engineering)

295

that allow limited passage of water. Naturally, as the water flow is obstructed, some deposition of the materials is noticed. As the velocity of water flow is retarded, the erosion potential also tends to reduce. (c) Other measures: Other popular techniques are also used to protect the riverbank. Some of those techniques are (1) dumping of geobags and (2) flow area expansion. Geobags has some unique properties that can withstand abrasion, tearing, puncturing, and flattening. Naturally, they are conveniently used in bank protection works. Before using the geo bags hanging bag test and pillow test are done to measure their efficiency to protect the bank. Another popular method is flow area expansion by the excavation of bed-deposited materials. This will increase the cubic capacity of the channel and reduce the bank fall rate (Islam, 2008).

8.3.1.2

Civil Engineering in West Bengal

Civil engineering or hard engineering deals with the design, construction, and maintenance of the physical and naturally built environment, including works like roads, bridges, canals, dams, and buildings. To protect the bank of the river Bhagirathi state irrigation department and Farakka Barrage Authority (FBA) have taken different measures viz. long spurs: (i) bull-headed submersible spurs and (ii) revetment of the river. Some spurs are earthen and some wholly of the stone boulder. Recently geo-tubes and geo-textiles are being increasingly used for bank protection of Bhagirathi. Though this type of engineering protects banks substantially in the short run it suffers from different problems. The first problem is the cost. For bank protection, improvement and strengthening of embankment, erosion, renovation of sluices and hydraulic structures and resuscitation of drainage channel it required 170.71 crores for 246 projects during 2010–2011 in West Bengal (Irrigation and Waterways Directorate, 2010, 2011). The second problem is disharmonious ecology and ecosystem. A perception survey among the fishermen proves this very clearly. In other words, nearly all respondents opined that the quantity, quality, and variety of fish catches have diminished substantially. Similar results have been reported by Simpson et al. (1982). The third is the negative process response system downstream as the river basin is an integrated system. Hard engineering is point focus solution, i.e., it solves the erosion problem of a specific site taking it as a just isolated entity from the whole fluvial system (Li & Eddleman, 2002). But as the fluvial system is integrated (FISRWG, 1998), bank protection in one place induces erosion either on the opposite bank (antipodal erosion), e.g., erosion of Chandipur opposite to Rukunpur bank protection site (Fig. 8.5a) or downstream. Such is the case of Gadkhali below Mayapur bank protection site, erosion of which is partly triggered by bank protection. This is quite natural and often explained from the perspectives of stream power, sediment budget, and discharge of the river. The fourth is the issue of the unsustainability of physical structure in the long run. Li and Eddleman (2002)

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Fig. 8.5 Futility of bank protection works, (a) near ISKCON Temple, Nabadwip, (b) near Rukunpur

have noted numerous stream bank failures. For river Bhagirathi breaching of embankments has been observed for all the sample bank protection sites viz. Matiari, Rukunpur, and Mayapur (Fig. 8.5b). One of the primary goals of hard engineering is to maintain stable channel geometry (Lane, 1955) which is neither possible nor desirable as bank erosion is integral to the river ecosystem and it promotes succession of riparian vegetation and thereby creates dynamic habitat vital for aquatic plants and animals (Florsheim et al., 2008). The assumption of stable channel geometry lies in steady and uniform flow which is not found in nature (Chow, 1959). Due to ever-changing sediment load and discharge, the river oscillates for its adjustment to morphogenic variables (Leopold & Langbein, 1966; Schumm, 1985). Last but not least is the perspective of environmental ethics and environmental flow. The former believes in the right to life for the ecological elements, e.g., trees, rivers, and archaeological structures, i.e., river as an entity of nature that will exist on its own (Mautner, 2009) not merely for human beings while the latter proposes uninterrupted flow of river without a human intervention like damming or other artificial control (Bunn & Arthington, 2002; Richter & Thomas, 2007).

8.3.1.3

Civil Engineering in Bangladesh

Riverbank erosion in Bangladesh is one of the most severe cases on a global scale (Paul et al., 2020). All the mighty rivers oscillate and engulf a thousand acres of land (both mainland and charland) as already discussed. Naturally, to protect the riverbank many civil engineering measures have already been undertaken in various parts of the country. Some of the massive civil measures are undertaken by the world bank, the national government of Bangladesh, and local administrations. The Bangladesh Water Development Board (BWDB) has taken several attempts to

8.3

Controlling Measures (Engineering)

297

protect the river banks. For example, during 2004–2005, Titporol and Debdanga along the Right Bank of the Jamuna River were embanked, however, in 2005 the monsoonal floods breached the protected sites especially upstream of the revetment (Rahman, 2010). Moreover, the design plan of groynes along the right bank of the Lower Bhadra River at Chandgar in Polder 29, Khulna, Bangladesh was prepared by the BWDB in 2017 for an emergency plan to be prepared before monsoon 2017 (Deltares, 2017). Blue gold, an initiative between the Government of the Netherlands and the Government of Bangladesh proposed the higher penetration depth of the piles for the civil structures (groynes) for bank protection (Blue Gold Program, 2023). Macdonald (2020) mentioned that the construction works of 5 embankments along the left bank of Jamuna in Shajadpur upazila started on February 15, 2018. These embankments intended to protect the resources by reducing the nature of bank erosion while the colossal flood events were also planned to be moderated by these embankments. Islam (2008) mentioned that BWDB constructed embankments along the right bank of the Jamuna River. However, it was subsequently washed away by the flood events and hence the T-shaped groynes were suggested instead of the single groynes. Another mega project by the World Bank in association with the Bangladesh Government targeted 2–3 million people living in the area of potential disaster triggered by the collapse of the Brahmaputra right bank at MathuraparaSariakandi due to flow down the Bangali river channel. This project will also benefit ~125,500 urban people amidst the threat of river bank erosion or chronic flooding at Sirajganj and Sariakandi. Property including 6400 houses and shops, 75 factories, around 9000 traditional dwellings were prevented from the damages in the first 5 years. The study also found that the economic rate of return (ERR) for the project was estimated as 39%, and 45% and 35% for the Sirajganj and SariakandiMathurapara subprojects.

8.3.2

Bio-engineering/Bio-technical Measures

From the close perusal of the works by Gray and Sotir (1996), USDA (1992), Allen and Leech (1997), Schiechtl and Stern (1994), Bentrup (1996), FISRWG (1998), and Landphair and Li (2001), 12 bio-technical stream bank stabilization techniques are recognized viz. (1) live stakes; (2) live fascines; (3) brush layering; (4) branch packing; (5) vegetated geogrids; (6) Live crib wall; (7) joint planting; (8) brush mattress; (9) tree revetment; (10) Root wad; (11) Dormant post-plantings; (12) Coconut fiber rolls. These practices have some advantages over the civil ones viz. eco-friendly if native species are planted, relatively less costly, and longevity of live plants. Gray and Sotir (1996) and Schiechtl and Stern (1994) have shown that biotechnical methods offer an ecological advantage over hard engineering while Parsons (1963) and Schiechtl (1980) have shown the role of biotechnical methods in maintaining and increasing the aesthetic beauty of a stream. Cavaillé et al. (2015) have shown that bio-engineering banks are close to natural banks for functional and taxonomic plant diversity compared to hard-engineered banks. For these types of

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No. of Engineering Structures

120 Civil Engineering Structure

y = 1E-05x6 - 0.0011x5 + 0.041x4 - 0.7433x3 + 5.9683x2 - 8.75x + 5 R² = 1

100 80

BioEngineering Structure

60

Poly. (Civil Engineering Structure)

40 20

y = 4E-06x6 - 0.0004x5 + 0.0154x4 - 0.2703x3 + 2.0723x2 - 5.8833x + 100 R² = 1

0 0

5

10

15 Time ( Years)

20

25

30

Poly. (BioEngineering Structure)

Fig. 8.6 Comparative effectiveness of bio-engineering and civil engineering practices over time (Based on Howell, 1999). It proves that bio-engineering structures are increasing at the expense of civil engineering structures

Fig. 8.7 Evaluation of bio-engineering measures. (a) Natural bank protection with kans grass along the left bank of the Bhagirathi River, (b) Bamboo root penetration deeper into the soil reduces the rate of riverbank erosion along the Bhagirathi near Rukunpur village. It is observed that places without bamboo root penetration have an accelerated rate of bank line shifting. (Source: Field survey, 2014)

attributes, these techniques are on the rise while the civil ones are dwindling day by day. The sixth-order polynomial proves it very clearly (Fig. 8.6). In Bangladesh vetiver grass (Vetiveria zizanioides) is used for slope stabilization along the river. Islam et al. (2013) have found that vetiver plantation has enhanced the safety of the embankment slopes against bank erosion and flood. For Bhagirathi, these techniques have recently been introduced along the banks in Nadia district by government but the assessment of slope stabilization with vetiver is too early to comment. It is pertinent here to mention that some rudimentary techniques using vegetative cover mainly kans (Saccharum spontaneum) grass are in operation by some farmers along the banks of the river (Fig. 8.7a).

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299

It has been proved that kans grass and bamboo have a great sand binding capacity and hence played an important role in bank protection. The root system of the vegetation has a great role to protect banks which has been proved by various scientists (e.g., Styczen & Morgan, 2003; Wu, 1995). But this technique also may not be sustainable in the long run for various reasons viz. selection of unsuitable species (Schiechtl, 1980); large flood washing out root system before stabilizing bank (Allen & Leech, 1997); insufficient rainfall and drought during plant establishment (Schaefer & Naeth, 2000); unsuitability of soil for root penetration and plant growth (Gray & Sotir, 1996); extraction of soil moisture and other hydrologic effects of trees not considered when the bank stabilized (Gray & Sotir, 1996); collapse of structural materials (Gray & Sotir, 1996); inappropriate site preparation, grading, and control of drainage system (Gray & Sotir, 1996); grazing of livestock (Allen & Leech, 1997); infestation by insects (USDA, 1992); disease of the plant (USDA, 1992); river bank with greater flow velocity and emerging turbulent situation (Li & Eddleman, 2002). At some locations near Rukunpur deep and dense root system of bamboo has been engulfed by the river (Fig. 8.7b). This failure is due to flood impulse combined with weak bank material (dominated by a thin upper silty layer and lower sandy layer) (Guchhait et al., 2016). Though bank protection with bio-engineering measures is better in some cases, it cannot ensure complete bank stabilization which is neither possible nor desirable from the perspective of environmental ethics. Thus, alternative social side measures are required which are discussed in the following sections.

8.4

Alternative Mitigation Measures (Social Engineering): Examples from West Bengal and Bangladesh

Through a detailed survey from the sample space along the course of Bhagirathi, it is perceived that the intensity of vulnerability depends upon the nature of society and the level of the economy. Except for Matiari (tier 1), Char-Kashthasali (tier 2), and Sujanpur villages (tier 3) other three villages viz. Rukunpur, Akandanga, and Ganjadanga are deeply affected. Matiari is an exception to their distressed economy as it is based on a non-land-based source of income through the brass metal industry. Most people of this village are not dependent on agriculture. They have a sound economic base which is not at all affected by bank erosion. Char-Kashthasali has experienced a little amount of land loss while no land loss in Sujanpur. Therefore, a non-land-based in-situ production economy can reduce the vulnerability of other mouzas. Most of the government schemes, discussed above, are general in nature and only the bank protection work has some positive check. Therefore, some special government schemes should be launched for erosion-induced environmental refugees. Empirical observation and intensive field study suggest some management strategies for both in-situ and ex-situ economic adjustments. All those alternative strategies explored which is feasible for this area to reduce vulnerability. Out of four

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such alternatives, the first three are in-situ economic adjustment, i.e., strengthening the economy by restructuring the economic base. The fourth alternative is quite different, i.e., ex-situ economic adjustment through labour migration. Victims consider that this is the option for the absence of the other three but in reality, it is more effective to reduce vulnerability. All these are analysed with respective modelling.

8.4.1

In-Situ Models

8.4.1.1

Matiari Model – Non-land-Based Household Manufacturing

Matiari has adopted household manufacturing that runs 2/3 a day (Fig. 8.8a, b). It is the brass metal manufacturing and selling. Its history dates back more than 100 years. Before the introduction of industry, few villagers were engaged in brass metal units of Kolkata. They grew old afterwards and were asked to retire. Returning to their native place – Matiari from Calcutta (now Kolkata), they started making brass utensils in their home. That got a tremendous success as they established market relations owing to their previous experience. Gradually, the household economy sets most reliance on it and agriculture has been neglected. However, around 40 years ago present agrarian economy got a setback due to bank erosion. Revealing the doomed future of the agrarian economy, people adopted the brass metal industry as their principal occupation; with the progress of time, it has become the dominant occupation which is not at all affected by bank erosion. Thereby, the per capita income level and general economic conditions of the people of Matiari have improved substantially with time in spite of losing land to bank erosion. It is now well developed within the villages and also getting prosperity day by day. At present (2014), it has engaged 23 big mahajans (those who are at the apex of the

Fig. 8.8 Brass metal industry in Matiari. (a) Sheet making; (b) shaping brass sheet in finished products. (Source: Field photograph, 2014)

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301

production system supplying raw materials and collecting finished products from small mahajans), 114 small mahajans (those who are under the control of big mahajans in the production chain), 232 “sheet and gala makers” (those who produce brass metal sheet from where utensils can be made), and 4675 artisans (labourers who make the utensils form the gala sheets). Estimate from the collected data in the year 2014 (Tables S8.4–S8.8) shows that the level of profit of each big mahajan is Rs. 5806 per day, for small mahajans profit is Rs. 735 per day, while the profit level for the sheet makers and artisans is Rs. 216 per day and Rs. 184 per day respectively. Matiari is a model that is an example of in-situ adjustment against bank erosion hazards. It has set the right direction in that a non-farm economy can be an alternative. The mode of operation of the Matiari model of the brass metal industry is very simple (Fig. 8.9). The whole production process starting from procurement of raw material to transshipment of finished products is controlled by mahajans although in some cases this mechanism is operated in discrete channels depending upon the availability of capital and size of firms (Marjit & Maiti, 2005). But the most crucial factor for the success of this model is the success of trade through the market link. For other villages, the non-farm economy can get successful unless and until a

Fig. 8.9 Flow diagram of Matiari model for the operation of brass metal industry

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successful market link is established. Small units purchase raw materials from Kolkata and sell the finished product to the mahajans of the villages or some others sell it in the shops of Kolkata. It is interesting to note that despite the active presence of mahajans, the system is satisfactorily run without any dissatisfaction from other workers and also gaining prosperity day by day. This is due to the reciprocal cooperation between mahajans and workers. The mahajans know very well that they are at the apex of the production pyramid, the base of which is constituted by the artisans. If the base collapses the apex will suffer. Mahajans never exploit artisans and artisans are also devoted to them. This is the spirit of sustainability in this industry. If labour-mahajan clash appears, the organization of artisans and union of mahajans solve the problem immediately, normally within 15 days. Long years of production have set a bond between mahajans and artisans. Therefore, the mahajans have affection for the other workers. Interdependency is at the root of such bonds in the context of rural production psychology where social bond mutual trust has enough room apart from economic rationality. Looking at the historical development of occupation of rural India, it can be said that people having more cropping land are devoted to farming, whereas landless people with marginal landholding have gradually engaged in non-land-based occupations like black-smithy, carpentry, clay modelling, etc. The erosion victims of Matiari have developed the brass-metal industry dating back to their grandfather’s generation. By manufacturing and selling brass-metal products, they are able to withstand the severe bank erosion at present. Such a model can really be an example to the erosion victims of another area in the nearby location. Rukunpur is one such village where it can be applied. Proposed estimations (Table 8.1) show that if 10 such units are developed it will benefit at least 13–23 households, considering one labour engaged in such production from each household. This is a minimum production function with the establishment of 10 units having a production per day of only 1.5 tons. If the units are more and the per day production is more than 1.5 tons, it will require more labour, artesian and mahazoni. In the village, 539 marginal households are there who have lost more than 50% of their cropping land. Therefore, at least 2 persons from each household can be gainfully employed provided that the market link for such firm production is established. This market link is really a matter of concern for the sustainability of rural household industries. At present, brass-metal products are facing decreasing demand in society due to the replacement of utensils by steel, aluminium, and plastic. Still, Hindu and Muslim rituals of marriage and rice-giving ceremonies need the essential gift of brass metal (Maiti, 2005). Here larger industrial firms are not competitors. Therefore, the market solely relies on the household industry. The success of this industry in Rukunpur can easily be possible if linked with the Matiari. These two villages are not far away (~35 km). The household industry has already established this market link for at least 3 generations. Therefore, if the mahajans supply their finished product to the traders or mahajans of Matiari with a low profit, it can easily get success.

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303

Table 8.1 Proposed brass metal industry for Rukunpur Total sheet-making units Peak period of production of a single firm during November to May Firm production in lean season from June to October Average production of a single firm per year Average production of a firm per day Average production of 10 firms per day Total number of artisans required Total number of sheet labour and gala labour required for 10 firms Total number of the owner (Mahajans) Total workers required for production (owner+sheet & gala labour +artisans) Total number of households to be benefitted considering two labour from each household Total number of households to be benefitted considering one labours from each household Total number of households in Rukunpur (District Census Handbook, 2001) Total population of Rukunpur (District Census Handbook, 2001) Average size of households in Rukunpur Number of marginal households (having less than 3 bighas land of cropping land) Total number of adversely affected marginal households (who have lost more than 50% of their cropping land)

10 (1.5 ton×168 days) = 252 ton (0.8 ton ×95 days) = 76 ton (252 ton+76 ton) = 328 ton (328 ton/365 days) = 0.892630 ton ((0.892630 ton ×10) × 100)) 8986.30 kg (8926.30 kg./7.345 kg) = 1223 (10 × 9) = 90 10 1323 662 1323 914 4300 4.70 648 539

Based on Islam and Guchhait (2021)

8.4.1.2

Common Property Resource Management

Common property resource management in the rural economy of India and Bangladesh is a means for the livelihood development of the poor and marginal people. Common property resource is available for individual use without individual occupancy (Arnold, 1990). In India, the concept of social forestry was initiated in 1976 by the National Commission on Agriculture. It has brought significant success for the livelihood development of the poor and marginal people around the forest though it has reduced biodiversity. In the study area of Bhagirathi common property resources are available in the form of charland, and palaeochannels. Though most of the chars are grabbed by the riverside people, the sandy chars, not suitable for agriculture still exist as lucrative pasture grounds. Palaeochannels are almost unutilized. Those can be used by the bank erosion victims with suitable management strategies initiated by local self-government. For Bangladesh, most of the larger class is occupied by bank erosion victims or environment refugees of the coastal areas. Still, huge small sandy or sandy silly chars of Tista and Brahmaputra are still

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Fig. 8.10 Hypothesized palaeochannel fishing for Akandanga, (a) Waterbody falling under the jurisdiction of Akandanga, (b) Present situation of the palaeochannel (Note: Channel cut-off area has been considered as palaeochannel area because it has already been neck cut-off and being gradually sedimented. (Source: Field photograph, 2014)

uninhabited. Those can be used for pasture grounds for the prosperity of animal husbandry. Palaeochannels of Tista, Brahmaputra, and Padma can be used for fishing, but Bangladesh is a land of rivers, and fishes are highly available. Still, palaeochannel can be the option for fishing the erosion victims if market demand and supply are in equilibrium. (a) Fishing in Palaeochannels Palaeochannel fishing can be possible for the major rivers under consideration. Due to meandering, all rivers are associated with palaeochannel. Co-operative fishing can be developed by engaging victims. The individual property right is negated as those are the common property resources. This perspective is examined through the model of others (Dandapat & Islam, 2009) and verified. It is highly feasible for this area. For meandering rivers, especially for the middle and lower courses of the large rivers, palaeochannels are common features that are nothing but the left-out course of the rivers or the oxbow lakes. Several palaeochannels are found for the river Bhagirathi around all the mouzas (Fig. 8.10) while most of the charlands

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305

Table 8.2 Annual income, expenditure, and savings of the fisherman household unit

Net rate of profit (per bigha) from each nursery pond Net rate of profit (per bigha) from each rearing pond Net rate of profit (per bigha) from each composite pond Total profit per acre (3 bighas) Average income per household per year (household with 1 acre of pond) Average expenditure (per household per year) Average household level savings per year (10100–9000)

INR at 2002 price level 3600 3400 3100 10,100 10,100

INR at 2012 price level 7311.744 6905.536 6296.224 20513.5 20513.5

9000 1100

18279.36 2234.144

Based on Dandapat and Islam (2009)

are grabbed by the riverside people most of the palaeochannel is the exception to this. These palaeochannels are either underutilized or non-utilized in respect of fishing. Few fishermen are engaged here for their subsistence in Rukunpur and Matiari without any restrictions as these are common properties. Commercial cooperative fishing can be adopted for these palaeochannels with the formation of the fishing cooperative as the palaeochannels are devoid of ownership. While discussing this model, villagers expressed their willingness, provided that the government or the local government will extend financial help. Village cooperatives can take this responsibility. A study conducted by Dandapat and Islam (2009) shows that the net profit per bigha from the nursery pond is INR 7314 (at the 2012 price level); for the rearing of the pond it is INR 6906 and for the composite culture pond the net profit is INR 6296 per year (Table S8.9–S8.11). The total profit from 3 bighas (1 acre) is INR 20,514 annually (Table 8.2). The palaeochannel area available for fishing in and around Akandanga is about 78.44 acres. This is computed through a buffering of 1 km radius from the centre of the mouza. A portion of the palaeochannel is beyond the boundary of the mouza. It is estimated that about 90% of the palaeochannels area falling within the boundary of the mouza while the rest area comes under the surrounding mouzas. If the area is developed into a commercial fishing ground, it will support 89 severely victimized households providing a monthly income of INR 1500 per month (Table 8.3). However, transforming palaeochannels into fishing grounds is associated with some problems (Islam et al., 2022). The first one is the problem of acquisition of palaeochannel area that may be done through the village panchayat involving the fishermen community along with others. The second is the mechanism of running the system while the third is the problem of limited scope. This can be developed with cooperative farming in an area. Its sustainability at a large scale is not questionable unlike the development of the brass metal industry in other villages. Because the demand for fish is very high in West Bengal and fish is imported from Odisha, Maharashtra, and Andhra Pradesh. But sustainable production of fish through well-developed co-operative farming in the common property resource is a critical one but possible.

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Table 8.3 Hypothesized palaeochannel fishing at Akandanga Total area available for fishing from palaeochannel Total profit per acre Total profit per year from the available fishing area (78.44 acres) Monthly profit from the available fishing area Total number of marginal households (having less than one acre of cropping land) Total number of adversely affected marginal households in the area (who have lost more than 50% of their cropping land) Number of marginal households to be supported with the additional income from palaeochannel fishing (INR 1500 per capita per month)

78.44 acre INR 20513.5 INR 20513.5 × 78.44 = 1,609,079 INR 1,609,079/12 = 134089.9 294 122 134089.9/1500 = 89

Based on Islam and Guchhait (2021)

(b) Animal Husbandry Animal husbandry is a lucrative option in the rural economy today where poultry farming, duckary, and goat farming are the more familiar. The present context is something different. Here, the rearing of goats, cows, and buffalo is the consideration for the availability of pasture land. For the study area of Bhagirathi, chars are the rich pasture ground of goats, cows, and buffaloes. The government or local selfgovernment has to encourage the erosion victims for the rearing of goats cows and buffaloes. They have to offer kids or cuffs as they are victims of bank erosion. There should be some ready provision in the budget for the hazard victims for such help. Chandy (2012) has successfully upheld the benefit of such animal husbandry in the Indian context, where he has taken goat rearing. He has shown that the profit per goat per year is 523 (Table S8.12). If each victimized family has 20 goats (19 sea goats and a buck) the annual profits become 20 × 523 = Rs. 10,460 per year, i.e., nearly Rs. 1000/month. In the present situation, it is more lucrative. In India, a mature goat is sold in the market at a minimum price of Rs. 8000 – 10,000. If a family has 12 such goats, and two of them have the probability of facing death by disease, selling 10 goats to a family can income of Rs. 65,000 to 80,0000 minimum. Of course, goat faces death through diseases. Therefore, proper care and vaccination facilities by the government are needed in this regard. In the context of Bangladesh, rearing cattle on the chars of Tista and Brahmaputra may be profitable because of the demand for beef for the majority of the Muslim population.

8.4.1.3

Development of Indigenous Small-Scale and Cottage Industry

Few indigenous small-scale and cottage industries could be established for in-situ economic adjustment. Some small-scale industries tant, and bidi-binding are observed in the study region (Fig. 8.11a, b) that extend minimum support for the livelihood of the bank erosion victims. It was also noted that environmental refugees

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307

Fig. 8.11 Small scale and cottage industry, (a) Tant, (b) Bidi-binding in Rukunpur. (Source: Field photograph, 2014)

occupied any livelihood option for stabilizing their economic base because “beggars cannot be choosers”. Apart from this, small earnings from tant or bidi-binding not only empower women but also signify the role of women and the disabled to stabilize their livelihood. (a) Tant (Handloom) Nadia is famous for cottage weaving (Tant). It is also popular in Bangladesh, though power loom and garment manufacturing have got tremendous prosperity within the last two decades. In the study area of Bhagirathi, tant and weaving is a traditional cottage industry. In the villages of Rukunpur, Char-Kashthasali, and Ganjadanga, most of the erosion victim families have at least one handloom unit and both male and female members are engaged in it. Women, after the completion of a household chore, start weaving from afternoon to evening. Males are engaged in preparing a spinning role, shuttle, or marketing the product. In most cases, mahajans supply the raw materials and male and female members are engaged in weaving. It is interesting to note that artisans under mahajans have monthly profit level of only INR 1050 whereas independent artisans’ profit level is INR 2250 in the year 2014. So, to make the artisans independent, financial support is required for setting up of tant by the government. The cost for setting up of a tant is INR 5350 (Tables S8.13– S8.15). The earnings range from INR 2500 to 4000/month and it becomes more during the festive seasons and the family members are engaged in weaving for the whole day on a shifting basis (Table 8.4). (b) Bidi-binding In the study area, bidi-binding is another option for the victim households. This work is mainly done by the female members for in-situ adjustment of the household economy. This is a very small amount of earning which is a significant support to the household economy but it empowers the women in society. Currently, a worker can earn INR 2376 per month in the study area (Table S8.16). But its wider feasibility is a question due to market demand and market link and some health problems. At

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Table 8.4 Number of households to be supported by tant industry in the study area

Name of the village Akandanga Rukunpur Ganjadanga CharKashthasali

Total households as per 2001 census 637 914 388 721

No. of households having below 3 bigha land (H1) 421 648 322 469

No. of households having below 3 bigha land (after losing 50% or more land by bank erosion) (H2) 369 539 298 144

Total amount of loan to be sanctioned (as per 40:40: 20 formula) For H1 900,940 1,386,720 689,080 1,003,660

For H2 789,660 1,153,460 637,720 308,160

Computed by the authors (2014) Table 8.5 Number of households to be supported by bidi binding in the study area

Name of the village Akandanga Rukunpur Ganjadanga CharKashthasali

Total households as per 2001 census 637 914 388 721

Total females as per 2001 census 1495 2094 909 1690

No. of households having below 3 bigha land 421 648 322 469

No. of females 421 648 322 469

% of Females to be employed 28.16 30.95 35.42 27.75

Computed by the authors (2014)

present, only a few people (2–3%) are involved in the study area. This work needs no investment at all for the workers. If properly developed, bidi biding can support quite a significant number of households involving 27–35% females in the study area (Table 8.5), if the market link is properly established. The development of small-scale and cottage industries like tant and bidi binding industry may absorb shock for the time being but firm stability in the economy cannot be possible through this mechanism. Nowadays demand for tant saree is increasing among middle-class women but still, it is facing kin competition with mill saree.

8.4.2

Ex-Situ Models

8.4.2.1

Model of Labour Migration

Labour migration is a mode of ex-situ economic adjustment. In all the surveyed villages, a significant portion of labourers have migrated to other districts, states, or beyond the nations for stabilizing their economy (Table S8.17). The percentage of labour migration varies from 33 to 44 in the surveyed villages. Most of the migrants

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309

Fig. 8.12 Nature of labour migration in the study area. (Based on Islam & Guchhait, 2021)

travel outside Bengal but within India. A quite significant portion of migrants in Rukunpur have crossed the national boundary. Within the locality wage level is very low as well as uncertain; while abroad it is high enough but it requires connection and includes barriers of passport for international migration. Thus the volume of the migration in the study area depends on three factors viz. distance, wage, and connections (Fig. 8.12).

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If labour force is developed with skills viz. construction, painting, and jewellry, the demand for those labour will not only increase but the wage level will also be enhanced in different spheres of labour market. As mentioned earlier, remittances from labour migration play a significant role in the erosion of victim families. Besides strengthening the families, a rural-urban linkage will be established that may improve the socio-economic outlook of an area (Chaudhuri, 1993). The monthly net income levels of the labour migrants in 2014 are Rs. 1500–1800, Rs. 4700–5800, and more than Rs. 15,000 for local, national and international migration respectively (Table S8.17). Naturally, if at least one member from a marginalized household (below 3 bighas land) opts for national or international migration about 421 households of Akandanga, 648 of Rukunpur, 322 of Ganjadanga and 469 of Char-Kashthasali may be benefitted.

8.4.2.2

Densification of Settlement

Bank erosion, char development, and dilluviation of chars are well documented in the history of Bangladesh. As Bangladesh is a land of active and mighty rivers that criss-crossed the entire nation from various directional geometry. Rivers oscillate as a natural trend from one position to another. Quite naturally, bank erosion, land grabbing, and environmental refugees are common here. Many attempts are made to better live with bank erosion as already discussed. But the most crucial issue is the availability of land in safer places because of the swing of the mighty rivers. One of the finest ideas was promoted by Mamun and Amin (1999) in their classical attempt to densify the settlements to better live with bank erosion. They considered Hizla thana located in the Barisal district of Bangladesh which was once prosperous economically but now most of it has been eroded by bank erosion. Now, this area has been impoverished and people are marinating low standards of living. They classified the areas of the Hizla district into two zones: (1) safer zone and (2) vulnerable zone (Fig. 8.13a, b). It is observed that most of the areas of the district are vulnerable and a very minimum percentage of area is located in the safer place. This was the major contentious point of thought on how to accommodate a huge number of people within a small area. This gave birth to the notion of densification of settlement (Fig. 8.14a, b). They conducted an in-depth survey where they provided three options to the respondents: (1) staying in the vulnerable zone for farming purposes, (2) shifting to the nearest safer zone from where they can continue cultivation, and (3) shifting to a completely new distant location for non-farming jobs. They found the highest positive response for option 2 which inspired them to hypothesize that densification would be possible with the relocation of vulnerable settlements to a close destination from where farmers can cultivate using good inland waterway communication through boats. They also advocated that if could be more practical if occupational diversification could be developed and human resource development could be done in a better way. However, they warned that this densification would be required only if recurrent and severe bank erosion is recorded in the recent past. It

8.4 Alternative Mitigation Measures (Social Engineering). . .

311

Fig. 8.13 Densification of settlements as an adaptational strategy to better live in erosion-prone areas of Bangladesh, (a) Location of Hizla Thana with safer and vulnerable location, (b) Directional geometry of the densification process. The pinkish arrows indicate the movement of settlements to safer locations from the vulnerable zone. (Based on Mamun & Amin, 1999)

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Fig. 8.14 Densification model and its framework. (a) Conceptual framework of the densification model, (b) Pathways to implementing the model. Note: Colour arrows do not convey any special meaning. This is only for graphical visualization. (Based on Mamun & Amin, 1999)

References

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could not be applied in all locations because it has certain limitations such as high density and chaotic situation, pressure on land and natural resources by a cluster of population, the problem of deforestation, social resistance, in-migration, land grabbing, and accidents. However, there are many situations like Hizla thana where this model could be applied with the diagnostic survey. The principle of densification may be utilized in any other similar regions of the Bengal Delta with proper rationale, justification, EIA, and suitability of the settlement planning of the concerned region.

8.5

Concluding Notes

In this section, coping strategy is the core idea where the idea has been used in the name of “swing against the tide”, which means how the erosion victims can get rid of this problem. Together three types of measures have been taken into consideration: in-situ strategy, ex-situ strategy, and support by the government. In-situ strategy is once again divided into two physical engineering (civil and bio-engineering) and social engineering. All those are associated with government support. Physical engineering is an immediate measure but it promotes erosion downstream and its lifespan is questionable along with its negative impact on ecology. Therefore, social engineering is a better measure but its feasibility is questionable in the long run. It also needs government financial support, which is not possible to provide for every victim and also for repeated times. Therefore, erosion victims of both Bangladesh and India have chosen the last option migrating towards urban centres as labourers even beyond the countries and the remittances they earn can support their families in the long run, keeping family-related problems or hazards left behind. They have no other way because beggars cannot be choosers. After all, the three types of measures are valid to withstand bank erosion hazards.

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Blue Gold Program. (2023). Water management for development. Accessed 10 Aug 2023. http:// www.bluegoldbd.org/#:~:text=The%20wiki%20version%20of%20this,bluegoldwiki.com% 20into%20your%20browser Bunn, S. E., & Arthington, A. H. (2002). Basic principles and ecological consequences of altered flow regimes for aquatic biodiversity. Environmental Management, 30(4), 492–507. Cavaillé, P., Ducasse, L., Breton, V., Dommanget, F., Tabacchi, E., & Evette, A. (2015). Functional and taxonomic plant diversity for riverbank protection works: Bioengineering techniques close to natural banks and beyond hard engineering. Journal of Environmental Management, 151, 65–75. https://doi.org/10.1016/j.jenvman.2014.09.028 Chandy, K. T. (2012). Goat introduction. Animal husbandry-goats: GTS:1 ( Booklet no. 208). Chaudhuri, J. R. (1993). Migration and remittance–inter-urban and rural-urban linkages. Sage. Choudhury, P. K., & Sanyal, T. (2013). Use of jute geotextiles in road, river and slope stabilization. Indian Geotechnical Conference. Chow, V. T. (1959). Open channel hydraulics. McGraw-Hill. Chowdhury, T., Rahman, M. A., Khan, M. A., & Akter, T. (2022). Livelihood assets and food consumption status of riverbank erosion hazard people in a selected area of Bangladesh. Archives of Agriculture and Environmental Science, 7(1), 70–79. Dandapat, D., & Islam, S. (2009). A study of production, productivity, and profitability of fisheries in the district of North 24-Parganas, West Bengal. Journal of Business and Economic Issues, 1(1), 92–101. Deltares. (2017). Review of BWDB designs for river bank erosion management in Polder 29, Khulna, Bangladesh. https://www.bluegoldwiki.com/images/d/d4/P29_Deltares_review_ of_BWDB_designs_30may_17.pdf. Accessed 25 Dec 2022. District Census Handbook (2001). Nadia District. Directorate of Census Operation, 2001. Government of India. Accessed on 15 March 2021. https://censusindia.gov.in/nada/index.php/catalog/2 7872/download/31041/DH_19_2001_NAD.pdf FISRWG. (1998). Stream corridor restoration: Principles, processes and practices. The Natural Resources Conservation Service. https://nepis.epa.gov/Exe/ZyPDF.cgi/50000Y7R.PDF? Dockey=50000Y7R.PDF. Accessed 10 Nov 2022. Florsheim, J. L., Mount, J. F., & Chin, A. (2008). Bank erosion as a desirable attribute of rivers. Bioscience, 58(6), 519–529. Gray, D. H., & Sotir, R. B. (1996). Biotechnical soil bioengineering slope stabilization: A practical guide for erosion control. Wiley. Guchhait, S. K., Islam, A., Ghosh, S., Das, B. C., & Maji, N. K. (2016). Role of hydrological regime and floodplain sediments in channel instability of the Bhagirathi River, Ganga-Brahmaputra Delta, India. Physical Geography, 37(6), 476–510. Hossain, B. (2021). Role of NGOs in post-flood rehabilitation in chars. In Living on the edge (pp. 241–251). Springer. Hossain, M. (2022). Climate disasters are pushing Bangladeshi children out of the school system. World Economic Forum. Accessed 10 April 2023. https://www.weforum.org/agenda/2022/05/ climate-disasters-bangladesh-children-work/ Howell, J. (1999). Roadside bio-engineering. His Majesty’s Government of Nepal. ICIMOD. (2012). Contribution of Himalayan ecosystems to water, energy, and food security in South Asia: A nexus approach. International Centre for Integrated Mountain Development (ICIMOD). Irrigation and Waterways Directorate. (2010). Annual flood report. Advance planing project, evlauation and monitoring cell. Jal Sampad Bhawan, Salt Lake, Kolkata. https://wbiwd.gov. in/uploads/anual_flood_report/ANNUAL_FLOOD_REPORT_2010.pdf. Accessed 15 Dec 2022. Irrigation and Waterways Directorate. (2011). Annual flood report. Advance planing project, evlauation and monitoring cell. Jal Sampad Bhawan, Salt Lake, Kolkata. https://www.wbiwd. gov.in/uploads/anual_flood_report/ANNUAL_FLOOD_REPORT_2011.pdf. Accessed 15 Dec 2022.

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Islam, M. S. (2008). River bank erosion and sustainable protection strategies. In Proceedings 4th international conference on scour and erosion (ICSE-4). November 5–7, 2008, Tokyo, Japan (pp. 316–323). https://izw.baw.de/publikationen/tc213/0/b_11.pdf Islam, A., & Guchhait, S. K. (2021). Social engineering as shock absorbing mechanism against bank erosion: A study along Bhagirathi river, West Bengal, India. International Journal of River Basin Management, 19(3), 379–392. Islam, M. S., Arifuzzaman, M., Shahin, H., & Nasrin, S. (2013). Effectiveness of vetiver root in embankment slope protection: Bangladesh perspective. International Journal of Geotechnical Engineering, 7(2), 136–148. Islam, A., Ghosh, S., Barman, S. D., Nandy, S., & Sarkar, B. (2022). Role of in-situ and ex-situ livelihood strategies for flood risk reduction: Evidence from the Mayurakshi River Basin, India. International Journal of Disaster Risk Reduction, 70, 102775. Khera, R. (2013). Democratic politics and legal rights: Employment guarantee and food security in India. (IEG Working Paper No. 327). Landphair, H. C., & Li, M. H. (2001). Regional applications for biotechnical methods of streambank stabilization in Texas: A literature review. https://ntlrepository.blob.core. windows.net/lib/18000/18400/18495/PB2002100235.pdf Lane, E. W. (1955). Design of stable channels. Transactions of the American Society of Civil Engineers, 120(1), 1234–1260. Leopold, L. B., & Langbein, W. B. (1966). River meanders. Scientific American, 214(6), 60–70. Li, M. H., & Eddleman, K. E. (2002). Biotechnical engineering as an alternative to traditional engineering methods: A biotechnical streambank stabilization design approach. Landscape and Urban Planning, 60(4), 225–242. https://doi.org/10.1016/S0169-2046(02) Macdonald, E. M. (2020). Flood and riverbank erosion risk management investment program (FRERMIP) project-1. Maiti, D. S. (2005). Organisational morphology of rural industries in Liberlised India: A study of West Bengal. www.cds.edu Mamun, M. Z., & Amin, A. T. (1999). Densification – A strategic plan to mitigate river bank erosion disasters in Bangladesh. The University Press Limited. Marjit, S., & Maiti, D. S. (2005). Globalization, reform and the informal sector (pp. 1–29). United Nations University, Research Paper No. 2015/12. Mautner, M. N. (2009). Life-centered ethics, and the human future in space. Bioethics, 23(8), 433–440. https://doi.org/10.1111/j.1467-8519.2008.00688.x Mortreux, C., de Campos, R. S., Adger, W. N., Ghosh, T., Das, S., Adams, H., & Hazra, S. (2018). Political economy of planned relocation: A model of action and inaction in government responses. Global Environmental Change, 50, 123–132. Nair, M., et al. (2013). Effect of the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) on malnutrition of infants in Rajasthan. A Mixed Methods Study. PLOSONE. Parsons, P. A. (1963). Vegetative control of streambank erosion. In Federal interagency sedimentation conference: Proceedings (Misc. Publ. 970) (pp. 130–136). USDA Agricultural Research Service. Parua, P. K. (2010). The Ganga: Water use in the Indian subcontinent (Vol. 64). Springer. Paul, B. K., Rahman, M. K., Crawford, T., Curtis, S., Miah, M. G., Islam, M. R., & Islam, M. S. (2020). Explaining mobility using the community capital framework and place attachment concepts: A case study of riverbank erosion in the Lower Meghna Estuary, Bangladesh. Applied Geography, 125, 102199. Paul, B. K., Rahman, M. K., Crawford, T., Curtis, S., Miah, M., Islam, R., & Islam, M. (2021). Coping strategies of people displaced by riverbank erosion in the Lower Meghna Estuary. In Living on the edge (pp. 227–239). Springer. Rahman, A. (2010). Comparative analysis of design and performance of bank protection works of Jamuna River at Titporol and Debdanga.

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Richter, B. D., & Thomas, G. A. (2007). Restoring environmental flows by modifying dam operations. Ecology and Society, 12(1), 12. [online] URL: http://www.ecologyandsociety.org/ vol12/iss1/art12/ Saha, V. D., & Makwana, M. (2011). Impact of Nrega on wage rates, food security and rural urban migration in Gujrat. Research Study. Schaefer, J. W., & Naeth, A. (2000). Live staking with willows fails to protect eroded lakeshore slope (Alberta). Ecological Restoration, 18(4), 267–268. Schiechtl, H. M. (1980). Bioengineering for land reclamation and conservation [Buch]. University of Alberta. Schiechtl, H. M., & Stern, R. (1994). Water bioengineering techniques. Blackwell Science. Schumm, S. A. (1985). Patterns of alluvial rivers. Annual Review of Earth and Planetary Sciences, 13, 5. https://user.engineering.uiowa.edu/~cee_171/handouts/Schumm_1985.pdf. Accessed 10 Sept 2022 SEPA. (2008). Engineering in the water environment good practice guide bank protection: Rivers and lochs. https://www.sepa.org.uk/media/150971/wat_sg_23.pdf. Accessed 15 Dec 2022. Simpson, P., Newman, J. R., Keirn, M. A., Matter, R. M., & Guthrie, P. A. (1982). Manual of stream channelization impacts on fish and wildlife. FWS/OBS-82/24 US Fish and Wildlife. https://pubs.usgs.gov/publication/fwsobs82_24 Styczen, M. E., & Morgan, R. P. C. (2003). Engineering properties of vegetation. In Slope stabilization and erosion control: A bioengineering approach (pp. 16–72). Taylor & Francis. USDA. (1992). Chapter 18: Soil bioengineering for upland slopeprotection and erosion protection. In USDA natural resources conservation service engineering handbook. Wu, T. H. (1995). Slope stabilization. In R. P. C. Morgan & R. J. Rickson (Eds.), Slope stabilization and erosion control: A bioengineering approach (pp. 221–264). E. and F.N.

Chapter 9

Future Speculations and Challenges

9.1

Perspectives of Future Speculations and Challenges

The end notes of this book necessarily incorporate future speculation and challenges. Throughout the earlier discussion, the global perspectives and regional dynamics of bank erosion process and its geomorphological imprints on fluvial landscape have been explored in Chaps. 3, 4 and 5. Moreover, a vivid enquiry into socioeconomic impacts and adaptive strategies is undertaken in Chaps. 6, 7 and 8. Based on the essence of those observations, future speculations and challenges are either hypothesized or proposed from two sides: (i) speculation in relation to climate change and sea level rise, and (ii) challenges in the sociocultural dimensions and speculation about the economy and livelihood struggle. Climate change and sea level rise are now an established reality. The phenomena of climate change have certainly induced sea level rise (Mimura, 2013). Therefore, the rise of sea level in such an estuarine region will certainly impact bank erosion (Brammer, 2014). Accelerating sea level rise and its impacts are estimations which may be beyond the accurate estimation (Siegert & Pearson, 2021). However, predicted erosion in the wake of climate change will intensify the challenges in the sociocultural dimensions and associated coping strategies. If the bank erosion is increased in future, the people will adopt in-situ displacement with adjustment or leave the place and will be transformed into environmental refugees or some other consideration. The last section in this regard is the challenges regarding economy and livelihood where the coping strategy of livelihood is the concern through which the victims will be adapted to an economy of stop and go.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Islam, S. K. Guchhait, Riverbank Erosion in the Bengal Delta, Springer Geography, https://doi.org/10.1007/978-3-031-47010-3_9

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9.2

9

Future Speculations and Challenges

Climate Change, Sea Level Rise, and Bank Erosion

In the era of the Anthropocene, climate change and sea level rise emerge as the two intertwined facets of the terrestrial system. Due to global warming, variability in the precipitation regime is tell-tale which frequently leads to episodes of frequent drought and floods across the world and a higher pace of hydrological cycles. These climatic phenomena tend to influence erosion events. For example, intensified rainfall after a dry spell often triggers huge soil and bank erosion. Therefore, in the context of the GBM delta, global warming will directly induce the accelerated rate of erosion events as discussed in Chap. 3. Moreover, the recent threat of sea level rise is also related to global warming. It has been demonstrated that the average sea level rise is faster in the GBM delta compared to the global average. For example, the global average sea level rose by 1.8 mm during the twentieth century (Bindoff et al., 2007); however, during 1993–2003 the rate of sea level rise escalated to 3.1 mm per year (Douglas, 1997). However, local sea level rise for the GBM was recorded at many locations as high as 25 mm per year (Alam, 1996; Ericson et al., 2005). Moreover, in West Bengal, a greater sea level rise is anticipated due to a greater rate of land subsidence by 1.5 mm/year (Becker et al., 2020). The higher sea level rise will reduce the slope-induced channel gradient and hence bed erosion will decrease with an increase in bank erosion. This can be clearly observed in a few areas in the GBM delta. For example, due to the natural forcing of the confluence zone for the major rivers debouching into the seas like the Padma-Brahmaputra and Meghna, bank erosion may be initiated because of the pool action, salinity intrusion, higher settling rate, braiding, and channel expansion. In the context of sea level rise, there is always a higher chance to register a higher settling velocity due to the mixing of freshwater with saline water that may develop channel braiding and channel widening by bank erosion. However, this may not be linear because of the effects of the sediment flux under the damming regime. A dam construction may inhibit the sediment dispersal rate largely and hence reduce the supply of sediment required for island formation in the downstream courses. In the GBM delta, the mushrooming of dams and barrages is a common phenomenon, especially for the western part of the GBM delta. All the major rivers of West Bengal like Damodar, Mayurakshi, and Kangasabati are dammed with lesser availability of sediment in the downstream courses. Rather the construction of dams like the FBP and subsequent ponding actions of water in the upper part of the FBP may result in higher erosion rates for the Ganga River with a lower trend for the lower part. Thus, the speculation of higher bank erosion under the regime of global warming and sea level rise needs to be addressed in more critical ways. Nowadays, bank erosion hazard is working in a feedback system instead of a linear chain, i.e., a more complex process response system is going to be sparked. For example, higher flood events may induce higher bank erosion and higher river bank erosion will accelerate the process of inundation. Thus, bank erosion, flood, climate change, and sea level rise are working in a loop manner and one hazard may compound another hazard (Fig. 9.1).

9.3

Sociocultural Changes and Bank Erosion

319

Climate change

Sea-level rise

Changes in precipitation nature and pattern

Coastal floods and storm surges

Increase in tropical cyclones

Riverine floods

Floods

Riverbank erosion

Loss of homestead

Economic distress and Labour migration

Occupational shifting

Agricultural distress

Infrastructural loss

Displacement

Increase in social instabilities

Seasonal unemployment and reduced income

Selling of assets

Increased loan

Accelerating poverty

Food insecurity

Decreased expenditure on health

Reduced education budget

Fig. 9.1 Framework integrating climate change, flood, and bank erosion in a loop manner. The figure demonstrates that floods will increase in the wake of climate change which tends to increase the riverbank erosion and socioeconomic instabilities

9.3

Sociocultural Changes and Bank Erosion

In articulating bank erosion of the GBM delta and its impact on society, the scenario in the Indian part of the study area is different from that of the study area of Bangladesh. Charland bank erosion is not a major problem in the study area of India as the chars are small in size and those are mostly unhabitable. Therefore, bank erosion is mainly confirmed for the two banks of the river. Bank erosion of Bhagirathi in India has experienced accelerated erosion with the new hydrological paradigm due to the construction of the Farakka Barrage (Islam & Guchhait, 2017a). This barrage-induced new equilibrium has set more intensive erosion than earlier. Therefore, the intensive erosion started in the middle of the 1980s, which with the progress of time has to some extent become stabilized (Islam & Guchhait, 2017b). But the meandering course of the river still continues erosion. Under such hazards, erosion victims were pugged losing their land resources and also the residential house. Lateral displacement was the initial phase but many of them have migrated to other villages. In-situ challenges are livelihood diversification which is not sufficient enough and migration as labours of the workable male members of almost all families is the most preferable option to safeguard the livelihood and also the

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household economy. Now they are habituated with this situation. Some of the families of Gangadanga and Rukunpur have shifted their households as an in-situ displacement more than three times. Now they have the realization that bank erosion is a game of nature and without much dependence on off-farm economy, they support their family by livelihood diversification and more profoundly by remittances. Through the widespread diffusion of the LPG economy in India mainly from the middle of the 1990s, poor people are habituated to the strategy of migration to the large cities of India and also towards the Middle East (Islam & Guchhait, 2021). It is true not only for the bank erosion victims but also for the other victims of cyclonic storms that frequently occur in the Gangetic Delta. This perspective has been gleaned from the field visit. While asking the question during a field visit in 2021, Nizamuddin Sekh of Rukunpur that, now the bank erosion is at low web, if it occurs once again, what will be your strategy? “We are habituated to this hazard, we know that our productive land will be grabbed by the river, maybe that we have to shift our residence in the nearby mouza, but we cannot leave this place as our fathers and grandfathers took birth and last shy. Remittances through labour migration will help us to stand against this odd.” For Bangladesh, the situation is to some extent different. Of course, remittance through labour migration is profound, but the nature of bank erosion of Padma and Meghna is high enough. Here most of the large chars are habitable chars with high fertility. A huge amount of people are colonized within the char area. They face the bank erosion of char not only during the peak monsoon period but at other times of the year as those estuarine rivers (Padma and Meghna) are the two-way channel. Bangladesh is the land of rivers. There are about 250 rivers of which larger rivers are highly erosion-prone (Mamun & Amin, 1999). There is a long history of bank erosion in Bangladesh. A sizable portion of charland people is the bank erosion victims of the nearby bank. Few of them have occupancy on the mainland also. At the time of submergence or due to severe bank erosion, people who have occupancy in the mainland, migrate to the mainland. At the same time, they shift their residence to another part of the charland as the land-man ratio is very high. There is another perspective of charland dwellers of the Padma, Jamuna, Meghna, and Brahmaputra. A sizable portion of the charland dwellers is the environmental refugees coming from the frontal estuarine tidal region. Being environmental refugees of the devastating cyclonic storm in the past, these people are evicted to the interior, mainly in the charland areas of Padma, Meghna, Jamuna, and Brahmaputra (Ullah et al., 2010). The mainland people call them Bhatias as they have migrated from the tidal estuarine front of Bangladesh (tidal areas or bhatir desh). They are habituated to those hazards, as they were facing hazards in their previous generation. Those people shift their habitat location from one part of the char to another, as their earlier occupation was fishing which could be possible staying in the charland. Therefore, apart from the extreme condition, the people are likely to stay in charland in future. However, if the sea level is increased the bank erosion scenario will change certainly. The average elevation of the coastal area in Bangladesh is below 1.5 m and the speculation is that the sea level of the Bay of Bengal will rise with a range of 0.3

9.4

Future Speculation About the Livelihood Strategies

321

to 1.5 m by 2050 (Karim & Mimura, 2006). Under such a condition, the submergence of chars of Meghna and the lower part of Padma will be the future reality. Those chars are large chars with a sizable population. They have to move towards the mainland. Charland erosion will be aggravated along with river bank erosion because the tidal flow will reach more interior along the channel. Therefore, the probability of bank erosion will be high disrupting the river bank site and the char areas. By another speculation, the load of the Padma and Meghna will decrease in future. Because within the last decade, numerous dams have been constructed over Tista; it is also true for the Brahmaputra (Sangpo) of China. Therefore, the likely bed aggradation of Padma and Meghna will decrease. By the balance of these opposite outcomes, erosion may increase or decrease. However, the first one will be the most probable reality of future, as it has been experienced by Padma and Meghna even after the construction of the Farakka Barrage. Considering this perspective of decreasing load and more active tidal flow towards the interior of the channel, two considerations can be hypothesized. In the lower part, i.e., Padma and Meghna people along the banks and over the chars will be under threat with the increase of sea level. They will face more vulnerability and their identity as environmental refugees will sustain in future. Migration away from the river bank will be their destiny and remittance will be their most preferable option to stable their household economy. Of course, remittance from foreign countries is the most striking force to stable the national economy of Bangladesh will add another momentum to a little. On the other hand, bank erosion and of course charland bank erosion of Tista and Padma will decrease, even after the rise of sea level. Because these two rivers are gradually transformed into tamed rivers. Therefore, the flow of these rivers is regulated, though the Brahmaputra for its huge discharge cannot be regulated in the peak period. However, with decreasing load and discharge in future neither the extreme charland bank erosion nor the river bank erosion will be the reality. This is speculation drawing from the Damodar River of West Bengal, India, where the channel is a sluggish one for most of the year (around for 11 months) after the dam site. Therefore, bank erosion victims of Tista especially and Brahmaputra to some extent will be less vulnerable in future.

9.4

Future Speculation About the Livelihood Strategies

The first and foremost visible expression of riverbank erosion becomes clear through the livelihood crisis and economic changes of the victims. It has been demonstrated in this work that the economic base especially the agrarian economy is largely threatened by the bank erosion events both in India and Bangladesh. The frequent relocation of households and emergence of the environmental refugees are the experienced reality and mental image of the victims. They are always trying to adjust to the emerging scenario through physical migration or labour migration.

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However, another trend speculated that two scenarios may surface. First, upkeeping of the two residential places – one at the village (place of erosion) for land and emotions with kith and kin feeling and another at the urban areas for main income sources. Second, a chain migration may develop in which the relatively well-off families after gaining the minimum economic inertia shift to a better place and new victims will occupy those disadvantageous locations left by another well-off group. This succession will continue until a climax is reached and permanent land allotment is settled. The future livelihood will then focus on the non-land-based or mixed economy where the shocks of bank erosion could be distributed and well managed. There will be a higher tendency to be engaged in multiple occupations instead of a single source, e.g., from a village location agricultural produce and earning remittance from urban areas (Ellis, 1998). Moreover, there may be another chance that women will be more engaged in the household economy, especially through some small and cottage industries to support their families. In brief, the dependencies on traditional agriculture may reduce to some extent and new practices may emerge.

9.5

Concluding Notes

Riverbank erosion as a natural process will probably be intensified due to the threats of climate change, sea level rise, and accelerated human interventions. As the GBM is the largest delta in the world, threats will appear and reappear intensively in a complex loop rather than a simplified reality. The lucid reason based inquiry supported by case study studies offered in the present volume will certainly elevate the physical-social integrated understanding of the subject in the Indo-Bangladesh region. The book may be helpful for all stakeholders for better planning of the concerned regions apart from the academic contribution. As it is a pioneer attempt to integrate the social with the physical dimensions of bank erosion of two sides of the Bengal Delta, certainly an integrated framework for planning may be developed for the participatory development of the regions keeping the major attributes of geology, hydrology, climate, drainage, hazards, demography, economy, and society. For future endeavor in the concerned field, Indo-Bangladesh region may have collaborative plans in these areas based on the study findings. However, there are many scopes for future work. First, future prediction of erosion scenarios was not done with validations due to the unavailability of many databases such as intensive storm surge data, flood impulse data, historical changes in the LULCs, and the mushrooming of dams and barrages along with the long-term climate change data. Second, socioeconomic changes are quite fast and sometimes highly subjective. Thus, future planners must consider the complex social fabric before any concrete plan for community development. Third, as West Bengal and Bangladesh exhibit similar physical-social landscapes in many cases, an integrated approach to deal with the hazards of the Bengal Delta may be initiated for the sustainability of the management plans. The present piece of work may grow interest among the future stakeholder and researchers for exploring the erosion modelling

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based on the critical perspective of riverbank erosion in the light of process approach, form approach, management and futuristic approach involving climate change, sea level rise, and socioeconomic changes.

References Alam, M. (1996). Subsidence of the Ganges-Brahamaputra Delta of Bangladesh and associated drainage, sedimentation and salinity problems. In J. D. Milliman & B. U. Haq (Eds.), Sea-level rise and coastal subsidence (pp. 169–187). Kluwer Academic Publishers. Becker, M., Papa, F., Karpytchev, M., Delebecque, C., Krien, Y., Khan, J. U., et al. (2020). Water level changes, subsidence, and sea level rise in the Ganges–Brahmaputra–Meghna delta. Proceedings of the National Academy of Sciences of the United States of America, 117(4), 1867–1876. Bindoff, N. L., Willebrand, J., Artale, V., Cazenave, A., Gregory, J., Gulev, S., Hanawa, K., LeQuere, C., Levitus, S., Nojiri, Y., Shum, C. K., Talley, L. D., & Unnikrishnan, A. (2007). Observations: Oceanic climate change and sea level. In S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor, & H. L. Miller (Eds.), Climate change 2007: The physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. Brammer, H. (2014). Bangladesh’s dynamic coastal regions and sea-level rise. Climate Risk Management, 1, 51–62. Douglas, B. C. (1997). Global sea rise: A redetermination. Surveys in Geophysics, 18, 279–292. https://doi.org/10.1023/A:1006544227856 Ellis, F. (1998). Household strategies and rural livelihood diversification. The Journal of Development Studies, 35(1), 1–38. Ericson, J. P., Vorosmarty, C. J., Dingman, S. L., Ward, L. G., & Meybeck, M. (2005). Effective sea-level rise and deltas: Causes of change and human dimension implications. Global Planetary Change, 50, 63–82. Islam, A., & Guchhait, S. K. (2017a). Analysing the influence of Farakka Barrage Project on channel dynamics and meander geometry of Bhagirathi river of West Bengal, India. Arabian Journal of Geosciences, 10(11), 1–18. Islam, A., & Guchhait, S. K. (2017b). Search for social justice for the victims of erosion hazard along the banks of river Bhagirathi by hydraulic control: A case study of West Bengal, India. Environment, Development and Sustainability, 19(2), 433–459. Islam, A., & Guchhait, S. K. (2021). Social engineering as shock absorbing mechanism against bank erosion: A study along Bhagirathi river, West Bengal, India. International Journal of River Basin Management, 19(3), 379–392. Karim, M. F., & Mimura, N. (2006). Sea level rise in the Bay of Bengal: Its impacts and adaptations in Bangladesh. Center for Water Environment Studies, Ibaraki University, Hitachi, Ibaraki, Japan. Microsoft PowerPoint–Poster for IOC_02June06_Karim. Mamun, M. Z., & Amin, A. N. (1999). Densification: A strategic plan to mitigate riverbank erosion disaster in Bangladesh. University Press Limited. Mimura, N. (2013). Sea-level rise caused by climate change and its implications for society. Proceedings of the Japan Academy, Series B, 89(7), 281–301. Siegert, M., & Pearson, P. (2021). Reducing uncertainty in 21st century sea-level predictions and beyond. Frontiers in Environmental Science, 9, 751978. Ullah, H., Islam, M. N., & Malak, M. A. (2010). Charland dynamics of the Brahmaputra-Jamuna river in Bangladesh. The Jahangirnagar Review, 34, 165–182.

Glossary

Aarat Village market based on different products from agricultural to textile which may function either daily or periodically. Adaptation Adaptation is the process through which people, groups, or societies modify or adapt their behaviour, norms, and values in response to environmental or other changes. Adaptive capacity The ability of people, organizations, communities, or systems to successfully respond to, adjust to, and survive in the face of changing circumstances, difficulties, or disruptions is referred to as adaptive capacity. Aman A type of rice sown in June-July and harvested during November-December in the Indian Monsoon climate. Amplitude Amplitude refers to the maximum distance between the crest and trough height of a meander loop. Anastomosis Anastomosis is a process of shaping a channel pattern in which two or more channels are interconnected. Anthropocene The Anthropocene, as it is known, is the current century in Earth’s history, and it is characterized by a significant and widespread human impact on the Earth’s geological, geomorphological, and ecosystem processes. The term “Anthropocene” is a combination of the Greek words “anthropos”, which translates to “human”, and “cene”, which translates to “new”. The Anthropocene idea contends that human activity is now the main driver of change in Earth’s atmosphere, oceans, land, biodiversity, etc. Anthropogenic approach The anthropogenic approach to riverbank erosion involves human involvement and management techniques to regulate or lessen the erosion along riverbanks. Antipodal erosion “Antipodal erosion” in the context of rivers refers to a specific pattern of erosion that occurs on opposite sides of a river’s bank relating to sediment deposition. Arc angle Arc angle refers to the angle between the two departure points of the curvature sections of a meander loop. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Islam, S. K. Guchhait, Riverbank Erosion in the Bengal Delta, Springer Geography, https://doi.org/10.1007/978-3-031-47010-3

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Asset strategy A strategy in rural and urban livelihood to have land, crops, domesticated animals, jewellry etc. as a resource that produces positive economic value. Aus A type of rice sown in May-June and harvested in September-October in the Indian Monsoon climate. BANCS BANCS stands for Bank Assessment for Non-Point Source Consequences of Sediment. This method was developed by Rosgen in 2001 to estimate the sediment yield from river bank erosion in a specific region based on the physical as well as observational measurements of the river bank. It is quantitatively assessed with the two bank erodibility tools namely Bank Erosion Hazard Index (BEHI) and Near Bank Stress (NBS). Bangal para A hamlated settlement of refugees from Bangladesh frequently found in West Bengal, India. Bank geometry The shape and physical attributes of the banks of a river channel are referred to as river bank geometry. It entails the analysis and measurement of many factors that characterize the shape and construction of the riverbank, which have a considerable impact on the riverbank. Bank height, slope, and material composition are important characteristics of riverbank geometry. Barind tract An undulating plain formed by the deposition of old alluvium beneath the foothills of Eastern Himalaya formed by the flood deposits by the southflowing rivers of Eastern Himalaya mainly in the districts of Malda, North and South Dinajpur districts of India and Rangpur and Jashore districts of Bangladesh. Baseline The term “baseline” refers to the original data or measurements made before the implementation of any erosion control or management activities. To evaluate the efficiency of erosion management techniques and quantify any changes in erosion rates, baseline data offer an initial point against which future erosion measurements may be compared. Behavioural model Behavioural model is a psychological model based on human action and behaviour extensively used in psychology to predict human behaviour. In the study, Tajfel Matrix (a behavioural model) is used for understanding the psychology of social desire concerning the distribution of resources in society. BEHI Bank Erosion Hazard Index (BEHI) is an index of measurement of River Bank stability. Bengal Basin The Bengal Basin is a sedimentary basin spread over the part of West Bengal of India and Bangladesh. It is the structural depression of Indian plates which was deposited by the sediment of the Ganga, Brahmaputra, and Meghna Rivers. It is surrounded by the Chotanagpur Plateau in the West, Rajmahal Pahar and Shillong Plateau in the north, and Surma Margin fault in the east. Bengal Delta The Bengal Delta, also known as the Ganges-Brahmaputra Delta, is a vast and highly dynamic river delta located in the Indian sub-continent. It is formed by the sediments at the confluence of several major rivers, including the Ganga, Padma, Brahmaputra, Jamuna, and Meghna, as they discharge into the Bay of Bengal.

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Bhatia People living in the tidal areas of coastal Bangladesh frequently face cyclonic hazards and tidal surges. As a result, adversely affected hazard victims are forced to migrate permanently into the interior areas. Inland people codify those environmental refugees as Bhatia with a sense of negligence. Bidi Indian indigenous cigarettes cheaper in price used by country people where the tobacco is raped by Kendu (Diospyros melanoxylon) leaves. Bill Low marshy land is formed mainly as a consequence of channel cut-off or depressed topography. Bio-engineering techniques Bio-engineering techniques may reduce river bank erosion by utilizing vegetation and other natural resources. Bio-engineering methods commonly integrate engineering concepts with biological processes to provide solutions that are both useful and ecologically sound. Blue gold program An initiative between the Government of the Netherlands and the Government of Bangladesh proposed a higher penetration depth of the piles for the civil structures (groynes) for bank protection. Boro A type of rice sown in November-December and harvested in March-April in the Indian Monsoon climate. Braiding Braiding refers to the network of multiple paths which are divided and joins simultaneously. Channel asymmetry Channel asymmetry refers to the areal differences and maximum depth displacement relative to the channel centreline. Channel instability Channel instability is the tendency for a natural waterway, such as a river or stream, to experience continuous changes in its shape, size, and pattern over time. Charland Charland, also known as river island, is a highly elevated land composed of sand and gravel which is deposited by the flow of a river. Chhotonagpur Plateau It is a physiographic unit of the eastern part of the central plateau of India. Civil structural measures Civil and structural solutions are designed approaches for preventing river bank erosion and protecting areas that are prone to erosion from the erosive forces of water. These activities frequently involve the construction of physical structures to support the riverbank and manage water flow. Cohesive bank A riverbank made of cohesive soils is referred to as a cohesive riverbank. Fine-grained soils (clay and silt particles) with cohesive properties have particles that attract one another strongly by electrochemical and physical forces. Compared to non-cohesive or granular river banks, cohesive banks are better able to withstand the erosive effects of flowing water. Common property resources Natural resource ground without any stakeholder. In the absence of stakeholders resources can be extracted by common people. Constant of Channel Maintenance Natural channels or rivers need some minimum area for their hydrological regime. Controlled hydrology Controlled hydrology, also known as arithmetic hydrology, deals with the adjustment of hydrological extremes by human interventions in the form of dams and barrages.

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Coping capacity In the context of disaster management and risk reduction, coping capacity refers to an individual’s or group of people’s capability to cope with and adjust to the negative effects of catastrophes or other stresses. Cratonic sediments Sediments that are enriched with cratonic materials able to withstand erosion. Cretaceous A geological period that began 165 million years ago and ended 66 million years ago marked by a worldwide lava eruption. Crop diversity Crop diversity refers to the variety or variability of crops that farmers grow in their agricultural fields. Cropping intensity Cropping intensity refers to the number of crops that are grown in the same field in a given agricultural year. D50 A measure used frequently in sediment analysis to describe the size distribution of sediment particles in a sample is known also as the median grain size. It stands for the particle size where 50% of the cumulative weight of the sediment particles is smaller, and 50% is larger. Dal Pulses are termed in the Indic language. Deccan region Deccan region is a plateau region situated between the Eastern Ghats and the Western Ghats of the Indian subcontinent. In the north, it is bounded by Satpura and Vindhya Ranges. The elevation ranges between about 300 ft and 3000 ft with a 2000 ft average elevation. Depth index It is the ratio between the actual depth and the ideal depth of a channel. Dhone Done (coriander) is a cash crop cultivated in winter in the Indian sub-continent. Digital shoreline analysis system The U.S. Geological Survey (USGS) developed the Digital Shoreline Analysis System (DSAS) to examine shoreline changes along coasts. To measure and evaluate changes in shoreline locations over time, DSAS uses satellite images and Geographic Information System (GIS) technologies. It provides a wide range of tools and methods for studying shoreline dynamics, including accretion, erosion, and other coastal phenomena. Direction angle The direction angle is that which creates the meandering path at the crossing of the sinuous axis and centreline of the meandering platform downstream of the river. Disasters Extreme events cause significant and widespread harm, devastation, deaths, and disturbance of daily life in a community or society. These events are usually caused by natural events like earthquakes, floods, storms, and wildfires as well as human-made catastrophes like industrial accidents. Simply, it is called the realization of a hazard. Dyking Dyking is a common civil engineering measure used to control river bank erosion and prevent inundation. Dykes are raised embankments or walls built along the riverbank to confine the river within a defined channel and protect adjacent areas from flooding and erosion. Embankment A wall-like structure built to run alongside a river or stream is known as a river embankment. It is designed to keep water inside the river

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channel and stop floods, erosion, and other detrimental effects on the surrounding landscape. Emic perspectives Emic perspectives are essential for anthropologists’ efforts to obtain a detailed understanding of a culture and to avoid interpreting others through their own cultural beliefs. Environmental refugees Environmental refugees are those who are forced to depart from their territory due to sudden or long-term changes in the local and regional environment changes that interrupt their livelihoods. EPR Net Shoreline Movement divided by the time interval produces the End Point Rate (EPR). Positive numbers indicate accretion and negative values indicate erosion. The rate is expressed in meters per year. Erodibility The term “erodibility” describes the susceptibility of substances to being eroded by natural processes, notably by the action of water, wind, ice, or other erosive agents. Erosional failure Erosional failure is the process through which a terrestrial surface progressively loses material like soil, rock, or sediment as a result of the impact of natural factors like water, wind, ice, or gravity. Erosivity The term “erosivity” describes the ability of natural processes, such as rainfall or water flow, to erode the surface of the Earth. Etic perspective Etic perspectives refer to explanations for behaviour made by an outside observer in ways that are meaningful to the observer. Exposure The term “exposure” describes the individuals, things, systems, or other components that are present in hazard zones and are hence vulnerable to possible losses. Ex-situ adjustment Ex-situ means outside of the location. In the study, ex-situ is used as a way of livelihood adjustment. Here, ex-situ adjustment specifies the substitution of primary livelihood outside the native place, here remittances. Farakka Barrage Project Farakka Barrage Project was started in 1962 and completed in 1972. The functions of the projects include maintaining the flow of the Bhagirathi-Hooghly River system by the Feeder Canal to increase the navigability of the Kolkata Port. Besides, it increases the supply of upland water to reduce the salinity of the Bhagirathi-Hooghly River and its surrounding areas. It also connects North Bengal with South Bengal by direct railway and road bridge which are constructed upon it. Farm income Farm income refers to profits and losses acquired through the operation of a farm. Financial capital It indicates stocks of money in the form of savings, access to credits, income, surplus agricultural income, gems and jewellry, etc. Flow hydraulics A branch of fluid mechanics that deals with the behaviour of fluids in motion, particularly in open channels, pipes, and other hydraulic structures. Flow slides It is an underwater slope failure due to the liquefaction/breaching process depending on the water level and seepage action in the subsoil.

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Fluvial entrainment Fluvial entrainment is a process that initiates the motion of particles in a set of hydraulic conditions. It occurs when the bed shear stress outstrips the threshold value for the sediment size. GBM Delta Ganga-Brahmaputra-Meghna (GBM) Delta is the largest delta in the world formed by the sediments carried out by the rivers Ganga, Brahmaputra, and Meghna River system. Geologic erosion Slow natural process of erosion essential to maintain the ecosystem balance. Geotextile A process of strengthening erosion-prone river banks or coasts through biotic materials. Group process It involves social interactions among the different members of a group. Guide bank The hydraulic structure of the river rank allows the river water to flow in a defined path by preventing its over-flanking. This is mainly constructed to maintain the navigability of a river. Hard engineering Construction by concrete technology or metallic structure used to stop riverbank erosion. In most cases, it involves huge monetary cost and disturb the natural flow of the river. Hazard An incident that has the potential to cause harm to people or the environment, property damage, or any combination of these. However, the actual harm is determined by the degree of exposure and vulnerability of particular people or entities to hazards. Himalayan sediment Sediments carried out from the Himalayas by the rivers of this region are more erosion-prone compared to the cratonic sediments. Hjulstorm curve It is a graphical illustration that shows how the velocity of water flow affects the erosion, movement, and deposition of sediment particles in a natural water system, such as rivers and streams. Holocene It is the current geological epoch that began at approximately 12000 BP. Human capital It implies skill, labour, ability to work, education, health, etc. Hydraulic erosion It is a kind of erosion driven by water flowing across the surface of the Earth. It entails the removal and transportation of soil, sediment, and rock particles by the force of moving water, such as rivers, streams, rainfall-runoff, and even ocean currents. Income portfolio It relates to income-related sources and data of a person or household. Indo-Bangladesh water-sharing treaties The water-sharing disputes that were resolved through two treaties signed between the two neighboring countries – India and Bangladesh related to the distribution of water of the Ganga River especially in the lean months (January to May) in the years 1977 and 1996. In-situ adjustment It is an adjustment with the system, using locally available potential resources. Intergroup process It entails the social interaction between various groups pertaining to certain events.

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Interpersonal process It involves the social interaction among the different individual members pertaining to certain events. Inverse Hernafindahl-Hirschman Index Inverse Hernafindahl-Hirschman Index (Inverse HHI) is used to denote diversification. In the study, the Inverse HHI was used to show occupational diversification. A higher value of Inverse HHI denotes a higher rate of diversification. Kans Kans grass (Saccharum spontaneum) is a grass native to South Asia. It is a perennial grass, growing up to three meters in height, with spreading rhizomatous roots. Leaves are harsh and linear, 0.5 to 1 meter long; 6 to 15 mm wide. Because of this cover and root characteristics, this species is proven to be most suitable for checking bank erosion. Kharif Kharif refers to crops that are cultivated mainly depending on monsoon rainfall. Kolkata port trust A statutory body for the management of the port of Kolkata now known as Dr Syama Prasad Mookerjee port. Lithology The scientific study of rocks and their features is known as lithology. It is a subfield of geology that concentrates on comprehending the composition, texture, structure, and other characteristics of rocks, including their mineral content, grain size, colour, hardness, porosity, and other characteristics. By studying these characteristics, they can identify different rock types and interpret the geological history of a region. Livelihood diversification Livelihood diversification refers to the process by which rural/urban families create a diverse portfolio of activities and social support capabilities in terms of surviving and improving their standards of living. Livelihood vulnerability It is the miserable condition of livelihood caused by natural or social hazards. Livelihood The term “livelihood” describes the ways and pursuits that people or families make a living, meet their essential requirements, and promote their wellbeing. It encompasses the various economic activities, occupations, and resources that individuals use to support their daily needs and ensure their social and financial stability. LRR It is a statistical parameter that is available within DSAS. Along with EPR and NSM, LRR is also used for erosion and accretion rate of shoreline studies. Mahajan/Dalal A person who lends money at a high-interest rate or a person who supplies materials to local manufacturers and collects the finished products for marketing. Masoor Red lentil is one kind of pulse that is grown in the winter season in the Indian sub-continent. Matiari model A non-land-based alternative economy (here brass metal cottage industry) to absorb the shocks of natural hazards say riverbank erosion. Meander geometry Meander geometry refers to the technical description of a watercourse including width, depth, slope, flow velocity, and plan shape.

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Meandering It is a natural process of the formation of a meander or sinuous channel (sinuosity index above 1.05). It is the outcome of river flow and sediment dynamics in an attempt to establish a hydraulic equilibrium. MGNREGA Rural employment generation scheme to combat the rural livelihood crisis with a notion of proving at least 100 days of compensation employment in a financial year for a 5-member family named as Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) which was passed on 23 August 2005 and was effected in February 2006 by the Government of India. Mid-channel bar It is a geomorphic feature developed in the centre of a river or stream channel in the old stage of the river. The distinguishing characteristic of this phenomenon is a raised area of silt or bed material that emerges in the middle of the watercourse. Mixed bank A mixed bank in a river context refers to a situation where the riverbank consists of both cohesive (fine-grained, clay-like) and non-cohesive (coarse-grained, sandy, or gravelly) materials. Monsoon regime The monsoon regime in India is a significant meteorological phenomenon characterized by a seasonal shift in wind patterns and precipitation. The monsoon regime greatly influences river discharge in the Bengal region, which includes the Ganga-Brahmaputra-Meghna (GBM) river basin. Mouza Map Mouza map (Cadastral Map) is a large-scale map (scale 1:3960) for revenue collection for the smallest administrative unit of India. Mouza Mouza refers to the smallest administrative units for revenue collection in India and Bangladesh. Natural approach Study of an event say bank erosion from the perspective of the natural process dynamics that can operate without any kind of human intervention. Natural capital It is more familiar with the land, soil, water bodies, forest, rivers, etc., that are helpful to generate means of survival. NBS NBS stands for near bank stress which estimates the level of shear stress acting upon the river bank due to channel hydraulic conditions. With the help of the Near Bank Stress and Bank Erosion Hazard Index, bank Assessment for Non-Point Source Consequences of Sediment has been calculated. Non-cohesive bank A riverbank of non-cohesive soils is referred to as a noncohesive riverbank composed of granular particles that do not firmly adhere to one another and have low inherent strength and hence becomes fragile in the wake of the hydraulic forces. Non-farm income Non-farm income is the term used to describe earnings or revenue produced by individuals or families from sources other than farm income. Off-farm income Off-farm income refers to the portion of farm household income which is derived from the off-farm wages and salaries, pensions, and interest income earned by farm households. Para It is a hamlated settlement that is inhabited by a specific group of the population.

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Peninsular sediment Sediments carried out from the Peninsular plateau also known as the cratonic sediment usually old and resistant to erosion. Personal process It refers to the social interaction operating within an individual. Physical capital Includes basic infrastructures like roads, canals, buildings, machines for performing occupations, etc. Piers In architecture, piers are the structural units (pillars and walls) that support upright structures such as bridges and arches. Piping erosion In the context of rivers, piping erosion is a phenomenon that affects both naturally occurring riverbanks and man-made embankments along river systems. It is a process where water flowing through the soil erodes fine particles and creates subsurface channels or pipes within the riverbank. This erosion may undermine the structure of the riverbank and cause instability, which may result in bank collapse and subsequent changes in the river’s pathway. Rabi Rabi refers to the winter season in which crops are cultivated mainly depending on irrigation facilities. Radius of curvature The radius of curvature refers to the radius of a circle drawn through the apex of the meander bend and two crossover midpoints Rajmahal hills A residual hill at the northern part of the Chotanagpur plateau. Rating curve The relationship between the stage (water level or height) of a river or stream and its associated discharge (volume flow rate) is represented by a rating curve, also known as a stage-discharge curve or a discharge rating curve. It is a fundamental tool used in hydrology and river flow monitoring to estimate the flow rate of water in a river at different stages. Rational approach It is different from the natural or behavioural approach which comes through logical reasoning for a better understanding of an event. Reach A “reach” in the context of a river refers to a particular section or stretch of the river that is selected for research. Reach characteristics include the channel form, flow regime, movement of sediment, and ecological characteristics. Remittance Remittance is a process of transferring money from one location to another, usually from a foreign worker’s home country to their own, or their family and dependents. These financial transfers are usually sent to support the financial needs of the recipient and often occur regularly. Resilience Risk is the chance or probability of a particular event as well as any potential negative effects or consequences. It combines the likelihood that an event will occur and the potential magnitude of its effects. Reynolds number The ratio of inertial forces to viscous forces within a fluid is known as the Reynolds number (Re). It is a dimensionless quantity that is used in fluid mechanics to identify the characteristics of a fluid. Risk society A society that is facing enormous risk. Risk strategy It is a strategy to combat risk. Risk Risk refers to the probability or likelihood of a specific event and the potential negative consequences or impacts associated with that event. It is the combination of the probability of an event happening and the potential severity of its consequences.

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Riverbank erosion The process by which the soil and sediment of river banks are gradually eroded and transported downstream by the force of the flowing water. The process is influenced by two key factors: the shear stress of the fluid and the shear strength of the river bank. River regime River regime generally describes the fluctuation of the flow of rivers in the different seasons. More specifically, it illustrates the relationship of a river discharge with its width, depth, and slope of the valley. Rural livelihood The term “rural livelihood” describes the ways that individuals who live in rural regions make a living to support their families, and maintain their general well-being. Scouring Scouring is an erosional process of the hydrodynamics forces that removes the materials from an object. Seasonality The fluctuation of conditions or phenomena due to changes in the season. Sediment budget A sediment budget is an accounting and investigation into the movement and balance of sediment within a particular area, such as a river basin, coastal zone, or any other geomorphic unit. Sediment flux The movement of sediment from its source to the sink region by natural and anthropogenic activities. Sediment load The entire quantity of sediment (particles and debris) transported by a river, stream, or other natural waterway over a specific time period is referred to as the sediment load. Sediment movement is an important component of fluvial geomorphology and hydrology because it influences the dynamics of river systems overall and shapes river channels and floodplains. Sediment production Sediment production is the process of producing and providing sediment particles to a river, stream, or other sedimentary settings from numerous sources, such as rocks, soils, and organic components. It is a normal geologic process that is essential for producing sedimentary deposits, sculpting landscapes, and preserving the equilibrium of material at the Earth’s surface. Seepage Seepage describes the steady, sluggish flow of water through soil or other porous materials. It happens when water infiltrates into or passes through the gaps between soil particles or other porous materials. Sensitivity Sensitivity in the context of hazards and disasters refers to how susceptible or vulnerable a community, population, or system is to the possible negative effects of a hazard or disaster occurrence. Settlement densification Settlement densification refers to the process of increasing the density of human settlement in a region. Shear failure Shear failure is a mechanical phenomenon that happens when a material or structure deforms or fails as a result of a shear stress that is greater than its shear strength. Shillong Plateau Shillong Plateau is a rolling tableland located in the Meghalaya state, north-eastern region of India. Garo, Khasi, and Jayanti hills bordered this plateau in western, southern, and northern parts respectively. This region is composed mainly of ancient Precambrian rocks with the overturned fringe of

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Tertiary and Mesozoic sediments which is also an outlier of the Indian peninsular shield. The average elevation of the plateau is about 1500m. Shocks The term “shocks” in the context of disaster refers to the sudden and significant change caused by an unexpected event that has a direct influence on the physical and mental health of an individual. Site A “site” in geomorphology refers to a particular place or location where geologists, geomorphologists, or researchers carry out in-depth analyses and investigations to comprehend the geological processes, landforms, and history of that specific area. Geomorphological sites are selected based on their unique features, geological significance, and potential to provide insights into the formation and evolution of landscapes. Slumping When discussing river erosion, the term “slumping” describes a specific kind of slope failure that takes place along a river’s banks. Sections of the riverbank collapse and migrate downwards as a result of the loss of stability or support. Slumping is frequently caused by the erosive forces of the river’s flow, which erodes and weakens the structure of the bank leading to failure. Social capital It considers social integrity, cohesiveness, network relation, etc. Social engineering To improve preparedness, resilience, and adaptive skills in the face of disasters, “social engineering” refers to the purposeful employment of methods and tactics to affect social behaviours, attitudes, and practices. It entails fostering constructive adjustments in how people view catastrophes, act upon them, and recover from them. Social fission The term “social fission” describes a division or splitting that takes place inside a social group, a community, or a society. It entails the separation or fragmentation of formerly cohesive groups into smaller, distinct groups. Disagreements, confrontations, and changes in values, are some of the causes of social fission. Social fusion The term “social fusion” describes the process of combining many social groupings, cultures, or identities into a unified and peaceful whole. It entails the interaction of several people or groups, frequently with varying histories, values, and customs, in order to create a cohesive social fabric. Increased collaboration, understanding, and shared experiences between various groups can result from social fusion. Social pathology In a society, social disorders, problems, and anomalies are studied and analysed as social pathology. Understanding the origins, effects, and manifestations of many problems that impair social systems is its main emphasis. Identifying the fundamental causes of behaviours, circumstances, and events that depart from a society’s norms and values is the goal of social pathology. Stratigraphy River bank stratigraphy refers to the arrangement and layering of different sedimentary deposits and materials that make up the geological structure of a river bank. It entails the investigation and evaluation of the different sediment layers and their composition, which can reveal important details about the history of the area and present environmental changes.

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Tajfel matrix It is a probability matrix propounded by Tajfel (1970) for depicting social segregation and clubbing in response to a utility distribution in the wake of Hazard. It is useful to detect the normal and hazardous psychology of the people in a region. Tant It denotes handloom, a type of cottage weaving industry. Technocentric It is an approach where technology is the means of solution. Til It is a type of oil seed. Toe Erosion Module Toe Erosion Module refers to a specific method developed to analyse erosion precisely at the base or toe of riverbanks. Transects Transect is a typical technique used to monitor and quantify erosion rates in many natural habitats, notably along shorelines, riverbanks, and other erosionprone locations. A transect is a linear path or line that is established across a specific area of interest. Transects offer a methodical approach for collecting information on elevation changes, sediment movement, and other characteristics across a predetermined distance in the context of measuring erosion rate. Union Union refers to the rural areas located between Mouza and the sub-district or upazila. Vetiver Chrysopogon zizanioides is also known as vetiver and khus. It is a perennial bunchgrass of the family Poaceae. Vetiver is mostly related to Sorghum but dividends many morphological features with other fragrant grasses, such as lemongrass, citronella, and palmarosa. Vulnerability It refers to the state of being susceptible to harm, damage, or adverse impacts from various hazards or stressors. Key characteristics of vulnerability include a. Exposure (a position where a person or entity can come into contact with a hazard or stressor); b. Sensitivity (the degree of responsiveness or reactivity of an individual, community, system, or environment when exposed to that particular hazard), and c. Adaptive capacity (the ability to cope with, respond to, and recover from the impacts of a hazard). Wavelength It is the horizontal distance between the two successive meander crests. Width index In denotes the ratio between the actual width and the ideal width of a channel. Width-depth ratio It is the ratio between the width and depth of a river channel. Zaid Zaid refers to the summer season in which crops are grown in the dry months between the rabi and kharif seasons. Zamindar Local landlord who is a landowner, especially one who leases his land to tenant farmers.

Index

A Above poverty level (APL), 289 Agrarian distress, 12 Agrarian economy, 31, 201, 202, 206, 209, 219, 230, 245, 287, 300, 321 Agricultural productivity, 12, 239–241 Ajay, 32, 50, 58–64, 66, 108, 161, 166, 179, 187, 189, 190, 318 Akandanga, 34, 35, 55, 56, 119, 123–125, 205, 207–211, 213–221, 223–225, 228–230, 232, 236–239, 241–243, 245, 250–254, 257–262, 265, 266, 277, 288, 290, 299, 304–306, 308, 310 Amplitude, 138, 139, 148, 159–161, 163–168, 175, 178, 325 Animal husbandry, 31, 303, 306 Anthropogenic, 6–8, 10, 41, 45, 54, 61, 76, 99, 101, 128, 132, 136, 139, 147, 184, 325, 334 Antyodaya yojna, 289 Arc angle, 159, 160, 169, 171, 172, 325 Asset, 203, 204, 206, 213–214, 229, 264, 265, 287, 326 Asset profile, 204–214 Avulsion, 9, 157

B Bank-attached bar, 277, 281 Bank erosion, 1, 4, 24, 41, 43, 99, 145, 147, 285, 287, 317 Bank erosion victims, 211, 221, 264, 281, 285, 287, 292, 303, 306, 320, 321 Bank material compositions, 49, 54, 55

Bansloi, 61 Bar dynamics, 182–185 Barrage, 41, 43, 76, 90, 99, 100, 104, 187, 318, 319, 321, 322 Basin-scale analysis, 111–118 Below poverty level (BPL), 289 Bengal Delta, 1, 10, 14, 26–33, 35, 43–45, 49–54, 76–92, 100, 117, 125, 137, 145, 147, 151, 180, 182, 186, 206, 209, 285, 313, 322, 326 Berhampore, 50, 61, 63–65, 104–108, 110, 134, 135 Bhagirathi, 24, 49, 99, 145, 147, 250, 288, 319 Bhatia, 10, 320, 327 Bidi binding, 203, 226, 306–308 Bio-engineering, 285, 297–299, 313, 327 Bi-polar society, 279 Brahmaputra, 24, 27–29, 31, 45, 52, 79, 83–85, 99, 111, 117, 119, 122, 130, 147–151, 156, 181–185, 187, 206, 244, 297, 303, 304, 306, 320, 321, 326, 330 Braiding, 5, 9, 145, 180–187, 244, 318, 327 Brass metal industry, 34, 123, 215, 217, 219, 223, 226, 228, 246, 252, 262, 273, 276, 299–303, 305 Brick fields, 130, 131 Brick mattressing, 293, 294

C Catchments, 13, 14, 16, 44, 73, 127 Channel asymmetry, 188, 193–197, 327 Channel cut-off, 158, 159, 304, 327 Channel dynamics, 24, 101, 159, 175, 193

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Islam, S. K. Guchhait, Riverbank Erosion in the Bengal Delta, Springer Geography, https://doi.org/10.1007/978-3-031-47010-3

337

338 Channel efficiency, 192 Channel form index (CFI), 192 Channel geometry, 54, 55, 145, 159, 162, 188–192, 296 Channel index, 156 Channel instability, 7, 28, 60, 61, 127–130, 147, 159, 165, 173, 327 Channel lengths, 152–155, 157, 159, 160, 168–170, 181 Channel morphology, 100, 135, 139, 145, 147–197 Channel oscillation, 31, 32, 58, 77, 80, 81, 83, 84, 86, 87, 135, 147–158, 168 Channel planform, 147–187 Channel shifting, 9, 31, 91, 92, 135 Char-Kashthasali, 34, 35, 55, 56, 120, 123–125, 204–207, 209–211, 213–221, 223–226, 228, 229, 232, 236–243, 246, 250, 251, 277, 299, 307, 308, 310 Charland, 5, 114, 120, 124, 125, 145, 187, 211, 235–241, 244–245, 276–282, 296, 303, 304, 319, 327 Chi-square test, 207, 210 Churni, 147 Chute cut-off, 148, 149, 157, 159 Civil engineering, 43, 285, 295, 296, 298, 328 Climate change, 7, 107, 244, 245, 285, 317–319, 322, 323 Coastal erosion, 26, 59, 245 Cohesive banks, 49, 139, 327 Common property resource (CPR), 31, 282, 303–305, 327 Community initiatives, 291 Community resource management, 303 Controlled hydrology, 7, 50, 64, 108, 163, 167, 187, 194, 327 Cottage industry, 202, 306–308, 322, 331 Crisscross porcupines, 294 Crop diversity, 12, 237, 328 Cropping intensity, 12, 235–237, 328 Cross-section, 89, 188, 189, 194 Cycle of erosion, 3 Cyclic displacement, 212

D D50, 62, 64, 66 Damodar, 58, 318, 321 Dams, 6, 10, 11, 41, 43, 45, 99, 128, 295, 318, 321, 322, 327 Delta, 5, 24, 32, 44, 58, 99, 100, 116, 147–150, 183, 187, 292, 318–320, 322

Index Densification of settlements, 310–313 Depth index, 188, 191–192, 328 Digital shoreline analysis system (DSAS), 74–92, 328, 331 Direction angle, 159, 160, 169, 172, 173, 328 Disaster, 13, 23, 135, 223, 256, 272, 292, 293, 297, 328, 334, 335 Discharge, 6, 11, 50, 52, 54–61, 64, 65, 73, 99–101, 103–110, 128, 135, 159, 174, 177, 179, 187, 189, 190, 194, 196, 281, 295, 296, 321, 326, 332–334 Displacement, 12, 110, 209, 210, 212, 287, 317, 319, 320, 327 Distribution of income, 218–221 Dredging, 293, 294 Dumping geo-bags, 294

E Ecological benefits, 46 Emic perspectives, 145, 268, 269, 276, 329 Environmental refugees, 10, 12, 202, 208, 261, 272, 299, 306, 310, 317, 320, 321, 327, 329 Erodibility, 5, 55, 68, 70–73 Erosion pin, 6, 25, 66, 68 Erosion-accretion sequence, 92, 117 Erosion sciences, 13, 67, 68 Erosivity, 5, 45, 55–57, 329 Etic perspectives, 268–276, 329 Ex-situ models, 308–313

F Farakka, 27, 64, 76, 90, 92, 100, 103–106, 152–155, 159, 162, 163, 167, 168, 170–174, 176–181, 188–192, 195–197, 319, 321 Farakka Barrage Project (FBP), 52, 64, 76, 78, 100–104, 106–108, 135, 159, 161, 163, 166, 168, 174, 175, 177, 179, 180, 192, 196, 223, 225, 318, 329 Farm income, 204, 215, 230 Fears, 264, 266 Feeder canal, 61, 62, 64, 66, 78, 100, 106–108, 110, 189, 329 Field techniques, 66–68 Financial capital, 203, 329 Fishing, 31, 211, 304–306, 320 Flood, 147, 159, 163, 166, 171, 174, 179 Floodplain, 5, 10, 11, 44, 69, 73, 79, 113, 128, 159, 334

Index Floods, 9, 10, 24–26, 32, 50, 58, 61, 104, 107, 131–133, 208, 240, 244, 252, 287, 290, 297–299, 318, 319, 322, 326, 328, 329 Flow fluctuations, 99, 100, 103, 107, 108 Flow hydrology, 9 Fluvial systems, 3, 11, 43, 139, 148, 180, 181, 276, 292, 295 Food subsidies, 288

G Ganga, 24, 52, 99, 147, 287, 318 Ganga-Brahmaputra-Meghna delta, 26–28 Ganjadanga, 34, 35, 204, 205, 207–211, 213–221, 223–225, 228–230, 232, 238, 240–243, 245, 246, 252–254, 257–262, 264–266, 299, 307, 308, 310 Gauge stations, 59, 61, 63, 104–108 Gender space, 264 Gibbs-Martin Index, 236 Gini Coefficient, 219, 221 Government, 206, 214, 250, 254, 271, 288–290, 292, 296–299, 305–307, 313, 327, 332 Groundwater recharge, 50 Group process, 255, 256, 260–263, 330 Groynes, 294, 297, 327 Guide bank, 135–137, 330

H Hardinge bridge, 103 Harirampur, 125, 126 Hazards, 4–13, 23, 24, 26, 31, 32, 35, 43, 55, 68, 70, 100, 114, 145, 201–204, 215, 218, 219, 223, 226, 230, 232, 233, 249, 250, 252–256, 258–260, 262, 264–267, 269, 270, 274, 276, 285, 287, 288, 290, 292, 301, 306, 313, 318–320, 322, 326–332, 334, 336 Head count index, 222 Healthcare, 249, 253–254 Herfindahl-Hirschman Index (HHI), 227, 228 Historical perspective, 6–11 Hooghly, 24, 31, 32, 60, 62, 63, 78–82, 99–101, 115, 118, 122, 138, 148–156, 181–183, 185, 187, 287 Human capital, 204, 330 Human geography, 31 Hydraulics, 4, 6, 45, 47–50, 62, 64, 68, 69, 72, 78, 91, 100, 107, 128, 135, 147, 156, 159, 167, 177, 184 Hydraulic sinuosity index (HSI), 149, 152–156

339 Hydrograph, 58, 61, 62, 69, 107–109 Hydrological cycle, 107, 318

I Identity crisis, 258 Income inequality, 258 Indo-Bangladesh water sharing treaty, 61 Ingroup favouritism, 267 Inland Waterway Authority of India (IWAI), 135, 137 In-situ models, 300–308 Intergroup processes, 255, 256, 258–260, 263, 330

J Jalangi, 27, 32, 61, 63, 147, 149, 156, 161 Jamuna, 24, 29–31, 53, 114, 125, 135, 297, 320 Jangipur barrage, 100

K Katwa, 28, 50, 55, 61–65, 78, 104, 105, 108, 110, 152–155, 157, 161, 166, 168, 172, 181, 182, 189, 193 Kinship, 249–251

L Labour market, 229 Labour migration, 292, 300, 308–310, 319–321 Land use and land cover (LULC), 10, 41, 109–125, 128, 205 Lateral erosion, 3, 4, 7, 11, 24, 25, 189 Linear movement, 212 Litholog, 51, 55, 56, 189 Livelihood, 12, 32, 34, 43, 201–204, 216, 219, 221, 223, 225, 229, 242, 245, 246, 267, 272, 288, 292, 303, 306, 307, 317, 319–322, 326, 329, 331, 332, 334 Livelihood strategies, 203 Livelihood vulnerability, 35, 114, 115, 203, 204, 230–235, 290, 331 Lorenz Curve, 219

M Mahajan, 213, 242, 300–303, 307, 331 Mainland, 209, 211, 235–241, 244–245, 296, 320, 321 Malda, 100, 149, 326

340 Marriage, 145, 213, 249, 257, 258, 269, 270, 277, 302 Mathabhanga, 147 Matiari, 34, 35, 55, 56, 119, 120, 123–125, 203, 205–211, 213–221, 223–229, 232–243, 245, 246, 250, 252–254, 257–262, 264–277, 290, 296, 299–302, 305, 331 Maximum Joint Profit, 267 Maximum Likelihood Classifier (MLC), 113 Mayurakshi, 50, 60–62, 64, 108, 179, 187, 318 Meander, 11, 24, 25, 76, 101, 137, 148–150, 156–180, 325, 331–333, 336 Meander deformations, 147–151 Meander form index, 159, 161, 178–180 Meander shape index, 159, 161, 175, 177–180 Meghna, 24, 31, 45, 54, 60, 79, 86–88, 114, 117, 120, 122, 147–156, 181–187, 206, 244, 318, 320, 321, 326, 330 Mekong, 24, 58–60, 115, 121 Mid-channel bar, 92, 136, 180, 276–281, 332 Migration, 11, 12, 25, 29, 31, 32, 44, 123, 135, 202, 209–211, 215, 246, 272, 288, 292, 300, 308–310, 319–322 Minimum Joint Benefit, 267 Mississippi, 11, 44, 49, 113–115, 121, 127 Mixed bank, 49, 57, 332 Mixed economy, 322 Monsoon regime, 58–59, 332 Mouza, 34, 55, 92, 118–120, 123–125, 127, 206, 211, 215, 236, 237, 239–241, 245, 272, 299, 304, 305, 320, 332, 336 Mulberry plantations, 202, 203, 254, 288, 290, 291 Murshidabad, 28, 61, 100, 117, 136

Index P Padma, 24, 29, 31, 53, 60, 76–78, 100, 104, 111, 114, 116, 117, 120, 125, 126, 147–149, 151, 183–185, 187, 304, 318, 320, 321 Pagla, 61 Palaeochannel fishing, 304–306 Palaeochannels, 31, 303–306 Permeable spur, 294 Phobias, 264, 266 Physical capital, 203, 333 Physical geography, 31 Physical stress, 264–266 Piping action, 52, 99 Population explosion, 285 Poverty, 12, 204, 221–223, 289 Poverty gap index, 222–224 Poverty indices, 223, 224 Poverty severity index, 222–224 Price index, 214, 215 Principal component analysis (PCA), 230, 262, 263 Psychological stress, 264, 266 Public distribution system (PDS), 288–290

N Nabadwip, 34, 55, 61, 132, 135, 137, 157, 161, 166, 168, 193, 236–238, 240, 296 Nadia, 33, 34, 100, 117, 131, 202, 213, 235–240, 242, 251, 298, 307 Natural capital, 203, 332 Neck cut-off, 148, 149, 175, 178, 304 Non-cohesive bank, 49, 332 Non-cohesive riverbank, 9, 332 Non-farm income, 215, 228, 332 Non-land-based economy, 31, 215, 271

R Radius of curvature, 70, 159, 161, 163–165, 168, 333 Radius/wavelength ratio, 159, 175, 176 Rational approach, 7, 8, 11, 333 Reach, 13, 14, 16, 24, 25, 45, 52, 55, 60, 61, 64, 67, 69, 91, 109, 130, 133, 152, 156–161, 168, 170, 181, 182, 187, 192, 245, 321, 333 Regulated river regime, 99–108, 189 Remittances, 12, 204, 215, 250, 288, 310, 313, 320–322, 329, 333 Revetment, 293–295, 297 Riparian vegetation, 9, 24, 44, 46, 73, 128, 190, 296 Risk, 6, 23, 31, 32, 68–70, 203, 204, 292, 328, 333 Risk strategy, 229, 333 Riverbank erosion research, 1, 6, 8 Road stream crossing, 130, 131, 133–136 Rukunpur, 34, 55, 119, 183, 186, 250, 288, 320

O Occupation diversifications, 310 Off-farm income, 215, 332 Ox-bow lakes, 174, 304

S Sea-level rise, 44, 285, 317, 318, 322, 323 Sediment budget, 62, 132, 295, 334 Sediment flux, 130–133, 318, 334

Index

341

Sediment supply, 43, 44, 61–66 Self-help groups (SHGs), 270 Ship movements, 41, 133, 138, 139 Shock, 5, 31, 203, 204, 227, 228, 230, 245, 253, 258, 264, 266, 270, 285, 292, 308, 322, 331, 335 Sinuosity, 145, 149–157, 174, 175 Site, 13, 16, 32, 44, 55, 56, 60, 110, 112, 187, 210, 211, 213, 281, 282, 295–297, 299, 321, 335 Site-specific analysis, 119–126 Social capital, 204, 335 Social engineering, 285, 292, 299–313, 335 Social fission, 276, 279, 280, 335 Social fusion, 276, 277, 279–282, 335 Social institutions, 249–254 Social processes, 145, 249, 255–264, 267, 276–282 Social psychology, 145, 249, 255, 256, 263–267 Social vulnerability, 13, 34, 252 Soil erodibility, 55 Space-time in bank erosion, 15 Spatial scale, 13, 14 Standard sinuosity index (SSI), 149, 152–156 Storm surges, 9, 10, 26, 59–60, 111, 322 Stratigraphy, 6, 49, 53, 54, 78, 335 Sujanpur, 34, 35, 204–206, 209, 211, 213–221, 223–229, 232, 299

Tectonic movements, 9 Temporal scales, 1, 14, 16, 127 Tension, 266 Terrestrial laser, 67–68 Thermal Power Project, 100 Topographic sinuosity index (TSI), 149, 152–156 Total station, 6, 67–68 Two-stage PCA, 262

T Tajfel matrix, 267, 268, 326, 336 Tant, 226, 270, 306–308, 336

Z Zaminders, 219

U Upazila, 125, 126, 297, 336 Urbanization, 5, 12, 41, 54, 115, 116, 127, 128

V Valley index (VI), 152–157 Vulnerability, 6, 10, 13, 252, 271, 282, 285, 292, 299, 300, 321

W Wavelength, 111, 159–161, 163, 164, 167, 168, 178, 336 Width/depth ratio, 189 Width index, 188, 190–191, 336 Wooden piling, 294