Water Conservation and Wastewater Treatment in BRICS Nations: Technologies, Challenges, Strategies and Policies [1 ed.] 012818339X, 9780128183397

Table of contents :
Cover
Water Conservation and Wastewater
Treatment in BRICS Nations:
Technologies, Challenges,
Strategies and Policies
Copyright
Contributors
Chapter 1 - Water-related problem with special reference to global climate change in Brazil
1.1 - Overview of Brazilian water resources
1.2 - Major threats for conservation of Brazilian Amazonian water resources and aquatic biodiversity
1.2.1 - Industrial and domestic effluents
1.2.2 - Changes in land-use and deforestation
1.2.3 - Petroleum hydrocarbon
1.2.4 - Pesticides and herbicides
1.2.5 - Global climate changes
Acknowledgments
References
Chapter 2 - Water-related problems with special reference to global climate change in Russia
Abstract
Keywords
2.1 - Introduction
2.2 - Water resources and anthropogenic impacts in Russia
2.3 - Climate change in Russia: trends and projections
2.4 - Impacts on water-related economic sectors
2.5 - Climatic risk management in Russia
2.6 - Conclusion
References
Chapter 3 - Water-related problem with special reference to global climate change in India
Abstract
Keywords:
3.1 - Introduction
3.2 - Indian context on climate change and water
3.2.1 - Climate change and precipitation
3.2.2 - Climate change and Indian monsoon pattern
3.2.3 - Climate change and glaciers of Himalaya
3.2.4 - Climate change and groundwater resources
3.2.5 - Climate change and drought and flood
3.3 - Impact on agricultural economy
3.4 - Indian context on climate change and water policies
3.5 - Scientific simulation model for future prediction
3.5.1 - The Soil and Water Assessment Tool (SWAT) modeling
3.5.2 - General Circulation Model or Global Climate Model (GCM)
3.5.3 - Regional Climate Modeling (RCM)
3.5.4 - ClimGen
3.5.5 - Precipitation Runoff Modelling Systems (PRMS)
3.6 - Conclusion
References
Chapter 4 - Water-related problems with special reference to global climate change in China
4.1 - Global climate change and China’s water resources status
4.1.1 - Global climate change and water vulnerability
4.1.2 - The status of China’s water resources
4.1.3 - The research history of the impact of climate change on hydrology and water resources
4.2 - China’s water problem in the context of climate change
4.2.1 - Climate change poses new challenges to China’s solutions to the water problem
4.2.2 - The sensitivity of China’s water systems to climate change
4.2.3 - Quantitative analysis of the impact of climate change on the measured runoff of typical rivers in China
4.3 - Quantitative evaluation of the vulnerability of China’s water systems under climate change conditions
4.3.1 - The concept and understanding of water resources vulnerability
4.3.2 - Index system construction
4.3.3 - Evaluation method
4.3.4 - Evaluation conclusion
4.4 - Future climate change trends in China and adaptive countermeasures
4.4.1 - Possible future climate change trends
4.4.2 - Climate change adaptive countermeasures
References
Chapter 5 - Influence of global climate change on water resources in South Africa: toward an adaptive management approach
5.1 - Introduction
5.2 - State of water resources and their management in South Africa
5.2.1 - Water availability
5.3 - Water resource quality
5.3.1 - Microbial pollution
5.3.2 - Eutrophication
5.3.3 - Salinization
5.3.4 - Acid Mine Drainage (AMD)
5.4 - Potential climate change impacts on water resources in South Africa
5.4.1 - Impacts on surface water resources
5.4.2 - Impacts on groundwater resources
5.4.3 - Impacts on rainwater harvesting
5.5 - Water security and governance in face of climate change risks
5.5.1 - Transitions toward adaptive management of water in South Africa: sector-wide challenges and opportunities
5.5.2 - Potential technologies in adaptation of the water sector to climate change
5.5.3 - Climate smart agriculture
5.5.4 - Recycling and reuse strategies
5.5.5 - Desalination
5.5.6 - Role of governance in adaptation to climate change
5.6 - Conclusion
References
Chapter 6 - Recent trends and research strategies for treatment of water and wastewater in Russia
6.1 - Introduction
6.2 - Materials and methods
6.3 - The Russian water supply and sanitation sector: key trends and uncertainties
6.4 - Strategies for Russian water supply and sanitation companies
6.5 - Policy recommendations for the governance of water resources
6.6 - Conclusion
Acknowledgments
References
Chapter 7 - Recent trends and research strategies for treatment of water and wastewater in India
7.1 - Introduction
7.2 - Water resources in India
7.2.1 - Water demand
7.2.2 - Water sources
7.2.3 - Water supply
7.3 - Water contaminants
7.4 - Water treatment technologies
7.4.1 - Thermal (heat-based) technologies
7.4.2 - Solar disinfection
7.4.3 - UV light technologies using lamps, including UV light-emitting diodes
7.4.4 - Coagulation–flocculation and/or sedimentation
7.4.5 - Chemical disinfection
7.4.5.1 - Chlorination
7.4.5.2 - Disinfection with iodine
7.4.5.3 - Ozone disinfection
7.4.5.4 - Disinfection by strong acids or bases
7.4.5.5 - Silver- and copper-based disinfectants
7.4.6 - Ion exchange
7.4.7 - Filtration
7.4.7.1 - Cloth filters
7.4.7.2 - Ceramic filters
7.4.7.3 - Granular media filters
7.4.7.4 - Carbon adsorption
7.4.7.5 - Ultrafiltration
7.4.7.6 - Nanofiltration
7.4.7.7 - Reverse osmosis
7.5 - Treatment of wastewater
7.5.1 - Primary treatment
7.5.1.1 - Screening
7.5.1.2 - Filtration
7.5.1.3 - Centrifugal separation
7.5.1.4 - Sedimentation and gravity separation
7.5.1.5 - Floatation
7.5.2 - Secondary treatment
7.5.2.1 - Aerobic decomposition
7.5.2.2 - Anaerobic decomposition
7.5.3 - Tertiary treatment
7.5.3.1 - Soil aquifer treatment
7.5.4 - Use of wastewater in agriculture and aquaculture
7.5.5 - Production of drinking water from wastewater
7.6 - Technological advances in water purification technologies
7.7 - Conclusion
References
Chapter 8 - Recent trends and research strategies for wastewater treatment in China
8.1 - A definition of wastewater and an overview of wastewater in China
8.1.1 - Definition of wastewater
8.1.2 - Types of wastewater treatment in China
8.1.3 - Commonly used methods in wastewater treatment
8.2 - Advances in wastewater treatment technology and research in China
8.2.1 - Process flow
8.2.2 - Sludge disposal
8.2.3 - Chlorination
8.2.4 - Phosphorus and nitrogen removal
8.3 - Methods and research progress in water treatment in different industries in China
8.3.1 - Industrial field
8.3.1.1 - Electroplating wastewater
8.3.1.2 - Heavy metal wastewater
8.3.1.3 - Grading
8.3.2 - Domestic water
8.3.3 - Environmental field
8.4 - Characteristics and experience of wastewater treatment in China
8.4.1 - Micro-electrolysis technology used in wastewater pretreatment
8.4.2 - Research on ceramic membranes: from organic membranes to inorganic membranes
8.4.3 - Combining water management and other administrative means to improve wastewater treatment efficiency
8.5 - Conclusion
References
Chapter 9 - Recent trends and national policies for water provision and wastewater treatment in South Africa
9.1 - Introduction
9.2 - The human right to water in South Africa
9.3 - Drinking water infrastructure in South Africa
9.4 - Water services regulation framework in South Africa
9.5 - Blue Drop Certification scheme
9.6 - Overview of wastewater treatment facilities in South Africa
9.7 - Wastewater reuse in South Africa
9.8 - Conclusion
References
Chapter 10 - Government initiative and policies on water conservation and wastewater treatment in Brazil
10.1 - Introduction
10.2 - Historical and legal framework
10.3 - National Policy of Water Resources – PNRH
10.3.1 - Water resources plans
10.3.2 - Framing of water bodies in classes of prevailing uses
10.3.3 - Granting of rights to use water resources
10.3.4 - Charge for the use of water resources
10.3.5 - National Information System on Water Resources
10.4 - Administrative aspects
10.5 - Additional government initiatives
References
Chapter 11 - Government initiative and policies on water conservation and wastewater treatment in Russia
11.1 - Introduction
11.2 - Materials and methods
11.3 - Water infrastructure state and environmental issues
11.4 - National regulation
11.5 - Water supply and sanitation infrastructure management system
11.6 - Tariff policy and financial standing of enterprises
11.7 - Water meters
11.8 - Mechanisms of public private partnership
11.9 - Is it possible to increase tariffs?
11.10 - Are there alternatives to unitary enterprises and concession?
11.11 - Conclusion
Acknowledgments
Legislative and normative acts
Chapter 12 - The role of sustainable decentralized technologies in wastewater treatment and reuse in subtropical Indian con...
12.1 - Introduction
12.2 - Decentralized wastewater treatment: Case studies
12.2.1 - Constructed wetlands
12.2.2 - Rooftop wastewater treatment gardens
12.2.3 - Zero liquid discharge technology for industry
12.3 - Conclusion
References
Chapter 13 - An exploration of China’s practices in water conservation and water resources management
13.1 - Introduction
13.2 - The evolution of water resources management in China
13.2.1 - Water resources management before the founding of the People’s Republic of China
13.2.2 - Water resources management after the founding of the People’s Republic of China
13.2.2.1 - Initial stage of water resources management (1949∼1977)
13.2.2.2 - The water supply management stage (1978–1997)
13.2.2.3 - The transitional stage of water demand management (1998∼2010)
13.2.2.4 - The deepening reform stage of water resources management (2011∼)
13.3 - The Most Stringent Water Resource Management System
13.3.1 - Background
13.3.2 - Implementation
13.3.3 - The Four Systems structure
13.3.3.1 - Total water consumption control system
13.3.3.2 - Water use efficiency improvement system
13.3.3.3 - The system on pollution carrying capacity in water functional zones
13.3.3.4 - The accountability and appraisal supporting system
13.4 - Achievements and major problems of water resources management in China
13.4.1 - Achievements
13.4.2 - Major problems
13.4.2.1 - A flawed monitoring system
13.4.2.2 - Incomplete reflection of regional differences
13.4.3.3 - An inadequate legal system
13.5 - Future trends in water resources management in China
13.5.1 - A management philosophy focused on sustainability
13.5.2 - A shift in the object of management
13.5.3 - Management objectives focused on diversification
13.5.4 - Management that combines administrative management and market forces
13.5.5 - Management that is gradually refined
13.6 - Conclusion
References
Chapter 14 - Government initiatives and policies for water conservation and wastewater treatment in South Africa and indige...
14.1 - Introduction
14.2 - Water management: A driver of the Millennium Development Goals
14.3 - Water legislation
14.3.1 The Constitution of the Republic of South Africa, 1996
14.3.2 The Water Services Act (Act 108 of 1997)
14.3.3 The White Paper on Water Supply and Sanitation Policy
14.4 - Government initiatives for water conservation
14.5 - Wastewater treatment in South Africa
14.6 - Indigenous knowledge and development
14.7 - Conclusion
References
Chapter 15 - Future prospects for the management of water resources in Russia using indigenous technical knowledge
15.1 - Introduction
15.2 - ITK conceptual framework
15.2.1 - Origins of the ITK concept
15.2.2 - Development of the ITK concept in Russia
15.3 - Opportunities for integration of ITK into water resources management in Russia
15.3.1 - Water supplies
15.3.2 - Demographic structure
15.3.3 - Regulatory environment
15.4 - Case studies of ITK application to water resources management in Russia
15.4.1 - Fishing in the Yamalo-Nenets Autonomous District
15.4.2 - Sea hunting in the Chukotka Autonomous District
15.4.3 - Poaching in the Khanty-Mansi Autonomous District
15.5 - Conclusion
Acknowledgment
References
Chapter 16 - Indigenous knowledge systems in sustainable water conservation and management
16.1 - Introduction
16.2 - Indigenous knowledge in water conservation and management: some examples
16.3 - Conclusions
Acknowledgment
References
Chapter 17 - The future prospect of China’s independent R&D technology (ITK) in water resources utilization and wastewater ...
17.1 - Introduction
17.2 - The general situation of water resources in China
17.3 - Problems in water resources utilization in China
17.4 - Development of seawater utilization technology
17.4.1 - Seawater desalination technology
17.4.2 - Seawater cooling technology
17.4.3 - Seawater desulfurization technology
17.4.4 - Comprehensive utilization technology of seawater chemical resources
17.4.5 - Marine water source heat pump technology
17.4.6 - Seawater irrigation technology
17.4.7 - Large-scale seawater technology
17.5 - Development of industrial wastewater treatment technology
17.5.1 - Coagulation-sedimentation method
17.5.2 - Method of adsorption
17.5.2.1 - Magnesium hydroxide
17.5.2.2 - Activated Cellulose Carbon (ACF)
17.5.2.3 - Chitosan and its derivatives
17.5.3 - Biodegradation method
17.5.4 - Ion exchange resin method
17.5.5 - Advanced oxidation-biochemical coupling
17.5.6 - Membrane separation technology
17.6 - Development of domestic sewage treatment technology
17.6.1 - Activated sludge process
17.6.2 - Intermittent activated sludge process
17.6.3 - Oxidation ditch process
17.6.4 - A/A/O process
17.6.5 - Application of membrane separation technology
17.6.6 - Constructed wetland process
17.6.7 - Stabilization pond system
17.7 - Development of circulating cooling water treatment technology
17.7.1 - Acidic formula
17.7.2 - Polyphosphate
17.7.3 - Organic phosphonic acid (ester)
17.7.4 - Development of limited phosphorus formula
17.7.5 - Copolymer scale inhibitor and dispersant
17.7.6 - Special water treatment agent
Chapter 18 - Future prospective and possible management of water resources in respect to indigenous technical knowledge in ...
18.1 - Introduction
18.2 - Global water scarcity
18.3 - Traditional knowledge systems (IKS)
18.4 - Agriculture
18.5 - Land and soil
18.6 - Natural resource management
18.7 - The South African perspective
18.8 - Contribution of water to the South African economy
18.9 - Indigenous knowledge and SA
18.10 - Water management strategies in SA
18.11 - Conclusion
References
Index
Back Cover

Citation preview

Water Conservation and Wastewater Treatment in BRICS Nations Technologies, Challenges, Strategies and Policies Edited by Pardeep Singh Yulia Milshina Kangming Tian Deepak Gusain João Paulo Bassin

Elsevier Radarweg 29, PO Box 211, 1000 AE Amsterdam, Netherlands The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States Copyright © 2020 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www. elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library ISBN: 978-0-12-818339-7 For information on all Elsevier publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Candice Janco Acquisitions Editor: Louisa Munro Editorial Project Manager: Danielle Mclean Production Project Manager: Joy Christel Neumarin Honest Thangiah Designer: Mark Rogers Typeset by Thomson Digital

Contributors Denis Moledo de Souza Abessa  São Paulo State University – UNESP. Praça Infante Dom Henrique, São Vicente, Brazil Adeyemi O. Adeeyo  Department of Hydrology and Water Resources, University of Venda, Thohoyandou, Limpopo Province, South Africa Andrea Pimenta Ambrozevicius  Agência Nacional de Águas – ANA. Setor Policial (SPO), Brasília, Brazil Anwesha Borthakur  Leuven International and European Studies (LINES), KU Leuven, Belgium Penggao Cheng  College of Chemical Engineering and Materials Science, Tianjin University of Science & Technology, Tianjin, China Wei Du  College of Chemical Engineering and Materials Science, Tianjin University of Science & Technology, Tianjin, China Rafael Mendonça Duarte  Biosciences Institute, São Paulo State University–UNESP, Coastal Campus, São Vicente, São Paulo, Brazil Olatunde S. Durowoju  Department of Hydrology and Water Resources, University of Venda, Thohoyandou, Limpopo Province, South Africa Joshua N. Edokpayi  Department of Hydrology and Water Resources, University of Venda, Thohoyandou, Limpopo Province, South Africa Abimbola M. Enitan-Folami  Department of Biotechnology and Food Technology, Durban University of Technology, Durban, South Africa Geoffrey Harris  Department of Public Management and Economics, Durban University of Technology, Durban, South Africa Fan He  China Institute of Water Resources and Hydropower Research, Beijing, China Xinxin Hua  College of Chemical Engineering and Materials Science, Tianjin University of Science & Technology, Tianjin, China Changshuo Huang  Nanjing Hydraulic Research Institute, Nanjing, China Ademola O. Jegede  Department of Public Law, University of Venda, Thohoyandou, Limpopo Province, South Africa

xiii

xiv Contributors Shan Jiang  China Institute of Water Resources and Hydropower Research, Beijing, China Tianyu Liu  College of Chemical Engineering and Materials Science, Tianjin University of Science & Technology, Tianjin, China Rachel Makungo  Department of Hydrology and Water Resources, University of Venda, Thohoyandou, Limpopo Province, South Africa Fhumulani Mathivha  Department of Hydrology and Water Resources, University of Venda, Thohoyandou, Limpopo Province, South Africa Yulia Milshina  National Research University Higher School of Economics, Moscow, Russia John O. Odiyo  Department of Hydrology and Water Resources, University of Venda, Thohoyandou, Limpopo Province, South Africa Daria Pavlova  National Research University Higher School of Economics, Moscow, Russia Liliana N. Proskuryakova  National Research University Higher School of Economics, Moscow, Russia C. Ramprasad  School of Civil Engineering; Center for Bioenergy, SASTRA Deemed University, Thanjavur, Tamil Nadu, India Ajay Vasudeo Rane  Composite Research Group, Department of Mechanical Engineering, Durban University of Technology, Durban, South Africa S. Rangabhashiyam  Department of Biotechnology, School of Chemical and Biotechnology; Center for Bioenergy, SASTRA Deemed University, Thanjavur, Tamil Nadu, India Nkuna Rivers  Department of Hydrology and Water Resources, University of Venda, Thohoyandou, Limpopo Province, South Africa George Safonov  National Research University Higher School of Economics, Center for Environmental and Natural Resource Economics, Moscow, Russia Pardeep Singh  Department of Environmental Studies, PGDAV College, University of Delhi, New Delhi, India Sergey Sivaev  National Research University Higher School of Economics, Moscow, Russia Nazia Talat  Centre for Studies in Science Policy, School of Social Sciences, Jawaharlal Nehru University, New Delhi, India Jiahui Tao  Nanjing Hydraulic Research Institute, Nanjing, China Rookmoney Thakur  Department of Public Management and Economics, Durban University of Technology, Durban, South Africa Surendra Thakur  BankSeta Research Chair (Digitalisation), Durban University of Technology, Durban, South Africa

Contributors xv Binota Thokchom  Centre of Nanotechnology, Indian Institute of Technology Guwahati, Amingao, Assam, India Adalberto Luis Val  National Institute for Amazonian Research, Manaus, Amanzonas, Brazil Tom Volenzo  Department of Hydrology and Water Resources, University of Venda, Thohoyandou, Limpopo Province, South Africa Songbo Wang  College of Chemical Engineering and Materials Science, Tianjin University of Science & Technology, Tianjin, China Jun Xiang  College of Chemical Engineering and Materials Science, Tianjin University of Science & Technology, Tianjin, China Jin Zhang  Center of African Studies, Shanghai Normal University, Shanghai, China Lei Zhang  College of Chemical Engineering and Materials Science, Tianjin University of Science & Technology, Tianjin, China Yongnan Zhu  China Institute of Water Resources and Hydropower Research, Beijing, China

CHAPTE R 1

Water-related problem with special reference to global climate change in Brazil Rafael Mendonça Duartea, Adalberto Luis Valb Biosciences Institute, São Paulo State University-UNESP, Coastal Campus, São Vicente, São Paulo, Brazil; National Institute for Amazonian Research, Manaus, Amazonas, Brazil

a

b

1.1  Overview of Brazilian water resources It is estimated that around 12-14% of global surface water drains through the 12 hydrographic regions in the Brazilian territory, achieving a total water-resource availability of around 91,271 m3/s in the country. The percentage of the total water available from the major water basins is as follows: Amazon: 80.80%, Paraná: 6.52%, Tocantins-Araguaia: 5.97%, São Francisco: 2.07%, Southeast Atlantic: 1.25%, Paraguay: 0.86%, South Atlantic: 0.71%, Uruguay: 0.62%, Parnaiba: 0.42%, Western North Atlantic: 0.35%, Eastern Atlantic: 0.33%, and Eastern Northeast Atlantic: 0.10% (ANA, 2012, 2013; Tundisi, 2008). This unequal distribution of water resources results mainly from differences in the mean annual precipitation among the drainage basin regions, which is reflected in marked regional and seasonal disparities in both the flow rate and availability of water from the rivers in each hydrographic region (ANA, 2013, 2017). These factors, together with the differences in population size, urbanization, industrialization, and agricultural activities that have a great impact on both quantitative (total water catchment) and qualitative (effluent discharges) water demands, have a pronounced impact on water balance throughout the country. For example, in terms of their water balance (i.e., the ratio between quantitative demand and availability), between 2006 and 2010 more than 90% of the main rivers of Amazon, Tocantins-Araguaia, and Paraguay drainage basins were classified as either “good” or “excellent,” while a high proportion of the main rivers and reservoirs of the Eastern Northeast Atlantic (greater than 90.0%), Eastern Atlantic (around 55.0%), and São Francisco and South Atlantic (between 45.0-55.5%) basins were classified as either “critical” or “extremely critical” (ANA, 2013). In the last two decades (data from 1997 to 2017) the demands for water resources in Brazil has increased by over 80%, which represents additional challenges for the maintenance of water availability and quality, and has resulted in severe hindrances to the establishment

Water Conservation and Wastewater Treatment in BRICS Nations http://dx.doi.org/10.1016/B978-0-12-818339-7.00001-1

3

Copyright © 2020 Elsevier Inc. All rights reserved.

4  Chapter 1 of effective policies to water governance (ANA, 2019; Tundisi et al., 2015). According to the National Water Agency (the Agência Nacional de Águas, or ANA), there are multiple water-resource uses in Brazil (such as navigation, hydroelectric generation, fishing, tourism, and leisure) that have little or no impact on the overall quality of water resources. However, water used for irrigation, urban water supplies, industrial applications, and livestock production together comprises more than 92% of the total water withdrawn from these resources (52%, 23.8%, 9.1%, and 8.0%, respectively) (ANA, 2019), and these activities have historically contributed to water quality degradation in several water bodies throughout Brazil (Tundisi et al., 2015; Val et al., 2019). Water quality degradation is known to have had a pronounced negative effect on the total water availability for multiple uses, particular for human supplies, food production, and industrial activities, thus directly compromising water security for human populations. The monitoring of water quality between 2001 and 2011 revealed that most of the water bodies classified as “bad” (19 < WQI < 36) or “terrible” (WQI < 19), under the water quality index (WQI) and “supereutrophic” and “hypereutrophic” under the trophic state index (TSI) drain highly urbanized and industrialized areas, particularly in the Paraná, Eastern Atlantic, São Francisco, Paraguay, and Southeast Atlantic basins (ANA, 2013). As previously revised by Val and colleagues (2019), today eutrophication is one of the biggest factors in water quality deterioration. After 1950 Brazil experienced accelerated urbanization that was not accompanied by widespread investments in wastewater treatment plants and resulted in a large accumulation of organic matter in rivers, lakes, and reservoirs. Nowadays the lack of adequate wastewater treatment infrastructure in urban areas has resulted in the discharge of emerging contaminants from pharmaceutical and personal care products (PCPs), which are present at high levels in wastewater effluent and reach receiving surface waters that includes rivers, lakes, and coastal waters (Pereira, Maranho, & Cortez, 2016). In addition, the large increment in the amount of land used for agricultural and in the use of fertilizers to increase crop production has contributed to the eutrophication of water bodies. Moreover, the alterations in land use associated with extensive agriculture practices have increased pesticide and herbicide contamination of water resources, which has been shown to exert a marked effect on aquatic biodiversity (Braz-Mota, Sadauskas-Henrique, Duarte, & Val, 2015). Furthermore, industrial activities and mineral exploitation have led to a great deterioration in water quality as a result of the input of dissolved organic substances and toxic contaminants, such as heavy metals, into surface waters. This anthropogenic-induced deterioration in water quality has resulted in economic losses for many municipalities and regions due to the increased cost for water treatment for the production of potable water and the cumulative impacts on human heath. It has also negatively affected both the environmental services and the biodiversity of aquatic ecosystems (Tundisi et al., 2015; Val et al., 2019). Significant alterations in hydrological cycles have been predicted in face of global climate change, with marked changes on both precipitation and evapotranspiration regimes that may

Water-related problem with special reference to global climate change in Brazil  5 greatly impact the availability and quality of water resources and potentially increase water vulnerability (Arnell, 1999; IPCC, 2013; Oki & Kanae, 2006). Although the exact impacts of climate changes on global and regional hydrological cycles are controversial and still uncertain, the expectation is that the main hydrographic basins in Brazil will experience pronounced alterations in precipitation and superficial water runoff, and that there will be negative effects on the recharge rates of groundwater aquifers (ANA, 2016). In addition, these changes in regional climate trends have the potential to increase the frequency of extreme climate events resulting in severe droughts and flooding, which have already been seen in some regions in Brazil, such as the three recent extensive floods and two major droughts in the Amazon basin between 2005 and 2012 (Magrin et al., 2014), and the severe droughts in the Southeast Atlantic basin in 2013 and 2014 (Cunningham, Cunha, Brito, Marengo, & Coutinho, 2017; Gomes, Bernardo, & Alcântara, 2017), and in both Eastern Northeast Atlantic and Parnaiba basins between 2012 and 2016 (Marengo, Torres, & Alves, 2017; Marengo, Alves, & Alvala, 2018). These extreme events negatively affected the availability of water resources in those regions and increased the vulnerability of population to waterresources stress, particularly those with low income and in high-risk conditions in highly urbanized areas. Although the ANA considers that Amazonian hydrographic region to have relatively high water security (ANA, 2013) due to its higher water availability and the higher mean flow of its main rivers compared to the other basins, there has been an incremental deterioration of water quality in this region (Borges, 2006; Cunha, Cunha, & Júnior, 2004; Pereira, Monteiro, & Guimarães, 2010). The lack of an adequate infrastructure for basic sanitation in both urbanized and rural areas (Borges, 2006) and an extremely insufficient system for water-quality monitoring (ANA, 2012) have resulted in a deterioration in water quality and reduced access to potable drinking water for human populations, as well as increased the risk to human health relative due to the prevalence of diseases and infections associated with the water available to these human populations (Borges, 2006; Cunha et al., 2004). In addition, the remarkable seasonal variation in the water level of main rivers, called “flood pulses” (Junk, Bayley, & Sparks, 1989), brings additional challenges for access to potable drinking water for riverine human populations in rural areas during drought seasons (Sampaio, 2019). Finally, as seen in other hydrographic regions in Brazil, anthropogenic activities such as mining and industrial enterprises, deforestation and changes in land-use, and the creation of dams for hydroelectric plants have had a significant impact on quality of water resources, enhancing the concern about a potential increase in water vulnerability in the face of global climate change. In this chapter we outline the major threats to water security in the Amazon basin, address the specific challenges associated with human pressures and global climate change on water quality, and analyze the impacts of these alterations on the biodiversity conservation in the largest and richness aquatic ecosystem in the world.

6  Chapter 1

1.2  Major threats for conservation of Brazilian Amazonian water resources and aquatic biodiversity The Amazonian hydrographic region drains a total area of almost 7,000,000 km2, representing over 63% of Brazil’s overall drainage area and comprising seven states of the national territory (the percentage of total drainage area in Amazon basin of each of these states is as follows: Acre: 3.4%; Amapá: 3.2%; Amazonas: 35.0%; Mato Grosso: 20.2%; Pará: 27.9%; Rondônia: 5.3%, and Roraima: 5.0%) (SRH, 2006). According the ANA (ANA, 2013), the Amazonian region has an average water availability of more than 73,000 m3/s and a mean flow of 132,000 m3/s, but there is unequal distribution of both across the hydrographic subregions (SRH, 2006). The Amazonian hydrographic region is divided into 10 subregions with enormous differences in hydric availability per capita/year (m3/hab/year) among them, as detailed by the Brazilian Ministry of Environment: Amapá Litoral (1,897,812 km2,or 27% of the total area), Solimões (1,191,866;17%), Xingu (824,223;12%), Purus (736,808;11%), Negro (613,942;9%), Tapajós (553,077;8%), Trombetas (498,224;7%), Foz Amazonas (250,906;4%), Paru (221,864;3%) and Madeira (206,336;2%) (SRH, 2006). The water storage capacity of reservoirs in the Amazonian hydrographic region represents only 3% (i.e., 21,140 km3) of the total storage capacity in Brazil, and it is mainly used for public supplies in urbanized areas and for hydroelectric power generation (ANA, 2013). Over the last decades, the rate of human population growth in the area of the Amazonian hydrographic region has been around 2.3 times higher than that of other regions in Brazil (population growth of this region was 28.8% between 2000 and 2010) (ANA, 2012), which has had a pronounced impact on water demand especially in highly urbanized areas. The activities with the most impact on demand for water are those related to animal supply (32.4%), urban supply (32.3%), irrigation (19.0%), hydroelectric power generation (7.4%), industries (4.2%), rural use (3.7%), and mining activities (1%) (ANA, 2019). The growth in population and in industrial activities in the Amazonian hydrographic region has not been accompanied by appropriate investments in basic sanitation infrastructure, implementation of state and municipal polices for management of water resources, or water quality monitoring stations, resulting in marked alterations in water quality parameters in several aquatic environments (ANA, 2012; SRH, 2006), that can be seen in many river channels and streams. In this region around 78% of the urban population has no regular access to potable drinking water, as only 6.2% is supplied by a sanitary sewage system (compared to 42.6% in Brazil overall) and only 4.6% of sewage is properly treated, which results in a daily organic domestic load that reaches the receiving surface waters of more than 275 t DBO/day (ANA, 2012). Three main types of river water are recognized in the Amazon region: “black water” from the Negro River drainage area (acidic pH ranging from 3.5-5.0, very low content of major cations and anions, and high concentration of dissolved organic carbon or DOC), “white water” from

Water-related problem with special reference to global climate change in Brazil  7 the Solimões (upper Amazon) River (near neutral pH, high nutrient content, high amount of suspended particles, and low DOC content) and “clear water” from the Tapajós River (neutral pH and low DOC and ionic levels) (Furch, 1984; Sioli, 1984). Thus water quality parameters (such as ionic composition, temperature, pH, and level of nitrogen compounds) are highly variable between the main types of water in the Amazonian region, and are directly influenced by the seasonal and spatial differences in precipitation and by variation of rivers levels (Cunha & Pascoaloto, 2009; Sioli, 1984; Souto, Oliveira, & Silva, 2015). These spatial and temporal differences in physicochemical composition of water in the Amazonian region clearly impose different challenges for the catchment and treatment of drinking water to both urban and riverine population throughout the region.

1.2.1  Industrial and domestic effluents The increasing load of domestic organic waste and industrial effluents (particularly from processing industries) contributes greatly to the deterioration of water quality in the Amazonian region and has a significant impact on aquatic communities. For example, in the estuary zone of the Amazon River the lack of an adequate urban wastewater treatment facility for the city of Brangança in the state of Pará has resulted in environmental problems related to deterioration of water quality. During the dry season the estuary waters are expressively more eutrophic, with a significant increase in nitrite (NO2-) and nitrate (NO3-), temperature, and pH, as well as in total fecal coliforms (Pereira et al., 2010). Similarly, strong microbiological pollution has been reported in estuary rivers that drain to Amazon River around Macapá and Santana, the two biggest cities of Amapá state, where increased levels of total fecal coliforms have been directly associated with domestic wastewater disposal, as well as with effluents from agriculture and port and industrial activities (Cunha et al., 2004). The evaluation of metal content in the water and the white muscle of several fish species collected from the Cassiporé River in Amapá state, an area historically impacted by gold-mining activities and by agricultural effluent, revealed that surface water had levels of cadmium (Cd), copper (Cu), chromium (Cr), lead (Pb), zinc (Zn) and mercury (Hg) higher than the limits allowed by Resolution No. 357 of the Brazilian Environmental National Council (CONAMA, 2005). In addition, the authors reported a pattern of accumulation of Cd (Plagioscion squamosissimus), Pb (Poptela compressa), Cr (P. compressa, Pimelodella cristata, and Cyphocharax gouldingi), and Hg (P. squamosissimus, Pseudoplatystoma fasciatum, Hoplias malabaricus, and Serrasalmus rhombeus) above the legal limits in various fish species that are consumed by riverine populations, which may result in increased risk to human health (Lima, Santos, & Silva, 2015). There is also increasing concern about Hg contamination of the Amazon River from goldmining activities as it relates to the food chain because Hg can be bioconcentrated in fish, as it is usually bioaccumulated at higher trophic levels (it is generally stored as methylmercury (MeHg) in muscle). For example, in Madeira River the level of total mercury (i.e, Hg and

8  Chapter 1 MeHg) in the white muscle of several piscivorous (e.g., Pinirampus pirinampu, Hydrolycus scomberoides, Rhaphiodon vulpinus, and Acestrorhynchus falcirostris) and carnivorous (e.g., Calophysus macropterus, Pellona flavipinnis, and Serrasalmus elongatus) fish species was higher than those measured in detritivorous and herbivorous species, and was higher than the limit of >0.50 mg/kg of total mercury in edible fish recommended by the World Health Organization (WHO) (Bastos, Dórea, & Bernard, 2016). Similarly, the Hg levels in the muscle of fish collected in the Purus River (Acre State) were generally higher (44% of species collected) than the threshold allowed by the WHO, with higher levels found in carnivorous (e.g., for C. macropterus and Cetopsis coecutiens the total Hg ranged from 0.14 to 5.39 mg/kg) and piscivorous species (e.g., for P. pirinampu, H. scomberoides, and Plagioscion squamosissimus the total Hg ranged from 0.06 to 1.09 mg/kg) in comparison to omnivorous and detritivorous fish (Castro, Braga, Trindade, Giarrizzo, & Costa, 2016). Hence the consumption of fish by indigenous and riverine communities may result in human exposure to Hg, as seen by the high levels of mercury in the breast milk (ranging from 0 to 24.8 ng/g) and hair of mothers (ranging from 2.0 to 37.2 µg/g), as well as the hair of infants (ranging from 1.4 to 34.2 µg/g), from very small communities in the area of the Madeira River (Barbosa & Dórea, 1998). High concentration of Hg has also been seen in different tissues (particularly in liver, muscle, and brain) of two species of Amazonian cetaceans-the tucuxi dolphin (Sotalia fluviatilis) and the boto dolphin (Inia geoffrensis)-living in the Japurá, Madeira, and Negro Rivers (Lailson-Brito, Dorneles, & Silva, 2008), indicating that Hg is in fact being bioaccumulating in higher trophic levels of food chain in some areas of the Amazon. In the area around the city of Manaus (Amazonas state) the unauthorized occupation of lateral margins of streams is associated with a crescent load of domestic wastewater and industrial effluent, which is contributing to a severe degradation in water quality in these aquatic environments (Borges, 2006). Previous studies have showed a significant increase in total ionic composition (for both cations and anions), nitrogen compounds (NO2-, NO3-, and ammonia), conductivity, and pH, and a decrease in dissolved oxygen, in several streams in highly urbanized areas and near the industrial district in Manaus that drains directly into the Negro River (Horbe, Gomes, Miranda, & Silva, 2005; Pinto, Horbe, & Silva, 2009; Silva, Ramos, & Pinto, 1999). These physicochemical alterations in water composition related to domestic sewage input are extremely harmful to the human population, as seen by the presence of viruses that can cause acute gastroenteritis in the streams of Manaus (Miagostovich et al., 2008), and also to aquatic biodiversity (particularly fish species). These species has developed specialized physiological and biochemical adaptations to live in the acidic, ion poor conditions of the black-waters environment of the Negro River basin (Gonzalez, Wood, Patrick, & Val, 2002; Gonzalez, Wilson, & Wood, 2006), and are considered relatively sensitive to nitrogen compounds (such as nitrite and ammonia); they have displayed hematological and metabolic disruptions after exposure to high environmental levels of ammonia that are closely associated with lethality (Avilez et al., 2004; Costa,

Water-related problem with special reference to global climate change in Brazil  9 Ferreira, Mendonça, & Fernandes, 2004; Souza-Bastos, Val, & Wood, 2017; Wood, Netto, & Wilson, 2017). The sewage input in urban surface waters is also introducing the release of contaminants into the streams around Manaus, where pharmaceuticals (such as antiepileptic, antidepressant, beta-blockers, and non-steroidal anti-inflammatory drugs) and illicit drugs (such as cocaine and its main metabolite, benzoylecognine), have been detected in main the channel of Negro River (Thomas, Silva, & Langford, 2014). Furthermore, the anthropogenic impact on the quality of surface waters is also resulting in the contamination of the sediment of streams by both sewage-derived organic matter and metals. A recent study evaluating the impact of sewage contamination revealed a high concentration (509-12,829 ng/g) and relative proportion (21%–54%) of coprostanol (an important biomarker of sewage-derived sterol input) in two of the main streams crossing a highly urbanized and industrialized area in Manaus (Melo, Silva, & Costa, 2019). In addition, there is strong evidence of metal contamination in the waters of some streams around Manaus that are promoting a persistent metal enrichment of their sediment. Some metals, such as Cobalt (Co), Nickel (Ni), Iron (Fe), Zn, Cd, Cu, and Pb are present at higher levels in both water and sediment (Santana & Barroncas, 2005; Silva et al., 1999) than those allowed by Resolution No. 357 of the Brazilian Environmental National Council (CONAMA, 2005), while an increased level of both Zn and Cu has been found in liver and white muscle samples of an facultative air-breathing armored catfish (Hoplosternum littorale) (Santana, 2016), one of the most tolerant fish species living in these highly impacted streams. Overall, the evidence clearly demonstrates a high level of deterioration in water quality in the surface waters of the Negro River tributaries in peri-urban area of Manaus due to industrial and domestic sewage input, which calls for the rapid and efficient implementation of programs for both sewage treatment plants and the monitoring of water quality parameters. The degradation of water quality in urban streams as a result of anthropogenic impacts has been accompanied by a loss of species and a great shift in aquatic community composition, resulting in significantly reduced biodiversity. In impacted streams, the loss of habitat due to rubbish deposition and organic wastewater load has also been accompanied by the deforestation of marginal forest, promoting a reduction in the diversity of aquatic and semiaquatic Heteroptera insects (Pereira, 2009). These impacts have also decreased the population of the most common fish species in these environments (77% of Characiforms, 55% of Perciforms and 70% of Siluriforms have been lost), which is highly correlated to increased ammonia and nitrite levels in waters (Anjos, 2007). A complete absence of five species from the Lebiasinidae family (Copella nattereri, C. nigrofasciata, Nannostomus beckfordi, N. marginattus, and Pyrrhulina brevis) has also been observed in impacted streams as compared to areas not impacted, and changes in the composition of fish species have also been noted, with a greater abundance of fish species with facultative air-breathing strategies, such as many catfish of Siluriforms order (e.g., Ancistrus sp., Liposarcus pardalis, Rineloricaria sp., Hoplosternum littorale, Callichthys callichthys, Megalechis personata,

10  Chapter 1 and Corydoras cf. aeneus) and electric fish (Electrophorus electrius) (Anjos, 2007). Another important issue related to aquatic biodiversity in impacted streams in the Amazonian region is the presence of exotic species, as seen in streams with increased levels of nitrogen compounds (mainly ammonia and nitrite), phosphorus, and conductivity, and depletion of oxygen levels, and where species such as Danio rerio (Cyprinidae), Poecilia reticulata, Xiphophorus helleri and X. maculatus (Poecilidade), and Oreochromis niloticus (Cichlidae) have been found (Guarido, 2014). These species are recognized as being very tolerant of significant alterations in water quality parameters. In summary, these studies suggest that loss of integrity and deterioration of water quality in aquatic environments due to anthropogenic pressures negatively impact native biodiversity and favor the invasion of nonnative species.

1.2.2  Changes in land-use and deforestation Over the last 60 years the Amazonian hydrographic region has faced significant landscape alteration caused by anthropogenic activities that are potentially threatening and increasing the pressure on the availability and quality of water resources. The main anthropogenic activities contributing to Amazonian deforestation and land-use changes are agricultural expansion and large-scale ranching, mining, intense urbanization and civil works, incremental paving of roads, and building of dam and reservoirs for hydroelectric power generation (Davidson, de Araújo, & Artaxo, 2012; Lees, Peres, & Fearnside, 2016; SRH, 2006). Agropastoral expansion in the Amazonian hydrographic region has accounted for almost 80% of deforestation according to Greenpeace International (2009) estimates, with the highest deforestation rates occurring in the southern watersheds of the Amazon and highest impact on the headwaters from Madeira, Tapajós, Xingu, Araguaia, and Tocantins Rivers (the loss of is between 8.3 to 20% of total area) (Trancoso, Carneiro-Filho, & Tomasella, 2009). In addition, agropastoral expansion in the Amazonian hydrographic region has been accompanied by vegetal extractivism and logging (SRH, 2006). Mining activities have also promoted changes in the landscapes of Amazonian hydrographic subregions, as can be seen as a result of gold mining in the Tapajós watersheds, manganese and chromium exploration in both the AmapáLitoral and Amazon river mouth hydrographic subregions, bauxite (aluminum ore) mining in the Trombetas basin, and the mining of cassiterite (tin ore), mainly in the Madeira watersheds but also on a lowered scale in Trombetas e Xingu subregions (SRH, 2006). The conservation of the structure and function of aquatic ecosystems and their environmental services are strictly dependent on the maintenance of riparian forest in the catchment areas from the watershed (Sparovek, Ranieri, & Gassner, 2002). Changes in land use and/or fragmentation of forest cover are the drivers of the degradation of habitat integrity, hydrology, and water quality of upland streams and rivers/floodplains throughout the Amazon basin (Castello et al., 2013). As riparian forests exert a fundamental role in the biogeochemical cycles of watersheds, their removal directly affects the physical habitat of aquatic systems by increasing both erosion and the input of fine sediment into the water column, increasing

Water-related problem with special reference to global climate change in Brazil  11 the runoff and loss of nutrients, lowering the retention of pollutants, and changing discharge rates (Leal, Pompeu, & Gardner, 2016). Thus the removal of riparian forest in the catchment area from a particular watershed might increases discharges, but on a larger scale the effect of deforestation would result in lowered evapotranspiration, consequently reducing both precipitation and river/streams discharges (Coe, Costa, & Soares-filho, 2009). For example, increased discharge rates and sediment transport have been reported in the hydrographic regions of the Tocantins and Araguaia Rivers (southeastern Amazon basin), particularly during the wet seasons, which can be directly associated with the increase in deforestation of those watersheds for the expansion of pasture and croplands (Davidson et al., 2012). In addition, degradation of the riparian forest has had a pronounced effect on water quality: the reduced canopy cover increases the incidence of light in the water column, directly influencing the water temperature. Because higher water temperature has a direct, negative impact on the level of dissolved oxygen in water, and since both parameters have been demonstrated to influence many biochemical, physiological, and biological responses of aquatic organisms (see Section 2.5), deforestation may impact both the structure and composition of aquatic communities and their distribution in aquatic environments. Furthermore, increases in the incidence of light and in water temperature may result in indirect effects on primary production, and may also change the level of nutrient runoff and sediment deposition, which in turn could affect other water quality parameters, such as conductivity and pH. In fact, the loss of riparian vegetation cover and its direct effect on local hydrology could negatively affect the distribution and composition of aquatic assemblages of invertebrates and fishes (Bojsen & Barriga, 2002; Leal et al., 2016; Nessimian, Venticinque, & Zuanon, 2008; Röpke, Amadio, & Zuanon, 2017). Bojsen and Barriga (2002) have demonstrated that while no significant effect of deforestation was seen in local fish richness in nine small streams of first to third order in the Ecuadorian Amazon, higher alpha and beta diversity of fish was positively correlated to forested areas, indicating that species composition was more heterogeneous in those locales than in deforested areas. In addition, a pronounced shift in species composition was also seen in forested and deforested areas: in forested areas there is a predominance of omnivorous/insectivorous fishes from the Characidae family (Characiformes), while in deforested areas with reduced canopy cover there is a greater occurrence of periphyton-feeding fish from the Loricariidae family (Siluriformes) (Bojsen & Barriga, 2002). A study of small streams of two sub-hydrographic regions in the eastern Amazon basin (Santarém and Paragominas) showed that deforestation and forest fragmentation had modified channel morphology and stream-bottom structure, particularly through increased sedimentation, resulting in changes in the functional structure of fish assemblages. It was observed that number of fish species occupying the mid and upper layers of these streams was negatively affected by the lowered water-column depth in deforested areas, while the reduction in bottom complexity and stability caused a reduction

12  Chapter 1 of the abundance of benthic fish species (Leitão, Zuanon, & Mouillot, 2018). Similarly, deforestation has been shown to have a significant impact on fish assemblages in the floodplains of the Amazonian hydrographic region, where fish taxonomic and functional diversity as well as their spatial distribution have been negatively affected by the decrease in forest cover. For example, the maintenance of forest cover in floodplain areas along the Amazon River was demonstrated to be critical for several fish species with specialized feeding (such as the herbivorous Serrasalmidade Colossoma macropomum, Piaractus brachypomus, and Myloplus spp.), lifecycles (such as the equilibrium and periodic strategists Osteoglossum bicirrhosum and many Cichlid species with biparental brood guarding), and swimming/microhabitat use strategies (such as many epibenthic cichlid and benthic catfish) (Arantes, Winemiller, Petrere, & Castello, 2017). Overall, changes in land use and consequent deforestation and forest fragmentation is particularly harmful to aquatic life, promoting a significant homogenization of fish assemblages through the reduction of both functional diversity and abundance of many species, which seems to be happening even at the local and regional levels and in both upland streams and floodplains from major rivers.

1.2.3  Petroleum hydrocarbon Petroleum drilling in the Amazon basin commenced in the 1980 and 1990s and has increased in the last decades. The most important field is located in the city of Coari at the edge of Urucu river (a tributary of Negro River), 600 km from Manaus. The potential for oil spills and hydrocarbon contamination in Amazonian water bodies is higher in the area around this field and when oil in barges is transported from Coari to Manaus to be refined. In fact, some accidents that have resulted in the release of significant amounts of oil and its derivates into water bodies have already been reported (Azevedo-Santos, Garcia-Ayala, & Fearnside, 2016; Couceiro, Forsberg, Hamada, & Ferreira, 2006; Fernandes, Paulino, & Sakuragui, 2013; Sadaukas-Henrique, 2014). Once released into bodies of water, the soluble and insoluble parts of the oil can lead to direct and indirect effects on both aquatic animals and plants. Low-weight hydrocarbons (e.g., polycyclic aromatic hydrocarbons, or PAHs) generally do not persist but are recognized as being the most acutely toxic to aquatic organisms, while light-weight hydrocarbons are less soluble and more persistent in the environment (Anderson, Neff, & Cox, 1974). The first reported spill of a large amount of oil in Amazonian water bodies occurred in 1999 when the rupture of a submerged pipeline released petroleumderived oil from the Manaus Refinery (REMAN/Petrobrás) to the water column of the Cururu stream, a tributary of the Negro River (Couceiro et al., 2006; Couceiro, Hamada, Ferreira, & Forsberg, 2007). The release of oil covered submerged vegetation and the sediment at the edge of the stream and directly impacted the communities of the benthic zone. The spill caused a marked reduction in dissolved oxygen in water that was associated with an increase in the mean concentration of phosphorus and total nitrogen, which was shown to greatly reduce the abundance and number of taxa of edaphic invertebrates. Significant changes in the

Water-related problem with special reference to global climate change in Brazil  13 composition of invertebrate communities, which had been more prominent during the lowand high-water seasons during the flood pulse of the Negro River, were reported (Couceiro et al., 2006; Couceiro et al., 2007). More recently, in 2013 an accident with a barge transporting of a petroleum asphaltic cement (CAP) released around 60 thousand liters of CAP into the waters of the Negro River near the São Raimundo harbor in Manaus. Although some mitigation protocols had been employed in order to reduce the impact of CAP release, the total concentration of PAHs in water was substantially elevated 45 days after the spill (Sadaukas-Henrique, 2014). In addition, the concentration of hydrocarbon metabolites (pyrene type, benzo[a]pyrene type, and naphthalene type) in the bile of two resident Cichlid fish species (Satanoperca jurupari and Acarichthys heckelii) was markedly increased and was combined with the activation of a phase-I detoxification enzyme (EROD) in the liver and an increase in both neurotoxic effects on the brain and genotoxic damage in the red blood cells of fish. These results indicate that organisms showed adverse responses and were still being exposed to a high amount of hydrocarbons even 90 days after the CAP release (Sadaukas-Henrique, 2014). These data confirm the picture that has emerged from several laboratory studies demonstrating that Amazonian aquatic plants and fish are relatively sensitive to petroleum hydrocarbon exposure.

1.2.4  Pesticides and herbicides The population growth seen in several parts of the Amazonian region over the last 50th years has resulted in a conflict between environmental conservation and increasing agricultural demands. This agricultural expansion has required a heavy use of pesticides (insecticides, herbicides, and fungicides) because most food production consists of nontraditional crops grow in floodplain areas (Waichman, Römbke, Ribeiro, & Nina, 2002; Waichman, 2008). Although floodplains can be highly productive due to the seasonal flood regime that naturally fertilizes these areas, the high susceptibility of crops to native insects and fungus and the competition with native vegetation has resulted in largely indiscriminate use of pesticides in order to reach the required levels of food production (Römbke, Waichman, & Garcia, 2008; Waichman et al., 2002). In addition, a marked expansion in agricultural production in “terra firme” areas has also been seen recently, especially close to the main cities, to satisfy increased demand from supermarkets, restaurants, and hotels (Waichman et al., 2002). The main active ingredients found in commercial pesticides commonly used for agricultural production in the Amazonian region are deltamethrin, malation, and methyl parathion (insecticides); copper oxychloride and Mancozeb (fungicides); and glyphosate (herbicides) (Römbke et al., 2008; Waichman, 2008; Waichman et al., 2002). However, the number of active ingredients used in pesticides in the Amazon region has increased from 15 to almost 40 between 2003 and 2008, with a particular increase in the use of extremely

14  Chapter 1 toxic ones (toxicological class I) (Schiesari et al., 2013). The increase in the environmental concentration of pesticides in water and the soil matrix has increased significantly over time because of the increased dosage used on crops, resulting in higher occupational risk to smallholders and more pronounced toxic effects on nontarget aquatic species, such as invertebrates, amphibians, and fish, due to pesticide contamination (Römbke et al., 2008; Schiesari et al., 2013). Notwithstanding the fact that few studies have directly determined pesticides in the surface water of the Amazonian hydrographic region, there is growing evidence of pesticide contamination in the region in that several of those contaminants have been detected in soil and the edible flesh of many fish species. For example, high concentrations of the insecticides malation, methyl parathion, and chlorpyrifos have been found in eight different fish species in the Tapajós and Amazon Rivers (in the city of Santarém in Pará state) during the low-water regime, where the highest concentration seen was positively correlated to higher lipid content in the muscle of the piscivorous fish P. flavipinnis (the mean concentration of malation was 0.1 µg/kg; of methyl parathion, 0.8 µg/kg; and of chlorpyrifos, 0.4 µg/kg; and the percentage of occurrence in fish was 40%, 100%, and 80%, respectively) (Soumis, Lucotte, & Sampaio, 2003). Furthermore, experiments have demonstrated that herbicides such as glyphosate are moderately to highly toxic to fish, potentially affecting the structure of respiratory epithelium in gills and promoting disturbances in blood parameters and genotoxic effects in red blood cells, in biotransformation, and in antioxidant responses in gills, liver, and brain, as seen in the native species C. macropomum (tambaqui) and Pseudoplatystoma sp. (surubim) (BrazMota et al., 2015; Sinhorin, Sinhorin, & Teixeira, 2014). Perhaps the most extensive studies regarding pesticide contamination in the Amazonian region are of the organochlorine insecticide 1,1,1-trichloro-2,2-bis (p-chlorophenyl)ethane (DDT). The presence of DDT and its metabolites has been reported in soil, river sediment, fish, and also in breast milk, in many places in the hydrographic region, and is usually associated with the widespread use of this insecticide between the early 1940s and the 1990s to control vector-borne diseases, such as malaria and leishmaniasis (Azeredo, Torres, & Fonseca, 2008; D’Amato, Torres, & Malm, 2004; Saldanha, Bastos, Torres, & Malm, 2010; Torres, Pfeiffer, & Markowitz, 2002). For example, a relatively high concentration of DDT (higher than its metabolites) was reported in the muscle of many fish species collected from both Tapajós and Madeira Rivers (ranging from 30 to 500 ng/g), such as Brachyplatystoma vaillanti (Filhote), Plagioscion squamosissimus (Pescada), and Pseudoplatystoma fasciatum (Surubim), as well as in the Amazonian cayman (Cayman jacare) (D’Amato et al., 2004; Torres et al., 2002). The bioaccumulation of DDT and its metabolite dichlorodiphenyldichloroethylene (DDE) was also reported in the white muscle of peacock bass (Cichla monoculus), sampled at the Samuel dam on the Jamari River (in Rondônia state), where DDT was significantly higher in the animals collected at dry season (Rabitto, Rodrigues, & Almeida, 2011). Similarly, DDT has also been found in high

Water-related problem with special reference to global climate change in Brazil  15 concentration (ranging from 190 to 3176 µg/g of lipid) in the tissue of the Amazonian red dolphin (I. geoffrensis), as sampled from the Solimões and Madeira Rivers (Torres, LailsonBrito, & Saldanha, 2009). Despite the increasing concern about pesticide contamination of Amazon surface waters and its bioaccumulation and potential adverse effects on aquatic biota, since 2018 the Brazilian Government has been more permissive about agrochemical (mainly pesticide) registration, with more than 200 new products being made available (Coelho, Lopes, Cavalcante, Corrêa, & Leduc, 2019), many of which contain chemicals with active agents classified as hazardous pesticides (PAN, 2019). Thus, the future points to an increase in problems related to pesticide contamination, leading to a greater threat to both human health and aquatic biota.

1.2.5  Global climate changes Changes in hydrological cycles, and consequently in quality and availability of water resources, have been predicted in face of global climate change. The predictions point to increasing frequency of hydrological extremes, such as severe droughts and floods; increases in contamination and reduction of water quality, particularly through salinization; eutrophication; and changes in the cycles of metals in aquatic environments; all of which could directly affect water resources and both regional and national economies (Arnell, 1999; Magrin et al., 2014; Tundisi, 2008). The global increase in greenhouse gas emissions as a result of deforestation and land degradation has been associated with climate change, and in the case of the Amazonian region the removal of forest will have a marked effect on local, regional, and global climate (Malhi, Roberts, & Betts, 2008). Studies have demonstrated that on a local scale the reduction in forest cover can decrease evapotranspiration and promote an increase in precipitation runoff, as seen in the eastern Amazonian region (Coe et al., 2009), and in central Amazonia, where the increase in runoff is as high as 22% in land converted to pasture (Trancoso et al., 2009). However, on a regional scale, models are indicating that deforestation can directly act on the variability of the rainfall regime in a region, in which case the replacement of forest by crops and pasture may negatively affect water recycling and reduce precipitation, but increase both the frequency and intensity of heavy rains (Coe et al., 2009; Magrin et al., 2014). Thus the picture that emerges is that changes in land use (and their effects on climate changes) can impact the hydrology of Amazonian aquatic environments, although fluctuations in rainfall pattern in the Amazonian region have historically been related to natural climate events, such as El Niño and La Ninã (Magrin et al., 2014). In fact, the frequency of extreme hydrological events has already been seen in the Amazonian region, such as the three major floods and two severe droughts seen in the region between 2005 and 2012, and studies are estimating that the chance of extreme droughts in the region will increase from the current 5% to 50% in 2030, and could reach over 90% in 2100 (Magrin et al., 2014; Marengo, 2008). These changes in hydrological patterns associated with climate

16  Chapter 1 change could directly influence the quality of Amazonian water resources, making these aquatic environments warmer and more acidic, and cause the depletion of dissolved oxygen levels (Val et al., 2019). During the severe drought in 2015 the connectivity between main river channels and lakes was interrupted and thousands of fish were trapped in small water bodies under hypoxic conditions, which resulted in a high mortality ratio of fish throughout the Amazon basin (Röpke et al., 2017; Tomasella, Pinho, & Borma, 2013). Recent studies have been able to demonstrate that interannual hydrological patterns are an important driving force in maintaining community stability and the assemblage structure of fish in floodplain areas of the Amazonian region. An analysis of fish composition in six floodplain lakes along Solimões River between 2004 and 2007 revealed that species composition became less heterogeneous following the 2015 drought, with an average decrease of carnivorous (e.g., Osteoglossum bicirrhosum) and omninovorous (e.g., Pristobrycon calmoni, Hemiodus sp, Astronotus ocellatus, and Astronotus crassipinnis) species, and an increased abundance of many planktivores, herbivores, and detritivores fish species (Freitas, Siqueira-Souza, Humston, & Hurd, 2013). Similarly, a long-term study conducted in a floodplain lake of the Negro River demonstrated significant changes in fish assemblages after the 2005 drought, where an overall reduction in both fish diversity and richness was seen followed by a relative predominance of first-level consumers species (Röpke et al., 2017). In addition, many species that are commercially important for human consumption that migrate between the river channel and floodplains for feeding and reproduction (as Hemiodus sp., Curimatella alburna, Triportheus angulatus, Colossoma macropomum, Prochilodus nigricans, and Semaprochilodus spp.), were less abundant in the years after the 2005 drought, suggesting that many migratory species could be especially sensitive to the reduced connectivity between aquatic environments caused by extreme hydrological events in Amazon floodplains (Röpke et al., 2017). Furthermore, incremental increases in temperature and more acidic waters might be potentially dangerous to aquatic biota, as these species have evolved in thermally stable environments with minor natural oscillations in pH and have developed very specialized physiological adaptations to live under these conditions (Val & Almeida-Val, 1995). Although several Amazonian fish species have been demonstrated to be tolerant of acidic conditions (Gonzalez et al., 2006), there is specific evidence that many species are extremely sensitive to low pH and do not exhibit the branchial specialization that would avoid marked osmoand ionoregulatory disturbances during acidic exposure (Duarte, Ferreira, Wood, & Val, 2013; Wilson et al., 1999). In addition, recent studies show that fish species in terra-firme streams will be particularly vulnerable to further increases in water temperature caused by global climate change, since they have limited ability to acclimate and live in environmental temperatures that are close to their upper critical thermal tolerance (Campos, 2019; Campos, Val, & Almeida-Val, 2018). That is particularly true of members of the Characidae family (e.g., Hyphessobrycon melazonatus, Hemigrammus geisleri, and Iguanodects geisleri) and the Crenuchidae family (Characidium pteroides, Crenuchus spilurus, and Microcharacidium

Water-related problem with special reference to global climate change in Brazil  17 eleotriodes), fish species that have exhibited the lowest values of upper critical thermal tolerance and higher resting and maximum metabolic rates, in contrast to Rivulidae (Anablepsoides micropus) and Cichlidae (Aequidens pallidus and Apistogramma hippolytae) species, suggesting that these group of species have a narrow range of thermal tolerance (Campos et al., 2018). In summary, the alterations in water quality and availability in the face of global climate change (and its relationship with changes in land use) could be extremely harmful to aquatic biota, and together with the increasing load of pollutants (such as metals, petroleum hydrocarbons, pesticides, nitrogenous compounds, and personal care products) represent additional challenges to the maintenance of Amazonian aquatic biodiversity. Thus we understand that improvements in monitoring systems and water treatment, as well as the conservation of riparian forest close to watersheds, are fundamental to mitigate severe impacts on aquatic biodiversity conservation in the Amazonian region.

Acknowledgments Special thanks to the Brazilian National Academy of Science (ABC) for the invitation to RMD to participate as a member of the Brazilian delegation in the 3rd BRICS Young Scientist Forum in Durban, South Africa (2018).

References Agência Nacional de Águas (ANA). (2012). Panorama da Qualidade das Águas Superficiais do Brasil. Ministério do Meio Ambiente, Brasília. Agência Nacional de Águas (ANA). (2013). Conjuntura dos Recursos Hídricos no Brasil. Ministério do Meio Ambiente, Brasília. Agência Nacional de Águas (ANA). (2016). Mudanças Climáticas e Recursos Hídricos: Avaliações e Diretrizes para Adaptação. Ministério do Meio Ambiente, Brasília. Agência Nacional de Águas (ANA). (2017). Conjuntura dos Recursos Hídricos do Brasil. Ministério do Meio Ambiente, Brasiíla. Agência Nacional de Águas (ANA). (2019). Manual de Usos Consuntivos da Água no Brasil. Ministério do Meio Ambiente, Brasília. Anderson, J. W., Neff, J. M., Cox, B. A., et al. (1974). Characteristics of dispersions and water-soluble extracts of crude and refined oils and their toxicity to estuarine crustaceans and fish. Marine Biology, 27, 75–88. doi: 10.1007/BF00394763. Anjos, H. Daniel B. dos. (2007). Efeitos da Fragmentação Florestal Sobre as Assembléias de Peixes de Igarapés da Zona Urbana de Manaus, Amazonas. Instituto Nacional de Pesquisas da Amazônia (INPA). Arantes, C. C., Winemiller, K. O., Petrere, M., & Castello, L. (2017). Relationships between forest cover and fish diversity in the Amazon River floodplain. Journal of Applied Ecology, 55(1), 386–395. doi: 10.1111/13652664.12967. Arnell, N. W. (1999). Climate change and global water resources. Global Environmental Change, 19(S1), doi: 10.1016/S0959-3780(99)00017-5. Avilez, I. M., Aguiar, L. H. de, Altran, A. E., & Moraes, G. (2004). Acute toxicity of nitrite to matrinxã, Brycon cephalus (Günther, 1869), (Teleostei-Characidae). Ciênicia Rural, 34, 1753–1756. Azeredo, A., Torres, J. P. M., Fonseca, F. M. De, et al. (2008). DDT and its Metabolites in breast milk from the Madeira River Basin in the Amazon, Brazil. Chemosphere, 73, 246–251. doi: 10.1016/j. chemosphere.2007.04.090. Azevedo-Santos, V. M., Garcia-Ayala, J. R., Fearnside, P. M., et al. (2016). Amazon aquatic biodiversity imperiled by oil spills. Biodiversity and Conservation, 25, 2831–2834. doi: 10.1007/s10531-016-1192-9.

18  Chapter 1 Barbosa, A. C., & Dórea, J. G. (1998). Indices of mercury contamination during breast feeding in the Amazon Basin. Environmental Toxicology and Pharmacology, 6, 71–79. Bastos, W. R., Dórea, J. G., Bernard, J. V. E., et al. (2016). Sex-related mercury bioaccumulation in fish from the Madeira River, Amazon. Environmental Research, 144, 73–80. doi: 10.1016/j.envres.2015.11.001. Bojsen, B. H., & Barriga, R. (2002). Effects of deforestation on fish community structure in Ecuadorian Amazon streams. Freshwater Biology, 47, 2246–2260. Borges, J. T. (2006). Saneamento e suas Interfaces com os Igarapés de Manaus. Rev T&C Amazonica, 50–58. Braz-Mota, S., Sadauskas-Henrique, H., Duarte, R. M., Val, A. L., & Almeida-Val, V. M. F. (2015). Roundup® exposure promotes gills and liver impairments, DNA damage and inhibition of brain cholinergic activity in the Amazon teleost fish Colossoma macropomum. Chemosphere, 135, 53–60. doi: 10.1016/j. chemosphere.2015.03.042. Campos D.F. (2019). Os peixes amazônicos vivem perto dos seus limites térmicos? O efeito das mudanças climáticas sobre o metabolismo de peixes de Igarapé da Amazônia Central. Instituto Nacional de Pesquisas da Amazônia (INPA). Campos, D. F., Val, A. L., & Almeida-Val, V. M. F. de (2018). The influence of lifestyle and swimming behavior on metabolic rate and thermal tolerance of twelve Amazon forest stream fish species. Journal of Thermal Biology, 72, 148–154. doi: 10.1016/j.jtherbio.2018.02.002. Castello, L., McgGrath, D. G., Hess, L. L., Coe, M. T., Lefebvre, P. A., Petry, P., Macedo, M. N., Renó, V. F., & ArantesF C. C. (2013). The vulnerability of Amazon freshwater ecosystems. Conservaton Letters, 6(4), 217–229. doi: 10.1111/conl.12008. Castro, N. S. S. de, Braga, C. M., Trindade, P. A. de. A., Giarrizzo, T., & Costa, M. de. L. (2016). Mercury in fish and sediment of Purus River, Acre State, Amazon. Cad Saúde Coletiva, 24, 294–300. doi: 10.1590/1414462X201600030142. Coe, M. T., Costa, M. H., & Soares-filho, B. S. (2009). The influence of historical and potential future deforestation on the stream flow of the Amazon River - Land surface processes and atmospheric feedbacks. Journal of Hydrology, 369, 165–174. doi: 10.1016/j.jhydrol.2009.02.043. Coelho, F. E. A., Lopes, L. C., Cavalcante, R. M. S., Corrêa, G. C., & Leduc, A. O. H. C. (2019). Brazil unwisely gives pesticides a free pass. Science, 365(6453), 80 552–553. CONAMA (Conselho Nacional do Meio Ambiente). (2005). Resolução no 357, de 17 de março de 2005. Dispõe Sobre a Classificação dos Corpos de Água e Diretrizes Ambientais para seu Enquadramento, bem como Estabelece as Condições e Padrões de Lançamento de Efluentes, e dá Outras Providências. Diário Oficial da República Federativa do Brasil, Brasília, Brasil. Costa, O. T. F. da, Ferreira, D. J. dos. S., Mendonça, F. lo. P., & Fernandes, M. N. (2004). Susceptibility of the Amazonian fish, Colossoma macropomum (Serrasalminae), to short-term exposure to nitrite. Aquaculture, 232, 627–636. doi: 10.1016/S0044-8486(03)00524-6. Couceiro, S. R. M., Forsberg, B. R., Hamada, N., & Ferreira, R. L. M. (2006). Effects of an oil spill and discharge of domestic sewage on the insect fauna of Cururu Stream, Manaus, AM, Brazil. Brazil Journal of Biology, 66, 35–44. Couceiro, S. R. M., Hamada, N., Ferreira, R. L. M., & Forsberg, B. R. (2007). Domestic sewage and oil spills in streams: Effects on edaphic invertebrates in flooded forest, Manaus, Amazonas, Brazil. Water Air and Soil Pollution, 180, 249–259. doi: 10.1007/s11270-006-9267-y. Cunha, H. B., & Pascoaloto, D. (2009). Hidroquímica dos Rios da Amazônia (1st ed.). Manaus: Secretaria do Estado da Cultura. Cunha, A. C. da, Cunha, H. F. A., Júnior, A. C. P. B., et al. (2004). Microbiologic water quality in urban and periurban rivers on low Amazon River - Study of case: Amapá State. Eng Sanitária e Ambient, 9, 322–328. doi: 10.1590/S1413-41522004000400009. Cunningham, C., Cunha, A. P., Brito, S., Marengo, J., & Coutinho, M. (2017). Climate change and drought in Brazil. In V. Marchezini, B. Wisner, L. R. Londe, & S. M. Saito (Eds.), Reduction of vulnerability to disasters: From knowledge to action (pp. 361–376). São Carlos, Brazil: RiMa Editora. D’Amato, C., Torres, J. P., Malm, O., et al. (2004). DDT in fishes from four different Amazon sites: Exposure assessment for breast feeding infants. Organohalogen Compound, 66, 2455–2462.

Water-related problem with special reference to global climate change in Brazil  19 Davidson, E. A., de Araújo, A. C., Artaxo, P., et al. (2012). The Amazon basin in transition. Nature, 481, 321–328. doi: 10.1038/nature10717. Duarte, R. M., Ferreira, M. S., Wood, C. M., & Val, A. L. (2013). Effect of low pH exposure on Na+ regulation in two cichlid fish species of the Amazon. Comparative Biochemistry and Physiology-Part A, 166, 441–448. doi: 10.1016/j.cbpa.2013.07.022. Fernandes, M. N., Paulino, M. G., Sakuragui, M. M., et al. (2013). Organochlorines and metals induce changes in the mitochondria-rich cells of fish gills: An integrative field study involving chemical, biochemical and morphological analyses. Aquatic Toxicologydoi: 10.1016/j.aquatox.2012.11.008. Freitas, C. E. C., Siqueira-Souza, K., Humston, R., & Hurd, L. E. (2013). An initial assessment of drought sensitivity in Amazonian fish communities. Hydrobiologia, 705, 159–171. doi: 10.1007/s10750-012-1394-4. Furch, K. (1984). Water chemistry of the Amazon basin: The distribution of chemical elements among fresh waters. In H. Sioli (Ed.), The Amazon: Limnology and landscape ecology of a mighty tropical river and its basin (pp. 167–200). Dordrecht: Dr. W. Junk Publishers. Gomes, A. C. C., Bernardo, N., & Alcântara, E. (2017). Accessing the southeastern Brazil 2014 drought severity on the vegetation health by satellite image. Natural Hazards, 89, 1401–1420. doi: 10.1007/s11069-017-3029-6. Gonzalez, R. J., Wood, C. M., Patrick, M. L., & Val, A. L. (2002). Diverse strategies for ion regulation in fish collected from the ion-poor. Acidic Rio Negro. Physiol Biochem Zool, 75, 37–47. Gonzalez, R. J., Wilson, R. W., & Wood, C. M. (2006). Ionoregulation in tropical fishes from ion-poor, acidic blackwaters. In Fish physiology: The physiology of tropical fishes (vol. 21) (pp. 583–596). Elsevier. Greenpeace International. (2009). Slaughtering the Amazon [report; p. 58]. Guarido, P. C. P. (2014). Degradação Ambiental e Presença de Espécies de Peixes Não Nativas em Pequenos Igarapés de Terra Firma de Manaus, Amazonas. Instituto Nacional de Pesquisas da Amazônia - INPA. Horbe, A. M. C., Gomes, I. L. F., Miranda, S. F., & Silva, M. do. S. R. da (2005). Contribution to the hydrochemistry of drainages in the municipality of Manaus-AM. Acta Amazonica, 35, 119–124. doi: 10.1590/ S0044-59672005000200002. IPCC (International Panel on Climate Change). (2013). Climate change 2013: The physical science basis (Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change). Cambridge, UK: Cambridge University Press. Junk, W. J., Bayley, P. B., & Sparks, R. E. (1989). The flood pulse concept in river-floodplain system. In D. P. Dodge (Ed.), Proceedings of the international large river symposium (pp. 110–127). Canadian Special Publication of Fisheries and Aquatic Sciences. Lailson-Brito, J. J., Dorneles, P. R., Silva, V. M. F., et al. (2008). Dolphins as indicators of micropollutant thropic flow in Amazon basin. Oecologia Australis, 12, 531–541. Leal, C. G., Pompeu, P. S., Gardner, T. A., et al. (2016). Multi-scale assessment of human-induced changes to Amazonian instream habitats. Landscape Ecology, 31, 1725–1745. doi: 10.1007/s10980-016-0358-x. Lees, A. C., Peres, C. A., Fearnside, P. M., et al. (2016). Hydropower and the future of Amazonian biodiversity. Biodiversity and Conservation, 25, 451–466. doi: 10.1007/s10531-016-1072-3. Leitão, R. P., Zuanon, J., Mouillot, D., et al. (2018). Disentangling the pathways of land use impacts on the functional structure of fish assemblages in Amazon streams. Ecography, 41, 219–232. doi: 10.1111/ ecog.02845. Lima, D. P. de, Santos, C., Silva, R. D. S., et al. (2015). Heavy metal contamination in fish and water from Cassiporé River basin, State of Amapá, Amazonia, Brazil. Acta Amazonica, 45, 405–414. doi: 10.1590/18094392201403995. Magrin, G. O., Marengo, J., Boulanger, P. et al. (2014). Central and South America. In V. R. Barros, C. B. Field, D. J. Dokken et al. (Eds.), Climate change 2014: impacts, adaptation and vulnerability. Part B: Regional aspects (pp. 1499-1566) [report]. Contribution of Working Group II to Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. Malhi, Y., Roberts, J. T., Betts, R. A., et al. (2008). Climate change, deforestation, and the fate of the Amazon. Science, 319(5860), 169–172. doi: 10.1126/science.1146961. Marengo, J. A. (2008). Water and climate change. Estudos Avançados, 22, 83–96.

20  Chapter 1 Marengo, J. A., Torres, R. R., & Alves, L. M. (2017). Drought in Northeast Brazil -Past, present, and future. Theoretical and Applied Climatology, 129, 1189–1200. doi: 10.1007/s00704-016-1840-8. Marengo, J. A., Alves, L. M., Alvala, R. C. S., et al. (2018). Climatic characteristics of the 2010-2016 drought in the semiarid Northeast Brazil region. Annals of the Brazilian Academy of Sciences, 90, 1973–1985. doi: 10.1590/0001-3765201720170206. Melo, M. G., Silva, B. A. da, Costa, G. de. S., et al. (2019). Sewage contamination of Amazon streams crossing Manaus (Brazil) by sterol biomarkers. Environmental Pollution, 244, 818–826. doi: 10.1016/j. envpol.2018.10.055. Miagostovich, M. P., Ferreira, F. F. M., Guimarães, F. R. et al. (2008). Molecular detection and characterization of gastroenteritis viruses occurring naturally in the stream waters of Manaus, Central Amazônia, Brazil. Applied and Environmental Microbiology, 74(2), 375-382. doi: 10.1128/AEM. 00944-07. Nessimian, J. L., Venticinque, E. M., Zuanon, J., et al. (2008). Land use, habitat integrity, and aquatic insect assemblages in central Amazonian streams. Hydrobiologia, 614, 117–131. doi: 10.1007/s10750-008-9441-x. Oki, T., & Kanae, S. (2006). Global hydrological cycles and world water resources. Science, 313, 1068–1073. doi: 10.1126/science.1128845. PAN (Pesticides Action Network International). (2019). PAN International list of highly hazardous pesticides. http://pan-international.org/wp-content/uploads/PAN_HHP_List.pdf Pereira, D. L. V. (2009). Efeitos da Poluição e do Desmatamento sobre as comunidades de Gerromorpha e Nepomorpha (Insecta: Heteroptera) nos Igarapés do Município de Manaus, Amazonas. Instituto Nacional de Pesquisas da Amazônia - INPA. Pereira, L. C. C., Monteiro, M. C., Guimarães, D. O., et al. (2010). Seasonal effects of wastewater to the water quality of the Caeté River estuary, Brazilian Amazon. Annals of the Brazilian Academy of Sciences, 82, 467–478. doi: 10.1590/S0001-37652010000200022. Pereira, C. D. S., Maranho, L. A., Cortez, F. S., et al. (2016). Occurrence of pharmaceuticals and cocaine in a Brazilian coastal zone. Science of the Total Environment, 548–549. doi: 10.1016/j.scitotenv.2016.01.051 148-154. Pinto, A. G. N., Horbe, A. M. C., Silva, M. do. S. R. da, et al. (2009). The human action effects on the hydrogeochemistry of Negro River at the Manaus shoreline. Acta Amazonica, 39, 627–638. doi: 10.1590/ S0044-59672009000300018. Rabitto, I. S., Rodrigues, W. R., Almeida, R., et al. (2011). Mercury and DDT exposure risk to fish-eating human populations in Amazon. Environment International, 37, 56–65. doi: 10.1016/j.envint.2010.07.001. Römbke, J., Waichman, A. V., & Garcia, M. V. B. (2008). Risk assessment of pesticides for soils of the Central Amazon, Brazil: Comparing outcomes with temperate and tropical data. Integrated Environmental Assessment and Management, 4, 94–104. Röpke, C. P., Amadio, S., Zuanon, J., et al. (2017). Simultaneous abrupt shifts in hydrology and fish assemblage structure in a floodplain lake in the Central Amazon. Scientific Reports, 1–10. doi: 10.1038/srep40170. Sadaukas-Henrique, H. (2014). Efeitos subletais da poluição por petróleo e derivados sobre peixes da Amazônia (Amazonas, Brasil). Instituto Nacional de Pesquisas da Amazônia - INPA. Saldanha, G. C., Bastos, W. R., Torres, J. P. M., & Malm, O. (2010). DDT in fishes and soils of lakes from Brazilian Amazon: Case study of Puruzinho Lake (Amazon, Brazil). Journal of the Brazilian Chemical Society, 21, 306–311. Sampaio, A. P. L. (2019). Water supply for Amazonian communities: Case study of the village of Lemnon Lake, Iranduba Municipality, State of Amazonas. Marupiara, 1–15. Santana, G. P. (2016). Heavy metal distribution in the sediment and Hoplosternum littorale from Manaus Industrial District. Journal of Engineering and Exact Sciencesdoi: 10.18540/jcecvl2iss2pp070-081. Santana, G. P., & Barroncas, P. de. S. R. (2005). Heavy Metals (Co, Cu, Fe, Cr, Ni, Mn, Pb and Zn) study in the Tarumã-Açu Basin - Manaus (AM). Acta Amazonica, 37, 111–118. Schiesari, L., Waichman, A., Brock, T. et al. (2013). Pesticide use and biodiversity conservation in the Amazonian agricultural frontier. Philosophical Transactions of the Royal Society B. doi: 10.1098/rstb.2012.0378 or Silva, M. S. R., Ramos, J. F., & Pinto, A. G. N. (1999). Transition metals in the sediments of the Manaus igarapés. Acta Limnologica Brasiliensia, 11, 89–100.

Water-related problem with special reference to global climate change in Brazil  21 Sinhorin, V. D. G., Sinhorin, A. P., Teixeira, J. M. dos. S., et al. (2014). Effects of the acute exposition to glyphosate-based herbicide on oxidative stress parameters and antioxidant responses in a hybrid Amazon fish surubim (Pseudoplatystoma sp). Ecotoxicology and Environmental Safety, 106, 181–187. doi: 10.1016/j. ecoenv.2014.04.040. Sioli, H. (1984). The Amazon and its main affluents: Hydrography, morphology of the river course, and river types. In H. Sioli (Ed.), The Amazon: Limnology and landscape ecology of a mighty tropical river and its basin (pp. 127–166). Dordrecht: Dr. W. Junk Publishers. Soumis, N., Lucotte, M., Sampaio, D., et al. (2003). Presence of organophosphate insecticides in fish of the Amazon River. Acta Amazonica, 33, 325–338. Souto, L. F. L., Oliveira, T. C. de. S., & Silva, M. do. S. R. da (2015). Spatial variation of cations, anions and physicochemical variables in the Solimões-Amazonas River, between Manaus and Jutaí Amazon basin. Acta Amazonica, 45, 415–424. doi: 10.1590/1809-4392201500722. Souza-Bastos, L. R., Val, A. L., & Wood, C. M. (2017). Are Amazonian fish more sensitive to ammonia? Toxicity of ammonia to eleven native species. Hydrobiologia, 789, 143–155. doi: 10.1007/s10750-015-2623-4. Sparovek, G., Ranieri, S. B. L., Gassner, A., et al. (2002). A conceptual framework for the definition of the optimal width of riparian forests. Agriculture, Ecosystems & Environment, 90, 169–175. SRH (Secretaria de Recursos Hídricos). (2006). Caderno da Região Hidrográfica: Amazônia. Ministério do Meio Ambiente, Brasília. Thomas, K. V., Silva, F. M. A. da, Langford, K. H., et al. (2014). Screening for selected human pharmaceuticals and cocaine in the urban streams of Manaus, Amazonas, Brazil. Journal of the American Water Resoures Association, 50, 302–308. doi: 10.1111/jawr.12164. Tomasella, J., Pinho, P. F., Borma, L. S., et al. (2013). The droughts of 1997 and 2005 in Amazonia: Floodplain hydrology and its potential ecological and human impacts. Climatic Change, 723–746. doi: 10.1007/s10584012-0508-3. Torres, J. P. M., Pfeiffer, W. C., Markowitz, S., et al. (2002). Dichlorodiphenyltrichloroethane in soil, river sediment, and fish in the Amazon in Brazil. Environmental Research, 139, 134–139. doi: 10.1006/ enrs.2001.4312. Torres, J. P. M., Lailson-Brito, J. J., Saldanha, G. C., et al. (2009). Persistent toxic substances in the Brazilian Amazon: Contamination of man and the environment. Journal of the Brazilian Chemical Society, 20, 1175–1179. Trancoso, R., Carneiro-Filho, A., Tomasella, J., et al. (2009). Deforestation and conservation in major watersheds of the Brazilian Amazon. Environmental Conservation, 36, 277–288. doi: 10.1017/S0376892909990373. Tundisi, J. G. (2008). Water resources in the future: Problems and solutions. Estudos Avançados, 22, 7–16. Tundisi, J. G., Matsumura-Tundisi, T., Ciminelli, V.S., & Barbosa, F. A. (2015). Water availability, water quality water governance: The future ahead. Proceedings of the International Association of Hydrological Sciences, 366, 75-79. doi: 10.5194/piahs-366-75-2015. Val, A. L., & Almeida-Val, V. M. F. (1995). Fishes of the Amazon and their environment. Berlin, Heidelberg: Springer. Val, A. L., Bicudo, C. E. M., Bicudo, D. C. et al. (2019). Water quality in Brazil. In: Water Quality in the Americas: Risk and opportunities [Inter-American Network of Academies of Sciences (IANAS) report]. Waichman, A. V. (2008). A proposal for integrated risk assessment of pesticides use in Amazon State, Brazil. Acta Amazonica, 38, 45–50. Waichman, A. V., Römbke, J., Ribeiro, M. O. A., & Nina, N. C. S. (2002). Use and fate of pesticides in the the Amazon State, Brazil. Environmental Science and Pollution Research, 9, 423–428. Wilson, R. W., Wood, C. M., Gonzalez, R. J. et al. (1999). Ion and acid-base balance in three species of Amazonian fish during gradual acidification of extremely soft water. Physiological and Biochemical Zoology, 72, 277–285. Wood, C. M., Netto, J. G. de. S., Wilson, J. M., et al. (2017). Nitrogen metabolism in tambaqui (Colossoma macropomum), a neotropical model teleost: hypoxia, temperature, exercise, feeding, fasting, and high environmental ammonia. Journal of Comparative Physiology B, 187, 135–151. doi: 10.1007/s00360-0161027-8.

CHAPTE R 2

Water-related problems with special reference to global climate change in Russia George Safonov National Research University Higher School of Economics, Center for Environmental and Natural Resource Economics, Moscow, Russia

2.1 Introduction Global climate change is having substantial impacts on Russian water resources and all water-related sectors of the economy, as well as social and ecological systems. A rise in surface and water temperatures, an increase or decrease in precipitation levels, and a change in the frequency and intensity of extreme weather events (floods, droughts) have already been observed in Russia. The impacts of climate change are occurring much faster in Russia than the global average, especially in northern areas and in the Arctic. Water problems associated with these impacts are very diversified due to the country’s huge amount of territory, and they vary substantially depending on season, economic activities, and population. The impacts from climate change have already been dramatic in many areas, with damages valued in multibillion USD, loss of human life, increased morbidity, and tragic consequences for ecosystems. The projections related to future climate change in Russia are worrisome, as the risks to water resources are expected to rise and more losses are envisaged if no adequate adaptation and resilience measures are implemented in time. Although large-scale climatic risk reduction measures are required in most Russian regions to avoid dangerous consequences in the near and medium term, so far Russia has had a very weak adaptation policy, has placed a low priority on climate action, and has tended to employ reactive instead of proactive decision-making even in the most vulnerable areas. Climatic risk-management tools and adaptation of a national strategy will be essential elements for water management under conditions of heightened climate change in Russia.

2.2  Water resources and anthropogenic impacts in Russia Russia is one of the world’s leaders in its amount of freshwater resources; over 20% of global surface and groundwater reserves are located there. Freshwater resources available for consumption (including rivers, lakes, and groundwater) amount to 4.5 trillion m3 per Water Conservation and Wastewater Treatment in BRICS Nations http://dx.doi.org/10.1016/B978-0-12-818339-7.00002-3

23

Copyright © 2020 Elsevier Inc. All rights reserved.

24  Chapter 2 Table 2.1: Renewable freshwater resources in Russia. Main rivers

Water resources, km3/y

Main lakes/reservoirs

Water resources, km3

Volga Don Amur Lena Enisei Ob Northern Dvina Pechora Total

198 12 412 578 686 539 86 180 4648

Baikal Lake Onezhskoe Lake Ladozhskoe Lake Khanka Lake Bratskoe water storage Krasnoyarskoe water storage Kuibyshevskoe water storage Volgogradskoe water storage Sayano-Shushenskoe water storage

23,615 292 911 18 170 73 58 32 31

Source: Rosstat (2017).

year, most of which are in the form of surface water sources (Rosstat, 2017). Per capita water resources in Russia amount to about 30,000 m3 per annum (the second most after Brazil). Russia has over 2.7 million lakes with about 27,000 km3 of freshwater reserves. The biggest lake in Asia, Baikal, stores 23,615 km3 of freshwater, or 19% of the total lake water reserves in the world (Table 2.1). A huge amount of freshwater in Russia is also conserved in permafrost, glaciers, and mountains. Water resources are distributed very unevenly across the country. The European part of Russia, where 80% of population and industry is situated, has approximately 10% of total renewable water resources (FAO, 2016). The regions of Russia can be split between waterrich and water-scarce ones. The Russian Far East is a leader in water richness, followed by Eastern Siberia and northern economic districts; the most water-deficient regions include the central European area and Caucasus. The national water-management system was created in the 17th century. Later development of the system was dictated by the requirements of industrialization, electrification (including large-scale hydropower plants), water transportation, and municipal water-supply systems in Russia, which were mostly carried out during the 20th century. Total annual water withdrawal has been declining since the 1990s and reached 53.5 billion m3 in 2017 (Fig. 2.1), 56% of which is used by industry (mostly for cooling power plants), 13% by agriculture, 14% by municipalities, and 16% by other economic sectors. Water pollution is one of the key environmental problems in Russia. Between 1992 and 2017 the annual discharge of contaminated water declined from 99 to 43 billion m3/y. However, pollution levels are still very high and include sulfates and chlorides (about 20% of total discharge), and very hazardous substances like mercury, lead, phenols, etc. (Rosstat, 2018). About 3000 cases of high and extremely high levels of pollution are registered in Russia each

Water-related problems with special reference to global climate change in Russia  25

Figure 2.1: Dynamics and structure of freshwater withdrawal in Russia, 1993–2017 (billion m3/y). Source: Rosstat (2019).

year. In the last five years, approximately 320–330 water reservoirs were reported as being highly polluted (Roshydromet, 2017). The most polluted waters have been reported in the Sverdlovsk region (Urals) and the Moscow region. There is a huge inefficiency in water use, especially in the European part of Russia. Overall losses are estimated to be as much as 9%–10%, while in industry water leakage and accidents lead to losses of over 25%. Municipal water systems lose 20%–40% of their water due to leakage in buildings and corrosion of water supply networks. In agriculture up to 30% is lost due to excessive water use in the livestock management and crop production (Klaptsov, 2011). Global forecasts of freshwater availability and consumption are worrisome: due to the rapid growth of the world’s population and economies, the demand for freshwater will be rising in the next few decades, while the availability of clean water will decline due to water loss, pollution, and the impacts of climate change (Danilov-Danil’yan, 2007). In the most pessimistic scenarios, the global demand may reach the water supply capacity in the middle of 21st century, leading the world to a potentially catastrophic water crisis. The consequences are multiple and extremely dramatic: billions of people without proper access to drinking water, migration, potential water wars, and so on (National Intelligence Council, 2012). Russia will be unlikely to experience such tragic impacts, as the country is overall sufficiently rich in water resources and the population is not under water stress in most of its territory today. However, these issues require more in-depth analysis.

26  Chapter 2

2.3  Climate change in Russia: trends and projections Global warming is a serious challenge for the world and for Russia in particular. The annual mean temperature in Russia is rising 2.5 times faster than the global average: between 1976 and 2016 local warming reached 0.45°C per decade. Precipitation has also changed substantially in Russia: annual precipitation has increased by 2.1% per decade since 1976, especially in the spring (5.9% per decade), while in summer the European part of Russia experiences declines in precipitation, most significantly in the southern areas. Snow cover periods have been declining in most of the country’s territory by an average of 1.01 days per decade. The annual water flow of major rivers in the last 30 years has been exceeding previous levels due to the increase in precipitation, more frequent winter thaws, flash floods, and ice deadlocks in rivers (Roshydromet, 2017). The frequency of the most dangerous hydrometeorological events has been continuously increasing over the last decade (Fig. 2.2) and is much higher than in previous years. Worrisome effects are being observed in cryolite zone areas, where the surface temperature is rising and in some areas the depth of seasonal melting is increasing. The speed with which the Arctic Ocean ice cover is melting is extremely dangerous: since 1981 it has increased to 13.3% per decade (as of 2016) (Fetterer et al., 2016). Projections of climate change in the 21st century are based on different scenarios of economic development, dynamics of natural systems, and numerous other factors. The scenarios of the Intergovernmental Panel on Climate Change (IPCC) provide various estimates of the expected average rise in global temperature by the end of 21st century: from 0.2–1.8°C under the most optimistic (RCP2.6) to 2.6–4.8°C under the most pessimistic (RCP8.5)

Figure 2.2: Annual number of dangerous hydrometeorological events leading to substantial damage to the national economy and population in Russia. Source: Roshydromet, 2018.

Water-related problems with special reference to global climate change in Russia  27 (IPCC, 2013). (RCP stands for Representative Concentration Pathway, a greenhouse gas concentration trajectory scenario adopted by the IPCC. Four RCPs have been selected for climate modeling and research.) All modern climatic models show a speed of warming much higher in Russia than the global average by 2100, especially in the winter season and in northern areas. In summer the temperature is expected to rise by 2–3°C (under the RCP2.6 scenario) to 3–4°C (under RCP8.5); however, in the Arctic seashore warming may reach 5–6°C (Climatic Center of Roshydromet, 2017). Overall precipitation will be increasing in Russia during this century. In winter, precipitation will increase over the whole country, especially in the eastern and northern regions. Some decline in precipitation is expected in the southern areas of European part of Russia by midcentury (Roshydromet, 2014). Global climate change processes will lead to changes in the frequency and intensity of extreme weather events. Most of Russia will experience an increasing number of days with anomalously high air temperatures and a reduction in the number of days with extremely low temperatures. The scale of precipitation will very likely also be exaggerated: stronger rainfalls, floods, storms, heat and cold waves (IPCC, 2013; Roshydromet, 2014). Many regions in the European part of Russia will also face an increasing number of days with anomalously high levels of precipitation in the winter and much lower levels in the summer (Kattsov, Shkol’nik, & Yefimov, 2017). Moreover, the snow cover of terrestrial areas in Russia is expected to decline; the speed of the decline depends on the particular scenario and the region involved. Under the RCP8.5 scenario, IPCC’s most pessimistic, the speed will increase in the second half of the 21st century, while under more optimistic scenarios the speed may be lower (Pavlova, Kattsov, Pikaleva, Sporyshev, & Govorkova, 2013). Different projections of the change in Arctic sea ice provide very diverse estimates; however, the most pessimistic scenarios assume disappearance of long-standing sea ice by the middle of the 21st century, which is considered possible (Pavlova and Kattsov, 2013). This will have a dramatic impact on fragile Arctic ecosystems, biodiversity, indigenous people, etc.

2.4  Impacts on water-related economic sectors Risks for water resources. Russian water resources experience significant year-by-year variability, which will likely be exacerbated by global warming, especially in the northern territories of Russia. Although in the last 35 years the average river-water flow has increased by approximately 5% (compared with 1936–1980), a few rivers were short of water at the beginning of the 21st century. For instance, the water in the Don River declined to its lowest

28  Chapter 2 level since 1891, meaning that the water reservoir of the Tsimlyanskoe hydropower plant did not have a sufficient inflow of water, which led to a sharp decrease in freight transportation on the lower Don, a worsening of ecological conditions, and a shortfall in water for all categories of users. The extreme duration of low water inflow has also been observed in the river basins of Baikal Lake. The annual flow of the Selenga River (representing 60% of the water supplied to Baikal Lake) declined below the average “normal” level in the period 1999–2016 (except 2013), which led to numerous economic and environmental problems. Similar issues have appeared in the basin of the Volga River (low water inflow in 2014–2015), though trends are not well determined so far. At the same time, the trend towards the increasing changeability of water resources and water level extremes (maximum and minimum) has been identified already for the Amur, the Enisei, and other large Russian rivers. The seasonal distribution of water flows in Russia is also vulnerable to climate change. Over the last 40 years the water flow in winter has been increasing, while in spring the level of water flow in the Volga, the Don, the Dnepr, and some other rivers has declined by 10–30%. Water use. The demand for water in Russia has declined since the 1980s by approximately 50%, mostly due to the economic restructuring. However, in the future water-consuming industries and agriculture will likely expand and demand for water will grow. The biggest industrial consumers of water in the country are power plants, whose demand could increase by 45% by 2030, from 29 to 42 km3 per year (Order of the Government of the Russian Federation, 2009). In rural areas, the primary user of water is irrigation for agriculture, which is expected to increase threefold under a federal governmental irrigation program. However, this expansion will only be possible in areas with an excess of water, such as the Russian Far East and Siberia; in the southern regions of the European part of Russia the water deficit will not allow the use of traditional irrigation technologies. Climate change–induced risks for water users have been determined for those regions that already face water shortages, particularly in the basins of the Don, the Kuban, the lower and middle Volga, and the Ural Rivers. In Siberia and the Far East water availability will not pose a risk for industrial and agricultural development. Dangerous hydrological events. Human populations and economic and ecological systems are at high risk due to flash floods, the intensity and frequency of which have been increasing in some regions (e.g., Northern Caucasus, Primorie). In 2013 the Amur River basin experienced an unprecedented extreme water rise, which led to economic damage estimated at over 20 billion USD. Other extreme events in the form of heavy rainfall and floods have been observed in the southern regions of Russia (e.g., the Kuban River basin), which led to the loss of human life and economic damage. The Russian hydrometeorological agency

Water-related problems with special reference to global climate change in Russia  29 (Roshydromet) has undertaken a detailed regional risk assessment for the main rivers of Russia through 2050 to develop resilience-building and risk-reduction measures (Shkolnik, Pavlova, Efimov, & Zhuravlev, 2018). It has also been determined that the increased variability of climate conditions will lead to anomalies in both high and low water flows in rivers and that often the shortage of water will cause substantial damage comparable with excessive water and floods. The main objects at risk include hydropower plants, river transportation, and supply systems for drinking water. Marine activities. Shipping, port operations, fisheries, and the energy sectors are the most vulnerable to climate change’s effects on Russian seas. Heavy sea swells reduce the speed of shipping by 10%–18% (Climatic Center of Roshydromet, 2017). Fog (especially in seashore areas) also affects the cruising speed of ships. Sea-level variation in seashore territories is the most dangerous in low-depth zones, where the water level may change up to 1.5 m in a short while, which may prevent the movement of ships through sea channels. Sea-level rise will negatively affect port infrastructures and require reconstruction of wharfs and creation of anti-wave protection systems. Fishery resources are vulnerable to shifts in the temperature, salinity, acidity (pH), and oxygen content of water, which may vary due to climate change. As a result of fish migration to more favorable locations, fishing areas and stocks of fish may change significantly and substantially affect the volume of fish caught. Increased sea-level variation may also lead to large-scale disruption of energy facilities, damage to oil tankers, and pollution of local areas by petroleum products. For example, an accident in the Kerch Strait in November 2007 led to an oil spill and environmental damage estimated at about 200 million USD (Korshenko, 2011). Climate risks in the Arctic area. The main risks to economic activities in the Arctic are related to low temperatures, which may affect certain features of various construction materials, icebergs, and sea ice, imposing an additional load on equipment and infrastructure and leading to the icing of ships. Climate change leads to a high frequency in and intensity of extremes in atmospheric conditions, sea ice creation, and impacts on water operations that include highly dangerous effects such as storm winds, ice, waves, low visibility, and ice surges in seashore areas. The Arctic environment has a well-expressed seasonal variation in vulnerability to climate change, which increases in the summer season as a result of more intensive economic activities. Development of oil and gas fields and transportation of hydrocarbons in Arctic seas pose a high risk of accidents and spills. As existing technologies for crude-oil collection are not effective under conditions of high waves and storms, such crude oil spills are extremely dangerous for the local environment and ecosystems. Agriculture. Although the warming climate is considered to be favorable for the harvesting of crops in Russia, more in-depth analysis shows that the frequency of dry seasons and the scale of damage to crop production has been increasing in the last few decades. Over 60% of crop production areas in Russia are located in places with low precipitation and water availability.

30  Chapter 2 The severe droughts in 2010 and 2012 in the country led to losses of 33% and 25% of the crop harvest, respectively, and overall economic damage of 9 billion USD (Safonov & Safonova, 2013). Localized small- and medium-scale droughts do not lead to significant losses of crops; however, large-scale and intensive droughts are increasingly more damaging to the national economy, affecting food prices and the economic stability of agribusinesses (Frolov & Strashnaya, 2011). In the coming decades the productivity of crops is expected to decline and some traditional agricultural areas will experience unfavorable weather conditions due to climate change, which will require strong efforts and high costs to introduce irrigation and develop new crop production technologies. Human health. Climate change has already had severe impacts on human health in Russia, and its negative consequences will likely increase in the future. The main water-related impacts include an increase in dangerous hydrometeorological events (floods, droughts, fires); an increase in precipitation and waterlogging; the melting of permafrost, especially in the northern areas of the European part of Russia; water stress; and desertification. These impacts have direct effects on mortality and morbidity (circulatory system problems, cardiovascular diseases, asthma, hypoxia, etc.) in human populations, as well as indirect impacts, such as expanded zones of disease vectors (malaria, encephalitis, etc.), infections, allergies, mental health problems, alcoholism, and others. The most destructive impacts in Russia include those related to floods, forest fires, and extreme heat, leading to an increased number of deaths, a worsening of epidemiological conditions, and more injuries. Another danger relates to the combined impact of periods of no precipitation, extreme heat waves, and high air pollution, which can result in dramatic health problems, as was observed in 2010 in the European part of the country (over 54,000 additional deaths over the summer season) (CRED/UNISDR, 2016; Revich, 2011). Global warming is also leading to an expansion of bacterial flora in food and water, and increasing the risk of morbidity from infections, parasites, and viruses (salmonella, rotaviruses, enteroviruses, etc.) (Grjibovski et al., 2013). Migration. Climate change may lead to an inflow of migrants (climate refugees) into Russia, which will affect the demographic characteristics and the social and ethnic structure of the population. By 2050 at least 200 million climate migrants will require support, mostly those in low-lying areas (3–4 m above sea level) and areas with severe drought (IPCC, 2013). A massive migration from Central Asia (Tajikistan, Uzbekistan, Kyrgyzstan) due to water shortages may become a big challenge for Russia in the coming decades (Shustov, 2010). Navigation and transport. Shorter periods of ice cover on waterways (rivers, channels) due to warming may increase the length of navigation seasons. Overall, most of the main rivers in Russia are expected to have increased water flow, providing favorable conditions for navigation. However, observable negative processes in riverbed formations will worsen conditions for river navigation and require massive investments into deepening and modifying riverbeds. The high frequency and intensity of dangerous hydrometeorological events will

Water-related problems with special reference to global climate change in Russia  31 also affect the safety of navigation. Another important issue relates to transport systems that depend on roads and ice crossings in winter. The city of Yakutsk (300,000 people) and many remote Arctic areas are highly dependent on receiving supplies via such transportation systems, which may become at risk due to climate change. Hydropower. Hydroenergy systems are vulnerable to climate change, due specifically to potential changes in precipitation, water availability, the demand for water in various economic sectors, and other factors. The nation’s hydropower plants were designed with a high level of hydrological safety; however, they face the risks of extremely low and extremely high volumes of water during periods of snowmelt and rain (a 1% change in monthly water inflow into reservoirs leads to a 1% change in power generation, on average) (Kobysheva, 2005). A change in water demand by various sectors of the Russian economy will also pose potential risks for hydropower generation: in dry seasons the agricultural sector and municipalities may substantially increase water intake, which may affect the supply of available hydropower from the Unified Energy System of Russia and local electricity systems. Melting permafrost. Climate change is leading to a temperature increase in long-standing frozen ground, destructive geocryological processes, uneven degradation of soil, etc. These processes have already been observed in some urban Arctic areas of Russia. In the last decade the number of buildings damaged due to melting permafrost in the city of Norilsk has increased dramatically (Grebenets, Streletskiy, & Shiklomanov, 2012). The most vulnerable areas include Chukotka, the Indigirka and Kolyma River basins, southeastern Yakutia, and some others, including regions with highly developed gas and oil infrastructure, where the risk of accidents and massive damage to the environment is rising.

2.5  Climatic risk management in Russia Prevention and mitigation of risks from climate change is a part of the Climate Doctrine of the Russian Federation and the government’s plan for its implementation. Scientific information on climatic processes should be used to reduce potential damage and realize opportunities for building resilience into social, economic, and ecological systems. The first step is the analysis of risks, including the identification of various kinds of risks, the quantitative assessment of them, and projections of their interaction with the anthropogenic environment. Each stage of risk analysis will require close cooperation between users of climatic information and decision makers. The identification of risks is a complex task that is highly dependent on the knowledge and capability of analysts: both primary and secondary consequences of dangerous climate conditions must be taken into account, different categories of risk targets should be included (social, natural, technical, etc.), and each identified risk needs to be assessed with respect to local circumstances.

32  Chapter 2 Monitoring of hydrometeorological conditions will play an important role in the projection of risks and should be coupled with technical monitoring of the vulnerabilities of targeted areas, including an analysis of exposure, degree of sensitivity, adaptive potential, and long-term changes in elements of targeted areas (e.g., aging of buildings and infrastructure). Adequate assessment of trends is especially needed under conditions of nonstationary and disbalanced climate. In Russia climatic monitoring uses a unified system of state environmental monitoring from the Ministry of Natural Resources and Environment. The World Meteorological Organization (WMO) has developed a software product called Climpact that allows users to assess changes in extreme levels of climatic parameters, which is important for specific industries and society. There is still no systematic monitoring of two other elements of risk management: exposure and vulnerability assessment. Both climatic and technical monitoring can be applied at a global, national, regional, and local level, and in some cases joint analysis can be helpful (e.g., analysis of regional trends may be less reliable than a global trend assessment). The projection of climatic risks is often based on modeling of future climate trends and information about socioeconomic development strategies and plans. Usually the models run different scenarios, including those aimed at the identification and evaluation of the effectiveness of policy measures. In Russia both global and regional climatic models are applied. The assessment of exposure of and impact on some targets is often very difficult, as relevant data (e.g., damage estimates) may be missing or not reliable. In such cases indirect methods can be applied; for instance, in the assessment of the vulnerability of specific territories to dangerous hydrometeorological events (Kobysheva et al., 2015). Another important issue deals with the assessment of acceptable risk, a concept developed in the 1980s. In Russia the methodology for calculating acceptable risk is based on the scale of damage and frequency of events and has three risk classifications: unacceptable, acceptable, and negligible (Akimov, Bykov, & Faleyev, 2004). In some cases targets face the impact of a combination of dangerous processes, which creates a complex risk profile, such as sea-level rise leading to the destruction of seashores, salinization of aquifers, etc. In such situation the analysis of risk in the target area requires the inclusion of a whole spectrum of impact factors and subjects of risk. The CliPLivE project provides a good example of complex risk assessment for climate change impacts (ENPI, 2012). In Russia, a complex climatic risk assessment was made of the socioeconomic situation in different regions. The biggest risk was assigned to the Central Federal District in

Water-related problems with special reference to global climate change in Russia  33 the European part of the country, where the high frequency and intensity of dangerous hydrometeorological events are combined with the most developed economy and a high density of population. High risks were also identified for the southern regions of the European part of Russia, for southern Siberia, and for the Far East. The effective climatic risk management should include the following basic strategies: • •

Hard strategy. The development of infrastructure more adapted to and resilient against climate change impacts. Soft strategy. The improvement of institutions and management systems, capacity building, scientific support, technical solutions, and the availability of financing and insurance.

Climate risk insurance is a highly expected direction of development in adaptation and resilience building in Russia. However, there are several barriers to implementing such a mechanism: lack of reliable scientific information about impacts and vulnerabilities on the local and corporate level, a relatively low level of development of the Russian insurance market, inadequate institutions, and a lack of experience in using different insurance instruments. The challenges of climate change require strong policy making in adaptation and resilience building in Russia. According to the national action plan, numerous measures have already been undertaken by different governmental bodies, industries, regions, and other stakeholders (Order of the Government of the Russian Federation, 2011). However, a comprehensive adaptation strategy through 2030 is still to be developed and adopted in Russia.

2.6 Conclusion The main ideas about climate change and water-related problems in Russia are as follows: Firstly, Russia is one of the world’s leaders in terms of its amount of freshwater resources. These, however, are unevenly distributed across the country. With respect to anthropogenic impacts, water pollution is one of the key environmental problems in Russia, along with a huge inefficiency in water use, especially in the European part of the country. Secondly, global warming represents a major challenge for Russia and for the world community. The annual mean temperature in Russia is rising much faster than the global average, while the frequency of the most dangerous hydrometeorological events has increased continuously in the last decades. These trends will continue in the same direction, according to the projections of the IPCC. Thirdly, climate change is expected to affect numerous water-related economic sectors in a detrimental way: from marine activities and fisheries, which are highly vulnerable to changes

34  Chapter 2 in temperature, salinity, acidity (pH), and oxygen levels, to human health, which may be impaired by the increase in bacterial flora in food and water, and, consequently, provoke massive migrations. Finally, the Russian government is currently addressing the problem of climate change within the framework of the Climate Doctrine and the government’s plan for its implementation. At the same time, there is a need to improve the national climatic risk-management system.

References Akimov, V. A., Bykov, A. A., & Faleyev, M. I. (2004). Normativno-ekonomicheskiye modeli upravleniya riskom. Problemy analiza riska, 1(2), 125–137. Climatic enter of Roshydromet. (2017). Doklad o klimaticheskikh riskakh na territorii Rossiyskoy Federatsii. – Sankt-Peterburg. https://meteoinfo.ru/images/media/books-docs/klim-riski-2017.pdf CRED/UNISDR. (2016). Poverty and death: disaster mortality 1996-2015. Danilov-Danil’yan, V. I. (2007). Voda - strategicheskiy faktor razvitiya ekonomiki Rossii. Vestnik Rossiyskoy akademii nauk, 77(2-S), 108–114. ENPI. (2012). Cliplive - climate proof living environment project. http://cliplive.infoeco.ru/index.php?id=4 FAO. (2016). AQUASTAT website. http://www.fao.org/nr/water/aquastat/countries_regions/RUS/ Fetterer, F., Knowles K., Meier, W. N., Savoie, M., & Windnagel, A. K. (2016). Sea Ice Index (Version 3) [Database/software]. Boulder, CO: National Snow and Ice Data Center (NSIDC). doi: http://dx.doi. org/10.7265/N5736NV7 Frolov, A.V., & Strashnaya, A.I. (2011). O zasukhe 2010 goda i yeye vliyanii na urozhaynost’ zernovykh kul’tur/ Analiz usloviy anomal’noy pogody na territorii Rossii letom 2010 g.: sb. dokladov/pod red. NP Shakinoy. M.: Triada-LTD. Grebenets, V., Streletskiy, D., & Shiklomanov, N. (2012). Geotechnical safety issues in the cities of polar regions. Geography, Environment, Sustainability, 5(3), 104–119. Grjibovski, A. M., Bushueva, V., Boltenkov, V. P., Buzinov, R. V., Degteva, G. N., Yurasova, E. D., & Nurse, J. (2013). Climate variations and salmonellosis in northwest Russia: A time-series analysis. Epidemiology & Infection, 141(2), 269–276. IPCC. (2013). Fifth Assessment Report. https://www.ipcc.ch/assessment-report/ar5/ Kattsov, V. M., Shkol’nik, I. M., & Yefimov, S. V. (2017). Perspektivnyye otsenki izmeneniy klimata v rossiyskikh regionakh: detalizatsiya v fizicheskom i veroyatnostnom prostranstvakh. Meteorologiya i gidrologiya(7), 68–80. Klaptsov V. (2011). Water resources and water problems in Russia. Moscow, RISI. https://riss.ru/analitycs/1049/ Kobysheva, N. V. (2005). Entsiklopediya klimaticheskikh resursov Rossiyskoy Federatsii. SPb, Gidrometeoizdat, 319 p 2005. Kobysheva, N.V., Akent’yeva, Ye. M., & Galyuk, L.P. (2015). Klimaticheskiye riski i adaptatsiya k izmeneniyam i izmenchivosti klimata v tekhnicheskoy sfere. Sankt-Peterburg, Kirillitsa, 214 p. Korshenko, A. (2011). Oil Spill Accident in the Kerch Strait in November 2007. Nauka. National Intelligence Council. (2012). Global water security: Intelligence community assessment (ICA 2012-08). https://www.dni.gov/files/documents/Special%20Report_ICA%20Global%20Water%20Security.pdf Order of the Government of the Russian Federation of 27.08.2009 N 1235-p (as amended on April 17, 2012) “On approving the Water Strategy of the Russian Federation for the period up to 2020” // “Sobraniye zakonodatel’stva RF”, 07.09.2009, No 36, st. 4362. Order of the Government of the Russian Federation of 25.04.2011 N 730-p (as amended on January 31, 2017) “On approving a comprehensive implementation plan for the Climate Doctrine of the Russian Federation for the period up to 2020” // “Sobraniye zakonodatel’stva RF”, 02.05.2011, N 18, st. 2680.

Water-related problems with special reference to global climate change in Russia  35 Pavlova, T. V., & Kattsov, V. M. (2013). Ploshchad’ ledyanogo pokrova Mirovogo okeana v raschetakh s pomoshch’yu modeley CMIP5. Trudy Glavnoy geofizicheskoy observatorii im. AI Voyeykova(568), 7–25. Pavlova, T. V., Kattsov, V. M., Pikaleva, A. A., Sporyshev, P. V., & Govorkova, V. A. (2013). Snezhnyy pokrov i mnogoletnyaya merzlota v modelyakh CMIP5: otsenki sovremennogo sostoyaniya i yego vozmozhnykh izmeneniy v XXI v. Trudy Glavnoy geofizicheskoy observatorii im. AI Voyeykova(569), 38–61. Revich, B. A. (2011). Volny zhary, kachestvo atmosfernogo vozdukha i smertnost’ naseleniya Yevropeyskoy chasti Rossii letom 2010 goda: rezul’taty predvaritel’noy otsenki. Ekologiya cheloveka, (7). Roshydromet. (2014). http://www.meteorf.ru/upload/iblock/4c0/Obzor_2014.pdf Roshydromet. (2017). Report on climate features on the territory of the Russian Federation in 2016. http://www. meteorf.ru/press/news/13595/;http://www.meteorf.ru/product/infomaterials/90/. Rosstat. (2017). Russia in numbers. http://www.gks.ru/free_doc/doc_2017/rusfig/rus17.pdf Rosstat. (2018). Russia in numbers. http://www.gks.ru/free_doc/doc_2018/rusfig/rus18.pdf Rosstat. (2019). Statistics. Environment. http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/ru/statistics/ environment/ Safonov, G., & Safonova, Y. (2013). Economic analysis of the impact of climate change on agriculture in Russia. Oxfam Research Reports. Shkolnik, I., Pavlova, T., Efimov, S., & Zhuravlev, S. (2018). Future changes in peak river flows across northern Eurasia as inferred from an ensemble of regional climate projections under the IPCC RCP8.5 scenario. Climate Dynamics, 50(1–2), 215–230. Shustov A., 2010: Klimat i migratsiya. Chem chrevaty dlya Rossii klimaticheskiye izmeneniya v stranakh Tsentral’noy Azii. http://www.stoletie.ru/geopolitika/klimat_i_migracija_2010-03-05.htm

CHAPTE R 3

Water-related problem with special reference to global climate change in India Binota Thokchom Centre of Nanotechnology, Indian Institute of Technology Guwahati, Amingao, Assam, India

3.1 Introduction The United Nations Framework Convention defines climate change as human activities that alter the composition of the global atmosphere, thereby causing destruction to natural environmental variability (United Nations Framework Convention on Climate Change, 1992). Some of the significant impacts of climate change are variation in weather patterns, rising sea levels, and the occurrence of unexpected calamities. This phenomenon is found to occur not only in one region or continent, but all around the world. From Cape Town to London, and from rural, sub-Saharan Africa to Asia’s teeming megacities like Bangalore and Beijing, there’s a global crisis, with issues on water being the most significant. It has been predicted that in the next few decades, billions of people, especially those residing in developing nations, will encounter a severe scarcity of basic commodities like water and food, consequently posing harm to health and life. New diseases will be introduced and productivity of healthy crops will be reduced, along with increased chances of consuming plagued food. Apart from that, glaciers are being feared to disappear in no time. Extreme weather conditions like floods, droughts, and storms, increased coastal flooding and species extinctions will be common in the near future. Since changes in atmospheric temperatures permutates the radiation balance, disrupting the evaporation rate, precipitation pattern, etc., climate change is expected to give the greatest constraint in water availability pattern in the future. These changes also determine the distribution pattern of river flows and groundwater recharge over space and time. In recent decades, enough reports have also been published worldwide against the impact of climate change on global hydrological cycle (Islam, Sikka, Chaudhuri, & Biswas, 2015; Loo, Billa, & Singh, 2015), including changes in water vapor content, changing patterns of precipitation, reduced snow and ice cover, differences in soil moisture and runoff. However, the most visible and altered footprints in India, as a result of climate change, seem to be incandescent flood and drought, both faced in a single year. One of the consequences of these two deadly calamities is the shortage of healthy consumable water, which is already posing a challenge to development and environmental sustainability in every corner of Water Conservation and Wastewater Treatment in BRICS Nations http://dx.doi.org/10.1016/B978-0-12-818339-7.00003-5

37

Copyright © 2020 Elsevier Inc. All rights reserved.

38  Chapter 3 the world. At present, globally, almost 1 in 9 people (i.e. around 844 million people) lack access to safe and clean water. To tackle these challenges, initiatives at the global level have been taken up, such as the UN’s Agenda 21, Millennium Development Goals, Millennium Ecosystem Assessment, World Water Development Report, the World Water Flora. The United Nations has also recognized March 22 as World Water Day, to remind the urgent need of combating the issues of global water crisis (https://sustainabledevelopment.un.org/post2015/ transformingourworld; https://www.worldvision.org/clean-water-news-stories/global-watercrisis-facts). However, developing countries with the least resources to adapt are expected to have the greatest culmination due to climate change. Among them, India, with the largest population of global poor (30%) (Goyal & Surampalli, 2018) and with agriculture as the main living source, will also be one. It is also estimated that by 2020, approximately 250 million people in Africa alone could be exposed to a greater risk of water shortage; in addition, melting of glaciers will lead to an increased risk of floods of coasts globally with some small island states probably facing total inundation (Climate Change, inpress3). Without going into details, it is already a known fact that in today’s era, the issue of climate change raises difficult questions to science and economics, and it has been debated widely over the years. However in India, ironically, not enough reports on legal policies have been formulated for solving this problem. Therefore, keeping in mind about the significant gaps, an attempt has been made to analyze climate change and its impact on water from different perspectives. Specifically, the chapter highlights various discussions on prevailing parameters that control nature and climate change, and also the consequences arising out of the country’s water scenario. Some of these parameters are precipitation, surface- and groundwater, flood and drought, and ice and glaciers. Along with that, the current legal framework related to climate change and water in India are also addressed. One of the most important topics, “impacts on Indian economy,” especially on agriculture is also covered. Last, as part of a solution-oriented approach, various mathematical models and simulation tools to predict the intensity of impacts received from climate change are also analyzed. Overall, the chapter aims to create awareness and to enhance the understanding of present degrading climatic conditions and their vulnerability to availability of clean and safe water to a developing country like India.

3.2  Indian context on climate change and water With its massive coastal lines of 7,517 km, the mighty snow-clad Himalayan region and numbers of islands (Goyal & Surampalli, 2018), India is also under the severe threat of climate change. It is facing some of the acute consequences through changes in magnitude and intensity of rainfall, improper groundwater recharge, floods and drought disasters, contamination of surface water and groundwater resources, etc. Situated in the north of the equator in South Asia, India is the seventh largest in area and the second most populous country in the world. It is rich in its water resources, which are highly modulated by its

Water-related problem with special reference to global climate change in India  39 topographical, hydrogeological, and climatic characteristics. The diverse topographical features of India, which include high mountains, hot deserts, high plateaus, and extensive plains traversed by large rivers strongly influence the regulation of the regional climate and also affect surface water retention and runoff rates, dictate the direction of groundwater flow and influence groundwater recharge and discharge (Madhusoodhanan, Sreeja, & Eldho, 2016). This diverse geography itself poses a major criterion to be extremely prone to destructive alteration by climate change. Below are some of the water-related issues that are affected and altered by change in the climate pattern of India.

3.2.1  Climate change and precipitation Global warming, which is a major event of climate change, intensifies the atmospheric moisture content, giving rise to extreme precipitation (Ghosh, Das, Kao, & Ganguly, 2012; Willett, Gillett, Jones, & Thorne, 2012). Min, Zhang, Zwiers, and Hegerl (2011), had predicted to further amplify this phenomenon under the influence of climate change, giving rise to many societal challenges like flooding, crop damages, health hazards, erosion, and water contamination (Min et al., 2011). Again, the water resources assessment in India is primarily based on the average amount of precipitation received. The estimate of the mean annual precipitation itself shows high variability across different datasets (Prakash, Sathiyamoorthy, Mahesh, & Gairola, 2014). There is also high spatial inter- and intra-annual variability in precipitation, which significantly affects both regional and seasonal surface and groundwater availability across the country. India’s precipitation is mainly contributed to its rainfall. Precipitation due to snowfall is limited to the sub-Himalayan region only (Mukherji, Shah, & Giordano, 2012). India has witnessed some of the most devastating extreme precipitation events, which have affected urban transportation, agriculture, and infrastructure. Despite the profound implications and damage due to extreme precipitation events, the influence of anthropogenic warming on the intensity and frequency of extreme precipitation events over India remains poorly constrained. Mukherjee, Aadhar, Stone, and Mishra (2018), has reported about extreme precipitation events in India during the last few decades by using climate models like the Coupled Model Intercomparison Project 5 (CMIP5) and Climate of 20th Century Plus (C20C+), detection and attribution (D&A) projects. It was successful in predicting that not only precipitation, but dew point temperature has also escalated during 1979–2015. It was also found that south India experienced higher scaling relationship between extreme precipitation and dew point temperature than in north India (Kendall, 1975; Mann, 1945; Mukherjee et al., 2018). In simple terms, it can be concluded that precipitation is highly influenced by global anthropogenic warming of the climate, which has further intimidation to the damage in water resources of India. This study was also in agreement with Krishnan et al. (2016), who

40  Chapter 3 had simulated at high resolution and showed an increase in the frequency of extremes in the core monsoon region of India under increased greenhouse gas emission scenario (Krishnan et al., 2016). Diverse mechanisms to explain such relative phenomena have appeared in various articles. NASA has also published on its website that the rising temperatures intensify the Earth’s water cycle, thus increasing evaporation. Increased evaporation will result in more storms, but also contribute to drying over some land areas. As a result, storm-affected areas are likely to experience increase in precipitation and also risk of flooding, while areas located far away from storm tracks are likely to experience less precipitation and increased risk of drought (https://pmm.nasa.gov/resources/faq/how-does-climate-change-affect-precipitation). One of the promising models to explain them is Clausius-Clapeyron (C-C), which shows the relationship between moisture-holding capacity/precipitation of the atmosphere with global warming. Bao, Sherwood, Alexander, and Evans (2017) have observed a negative C-C scaling relationship between extreme precipitation and surface air temperature in tropics, due to temporarily local cooling (Bao et al., 2017). Vittal, Ghosh, Karmakar, Pathak, and Murtugudde (2016) also reported a negative relationship between surface air temperature and extreme precipitation as a result of localized cooling of air temperature and seasonal rainfall (Vittal et al., 2016). Due to the negative C-C relationship between precipitation and surface air temperature over the tropical regions, Lenderink and Meijgaard (2010) argued that dew point temperature is a better prediction of extreme precipitation than surface air temperature over the tropics (Lenderink & Meijgaard, 2010). In short, a climatic condition of a specific area is controlled by the quantity and nature of precipitation received. Besides, it directly or indirectly influences the soil condition and vegetation type, agricultural activity, quantity of water available for human consumption, and apparently decides whether the place is habitable. The liveliest examples in Indian context on precipitation phenomenon are the rain forest and the seasonal monsoon climate. On the contrary, when the Earth’s temperature rises up dramatically as a result of climate change, precipitation patterns also face its share of destruction, and ultimately causes harm to the living dynamics. Increases in temperature beyond a certain limit can speed up the evaporation rate, thus encouraging rapid surface drying and eventually escalating the intensity and duration of drought. Not only that, wildfires have become a common phenomenon in regions where there is a shortage of precipitation process taking place within a season. Western states of the US have been reported to face this event frequently. It is also predicted that immedicable scantiness of precipitation can convert a place into desert. Nonetheless, with every increase of 1˚C, it is reported that the water-holding capacity is increased by 7%. This again intimidates the precipitation pattern by fluctuating the water vapor content in the atmosphere. Precipitation also contributes to tropical rainfall and cyclones, thunderstorms and hurricanes, etc. In such cases the chance of occurring flood is high (Trenberth, 2005). Hence, it can be concluded that even though precipitation may not be the whole cause, it fosters most of the weather events that involve atmospheric motion and condensation heat liberation like tropical cyclones, storms, cold fronts, etc.

Water-related problem with special reference to global climate change in India  41

3.2.2  Climate change and Indian monsoon pattern The Indian subcontinent experiences wet summers and dry winters. It has four monsoonal seasons (June–September); 75 % of the annual average precipitation (1100 mm) is contributed to this season. The Indian monsoon is credited to the intense solar heating that travels from the equator to the north. India follows a plethora of heterogeneity, both in spatial and temporal spaces. Due to its massive geological variation, the mean rainfall from region to region has not been distributed uniformly. During monsoon, the temperatures in the Northern Indian Ocean, sea surface, plains of northern India, and the Tibetan Plateau are significantly warm. One reason is that they are situated at an elevation of more than 4500 m on average. However, as the southern part of the country faces cooler climate during the same time, a temperature and pressure gradient is created, resulting in atmospheric movement carrying moisture evaporated from the warmer Indian Ocean to the cooler mountains Indian west coast and finally to the Bay of Bengal. It is more commonly known as “monsoon trough” of northern India, where more rain falls. On the other hand, the western part of its region (Rajasthan) receives only 100 mm of mean rainfall, while the eastern region holds the record of the highest rainfall point in the world with around 11,700 mm in Chirapunji, Meghalaya. The magnitude of annual rainfall is large in north eastern states and south western regions, which experience both southwest and northeast monsoons. In India, maximum mean rainfall value of 395.02 mm was observed during the month of August, which is also the peak time of southwest monsoon. Similarly, the minimum mean rainfall value of 5.47 mm was observed in the month of April, which is again the peak summer season (Climate Variability and Its Impacts on Water, inpress6). We should always keep in mind that even a slight deviation in this pattern can at times bring significant mutilation in the country’s assets. As cited in the next paragraph, India has faced the outcomes in all its corners, showing that climate change and its impact show no partiality, regardless of time and region. The Bangalore flood of July 2016 as a result of heavy rainfall disrupted many lives, terminating normal conveyance (The Hindu, 2016). The flash flood of the south that occurred in Tamil Nadu and Andhra Pradesh, 2015, touched nearly 4 million people, bringing confiscation of around 3 billion US dollars (Kotteswaran, 2015). The Mumbai flood of 2005 claimed approximately 1094 lives (Kumar, Dudhia, Rotunno, Niyogi, & Mohanty, 2008). However, the outpouring of Uttarakhand in 2013 led to financial depreciation of more than 3.8 billion US dollars, along with the death of nearly 6000 people (Rapidly Assessing Flood Damage, 2014). A cross-country flood of India–Pakistan in September 2014 affected Jammu and Kashmir in north India, claiming 277 people in India and 280 people in Pakistan. It also brought economic damage of around 1.5 billion US dollars (Trenberth, Dai, Rasmussen, & Parsons, 2003). In the northeast, the annual flooding in Assam between June and July 2012 reported that around 4.65 lakh hectares of farmland were submerged, affecting 3,829 villages and 23.08 lakh people (https://thewire.in/environment/kazirangarhinos-assam-brahmaputra-flood). The June 2005 flood in the west, i.e. Gujarat, affected 4547

42  Chapter 3 villages, 31 towns related to electricity supply. Also, 108 people were reported to have lost their lives either due to drowning and collapse of building walls (https://reliefweb.int/report/ india/india-gujarat-floods-situation-report-2-jul-2005-500pm). These are just a few examples of the outcomes of climate change on rainfall pattern that has caused serious floods in many parts of India, recently. There are also other similar devastating flood events caused by heavy rainfall not reported here. However, from all the observations, a conclusive idea can be drawn that India is now experiencing an atypical motif of rainfall events, sometimes bringing highintensity saggy damages, from infrastructure to loss of precious lives.

3.2.3  Climate change and glaciers of Himalaya Another dimension that is susceptible to adverse impacts of climate change and global warming is that of melting of ice and glaciers, at the same time retreating in some regions. Climate heat causes thermal expansion leading to melting ice in high altitudes. In India, many of its rivers are fed by ice and glaciers from the mighty Himalaya, thus vulnerable to climate change. The youngest and highest Himalayan mountains are the home of enormous freshwater reservoirs in the form of snow, glaciers, natural lakes, permafrost, and wetland. The Hindu Kush-Himalaya alone fetches ∼50% (by area) of all the Himalayan glaciers. If climate change further escalates temperature, then there will be more melting of glaciers, leading to significant shrinking, and then finally to unavoidable catastrophic outcomes. Eventually, the Ganges will have stunted flow, with a prediction of almost a decrease by two-thirds and affecting more than 400 million people who depend on it. However, as an immediate impact, it is expected to cause outbursts of river swelling and floods, leading to devastation in lowland valleys (http://www.scind.org/1148/Environment/how-much-indian-glaciers-are-affectedby-the-climate-change-in-indian-subcontinents.html). It is reported that if the current trends of climate change continue, by 2030 the size of the glaciers could be reduced by as much as 80%. As per the Intergovernmental Panel on Climate Change (IPCC), as of now, Himalayan glaciers have the largest fresh water next to the polar icecaps (Sharma & Sharma, 2008). On the other hand, it has been reported that almost 67% of the glaciers in the Himalayan mountain ranges have retreated and is expected to continue retreating. As a consequence, the main rivers of India, such as Brahmaputra and Ganga, have decreased their flows during the retreating season, shrinking their water supply from time to time, and hence disrupting the food and energy securities of the region. Glacial disruption by climate change has not only vandalized India, but also neighboring countries in terms of millions of population. It has also resulted in strange polar implications like sea level rise and at the same time drought in delta regions, dwindling in precipitation and torrential summer monsoon outpours, etc. In certain regions, significant outcomes like wetland dehydration, ecosystem retardation, water availability issues, and less access to quality environment are being encountered (Taenzler, Ruettinger, Ziegenhagen, & Murthy, 2011). For example, Anil V Kulkarni (Indian Institute of Sciences, Bangalore) opined that in the wake of climate change, the overall glaciers

Water-related problem with special reference to global climate change in India  43 may not decrease, but water content may shrink. It can also be accounted that from 1984 to 2012, the Chandra basin of western Himalaya has lost 11.1 gega-tonnes of water, which is nearly one-fifth of the evaluated amount. In another study, he mentioned Himalayan glaciers have retreated by around 13% in last four decades, with the water loss of 9 gega-tonnes per year in 1975–1985 to 20 gega-tonnes per year in 2010–2015 (http://www.scind.org/1148/ Environment/how-much-indian-glaciers-are-affected-by-the-climate-change-in-indiansubcontinents.html). Since glaciers feed the Indus River, too, it is also highly vulnerable to climate change (WWF, 2007). As temperature is a big limiting factor for glacier cycles, climate change and heating up will directly and indirectly control the well-being of the communities residing nearby. Populations resting on glaciers will thus have the respective outcomes of water shortages, variability and potentially greater flooding, too (Rizvi, 2005; WWF, 2005). One such vulnerable area is that of the aforementioned river, the Indus; 70% to 80% of the Indus water is fed by Himalayan glaciers. It is the highest amount received among the Asian rivers, which is also twice the amount received by the Ganges (30%–40%). Yang (1991) reported that in China alone, Himalayan glaciers deliver 44.8% of the water in the Upper Indus (Khaleeq, 2005; Yang, 1991).` Given below is the table (Hasnain, 1999) showing river systems fed by Himalayan glaciers. These rivers, if subjected to climate change, are prone to impact the downstream, too (Table 3.1). Table 3.1: Principal glacier-fed river systems of the Himalaya. River

Major river system

Mountain area, km2

Glacier area, km2

% Glaciation

Indus Jhelum Chenab Ravi Sutlej Baes Jamuna Ganga Ramganga Kali Karnali Gandar Kosi Tista Raikad Nanas Subansiri Brahmaputra Dibang Lunit

Indus System

268,842 33,670 27,195 8,092 47,915 12,504 11,655 23,051 6,734 16,317 53,354 37,814 61,901 12,432 26,418 31,080 81,130 256,928 12,950 20,720

7,890 170 2,944 206 1,295 638 125 2,312 3 997 1,543 1,845 1,281 495 195 528 725 108 90 425

3.3 5.0 10.0 2.5 2.7 4.4 1.1 10.0 0.04 6.01 2.9 4.9 2.1 4.0 0.7 1.7 4.0 0.4 0.7 2.0

Ganga System

Brahmaputra System

Source: Hasnain (1999).

44  Chapter 3

3.2.4  Climate change and groundwater resources Out of the total estimated annual precipitation of 4000 km3, total freshwater availability is estimated to be 1869 km3, in which the utilizable yield is assessed as 1123 km3 due to physiographical, social, legal, and technological constraints. Out of this, surface water contributes 690 km3 and replenishable groundwater contributes 433 km3 annually. Two-thirds of the available surface water and half of the groundwater potential are confined to three major river basins of Ganga, Brahmaputra, and Godavari (Mall, Bhatla, & Pandey, 2007). Although the most noticeable impacts of climate change could be fluctuations in surfacewater levels and quality, the greatest concern of water managers and government is the potential decrease and quality of groundwater supplies, as it is the main available potable water supply source for human consumption and irrigation of agriculture produce worldwide. It is increasingly recognized that groundwater cannot be considered, but should be managed holistically with surface-water dynamics. As part of the hydrologic cycle, it can be anticipated that groundwater systems will be affected by changes in recharge (which encompass changes in precipitation and evapotranspiration) and potentially by changes in the nature of the interactions between the groundwater and surface-water systems. Groundwater is directly interconnected to climate change via surface-water bodies like lakes and rivers; it is also indirectly associated via its recharge activity. While climate change affects surface-water resources directly through changes in the major long-term climate variables such as air temperature, precipitation, and evapotranspiration, the relationship between the changing climate variables and groundwater is more complicated and poorly understood. Because groundwater aquifers are recharged mainly by precipitation or through interaction with surface-water bodies, the direct influence of climate change on precipitation and surface water ultimately affects groundwater systems. Again, water from surface, namely rainfall, rivers, and lakes may reach aquifers and recharge groundwater rapidly, through macropores or fissures, or more slowly by infiltrating through soils and permeable rocks overlying the aquifer. A change in the amount of effective rainfall will alter recharge, and in the earlier sections, the impacts of climate change on rainfall had already been explained clearly (Kumar, 2012). Another aspect of climate change that is likely to affect the quality of groundwater is intrusion of salty water near coastal and island aquifers due to rising sea levels caused by global warming. Saltwater intrusion occurs as result of the landward movement of sea water into the coastal aquifer. This landward movement is caused by a change in the freshwater and saltwater pressure gradients. Sea-level rise increases the volume of saltwater resulting in increased saltwater hydraulic head. Again, warm air holds more moisture and increases evaporation of surface moisture. With more moisture in the atmosphere, rainfall and snowfall events tend to be more intense, increasing the potential for floods. However, if there is little or no moisture in the soil to evaporate, the incident solar radiation goes into raising

Water-related problem with special reference to global climate change in India  45 the temperature, which could contribute to longer and more severe droughts. Therefore, climate change has the potential to alter the recharge of the ground, which can control the characteristics of flood and drought. Changes in recharge therefore will be determined by changes in the duration of flow of these streams, which may locally increase or decrease, and the permeability of the overlying beds, but increased evaporative demands would tend to lead to lower groundwater storage. On the other hand, a confined aquifer is characterized by an overlying bed that is impermeable, and local rainfall does not influence the aquifer. It is normally recharged from lakes, rivers, and rainfall that may occur at distances ranging from a few kilometers to thousands of kilometers (Saltwater intrusion, inpress12). Groundwater is the source of nearly 85% of the rural water supply in India. Every year, this country’s groundwater has the potential of recharging up to 45.22 Mha-m (Kumar, 2012; Suhag, 2016). However, careless handling and extraction of subsurface water has resulted in significantly decreased levels of water tables. One example is Ahmedabad of Gujarat, where it has been reported that every year, 4–5 m of the groundwater level are being dropped. Mall, Gupta, Singh, Singh, and Rathore (2006) has mentioned that an escalation of 1% total carbon emission of India is almost equivalent to every 1 m decrease of groundwater (Mall et al., 2006).

3.2.5  Climate change and drought and flood India has been facing drought for decades. In 1871–2002, it has recorded 22 major drought years. Many researchers have been citing the phenomenon of El Nino-Southern Oscillation as the reason for this abnormality in Indian monsoon (Gadgil, Vinayachandran, & Francis, 2003; Saith & Slingo, 2006). El Nino pattern is the abnormal warming of the Eastern Pacific Ocean, bringing chaos in weather patterns and linked with abnormal rains in the Asia Pacific Region, including India. An encyclopedic survey by Sikka (1999) quoted that the monsoonal aberrations were more frequent during the era 1890–1920 and 1960–1990. It was further added that the staggering droughts of 1877, 1899, 1918, and 1972 on the All India scale had seasonal rainfall deficiencies of more than −26% below the mean (Sikka, 1999). On a subdivisional scale, according to Ray and Shewale (2001), the frequency of droughts seems to be high over western and central India and the northern peninsula (Ray & Shewale, 2001). The team of Mooley and Parthasarathy (1983) concluded that moderate to strong El Nino occurrences are the root cause (Mooley & Parthasarathy, 1983). Reddy (2008) estimated that the impeded southwest monsoon rain or the midway retreating of it or unexpected interval is the general phenomenon in India, which is also supposed to be correlated with the above episode. He also illustrated his findings in a chart (Fig. 3.1) (Reddy, 2008): The National Academy of Agricultural Sciences (2011) has distinguished 13 states in India with about 185 districts (1173 developmental blocks) as water-stressed areas (NAAS, 2011). Drought-prone areas can also be identified based on moisture index as shown in the next

46  Chapter 3

Figure 3.1: Probable abnormal monsoon conditions in India. Reddy (2008).

equation and the table given, which can be further extrapolated through the equation. Here, P and PET represent the annual precipitation and the potential evapotranspiration, respectively (Thornthwaite & Mather, 1955). Moisture Index =

( P − PET ) PET

As shown in Table 3.2, Khanna and Khanna (2011) has also identified the percent drought prone areas of India in accordance with climatic zone and moisture index (Khanna & Khanna, 2011). Nevertheless, the rise in surface temperature due to climate change is likely to boost monsoon depressions over India, which will increase the frequency of extreme rainfall events. Past studies have reported that the atmospheric moisture content in India has magnified due to intensification in surface warming, induced by climate change. The phenomenon can be well explained by the fact that the increase in moisture increases the water holding capacity of the air, as warmer air can accommodate additional moisture and hence likely to intensify the monsoon depressions. As described in Section 2.2, the atmosphere becomes warmer Table 3.2: Identification of drought prone areas (Khanna & Khanna, 2011). Moisture index

Climatic zone

Percent area of India

< −66.7 −66.7 to −33.3 −33.2 to 0 0 to +20 +20.1 to +99.9 > +100

Arid Semi-arid Dry subhumid Moist subhumid Humid Per-humid

19.6 34.0 21.1 10.2 7.8 8.3

Water-related problem with special reference to global climate change in India  47 due to cloud heating. When the clouds condense over the atmosphere, they release heat. As the heat aggravates, it creates a low pressure against the high-pressured bottom layer, hence resulting to a gradient. Ultimately, the vertical motion becomes stronger with amplification of the storm, and also sustains depression in a more intense way. According to a recent study, India has been reported to have faced 649 disasters from 1915 to 2015. Out of these 649 events 302 disasters were caused by floods with on an average of three floods per year (http://www.scind.org/1294/Environment/will-climate-change-lead-to-more-rainfall-andextreme-floods-in-india.html). The Indian Institute of Tropical Meteorology study based on rainfall data collected since 1900 reported that the intensity of the monsoon rain has been increasing and one of the factors is global warming (Government of India, inpress14).  Prof. Vimal Mishra, IIT Gandhinagar, published a study on the most recent and deadliest Kerala flood that defied the normal monsoon rain. The study concluded that four factors—above normal rainfall, extreme rainfall events, more than 90% reservoir storage before the rains, and unprecedented extreme rainfall in catchment areas contributed to the flooding witnessed in Kerala. On an average, Kerala receives around 3000 mm of rain annually. Of this, the monsoon is responsible for slightly more than 2000 mm. But on August 19, 2018, the state had already received 2350 mm of rainfall despite the fact that around a third of the monsoon season is yet to come. According to the Indian Meteorological Department, Kerala received 2346.6 mm of rainfall against a normal of 1649.5 mm since the beginning of June—an excess of 42% (Rainfall over Kerala, 2018). Hence, many have reported a decline in monsoon rainfall since the 1950s, at the same time the frequency and intensity of heavy rainfall events have also increased. It can be fairly understood from the research that an abrupt change in the monsoon could precipitate a major crisis, triggering more frequent droughts as well as greater flooding in large parts of India.

3.3  Impact on agricultural economy With the great diversity in geology and structure of the country, India also possesses greater varieties and differences in climate. One can find extreme cold with seasonal snowfall on its top, a desert in its north, unending sea and ocean in the downward curve, the hottest region in the center, and arid to extremely humid regions distributed unevenly. Besides, drought-prone areas to flood-prone areas are also divided clearly from region to region. Hence, the prevailing climatic conditions in a particular zone tend to govern the circulation of water resources in the country. Accordingly, the fauna and flora are also regulated and as a result the climatic factor assumes great importance in determining the economic performance and social progress of the Indian subcontinent. The Indian agriculture sector, with a contribution of 18% to the India’s gross domestic product (GDP), is the most important component in the country’s economy. It also accounts for 50% of the country’s employment (Ministry of External Affairs, 2015). However, 31.4% of the cultivated land depends on irrigation and 60% depends on the rain, thereby making it

48  Chapter 3 vulnerable to any changes in monsoon patterns due to climate change. As per the observation of the current scenario, India is likely to increase its water demand significantly for irrigation by 2025 (Madhusudhan, 2015). It can be known from discussions in the earlier sections that the southwest monsoon season of India accounts for 75% of the rainfall and that in recent years, drought and flood have become very common, with the greatest impact on economy and agriculture. Therefore, it can be deduced that the economic sustainability of India through agriculture is intrinsically interlinked to the global, or more specifically, to climate change. This change in natural pattern cannot be ignored based on the fact that it has also paid off significantly by reducing the productivity of rice and wheat in the Indo-Gangetic Plains. The increase in temperature by 2°C–2.5°C from the preindustrial era have contradictorily diminished the water availability at various important river basins of the Indus, Ganges, and Brahmaputra. Moreover, with no signal of halting the change, many experts and scientists have predicted a further worsening alteration on the precipitation pattern and atmospheric temperature, thereby augmenting more regional water shortages. Along with it, the food adequacy of some 63 million people is also anticipated to be hampered by 2050s (Aggarwal, Joshi, Ingram, & Gupta, 2004). Here, it can be recalled that the infamous Indian drought that occurred in 2016 brought an overall economic loss of $100 billion, affecting 330 million people across 10 states (ASSOCHAM, 2016). Not only the economic loss, but the country also recorded the highest number of deaths with 2119 fatalities and also property damage of more than $21 billion, which is calculated to be almost 1% of India’s GDP. The poverty rate is bound to increase with increased climatic temperatures, with people in poverty who depend on rain-based agriculture being affected the most. In general, the crop production is expected to narrow down by 12% with every increment of 2°C. The International Monetary Fund has concluded that El-Nino is the main source for the possibility of this temperature increment (https://www.indiawaterportal. org/articles/climate-change-and-its-impact-water-resources). Selvaraju (2003) has also clearly reported the association of Indian food grain production with ENSO (Selvaraju, 2003). According to a study conducted during the period 1970–2015, it was observed that the farmers’ earning would be reduced by 15% for kharif season and 7% for rabi season and that was when the rainfall level shrinks below mean average by 100 mm. It also reported that the annual agricultural income is in jeopardy of climate change. The income is likely to be decreased by 15%–18% on average. However, for the nonirrigated regions, it can shoot up to 20%–25%. Some of the well-irrigated regions of India are the Indo-Gangetic plain, parts of Gujarat and Madhya Pradesh. However, part of regions like Karnataka, Maharashtra, MP, Rajasthan, Chhattisgarh, and Jharkhand not well irrigated, hence making them vulnerable to climate change (https://www.eea.europa.eu/themes/climate/policy-context). Apart from this abnormal rainfall pattern, other factors like hailstorms also have the potential to bring damages. Not only the personal property, but severe hailstorm cases have the record of destroying standing crops at large. Hence, it is clear that there is an inevitable link that revolves in between the Indian monsoon season and the dependant agricultural sector to the

Water-related problem with special reference to global climate change in India  49 regional and global climate system. Therefore, with that, the Indian economy is also very vulnerable to the changes in climatic conditions both at regional and global scales.

3.4  Indian context on climate change and water policies The United Nations Framework Convention on Climate Change (UNFCCC) is the governing body to handle the issue of climate change at a global scale. Based on its objective “to stabilize atmospheric greenhouse gas concentrations at a level that would prevent dangerous anthropogenic interference with the climate system,” various global policies have been successfully framed to fight the harmful effects of climate change on our environment (Amarasinghe et al., 2005). In India, climate change policies cannot be framed without making water the forefront issue. One big reason is the consequent hydrometeorological impacts across the country, resulting in many challenging situations of water shortage in all sectors, including the termination of the river basin (Gosain, Rao, & Arora, 2011). However, the water sector has not been given enough priority in relation to climate change, as much as has been given to the energy domain. It is high time to understand that water stress is an undeniable issue prevailing in the entire region of the Indian Subcontinent. Besides, the important southern city of India, Bangalore, has touched the extreme situation of drinking water shortage that it has been listed as just next to Cape Town of South Africa in battling the condition. Not only for Bangalore, but the World Bank has warnings for almost all the states of India. Even after that, no special legislation has been solely designed to handle climate change and its impacts in this country (Iyer, 2013). Going back in history (1830s–1940s) the British way of maintaining hydraulic missions was to build dams and canals for irrigation and large-scale reservoirs to store water. They had given basic priorities on increasing food production through canal irrigation and providing enough drinking water requirements and also to expand urban centers and industries. Since then, the Ministry of Water Resources and Irrigation Departments, India, hasn’t made strong decisions on changing the course to cross beyond these large-scale infrastructure-based supply approaches to water management. So far, no significant reformation on changing the existing policies, legal acts, and projects from the historical approach can be seen (Mollinga, 2005; Wester, 2008). However, in 1974, the parliament passed the Water Prevention and Control of Pollution Act. This is the closest and most proper legislation for tackling the climate-related issue with water. It was followed by the Air Prevention and Control of Pollution Act, 1981, enacted under the Article 253 of the Constitution. The two acts have similar provisions, however, though close to the issue, in both the cases the term Climate Change was not given the required priority. To fill the gaps, the parliament enacted another core legal regime called the Environment (Protection) Act in 1986, with the purpose of providing protection and improvement to the environment (http://eprints.lancs.ac.uk/125076/1/CLIMATE_CHANGE_ AND_ITS_IMPACT_ON_INDIA_A_COMMENT.pdf). Nevertheless, a competent authority to handle specific judicial questions on climate-related claims wasn’t strongly formed. Therefore, in 2008, India finally launched the National Action Plan on Climate Change (NAPCC). It aims

50  Chapter 3 to reduce actions that can bring alteration in climatic conditions, and set strategies to guide the nation on its possible drastic impacts, ways to overcome and to ensure the availability of healthy water. Unlike other plans, this one clearly mentions a prioritized concern about climate change scenarios and their consequent water scarcity issues. Among its eight national missions being framed, water and climate change are given mandatory importance. As a whole new approach, this policy covers global warming issues, sustainable development, economic advances, and environmental management. The NAPCC has shown the rationality on the water scarcity controversy caused by the changing climate scenario by forming a new national water policy separately under it. The “Water Mission” with an objective of 20% advancement in coherent water use, also takes into account the need to attenuate and customize the water stress scenarios that may arise out of climate change. It also focuses on creating databases and assessing the relation between the two, encourages the public and the states on water conservation, augmentation, and preservation, with greater emphasis given on overexploited areas. Last, it promotes proper management of basin level integrated water resources (Government of India, 2008; Matthew, 2018). The mission also supports implementation of advanced techniques like seawater desalination for coastal regions, rainwater harvesting, water recycling, etc. Along with the establishment of well-designed management systems, an urgent necessity to elevate more water storage unit is also mentioned. Some of the progress initiated by the National Water Mission, under the Ministry of National Water Resources is shown in Table 3.3. Table 3.3: National Water Mission (NWM) policy development timeline and other related government initiatives. Date

Government activity

June 2007 July 2008 July 2008 December 2008 March 2009 April 2009 October 2010 April 2011 October 2012 2010–2013 October 2013 July 2014 February, 2015 August 2015 July 2015 October 2015 May 2016 2016–2017 October 2017

Prime Minister’s Advisory Council on Climate Change (PMACCC) launched National Action Plan on Climate Change launched PMACCC charge the Ministry of Water Resources (MWR) to develop NWM First draft of NWM published MWR convene first workshop to discuss NWM State governments asked to develop State Action Plan for Climate Change (SAPCC) MWR convene second workshop to discuss NWM NWM approved by the PMACCC National Water Policy updated and published State governments prepare SAPCC National Bureau of Water Use Efficiency proposed Neeranshal National Watershed Programme launched MWR advise state government to develop State Specific Action Plans on Water (SSAP-Water) National Adaptation Fund on Climate Change (NAFCC) established. Pradhan Mantri Kishi Sinchal Yojana mission launched India Intended Nationally Determined Contribution submitted to UNFCCC Draft National water Framework Bill published for consultation State governments submit project funding requests to NAFCC MWR convene workshop to discuss SSAP-Water with state governments

Source: Matthew (2018).

Water-related problem with special reference to global climate change in India  51 On January 6, 2010, India took certain initiatives to fight climate change under the guidance of the Ministry of Environment and Forest, Government of India. The 24 initiatives covered the following areas: Science and Research, Policy Development, Policy Implementation, International Co-operation and Forestry. Some of the initiatives under these heads that are worth mentioning are: Indian Network for Climate Change Assessment (INCCA) where a network of 120 research institutions and 250 scientists launched; major conferences were planned in May and November 2010. Under the Himalayan Glaciers Monitoring Programme, comprehensive plans to scientifically monitor the Himalayan glaciers, Phase I was completed, Phase II launched, and a discussion paper on the state of Himalayan glaciers was also released. State Action Plans on Climate Change under Policy Development steered Delhi to become the first state to release a climate change action plan. As follow ups, other states are also finalizing their plans (Recent Initiatives Related, 2010). In India, unlike the governmental bodies such as the Ministry of Water Resources, state irrigation departments, the nongovernmental societies emphasize more on a small-scale level. When government firms anchored on top-down approaches with comprehensive infrastructurebased propositions like building of dams, reservoirs, canal irrigations, urban and rural drinking water facilities, the nongovernmental group focused more on the opposite issues. However, even though the NGOs are operated at the private sector level, most of the funding and technical aids are provided by the government; for example, the Pani Panchayats, a registered society of farmers related to irrigation and groundwater recharge design (Wester, 2008). Despite all these undertakings, on overall accountability India seems to be still lacking strong policies to overcome the issues. A robust system is still expected in a diverse country like India where sustainable goals based on social, environmental, and economical policies are put in the front.

3.5  Scientific simulation model for future prediction Even though no stringent legal act has been framed in India, one way to combat or take precautions and give awareness to the public is through research and prediction based on the available records. This can be done by generating the weather information from documented data. Here, stochastic weather data generators come to the rescue helping in reproducing missing weather data and also to constrict the statistical values from bigger regions to localized climatic conditions. This methodology can also help in risk assessment for domains like hydrology, ecosystem management, and the environment at large. Besides, by the implementation of various computational models, the consequent abnormal weather events as a result of climate variation were also successfully simulated. Scientists have already worked on various hypotheses and reports on various interpretations of the complex systems of the Earth and climate have been determined. One such application is the prediction of tropical cyclones off the coast of India using climate models.

52  Chapter 3 Data generation has made drastic advancement. Likewise, advanced technologies have made it possible to extract climate-related data from unusual sources like cores of ice, trees, and coral. Some of the important statistics that can be obtained through the techniques are historic activities of humans, temperature alteration in oceans, extreme drought events, and much more. The more data, the more there is accuracy in establishing a typical baseline of a climate model and hence, enhancing in event forecast. By establishing these variables, researchers can calculate anything from sea level rise to increased temperatures and risk of drought and forest fires. In the present context, to build up a relationship model between climate change and its impact like major future floods, simulation on hydrological computations will help. In the next section some of the models are explained briefly, considering attributes like assessing future flood impact, checking the interaction between climate change and water, extraction of historic data, downscaling, parameterization, and event prediction (Cloke, Wetterhall, He, Freer, & Pappenberger, 2012).

3.5.1  The Soil and Water Assessment Tool (SWAT) modeling SWAT is a comparatively small-scale model that limits the size of a small watershed or river basin. It can simulate the quality and quantity of surface- and groundwater, and can deliver high-quality spatial description by dividing watershed into numerous subwatersheds. The major parameters for computation include weather, hydrology, soil temperature, plant growth, nutrients, pesticides, and land management (Saleh et al., 2000). By assuming a constant land use pattern, SWAT hydrological modeling can estimate the prevailing interaction between water resources and climate change impact. Similarly, by neglecting the construction of developmental structure like dams, the amount of water available at a given time and space can be simulated. The probable hydrological budget under the influence of climate change can be estimated by feeding future climate inputs. Likewise, water yield as a consequence of climate change can also be computed using present climate scenarios. Apart from applying readily available data, a few more advantages of selecting SWAT model are easy to operate, totally physical dependent and can also generate the changes in management. It is a distributed parameter and continuous time simulation model. Besides, complex calibration is not needed as compared to other conventional conceptual simulation models. Hence, it can also be applied in the normal ungauged watersheds. However, some of the static units that are required for this modeling are information on terrain, soil profile, and land use of the basin area along with weather factors from the present and future. As for the meteorological input, the necessary entities are daily precipitation, maximum/minimum air temperature, solar radiation, wind speed, and relative humidity. All these inputs can be easily procured from the global sources (Gosain et al., 2011; Jatin, Gosaina, Khosaa, & Srinivasanb, 2018).

3.5.2  General Circulation Model or Global Climate Model (GCM) GCM is a mathematical model that calculates the planetary atmospheric movement or oceanic course or linkage between the two. It analyzes the representative fundamental parameters

Water-related problem with special reference to global climate change in India  53 of a hydro-climate interactive study at multiple spatial and temporal resolutions. Important hydrological units that establish the water resources characteristics of a region and that are also accounted for by GCM simulation are runoff, soil moisture, and evapotranspiration. Likewise, precipitation and temperature are two undeniable parameters for climatic domain, and GCM works for it by applying a three-dimensional grid over the globe. The atmospheric and oceanic realms to be studied should have 10–20 vertical layers and 30 layers, respectively. Besides, the horizontal resolution should be in between 250 and 600 km. GCM considers various natural statistics like water vapor and warming, clouds and radiation, ocean circulation and ice and snow albedo, to estimate feedback mechanisms (IPCC-TGCIA, 2007). In order to simulate the Earth’s atmosphere or oceans and to forecast climatic change or to understand the weather conditions, basic equations such as Navier– Stokes are applied. Here, thermodynamic figures for various energy sources like radiation and latent heat are used as inputs for basic programming of a rotating sphere. As a unique approach, it segregates atmospheric and oceanic grids into cells and harmonizes it with the equations for fluid motion and energy transfer over time. GCMs, in coordination with other models, can explore the observed and predicted dynamics of climate change and its impacts on the water resources. Its combination with Regional Climate Modeling (RCM, explained in the next section) can predict various emission scenarios that lead to climate change. This combination again collaborates with Land Surface model (LSM) and can assess hydrologic variables (Madhusoodhanan et al., 2016). Another combination that can enhance the computation is atmosphere-ocean coupled general circulation model (AOGCM). It is an integration of atmospheric and oceanic GCMs (AGCM and OGCM). It encompasses various key components of atmosphere, sea surface temperature, and land surface parameters. A full climate model is cooked up with the inclusion of submodels like evapotranspiration over land, and all the different domains (land, air and ocean) are treated as different entities (Guangqing et al., 2016).

3.5.3  Regional Climate Modeling (RCM) RCMs provide sufficient information for the hydrological modeling of impact of expected climate change on the river runoff. The motivation behind RCMs is the concept of “downscaling,” refining the data regardless of its resolution. Its purpose is to obtain regional or local detail from either sparse observations or low-resolution numerical simulations. Regional models are sometimes called comprehensive, consistent, and physically based interpolator or, in more popular terms, a magnifying glass. The two main downscaling methods are known as statistical and dynamical downscaling. The former involves finding robust statistical relationships between large-scale climate variables (e.g. the mean sea level pressure field) and local ones (such as temperature or precipitation). Some of the important applications of RCMs are seasonal forecasting, end-to-end model systems combining regional climate and impact modeling systems, test-benches for

54  Chapter 3 developing process parameterizations for global models, studies of the far past, specific process studies such as the influence of snow cover on the atmosphere, and regional reanalyses. As mentioned, regional models are also used for short-range weather forecasting. In return, impact studies that make use of RCM results provide means of model evaluation, in an integrated sense. An example is river run-off that is affected by precipitation, snow, temperature (via evapotranspiration), and soil moisture. In the interdisciplinary setting, the context of RCMs is, however, how they enable impact studies and otherwise provide useful information, not least on climate change. The primary assumption in regional modeling is that data on the climate large-scale information is used to propel an RCM over a limited area. Such a regional domain, as compared to a global one, allows for high resolution without a prohibitive increase in computational cost. Driving data are supplied to the regional model as lateral (and often also sea surface) boundary conditions. The basic set of boundary conditions contains temperature, moisture, and circulation (winds), as well as sea-surface temperature and sea ice. An accurate treatment of boundary conditions is a central issue in regional modeling (Yuqing et al., 2004).

3.5.4 ClimGen In ClimGen, hydrological modeling is performed using weather inputs like evaporation, infiltration, and runoff, and generates globally consistent climate scenarios. It can analyze the hydrological dynamics of climate change in varied scales of global, regional, or catchment. However, this model accounts for a prescribed level of global warming along with specific greenhouse gas emission. In this type of simulation, at a given mean temperature change, spatial climate change data, for instance, geographical, seasonal, and multivariable structure, are created through “pattern-scaling” (PS). PS/ClimGen was originally fabricated to forecast transient climate from GCM’s equilibrium feedback to CO2 doubling, but it has also been helping successfully in assessing the probable variability that may arise in the process. In the case of AOGCM, the normalized patterns of climate change show considerable variation between different simulations, and ClimGen is principally designed to explore this variation. Another advantage of ClimGen is that it has also the option to anticipate storm events or rain fall break point by cleaving intervals in the daily precipitation. The segregated interval is supposed to be 30 minutes on average, and this has been successfully done by ClimGen. It can generate breakpoint precipitation for every half an hour, which is considered to be superior in comparison to other models. The credit for this is Weibull distribution processed in it (McKague, Rudra, & Ogilvie, 2003; Timothy, Craig, Ian, & Thomas, 2016). ClimGen can produce persistent weather statistics files that can constitute as recorded historical data for assessing rural water quality. Another advantage over other weather generation tools is that it can also automatically extract old data from weather station. The team has also cited some advantages of using ClimGen over other models. They have

Water-related problem with special reference to global climate change in India  55 mentioned that ClimGen can automatically generate the historical data, regularly from new stations of interest, also, in a format where the simulation software can be read easily. The original ClimGen software, started by Campbell summarizes data on monthly or everyday basis. It tells the usual information on highest and lowest temperatures, precipitation, solar radiation, and vapor pressure. Now, an enhanced version of ClimGen called ClimGen-Up has been developed as new user-friendly Windows software. It has the advantage of the possibility to store the extracted data for a longer period of time. Graphical displays on past and current information are also possible (McKague et al., 2003).

3.5.5  Precipitation Runoff Modelling Systems (PRMS) The PRMS is a computational system that can simulate the combined impact of land use and climate on watershed hydrology. The fundamental parameters that are necessary to operate it in the daily-flow mode are precipitation and the highest and lowest recorded temperatures on an everyday basis. Therefore, it is a standardized process-based modeling that will clearly determine the prevailing interaction between climate and water factors. In the case of simulation involving snowmelt, daily atmospheric temperature data can be substituted by solar radiation values, and if snowmelt is not accounted, then pan-evaporation data can be used. In other cases, descriptive data such as physiography, vegetation, soils, hydrologic characteristic, and climate variation over watershed can be used as inputs. By doing so, both mean daily flows and storm flow hydrographs can be simulated, making it operate as a lumped- or distributed-parameter type model. The output of the simulation can be given on daily, monthly, or yearly modes. It will contain observed and projected values or storm-event or streamflow summaries. Results comprising of major climate and water-balance elements can also be obtained (Leavesley et al., inpress20).

3.6 Conclusion As a developing nation, India is expected to be slammed drastically before other developed nations by the adverse reactions of climate change. Correspondingly, it can be seen that India is making national plans to focus more on the policies that give preferences on utilizing green and renewable energy over environmentally harmful approaches. As per many researchers, almost all the corners of the country are anticipated to be affected by climate change, and with time it is expected to escalate if no significant action is taken. Mention can be made that any further changes in the pattern and intensity of precipitation event will invite inconsistency in management and planning of the country’s water resources. This includes design of hydrological structures, flood and drought management, and urban planning and development. Besides, India’s economy that depends largely on agriculture will definitely be not spared either. The survival and productivity of agriculture being determined by the pattern of monsoon and rainfall intensity, it is also one of the most vulnerable sectors of

56  Chapter 3 climate change. Hence, it is essential for India to be always on alert for the assessment quality of the prevailing parameters by studying the historical statistics and the present climatic scenario. However, existing water resource systems have crucial gaps in many aspects. The water circulation system in terms of information gathering, monitoring, processing, storage, etc., are reported to be inferior in front of the challenges put up by dynamically changing climatic factors. Here, the application of the right mathematical simulation and computational models can come to the rescue. Nevertheless, a complete solution cannot be achieved without the expansion of domestic research inside the country and also without the contribution of nongovernmental organizations. Other initiatives at individual levels are changes in living style and switching to more environmental-friendly approaches. It may include increases in using less–power consuming LED lighting, shifting consumption of petrol and diesel to compressed natural gas as fuel, imposing stringent norms on waste emission by moving vehicles, and usage of renewable sources of energy. The need to consider this side has given rise to a strong need of a national environmental policy with rigid rules based on reducing environmental pollution and following proper waste management right from the domestic level. The country must therefore introduce and encourage the whole nation to participate in monitoring pollutions. Overall, greenhouse gas emissions, which are one of the root causes, must be checked in time constantly to combat climate change and protect threatened water sources. This chapter focuses on the current scenario of climate change and its impact on water; it also evaluates the aggravated distress faced by India on climate change, and more importantly, a solution-based approach has been proposed. However, from the overall assessment, it can be concluded that there is an urgent need to validate stronger legislations, with constructive protocols, keeping the malicious issues of these water and climate change domains in the forefront. As per the research, so far, the ordinances being framed and implemented by the government on this controversy have been faintly comprehended, while enumerating the plight and degree of the fallout sustained by this country. Hence, strong and resilient proclamation from the both the central and state authorities is being suggested as its utmost necessity. In some cases, India can be seen to have complied with several international accords to fight the issues, but most of these provisions seem to be inconsistent with the condition of the country. India requires a modus operandi with strict disciplinary laws. Simultaneously, India needs to build up an environment where all the sections are compelled to abide to a stringent indictable penal code in order to safeguard and deal with climate change, environmental protection, and the impact it has on the people in poverty and the vulnerable. It can be clearly mentioned that, only when the central, state, judiciary, and civil society join hands, the prevailing issues can be dispensed to the root level. However, the successful enactment of a national water policy receptive to the climate challenge will demand a well-accountable knowledge and standard, along with commendable institutional support at the national, regional, and local levels.

Water-related problem with special reference to global climate change in India  57 On the technical side, apart from implementing modern sophisticated methods like desalination processes and waste water recycling, the application of predictive models can also be effective in formulating the preliminary constrains, as well as predicting the potential complication of future changes in hydrological systems due to the climatic factors. Protocols can be made to install methodologies for continuously monitoring data of the prevailing parameters of water domains as a response to changing climatic conditions. Nowadays, realtime recording has also been made possible. Besides, options can be adopted where building of water resources that are resilient to climate change impact are considered, be it in the form of water-saving technologies or low input–high output practices. Another mitigation approach can be the application of water-harvesting processes through construction of microstorage facilities in watersheds. Hence, while contemplating the continuous need for healthy water for unavoidable human activities, it is also necessary to calculate the availability of clean and safe water for future purposes. While doing so, the escalating impacts of climate change should also be kept in the forefront while planning and managing the resources and requirements. Overall, there is an urgent need to maintain a balance between proper management and planning with the application and implementation of modern technologies used for human comfort.

References Aggarwal, P. K., Joshi, P. K., Ingram, J. S., & Gupta, R. K. (2004). Adapting food systems of the Indo-Gangetic plains to global environmental change: Key information needs to improve policy formulation. Environmental Science & Policy, 7, 487–498. Amarasinghe, U. A., Sharma, B. R., Aloysius, N., Scott, C., Smakhtin, V., & De Fraiture, C. (2005). Spatial variation of water supply and demand across river basins of India (IWMI Report 83). Colombo: International Water Management Institute. ASSOCHAM Report. (2016). “Drought situation to cost Rs 6.5 lakh crore to economy.” The Associated Chambers of Commerce & Industry of India. Available from: http://www.assocham.org/newsdetail.php?id=5678 Bao, J., Sherwood, S. C., Alexander, L. V., & Evans, J. P. (2017). Future increases in extreme precipitation exceeds observed scaling rates. Nature Climate Change, 7, 128–132. Climate Change: Impacts, Vulnerabilities and Adaption in Developing Countries, United Nation Framework Convention on Climate Change. https://unfccc.int/resource/docs/publications/impacts.pdf Climate Variability and Its Impacts on Water, Energy and Food Systems in South Asia: Adaptive Water Management Approaches within the Framework of IWRM. Cloke, H. L., Wetterhall, F., He, Y., Freer, J. E., & Pappenberger, F. (2012). Modelling climate impact on floods with ensemble climate projections. Quarterly Journal of the Royal Meteorological Society, 139, 282–297. Gadgil, S., Vinayachandran, P. N., & Francis, P. A. (2003). Droughts of the Indian summer monsoon: Role of clouds over the Indian Ocean. Current Science, 85(12), 1713–1719. Ghosh, S., Das, D., Kao, S. C., & Ganguly, A. R. (2012). Lack of uniform trends but increasing spatial variability in observed Indian rainfall extremes. Nature Climate Change, 2, 86–91. Gosain, A. K., Rao, S., & Arora, A. (2011). Climate change impact assessment of water resources of India. Current Science, 101, 356–371. Government of India. (2008). National action plan on climate change. Prime Ministers Advisory Council on climate change. New Delhi: Ministry of Water Resources, Government of India.

58  Chapter 3 Government of India Earth System Science Organization Ministry of Earth Sciences India Meteorological Department. Goyal, M. K., & Surampalli, R. Y. (2018). Impact of climate change on water resources in India. Journal of Environmental Engineering, 144(7), 04018054. Guangqing, Z., He, Z., Feng, Z., Jiping, X., Feng, X., & Xiaobao, Y. (2016). Studies on High-Resolution Atmospheric and Oceanic General Circulation Models, Springer Science Business Media Singapore. Hasnain, S. I. (1999). Himalayan glaciers – Hydrology and hydrochemistry. New Delhi: Allied Publishers Ltd. IPCC-TGCIA. (2007). General Guidelines on the Use of Scenario Data for Climate Impact and Adaptation Assessment. Version 1, 312, Intergovernmental Panel on Climate Change, 66. Islam, A., Sikka, A. K., Chaudhuri, S. K., & Biswas, P. P. (2015). Climate change impact on water resources: An overview. Journal of Agricultural Physics, 15(9), 7–15. Iyer, R. R. (2013). Viewpoint: The story of a troubled relationship. Water Alternatives, 6(2), 168–176. Jatin, A., Gosaina, A. K., Khosaa, R., & Srinivasanb, R. (2018). Regional scale hydrologic modeling for prediction of water balance, analysis of trends in streamflow and variations in streamflow: The case study of the Ganga River basin. Journal of Hydrology, 16, 32–53. Kendall, M. G. (1975). Rank correlation methods (4th ed.). San Francisco, CA: Charles Griffin. Khaleeq, K. (2005). Water-related crisis feared in 20 years. Dawn: the Internet Edition, 2005. Islamabad, Pakistan: The Dawn Group of Newspapers. Khanna, B. K., &, Khanna, N. (2011). Drought. In Disaster: Strengthening community mitigation and preparedness (pp. 45–53). New Delhi: New India Publication Agency. Kotteswaran, C. S. (2015). Tamil Nadu: Chennai floods cause a loss of Rs 50,000-cr. Deccan Chronicle. Krishnan, R., Sabin, T. P., Vellore, R., Mujumdar, M., Sanjay, J., Goswami, B. N., Hourdin, F., Dufresne, J. L., & Terray, P. (2016). Deciphering the desiccation trend of the South Asian monsoon hydroclimate in a warming world. Climate Dynamics, 47, 1007–1027. Kumar, C. P. (2012). Climate change and its impact on groundwater resources. International Journal of Engineering and Science, 1, 43–60. Kumar, A., Dudhia, J., Rotunno, R., Niyogi, D., & Mohanty, U. C. (2008). Analysis of the 26 July 2005 heavy rain event over Mumbai. India Using the Weather Research and Forecasting (WRF) Model, 134, 1897–1910. Leavesley, G. H., Lichty, R.W., Troutman, B.M., & Saindon, L.G. Precipitation-Runoff modeling system: User’s manual, Water-Resources Investigations Report 83-4238. Lenderink, G., & Meijgaard, E. V. (2010). Linking increases in hourly precipitation extremes to atmospheric temperature and moisture changes. Environmental Research Letters, 5(9). Loo, Y. Y., Billa, L., & Singh, A. (2015). Effect of climate change on seasonal monsoon in Asia and its impact on the variability of monsoon rainfall in Southeast Asia. Geoscience Frontiers, 6, 817. Madhusoodhanan, C. G., Sreeja, K. G., & Eldho, T. I. (2016). Climate change impact assessments on the water resources of India under extensive human interventions. Ambio, 45, 725–741. Madhusudhan, L. (2015). Agriculture role on Indian economy. Business and Economics Journal, 6, 4. Mall, R. K., Gupta, A., Singh, R., Singh, R. S., & Rathore, L. S. (2006). Water resources and climate change: An Indian perspective. Current Science, 90(12). Mall, R. K., Bhatla, R., & Pandey, S. N. (2007). Water resources in India and impact of climate change. Jalvigyan Sameeksha, 22, 157–176. Mann, H. B. (1945). Nonparametric tests against trend. Econometrica, 13(13), 245. Matthew, I. E. (2018). India’s water policy response to climate change. Water International, 43(4), 512–530. McKague, K., Rudra, R., & Ogilvie, J. (2003). ClimGen: A convenient weather generation tool for Canadian climate stations, The Canadian Society for Engineering in Agriculture. Food and Biological System, 03–118. Min, S. K., Zhang, X., Zwiers, F. W., & Hegerl, G. C. (2011). Human contribution to more intense precipitation extremes. Nature, 470, 378–381. Ministry of External Affairs. (2015). India in Business. Investment and Technology Promotion Division, Govt. of India. Mollinga, P. P. (2005). The water resources policy process in India: Centralisation, polarisation and new demands on governance. Centre for Development Research Department of Political and Cultural Change (ZEF Working Paper 7). Bonn, Germany: University of Bonn.

Water-related problem with special reference to global climate change in India  59 Mooley, D. A., & Parthasarathy, B. (1983). Indian Summer Monsoon and El Nino. PAGEOPH, 121(2), 339–352. Mukherjee, S., Aadhar, S., Stone, D., & Mishra, V. (2018). Increase in extreme precipitation events under anthropogenic warming in India. Weather and Climate Extremes, 20, 45–53. Mukherji, A., Shah, T., Giordano, M. (2012). Managing energy irrigation nexus in India: A typology of state interventions. In IWMI Tata Water Policy Research Highlight. Gujarat: IWMI-Tata Water Policy Programme. NAAS. (2011). Drought Preparedness and Mitigation, Policy Paper No. 50 (p. 22). New Delhi: National Academy of Agricultural Sciences. Prakash, S., Sathiyamoorthy, V., Mahesh, C., & Gairola, R. (2014). An evaluation of high-resolution multisatellite rainfall products over the Indian monsoon region. International Journal of Remote Sensing, 35, 3018–3035. Rainfall over Kerala during Monsoon Season-2018 and forecast for next 5 days, 19th August, 2018. Available from: https://www.imdtvm.gov.in/images/rainfall%20over%20kerala%20during%20monsoon%20 season-2018%20and%20forecast%20for%20next%205%20days.pdf Rapidly Assessing Flood Damage in Uttarakhand, India. (2014). World Bank. Available from: http://www. worldbank.org/en/results/2014/07/29/rapidly-assessing-flood-damageuttarakhand-india Ray, K. C. S., & Shewale, M. P. (2001). Probability of occurrence of drought in various subdivisions of India. Mausam, 52(3), 541–546. 24 Recent Initiatives Related to Climate Change. (6th January, 2010). India: Taking on climate change. Ministry of Environment & Forests, Government of India. Reddy, S. R. (2008). Principles of crop production. Ludhiana: Kalyani Publishers 793. Rizvi, M. (2005). Forecasting water flows in Pakistan’s indus river, 2001. Ottawa, Canada: International Development Research Council. Saith, N., & Slingo, J. (2006). The role of the Midden-Julian Oscillation in the El Nino and Indian drought of 2002. International Journal of Climatology, 26, 1361–1378. Saleh, A., Arnold, J. G., Gassman, P. W., Hauck, L. W., Rosenthal, W. D., Williams, J. R., & Mc Farland, A. M. S. (2000). Application of SWAT for the upper North Bosque River watershed. Transactions of the ASAE, 43(5), 1077–1087. Saltwater intrusion and climate change, A primer for local and provincial decision makers, Atlantic Climate Adaptation Solutions Association. Selvaraju, R. (2003). Impact of El Nino-Southern Oscillation on Indian foodgrain production. International Journal Climatology, 23, 187–206. Sharma, B. R., & Sharma, D. (2008). Impact of Climate Change on Water Resources and Glacier Melt and Potential Adaptations for Indian Agriculture, Keynote Address at 33rd Indian Agricultural Universities Association Vice Chancellors’ Annual Convention on “Climate Change and its Effect on Agriculture”, December 4-5, 2008; Anand Agricultural University, Anand (Gujarat), India (Convention Proceedings Page 86–101, IAUA, NASC Complex, Pusa, New Delhi, India). Sikka, D. R. (1999). Monsoon droughts, Joint COLA/CARE Tech. Rep. No. 2, 269. Suhag, R. (February, 2016). Overview of groundwater in India. Taenzler, D., Ruettinger, L., Ziegenhagen, K., & Murthy, G. (2011). Academy of Gandhian Studies Water, Crisis and Climate Change in India: A Policy Brief, IfP-EW Cluster: Climate Change and Conflict, October 2011. The Hindu. (July 19, 2016). Thornthwaite, C. W., & Mather, J. R. (1955). The water balance. In Climatology, Vol. 8 (p. 1). Centerton, NJ: Drexel Institute of Technology, Laboratory of Climatology. Timothy, J. O., Craig, J. W., Ian, C. H., & Thomas, M. M. (2016). Pattern scaling using ClimGen: monthlyresolution future climate scenarios including changes in the variability of precipitation. Climatic Change, 134, 353–369. Trenberth, K. (2005). The impact of climate change and variability on heavy precipitation, floods, and droughts. In M. G. Anderson (Ed.), Encyclopedia of hydrological sciences. New Jersey: John Wiley & Sons, Ltd. Trenberth, K. E., Dai, A., Rasmussen, R. M., & Parsons, D. B. (2003). The changing character of precipitation. Bulletin of the American Meteorological Society, 84, 1205–1217. United Nations Framework Convention on Climate Change 1992, part 1. Vittal, H., Ghosh, S., Karmakar, S., Pathak, A., & Murtugudde, R. (2016). Lack of dependence of Indian summer monsoon rainfall extremes on temperature: an observational evidence. Scientific Reports, 6, 31039.

60  Chapter 3 Wester, P. (2008). Shedding the waters: Institutional change and water control in the Lerma-Chapala Basin, Mexico. PhD dissertation. Wageningen: Wageningen University. Willett, K. M., Gillett, N. P., Jones, P. D., & Thorne, P. W. (2012). Attribution of observed surface humidity changes to human influence. Nature, 449, 710–712. WWF. (2005). An Overview of Glaciers, Glacier Retreat and Subsequent Impacts in Nepal, India and China. Kathmandu, Nepal: WWF Nepal Program. WWF. (2007). World’s top 10 rivers at risk. Gland, Switzerland: WWF International. Yang, Z. (1991). China’s Glacier Water Resources (in Chinese). Lanzhou, China: Gansu S&T Press. Yuqing, W., Ruby, L. L., John, L. M., Dong-Kyou, L., Wei-Chyung, W., Yihui, D., & Fujio, K. (2004). Regional climate modeling: Progress, challenges, and prospects. Journal of Meteorological Society of Japan, 82(6).

CHAPTE R 4

Water-related problems with special reference to global climate change in China Changshuo Huang, Jiahui Tao Nanjing Hydraulic Research Institute, Nanjing, China

4.1  Global climate change and China’s water resources status 4.1.1  Global climate change and water vulnerability Given the enormous impact of global climate change on human society, the World Meteorological Organization (WMO) and the United Nations Environment Programme (UNEP) jointly formed the Intergovernmental Panel on Climate Change (IPCC) in 1998 (IPCC, 2007). Based on scientific literature, taking changes in global climate as the entry point, and using rules and procedures approved by IPCC plenary sessions as benchmarks, the IPCC brings together scientists from developed countries, developing countries, and countries with transition economies to conduct scientific assessments of the basis for global climate change, as well as its impacts, possible adaptation and mitigation strategies, sensitivities, and vulnerabilities of global climate change, to build upon the United Nations Framework Convention on Climate Change (UNFCCC). The fourth assessment report of IPCC Working Group I, Climate Change 2007: The Physical Science Basics, states that the surface temperature of the Earth has risen by 0.74°C in the past 100 years. The average linear warming rate over the past 50 years is 0.13°C every ten years, which is almost twice the average increase over nearly 100 years. Global climate conditions have demonstrated significant changes due to this warming. The warming of China’s climate is basically consistent with global trends (Zhang & Wang, 2008). The IPCC technical report Climate Change and Water states that observational records and climate projections provide ample evidence that water resources are vulnerable and may be strongly influenced by climate change, bringing a wide range of consequences to human society and ecosystems. However, to date water resources issues have not been fully considered in climate change analysis and climate policy development. Similarly, in most cases climate change issues, water resources management, and policy development have not been fully addressed. Water and available water resources will be the main pressures

Water Conservation and Wastewater Treatment in BRICS Nations http://dx.doi.org/10.1016/B978-0-12-818339-7.00004-7

61

Copyright © 2020 Elsevier Inc. All rights reserved.

62  Chapter 4 faced by societies and by the environment under climate change, and will bring a series of problems to these societies and the environment.

4.1.2  The status of China’s water resources China is located on the east coast of the Eurasian continent, with the Pacific Ocean located to the southeast and the hinterland of the country in the northwest. It is located at 73°–135° east longitude and 4°–53° north latitude. The land area of the country is 9.6 million km2 and accounts for 1/15 of the total land area of the world. It is second in size only to Russia and Canada. The terrain of China is high in the west and low in the east. It is distributed in a step-like manner, with a large area of mountains and plateaus. The distance between east and west is about 5000 km, and the coastline of the mainland is about 18,000 km long. The temperature difference between different places is large, forming a variety of climates. The main rivers are the Yangtze River, the Yellow River, the Heilongjiang River, the Pearl River, the Huaihe River, the Haihe River, and the Liaohe River. The current status of China’s water resources can be summarized in four points: 1. The total amount of water resources is abundant, but per capita water resources are relatively scarce. China’s water resource situation is characterized by a large number of people with a lack of access to water, a relative scarcity of water resources, and an uneven spatial and temporal distribution of water resources. China is one of the countries with the poorest per capita water resources in the world. The United Nations defines it as a water-stressed country. Although China has the fourth largest amount of water resources in the world, due to its large population per capita water resources are only 2,300 m3, which is only one-fourth of the world’s average per capita water resources. In the western and northern regions of China, per capita water resources are only one-tenth of the world’s average per capita water resources. Among more than 660 cities across the country, more than 400 have water shortages. 2. The spatial and temporal distribution of water resources is uneven, and the total amount of water resources is decreasing year by year. China’s spatial and temporal distribution of water resources is mainly characterized by less in the south and more in the north, less in the east and more in the west, less in the mountains and more in the plains, and more in the summer and autumn than in the winter and spring. The uneven distribution of water resources in China has caused a high frequency of flood disasters in southern China, many droughts in the north, many floods in summer and autumn, and many droughts in winter and spring, resulting in an increase in infrequent rainfall, strong typhoons, and heavy drought. Using the Yellow River as an example (Fig. 4.1), the average annual precipitation in the Yellow River basin since the 1950s has been 455.5 mm, and

Water-related problems with special reference to global climate change in China  63

Figure 4.1: Characteristics of average precipitation and natural runoff in the Yellow River basin.

precipitation in each year has shown a decreasing trend year by year. The average annual runoff of the Yellow River basin during the flood season is 571.5 m3, which is also decreasing year by year. Based on the changes in average annual precipitation and runoff in the Yellow River basin, analysis shows that since the year 2000 the Yellow River basin has been affected by precipitation changes and the amount of incoming water has decreased. This will lead directly to a reduction in water resources availability. There are many rivers in China and more than 1500 rivers with a drainage area of more than 1000 km2. Affected by topography and climate, most of China’s rivers are distributed in the humid and rainy monsoon region of the east (Zhang & Zhang 2007). Table 4.1 shows that of the seven major rivers, the Yellow River, the Huaihe River, Haihe River, and Liaohe River basins have smaller water volumes and the Yangtze, Pearl, and Songhua River basins have larger water volumes, and that water in the arid regions of the northwestern China is scarce and water in the southwestern mountains is abundant.

Table 4.1: Characteristics of area, annual precipitation, and annual runoff of major river basins in China. Drainage basin

Yangtze

YellowHuaihe-Haihe Songliao

Southwestern Pearl, southrivers eastern rivers

Drainage area, 104 km2 Annual precipitation, mm Annual runoff, 108 m3

180 1070 9513

144 575 1691

85 1098 5853

124.8 510 1653

68 1600 5895

64  Chapter 4 3. The conflict between water supply and demand is increasingly pronounced. There is growing evidence that China is facing an increasingly serious water shortage problem. The main cause of water shortages is the reduction in water supply and the increase in water demand. The reduction in water supply is mainly due to the lack of precipitation. Between the 1980s and the 1990s the average precipitation in North China decreased 10%–15% over 10 years. After the 1990s the annual average precipitation reduction range broadened from North China to the Yellow River basin, the Liaohe River basin, the Huaihe River basin, and the Sichuan Basin in the southwest. Under conditions of a reduced or tight supply of water, the demand for water is increasing. With the continuous development of the economy and society, China’s water demand is increasing. Although the water supply increased from 443.7 billion m3 in the 1980s to 609 billion m3 in 2017, there is still a shortage of water. At present, the total water shortage in the country is about 60 billion m3. China’s population is expected to reach 1.6 billion in 2030. By then, per capita water resources will be only 1750 m3. China will become a country with severe water shortages, and the conflict between water supply and demand will become more pronounced. 4. Water use efficiency is low and infrastructure is limited. For a long time China’s water resources utilization efficiency has been low and the ways in which water is utilized relatively extensive. In terms of water use efficiency and infrastructure, there is a big gap between China and developed countries. For example, in agricultural irrigation the coefficient of effective utilization of farmland irrigation water is 0.4–0.5 while that of developed countries is 0.7–0.8; the industrial added value per 10,000 yuan of water consumption is about 50 m3 while that of developed countries is only 7–9 m3; the industrial water recycling rate is less than 50% while in developed countries it is 85%; and the leakage rate of city water-supply pipelines exceeds 15% while it is less than 10% in developed countries. About 70% of China’s water is used for agriculture; irrigated areas account for 40% of cultivated land, and the level of water use for agricultural irrigation is high but very inefficient. The demand for groundwater in rural areas far exceeds the water resupply rate. Given the increasing conflict between water supply and demand, and severe water problems brought about by climate change, it is urgent to strengthen water resources management, improve water use efficiency and infrastructure, and build a water-saving society.

4.1.3  The research history of the impact of climate change on hydrology and water resources International research development history. International studies on the effects of climate change began in the late 1970s, but research on the effects of climate change on water cycles and water resources became highly valued after the mid-1980s. Over the course of this

Water-related problems with special reference to global climate change in China  65 Table 4.2: Major international conferences on the impact of climate change on hydrology and water resources. Development stage

Date(s)

Late 1970s

Beginning stages

1977

After the mid1980s

Society 1985 attaches great importance 1987 1987

1988 1990–2007

2009 2012 2015 2018

Sponsoring organization or meeting

Outcome

WMO, ICSU, UNEP, Research projects such as the World IAHS Climate Research Programme (WCRP) and Global Energy and Water Cycle Exchanges (GEWEX) USNRC Seminar on the relationship between climate change and water supply and its impact WMO Summary report on the impact of climate change on hydrology and water resources Sensitivity analysis report of hydrology and water resources to climate change 19th IUGG “The Impact of Climate Change and Climate Fluctuation on Hydrology and Water Resources” (seminar) WMO and UNEP Jointly set up IPCC IPCC Completed four assessment reports to analyze the impact of climate change on hydrology and water resources 5th World Water Focused on the impact of global climate Forum change and its countermeasures 6th World Water “Water and Climate Change Forum Adaptation” (high-level round table) 7th World Water “Infrastructure and Climate Change” Forum (topic launch) 8th World Water “Water and Land Management Forum for Climate Change Mitigation” (discussion)

Note: WMO, World Meteorological Organization; ICSU, International Council for Science; UNEP, United Nations Environment Programme; IAHS, International Association of Hydrological Sciences; IUGG, International Union of Geodesy and Geophysics; IPCC, Intergovernmental Panel on Climate Change; IGBP, International Geosphere-Biosphere Programme; USNRC, United States National Research Council.

evolution many scientific research projects have been carried out internationally and relevant international conferences have been held (Table 4.2), which have promoted the development of hydrological and water resources responses based on climate change research. Domestic research development history. The study of the impact of climate change on hydrology and water resources in China began in the 1980s. Since then China has organized various major scientific research projects in the Huang-Huai-Haihe basin, the Yangtze River basin, the Pearl River basin, and the Songhua River basin (Table 4.3) to study the impact of

66  Chapter 4 Table 4.3: Major Chinese initiatives on the impact of climate change on hydrology and water resources. Project classification

Period/date

National Science and Technology Research (National Science and Technology Support Program) Project

Eighth Five-Year “Study on the Impact of Climate Change Plan on Hydrology and Water Resources and Adaptation Strategies” Ninth Five-Year “Evaluation Model of Impacts of Climate Plan Abnormality on Water Resources and Water Cycle in China” (special study) Tenth Five-Year “The Threshold of the Impact of Climate Plan Abnormality on China’s Freshwater Resources and Comprehensive Evaluation” (topic) Eleventh Five“Demonstration of Adaptation Technologies for Year Plan Climate Change in Typical Vulnerable Regions” Twelfth Five“Development and Application of Climate Year Plan Change Adaptation Technologies in Coastal Areas” 1988 “China Climate and Sea Surface Change and Its Trends and Impacts” (Chinese Academy of Sciences and the National Natural Science Foundation of China) 2008 “Study on the Impact of Climate Change on China’s Water Security and Adaptive Countermeasures” (major research project of the water conservation industry) 2009 “The Impact of Climate Change on Land Water Cycle and Water Resources Security in the Monsoon Region of Eastern China and Adaptation Countermeasures” 2010 “Influence Mechanism of Climate Change on Water Cycle in Huang-Huai-Haihe Region and Water Resources Safety Assessment” 2010 “Study on the Impact Mechanism of Climate Change on Water Cycle in Northwest Arid Areas and Water Resources Safety” 2011 “Influence Mechanism of Climate Change on Water Cycle in Huang-Huai-Haihe Region and Water Resources Safety Assessment” 2012 “Development and application of climate change adaptation technologies in coastal areas” 2016 “The Impact of Climate Change on Drought and Flood Disasters and Risk Assessment Techniques” 2018 “Dynamic Evaluation and Water Demand Evolution of Water Resources in the Yellow River Basin under Changing Environment”

Related projects supported by various departments

National Key Basic Research Development Program

National Basic Research Program of China

National Science and Technology Support Program National Key Basic Research Development Program National Key R&D Program of China

Project name

Water-related problems with special reference to global climate change in China  67 climate change on water cycles and water resources. The research covers water resources change trends, impact assessment models, and climate change threshold studies under climate change. The impact of climate change on water cycles and water resources, and water resources security and adaptation strategies for different areas in the country and typical regions are important focuses of China’s R&D, and this R&D is important for ensuring food security, ecological security, and sustainable socioeconomic development.

4.2  China’s water problem in the context of climate change 4.2.1  Climate change poses new challenges to China’s solutions to the water problem The fourth assessment report of the IPCC shows that the effects of global climate change are mainly reflected in levels of precipitation, temperature, and evapotranspiration, and in sea level rise (Piao, Philippe, & Huang, 2010). These four elements are directly related to water, and water resources are more sensitive to climate change impacts. As climate-warming trends intensify, in the future the frequency of extreme weather events in China may increase further. Currently the spatial and temporal distribution of precipitation is more obviously uneven, the scope of drought is expanding, the shortage of water is increasing, and the conflict between the supply of and demand for water resources is further aggravated. These conditions bring new challenges to managing water resources and solving water problems, including the four challenges outlined below: 1. Temperatures are rising, the range of droughts is expanding, and precipitation is decreasing. Climate change is the main factor affecting the distribution of and changes in drought and flood patterns in time and space. The uneven distribution of precipitation in time and space is one of the main causes of drought. Aridification caused by a warming climate and high temperatures is seen globally, while at the same time aridification and temperature increases in northwestern China, northern China, and southwestern China are closely related to a decrease in precipitation, which is basically consistent with the trend of climate warming. The north of China has been suffering from drought since the 1980s. In 2010 the southwestern region of the country experienced a period of unusual droughts that lasted a long time and had a great impact. Also, the area in the north affected by drought is expanding, seriously affecting people’s lives and productivity. 2. Climate change is exacerbating the reduction in river runoff. Climate change is causing changes in river runoff in China: over the past 30 years, the total amount of water in the Yellow River, Huaihe River, Haihe River, and Liaohe River has decreased significantly. As the temperature increases, the annual average evaporation of the basin also increases. For example, the evaporation capacity of the Yellow River and inland rivers has increased by 15%, and river runoff has increased even more. The annual average

68  Chapter 4 runoff in northern China has decreased by 7%–10%. Some analysis has shown that in the middle and lower reaches of the Yellow River, 38.5% of the reduction in river runoff is due to climate change. Rivers in arid regions will become increasingly more sensitive to climate change, and the reduction in river runoff will exacerbate the conflict between the unstable, tight supply of China’s water resources and demand. 3. Climate change has led to an increase in the frequency of floods. Climate change is causing floods to become more frequent and extreme weather phenomena to increase significantly. The frequency and intensity of floods in China have increased significantly since the 1990s. During the flood season of 2017 there were 36 heavy rains in the country, which were extremely intense and fell mainly in areas with a high degree of overlap. In the north of North China, northeastern China, and the eastern part of Inner Mongolia, there were droughts in the spring and summer. In Jianghuai, Jianghan, and in other places, droughts occurred from mid-July to mid-August. The agricultural area affected by drought measured 273 million mu, and the total direct economic loss was 43.8 billion yuan. Focusing only on the direct economic losses from heavy rains and geological disasters during the year understates the problem, however, as the increase in flood disasters not only causes an increase in direct economic losses, but also poses a severe test for flood control safety. It underscores the need to improve the capacity of water conservation projects to cope with climate change and resist natural disasters, and to adapt water conservation facilities to climate change impacts. 4. The ecological environment of water resources is deteriorating. The natural ecosystem is an interdependent whole. Temperature, precipitation, and sunlight, and soil’s organic matter, water content, permeability, and so on are interrelated and affect biological growth. Climate change has an impact on the ecosystem of water resources, mainly through the changes in soil, water, and nutrients that affect biological growth. Floods lead to soil and water loss, river sedimentation, and a decline in soil fertility. The reduction of organic matter in soil means that the soil becomes less permeable, leading to a decrease in water absorption, nutrients, and soil productivity, thus aggravating regional drought. Drought and water shortages lead people to use water resources more irresponsibly by extracting excessive groundwater, polluting water bodies, and so on, eventually causing problems such as erosion, a decline in groundwater levels and exhaustion of the resource, a reduction of the water-storage capacity of rivers and lakes, and deterioration of the water resource’s ecological environment. Studies have shown that in areas of water and soil sensitivity, the conflict between water supply and demand can be particularly pronounced.

4.2.2  The sensitivity of China’s water systems to climate change Due to the complexity of water resources recycling processes and the differences in flow conditions in different regions, water systems in different regions have different sensitivities

Water-related problems with special reference to global climate change in China  69 to climate change. “Sensitivity” is defined by the IPCC as the extent to which a system is affected by climate-related stimuli, including adverse and beneficial effects. These effects can be direct (such as changes in crop yields due to climate averaging and climate variability) or indirect (such as losses due to the increased frequency of floods in coastal zones caused by sea level rise). Climate-related stimuli refer to all climate change characteristics, namely the average climate state, climate variability, and the frequency and intensity of extreme events (Zhang, Huang, Wang, & Zhang, 2011). For water systems, the climate change sensitivity of hydrologic elements in a system refers to the extent to which runoff, evaporation, and soil water respond to assumed climate change scenarios. If the response of an element is greater under a given climate change scenario, the hydrologic element is deemed more sensitive; otherwise it is not sensitive. Sensitivity studies are useful for revealing the mechanisms of and differences between hydrological elements in different basins under climate change conditions (Wang & Zhang, 2008). It is important to clarify the sensitivity of water systems to climate change to address the water problem under climate change conditions. Precipitation, potential evapotranspiration, and the aridity index (or moisture index) can express regional water incomes and/or expenditures as a quantitative measure of sensitivity. Average potential evaporation and the average aridity index are used to indicate how China’s water status will respond to future global climate change conditions. Due to the complexity of studies involving space and time, the current methods for estimating potential evapotranspiration include theoretical analysis methods, experiential methods, and remote sensing methods (Alessa, Kliskey, & Busey, 2008). The primary methods for estimating potential evapotranspiration that are derived from theoretical analysis include the aerodynamic method, the energy balance method, and the synthesis method (the Penman formula). Based on monthly average observation data from the China Meteorological Administration between 1971 and 2000, the improved Penman formula was used to estimate the potential evapotranspiration of each month and compared with the 10,860 effective observations of 905 meteorological sites. The Penman method has a high accuracy rate (R2 = 0.9288). Using current climate conditions as a baseline and assuming an average monthly precipitation increase of 10%, three hypothetical future climate scenarios were tested, with an average temperature increase of 1.5°C under the first scenario, 3.0°C under the second, and 4.5°C under the third. The improved Penman formula was used to estimate potential evapotranspiration and aridity index distribution to analyze the sensitivity of China’s water resources to global climate change (Fig. 4.2). As the temperature increases, the amount of potential evapotranspiration will increase almost linearly. The change in the aridity index is more complicated. Under changes assumed in the three future scenarios, China will trend drier with the increase in temperature. Compared with current conditions, under the first hypothetical future climate scenario China will become

70  Chapter 4

Figure 4.2: Average potential evapotranspiration and average aridity index under current climate conditions and three hypothetical future climate scenarios.

slightly wetter; in the second scenario, China’s water status will change little; while in the third scenario it will become slightly drier.

4.2.3  Quantitative analysis of the impact of climate change on the measured runoff of typical rivers in China Due to the uncertainty of forecasting future climate conditions and of evaluation results, appropriate scientific indicators are needed to determine the impact of climate change on water systems. Changes in river runoff are the result of a combination of human activities and climate change, and are important indicators for water resources planning in river basins. Therefore, quantitative analysis of the effects of climate change on river runoff is particularly important (Oki & Kanae, 2006). Studies have shown that due to global climate change and accelerated human activities, the measured runoff of some rivers in China, such as in the Yellow River, Haihe River, and Liaohe River basins, has shown a trend of significant decline. Using the Yellow River basin as a model, the sequential clustering method and the moving average method were used to determine the hydrological series change point in the middle reaches of the Yellow River. Analysis showed that the runoff in the middle reaches and in the majority of the tributary rivers in the basin changed significantly around 1970. Therefore the pre-1970 hydrological series was regarded as the natural series, and the hydrological model’s parameters were calibrated accordingly. The hydrological simulation was used to show what natural runoff after 1970 would have been (Zhang & Wang, 2009). The impact of climate change and human activities on river runoff was then analyzed, using measured runoff before 1970 as a baseline (Fig. 4.3). Four conclusions were reached:

Water-related problems with special reference to global climate change in China  71

Figure 4.3: Measured values and reference values for Yellow River runoff, 1970–2010.

1. Between 1970 and 2010, the measured runoff in the middle reaches of the Yellow River showed a trend of significant decline, with the largest decrease between 1990 and 2010, and a measured runoff of close to half of the baseline value. 2. The effect of human activities and climate change on runoff is different for different periods, and the degree of impact of human activities on runoff is increasing. For example, the degree of impact of human activities increased from 55.9% in 1970–1979 to 65.2% in 2000–2010 (Table 4.4). 3. The relative impact of climatic factors on runoff showed a decreasing trend, reaching a maximum of 44.1% in the 1970s. 4. On average, human activity is the main reason for the decline of runoff in the middle reaches of the Yellow River (Shang & Gao, 2001). Between 1970 and 2010, the effect of climate change and human activities on runoff accounted for 34.8% and 65.2% of the total runoff reduction, respectively. Table 4.4: Impact of climate change and human activities on Yellow River runoff. Climatic factors Period

Total reduction, 108 m3

Total reduction, 108 m3

1970–1979 1980–1989 1990–1999 2000–2010 1970–2010

91.3 70.1 137.8 150.4 102.3

40.3 22.6 56.1 54.4 35.6

Human factors

% impact

Total reduction, 108 m3

% impact

44.1 32.3 40.7 36.2 34.8

51.0 47.5 81.7 96.0 66.7

55.9 67.7 59.3 63.8 65.2

72  Chapter 4

4.3  Quantitative evaluation of the vulnerability of China’s water systems under climate change conditions 4.3.1  The concept and understanding of water resources vulnerability Global warming is a major resource and environmental issue facing the world today. A good understanding of the vulnerability of China’s water resources to climate change is important for the scientific management and rational allocation of water resources. The next 30 to 50 years will be a crucial period in China’s economic and social development, an unprecedented period of severe population-growth pressure, and a period of significant impact on water resources due to climate change, all of which will put greater demands on China’s future water resources management. Conducting water resources vulnerability research and climate change adaptive countermeasures, analyzing the extent and characteristics of water systems affected by climatic and socioeconomic factors, improving the adaptability of water systems to climate change, reducing the adverse effects of future uncertainties and risks on human society, and thus ensuring the healthy development of society and the economy are major demands for China’s water resources to ensure water resources security and support China’s social and economic stability and rapid development in the context of future climate change (Weng, 2012). A special report issued by the IPCC in November 2011, Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, analyzes vulnerability and exposure. Vulnerability is defined as the tendency of people, livelihoods, environmental services and resources, infrastructure, and economic, social, and cultural assets to be adversely affected (Farley, Tague, & Grant, 2011). Using this definition, the vulnerability of water resources under climate change conditions can be considered to be changes in the structure of water systems; reductions in the quantity of water resources and the quality of water systems; changes in water supply, demand, and management; and the frequency of natural disasters such as droughts and floods because of climate change and human activities (Vörösmarty, Green, Salisbury, & Lammers, 2000). Understanding of water-resources vulnerability includes the following four elements: 1. Water resources vulnerability is an intrinsic property of water systems, and their internal structures and characteristics are decisive factors for their vulnerability. 2. Water resources vulnerability is characterized by the water system’s sensitivity and adaptability to the external impact (especially adverse effects). 3. Water resources vulnerability is influenced by two factors: natural environmental vulnerability and social and economic vulnerability. 4. Water resources vulnerability is influenced by the scale and spatial distribution of the particular water system.

Water-related problems with special reference to global climate change in China  73 The evaluation of water resources vulnerability can be roughly divided into qualitative evaluation and quantitative evaluation. Qualitative evaluation is a qualitative analysis of the factors affecting a water system that looks for the main influencing factors so as to propose measures to reduce the vulnerability of the water resource (Hamouda, El-din, & Moursy, 2009; Tang, Li, & Liu, 2000). Water-resources vulnerability mostly is assessed using quantitative evaluation. Quantitative evaluation methods of water resource vulnerability can be roughly divided into the index method and the function method. The index method has the advantages of being a clear-cut system with flexible construction, comprehensive consideration, and easy operation. Therefore, this system has been adopted to carry out vulnerability assessments for individual or regional water resources under climate change conditions. The main steps of this method are: 1. 2. 3. 4.

Select the indicators to build an index evaluation system. Standardize the data. Determine the weight of each indicator. Calculate the water vulnerability index (WVI) using a weighted method.

4.3.2  Index system construction There are many factors that affect the vulnerability of water systems, with multiple levels of characteristics belonging to more complex systems. In analyzing the existing research results for China and for the world using the overall evaluation objectives of vulnerability and the screening principles of science, integrity, dominance, independence, and operability, we first established a three-tiered index system of target criteria indicators to calculate and evaluate water resources vulnerability (Brouwer & Falkenmark, 1989; Doerfliger, Jeannin, & Zwahlen, 1999). The following five principles for creating indicators were considered: 1. Scientific meaning. The scientific meaning of the indicator system should be clear, should objectively and accurately reflect the characteristics of the water system, and should accurately measure the vulnerability of water resources. 2. Integrity. The indicator system should correlate the relationship among subindicators and comprehensively reflect the vulnerability of water resources. 3. Dominance. The indicator system should play a leading role in determining water resource vulnerability. 4. Independence. The indicators should be as independent as possible in terms of concept and quantity. 5. Operability. Indicator data should be easy to obtain and recognized by most scholars. Using the construction principles above, eight indicators – mean annual precipitation, drought index, water yield coefficient, supply and demand ratio, regulation and storage capacity of the hydro project, water use per ten thousand yuan GDP, GDP per capita, and population density – were selected for the water vulnerability assessment. These indicators were divided into

74  Chapter 4

Figure 4.4: Water resources vulnerability index assessment system.

two categories: natural environmental vulnerability and socioeconomic vulnerability. A block diagram of the indicator system is shown in Fig. 4.4. The drought index reflects the dryness and wetness of the climatic environment; the water yield coefficient reflects the ability of the rainfall to produce surface and groundwater resources in the year of evaluation; the ratio of supply and demand in the current year is the ratio of the water supply to the available water resources in the evaluation year; water use amount per ten thousand yuan GDP and GDP per capita use the value of evaluation year.

4.3.3  Evaluation method The data evaluation method has three steps: 1. Data standardization Since the selected indicators have different dimensions, they should be standardized before evaluation (Feng & Daming, 2009). The maximum difference normalization method is used to standardize the data corresponding to each indicator in accordance with the actual situation. Of the eight indicators, the drought index, the supply and demand ratio in the current year, population density, and water use amount per ten thousand yuan GDP are positive indicators, which are standardized using Eq. (4.1). Mean annual precipitation, water yield coefficient, GDP per capita, and regulation and storage capacity of the hydro project are negative indicators and are normalized using Eq. (4.2). In Eq. (4.1), xij′ is a normalized value, xij is the value before normalization, max {xij} is the maximum value of xij, and min {xij} is the minimum value of xij.

Water-related problems with special reference to global climate change in China  75 Table 4.5: Index evaluation weights. Index

Weight

Index

Weight

Mean annual precipitation

0.071

0.077

Drought index

0.104

Water yield coefficient Supply and demand ratio

0.063 0.399

Regulation and storage capacity of the hydro project Water use amount per ten thousand yuan GDP GDP per capita Population density

xij′ =



xij′ =

0.032 0.071 0.183

xij − min{xij } max{xij } − min{xij } max{xij } − xij max{xij } − min{xij }

(4.1)

(4.2)

2. Weight determination The analytic hierarchy process is used to determine the weight of each indicator. Due to space limitations, the specific steps of the analytic hierarchy process are not described here. The analytic hierarchy process of index weights is scored using Saaty’s nine-point scale. The relative importance of the two indicators is determined by expert consultation. The weight calculation results are shown in Table 4.5. 3. Water vulnerability index The WVI is calculated using a comprehensive index weighted summation method; see Eq. (4.3). WVI = ∑ j =1 xij′ wij′ m



(4.3)

In Eq. (4.3), WVIi is the water vulnerability index, xij′ is the standardized indicator value, and wij′ is the weight corresponding to the indicator value. The greater the vulnerability index of water resources, the higher the vulnerability of the assessment unit to water resources, and vice versa. The WVI ranges from 0 to 1.

4.3.4  Evaluation conclusion Changes in the dryness and wetness of the climate and extreme events caused by climate change are exacerbating the vulnerability of China’s water systems. Facing severe water resources conditions, the quantitative evaluation of water resources vulnerability under the dual influences of climate change and social and economic development has become an

76  Chapter 4 Table 4.6: Classification levels of the water resources vulnerability index. Vulnerability index interval

Grading

0≤WVI