The future nexus of the Brahmaputra River Basin: Climate, water, energy and food trajectories

Abstract Advance knowledge of conflicting trajectories of water–energy–food (WEF) nexus is highly relevant for water policy and planning, especially for basins that cross national boundaries. The Brahmaputra River Basin in South Asia, home for 130 million people, is such a basin. Development of new hydropower projects, upstream water diversions and possible climate changes introduce concerns among riparian countries about future water supply for energy and food production in the basin. This study presents a new hydro-economic water system model of the basin coupled with ex post scenario analysis under the “nexus thinking” concept to identify and illustrate where development paths are in conflict. Results indicate that the ability of future development to remain free of conflict hinges mostly on the amount of precipitation falling in the basin in the future. Uncertain future precipitation along with uncertain future temperature and the unknown amount of upstream water diversion combine to strongly influence future water, energy and food production in the basin. Specifically, decreases in precipitation coupled with large upstream diversions (e.g., diversion in the territory of China) would leave one or more riparian countries unable to secure enough water to produce their desired energy and food. Future climate projected by General Circulation Models suggest a warmer and wetter climate condition in the region, which is associated with an increase in streamflow and easing of conflicts at the WEF nexus in the basin. The methodology presented here is expected to be generally useful for diagnosing the conditions that may cause water resources development goals to not be achieved due to either changes in climate or water use among competing users.

[1]  Salman M. A. Salman,et al.  Legal aspects of sharing and management of transboundary waters in South Asia: preventing conflicts and promoting cooperation , 2011 .

[2]  J. O. G. Duloy.  Issues of efficiency and interdependence in water resource investments : lessons from the Indus Basin of Pakistan , 1983 .

[3]  Patrick A. Ray,et al.  Room for improvement , 1996 .

[4]  Ximing Cai,et al.  A Decentralized Optimization Algorithm for Multi-Agent System Based Watershed Management , 2009 .

[5]  Jeffrey G. Arnold,et al.  Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations , 2007 .

[6]  Md. Jakir Hossain,et al.  Groundwater Use for Irrigation and its Productivity: Status and Opportunities for Crop Intensification for Food Security in Bangladesh , 2014, Water Resources Management.

[7]  S. Jain,et al.  Trend analysis of rainfall and temperature data for India , 2012 .

[8]  Patrick A. Ray,et al.  Confronting Climate Uncertainty in Water Resources Planning and Project Design: The Decision Tree Framework , 2015 .

[9]  T. Hartani,et al.  The nexus approach to water–energy–food security: an option for adaptation to climate change in Algeria , 2018 .

[10]  Ximing Cai,et al.  A decentralized optimization algorithm for multiagent system–based watershed management , 2009 .

[11]  F. Pithan.  Asian water towers: more on monsoons. , 2010, Science.

[12]  C. Rosenzweig,et al.  Multi-factor impact analysis of agricultural production in Bangladesh with climate change , 2013 .

[13]  Adb Avenue,et al.  © 2005 Asian Development Bank, The International Bank for Reconstruction and Development/The World Bank, and Japan Bank for International Cooperation , 2005 .

[14]  M. Hulme,et al.  Does climate adaptation policy need probabilities? , 2004 .

[15]  Casey Brown,et al.  An alternate approach to assessing climate risks , 2012 .

[16]  Ximing Cai,et al.  Decentralized Optimization Method for Water Allocation Management in the Yellow River Basin , 2012 .

[17]  G. Rasul,et al.  The nexus approach to water–energy–food security: an option for adaptation to climate change , 2016 .

[18]  Martin Smith,et al.  CLIMWAT for CROPWAT: A climatic database for irrigation planning and management , 1993 .

[19]  Peter H. Gleick,et al.  The World’s Water , 2011 .

[20]  Karl E. Taylor,et al.  An overview of CMIP5 and the experiment design , 2012 .

[21]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[22]  Zhu Chuan-bao.  Application of a Distributed Hydrological Model for the Yarlung Zangbo River and Analysis of the River Runoff , 2008 .

[23]  A. Turner,et al.  Climate change and the South Asian summer monsoon , 2012 .

[24]  Samjwal Ratna Bajracharya,et al.  The Status of Glaciers in the Hindu Kush-Himalayan Region , 2011 .

[25]  Myles T. Collins,et al.  Managing the Risk of Uncertain Threshold Responses , 2007 .

[26]  K. Frieler,et al.  Consistent increase in Indian monsoon rainfall and its variability across CMIP-5 models , 2013 .

[27]  Casey M. Brown,et al.  Estimation of flood damage functions for river basin planning: a case study in Bangladesh , 2015, Natural Hazards.

[28]  Avi Ostfeld,et al.  The future of water resources systems analysis: Toward a scientific framework for sustainable water management , 2015 .

[29]  R. Muñoz‐Carpena,et al.  Performance evaluation of hydrological models: Statistical significance for reducing subjectivity in goodness-of-fit assessments , 2013 .

[30]  Yi-Chen E. Yang,et al.  Calibration approaches for distributed hydrologic models in poorly gaged basins: implication for streamflow projections under climate change , 2015 .

[31]  Aslak Grinsted,et al.  An estimate of global glacier volume , 2012 .

[32]  Kevin Hamilton,et al.  The South Asian Summer Monsoon and Its Relationship with ENSO in the IPCC AR4 Simulations , 2007 .

[33]  Olli Varis,et al.  Integrated water management of the Brahmaputra basin: Perspectives and hope for regional development , 2009 .

[34]  Geoffrey M. Henebry,et al.  Assessing the impacts of climate and land use and land cover change on the freshwater availability in the Brahmaputra River basin , 2015 .

[35]  Richard Washington,et al.  Issues in the interpretation of climate model ensembles to inform decisions , 2007, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[36]  Marc Jeuland,et al.  Interdependence in Water Resource Development in the Ganges: An Economic Analysis , 2013 .

[37]  Fahad Saeed,et al.  Downscaled climate change projections with uncertainty assessment over India using a high resolution multi-model approach. , 2013, The Science of the total environment.

[38]  C. Scott,et al.  The Water-Energy-Food Nexus: Enhancing Adaptive Capacity to Complex Global Challenges , 2015 .

[39]  U. Schneider,et al.  GPCC's new land surface precipitation climatology based on quality-controlled in situ data and its role in quantifying the global water cycle , 2013, Theoretical and Applied Climatology.

[40]  Yi-Chen E. Yang,et al.  Calibration approaches for distributed hydrologic models using high performance computing: implication for streamflow projections under climate change , 2014 .

[41]  Warren E. Walker,et al.  Dynamic adaptive policy pathways: A method for crafting robust decisions for a deeply uncertain world , 2013 .

[42]  T. Bolch,et al.  The Randolph Glacier inventory: a globally complete inventory of glaciers , 2014 .

[43]  A. Kitoh,et al.  APHRODITE: Constructing a Long-Term Daily Gridded Precipitation Dataset for Asia Based on a Dense Network of Rain Gauges , 2012 .

[44]  David G. Groves,et al.  A New Analytic Method for Finding Policy-Relevant Scenarios: , 2007 .

[45]  A. Neef,et al.  Sustainable development and the water–energy–food nexus: A perspective on livelihoods , 2015 .

[46]  David E. Rosenberg,et al.  Hydro-economic models: concepts, design, applications, and future prospects. , 2009 .

[47]  Aaron T. Wolf,et al.  Shared Waters: Conflict and Cooperation , 2007 .

[48]  Elisa Palazzi,et al.  Precipitation in the Hindu‐Kush Karakoram Himalaya: Observations and future scenarios , 2013 .

[49]  G. Rasul.  Food, water, and energy security in South Asia: A nexus perspective from the Hindu Kush Himalayan region☆ , 2014 .

[50]  V. Kousky,et al.  Simulations and Seasonal Prediction of the Asian Summer Monsoon in the NCEP Climate Forecast System , 2008 .

[51]  David G. Groves,et al.  A General, Analytic Method for Generating Robust Strategies and Narrative Scenarios , 2006, Manag. Sci..

[52]  Myles T. Collins,et al.  Managing the Risk of Uncertain Threshold Responses: Comparison of Robust, Optimum, and Precautionary Approaches , 2007, Risk analysis : an official publication of the Society for Risk Analysis.

[53]  C. Rosenzweig,et al.  Climate Change Risks and Food Security in Bangladesh , 2010 .

[54]  Casey Brown,et al.  The Indus Basin of Pakistan: The Impacts of Climate Risks on Water and Agriculture , 2013 .

[55]  Martin Beniston,et al.  CLIMATIC CHANGE AT HIGH ELEVATION SITES: AN OVERVIEW , 1997 .

[56]  M. Bierkens,et al.  Impact of climate change on the stream flow of the lower Brahmaputra: trends in high and low flows based on discharge-weighted ensemble modelling , 2011 .

[57]  Casey Brown,et al.  Decision scaling: Linking bottom‐up vulnerability analysis with climate projections in the water sector , 2012 .

[58]  X. Jianchu,et al.  The Changing Himalayas; Impact of Climate Change on Water Resources and Livelihoods in the Greater Himalayas , 2009 .