Adaptation to Climate Change in Basins within the Context of the Water-Energy-Food Nexus
Publication: Journal of Water Resources Planning and Management
Volume 149, Issue 11
Abstract
This study uses a water-food-energy nexus model, which connects water-based productive activities and allocation policies, to simulate water resources management strategies for adapting the Maule Basin in Chile to climate change impacts. Two strategies are considered: introducing linear hedging rules to a reservoir and establishing adaptative water rights linked to irrigation efficiency of crops in the area. The simulations are run over 14 different climatic scenarios that project different water availability conditions. A multiobjective optimization of environmental, agricultural, and energy outcome indicators is conducted to generate noninferior portfolios that combine the strategies proposed. Simulation results, though limited to a deterministic approach and pessimistic climate scenarios, show that 79 out of the 84 combinations of objective-scenarios increase their performance because of the strategies, with notable increases in agricultural resilience (64%), outflow (92%), and total benefits (26%). We find considerable trade-offs between the food/energy production and water outflow, alongside agricultural vulnerability and resilience.
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Data Availability Statement
All data, models, or code generated or used during the study are available in a repository online in accordance with funder data retention policies. A public repository has been created via Github, containing all the data at https://github.com/VJander/Maule-Basin.
Reproducible Results
The authors have made all data, models, code, and directions findable and accessible in an online public repository.
Acknowledgments
We thank the help of J. Tomlinson, who provided guidance and supported the coding of additional features required for this work in Pywr. Also, we would like to recognize the ARClim project, which produced the downscaled climate scenarios and results used in this study. Finally, we would like to thank I. Ricalde and M. Canales for advisory on Pywr, repositories, and multiobjective optimization modeling.
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Published In
Journal of Water Resources Planning and Management
Volume 149 • Issue 11 • November 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Sep 20, 2021
Accepted: Jun 15, 2023
Published online: Aug 28, 2023
Published in print: Nov 1, 2023
Discussion open until: Jan 28, 2024
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