Comprehensive framework for long-term reservoir management under deep uncertainty
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(Published version)
Date
2026
Authors
Huang, J.
Wu, W.
Maier, H.R.
Hughes, J.
Wang, Q.J.
Cao, Y.
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Environmental Modelling & Software, 2026; 195:106740-1-106740-11
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Jiajia Huang, Wenyan Wu, Holger R. Maier, Justin Hughes, Quan J. Wang, Yuan Cao
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Abstract
Reservoir systems play a crucial role in providing essential services such as water supply, flood protection, and energy generation. However, reservoir management is highly complex due to (i) multiple conflicting management goals, (ii) long-term changes in water availability and demand over the long life span of these systems, and (iii) deep uncertainty. While some of these challenges have been addressed in previous studies, there is a lack of a comprehensive framework that can maximize the co-benefits of addressing these challenges in an integrated manner. Such an optimization framework has been developed in this study. By incorporating deep uncertainty, the causal relationships between decisions, system performance, and robustness can be explored. By adapting both operation policy and infrastructure upgrade decisions to long-term changes, infrastructure investments can be reduced without compromising system performance. By explicitly accounting for multiple conflicting objectives, the framework also provides a platform for negotiation during the decision-making process.
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© 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).