Optimizing Operation Rules of Cascade Reservoirs for Adapting Climate Change

Shaokun He (), Shenglian Guo (), Guang Yang, Kebing Chen, Dedi Liu and Yanlai Zhou
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Shaokun He: Wuhan University
Shenglian Guo: Wuhan University
Guang Yang: Wuhan University
Kebing Chen: Wuhan University
Dedi Liu: Wuhan University
Yanlai Zhou: Wuhan University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2020, vol. 34, issue 1, No 7, 120 pages

Abstract: Abstract Climate change leads to great impact on hydrological cycle and consequently affects water resources management. Historical strategies are no longer applicable under a changing environment. Therefore, adaptive management, especially adaptive operation rules for reservoirs, has been developed to mitigate the potential adverse impacts of climate change. However, previous studies generally provide a similar framework for adaptation strategies of individual reservoir without consideration of cascade reservoirs in the future scenario. This study derives adapting operation rules for cascade reservoir system based on future projections (2021–2100) of two global climate change models (GCMs). By using Pareto archived dynamically dimensioned search (PA-DDS) algorithm with maximization of water supply and power generation, the performance of the adaptive operation rule curves is compared with the designed operation rule. The results demonstrate that Pareto solutions of the PA-DDS algorithm provide a wider, more optimal range of annual power generation and water supply, and the projection pursuit method can select the best. The adaptive operation rules focusing on power generation can significantly increase the cascade reservoir annual power generation (by 3.7% in GCM-BCC or 4.8% in GCM-BNU), which shows that the proposed method can adapt future climate change.

Keywords: Cascade reservoir; Multi-objective; Adaptive operation rules; Climate change; PA-DDS algorithm; Hanjiang River basin (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s11269-019-02405-6

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