Multicriteria Decision-Making Model of Reservoir Operation Considering Balanced Applicability in Past and Future: Application to the Three Gorges Reservoir
Publication: Journal of Water Resources Planning and Management
Volume 146, Issue 6
Abstract
Motivated by the emerging need for long-term and sustainable reservoir management, this paper developed a multicriteria decision-making (MCDM) model of reservoir operation with consideration of balanced applicability in both the past and the future. The proposed method consists of four modules: (1) the multiobjective optimization model of reservoir operation is built based on historical streamflow and then solved by the evolutionary multiobjective direct policy search (EMOPDS) with the nondominated sorting genetic algorithm-II (NSGA-II); (2) an evaluation criteria matrix is made considering the benefits and risks of the same objectives under future climate change; (3) objective interrelationships are qualitatively identified by visual analytics and quantitatively described by the structural equation model (SEM); and (4) an objective-based space coordinate system (SCS) is established to calculate the evaluation criteria weights based on SEM results, from which the optimum Pareto solution is determined by a decision-making function. The Three Gorges Reservoir (TGR) was selected as a case study, which simultaneously provides hydropower generation (pow), ecology (eco), and water storage (stor). Results indicate that eco negatively interacts with both pow and stor; however, pow is positively correlated with stor. Moreover, the design of the SCS-MCDM model can significantly improve benefits in both pow and stor and slightly sacrifice benefit in eco, compared with fuzzy optimum selection (FOS)-1 and FOS-2. Generally, the SCS-MCDM model outperforms FOS-1 and FOS-2 in terms of benefits for past and future and robustness in operation process under climate change. Therefore, the SCS-MCDM model facilitates decision makers to make a sustainable and balanced decision for reservoir management under uncertain climate change.
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Data Availability Statement
All data, models, or code generated or used during this study are available from the corresponding author by request.
Acknowledgments
The authors thank the editor and two anonymous reviewers for their valuable suggestions, which helped to improve the quality of the paper. This study was supported by the National Key Research and Development Project (2017YFC0404405), the China Scholarship Council, the National Natural Science Foundation of China (Grant No. 51709276), and the National Key Research and Development Project (2016YFC0402208).
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Journal of Water Resources Planning and Management
Volume 146 • Issue 6 • June 2020
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©2020 American Society of Civil Engineers.
History
Received: Nov 15, 2018
Accepted: Dec 6, 2019
Published online: Mar 27, 2020
Published in print: Jun 1, 2020
Discussion open until: Aug 27, 2020
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