Surrogate-Based Multiperiod, Multiobjective Reservoir Operation Optimization for Quality and Quantity Management
Publication: Journal of Water Resources Planning and Management
Volume 146, Issue 8
Abstract
Deriving optimal reservoir operation rules in a selective withdrawal framework (SWF) considering quality and quantity objectives is a challenging problem due to its computational burdens. To overcome the computational bottleneck, two surrogate models have been developed and coupled with the evolutionary algorithm in an adaptive-recursive framework to form the surrogate-based multiobjective optimization technique (SBMOOT). SBMOOT is used to derive the optimal reservoir operating strategies and the set of nondominated optimal solutions to enhance reservoir outflow water quality and maximize water supply and hydropower energy generation. The most desirable scenarios of the Pareto front have been identified to derive monthly operating rules in the SWF. The operating rules focusing on water supply, hydropower energy, and water quality objectives are estimated using polynomial regression technique. The performances of the operating rules, with and without regarding the uncertainty of inflows, have been compared with the historical operating strategy in Karkheh Reservoir, Khuzestan, Iran. The results show that water quality measure may be enhanced while maintaining desirable water supply and/or hydropower energy compared with the historical operating strategy of Karkheh Reservoir.
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Data Availability Statement
1.
The meteorological data of the studied area are available online at jira.irimo.ir:8081/irimoReportServer/login.html.
2.
The technical and environmental studies of Karkheh project applied in this research were provided by MGCE as cited in the reference section. Direct requests for these materials may be made to MGCE.
3.
The Karkheh Reservoir operation data are accessible with permission of Iran Water Resources Management Company (IWRMC). Direct requests for these materials may be made to IWRMC.
Acknowledgments
The authors would like to express their very great appreciation to Iran Water Resources Management Company (IWRMC), MGCE Company, and Iran Meteorological Organization for providing access to invaluable technical reports and data.
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Published In
Journal of Water Resources Planning and Management
Volume 146 • Issue 8 • August 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Apr 20, 2019
Accepted: Feb 11, 2020
Published online: May 21, 2020
Published in print: Aug 1, 2020
Discussion open until: Oct 21, 2020
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