Reservoir Flood Season Segmentation and Risk–benefit Cooperative Decision of Staged Flood Limited Water Level

Xiaoying Li, Yan Zhang (), Zechun Tong and Guo-Yue Niu
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Xiaoying Li: Hohai University
Yan Zhang: Hohai University
Zechun Tong: Hohai University
Guo-Yue Niu: the University of Arizona

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2022, vol. 36, issue 10, No 4, 3463-3479

Abstract: Abstract Investigation of seasonal inconsistency between water consumption and rainfall variation is important for more efficient use of floodwater resources. Adjustment of the flood limited water level (FLWL) is an effective way to improve the floodwater use efficiency. Flood season segmentation provides the basis for determining the FLWL and tapping the potential use of floodwater resources. Compromise between the benefit of floodwater use and flood control is crucial to FLWL decision. We use the circular distribution method for flood season segmentation and the relative frequency method for verification. We select the performances of water supply and hydropower generation as the benefit index and the extreme risk rate as the risk index. On the basis of the game theory, we establish a multi-objective cooperative decision-making model and obtain a Nash negotiation solution of staged FLWL. An optimal scheme is determined according to the fuzzy pattern recognition theory. When the risk and benefit are equally valued, the resulting FLWLs of the optimal scheme are 129.0 m, and 128.5 m for a selected reservoir in the pre-flood season and the post-flood season, respectively. By adjusting the preference values of the risk and benefit indexes, we determine the optimal FLWL scheme under different preferences to risk and benefit for each stage.

Keywords: Flood season segmentation; Extreme risk rate; Multi-objective cooperative decision; Nash negotiation; Adjustment of flood limited water level (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11269-022-03184-3

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