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Water 2018, 10(9), 1184; https://doi.org/10.3390/w10091184

Water Resource Optimal Allocation Based on Multi-Agent Game Theory of HanJiang River Basin

State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
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Received: 27 July 2018 / Revised: 23 August 2018 / Accepted: 28 August 2018 / Published: 4 September 2018
(This article belongs to the Special Issue Adaptive Catchment Management and Reservoir Operation)
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Abstract

Water scarcity is an important issue in many countries, and it is therefore necessary to improve the efficiency and equality of water resource allocation for decision makers. Based on game theory (GT), a bi-level optimization model is developed from the perspective of a leader-follower relationship among agents (stakeholders) of a river basin in this study, which consists of a single-agent GT-based optimization model of common interest and a multi-agent cooperative GT-based model. The Hanjiang River Basin is chosen as a case study, where there are conflicts among different interest agents in this basin. The results show that the proposed bi-level model could attain the same improvement of common interest by 8%, with the conventional optimal model. However, different from the conventional optimal model, since the individual interests have been considered in the bi-level optimization model, the willingness of cooperation of individuals has risen from 20% to 80%. With a slight decrease by 3% of only one agent, the increases of interest of other agents are 14%, 18%, 7%, and 14%, respectively, when using the bi-level optimization model. The conclusion could be drawn that the proposed model is superior to the conventional optimal model. Moreover, this study provides scientific support for the large spatial scale water resource allocation model. View Full-Text
Keywords: multi-agent of river basin; game theory; water resources allocation multi-agent of river basin; game theory; water resources allocation
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Han, Q.; Tan, G.; Fu, X.; Mei, Y.; Yang, Z. Water Resource Optimal Allocation Based on Multi-Agent Game Theory of HanJiang River Basin. Water 2018, 10, 1184.

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