A Fair Approach for Multi-Objective Water Resources Allocation
Jing Tian,
Shenglian Guo (),
Dedi Liu,
Zhengke Pan and
Xingjun Hong
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Jing Tian: Wuhan University
Shenglian Guo: Wuhan University
Dedi Liu: Wuhan University
Zhengke Pan: Wuhan University
Xingjun Hong: Wuhan University
Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2019, vol. 33, issue 10, No 18, 3633-3653
Abstract:
Abstract Due to the effect of climate change, rapid population growth and widespread water pollution, fresh water becomes an increasingly scarce natural resource. Optimal allocation of water resources is one of the most effective resolutions to deal with rising water demand and insufficient freshwater resources. This study proposes a fair approach for water resources allocation by employing the Sperner’s lemma to solve the conflicts of different objectives and those of competing regions. A multi-objective optimal allocation model is firstly formulated to generate the Pareto frontier surface, which maximizes the economic interest while minimizing the amount of organic pollutants. Subsequently, the approach searches for acceptable allocation schemes over the Pareto frontier surfaces through the total water quantity and envy-free constraints. The proposed model is applied to the middle and lower reaches of Hanjiang river basin in China. Results indicate that water allocation between multi-region can achieve Nash equilibrium by using the water conflict resolution method to select fair water allocation schemes, in which each region obtains its preferred water quantity. The proposed approach is proved effective for water resources management in the case study and demonstrates the potential for effective application in other basins.
Keywords: Water resources; Fair allocation; Multi-objective; Conflicts resolution; Sperner’s lemma; Pareto frontier surface (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (12)
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DOI: 10.1007/s11269-019-02325-5
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