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Multi-Objective Optimal Allocation of Urban Water Resources While Considering Conflict Resolution Based on the PSO Algorithm: A Case Study of Kunming, China

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  • Junfei Chen

    (State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
    Business School, Hohai University, Nanjing 211100, China)

  • Cong Yu

    (Business School, Hohai University, Nanjing 211100, China)

  • Miao Cai

    (Business School, Hohai University, Nanjing 211100, China)

  • Huimin Wang

    (State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
    Business School, Hohai University, Nanjing 211100, China)

  • Pei Zhou

    (Business School, Hohai University, Nanjing 211100, China)

Abstract

With the rapid increase of water demand in urban life, ecology and production sectors, the problem of water resources allocation has become increasingly prominent. It has hindered the sustainable development of urban areas. Based on the supply of various water sources and the water demand of different water users, a multi-objective optimal allocation model for urban water resources was proposed. The model was solved using the algorithm of particle swarm optimization (PSO). The algorithm has a fast convergence and is both simple and efficient. In this paper, the conflict over Kunming’s water resources allocation was taken as an example. The PSO algorithm was used to obtain optimized water resources allocation plans in the year 2020 and 2030, under the circumstances of a dry year (inflow guarantee rate p = 0.825) and an unusually dry year (inflow guarantee rate p = 0.885), respectively. The results showed that those allocation plans can lower the future potential water shortage rates of Kunming. At the same time, the interests of different sectors can all be satisfied. Therefore, conflicts over urban water use can be effectively alleviated.

Suggested Citation

  • Junfei Chen & Cong Yu & Miao Cai & Huimin Wang & Pei Zhou, 2020. "Multi-Objective Optimal Allocation of Urban Water Resources While Considering Conflict Resolution Based on the PSO Algorithm: A Case Study of Kunming, China," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:4:p:1337-:d:319666
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    References listed on IDEAS

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    Cited by:

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    2. Ijaz Ahmad & Fan Zhang, 2022. "Optimal Agricultural Water Allocation for the Sustainable Development of Surface and Groundwater Resources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(11), pages 4219-4236, September.
    3. Jitao Zhang & Zengchuan Dong & Tian Chen, 2020. "Multi-Objective Optimal Allocation of Water Resources Based on the NSGA-2 Algorithm While Considering Intergenerational Equity: A Case Study of the Middle and Upper Reaches of Huaihe River Basin, Chin," IJERPH, MDPI, vol. 17(24), pages 1-18, December.
    4. Meraj Sohrabi & Zeynab Banoo Ahani Amineh & Mohammad Hossein Niksokhan & Hossein Zanjanian, 2023. "A framework for optimal water allocation considering water value, strategic management and conflict resolution," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(2), pages 1582-1613, February.
    5. Arya Yaghoubzadeh-Bavandpour & Omid Bozorg-Haddad & Mohammadreza Rajabi & Babak Zolghadr-Asli & Xuefeng Chu, 2022. "Application of Swarm Intelligence and Evolutionary Computation Algorithms for Optimal Reservoir Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(7), pages 2275-2292, May.

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