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Two-Stage Multi-Water Sources Allocation Model in Regional Water Resources Management under Uncertainty

Author

Listed:
  • Dong Liu

    (Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University)

  • Wenting Liu

    (Ministry of Water Resources)

  • Qiang Fu

    (Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University)

  • Yongjia Zhang

    (Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University)

  • Tianxiao Li

    (Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University)

  • Khan M. Imran

    (Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University)

  • Faiz M. Abrar

    (Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University)

Abstract

Water shortages are common in society, and the effective allocation of limited water resources to each competitive sector has become one of the urgent concerns for water resource managers. With the increasing conflict between supply and demand of water resources, the problem of optimized allocation has attracted considerable attention. In this paper, regarding the Hongxinglong Administration of Heilongjiang Agricultural Reclamation in Sanjiang Plain, China as the study area, a two-stage regional multi-water source allocation (TRMSA) model is introduced to determine the characteristics of water supply sources, which consist of surface water, groundwater and transit water. When water resources managers periodically make different decisions over time, the TRMSA model can express the uncertain problem of water resources allocation as probability distributions and solve these problems effectively. Using this model, the optimized water supply target and shortage with different inflow levels in three sectors, namely, domestic, agriculture and industry, are analyzed for a dry year, and the optimized water allocation can be determined from the water allocation demands in these sectors. In addition, the satisfaction of supply targets in each sector in normal and high years as well as the recognition of the decision variables and different scenarios in this model are also discussed. Thus, water resource managers can obtain variable optimized water allocation schemes according to different water requirements, and decision makers can make practical judgments through multiple choices.

Suggested Citation

  • Dong Liu & Wenting Liu & Qiang Fu & Yongjia Zhang & Tianxiao Li & Khan M. Imran & Faiz M. Abrar, 2017. "Two-Stage Multi-Water Sources Allocation Model in Regional Water Resources Management under Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(11), pages 3607-3625, September.
    • Handle: RePEc:spr:waterr:v:31:y:2017:i:11:d:10.1007_s11269-017-1688-4
    DOI: 10.1007/s11269-017-1688-4
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    References listed on IDEAS

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    1. Yong Li & Guo Huang, 2008. "Interval-parameter Two-stage Stochastic Nonlinear Programming for Water Resources Management under Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(6), pages 681-698, June.
    2. L. Zhang & C. Li, 2014. "An Inexact Two-Stage Water Resources Allocation Model for Sustainable Development and Management Under Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 3161-3178, August.
    3. Chang, Ni-Bin & Wang, S.F., 1997. "A fuzzy goal programming approach for the optimal planning of metropolitan solid waste management systems," European Journal of Operational Research, Elsevier, vol. 99(2), pages 303-321, June.
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    Cited by:

    1. Z. Ghaffari Moghadam & E. Moradi & M. Hashemi Tabar & A. Sardar Shahraki, 2023. "Developing a Bi-level programming model for water allocation based on Nerlove’s supply response theory and water market," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(6), pages 5663-5689, June.
    2. Dan Yan & Mingtian Yao & Fulco Ludwig & Pavel Kabat & He Qing Huang & Ronald W. A. Hutjes & Saskia E. Werners, 2018. "Exploring Future Water Shortage for Large River Basins under Different Water Allocation Strategies," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(9), pages 3071-3086, July.
    3. Zhang, Fan & Zhang, Chenglong & Yan, Zehao & Guo, Shanshan & Wang, Youzhi & Guo, Ping, 2018. "An interval nonlinear multiobjective programming model with fuzzy-interval credibility constraint for crop monthly water allocation," Agricultural Water Management, Elsevier, vol. 209(C), pages 123-133.
    4. Ijaz Ahmad & Fan Zhang & Junguo Liu & Muhammad Naveed Anjum & Muhammad Zaman & Muhammad Tayyab & Muhammad Waseem & Hafiz Umar Farid, 2018. "A linear bi-level multi-objective program for optimal allocation of water resources," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-25, February.
    5. Zhang, Yu & Ren, Chongfeng & Zhang, Hongbo & Xie, Zhishuai & Wang, Yashi, 2022. "Managing irrigation water resources with economic benefit and energy consumption: an interval linear multi-objective fractional optimization model under multiple uncertainties," Agricultural Water Management, Elsevier, vol. 272(C).

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