A fuzzy interval dynamic optimization model for surface and groundwater resources allocation under water shortage conditions, the case of West Azerbaijan Province, Iran

被引：0
作者：
Azari P. [1 ]
Sobhanardakani S. [2 ]
Cheraghi M. [2 ]
Lorestani B. [2 ]
Goodarzi A. [3 ]
机构：
[1] Department of Environmental Engineering, College of Engineering, Hamedan Branch, Islamic Azad University, Hamedan
[2] Department of the Environment, College of Basic Sciences, Hamedan Branch, Islamic Azad University, Hamedan
[3] Department of Civil Engineering, College of Engineering, Hamedan Branch, Islamic Azad University, Hamedan
来源：
Environmental Science and Pollution Research | / 31卷 / 17期
关键词：
Dynamic programming; Fuzzy interval programming; Iran; Multi-objective optimization; Water resources allocation;
D O I：
10.1007/s11356-024-32919-5
中图分类号：
学科分类号：
摘要：
The allocation of water in areas which face shortage of water especially during hot dry seasons is of utmost importance. This is normally affected by various factors, the management of which takes a lot of time and energy with efforts falling infertile in many cases. In recent years, scholars have been trying to investigate the applicability of fuzzy interval optimization models in attempts to address the problem. However, a review of literature indicates that in applicating such models, the dynamic nature of the problem has mostly been overlooked. Therefore, the aim of the present study is to provide a fuzzy interval dynamic optimization model for the allocation of surface and groundwater resources under water shortage conditions in West Azerbaijan Province, Iran. In so doing, an optimization model for the allocation of water resources was designed and then was validated by removing surface and groundwater resources and analyzing its performance once these resources were removed. The model was then applied in the case study of ten regions in West Azerbaijan Province and the optimal allocation values and water supply percentages were determined for each region over 12 periods. The results showed that the increase in total demand has the greatest effect while the increase in groundwater industrial demand has the least effect on the supply reduction rate. The increase of uncertainty up to 50% in the fuzzy interval programming would lead to subsequent increases in groundwater extraction by up to 19% and decreases in water supply by up to 10%. The increase of uncertainty in the fuzzy interval dynamic model would cause an increase in groundwater extraction to slightly more than 10% and a decrease in water supply to 0.05%. Therefore, implementing the fuzzy interval dynamic programming model would result in better gains and would reduce uncertainty effects. This would imply that using a mathematical model can result in better gains and can provide better footings for more informed decisions by authorities for managing water resources. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
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页码：26217 / 26230
页数：13
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共 31 条
  • [11] Huang Z., Liu X., Sun S., Tang Y., Yuan X., Tang Q., Global assessment of future sectoral water scarcity under adaptive inner-basin water allocation measures, Sci Total Environ, 783, (2021)
  • [12] Jia W., Wei Z., Zhang L., A novel prediction and planning model for the benefit of irrigation water allocation based on deep learning and uncertain programming, Water, 14, 5, (2022)
  • [13] Kang A., Li J., Lei X., Ye M., Optimal allocation of water resources considering water quality and the absorbing pollution capacity of water, Water Res, 47, pp. 336-347, (2020)
  • [14] Karasu S., Altan A., Bekiros S., Ahmad W., A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time series, Energy, 212, (2020)
  • [15] Laszczyk M., Myszkowski P.B., Improved selection in evolutionary multi-objective optimization of multi-skill resource-constrained project scheduling problem, Inform Sci, 481, pp. 412-431, (2019)
  • [16] Li F., Zhang G., Hu S., An algorithm for optimal allocation of water resources in receiving areas based on adaptive decreasing inertia weights, J Adv Transport, 2022, (2022)
  • [17] Li Y., Han Y., Liu B., Li H., Du X., Wang Q., Wang X., Zhu X., Construction and application of a refined model for the optimal allocation of water resources—taking Guantao County China as an Example, Ecol Indic, 146, (2023)
  • [18] Liu W.Q., Sun Y.G., Gu S.H., He J.K., Game analysis for conflicts in water resource allocation, Syst Eng-Theory Pract, 1, pp. 16-25, (2022)
  • [19] Martinsen G., Liu S., Mo X., Bauer-Gottwein P., Joint optimization of water allocation and water quality management in Haihe River basin, Sci Total Environ, 654, pp. 72-84, (2019)
  • [20] Naghdi S., Bozorg-Haddad O., Khorsandi M., Chu X., Multi-objective optimization for allocation of surface water and groundwater resources, Sci Total Environ, 776, (2021)
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