Abstract：
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.
摘要：
在面临缺水的地区，特别是在炎热干燥的季节，水的分配至关重要。这通常会受到各种因素的影响，在许多情况下，管理需要大量的时间和精力，努力使其不育。近年来,学者们一直试图研究模糊区间优化模型的适用性，试图解决这个问题。然而,文献综述表明，在应用这些模型时，问题的动态性大多被忽视了。因此,本研究的目的是为西阿塞拜疆省缺水条件下的地表水和地下水资源配置提供模糊区间动态优化模型，伊朗。这样做,设计了水资源配置的优化模型，然后通过去除地表水和地下水资源并分析其在去除这些资源后的性能进行了验证。然后将该模型应用于西阿塞拜疆省十个地区的案例研究中，并在12个时期内确定了每个地区的最佳分配值和供水百分比。结果表明，总需求的增加对供应减少率的影响最大，而地下水工业需求的增加对供应减少率的影响最小。模糊区间规划中不确定性的增加高达50％，将导致随后的地下水开采量增加高达19％，供水量减少高达10％。模糊区间动态模型不确定性的增加会导致地下水开采量增加到略高于10%，供水量减少到0.05%。因此,实现模糊区间动态规划模型将获得更好的收益，并减少不确定性影响。这意味着使用数学模型可以带来更好的收益，并可以为当局管理水资源的更明智的决定提供更好的基础。
