Determining the optimized policies in the exploitation of groundwater water resources is a complicated issue, especially when there are several different managers with conflicting goals. The current study presents a new multi-purpose method to reach a compromise among different stakeholders by determining optimal social policies and sustainable hydro-environmental management of underground water resources. This method simultaneously considers qualitative and quantitative simulation and optimization, stakeholders’ preferences, and uncertainty analysis. In this study, the recharge was determined and incorporated in MODFLOW groundwater current model and MT3DMS pollution transfer model by using the hydrological model SWAT. In addition, DREAM (zs) algorithm (derived from algorithms based on Markov chain Monte Carlo) was used to examine the uncertainty of MODFLOW model parameters. The optimal head and TDS rate were determined in the studied aquifer by linking the model with MOPSO. Then, the Pareto frontier derived from the previous step, was utilized to determine the allocation rate of groundwater resources among a set of non-dominated solutions using Social Choice Rules (SCR) including Condorcet, Median Voting Rule (MVR), and Fallback Bargaining (FB) including unanimity fallback bargaining and fallback bargaining with impasse. The results showed that almost all the selected methods of conflict resolution in this research behaved similarly, and their results were not significantly different from each other. However, the comparison of these methods indicated that the MVR with the minimum reduction in withdrawal discharge and the maximum elevation in response to optimal allocation policies had the best performance. The amount of water extracted from the study area is about 540 million m³/year, which reaches 395 million m³/year.

在开发地下水水资源方面确定最佳政策是一个复杂的问题，尤其是当有几个目标不同的管理者时。当前的研究提出了一种新的多用途方法，通过确定最佳的社会政策和地下水资源的可持续水环境管理，在不同利益相关者之间达成折衷。该方法同时考虑了定性和定量的模拟和优化，利益相关者的偏好以及不确定性分析。在这项研究中，确定补给量，并使用水文模型SWAT将其纳入MODFLOW地下水流模型和MT3DMS污染转移模型中。此外，DREAM（zs）算法（源自基于马尔可夫链蒙特卡罗的算法）用于检验MODFLOW模型参数的不确定性。通过将模型与MOPSO链接，在研究的含水层中确定了最佳水头和TDS速率。然后，利用社交选择规则（SCR）包括Condorcet，中值投票规则（MVR）和后备议价协议（SCR），从上一步得出的帕累托边界用于确定一组非主导解决方案中的地下水资源分配率。 FB）包括一致的后备谈判和具有僵局的后备谈判。结果表明，在本研究中，几乎所有选择的解决冲突的方法都表现出相似的效果，并且它们的结果之间没有显着差异。然而，这些方法的比较表明，MVR在最佳分配策略的响应下，出水流量的最小减少和最大抬高是最佳的。从研究区域提取的水量约为5.4亿米³ /年，达到3.95亿m ³ /年。