Groundwater resources are the only source of water in many arid and semi-arid regions. It is important to manage these resources to have a sustainable development. However, there are many factors influencing the accuracy of the results in groundwater modeling. In this research, the uncertainty of two important groundwater model parameters (hydraulic conductivity and specific yield) were considered as the main sources of uncertainty in estimating water level in an unconfined aquifer, in Iran. For this purpose, a simple method called Rosenblueth Point Estimate Method (RPEM) was used to assess groundwater modeling parametric uncertainty, and its performance was compared with Monte Carlo method as a very complicated and time-consuming method. According to calibrated values of hydraulic conductivity and specific yield, several uncertainty intervals were considered to analyze uncertainty. The results showed that the optimum interval for hydraulic conductivity was 40% increase–30% decrease of the calibrated values in both Monte Carlo and RPEM methods. This interval for specific yield was 200% increase–90% decrease of the calibrated values. RPEM showed better performance using the evaluating indices in comparison with Monte Carlo method for both hydraulic conductivity and specific yield with 43% and 17% higher index values, respectively. These results can be used in groundwater management and future prediction of groundwater level.

中文翻译：

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使用蒙特卡罗方法和 RPEM 对地下水数值模型中的水动力系数进行参数不确定性分析

在许多干旱和半干旱地区，地下水资源是唯一的水源。管理这些资源以实现可持续发展非常重要。然而，影响地下水模拟结果准确性的因素很多。在这项研究中，两个重要的地下水模型参数（水力传导率和比产量）的不确定性被认为是估算伊朗非承压含水层水位的主要不确定性来源。为此，使用一种称为 Rosenblueth Point Estimate Method (RPEM) 的简单方法来评估地下水建模参数不确定性，并将其性能与作为非常复杂且耗时的蒙特卡罗方法进行比较。根据水力传导率和比产量的标定值，考虑了几个不确定性区间来分析不确定性。结果表明，在蒙特卡罗和 RPEM 方法中，水力传导率的最佳区间是校准值增加 40% - 减少 30%。特定产量的这个区间是校准值的 200% 增加 - 90% 减少。与蒙特卡罗方法相比，RPEM 使用评估指数表现出更好的性能，分别提高了 43% 和 17% 的指数值。这些结果可用于地下水管理和地下水位的未来预测。特定产量的这个区间是校准值的 200% 增加 - 90% 减少。与蒙特卡罗方法相比，RPEM 使用评估指数表现出更好的性能，分别提高了 43% 和 17% 的指数值。这些结果可用于地下水管理和地下水位的未来预测。特定产量的这个区间是校准值的 200% 增加 - 90% 减少。与蒙特卡罗方法相比，RPEM 使用评估指数表现出更好的性能，分别提高了 43% 和 17% 的指数值。这些结果可用于地下水管理和地下水位的未来预测。