Rainwater-harvesting (RWH) agriculture has been accepted as an effective approach to easing the overexploitation of groundwater and the associated socioeconomic impacts in arid and semiarid areas. However, the stability and reliability of the traditional methods for selecting optimal sites for RWH agriculture need to be further enhanced. Based on a case study in Tehran Province, Iran, this study proposed a new decision support system (DSS) that incorporates the Best-Worst Method (BWM) and Fuzzy logic into a geographic information system (GIS) environment. The probabilistic analysis of the rainfall pattern using Monte Carlo simulation was conducted and adopted in the DSS. The results have been demonstrated using suitability maps based on three types of RWH systems, i.e., pans and ponds, percolation tanks, and check dams. Compared with traditional methods, the sensitivity analysis has verified that the proposed DSS is more stable and reliable than the traditional methods. Based on the results, a phase-wise strategy that shifts the current unsustainable agriculture to a new paradigm based on RWH agriculture has been discussed. Therefore, this DSS has enhanced the information value and thus can be accepted as a useful tool to ease the dilemma resulting from unsustainable agriculture in arid and semiarid areas.

中文翻译：

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在基于 GIS 的决策支持系统中使用最佳最差方法和模糊逻辑确定伊朗雨水收集农业计划的最佳地点

雨水收集 (RWH) 农业已被公认为缓解干旱和半干旱地区地下水过度开发及其相关社会经济影响的有效方法。然而，传统的RWH农业选址方法的稳定性和可靠性有待进一步提高。本研究基于伊朗德黑兰省的案例研究，提出了一种新的决策支持系统 (DSS)，该系统将最佳-最差方法 (BWM) 和模糊逻辑结合到地理信息系统 (GIS) 环境中。在 DSS 中进行并采用了使用蒙特卡罗模拟的降雨模式的概率分析。已使用基于三种类型的 RWH 系统的适宜性地图证明了结果，即盘和池塘、渗滤池和检查坝。与传统方法相比，敏感性分析验证了所提出的DSS比传统方法更稳定可靠。基于结果，讨论了将当前不可持续的农业转变为基于 RWH 农业的新范式的分阶段策略。因此，该DSS增强了信息价值，因此可以作为缓解干旱和半干旱地区农业不可持续发展困境的有用工具。