In theory, emergence of robustness concept has pushed decision-makers toward designing alternatives, such as resistant against the potential fluctuations fueled by uncertain surrounding environment. This study promotes an objective-based multi-attributes decision-making framework that takes into account the uncertainties associated with the impacts of the climate change on water resources systems. To capture the uncertainties of climate change, Monte Carlo approach has been used to generate a series of ensembles. These generated ensembles represent the stochastic behavior of the hydro-climatic variables under climate change. This framework represents the inherent uncertainties associated with hydro-climatic simulations. Next, a coupled TOPSIS/Entropy multi-attribute decision-making framework has been formed to prioritize the feasible alternatives using system performance measures. The main objective of this framework is to minimize the risk of deceptive and subjective assessments during decision-making process. Karkheh River basin has been selected as a case study to demonstrate the implication of this framework. Using a set of system performance attributes, the performance of two hydropower systems has been estimated during the baseline period and under the future climate change conditions. According to the conducted frequency analysis, the alternative in which both hydropower projects would go under construction emerged as the robust solution (i.e., there was a 99.9% chance that it outperforms other solutions). The results indicate that the construction of these hydropower systems leads to the increase of Karkheh River basin robustness in the future.

从理论上讲，健壮性概念的出现促使决策者设计替代方案，例如抵抗由不确定的周围环境引发的潜在波动。这项研究促进了一个基于目标的多属性决策框架，该框架考虑了与气候变化对水资源系统的影响相关的不确定性。为了捕捉气候变化的不确定性，蒙特卡罗方法已用于生成一系列合奏。这些生成的合奏代表了气候变化下水文气候变量的随机行为。该框架表示与水文气候模拟相关的固有不确定性。下一个，已经形成了一个耦合的TOPSIS /熵多属性决策框架，以利用系统性能度量对可行的替代方案进行优先排序。该框架的主要目标是在决策过程中最大程度地降低进行欺骗性和主观评估的风险。选择了卡赫河流域作为案例研究，以证明该框架的含义。使用一组系统性能属性，已在基准期间和未来气候变化条件下估算了两个水电系统的性能。根据进行的频率分析，两个水电项目都将在建设中的替代方案作为可靠的解决方案出现了（即，有99.9％的机会胜过其他解决方案）。