A multi-agent decision-making framework for evaluating water and environmental resources management scenarios under climate change

This paper introduces a hierarchical multi-agent decision-making framework for Water and Environmental Resources Management Scenarios (WERMSs) under uncertain conditions of climate change and complex agent characteristics. The proposed framework utilizes three Game Theory concepts: the Stackelberg, Bayesian (Incomplete), and Imperfect games, in order to incorporate the hierarchical structure of the agents and the temporal distribution and accuracy of information between them. The methodology is applied to the Zarrinehroud River Basin (ZRB), the largest hypersaline lake in the Middle East. The area of the lake has decreased dramatically (about 50 %) during past decades causing var-ious environmental, social, and economic problems. WERMSs were evaluated using qualitative and quantitative hy-drological, social, economic, and ecological criteria under different climate change scenarios. The proposed methodology provides equilibriums in the decision-making process while considering different climate change scenar-ios. Applying the selected WERM results in an accumulated value of 2995 million m3 of water flow to the lake until 2049. Moreover, the lake's elevation reaches a new level of 1272.6 m above sea level at the end of the following 30 years, compared to the elevation of 1271.3 at the beginning of the evaluation period.

Automated summary

This paper introduces a hierarchical multi-agent decision-making framework for managing water and environmental resources under uncertain conditions. The framework incorporates the hierarchical structure of the agents and the distribution and accuracy of information using three Game Theory concepts. It is applied to the Zarrinehroud River Basin to address the decreasing size of the largest hypersaline lake in the Middle East. The proposed methodology provides equilibriums in decision-making process and evaluates the effects of different climate change scenarios.