A regret-based behavioral model for shared water resources management: Application of the correlated equilibrium concept.

The competition over water use in shared water resources systems may lead to conflict. Conflict can lead to strategic behaviors with the consequence of "Tragedy of Common" in water resources. In this paper, a novel approach is proposed for the quantity and quality management of shared water resources using the Correlated Equilibrium (CE) concept. For the first time in water resources management studies, a Reinforcement Learning (RL)-based method, namely Regret Matching (RM), is proposed to simulate agents' behaviors. In the proposed methodology, an agent, which is responsible for water allocations, tries to reduce illegal water withdrawal from resources, using some non-mandatory and mandatory suggestions. This agent's objectives are leading the system towards social optimality (SO) and reaching the environmental sustainability goal. A modified RM algorithm is also developed for behavioral simulation in urban areas. The proposed methodology's applicability and efficiency are evaluated considering some criteria such as the concentration of the nitrate pollutant in groundwater, the groundwater table fluctuations, the rate of illegal water extraction from the groundwater, and the stakeholders' general satisfaction. The results of applying the methodology to the western part of the Tehran metropolitan area show its ability to deal with the water and treated wastewater allocation problems in urban areas and increase in the learning and cooperation among agents. According to the results, a meaningful decrease in nitrate concentration in the aquifer and an increase in groundwater table levels are observed. The results also indicate that the model could teach the stakeholders to act more responsibly towards protecting the environment and conserving shared water resources.