Optimal reservoir operation using Nash bargaining solution and evolutionary algorithms

Optimizing reservoir operation is critical to ongoing sustainable water resources management. However, different stakeholders in reservoir management often have different interests and resource competition may provoke conflicts. Resource competition warrants the use of bargaining solution approaches to develop an optimal operational scheme. In this study, the Nash bargaining solution method was used to formulate an objective function for water allocation in a reservoir. Additionally, the genetic and ant colony optimization algorithms were used to achieve optimal solutions of the objective function. The Mahabad Dam in West Azerbaijan, Iran, was used as a case study site due to its complex water allocation requirements for multiple stakeholders, including agricultural, domestic, industrial, and environmental sectors. The relative weights of different sectors in the objective function were determined using a discrete kernel based on the priorities stipulated by the government (the Lake Urmia National Restoration Program). According to the policies for the agricultural sector, water allocation optimization for different sectors was carried out using three scenarios: (1) the current situation, (2) optimization of the cultivation pattern, and (3) changes to the irrigation system. The results showed that the objective function and the Nash bargaining solution method led to a water utility for all stakeholders of 98%. Furthermore, the two optimization algorithms were used to achieve the global optimal solution of the objective function, and reduced the failure of the domestic sector by 10% while meeting the required objective in water-limited periods. As the conflicts among stakeholders may become more common with a changing climate and an increase in water demand, these results have implications for reservoir operation and associated policies.