Optimal Exploitation of Water Resources by Using New Multi-Objective Reptile Search Algorithm (MORSA)

In dry months, there are acute water shortages as a result of reservoir water being released to improve reliability based on the full supply of needs in certain months. This study provides a method that stores some water from rainy months in the reservoir to be released during dry months to reduce failure during those times. The method is based on reservoir zoning and uses a multi-objective optimization system. The multi-objective gray wolf optimization (MOGWO) and multi-objective reptile search algorithm (MORSA) are connected to the WEAP simulator model and contrasted for this purpose. The primary goal of this type of system is to propose a solution that raises the proportion of demand supplied during dry months while maintaining an acceptable level of demand supply reliability across the entire duration. Ultimately, the role curve is assessed using the outcomes of two scenarios: the OS and the RS (depending on the actual circumstances). The findings demonstrate that MORSA outperforms MOGWO in terms of response quality and convergence time. The RS results show that in many dry years, particularly the last planning years, the percentage of supply for demand in three to five consecutive months is equal to zero in most uses, and in the remaining low-water years, it is less than five percent in the same months. In the best-case scenario, the percentage of demand during these months ranges from 30 to 60% thanks to optimization of the dam's rule curve using MORSA. Furthermore, in low-water months, the OS increases the proportion of meeting downstream environmental obligations. This study demonstrates that applying this strategy results in appropriate reservoir management and lessens the degree of failure when providing different uses during low-water months.