Enhancing reservoir operations with charged system search (CSS) algorithm: Accounting for sediment accumulation and multiple scenarios

Optimizing reservoir operation is a complex problem with non-linearities, numerous decision variables, and challenging constraints to simulate and solve. Researchers have tested various metaheuristics algorithms (MHAs) to reduce water deficit in reservoirs and presented them to decision-makers for adoption. Optimization methods vary depending on objectives, reservoir type, and algorithms used. The paper utilizes the CSS algorithm to study the impact of various scenarios on the optimal operation of the Mujib reservoir in Jordan to reduce water deficits using historical date between 2004 and 2019. The study explores different scenarios, including sediment impact, water demand management, and increasing the storage volume for the reservoir, to identify the optimal operation of the reservoir. The study compares the results of these scenarios with the current operation of the reservoir. Risk analysis (volumetric reliability, shortage index (SI), resilience, vulnerability) and error indexes (correlation coefficient R2, the root mean square error (RMSE), and the mean absolute error (MAE)) were used to compare results between scenarios, in addition to the annual water deficit values from the CSS algorithm for each scenario. The simulation of monthly sediment values in the Mujib reservoir showed that sediment accumulation accounts for 14.6% of the reservoir's volume at the end of 2019. Removing sediments retained by the dam can reduce water deficit by 19.42% when using the CSS algorithm. Additionally, reducing agricultural water demand by 11% and removing sediment reduced water deficit by 42.40%. The study also examined the impact of increasing the storage capacity of the reservoir by 10%, 20%, and 30%, revealing a decrease in water deficit by 35.44% when sediment removal was included in the analysis. The study examined the scenario of increasing the storage capacity of the Mujib reservoir by 30%, reducing water demand by 11%, and removing sediment. This scenario resulted in a 53.59% decrease in water deficit, providing decision-makers with viable solutions to address the water deficit problem in the reservoir.