Optimal Operation of Dam Reservoir Using Gray Wolf Optimizer Algorithm (Case Study: Urmia Shaharchay Dam in Iran)

Abstract

Reservoir storage prediction is so crucial for water resources planning and managing water resources, drought risk management and flood predicting throughout the world. In this study, Gray Wolf Optimizer algorithm (GWO) was applied to predict Shaharchay dam reservoir storage of located in the Urmia Lake basin, northwest of Iran. The results of the GWO algorithm have been compared with the continuous genetic algorithm (CGA). The predicted values from the GWO algorithm matched the measured values very well. According to the results, the error is not significant (2.11%) in the implementation of the GWO and the correlation coefficient between the predicted and measured values is 0.92. In addition, the statistical criteria of RMSE, MAE and NSE for GWO algorithm were estimated to be 0.03, 0.41 and 0.74, respectively, indicated a satisfactory performance. Excessive value of correlation coefficient expresses that the GWO algorithm pretty suit the variables and may finally be used for predicting of reservoir storage for operational overall performance. Comparison of results showed that the GWO algorithm with average best objective function value of 121, 112 and 83.10 with a number of further evaluations of the objective function to achieve higher capacity is the optimum answer.