The Application of Imperialist Competitive Algorithm in Determining the Optimal Parameters of Empirical Area Reduction Method to Predict the Sedimentation Process in Dez Dam

Sedimentation in reservoir of dams, especially in sediment transport susceptible areas, leads to the reduction of reservoir capacity, disruption in flood control and spillway performance, reduction of hydropower generation and reservoir water quality. The area reduction method is one of the most common methods to estimate sediment distribution in reservoirs. The parameters of this method are based on the data of a limited number of dams in America. The results of applying these parameters to estimate the distribution of reservoirs sediment in the other dams, will not be correct. Therefore, the present study aims to extract the optimal parameters of the area reduction method using imperialist competitive algorithm to achieve the accurate prediction of sediment distribution and compare it with the results of reservoir hydrography. First, combining this algorithm with the area reduction method in MATLAB, the optimal values of the three parameters m, n, and c were obtained in the general equation of the reservoir type. Finally, the model was updated based on the optimal parameters of the surface area reduction method. Then, by introducing new reservoir hydrography data in the optimal model, the sedimentation trend was predicted in the feature years (1410 and 1420). The results showed that this method was more consistent with the actual volume of the reservoir at different levels of the dams rather than the methods of Borland and Miller and Lara. According to the results, in the years mentioned, about 26 and 36 percent of the active capacity of the reservoir will be reduced respectively. Based on the satisfactory results of this research, regarding the combination of optimization method with area reduction method, it is suggested to use this model as a useful method in other important and strategic dams in the country in which the reservoir hydrography carried out. In this case, by understanding distribution and prediction of sediment amount, it is possible to utilize the reservoir operation policies to decide with higher reliability on the problems caused by sediments.