• 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.
 
 
 
Extended Abstract
1-Introduction
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 the sediment distribution and correction of the height–area–volume curves of reservoirs. The parameters of this method have a direct impact on the sediment distribution over time which should be corrected based on the physical and hydraulic properties of each dam. Therefore, the present study aims to investigate the efficiency of imperialist competitive algorithm in extracting optimal parameters of area reduction method and prediction of sedimentation process using this method. So that, it minimizes the difference between the amount of reservoir sedimentation in the area reduction method and the results of reservoir hydrograph at the end of period.
2-Materials and Methods
The research area of this study is Dez Dam reservoir. Dez dam is located on the Dez River at 23 km northeast of Andimeshk. Area reduction empirical method was used to predict the sedimentation process in the reservoir. This mathematical method is based on observational principles using reservoir type equations and a dynamic solving method to extract height–area–volume curves whose parameters need to be estimated accurately. As a result, combining the imperialist competitive algorithm with the area reduction method in MATLAB, optimal values of the three parameters m, n, and c were obtained in general relation of the reservoir type. Then, the results of this method and the methods of Borland and Miller (1958) and Lara (1962) were compared with the reservoir hydrography data. 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).
3-Results and Discussion
The results showed that the application of imperialist competitive algorithm for the extraction of optimal parameters of the area reduction method would lead to a greater correlation between estimated and actual volumes of the reservoir (reservoir hydrography in 2010) at different levels compared with methods of the Borland, Miller and Lara. So that the total calculation errors in estimating of reservoir volume at different levels in these methods was 0.25, 14.7 and 17 (percent)  respectively. Finally, by applying the optimal parameters of imperialist competitive algorithm in the area reduction method, the height–area–volume curves of the reservoir were predicted for the years of 1410 and 1420 that showed a reduction of the reservoir active capacity about 709 and 972 million cubic meters in these years. Given the need of water supply for 125,000 hectare downstream dam lands in these years, this situation will create a major challenge for water resource specialists in the region.
4-Conclusion
With passing of time and sediment accumulation behind the reservoir, the useful volume and useful life of the reservoir are reduced and the volume-level-height curves need to be corrected. Common methods for correcting these curves after reservoir sedimentation have been developed based on the conditions and statistics and information recorded in reservoirs abroad. The use of the same methods for country interior dams without optimizing the coefficients have problems and sometimes full of errors. Therefore, calibration of area reduction method and extracting optimal parameters of this method have a special importance in predicting the sedimentation process in reservoirs, which greatly reduces the predictive error. In this regard, the use of imperialist competitive algorithm for optimization has dramatic results. So, considering the satisfactory results of this study regarding the combination of the optimization method with area reduction method, it is recommended this model be used in other important and strategic dams of the country where the reservoir hydrography is carried out.