mathematical model for auto-calibration of area-reduction method in sediment distribution of dam reservoir using genetic algorithm

abstract area-reduction method is one of the most common experimental methods that determines the sediment distribution in reservoirs. in this method, reservoirs are geometrically divided into four types. for all reservoir types, parameters are achieved based on a limited number of reservoirs which leads to large scale errors for prediction of this method. so suitable parameters can be achieved in dams that are in operation and hydrography of reservoir is carried out at least once. in other words the method can be calibrated for the reservoir. in this study initially a computer model based on the area-reduction method was provided using matlab software. then optimization model was prepared using genetic algorithm and these two models were combined, finally. the above mentioned model determines area-reduction method parameters, so that the most compatibility occurs between computational and measured values. for calibration and verification of the model at least three measured data are required. due to lack of enough hydrographic data in iranian dams, first the model was applied for altus dam in usa with three hydrographic data. results showed that there was a significant increase in accuracy of estimation, using optimal parameters. finally optimal parameters were achieved using this model for karde dam that had only two hydrographic data available. then based on optimal parameters sediment distribution of karde dam was predicted for next years.