Comparing PSO Algorithm Automatic Calibration and Nelder&Mead Algorithm on the HEC-HMS Hydrologic Model (Case Study: Kardeh Watershed)

Due to the time consuming manual calibration data, especially in low and high parameters automatic calibration methods based on the use of systematic search methods in multi-dimensional space using an objective function is very useful. In this study, the simulation model HEC-HMS and collective intelligence algorithms, PSO as an optimization model act. The integrated model proposed dam basin has been studied Kardh. Model calibration was performed using the objective function NASH and RMSE resulting parameters were used to those achieve. To evaluate the ability of the PSO algorithm to achieve the optimal solution, a single calibration approach results occurred with semi-automatic calibration results based on Nelder & Mead search algorithm in HEC-HMS PBIAS and RMSE were compared by functions that PSO algorithm represents the connection to a hydrological model. The results show that both the objective function values obtained in the semi-automatic model is considerably higher than the model introduced. Also simulated hydrographs obtained from PSO-HMS model is much better. Finally, those parameters were determined from single approach occurred in the event verification. The results showed that the method according to the solution of the calibration problem of Ghyrmnfrd an inverse problem can be effective in limiting the number of candidate solutions.