swarm intelligence algorithms of pso

Structural constraints of hydrological models and a lack of access to all the parameters of watershed along with an impossibility of determining the boundary and initial conditions, necessitates the need for calibration of hydrological models. As manual calibration is tedious, especially in the face of limited data and plenty of parameters, automatic calibration methods, employing a systematic search in a multidementional space, could be in finding suitable parameter sets through at least one objective function. Throughout the present work HEC-HMS acts as the simulation model and PSO as the optimization one. The HEC-HMS programming was done through MATLAB. The proposed integrated model was implemented for Kardeh dam basin in Khorasan Razavi province. The Model calibrated through RMSE objective function in three-event different scenarios led to the bunch of different parameters. All scenarios were validated and a comparison of objective function values as well as correlation coefficient between the observed and simulated discharge done. Results indicated three sets of solutions as an optimal solution, which emphasized the impossibility of obtaining unique parameters for a river basin. This method of solution, because of non-unique solution for calibration, would be helpful as an inverse problem which can limit the number of candidate answers.