Automatic Calibration of Hydrologic Event-Based Model Using PSO Meta-Heuristic Algorithm

Document Type : Research Article



The conceptual hydrologic HEC-HMS model that includes a library of different event-based models for simulating rainfall-runoff process has been gained a significant attention in different applications. Automatic calibration of HMS model has been considered in this study using particle swarm optimization (PSO) algorithm and its application has been assessed in modeling Tamar basin in North of IRAN. The PSO algorithm has been coded in MATLAB where the HMS model is called and run from through transferring to DOS applications. Firstly, Model calibration is performed in single event scenarios and the results were compared with Nelder and Mead local search algorithm method built in HMS model. The results revealed the outperformance of the proposed PSO-HMS model. Since no unique parameter set was obtained in single event scenarios, the model was employed to calibrate three calibration events jointly. Then all candidate parameter sets obtained from single and jointly-event calibration scenarios were tested in verification stage in which parameters of initial abstraction coefficients were recalibrated. The procedure resulted in choosing more suitable parameter sets to be screened out, although no unique parameter set can be obtained. 


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