application of the genetic algorithm technique for optimization of the hydrologic tank and simhhyd models’ parameters

in the past decades, much effort has been devoted to simulation of the rainfall-runoff process. hydrological models are simplified representations of the natural hydrologic system. in each case, the choice of the model to be applied depends mainly on the objective of the modeling but also on the available information. the relative performances of two lumped conceptual-based hydrology models (tank and symhyd) were compared based on daily data of chehel_chay catchment in the northeast region of golestan province. as in tank and simhyd models, parameter spaces are high dimensional, it is difficult to obtain optimal parameters using manual trial and error procedure. these parameters need to be estimated through an inverse method by calibration. therefore, an automatic optimization procedure based on the genetic algorithm (ga) was tested for parameter calibration of two models. for testing the applicability of the model in gauged basin, the model was calibrated for a period of 1992–1996 and validated for a period of 2002–2005. the result showed that rmse of discharge predictions were as low as 0.821 for a nash-sutcliffe coefficient of 0.599 for the tank model, against 0.819 for a nash-sutcliffe coefficient of 0.602 for the symhyd model in calibration period. when evaluating the model performance in validation period, symhyd model is performing most accurately with rmse=0.490 and e=0617. it was found the rmse for tank model is 0.522, which is slightly higher than simhyd (rmse=0.490). simhyd is performing most accurately with e equal to 0.602 and 0.607 in calibration and validation periods, respectively.