Runoff Rainfall Simulation using RRL Toolkit(Case Study: Rahim Abad Station - Silakhor Plain)

Estimation of runoff from atmospheric rainfall has a special importance in hydrology studies, watershed management and soil science water conservation. In order to efficiently manage the watershed, the need to investigate the efficiency of hydrological models is more effective. The software package RRL is designed to simulate the runoff relationships of the basin and consists of five sub-conceptual models. In this study, conceptual models of AWBM, SACRAMENTO, SIMHYD, SMAR and TANK were used for Silakhor plain watershed (Rahim Abad station). The daily data of precipitation, evaporation and discharge were used in the statistical period of 1998 to 2018. For all conceptual models, from 1998 to 2000, as a balance period, from 2001 to 2013 as calibration and from 2014 to 2018, it was selected as the verification period. In the SIMHYD model, the Nash-Sutcliffe coefficient in the Multi Pattern Search Start method in the calibration and validation stages were 0.70 and 0.68, respectively, which indicates the relative ability of this model to simulate runoff among other models. In the TANK model, calibration and validation using Genetic Algorithm were 0.47 and 0.44, respectively, which had the lowest efficiency among the models. The results showed that in the different optimization methods, the Multi Pattern Search Start method provides better results.