Integrating the Sacramento Conceptual Rainfall-Runoff Model and Reanalyzed Datasets for Runoff Simulation

Accurate estimation of runoff plays an important role in water resources and hydrological studies. Due to simple structure and minimum data requirements, the conceptual hydrologic models are the best way to estimate runoff. The main objective of this study is to investigate the performance of Sacramento model in runoff simulation and determining the best reanalyzed evapotranspiration dataset for using in the model. In this study, four different datasets including HBV, ORCHIDEE, PCR-GLOBW, WATERGAP3 and W3RA are used in Sacramento model. Also, for estimation of basin-averaged rainfall time seri, the Thiessen method was used based on ground gage observations. Results indicate that using most of the reanalyzed datasets in Sacramento model lead to reliable outputs and the performance of model in simulation of daily stream flow is relatively high. However, the performance of model in the case of using W3RA and WATERGAP3 is better than the other data sources, and in both calibration and verification phases the Nash-Sutcliffe efficiency (NSE) is higher than 0.60 and 0.87, respectively. Moreover, findings show that the W3RA dataset is the best one for estimation of runoff volume, high flows (peak floods) and the time to peak flows. Overall, based on the outputs of this research, the reanalyzed datasets can be considered as an alternative or complementary in data-limited regions for water resources and hydrological studies.