The effects of soil data sources on the performance of hydrologic model simulations remain poorly understood compared to the effects of other data inputs. This paper investigated the effects of different soil datasets in simulating streamflow and sediment yield using the Soil and Water Assessment Tool (SWAT). Furthermore, potential improvements in watershed simulations were evaluated by integrating field measured soil parameters (user soil) with global soil datasets. Five soil datasets, namely user soil, AfSIS (Africa Soil Information Service), Food and Agriculture Organization (FAO), and two integrated soils (User-AfSIS and User-FAO) produced by assimilating the user soil with the latter two, were evaluated. The benefits of the user soil in improving streamflow simulations to better replicate observed flow were greater at daily time steps than monthly. Compared to the individual AfSIS and FAO soils, their integration with the user soil improved the daily Nash-Sutcliffe Efficiency (NSE) by 0.19 and 0.17 during model calibration, respectively. Overall, all soils performed relatively similar with monthly sediment yield simulations, which were improved when it was integrated with the user soil. Based on selected rainfall events, the watershed response time was less than 1 h, which suggests that the watershed has a quick runoff response time. This paper showed that streamflow and sediment yield simulation performances of freely available global soil datasets can be improved through integration with locally measured soil information. This study demonstrated that the availability of local soil information is critical for daily hydrologic model simulations, which is critical for planning effective soil and water management practices at plot and field scales.
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