| Abstract: | Precipitation is a significant input variable required in hydrological models such as the Soil
&Water Assessment Tool (SWAT). The utilization of inaccurate precipitation data can result in the
poor representation of the true hydrologic conditions of a catchment. SWAT utilizes the conventional
nearest neighbor method in assigning weather parameters for each subbasin; a method inaccurate
in representing spatial variations in precipitation over a large area, with sparse network of gauging
stations. Therefore, this study aims to improve the spatial variation in precipitation data to improve
daily streamflow simulation with SWAT, even pre-model calibration. The daily streamflow based on
four interpolation methods, nearest neighbor (default), inverse-distance-weight, radial-basis function,
and ordinary kriging, were evaluated to determine which interpolation method is best represents
the precipitation at Yongdam watershed. Based on the results of this study, the application of spatial
interpolation methods generally improved the performance of SWAT to simulate daily streamflow
even pre-model calibration. In addition, no universal method can accurately represent the longterm
spatial variation of precipitation at the Yongdam watershed. Instead, it was observed that the
optimal selection of interpolation method at the Yongdam watershed is dependent on the long-term
climatological conditions of the watershed. It was also observed that each interpolation method was
optimal based on certain meteorological conditions at Yongdam watershed: nearest neighbor for
cases when the occurrence probability of extreme precipitation is high during wet to moderately
wet conditions; radial-basis function for cases when the number of dry days were high, during wet,
severely dry, and extremely dry conditions; and ordinary kriging or inverse-weight-distance method
for dry to moderately dry conditions. The methodology applied in this study improved the daily
streamflow simulations at Yongdam watershed, even pre-model calibration of SWAT. |