Assessing the Effects of Spatial Interpolation of Rainfall on the Streamflow Response

Abstract

Precipitation within a river basin varies spatially and temporally and hence, is the most relevant input for hydrologic modelling. Various interpolation methods exist to distribute rainfall spatially within a basin. The sparse distribution of raingauge stations within a river basin and the differences in interpolation methods can potentially impact the streamflow simulated using a hydrologic model. The present study focuses on assessing the effect of spatial interpolation of rainfall using Theissen polygon, Inverse distance weighted (IDW) method and Ordinary Kriging on the streamflow simulated using a physically based spatially distributed model-SHETRAN in Vamanapuram river basin in Southern Kerala, India. The SHETRAN model in the present study utilises rainfall data from the available rain gauge stations within the basin and potential evapo-transpiration calculated using Penman-Monteith method, along with other input parameters like soil and landuse. Four years of rainfall and evapo-transpiration data on a daily scale is used for model calibration and one year data for validation. The performance of the different spatial interpolation methods were assessed based on the Mean Annual flow and statistical parameters like NashSutcliffe Efficiency, coefficient of determination. The ordinary kriging and IDW methods were found to be satisfactory in the spatial interpolation of rainfall. .