Bias Correction of Hourly Satellite Precipitation Products and Their Application in Hydrological Modeling in a Hilly Watershed, China

Abstract

Correcting the bias of satellite precipitation products (SPPs) based on ground rainfall observations is one effective approach to improve their performance. To date, there have been limited efforts in correcting the bias of hourly SPPs with mixed results. In this study, ratio bias correction (RBC) and probability density matching (PDF) are used to correct the bias of four hourly SPPs (GSMaP_NRT, IMERG_E, IMERG_L, and IMERG) based on ground rainfall observations in a hilly watershed, China. Furthermore, SWAT (Soil and Water Assessment Tool) models are developed using ground rainfall observations, original SPPs, and bias-corrected SPPs to simulate the daily streamflow at the Yuetan Hydrological Station so as to comprehensively compare the performance of the two bias correction methods and evaluate the potentials of the four hourly SPPs in hydrological modeling applications. Our study results show that both RBC and PDF could improve the accuracy of hourly SPPs to various degrees, with PDF outperforming RBC considerably. After being corrected by PDF, the CC values of the four SPPs all reached 0.65. In addition, the SWAT models utilizing the PDF-corrected SPPs simulated the daily streamflow at the Yuetan Station better than those utilizing the RBC-corrected SPPs. Specifically, PDF-corrected IMERG_F performed the best among the four hourly SPPs, with a R2 of 0.89, NSE of 0.89, and RB of −8.14%. After bias correction, hourly satellite precipitation products can be well applied to hydrological modeling in the region.