Streamflow simulations using error correction ensembles of satellite rainfall products over the Huaihe river basin

This study aims to investigate the hydrologic applicability of an error correction method - SREM2D (two-dimensional stochastic satellite rainfall error model) to three satellite precipitation products in streamflow simulations. Three satellite precipitation products, including the Tropical Rainfall Measuring Mission (TRMM) Multiple-Satellite Precipitation Analysis (TMPA) real-time 3B42 product (3B42RT), the Climate Prediction Centre (CPC) morphing technique (CMORPH) gauge merged product (CMORPH BLD), and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network - Climate Data Record (PERSIANN CDR), are corrected using SREM2D. Over the upper Huaihe river basin, streamflow ensemble simulations are derived by forcing the distributed Variable Infiltration Capacity (VIC) model with the SREM2D-based rainfall ensemble. After applying SREM2D to satellite precipitation products, the streamflow simulations forced by TMPA 3B42RT and PERSIANN CDR rainfall ensembles are capable to capture flood peaks. However, the streamflow simulations forced by CMORPH BLD rainfall ensemble show poor performance for the extreme events, but exhibit good accuracy in non-flood flow simulation. The calibration of the model over the headwater subbasin betters the streamflow simulation, especially for reproducing extreme events during the main flood cases. Overall, SREM2D provides great potential to facilitate the application of satellite precipitation products in water management and decision making over Chinese river basins.