Evaluation of reanalysis and satellite-based precipitation datasets in driving hydrological models in a humid region of Southern China

This paper compares the original and bias corrected global gridded precipitation datasets, tropical rainfall measuring mission (TRMM) and water and global change forcing data (WFD) with gauged precipitation and evaluates the usefulness of gridded precipitation datasets for hydrological simulations using the distributed soil and water assessment tool (SWAT) and lumped Xinanjiang model in Xiangjiang River basin, Southern China. The results show that the differences in areal mean rainfalls of original TRMM and WFD datasets and gauged dataset are in acceptable limits of less than 10 %, while larger differences exist in maximal 5-day rainfalls, dry spells and Frechet distance. The bias correction methods are able to significantly improve the biases in the mean values of TRMM and WFD datasets. The nonlinear bias correction method gives good results in correcting the standard deviations of TRMM/WFD data. The hydrological modelling results show that the WFD datasets perform relatively better than TRMM datasets even though the results are poor as compared with using gauged rainfall as input in daily step hydrological models. At monthly time step, both TRMM and WFD data produce acceptable model simulation results in terms of Nash–Sutcliffe efficiency (E ns > 0.7 for original TRMM/WFD data and E ns > 0.8 for linearly corrected TRMM/WFD data) and relative error (|R E | < 10 %).