Applicability of TRMM satellite precipitation in driving hydrological model for identifying flood events: a case study in the Xiangjiang River Basin, China

Floods are one of the most hazardous types of natural disaster and cause huge losses and casualties every year. A good understanding of extreme stream flows is important for identifying potential flood events and thereby achieving the goals of disaster monitoring and risk management. Remote sensing precipitation data with high spatial–temporal resolution have been shown to be a potential alternative to ground-gauged data, which is sparse or unavailable in many locations. The objective of this study is to evaluate the applicability of satellite-based precipitation data (TRMM 3B42V7) in driving the HEC-HMS hydrological model for flood monitoring in humid Xiangjiang River Basin in China. The results indicate that the TRMM precipitation data can be applied to identify flood events with hydrological model despite biases in the time and magnitude of flood peaks compared to those derived from historical records. In addition, the hydrological model is shown to have smoothing effects on the propagation of biases or errors in the TRMM precipitation data in the hydrological simulations. However, for a few extreme storm events, the data produced relatively large overestimations in precipitation volume and biases in the precipitation time, which caused overestimations in the streamflow simulations and deviation in the peak time, and should be regarded with caution.