Study on the large scale hydrologic simulation using multi-satellite precipitation

High-quality rainfall information is critical for accurate simulation of runoff and the water cycle process on the land surface. In situ monitoring of precipitation has a very limited usefulness on the regional and global scale because of the high spatial and temporal variability of precipitation. It is unlikely to improve rainfall station network and rainfall radar network in short term in all regions. The inaccuracy of rainfall in some areas with sparse rainfall stations is bound to bring great uncertainty into the runoff and water cycle process simulation. On the way to overcome these problems, microwave remote sensing observations are appropriate for retrieving the spatial and temporal precipitation coverage because of the global and frequent availability. With the development of the satellite radar technology, TRMM precipitation data get more and more attention by meteorologists and hydrologists because of its high temporal (3 hours) and spatial (0.25°×0.25°) resolution. For distributed hydrological model, the distributed input data is the basic condition for hydrological simulation. This paper addresses the question of whether remotely sensed precipitation estimates over a catchment can be used to improve distributed hydrological model water balance computations. The TRMM (Tropical Rainfall Measuring Mission) precipitation product was introduced into the hydrological cycle simulation for Yangtze basin, in south China. A tool was developed to interpolate the observations into the same spatial and temporal resolution with TRMM data and then evaluate the precision of TRMM data from 1998 to 2006. It shows that TRMM rainfall in the moderate-intensity with high accuracy, but low-intensity and heavy-intensity rainfall with low fidelity. So the integrated application of TRMM data and ground observations was proposed to the watershed hydrology process simulation and achieved good results.