Abstract: Rainfall data are often obtained by ground-based observatories. However, traditional measurements based on raingauge stations can't reflect the spatial variation of precipitation effectively, especially in the Shiyang River Basin, which is a typical area with complicated terrain and climatic characteristics. There is great potential in making hydrological predictions by using satellite-based rainfall estimation. As a precipitation radar satellite, TRMM has been collecting plenty of fine temporal-spatial precipitation data. However, when applied to local basins and regions, the spatial resolution of TRMM products is too coarse, so it is necessary to develop a method to improve the spatial resolution of TRMM before using it. In this paper, a statistical downscaling algorithm based on the relationship between Tropical Rainfall Measuring Mission (TRMM) 3B43 dataset and the DEM(GTOPO30)from USGS is presented. A multiple linear regression model was established under the scale of 1 km. By applying a downscaling methodology based on 1 km resolution, the TRMM3B43 0.25°×0.25° precipitations were downscaled to 1 km×1 km pixel precipitation for each year from 2001 to 2010. The downscaled precipitation estimates were subsequently validated by using the observations obtained from 34 raingauge stations for the duration of 10 years in the Shiyang River Basin. These results showed that: the downscaling procedure resulted in significant improvement in spatial resolution and data quality for annual precipitation during 2001-2010, as well as for a typical dry year (2001) and wet year (2007), and captured the trends of precipitation in spatial distribution and inter-annual variability of annual precipitation with the coefficient of determination R2 ranging from 0.45 to 0.93 at 34 different raingauge stations.

Key words: downscaling, precipitation, the upstream of Shiyang River Basin, TRMM