资源环境科技发展态势分析平台

Global Satellite Mapping of Precipitation (GSMaP) product is an important satellite precipitation product of Global Precipitation Measurement (GPM) mission, which provides an alternative means to ground-based rainfall estimates, in which case a rigorous product assessment was required before implementation. The objective of this paper is to evaluate and calibrate the errors of GSMaP_Gauge (GG) products, then SWAT model is chosen to evaluate its performance in hydrological simulation. It was found that the GG has a superior ability in detecting moderate rainfall events of 10-20 mm/d, while other magnitude accuracy needs to be strengthened. The Nash-Sutcliffe coefficient of efficiency (NS), coefficient of determination (R-2) and the percent bias (PBIAS) were used to evaluate hydrological model performance in the daily scale, supporting the view that GG still allow considerable room for improvement. SWAT model driving by GG performed relatively poorly which is 0.77 <= R-2 <= 0.84, 0.53 <= NS <= 0.64 and vertical bar PBIAS vertical bar < 9%, while the performance of corrected GG is relatively better that is 0.85 <= R-2 <= 0.87, 0.70 <= NS <= 0.75 and vertical bar PBIAS vertical bar < 15%. Through the error's correction of GG, it brings a better performance of runoff simulation under SWAT modeling, leading to 11.94% and 6.1% maximum increase in NS and R-2 respectively. Certain shortcomings are also noted that improvements to the relative runoff depth errors are limited or worse. But in general, GSMaP product has the potential to be an alternative data source for the research on hydrological simulation and water resources management in data-poor or ungauged basins.