Abstract
The present study aims to evaluate three global satellite precipitation products [TMPA 3B42, version 7 (3B42 V7); TMPA 3B42 real time (3B42 RT); and Climate Prediction Center morphing technique (CMORPH)] during 2003–12 for multiscale hydrologic applications—including annual water budgeting, monthly and daily streamflow simulation, and extreme flood modeling—via a distributed hydrological model in the Yangtze River basin. The comparison shows that the 3B42 V7 data generally have a better performance in annual water budgeting and monthly streamflow simulation, but this superiority is not guaranteed for daily simulation, especially for flood monitoring. It is also found that, for annual water budgeting, the positive (negative) bias of the 3B42 RT (CMORPH) estimate is mainly propagated into the simulated runoff, and simulated evapotranspiration tends to be more sensitive to negative bias. Regarding streamflow simulation, both near-real-time products show a region-dependent bias: 3B42 RT tends to overestimate streamflow in the upper Yangtze River, and, in contrast, CMORPH shows serious underestimation in those downstream subbasins while it is able to effectively monitor streamflow into the Three Gorges Reservoir. Using 394 selected flood events, the results indicate that 3B42 RT and CMORPH have competitive performances for near-real-time flood monitoring in the upper Yangtze, but for those downstream subbasins, 3B42 RT seems to perform better than CMORPH. Furthermore, the inability of all satellite products to capture some key features of the July 2012 extreme floods reveals the deficiencies associated with them, which will limit their hydrologic utility in local flood monitoring.
