Satellite precipitation products offer an opportunity to evaluate extreme events (flood and drought)for areas where rainfall data are not available or rain gauge stations are sparse. In this study, dailyprecipitation amount and frequency of TRMM 3B42V.7 and CMORPH products have been validatedagainst daily rain gauge precipitation for the monsoon months (June–September or JJAS) from 2005–2010 in the trans-boundary Gandak River basin. The analysis shows that the both TRMM and CMORPHcan detect rain and no-rain events, but they fail to capture the intensity of rainfall.The detection of precipitation amount is strongly dependent on the topography. In the plains areas,TRMM product is capable of capturing high-intensity rain events but in the hilly regions, it underestimatesthe amount of high-intensity rain events. On the other hand, CMORPH entirely fails to capturethe high-intensity rain events but does well with low-intensity rain events in both hilly regions as well asthe plain region. The continuous variable verification method shows better agreement of TRMM rainfallproducts with rain gauge data. TRMM fares better in the prediction of probability of occurrenceof high-intensity rainfall events, but it underestimates intensity at high altitudes. This implies thatTRMM precipitation estimates can be used for flood-related studies only after bias adjustment for thetopography.

The paper examines the quality of Tropical Rainfall Monitoring Mission (TRMM) 3B42 V7 precipitation product to simulate the streamflow using Soil Water Assessment Tool (SWAT) model for various rainfall intensities over the Himalayan region. The SWAT model has been set up for Gandak River Basinwith 41 sub-basins and 420 HRUs. Five stream gauge locations are used to simulate the streamflow for a time span of 10 years (2000–2010). Daily streamflow for the simulation period is collected from Central Water Commission (CWC), India and Department of Hydrology and Meteorology (DHM), Nepal. The simulation results are found good in terms of Nash–Sutcliffe efficiency (NSE) >0.65, coefficient of determination (R²)>0.67 and Percentage Bias (PBIAS) <15%, at each stream gauge sites. Thereafter, we have calculated the PBIAS and RMSE-observations standard deviation ratio (RSR) statistics between TRMM simulated and observed streamflow for various rainfall intensity classes, viz., light (<7.5mm/d), moderate (7.5 to 35.4 mm/d), heavy (35.5 to 124.4 mm/d) and extremely heavy (>124.4mm/d). The PBIAS and RSR show that TRMM simulated streamflow is suitable for moderate to heavy rainfall intensities. However, it does not perform well for light- and extremely-heavy rainfall intensities. The finding of the present work is useful for the problems related to water resources management, irrigation planning and hazard analysis over the Himalayan regions.