Advancing the Use of Satellite Rainfall Datasets for Flood Prediction in Ungauged Basins: The Role of Scale, Hydrologic Process Controls and the Global Precipitation Measurement Mission

1.0 INTRODUCTION Floods account for about 15 % of the total death toll related to natural disasters, wherein typically more than 10 million lives are either displaced or lost each year internationally (Hossain, 2006). Rainfall is the primary determinant of floods and its intimate interaction with the landform (i.e., topography, vegetation and channel network) magnified by highly wet antecedent conditions leads to catastrophic flooding in medium (i.e., 1000 ~ 5000 km) and large (i.e., > 5000 km) river basins. Furthermore, floods are more destructive over tropical river basins that lack adequate surface stations necessary for real-time rainfall monitoring – i.e., the ungauged river basins (Hossain and Katiyar, 2006a) (see Figure 1, left panel). However, flood prediction is becoming ever more challenging in these mediumto-large river basins due to the systematic decline of in situ rainfall networks world-wide. The gradual erosion of these conventional rainfall data sources has lately been recognized as a major concern for advancing hydrologic monitoring, especially in basins that are ungauged or already sparsely instrumented (Stokstad, 1999; Shikhlomanov et al., 2002). As a collective response, the hydrologic community have recently established partnerships for the development of space-borne missions for cost-effective, yet global,