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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

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Quantitative Information Fusion for Hydrological Sciences

Part of the book series: Studies in Computational Intelligence ((SCI,volume 79))

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 km2) and large (i.e., >5000 km2) river basins. Furthermore, floods are more destructive overtropical river basins that lack adequate surface stations necessary for real-time rainfall monitoring — i.e., the ungauged river basins (Hossain and Katiyar, 2006) (see Figure 1, left panel).

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Hossain, F., Katiyar, N. (2008). 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. In: Cai, X., Yeh, T.C.J. (eds) Quantitative Information Fusion for Hydrological Sciences. Studies in Computational Intelligence, vol 79. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75384-1_7

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