Abstract

Abstract—Floods are among the most catastrophic natural dis-asters around the globe impacting human lives and infrastruc-ture. Implementation of a flood prediction system can potentially help mitigate flood-induced hazards. Such a system typically re-quires implementation and calibration of a hydrologic model using in situ observations (i.e., rain and stream gauges). Recently, satel-lite remote sensing data have emerged as a viable alternative or supplement to in situ observations due to their availability over vast ungauged regions. The focus of this study is to integrate the best available satellite products within a distributed hydrologic model to characterize the spatial extent of flooding and associated hazards over sparsely gauged or ungauged basins. We present a methodology based entirely on satellite remote sensing data to set up and calibrate a hydrologic model, simulate the spatial extent of flooding, and evaluate the probability of detecting inun-dated areas. A raster-based distributed hydrologic model, Coupled Routing and Excess STorage (CREST), was implemented for the