Evaluation of Global Flood Detection Using Satellite-Based Rainfall and a Hydrologic Model

A new version of a real-time global flood monitoring system (GFMS) driven by Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) rainfall has been developed and implemented using a physically based hydrologic model. The purpose of this paper is to evaluate the performance of this new version of the GFMS in terms of flood event detection against flood event archives to establish a baseline of performance and directions for improvement. This new GFMS is quantitatively evaluated in terms of flood event detection during the TRMM era (1998‐2010) using a global retrospective simulation(3-hourlyand 1 /88spatialresolution)withtheTMPA3B42V6rainfall.Fourmethodswereexplored todefinefloodthresholds fromthemodelresults, includingthreepercentile-basedstatistical methodsandaLog Pearson type-III flood frequency curve method. The evaluation showed the GFMS detection performance improves [increasing probability ofdetection (POD)] with longerflood durationsand largeraffected areas. The impactofdams wasdetectedinthevalidationstatistics,withthepresenceofdamstendingtoresultinmorefalse alarms and greater false-alarm duration. The GFMS validation statistics for flood durations .3 days and for areas without dams vary across the four methods, but center around a POD of ;0.70 and a false-alarm rate (FAR) of ;0.65. The generally positive results indicate the value of this approach for monitoring and researching floods on a global scale, but also indicate limitations and directions for improvement of such approaches. These directions include improving the rainfall estimates, utilizing higher resolution in the runoffrouting model, taking into account the presence of dams, and improving the method for flood identification.

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