Satellite-based Precipitation and a Coupled Land

12 A widely used land surface model, the Variable Infiltration Capacity (VIC) model, is coupled 13 with a newly developed hierarchical dominant river tracing-based runoff-routing model to form 14 the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model, which 15 serves as the new core of the real-time Global Flood Monitoring System (GFMS). The GFMS 16 uses real-time satellite-based precipitation to derive flood-monitoring parameters for the latitude-17 band 50°N-50°S at relatively high spatial (~12km) and temporal (3-hourly) resolution. Examples 18 of model results for recent flood events are computed using the real-time GFMS 19 (http://flood.umd.edu). To evaluate the accuracy of the new GFMS, the DRIVE model is run 20 retrospectively for 15 years using both research-quality and real-time satellite precipitation 21 products. Evaluation results are slightly better for the research-quality input and significantly 22 better for longer duration events (three-day events vs. one-day events). Basins with fewer dams 23 tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, 24 the probability of detection is ~0.9 and the false alarm ratio is ~0.6. In general, these statistical 25 results are better than those of the previous system. Streamflow was evaluated at 1,121 river 26 gauges across the quasi-global domain. Validation using real-time precipitation across the tropics 27 (30ºS–30ºN) gives positive daily Nash-Sutcliffe Coefficients for 107 out of 375 (28%) stations 28 with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. There 29 were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation 30 input. 31 32 1. Introduction 35 36 Floods are a leading natural disaster with worldwide, significant, negative social-economic 37 impacts. According to World Disaster Report [2012], floods and associated landslides caused 38 more than 55% (2,000) of a total of 3,600 significant natural disasters during 2002-2011 over the 39 globe; they killed over 65,000 people, affected over 1.1 billion people and cost an estimated 40 $280 billion (US Dollars in 2011). Most of these disasters occurred in densely populated and 41 underdeveloped areas where an effective flood monitoring and forecasting system is lacking due 42 to insufficient resources [Wu et al., 2012a]. A reliable flood monitoring and forecasting system at 43 a global scale is extremely desirable to a variety of national and international agencies for 44 humanitarian response, hazard mitigation and management. …