This study provides an initial evaluation of a global flood monitoring system (GFMS) using satellite-based precipitation and readily available geospatial datasets. The GFMS developed by our group uses a relatively simple hydrologic model, based on the run-off curve number method, to transform precipitation into run-off. A grid-to-grid routing scheme moves run-off downstream. Precipitation estimates are from the TRMM Multi-satellite Precipitation Analysis (TMPA). We first evaluated the TMPA algorithm using a radar/gauge merged precipitation product (Stage IV) over south-east USA. This analysis indicated that the spatial scale (and hence the basin size) as well as regional and seasonal considerations are important in using the TMPA to drive hydrologic models. GFMS-based run-off simulations were evaluated using observed streamflow data at the outlet of two US basins and also using a global flood archive. Basin-scale analysis showed that the GFMS was able to simulate the onset of flood events produced by heavy precipitation; however, the simulation performance deteriorated in the later stages. This result points out the need for an improved routing component. Global-scale analysis indicated that the GFMS is able to detect 38% of the observed floods; however, it suffers from region-dependent bias.