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This research aims to develop a framework using the Geographic Information System (GIS) to perform modeling and mapping of flood spatiotemporal variation in urban micro-watersheds. The GIS-framework includes a workflow of several methods and processes including delineation of urban watershed, generation of runoff hydrographs, and time series mapping of inundation depths and flood extent. This framework is tested in areas previously known to have experienced flooding at the University of Nevada, Las Vegas main campus, including Black Parking Lot (Blacklot) and East Mall. Calibration is performed by varying Digital Elevation Model (DEM) resolution, rainfall temporal resolution, and clogging factor whereas validation is performed using flood information from news reports and photographs. The testing at the Blacklot site resulted in calibration at 5 m DEM resolution and clogging factor of 0.83. The flood model resulted in an error of 24% between the estimated (26 inches/66 cm) and actual (34 inches/86.36 cm) flood depths. The estimated flood extents are consistent with the reported conditions and observed watermarks in the area. The flood beginning time estimated from the model is also consistent with the news reports. The testing at East Mall site also shows consistent results. The GIS framework provides spatiotemporal maps of flood inundation for visualization of flood dynamics. This research provides insight into flood modeling and mapping for a storm drain inlet-based watershed.
Abedin et al. (Sat,) studied this question.