Authors: Peng Gao*, University of South Carolina, Gregory Carbone, University of South Carolina, Junyu Lu, University of South Carolina
Topics: Water Resources and Hydrology, Hazards, Risks, and Disasters, Physical Geography
Keywords: radar data, heavy precipitation, flooding, hydrologic simulations
Session Type: Paper
Start / End Time: 8:00 AM / 9:40 AM
Room: Napoleon B3, Sheraton 3rd Floor
Presentation File: No File Uploaded
Flooding induced by extreme rainfall events causes tremendous loss of life and property, and infrastructure failure. Accurate representation of precipitation, which has high variation in space and time, is critical to hydrologic model simulations and flood analyses. In this study, we examined responses of differently-sized United States Geological Survey (USGS) hydrologic units to heavy precipitation using three different data sets. The first one is rainfall observation at individual meteorological stations. The second blends the advantages of meteorological station data with high temporal resolution, with the spatial coverage of Parameter-elevation Relationships on Independent Slopes Model (PRISM) data. The third uses National Centers for Environmental Prediction (NCEP) National Multi-sensor Hourly Precipitation Analysis Stage IV Data. We examined how urban watersheds affected by an October 2015 flooding event in South Carolina respond to the two different representations of heavy rainfall, using the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) developed by the US Army Corps of Engineers. We found that although the latter two methods that consider spatial representation of rainfall yields similar performance, they improved simulated streamflow as compared to that using rainfall observed at individual meteorological stations. Our study helps identify uncertainties associated with precipitation inputs for flood analyses and informs floodplain management and planning.