Downscaling of Real-Time Coastal Flooding Predictions for Decision Support

Emergency managers rely on fast and accurate storm surge forecasts from numerical models to make decisions and estimate damages during storm events. One of the challenges for such models is providing a high level of resolution along the coast without significantly increasing the computational time. Models with large domains, such as the Advanced CIRCulation (ADCIRC) model used in this study, may be accurate in predicting water levels, however predicting flooding at the spatial scale of buildings and roadways is often difficult due to limited resolution. A new tool has been developed that uses Geographic Information System (GIS) scripts to enhance the resolution of maximum water level predictions at the boundary of predicted flooding using a high-resolution Digital Elevation Model (DEM). The water levels predicted by the lower resolution model are extrapolated outward to where the water would intersect with the higher resolution elevation dataset. This tool can process a 50-ft DEM for all 32 coastal North Carolina counties in less than 15 minutes during a storm event. Comparison of results using spatial building datasets for Carteret County showed that for a simulation of Hurricane Matthew, 2,435 buildings were predicted to be flooded prior to enhancing resolution and 3,886 post-enhancement, an increase of 60 percent. This dramatic increase in flooded buildings shows the importance of achieving high accuracy in floodplains, as a relatively small change in predicted flooding extent can have a substantial impact on the predicted number of flooded buildings. The validity of these results was tested by comparing them to results of an ADCIRC model with the same 50-ft resolution as the DEM in Dare County. Dare County is a coastal region with widely-varying topography and land cover, and preliminary comparisons have shown that results are more similar in coastal regions with steeper slopes and less similar in flatter, low-lying areas.