Using integrated modeling for generating watershed-scale dynamic flood maps for Hurricane Harvey

Hurricane Harvey, which was categorized as a 1000-year return period event, produced unprecedented rainfall and flooding in Houston. Although the expected rainfall was forecasted much before the event, there was no way to identify which regions were at higher risk of flooding, the magnitude of flooding, and when the impacts of rainfall would be highest. The inability to predict the location, duration, and depth of flooding created uncertainty over evacuation planning and preparation. This catastrophic event highlighted that the conventional approach to managing flood risk using 100-year static flood inundation maps is inadequate because of its inability to predict flood duration and extents for 500-year or 1000-year return period events in real-time. The purpose of this study is to create models that can dynamically predict the impacts of rainfall and subsequent flooding, so that necessary evacuation and rescue efforts can be planned in advance. This study uses a 2D integrated surface water-groundwater model called ICPR (Interconnected Channel and Pond Routing) to simulate both the hydrology and hydrodynamics for Hurricane Harvey. The methodology involves using the NHD stream network to create a 2D model that incorporates rainfall, land use, vadose zone properties and topography to estimate streamflow and generate dynamic flood depths and extents. The results show that dynamic flood mapping captures the flood hydrodynamics more accurately and is able to predict the magnitude, extent and time of occurrence for extreme events such as Hurricane Harvey. Therefore, integrated modeling has the potential to identify regions that are more susceptible to flooding, which is especially useful for large-scale planning and allocation of resources for protection against future flood risk.