A Comprehensive Flood Inundation Mapping for Hurricane Harvey Using an Integrated Hydrological and Hydraulic Model

Because climate change will increase the frequency and intensity of precipitation extremes and coastal flooding, there is a clear need for an integrated hydrology and hydraulic system that has the ability to model the hydrologic conditions over a long period and the flow dynamic representations of when and where the extreme hydrometeorological events occur. This system coupling provides comprehensive information (flood wave, inundation extents, and depths) about coastal flood events for emergency management and risk minimization. This study provides an integrated hydrologic and hydraulic coupled modeling system that is based on the Coupled Routing and Excessive Storage (CREST) model and the Australia National University-Geophysics Australia (ANUGA) model to simulate flood. Forced by the near-real-time Multi-Radar Multi-Sensor (MRMS) quantitative precipitation estimates, this integrated modeling system was applied during the 2017 Hurricane Harvey event to simulate the streamflow, the flood extent, and the inundation depth. The results were compared with postevent high-water-mark survey data and its interpolated flood extent by the U.S. Geological Survey and the Federal Emergency Management Agency flood insurance claims, as well as a satellite-based flood map, the National Water Model (NWM), and the Fathom (LISFLOOD-FP) model simulated flood map. The proposed hydrologic and hydraulic model simulation indicated that it could capture 87% of all flood insurance claims within the study area, and the overall error of water depth was 0.91 m, which is comparable to the mainstream operational flood models (NWM and Fathom). SIGNIFICANCE STATEMENT We wanted to provide a tool for local emergency response officials to visualize the possible flood conditions in their region, because the heavy rainfall flood is likely becoming more frequent and more intense, possibly as a result of climate change. The simulated flood information includes the water channel flowrate, two-dimensional flood extent, and the inundation depth throughout the flooded area. The results proved that, with less data requirement, the proposed tool can provide the comprehensive flood information, with accuracy of flood extent simulation comparable to mainstream flood models and acceptable inundation-depth simulation. We will keep working to expand the capability of the framework from the real-time simulation to the 1-h lead-time prediction.