Abstract. Deltas, estuaries, and wetlands are prone to frequent coastal flooding throughout the world. In addition, a large number of people in the United States have settled in these low-lying regions. Therefore, the ecological merit of wetlands for maintaining sustainable ecosystems highlights the importance of flood risk and hazard management in these regions. Typically, hydrodynamic models are used for coastal flood hazard mapping. The huge computational resources required for hydrodynamic modeling and the long-running time of these models (order of hours or days) are two major drawbacks that limit the application of these models for prompt decision-making by emergency responders. In the last decade, DEM-based classifiers based on Height Above Nearest Drainage (HAND) have been widely used for rapid flood hazard assessment demonstrating satisfactory performance for inland floods. The main limitation is the high sensitivity of HAND to the topography which degrades the accuracy of these methods in flat coastal regions. In addition, these methods are mostly used for a given return period and generate static hazard maps for past flood events. To cope with these two limitations, here we modify HAND and propose a composite hydrogeomorphic index for rapid flood hazard assessment in coastal areas. We also propose the development of hydrogeomorphic threshold operative curves for real-time flood hazard mapping. We select the Savannah river delta as a testbed, calibrate the proposed hydrogeomorphic index on Hurricane Matthew and validate the performance of the developed operative curves for Hurricane Irma. Validation results demonstrate that the operative curves can rapidly generate flood hazard maps with satisfactory accuracy. This indicates the high efficiency of our proposed methodology for fast and accurate estimation of hazard areas for an upcoming coastal flood event which can be beneficial for emergency responders and flood risk managers.
Supplementary material to "Real-time coastal flood hazard assessment using DEM-based hydrogeomorphic classifiers"
