MatFlood: An efficient algorithm for mapping flood extent and depth
Alejandra R. Enríquez, Thomas Wahl, Stefan A. Talke, Philip Orton, James F. Booth, Miguel Agulles, Sara Santamaria-Aguilar
Abstract
Mapping inundation areas and flood depths is necessary for coastal and riverine management and planning. Flood maps help communicate flooding risk to affected communities and vulnerable populations and are essential for evaluating flooding impacts. Here, we introduce MatFlood, a computationally efficient static flood tool that exploits image-processing algorithm for estimation of flood extension and depth. Features include (a) an algorithm that evaluates hydro-connectivity; (b) functionality to calculate spatially varying flood water levels and (c) the inclusion of a reduction factor to mimic the effects of physical processes not explicitly resolved. The efficiency of the tool is well-suited for simulating numerous flooding maps using different inputs (flood water levels or digital elevation models), over large areas, and high spatial resolution. We apply MatFlood to assess the flood extent and depth of Hurricane Sandy (2012) in the New York/New Jersey area to illustrate its use. In comparison to existing approaches based on geographic information systems, MatFlood performs the same calculations six times faster in the Hurricane Sandy study case.