Development of the Fully Adaptive Storm Tide (FAST) Model for hurricane induced storm surges and associated inundation

A new state-of-the-art model (the Fully Adaptive Storm Tide model, FAST) for the prediction of storm surges over complex landscapes is presented. The FAST model is based on the conservation form of the full non-linear depth-averaged long wave equations. The equations are solved via an explicit finite volume scheme with interfacial fluxes being computed via Osher's approximate Riemann solver. Geometric source terms are treated in a high order manner that is well-balanced. The numerical solution technique has been chosen to enable the accurate simulation of wetting and drying over complex topography. Another important feature of the FAST model is the use of a simple underlying Cartesian mesh with tree-based static and dynamic adaptive mesh refinement (AMR). This permits the simulation of unsteady flows over varying landscapes (including localized features such as canals) by locally increasing (or relaxing) grid resolution in a dynamic fashion. The use of (dynamic) AMR lowers the computational cost of the storm surge model whilst retaining high resolution (and thus accuracy) where and when it is required. In additional, the FAST model has been designed to execute in a parallel computational environment with localized time-stepping. The FAST model has already been carefully verified against a series of benchmark type problems (Kelly et al. 2015). Here we present two simulations of the storm tide due to Hurricane Ike(2008) and Hurricane Sandy (2012). The model incorporates high resolution LIDAR data for the major portion of the New York City. Results compare favorably with water elevations measured by NOAA tidal gauges, by mobile sensors deployed and high water marks collected by the USGS.