Downscaling of real-time coastal flooding predictions for decision support

Abstract

During coastal storms, forecasters and researchers use numerical models to predict the magnitude and extent of coastal flooding. These models must represent the large regions that may be affected by a storm, and thus, they can be computationally costly and may not use the highest geospatial resolution. However, predicted flood extents can be downscaled (by increasing resolution) as a post-processing step. Existing downscaling methods use either a static extrapolation of the flooding as a flat surface, or rely on subsequent simulations with nested, full-physics models at higher resolution. This research explores a middle way, in which the downscaling includes simplified physics to improve accuracy. Using results from a state-of-the-art model, we downscale its flood predictions with three methods: (1) static, in which the water surface elevations are extrapolated horizontally until they intersect the ground surface; (2) slopes, in which the gradient of the water surface is used; and (3) head loss, which accounts for energy losses due to land cover characteristics. The downscaling methods are then evaluated for forecasts and hindcasts of Hurricane Florence (2018), which caused widespread flooding in North Carolina. The static and slopes methods tend to overestimate the flood extents. However, the head loss method generates a downscaled flooding extent that is a close match to the predictions from a higher-resolution, full-physics model. These results are encouraging for the use of these downscaling methods to support decision-making during coastal storms.

c-HAND: near real-time coastal flood mapping

“…This result is visually confirmed by observing that the green FP area is larger than the red FN area, as shown in Figure 12. Previous studies have also shown that static methods tend to overpredict flood inundation (Ramirez et al, 2016;Didier et al, 2019;Rucker et al, 2021;Li et al, 2022).…”

“…We neglect the other bank across from the coast, which is analogous to another continent or island. The ocean water surface elevation is extended horizontally from the ocean surface to the landscape topography, taking an approximate but computationally efficient approach that can be referred to as "bathtub," "equilibrium," or "static" (Gallien et al, 2011;Rucker et al, 2021). We apply a static equilibrium assumption to the water surface, assuming that the water surface is absolutely motionless and horizontal, similar to the water surface of a still bathtub (Figure 8).…”

“…For the remainder of this study, we dub this combination of satisfying both elevation and ocean connectivity constraints the c-HAND method. Topography-based coastal inundation mapping methods have been applied to inform land-use management policy (Brown, 2006), assess damages due to climate change (Lichter and Felsenstein, 2012), and downscale coarse hydrodynamic outputs (Rucker et al, 2021), but to the authors' knowledge, this is the first time a topography-based approach has been applied to high-fidelity near real-time coastal flood inundation mapping.…”

Integrating Evacuation and Storm Surge Modeling Considering Potential Hurricane Tracks: The Case of Hurricane Irma in Southeast Florida

“…The coupled ADCIRC+SWAN model is previously validated in terms of its long-term impact on storm surge on the Gulf coast [15][16][17]. Inland inundation modeling requires a small, fine resolution finite element domain to capture flood water behavior over small-sized land features [18]. This smaller domain is nested within the larger coupled model domain as performed in a number of studies [19][20][21].…”