Lidar In Coastal Storm Surge Modeling: Modeling Linear Raised Features

A method for extracting linear raised features from laser scanned altimetry (LiDAR) datasets is presented. The objective is to automate the method so that elements in a coastal storm surge simulation finite element mesh might have their edges aligned along vertical terrain features. Terrain features of interest are those that are high and long enough to form a hydrodynamic impediment while being narrow enough that the features might be straddled and not modeled if element edges are not purposely aligned. These features are commonly raised roadbeds but may occur due to other manmade alterations to the terrain or natural terrain. The implementation uses the TauDEM watershed delineation software included in the MapWindow open source Geographic Information System to initially extract watershed boundaries. The watershed boundaries are then examined computationally to determine which sections warrant inclusion in the storm surge mesh. Introductory work towards applying image analysis techniques as an alternate means of vertical feature extraction is presented as well. Vertical feature lines extracted from a LiDAR dataset for Manatee County, Florida are included in a limited storm surge finite element mesh for the county and Tampa Bay. Storm surge simulations using the ADCIRC-2DDI model with two meshes, one which includes linear raised features as element edges and one which does not, verify the usefulness of the method

Implications of Beach and Dune Topography on Storm Surge Dynamics on the Florida Panhandle

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Development of a High-Resolution, Wind-Wave, Tide, and Hurricane Storm Surge Model for Southern Mississippi

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Cottage Hospitals

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Terrain-Driven Unstructured Mesh Development Through Semi-Automatic Vertical Feature Extraction

A semi-automated vertical feature terrain extraction algorithm is described and applied to a two-dimensional, depth-integrated, shallow water equation inundation model. The extracted features describe what are commonly sub-mesh scale elevation details (ridge and valleys), which may be ignored in standard practice because adequate mesh resolution cannot be afforded. The extraction algorithm is semi-automated, requires minimal human intervention, and is reproducible. A lidar-derived digital elevation model (DEM) of coastal Mississippi and Alabama serves as the source data for the vertical feature extraction. Unstructured mesh nodes and element edges are aligned to the vertical features and an interpolation algorithm aimed at minimizing topographic elevation error assigns elevations to mesh nodes via the DEM. The end result is a mesh that accurately represents the bare earth surface as derived from lidar with element resolution in the floodplain ranging from 15 m to 200 m. To examine the influence of the inclusion of vertical features on overland flooding, two additional meshes were developed, one without crest elevations of the features and another with vertical features withheld. All three meshes were incorporated into a SWAN+ADCIRC model simulation of Hurricane Katrina. Each of the three models resulted in similar validation statistics when compared to observed time-series water levels at gages and post-storm collected high water marks. Simulated water level peaks yielded an R2 of 0.97 and upper and lower 95% confidence interval of ~ ± 0.60 m. From the validation at the gages and HWM locations, it was not clear which of the three model experiments performed best in terms of accuracy. Examination of inundation extent among the three model results were compared to debris lines derived from NOAA post-event aerial imagery, and the mesh including vertical features showed higher accuracy. The comparison of model results to debris lines demonstrates that additional validation techniques are necessary for state-of-the-art flood inundation models. In addition, the semi-automated, unstructured mesh generation process presented herein increases the overall accuracy of simulated storm surge across the floodplain without reliance on hand digitization or sacrificing computational cost

Low-Versus High-Resolution Finite Element Modeling Of Storm Surge In The Yellow River, Florida

In this study, select riverine parameters are adjusted in a shallow water equations model of the Yellow River (Florida Panhandle) for the purpose of examining the impact on simulated storm tide. The objective is to identify the physical attributes of the coastal riverine system that influence propagation of hurricane-driven storm tide. Low-and high-resolution unstructured finite element meshes are constructed for the Yellow River. Each model is set up to simulate shallow water flow forced by astronomic tides, river inflow and wind and pressure fields. Numerical experiments are conducted by modifying different combinations of forcings on several spatially varying mesh resolutions. Simulated storm tide is analyzed in terms of sensitivity of the model to adjustments in each of the channel parameters. Lastly, the model solutions are assessed in terms of mesh resolution (i.e. low- versus high-resolution). The findings are discussed in the context of meshing requirements for coastal riverine domains. © 2011 ASCE