Extraction of Lidar-Based Dune-Crest Elevations for Use in Examining the Vulnerability of Beaches to Inundation During Hurricanes

Abstract

The morphology of coastal sand dunes plays an important role in determining how a beach will respond to a hurricane. Accurate measurements of dune height and position are essential for assessing the vulnerability of beaches to extreme coastal change during future landfalls. Lidar topographic surveys provide rapid, accurate, high-resolution datasets for identifying the location, position, and morphology of coastal sand dunes over large stretches of coast. An algorithm has been developed for identification of the crest of the most seaward sand dune that defines the landward limit of the beach system. Based on changes in beach slope along cross-shore transects of lidar data, dune elevation and location can automatically be extracted every few meters along the coastline. Dune elevations in conjunction with storm-induced water levels can be used to predict the type of coastal response (e.g., beach erosion, dune erosion, overwash, or inundation) that may be expected during hurricane landfall. The vulnerability of the beach system at Fire Island National Seashore in New York to the most extreme of these changes, inundation, is assessed by comparing lidar-derived dune elevations to modeled wave setup and storm surge height. The vulnerability of the beach system to inundation during landfall of a Category 3 hurricane is shown to be spatially variable because of longshore variations in dune height (mean elevation = 5.44 m, standard deviation = 1.32 m). Hurricane-induced mean water levels exceed dune elevations along 70% of the coastal park, making these locations more vulnerable to inundation during a Category 3 storm.