Spatial Analysis of Flood Susceptibility Throughout Currituck County, North Carolina

Abstract

A probabilistic approach to flood susceptibility determination is investigated in this paper. Nonclimatic flood risk factors are considered and used to develop a base for flood potential prior to investigating the potential impacts due to climate change, which is mapped within Currituck County, North Carolina, using a multivariate logistic regression. Several site characteristics (elevation, slope, curvature, land cover, impervious surface, distance to water, tree density, surficial materials, and soil drainage) were identified as potential flood risk factors and divided into classes. An attempt was made to correlate these flood risk factors to the spatial extent of the FEMA 100-year Special Flood Hazard Area (SFHA). Site characteristics of an equal number of locations (∼43,000) from within and outside of the SFHA were used to train the statistical model. Logistic regression was then used to estimate coefficients for each class of each flood risk factor. It was found that elevation, land slope, and soil drainage class have the greatest correlation to flood inundation in the county. The coefficients were then used to create a logistic regression equation from which probabilities of flooding were estimated for the entire county at a 30-m resolution. Large areas of the central portion of the county and the northern Outer Banks were classified as very high risk (80%–100%) and high risk (60%–80%). While all other high-risk areas corresponded to areas already located within the SFHA, the Outer Banks encompassed areas that are not included in the SFHA. Critical infrastructure related to basic human needs, such as education, safety, and health, located in this high-risk area warrant additional attention regarding potential flood mitigation efforts.