Spatial Analysis of Flood Susceptibility Throughout Currituck County, North Carolina
Publication: Journal of Hydrologic Engineering
Volume 25, Issue 8
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 () 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.
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Acknowledgments
This work was performed for Currituck County as part of the requirements of a project funded jointly by the Division of Coastal Management of the North Carolina Department of Environmental Quality, Planning and Management Grant Program (Contract No. 7284), in collaboration with the Nature Conservancy. The contents of this article are solely the responsibility of the authors and do not necessarily represent the official views of funding agencies and collaborators. Data sources are given in tables and references included in this paper.
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Journal of Hydrologic Engineering
Volume 25 • Issue 8 • August 2020
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©2020 American Society of Civil Engineers.
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Received: Nov 14, 2018
Accepted: Feb 13, 2020
Published online: Jun 13, 2020
Published in print: Aug 1, 2020
Discussion open until: Nov 13, 2020
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