Developing a Coastal Resilience Assessment for North Carolina’s Cape Fear River Basin and the South Atlantic CoastAs sea levels rise and heavy precipitation events occur with increased intensity and frequency,¹ many coastal communities—both human and natural—become more vulnerable to the impacts caused by our changing climate: coastal erosion, flooding, impaired water quality, and storm surge, to name a few.

To identify landscapes where community and natural assets are potentially exposed to damage caused by impacts of these climate hazards, UNC Asheville’s National Environmental Modeling and Analysis Center (NEMAC) partnered with the National Fish and Wildlife Foundation (NFWF) to develop a strategy to increase the resilience of valued coastal communities and fish and wildlife habitats.

Through the integration of GIS analysis and spatial modeling² with a vulnerability assessment methodology,³ the resulting products aim to expand the understanding of coastal resilience needs for areas in North Carolina’s Cape Fear River Basin—and also more broadly in the coastal watersheds of the South Atlantic—and can help stakeholders determine priority areas where valued assets are most vulnerable. This information can be used to help communities estimate risks, investigate available options, and prioritize actions—with the overall aim of increasing their capacity to respond to future impacts caused by severe storm and flooding events.

The analysis focuses on the concept of exposure, defined as the location of a community’s asset—such as a school, a home, or its people—in relation to an area potentially impacted by a threat or hazard.⁴ Community resilience (or vulnerability) to natural hazards and threats is dependent upon both exposure and the capacity the community has to cope.

To identify places where assets are most exposed to flood hazards, two models were created: the tThreat Index:, a model spatially depicting relevant hazards and their potential intensities, and the Community Asset Index, a model spatially depicting the presence and quantity of relevant assets. Three classifications of presence among each of the two models—Low, Medium, and High—were determined by a quantile distribution of the summed values of each gridded cell for all input datasets.

Identifying Exposure to Severe Storm and Flood Events

Threat datasets were selected to represent the impacts potentially caused by two climate-related

hazards—severe storms and flood events. The six geospatial data inputs were mapped, weighted, and ranked

to serve in a single model showing high-hazard areas within the Cape Fear River Basin and the South Atlantic coastal

watersheds. These inputs include sea level rise scenarios, areas of low slope, flood-prone areas, storm surge scenarios, soils with poor drainage potential, and soils with high erodibility potential.

Threat Index

Datasets were selected that might affect a community’s capacity to respond and adjust to a

stressor. The geospatial data inputs used to create the Community Asset Index for the Cape Fear River Basin

and the coastal watersheds of the South Atlantic include critical facilities, population density, impervious surfaces, and

additional critical infrastructure, such as dams and water treatment facilities. The map at left illustrates areas in the Cape Fear River Basin where, and how many, of these assets exist on the landscape.

Community Asset Index

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Asset Presence

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Threat Presence

The exposure analysis considers the relationship between threats and the pres-ence of community assets that are potentially impacted during a severe storm or flooding event. The map shows three levels of exposure: Low, Medium, and High. Areas with the highest presence of threats and the highest presence of valued community assets were determined as being the most exposed.

Exposure Index

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Medium

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Exposure

Exposure is defined by the presence of an asset impacted by a threat. The Exposure Index shows where and at what intensity assets are potentially impacted by hazards by combining the Threat Index and Asset Index. Through a raster analysis, a system of ranking based on the cell rankings of each index was used to illustrate the intensities of the intersections between threats and assets.

Determining Exposure

At right: The determination of exposure was based on the combination of Threats and Asset Indices. The matrix at left shows how the product of the threat and asset values in each cell determined its level of exposure.

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Threat Index Ranking

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Low Med High

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NEMAC is currently working with NFWF to expand this methodology to model exposure for the watersheds of the North Atlantic. In addition to modeling exposure of assets in human communities, the effort to model exposure among coastal fish and wildlife assets is also underway.

Next Steps

Ian Johnson, Greg Dobson, Kim Rhodes, Matt Hutchins, Caroline Dougherty, UNC Asheville’s NEMAC

Mandy Chesnutt, National Fish and Wildlife Foundation