RAPID: The response and recovery of adjacent natural and built coastlines impacted by Hurricane Florence

The recent passage of the 2018 Hurricane Florence, despite its category 2 status at landfall, altered the North Carolina coastline by eroding sand resources from beaches, eroding and over washing protective sand dunes, and inundating both built and natural back-barrier environments. Unfortunately, this type of impact from hurricanes is not unique. The same stretch of coastline was affected by Hurricane Matthew in 2016. The coastlines of Texas, Florida, Georgia, and Puerto Rico have also recently experienced similar impacts in 2017 due to hurricanes Harvey, Irma, and Maria, respectively. While still not perfect, over the last decade, the accuracy of meteorological and oceanographic models has improved. They can now generally predict the location, strength of maximum winds, and storm surge elevations associated with such events. The ability to predict coastal impacts, however, has not improved at the same rate, and operational models to predict how coastlines change during storms are in their nascent stages. This is due, in part, to a lack of data documenting the pre- and post-coastal changes associated with major storm events. For example, beaches and dunes are constantly changing features, even when there are no storms. Thus, pre-storm elevation data is often out-of-date and post-storm data may not reflect the storm-related conditions because it was collected after the start of restoration activities (e.g., bulldozing sand to clear areas and re-establishing dune barriers). Pre- and post-storm data of the natural system, therefore, are vital to increasing our fundamental understanding of the impacts these storms have on the nation's coastlines. This research program conducts post-Florence drone aerial mapping on Masonboro Island and Wrightsville Beach, both just south and/or east of Wilmington, North Carolina where Hurricane Florence made landfall in September 2018. These surveys will be used to create post-Florence surface models. These models can be compared with those from identical surveys taken at the same locations just days prior to the hurricane (Masonboro Island) and from those taken in the past (Wrightsville Beach). In addition, over wash deposits will be cored and samples will be taken and examined with respect to grain size and shelly sub-bottom dwelling organisms to identify indicators of storm wave strength and off shore seabed erosion. Broader implications of the work are significant for coastal communities and coastal land/resource managers in terms of providing input for coastal erosion, overtopping, flooding, and sediment transport models that are used to determine risk. There will also be interactions and discussion of results with the US Geological Survey and managers of the Masonboro Island National Estuarine Research Reserve. There are plans to incorporate this work and discuss its results with local North Carolina high school classrooms.

This research will collect post-Hurricane Florence drone-based imagery surveys and sediment samples of the beach , dune, and over wash areas of Masonboro Island, a part of the National Estuarine Research Reserve, in addition to surveying and sampling Wrightsville Beach, which is a built environment serving the Wilmington NC area. Both locations have good pre-storm data to which post-storm measurements can be compared, some of it collected just days prior to Hurricane Florence landfall (Masonboro Island). Aerial images collected at both location as a result of this project will be converted to 3D elevation models that reflect the coastal geomorphology immediately before and after the storm. On Masonboro Island, prior to the storm, land-based GPS profiles along different regions of the island and sediment samples were collected. These samples and the sets of pre- and post- elevation models will be used to quantify changes in the coast in the target areas resulting from Hurricane Florence. These surveys will be used to document the magnitude of beach and dune erosion, dune over wash, and back-barrier sediment deposition. The land surveys will be used to validate the aerial drone-based digital surface models to better identify elevation change in vegetated or low-lying areas including thin and diffuse over wash deposits that may not be captured with required accuracy to detect change. Surface sediment samples and cores of over wash deposits will be collected in the course of this work along shore-perpendicular and shore-parallel transects. Grain size and foraminiferal analysis of surface sediment samples and cores will be used to potentially determine minimum surge velocities, the depth of wave excavation of the seabed, over wash sediment volume, and possible sediment sources. The analysis of these data will link the hydrodynamic processes of the storm with the coastal response in areas of diverse barrier island landforms and provide baseline data for future evaluation of post-storm recovery in both built and natural environments.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.