Georgina Sanchez

From its Appalachian Mountains to the Atlantic Ocean, North Carolina is rich in its wide-ranging landscape, its diverse population, and flourishing economy. With several grand metropolitan areas and cozy rural towns, the state offers the best of both urban living and small-town life. Currently, North Carolina is considered the 9th most populous state. If population predictions hold, the state will become the 7th most populous state by 2032. With population growth, comes increased urbanization and infrastructure development, a growing rural and urban interface, and encroachment on communities and areas that support and serve the state������������������s military installations. In an effort to establish a landscape scale approach to natural resources management that enriches compatible land use while minimizing multiple encroachment threats and alleviating on-installation constraints, North Carolina is looking to enhance its Eastern Sentinel Landscape to support flexibility for military readiness beyond 2060 while linking co-benefits of conservation and keeping working forests and farms, working.

Since 2016, flooding from extreme weather events has caused over $40 billion in damages across eastern North Carolina, as a result coastal municipalities are seeking strategies to reduce current and future flood risk (NOAA, 2022). Land use policies and zoning regulations have been successfully implemented to protect residents and reduce long-term vulnerability to flooding. However, zoning data are limited in scale and availability making regional-scale assessments of zoning regulations in flood-prone areas difficult. In this study, we propose using machine-learning methods to predict zoning codes for North Carolina���s Coastal Plain and locate high-risk, overburdened, and under-served communities where adaptive zoning strategies could be implemented for flood adaptation and resilience.

In the past four years, the coast of North Carolina experienced two 500-year flood events resulting in over 70 fatalities and billions of dollars in property damage. The area's highly valued environmental amenities of beautiful coastlines and open water features have concentrated population in areas vulnerable to anticipated sea level rise and increased flood frequencies in the future. Recent modeling studies have shown Federal Emergency Management Agency (FEMA) regulatory flood maps to be outdated and underestimate risk. Flood maps inform flood risk management decisions in North Carolina and across the U.S.; underestimation of risk will result in residents, prospective homeowners, and developers being misguided to continue development in areas that are likely to experience extreme flooding. In this study, we will couple climate change projections of hydrologic conditions with the Height Above Nearest Drainage (HAND) model to simulate how the probability of annual flooding is likely to change in the future. We will evaluate how different scenarios of climate warming, associated with low and high greenhouse gas emissions, are likely to affect the spatial distribution of future flood probabilities. Our study area is shaped by four 10-digit Hydrologic Unit Code (HUC) catchments near Wilmington, North Carolina, a low lying moderately urbanized area, highly vulnerable to flooding due its location adjacent to the Cape Fear River and along the coast. Our goal is to establish the basis for a replicable and scalable methodology to develop flood projections under future climate scenarios at larger geographic scales (e.g., 2-digit or 4-digit Hydrologic Unit Code). The resulting maps of probability of future flooding can assist local land-use planners to visualize and anticipate flood hotspots. Furthermore, we anticipate that our scenario-based approach will better inform risk management and development decisions across the study area.