Impacts of coastal flooding on watersheds in Hampton Roads, VA

Abstract

Coastal communities face threats of flooding associated with episodic storm events and high tides that are increasing in severity and frequency due to climate change and sea level rise (SLR). The Mid-Atlantic U.S. is experiencing SLR at rates faster than the global average, especially in Hampton Roads, Virginia where the rate of SLR is accelerating due to land subsidence. Adaptation plans for coastal flooding are mostly made at the municipality level, ignoring the propagation of water across its administrative boundaries. Impact assessment at the watershed scale identifies areas where municipalities will need to collaborate to mitigate the flood impact. The main purpose of this project was to evaluate the impact of flooding among watersheds in Hampton Roads and identify those most at risk that overlap one or more municipal boundary. Additionally, this research assessed the impact on land use/cover and population throughout the Hampton Roads region and within a case study watershed. To meet these objectives, we used U.S. Army Corps of Engineers 50-year floodplain and NOAA intermediate SLR scenarios for 2030, 2060, and 2090 to calculate the percent land area inundated for each watershed in Hampton Roads. Further, we assessed the flood impact on populations and specific land use/covers throughout the region for each SLR scenario, as well as within the Elizabeth River watershed. Key findings show that five watersheds will see a greater increase in inundated area than the surrounding watersheds, with two that overlap multiple municipalities. The anticipated land use impacts indicate significant inundation of land occupied by military, followed by commercial, industrial, and wetland covers both in Hampton Roads and within the Elizabeth River watershed. These findings not only highlight the need for more synchronized collaboration on adaptation between municipalities in Hampton Roads, but also provide a framework for the impact assessments in similar settings globally.