The frequency and intensity of both floods and droughts are expected to increase in response to climate change; however, significant uncertainties remain regarding regional changes, especially for extreme rainfall. In particular, North Carolina’s geographic position makes it vulnerable to several natural hazards that pose significant flooding risks, including hurricanes, severe thunderstorms, and large winter storms. The most obvious problems within NC in recent years are the pluvial and fluvial flooding from notable hurricanes which paralyzed the eastern NC highway system for days to weeks. The heavy rainfall associated with Hurricanes Floyd (1999), Matthew (2016), Florence (2018), and Dorian (2019) generated record-breaking fluvial flooding along key economic corridors including I-95, I-40, US-70, NC-12, and US-64, and created a chain of transportation infrastructure problems that affected emergency response operations and the transportation of goods. In particular, I-95 facilitates 40 percent of the Nation’s GDP while US-70 and I-40 are key routes for supporting the military, agriculture and the economy in eastern NC. Though hurricanes receive a lot of attention in resilient design, as they should, transportation engineers face additional challenges, including possible changes to rainfall intensity from localized thunderstorms and even drought. NC officials, recognizing the risks posed by a changing climate, developed Executive Order 80 (EO80) to help protect the people, natural environment, and economy of North Carolina. NC DOT is likewise working to implement solutions to become more resilient to weather extremes in a changing climate.
This objective of this study is to improve confidence in climate change projections by quantifying future precipitation extremes within NC for resilient design (e.g., precipitation intensity, duration, frequency curves). This project will incorporate guidance developed for the National Cooperative Highway Transportation Research Board, NCHRP 15-61, with additional methods and numerical model experiments to improve confidence in future precipitation extremes, and to inform design concepts for potential future events.
