CCEE Researchers respond rapidly to Hurricane Florence
Much of the North Carolina coast is lined with sandy beaches and dunes, which can erode during storms, allowing sand onto major roadways and floodwaters into communities. To develop predictions for this erosion and its effects on infrastructure, it was critical to collect observations shortly after the storm. A multi-disciplinary team led by Dr. Elizabeth Sciaudone traveled to Dare County to collect time-sensitive data at Kitty Hawk, Nags Head, Pea Island, and Hatteras Island. Working in conjunction with the Institute for Transportation Research and Education (ITRE), the Center for Geospatial Analytics in the College of Natural Resources, and industry partner SenseFly, researchers surveyed beach and dune changes. Real-Time Kinematic GPS equipment was used to survey select cross-shore beach and dune profiles and document the extent of dune erosion and overwash (inland sand deposits), such as when NC Highway 12 becomes covered after large storms.
The goal, locations, and a few pictures of the wave gauge deployment are included below.
|Ph.D. Student (Graduate Research Assistant)
Department of Civil, Construction and Environmental Engineering
North Carolina State University
Mann Hall, Room 424
2501 Stinson Drive
Raleigh, NC 27607
Ahoy! I am a first-year Ph.D. student in the Coastal and Computational Hydraulics Team (CCHT) at NC State. Having been born and raised in Florida, I developed a love for the coastline and a passion for understanding and protecting it. During my undergraduate studies at the University of Florida, I took a few classes in coastal/water resources engineering and decided to pursue it further with a master’s degree at Georgia Tech. There I specialized in coastal and water resources engineering and found my passion.
At Georgia Tech, I took a particular interest in Coastal Hazards work which led me to the CCHT here at NC State. I am currently working on the NSF project “Subgrid-Scale Corrections to Increase the Accuracy and Efficiency of Storm Surge Models,” which aims to reduce computation times of storm surge forecasting while retaining the same level of accuracy used in high resolution models. Although I am just starting out, I am extremely excited to dive deeper into this project so that I may better understand the complex numerical processes that are involved in storm surge prediction. I hope to incorporate rapid deployment field observations into my Ph.D. to help validate the results of our models. In addition, I would like to investigate the interaction between storm surge and rainfall events and its effects on both coastal and inland structures.