
Modeling storm surge flooding for participatory transformation of barrier islands: Hatteras Island, NC, USA.

Neural Network Predictions of Flood Maps

Baroclinic 3D modeling of circulation patterns in the Pamlico-Albemarle Sound System

Modeling storm surge flooding for participatory transformation of barrier islands: Hatteras Island, NC, USA.

Neural Network Predictions of Flood Maps

Baroclinic 3D modeling of circulation patterns in the Pamlico-Albemarle Sound System
The U.S. Atlantic and Gulf of Mexico coasts are vulnerable to storms, which can cause significant erosion of beaches and dunes that protect coastal communities. Real-time forecasts of storm-driven erosion are useful for decision support, but they are limited due to demands for computational resources and uncertainties in dynamic coastal systems and storm forcings. Current methods for coastal change forecasts are based on empirical calculations for wave run-up and conceptual models for erosion, which do not represent sediment transport and morphological change during the storm. However, with continued advancements in high-resolution geospatial data and computational efficiencies, there is an opportunity to apply morphodynamic models for forecasts of beach and dune erosion as a storm approaches the coast. In this study, we implement a forecast system based on a deterministic, dynamic model. The morphodynamic model is initialized with digital elevation models of the most up-to-date conditions and forced with hydrodynamics from wave and circulation model forecasts, and its predictions are categorized based on impact to the primary dune, defined in this study as the first ridge of sand landward of the beach. Results are compared spatially to the observed post-storm topography using changes to dune crest elevations and volumes, and temporally to the predicted total water level at the forecasted moment of dune impact.

Nahruma received the People’s Choice Award from CCEE Department Head, Dr. Gibson.
“I’m thankful that my work was well received by the community,” Nahruma said. “I’m especially grateful to my advisor, Dr. Casey Dietrich, whose guidance and support made this possible. I’m also thankful to the National Oceanographic Partnership Program (NOPP) for funding my work on predicting coastal dune erosion, which will be necessary given our recent climate change scenario, as storms increase in frequency and intensity.”
Congratulations to Nahruma!

Spatial controls and efficiency gains within a spectral wave model.

Analyzing Dune Maintenance effects on Storm Surge at Tyndall Air Force Base.

Prediction of Dune Erosion and Inlet Formation during Hurricanes Helene and Milton.

Neural Network Predictions of Flood Maps

Casey and Jorge enjoy a tour of Nagoya harbor with Profs. Tomoaki Nakamura and Yonghwan Cho.