Category Archives: XBeach
Deterministic, Dynamic Model Forecasts of Storm‑Driven Coastal Erosion

Nahruma wins People’s Choice Award at EWC Symposium

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!
Posters: EWC Symposium 2025

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
News: Erosion Forecast Framework
New technology forecasts beach and dune erosion before hurricanes strike
“Physics-based models can predict how the dune may be lowered, and how much water may flood behind it,” said Jess Gorski (MS 2023), who worked with Professor Casey Dietrich on the project. “Our forecasts can provide information about coastal change to decision makers during a storm.”
In collaboration with the USGS, CCEE researchers developed a framework for running the eXtreme Beach (XBeach) model in real time. The U.S. Gulf and Atlantic coasts are described with thousands of transects, which quantify the offshore depths and the shape of the beach and dune at intervals of 500 m to 2 km along the coast. When a storm approaches, the framework can select the transects that may be affected, and then run a few hundred simulations of the coastal erosion.
Conference : YCSECA 2024
Deterministic, Dynamic Model Forecasts of Storm-Driven Erosion
In this study, we apply the state-of-art model eXtreme Beach (XBeach) to predict coastal erosion due to Hurricanes Michael (2018) and Ian (2022). Sandy beaches along the U.S. Atlantic and Gulf coasts are represented with thousands of one-dimensional transects, which are sampled for real-time forecasts based on the storms’ tracks and projected landfall locations. The morphodynamic model is initialized with high-resolution digital elevation models of the present-day conditions and forced with hydrodynamics from high-resolution wave and circulation models, and its predictions are categorized based on impacts to the primary dune. A key contribution of this study is the semi-automation of the modeling system, so the modeling framework can be applied to different regions of the coast as the landfall location shifts.
To demonstrate this, forecasts for Ian (2022) were initiated several days before the initial landfall location in Punta Gorda, Florida, and continued as the track made a secondary landfall near Georgetown, South Carolina. About 1800 transects are selected for each of the 25 advisories. The simulations are monitored, evaluated, and visualized to communicate the XBeach predictions of coastal change. The framework produces results in less than an hour and then publishes visualizations in less than 10 minutes. Results are compared spatially and temporally to qualitative post-Ian observations and total water level predictions. XBeach can predict dune impact compared to an established coastal change forecasting model while providing additional morphodynamic information not typically available, such as timing and magnitude of volume change. The addition of fully resolved ground surface information and morphodynamics in the model makes it possible to better understand the storm evolution and how that translates into erosion of beaches and dunes.
Jessica Gorski defends MS Thesis

Jessica starts her thesis defense.