Welcome to the CCHT! We develop computational models for wind waves and coastal circulation, and then apply these models to high-resolution simulations of ocean behavior. Our goals are to understand how coastlines are threatened during storms, how materials are transported in the coastal environment, and how to communicate these hazard risks for use in decision support. Our research spans the disciplines of coastal engineering, numerical methods, computational mathematics, and high-performance computing.

In this web site, we share our research progress, from development to application, and from coding to publishing. Learn more about What We Do and how to Join Our Team.

Subgrid Theory for Storm Surge Modelling

Averaging techniques are used to generate upscaled forms of the shallow water equations for storm surge including subgrid corrections. These systems are structurally similar to the standard shallow water equations but have additional terms related to integral properties of the fine-scale bathymetry, topography, and flow. As the system only operates with coarse-scale variables (such as averaged fluid velocity) relating to flow, these fine-scale integrals require closures to relate them to the coarsened variables. Closures with different levels of complexity are identified and tested for accuracy against high resolution solutions of the standard shallow water equations. Results show that, for coarse grids in complex geometries, inclusion of subgrid closure terms greatly improves model accuracy when compared to standard solutions, and will thereby enable new classes of storm surge models.

AB Kennedy, D Wirasaet, A Begmohammadi, T Sherman, D Bolster, JC Dietrich (2019). “Subgrid Theory for Storm Surge Modelling.” Ocean Modelling, in press, DOI: 10.1016/ocemod.2019.101491.

Carter Rucker helps with Pilot Study for DUNEX

CCHT member Carter Rucker joined a field pilot study with other members of the NCSU Coastal Engineering Team. The collaborative During Nearshore Event Experiment (DUNEX) pilot study is now underway along the Outer Banks of North Carolina, home to the U.S. Army Engineer Research and Development Center’s Coastal and Hydraulics Laboratory’s Field Research Facility.

DUNEX is a multi-agency, academic and non-governmental organization collaborative community experiment to study nearshore coastal processes during coastal storms. The multi-phase experiment plan begins with the pilot study, followed by the full experiment starting in fall 2020 and extending into winter 2021. Learn more here.

Carter Rucker (right) setting markers in the Pea Island marsh preparing for ADCP surveys later in the week. Photo courtesy Beth Sciaudone.

News: Connecting Erosion to Flooding

2019/09/26 – NC Sea Grant Coastwatch
XBeach Model Predicts Storm Impacts on Beaches and Dunes

Alireza Gharagozlou (below) is a doctoral student in the Department of Civil, Construction, and Environmental Engineering at NC State University. He studies how to connect predictions of beach and dune erosion to community-wide flooding and serves with Casey Dietrich on NC State’s Coastal & Computational Hydraulics Team. North Carolina Sea Grant has supported their work.

Alireza surveying the beach profile near Hatteras, NC, with RTK-GPS after Hurricane Florence.


2019/04/26 – NC Sea Grant Coastwatch Currents
Model Predicts Storm Impacts on Beaches and Dunes

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During storms, strong waves and currents can erode beaches and dunes and create low-lying areas vulnerable to flooding. We use field surveys and a computer model called XBeach to predict this erosion, as well as to understand its interactions with storm-driven flooding of larger regions.

Computer models allow us to see how the storm surge and waves impact the beach over time, and which locations are vulnerable to large-scale damage. Good predictions of such storm impacts help emergency managers take better-informed measures to protect coastal areas. Understanding vulnerabilities also instructs highway access design and residential area planning.

We used the XBeach computer model on more than 30 kilometers of Hatteras Island between Avon and Rodanthe to explore how to connect erosion predictions to larger areas. Could XBeach cover more of the island, yet still provide good erosion predictions at beach and dune scales? And how could we connect erosion predictions to other models for storm surge and flooding?

Presentation : ASCE NC Fall Conference

Predictive Multi-Hazard Hurricane Data-Based Fragility Model for Residential Homes

Multi-hazard hurricane data-based fragility models are able to represent multiple predictor variables, be validated based on observed data, and consider variability in building characteristics and hazard variables. This paper develops predictive hurricane, multi-hazard, single-family building fragility models for ordered categorical damage states (DS) and binary complete failure/non-complete failure using proportional odds cumulative logit and logistic regression models, respectively. In addition to their simplicity, these models are able to represent multiple hurricane hazard variables and include variable interactions, thus improving model fitting and damage prediction. Surveys of physical damage in coastal Mississippi following Hurricane Katrina (2005) and high-resolution numerical hindcast hazard intensities from the Simulating WAves Nearshore and ADvanced CIRCulation (SWAN + ADCIRC) models are used as model input. Prediction accuracy is expressed in terms of cross-validation (CV) and evaluated using leave-one-out cross-validation (LOOCV).

Thirty-nine combinations of global damage response variables were investigated. Of these models, six DS and one complete failure model met the evaluation criteria. Maximum significant wave height was the only significant hazard variable for the DS models, while maximum 3-s gust wind speed, maximum surge depth, and maximum water speed were found to be significant predictors for the complete failure model. Model prediction external accuracy ranged from 81% to 87%.

CC Massarra, CJ Friedland, BD Marx, JC Dietrich (2019). “Predictive Multi-Hazard Hurricane Data-Based Fragility Model for Residential Homes.” Coastal Engineering, 151, 10-21, DOI: 10.1016/j.coastaleng.2019.04.008.