A Thomas, JC Dietrich, TG Asher, M Bell, BO Blanton, JH Copeland, AT Cox, CN Dawson, JG Fleming, M Loveland, RA Luettich. “Using a Multi-Resolution Approach to Improve the Accuracy and Efficiency of Flooding Predictions.” ADCIRC Users Group Meeting, US Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, Vicksburg, Mississippi, 20 May 2019.
A Gharagozlou, JC Dietrich, A Karanci, MF Overton, RA Luettich. “Storm-Driven Erosion and Inundation of Barrier Islands at Dune- and Region-Scales.” ADCIRC Users Group Meeting, US Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, Vicksburg, Mississippi, 20 May 2019.
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.
However, we found an error in their solution for wind-driven setup on a polar domain. It appears to be a typographical error — the variables are not updated correctly at the last step, when the solution is generalized for a wind with arbitrary direction. This solution is not used frequently, and we did not find a correction to this error in the literature (although we were unable to access every subsequent manuscript that cited the Lynch and Gray solution). So we are documenting it here.
A Thomas, JC Dietrich, TG Asher, M Bell, BO Blanton, JH Copeland, AT Cox, CN Dawson, JG Fleming, RA Luettich (2019). “Influence of Storm Timing and Forward Speed on Tide-Surge Interactions during Hurricane Matthew.” Ocean Modelling, 137, 1-19, DOI: 10.1016/j.ocemod.2019.03.004.
After the Storm
Dr. Casey Dietrich, an assistant professor in the Department of Civil, Construction, and Environmental Engineering (CCEE), leads the Coastal and Computational Hydraulics Team and develops computational models that predict storm surge and coastal flooding. Using the model ADCIRC, the team makes predictions about how high sea waters will rise, which areas will be flooded and for how long. These predictions are made for the entire coastline, and then his team visualizes the flooding at the scales of individual buildings and coastal infrastructure. During Florence, Dietrich’s team and collaborators acted as liaisons for state emergency managers to aid their decision making.
“The models are just one data point among many, but they’re helpful in understanding hazards and used to make predictions in real time — partly to make decisions about evacuation, where to deploy resources after, safe places to put emergency vehicles and water supplies,” he said.
The state emergency managers are able to use the flooding predictions to get immediate estimates on damages, which helps communities that are figuring out how much recovery will cost.
After Hurricane Matthew in 2016, Dietrich and his colleagues improved the models’ ability to forecast encroaching water along shorelines. Post-Florence, Dietrich said the research focus is to speed up the model and allow for more permutations to see what might happen if a storm slows down or shifts direction.
Model Predicts Storm Impacts on Beaches and Dunes
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?