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.
Updated 2020/06/24: Added documentation for
--growradius none option.
Updated 2020/04/15: Added documentation for DEM vertical unit conversions.
The ADCIRC modeling system is used often to predict coastal flooding due to tropical cyclones and other storms. The model uses high resolution to represent the coastal environment, including flow pathways (inlets, man-made channels, rivers) and hydraulic controls (barrier islands, raised features). However, due to the use of large domains to represent hazards on coastlines in an entire state or multiple states, the highest resolution is typically about 20 to 50 m in coastal regions. Thus, there is a potential gap between the flooding predictions and the true flooding extents. We have developed a geospatial software to downscale the flooding extents to higher resolution.
The following documentation is for downscaling the flooding predictions by using Kalpana. This software was created originally to view ADCIRC outputs as either ESRI shapefiles or KML files (for viewing in Google Earth). ADCIRC (the ADvanced CIRCulation model) uses finite element methods to predict water levels throughout the modeled domain. Although this model is able to provide accurate predictions in a matter of minutes, these predictions have a limited resolution and are not able to provide information at the scale of buildings, roadways, and other critical infrastructure.
N Tull, JC Dietrich+, TE Langan, H Mitasova, CA Rucker, BO Blanton, JG Fleming, RA Luettich. “Enhancing Visualization of Storm Surge Guidance.” Coffee & Viz, NCSU Libraries, North Carolina State University, Raleigh, North Carolina, 19 October 2018.
This seminar was part of the NCSU Libraries’ Coffee & Viz event series, and it was held in the Teaching and Visualization Lab. This lab has 10 overhead projectors and can display graphics on three walls — the entire front and both full sides of the room. More photos are included below.
N Tull, JC Dietrich+, TE Langan, H Mitasova, CA Rucker, BO Blanton, JG Fleming, RA Luettich. “Downscaling and Extrapolation of Coastal Flooding Forecasts for Decision Support.” Geospatial Forum, Center for Geospatial Analytics, North Carolina State University, Raleigh, North Carolina, 18 October 2018.