Author Archives: Casey Dietrich
Numerical Extensions to Incorporate Subgrid Corrections in an Established Storm Surge Model
Inundation models represent coastal regions with a grid of computational points, often with varying resolution of flow pathways and barriers. Models based on coarse grid solutions of shallow water equations have been improved recently via the use of subgrid corrections, which account for information (ground surface elevations, roughness characteristics) at smaller scales. In this work, numerical approaches of an established storm surge model are extended to include subgrid corrections. In an attempt to maintain continuity with existing users and results, model extensions were limited to those needed to provide basic subgrid capabilities, and included two major additions. First, a finite volume method is used to incorporate corrections to the mass and momentum equations using high-resolution ground surface elevations. Second, the no-slip condition imposed on the B-grid wet/dry interface in the model is modified to a slip condition to enable flows in channels with widths comparable to cell size. Numerical results demonstrate these numerical extensions can significantly enhance the accuracy of the model’s predictions of coastal flooding, with low additional computational cost.
Storm Surge Predictions from Ocean to Subgrid Scales
The inland propagation of storm surge caused by tropical cyclones depends on large and small waterways to connect the open ocean to inland bays, estuaries, and floodplains. Numerical models for storm surge require these waterways and their surrounding topography to be resolved sufficiently, which can require millions of computational cells for flooding simulations on a large (ocean scale) computational domain, leading to higher demands for computational resources and longer wall-clock times for simulations. Alternatively, the governing shallow water equations can be modified to introduce subgrid corrections that allow coarser and cheaper simulations with comparable accuracy. In this study, subgrid corrections are extended for the first time to simulations at the ocean scale. Higher-level corrections are included for bottom friction and advection, and look-up tables are optimized for large model domains. Via simulations of tides, storm surge, and coastal flooding due to Hurricane Matthew in 2016, the improvements in water level prediction accuracy due to subgrid corrections are evaluated at 218 observation locations throughout 1500 km of coast along the South Atlantic Bight. The accuracy of the subgrid model with relatively coarse spatial resolution (ERMS = 0.41 m) is better than that of a conventional model with relatively fine spatial resolution (ERMS = 0.67 m). By running on the coarsened subgrid model, we improved the accuracy over efficiency curve for the model, and as a result, the computational expense of the simulation was decreased by a factor of 13.
Jessica is CoE Masters Scholar of the Year for Research
M.S. student Jessica Gorski was recognized as the Masters Scholar of the Year for Research by the NCSU College of Engineering (CoE). Students were nominated by departments within the CoE, and Jessica was selected for this award to recognize outstanding scholarly achievement and dedication to the NC State community and beyond. The award includes a cash stipend.
Jessica’s research is centered on finding answers to this question: During a hurricane, where will the beaches and dunes ‘fail’ along our coast? These systems are heavily engineered – communities invest in and rely on beaches and dunes to protect homes and lives during storms. She has become a leader in research with computational models to advance understanding of storm-driven erosion and flooding of coastal regions.
This award was publicized by both the CoE and our department.
Congratulations to Jessica!
Jenero selected as Global Change Research Fellow
Ph.D. student Jenero Knowles was selected as a Global Change Research Fellow by the Southeast Climate Adaptation Science Center. Jenero will participate in the 2023-2024 cohort and receive training and collaborate with students from across disciplines in climate science.
The fellowship program is designed to train the next generation of global change scientists by providing financial, scientific, and professional development support for graduate students who are interested in multi-disciplinary research. They come together across disciplines to discover, collaborate, and share their knowledge with diverse stakeholders. Learn more about the program at the SECASC web site.
Congratulations to Jenero!
Jessica wins Charles Smallwood Graduate Award
M.S. student Jessica Gorski won the Charles Smallwood Graduate Award from our Department of Civil, Construction, and Environmental Engineering. This award is one of several awards given to recognize excellence by our graduate students. The award includes a cash stipend.
Congratulations to Jessica!
Jessica Gorski (right) celebrates her award, with Ranji Ranjithan.
Webinar: ADCIRC Coordination
News: Preparing for a Changing Climate
2023/01/11 – UDaily, University of Delaware
UD civil engineers lead research to examine models for coastal readiness at U.S. military bases
UD civil engineers lead research to examine models for coastal readiness at U.S. military bases
University of Delaware civil engineers are leading a multi-institutional effort to identify the best models to calculate flood risk at coastal military installations where climate change threatens to increase the risk of flood damage from sea level rise and storm surge.
The four-year project, which launched in mid-2022 and will run through spring 2025, is funded by a $2.2 million grant from the U.S. Department of Defense (DoD). Project partners include faculty and students from the Netherlands, North Carolina State University, the University of South Alabama, Texas A&M and the United States Geological Survey (USGS).
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“The goal is to provide guidance to the DoD about the strengths and weaknesses of each model in comparison. They’re all going to have things they’re good with and things they struggle with,” Dietrich said. Those comparisons will help the agencies decide what types of models they want to use to get what types of information — depending on how much time, effort and funding they want to commit.
There’s also a goal of reducing cost and building smarter models, he said.
“If we are able to improve our predictions at very specific sites along the coast, we also can have better predictions at other specific sites along the coast, like someone’s house or a bridge or other infrastructure,” Dietrich said.