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

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).

“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.

Conference: YCSECA 2022

Virtual Conference: 2022 Ocean Sciences Meeting

Improved Wave Predictions with ST6 Physics and ADCIRC+SWAN

The Simulating WAves Nearshore (SWAN, Booij et al. 1999) model is used widely for predictions of waves in coastal regions. Like other spectral wave models, SWAN uses parameterizations to represent wave evolution due to sources (e.g. wind), sinks (e.g. whitecapping, bottom friction, depth-limited breaking), and resonance (e.g. quadruplet and triad wave-wave interactions). Each parameterization is based typically on observational data to represent the transfer of energy to, from, and between waves. It is necessary for each term to represent its physical process, but it is also necessary for the terms to be calibrated collectively to represent their combined effects on wave evolution. The calibrated wave predictions can then be coupled with models for circulation and coastal flooding, e.g. ADvanced CIRCulation (ADCIRC, Luettich et al. 1992).

SWAN release version 41.20 included a new “package” of wave physics (referred to as ST6 physics). This package has new parameterizations of wind input, whitecapping, swell dissipation, wind speed scaling, and other processes (Rogers et al. 2012). The ST6 physics have been adopted by other wave models (e.g. NOAA’s WaveWatch III, Liu et al. 2019), and it may become the preferred physics package for SWAN. However, because the ST6 physics package has changes to so many parameterizations, it is necessary to quantify its effects on wave predictions. Recent studies (e.g. Aydogan and Ayat 2021) have demonstrated the benefits of using the ST6 physics in the standalone version of SWAN, but its effects have not been quantified for the coupled ADCIRC+SWAN (Dietrich et al. 2011a), which is used for real-time forecasts during impending storms. Do the ST6 physics improve the ADCIRC+SWAN wave predictions?

CC Day, JC Dietrich (2022). “Improved wave predictions with ST6 Physics and ADCIRC+SWAN.” Shore & Beach, 90(1), 59-61, DOI: 10.34237/1009016.