Interactions between Waves, Flooding and Beach Morphology during Storm Events

Our goal is to improve simulations of coastal flooding in regions where the beach morphology is highly dynamic during a storm event. The feedback between waves, surge and morphology must be better linked, specifically through the extension and coupling of state-of-the-art numerical models. Although most morphology models are limited in their geographic extents, we will extend and apply a process-driven model to represent erosion and breaching at larger scales. And, although most wave, surge and morphology models are coupled with one-way communication, we will develop an automated system to map information in both ways. This research will produce modeling technologies that will benefit coastal communities within North Carolina, and we will share these technologies and findings with stakeholders. Simulations of wave propagation and flooding (and specifically the simulations from our models) are used in North Carolina and elsewhere for building design, the establishment of flood insurance rates, and real-time decision support during storm events. These predictions will be strengthened via the proposed tight coupling with a beach morphology model. The resulting modeling system will better represent the nearshore response to storm impacts.

JC Dietrich, MF Overton, RA Luettich Jr. “Interactions between Waves, Flooding and Beach Morphology during Storm Events.” National Oceanic and Atmospheric Administration, North Carolina Sea Grant, 2015/07/02, $98,225 (Dietrich: $88,378).

Improving the Efficiency of Wave and Surge Models via Adaptive Mesh Resolution

The goal of this project is to improve the efficiencies of the widely-used SWAN+ADCIRC models for hurricane waves and storm surge. This goal will be achieved through the use of adaptive mesh resolution and dynamic redistribution of the computational load across multiple processing cores. The objectives of the research are to (a) optimize the computational workload of storm surge calculations by modifying adaptively the mesh resolution as dictated by storm track and cone of uncertainty, and (b) to do so in a way that does not sacrifice parallel efficiency.

RA Luettich Jr, G Smith, et al. “Coastal Resilience Center of Excellence at UNC.” Department of Homeland Security, Science and Technology Directorate, 2016/01/01 to 2020/06/30, (Dietrich: $470,000).

Presentation: CARTHE 2015

JC Dietrich, A Muhammad, M Curcic, A Fathi, CN Dawson, S Chen, RA Luettich Jr. “Sensitivity of Storm Surge Predictions to Meteorological Forcing for Hurricane Isaac (2012).” CARTHE All-Hands Meeting, Coral Gables, Florida, 19 October 2015.

Please click here for more information about CARTHE.

Conference: YCSEC-NA 2015

R Cyriac, JC Dietrich, JG Fleming, BO Blanton, RA Luettich, C Kaiser. “Forecast Predictions of Winds, Waves and Storm Surge during Hurricane Arthur (2014).” Young Coastal Scientists and Engineers Conference – North America 2015, University of Delaware, Newark, Delaware, USA, 27-29 July 2015.

RADE: A Risk Analytics Discovery Environment

Coastal property values are sensitive to many factors, including environmental stressors related to changing regional climate and changing sea levels. Predictions of property value changes are essential for coastal planning and development, and form a central part of understanding our state’s exposure to long‐term coastal hazards, particularly the co‐occurrence of tropical cyclones and rising sea levels. Essentially, can we predict long‐term changes in coastal property values and quantify associated uncertainty? What are the impacts of various levels of sea level increase on present and future coastal property values?

This use case will develop a predictor of coastal property values in RADE, and then use that predictor to examine changes under future scenarios of climate and sea level changes. Given other geospatial data to describe a coastal property, the predictor will estimate the assessed price per square foot. Once a reliable predictor model is established, we will perturb it with scenarios of storm winds and flooding from detailed storm surge and wave simulations from the ADCIRC model (Westerink et al, 2008). RENCI has a very large database of ADCIRC simulations from recent FEMA‐funded coastal risk assessments, including the Coastal Flood Insurance Study (Blanton and Luettich, 2010) and a comprehensive Sea Level Rise Impacts Assessment (NCDEM, 2009). We will insert the relevant outputs of these NC coastal model results into the data grid for use by this use case and any other interested researchers. The output includes inundation extents from a sequence of sea level rise increments up to 1 meter, various derived quantities for wind wave impacts, and coastal flooding.

WC Lenhardt, et al. “RADE: A Risk Analytics Discovery Environment.” UNC Research Opportunities Initiative, North Carolina Data Science and Analytics Initiative, 2015/07/01 to 2017/06/30, (Dietrich: $27,270).