- NH42B-01: AI-Enabled Coastal Resilience via Storm Generation, Surrogate Modeling, and Optimization
-
NOLA CC
Author(s):Generic 'disconnected' Message
Alexander New, Johns Hopkins University Applied Physics Laboratory (First Author)
Jared Markowitz, Johns Hopkins University Applied Physics Laboratory
Jennifer Sleeman, Applied Physics Laboratory Johns Hopkins (Presenting Author)
Genevieve Brett, Woods Hole Oceanographic Institution
Nathaniel Winstead, The Johns Hopkins University/Applied Physics Laboratory
As climate change intensifies, coastal regions will become increasingly vulnerable to extreme weather. We have used an AI-driven framework to predict optimized intervention schemes, given storm field properties and cost for improved resilience to coastal flooding. We evaluated our methodology on a specific use case for optimizing the placement and height of a sea wall and oyster reefs near Tyndall Air Force Base in Florida, an area that was catastrophically impacted by Hurricane Michael. We find that interventions are predicted to affect projected flooding costs of billions of dollars per storm. Our framework will allow for characterization of current coastal resilience capabilities while guiding development of new intervention types based on gaps identified during this assessment.
Scientific DisciplineNeighborhoodType
Enter Note
Go to previous page in this tab
Session


