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Coastal and Urban Flooding – Integrated Data-Driven Modeling with AI/ML to Address the Grand Challenge

Presentation Date
Tuesday, August 6, 2024 at 1:20pm - Tuesday, August 6, 2024 at 1:27pm
Authors

Lead Presenter

Co-Author

Abstract

Coastal and urban flooding from landfalling tropical cyclones (TCs) and extra-tropical cyclones is a major hazard with increasing severity in a warming climate and sea level rise. It is difficult to predict because of highly complex compound effects of storm induced heavy rainfall, storm surge, stream flow and river discharge. Furthermore, built environment including land use and poor drainage system can increase the flood risk. These present a grand challenge for coastal regions. Traditional approach to study coastal and urban flooding has been siloed into separated disciplines. The rainfall is studied by the atmospheric scientists, storm surge by oceanographers, stream flow and river discharge by hydrologists, and built environment by engineers. In addition to physical sciences, societal response and decision making require engaging social behavior sciences. Coastal and urban flooding often affects poor and vulnerable communities disproportionally worldwide.

The Integrated Coastal Modeling (ICoM) project aims to develop, evaluate, and apply a diverse sets of modeling tools to address the problem systematically. Working with the ICoM team, we are leveraging the advancement in multi-scale Earth system modeling and observing capabilities over the coastal regions from flooding events of Superstorm Sandy (2012) and Hurricane Ida (2021) in New York, to the record flooding from sequential storms of Hurricane Irene and Tropical Storm Lee (2011) in the Mid-Atlantic region. We focus on better understanding and improving prediction of the compound effects of rain, storm surge, and river discharge using high-resolution, coupled Earth system models and observations from various satellite and radar-gauge rainfall products, streamflow data, NDBC buoys, NOAA tide gauges, and USGS estuary sites.  AI/ML methods are used to connect the model predictions and observations to flood risks with coastal natural and urban built environmental conditions. These results have important implications in decision making relevant to building resiliency to coastal and urban flooding.

Presentation File(s)
Category
Coastal
Extremes Events
Strengthening EESM Integrated Modeling Framework – Towards a Digital Earth
Innovative and Emerging technologies: ML/AI, Digital Earth, Exascale and Quantum Computing, advanced software infrastructures
Funding Program Area(s)