Scientists at the Department of Energy’s Oak Ridge National Laboratory (ORNL) have developed a cutting-edge 3D modeling framework to predict long-term flooding risks by capturing the intricate dynamics of water flow across landscapes. This tool is designed to provide crucial insights into community vulnerabilities as climate conditions change, specifically for urban areas like Southeast Texas.
Framework Overview
The model offers powerful capabilities for urban planning, generating robust estimates of both frequent and rare flood events by simulating physical processes that turn rainfall into runoff. By incorporating factors such as land cover, soil properties, and land slope, along with population density data, the framework provides a comprehensive perspective on flood risks across large areas like river basins. The study detailing this framework is published in the Journal of Hydrology.
Developed as part of the Southeast Texas Urban Integrated Field Laboratory (IFL) project, the framework is particularly valuable for the Beaumont-Port Arthur region, which houses the nation’s largest oil refinery and is a major industrial hub. This area’s proximity to the Gulf Coast makes it susceptible to flooding and land subsidence, posing significant challenges to local decision-makers.
Key Features and Capabilities
The model estimates the streamflow magnitude and flood depth of rare events, such as a 100-year flood. By utilizing the Amanzi-ATS software, the framework integrates surface-subsurface hydrological models to provide a holistic view of hydrological systems.
The model incorporates a wide range of data, including population estimates, land and soil datasets, hourly radar rainfall data, and streamflow measurements, to simulate flood events with high detail and accuracy.
On the 2,227-kilometer-square Village Creek basin upstream of Beaumont-Port Arthur, the framework simulated thousands of flood events to estimate flood hazards and population exposure for events up to a 500-year return period. The simulation, run on the Perlmutter supercomputer at the National Energy Research Scientific Computing Center (NERSC), involved nearly 1.9 million elements, showcasing the immense computational power required for such detailed modeling.
Next steps involve applying the model to larger sections of the Beaumont-Port Arthur region to simulate flood responses under various future climate projections and land use changes. This includes modeling compound flooding events and the interaction between precipitation and urban infrastructure. The ultimate goal is to equip urban planners with tools to answer scenario-driven queries, such as the impact of wetland restoration on reducing the need for additional flood control infrastructure.
The Southeast Texas Urban IFL is one of four DOE-sponsored field labs across the U.S. aimed at understanding climate change impacts and developing equitable adaptation strategies. The insights gained from this project will be transferrable to other regions, enhancing the national capacity for climate resilience.
Gabriel Perez, a key researcher now at Oklahoma State University, emphasized the unique capability of the model in quantifying the evolution of flood risks due to climate change and urbanization. Ethan Coon, the project co-lead, highlighted the importance of physics-based models for long-term planning, ensuring reliability over decades.
ORNL’s innovative 3D modeling framework stands as a significant advancement in predicting and managing flood risks. By integrating advanced AI and classical hydrological methods, this tool provides valuable insights for urban planning and climate resilience, ultimately contributing to safer and more sustainable communities.
Reference: https://www.ornl.gov/news/scientists-add-human-element-long-term-flood-predictions