Researchers from the University of Virginia’s (U.Va.) School of Engineering and Applied Science, along with collaborators at the Virginia Center for Transportation Innovation and Research, are leading a project to evaluate a risk assessment model designed to gauge the potential impacts of severe weather on U.S. transportation infrastructure.
The group recently won a $250,000 nationally competitive grant from the Federal Highway Administration, or FHWA, to conduct the research. The researchers will pilot a conceptual risk assessment model developed by the FHWA to identify, analyze and prioritize a comprehensive list of transportation assets that have the highest exposure to severe weather threats. The findings will support future work in making specific adaptations to the infrastructure, such as resizing culverts or revising evacuation plans.
At the conclusion of the one-year study, the research group will provide feedback to FHWA on the viability of the model and lessons learned through a case study on the Hampton Roads region. Ultimately, the model is intended to provide transportation agencies guidance on how to best protect and secure roads, bridges and other transportation assets in the face of extreme weather events caused by climate change.
The project will draw on U.Va. Department of Civil and Environmental Engineering researchers’ expertise in sustainable infrastructure, specifically transportation issues and water resource management. Researchers from the U.Va. Center for Risk Management of Engineering Systems are also working on the project.
“We’re seeking to improve Virginia’s transportation infrastructure while having minimal negative societal and environmental impacts,” said Brian Smith, chair and professor in the U.Va. Department of Civil and Environmental Engineering. “We want to ensure the transportation infrastructure in vulnerable areas, particularly coastal areas, can continue to do its job in the face of a changing environment.”
While the study is not intended to critically evaluate the vulnerability of the infrastructure in Hampton Roads, but rather to use that region as a case study for evaluating FHWA’s risk assessment model, valuable lessons will likely be learned with respect to protecting key elements of the region’s transportation system.
“Extreme weather events can have a significant short-term and long-term impact in coastal areas,” said Jose Gomez, associate director at the Virginia Center for Transportation Innovation and Research. “Understanding these impacts, and more importantly, being able to critically assess them to make recommendations to minimize them, requires a multi-disciplinary approach. Working with the School of Engineering and Applied Science, we have assembled a highly qualified team of experts to achieve this goal.”
Hampton Roads offers a case study for national transportation planning because of its high-density population and coastal setting. It also features numerous ports, military bases, historical and recreational destinations, and thriving industry.
The area’s complex transportation infrastructure is already subject to flooding and these problems are projected to increase due to changing weather patterns, according to the researchers. A United States Geological Survey study found the area to be second only to New Orleans in terms of risk from an increased frequency and intensity of coastal storms due to climate change.
“This conceptual model will allow us to collect data on the age of structures, materials used, as well as statistical climate data,” said Andres Clarens, assistant professor in the U.Va. Department of Civil and Environmental Engineering, who specializes in water resources management. “With this data, we’ll be able to connect the dots for future events and offer recommendations for how the region can prepare.”
The Virginia Department of Transportation’s Center for Transportation and Innovation Research is the leading the project with support from the Hampton Roads Planning District Commission and the Hampton Roads Transportation Planning Organization. ##