Characterizing & Understanding Historical Flood-related Road Closures

DOT plans to incorporate resilience in transportation planning, project delivery, operations and maintenance. Virginia Department of Transportation's (VDOT’s) November 2022 Resilience Plan is to identify operational, maintenance, and emergency management resilience measures. VDOT seeks to characterize and understand locations known to flood in order to inform future efforts to mitigate flood risk. VDOT has identified an opportunity to build on historical flood information by evaluating the deployment of technology solutions such as early warning flood devices like flood roadway sensors to monitor real-time infrastructure conditions. The purpose of this project is to: Historical Flood Road Closures: Expand a previous study of flood-related road closures to cover the entire state and gain a deeper understanding of the root causes and impacts to infrastructure related to flooding. Flood Sensor Pilot Plan: Design a flood sensor pilot study. The planning and execution of activities conducted during this project will be coordinated to maximize the utility of data generated, leverage activities for multiple purposes, efficiently engage with VDOT staff, and minimize duplication of effort. Some of the cross-project considerations are: Collaboration on Data Collection: Collect information from VDOT staff for multiple purposes – develop an understanding of historic flooding events, current operations and systems, potential future data needs, data integration feasibility, etc. Information collection efforts will be coordinated to minimize duplication, maximize information sharing, and ultimately reduce the burden on staff time. Task Phasing: Findings from the collection of historical flood closures will inform the refinement of the preliminary flood sensor locations identified in the PROTECT Grant application. Therefore, project tasks will be scheduled so that the historic flood closure evaluation is completed prior to designing the future flood sensor pilot.