Computational Enhancements for the Virginia Department of Transportation’s Regional River Severe Storm Model: Phase II

About the report:

Climate change is projected to increase the risk of flooding, which can cause severe damage and threaten lives. This increased risk makes it even more important to accurately forecast potential flooding impacts. The report details efforts by the University of Virginia to enhance key aspects of the Virginia Department of Transportation’s (VDOT) Regional River Severe Storm Model (R2S2) that aims to forecast potential flooding impacts in real-time for transportation infrastructure. This model serves as a planning tool for a large portion of the Hampton Roads District to assist residency administrators in efficiently allocating scarce resources to close roads and to assist first responders in accessing flood prone areas.

In this study, researchers first designed and implemented methods to improve the accuracy of R2S2 and reassessed the model against the stream data for two different storm events. The calibrated model shows good predictive capability for the majority of the study region, while the easternmost portion of the watershed, which has very flat terrain, remains the most difficult region to model accurately. The final task included automation of the cloud-based system that can provide end-to-end automation of flood warning for bridges and culverts in the region. The system is now available for implementation by VDOT for use during extreme weather events.

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