Predictive Deep Learning for Flood Evacuation Planning and Routing

Although Departments of Transportation have detailed safety and disaster planning response documents in place, these plans have limited effectiveness for flash flood scenarios resulting from higher than average rainfalls or other unexpected conditions impacting roadways and roadway infrastructure along river basins. The lack of real-time rate of water rise information can prevent effective evacuation or detour routing before rising flood waters overtop impacted routes. This proposed research uses deep learning methods, along with geospatial data from the USGS National Map and other public geospatial data sources, to develop forecasting tools capable of assessing water level rate of change in high risk flood areas. These tools build on existing models developed by the USGS, FEMA, and others and are used to determine evacuation routing and detours to mitigate the potential for loss of life during flash floods. The project scope includes analysis of publically available flood data along a river basin as part of a pilot project in Missouri.


  • English


  • Status: Active
  • Funding: $86548
  • Contract Numbers:


  • Sponsor Organizations:

    Missouri Department of Transportation

    1617 Missouri Boulevard
    P.O. Box 270
    Jefferson City, MO  United States  65102

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Project Managers:

    Harper, Jennifer

  • Performing Organizations:

    Missouri University of Science and Technology, Rolla

    1870 Miner Circle
    Rolla, MO  United States  65409

    Mid-America Transportation Center

    University of Nebraska-Lincoln
    2200 Vine Street, PO Box 830851
    Lincoln, NE  United States  68583-0851
  • Principal Investigators:

    Long, Suzanna

  • Start Date: 20190208
  • Expected Completion Date: 20191231
  • Actual Completion Date: 0

Subject/Index Terms

Filing Info

  • Accession Number: 01703623
  • Record Type: Research project
  • Source Agency: Missouri Department of Transportation
  • Contract Numbers: TR201912
  • Files: UTC, RiP, STATEDOT
  • Created Date: Apr 30 2019 2:35PM