Deep Learning for Unmonitored Water Level Prediction and Risk Assessment

This research is a match project designed to run in tandem between the Mid-America Transportation Center (MATC) and the Missouri Department of Transportation (MoDOT). It uses deep learning and other computational intelligence methods to leverage public geospatial data and historical National Oceanic and Atmospheric Administration (NOAA) data to develop forecasting tools to create virtual water level monitors. These tools inform existing models developed in previous MATC/MoDOT projects for flood prediction and models develop by the United States Geological Survey (USGS), Federal Emergency Management Agency (FEMA), NOAA, and others and are used to reduce the errors from these models due to sparse data for prediction. The project scope includes a survey instrument to gather data from first responders who are required to travel during these hazardous events. These data are then used to determine the water levels and rate of change at unmonitored sites based on projected rainfall totals based on drainage basin information and recent weather patterns. The data from these virtual monitors is then used for flood event prediction to improve accuracy. The results of these virtual monitors will be validated by manual testing at prediction locations. In addition, the data from the virtual monitors and the validation readings will be used to determine the sources of uncertainty in the predictions and recommend where physical monitors should be placed to improve future predictions. This provides the transportation safety or disaster planner increased accuracy to better plan for flooding events.


    • English


    • Status: Active
    • Funding: $200000
    • Contract Numbers:


    • Sponsor Organizations:

      Office of the Assistant Secretary for Research and Technology

      University Transportation Centers Program
      Department of Transportation
      Washington, DC  United States  20590
    • Managing Organizations:

      Mid-America Transportation Center

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

      Missouri University of Science & Technology, Rolla

      Department of Engineering
      202 University Center
      Rolla, MO    65409
    • Principal Investigators:

      Corns, Steve

      Long, Suzanna

    • Start Date: 20210101
    • Expected Completion Date: 20220630
    • Actual Completion Date: 0
    • USDOT Program: University Transportation Centers

    Subject/Index Terms

    Filing Info

    • Accession Number: 01762018
    • Record Type: Research project
    • Source Agency: Mid-America Transportation Center
    • Contract Numbers: 69A3551747107
    • Files: UTC, RiP
    • Created Date: Jan 7 2021 12:49PM