Deep Learning for Unmonitored Water Level Prediction and Risk Assessment
This proposed research is a match project designed to run in tandem between the Mid-America Transportation Center (MATC) and the Missouri Department of Transportation (MoDOT). This project 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 Mid-America Transportation Center/Missouri Department of Transportation (MATC/MoDOT) projects for flood prediction and models developed 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.
Language
- English
Project
- Status: Active
- Funding: $300000
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Contract Numbers:
TR202111
69A3551747107
RiP Project 91994-88
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Sponsor Organizations:
Missouri Department of Transportation
1617 Missouri Boulevard
P.O. Box 270
Jefferson City, MO United States 65102Office 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 -
Project Managers:
Schulte, Brent
Stearns, Amy
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Performing Organizations:
Missouri University of Science & Technology, Rolla
Department of Engineering
202 University Center
Rolla, MO 65409Mid-America Transportation Center
University of Nebraska-Lincoln
2200 Vine Street, PO Box 830851
Lincoln, NE United States 68583-0851 -
Principal Investigators:
Corns, Steven
Long, Suzanna
- Start Date: 20210208
- Expected Completion Date: 20221231
- Actual Completion Date: 0
Subject/Index Terms
- TRT Terms: Accuracy; Data collection; First responders; Floods; Forecasting; Machine learning; Rainfall; Risk assessment; Routes and routing; Uncertainty; Validation
- Subject Areas: Highways; Hydraulics and Hydrology; Operations and Traffic Management; Planning and Forecasting; Security and Emergencies;
Filing Info
- Accession Number: 01769437
- Record Type: Research project
- Source Agency: Missouri Department of Transportation
- Contract Numbers: TR202111, 69A3551747107, RiP Project 91994-88
- Files: UTC, RIP, STATEDOT
- Created Date: Apr 14 2021 10:23AM