Holistic Network-level Assessment of Pavement Flood Damages using the FEMA's Hazus Flood Models and Maintenance Cost Prediction

After recent catastrophic disasters, roadways in the South-Central region suffer not only from the flood inundation, but also from the long-term recovery processes that incur enormous maintenance costs. To assess the impacts of flooding disasters on roadways, various studies have investigated sampled roadway damages with pavement engineering techniques such as a direct damage analysis using cores/bores. However, current methods for evaluating roadway damages are time-consuming and labor-intensive. In addition, even though existing methods provide a detailed damage analysis of pavement in a particular location for a particular time period, there is still a large practical knowledge gap in understanding network-level roadway functional/structural damages before-and-after historic flooding as well as assessing flooding impacts on roadways over time. The primary objective of this project is to develop a holistic roadway damage assessment method using the FEMA’s Hazus flood models and the pavement condition data accumulated over the years. This project also aims to provide a means for Louisiana and Texas to intuitively identify roadway damage patterns at the network level caused by flooding over time as well as accurately predict roadway maintenance cost. Research objectives will be achieved through the completion of the following tasks: (1) Investigate all roadways in Louisiana and Texas damaged by previous flood disasters using the FEMA’s Hazus models of previous flooding and hurricane events as well as the Base Flood Elevation (BFE) which is the elevation with 100-year flood; (2) analyze pavement assessment data obtained from the Pavement Management System (PMS) in the Louisiana Department of Transportation and Development (LaDOTD) as well as the Pavement Analyst in the Texas Department of Transportation (TxDOT); (3) incorporate pavement condition data into the Hazus flood model in GIS; (4) evaluate network-level functional and structural pavement damages; (5) develop damage pattern detection and spatial clustering models that indicate space-time pavement damage trends after flooding events; (6) build a prediction model of post-flood roadway maintenance cost and a quantifying model of future maintenance costs of flood damaged roadways; and (7) assess pavement damage patterns by comparing with PMS and Pavement Analyst data.


  • English


  • Status: Completed
  • Funding: $120000
  • 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:

    Transportation Consortium of South-Central States (Tran-SET)

    Louisiana State University
    Baton Rouge, LA  United States  70803
  • Project Managers:

    Melson, Christopher

  • Performing Organizations:

    Louisiana State University and A&M College

    202 Himes Hall
    Baton Rouge, LA  United States  70803

    Texas A&M University, College Station

    318 Jack K. Williams Administration Building
    College Station, TX  United States  77843
  • Principal Investigators:

    Lee, Yong-Cheol

    Choi, Kunchee

  • Start Date: 20190815
  • Expected Completion Date: 20210215
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01713216
  • Record Type: Research project
  • Source Agency: Transportation Consortium of South-Central States (Tran-SET)
  • Contract Numbers: 69A3551747106
  • Files: UTC, RIP
  • Created Date: Aug 2 2019 6:49AM