Flood Hydrograph Generation for Predicting Bridge Scour in Cohesive Soils

This research has three main objectives. First, select three bridge sites in South Dakota with long stream flow records (> 50 years) to compute the scour histories using the Scour Rate In COhesive Soils (SRICOS) method. The results will be analyzed to understand the relationship between time sequence of flows, rate of scour, and final scour depth to answer the fundamental question of how the characteristics of a hydrograph such as flood magnitude and duration, and the order of occurrence of floods would influence scour development in cohesive soils. Second, develop a decision tool to identify the types of field situations where the SRICOS method will be appropriate and beneficial. Third, provide guidelines for hydrologic analysis and hydrograph generation for using the SRICOS method based on the site conditions and project requirements.

Language

  • English

Project

  • Status: Completed
  • Funding: $139672
  • Contract Numbers:

    DTRT13-G-UTC38

  • 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:

    Mountain-Plains Consortium

    North Dakota State University
    Fargo, ND  United States  58108
  • Project Managers:

    Tolliver, Denver

  • Performing Organizations:

    Dept. of Civil and Environmental Engineering

    South Dakota State University
    Brookings, SD  United States 
  • Principal Investigators:

    Ting, Francis

  • Start Date: 20170328
  • Expected Completion Date: 20190930
  • Actual Completion Date: 20220722
  • USDOT Program: University Transportation Centers Program
  • Source Data: MPC-531

Subject/Index Terms

Filing Info

  • Accession Number: 01648621
  • Record Type: Research project
  • Source Agency: Mountain-Plains Consortium
  • Contract Numbers: DTRT13-G-UTC38
  • Files: UTC, RIP
  • Created Date: Oct 20 2017 11:08AM