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Criteria for Predicting Scour of Erodible Rock in West Virginia

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  • English
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    Details:

    • Creators:
    • Corporate Creators:
      Nick J. Rahall, II Appalachian Transportation Institute (U.S.)
    • Corporate Contributors:
      United States. Federal Highway Administration
    • Subject/TRT Terms:
    • Publication/ Report Number:
      RP-273
    • Resource Type:
      Tech Report
    • Geographical Coverage:
    • TRIS Online Accession Number:
      01516400
    • Corporate Publisher:
      West Virginia. Dept. of Transportation
    • Abstract:
      This research project was conducted to characterize the hydraulic scour of rock at 15 selected bridge sites in West Virginia (at least one site in each of West Virginia Division of Highway's (WVDOH’s) ten districts). The study assessed the applicability of a recently-developed rock scour prediction technique to the types of rock and scour conditions found in West Virginia, and identified techniques that can be used to better characterize scour potential at existing and proposed bridge locations. Foundation inspection, rock coring and sample collection, and measurement of scour depth at all sites led to a determination of each site’s mode of scour and enabled modified slake durability testing to develop a median Geotechnical Scour Number (GSN) for rock encountered at each bridge site. Flow conditions over time were assessed for each site using stream gage data where such data was available (three sites), and watershed models, coupled with probabilistic characterizations of precipitation, where stream gage data was not available (12 sites). Scour depth observed at each site, coupled with estimates of Cumulative Excess Stream Power, enabled the calculation of a Scour Number at each site. The scour prediction method applied for this project is designed specifically for sites characterized by abrasion of degradable rock. Ideally, this mode of scour can be confirmed before the method is applied, but in cases where the mode of scour is not clear from field data, or where more than one mode of scour is operating at the same site, this may not be possible or practical. For sites affected only by abrasion, Scour Number and GSN should be consistent, allowing GSN to be used as a predictive measure of scour potential. In this project, however, Scour Number and GSN deviated considerably. The Scour Number/GSN (which, if GSN is to be predictive should have been near 1.0) varied from 3.9 – 17,000. The quarrying mode of scour, where durable, fractured rock is plucked away in discrete scour events from its original location, was evident to varying degrees at 14 of the 15 project sites, and explains why the GSN-centered approach of predicting rock scour, which is contingent on the progressive wear (i.e., abrasion) of non-durable degradable rock, did not apply to the data collected. In those cases where the mode of scour was unclear from field evidence, the lack of agreement between Scour Number and GSN served as indirect confirmation that scour was significantly or wholly attributable to quarrying and not abrasion. Though methodologies have been proposed to attempt scour depth prediction for quarrying , such methods require a comprehensive characterization of the distribution of block shape and dimensions, joint angle, block density, block protrusion, and flow field conditions, and applying such an approach was beyond the scope of this project. Other likely contributors to differences between Scour Number and GSN include uncertainties inherent in probabilistic characterizations of flow, and variations in the flow field along abutments (in contrast to the relative simplicity of the flow field at a pier). Results lead to the conclusion that GSN may not be a universally-appropriate tool for predicting rock scour across the range of rock types and flow conditions found in West Virginia, particularly in view of widespread quarrying of durable rock at the project sites. A Scour Mode Decision Tree was developed to aid in identifying scour mode at future sites where scour assessments are performed, and a method was developed for generating a probabilistic estimation of Average Annual Cumulative Effective Stream Power.
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    • Funding:
      MURC: 211222
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