Effect of model data availability on scour risk of bridges

H. Zaifoglu () and B. Imam ()
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H. Zaifoglu: Middle East Technical University
B. Imam: University of Surrey

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2022, vol. 114, issue 3, No 45, 3445-3469

Abstract: Abstract Access to detailed data sets which can enable detailed hydraulic modelling of the river around a bridge structure is not always possible and may require extensive surveys. It is important for infrastructure managers to decide whether additional data availability that may increase the accuracy of scour risk assessments may be worthwhile. In this regard, this paper aims to examine the scour risk assessment of bridges under different model resolutions by using two commonly used scour risk assessment procedures for railway bridges in the UK and investigate the sensitivity of a number of hydraulic parameters used in the scour prediction equations. These procedures are applied to four case study railway bridges coupled with four data availability scenarios capturing different levels of topographical and hydrological data available for the bridge/river site. The results show that the estimations of hydraulic parameters based on the simple empirical equations recommended by EX2502 for data scarcity conditions have a tendency to cause a significant disparity compared to the estimates from 1D and 2D HEC-RAS models. Particularly 2D models with bathymetric representation of river can provide more reliable results and improve the accuracy of scour risk assessments, especially for bridges that are close to the thresholds distinguishing different scour risk categories, i.e. medium to high risk. Sensitivity analysis of hydraulic parameters suggests that the most influential parameter that causes significant variations in total scour depth and scour risk is average velocity, followed by mean flow depth, mean floodplain depth, and mean floodplain width.

Keywords: Data availability; 1D and 2D HEC-RAS models; Total scour depth; Scour risk; Sensitivity analysis (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11069-022-05527-0

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