Semi-Empirical Estimation of Velocity Profile for Shallow Gravel Bed Channel

  • Rahma Yanda Institut Teknologi Sumatera
  • Morihiro Harada River Basin Research Center, Gifu University
  • Ichiro Tamagawa River Basin Research Center, Gifu University


The dependence of flow velocity distribution near the bed on the roughness geometry has led to various approaches for estimating the velocity. Themodels proposed bypreviousstudies aremostlybased on segmented velocityprofiles(e.g., a linear distribution within theinterfacial sublayer and logarithmic distributions above the interfacial sublayer). By increasing number of segments, the possibility of errors in the parameters, as well as constants, are likely to rise. This study assessed the applicability of a hyperbolic tangent function velocity model to estimate double-averaged velocity profile for shallow flow over a rough gravel bed as a single model concept, especially for the area within roughness layer. Velocity profiles over gravel beds with different arrangements and roughness densities from previously published studies using laboratory measurements were used to validate this model. The behaviours of related constants for this model in response to changes in the flow depth and roughness geometry were investigated, and limitations on it application were evaluated. It was found that the constants required to apply hyperbolic tangent function are affected by roughness geometry function and relative submergence. Through this study also observed that HTF is reliable to describe the velocity profile for about twice of geometric roughness height.


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Author Biographies

Morihiro Harada, River Basin Research Center, Gifu University

River Basin Research Center, Gifu University

Ichiro Tamagawa, River Basin Research Center, Gifu University

River Basin Research Center, Gifu University


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How to Cite
YANDA, Rahma; HARADA, Morihiro; TAMAGAWA, Ichiro. Semi-Empirical Estimation of Velocity Profile for Shallow Gravel Bed Channel. Journal of Science and Applicative Technology, [S.l.], v. 6, n. 2, p. 64-76, dec. 2022. ISSN 2581-0545. Available at: <>. Date accessed: 20 june 2024. doi: