Size distributions of different sediment mixtures associated with near-bed turbulence over an abruptly sloping bed

Article Type

Research Article

Publication Title

Journal of Hydrology

Abstract

This study explores the incipient motion and grain-size sorting in sediment mixtures under unidirectional flow conditions over a sloping bed. Flume experiments are conducted using four different sediment beds—trimodal, bimodal, and unimodal mixtures of fine sand, coarse sand, and gravel to evaluate their influence on sediment transport and turbulence. The results indicate that sediment mobility is strongly influenced by the grain size heterogeneity, local flow, and bed slope. The grain-size distribution along the sloping bed showed a change, and it was noted that the initial trimodal distribution was transformed to a bimodal grain-size distribution in the sloping bed. Here, the Shields parameter was utilized to evaluate how different sediment mixtures responded to varying flow conditions along the sloping bed. Shield's parameter associated with its spatial variations along the slope revealed the distinct hiding and exposure effects, where coarser grains stabilized finer sediments altering transport rates, leading to modification of Hiding Function equation by Wilcock and Crowe (2003). This study also examined the bedform evolution, showing that ripple characteristics varied based upon sediment composition. In addition, near-bed turbulence characteristics are quantified using Reynolds shear stress, turbulence kinetic energy, power spectral density, and quadrant analysis, highlighting how bed roughness and sediment composition influence energy dissipation and sediment entrainment. These findings enhance the understanding of sediment–fluid interactions and support improved modelling and management of sediment transport in both natural and engineered river systems, particularly downstream of dams, weirs, and artificial knickpoints.

DOI

10.1016/j.jhydrol.2025.134076

Publication Date

12-1-2025

Link to Full Text

Share

COinS