Effects of particle exposure, near-bed velocity and pressure fluctuations on incipient motion of particle-size mixtures

Abstract

For the prediction of river bed destabilisation and fractional sediment transport of mixtures, we aim to solve two problems that are poorly understood. First, the flow and pressure fluctuations surrounding both the embedded and exposed particles must be parameterised for hydraulically smooth to rough flow. Second, an adequaterelationbetweenparticlesizeandparticleexposureshouldbebasedontheparticlesizedistributionand the (water-worked) bed structure. We use a recently developed force balance model for the threshold of motion of uniform sediments incorporating the effects of particle exposure, pressure fluctuations into the bed, very shallow flow and bed slope. The flow module is extended to non-uniform roughness of sediment mixtures. Our extended model predicts the critical Shields values of arbitrary mixtures directly as function of exposure and no longer needs empirical hiding-exposure relations. Several empirical and geometrical relations between particle size and exposure were tested. The results are compared to extensive datasets from the literature of incipient fractional transport rates. The modelled hiding-exposure relations are very sensitive to the relation between particle size and exposure, which differ for unimodal, skewed and bimodal mixtures. This is explained by the pore structure of these sediments.The existing relations fail particularly for the smaller particles in bimodal and skewed distributions.These small particles percolate through the pores so their exposure or embedding strongly depends on the fractional content and pore structure, in agreement with empirical data. We are working on a universalrelationforexposurecontainingparticlesizedistribution,porestructureandwater-working.Themodel reproduces data of uniform sediments well for the entire physically possible range of particle exposures and for hydraulically rough to nearly smooth conditions. Trends in existing data for mixtures are also reproduced but depend strongly on exposures that were not measured.