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In this short communication, the erosion process of the fine, cohesive sediment collected from the upper River Taw in South West England was studied in a rotating annular flume located in the National Water Research Institute in Burlington, Ontario, Canada. This study is part of a research project that is underway to model the transport of fine sediment and the associated nutrients in that river system. The erosion experimental data show that the critical shear stress for erosion of the upper River Taw sediment is about 0.09 Pa and it did not depend on the age of sediment deposit. The eroded sediment was transported in a flocculated form and the agent of flocculation for the upper River Taw sediment may be due to the presence of fibrils from microorganisms and organic material in the system. The experimental data were analysed using a curve fitting approach of Krone and a mathematical model of cohesive sediment transport in rotating circular flumes developed by Krishnappan. The modelled and measured data were in good agreement. An evaluation of the physical significance of Krone’s fitting coefficients is presented. Variability of the fitting coefficients as a function of bed shear stress and age of sediment deposit indicate the key role these two factors play in the erosion process of fluvial cohesive sediment.

Mixed sediments are constituted of cohesive and non-cohesive materials with distinct behaviours that numerical models traditionally manage separately. This paper first introduces a rapid state of the Art in sediment transport modelling in order to point out the specific requirements for process-based models applied to mixed sediments. Based on a preliminary study by Waeles et al. (2007) , which showed the validity of the advection approach to compute fine sand transport, a complete modelling strategy is described: it is applied to the suspended transport of sand and mud mixtures, and accounts for consolidation of mixed sediments. Special care is paid to the realistic representation of the structure and density of sand and mud mixtures, and to the segregation in consolidating sediment layers. The model state variables are the different classes of particles, generally classified according to their size, and grouped into categories that are either transported as bedload or in suspension. The bed is described as thin layers characterised by a distribution of these classes. The erosion law for fine sands and for sand and mud mixtures is a function of the excess shear stress calibrated against measurements in a small flume. The transition between cohesive and non-cohesive behaviours is parameterised through a critical mud fraction that depends on the sand grain size: the coarser the sand, the higher the mud content before the sediment becomes cohesive. The consolidation module is based on Gibson equation formulated for each class, and modified to account for segregation. Constitutive relationships are calibrated by means of laboratory settling tests. In the deposition module, new deposits may be managed in different ways (creation of a new layer or integration into the existing surficial layer) depending on the mud fraction and its relative concentration. When deposited material is mixed with the surficial sediment, pores between coarser particles are first filled up with finer particles before increasing the layer thickness. The new modelling frame has first been used to simulate laboratory settling tests with mixed sediments. When the initial mixture density is low, sand particles can settle through the mud and form a dense sandy layer on the bottom. In a second application, the model is used to describe sorting processes when tidal currents re-suspend a sand and mud mixture. A sand layer is then likely to form within the sediment, while the surficial layers are muddier. A dynamic bed armouring process is shown: although sand is easily resuspended, eroded grains in the sand layer settle rapidly, reducing the erosion of underlying sediment. Resulting suspended sediment concentration is strongly reduced, as well as sediment fluxes. The application demonstrates the model ability to simulate layering processes and time-variations of sediment erodibility.

Sediment transport modelling in estuarine environments, characterised by cohesive and non-cohesive sediment mixtures, has to consider a time variation of erodibility due to consolidation. Generally, validated by settling column experiments, mud consolidation is now fairly well simulated; however, numerical models still have difficulty to simulate accurately the sedimentation and consolidation of mixed sediments for a wide range of initial conditions. This is partly due to the difficulty to formulate the contribution of sand in the hindered settling regime when segregation does not clearly occur. Based on extensive settling experiments with mud-sand mixtures, the objective of this study was to improve the numerical modelling of mixed-sediment consolidation by focusing on segregation processes. We used constitutive relationships following the fractal theory associated with a new segregation formulation based on the relative mud concentration. Using specific sets of parameters calibrated for each test—with different initial sediment concentration and sand content—the model achieved excellent prediction skills for simulating sediment height evolutions and concentration vertical profiles. It highlighted the model capacity to simulate properly the segregation occurrence for mud-sand mixtures characterised by a wide range of initial conditions. Nevertheless, calibration parameters varied significantly, as the fractal number ranged from 2.64 to 2.77. This study investigated the relevance of using a common set of parameters, which is generally required for 3D sediment transport modelling. Simulations were less accurate but remained satisfactory in an operational approach. Finally, a specific formulation for natural estuarine environments was proposed, simulating correctly the sedimentation-consolidation processes of mud-sand mixtures through 3D sediment transport modelling.