Abstract. The prediction of cohesive sediment transport requires numerical models which include the dominant physico-chemical processes of fine sediments. Mainly in terms of simulating small scale processes, flocculation of fine particles plays an important role since aggregation processes affect the transport and settling of fine-grained particles. Flocculation algorithms used in numerical models are based on and calibrated using experimental data. A good agreement between the results of the simulation and the measurements is a prerequisite for further applications of the transport functions.

In this work, the sediment transport model (SSIIM) was extended by implementing a physics-based aggregation process model based on McAnally (1999). SSIIM solves the Navier-Stokes-Equations in a three-dimensional, non-orthogonal grid using the k-ε turbulence model. The program calculates the suspended load with the convection-diffusion equation for the sediment concentration.

Experimental data from studies in annular flumes (Hillebrand, 2008; Klassen, 2009) is used to test the flocculation algorithm. Annular flumes are commonly used as a test rig for laboratory studies on cohesive sediments since the flocculation processes are not interfered with by pumps etc. We use the experiments to model measured floc sizes, affected by aggregation processes, as well as the sediment concentration of the experiment. Within the simulation of the settling behavior, we use different formulas for calculating the settling velocity (Stokes, 1850 vs. Winterwerp, 1998) and include the fractal dimension to take into account the structure of flocs.

The aim of the numerical calculations is to evaluate the flocculation algorithm by comparison with the experimental data. The results from these studies have shown, that the flocculation process and the settling behaviour are very sensitive to variations in the fractal dimension. We get the best agreement with measured data by adopting a characteristic fractal dimension n_fc to 1.4. Insufficient results were obtained when neglecting flocculation processes and using Stokes settling velocity equation, as it is often done in numerical models which do not include a flocculation algorithm.

These numerical studies will be used for further applications of the transport functions to the SSIIM model of reservoirs of the Upper Rhine River, Germany.