We are excited that Rae’s MS work on modeling of floc sizes was recently published in the Journal of Geophysical Research: Oceans.
Kuprenas, R., D. Tran, and K. Strom. (2018), A shear‐limited flocculation model for dynamically predicting average floc size, Journal of Geophysical Research: Oceans, doi: 10.1029/2018JC014154
- A modification to the floc breakup model of Winterwerp (1998) is presented
- The modification limits floc sizes to that of the Kolmogorov microscale
- Doing so allows floc model calibration coefficients to be used more broadly
The accuracy of sediment transport models depends on the selection of an appropriate sediment settling velocity. In general, settling velocity is primarily dependent on the size and density of the particles in the water column. Determining this value for mud suspensions can be difficult because the small cohesive particles can aggregate to form flocs whose sizes and density are a function of hydrodynamic and physiochemical conditions of the suspension. Here we present a new model for predicting floc size as a function of hydrodynamic conditions and inherited floc sizes. The new approach is a simple modification to the existing Winterwerp (1998) floc size model. The modification is significant in that it yields predictions that are more inline with observations and theory regarding the upper limit on floc size. The modification we propose is to make the ratio of the applied stress on a floc, over the strength of the floc, a function of the floc size relative to the Kolmogorov microscale. The outcome of the modification is that flocs are not allowed to surpass the Kolmogorov microscale in size and that calibrated aggregation and breakup coefficients obtained at one suspended sediment concentration can be used to predict floc size under other concentrations without recalibration. In this paper, we present the motivation for the modification, the functionality of the modification, and we make a comparison of the updated model with laboratory and field data. Overall the modification shows promise as a tool for improved prediction of cohesive mud transport.