On the importance of temporal floc size statistics and yield strength for population balance equation flocculation model.

Many aquatic environments contain cohesive sediments that flocculate and create flocs with a wide range of sizes. The Population Balance Equation (PBE) flocculation model is designed to predict the time-dependent floc size distribution and should be more complete than models based on median floc size. However, a PBE flocculation model includes many empirical parameters to represent important physical, chemical, and biological processes. We report a systematic investigation of key model parameters of the open-source PBE-based size class flocculation model FLOCMOD (Verney, Lafite, Claude Brun-Cottan and Le Hir, 2011) using the measured temporal floc size statistics reported by Keyvani and Strom (2014) at a constant turbulent shear rate S. Results show that the median floc size d50, in terms of both the equilibrium floc size and the initial floc growth, is insufficient to constrain the model parameters. A comprehensive error analysis shows that the model is capable of predicting three floc size statistics d16, d50 and d84, which also reveals a clear trend that the best calibrated fragmentation rate (inverse of floc yield strength) is proportional to the floc size statistics considered. Motivated by this finding, the importance of floc yield strength is demonstrated in the predicted temporal evolution of floc size by modeling the floc yield strength as microflocs and macroflocs giving two corresponding fragmentation rates. The model shows a significantly improved agreement in matching the measured floc size statistics.

Modeling the Morphodynamics of Coastal Responses to Extreme Events: What Shape Are We In?

This review focuses on recent advances in process-based numerical models of the impact of extreme storms on sandy coasts. Driven by larger-scale models of meteorology and hydrodynamics, these models simulate morphodynamics across the Sallenger storm-impact scale, including swash,collision, overwash, and inundation. Models are becoming both wider (as more processes are added) and deeper (as detailed physics replaces earlier parameterizations). Algorithms for wave-induced flows and sediment transport under shoaling waves are among the recent developments. Community and open-source models have become the norm. Observations of initial conditions (topography, land cover, and sediment characteristics) have become more detailed, and improvements in tropical cyclone and wave models provide forcing (winds, waves, surge, and upland flow) that is better resolved and more accurate, yielding commensurate improvements in model skill. We foresee that future storm-impact models will increasingly resolve individual waves, apply data assimilation, and be used in ensemble modeling modes to predict uncertainties.

Oil-mineral flocculation and settling velocity in saline water.

Cohesive particles in aquatic systems can play an important role in determining the fate of spilled oil via the generation of Oil-Mineral Aggregates (OMAs). Series of laboratory experiments have been conducted aiming at filling the knowledge gap regarding how cohesive clay particles influence the accumulation of petroleum through forming different aggregate structures and their resulting settling velocity. OMAs have been successfully created in a stirring jar with artificial sea-water, crude oil and two types of most common cohesive minerals, Kaolinite and Bentonite clay. With the magnetic stirrer adjusted to 490 rpm to provide a high level homogeneous flow turbulence (Turbulence dissipation ε estimated to be about 0.02 m2⋅s-3), droplet OMAs and flake/solid OMAs were obtained in oil-Kaolinite sample and oil-Bentonite sample, respectively. Kaolinite clay with relatively low flocculation rate (Rf = 0.13 min-1) tends to physically attach around the surface of oil droplets. With the lower density of oil, these oil-Kaolinite droplet OMAs generally show lower settling velocity comparing to pure mineral Kaolinite flocs. Differently, Bentonite clay with higher flocculation rate (Rf = 0.66 min-1) produces more porous flocs that can absorb or be absorbed by the oil and form compact flake/solid OMAs with higher density and settling velocity than pure Bentonite flocs. In the mixed Kaolinite-Bentonite sample (1:1 in weight), oil is observed to preferably interacting with Bentonite and increase settling velocity especially in larger floc size classes.