The flocculation of cohesive sediment in the presence of waves is investigated using high-resolution field observations and a newly-developed flocculation model based on artificial neural networks. Vertical profiles of suspended sediment concentration and turbulent intensity are estimated using measurements of current profile and acoustic backscatter. The vertical distribution of floc size is estimated using an artificial neural network (ANN) that is trained and validated using floc size measurements at one vertical level. Data analysis suggests a linear correlation between suspended sediment concentration and turbulence intensity. Observations and numerical simulations show that floc size is inversely related to sediment concentration, turbulence intensity and water temperature. The numerical results indicate that floc growth is supported by low concentration and low turbulence. In the vertical direction, mean size of flocs decreases toward the bottom, suggesting floc breakage due to increasing turbulence intensity toward the bed. A significant decrease in turbulent shear could occur within the bottom few-cm, related to increased damping of turbulence by sediment induced density stratification. The results of the numerical simulations presented here are consistent with the concept of a cohesive sediment particle undergoing aggregation-fragmentation processes, and suggest that the ANN can be a precise tool to study flocculation processes.
Backscatter output from a 10 MHz acoustic Doppler velocimeter (ADV) was used to quantify suspended sediment concentrations in a laboratory setting using sand-sized particles. The experiments included (a) well-sorted sand samples ranging in size from 0.112 to 0.420 mm, obtained by the sieving of construction sand, (b) different, known mixtures of these well-sorted fractions, and (c) sieved natural beach sand with median sizes ranging from 0.112 to 0.325 mm. The tested concentrations ranged from 25 to 3000 mg·L −1 . The backscatter output was empirically related to concentration and sediment size, and when non-dimensionalized by acoustic wavelength, a dimensionless sediment size gradation coefficient. Size-dependent upper and lower bounds on measurable concentrations were also established empirically. The range of measurable conditions is broad enough to make the approach useful for sand sizes and concentrations commonly encountered in nature. A new method is proposed to determine concentrations in cases of mixed-size sediment suspensions when only calibration data for well-sorted constituent sands are available. This approach could potentially allow better estimates when the suspended load is derived from but is not fully representative of the bed material, and when the size characteristics of the suspended material are varying in time over the period of interest. Differences in results between the construction and beach sands suggest that sediment shape may also need to be considered, and point to the importance of calibrating to sediments encountered at the site of interest.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.