Erosion characteristics and floc strenght of Athabasca river cohesive sediments: towards managing sediment-related issues

Purpose: Most of Canada’s tar sands exploitations are located in the Athabasca river basin. Deposited cohesive sediments in Athabasca river and tributaries are a potential source of PAHs in the basin. Erosional behavior of cohesive sediments depends not only of fluid turbulence but on sediments structure and particularly the influence of organic content. This research tries to describe this behavior in Athabasca river sediments. Methods: An experimental study of cohesive sediments dynamics in one of the tributaries, the Muskeg river, was developed in a rotating annular flume. Variation of the shear stress allowed the determination of erosional strength for beds with different consolidation periods. Particle size measurements were made with a laser diffraction device operated in a continuous flow through mode. Optical analyses of flocs (ESEM and TEM) were performed with samples taken at the end of the experiments. Results: An inverse relationship between suspended sediment concentration (SS) and the consolidation period was found. The differences are related in this research to the increasing organic content of the sediments with consolidation period. The particle size measurements during the experiments showed differences on floc strength that are also related to changing organic content during different consolidation periods. ESEM and TEM observations confirm the structural differences for beds with different consolidation periods. The effects of SFGL on floc structure and in biostabilization of the bed are discussed. Conclusions: It is recommended in this paper that consolidation period should be taken into account for the modeling of erosion of cohesive sediments in the Athabasca river. Relating to transport models of pollutants (PAHs) it is highly recommended to consider flocs organic content, particularly algae, in the resuspension module.Environment Canada, CONACY

A structure-function based approach to floc hierarchy and evidence for the non-fractal nature of natural sediment flocs

Abstract Natural sediment flocs are fragile, highly irregular, loosely bound aggregates comprising minerogenic and organic material. They contribute a major component of suspended sediment load and are critical for the fate and flux of sediment, carbon and pollutants in aquatic environments. Understanding their behaviour is essential to the sustainable management of waterways, fisheries and marine industries. For several decades, modelling approaches have utilised fractal mathematics and observations of two dimensional (2D) floc size distributions to infer levels of aggregation and predict their behaviour. Whilst this is a computationally simple solution, it is highly unlikely to reflect the complexity of natural sediment flocs and current models predicting fine sediment hydrodynamics are not efficient. Here, we show how new observations of fragile floc structures in three dimensions (3D) demonstrate unequivocally that natural flocs are non-fractal. We propose that floc hierarchy is based on observations of 3D structure and function rather than 2D size distribution. In contrast to fractal theory, our data indicate that flocs possess characteristics of emergent systems including non-linearity and scale-dependent feedbacks. These concepts and new data to quantify floc structures offer the opportunity to explore new emergence-based floc frameworks which better represent natural floc behaviour and could advance our predictive capacity

A neighborhood statistics model for predicting stream pathogen indicator levels

Because elevated levels of water-borne Escherichia coli in streams are a leading cause of water quality impairments in the U.S., water-quality managers need tools for predicting aqueous E. coli levels. Presently, E. coli levels may be predicted using complex mechanistic models that have a high degree of unchecked uncertainty or simpler statistical models. To assess spatio-temporal patterns of instream E. coli levels, herein we measured E. coli, a pathogen indicator, at 16 sites (at four different times) within the Squaw Creek watershed, Iowa, and subsequently, the Markov Random Field model was exploited to develop a neighborhood statistics model for predicting instream E. coli levels. Two observed covariates, local water temperature (degrees Celsius) and mean cross-sectional depth (meters), were used as inputs to the model. Predictions of E. coli levels in the water column were compared with independent observational data collected from 16 in-stream locations. The results revealed that spatio-temporal averages of predicted and observed E. coli levels were extremely close. Approximately 66 % of individual predicted E. coli concentrations were within a factor of 2 of the observed values. In only one event, the difference between prediction and observation was beyond one order of magnitude. The mean of all predicted values at 16 locations was approximately 1 % higher than the mean of the observed values. The approach presented here will be useful while assessing instream contaminations such as pathogen/pathogen indicator levels at the watershed scale

A structure–function based approach to floc hierarchy and evidence for the non-fractal nature of natural sediment flocs

AbstractNatural sediment flocs are fragile, highly irregular, loosely bound aggregates comprising minerogenic and organic material. They contribute a major component of suspended sediment load and are critical for the fate and flux of sediment, carbon and pollutants in aquatic environments. Understanding their behaviour is essential to the sustainable management of waterways, fisheries and marine industries. For several decades, modelling approaches have utilised fractal mathematics and observations of two dimensional (2D) floc size distributions to infer levels of aggregation and predict their behaviour. Whilst this is a computationally simple solution, it is highly unlikely to reflect the complexity of natural sediment flocs and current models predicting fine sediment hydrodynamics are not efficient. Here, we show how new observations of fragile floc structures in three dimensions (3D) demonstrate unequivocally that natural flocs are non-fractal. We propose that floc hierarchy is based on observations of 3D structure and function rather than 2D size distribution. In contrast to fractal theory, our data indicate that flocs possess characteristics of emergent systems including non-linearity and scale-dependent feedbacks. These concepts and new data to quantify floc structures offer the opportunity to explore new emergence-based floc frameworks which better represent natural floc behaviour and could advance our predictive capacity.</jats:p