Abstract
Turbulent shear generated within the water column is recognised as having a controlling influence over both the flocculation of fine grained cohesive sediments within estuarine waters, and their respective aggregate break-up. This study examines the inter-relationships between floc characteristics over increasing turbidity (80–200 mg l −1) and turbulent shear (0–0.6 N m −2) environments, by the use of a laboratory flume within which a suspension can be sheared at a controlled rate, and with an unintrusive macro-lens miniature video camera mounted in a viewing port on the flume channel wall. The camera enables the direct simultaneous measurement of both floc size and settling velocity, from which accurate estimates of floc effective density and porosity can be made. Measurements were made 120 s after the induced turbulence has ceased. The instrument has an upper viewing turbidity limit of 210 mg l −1, and a lower resolution of 20 μm. The sediment was collected from the inter-tidal mudflats at Weir Quay on the Tamar Estuary in Devon, Southwest England. The results indicated that increasing turbidity at low shear levels encouraged floc growth, but the effect of the increasing turbulent shear (0.35 N m −2) together with increasing concentration in suspension causes disruption rather than enhancing the flocculation process. At shears up to 0.35 N m −2, the largest size and settling velocity flocs were produced at high concentrations, whereas above 0.35 N m −2 disruption caused smaller flocs at higher concentrations. The use of algorithms which were based either on a single floc characteristic (i.e., size or settling velocity) or a mean fractal dimension, were seen not to accurately approximate the experimental data. A multiple regression analysis of the experimental data produced the following formula, based on mean values of the 20 largest flocs sampled under each of the imposed environmental conditions (referred to as max20size mean values): settling velocity=0.301−0.00337 rms of the gradient in turbulent velocity fluctuations−0.000606 SPM+0.00335 floc size, which proved to be the most accurate representation with an R 2 value of 0.95. A similar formula was determined for the average value of the four fastest settling flocs within each sample-group (max4W S). This highlights the importance of modelling algorithms that are developed from data that take into account effective density variations (i.e., simultaneous size and settling velocity measurement).
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