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A. Manning and K. Dyer (2007)

Mass settling flux of fine sediments in Northern European estuaries: Measurements and predictions

Marine Geology, 245(1):107-122.

This study describes a new flocculation model, which was based entirely on observations of settling floc spectra and turbulent shear stresses, acquired primarily from a series of in-situ experiments conducted in several European estuaries. The synthesis identified that the key components which best quantitatively describe a floc population are: the changes in the macrofloc (160 μm) and microfloc settling velocities (WsmacroEM and WsmicroEM), together with how the suspended matter is distributed across each floc sub-population (SPMratioEM). The WsmacroEM algorithm displayed an increase in settling velocity at low shear stresses due to flocculation enhanced by shear, and floc disruption at higher stresses for the same concentration; the transition being a turbulent shear stress of about 0.36 N m−2. The combination of the three algorithms into a single equation to predict mass settling flux (MSFEM), estimated the total flux of the 157 measured floc samples with a cumulative error4\%. In comparison, the use of single Ws of 0.5 mm s−1 and 5 mm s−1 were both in error by an average of −86\% and +41\%, respectively. A concentration — settling parameterisation and the van Leussen techniques under-predicted the total cumulative flux by 35 and 38\%, respectively. Furthermore, the analysis indicated that the various existing methods all incurred high predictive errors, at times under-estimating by over 70\%, as concentration levels rose in close proximity to the bed. The findings of this study demonstrate the new Manning Floc Settling Velocity (MFSV) empirical model has flexibility in adapting to a wide range of both turbulent shear stress and suspended sediment concentration estuarine conditions.

turbulent shear stress, flocculation, INSSEV instrument, mass settling flux, cohesive sediment, settling velocity, parameterisation, macrofloc, numerical sediment transport models, Suspended particulate matter
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