Journal
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
Volume 116, Issue -, Pages -Publisher
AMER GEOPHYSICAL UNION
DOI: 10.1029/2010JC006352
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Funding
- U.S. Office of Naval Research [N00014-09-1-0134]
- National Science Foundation [OCE-0913283, OCE-0926974]
- ONR [N00014-07-1-0494]
- Division Of Ocean Sciences
- Directorate For Geosciences [0926974] Funding Source: National Science Foundation
- Division Of Ocean Sciences
- Directorate For Geosciences [0913283] Funding Source: National Science Foundation
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Flocculation and bed erodibility are two main processes causing the transport of cohesive sediments to be more complicated than typical noncohesive sediments. Earlier flocculation models assume a constant fractal dimension and/or a constant floc yield strength. However, recent studies have shown that considering both the fractal dimension and the floc yield strength to be variable is critical to the prediction of temporal evolution of floc size. Due to consolidation, it is also well established that critical bed shear stress of a mud bed cannot be parameterized as a constant. This study further investigates how flocculation models with different degrees of complexity and bed erodibility can affect the resulting cohesive sediment resuspension driven by tidal flows. A one-dimensional vertical numerical model for sediment transport is revised to incorporate modules for flocculation and bed erodibility. Model results are compared with data measured in the Ems/Dollard estuary. Model study suggests that it is important to incorporate variable critical shear stress in order to properly model the supply of sediment from the bed. When flocculation is neglected or incorporated incompletely, numerical model predicts nearly zero sediment concentration during slack water and very steep concentration gradient, which are inconsistent with the observed data. When the fractal dimension and the floc yield strength are both considered to be variable, the numerical model predicts much smaller settling velocity and hence captures the more well-mixed condition consistent with field observations.
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