Journal
ESTUARINE COASTAL AND SHELF SCIENCE
Volume 281, Issue -, Pages -Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ecss.2022.108183
Keywords
Cohesive suspended sediment; Floc size; Meghna estuary; Uncertainty; Sediment deposition rate
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This article examines the uncertainty propagation from input floc size to output sedimentation rate in the Meghna estuary, Bangladesh. The results show that the coefficient of variation ranges from 20% to 38% across three locations. Planners need to consider substantial uncertainty in cohesive sediment transport estimates, especially in deposition-prone areas with increased flooding risk.
Suspended sediment in the Meghna estuary, Bangladesh, typically consists of fine to medium silt near the water surface, silty sand at increasing depth, and sandy silt close to the bed. The behavior of fine, cohesive sediment in a complex environment with multiple drivers, such as river and tidal flows, is comparatively little understood because the deposition and erosion processes depend on many chemical, biological, and physical factors. This article examines the propagation of uncertainty from input floc size to output sedimentation rate in the Meghna estuary, Bangladesh, using a fine-sediment hydro-morphodynamic model that utilizes the cohesive sediment transport module in Delft3D. We assume that sediment particles and flocs are both single-sized throughout the solution domain. The effect of uncertainty in floc size on output sediment transport statistics is examined at three sites of interest located in the Meghna estuary using a novel numerical derived distribution approach. After deriving the probability distribution of suspended cohesive sediment, we find the coefficient of variation to range from 20% to 38% across the three locations. Planners therefore need to consider substantial uncertainty in cohesive sediment transport estimates for the coastal zone of Bangladesh, especially given the increased risk of flooding in deposition-prone areas as they become shallower. The methodology may be readily extended to the estimation of uncertainty in land reclamation and erosion control planning studies.
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