Date of Award

Winter 2019

Project Type


Program or Major

Earth Sciences

Degree Name

Doctor of Philosophy

First Advisor

Thomas C. Lippmann

Second Advisor

Diane L Foster

Third Advisor

Christopher R. Sherwood


The goals of this research are to expand our understanding of, and improve predictions of bed shear stress in estuarine environments using both observational datasets and numerical modeling. To accurately predict sediment transport, a good understanding of the bed shear stress that drives the sediment erosion, suspension and deposition is essential. Shear stress is a function of both the hydrodynamics in the system and the characteristics of the sediment that comprise the bed itself. The hydrodynamic forcing is determined by tides, waves, meteorological effects, rivers, or some combination that can change on time scales of a few minutes to a few days. The sediment characteristics are site specific, and often vary spatially within a given estuary. The size, shape, material type, organic content, and time in a given location can determine whether the sediment will move, and what mode of transportation is probable (i.e. bed load or suspended load). The temporal and spatial variability of these factors make it difficult to collect comprehensive observational datasets, and often only represent a small portion of the overall processes of interest. Numerical models become useful tools to predict how the interactions of different hydrodynamic conditions and sediment characteristics can change the bed shear stress on a variety of scales. Consequently, these models require parameterizing sub-grid scale processes, and suppressing noise associated with numerical discretization. A useful model then becomes a balance between capturing the processes of interest within a particular grid scale and the available computational resources. The purpose of this research is to use the observational datasets from both the hydrodynamics and sediment and bed characteristics of a particular estuary, and 1) verify the hydrodynamic model, and 2) use that model to characterize and predict the spatial and temporal variability of bed shear stress and sediment transport under different hydrodynamic conditions (tides, waves, meteorological forcing, etc.) and in the presence/absence of vegetation (eelgrass). Ultimately this knowledge will useful for more accurate estimates of sediment transport and nutrient fluxes under varying hydrodynamic conditions in the Great Bay estuary (and inform similar estuarine mudflat environments), which has been previously difficult.