Abstract. In estuaries suspended sediment concentration (SSC) is one of the most important contributors to turbidity, which influences habitat conditions and ecological functions of the system. Sediment dynamics differs depending on sediment supply and hydrodynamic forcing conditions that vary over space and over time. A robust sediment transport model is a first step in developing a chain of models enabling simulations of contaminants, phytoplankton and habitat conditions.This works aims to determine turbidity levels in the complex-geometry delta of the San Francisco estuary using a process-based approach (Delft3D Flexible Mesh software). Our approach includes a detailed calibration against measured SSC levels, a sensitivity analysis on model parameters and the determination of a yearly sediment budget as well as an assessment of model results in terms of turbidity levels for a single year, water year (WY) 2011.Model results show that our process-based approach is a valuable tool in assessing sediment dynamics and their related ecological parameters over a range of spatial and temporal scales. The model may act as the base model for a chain of ecological models assessing the impact of climate change and management scenarios. Here we present a modeling approach that, with limited data, produces reliable predictions and can be useful for estuaries without a large amount of processes data.

Suspended sediment concentration is an important estuarine health indicator. Estuarine ecosystems rely on the maintenance of habitat conditions, which are changing due to direct human impact and climate change. This study aims to evaluate the impact of climate change relative to engineering measures on estuarine fine sediment dynamics and sediment budgets. We use the highly engineered San Francisco Bay-Delta system as a case study. We apply a process-based modeling approach (Delft3D-FM) to assess the changes in hydrodynamics and sediment dynamics resulting from climate change and engineering scenarios. The scenarios consider a direct human impact (shift in water pumping location), climate change (sea level rise and suspended sediment concentration decrease), and abrupt disasters (island flooding, possibly as the results of an earthquake). Levee failure has the largest impact on the hydrodynamics of the system. Reduction in sediment input from the watershed has the greatest impact on turbidity levels, which are key to primary production and define habitat conditions for endemic species. Sea level rise leads to more sediment suspension and a net sediment export if little room for accommodation is left in the system due to continuous engineering works. Mitigation measures like levee reinforcement are effective for addressing direct human impacts, but less effective for a persistent, widespread, and increasing threat like sea level rise. Progressive adaptive mitigation measures to the changes in sediment and flow dynamics Climatic Change (2017) resulting from sea level rise may be a more effective strategy. Our approach shows that a validated process-based model is a useful tool to address long-term (decades to centuries) changes in sediment dynamics in highly engineered estuarine systems. In addition, our modeling approach provides a useful basis for long-term, process-based studies addressing ecosystem dynamics and health.

Peak river flows transport fine sediment, nutrients, and contaminants that may deposit in the estuary. This study explores the importance of peak river flows on sediment dynamics with special emphasis on channel network configurations. The Sacramento-San Joaquin Delta, which is connected to San Francisco Bay (California, USA), motivates this study and is used as a validation case. Besides data analysis of observations, we applied a calibrated process-based model (D-Flow FM) to explore and analyze high-resolution (∼100 m, ∼1 h) dynamics. Peak river flows supply the vast majority of sediment into the system. Data analysis of six peak flows (between 2012 and 2014) shows that on average, 40 % of the input sediment in the system is trapped and that trapping efficiency depends on timing and magnitude of river flows. The model has 90 % accuracy reproducing these trapping efficiencies. Modeled deposition patterns develop as the result of peak river flows after which, during low river flow conditions, tidal currents are not able to significantly redistribute deposited sediment. Deposition is quite local and mainly takes place at a deep junction. Tidal movement is important for sediment resuspension, but river induced, tide residual currents are responsible for redistributing the sediment towards the river banks and to the bay. We applied the same forcing for four different channel configurations ranging from a full delta network to a schematization of the main river. A higher degree of network schematization leads to higher peak-sediment export downstream to the bay. However, the area of sedimentation is similar for all the configurations because it is mostly driven by geometry and bathymetry.

No abstract

Abstract. In estuaries most of the sediment load is carried in suspension. Sediment dynamics differ depending on sediment supply and hydrodynamic forcing conditions that vary over space and over time. Suspended sediment concentration (SSC) is one of the most important contributors to turbidity, which influences habitat conditions and ecological functions of the system. A robust sediment model is the first step towards a chain of model including contaminants and phytoplankton dynamics and habitat modeling. This works aims to determine turbidity levels in the complex-geometry Delta of San Francisco Estuary using a process-based approach (D-Flow Flexible Mesh software). Our approach includes a detailed calibration against measured SSC levels, a sensitivity analysis on model parameters, the determination of a yearly sediment budget as well as an assessment of model results in terms of turbidity levels for a single year (Water Year 2011). Model results shows that our process-based approach is a valuable tool in assessing sediment dynamics and their related ecological parameters over a range of spatial and temporal scales. The current model may act as the base model for a chain of ecological models and climate scenario forecasting.