Outflow from the Sacramento–San Joaquin Delta is a key parameter used in the management of the San Francisco Bay–Delta system. At present we can estimate this by assuming a steady state balance of inflows and outflows (Dayflow) or by direct measurement. In this paper, I explore differences between observed sub-tidal variations in measured outflow and Dayflow values using water level and flow data taken during the summer of 2015 and an analytical framework based on the sub-tidally filtered St. Vénant equations. This analysis shows that flows associated with sub-tidal water level variations in the Delta explain most of the difference between the two flow measures. These variations largely result from low-frequency variations in sea level in the coastal ocean and to wind stresses acting on Suisun Bay, with spring–neap variations in tides playing a lesser role. Overall, a comparison of Dayflow and the direct flow measurement for water years 2008 to 2014 shows that the two flow measures are in good agreement, although the root mean square difference between the two values (ca. 5,000 cfs) is comparable to—or larger than—typical low flow values of Dayflow.

This paper, part of the collection of research comprising the State of Bay–Delta Science 2016, describes advances during the past decade in understanding flow dynamics and how water-quality constituents move within California’s Sacramento–San Joaquin River Delta (Delta). Water-quality constituents include salinity, heat, oxygen, nutrients, contaminants, organic particles, and inorganic particles. These constituents are affected by water diversions and other human manipulations of flow, and they greatly affect the quantity and quality of benthic, pelagic, and intertidal habitat in the Delta. The Pacific Ocean, the Central Valley watershed, human intervention, the atmosphere, and internal biogeochemical processes are all drivers of flow and transport in the Delta. These drivers provide a conceptual framework for presenting recent findings. The tremendous expansion of acoustic and optical instruments deployed in the Delta over the past decade has greatly improved our understanding of how tidal variability affects flow and transport. Sediment is increasingly viewed as a diminishing resource needed to sustain pelagic habitat and tidal marsh, especially as sea level rises. Connections among the watershed, Delta, and San Francisco Bay that have been quantified recently highlight that a landscape view of this system is needed, rather than consideration of each region in isolation. We discuss interactions of multiple drivers and information gaps.

A one-dimensional numerical model that simulates the effects of whitecapping waves was used to investigate the importance of whitecapping waves to vertical mixing at a 3-meter-deep site in Franks Tract in the Sacramento-San Joaquin Delta over an 11-day period. Locally-generated waves of mean period approximately 2 s were generated under strong wind conditions; significant wave heights ranged from 0 to 0.3 m. A surface turbulent kinetic energy flux was used to model whitecapping waves during periods when wind speeds > 5 m s-1 (62% of observations). The surface was modeled as a wind stress log-layer for the remaining 38% of the observations. The model results demonstrated that under moderate wind conditions (5–8 m s-1 at 10 m above water level), and hence moderate wave heights, whitecapping waves provided the dominant source of turbulent kinetic energy to only the top 10% of the water column. Under stronger wind (> 8 m s-1), and hence larger wave conditions, whitecapping waves provided the dominant source of turbulent kinetic energy over a larger portion of the water column; however, this region extended to the bottom half of the water column for only 7% of the observation period. The model results indicated that phytoplankton concentrations close to the bed were unlikely to be affected by the whitecapping of waves, and that the formation of concentration boundary layers due to benthic grazing was unlikely to be disrupted by whitecapping waves. Furthermore, vertical mixing of suspended sediment was unlikely to be affected by whitecapping waves under the conditions experienced during the 11-day experiment. Instead, the bed stress provided by tidal currents was the dominant source of turbulent kinetic energy over the bottom half of the water column for the majority of the 11-day period.

Over the past 15 years, the development and application of multi-dimensional hydrodynamic models in San Francisco Bay and the Sacramento–San Joaquin Delta has transformed our ability to analyze and understand the underlying physics of the system. Initial applications of three-dimensional models focused primarily on salt intrusion, and provided a valuable resource for investigating how sea level rise and levee failures in the Delta could influence water quality in the Delta under future conditions. However, multi-dimensional models have also provided significant insights into some of the fundamental biological relationships that have shaped our thinking about the system by exploring the relationship among X2, flow, fish abundance, and the low salinity zone. Through the coupling of multi-dimensional models with wind wave and sediment transport models, it has been possible to move beyond salinity to understand how large-scale changes to the system are likely to affect sediment dynamics, and to assess the potential effects on species that rely on turbidity for habitat. Lastly, the coupling of multi-dimensional hydrodynamic models with particle tracking models has led to advances in our thinking about residence time, the retention of food organisms in the estuary, the effect of south Delta exports on larval entrainment, and the pathways and behaviors of salmonids that travel through the Delta. This paper provides an overview of these recent advances and how they have increased our understanding of the distribution and movement of fish and food organisms. The applications presented serve as a guide to the current state of the science of Delta modeling and provide examples of how we can use multi-dimensional models to predict how future Delta conditions will affect both fish and water supply.

We investigate the fidelity of the Delta Simulation Model-2 (DSM2), a one-dimensional branched network hydrodynamics solver, which is used to model water quality and ecology in the Sacramento–San Joaquin Delta estuary. We find that while DSM2 reproduces the total flows well, it does not accurately represent the harmonic components of the tides and tidal modulation of subtidal flow. The inaccurate representation of tidal dynamics affects prediction of subtidal flows, flow splits at key junctions, and salinity. These deviations are the result of coarse spatial and temporal representation of tides as well as unrepresented estuarine physical processes. We propose and evaluate two types of schemes intended to improve fidelity: modifying the model domain and specifying fine grid and boundary conditions, and incorporating and parameterizing more complex physical processes into the 1-D model. We also develop a comprehensive protocol to evaluate the model in which we assess the fidelity of model results. In this protocol, we also include a decomposition of the model error into a systematic component because of model representation, and an unsystematic component, which includes errors from both unmodeled physical processes and data precision. Our analysis reveals that these recommendations would be effective provided they can be incorporated with model recalibration. Both our proposed schemes and the model evaluation process will be useful in analyzing models of networked surface water systems such as the Delta in which the distribution of observations is spatially inhomogeneous.