There has been considerable debate about effects of entrainment of endangered Delta Smelt (Hypomesus transpacificus) at water export facilities located in the Sacramento–San Joaquin River Delta. In this paper we use a behavior-driven movement model (BMM) to simulate the movement of adult Delta Smelt, which, in conjunction with a population dynamics model, estimates the proportion of the population that is lost to entrainment, i.e., proportional entrainment loss (PEL). Parameters of the population model are estimated by maximum likelihood by comparing predictions to data from Fall Midwater Trawl (FMWT) and Spring Kodiak Trawl (SKT) surveys, as well as to daily salvage estimates. Our objectives are to evaluate different movement behavior hypotheses, to rank estimates of PEL based on how well predictions fit the data, and to sharpen our understanding of the data to inform future research and monitoring decisions.

We applied the modeling framework to data from water year 2002—a year when salvage was high—and tested 30 combinations of six behavior and five population dynamics models. More complex process and observation assumptions in the population model led to much improved fits in most cases, but did not appreciably influence PEL predictions, which were largely determined by movement predictions from the BMMs. Estimates of PEL varied considerably among behaviors (2% to 40%). The model with the highest predictive capability explained 98% of the variation in FMWT data across regions, 70% of the variation in SKT data across regions and surveys, and 28% and 43% of the daily variation in salvage at federal and state fish screening facilities, respectively. The PEL estimate from this model was 35%, more than double the original estimate from Kimmerer (2008) of 15%. While PEL estimates provided in this study should be considered preliminary, our framework for testing combined behavior-driven movement models and population dynamics models is an improvement compared to earlier efforts.

Delta Smelt, Hypomesus transpacificus, is an endangered pelagic fish native to the San Francisco Estuary. The distribution of Delta Smelt in the estuary shifts landward from low-salinity habitat to freshwater habitat before spawning. This spawning migration often coincides with the first substantial freshwater inflow to the estuary during winter. To accomplish this landward shift in distribution, Delta Smelt are believed to use the tides by swimming to faster-moving currents during flood tides and then repositioning themselves to slower-moving currents to reduce seaward movement on ebb tides. Studies have hypothesized that the swimming behavior of Delta Smelt during this period is influenced by environmental conditions such as salinity and turbidity. The details of these swimming behaviors—including the extent to which flows, salinity, and turbidity affect behaviors and distributions—are uncertain. The spawning migration is of management interest because an increase in observed counts of Delta Smelt at the South Delta water-export facilities has coincided roughly with the spawning migration in many years. In this study, we investigated a range of hypothesized swimming behaviors using a three-dimensional particle-tracking model for water year 2002 during the spawning migration, and compared the predicted distributions of Delta Smelt to distributions inferred from catch data. Our goal was to improve understanding of the influence of Delta Smelt swimming on distribution, and, ultimately, to develop a modeling tool to help management agencies identify conditions associated with entrainment losses. Predictions of Delta Smelt distributions and entrainment varied greatly among behaviors. Without swimming, Delta Smelt would be rapidly transported seaward of Suisun Bay, while continuous tidal migration would move them deep into the interior Delta. These behaviors and a simple turbidity-driven behavior model predicted distributions inconsistent with observations, while more complex behavior rules allowed improved predictions.