Forecasting Estuarine and Coastal Salinity to Improve Fisheries Management and Aquaculture Productivity

Host: Andrew Ross and Charles Stock

Estuaries and other coastal ocean environments present a challenge for earth system modeling and forecasting as they integrate forcing from the atmosphere, land, and ocean over fine spatial and temporal scales. Nevertheless, skillful forecasts of estuarine conditions, such as water temperature and salinity, have the potential to aid management of water quality, improve yields and sustainability of fisheries, and reduce the public health impacts of harmful algal blooms and pathogenic bacteria. Previous research into estuarine and coastal forecasts has primarily focused on near-term forecasts for the next 1-2 days, but realizing many of the potential benefits of these forecasts will require longer-range outlooks.

In this project, we will explore whether extended-range forecasts of freshwater river discharge can enable skillful and useful forecasts of coastal and estuarine salinity. The project will begin with a targeted application on the East Coast of the United States in Chesapeake Bay, although applications to a domain spanning the broader Northwest Atlantic Ocean are also possible. Our previous research has used a numerical ocean model to produce 35-day forecasts of water temperature, salinity, and dissolved oxygen for Chesapeake Bay. This project will enhance these forecasts by working with output from NOAA’s operational National Water Model to develop forecasts of river discharge for the major tributaries of Chesapeake Bay, adding these forecasts as drivers to the Chesapeake Bay model, and assessing the resulting salinity forecast skill and potential applications to aquaculture and fisheries management. Our hypothesis is that these river forecasts will improve the model forecasts of salinity in the tributary estuaries of Chesapeake Bay, making the salinity forecasts more useful for aquaculture and other applications that are sensitive to the sharp gradients and rapid fluctuations in salinity that occur in the tributaries.

The intern will gain experience working with NOAA’s operational forecast products and coastal ocean observational data. Some previous experience using Python to analyze and visualize model output and time series data will be helpful, and the prospective intern should have an interest in learning about hydrodynamic models used to simulate estuaries and oceans. The project has some adaptability depending on the applicant’s background and interests, which may include oceanography, hydrology, weather forecasting, estuarine ecology and fisheries management, or related fields.