Modeling Water Column Oil Concentrations with a Lagrangian Element Oil Spill Model (GNOME)

Predicting water column concentrations can be important during an oil spill response in order to understand potential impacts and consider mitigation strategies. These concentrations are also critical to understanding exposure of organisms to oil compounds in the aftermath of a spill (for example, in the injury assessment process). Most oil spill fate and transport models, including NOAA’s “GNOME” model, use a Lagrangian element (particle tracking) approach. This approach has many advantages including allowing for the addition of “behavior” to the particles -- in the case of oil this includes weathering processes like evaporation from surface slicks, dissolution under the surface, and/or rise velocities for droplets within the water column.

Prediction of water column concentrations is sensitive to a number of factors that are not typically well known or understood. These include: the turbulence profile of the water column, the droplet size distribution of oil under the surface, and oil entrainment rates under white-capping seas. Here we review the challenges of modeling oil concentrations in the water column in general, and specifically the challenges of using a Lagrangian element approach. The results of various assumptions are explored with a sensitivity analysis and compared against oil concentrations measured in the field.