Comparison of the Coupled Model for Oil spill Prediction (CMOP) and the Oil Spill Contingency and Response model (OSCAR) during the DeepSpill field experiment

An oil spill model is an important tool for environmental risk assessment, strategic planning, and tactical decision making in the event of an oil spill. However, limited data exist to evaluate such models and their performance. During the DeepSpill field campaign, a unique dataset was acquired by monitoring a deliberate deep-water oil blowout. In this work, we evaluate and compare two oil spill models ? the Coupled Model for Oil spill Prediction (CMOP) and the Oil Spill Contingency and Response model (OSCAR) against the DeepSpill experiment. We find that the general plume trajectory is captured well with a default model setup for both models. However, to accurately model the surface slick development, it was necessary to alter modeling parameters and incorporate model changes to increase scenario flexibility. Through this work, we build further confidence in the two models and provide suggestions for improvements.

Automated summary

An oil spill model is a crucial tool for environmental risk assessment and decision making during a spill, but there is limited data to assess their performance. This study evaluated and compared two models against a unique dataset from the DeepSpill experiment, finding that default setups captured general plume trajectories well, but adjustments were needed for surface slick development. The study provides suggestions for improvements and increases confidence in the two models.