Progress in Operational Modeling in Support of Oil Spill Response

Abstract

Following the 2010 Deepwater Horizon accident of a massive blow-out in the Gulf of Mexico, scientists from government, industry, and academia collaborated to advance oil spill modeling and share best practices in model algorithms, parameterizations, and application protocols. This synergy was greatly enhanced by research funded under the Gulf of Mexico Research Initiative (GoMRI), a 10-year enterprise that allowed unprecedented collection of observations and data products, novel experiments, and international collaborations that focused on the Gulf of Mexico, but resulted in the generation of scientific findings and tools of broader value. Operational oil spill modeling greatly benefited from research during the GoMRI decade. This paper provides a comprehensive synthesis of the related scientific advances, remaining challenges, and future outlook. Two main modeling components are discussed: Ocean circulation and oil spill models, to provide details on all attributes that contribute to the success and limitations of the integrated oil spill forecasts. These forecasts are discussed in tandem with uncertainty factors and methods to mitigate them. The paper focuses on operational aspects of oil spill modeling and forecasting, including examples of international operational center practices, observational needs, communication protocols, and promising new methodologies.

Oil Spill Modeling: A Critical Review on Current Trends, Perspectives, and Challenges

“…The paper is structured as follows: in Section 2, the physical transport and the physico-chemical OWPs are described; in Section 3, the state-of-the-art oil spill models are critically reviewed; Section 4 presents a critical comparison of existing oil spill models, while Section 5 proposes technical recommendations and modeling improvements. The present work expands and updates similar critical review papers, such as [10][11][12][13][14][15].…”

“…This process has a significant role in the vertical interchange among the surface oil spill and the vertical layers of the water column [112]. The main source of uncertainty in oil spill simulations arises from uncertainties in the forcing of models, i.e., ocean circulation, wave and atmospheric coupled models, therefore reliable forecasts are essential for accurately determining the advective transport [15,136]. The volume of turbulent mixing is widely represented via an eddy diffusivity coefficient.…”

“…On the other hand, the Lagrangian models discretize oil slicks as a large number of particles advected by the merged result of winds, waves, and currents, but also being transported via dispersion. Researchers have shown that Lagrangian models are more appropriate for prompt simulations, when oil spill accidents occur, and consequently are easier, more efficient, and computationally more cost-effective than the Eulerian approaches [10,15,147]. The precision of the particle position will depend on the precision of its initial position, on the capacity of the coupled metocean models to guarantee reliable forecasting, and on the involvement of suitable physical mechanisms taking action on the tracked particles [145].…”

The Role of Mesoscale Dynamics over Northwestern Cuba in the Loop Current Evolution in 2010, during the Deepwater Horizon Incident

“…that may affect large-scale circulation is crucial for improving preparedness and response measures in the case of large oil pollution incidents. In a synthesis study that discusses the scientific experience gained in the aftermath of the DwH oil spill, Barker et al [52] argued that high-resolution modeling is necessary to resolve coastal and shelf processes. We showed that among other major meteorological and oceanographic conditions that mainly control the LC/FC evolution, specific southeastern GoM mesoscale processes may also participate in the evolution of hydrocarbon pathways.…”

Responder Needs Addressed by Arctic Maritime Oil Spill Modeling

“…The AMSM project assessed the state of the art of oil spill models used by the private sector, the U.S. and Canadian governments, and other international agencies. In addition to the GNOME model used by the U.S. government, some of these models include the Canadian Oil Spill Modelling Suite, Marine Environmental Modeling Workbench, and OILMAP and SIMAP [23][24][25]. The project identified ice-related gaps in existing oil spill models (e.g., under ice oil storage capacity and spreading, melting, and pooling of oil on ice) that might address them.…”