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Ocean Numerical Forecast Modelling of Oil Spill
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Ocean Numerical Forecast Modelling of Oil Spill

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Coastal Engineering".

Deadline for manuscript submissions: closed (5 July 2021) | Viewed by 24334

Special Issue Editor

Dr. C. J. Beegle-Krause

E-Mail Website
Guest Editor
SINTEF Ocean, Trondheim, Norway
Interests: ecological modeling; oil; larval fish modeling; decision support; oceanography; marine environment; water quality

Special Issue Information

Dear Colleagues,

The Deepwater Horizon oil spill was a turning point in oil spill preparedness and response. The scientific, governmental, and industry R&D communities have been working hard in the decade since. This Special Issue highlights key developments from these three sectors. Oil spill modeling developments from the Gulf of Mexico Research Initiative are summarized to show the breadth of the research and how this can improve oil spill response and planning. The U.S. Bureau of Ocean Energy Management highlights research to improve oil spill preparedness in the Pacific and Arctic Oceans, in tandem with the GoMRI program. Industry has funded detailed work in areas of changes in dissolved oxygen levels from subsurface oil to improvements in response and analysis.

Dr. C. J. Beegle-Krause
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Oil spill
  • Modeling
  • Lagrangian
  • Oil weathering
  • Oil fate
  • Toxicity
  • Fate and effects
  • Gulf of Mexico
  • Deepwater Horizon oil spill
  • Statistics

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Published Papers (7 papers)

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Research

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19 pages, 1579 KiB  
Article
Numerical Modelling of Oil Spill Transport in Tide-Dominated Estuaries: A Case Study of Humber Estuary, UK
by Chijioke D. Eke, Babatunde Anifowose, Marco J. Van De Wiel, Damian Lawler and Michiel A. F. Knaapen
J. Mar. Sci. Eng. 2021, 9(9), 1034; https://doi.org/10.3390/jmse9091034 - 19 Sep 2021
Cited by 3 | Viewed by 4349
Abstract
Oil spills in estuaries are less studied and less understood than their oceanic counterparts. To address this gap, we present a detailed analysis of estuarine oil spill transport. We develop and analyse a range of simulations for the Humber Estuary, using a coupled [...] Read more.
Oil spills in estuaries are less studied and less understood than their oceanic counterparts. To address this gap, we present a detailed analysis of estuarine oil spill transport. We develop and analyse a range of simulations for the Humber Estuary, using a coupled hydrodynamic and oil spill model. The models were driven by river discharge at the river boundaries and tidal height data at the offshore boundary. Satisfactory model performance was obtained for both model calibration and validation. Some novel findings were made: (a) there is a statistically significant (p < 0.05) difference in the influence of hydrodynamic conditions (tidal range, stage and river discharge) on oil slick transport; and (b) because of seasonal variation in river discharge, winter slicks released at high water did not exhibit any upstream displacement over repeated tidal cycles, while summer slicks travelled upstream into the estuary over repeated tidal cycles. The implications of these findings for operational oil spill response are: (i) the need to take cognisance of time of oil release within a tidal cycle; and (ii) the need to understand how the interaction of river discharge and tidal range influences oil slick dynamics, as this will aid responders in assessing the likely oil trajectories. Full article
(This article belongs to the Special Issue Ocean Numerical Forecast Modelling of Oil Spill)
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17 pages, 1743 KiB  
Article
Responder Needs Addressed by Arctic Maritime Oil Spill Modeling
by Jessica Manning, Megan Verfaillie, Christopher Barker, Catherine Berg, Amy MacFadyen, Michael Donnellan, Mark Everett, Clifton Graham, Jason Roe and Nancy Kinner
J. Mar. Sci. Eng. 2021, 9(2), 201; https://doi.org/10.3390/jmse9020201 - 16 Feb 2021
Cited by 7 | Viewed by 3196
Abstract
There is a greater probability of more frequent and/or larger oil spills in the Arctic region due to increased maritime shipping and natural resource development. Accordingly, there is an increasing need for effective spilled-oil computer modeling to help emergency oil spill response decision [...] Read more.
There is a greater probability of more frequent and/or larger oil spills in the Arctic region due to increased maritime shipping and natural resource development. Accordingly, there is an increasing need for effective spilled-oil computer modeling to help emergency oil spill response decision makers, especially in waters where sea ice is present. The National Oceanic & Atmospheric Administration (NOAA) Office of Response & Restoration (OR&R) provides scientific support to the U.S. Coast Guard Federal On-Scene Coordinator (FOSC) during oil spill response. OR&R’s modeling products must provide adequate spill trajectory predictions so that response efforts minimize economic, cultural, and ecologic impacts, including those to species, habitats, and food supplies. The Coastal Response Research Center is conducting a project entitled Oil Spill Modeling for Improved Response to Arctic Maritime Spills: The Path Forward, in conjunction with modelers, responders, and researchers. A goal of the project is to prioritize new investments in model and tool development to improve response effectiveness in the Arctic. The project delineated FOSC needs during Arctic maritime spill response and provided a solution communicating sources of uncertainty in model outputs using a Confidence Estimates of Oil Model Inputs and Outputs (CEOMIO) table. The table shows the level of confidence (high, medium, low) in a model’s trajectory prediction over scenario-specific time intervals and the contribution of different component inputs (e.g., temperature, wind, ice) to that result. Full article
(This article belongs to the Special Issue Ocean Numerical Forecast Modelling of Oil Spill)
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22 pages, 9449 KiB  
Article
Progress of the Oil Spill Risk Analysis (OSRA) Model and Its Applications
by Zhen-Gang Ji, Zhen Li, Walter Johnson and Guillermo Auad
J. Mar. Sci. Eng. 2021, 9(2), 195; https://doi.org/10.3390/jmse9020195 - 12 Feb 2021
Cited by 5 | Viewed by 3197
Abstract
The Bureau of Ocean Energy Management (BOEM) is responsible for managing the development of US Outer Continental Shelf (OCS) energy and mineral resources. Because oil spills may occur from offshore oil and gas activities, BOEM conducts oil spill risk analysis (OSRA) prior to [...] Read more.
The Bureau of Ocean Energy Management (BOEM) is responsible for managing the development of US Outer Continental Shelf (OCS) energy and mineral resources. Because oil spills may occur from offshore oil and gas activities, BOEM conducts oil spill risk analysis (OSRA) prior to oil and gas lease sales. Since the 1970s, BOEM has developed and applied the OSRA model to evaluate the risk of potential oil spills to environmental resources. This paper summarizes some of the OSRA model progress and applications in the past decade: (1) calculation of the risk of catastrophic oil spills (with a volume over one million barrels), which concludes that the return period of a catastrophic oil spill in OCS areas is estimated to be 165 years; (2) a more efficient way to estimate the probability of oil spill contact to environmental resources in the Gulf of Mexico; (3) weathering calculations in OSRA, which enhances the accuracy of the OSRA model results; and (4) application of OSRA to the Ixtoc I oil spill as an example of how the OSRA model simulates large oil spills for oil spill preparedness and response. Full article
(This article belongs to the Special Issue Ocean Numerical Forecast Modelling of Oil Spill)
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20 pages, 2725 KiB  
Article
Evidence for Ecosystem-Level Trophic Cascade Effects Involving Gulf Menhaden (Brevoortia patronus) Triggered by the Deepwater Horizon Blowout
by Jeffrey W. Short, Christine M. Voss, Maria L. Vozzo, Vincent Guillory, Harold J. Geiger, James C. Haney and Charles H. Peterson
J. Mar. Sci. Eng. 2021, 9(2), 190; https://doi.org/10.3390/jmse9020190 - 12 Feb 2021
Cited by 4 | Viewed by 3249
Abstract
Unprecedented recruitment of Gulf menhaden (Brevoortia patronus) followed the 2010 Deepwater Horizon blowout (DWH). The foregone consumption of Gulf menhaden, after their many predator species were killed by oiling, increased competition among menhaden for food, resulting in poor physiological conditions and [...] Read more.
Unprecedented recruitment of Gulf menhaden (Brevoortia patronus) followed the 2010 Deepwater Horizon blowout (DWH). The foregone consumption of Gulf menhaden, after their many predator species were killed by oiling, increased competition among menhaden for food, resulting in poor physiological conditions and low lipid content during 2011 and 2012. Menhaden sampled for length and weight measurements, beginning in 2011, exhibited the poorest condition around Barataria Bay, west of the Mississippi River, where recruitment of the 2010 year class was highest. Trophodynamic comparisons indicate that ~20% of net primary production flowed through Gulf menhaden prior to the DWH, increasing to ~38% in 2011 and ~27% in 2012, confirming the dominant role of Gulf menhaden in their food web. Hyperabundant Gulf menhaden likely suppressed populations of their zooplankton prey, suggesting a trophic cascade triggered by increased menhaden recruitment. Additionally, low-lipid menhaden likely became “junk food” for predators, further propagating adverse effects. We posit that food web analyses based on inappropriate spatial scales for dominant species, or solely on biomass, provide insufficient indication of the ecosystem consequences of oiling injury. Including such cascading and associated indirect effects in damage assessment models will enhance the ability to anticipate and estimate ecosystem damage from, and provide recovery guidance for, major oil spills. Full article
(This article belongs to the Special Issue Ocean Numerical Forecast Modelling of Oil Spill)
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22 pages, 10904 KiB  
Article
Design of Real—Time Sampling Strategies for Submerged Oil Based on Probabilistic Model Predictions
by Chao Ji, James D. Englehardt and Cynthia Juyne Beegle-Krause
J. Mar. Sci. Eng. 2020, 8(12), 984; https://doi.org/10.3390/jmse8120984 - 3 Dec 2020
Cited by 3 | Viewed by 2200
Abstract
Locating and tracking submerged oil in the mid depths of the ocean is challenging during an oil spill response, due to the deep, wide-spread and long-lasting distributions of submerged oil. Due to the limited area that a ship or AUV can visit, efficient [...] Read more.
Locating and tracking submerged oil in the mid depths of the ocean is challenging during an oil spill response, due to the deep, wide-spread and long-lasting distributions of submerged oil. Due to the limited area that a ship or AUV can visit, efficient sampling methods are needed to reveal the real distributions of submerged oil. In this paper, several sampling plans are developed for collecting submerged oil samples using different sampling methods combined with forecasts by a submerged oil model, SOSim (Subsurface Oil Simulator). SOSim is a Bayesian probabilistic model that uses real time field oil concentration data as input to locate and forecast the movement of submerged oil. Sampling plans comprise two phases: the first phase for initial field data collection prior to SOSim assessments, and the second phase based on the SOSim assessments. Several environmental sampling techniques including the systematic random, modified station plans as well zig-zag patterns are evaluated for the first phase. The data using the first phase sampling plan are then input to SOSim to produce submerged oil distributions in time. The second phase sampling methods (systematic random combined with the kriging-based sampling method and naive zig-zag sampling method) are applied to design the sampling plans within the submerged oil area predicted by SOSim. The sampled data obtained using the second phase sampling methods are input to SOSim to update the model’s assessments. The performance of the sampling methods is evaluated by comparing SOSim predictions using the sampled data from the proposed sampling methods with simulated submerged oil distributions during the Deepwater Horizon spill by the OSCAR (oil spill contingency and response) oil spill model. The proposed sampling methods, coupled with the use of the SOSim model, are shown to provide an efficient approach to guide oil spill response efforts. Full article
(This article belongs to the Special Issue Ocean Numerical Forecast Modelling of Oil Spill)
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14 pages, 1975 KiB  
Article
Application of the SOSim v2 Model to Spills of Sunken Oil in Rivers
by Mary Jacketti, James D. Englehardt and C.J. Beegle-Krause
J. Mar. Sci. Eng. 2020, 8(9), 729; https://doi.org/10.3390/jmse8090729 - 22 Sep 2020
Cited by 6 | Viewed by 2382
Abstract
Sunken oil transport processes in rivers differ from those in oceans, and currently available models may not be generally applicable to sunken oil in river settings. The open-source Subsurface Oil Simulator (SOSim) model has been expanded to handle spills of sunken oil in [...] Read more.
Sunken oil transport processes in rivers differ from those in oceans, and currently available models may not be generally applicable to sunken oil in river settings. The open-source Subsurface Oil Simulator (SOSim) model has been expanded to handle spills of sunken oil in navigable rivers, utilizing Bayesian inference to integrate field concentration data with bathymetric data to predict the location and movement of sunken oil. A novel prior likelihood function incorporates bathymetric input, with sampling grid and default parameters adapted appropriately for rivers. SOSim v2 was demonstrated versus field observations taken following the M/T (Motor Tanker) Athos I oil spill. The model was also modified to operate in 1-D, to assess the longitudinal distribution of sunken oil in a non-navigable river using available poling data collected following the Enbridge Kalamazoo River oil spill in 2010. Results of both case studies were consistent with observed data and local bathymetry in 2-D and 1-D, and the model is suggested as a complement to deterministic models for oil spill emergency response in rivers. Full article
(This article belongs to the Special Issue Ocean Numerical Forecast Modelling of Oil Spill)
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Review

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26 pages, 31281 KiB  
Review
A Multifaceted Approach to Advance Oil Spill Modeling and Physical Oceanographic Research at the United States Bureau of Ocean Energy Management
by Zhen Li, Caryn Smith, Christopher DuFore, Susan F. Zaleski, Guillermo Auad, Walter Johnson, Zhen-Gang Ji and S. E. O’Reilly
J. Mar. Sci. Eng. 2021, 9(5), 542; https://doi.org/10.3390/jmse9050542 - 17 May 2021
Viewed by 3670
Abstract
The Environmental Studies Program (ESP) at the United States Bureau of Ocean Energy Management (BOEM) is funded by the United States Congress to support BOEM’s mission, which is to use the best available science to responsibly manage the development of the Nation’s offshore [...] Read more.
The Environmental Studies Program (ESP) at the United States Bureau of Ocean Energy Management (BOEM) is funded by the United States Congress to support BOEM’s mission, which is to use the best available science to responsibly manage the development of the Nation’s offshore energy and mineral resources. Since its inception in 1973, the ESP has funded over $1 billion of multidisciplinary research across four main regions of the United States Outer Continental Shelf: Gulf of Mexico, Atlantic, Alaska, and Pacific. Understanding the dynamics of oil spills and their potential effects on the environment has been one of the primary goals of BOEM’s funding efforts. To this end, BOEM’s ESP continues to support research that improves oil spill modeling by advancing our understanding and the application of meteorological and oceanographic processes to improve oil spill modeling. Following the Deepwater Horizon oil spill in 2010, BOEM has invested approximately $28 million on relevant projects resulting in 73 peer-reviewed journal articles and 42 technical reports. This study describes the findings of these projects, along with the lessons learned and research information needs identified. Additionally, this paper presents a path forward for BOEM’s oil spill modeling and physical oceanographic research. Full article
(This article belongs to the Special Issue Ocean Numerical Forecast Modelling of Oil Spill)
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