A Review of River Oil Spill Modeling

River oil spills are generally more frequent and pose greater environmental and public health risk than coastal and offshore oil spills. However, the river oil spill research has received a negligible amount of academic attention in the past three decades, while at the same time the coastal and offshore oil spill research has expanded and evolved tremendously. This paper provides the state-of-the-art review of river oil spill modeling and summarizes the developments in the field from 1994 to present. The review has revealed that the majority of the gaps in knowledge still remain. Thus, there is a need for (i) experimental studies in order to develop and validate new models and better understand the main physicochemical processes, (ii) studies on inter-linking of the governing processes, such as hydrodynamics, advection–dispersion, and weathering processes, (iii) adaptation and validation of coastal and offshore oil spill models for applications in riverine environments, and (iv) development of river oil spill remote sensing systems and detection techniques. Finally, there is a need to more actively promote the importance of river oil spill research and modeling in the context of environmental and public health protection, which would form the basis for obtaining more research funding and thus more academic attention.

A Multifaceted Approach to Advance Oil Spill Modeling and Physical Oceanographic Research at the United States Bureau of Ocean Energy Management

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. We also present a path forward for BOEM’s oil spill modeling and physical oceanographic research.

Using Oil Spill Modeling in Oil Spill Exercises and Drills

ABSTRACT Oil spill trajectory and fate modeling was used in inland response Full Scale Exercises including the Enbridge Des Plains River (fall 2018) and Wisconsin River (fall 2019). The Spill Impact Model Application Package (SIMAP) was used to predict the three-dimensional movement (i.e. trajectory) and behavior (i.e. fate) of a hypothetical release of oil using site-specific environmental and geographic conditions (including seasonal and hydrographic information) for the date of the exercise. The RPS OILMAPLand model was also used to predict the two-dimensional movement and behavior of the oil over the land surface, before it was predicted to enter the waterway. The oil spill modeling evaluated the spatial extent, timing, and magnitude of hydrocarbon contamination at downstream locations including thicknesses of floating surface oil and the mass of oil on shorelines and sediments. The assessments included the potential for released oil to move over the land surface, before entering the waterway, as well as becoming entrained in the water column as a result of surface floating oil passing over local features such as locks and dams. The results were presented at two separate exercise planning session and the full scale exercise as static images, GIS shape files, and videos. Results were also included in the COP for the exercise itself, with predicted results provided at hourly intervals for several days.

Oil Spill Modeling Lessons Learned over Four Decades of Catastrophic Spills

ABSTRACT Oil spill modeling developed tremendously over the past four decades, from simple floating particle trajectories of the 1979 Ixtoc spill to four-dimensional oil trajectory and fate models coupled with biological exposure, toxicity, and population models begun in the late 1980s to early 1990s, spurred by the Exxon Valdez, other major spills at that time and the Oil Pollution Oct of 1990. While many of the basic concepts and algorithms were developed in the 1990s, advances in computer hardware/software, as well as modeling techniques, have allowed for much better resolution of the needed model inputs, computations and outputs. Data availability and assimilation has greatly improved the performance of meteorological, hydrodynamic and ice (metocean) models, which are critical inputs to oil spill modeling. While large oil spills are traumatic events adversely impacting the environment and socioeconomic interests, they provide opportunities for process studies, model development and validation due to resources supporting the efforts and collections of needed data. Among other lessons, the Ixtoc spill modeling demonstrated the need for comprehensive, time-varying winds and currents from metocean models as input. In modeling the Exxon Valdez, spatially and temporally (hourly) varying winds driven by mountainous terrain, as well as coastal currents, were highly influential to the trajectory and fate of the oil. Measurement data was needed to drive modeling as the existing metocean models were not sufficiently accurate to account for observed oil movements. Other large spills in 1989 were in estuaries and coastal areas where oil movements were primarily driven by river and tidal currents, for which hydrodynamic models were reliable. The 1996 North Cape oil spill was the first for which water column exposure and effects modeling could be verified with field data. The Erika and Prestige spill trajectories were largely driven by the ships' movements while releasing oil and the winds. In modeling the Deepwater Horizon spill, metocean models were able to predict observed surface oil movements for several days and in terms of general overall direction. However, the modeled deepwater plume moved in various directions depending upon the hydrodynamic model used as input, highlighting the need for more accuracy in ocean models below surface waters. Recent developments in instrumentation, remote sensing, and data assimilation should improve both deepwater and surface trajectories. This combined with advancements in toxicity modeling and supporting data will facilitate confidence in biological effects modeling results. Described research and monitoring needs are based on modeling lessons learned.

Responder Needs Addressed by Arctic Maritime Oil Spill Modeling

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.

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

Several oil spill simulation models exist in the literature, which are used worldwide to simulate the evolution of an oil slick created from marine traffic, petroleum production, or other sources. These models may range from simple parametric calculations to advanced, new-generation, operational, three-dimensional numerical models, coupled to meteorological, hydrodynamic, and wave models, forecasting in high-resolution and with high precision the transport and fate of oil. This study presents a review of the transport and oil weathering processes and their parameterization and critically examines eighteen state-of-the-art oil spill models in terms of their capacity (a) to simulate these processes, (b) to consider oil released from surface or submerged sources, (c) to assimilate real-time field data for model initiation and forcing, and (d) to assess uncertainty in the produced predictions. Based on our review, the most common oil weathering processes involved are spreading, advection, diffusion, evaporation, emulsification, and dispersion. The majority of existing oil spill models do not consider significant physical processes, such as oil dissolution, photo-oxidation, biodegradation, and vertical mixing. Moreover, timely response to oil spills is lacking in the new generation of oil spill models. Further improvements in oil spill modeling should emphasize more comprehensive parametrization of oil dissolution, biodegradation, entrainment, and prediction of oil particles size distribution following wave action and well blow outs.