Oil spill fishery impact assessment model: Sensitivity to spill location and timing

Spaulding, Malcolm L.; Reed, Mark; Anderson, Elaine A.; Isaji, T.; Swanson, J. Craig; Saila, Saul B.; Lorda, Ernesto; Walker, Henry A.

doi:10.1016/0272-7714(85)90117-9

Cited by 12 publications

(4 citation statements)

References 3 publications

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“…Earlier modeling * dfrench@appsci.com. efforts for impact assessment relied on calculating the intersection of oil trajectories with biota, assuming an impact threshold [31][32][33][34][35][36][37][38]. In some cases, wildlife (seabird or marine mammal) population and migration models were used to simulate the distribution, behavior, and recovery of the affected species, in conjunction with their intersection with oil trajectories [39][40][41][42][43][44][45].…”

Section: Introductionmentioning

confidence: 99%

Oil spill impact modeling: Development and validation

French-McCay

2004

Enviro Toxic and Chemistry

213

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Abstract-A coupled oil fate and effects model has been developed for the estimation of impacts to habitats, wildlife, and aquatic organisms resulting from acute exposure to spilled oil. The physical fates model estimates the distribution of oil (as mass and concentrations) on the water surface, on shorelines, in the water column, and in the sediments, accounting for spreading, evaporation, transport, dispersion, emulsification, entrainment, dissolution, volatilization, partitioning, sedimentation, and degradation. The biological effects model estimates exposure of biota of various behavior types to floating oil and subsurface contamination, resulting percent mortality, and sublethal effects on production (somatic growth). Impacts are summarized as areas or volumes affected, percent of populations lost, and production foregone because of a spill's effects. This paper summarizes existing information and data used to develop the model, model algorithms and assumptions, validation studies, and research needs. Simulation of the Exxon Valdez oil spill is presented as a case study and validation of the model.

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Section: Introductionmentioning

confidence: 99%

Oil spill impact modeling: Development and validation

French-McCay

2004

Enviro Toxic and Chemistry

213

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“…In fact, software with the ability to model and predict spill outcomes has existed for decades. Readers are encouraged to consult Reed et al (1995) and Spaulding et al (1985) for early oil spill impact modeling frameworks. However, it is increasingly common for efforts to model spills, spill impacts, risk, and vulnerability to rely upon data in native GIS formats (Nelson et al, 2015; Sim et al, 2015; Zelenke et al, 2012) – most of which is made available from federal, state and local agencies, or local response and research teams.…”

Section: Gis and Spatial Analysismentioning

confidence: 99%

Oil spill modeling: computational tools, analytical frameworks, and emerging technologies

Nelson

Grubesic

2018

Progress in Physical Geography: Earth and Environment

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Following the Deepwater Horizon oil spill of 2010, a substantial body of research has focused on the development of computational tools and analytical frameworks for modeling oil spill events. Much of this work is dedicated to deepening our understanding of the interactions between oil, fragile ecosystems, and the environment, as well as the impacts of oil on human settlements which are vulnerable to spill events. These advances in oil spill modeling and associated analytics have not only increased the efficiency of spill interdiction and mitigation efforts, they have also helped to nurture proactive, versus reactive, response strategies and plans for local and regional stakeholders. The purpose of this paper is to provide a progress report on the wide range of computational tools, analytical frameworks, and emerging technologies which are necessary inputs for a complete oil spill modeling package. Specifically, we explore the use of relatively mature tools, such as dedicated spill modeling packages, geographic information systems (GIS), and remote sensing, as well emerging technologies such as aerial and aquatic drones and other in-situ sensing technologies. The integration of these technologies and the advantages associated with using a geographic lens for oil spill modeling are discussed.

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“…It is now possible to incorporate the knowledge and predictive capabilities reviewed in earlier sections of this paper into dynamic models ofentire ecosystems involving geophysical fluid dynamics, turbulence, sediment transport, and life-cycle stages ofvarious species and arrive at some predictive capabilities with respect to contamination of edible tissues from marine organisms. O'Connor et al (93) and Spaulding et al (94) among others have presented such models.…”

Section: Mathematical Models Of Coastal Ecosystems: From Inputs To Comentioning

confidence: 99%

“…The agreement seems reasonable to a first approximation although reasonable agreement depends on the use ofthe model and the degree of uncertainty that will be accepted, and this probably will vary depending on the perceived or real importance of relative risks to aquatic biota or human health. The types ofmathematical models exemplified by the work ofO'Connor et al (93,95), Thomann (96), Spaulding et al (94), and references cited therein are becoming an essential part ofenvironinental risk assessment for issues ranging from oil spills to remedial action plans for Superfund sites in coastal estuaries (94,97).…”

Section: Mathematical Models Of Coastal Ecosystems: From Inputs To Comentioning

confidence: 99%

Biogeochemical processes governing exposure and uptake of organic pollutant compounds in aquatic organisms.

Farrington

1991

Environ Health Perspect

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This paper reviews current knowledge of biogeochemical cycles of pollutant organic chemicals in aquatic ecosystems with a focus on coastal ecosystems. There is a bias toward discussing chemical and geochemical aspects of biogeochemical cycles and an emphasis on hydrophobic organic compounds such as polynuclear aromatic hydrocarbons, polychlorinated biphenyls, and chlorinated organic compounds used as pesticides. The complexity of mixtures of pollutant organic compounds, their various modes of entering ecosystems, and their physical chemical forms are discussed. Important factors that influence bioavailability and disposition (e.g., organism-water partitioning, uptake via food, food web transfer) are reviewed. These factors include solubilities of chemicals; partitioning of chemicals between solid surfaces, colloids, and soluble phases; variables rates of sorption, desorption; and physiological status of organism. It appears that more emphasis on considering food as a source of uptake and bioaccumulation is important in benthic and epibenthic ecosystems when sediment-associated pollutants are a significant source of input to an aquatic ecosystem. Progress with mathematical models for exposure and uptake of contaminant chemicals is discussed briefly.

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Oil spill fishery impact assessment model: Sensitivity to spill location and timing

Cited by 12 publications

References 3 publications

Oil spill impact modeling: Development and validation

Oil spill impact modeling: Development and validation

Oil spill modeling: computational tools, analytical frameworks, and emerging technologies

Biogeochemical processes governing exposure and uptake of organic pollutant compounds in aquatic organisms.

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