Oil-spill fishery impact assessment model: Application to selected Georges Bank fish species

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

doi:10.1016/0272-7714(83)90083-5

Cited by 19 publications

(4 citation statements)

References 2 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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“…Modeling methodology The impact assessment model system discussed here follows essentially the approach given by Spaulding (1978, 1979), and Reed (1980), although all components of the system have been greatly strengthened by recent work (Spaulding, . e t -al., 1981, 1982a, 1982b, 1982c, Reed, et al, 1982, Lorda and Saila, 1980 &., 1982, Anderson and Spaulding, 1981). The model system addresses first order direct impacts on a commercial fishery through pollutant induced egg and larval mortality, as well as coastal impacts of surface oil slicks.…”

Section: Introductionmentioning

confidence: 92%

A computer model system for marine pollutant impact assessment: Potentials for coastal state use

Reed

Spaulding²

1982

Oceans 82

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A system of numerical models has been created to assess the impacts of oil spills and other pollutant events on commercially important fish and shellfish species. The model system is composed of four components: a pollutant transport and fate model, a three dimensional hydrodynamic model, an egg and larval transport model and a fishery population model with both spatial and temporal dynamics. Examples of the application of the model of interest to state government include oil refinery siting and impact assessment for continental shelf hydrocarbon exploration.

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“…In modeling oil spill fate, it is common practice to use Lagrangian (particle) trajectory models to predict the transport of socalled spillets (Lagrangian elements, LEs, etc. ), which represent sub-lots of the spilled oil (e.g., Mackay et al, 1982;Spaulding et al, 1983;Spaulding, 1988;Lehr et al, 1995Lehr et al, , 2000French et al, 1996;Galt, 1998;Reed et al, 1999Reed et al, , 2000French McCay, 2003, 2004. The current and wind fields used to force these models are either supplied by hydrodynamic and meteorological models or are interpolated/extrapolated current and wind observations.…”

Section: Objectives and Approachmentioning

confidence: 99%

“…The transport model in SIMAP (French McCay, 2003, 2004, also earlier version in French et al, 1996) and other oil spill models (Mackay et al, 1982;Spaulding et al, 1983;Spaulding, 1988;Lehr et al, 1995Lehr et al, , 2000Galt, 1998;Reed et al, 1999Reed et al, , 2000 utilize similar algorithms for calculating advective movements and turbulent dispersion. Lagrangian particles ("spillets") are used to track the oil movements and weathering.…”

Section: Transport and Fate Modelmentioning

confidence: 99%

Dispersed Oil Transport Modeling Calibrated by Field-Collected Data Measuring Fluorescein Dye Dispersion

French-McCay

Mueller

Payne³

et al. 2008

International Oil Spill Conference Proceedings

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Oil-spill fate and transport modeling may be used to evaluate water column hydrocarbon concentrations, potential exposure to organisms, and impacts of oil spills with and without dispersant use. Important inputs to transport modeling for such analyses are current velocities and turbulent dispersion coefficients. Fluorescein dye studies off San Diego, California, were used to calibrate an oil transport model by hindcasting movement and dispersion of dye. The oil spill model was then used to predict subsurface hydrocarbon concentrations and potential water column impacts if oil were to be dispersed into the water column under similar conditions. Field-collected data included surface currents calculated from high-frequency radar data (HF-Radar), near-surface currents from drifter measurements drogued at several depths (Im, 2m, 4m or 5m), dye concentrations measured by fluorescence, spreading and dye intensity measurements based on aerial photography, and water density profiles from CTD casts. As the dye plume quickly extended throughout an upper mixed layer (7-I5m), the horizontal dye movements were better indicated by the drifters drogued to a depth near the middle of that layer than the HF-Radar, which measured surface (-top 50 cm) currents (including wind drift). Diffusion rates were estimated based on dye spreading measured by aerial photography and fluorescence-depth profiles. The model used these data as inputs, modeling of wind-forced surface water turbulence and drift as a function of wind speed and direction (based on published results of fluid dynamics studies), and Stokes law for droplet rise/sinking rates, to predict oil transport and dispersion rates within the water column. Use of such diffusion rate data in an oil fate model can provide estimates of likely dispersed oil concentrations under similar conditions, which may be used to evaluate potential impacts on water column biota. However, other conditions with different patterns of current shear (due to background currents, tidal currents, and wind stress) should be examined before these results can be generalized.

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Oil-spill fishery impact assessment model: Application to selected Georges Bank fish species

Cited by 19 publications

References 2 publications

Oil spill impact modeling: Development and validation

Oil spill impact modeling: Development and validation

A computer model system for marine pollutant impact assessment: Potentials for coastal state use

Dispersed Oil Transport Modeling Calibrated by Field-Collected Data Measuring Fluorescein Dye Dispersion

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