Search

Based on oil fate modeling of the Deepwater Horizon spill through August 2010, during June and July 2010, ~89% of the oil surfaced, ~5% entered (by dissolving or as microdroplets) the deep plume (900 m), and ~6% dissolved and biodegraded between 900 m and 40 m. Subsea dispersant application reduced surfacing oil by ~7% and evaporation of volatiles by ~26%. By July 2011, of the total oil, ~41% evaporated, ~15% was ashore and in nearshore (10 m) sediments, ~3% was removed by responders, ~38.4% was in the water column (partially degraded; 29% shallower and 9.4% deeper than 40 m), and ~2.6% sedimented in waters10 m (including 1.5% after August 2010). Volatile and soluble fractions that did not evaporate biodegraded by the end of August 2010, leaving residual oil to disperse and potentially settle. Model estimates were validated by comparison to field observations of floating oil and atmospheric emissions.

Oil spill modeling of the 2010 Deepwater Horizon discharge was performed to evaluate the fate of the oil in subsurface waters of the Gulf of Mexico. The oil fate model Spill Impact Model Application Package (SIMAP) was used to estimate rise rate of oil droplets, dissolution of oil constituents, movements of oil droplets and dissolved components, and degradation of hydrocarbon components in the deep-sea. As sampling during April–July 2010 was primarily performed within 20 km of the spill site, model predictions were compared to field data from within a 25-by-25-km box centered on the wellhead. Concentrations of soluble and semisoluble hydrocarbon components predicted by the model agreed well with chemical measurements when compared as frequency distributions within varying depth zones of the water column. The results showed that the soluble hydrocarbons primarily dissolved near the release depth, while semisoluble compounds were partially dissolved at depth and as droplets rose.

An oil spill response model, configured for operation on a personal computer, was developed for the Canadian Beaufort Sea (in the Mackenzie Bay-Tuktoyaktuk Peninsula area) for a consortium of oil companies operating in the region. The spill model predicts the drift, spread, evaporation, dispersion, emulsification, and shoreline interaction of spilled oil in ice-infested waters. Wind conditions and ice distribution data are input by the user. Currents are provided by a three-dimensional, fine-grid hydrodynamic model of the study region forced by river flow and wind. The spill model allows the user to reinitialize the spill location based on observations and to simulate either instantaneous or continuous spill scenarios. The model predicts the spill's trajectory, the areal distribution of the oil slick, the oiled shoreline, and the oil mass balance as a function of time. Model output is provided on a color ink printer or a color graphics monitor.

A numerical model system was developed to quantify the probability of endangered bowhead and gray whales encountering spilled oil in Alaskan waters. Migration and diving-surfacing models for bowhead and gray whales, and an oil spill trajectory model comprise the system. The migration models were developed from conceptual considerations, then calibrated with and tested against observations. The distribution of whales is represented in space and time by discrete points, each of which may represent one or more whales. The movement of a whale point is governed by a random walk algorithm which stochastically follows a migratory pathway. Stochastic diving-surfacing models are used to stimulate surfacing behavior sequences for each species. The oil spill model accounts for oil transport and spreading in open water and in the presence of sea ice. Historical wind records and ice cover data sets provide the environmental conditions to generate stochastic oil spill scenarios. The oil spill, whale migration and diving-surfacing models are linked to provide quantitative estimates of whale-oil interactions. The model system was applied to the Alaskan Beaufort Sea to investigate the probability that bowhead whales would encounter oil spilled in this region.

Numerical models of migrating bowhead and gray whales were developed as part of a larger project to assess the probability that these endangered marine mammals will encounter spilled oil in Alaskan waters. The distribution of animals is represented in space and time by discrete points, each of which may represent one or more whales. The movement of a whale point is governed by a random walk algorithm which follows stochastically a migratory pathway. The migration models rely on sightings of whales to define mean migration pathways. Distances traveled over 3–6 months, divided by the travel time, were used to estimate mean migratory speeds over appropriate sections of the migration route. Stochastic velocity components were added such that maximum instanteneous swimming speeds did not exceed those observed. Modeled whale densities were then compared with field estimates at various times and locations, as available, and mean migration speeds were adjusted locally to calibrate the model. The model proved to be an extremely useful tool for exploring the raw observational data, making clear a number of inconsistencies therein.

A comprehensive oilspill fates model, developed by Cornillon and Spaulding at the University of Rhode Island, has been employed to hindcast the well-studied Argo Merchant spill. Using data collected during the spill to define the environmental conditions and the oil composition, properties and release rates, the oil spill fates model was used to predict the spatial and temporal distribution of spilled oil from December 16 to 31, 1976. Comparison of model predictions to observations for spilled oil mass balance, surface trajectories and oiled surface area was in general quite good. Improved predictions require a better definition of the wind and tidally-forced circulation in the vicinity of the wreck site, a more soundly based theory for oil entrainment or dispersion into the water column and an oil spreading theory which more accurately addresses the complex behaviour of a weathering multicomponent petroleum hydrocarbon.

An Arctic coastal sea model system, consisting of submodels for weather, hydrodynamics, waves, suspended sediment, ice cover, oil spill trajectory and fates, and ecosystem dynamics is presented. The structure and operation of each sub-model and linkages among the various model components are briefly described. The weather, hydrodynamic, ice, and oil spill fates components of the model system are applied to predict hydrodynamics and oil spill trajectories from selected release points in the Bering Sea. Trajectory data are analyzed to describe the percent of trajectories affecting land and the direction, length, and duration distribution of trajectories. A detailed sensitivity study is performed to determine the role of the various mean current components and wind drift effects in describing spill trajectories. Model predictions highlight the importance of accurately representing the environmental data used as input to the model.