Geology topics
Publications and source records attributed to K.J. Lanfear.
This coverage is of the county boundaries of the conterminous United States. It was derived from the Digital Line Graph (DLG) files representing the 1:2,000,000-scale map in the National Atlas of the United States.
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Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
An analysis was made of the relative impact to the shoreline of the Gulf of Mexico from proposed Federal Outer Continental Shelf oil and gas leasing activity. An oil spill trajectory model was coupled with a land segment vulnerability characterization to predict the risks to the shoreline. Such a technique allows spatial and temporal variability in oil spill sensitivity to be represented and combined with the likelihood of oil spill contact to specific coastal segments in the study area. Predicted relative impact was greatest along the coastlines of Louisiana, Mississippi, and Alabama. Useful information is provided for environmental impact analysis, as well as oil spill response planning.
The U.S. Geological Survey has developed an oilspill risk analysis model to aid in estimating the environmental hazards of developing oil resources in Outer Continental Shelf (OCS) lease areas. The large, computerized model analyzes the probability of spill occurrence, as well as the likely paths or trajectories of spills in relation to the locations of recreational and biological resources which may be vulnerable. The analytical methodology can easily incorporate estimates of weathering rates , slick dispersion, and possible mitigating effects of cleanup. The probability of spill occurrence is estimated from information on the anticipated level of oil production and method of route of transport. Spill movement is modeled in Monte Carlo fashion with a sample of 500 spills per season, each transported by monthly surface current vectors and wind velocities sampled from 3-hour wind transition matrices. Transition matrices are based on historic wind records grouped in 41 wind velocity classes, and are constructed seasonally for up to six wind stations. Locations and monthly vulnerabilities of up to 31 categories of environmental resources are digitized within an 800,000 square kilometer study area. Model output includes tables of conditional impact probabilities (that is, the probability of hitting a target, given that a spill has occurred), as well as probability distributions for oilspills occurring and contacting environmental resources within preselected vulnerability time horizons. (USGS)
If an oilspill contacts a colony of glaucous-winged gulls Larus hyperboreus, reducing the population by 50%, the population is expected to recover to its pre-spill level in c.20 yr. For common murres Uria aalge, this same situation yields a recovery time of c.70 yr. Assuming that oil is found in the study area, and based on the expected number of oilspills to occur and contact these colonies during the lease lifetime, and assuming that each oilspill contact causes a fractional population loss of 0.95, the probability of reducing the population to some fraction of its initial level was calculated. For gulls, only a 10% change of population reduction to less than one-half the pre-spill level was calculated for the lease lifetime. For murres, only a 4% change of similar reduction was calculated.-from Authors
An oilspill risk analysis was conducted to determine the relative environmental hazards of developing oil in different regions of the Beaufort Sea, Alaska, (Proposed Sale 71) Outer Continental Shelf (OCS) lease area. The probability of spill occurrences, likely movement of oil slicks, and locations of resources vulnerable to spilled oil were analyzed. The model predicted movement of the center of spill mass and estimated the times between spill occurrence and contact with various resources, to allow a qualitative assessment of oil characteristics at the time of contact; no direct computation was made of weathering and cleanup. The model also assumed that any oil spilled under ice would remain in place, unchanged, until spring breakup. Ice movements, or travel of oil under ice, if occurring, would affect the results in a manner not directly predictable at this time. The combined results of spill occurrence and spill movement predictions yielded estimates of the overall risks associated with development of the proposed lease area. Assuming that oil exists in the lease area (a 99.3-percent chance) it is estimated that the leasing of the tracts proposed for OCS Sale 71 will result in an expected 9.2 oilspills (of 1,000 barrels or larger) over the lease lifetime of 25 years. This estimate is based on historic oilspill accident data for platforms and pipelines on the U.S. OCS (Gulf of Mexico and California). The estimated probability that land will be contacted by one or more oilspills (of 1,000 barrels or larger) that have been at sea less than 30 days (not counting any time trapped under ice) is greater than 99.5 percent. If oilspill accident data for Prudhoe Bay, Alaska, is used in the analysis, it is estimated that 5.6 oilspills (1,000 barrels or larger) will occur over the lease lifetime. The estimated probability that one or more oilspills (1,000 barrels or larger)will occur and contact land is99 percent. The results of a recent experimental cleanup operation for oilspills under ice in Canadian Arctic waters showed a substantial degree of success; this should be considered in evaluating impacts of spills predicted by this model. Oilspill occurrence probabilities are high primarily because of the large amount of oil believed to be present in the area.
The U.S. Geological Survey has developed an oilspill risk analysis model to aid in estimating the environmental hazards of developing oil resources in Outer Continental Shelf (OCS) lease areas. The large, computerized model analyzes the probability of spill occurrence, as well as the likely paths or trajectories of spills in relation to the locations of recreational and biological resources which may be vulnerable. The analytical methodology can easily incorporate estimates of weathering rates , slick dispersion, and possible mitigating effects of cleanup. The probability of spill occurrence is estimated from information on the anticipated level of oil production and method and route of transport. Spill movement is modeled in Monte Carlo fashion with a sample of 500 spills per season, each transported by monthly surface current vectors and wind velocities sampled from 3-hour wind transition matrices. Transition matrices are based on historic wind records grouped in 41 wind velocity classes, and are constructed seasonally for up to six wind stations. Locations and monthly vulnerabilities of up to 31 categories of environmental resources are digitized within an 800,000 square kilometer study area. Model output includes tables of conditional impact probabilities (that is, the probability of hitting a target, given that a spill has occurred), as well as probability distributions for oilspills occurring and contacting environmental resources within preselected vulnerability time horizons. (USGS)