The oilspill risk analysis model of the U. S. Geological Survey

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The US Geological Survey has developed an oilspill risk analysis model to aid in estimating the environmetal 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 baesd 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 km/sup 2/ study area. Model output includes tables of conditional impact probabilities as well as probability distributions for oilspills occurring and contacting environmental resources within preselectedmore » vulnerability time horizons. The model provides the US Department of the Interior with a method for realistically assessing oilspill risks associated with OCS development. To date, it has been used in oilspill risk assessments for eight OCS lease sales with the results reported in Federal environmental impact statements. A sumary of results is presented herein. A real time version was also used to forecast the movement of oil from the 1976-1977 Argo Merchant oilspill. Additional model runs are planned for future OCS lease sales in frontier areas. 35 references, 13 figures, 10 tables.« less