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At least 37 records · Page 2Linked to original sources
USGS1981

An oilspill risk analysis for the Beaufort Sea, Alaska (proposed sale 71)outer continental shelf lease area

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.

Open-File Report↗
USGS1982

An oilspill risk analysis for the Mid-Atlantic (proposed sale 76) outer continental shelf lease area

An oilspill risk analysis was conducted for the mid-Atlantic (proposed sale 76) Outer Continental Shelf (OCS) lease area. The analysis considered: the probability of spill occurrences based on historical trends; likely movement of oil slicks based on a climatological model; and locations of environmental resources which could be vulnerable to spilled oil. The times between spill occurrence and contact with resources were estimated to aid analysts in estimating slick characteristics. Critical assumptions made for this particular analysis were (1) that oil exists in the lease area, and (2) that 0.879 billion barrels of oil will be found and produced from tracts sold in sale 76. On the basis of this resource estimate, it was calculated that 3 to 4 oilspills of 1,000 barrels or greater will occur over the 30-year production life of the proposed sale 76 lease tracts. The results also depend upon the routes and methods chosen to transport oil from 0CS platforms to shore. Given the above assumptions, the estimated probability that one or more oilspills of 1,000 barrels or larger will occur and contact land after being at sea less than 30 days is 0.36; for spills 10,000 barrels or larger, the probability is 0.22. These probabilities also reflect the following assumptions: oilspills remain intact for up to 30 days, do not weather, and are not cleaned up. It is noteworthy that over 90 percent of the risk from proposed sale 76 is due to transportation rather than production of oil. In addition, the risks from proposed sale 76 are about 1/10 to 1/15 those of existing tanker transportation of crude oil imports and refined products in the mid-Atlantic area.

Open-File Report↗
USGS1980

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

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)

Open-File Report↗
USGS1982

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

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)

Professional Paper↗
USGS2020

Introduction to risk analysis

Many decisions are made in the face of uncertainty that either cannot or will not be reduced, and the challenge to the decision maker is how to manage the risk imposed by that uncertainty. This chapter will introduce the field of risk analysis, focusing on both the scientific tasks (estimating the probabilities and magnitudes of possible outcomes) and the policy-relevant value judgments needed (understanding the risk tolerances of the decision makers and stakeholders). The three case studies that follow demonstrate a range of approaches to risk management in a natural resource setting.

Book chapter↗
USGS2021

Terrestrial ecological risk analysis via dietary exposure at uranium mine sites in the Grand Canyon watershed (Arizona, USA)

The U.S. Department of the Interior recently included uranium (U) on a list of mineral commodities that are considered critical to economic and national security. The uses of U for commercial and residential energy production, defense applications, medical device technologies, and energy generation for space vehicles and satellites are known, but the environmental impacts of uranium extraction are not always well quantified. We conducted a screening-level ecological risk analysis based on exposure to mining-related elements via diets and incidental soil ingestion for terrestrial biota to provide context to chemical characterization and exposures at breccia pipe U mines in northern Arizona. Relative risks, calculated as hazard quotients (HQs), were generally low for all biological receptor models. Our models screened for risk to omnivores and insectivores (HQs>1) but not herbivores and carnivores. Uranium was not the driver of ecological risk; arsenic, cadmium, copper, and zinc were of concern for biota consuming ground-dwelling invertebrates. Invertebrate species composition should be considered when applying these models to other mining locations or future sampling at the breccia pipe mine sites. Dietary concentration thresholds (DCTs) were also calculated to understand food concentrations that may lead to ecological risk. The DCTs indicated that critical concentrations were not approached in our model scenarios, as evident in the very low HQs for most models. The DCTs may be used by natural resource and land managers as well as mine operators to screen or monitor for potential risk to terrestrial receptors as mine sites are developed and remediated in the future.

Arizona↗
USGS1976

An oilspill risk analysis for the North Atlantic outer continental shelf lease area

The Federal Government has proposed to lease 1,172,795 acres of Outer Continental Shelf (OCS) lands on Georges Bank off the New England Coast for oil and gas development. Estimated recoverable petroleum resources for the proposed 206 tract sale area range from 180 to 650 million barrels. Contingent upon actual discovery of this quantity of oil, production is expected to span a period of about 20 years. An oilspill risk analysis was conducted to determine relative environmental hazards of developing oil in the North Atlantic Outer Continental Shelf lease area. The study analyzed probability of spill occurrence, likely path of pollutants from spills, and locations in space and time of recreational and biological resources likely to be vulnerable. These results are combined to yield estimates of the overall oilspill risk associated with development of the lease area. (Woodard-USGS)

Open-File Report↗
USGS2018

Spatial distribution of estuarine diamond-backed terrapins (Malaclemys terrapin) and risk analysis from commercial blue crab (Callinectes sapidus) trapping at the Savannah Coastal Refuges Complex, USA

The diamond-backed terrapin (Malaclemys terrapin) is a small estuarine turtle distributed along the Atlantic and Gulf Coasts of the USA. Terrapin populations are declining throughout their range and one of the main causes is mortality by drowning as bycatch in commercially-fished blue crab (Callinetes sapidus) traps (aka pots). We conducted head counts of terrapins and documented the distribution and number of crab pots on the Savannah Coastal Refuges Complex in southeast Georgia, USA. Using an index for representing relative degree of crabbing pressure, we conducted a spatial risk analysis for each of the four refuges surveyed. We fit a series of generalized linear mixed effect models to test hypotheses about the scale (creek scale vs. refuge/island scale) at which terrapin relative abundances respond to crab trapping. Several creeks were found to be at high risk of terrapin mortality from crab pots. Areas with low terrapin head counts may be a result of past crab pot mortality. The best model relating terrapin counts to crab trapping revealed a negative effect of crab pots calculated at the refuge/island scale and included a positive association between cloud cover and terrapin counts. The estimated effect of crab pot number at the refuge/island scale suggests that an increase in crab pot density of one pot per creek is associated with a 74.6% decline in terrapin head counts, underscoring the sensitivity of terrapin populations to crab pot mortality. Mitigation of this mortality factor via redesigned crab traps with bycatch reduction devices may be necessary to maintain healthy terrapin populations on the refuges.

Georgia↗
USGS2022

Multi-hazard risk analysis for the U.S. Department of the Interior: An integration of expert elicitation, planning priorities, and geospatial analysis

An integral part of disaster risk management is identifying and prioritizing hazards and their potential impacts in a meaningful way to support risk-reduction planning. There has been considerable use and subsequent criticism of threat prioritization efforts that simply compare likelihoods and consequences of plausible threats. This article summarizes a new mixed-methods and scalable approach for prioritizing risks in a multi-hazard, multi-objective, and multi-criteria organizational context. This approach integrates (1) hazard characterizations using subject-matter-expert (SME) elicitation, (2) expressed preferences in planning priorities provided by emergency managers, and (3) quantitative estimates of asset exposure to hazards using geospatial data and geographic-information-systems (GIS) software. We demonstrate this approach with a case study designed to support multi-hazard mitigation and response planning done by the U.S. Department of the Interior (DOI) Office of Emergency Management, which required a national understanding of the risks posed by 75 natural, technological, and adversarial hazards to DOI managed and administered lands, facilities, people, revenues, and resources. Results demonstrate that hazard priorities vary depending on the asset, scale, and risk-management context, thereby making the case that “one-size-fits-all” hazard rankings have limited utility or relevance to real-world, risk mitigation and response planning. Our results suggest that recognizing the risk-management context provides greater transparency, flexibility, and relevance in comparing threats than traditional likelihood-threat matrices or the use of hazard SMEs to decide for planners which hazard scenarios are emphasized in risk planning.

International Journal of Disaster Risk Reduction↗
USGS2005

Exposing extinction risk analysis to pathogens: Is disease just another form of density dependence?

In the United States and several other countries, the development of population viability analyses (PVA) is a legal requirement of any species survival plan developed for threatened and endangered species. Despite the importance of pathogens in natural populations, little attention has been given to host-pathogen dynamics in PVA. To study the effect of infectious pathogens on extinction risk estimates generated from PVA, we review and synthesize the relevance of host-pathogen dynamics in analyses of extinction risk. We then develop a stochastic, density-dependent host-parasite model to investigate the effects of disease on the persistence of endangered populations. We show that this model converges on a Ricker model of density dependence under a suite of limiting assumptions, including a high probability that epidemics will arrive and occur. Using this modeling framework, we then quantify: (1) dynamic differences between time series generated by disease and Ricker processes with the same parameters; (2) observed probabilities of quasi-extinction for populations exposed to disease or self-limitation; and (3) bias in probabilities of quasi-extinction estimated by density-independent PVAs when populations experience either form of density dependence. Our results suggest two generalities about the relationships among disease, PVA, and the management of endangered species. First, disease more strongly increases variability in host abundance and, thus, the probability of quasi-extinction, than does self-limitation. This result stems from the fact that the effects and the probability of occurrence of disease are both density dependent. Second, estimates of quasi-extinction are more often overly optimistic for populations experiencing disease than for those subject to self-limitation. Thus, although the results of density-independent PVAs may be relatively robust to some particular assumptions about density dependence, they are less robust when endangered populations are known to be susceptible to disease. If potential management actions involve manipulating pathogens, then it may be useful to model disease explicitly. ?? 2005 by the Ecological Society of America.

Ecological Applications↗
USGS1978

FRISK: computer program for seismic risk analysis using faults as earthquake sources

This computer program makes probabilistic seismic hazard calculations at sites affected by earthquakes occurring on faults which are defined by the user as a series of line segments. The length of rupture of the fault as a function of earthquake magnitude is accounted for, and ground motion estimates at the site are made using the magnitude of the earthquake and the closest distance from the site to the rupture zone. Uncertainty in the earthquake magnitude, in the rupture given magnitude, in the location of the rupture zone on the fault, in the maximum possible magnitude of earthquakes, and in the ground motion at the site given the earthquake, its size, rupture length, and location, are accounted for explicitly. FRISK (Fault RISK) was written to take advantage of repeated calculations, so that seismic hazard analyses for several ground motion parameters (for instance, peak ground acceleration, velocity, and displacement), and for several sites, are most efficiently made with one execution of the program rather than with repeated executions. The program uses a step-truncated exponential distribution for earthquake magnitude, a lognormal distribution for rupture length given magnitude, a uniform distribution for rupture location on faults, and a lognormal distribution of site amplitude given magnitude of the earthquake and distance from the rupture zone to the site. The program has been structured so that other functions may easily be substituted if this is appropriate for a particular problem; for example a wide range of deterministic or probabilistic geophysical models for estimating ground motion may be incorporated, and the program will yield probabilistic estimates of seismic hazard.

Open-File Report↗
USGS2008

Climate simulation and flood risk analysis for 2008-40 for Devils Lake, North Dakota

Devils Lake and Stump Lake in northeastern North Dakota receive surface runoff from a 3,810-square-mile drainage basin, and evaporation provides the only major water loss unless the lakes are above their natural spill elevation to the Sheyenne River. In September 2007, flow from Devils Lake to Stump Lake had filled Stump Lake and the two lakes consisted of essentially one water body with an elevation of 1,447.1 feet, about 3 feet below the existing base flood elevation (1,450 feet) and about 12 feet below the natural outlet elevation to the Sheyenne River (1,459 feet). Devils Lake could continue to rise, causing extensive additional flood damages in the basin and, in the event of an uncontrolled natural spill, downstream in the Red River of the North Basin. This report describes the results of a study conducted by the U.S. Geological Survey, in cooperation with the Federal Emergency Management Agency, to evaluate future flood risk for Devils Lake and provide information for developing updated flood-insurance rate maps and planning flood-mitigation activities such as raising levees or roads. In about 1980, a large, abrupt, and highly significant increase in precipitation occurred in the Devils Lake Basin and elsewhere in the Northern Great Plains, and wetter-than-normal conditions have persisted through the present (2007). Although future precipitation is impossible to predict, paleoclimatic evidence and recent research on climate dynamics indicate the current wet conditions are not likely to end anytime soon. For example, there is about a 72-percent chance wet conditions will last at least 10 more years and about a 37-percent chance wet conditions will last at least 30 more years. A stochastic simulation model for Devils Lake and Stump Lake developed in a previous study was updated and used to generate 10,000 potential future realizations, or traces, of precipitation, evaporation, inflow, and lake levels given existing conditions on September 30, 2007, and randomly generated future duration of the current wet period. On the basis of the simulations, and assuming ice-free conditions and calm wind, the Devils Lake flood elevation for an annualized flood risk of 1 percent (analogous to a “100-year” riverine flood) was estimated to be 1,454.6 feet for a 10-year time horizon (2008­­­–17). Therefore, without adjusting for wind or ice, a residence near Devils Lake at elevation 1,454.6 feet has the same chance of being flooded sometime during the next 10 years as a residence at the edge of the 100-year flood plain along a river. Adjusting for the effects of wind or ice, which will increase the flood elevations for many locations near the lakes, was not within the scope of this study.

North Dakota↗
USGS1997

The role of mesocosm studies in ecological risk analysis

Mesocosms have been primarily used as research tools for the evaluation of the fate and effects of xenobiotic chemicals at the population, community, and ecosystem levels of biological organization. This paper provides suggestions for future applications of mesocosm research. Attention should be given to the configuration of mesocosm parameters to explicitly study regional questions of ecological interest. The initial physical, chemical, and biological conditions within mesocosms should be considered as factors shaping the final results of experiments. Certain fundamental questions such as the ecological inertia and resilience of systems with different initial ecological properties should be addressed. Researchers should develop closer working relationships with mathematical modelers in linking computer models to the outcomes of mesocosm studies. Mesocosm tests, linked with models, could enable managers and regulators to forecast the regional consequences of chemicals released into the environment.

Ecological Applications↗