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USGS1991

A microcomputer program for energy assessment and aggregation using the triangular probability distribution

A general risk-analysis method was developed for petroleum-resource assessment and other applications. The triangular probability distribution is used as a model with an analytic aggregation methodology based on probability theory rather than Monte-Carlo simulation. Among the advantages of the analytic method are its computational speed and flexibility, and the saving of time and cost on a microcomputer. The input into the model consists of a set of components (e.g. geologic provinces) and, for each component, three potential resource estimates: minimum, most likely (mode), and maximum. Assuming a triangular probability distribution, the mean, standard deviation, and seven fractiles (F100, F95, F75, F50, F25, F5, and F0) are computed for each component, where for example, the probability of more than F95 is equal to 0.95. The components are aggregated by combining the means, standard deviations, and respective fractiles under three possible siutations (1) perfect positive correlation, (2) complete independence, and (3) any degree of dependence between these two polar situations. A package of computer programs named the TRIAGG system was written in the Turbo Pascal 4.0 language for performing the analytic probabilistic methodology. The system consists of a program for processing triangular probability distribution assessments and aggregations, and a separate aggregation routine for aggregating aggregations. The user's documentation and program diskette of the TRIAGG system are available from USGS Open File Services. TRIAGG requires an IBM-PC/XT/AT compatible microcomputer with 256kbyte of main memory, MS-DOS 3.1 or later, either two diskette drives or a fixed disk, and a 132 column printer. A graphics adapter and color display are optional. ?? 1991.

Computers & Geosciences↗

USGS2021

Elemental and radionuclide exposures and uptakes by small rodents, invertebrates, and vegetation at active and post-production uranium mines in the Grand Canyon watershed

The effects of breccia pipe uranium mining in the Grand Canyon watershed (Arizona) on ecological and cultural resources are largely unknown. We characterized the exposure of biota to uranium and co-occurring ore body elements during active ore production and at a site where ore production had recently concluded. Our results indicate that biota have taken up uranium and other elements (e.g., arsenic, cadmium, copper, molybdenum, uranium) from exposure to ore and surficial contamination, like blowing dust. Results indicate the potential for prolonged exposure to elements and radionuclides upon conclusion of active ore production. Mean radium-226 in deer mice was up to 4 times greater than uranium-234 and uranium-238 in those same samples; this may indicate a potential for, but does not necessarily imply, radium-226 toxicity. Soil screening benchmarks for uranium and molybdenum and other toxicity thresholds for arsenic, copper, selenium, uranium (e.g., growth effects) were exceeded in vegetation, invertebrates, and rodents ( Peromyscus spp. , Thomomys bottae, Tamias dorsalis, Dipodomys deserti ). However, the prevalence and severity of microscopic lesions in rodent tissues (as direct evidence of biological effects of uptake and exposure) could not be definitively linked to mining. Our data indicate that land managers might consider factors like species, seasonal changes in environmental concentrations, and bioavailability, when determining mine permitting and remediation in the Grand Canyon watershed. Ultimately, our results will be useful for site-specific ecological risk analysis and can support future decisions regarding the mineral extraction withdrawal in the Grand Canyon watershed and elsewhere.

Arizona↗

USGS2021

Groundwater quality of aquifers overlying the Oxnard Oil Field, Ventura County, California

Groundwater samples collected from irrigation, monitoring, and municipal supply wells near the Oxnard Oil Field were analyzed for chemical and isotopic tracers to evaluate if thermogenic gas or water from hydrocarbon-bearing formations have mixed with surrounding groundwater. New and historical data show no evidence of water from hydrocarbon-bearing formations in groundwater overlying the field. However, thermogenic gas mixed with microbial methane was detected in 5 wells at concentrations ranging from 0.011–9.1 mg/L. The presence of these gases at concentrations <10 mg/L do not indicate degraded water quality posing a known health risk. Analysis of carbon isotopes (δ 13 C-CH 4 ) and hydrogen isotopes (δ 2 H-CH 4 ) of methane and ratios of methane to heavier hydrocarbon gases were used to differentiate sources of methane between a) microbial, b) thermogenic or c) mixed sources. Results indicate that microbial-sourced methane is widespread in the study area, and concentrations overlap with those from thermogenic sources. The highest concentrations of thermogenic gas were observed in proximity to relatively high density of oil wells, large injection volumes of water disposal and cyclic steam, shallow oil development, and hydrocarbon shows in sediments overlying the producing oil reservoirs. Depths of water wells containing thermogenic gas were within approximately 200 m of the top of the Vaca Tar Sand production zone (approximately 600 m below land surface). Due to the limited sampling density, the source and pathways of thermogenic gas detected in groundwater could not be conclusively determined. Thermogenic gas detected in the absence of co-occurring water from hydrocarbon-bearing formations may result from natural gas migration over geologic time from the Vaca Tar Sand or deeper formations, hydrocarbon shows in sediments overlying producing zones, and/or gas leaking from oil-field infrastructure. Denser sampling of groundwater, potential end-members, and pressure monitoring could help better distinguish pathways of thermogenic gases.

California↗

USGS2003

Data-based comparisons of moments estimators using historical and paleoflood data

This paper presents the first systematic comparison, using historical and paleoflood data, of moments-based flood frequency methods. Peak flow estimates were compiled from streamflow-gaging stations with historical and/or paleoflood data at 36 sites located in the United States, Argentina, United Kingdom and China, covering a diverse range of hydrologic conditions. The Expected Moments Algorithm (EMA) and the Bulletin 17B historical weighting procedure (B17H) were compared in terms of goodness of fit using 25 of the data sets. Results from this comparison indicate that EMA is a viable alternative to current B17H procedures from an operational perspective, and performed equal to or better than B17H for the data analyzed. We demonstrate satisfactory EMA performance for the remaining 11 sites with multiple thresholds and binomial censoring, which B17H cannot accommodate. It is shown that the EMA estimator readily incorporates these types of information and the LP-III distribution provided an adequate fit to the data in most cases. The results shown here are consistent with Monte Carlo simulation studies, and demonstrate that EMA is preferred overall to B17H. The Bulletin 17B document could be revised to include an option for EMA as an alternative to the existing historical weighting approach. These results are of practical relevance to hydrologists and water resources managers for applications in floodplain management, design of hydraulic structures, and risk analysis for dams. ?? 2003 Elsevier Science B.V. All rights reserved.

Journal of Hydrology↗

USGS2006

Modeling the influence of river rehabilitation scenarios on bed material sediment flux in a large river over decadal timescales

A stochastic flood generator and calibrated sediment transport formulae were used to assess the decadal impact of major river rehabilitation strategies on two fraction bed material sediment flux and net storage, first‐order indicators of aquatic riverine habitat, in a large river system. Model boundary conditions were modified to reflect the implementation of three major river rehabilitation strategies being considered in the Sacramento River Valley: gravel augmentation, setting back of levees, and flow alteration. Fifty 30‐year model simulations were used to compute probabilities of the response in sediment flux and net storage to these strategies. Total annual average bed material sediment flux estimates were made at six gauged river cross sections, and ∼60 km reach‐scale sediment budgets were evaluated between them. Gravel augmentation to improve spawning habitat induced gravel accumulation locally and/or downstream, depending on the added mixture. Levee setbacks to recreate the river corridor reduced flow stages for most flows and hence lowered sediment flux. Flow alteration to mimic natural flow regimes systematically decreased total annual average flux, suggesting that high‐magnitude low‐frequency transport events do not affect long‐term trends in bed material flux. The results indicate that each rehabilitation strategy reduces sediment transport in its target reaches and modulates imbalances in total annual bed material sediment budgets at the reach scale. Additional risk analysis is necessary to identify extreme conditions associated with variable hydrology that could affect rehabilitation over decades. Sensitivity analysis suggests that sorting of bed material sediment is the most important determinant of modeled transport and storage patterns.

Water Resources Research↗

USGS2023

Understanding uncertainties in contemporary and future extreme wave events for broad-scale impact and adaptation planning

Understanding uncertainties in extreme wind-wave events is essential for offshore/coastal risk and adaptation estimates. Despite this, uncertainties in contemporary extreme wave events have not been assessed, and projections are still limited. Here, we quantify, at global scale, the uncertainties in contemporary extreme wave estimates across an ensemble of widely used global wave reanalyses/hindcasts supported by observations. We find that contemporary uncertainties in 50-year return period wave heights ( H s 50 "> H 50 s 50 ) reach (on average) ~2.5 m in regions adjacent to coastlines and are primarily driven by atmospheric forcing. Furthermore, we show that uncertainties in contemporary H s 50 "> H 50 s 50 estimates dominate projected 21st-century changes in H s 50 "> H 50 s 50 across ~80% of global ocean and coastlines. When translated into broad-scale coastal risk analysis, these uncertainties are comparable to those from storm surges and projected sea level rise. Thus, uncertainties in contemporary extreme wave events need to be combined with those of projections to fully assess potential impacts.

Science Advances↗

USGS2021

Behavioral responses of sea lamprey (Petromyzon marinus) and white sucker (Catostomus commersonii) to turbulent flow during fishway passage attempts

An understanding of how undesirable and desirable fish species respond behaviorally to turbulent flow in fishways would guide development of selective fish passage techniques. We applied high-resolution computational fluid dynamics modeling and competing risks analysis towards the development of predictive selective passage models. Sea lamprey ( Petromyzon marinus ; an invasive fish in the Great Lakes Basin, North America) upstream passage probability declined from 0.73 to 0.03 as flow conditions became increasingly turbulent, while declines in white sucker ( Catostomus commersonii , a native fish in the region) upstream passage probability were less substantial (0.53 to 0.44). Deploying a sea lamprey trap in the fishway did not effectively reduce sea lamprey upstream passage probability, though capture rate increased during trials with cooler water temperature and low total kinetic energy. Bifurcated fishways that maintain low turbulent flow in the entrapment route and high turbulent flow in the upstream passage route could increase the effectiveness of trapping sea lamprey in fishways as a means to advance selective passage goals.

Wisconsin↗

USGS2011

Introduction to fire danger rating and remote sensing - Will remote sensing enhance wildland fire danger prediction?

While ‘Fire Danger’ per se cannot be measured, the physical properties of the biotic and abiotic world that relate to fire occurrence and fire behavior can. Today, increasingly sophisticated Remote Sensing methods are being developed to more accurately detect fuel properties such as species composition (fuel types), vegetation structure or plant water content - to name a few. Based on meteorological input data and physical, semi-physical or empirical model calculations, Wildland Fire Danger Rating Systems provide ‘indirect values’ - numerical indices - at different temporal scales (e.g., daily, weekly, monthly) denoting the physical conditions that may lead to fire ignition and support fire propagation. The results can be expressed as fire danger levels, ranging from ‘low’ to ‘very high’, and are commonly used in operational wildland fire management (e.g., the Canadian Fire Weather Index [FWI] System, the Russian Nesterov Index, or the U.S. National Fire Danger Rating System [NFDRS]). Today, fire danger levels are often turned into broad scale maps with the help of Geographical Information Systems (GIS) showing the areas with the different fire danger levels, and are distributed via the World Wide Web. In this chapter we will outline some key issues dealing with Remote Sensing and GIS techniques that are covered in the following chapters, and elaborate how the Fire Danger Rating concepts could be integrated into a framework that enables comprehensive and sustainable wildland fire risk assessment. To do so, we will first raise some general thoughts about wildland fires and suggest how to approach this extremely complex phenomenon. Second, we will outline a possible fire risk analysis framework and third we will give a short overview on existing Fire Danger Rating Systems and the principles behind them.

Series in Remote Sensing↗

USGS2010

Global building inventory for earthquake loss estimation and risk management

We develop a global database of building inventories using taxonomy of global building types for use in near-real-time post-earthquake loss estimation and pre-earthquake risk analysis, for the U.S. Geological Survey’s Prompt Assessment of Global Earthquakes for Response (PAGER) program. The database is available for public use, subject to peer review, scrutiny, and open enhancement. On a country-by-country level, it contains estimates of the distribution of building types categorized by material, lateral force resisting system, and occupancy type (residential or nonresidential, urban or rural). The database draws on and harmonizes numerous sources: (1) UN statistics, (2) UN Habitat’s demographic and health survey (DHS) database, (3) national housing censuses, (4) the World Housing Encyclopedia and (5) other literature.

Earthquake Spectra↗

USGS1984

Earth and water resources and hazards in Central America

Long-range economic development in Central America will depend in large part on production of indigenous mineral, energy, and water resources and on mitigation of the disastrous effects of geologic and hydrologic hazards such as landslides, earthquakes, volcanic eruptions, and floods. The region has six world-class metal mines at present as well as additional evidence of widespread mineralization. Systematic investigations using modern mineral exploration techniques should reveal more mineral deposits suitable for development. Widespread evidence of lignite and geothermal resources suggests that intensive studies could identify producible energy sources in most Central American countries. Water supply and water quality vary greatly from country to country. Local problems of ground- and surface-water availability and of contamination create a need for systematic programs to provide better hydrologic data, capital improvements, and management. Disastrous earthquakes have destroyed or severely damaged many cities in Central America. Volcanic eruptions, landslides, mudflows, and floods have devastated most of the Pacific side of Central America at one time or another. A regional approach to earthquake, volcano, and flood-risk analysis and monitoring, using modern technology and concepts, would provide the facilities and means for acquiring knowledge necessary to reduce future losses. All Central American countries need to strengthen institutions and programs dealing with earth and water resources and natural hazards. Some of these needs may be satisfied through existing or pending projects and technical and economic assistance from U.S. or other sources. The need for a comprehensive study of the natural resources of Central America and the requirements for their development is evident. The U.S. Caribbean Basin Initiative offers both an excellent opportunity for a regional approach to these pervasive problems and an opportunity for international cooperation.

Circular↗

USGS2015

A conceptual model for site-level ecology of the giant gartersnake ( Thamnophis gigas ) in the Sacramento Valley, California

Giant gartersnakes (Thamnophis gigas) comprise a species of semi-aquatic snakes precinctive to marshes in the Central Valley of California (Hansen and Brode, 1980; Rossman and others, 1996). Because more than 90 percent of their historical wetland habitat has been converted to other uses (Frayer and others, 1989; Garone, 2007), giant gartersnakes have been listed as threatened by the State of California (California Department of Fish and Game Commission , 1971) and the United States (U.S. Fish and Wildlife Service, 1993). Giant gartersnakes currently occur in a highly modified landscape, with most extant populations occurring in the rice - growing regions of the Sacramento Valley, especially near areas that historically were tule marsh habitat (Halstead and others, 2010, 2014). In ricelands and managed marshes, many operational decisions likely affect the health and viability of giant gartersnake populations. Land-use decisions, including the management of water, aquatic vegetation, terrestrial vegetation, and co-occurring species, have the potential to affect giant gartersnakes. Little is known, however, about the effects of these types of decisions on the viability of giant gartersnake populations. Bayesian network models are a useful tool to help guide decisions with uncertain outcomes. These models require the articulation of what experts think they know about a system, and facilitate learning about the hypothesized relations (Marcot and others, 2001; Uusitalo , 2007). Bayesian networks further provide a clear visual display of the model that facilitates understanding among various stakeholders (Marcot and others, 2001; Uusitalo , 2007). Empirical data and expert judgment can be combined, as continuous or categorical variables, to update knowledge about the system (Marcot and others, 2001; Uusitalo , 2007). Importantly, Bayesian network models allow inference from causes to consequences, but also from consequences to causes, so that data can inform the states of nodes (values of different random variables) in either direction (Marcot and others, 2001; Uusitalo , 2007). Because they can incorporate both decision nodes that represent management actions and utility nodes that quantify the costs and benefits of outcomes, Bayesian networks are ideally suited to risk analysis and adaptive management (Nyberg and others, 2006; Howes and others, 2010). Thus, Bayesian network models are useful in situations where empirical data are not available, such as questions concerning the responses of giant gartersnakes to management.

California↗

USGS2021

Probabilistic methodology for the assessment of original and recoverable coal resources, illustrated with an application to a coal bed in the Fort Union Formation, Wyoming

Executive Summary The U.S. Geological Survey (USGS) has been using its Circular 891 for evaluating uncertainty in coal resource assessments for more than 35 years. Calculated cell tonnages are assigned to four qualitative reliability classes depending exclusively on distance to the nearest drill hole. The main appeal of this methodology, simplicity, is also its main drawback. Reliability may depend so marginally on distance to the nearest drill hole that, over time, it has become evident that Circular 891 is inadequate for modeling reliability and is limited by other shortcomings. The present publication describes the use of geostatistics as an approach allowing a more satisfactory performance than that which is achieved following Circular 891. Geostatistics takes advantage of partly random and partly organized fluctuations in attributes such as coal thickness, coal density, and elevation of the top of a coal bed, borrowing concepts and tools that have been standard features in statistics and risk analysis for decades. Considering that readers interested in this study may not have the background to go directly into the details of the methodology, we start by explaining geostatistical concepts and modeling techniques. The remainder of the publication is devoted to formulating the assessment methodology, applying it to data from the Fillmore Ranch coal bed in the Fort Union Formation in Wyoming, and explaining the computer software applied for performing calculations and displays. The assessment methodology has been designed to report three different forms of resources: coal in place, coal mineable by surface mining methods, and coal mineable by underground mining methods. These three types of resources are reported graphically by displaying both the magnitude and the reliability of total coal resources and resources at the cell scale. In the case of the Fillmore Ranch coal bed example, there is a 90-percent probability that the resources in place are 9.687 ± 0.383 billion short tons (bst), while the coal available for underground mining is 2.279 ± 0.160 bst, and that available for surface mining is only 0.240 ± 0.025 bst because of the steep dip to the west away from the outcrop. These magnitudes are derived from numerical probability distributions not following any specific form.

Wyoming↗

USGS2001

Model simulation of the Manasquan water-supply system in Monmouth County, New Jersey

Model simulation of the Manasquan Water Supply System in Monmouth County, New Jersey, was completed using historic hydrologic data to evaluate the effects of operational and withdrawal alternatives on the Manasquan reservoir and pumping system. Changes in the system operations can be simulated with the model using precipitation forecasts. The Manasquan Reservoir system model operates by using daily streamflow values, which were reconstructed from historical U.S. Geological Survey streamflow-gaging station records. The model is able to run in two modes--General Risk analysis Model (GRAM) and Position Analysis Model (POSA). The GRAM simulation procedure uses reconstructed historical streamflow records to provide probability estimates of certain events, such as reservoir storage levels declining below a specific level, when given an assumed set of operating rules and withdrawal rates. POSA can be used to forecast the likelihood of specified outcomes, such as streamflows falling below statutory passing flows, associated with a specific working plan for the water-supply system over a period of months. The user can manipulate the model and generate graphs and tables of streamflows and storage, for example. This model can be used as a management tool to facilitate the development of drought warning and drought emergency rule curves and safe yield values for the water-supply system.

Water-Resources Investigations Report↗

USGS2023

Neonicotinoid sunflower seed treatment, while not detected in pollen and nectar, still impacts wild bees and crop yield

Neonicotinoid seed treatments are commonly used in agricultural production even though their benefit to crop yield and their impact on pollinators, particularly wild bees, remains unclear. Using an on-farm matched pair design in which half of each field was sown with thiamethoxam treated seed and half without, we assessed honey bee and wild bee exposure to pesticides in sunflower fields by analyzing pesticide residues in field soil, sunflower pollen and nectar, pollen-foraging and nec-tar-foraging honey bees, and a sunflower specialist wild bee (Melissodes agilis). We also quantified the effects of thiamethoxam-treated seed on wild bee biodiversity and crop yield. M. agilis abundance was significantly lower with thiamethoxam treatment and overall wild bee abundance trending lower but was not significantly different. Furthermore, crop yield was significantly lower in plots with thiamethoxam treatment, even though thiamethoxam was only detected at low concentrations in one soil sample (and its primary metabolite, clothianidin, was never detected). Conversely, wild bee richness was significantly higher and diversity was marginally higher with thiamethoxam treatment. Nectar volumes harvested from the nectar-foraging honey bees were also significantly higher with thiamethoxam treatment. Several pesticides that were not used in the sunflower fields were detected in our samples, some of which are known to be deleterious to bee health, highlighting the importance of the landscape scale in the assessment of pesticide exposure for bees. Overall, our results suggest that thiamethoxam seed treatments may negatively impact wild bee pollination services in sunflower. Importantly, this study highlights the advantages of the inclusion of other metrics, such as biodiversity or behavior, in pesticide risk analysis, as pesticide residue analysis, as an independent metric, may erroneously miss the impacts of field realistic pesticide exposure on bees.

California↗

USGS2021

Using the Landsat Burned Area products to derive fire history relevant for fire management and conservation in the state of Florida, southeastern USA

Development of comprehensive spatially explicit fire occurrence data remains one of the most critical needs for fire managers globally, and especially for conservation across the southeastern United States. Not only are many endangered species and ecosystems in that region reliant on frequent fire, but fire risk analysis, prescribed fire planning, and fire behavior modeling are sensitive to fire history due to the long growing season and high vegetation productivity. Spatial data that map burned areas over time provide critical information for evaluating management successes. However, existing fire data have undocumented shortcomings that limit their use when detailing the effectiveness of fire management at state and regional scales. Here, we assessed information in existing fire datasets for Florida and the Landsat Burned Area products based on input from the fire management community. We considered the potential of different datasets to track the spatial extents of fires and derive fire history metrics (e.g., time since last burn, fire frequency, and seasonality). We found that burned areas generated by applying a 90% threshold to the Landsat burn probability product matched patterns recorded and observed by fire managers at three pilot areas. We then created fire history metrics for the entire state from the modified Landsat Burned Area product. Finally, to show their potential application for conservation management, we compared fire history metrics across ownerships for natural pinelands, where prescribed fire is frequently applied. Implications of this effort include increased awareness around conservation and fire management planning efforts and an extension of derivative products regionally or globally.

Florida↗

USGS2020

Planners tool up for the next big one

Data, modeling, risk analysis, and hazard scenario resources can help put earthquake mitigation efforts on firmer ground. Article discusses general earthquake information and findings of the HayWired scenario for a planner audience.

Planning↗

USGS2010

An analysis of the risk of introduction of additional strains of the rust puccinia psidii Winter ('Ohi'a Rust) to Hawai'i

In April 2005, the rust fungus Puccinia psidii (most widely known as guava rust or eucalyptus rust) was found in Hawai'i. This was the first time this rust had been found outside the Neotropics (broadly-defined, including subtropical Florida, where the rust first established in the 1970s). First detected on a nursery-grown 'ohi'a plant, it became known as ''ohi'a rust'in Hawai'i. The rust spread rapidly and by August 2005 had been found throughout the main Hawaiian Islands. The rust probably reached Hawai'i via the live plant trade or via the foliage trade. In Hawai'i, the rust has infected three native plant species and at least eight non-native species. Effects have been substantial on the endangered endemic plant Eugenia koolauensis and the introduced rose apple, Syzygium jambos. Billions of yellow, asexual urediniospores are produced on rose apple, but a complete life cycle (involving sexual reproduction) has not yet been observed. The rust is autoecious (no alternate host known) on Myrtaceae. The strain introduced into Hawai'i is found sparingly on 'ohi'a (Metrosideros polymorpha), the dominant tree of Hawai'i's forests, with sporadic damage detected to date. The introduction of a rust strain that causes widespread damage to 'ohi'a would be catastrophic for Hawai'i's native biodiversity. Most imports of material potentially contaminated with rust are shipped to Hawai'i from Florida and California (from which P. psidii was reported in late 2005 by Mellano, 2006). Florida is known to have multiple strains. The identity of the strain or strains in California is unclear, but one of them is known to infect myrtle, Myrtus communis, a species commonly imported into Hawai'i. It is important to ecosystem conservation and commercial forestry that additional rust strains or genotypes be prevented from establishing in Hawai'i. The purpose of this analysis of risk is to evaluate the need for an interim rule by the Hawai'i Department of Agriculture to regulate plant material of Myrtaceae arriving from the continental United States and to clarify consequences of such a rule, especially implications for possible eventual action by the U.S. Department of Agriculture, Animal and Plant Health Inspection Service, to assist in protection of Hawai'i's native and non-native Myrtaceae from plant pests.