SEARCH · Search USGS

Results for “Statistical Methodology”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3Linked to original sources

USGS2006

Selected Streamflow Statistics and Regression Equations for Predicting Statistics at Stream Locations in Monroe County, Pennsylvania

A suite of 28 streamflow statistics, ranging from extreme low to high flows, was computed for 17 continuous-record streamflow-gaging stations and predicted for 20 partial-record stations in Monroe County and contiguous counties in north-eastern Pennsylvania. The predicted statistics for the partial-record stations were based on regression analyses relating inter-mittent flow measurements made at the partial-record stations indexed to concurrent daily mean flows at continuous-record stations during base-flow conditions. The same statistics also were predicted for 134 ungaged stream locations in Monroe County on the basis of regression analyses relating the statistics to GIS-determined basin characteristics for the continuous-record station drainage areas. The prediction methodology for developing the regression equations used to estimate statistics was developed for estimating low-flow frequencies. This study and a companion study found that the methodology also has application potential for predicting intermediate- and high-flow statistics. The statistics included mean monthly flows, mean annual flow, 7-day low flows for three recurrence intervals, nine flow durations, mean annual base flow, and annual mean base flows for two recurrence intervals. Low standard errors of prediction and high coefficients of determination (R2) indicated good results in using the regression equations to predict the statistics. Regression equations for the larger flow statistics tended to have lower standard errors of prediction and higher coefficients of determination (R2) than equations for the smaller flow statistics. The report discusses the methodologies used in determining the statistics and the limitations of the statistics and the equations used to predict the statistics. Caution is indicated in using the predicted statistics for small drainage area situations. Study results constitute input needed by water-resource managers in Monroe County for planning purposes and evaluation of water-resources availability.

Scientific Investigations Report↗

USGS2010

Development and analysis of a meteorological database, Argonne National Laboratory, Illinois

A database of hourly values of air temperature, dewpoint temperature, wind speed, and solar radiation from January 1, 1948, to September 30, 2003, primarily using data collected at the Argonne National Laboratory station, was developed for use in continuous-time hydrologic modeling in northeastern Illinois. Missing and apparently erroneous data values were replaced with adjusted values from nearby stations used as 'backup'. Temporal variations in the statistical properties of the data resulting from changes in measurement and data-storage methodologies were adjusted to match the statistical properties resulting from the data-collection procedures that have been in place since January 1, 1989. The adjustments were computed based on the regressions between the primary data series from Argonne National Laboratory and the backup series using data obtained during common periods; the statistical properties of the regressions were used to assign estimated standard errors to values that were adjusted or filled from other series. Each hourly value was assigned a corresponding data-source flag that indicates the source of the value and its transformations. An analysis of the data-source flags indicates that all the series in the database except dewpoint have a similar fraction of Argonne National Laboratory data, with about 89 percent for the entire period, about 86 percent from 1949 through 1988, and about 98 percent from 1989 through 2003. The dewpoint series, for which observations at Argonne National Laboratory did not begin until 1958, has only about 71 percent Argonne National Laboratory data for the entire period, about 63 percent from 1948 through 1988, and about 93 percent from 1989 through 2003, indicating a lower reliability of the dewpoint sensor. A basic statistical analysis of the filled and adjusted data series in the database, and a series of potential evapotranspiration computed from them using the computer program LXPET (Lamoreux Potential Evapotranspiration) also was carried out. This analysis indicates annual cycles in solar radiation and potential evapotranspiration that follow the annual cycle of extraterrestrial solar radiation, whereas temperature and dewpoint annual cycles are lagged by about 1 month relative to the solar cycle. The annual cycle of wind has a late summer minimum, and spring and fall maximums. At the annual time scale, the filled and adjusted data series and computed potential evapotranspiration have significant serial correlation and possibly have significant temporal trends. The inter-annual fluctuations of temperature and dewpoint are weakest, whereas those of wind and potential evapotranspiration are strongest.

Open-File Report↗

USGS2020

Aligning climate models with stakeholder needs: Advances in communicating future rainfall uncertainties for south Florida decision makers

Changes in future precipitation are of great importance to climate data users in South Florida. A recent U.S. Geological Survey workshop, “Increasing Confidence in Precipitation Projections for Everglades Restoration,” highlighted a gap between standard climate model outputs and the climate information needs of some key Florida natural resource managers. These natural resource managers (hereafter broadly defined as “climate data users”) need more tailored output than is commonly provided by the climate modeling community. This study responds to these user needs by outlining and testing an adaptable methodology to select output from ensemble climate‐model simulations based on user‐defined precipitation drivers, using statistical methods common across scientific disciplines. This methodology is developed to provide a “decision matrix” that guides climate data users to specify the subset of models most important to their work based on each user's season (winter, summer, and annual) and the condition (dry, wet, neutral, and no threshold events) of interest. The decision matrix is intended to better communicate the subset of models best representing precipitation drivers. This information could increase users' confidence in climate models as a resource for natural resource planning and can be used to direct future dynamical downscaling efforts. This methodology is based in dynamical processes controlling precipitation via remote and local teleconnections. We also suggest that future climate studies in South Florida include high‐resolution climate model runs (i.e., ocean eddy resolving) in conjunction with dynamical downscaling to adequately capture precipitation variability.

South Florida↗

USGS2017

Factors associated with bat mortality at wind energy facilities in the United States

Hundreds of thousands of bats are killed annually by colliding with wind turbines in the U.S., yet little is known about factors causing variation in mortality across wind energy facilities. We conducted a quantitative synthesis of bat collision mortality with wind turbines by reviewing 218 North American studies representing 100 wind energy facilities. This data set, the largest compiled for bats to date, provides further evidence that collision mortality is greatest for migratory tree-roosting species (Hoary Bat [ Lasiurus cinereus ], Eastern Red Bat [ Lasiurus borealis ], Silver-haired Bat [ Lasionycteris noctivagans ]) and from July to October. Based on 40 U.S. studies meeting inclusion criteria and analyzed under a common statistical framework to account for methodological variation, we found support for an inverse relationship between bat mortality and percent grassland cover surrounding wind energy facilities. At a national scale, grassland cover may best reflect openness of the landscape, a factor generally associated with reduced activity and abundance of tree-roosting species that may also reduce turbine collisions. Further representative sampling of wind energy facilities is required to validate this pattern. Ecologically informed placement of wind energy facilities involves multiple considerations, including not only factors associated with bat mortality, but also factors associated with bird collision mortality, indirect habitat-related impacts to all species, and overall ecosystem impacts.

Biological Conservation↗

USGS2016

Establishing a pre-mining geochemical baseline at a uranium mine near Grand Canyon National Park, USA

During 2012, approximately 404,000 ha of Federal Land in northern Arizona was withdrawn from consideration of mineral extraction for a 20-year period to protect the Grand Canyon watershed from potentially adverse effects of U mineral exploration and development. The development, operation, and reclamation of the Canyon Mine during the withdrawal period provide an excellent field site to understand and document off-site migration of radionuclides within the withdrawal area. As part of the Department of Interior's (DOI's) study plan for the exclusion area, the objective of our study is to utilize pre-defined decision units (DUs) in areas within and surrounding the Canyon Mine to demonstrate how newly established incremental sampling methodologies (ISM) combined with multivariate statistical methods can be used to document a repeatable and statistically defensible measure of pre-mining baseline conditions in surface soils and stream sediment samples prior to ore extraction. During the survey in June 2013, the highest pre-mining 95% upper confidence level (UCL) concentrations with respect to As, Mo, U, and V were found in the triplicate samples collected from surface soils in the mine site DU designated as M1. Gamma activities were slightly elevated in soils within the M1 DU (up to 28 μR/h); however, off-site gamma activities in soil and stream-sediment samples were lower (< 6 to 12 μR/h). Hierarchical cluster analysis (HCA) was applied to 33 chemical constituents contained in the multivariate data generated from the analysis of triplicate samples collected in the soil and stream sediment DUs within and surrounding Canyon Mine. Most of the triplicate samples from individual DUs were grouped in the same dendrogram cluster when using a similarity value (SV) of 0.70 (unitless). Different group membership of triplicate samples from two of the four haul road DUs was likely the result of heterogeneity induced by non-native soil material introduced from the gravel road base or from vehicular traffic. Application of HCA and ISM will provide critical metrics to meet DOI's long-term goals for assessing off-site migration of radionuclides resulting from mining and reclamation in the current (2015) exclusion area associated within the Grand Canyon watershed and the associated national park.

Arizona↗

USGS2015

Desert tortoises ( Gopherus agassizii ) are selective herbivores that track the flowering phenology of their preferred food plants

Previous studies of desert tortoise foraging ecology in the western Mojave Desert suggest that these animals are selective herbivores, which alter their diet according to the temporal availability of preferred food plants. These studies, however, did not estimate availability of potential food plants by taking into account the spatial and temporal variability in ephemeral plant abundance that occurs within the spring season. In this study, we observed 18 free-ranging adult tortoises take 35,388 bites during the spring foraging season. We also estimated the relative abundance of potential food plants by stratifying our sampling across different phenological periods of the 3-month long spring season and by different habitats and microhabitats. This methodology allowed us to conduct statistical tests comparing tortoise diet against plant abundance. Our results show that tortoises choose food plants non-randomly throughout the foraging season, a finding that corroborates the hypothesis that desert tortoises rely on key plants during different phenological periods of spring. Moreover, tortoises only consumed plants in a succulent state until the last few weeks of spring, at which time most annuals and herbaceous perennials had dried and most tortoises had ceased foraging. Many species of food plants—including several frequently eaten species—were not detected in our plant surveys, yet tortoises located these rare plants in their home ranges. Over 50% of bites consumed were in the group of undetected species. Interestingly, tortoises focused heavily on several leguminous species, which could be nutritious foods owing to their presumably high nitrogen contents. We suggest that herbaceous perennials, which were rare on our study area but represented ~30% of tortoise diet, may be important in sustaining tortoise populations during droughts when native annuals are absent. These findings highlight the vulnerability of desert tortoises to climate change if such changes alter the availability of their preferred food plants.

California↗

USGS2016

Book review: Mineral resource estimation

Mineral Resource Estimation is about estimating mineral resources at the scale of an ore deposit and is not to be mistaken with mineral resource assessment, which is undertaken at a significantly broader scale, even if similar data and geospatial/geostatistical methods are used. The book describes geological, statistical, and geostatistical tools and methodologies used in resource estimation and modeling, and presents case studies for illustration. The target audience is the expert, which includes professional mining geologists and engineers, as well as graduate-level and advanced undergraduate students. Review info: Mineral Resource Estimation . By Mario E. Rossi, Clayton V. Deutsch . 2014 . ISBN 978-1-4020-5716-8 332 pp.

Economic Geology↗

USGS2018

Model methodology for estimating pesticide concentration extremes based on sparse monitoring data

This report describes a new methodology for using sparse (weekly or less frequent observations) and potentially highly censored pesticide monitoring data to simulate daily pesticide concentrations and associated quantities used for acute and chronic exposure assessments, such as the annual maximum daily concentration. The new methodology is based on a statistical model that expresses log-transformed daily pesticide concentration in terms of a seasonal wave, flow-related variability, long-term trend, and serially correlated errors. Methods are described for estimating the model parameters, generating conditional simulations of daily pesticide concentration given sparse (weekly or less frequent) and potentially highly censored observations, and estimating concentration extremes based on the conditional simulations. The model can be applied to datasets with as few as 3 years of record, as few as 30 total observations, and as few as 10 uncensored observations. The model was applied to atrazine, carbaryl, chlorpyrifos, and fipronil data for U.S. Geological Survey pesticide sampling sites with sufficient data for applying the model. A total of 112 sites were analyzed for atrazine, 38 for carbaryl, 34 for chlorpyrifos, and 33 for fipronil. The results are summarized in this report; and, R functions, described in this report and provided in an accompanying model archive, can be used to fit the model parameters and generate conditional simulations of daily concentrations for use in investigations involving pesticide exposure risk and uncertainty.

Scientific Investigations Report↗

USGS2012

A methodology for conducting national-scale alluvial diamond resource potential and production capacity assessments, with a focus on artisanal mining

In May of 2000, a meeting was convened in Kimberley, South Africa, by representatives of the diamond industry and leaders of African governments to develop a certification process intended to assure that export shipments of rough diamonds were free of conflict concerns. Outcomes of the meeting were formally supported later in December of 2000 by the United Nations in a resolution adopted by the General Assembly. By 2002, the Kimberley Process Certification Scheme was ratified and signed by diamond-producing and diamond-importing countries. As of August 2012, the Kimberley Process (KP) had 51 participants representing 77 countries. It is often difficult to obtain independent verification of the diamond production statistics that are provided to the KP. However, some degree of independent verification can be obtained through an understanding of a country’s naturally occurring endowment of diamonds and the intensity of mining activities. Studies that integrate these two components can produce a range of estimated values for a country’s diamond production, and these estimates can then be compared to the production statistics released by that country. This methodology is used to calculate (1) the diamond resource potential of a country, which refers to the total number of carats estimated to be remaining in the country, and (2) the diamond production capacity of a country, which is the current volume of diamonds that may realistically be produced per year utilizing current human and physical resources. The following sections outline the methodology used by the U.S. Geological Survey (USGS) to perform diamond assessments in Mali, the Central African Republic, Ghana, and Guinea.

Fact Sheet↗

USGS2005

Streamflow statistics for the Paradise and Pocono Creek watersheds and selected streamflow-gaging stations in Monroe County, Pennsylvania

suite of 36 observed streamflow statistics, ranging from high to low flows, were computed for 7 continuous-record and predicted for 12 partial-record streamflow-gaging stations in Monroe County, Pa. The predicted statistics for the partial-record stations were determined from regression analyses of intermittent streamflow measurements made at the partial-record stations and concurrent daily mean flows at index continuous-record stations. The prediction methodology has been previously used only for estimating low-flow statistics. Results from this study indicate the methodology may have applicability for predicting high- and intermediate-flow statistics as well. Three sets of base-flow measurements were made at 40 sites in the Paradise and Pocono Creek watersheds to determine subbasin yields and stream reaches gaining or losing flow. Subbasin yields, the base-flow measurements normalized to respective drainage areas, were consistent for each measurement period.

Scientific Investigations Report↗

USGS2003

On the use of attractor dimension as a feature in structural health monitoring

Recent works in the vibration-based structural health monitoring community have emphasised the use of correlation dimension as a discriminating statistic in seperating a damaged from undamaged response. This paper explores the utility of attractor dimension as a 'feature' and offers some comparisons between different metrics reflecting dimension. This focus is on evaluating the performance of two different measures of dimension as damage indicators in a structural health monitoring context. Results indicate that the correlation dimension is probably a poor choice of statistic for the purpose of signal discrimination. Other measures of dimension may be used for the same purposes with a higher degree of statistical reliability. The question of competing methodologies is placed in a hypothesis testing framework and answered with experimental data taken from a cantilivered beam.

Mechanical Systems and Signal Processing↗

USGS2014

Evaluation of statistically downscaled GCM output as input for hydrological and stream temperature simulation in the Apalachicola–Chattahoochee–Flint River Basin (1961–99)

The accuracy of statistically downscaled general circulation model (GCM) simulations of daily surface climate for historical conditions (1961–99) and the implications when they are used to drive hydrologic and stream temperature models were assessed for the Apalachicola–Chattahoochee–Flint River basin (ACFB). The ACFB is a 50 000 km 2 basin located in the southeastern United States. Three GCMs were statistically downscaled, using an asynchronous regional regression model (ARRM), to ⅛° grids of daily precipitation and minimum and maximum air temperature. These ARRM-based climate datasets were used as input to the Precipitation-Runoff Modeling System (PRMS), a deterministic, distributed-parameter, physical-process watershed model used to simulate and evaluate the effects of various combinations of climate and land use on watershed response. The ACFB was divided into 258 hydrologic response units (HRUs) in which the components of flow (groundwater, subsurface, and surface) are computed in response to climate, land surface, and subsurface characteristics of the basin. Daily simulations of flow components from PRMS were used with the climate to simulate in-stream water temperatures using the Stream Network Temperature (SNTemp) model, a mechanistic, one-dimensional heat transport model for branched stream networks. The climate, hydrology, and stream temperature for historical conditions were evaluated by comparing model outputs produced from historical climate forcings developed from gridded station data (GSD) versus those produced from the three statistically downscaled GCMs using the ARRM methodology. The PRMS and SNTemp models were forced with the GSD and the outputs produced were treated as “truth.” This allowed for a spatial comparison by HRU of the GSD-based output with ARRM-based output. Distributional similarities between GSD- and ARRM-based model outputs were compared using the two-sample Kolmogorov–Smirnov (KS) test in combination with descriptive metrics such as the mean and variance and an evaluation of rare and sustained events. In general, precipitation and streamflow quantities were negatively biased in the downscaled GCM outputs, and results indicate that the downscaled GCM simulations consistently underestimate the largest precipitation events relative to the GSD. The KS test results indicate that ARRM-based air temperatures are similar to GSD at the daily time step for the majority of the ACFB, with perhaps subweekly averaging for stream temperature. Depending on GCM and spatial location, ARRM-based precipitation and streamflow requires averaging of up to 30 days to become similar to the GSD-based output. Evaluation of the model skill for historical conditions suggests some guidelines for use of future projections; while it seems correct to place greater confidence in evaluation metrics which perform well historically, this does not necessarily mean those metrics will accurately reflect model outputs for future climatic conditions. Results from this study indicate no “best” overall model, but the breadth of analysis can be used to give the product users an indication of the applicability of the results to address their particular problem. Since results for historical conditions indicate that model outputs can have significant biases associated with them, the range in future projections examined in terms of change relative to historical conditions for each individual GCM may be more appropriate.

Florida, Georgia↗

USGS2003

Environmental characteristics and benthic invertebrate assemblages in Colorado mountain lakes

Twenty-two high-elevation lakes (>3000 m) in Rocky Mountain National Park and Indian Peaks Wilderness Area, Colorado, were surveyed during summer 1998 to explore relationships among benthic invertebrates, water chemistry (particularly nitrate concentrations), and other environmental variables. Water samples were collected from the deepest portion of each lake and analyzed for ions and other water chemistry parameters. Benthic invertebrates were collected from the littoral zone using both a sweep net and Hess sampler. Physical and geographical measurements were derived from maps. Relationships among benthic invertebrate assemblages and environmental variables were examined using canonical correspondence analysis, and the importance of sampling methodology and taxonomie resolution on these relationships was evaluated. Choice of sampling methodology strongly influenced the outcome of statistical analyses, whereas taxonomie resolution did not. Presence/absence of benthic invertebrate taxa among the study lakes was best explained by elevation and presence of fish. Relative abundance and density of benthic invertebrate taxa were more strongly influenced by sampling date and water chemistry. Nitrate (NO₃⁻) concentration, potentially on the rise due to regional nitrogen deposition, was unrelated to benthic invertebrate distribution regardless of sampling method or taxonomie resolution.

Western North American Naturalist↗

USGS2012

Bayesian WLS/GLS regression for regional skewness analysis for regions with large crest stage gage networks

This paper summarizes methodological advances in regional log-space skewness analyses that support flood-frequency analysis with the log Pearson Type III (LP3) distribution. A Bayesian Weighted Least Squares/Generalized Least Squares (B-WLS/B-GLS) methodology that relates observed skewness coefficient estimators to basin characteristics in conjunction with diagnostic statistics represents an extension of the previously developed B-GLS methodology. B-WLS/B-GLS has been shown to be effective in two California studies. B-WLS/B-GLS uses B-WLS to generate stable estimators of model parameters and B-GLS to estimate the precision of those B-WLS regression parameters, as well as the precision of the model. The study described here employs this methodology to develop a regional skewness model for the State of Iowa. To provide cost effective peak-flow data for smaller drainage basins in Iowa, the U.S. Geological Survey operates a large network of crest stage gages (CSGs) that only record flow values above an identified recording threshold (thus producing a censored data record). CSGs are different from continuous-record gages, which record almost all flow values and have been used in previous B-GLS and B-WLS/B-GLS regional skewness studies. The complexity of analyzing a large CSG network is addressed by using the B-WLS/B-GLS framework along with the Expected Moments Algorithm (EMA). Because EMA allows for the censoring of low outliers, as well as the use of estimated interval discharges for missing, censored, and historic data, it complicates the calculations of effective record length (and effective concurrent record length) used to describe the precision of sample estimators because the peak discharges are no longer solely represented by single values. Thus new record length calculations were developed. The regional skewness analysis for the State of Iowa illustrates the value of the new B-WLS/BGLS methodology with these new extensions.

Conference Paper↗

USGS2001

Declining scaup populations: A retrospective analysis of long-term population and harvest survey data

We examined long-term databases concerning population status of scaup (lesser [ Aythya affinis ] and greater scaup [ A. marila ] combined) and harvest statistics of lesser scaup to identify factors potentially limiting population growth. Specifically, we explored evidence for and against the general hypotheses that scaup populations have declined in association with declining recruitment and/or female survival. We examined geographic heterogeneity in scaup demographic patterns that could yield evidence about potential limiting factors. Several biases exist in survey methodology used to estimate scaup populations and harvest statistics; however, none of these biases likely accounted for our major findings that (1) the continental scaup breeding population has declined over the last 20 years, with widespread and consistent declines within surveyed areas of the Canadian western boreal forest where most lesser scaup breed; (2) sex ratios of lesser scaup in the U.S. harvest have increased (more males now relative to females); and (3) age ratios of lesser scaup in the U.S. harvest have declined (fewer immatures now relative to adults), especially in the midcontinent region. We interpreted these major findings as evidence that (1) recruitment of lesser scaup has declined over the last 20 years, particularly in the Canadian western boreal forest; and (2) survival of female lesser scaup has declined relative to that of males. We found little evidence that harvest was associated with the scaup population decline. Our findings underscore the need for both improvements and changes to population survey procedures and new research to discriminate among various hypotheses explaining the recent scaup population decline.

North America↗

USGS2019

A parametric numerical analysis of factors controlling ground ruptures caused by groundwater pumping

A modeling analysis is used to investigate the relative susceptibility of various hydrogeologic configurations to aseismic rupture generation due to deformation of aquifer systems accompanying groundwater pumping. An advanced numerical model (GEPS3D) is used to simulate rupture generation and propagation for three typical processes: (i) reactivation of a preexisting fault, (ii) differential compaction due to variations in thickness of aquifer/aquitard layers constituting the aquifer system, and (iii) tensile fracturing above a bedrock ridge that forms the base of the aquifer system. A sensitivity analysis is developed to address the relative importance of various factors, including aquifer depletion, aquifer thickness, the possible uneven distribution and depth below land surface of the aquifer/aquitard layers susceptible to aquifer-system compaction, and the height of bedrock ridges beneath the aquifer system which contributes to thinning of the aquifer system. The rupture evolution is classified in two occurrences. In one, the rupture develops at the top of the aquifer or at land surface and does not propagate. In the other, the developed rupture propagates from the aquifer top toward the land surface and/or from the land surface downward. The aquifer depth is the most important factor controlling rupture evolution. Specifically, the probability of a significant rupture propagation is higher when the aquifer top is near land surface. The numerical results are processed by a statistical regression analysis to provide a general methodology for a preliminary evaluation of possible ruptures development in exploited aquifer systems susceptible to aquifer-system compaction and accompanying land subsidence. A comparison with a few representative case studies in Arizona, USA, China, and Mexico supports the study outcomes.

Arizona↗

USGS2012

Geologic framework for the national assessment of carbon dioxide storage resources: Bighorn Basin, Wyoming and Montana: Chapter A in Geologic framework for the national assessment of carbon dioxide storage resources

The 2007 Energy Independence and Security Act ( Public Law 110–140 ) directs the U.S. Geological Survey (USGS) to conduct a national assessment of potential geologic storage resources for carbon dioxide (CO 2 ). The methodology used for the national CO 2 assessment follows that of previous USGS work. The methodology is non-economic and intended to be used at regional to subbasinal scales. This report identifies and contains geologic descriptions of twelve storage assessment units (SAUs) in six separate packages of sedimentary rocks within the Bighorn Basin of Wyoming and Montana and focuses on the particular characteristics, specified in the methodology, that influence the potential CO 2 storage resource in those SAUs. Specific descriptions of the SAU boundaries as well as their sealing and reservoir units are included. Properties for each SAU such as depth to top, gross thickness, net porous thickness, porosity, permeability, groundwater quality, and structural reservoir traps are provided to illustrate geologic factors critical to the assessment. Although assessment results are not contained in this report, the geologic information included here will be employed, as specified in the methodology of earlier work, to calculate a statistical Monte Carlo-based distribution of potential storage space in the various SAUs. Figures in this report show SAU boundaries and cell maps of well penetrations through the sealing unit into the top of the storage formation. Wells sharing the same well borehole are treated as a single penetration. Cell maps show the number of penetrating wells within one square mile and are derived from interpretations of incompletely attributed well data, a digital compilation that is known not to include all drilling. The USGS does not expect to know the location of all wells and cannot guarantee the amount of drilling through specific formations in any given cell shown on cell maps.

Wyoming, Montana↗

USGS2016

USGS approach to real-time estimation of earthquake-triggered ground failure - Results of 2015 workshop

The U.S. Geological Survey (USGS) Earthquake Hazards and Landslide Hazards Programs are developing plans to add quantitative hazard assessments of earthquake-triggered landsliding and liquefaction to existing real-time earthquake products (ShakeMap, ShakeCast, PAGER) using open and readily available methodologies and products. To date, prototype global statistical models have been developed and are being refined, improved, and tested. These models are a good foundation, but much work remains to achieve robust and defensible models that meet the needs of end users. In order to establish an implementation plan and identify research priorities, the USGS convened a workshop in Golden, Colorado, in October 2015. This document summarizes current (as of early 2016) capabilities, research and operational priorities, and plans for further studies that were established at this workshop. Specific priorities established during the meeting include (1) developing a suite of alternative models; (2) making use of higher resolution and higher quality data where possible; (3) incorporating newer global and regional datasets and inventories; (4) reducing barriers to accessing inventory datasets; (5) developing methods for using inconsistent or incomplete datasets in aggregate; (6) developing standardized model testing and evaluation methods; (7) improving ShakeMap shaking estimates, particularly as relevant to ground failure, such as including topographic amplification and accounting for spatial variability; and (8) developing vulnerability functions for loss estimates.

Open-File Report↗