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At least 145 records · Page 8Linked to original sources
USGS2003

Maps showing geology, oil and gas fields, and geologic provinces of the Arctic

Introduction This CD-ROM was compiled according to the methodology developed by the U.S. Geological Survey's World Energy Project . The geologic map of the Arctic was compiled and synthesized from the Circumpolar Geological Map of the Arctic, by Okulitch A.V., Lopatin B.G., and Jackson H.R., scale 1:6,000,000, published by the Geological Survey of Canada in 1989 (see References ). Specific details of the data sources are given in the metadata files on this CD-ROM. Map units were kept as close as possible to original map (more than 100 unique values). These Arctic maps were compiled using Environmental Systems Research Institute Inc. (ESRI) ARC/INFO software. Political boundaries and cartographic representations on this map are shown (with permission) from ESRI's ArcWorld 1:3M digital coverage. They have no political significance and are displayed as general reference only. Portions of this database covering the coastline, rivers and country boundaries contain proprietary property of ESRI. (© 1992 and 1996, Environmental Systems Research Institute Inc. All rights reserved. The bathymetric data were derived from the International Bathymetric Chart of the Arctic Ocean (IBCAO) which was downloaded from the NOAA web site. Oil and gas centerpoints were derived from Probe 4.0 database - proprietary property of Petroleum Information/Dwights LLC d/b/a/IHS Energy Group. Specific details of the data sources and map compilation are given in the metadata files on this CD-ROM.

Open-File Report↗
USGS2005

Statistical analysis of water-quality data containing multiple detection limits: S-language software for regression on order statistics

Trace contaminants in water, including metals and organics, often are measured at sufficiently low concentrations to be reported only as values below the instrument detection limit. Interpretation of these "less thans" is complicated when multiple detection limits occur. Statistical methods for multiply censored, or multiple-detection limit, datasets have been developed for medical and industrial statistics, and can be employed to estimate summary statistics or model the distributions of trace-level environmental data. We describe S-language-based software tools that perform robust linear regression on order statistics (ROS). The ROS method has been evaluated as one of the most reliable procedures for developing summary statistics of multiply censored data. It is applicable to any dataset that has 0 to 80% of its values censored. These tools are a part of a software library, or add-on package, for the R environment for statistical computing. This library can be used to generate ROS models and associated summary statistics, plot modeled distributions, and predict exceedance probabilities of water-quality standards. ?? 2005 Elsevier Ltd. All rights reserved.

Computers & Geosciences↗
USGS2007

Surficial sediment character of the New York-New Jersey offshore continental shelf region: A GIS compilation

Broad continental shelf regions such as the New York Bight are the product of a complex geologic history and dynamic oceanographic processes, dominated by the Holocene marine transgression (>100 m sea-level rise) following the end of the last Pleistocene ice advance ~ 20,000 years ago. The area of the U.S. Exclusive Economic Zone (U.S. EEZ) territory, extending 200 nautical miles seaward from the coast, is larger than the continental U.S. and contains submerged landforms that provide a variety of natural functions and societal benefits, such as: critical habitats for fisheries, ship navigation and homeland security, and engineering activities (i.e. oil and gas platforms, pipeline and cable routes, potential wind-energy-generation sites). Some parts of the continental margins, particularly inner-continental shelf regions, also contain unconsolidated hard-mineral deposits such as sand and gravel that are regarded as potential aggregate resources to meet or augment needs not met by onshore deposits (Williams, 1992). The present distribution of surficial sediment off the northeastern United States is shaped from the deposits left by the last glaciation and reflects the cumulative effects of sediment erosion, transport, sorting, and deposition by storm and tidal processes during the Holocene rise in sea level. As a result, the sediments on the sea floor represent both an historical record of former conditions and a guide to possible future sedimentary environments. The U.S. Geological Survey (USGS) through the Coastal and Marine Geology Program, in cooperation with the University of Colorado and other partners, has compiled extant sediment character and textural data as well as other geologic information on the sea floor from all regions around the U.S. into the usSEABED data system (Reid and others, 2005; Buczkowski and others, 2006; Reid and others, 2006). The usSEABED system, which contains information on sediment grain size and lithology for more than 340,500 stations within the U.S. EEZ. has been developed and populated with data as part of the USGS Marine Aggregate Resources and Processes and the National Benthic Habitats projects in order to provide the base-line data needed to update the current maps of offshore surficial geologic character and sediment distribution. The maps are also used to characterize benthic sea floor environments important for marine ecosystems. U.S. Geological Survey, Data Series 118 (Reid and others, 2005), of the usSEABED data release series, represents the combined efforts of the USGS and several other government agencies to provide a unified resource for accessing and preserving records of U.S. east coast sea floor geologic information and sediment texture data. For this present report, we have chosen to focus on the New York-New Jersey region, an area that has been intensely studied by the USGS for many years to address many complex issues. This report illustrates the uses of the usSEABED database for GIS applications, while offering additional insight into the resources and data available from the USGS and its collaborative institutions. This report is based on data contained in U.S. Geological Survey Data Series 118 (Reid and others, 2005) and shows an assortment of example GIS products that are possible using usSEABED. All data are intended to be GIS-ready and should not require any additional cleanup, formatting, or renaming of fields in order to use the data in a Geographic Information System. This project employs the Environmental Systems Research Institute's (ESRI) ArcView™ software. Many of these maps were made as part of the ongoing USGS study to assess marine aggregate resources offshore New York and New Jersey, but these maps can serve many other purposes. The marine science community, educators, students and others are encouraged to use these data to generate GIS products for their own purposes. The objectives of the Marine Aggregate Resources and Processes project are to produce a series of new geologic maps and reports of the sea floor that will provide scientific insights into the character and geologic development of U.S. continental margins and to use these maps and information to assess the potential availability of offshore sand and gravel resources. The mapping and aggregate resource assessments are being conducted on a national scale using the usSEABED data base as described in Williams and others (2003). Potential uses for these data include: (1) defining the geological variability of the sea floor in relation to benthic habitat diversity; (2) improving our understanding of the processes that control the distribution and transport of bottom sediments and benthic habitats; (3) locating aggregate resources for beach nourishment and industrial applications; and (4) providing a detailed geospatial framework for future marine science research, monitoring, and management activities. The initial assessments are in progress for the New York Bight and Louisiana offshore areas.

New Jersey, New York↗
USGS1993

Wetland modeling and information needs at Stillwater National Wildlife Refuge

The marshes in and around Stillwater National Wildlife Refuge (the Refuge) are extremely dynamic; expanding and contracting in size both seasonally, due to runoff and subsequent evapotranspiration, and over longer periods, due to climatic variation. The dynamic nature of these marshes results in a diversity of wetland habitats, which support a variety of migratory birds. To maintain this wetland diversity and control the loss of migratory bird habitat in the Lahontan Valley, the Refuge was established and currently manages a complex of marsh units. However, changes in the hydrology, and changes that will occur as a result of the Fallon Paiute-Shoshone and Truckee-Carson-Pyramid Lake Water Rights Settlement Act (Public Law 101-618, 104 Stat. 3389), greatly affect the Refuge's wetland management capability. In light of these changes, and the legal requirements associated with environmental impact assessments, the Refuge convened a workshop to discuss several aspects of wetland management in the Lahontan Valley. The workshop, described in this report, had three primary objectives: 1. discuss the types and relative proportions of primary wetland habitats that should be provided as described in the settlement act; 2. discuss wetland management models that might be developed to help manage these marshes under hydrologic regimes likely in the future; and 3. discuss future information and monitoring needs, including proposals for valley-wide biodiversity surveys, which would be helpful when considering withdrawn Bureau of Reclamation (BR) lands for possible incorporation into the Refuge. Several presentations at the beginning of the workshop provided a common basis for discussing these objectives. Refuge staff provided background on the history and past management. The Nature Conservatory discussed their role in the settlement act, proposals for valley-wide biodiversity surveys, and results of a literature review for Stillwater Marsh and the Lahontan Valley (Nachlinger 1993). Kay Fowler provided an historical context of changes in vegetation and waterbird use of the marshes based on her ethnography of the local Paiute Indians (Fowler 1993). Finally, Bob Elston discussed a model that predicts archaeological sites based on environmental variables (Raven and Elston 1989). The workshop was organized by staff from the Refuge and facilitated by the authors of this report. Participants included Ron Anglin, Bill Henry, Anne Janik, Cliff Creger, Fred Paveglio, and Mary Jo Elpers of the U.S. Fish and Wildlife Service (the Service); Jeff Baumgartner, Jan Nachlinger, Hope Humphries, and Graham Chisholm of The Nature Conservancy; David Yardas of the Environmental Defense Fund; David Robertson of Robertson Software, Inc.; Norm Saake, Terry Retterer, and Larry Neel of the Nevada Department of Wildlife; Lew Oring and Kay Fowler of the University of Nevada; and Robert Elston of Intermountain Research.

Report↗
USGS2018

Stream permanence is related to crayfish occupancy and abundance in the Ozark Highlands, USA

Crayfish use of intermittent streams is especially important to understand in the face of global climate change. We examined the influence of stream permanence and local habitat on crayfish occupancy and species densities in the Ozark Highlands, USA. We sampled in June and July 2014 and 2015. We used a quantitative kick–seine method to sample crayfish presence and abundance at 20 stream sites with 32 surveys/site in the Upper White River drainage, and we measured associated local environmental variables each year. We modeled site occupancy and detection probabilities with the software PRESENCE, and we used multiple linear regressions to identify relationships between crayfish species densities and environmental variables. Occupancy of all crayfish species was related to stream permanence. Faxonius meeki was found exclusively in intermittent streams, whereas Faxonius neglectus and Faxonius luteus had higher occupancy and detection probability in permanent than in intermittent streams, and Faxonius williamsi was associated with intermittent streams. Estimates of detection probability ranged from 0.56 to 1, which is high relative to values found by other investigators. With the exception of F. williamsi , species densities were largely related to stream permanence rather than local habitat. Species densities did not differ by year, but total crayfish densities were significantly lower in 2015 than 2014. Increased precipitation and discharge in 2015 probably led to the lower crayfish densities observed during this year. Our study demonstrates that crayfish distribution and abundance is strongly influenced by stream permanence. Some species, including those of conservation concern (i.e., F. williamsi , F. meeki ), appear dependent on intermittent streams, and conservation efforts should include consideration of intermittent streams as an important component of freshwater biodiversity.

Arkansas, Missouri↗
USGS2020

Time-series model, statistical methods, and software documentation for R–QWTREND—An R package for analyzing trends in stream-water quality

As part of a U.S. Geological Survey water-quality study started in 2018, in cooperation with the International Joint Commission, North Dakota Department of Environmental Quality, and Minnesota Pollution Control Agency, a publicly available software package called R–QWTREND was developed for analyzing trends in stream-water quality. The R–QWTREND package is a collection of functions written in R, an open source language and a general environment for statistical computing and graphics. The package uses a parametric time-series model to express logarithmically transformed concentration in terms of flow-related variability, trend, and serially correlated model errors. Flow-related variability captures natural variability in concentration on the basis of concurrent and antecedent streamflow. The trend identifies systematic changes in concentration in terms of potential step trends, piecewise monotonic trends, or user-specified trends. Maximum likelihood estimation is used to estimate model parameters and determine the best-fit trend model. This report describes the time-series model and statistical methodology behind R–QWTREND and provides formal documentation for installing and using the package.

Open-File Report↗
USGS2013

Developing and implementing the use of predictive models for estimating water quality at Great Lakes beaches

Predictive models have been used at beaches to improve the timeliness and accuracy of recreational water-quality assessments over the most common current approach to water-quality monitoring, which relies on culturing fecal-indicator bacteria such as Escherichia coli (E. coli.) . Beach-specific predictive models use environmental and water-quality variables that are easily and quickly measured as surrogates to estimate concentrations of fecal-indicator bacteria or to provide the probability that a State recreational water-quality standard will be exceeded. When predictive models are used for beach closure or advisory decisions, they are referred to as “nowcasts.” During the recreational seasons of 2010-12, the U.S. Geological Survey (USGS), in cooperation with 23 local and State agencies, worked to improve existing nowcasts at 4 beaches, validate predictive models at another 38 beaches, and collect data for predictive-model development at 7 beaches throughout the Great Lakes. This report summarizes efforts to collect data and develop predictive models by multiple agencies and to compile existing information on the beaches and beach-monitoring programs into one comprehensive report. Local agencies measured E. coli concentrations and variables expected to affect E. coli concentrations such as wave height, turbidity, water temperature, and numbers of birds at the time of sampling. In addition to these field measurements, equipment was installed by the USGS or local agencies at or near several beaches to collect water-quality and metrological measurements in near real time, including nearshore buoys, weather stations, and tributary staff gages and monitors. The USGS worked with local agencies to retrieve data from existing sources either manually or by use of tools designed specifically to compile and process data for predictive-model development. Predictive models were developed by use of linear regression and (or) partial least squares techniques for 42 beaches that had at least 2 years of data (2010-11 and sometimes earlier) and for 1 beach that had 1 year of data. For most models, software designed for model development by the U.S. Environmental Protection Agency (Virtual Beach) was used. The selected model for each beach was based on a combination of explanatory variables including, most commonly, turbidity, day of the year, change in lake level over 24 hours, wave height, wind direction and speed, and antecedent rainfall for various time periods. Forty-two predictive models were validated against data collected during an independent year (2012) and compared to the current method for assessing recreational water quality-using the previous day’s E. coli concentration (persistence model). Goals for good predictive-model performance were responses that were at least 5 percent greater than the persistence model and overall correct responses greater than or equal to 80 percent, sensitivities (percentage of exceedances of the bathing-water standard that were correctly predicted by the model) greater than or equal to 50 percent, and specificities (percentage of nonexceedances correctly predicted by the model) greater than or equal to 85 percent. Out of 42 predictive models, 24 models yielded over-all correct responses that were at least 5 percent greater than the use of the persistence model. Predictive-model responses met the performance goals more often than the persistence-model responses in terms of overall correctness (28 versus 17 models, respectively), sensitivity (17 versus 4 models), and specificity (34 versus 25 models). Gaining knowledge of each beach and the factors that affect E. coli concentrations is important for developing good predictive models. Collection of additional years of data with a wide range of environmental conditions may also help to improve future model performance. The USGS will continue to work with local agencies in 2013 and beyond to develop and validate predictive models at beaches and improve existing nowcasts, restructuring monitoring activities to accommodate future uncertainties in funding and resources.

Great Lakes↗
USGS1988

Federal microcomputer software for urban hydrology

The purpose of this paper is to describe the development, availability, and general use of selected urban hydrology microcomputer software developed by: U.S. Soil Conservation Service (SCS); U.S. Army Corps of Engineers, Hydrologic Engineering Center (HEC); U.S. Environmental Protection Agency (EPA); and U.S. Geological Survey (USGS). The discussion is limited to software used for design and planning for urban stormwater flows.

Conference Paper↗
USGS2007

Statistical analysis of water-quality data containing multiple detection limits II: S-language software for nonparametric distribution modeling and hypothesis testing

Analysis of low concentrations of trace contaminants in environmental media often results in left-censored data that are below some limit of analytical precision. Interpretation of values becomes complicated when there are multiple detection limits in the data-perhaps as a result of changing analytical precision over time. Parametric and semi-parametric methods, such as maximum likelihood estimation and robust regression on order statistics, can be employed to model distributions of multiply censored data and provide estimates of summary statistics. However, these methods are based on assumptions about the underlying distribution of data. Nonparametric methods provide an alternative that does not require such assumptions. A standard nonparametric method for estimating summary statistics of multiply-censored data is the Kaplan-Meier (K-M) method. This method has seen widespread usage in the medical sciences within a general framework termed "survival analysis" where it is employed with right-censored time-to-failure data. However, K-M methods are equally valid for the left-censored data common in the geosciences. Our S-language software provides an analytical framework based on K-M methods that is tailored to the needs of the earth and environmental sciences community. This includes routines for the generation of empirical cumulative distribution functions, prediction or exceedance probabilities, and related confidence limits computation. Additionally, our software contains K-M-based routines for nonparametric hypothesis testing among an unlimited number of grouping variables. A primary characteristic of K-M methods is that they do not perform extrapolation and interpolation. Thus, these routines cannot be used to model statistics beyond the observed data range or when linear interpolation is desired. For such applications, the aforementioned parametric and semi-parametric methods must be used.

Computers & Geosciences↗
USGS2022

NWTOPT — A hyperparameter optimization approach for selection of environmental model solver settings

Hyperparameter optimization approaches were applied to improve performance and accuracy of groundwater flow models. Freely available new software, NWTOPT, is described that uses Tree of Parzen Estimators (TPE) and Random Search algorithms to optimize MODFLOW-NWTs solver settings. We ran 3500 trials on a steady-state and transient model. To quantify the performance of candidate solver settings, we defined a loss function based on time elapsed and mass balance error of the MODFLOW-NWT forward run. Before optimization the steady- state model ran in ~12 min and the transient model ran in ~5 h with acceptable mass balance error (<1%). After optimization runtimes were reduced to ~2.7 min (steady state) and ~48 min (transient) with errors below 0.1%. In both cases TPE found hyperparameters that resulted in faster running and lower error models than those found by Random Search. The time to complete the optimization trials was also shorter with the TPE algorithm.

Environmental Modelling and Software↗
USGS1987

UTILIZATION OF GEOGRAPHIC INFORMATION SYSTEMS TECHNOLOGY IN THE ASSESSMENT OF REGIONAL GROUND-WATER QUALITY.

The U. S. Geological Survey (USGS) in cooperation with the U. S. Environmental Protection Agency Office of Pesticide Programs and several State agencies in Oregon has prepared a digital spatial database at 1:500,000 scale to be used as a basis for evaluating the potential for ground-water contamination by pesticides and other agricultural chemicals. Geographic information system (GIS) software was used to assemble, analyze, and manage spatial and tabular environmental data in support of this project. Physical processes were interpreted relative to published spatial data and an integrated database to support the appraisal of regional ground-water contamination was constructed. Ground-water sampling results were reviewed relative to the environmental factors present in several agricultural areas to develop an empirical knowledge base which could be used to assist in the selection of future sampling or study areas.

Conference Paper↗
USGS2018

SWToolbox: A surface-water tool-box for statistical analysis of streamflow time series

This report is a user guide for the low-flow analysis methods provided with version 1.0 of the Surface Water Toolbox (SWToolbox) computer program. The software combines functionality from two software programs—U.S. Geological Survey (USGS) SWSTAT and U.S. Environmental Protection Agency (EPA) DFLOW. Both of these programs have been used primarily for computation of critical low-flow statistics. The main analysis methods are the computation of hydrologic frequency statistics such as the 7-day minimum flow that occurs on average only once every 10 years (7Q10), computation of design flows including biologically based flows, and computation of flow-duration curves and duration hydrographs. Other annual, monthly, and seasonal statistics can also be computed. The interface facilitates retrieval of streamflow discharge data from the USGS National Water Information System and outputs text reports for a record of the analysis. Tools for graphing data and screening tests are available to assist the analyst in conducting the analysis.

Techniques and Methods↗
USGS2006

Analysis of environmental variation in a Great Plains reservoir using principal components analysis and geographic information systems

We present a method for spatial interpretation of environmental variation in a reservoir that integrates principal components analysis (PCA) of environmental data with geographic information systems (GIS). To illustrate our method, we used data from a Great Plains reservoir (Skiatook Lake, Oklahoma) with longitudinal variation in physicochemical conditions. We measured 18 physicochemical features, mapped them using GIS, and then calculated and interpreted four principal components. Principal component 1 (PC1) was readily interpreted as longitudinal variation in water chemistry, but the other principal components (PC2-4) were difficult to interpret. Site scores for PC1-4 were calculated in GIS by summing weighted overlays of the 18 measured environmental variables, with the factor loadings from the PCA as the weights. PC1-4 were then ordered into a landscape hierarchy, an emergent property of this technique, which enabled their interpretation. PC1 was interpreted as a reservoir scale change in water chemistry, PC2 was a microhabitat variable of rip-rap substrate, PC3 identified coves/embayments and PC4 consisted of shoreline microhabitats related to slope. The use of GIS improved our ability to interpret the more obscure principal components (PC2-4), which made the spatial variability of the reservoir environment more apparent. This method is applicable to a variety of aquatic systems, can be accomplished using commercially available software programs, and allows for improved interpretation of the geographic environmental variability of a system compared to using typical PCA plots. ?? Copyright by the North American Lake Management Society 2006.

Lake and Reservoir Management↗
USGS2013

Capture-recapture methodology

Capture-recapture methods were initially developed to estimate human population abundance, but since that time have seen widespread use for fish and wildlife populations to estimate and model various parameters of population, metapopulation, and disease dynamics. Repeated sampling of marked animals provides information for estimating abundance and tracking the fate of individuals in the face of imperfect detection. Mark types have evolved from clipping or tagging to use of noninvasive methods such as photography of natural markings and DNA collection from feces. Survival estimation has been emphasized more recently as have transition probabilities between life history states and/or geographical locations, even where some states are unobservable or uncertain. Sophisticated software has been developed to handle highly parameterized models, including environmental and individual covariates, to conduct model selection, and to employ various estimation approaches such as maximum likelihood and Bayesian approaches. With these user-friendly tools, complex statistical models for studying population dynamics have been made available to ecologists. The future will include a continuing trend toward integrating data types, both for tagged and untagged individuals, to produce more precise and robust population models.

Book chapter↗
USGS2026

Effects of carbamazepine to visual function in early life stage fish

The frequent detection of pharmaceuticals and personal care products (PPCPs) in the environment raises concern for aquatic systems. Carbamazepine (CBZ), an antiepileptic drug, is among the most detected PPCP globally, with concentrations in surface water exceeding those that induce toxicity to aquatic organisms. Non-targeted transcriptomic profiling was conducted in zebrafish ( Danio rerio ) larvae exposed to 0, 1, 5, 10, or 50 μg/L CBZ from 2 h post fertilization (hpf) through hatching, and then sampled at 48, 72, or 144 hpf. Transcriptomic profiles were annotated and characterized with in silico bioinformatic software to assess top enriched pathways and identify targets of environmentally relevant concentrations of CBZ and anchor molecular effects to higher levels of biological organization. Based on this analysis, CBZ was predicted to impair visual perception and sensory system development. The number of eye saccades, determined with a visually mediated behavioral assay, optokinetic response, was significantly reduced in 144 hpf larvae exposed to concentrations as low as 1 μg/L CBZ. These results indicate that environmentally relevant concentrations of CBZ may target and impact processes involved in visual function in fish.

Environmental Research↗
USGS2002

HAZPAC: An interactive map of Pacific Rim natural hazards, population, and infrastructure

This is an online version of a CD-ROM publication. The text files that describe using this publication make reference to software provided on the disc. For this online version the software can be downloaded for free from Adobe Systems and Environmental Systems Research Institute, Inc. (ESRI). Welcome to HAZPAC! HAZPAC is an interactive map about natural hazard risk in the Pacific Rim region. It is intended to communicate to a broad audience the ideas of 'Crowding the Rim,' which is an international, public-private partnership that fosters collaborative solutions for regional risks. HAZPAC, which stands for 'HAZards of the PACific,' uses Geographic Information System (GIS) technology to help people visualize the socioeconomic connections and shared hazard vulnerabilities among Pacific Rim countries, as well as to explore the general nature of risk. Please refer to the 'INTRODUCTION TO HAZPAC' section of the readme file below to determine which HAZPAC project will be right for you. Once you have decided which HAZPAC project is suitable for you, please refer to the 'GETTING STARTED' sections in the readme file for some basic information that will help you begin using HAZPAC. Also, we highly recommend that you follow the Tutorial exercises in the project-specific HAZPAC User Guides. The User Guides are PDF (Portable Document Format) files that must be read with Adobe Acrobat Reader (a free copy of Acrobat Reader is available using the link near the bottom of this page).

Data Series↗
USGS1997

Revision and product generation software

The U.S. Geological Survey (USGS) developed revision and product generation (RevPG) software for updating digital line graph (DLG) data and producing maps from such data. This software is based on ARC/INFO, a geographic information system from Environmental Systems Resource Institute (ESRI). RevPG consists of ARC/INFO Arc Macro Language (AML) programs, C routines, and interface menus that permit operators to collect vector data using aerial images, to symbolize the data on-screen, and to produce plots and color-separated files for use in printing maps.

Fact Sheet↗
USGS1999

Revision and Product Generation Software

The U.S. Geological Survey (USGS) developed revision and product generation (RevPG) software for updating digital line graph (DLG) data and producing maps from such data. This software is based on ARC/INFO, a geographic information system from Environmental Systems Resource Institute (ESRI). RevPG consists of ARC/INFO Arc Macro Language (AML) programs, C routines, and interface menus that permit operators to collect vector data using aerial images, to symbolize the data onscreen, and to produce plots and color-separated files for use in printing maps.

Fact Sheet↗