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At least 199 records · Page 11Linked to original sources
USGS1991

System requirements specification for the U.S. Geological Survey's National Water Information System II

The U.S. Geological Survey's Water Resources Division is designing and developing a new computer software system for processing and storing hydrologic data. This system, the National Water Information System (NWIS-II) will replace the current water-data and information systems: the National Water Data Storage and Retrieval System (WATSTORE), the National Water Data Exchange (NAWDEX), and the National Water-Use Information System, as well as the current National Water Information System (NWIS-I). The new system will be utilized across the Nation on the Distributed Information System (DIS-II), a network of 32-bit microcomputers on a wide-area network of desktop workstations and related hardware. The purpose of the NWIS-II System Requirements Specification is to integrate requirements described by eight User Groups representing the disciplines for Surface Water, Ground Water, Water Quality, Water Sediment, Water Use, Biology, Geographic Information, and National Water Data Exchange. The requirements specified in this document will serve as the framework for subsequent design and development activities throughout the life cycle of NWIS-II to ensure that the development products reflect the needs of the users. Specification details and associated data-base plans are contained in the description of the integrated functional requirements, the logical data model and the data dictionary, the plan for transferring data from the existing system to NWIS-II, and the descriptions of performance requirements and design constraints. The NWIS-II will be consistent across hydrologic disciplines and the other major Division software systems. The color-graphics desktop environment of NWIS-II will utilize multi-window and multi-tasking capabilities with multilevel of help for the users. Data will be distributed among nodes and be automatically accessible during input, editing, verification and analysis of data. Hydrologic data will be cataloged independent of the Environmental Protection Agency's storage and retrieval (STORET) codes. Character, digital, and graphical data will be entered into NWIS-II from digital and analog recorders, external files, or keyboard through standard and user-defined input forms. Data will be verified manually or automatically during input, retrieval, and editing of data. Numerous reference lists will be maintained so that entry of codes on forms will not be required. User-defined series of computer actions for standard programs will be supported for processing basic data and other frequently repeated processes. Data will be verified and exchanged through links to other DIS-II software, including a Geographic Information System, and selected external software. Quality assurance of data will include aging of data through change on status type and tracking access violations. Output of data will be to a variety of media in standard and user-defined formats. The data base will be preserved by operations such as backup, recovery, audit trails, archiving, and data histories. In addition, an index of water data from USGS and other agencies will be maintained.

Open-File Report↗
USGS1995

A computerized data base of nitrate concentrations in Indiana ground water

As part of a cooperative study with the Indiana Department of Environmental Management, the U.S. Geological Survey compiled a computerized data base of nitrate concentrations in Indiana ground water. The data included nitrate determinations from more than 29 studies by five Federal and State agencies during June 1973 through August 1991. The National Water Information System software of the U.S. Geological Survey was used to store the data at the U.S. Geological Survey office in Indianapolis, Indiana. Electronic data sets were converted to a standard format of well data, sample data, and analytical data. Data were screened by several error-checking procedures before they were retained in the data base; they were examined for potential duplicates of well location and name. The data base of nitrate concentrations in Indiana ground water contains records of 5,525 samples collected from 4,448 wells in 88 of 92 counties during 1973-91. Those wells included 3,832 drinking-water wells; 536 monitoring wells, 38 livestock-supply wells; and 42 irrigation wells. Nitrate concentrations greater than minimum reporting limits of 0.0 to 0.5 milligrams per liter (mg/L) were determined in 2,453 samples (44 percent of the total). Nitrate in ground water at concentrations greater than 3 mg/L have been considered to be the result of human activities. Nitrate concentrations ranged from 0.005 to 380 mg/L with a median nitrate concentration of 0.3 mg/L. Nitrate concentrations were greater than or equal to 3 mg/L in 704 samples (13 percent of the total). Nitrate concentrations were greater than or equal to the U.S. Environmental Protection Agency Maximum Contaminant Level of 10 mg/L in 188 samples (3.4 percent of the total). Of the 3,832 drinking- water wells in the data base, 147 had at least one sample in which a nitrate concentration was greater than the Maximum Contaminant Level. The percentage of samples with nitrate concentrations greater than or equal to 3 mg/L and greater than or equal to 10 mg/L generally increased during the period 1973 through 1991. The nitrate data base was compiled from numerous data sets that were readily accessible in electronic format. The uses of these data may be limited because they were neither comprehensive nor of a single statistical design. Nonetheless, the nitrate data can be used in several ways: (1) to identify geographic areas with and without nitrate data; (2) to evaluate assumptions, models, and maps of ground-water-contamination potential; and (3) to investigate the relation between environmental factors, land-use types, and the occurrence of nitrate.

Indiana↗
USGS2018

Implementation of MOVE.1, censored MOVE.1, and piecewise MOVE.1 low-flow regressions with applications at partial-record streamgaging stations in New Jersey

The U.S. Geological Survey (USGS) uses Maintenance of Variance Extension Type 1 (MOVE.1) regression to transfer streamflows measured at long-term continuous-record streamgaging stations to partial-record (PR) streamgaging stations where intermittent base-flow measurements are available. MOVE.1 regression is used widely throughout the hydrologic community to extend historic low flows and low-flow statistics at continuous-record streamgaging stations to streamgaging stations that have access to only a partial record of low flows. The method correlates base-flow measurements at PR streamgaging stations with daily mean streamflows measured at index stations that exhibit similar streamflow characteristics. Following changes in the computing platform for storing, processing, retrieving, and publishing National Water Information System (NWIS) hydrologic data, legacy Statistical Analysis System (SAS) code developed by the USGS to implement the MOVE.1 regression was no longer suitable for reading and processing NWIS streamflow data. To migrate the MOVE.1 program so that it could continue to read streamflow data using the new hydrologic data platform, the SAS code was re-written in R, an open source programming language and software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The work described in this report was performed in a study conducted by USGS in cooperation with the New Jersey Department of Environmental Protection. During migration from SAS to R, graphical and tabular output generated by the R script was compared to output produced by the legacy SAS code to ensure that equations used to perform the MOVE.1 regression remained the same. An option to perform censored MOVE.1 regression was added to extend the MOVE.1 methodology to cases where one or more measured continuous-record or PR streamgaging station flows are zero valued. In addition to permitting censored regression, the new R script includes an option to perform piecewise MOVE.1 regression when the relation between PR station and index station low flows varies significantly across the range of index station streamflows. Together with traditional MOVE.1 regression, censored, and piecewise MOVE.1 regression methods implemented by the R script offer less biased estimates than ordinary least squares regression for the annual 7-day 10-year and other low-flow statistics at PR stations for a range of base-flow conditions. The R script is used to implement the MOVE.1 regression methods across a variety of computing platforms.

New Jersey↗
USGS2025

Assessing nonpoint-source uranium pollution in an irrigated stream-aquifer system

Uranium (U) in rocks and soils of arid and semi-arid environments can be mobilized by irrigation and fertilization, posing environmental and health risks. Elevated U, along with selenium (Se) and nitrate (NO 3 ) co-constituents, necessitates careful monitoring and management. We developed a distributed-parameter numerical model to assess U pollution in an irrigated stream-aquifer system, applying it to a 552 km 2 region in Colorado's Lower Arkansas River Valley (LARV) over 14 years. A MODFLOW model, describing groundwater and stream flow, was coupled with an RT3D-OTIS model to portray reactive U transport. Calibration using the PESTPP-iES iterative ensemble smoother (iES) software indicated good agreement with observed U concentrations. The model revealed substantial and variable U levels across the LARV, highlighting potential hotspots and possible contributing factors, such as geological composition of the bedrock and near-surface shale and aquifer sediments derived from them, irrigation practices, and riparian landscape. U levels exceed the chronic standard (85th percentile = 30 μg/L, set by the US Environmental Protection Agency), which is the permissible regulatory threshold, in groundwater across 44 % of the region and along the river by an average factor of 2.9. Simulated average U concentrations in the non-riparian aquifer and river are 124 μg/L and 60 μg/L, respectively, compared with 112 μg/L and 62 μg/L for measured values. The average 85th percentile U concentration is 222 μg/L in the aquifer and 82 μg/L in the river. Average simulated U mass loading to the river is 0.17 kg/day per km, compared to an estimated 0.23 kg/day per km. Findings provide a baseline for comparing future simulated outcomes of alternative best management practices (BMPs) for U pollution mitigation and offer a methodology applicable to other irrigated regions.

Colorado↗
USGS2014

User's manual for the upper Delaware River riverine environmental flow decision support system (REFDSS), Version 1.1.2

Between 2002 and 2006, the Fort Collins Science Center (FORT) at the U.S. Geological Survey (USGS) conducted field surveys, organized workshops, and performed analysis of habitat for trout and shad in the Upper Delaware River Basin. This work culminated in the development of decision support system software (the Delaware River DSS–DRDSS, Bovee and others, 2007) that works in conjunction with the Delaware River Basin Commission’s reservoir operations model, OASIS, to facilitate comparison of the habitat and water-delivery effects of alternative operating scenarios for the Basin. This original DRDSS application was developed in Microsoft Excel and is available to all interested parties through the FORT web site ( http://www.fort.usgs.gov/Products/Software/DRDSS/ ). Initial user feedback on the original Excel-based DSS highlighted the need for a more user-friendly and powerful interface to effectively deliver the complex data and analyses encapsulated in the DSS. In order to meet this need, the USGS FORT and Northern Appalachian Research Branch (NARB) developed an entirely new graphical user interface (GUI) application. Support for this research was through the DOI WaterSmart program ( http://www.doi.gov/watersmart/html/index.php ) of which the USGS component is the National Water Census ( http://water.usgs.gov/watercensus/WaterSMART.html ). The content and methodology of the new GUI interface emulates those of the original DSS with a few exceptions listed below. Refer to Bovee and others (2007) for the original information. Significant alterations to the original DSS include: • We moved from Excel-based data storage and processing to a more powerful database back end powered by SQLite. The most notable effect of this is that the previous maximum temporal extent of 10 years has been replaced by a dynamic extent that can now cover the entire period of record for which we have data (1928–2000). • We incorporated interactive geographic information system (GIS) visualization and dynamic data processing. Previous habitat maps were generated outside of the DSS in an ad hoc process that the end user could not update or investigate. • The original bathymetric data collected in 2005 at the three main stem reaches was augmented with a higher resolution dataset collected in 2010. This new dataset was collected in order to conduct higher resolution (finer pixel size) two-dimensional (2D) hydrodynamic modeling for evaluating dwarf wedgemussel (DWM, Alasmidonta heterodon ) habitat. • Results charts are now substantially more interactive, dynamic, and accessible, which allows users to more easily focus on their particular topics of interest as well as drill down to the source data used to calculate given results.

Open-File Report↗
USGS2021

A hidden Markov model for estimating age-specific survival when age and size are uncertain

Estimates of age-specific survival probabilities are needed for age-structured population models and to inform conservation decisions. However, determining the age of individuals in wildlife populations is often problematic. We present a hidden Markov model for estimating age-specific survival from capture–recapture or capture–recapture–recovery data when age is unknown and indicators of age, such as size and growth layer counts, are imprecise. The model is evaluated through simulations, and its implementation is illustrated with maximum likelihood and Bayesian approaches in commonly used software. The model is then applied to genetic capture–recapture data of Florida manatees to estimate age- and time-variant survival probabilities. The approach is broadly applicable to studies aiming to quantify age-specific effects of environmental change and management actions on population dynamics, including studies that rely on minimally invasive methods such as genetic and photo identification.

Ecology↗
USGS2016

Developing integrated methods to address complex resource and environmental issues

Introduction This circular provides an overview of selected activities that were conducted within the U.S. Geological Survey (USGS) Integrated Methods Development Project, an interdisciplinary project designed to develop new tools and conduct innovative research requiring integration of geologic, geophysical, geochemical, and remote-sensing expertise. The project was supported by the USGS Mineral Resources Program, and its products and acquired capabilities have broad applications to missions throughout the USGS and beyond. In addressing challenges associated with understanding the location, quantity, and quality of mineral resources, and in investigating the potential environmental consequences of resource development, a number of field and laboratory capabilities and interpretative methodologies evolved from the project that have applications to traditional resource studies as well as to studies related to ecosystem health, human health, disaster and hazard assessment, and planetary science. New or improved tools and research findings developed within the project have been applied to other projects and activities. Specifically, geophysical equipment and techniques have been applied to a variety of traditional and nontraditional mineral- and energy-resource studies, military applications, environmental investigations, and applied research activities that involve climate change, mapping techniques, and monitoring capabilities. Diverse applied geochemistry activities provide a process-level understanding of the mobility, chemical speciation, and bioavailability of elements, particularly metals and metalloids, in a variety of environmental settings. Imaging spectroscopy capabilities maintained and developed within the project have been applied to traditional resource studies as well as to studies related to ecosystem health, human health, disaster assessment, and planetary science. Brief descriptions of capabilities and laboratory facilities and summaries of some applications of project products and research findings are included in this circular. The work helped support the USGS mission to “provide reliable scientific information to describe and understand the Earth; minimize loss of life and property from natural disasters; manage water, biological, energy, and mineral resources; and enhance and protect our quality of life.” Activities within the project include the following: Spanned scales from microscopic to planetary; Demonstrated broad applications across disciplines; Included life-cycle studies of mineral resources; Incorporated specialized areas of expertise in applied geochemistry including mineralogy, hydrogeology, analytical chemistry, aqueous geochemistry, biogeochemistry, microbiology, aquatic toxicology, and public health; and Incorporated specialized areas of expertise in geophysics including magnetics, gravity, radiometrics, electromagnetics, seismic, ground-penetrating radar, borehole radar, and imaging spectroscopy. This circular consists of eight sections that contain summaries of various activities under the project. The eight sections are listed below: Laboratory Facilities and Capabilities, which includes brief descriptions of the various types of laboratories and capabilities used for the project; Method and Software Development, which includes summaries of remote-sensing, geophysical, and mineralogical methods developed or enhanced by the project; Instrument Development, which includes descriptions of geophysical instruments developed under the project; Minerals, Energy, and Climate, which includes summaries of research that applies to mineral or energy resources, environmental processes and monitoring, and carbon sequestration by earth materials; Element Cycling, Toxicity, and Health, which includes summaries of several process-oriented geochemical and biogeochemical studies and health-related research activities; Hydrogeology and Water Quality, which includes descriptions of innovative geophysical, remote-sensing, and geochemical research pertaining to hydrogeology and water-quality applications; Hazards and Disaster Assessment, which includes summaries of research and method development that were applied to natural hazards, human-caused hazards, and disaster assessments; and Databases and Framework Studies, which includes descriptions of fundamental applications of geophysical studies and of the importance of archived data.

Circular↗
USGS2021

Improved Automated Identification and Mapping of Iron Sulfate Minerals, Other Mineral Groups, and Vegetation using Landsat 8 Operational Land Imager Data, San Juan Mountains, Colorado, and Four Corners Region

Multispectral remote sensing data acquired by the Landsat 8 Operational Land Imager (OLI) sensor were analyzed using a new, automated technique to generate a map of exposed mineral and vegetation groups in the western San Juan Mountains, Colo., and the Four Corners Region of the United States. Band ratio results were combined into displayed mineral and vegetation groups using Boolean algebra. New analysis logic has been implemented to exploit the coastal aerosol band in Landsat 8 OLI data and identify concentrations of iron sulfate minerals. These may indicate the presence of near-surface pyrite, which can be a potential nonpoint source of acid rock drainage. Zoned occurrences of iron sulfate minerals in areas surrounding and down gradient of known sources of pyrite have been mapped using this technique. They show high correlation with occurrences of jarosite-bearing mineral assemblages, as mapped using airborne imaging spectrometer data and supporting field verification surveys. Mapping the occurrence of iron sulfate minerals produced by the weathering and oxidation of pyrite in exposed hydrothermally altered rocks can also provide an important indicator of the genetic environment of alteration and the associated mineral deposit type. The automated analysis methodology is being employed to rapidly and cost-effectively generate maps of large regions of the United States in support of U.S. Geological Survey mineral resource and mineral-environmental assessments. This map, which includes the ERDAS IMAGINE thematic raster format in the data release, has been attributed by pixel value with mineral and vegetation group classification data, which can be queried in most image processing and GIS software packages.

Colorado, Utah↗
USGS2016

Groundwater contaminant plume maps and volumes, 100-K and 100-N Areas, Hanford Site, Washington

This study provides an independent estimate of the areal and volumetric extent of groundwater contaminant plumes which are affected by waste disposal in the 100-K and 100-N Areas (study area) along the Columbia River Corridor of the Hanford Site. The Hanford Natural Resource Trustee Council requested that the U.S. Geological Survey perform this interpolation to assess the accuracy of delineations previously conducted by the U.S. Department of Energy and its contractors, in order to assure that the Natural Resource Damage Assessment could rely on these analyses. This study is based on previously existing chemical (or radionuclide) sampling and analysis data downloaded from publicly available Hanford Site Internet sources, geostatistically selected and interpreted as representative of current (from 2009 through part of 2012) but average conditions for groundwater contamination in the study area. The study is limited in scope to five contaminants—hexavalent chromium, tritium, nitrate, strontium-90, and carbon-14, all detected at concentrations greater than regulatory limits in the past. All recent analytical concentrations (or activities) for each contaminant, adjusted for radioactive decay, non-detections, and co-located wells, were converted to log-normal distributions and these transformed values were averaged for each well location. The log-normally linearized well averages were spatially interpolated on a 50 × 50-meter (m) grid extending across the combined 100-N and 100-K Areas study area but limited to avoid unrepresentative extrapolation, using the minimum curvature geostatistical interpolation method provided by SURFER ® data analysis software. Plume extents were interpreted by interpolating the log-normally transformed data, again using SURFER ® , along lines of equal contaminant concentration at an appropriate established regulatory concentration . Total areas for each plume were calculated as an indicator of relative environmental damage. These plume extents are shown graphically and in tabular form for comparison to previous estimates. Plume data also were interpolated to a finer grid (10 × 10 m) for some processing, particularly to estimate volumes of contaminated groundwater. However, hydrogeologic transport modeling was not considered for the interpolation. The compilation of plume extents for each contaminant also allowed estimates of overlap of the plumes or areas with more than one contaminant above regulatory standards. A mapping of saturated aquifer thickness also was derived across the 100-K and 100–N study area, based on the vertical difference between the groundwater level (water table) at the top and the altitude of the top of the Ringold Upper Mud geologic unit, considered the bottom of the uppermost unconfined aquifer. Saturated thickness was calculated for each cell in the finer (10 × 10 m) grid. The summation of the cells’ saturated thickness values within each polygon of plume regulatory exceedance provided an estimate of the total volume of contaminated aquifer, and the results also were checked using a SURFER ® volumetric integration procedure. The total volume of contaminated groundwater in each plume was derived by multiplying the aquifer saturated thickness volume by a locally representative value of porosity (0.3). Estimates of the uncertainty of the plume delineation also are presented. “Upper limit” plume delineations were calculated for each contaminant using the same procedure as the “average” plume extent except with values at each well that are set at a 95-percent upper confidence limit around the log-normally transformed mean concentrations, based on the standard error for the distribution of the mean value in that well; “lower limit” plumes are calculated at a 5-percent confidence limit around the geometric mean. These upper- and lower-limit estimates are considered unrealistic because the statistics were increased or decreased at each well simultaneously and were not adjusted for correlation among the well distributions (i.e., it is not realistic that all wells would be high simultaneously). Sources of the variability in the distributions used in the upper- and lower-extent maps include time varying concentrations and analytical errors. The plume delineations developed in this study are similar to the previous plume descriptions developed by U.S. Department of Energy and its contractors. The differences are primarily due to data selection and interpolation methodology. The differences in delineated plumes are not sufficient to result in the Hanford Natural Resource Trustee Council adjusting its understandings of contaminant impact or remediation.

Washington↗
USGS2011

Compilation of watershed models for tributaries to the Great Lakes, United States, as of 2010, and identification of watersheds for future modeling for the Great Lakes Restoration Initiative

As part of the Great Lakes Restoration Initiative (GLRI) during 2009–10, the U.S. Geological Survey (USGS) compiled a list of existing watershed models that had been created for tributaries within the United States that drain to the Great Lakes. Established Federal programs that are overseen by the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Army Corps of Engineers (USACE) are responsible for most of the existing watershed models for specific tributaries. The NOAA Great Lakes Environmental Research Laboratory (GLERL) uses the Large Basin Runoff Model to provide data for the management of water levels in the Great Lakes by estimating United States and Canadian inflows to the Great Lakes from 121 large watersheds. GLERL also simulates streamflows in 34 U.S. watersheds by a grid-based model, the Distributed Large Basin Runoff Model. The NOAA National Weather Service uses the Sacramento Soil Moisture Accounting model to predict flows at river forecast sites. The USACE created or funded the creation of models for at least 30 tributaries to the Great Lakes to better understand sediment erosion, transport, and aggradation processes that affect Federal navigation channels and harbors. Many of the USACE hydrologic models have been coupled with hydrodynamic and sediment-transport models that simulate the processes in the stream and harbor near the mouth of the modeled tributary. Some models either have been applied or have the capability of being applied across the entire Great Lakes Basin; they are (1) the SPAtially Referenced Regressions On Watershed attributes (SPARROW) model, which was developed by the USGS; (2) the High Impact Targeting (HIT) and Digital Watershed models, which were developed by the Institute of Water Research at Michigan State University; (3) the Long-Term Hydrologic Impact Assessment (L–THIA) model, which was developed by researchers at Purdue University; and (4) the Water Erosion Prediction Project (WEPP) model, which was developed by the National Soil Erosion Research Laboratory of the U.S. Department of Agriculture. During 2010, the USGS used the Precipitation-Runoff Modeling System (PRMS) to create a hydrologic model for the Lake Michigan Basin to assess the probable effects of climate change on future groundwater and surface-water resources. The Water Availability Tool for Environmental Resources (WATER) model and the Analysis of Flows In Networks of CHannels (AFINCH) program also were used to support USGS GLRI projects that required estimates of streamflows throughout the Great Lakes Basin. This information on existing watershed models, along with an assessment of geologic, soils, and land-use data across the Great Lakes Basin and the identification of problems that exist in selected tributary watersheds that could be addressed by a watershed model, was used to identify three watersheds in the Great Lakes Basin for future modeling by the USGS. These watersheds are the Kalamazoo River Basin in Michigan, the Tonawanda Creek Basin in New York, and the Bad River Basin in Wisconsin. These candidate watersheds have hydrogeologic, land-type, and soil characteristics that make them distinct from each other, but that are representative of other tributary watersheds within the Great Lakes Basin. These similarities in the characteristics among nearby watersheds will enhance the usefulness of a model by improving the likelihood that parameter values from a previously modeled watershed could reliably be used in the creation of a model of another watershed in the same region. The software program Hydrological Simulation Program–Fortran (HSPF) was selected to simulate the hydrologic, sedimentary, and water-quality processes in these selected watersheds. HSPF is a versatile, process-based, continuous-simulation model that has been used extensively by the scientific community, has the ongoing technical support of the U.S. Environmental Protection Agency and USGS, and provides a means to evaluate the effects that land-use changes or management practices might have on the simulated processes.

Great Lakes Basin↗
USGS2006

Spectral reflectance properties (0.4-2.5 um) of secondary Fe-oxide, Fe-hydroxide, and Fe-sulfate-hydrate minerals associated with sulfide-bearing mine waste

Fifteen Fe-oxide, Fe-hydroxide, and Fe-sulphate-hydrate mineral species commonly associated with sulphide bearing mine wastes were characterized by using X-ray powder diffraction and scanning electron microscope methods. Diffuse reflectance spectra of the samples show diagnostic absorption features related to electronic processes involving ferric and/or ferrous iron, and to vibrational processes involving water and hydroxyl ions. Such spectral features enable field and remote sensing based studies of the mineral distributions. Because secondary minerals are sensitive indicators of pH, Eh, relative humidity, and other environmental conditions, spectral mapping of these minerals promises to have important applications to mine waste remediation studies. This report releases digital (ascii) spectra (spectral_data_files.zip) of the fifteen mineral samples to facilitate usage of the data with spectral libraries and spectral analysis software. The spectral data are provided in a two-column format listing wavelength (in micrometers) and reflectance, respectively.

Open-File Report↗
USGS2008

Hierarchical modeling of bycatch rates of sea turtles in the western North Atlantic

Previous studies indicate that the locations of the endangered loggerhead Caretta caretta and critically endangered leatherback Dermochelys coriacea sea turtles are influenced by water temperatures, and that incidental catch rates in the pelagic longline fishery vary by region. We present a Bayesian hierarchical model to examine the effects of environmental variables, including water temperature, on the number of sea turtles captured in the US pelagic longline fishery in the western North Atlantic. The modeling structure is highly flexible, utilizes a Bayesian model selection technique, and is fully implemented in the software program WinBUGS. The number of sea turtles captured is modeled as a zero-inflated Poisson distribution and the model incorporates fixed effects to examine region-specific differences in the parameter estimates. Results indicate that water temperature, region, bottom depth, and target species are all significant predictors of the number of loggerhead sea turtles captured. For leatherback sea turtles, the model with only target species had the most posterior model weight, though a re-parameterization of the model indicates that temperature influences the zero-inflation parameter. The relationship between the number of sea turtles captured and the variables of interest all varied by region. This suggests that management decisions aimed at reducing sea turtle bycatch may be more effective if they are spatially explicit. ?? Inter-Research 2008.

Endangered Species Research↗
USGS2012

Approaches in highly parameterized inversion - PEST++, a Parameter ESTimation code optimized for large environmental models

An object-oriented parameter estimation code was developed to incorporate benefits of object-oriented programming techniques for solving large parameter estimation modeling problems. The code is written in C++ and is a formulation and expansion of the algorithms included in PEST, a widely used parameter estimation code written in Fortran. The new code is called PEST++ and is designed to lower the barriers of entry for users and developers while providing efficient algorithms that can accommodate large, highly parameterized problems. This effort has focused on (1) implementing the most popular features of PEST in a fashion that is easy for novice or experienced modelers to use and (2) creating a software design that is easy to extend; that is, this effort provides a documented object-oriented framework designed from the ground up to be modular and extensible. In addition, all PEST++ source code and its associated libraries, as well as the general run manager source code, have been integrated in the Microsoft Visual Studio® 2010 integrated development environment. The PEST++ code is designed to provide a foundation for an open-source development environment capable of producing robust and efficient parameter estimation tools for the environmental modeling community into the future.

Techniques and Methods↗
USGS2016

Delineation of areas contributing groundwater to selected receiving surface water bodies for long-term average hydrologic conditions from 1968 to 1983 for Long Island, New York

To assist resource managers and planners in developing informed strategies to address nitrogen loading to coastal water bodies of Long Island, New York, the U.S. Geological Survey and the New York State Department of Environmental Conservation initiated a program to delineate a comprehensive dataset of groundwater recharge areas (or areas contributing groundwater), travel times, and outflows to streams and saline embayments on Long Island. A four-layer regional three-dimensional finite-difference groundwater-flow model of hydrologic conditions from 1968 to 1983 was used to provide delineations of 48 groundwater watersheds on Long Island. Sixteen particle starting points were evenly spaced within each of the 4,000- by 4,000-foot model cells that receive water-table recharge and tracked using forward particle-tracking analysis modeling software to outflow zones. For each particle, simulated travel times were grouped by age as follows: less than or equal to 10 years, greater than 10 years and less than or equal to 100 years, greater than 100 years and less than or equal to 1,000 years, and greater than 1,000 years; and simulated ending zones were grouped into 48 receiving water bodies, based on the New York State Department of Environmental Conservation Waterbody Inventory/Priority Waterbodies List. Areal delineation of travel time zones and groundwater contributing areas were generated and a table was prepared presenting the sum of groundwater outflow for each area.

New York↗
USGS2000

Using an analytical geometry method to improve tiltmeter data presentation

The tiltmeter is a useful tool for geologic and geotechnical applications. To obtain full benefit from the tiltmeter, easy and accurate data presentations should be used. Unfortunately, the most commonly used method for tilt data reduction now may yield inaccurate and low-resolution results. This article describes a simple, accurate, and high-resolution approach developed at the Illinois State Geological Survey for data reduction and presentation. The orientation of tiltplates is determined first by using a trigonometric relationship, followed by a matrix transformation, to obtain the true amount of rotation change of the tiltplate at any given time. The mathematical derivations used for the determination and transformation are then coded into an integrated PC application by adapting the capabilities of commercial spreadsheet, database, and graphics software. Examples of data presentation from tiltmeter applications in studies of landfill covers, characterizations of mine subsidence, and investigations of slope stability are also discussed.

Environmental & Engineering Geoscience↗
USGS1994

Land use and land cover digital data

Computer tapes derived from land use and land cover (LULC) data and associated maps at scales of 1 :250,000 and 1: 100,000 are available from the U.S. Geological Survey. This data can be used alone or combined with a base map or other supplemental data for a variety of applications, using commercially available software. You can produce area summary statistics, select specific portions of a map to study or display single classifications, such as bodies of water. LULC and associated digital data offer convenient, accurate, flexible, and cost-effective access to users who are involved in environmental studies, land use planning, land management, or resource planning.

Fact Sheet↗
USGS2010

Genetic landscapes GIS Toolbox: Tools to map patterns of genetic divergence and diversity.

The Landscape Genetics GIS Toolbox contains tools that run in the Geographic Information System software, ArcGIS ® , to map genetic landscapes and to summarize multiple genetic landscapes as average and variance surfaces. These tools can be used to visualize the distribution of genetic diversity across geographic space and to study associations between patterns of genetic diversity and geographic features or other geo‐referenced environmental data sets. Together, these tools create genetic landscape surfaces directly from tables containing genetic distance or diversity data and sample location coordinates, greatly reducing the complexity of building and analyzing these raster surfaces in a Geographic Information System.

Molecular Ecology Resources↗
USGS2001

All equal-area map projections are created equal, but some are more equal than others

High-resolution regional and global raster databases are currently being generated for a variety of environmental and scientific modeling applications. The projection of these data from geographic coordinates to a plane coordinate system is subject to significant areal error. Sources of error include users selecting an inappropriate projection or incorrect parameters for a given projection, algorithmic errors in commercial geographic information system (GIS) software, and errors resulting from the projection of data in the raster format. To assess the latter type of errors, the accuracy of raster projection was analyzed by two methods. First, a set of 12 one-degree by one-degree quadrilaterals placed at various latitudes was projected at several raster resolutions and compared to the projection of a vector representation of the same quadrilaterals. Second, several different raster resolutions of land cover data for Asia were projected and the total areas of 21 land cover categories were tabulated and compared. While equal-area projections are designed to specifically preserve area, the comparison of the results of the one-degree by one-degree quadrilaterals with the common equal area projections (e.g., the Mollweide) indicates a considerable variance in the one-degree area after projection. Similarly, the empirical comparison of land cover areas for Asia among various projections shows that total areas of land cover vary with projection type, raster resolution, and latitude. No single projection is best for all resolutions and all latitudes. While any of the equal-area projections tested are reasonably accurate for most applications with resolutions of eight-kilometer pixels or smaller, significant variances in accuracies appear at larger pixel sizes.

Cartography and Geographic Information Science↗