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

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USGS1978

Definitions of components of the Water Data Sources Directory maintained by the National Water Data Exchange

This report contains a definition and description of each component of the Water Data Souces Directory data base maintained by the National Water Data Exchange (NAWDEX). It is intended, primarily, to assist those persons using the Water Data Sources Directory in understanding information obtained from the data base. The Water Data Sources Directory is a computerized data base maintained and operated using the System 2000 data base management system. It contains information about organizations that collect, store, and disseminate water data. (Woodard-USGS)

Open-File Report↗
USGS1982

Definitions of components of the Water Data Sources Directory maintained by the National Water Data Exchange

This report contains a definition and description of each component of the Water Data Sources Directory data base maintained by the National Water Data Exchange (NAWDEX). It is intended, primarily, to assist those persons using the Water Data Sources Directory in understanding information obtained from the data base. The Water Data Sources Directory is a computerized data base maintained and operated using the System 2000 data base management system. It contains information about organizations that collect, store, and disseminate water data. (USGS)

Open-File Report↗
USGS1990

National water information system user's manual; Volume 2, Chapter 5, Water-Use Data System; Part 1, Site-Specific Water-Use Data System (SSWUDS)

The Water-Use Data System (WUDS) is a water-use data storage and retrieval system. The WUDS is part of the National Water Information System (NWIS), which was developed by the U.S. Geological Survey (USGS). The National Water Information System is a distributed national data base in which data can be processed over a network of minicomputers at USGS offices throughout the United States. This system comprises the Automated Data Processing System, the Ground-Water Site Inventory System, the Water-Quality System, and the WUDS. This manual reflects the status of WUDS for the 90.2 version of NWIS, and contains user information and discussion on the general operating procedures for the programs found within the WUDS menus. The WUDS comprises two subsystems, the Site- Specific Water-Use Data System (SSWUDS) and the Aggregate Water- Use Data System (AWUDS). This manual documents SSWUDS and covers the following major topics: Overall SSWUDS Concepts SSWUDS Menu Structures SSWUDS Data Entry Program SSWUDS Data Dictionary

Open-File Report↗
USGS1998

Computer Programs to Display and Modify Data in Geographic Coordinates and Methods to Transfer Positions to and from Maps, with Applications to Gravity Data Processing, Global Positioning Systems, and 30-Meter Digital Elevation Models

Computer programs were written in the Fortran language to process and display gravity data with locations expressed in geographic coordinates. The programs and associated processes have been tested for gravity data in an area of about 125,000 square kilometers in northwest Nevada, southeast Oregon, and northeast California. This report discusses the geographic aspects of data processing. Utilization of the programs begins with application of a template (printed in PostScript format) to transfer locations obtained with Global Positioning Systems to and from field maps and includes a 5-digit geographic-based map naming convention for field maps. Computer programs, with source codes that can be copied, are used to display data values (printed in PostScript format) and data coverage, insert data into files, extract data from files, shift locations, test for redundancy, and organize data by map quadrangles. It is suggested that 30-meter Digital Elevation Models needed for gravity terrain corrections and other applications should be accessed in a file search by using the USGS 7.5-minute map name as a file name, for example, file '40117_B8.DEM' contains elevation data for the map with a southeast corner at lat 40? 07' 30' N. and lon 117? 52' 30' W.

Open-File Report↗
USGS2012

Evaluation of volatile organic compound (VOC) blank data and application of study reporting levels to groundwater data collected for the California GAMA Priority Basin Project, May 2004 through September 2010

Volatile organic compounds (VOCs) were analyzed in quality-control samples collected for the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project. From May 2004 through September 2010, a total of 2,026 groundwater samples, 211 field blanks, and 109 source-solution blanks were collected and analyzed for concentrations of 85 VOCs. Results from analyses of these field and source-solution blanks and of 2,411 laboratory instrument blanks during the same time period were used to assess the quality of data for the 2,026 groundwater samples. Eighteen VOCs were detected in field blanks or source-solution blanks: acetone, benzene, bromodichloromethane, 2-butanone, carbon disulfide, chloroform, 1,1-dichloroethene, dichloromethane, ethylbenzene, tetrachloroethene, styrene, tetrahydrofuran, toluene, trichloroethene, trichlorofluoromethane, 1,2,4-trimethylbenzene, m - and p -xylenes, and o -xylene. The objective of the evaluation of the VOC-blank data was to determine if study reporting levels (SRLs) were needed for any of the VOCs detected in blanks to ensure the quality of the data from groundwater samples. An SRL is equivalent to a raised reporting level that is used in place of the reporting level used by the analyzing laboratory [long‑term method detection level (LT-MDL) or laboratory reporting level (LRL)] to reduce the probability of reporting false-positive detections. Evaluation of VOC-blank data was done in three stages: (1) identification of a set of representative quality‑control field blanks (QCFBs) to be used for calculation of SRLs and identification of VOCs amenable to the SRL approach, (2) evaluation of potential sources of contamination to blanks and groundwater samples by VOCs detected in field blanks, and (3) selection of appropriate SRLs from among four potential SRLs for VOCs detected in field blanks and application of those SRLs to the groundwater data. An important conclusion from this study is that to ensure the quality of the data from groundwater samples, it was necessary to apply different methods of determining SRLs from field blank data to different VOCs, rather than use the same method for all VOCs. Four potential SRL values were defined by using three approaches: two values were defined by using a binomial probability method based on one-sided, nonparametric upper confidence limits, one was defined as equal to the maximum concentration detected in the field blanks, and one was defined as equal to the maximum laboratory method detection level used during the period when samples were collected for the project. The differences in detection frequencies and concentrations among different types of blanks (laboratory instrument blanks, source-solution blanks, and field blanks collected with three different sampling equipment configurations) and groundwater samples were used to infer the sources and mechanisms of contamination for each VOC detection in field blanks. Other chemical data for the groundwater samples (oxidation-reduction state, co-occurrence of VOCs, groundwater age) and ancillary information about the well sites (land use, presence of known sources of contamination) were used to evaluate whether the patterns of detections of VOCs in groundwater samples before and after application of potential SRLs were plausible. On this basis, the appropriate SRL was selected for each VOC that was determined to require an SRL. The SRLs for ethylbenzene [0.06 microgram per liter (μg/L)], m - and p -xylenes (0.33 μg/L), o -xylene (0.12 μg/L), toluene (0.69 μg/L), and 1,2,4-trimethylbenzene (0.56 μg/L) corresponded to the highest concentrations detected in the QCFBs and were selected because they resulted in the most censoring of groundwater data. Comparisons of hydrocarbon ratios in groundwater samples and blanks and comparisons between detection frequencies of the five hydrocarbons in groundwater samples and different types of blanks suggested three dominant sources of contamination that affected groundwater samples and blanks: (1) ethylbenzene, m - and p -xylenes, o -xylene, and toluene from fuel or exhaust components sorbed onto sampling lines, (2) toluene from vials and the source blank water, and (3) 1,2,4-trimethylbenzene from materials used for collection of samples for radon-222 analysis.

California↗
USGS1993

Accessibility of geotechnical earthquake Engineering data and the need for data storage and dissemination standards

Ease of data access and data standards are two issues critical to the success of GIS technology when applied to earthquake hazards research problems that require geotechnical engineering and related data. Efforts to reduce data accession costs and to streamline the data exchange process will result in short-term cost and time saving and will add long-term value to the data sets themselves. Such efforts might include centralized data centers, standardized data base designs and formats, cooperative efforts to fill data gaps, and standardized distribution methods and media.

Conference Paper↗
USGS2026

Logical data model for hydrographic data based on HY_Features concepts

This report describes background and design of the “hydrofabric data model” which defines logic for implementation of data schemas and software that deals with hydrologic geospatial data. As a “logical” data model, the hydrofabric data model specifies details necessary to support compatibility of data and software that satisfy diverse needs without unnecessarily restricting implementation details. The logic presented in this report is based on concepts defined in WaterML2 Part 3 Surface Hydrology Features Concepts and is designed to serve the needs of a range of hydroscience use cases. Development of international community standards applicable to hydrofabrics began, prompted by the World Meteorological Organization Commission for Hydrology, in 2012 [5] . More than 10 years later, this report documents one aspect of a long-term research and development activity that traces its roots back that far. This report describes terminology, use cases, and background as context preceding presentation of the logical model and discussion of its design. Three appendices document related data models, an example encoding of the hydrofabric data model, and an artificial schematic and tabular data example. The sections of the report can be accessed in the Clause 5 section.

OCG Public Engineering Report↗
USGS2018

Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2015, and previously unpublished data from 2013 to 2014

Groundwater-quality data were collected from 502 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water-Quality Program and are included in this report. Most of the wells (500) were sampled from January through December 2015, and 2 of them were sampled in 2013. The data were collected from five types of well networks: principal aquifer study networks, which are used to assess the quality of groundwater used for public water supply; land-use study networks, which are used to assess land-use effects on shallow groundwater quality; major aquifer study networks, which are used to assess the quality of groundwater used for domestic supply; enhanced trends networks, which are used to evaluate the time scales during which groundwater quality changes; and vertical flow-path study networks, which are used to evaluate changes in groundwater quality from shallow to deeper depths. Groundwater samples were analyzed for a large number of water-quality indicators and constituents, including major ions, nutrients, trace elements, volatile organic compounds, pesticides, radionuclides, and some constituents of special interest (arsenic speciation, chromium [VI], and perchlorate). These groundwater-quality data, along with data from quality-control samples, are tabulated in this report and in an associated data release. Some data from environmental samples collected in 2013 and quality-control samples collected in 2014 also are included in the associated data release; these data are associated with networks described in this report and have not been published previously.

Data Series↗
USGS2024

State of the data: Assessing the FAIRness of USGS data

In response to recent shifts towards open science that emphasize transparency, reproducibility, and access to research data, the US Geological Survey (USGS) conducted a study to assess the degree to which USGS data assets meet the FAIR data principles (Findable, Accessible, Interoperable, and Reusable). The USGS designed and applied a methodology for quantitative analysis of FAIR characteristics. A new rubric was derived from a crosswalk of existing FAIR evaluation frameworks and customized for the USGS. The rubric, consisting of 62 yes/no questions, was applied to 392 metadata records of USGS data products published between 1987 and 2022. Results were analyzed to show which FAIR characteristics were most and least present in the metadata and how these scores changed after the implementation of data policy requirements in 2016. Aggregated scores showed specific areas of strength and needed improvements. The greatest increases in FAIR scores over time were for elements that were required by new data policies, especially in the ‘Findable’ category. Based on the results, this paper presents strategies to further improve USGS alignment with FAIR. The suggested strategies are organized in four key areas: USGS data repository characteristics, training and communities of practice, data management policy considerations, and metadata standards, tools, and best practices.

Data Science Journal↗
USGS2019

Modern pollen-assemblages data from small lakes paired with local forest-composition data in northeastern United States

For the past century, pollen analysis has served as a primary tool for inferring past changes in vegetation composition and structure (Birks et al. 2016, Edwards et al. 2017). Pollen-based inferences are supported by empirical studies comparing modern pollen assemblages with modern vegetation composition. In one approach, pollen abundances (usually percentages) for individual taxa are compared directly with quantitative estimates of abundance in surrounding vegetation (Jackson 1994, Davis 2000). This approach has been applied most frequently using spatially extensive but coarse-scale forest inventory data (Webb et al. 1981, Bradshaw and Webb 1985, Prentice & Webb 1986, Prentice et al. 1987, Paciorek & McLachlan 2009, Dawson et al. 2016, Kujawa et al. 2016). In these studies, forest composition cannot usually be estimated accurately within a 1- to 10 km radius of the individual sites owing to limited spatial density of forest inventory data. A few studies have compared vegetation composition within 50-100 m of pollen-sampling sites, but in these cases the pollen is from forest-floor assemblages (Bradshaw 1981, Jackson & Wong 1994, Jackson & Kearsley 1998) or from small forest hollows (Calcote 1995, 1998, Parshall & Calcote 2001). Largely lacking are pollen assemblage data from lake sediments paired with local forest composition, measured within 100 to 1000 m of the lake margins (Jackson 1990). This absence represents a substantial gap in ability to understand and model pollen-vegetation relationships, because lakes are the primary source of fossil-pollen sequences worldwide, and because the leptokurtic nature of pollen dispersal ensures that local vegetation has an important effect on pollen composition in sediments (Jackson 1994, Sugita 1994, 2007a, 2007b, Jackson & Lyford 1999). Here, I present a data set pairing modern pollen assemblages from 33 small lakes in the forested northeastern United States (Fig. 1) with forest composition data measured within 20, 50, 100, 500, and 1000 metres of the lake margins. This data set incorporates most of the sites used in Jackson (1990), adding 16 new sites and delivering the vegetation data by species in absolute units (i.e., total basal area), which allows various weightings and transformations to be applied. The data set should be of value to paleoecologists and forest ecologists in understanding, modeling, and validating the pollen-vegetation relationships that are at the heart of paleoecological inference.

Northeastern United States↗
USGS2011

Topographic mapping data semantics through data conversion and enhancement

This paper presents research on the semantics of topographic data for triples and ontologies to blend the capabilities of the Semantic Web and The National Map of the U.S. Geological Survey. Automated conversion of relational topographic data of several geographic sample areas to the triple data model standard resulted in relatively poor semantic associations. Further research employed vocabularies of feature type and spatial relation terms. A user interface was designed to model the capture of non-standard terms relevant to public users and to map those terms to existing data models of The National Map through the use of ontology. Server access for the study area triple stores was made publicly available, illustrating how the development of linked data may transform institutional policies to open government data resources to the public. This paper presents these data conversion and research techniques that were tested as open linked data concepts leveraged through a user-centered interface and open USGS server access to the public.

Book chapter↗
USGS1983

The Eastern Gas Shales Project (EGSP) Data System: A case study in data base design, development, and application

The U.S. Geological Survey and Petroleum Information Corporation in Denver, Colorado, developed the Eastern Gas Shale Project (EGSP)Data System for the U.S. Department of Energy, Morgantown, West Virginia. Geological, geochemical, geophysical, and engineering data from Devonian shale samples from more than 5800 wells and outcrops in the Appalachian basin were edited and converted to a Petroleum Information Corporation data base. Well and sample data may be retrieved from this data system to produce (1)production-test summaries by formation and well location; (2)contoured isopach, structure, and trendsurface maps of Devonian shale units; (3)sample summary reports for samples by location, well, contractor, and sample number; (4)cross sections displaying digitized log traces, geochemical, and lithologic data by depth for wells; and (5)frequency distributions and bivariate plots. Although part of the EGSP Data System is proprietary, and distribution of complete well histories is prohibited by contract, maps and aggregated well-data listings are being made available to the public through published reports. ?? 1983 Plenum Publishing Corporation.

Journal of the International Association for Mathe↗
USGS2022

MTH5: An archive and exchangeable data format for magnetotelluric time series data

Magnetotellurics (MT) is a passive electromagnetic geophysical method that measures variations in subsurface electrical resistivity. MT data are collected in the time domain and processed in the frequency domain to produce estimates of a transfer function representing the Earth’s electrical structure. Unfortunately, the MT community lacks metadata and data standards for time series data. As the community grows and findability, accessibility, interoperability, and reuse of digital assets (FAIR) data principles are enforced by government and funding agencies, a standard is needed for time series data. Presented here is a hierarchical data format (MTH5) that is logically formatted to how MT data are collected. Open-source Python packages are also described to read, write, and manipulate MTH5 files. These include a package to deal with metadata ( mt_metadata ) based on standards developed by the Working Group for Magnetotelluric Data Handling and Software assembled by the Incorporated Research Institutions for Seismology (IRIS), and mth5 : a package to interact with MTH5 files that uses mt_metadata . Example code and workflows are presented.

Computers & Geosciences↗
USGS1997

The International Geosphere Biosphere Programme Data and Information System global land cover data set (DISCover)

The International Geosphere Biosphere Programme Data and Information System (IGBP-DIS), through the mapping expertise of the U.S. Geological Survey and the European Commission's Joint Research Centre, recently guided the completion of a 1-km resolution global land cover data set from advanced very high resolution radiometer (AVHRR) data. The 1-km resolution land cover product, “DISCover,” was based on monthly normalized difference vegetation index composites from 1992 and 1993. The development of DISCover was coordinated by the IGBP-DIS Land Cover Working Group as part of the IGBP-DIS Focus 1 activity. DISCover is a 17-class land cover data set based on the scientific requirements of IGBP elements. The mapping used unsupervised classification and postclassification refinement using ancillary data. The development of this data set was motivated by the need for global land cover data with higher spatial resolution, unproved temporal specificity, and known classification accuracy. The completed DISCover data set will soon be validated to determine the accuracy of the global classification.

Acta Astronautica↗
USGS2010

The IGBP-DIS global 1 km land cover data set, DISCover: First results

The International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS) is co-ordinating the development of global land data sets from Advanced Very High Resolution Radiometer (AVHRR) data. The first is a 1 km spatial resolution land cover product 'DISCover', based on monthly Normalized Difference Vegetation Index composites from 1992 and 1993. DISCover is a 17 class land cover dataset based on the science requirements of IGBP elements. Mapping uses unsupervised classification with post-classification refinement using ancillary data. Draft Africa, North America and South America products are now available for peer review.

International Journal of Remote Sensing↗
USGS2024

Automated deep learning-based point cloud classification on USGS 3DEP lidar data using transformer

The goal of the U.S. Geological Survey’s (USGS) 3D Elevation Program (3DEP) is to facilitate the acquisition of nationwide lidar data. Although data meet USGS lidar specifications, some point cloud tiles include noisy and incorrectly classified points. The enhanced accuracy of classified point clouds can improve support for many downstream applications such as hydrologic analysis, urban planning, and forest management. Despite noisy and incorrectly classified points, the current 3DEP classification specifications result in data that can be useful for Digital Terrain Model (DTM) extraction; however, the quality of the classification application can be improved to match state-of-the-art capabilities. Deep Learning (DL)-based approaches have been developed with outstanding performance for point cloud classification. This study will utilize the proven DL technologies to prepare for developing a user-friendly open-source toolkit that would automate classification to refine and enrich the results of existing and future 3DEP data.

Conference Paper↗
USGS2016

An analysis of water data systems to inform the Open Water Data Initiative

Improving access to data and fostering open exchange of water information is foundational to solving water resources issues. In this vein, the Department of the Interior's Assistant Secretary for Water and Science put forward the charge to undertake an Open Water Data Initiative (OWDI) that would prioritize and accelerate work toward better water data infrastructure. The goal of the OWDI is to build out the Open Water Web (OWW). We therefore considered the OWW in terms of four conceptual functions: water data cataloging, water data as a service, enriching water data, and community for water data. To describe the current state of the OWW and identify areas needing improvement, we conducted an analysis of existing systems using a standard model for describing distributed systems and their business requirements. Our analysis considered three OWDI-focused use cases—flooding, drought, and contaminant transport—and then examined the landscape of other existing applications that support the Open Water Web. The analysis, which includes a discussion of observed successful practices of cataloging, serving, enriching, and building community around water resources data, demonstrates that we have made significant progress toward the needed infrastructure, although challenges remain. The further development of the OWW can be greatly informed by the interpretation and findings of our analysis.

Journal of the American Water Resources Associatio↗
USGS2004

Geophysical data reveal the crustal structure of the Alaska range orogen within the aftershock zone of the Mw 7.9 Denali fault earthquake

Geophysical information, including deep-crustal seismic reflection, magnetotelluric ( mt ), gravity, and magnetic data, cross the aftershock zone of the 3 November 2002 M w 7.9 Denali fault earthquake. These data and aftershock seismicity, jointly interpreted, reveal the crustal structure of the right-lateral-slip Denali fault and the eastern Alaska Range orogen, as well as the relationship between this structure and seismicity. North of the Denali fault, strong seismic reflections from within the Alaska Range orogen show features that dip as steeply as 25° north and extend downward to depths between 20 and 25 km. These reflections reveal crustal structures, probably ductile shear zones, that most likely formed during the Late Cretaceous, but these structures appear to be inactive, having produced little seismicity during the past 20 years. Furthermore, seismic reflections mainly dip north, whereas alignments in aftershock hypocenters dip south. The Denali fault is nonreflective, but modeling of mt , gravity, and magnetic data suggests that the Denali fault dips steeply to vertically. However, in an alternative structural model, the Denali fault is defined by one of the reflection bands that dips to the north and flattens into the middle crust of the Alaska Range orogen. Modeling of mt data indicates a rock body, having low electrical resistivity (>10 Ω·m), that lies mainly at depths greater than 10 km, directly beneath aftershocks of the Denali fault earthquake. The maximum depth of aftershocks along the Denali fault is 10 km. This shallow depth may arise from a higher-than-normal geothermal gradient. Alternatively, the low electrical resistivity of deep rocks along the Denali fault may be associated with fluids that have weakened the lower crust and helped determine the depth extent of the aftershock zone.

Alaska↗