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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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At least 73 records · Page 4Linked to original sources
USGS2011

A trans-dimensional Bayesian Markov chain Monte Carlo algorithm for model assessment using frequency-domain electromagnetic data

A meaningful interpretation of geophysical measurements requires an assessment of the space of models that are consistent with the data, rather than just a single, ‘best’ model which does not convey information about parameter uncertainty. For this purpose, a trans-dimensional Bayesian Markov chain Monte Carlo (MCMC) algorithm is developed for assessing frequencydomain electromagnetic (FDEM) data acquired from airborne or ground-based systems. By sampling the distribution of models that are consistent with measured data and any prior knowledge, valuable inferences can be made about parameter values such as the likely depth to an interface, the distribution of possible resistivity values as a function of depth and non-unique relationships between parameters. The trans-dimensional aspect of the algorithm allows the number of layers to be a free parameter that is controlled by the data, where models with fewer layers are inherently favoured, which provides a natural measure of parsimony and a significant degree of flexibility in parametrization. The MCMC algorithm is used with synthetic examples to illustrate how the distribution of acceptable models is affected by the choice of prior information, the system geometry and configuration and the uncertainty in the measured system elevation. An airborne FDEM data set that was acquired for the purpose of hydrogeological characterization is also studied. The results compare favorably with traditional least-squares analysis, borehole resistivity and lithology logs from the site, and also provide new information about parameter uncertainty necessary for model assessment.

Geophysical Journal International↗
USGS2015

Building a multi-scaled geospatial temporal ecology database from disparate data sources: Fostering open science through data reuse

Although there are considerable site-based data for individual or groups of ecosystems, these datasets are widely scattered, have different data formats and conventions, and often have limited accessibility. At the broader scale, national datasets exist for a large number of geospatial features of land, water, and air that are needed to fully understand variation among these ecosystems. However, such datasets originate from different sources and have different spatial and temporal resolutions. By taking an open-science perspective and by combining site-based ecosystem datasets and national geospatial datasets, science gains the ability to ask important research questions related to grand environmental challenges that operate at broad scales. Documentation of such complicated database integration efforts, through peer-reviewed papers, is recommended to foster reproducibility and future use of the integrated database. Here, we describe the major steps, challenges, and considerations in building an integrated database of lake ecosystems, called LAGOS (LAke multi-scaled GeOSpatial and temporal database), that was developed at the sub-continental study extent of 17 US states (1,800,000 km 2 ). LAGOS includes two modules: LAGOS GEO , with geospatial data on every lake with surface area larger than 4 ha in the study extent (~50,000 lakes), including climate, atmospheric deposition, land use/cover, hydrology, geology, and topography measured across a range of spatial and temporal extents; and LAGOS LIMNO , with lake water quality data compiled from ~100 individual datasets for a subset of lakes in the study extent (~10,000 lakes). Procedures for the integration of datasets included: creating a flexible database design; authoring and integrating metadata; documenting data provenance; quantifying spatial measures of geographic data; quality-controlling integrated and derived data; and extensively documenting the database. Our procedures make a large, complex, and integrated database reproducible and extensible, allowing users to ask new research questions with the existing database or through the addition of new data. The largest challenge of this task was the heterogeneity of the data, formats, and metadata. Many steps of data integration need manual input from experts in diverse fields, requiring close collaboration.

Connecticut, Delaware, Illinois, Indiana, Iowa, Ma↗
USGS2003

Data model and relational database design for the New Jersey Water-Transfer Data System (NJWaTr)

The New Jersey Water-Transfer Data System (NJWaTr) is a database design for the storage and retrieval of water-use data. NJWaTr can manage data encompassing many facets of water use, including (1) the tracking of various types of water-use activities (withdrawals, returns, transfers, distributions, consumptive-use, wastewater collection, and treatment); (2) the storage of descriptions, classifications and locations of places and organizations involved in water-use activities; (3) the storage of details about measured or estimated volumes of water associated with water-use activities; and (4) the storage of information about data sources and water resources associated with water use. In NJWaTr, each water transfer occurs unidirectionally between two site objects, and the sites and conveyances form a water network. The core entities in the NJWaTr model are site, conveyance, transfer/volume, location, and owner. Other important entities include water resource (used for withdrawals and returns), data source, permit, and alias. Multiple water-exchange estimates based on different methods or data sources can be stored for individual transfers. Storage of user-defined details is accommodated for several of the main entities. Many tables contain classification terms to facilitate the detailed description of data items and can be used for routine or custom data summarization. NJWaTr accommodates single-user and aggregate-user water-use data, can be used for large or small water-network projects, and is available as a stand-alone Microsoft? Access database. Data stored in the NJWaTr structure can be retrieved in user-defined combinations to serve visualization and analytical applications. Users can customize and extend the database, link it to other databases, or implement the design in other relational database applications.

Open-File Report↗
USGS2011

Description and testing of the Geo Data Portal: Data integration framework and Web processing services for environmental science collaboration

Interest in sharing interdisciplinary environmental modeling results and related data is increasing among scientists. The U.S. Geological Survey Geo Data Portal project enables data sharing by assembling open-standard Web services into an integrated data retrieval and analysis Web application design methodology that streamlines time-consuming and resource-intensive data management tasks. Data-serving Web services allow Web-based processing services to access Internet-available data sources. The Web processing services developed for the project create commonly needed derivatives of data in numerous formats. Coordinate reference system manipulation and spatial statistics calculation components implemented for the Web processing services were confirmed using ArcGIS 9.3.1, a geographic information science software package. Outcomes of the Geo Data Portal project support the rapid development of user interfaces for accessing and manipulating environmental data.

Open-File Report↗
USGS2017

Sharing our data—An overview of current (2016) USGS policies and practices for publishing data on ScienceBase and an example interactive mapping application

This report provides an overview of current (2016) U.S. Geological Survey policies and practices related to publishing data on ScienceBase, and an example interactive mapping application to display those data. ScienceBase is an integrated data sharing platform managed by the U.S. Geological Survey. This report describes resources that U.S. Geological Survey Scientists can use for writing data management plans, formatting data, and creating metadata, as well as for data and metadata review, uploading data and metadata to ScienceBase, and sharing metadata through the U.S. Geological Survey Science Data Catalog. Because data publishing policies and practices are evolving, scientists should consult the resources cited in this paper for definitive policy information. An example is provided where, using the content of a published ScienceBase data release that is associated with an interpretive product, a simple user interface is constructed to demonstrate how the open source capabilities of the R programming language and environment can interact with the properties and objects of the ScienceBase item and be used to generate interactive maps.

Open-File Report↗
USGS1983

Instructions for the submission of data to the Master Water Data Index

Instructions are given for the computerized processing of data prepared for entry into the Master Water Data Index of the U.S. Geological Survey 's National Water Data Exchange (NAWDEX), as discussed in the manual entitled ' Instructions for the Preparation of Data for the Master Water Data Index. ' Two processing procedures are provided: The edit of data and the submission of data for storage in the Master Water Data Index. These instructions are applicable to both new data being submitted for storage and to update transactions for data previously processed and stored. (USGS)

Open-File Report↗
USGS1985

Quantity and quality of storm runoff in the Irondequoit Creek basin near Rochester, New York; Part 1. Data-collection network and methods, quality-assurance program, and description of available data

A 14-month data collection program of quantity and quality of storm precipitation and runoff was conducted in the Irondequoit Creek basin, a 438-sq km area along the south shore of Lake Ontario in north-central New York, from July 1980 through August 1981. The data from a basis for study of nutrient inflow to Irondequoit Bay. This report describes the methods used to collect and verify the data and includes some representative examples of the data base. Stream discharge and water quality data were collected at 17 sites representing rural and urban land uses. Precipitation data were collected at five continuous-record gages and 11 daily total gages. Evaporation data were collected at one site; chemical quality of precipitation and dustfall data were collected at four sites. Tables list watershed characteristics, precipitation data (including chemical quality of atmospheric deposition, monthly precipitation, and evaporation), and annual loadings of eight selected nutrients and heavy metals from the five major subbasins and three discrete land-use site. Examples of computer printouts of streamflow, precipitation, and water quality data available from the Geological Survey 's WATSTORE computer system are included. (USGS)

New York↗
USGS1990

Water-quality data-collection activities in Colorado and Ohio; Phase III, evaluation of existing data for use in assessing regional water-quality conditions and trends

During the past several years, a growing number of questions have been raised by members of Congress and others about the status of current waterquality conditions in the Nation, trends in water quality, and the major factors that affect water-quality conditions and trends. One area of particular interest and concern has been the suitability of existing water-quality data for addressing these types of questions at regional and national scales. In response to these questions and concerns, the U.S. Geological Survey began a pilot study in Colorado and Ohio to (1) determine the characteristics of current water-quality data-collection activities of Federal, State, regional, and local agencies and universities; and (2) determine how well the data from these activities, collected for various purposes and using different procedures, can be used to improve our ability to address the aforementioned questions. Colorado and Ohio were chosen for the pilot study because they represent regions with different types of water-quality issues and programs. The results of the study are specific to the two States and are not intended to be extrapolated to other States. The study was divided into three phases whose objectives were: Phase I Identify and inventory 1984 water-quality data-collection programs, including costs, in Colorado and Ohio, and identify those programs that meet a set of broad criteria for producing data that potentially are appropriate for water-quality assessments of regional and national scope. Phase II Evaluate the quality assurance of field and laboratory procedures used to produce the data from programs that met the broad criteria of Phase I. Phase III Compile the qualifying data from Phase II and evaluate the extent to which the resulting data base can be used to address selected water-quality questions for the two States. This report presents the results of Phase III, focusing on (1) the number of measurements made at each data-collection site for selected constituents, (2) the areal distribution of those sites that have sufficient data for selected types of analyses, and (3) the availability of key ancillary information such as streamflow to address broad-scope questions such as: What are existing water-quality conditions? Has the water quality changed? and How do existing water-quality conditions and changes in these conditions relate to natural factors and human-induced activities?

Colorado, Ohio↗
USGS2011

Metadata for data rescue and data at risk

Scientific data age, become stale, fall into disuse and run tremendous risks of being forgotten and lost. These problems can be addressed by archiving and managing scientific data over time, and establishing practices that facilitate data discovery and reuse. Metadata documentation is integral to this work and essential for measuring and assessing high priority data preservation cases. The International Council for Science: Committee on Data for Science and Technology (CODATA) has a newly appointed Data-at-Risk Task Group (DARTG), participating in the general arena of rescuing data. The DARTG primary objective is building an inventory of scientific data that are at risk of being lost forever. As part of this effort, the DARTG is testing an approach for documenting endangered datasets. The DARTG is developing a minimal and easy to use set of metadata properties for sufficiently describing endangered data, which will aid global data rescue missions. The DARTG metadata framework supports rapid capture, and easy documentation, across an array of scientific domains. This paper reports on the goals and principles supporting the DARTG metadata schema, and provides a description of the preliminary implementation.

Conference Paper↗
USGS1993

Availability of Earth observations data from the U.S. Geological Survey's EROS data center

For decades federal and state agencies have been collecting regional, continental, and global Earth observations data acquired by satellites, aircraft, and other information-gathering systems. These data include photographic and digital remotely sensed images of the Earth's surface, as well as earth science, cartographic, and geographic data. Since 1973, the U.S. Geological Survey's Earth Resources Observation Systems (EROS) Data Center (EDC) in Sioux Falls, South Dakota, has been a data management, production, dissemination, and research center for these data. Currently, the Data Center holds over 10 million satellite images and aerial photographs, in photographic and digital formats. Users are able to place inquiries and orders for these holdings via a nationwide computer network. In addition to cataloging the data stored in its archives, the Data Center provides users with rapid access to information on many data collections held by other facilities.

Pecora 12 Symposium↗
USGS2006

Balancing data sharing requirements for analyses with data sensitivity

Data sensitivity can pose a formidable barrier to data sharing. Knowledge of species current distributions from data sharing is critical for the creation of watch lists and an early warning/rapid response system and for model generation for the spread of invasive species. We have created an on-line system to synthesize disparate datasets of non-native species locations that includes a mechanism to account for data sensitivity. Data contributors are able to mark their data as sensitive. This data is then 'fuzzed' in mapping applications and downloaded files to quarter-quadrangle grid cells, but the actual locations are available for analyses. We propose that this system overcomes the hurdles to data sharing posed by sensitive data. ?? 2006 Springer Science+Business Media B.V.

Biological Invasions↗
USGS2026

The Sedimentary Geochemistry and Paleoenvironments Project Phase 2 data release: An open data resource for the study of Earth's environmental history

Geochemical data from sedimentary rocks are the primary source of information regarding Earth's surface evolution through time, including its air and water envelopes and interactions with life and deep Earth processes. The Sedimentary Geochemistry and Paleoenvironments Project (SGP) is a scientific consortium centered around open data and community-driven development of cyberinfrastructure tools and resources for sedimentary geochemistry and Earth history. Here we describe the SGP Phase 2 data release, which focused on incorporating Paleoproterozoic and Mesoproterozoic (2500–1000 million years ago) data and better accommodating carbonate data. This data release was built through the involvement of >200 researchers worldwide in academia, government, and industry, and provides the largest available public data resource for our user community in the academic fields of geochemistry, sedimentology, tectonics, paleontology, Earth history, and paleoclimate, as well as the petroleum and minerals industries. The dataset now encompasses 126,006 samples and 4,132,371 geochemical analyses. In addition to direct entry by SGP Team Members, we have ingested and incorporated datasets from the Geoscience Australia OZCHEM database, the Alberta Geological Survey, and the Deep-Time Marine Sedimentary Element Database (DM-SED) compilation. This paper details sampling in the Phase 2 dataset with respect to age, geography, lithology, and other geological characteristics, documents access via our search website and API, discusses possible issues and/or biases in the dataset that could impact analyses, describes plans for governance and stewardship of data from Indigenous lands, and serves as the citable reference paper for the data release.

Chemical Geology↗
USGS2012

Landsat Data Continuity Mission (LDCM) space to ground mission data architecture

The Landsat Data Continuity Mission (LDCM) is a scientific endeavor to extend the longest continuous multi-spectral imaging record of Earth's land surface. The observatory consists of a spacecraft bus integrated with two imaging instruments; the Operational Land Imager (OLI), built by Ball Aerospace & Technologies Corporation in Boulder, Colorado, and the Thermal Infrared Sensor (TIRS), an in-house instrument built at the Goddard Space Flight Center (GSFC). Both instruments are integrated aboard a fine-pointing, fully redundant, spacecraft bus built by Orbital Sciences Corporation, Gilbert, Arizona. The mission is scheduled for launch in January 2013. This paper will describe the innovative end-to-end approach for efficiently managing high volumes of simultaneous realtime and playback of image and ancillary data from the instruments to the reception at the United States Geological Survey's (USGS) Landsat Ground Network (LGN) and International Cooperator (IC) ground stations. The core enabling capability lies within the spacecraft Command and Data Handling (C&DH) system and Radio Frequency (RF) communications system implementation. Each of these systems uniquely contribute to the efficient processing of high speed image data (up to 265Mbps) from each instrument, and provide virtually error free data delivery to the ground. Onboard methods include a combination of lossless data compression, Consultative Committee for Space Data Systems (CCSDS) data formatting, a file-based/managed Solid State Recorder (SSR), and Low Density Parity Check (LDPC) forward error correction. The 440 Mbps wideband X-Band downlink uses Class 1 CCSDS File Delivery Protocol (CFDP), and an earth coverage antenna to deliver an average of 400 scenes per day to a combination of LGN and IC ground stations. This paper will also describe the integrated capabilities and processes at the LGN ground stations for data reception using adaptive filtering, and the mission operations approach fro- the LDCM Mission Operations Center (MOC) to perform the CFDP accounting, file retransmissions, and management of the autonomous features of the SSR.

Conference Paper↗
USGS2012

Description of the U.S. Geological Survey Geo Data Portal data integration framework

The U.S. Geological Survey has developed an open-standard data integration framework for working efficiently and effectively with large collections of climate and other geoscience data. A web interface accesses catalog datasets to find data services. Data resources can then be rendered for mapping and dataset metadata are derived directly from these web services. Algorithm configuration and information needed to retrieve data for processing are passed to a server where all large-volume data access and manipulation takes place. The data integration strategy described here was implemented by leveraging existing free and open source software. Details of the software used are omitted; rather, emphasis is placed on how open-standard web services and data encodings can be used in an architecture that integrates common geographic and atmospheric data.

IEEE Journal of Selected Topics in Applied Earth O↗
USGS2015

Evaluation of the Global Land Data Assimilation System (GLDAS) air temperature data products

There is a high demand for agrohydrologic models to use gridded near-surface air temperature data as the model input for estimating regional and global water budgets and cycles. The Global Land Data Assimilation System (GLDAS) developed by combining simulation models with observations provides a long-term gridded meteorological dataset at the global scale. However, the GLDAS air temperature products have not been comprehensively evaluated, although the accuracy of the products was assessed in limited areas. In this study, the daily 0.25° resolution GLDAS air temperature data are compared with two reference datasets: 1) 1-km-resolution gridded Daymet data (2002 and 2010) for the conterminous United States and 2) global meteorological observations (2000–11) archived from the Global Historical Climatology Network (GHCN). The comparison of the GLDAS datasets with the GHCN datasets, including 13 511 weather stations, indicates a fairly high accuracy of the GLDAS data for daily temperature. The quality of the GLDAS air temperature data, however, is not always consistent in different regions of the world; for example, some areas in Africa and South America show relatively low accuracy. Spatial and temporal analyses reveal a high agreement between GLDAS and Daymet daily air temperature datasets, although spatial details in high mountainous areas are not sufficiently estimated by the GLDAS data. The evaluation of the GLDAS data demonstrates that the air temperature estimates are generally accurate, but caution should be taken when the data are used in mountainous areas or places with sparse weather stations.

Journal of Hydrometeorology↗
USGS2001

Data model and relational database design for the New England Water-Use Data System (NEWUDS)

The New England Water-Use Data System (NEWUDS) is a database for the storage and retrieval of water-use data. NEWUDS can handle data covering many facets of water use, including (1) tracking various types of water-use activities (withdrawals, returns, transfers, distributions, consumptive-use, wastewater collection, and treatment); (2) the description, classification and location of places and organizations involved in water-use activities; (3) details about measured or estimated volumes of water associated with water-use activities; and (4) information about data sources and water resources associated with water use. In NEWUDS, each water transaction occurs unidirectionally between two site objects, and the sites and conveyances form a water network. The core entities in the NEWUDS model are site, conveyance, transaction/rate, location, and owner. Other important entities include water resources (used for withdrawals and returns), data sources, and aliases. Multiple water-exchange estimates can be stored for individual transactions based on different methods or data sources. Storage of user-defined details is accommodated for several of the main entities. Numerous tables containing classification terms facilitate detailed descriptions of data items and can be used for routine or custom data summarization. NEWUDS handles single-user and aggregate-user water-use data, can be used for large or small water-network projects, and is available as a stand-alone Microsoft? Access database structure. Users can customize and extend the database, link it to other databases, or implement the design in other relational database applications.

Open-File Report↗