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At least 613 records · Page 34Linked to original sources
USGS2006

Water resources data, Puerto Rico and the U.S. Virgin Islands, water year 2004

The Caribbean Water Science Center of the U.S. Geological Survey (USGS), in cooperation with local and Federal agencies obtains a large amount of data pertaining to the water resources of the Commonwealth of Puerto Rico and the Territory of the U.S. Virgin Islands each water year. These data, accumulated during many water years, constitute a valuable data base for developing an improved understanding of the water resources of the area. To make these data readily available to interested parties outside the U.S. Geological Survey, the data are published annually in this report series entitled 'Water Resources Data for Puerto Rico and the U.S. Virgin Islands.' This report includes records on both surface and ground water. Specifically, it contains: (1) discharge records for 89 streamflow-gaging stations, daily sediment records for 13 sediment stations, stage records for 18 reservoirs, and (2) water-quality records for 20 streamflow-gaging stations, and for 38 ungaged stream sites, 13 lake sites, 2 lagoons, and 1 bay, and (3) water-level records for 72 observation wells. Water-resources data for Puerto Rico for calendar years 1958-67 were released in a series of reports entitled 'Water Records of Puerto Rico.' Water-resources data for the U.S. Virgin Islands for the calendar years 1962-69 were released in a report entitled 'Water Records of U.S. Virgin Islands.' Included were records of streamflow, ground-water levels, and water-quality data for both surface and ground water. Beginning with the 1968 calendar year, surface-water records for Puerto Rico were released separately on an annual basis. Ground-water level records and water-quality data for surface and ground water were released in companion reports covering periods of several years. Data for the 1973-74 reports were published under separate covers. Water-resources data reports for 1975 to 2003 water years consist of one volume each and contain data for streamflow, water quality, and ground water.

Water Data Report↗
USGS2020

An open source database for the synthesis of soil radiocarbon data: ISRaD version 1.0

Radiocarbon is a critical constraint on our estimates of the timescales of soil carbon cycling that can aid in identifying mechanisms of carbon stabilization and destabilization and improve the forecast of soil carbon response to management or environmental change. Despite the wealth of soil radiocarbon data that have been reported over the past 75 years, the ability to apply these data to global-scale questions is limited by our capacity to synthesize and compare measurements generated using a variety of methods. Here, we present the International Soil Radiocarbon Database (ISRaD; http://soilradiocarbon.org , last access: 16 December 2019), an open-source archive of soil data that include reported measurements from bulk soils, distinct soil carbon pools isolated in the laboratory by a variety of soil fractionation methods, samples of soil gas or water collected interstitially from within an intact soil profile, CO 2 gas isolated from laboratory soil incubations, and fluxes collected in situ from a soil profile. The core of ISRaD is a relational database structured around individual datasets (entries) and organized hierarchically to report soil radiocarbon data, measured at different physical and temporal scales as well as other soil or environmental properties that may also be measured and may assist with interpretation and context. Anyone may contribute their own data to the database by entering it into the ISRaD template and subjecting it to quality assurance protocols. ISRaD can be accessed through (1) a web-based interface, (2) an R package (ISRaD), or (3) direct access to code and data through the GitHub repository, which hosts both code and data. The design of ISRaD allows for participants to become directly involved in the management, design, and application of ISRaD data. The synthesized dataset is available in two forms: the original data as reported by the authors of the datasets and an enhanced dataset that includes ancillary geospatial data calculated within the ISRaD framework. ISRaD also provides data management tools in the ISRaD-R package that provide a starting point for data analysis; as an open-source project, the broader soil community is invited and encouraged to add data, tools, and ideas for improvement. As a whole, ISRaD provides resources to aid our evaluation of soil dynamics across a range of spatial and temporal scales. The ISRaD v1.0 dataset is archived and freely available at https://doi.org/10.5281/zenodo.2613911 (Lawrence et al., 2019).

Earth System Science Data↗
USGS2016

A strategy for recovering continuous behavioral telemetry data from Pacific walruses

Tracking animal behavior and movement with telemetry sensors can offer substantial insights required for conservation. Yet, the value of data collected by animal-borne telemetry systems is limited by bandwidth constraints. To understand the response of Pacific walruses ( Odobenus rosmarus divergens ) to rapid changes in sea ice availability, we required continuous geospatial chronologies of foraging behavior. Satellite telemetry offered the only practical means to systematically collect such data; however, data transmission constraints of satellite data-collection systems limited the data volume that could be acquired. Although algorithms exist for reducing sensor data volumes for efficient transmission, none could meet our requirements. Consequently, we developed an algorithm for classifying hourly foraging behavior status aboard a tag with limited processing power. We found a 98% correspondence of our algorithm's classification with a test classification based on time–depth data recovered and characterized through multivariate analysis in a separate study. We then applied our algorithm within a telemetry system that relied on remotely deployed satellite tags. Data collected by these tags from Pacific walruses across their range during 2007–2015 demonstrated the consistency of foraging behavior collected by this strategy with data collected by data logging tags; and demonstrated the ability to collect geospatial behavioral chronologies with minimal missing data where recovery of data logging tags is precluded. Our strategy for developing a telemetry system may be applicable to any study requiring intelligent algorithms to continuously monitor behavior, and then compress those data into meaningful information that can be efficiently transmitted.

Wildlife Society Bulletin↗
USGS2024

From field station to forecast: Managing data at the Alaska Volcano Observatory

The Alaska Volcano Observatory (AVO) uses multidisciplinary data to monitor and study dozens of active and potentially active volcanoes. Here, we provide an overview of internally and externally generated data types, tools and resources used in their management, and challenges faced. Data sources include the following: (1) a multiparameter (seismic, infrasound, GNSS, web cameras) ground-based monitoring network that spans 3000 km and transmits data in real time; (2) a variety of satellite-borne sensors that provide information about surface change and volcanic emissions; (3) geologic and gas field campaigns; and (4) other external data products that provide situation awareness. Each data type requires distinct acquisition, processing, storage, visualization, and archiving approaches. AVO uses a variety of externally and internally developed tools to handle individual data types as well as multidisciplinary volcanological data. A primary tool is the Geologic Database of Information on Volcanoes in Alaska (GeoDIVA), which stores detailed, searchable information on more than 140 volcanoes and over 1000 eruptions and unrest events, including images, eruption descriptions, and geologic station and sample data, metadata, and analyses. It interacts with other internal tools that store monitoring reports and other operational records. Additional data management resources used by AVO assist with alarms and alerts, state-of-health monitoring, and multiparameter visualization. Requirements for 24/7 accessibility, the ever-expanding portfolio of data, and transitioning new tools from development to operations are all challenges faced by AVO and other volcano observatories. AVO strives to meet FAIR data practices and ensure that data are available to national and international community efforts using external repositories as well as those hosted by AVO and its parent institutions.

Alaska↗
USGS2021

Synthesizing and analyzing long-term monitoring data: A greater sage-grouse case study

Long-term monitoring of natural resources is imperative for increasing the understanding of ecosystem processes, services, and how to manage those ecosystems to maintain or improve function. Challenges with using these data may occur because methods of monitoring changed over time, multiple organizations collect and manage data differently, and monetary resources fluctuate, affecting many aspects of data. Because many species respond to changes in habitat conditions and predator-prey relationships across different spatial scales that span management boundaries, greater efforts for collaborating are essential. We demonstrate the challenges and methods for standardizing greater sage-grouse ( Centrocercus urophasianus ) long-term monitoring data across the species range in the western United States to inform population modeling needs identified by the Western Association of Fish and Wildlife Agencies. We used automated and repeatable methods of standardizing data via custom open-source software ( grsg_lekdb ) to improve the scientific integrity of future sage-grouse population assessments within and among states. Data standardization included reconciling uses of different terminology and expunging unusable data, resulting in the removal of 26% of data records due to database insertion errors and modifications to >1 million values to correct formatting and typing errors. Our approaches maximized the inclusion of usable data and identified data that could inform detection probabilities, population trends, and monitoring guidelines. Using sage-grouse databases as an example, we identified the importance of data management and how quality assurance and quality control measures can improve the usefulness of these data for future research needs. Our methods of using informatics and concluding recommendations can support similar endeavors of flora and fauna monitoring programs, whether those efforts are to use existing data or support new monitoring programs.

Ecological Informatics↗
USGS1987

Design of a spatial data structure using the relational normal forms

In previous work, a relational data structure aimed at the exchange of spatial data between systems was developed. As this data structure was relational it was of first normal form, but compliance with the higher normal forms was not investigated. Recently, a new procedural method for composing fully normalized data structures from the basic data fields has been developed by H. C. Smith, as an alternative to the process of non-loss decomposition which is difficult to understand. Smith's method has been applied to data fields required to store points, lines and polygons in a chain-node spatial data model. When geographic domain, coverage layer and map are also considered, the procedure naturally leads to a catalogue model, needed for the exchange of spatial data. Although the method produces a fully normalized data structure, it is not as easy to identify which normal forms are responsible for the ultimate arrangement of the data fields into relations, but the benefits of these criteria for data base development also apply to spatial data structures and related ancillary data.

International Journal of Geographical Information ↗
USGS2015

Interactive access to LP DAAC satellite data archives through a combination of open-source and custom middleware web services

Current methods of searching for and retrieving data from satellite land remote sensing archives do not allow for interactive information extraction. Instead, Earth science data users are required to download files over low-bandwidth networks to local workstations and process data before science questions can be addressed. New methods of extracting information from data archives need to become more interactive to meet user demands for deriving increasingly complex information from rapidly expanding archives. Moving the tools required for processing data to computer systems of data providers, and away from systems of the data consumer, can improve turnaround times for data processing workflows. The implementation of middleware services was used to provide interactive access to archive data. The goal of this middleware services development is to enable Earth science data users to access remote sensing archives for immediate answers to science questions instead of links to large volumes of data to download and process. Exposing data and metadata to web-based services enables machine-driven queries and data interaction. Also, product quality information can be integrated to enable additional filtering and sub-setting. Only the reduced content required to complete an analysis is then transferred to the user.

IEEE Geoscience and Remote Sensing Letters↗
USGS2000

Acoustic Doppler Current Profiler Data Processing System manual [ADCP]

This open-file report describes the data processing software currently in use by the U.S. Geological Survey (USGS), Woods Hole Coastal and Marine Science Center (WHCMSC), to process time series of acoustic Doppler current data obtained by Teledyne RD Instruments Workhorse model ADCPs. The Sediment Transport Instrumentation Group (STG) at the WHCMSC has a long-standing commitment to providing scientists high quality oceanographic data published in a timely manner. To meet this commitment, STG has created this software to aid personnel in processing and reviewing data as well as evaluating hardware for signs of instrument malfunction. The output data format for the data is network Common Data Form (netCDF), which meets USGS publication standards. Typically, ADCP data are recorded in beam coordinates. This conforms to the USGS philosophy to post-process rather than internally process data. By preserving the original data quality indicators as well as the initial data set, data can be evaluated and reprocessed for different types of analyses. Beam coordinate data are desirable for internal and surface wave experiments, for example. All the code in this software package is intended to run using the MATLAB program available from The Mathworks, Inc. As such, it is platform independent and can be adapted by the USGS and others for specialized experiments with non-standard requirements. The software is continuously being updated and revised as improvements are required. The most recent revision may be downloaded from: http://woodshole.er.usgs.gov/operations/stg/Pubs/ADCPtools/adcp_index.htm The USGS makes this software available at the user?s discretion and responsibility.

Open-File Report↗
USGS2001

Hydrogeologic data for the Big River–Mishnock River stream-aquifer system, central Rhode Island

Hydrogeology, ground-water development alternatives, and water quality in the BigMishnock stream-aquifer system in central Rhode Island are being investigated as part of a long-term cooperative program between the Rhode Island Water Resources Board and the U.S. Geological Survey to evaluate the ground-water resources throughout Rhode Island. The study area includes the Big River drainage basin and that portion of the Mishnock River drainage basin upstream from the Mishnock River at State Route 3. This report presents geologic data and hydrologic and water-quality data for ground and surface water. Ground-water data were collected from July 1996 through September 1998 from a network of observation wells consisting of existing wells and wells installed for this study, which provided a broad distribution of data-collection sites throughout the study area. Streambed piezometers were used to obtain differences in head data between surface-water levels and ground-water levels to help evaluate stream-aquifer interactions throughout the study area. The types of data presented include monthly ground-water levels, average daily ground-water withdrawals, drawdown data from aquifer tests, and water-quality data. Historical water-level data from other wells within the study area also are presented in this report. Surface-water data were obtained from a network consisting of surface-water impoundments, such as ponds and reservoirs, existing and newly established partial-record stream-discharge sites, and synoptic surface-water-quality sites. Water levels were collected monthly from the surface-water impoundments. Stream-discharge measurements were made at partial-record sites to provide measurements of inflow, outflow, and internal flow throughout the study area. Specific conductance was measured monthly at partial-record sites during the study, and also during the fall and spring of 1997 and 1998 at 41 synoptic sites throughout the study area. General geologic data, such as estimates of depth to bedrock and depth to water table, as well as indications of underlying geologic structure, were obtained from geophysical surveys. Site-specific geologic data were collected during the drilling of observation wells and test holes. These data include depth to bedrock or refusal, depth to water table, and lithologic information.

Rhode Island↗
USGS2001

Quality-assurance data for routine water quality analyses by the U. S. Geological Survey laboratory in Troy, New York; July 1993 through June 1995

A laboratory for analysis of low-ionic strength water has been developed at the U.S. Geological Survey (USGS) office in Troy, N.Y., to analyze samples collected by USGS projects in the Northeast. The laboratory's quality-assurance program is based on internal and interlaboratory quality-assurance samples and quality-control procedures developed to ensure proper sample collection, processing, and analysis. The quality-assurance/quality-control data are stored in the laboratory's SAS data-management system, which provides efficient review, compilation, and plotting of quality-assurance/quality-control data. This report presents and discusses samples analyzed from July 1993 through June 1995. Quality-control results for 18 analytical procedures were evaluated for bias and precision. Control charts show that data from seven of the analytical procedures were biased throughout the analysis period for either high-concentration or low-concentration samples but were within control limits; these procedures were: acid-neutralizing capacity, dissolved inorganic carbon, dissolved organic carbon (soil expulsions), chloride, magnesium, nitrate (colorimetric method), and pH. Three of the analytical procedures were occasionally biased but were within control limits; they were: calcium (high for high-concentration samples for May 1995), dissolved organic carbon (high for highconcentration samples from January through September 1994), and fluoride (high in samples for April and June 1994). No quality-control sample has been developed for the organic monomeric aluminum procedure. Results from the filter-blank and analytical-blank analyses indicate that all analytical procedures in which blanks were run were within control limits, although values for a few blanks were outside the control limits. Blanks were not analyzed for acid-neutralizing capacity, dissolved inorganic carbon, fluoride, nitrate (colorimetric method), or pH. Sampling and analysis precision are evaluated herein in terms of the coefficient of variation obtained for triplicate samples in 14 of the 18 procedures. Data-quality objectives were met by more than 90 percent of the samples analyzed in all procedures except total monomeric aluminum (85 percent of samples met objectives), total aluminum (70 percent of samples met objectives), and dissolved organic carbon (85 percent of samples met objectives). Triplicate samples were not analyzed for ammonium, fluoride, dissolved inorganic carbon, or nitrate (colorimetric method). Results of the USGS interlaboratory Standard Reference Sample Program indicated high data quality with a median result of 3.6 of a possible 4.0. Environment Canada's LRTAP interlaboratory study results indicated that more than 85 percent of the samples met data-quality objectives in 6 of the 12 analyses; exceptions were calcium, dissolved organic carbon, chloride, pH, potassium, and sodium. Data-quality objectives were not met for calcium samples in one LRTAP study, but 94 percent of samples analyzed were within control limits for the remaining studies. Data-quality objectives were not met by 35 percent of samples analyzed for dissolved organic carbon, but 94 percent of sample values were within 20 percent of the most probable value. Data-quality objectives were not met for 30 percent of samples analyzed for chloride, but 90 percent of sample values were within 20 percent of the most probable value. Measurements of samples with a pH above 6.0 were biased high in 54 percent of the samples, although 85 percent of the samples met data-quality objectives for pH measurements below 6.0. Data-quality objectives for potassium and sodium were not met in one study (only 33 percent of the samples analyzed met the objectives), although 85 percent of the sample values were within control limits for the other studies. Measured sodium values were above the upper control limit in all studies. Results from blind reference-sample analyses indicated that data

Open-File Report↗
USGS2001

Water-quality and lake-stage data for Wisconsin lakes, water year 2001

The U.S. Geological Survey (USGS), in cooperation with local and other agencies, collects data at selected lakes throughout Wisconsin. These data, accumulated over many years, provide a data base for developing an improved understanding of the water quality of lakes. To make these data available to interested parties outside the USGS, the data are published annually in this report series. The locations of water-quality and lake-stage stations in Wisconsin for water year 2001 are shown in figure 1. A water year is the 12-month period from October 1 through September 30. It is designated by the calendar year in which it ends. Thus, the period October 1, 2000 through September 30, 2001 is called "water year 2001." The purpose of this report is to provide information about the chemical and physical characteristics of Wisconsin lakes. Data that have been collected at specific lakes, and information to aid in the interpretation of those data, are included in this report. Data collected include measurements of in-lake water quality and lake stage. Time series of Secchi depths, surface total phosphorus and chlorophyll a concentrations collected during non-frozen periods are included for all lakes. Graphs of vertical profiles of temperature, dissolved oxygen, pH, and specific conductance are included for sites where these parameters were measured. Descriptive information for each lake includes: location of the lake, area of the lake's watershed, period for which data are available, revisions to previously published records, and pertinent remarks. Additional data, such as streamflow and water quality in tributary and outlet streams of some of the lakes, are published in another volume: "Water Resources Data-Wisconsin, 2001." Water-resources data, including stage and discharge data at most streamflow-gaging stations, are available throught the World Wide Web on the Internet. The Wisconsin District's home page is at http://wi.water.usgs.gov/. Information on the Wisconsin District's Lakes Program is found at wi.water.usgs.gov/lake/index.html.

Wisconsin↗
USGS2004

Water-quality and lake-stage data for Wisconsin Lakes, water year 2003

The U.S. Geological Survey (USGS), in cooperation with local and other agencies, collects data at selected lakes throughout Wisconsin. These data, accumulated over many years, provide a data base for developing an improved understanding of the water quality of lakes. To make these data available to interested parties outside the USGS, the data are published annually in this report series. The locations of water-quality and lake-stage stations in Wisconsin for water year 2003 are shown in figure 1. A water year is the 12-month period from October 1 through September 30. It is designated by the calendar year in which it ends. Thus, the period October 1, 2002 through September 30, 2003 is called "water year 2003." The purpose of this report is to provide information about the chemical and physical characteristics of Wisconsin lakes. Data that have been collected at specific lakes, and information to aid in the interpretation of those data, are included in this report. Data collected include measurements of in-lake water quality and lake stage. Time series of Secchi depths, surface total phosphorus and chlorophyll a concentrations collected during non-frozen periods are included for all lakes. Graphs of vertical profiles of temperature, dissolved oxygen, pH, and specific conductance are included for sites where these parameters were measured. Descriptive infor- mation for each lake includes: location of the lake, area of the lake's watershed, period for which data are available, revisions to previously published records, and pertinent remarks. Additional data, such as streamflow and water quality in tributary and outlet streams of some of the lakes, are published in another volume: "Water Resources Data-Wisconsin, 2003." Water-resources data, including stage and discharge data at most streamflow-gaging stations, are available throught the World Wide Web on the Internet. The Wisconsin District's home page is at http://wi.water.usgs.gov/. Information on the Wisconsin District's Lakes Program is found at wi.water.usgs.gov/lake/index.html and wi.water.usgs.gov/projects/ index.html.

Wisconsin↗
USGS2005

Water-quality and Llake-stage data for Wisconsin Lakes, Water Year 2004

The U.S. Geological Survey (USGS), in cooperation with local and other agencies, collects data at selected lakes throughout Wisconsin. These data, accumulated over many years, provide a data base for developing an improved understanding of the water quality of lakes. To make these data available to interested parties outside the USGS, the data are published annually in this report series. The locations of water-quality and lake-stage stations in Wisconsin for water year 2004 are shown in figure 1. A water year is the 12-month period from October 1 through September 30. It is designated by the calendar year in which it ends. Thus, the period October 1, 2003 through September 30, 2004 is called 'water year 2004.' The purpose of this report is to provide information about the chemical and physical characteristics of Wisconsin lakes. Data that have been collected at specific lakes, and information to aid in the interpretation of those data, are included in this report. Data collected include measurements of in-lake water quality and lake stage. Time series of Secchi depths, surface total phosphorus and chlorophyll a concentrations collected during non-frozen periods are included for all lakes. Graphs of vertical profiles of temperature, dissolved oxygen, pH, and specific conductance are included for sites where these parameters were measured. Descriptive information for each lake includes: location of the lake, area of the lake's watershed, period for which data are available, revisions to previously published records, and pertinent remarks. Additional data, such as streamflow and water quality in tributary and outlet streams of some of the lakes, are published in another volume: 'Water Resources Data-Wisconsin, 2004.' Water-resources data, including stage and discharge data at most streamflow-gaging stations, are available throught the World Wide Web on the Internet. The Wisconsin Water Science Center's home page is at http://wi.water.usgs.gov/. Information on the Wisconsin Water Science Center's Lakes Program is found at wi.water.usgs.gov/lake/index.html and wi.water.usgs.gov/projects/index.html

Wisconsin↗
USGS2006

Watershed Data Management (WDM) Database for Salt Creek Streamflow Simulation, DuPage County, Illinois

The U.S. Geological Survey (USGS), in cooperation with DuPage County Department of Engineering, Stormwater Management Division, maintains a database of hourly meteorologic and hydrologic data for use in a near real-time streamflow simulation system, which assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek watershed in DuPage County, Illinois. The majority of the precipitation data are collected from a tipping-bucket rain-gage network located in and near DuPage County. The other meteorologic data (wind speed, solar radiation, air temperature, and dewpoint temperature) are collected at Argonne National Laboratory in Argonne, Illinois. Potential evapotranspiration is computed from the meteorologic data. The hydrologic data (discharge and stage) are collected at USGS streamflow-gaging stations in DuPage County. These data are stored in a Watershed Data Management (WDM) database. This report describes a version of the WDM database that was quality-assured and quality-controlled annually to ensure the datasets were complete and accurate. This version of the WDM database contains data from January 1, 1997, through September 30, 2004, and is named SEP04.WDM. This report provides a record of time periods of poor data for each precipitation dataset and describes methods used to estimate the data for the periods when data were missing, flawed, or snowfall-affected. The precipitation dataset data-filling process was changed in 2001, and both processes are described. The other meteorologic and hydrologic datasets in the database are fully described in the annual U.S. Geological Survey Water Data Report for Illinois and, therefore, are described in less detail than the precipitation datasets in this report.

Open-File Report↗
USGS2007

Water-Quality and Lake-Stage Data for Wisconsin Lakes, Water Year 2006

The U.S. Geological Survey (USGS), in cooperation with local and other agencies, collects data at selected lakes throughout Wisconsin. These data, accumulated over many years, provide a data base for developing an improved understanding of the water quality of lakes. To make these data available to interested parties outside the USGS, the data are published annually in this report series. The locations of water-quality and lake-stage stations in Wisconsin for water year 2006 are shown in figure 1. A water year is the 12-month period from October 1 through September 30. It is designated by the calendar year in which it ends. Thus, the period October 1, 2005 through September 30, 2006 is called 'water year 2006.' The purpose of this report is to provide information about the chemical and physical characteristics of Wisconsin lakes. Data that have been collected at specific lakes, and information to aid in the interpretation of those data, are included in this report. Data collected include measurements of in-lake water quality and lake stage. Time series of Secchi depths, surface total phosphorus and chlorophyll a concentrations collected during non-frozen periods are included for all lakes. Graphs of vertical profiles of temperature, dissolved oxygen, pH, and specific conductance are included for sites where these parameters were measured. Descriptive information for each lake includes: location of the lake, area of the lake's watershed, period for which data are available, revisions to previously published records, and pertinent remarks. Additional data, such as streamflow and water quality in tributary and outlet streams of some of the lakes, are published in another volume: 'Water Resources Data-Wisconsin, 2006.' Water-resources data, including stage and discharge data at most streamflow-gaging stations, are available through the World Wide Web on the Internet. The Wisconsin Water Science Center's home page is at http://wi.water.usgs.gov/. Information on the Wisconsin Water Science Center's Lakes Program is found at http://wi.water.usgs.gov/lake/index.html and http://wi.water.usgs.gov/projects/index.html.

Open-File Report↗
USGS2009

Quality-assurance data for routine water analyses by the U.S. Geological Survey laboratory in Troy, New York - July 2003 through June 2005

The laboratory for analysis of low-ionic-strength water at the U.S. Geological Survey (USGS) Water Science Center in Troy, N.Y., analyzes samples collected by USGS projects throughout the Northeast. The laboratory's quality-assurance program is based on internal and interlaboratory quality-assurance samples and quality-control procedures that were developed to ensure proper sample collection, processing, and analysis. The quality-assurance and quality-control data were stored in the laboratory's Lab Master data-management system, which provides efficient review, compilation, and plotting of data. This report presents and discusses results of quality-assurance and quality control samples analyzed from July 2003 through June 2005. Results for the quality-control samples for 20 analytical procedures were evaluated for bias and precision. Control charts indicate that data for five of the analytical procedures were occasionally biased for either high-concentration or low-concentration samples but were within control limits; these procedures were: acid-neutralizing capacity, total monomeric aluminum, pH, silicon, and sodium. Seven of the analytical procedures were biased throughout the analysis period for the high-concentration sample, but were within control limits; these procedures were: dissolved organic carbon, chloride, nitrate (ion chromatograph), nitrite, silicon, sodium, and sulfate. The calcium and magnesium procedures were biased throughout the analysis period for the low-concentration sample, but were within control limits. The total aluminum and specific conductance procedures were biased for the high-concentration and low-concentration samples, but were within control limits. Results from the filter-blank and analytical-blank analyses indicate that the procedures for 17 of 18 analytes were within control limits, although the concentrations for blanks were occasionally outside the control limits. The data-quality objective was not met for dissolved organic carbon. Sampling and analysis precision are evaluated herein in terms of the coefficient of variation obtained for triplicate samples in the procedures for 18 of the 22 analytes. At least 85 percent of the samples met data-quality objectives for all analytes except total monomeric aluminum (82 percent of samples met objectives), total aluminum (77 percent of samples met objectives), chloride (80 percent of samples met objectives), fluoride (76 percent of samples met objectives), and nitrate (ion chromatograph) (79 percent of samples met objectives). The ammonium and total dissolved nitrogen did not meet the data-quality objectives. Results of the USGS interlaboratory Standard Reference Sample (SRS) Project indicated good data quality over the time period, with ratings for each sample in the satisfactory, good, and excellent ranges or less than 10 percent error. The P-sample (low-ionic-strength constituents) analysis had one marginal and two unsatisfactory ratings for the chloride procedure. The T-sample (trace constituents)analysis had two unsatisfactory ratings and one high range percent error for the aluminum procedure. The N-sample (nutrient constituents) analysis had one marginal rating for the nitrate procedure. Results of Environment Canada's National Water Research Institute (NWRI) program indicated that at least 84 percent of the samples met data-quality objectives for 11 of the 14 analytes; the exceptions were ammonium, total aluminum, and acid-neutralizing capacity. The ammonium procedure did not meet data quality objectives in all studies. Data-quality objectives were not met in 23 percent of samples analyzed for total aluminum and 45 percent of samples analyzed acid-neutralizing capacity. Results from blind reference-sample analyses indicated that data-quality objectives were met by at least 86 percent of the samples analyzed for calcium, chloride, fluoride, magnesium, pH, potassium, sodium, and sulfate. Data-quality objectives were not met by samples analyzed for fluoride.

Open-File Report↗
USGS2011

Usage and administration manual for a geodatabase compendium of water-resources data: Rio Grande Basin from the Rio Arriba-Sandoval County line, New Mexico, to Presidio, Texas, 1889-2009

The U.S. Geological Survey, in cooperation with the New Mexico Interstate Stream Commission, developed a geodatabase compendium (hereinafter referred to as the 'geodatabase') of available water-resources data for the reach of the Rio Grande from Rio Arriba-Sandoval County line, New Mexico, to Presidio, Texas. Since 1889, a wealth of water-resources data has been collected in the Rio Grande Basin from Rio Arriba-Sandoval County line, New Mexico, to Presidio, Texas, for a variety of purposes. Collecting agencies, researchers, and organizations have included the U.S. Geological Survey, Bureau of Reclamation, International Boundary and Water Commission, State agencies, irrigation districts, municipal water utilities, universities, and other entities. About 1,750 data records were recently (2010) evaluated to enhance their usability by compiling them into a single geospatial relational database (geodatabase). This report is intended as a user's manual and administration guide for the geodatabase. All data available, including water quality, water level, and discharge data (both instantaneous and daily) from January 1, 1889, through December 17, 2009, were compiled for the study area. A flexible and efficient geodatabase design was used, enhancing the ability of the geodatabase to handle data from diverse sources and helping to ensure sustainability of the geodatabase with long-term maintenance. Geodatabase tables include daily data values, site locations and information, sample event information, and parameters, as well as data sources and collecting agencies. The end products of this effort are a comprehensive water-resources geodatabase that enables the visualization of primary sampling sites for surface discharges, groundwater elevations, and water-quality and associated data for the study area. In addition, repeatable data processing scripts, Structured Query Language queries for loading prepared data sources, and a detailed process for refreshing all data in the compendium have been developed. The geodatabase functionality allows users to explore spatial characteristics of the data, conduct spatial analyses, and pose questions to the geodatabase in the form of queries. Users can also customize and extend the geodatabase, combine it with other databases, or use the geodatabase design for other water-resources applications.

New Mexico, Texas↗
USGS2017

Watershed Data Management (WDM) database for West Branch DuPage River streamflow simulation, DuPage County, Illinois, January 1, 2007, through September 30, 2013

The U.S. Geological Survey (USGS), in cooperation with the DuPage County Stormwater Management Department, maintains a database of hourly meteorological and hydrologic data for use in a near real-time streamflow simulation system. This system is used in the management and operation of reservoirs and other flood-control structures in the West Branch DuPage River watershed in DuPage County, Illinois. The majority of the precipitation data are collected from a tipping-bucket rain-gage network located in and near DuPage County. The other meteorological data (air temperature, dewpoint temperature, wind speed, and solar radiation) are collected at Argonne National Laboratory in Argonne, Ill. Potential evapotranspiration is computed from the meteorological data using the computer program LXPET (Lamoreux Potential Evapotranspiration). The hydrologic data (water-surface elevation [stage] and discharge) are collected at U.S.Geological Survey streamflow-gaging stations in and around DuPage County. These data are stored in a Watershed Data Management (WDM) database. This report describes a version of the WDM database that is quality-assured and quality-controlled annually to ensure datasets are complete and accurate. This database is named WBDR13.WDM. It contains data from January 1, 2007, through September 30, 2013. Each precipitation dataset may have time periods of inaccurate data. This report describes the methods used to estimate the data for the periods of missing, erroneous, or snowfall-affected data and thereby improve the accuracy of these data. The other meteorological datasets are described in detail in Over and others (2010), and the hydrologic datasets in the database are fully described in the online USGS annual water data reports for Illinois (U.S. Geological Survey, 2016) and, therefore, are described in less detail than the precipitation datasets in this report.

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