USGS Science⌕ Search

SEARCH · USGS Science

Results for “Data”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30Linked to original sources
USGS2002

Selected micrometeorological and soil-moisture data at Amargosa Desert Research Site in Nye County near Beatty, Nevada, 1998-2000

Selected micrometeorological and soil-moisture data were collected at the Amargosa Desert Research Site adjacent to a low-level radioactive waste and hazardous chemical waste facility near Beatty, Nev., 1998-2000. Data were collected in support of ongoing research studies to improve the understanding of hydrologic and contaminant-transport processes in arid environments. Micrometeorological data include precipitation, air temperature, solar radiation, net radiation, relative humidity, ambient vapor pressure, wind speed and direction, barometric pressure, soil temperature, and soil-heat flux. All micrometeorological data were collected using a 10-second sampling interval by data loggers that output daily mean, maximum, and minimum values, and hourly mean values. For precipitation, data output consisted of daily, hourly, and 5-minute totals. Soil-moisture data included periodic measurements of soil-water content at nine neutron-probe access tubes with measurable depths ranging from 5.25 to 29.75 meters. The computer data files included in this report contain the complete micrometeorological and soil-moisture data sets. The computer data consists of seven files with about 14 megabytes of information. The seven files are in tabular format: (1) one file lists daily mean, maximum, and minimum micrometeorological data and daily total precipitation; (2) three files list hourly mean micrometeorological data and hourly precipitation for each year (1998-2000); (3) one file lists 5-minute precipitation data; (4) one file lists mean soil-water content by date and depth at four experimental sites; and (5) one file lists soil-water content by date and depth for each neutron-probe access tube. This report highlights selected data contained in the computer data files using figures, tables, and brief discussions. Instrumentation used for data collection also is described. Water-content profiles are shown to demonstrate variability of water content with depth. Time-series data are plotted to illustrate temporal variations in micrometeorological and soil-water content data. Substantial precipitation at the end of an El Ni?o cycle in early 1998 resulted in measurable water penetration to a depth of 1.25 meters at one of the four experimental soil-monitoring sites.

Nevada↗
USGS2007

Analysis of flood-magnitude and flood-frequency data for streamflow-gaging stations in the Delaware and North Branch Susquehanna River Basins in Pennsylvania

The Delaware and North Branch Susquehanna River Basins in Pennsylvania experienced severe flooding as a result of intense rainfall during June 2006. The height of the flood waters on the rivers and tributaries approached or exceeded the peak of record at many locations. Updated flood-magnitude and flood-frequency data for streamflow-gaging stations on tributaries in the Delaware and North Branch Susquehanna River Basins were analyzed using data through the 2006 water year to determine if there were any major differences in the flood-discharge data. Flood frequencies for return intervals of 2, 5, 10, 50, 100, and 500 years (Q2, Q5, Q10, Q50, Q100, and Q500) were determined from annual maximum series (AMS) data from continuous-record gaging stations (stations) and were compared to flood discharges obtained from previously published Flood Insurance Studies (FIS) and to flood frequencies using partial-duration series (PDS) data. A Wilcoxon signed-rank test was performed to determine any statistically significant differences between flood frequencies computed from updated AMS station data and those obtained from FIS. Percentage differences between flood frequencies computed from updated AMS station data and those obtained from FIS also were determined for the 10, 50, 100, and 500 return intervals. A Mann-Kendall trend test was performed to determine statistically significant trends in the updated AMS peak-flow data for the period of record at the 41 stations. In addition to AMS station data, PDS data were used to determine flood-frequency discharges. The AMS and PDS flood-frequency data were compared to determine any differences between the two data sets. An analysis also was performed on AMS-derived flood frequencies for four stations to evaluate the possible effects of flood-control reservoirs on peak flows. Additionally, flood frequencies for three stations were evaluated to determine possible effects of urbanization on peak flows. The results of the Wilcoxon signed-rank test showed a significant difference at the 95-percent confidence level between the Q100 computed from AMS station data and the Q100 determined from previously published FIS for 97 sites. The flood-frequency discharges computed from AMS station data were consistently larger than the flood discharges from the FIS; mean percentage difference between the two data sets ranged from 14 percent for the Q100 to 20 percent for the Q50. The results of the Mann-Kendall test showed that 8 stations exhibited a positive trend (i.e., increasing annual maximum peaks over time) over their respective periods of record at the 95-percent confidence level, and an additional 7 stations indicated a positive trend, for a total of 15 stations, at a confidence level of greater than or equal to 90 percent. The Q2, Q5, Q10, Q50, and Q100 determined from AMS and PDS data for each station were compared by percentage. The flood magnitudes for the 2-year return period were 16 percent higher when partial-duration peaks were incorporated into the analyses, as opposed to using only the annual maximum peaks. The discharges then tended to converge around the 5-year return period, with a mean collective difference of only 1 percent. At the 10-, 50-, and 100-year return periods, the flood magnitudes based on annual maximum peaks were, on average, 6 percent higher compared to corresponding flood magnitudes based on partial-duration peaks. Possible effects on flood peaks from flood-control reservoirs and urban development within the basin also were examined. Annual maximum peak-flow data from four stations were divided into pre- and post-regulation periods. Comparisons were made between the Q100 determined from AMS station data for the periods of record pre- and post-regulation. Two stations showed a nearly 60- and 20-percent reduction in the 100-year discharges; the other two stations showed negligible differences in discharges. Three stations within urban basins were compared to 38 stations

Pennsylvania↗
USGS1995

Digital aeromagnetic anomaly data from eastern-most Guyana

The Center for Inter-American Mineral Resource Investigations (CIMRI) supported distribution and analysis of geoscientific and mineral resource related information concerning Latin America. CIMRI staff digitized aeromagnetic data for eastern-most Guyana as part of a preliminary regional assessment of minerals in the Guyana Shield, South America. The data were digitized from 145 aeromagnetic contour maps at a scale of 1:50,000 and merged into a single digital data set. The data were used to examine the Precambrian shield, greenstone belts, and other tectonic boundaries as well as explore ideas concerning mineral deposits within the area. A subset of these digital data were presented to the Guyanan government during early 1995 (Pierce, 1994). This Open-File report, consisting of this text and seven (7) 3.5" IBM-PC compatible ASCII magnetic disks, makes the digital data available to the public. Information regarding the source of data and subsequent processing is included below. The data were collected in Guyana by two contractors at different times. The first data were collected from 1962 to 1963. These data are several aeromagnetic surveys covering parts of 12 quadrangles funded by the United Nations and flown by Aero Service Corporation. The second and more extensive data set was collected from 1971 to 1972 by the Canadian International Development Agency flown by Terra Surveys Ltd. under a contract with the Geological Survey of Guyana. The Guyana Government published the data as contour maps that are available in Georgetown through the Guyana Government. Coverage extends from about 2°45*N to 8°30*N latitude and from 60°0'W to 57°0'W longitude (see Figure 1.). The contour maps were digitized at points where the magnetic contours intersect the flight lines. The data files include XYZ ASCII files, XYZ binary files, ASCII grids, and binary "standard USGS" grids. There are four grids consisting of the following data types: unprotected raw data grid unprotected residual or International Geomagnetic Reference Field (IGRF) removed grid UTM projected residual (IGRF removed) grid UTM projected residual with a second order surface removed These data files were transferred to 3.5" 1.44 megabyte floppy disks readable on IBM-compatible personal computers. These data are also available from the Department of Commerce National Geophysical Data Center.

Open-File Report↗
USGS2012

Estimation of evaporation from open water - A review of selected studies, summary of U.S. Army Corps of Engineers data collection and methods, and evaluation of two methods for estimation of evaporation from five reservoirs in Texas

Organizations responsible for the management of water resources, such as the U.S. Army Corps of Engineers (USACE), are tasked with estimation of evaporation for water-budgeting and planning purposes. The USACE has historically used Class A pan evaporation data (pan data) to estimate evaporation from reservoirs but many USACE Districts have been experimenting with other techniques for an alternative to collecting pan data. The energy-budget method generally is considered the preferred method for accurate estimation of open-water evaporation from lakes and reservoirs. Complex equations to estimate evaporation, such as the Penman, DeBruin-Keijman, and Priestley-Taylor, perform well when compared with energy-budget method estimates when all of the important energy terms are included in the equations and ideal data are collected. However, sometimes nonideal data are collected and energy terms, such as the change in the amount of stored energy and advected energy, are not included in the equations. When this is done, the corresponding errors in evaporation estimates are not quantifiable. Much simpler methods, such as the Hamon method and a method developed by the U.S. Weather Bureau (USWB) (renamed the National Weather Service in 1970), have been shown to provide reasonable estimates of evaporation when compared to energy-budget method estimates. Data requirements for the Hamon and USWB methods are minimal and sometimes perform well with remotely collected data. The Hamon method requires average daily air temperature, and the USWB method requires daily averages of air temperature, relative humidity, wind speed, and solar radiation. Estimates of annual lake evaporation from pan data are frequently within 20 percent of energy-budget method estimates. Results of evaporation estimates from the Hamon method and the USWB method were compared against historical pan data at five selected reservoirs in Texas (Benbrook Lake, Canyon Lake, Granger Lake, Hords Creek Lake, and Sam Rayburn Lake) to evaluate their performance and to develop coefficients to minimize bias for the purpose of estimating reservoir evaporation with accuracies similar to estimates of evaporation obtained from pan data. The modified Hamon method estimates of reservoir evaporation were similar to estimates of reservoir evaporation from pan data for daily, monthly, and annual time periods. The modified Hamon method estimates of annual reservoir evaporation were always within 20 percent of annual reservoir evaporation from pan data. Unmodified and modified USWB method estimates of annual reservoir evaporation were within 20 percent of annual reservoir evaporation from pan data for about 91 percent of the years compared. Average daily differences between modified USWB method estimates and estimates from pan data as a percentage of the average amount of daily evaporation from pan data were within 20 percent for 98 percent of the months. Without any modification to the USWB method, average daily differences as a percentage of the average amount of daily evaporation from pan data were within 20 percent for 73 percent of the months. Use of the unmodified USWB method is appealing because it means estimates of average daily reservoir evaporation can be made from air temperature, relative humidity, wind speed, and solar radiation data collected from remote weather stations without the need to develop site-specific coefficients from historical pan data. Site-specific coefficients would need to be developed for the modified version of the Hamon method.

Texas↗
USGS2016

Borehole deviation and correction factor data for selected wells in the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Energy, has maintained a water-level monitoring program at the Idaho National Laboratory (INL) since 1949. The purpose of the program is to systematically measure and report water-level data to assess the eastern Snake River Plain aquifer and long term changes in groundwater recharge, discharge, movement, and storage. Water-level data are commonly used to generate potentiometric maps and used to infer increases and (or) decreases in the regional groundwater system. Well deviation is one component of water-level data that is often overlooked and is the result of the well construction and the well not being plumb. Depending on measured slant angle, where well deviation generally increases linearly with increasing slant angle, well deviation can suggest artificial anomalies in the water table. To remove the effects of well deviation, the USGS INL Project Office applies a correction factor to water-level data when a well deviation survey indicates a change in the reference elevation of greater than or equal to 0.2 ft. Borehole well deviation survey data were considered for 177 wells completed within the eastern Snake River Plain aquifer, but not all wells had deviation survey data available. As of 2016, USGS INL Project Office database includes: 57 wells with gyroscopic survey data; 100 wells with magnetic deviation survey data; 11 wells with erroneous gyroscopic data that were excluded; and, 68 wells with no deviation survey data available. Of the 57 wells with gyroscopic deviation surveys, correction factors for 16 wells ranged from 0.20 to 6.07 ft and inclination angles (SANG) ranged from 1.6 to 16.0 degrees. Of the 100 wells with magnetic deviation surveys, a correction factor for 21 wells ranged from 0.20 to 5.78 ft and SANG ranged from 1.0 to 13.8 degrees, not including the wells that did not meet the correction factor criteria of greater than or equal to 0.20 ft. Forty-seven wells had gyroscopic and magnetic deviation survey data for the same well. Datasets for both survey types were compared for the same well to determine whether magnetic survey data were consistent with gyroscopic survey data. Of those 47 wells, 96 percent showed similar correction factor estimates (≤ 0.20 ft) for both magnetic and gyroscopic well deviation surveys. A linear comparison of correction factor estimates for both magnetic and gyroscopic deviation well surveys for all 47 wells indicate good linear correlation, represented by an r-squared of 0.88. The correction factor difference between the gyroscopic and magnetic surveys for 45 of 47 wells ranged from 0.00 to 0.18 ft, not including USGS 57 and USGS 125. Wells USGS 57 and USGS 125 show a correction factor difference of 2.16 and 0.36 ft, respectively; however, review of the data files suggest erroneous SANG data for both magnetic deviation well surveys. The difference in magnetic and gyroscopic well deviation SANG measurements, for all wells, ranged from 0.0 to 0.9 degrees. These data indicate good agreement between SANG data measured using the magnetic deviation survey methods and SANG data measured using gyroscopic deviation survey methods, even for surveys collected years apart.

Idaho↗
USGS1972

Water-temperature data acquisition activities in the United States

Along with the growing interest in water quality during the last decade, the need for data on all types of water-quality parameters has also increased. One parameter of particular interest, because of its many ramifications, is temperature. It influences many of the chemical and physical processes that take place in water. The solubility of gases--for example, oxygen and carbon dioxide--and the solution of mineral matter in water are functions of temperature. Such physical properties as density and viscosity vary with temperature. Oxidation of organic materials, as well as algal and bacterial growth, is promoted or retarded by favorable or unfavorable temperatures. Further, temperature bears on the utility of water: as a source of public water supplies; for industrial use, particularly if the water is used for cooling; and in the field of recreation involving contact sports, fishing, and fish culture. In recent years, temperature changes resulting from inflow of heated industrial waste, particularly effluent from power generating plants, have increased the need for temperature data to determine the degree of change, its effect on ecology, and the effect of any remedial action. Thus, because of the many extensive and intensive effects, a large amount of temperature data is collected on surface and ground waters by many agencies throughout the country. Moreover, because of its importance, there is a widespread interest in temperature even by those who are not active collectors of the data themselves. The industrialist, the manager, the public official, and others at one time or another may have need for temperature data and may well raise the questions: Who is collecting temperature data? What is the extent of the activity? Where are the data being collected? The purpose of this report is to answer these questions. The information in the report is confined to the activities of Federal and non-Federal agencies. It is based on information furnished to the Office of Water Data Coordination, U.S. Geological Survey, and published in the "Catalog of Information on Water Data, Index to Water Quality Section, Edition 1970." This is one of four indexes, each of which is a separate section of the Catalog. Three of the indexes, "Index to Water-Quality Section," "Index to Surface-Water Section," and "Index to Ground-.Water Stations," contain information on data acquired on a recurrent basis at specific locations for a period of 3 years or more. The fourth section, "Index to Areal Investigations and Miscellaneous Activities," is concerned with specific projects or shorter-term data activities that involve field or laboratory measurements or observations not included in any other section of the Catalog. The Catalog is a record of activities throughout the country (and in some places along the international border between the United States and Canada) conducted by Federal and non-Federal agencies engaged in the acquisition of water data and who furnish such information for presentation in the Catalog. The Catalog itself is an outgrowth of an assignment to the Department of the Interior and in turn to the Geological Survey, by the Office of Management and Budget, through the medium of OMB Circular A-67. This Circular states in part that one of the assigned responsibilities will be maintenance of a "central catalog of information on...water data and on Federal activities being planned or conducted to acquire such data." As an extension of this activity, non-Federal agencies are solicited to participate in the program. In this report, information is presented by means of tables and illustrations preceded by brief explanations. It includes the agencies collecting the data, the number of stations located on surface and ground waters where temperature measurements are made, the distribution of stations by States and by the 21 regions of the Water Resources Council (WRC) (a Federal agency created in accordance with the Water Resources Planning Act of 1965), and the frequency of measurements. Acquisition activities were not reported for those areas left blank on some illustrations. The report does not contain the actual temperature data. For this information, the particular agency, Federal or non-Federal, acquiring the data will have to be contacted. However, a bibliography at the end of this report lists 194 references which contain temperature data. Many of these references, especially the publications of the Geological Survey, may be available in major public and university libraries and libraries of Federal and non-Federal agencies.

Water-Resources Investigations Report↗
USGS2009

Optical satellite data volcano monitoring: a multi-sensor rapid response system

In this chapter, the use of satellite remote sensing to monitor active geological processes is described. Specifically, threats posed by volcanic eruptions are briefly outlined, and essential monitoring requirements are discussed. As an application example, a collaborative, multi-agency operational volcano monitoring system in the north Pacific is highlighted with a focus on the 2007 eruption of Kliuchevskoi volcano, Russia. The data from this system have been used since 2004 to detect the onset of volcanic activity, support the emergency response to large eruptions, and assess the volcanic products produced following the eruption. The overall utility of such integrative assessments is also summarized. The work described in this chapter was originally funded through two National Aeronautics and Space Administration (NASA) Earth System Science research grants that focused on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument. A skilled team of volcanologists, geologists, satellite tasking experts, satellite ground system experts, system engineers and software developers collaborated to accomplish the objectives. The first project, Automation of the ASTER Emergency Data Acquisition Protocol for Scientific Analysis, Disaster Monitoring, and Preparedness , established the original collaborative research and monitoring program between the University of Pittsburgh (UP), the Alaska Volcano Observatory (AVO), the NASA Land Processes Distributed Active Archive Center (LP DAAC) at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, and affiliates on the ASTER Science Team at the Jet Propulsion Laboratory (JPL) as well as associates at the Earth Remote Sensing Data Analysis Center (ERSDAC) in Japan. This grant, completed in 2008, also allowed for detailed volcanic analyses and data validation during three separate summer field campaigns to Kamchatka Russia. The second project, Expansion and synergistic use of the ASTER Urgent Request Protocol (URP) for natural disaster monitoring and scientific analysis , has expanded the project to other volcanoes around the world and is in progress through 2011. The focus on ASTER data is due to the suitability of the sensor for natural disaster monitoring and the availability of data. The instrument has several unique facets that make it especially attractive for volcanic observations (Ramsey and Dehn, 2004). Specifically, ASTER routinely collects data at night, it has the ability to generate digital elevation models using stereo imaging, it can collect data in various gain states to minimize data saturation, it has a cross-track pointing capability for faster targeting, and it collects data up to ±85° latitude for better global coverage. As with any optical imaging-based remote sensing, the viewing conditions can negatively impact the data quality. This impact varies across the optical and thermal infrared wavelengths as well as being a function of the specific atmospheric window within a given wavelength region. Water vapor and cloud formation can obscure surface data in the visible and near infrared (VNIR)/shortwave infrared (SWIR) region due mainly to non-selective scattering of the incident photons. In the longer wavelengths of the thermal infrared (TIR), scattering is less of an issue, but heavy cloud cover can still obscure the ground due to atmospheric absorption. Thin clouds can be optically-transparent in the VNIR and TIR regions, but can cause errors in the extracted surface reflectance or derived surface temperatures. In regions prone to heavy cloud cover, optical remote sensing can be improved through increased temporal resolution. As more images are acquired in a given time period the chances of a clear image improve dramatically. The Advanced Very High Resolution Radiometer (AVHRR) routine monitoring, which commonly collects 4-6 images per day of any north Pacific volcano, takes advantage of this fact. The rapid response program described in this chapter also improves the temporal resolution of the ASTER instrument. ASTER has been acquiring images of volcanic eruptions since soon after its launch in December 1999. An early example included the observations of the large pyroclastic flow deposit emplaced at Bezymianny volcano in Kamchatka, Russia. The first images in March 2000, just weeks after the eruption, revealed the extent, composition, and cooling history of this large deposit and of the active lava dome (Ramsey and Dehn, 2004). The initial results from these early datasets spurred interest in using ASTER data for expanded volcano monitoring in the north Pacific. It also gave rise to the multi-year NASA-funded programs of rapid response scheduling and imaging throughout the Aleutian, Kamchatka and Kurile arcs. Since the formal establishment of the programs, the data have provided detailed descriptions of the eruptions of Augustine, Bezymianny, Kliuchevskoi and Sheveluch volcanoes over the past nine years (Wessels et al., in press; Carter et al., 2007, 2008; Ramsey et al., 2008; Rose and Ramsey, 2009). The initial research focus of this rapid response program was specifically on automating the ASTER sensor’s ability for targeted observational scheduling using the expedited data system. This urgent request protocol is one of the unique characteristics of ASTER. It provides a limited number of emergency observations, typically at a much-improved temporal resolution and quicker turnaround with data processing in the United States rather than in Japan. This can speed the reception of the processed data by several days to a week. The ongoing multi-agency research and operational collaboration has been highly successful. AVO serves as the primary source for status information on volcanic activity, working closely with the National Weather Service (NWS), Federal Aviation Administration (FAA), military and other state and federal emergency services. Collaboration with the Russian Institute of Volcanology and Seismology (IVS)/Kamchatka Volcanic Eruption Response Team (KVERT) is also maintained. Once a volcano is identified as having increased thermal output, ASTER is automatically tasked and the volcano is targeted at the next available opportunity. After the data are acquired, scientists at all the agencies have access to the images, with the primary science analysis carried out at the University of Pittsburgh and AVO. Results are disseminated to the responsible monitoring agencies and the global community through e-mail mailing lists.

Book chapter↗
USGS1987

Data integration using color space transforms

The demand for increased spatial resolution without sacrificing spectral discrimination can be fulfilled by integration of data from different sensor systems and satellite programs. Data of high spatial resolution are frequently available in panchromatic (black-and-white) form rather than multispectral. Techniques gave been developed to combine the higher resolution panchromatic data with a multispectral data set of lower spatial resolution. The standard method of integration modulates the intensity of the mutispectral with the panchromatic data. A less subjective approach uses an algorithm that describes color in terms of intensity (I), hue (H), and saturation (S). Combinations of high resolution panchromatic data (SPOT panchromatic) and lower resolution multispectral data [Landsat thematic mapper (TM), SPOT XS] have been developed. The SPOT data were acquired on April 3, 1986, and the Landsat TM data were acquired on April 5, 1986. The data sets were registered to each other and the multi-spectral data sets were contrast enhanced. The enhanced multispectral data sets were then transformed from red/green/blue (RGB) color space into IHS space. In each case (TM/SPOT panchromatic and SPOT XS/SPOT panchromatic), the SPOT panchromatic data were remapped on a cumulative histogram percentage basis to match the multispectral "I" data. These remapped SPOT panchromatic data were substituted for the original multispectral "I" and the hybrid IHS data transformed back into RGB space for display. While this technique is experimental and still being refined, the results, to date, indicate that the IHS method will be valuable for generating improved images that effectively present both high resolution spatial digital data and multispectral data.

Pecora XI Symposium↗
USGS2007

Selected micrometeorological, soil-moisture, and evapotranspiration data at Amargosa Desert Research Site in Nye County near Beatty, Nevada, 2001-05

Selected micrometeorological and soil-moisture data were collected at the Amargosa Desert Research Site adjacent to a low-level radio-active waste and hazardous chemical waste facility near Beatty, Nevada, 2001-05. Evapotranspiration data were collected from February 2002 through the end of December 2005. Data were col-lected in support of ongoing research to improve the understanding of hydrologic and contaminant-transport processes in arid environments. Micrometeorological data include solar radiation, net radiation, air temperature, relative humidity, saturated and ambient vapor pressure, wind speed and direction, barometric pressure, precipitation, near-surface soil temperature, soil-heat flux and soil-water content. All micrometeorological data were collected using a 10-second sampling interval by data loggers that output daily and hourly mean values. Daily maximum and minimum values are based on hourly mean values. Precipitation data output includes daily and hourly totals. Selected soil-moisture profiles at depth include periodic measurements of soil volumetric water-content measurements at nine neutron-probe access tubes to depths ranging from 5.25 to 29.25 meters. Evapotranspiration data include measurement of daily evapotranspiration and 15-minute fluxes of the four principal energy budget components of latent-heat flux, sensible-heat flux, soil-heat flux, and net radiation. Other data collected and used in equations to determine evapotranspiration include temperature and water content of soil, temperature and vapor pressure of air, and covariance values. Evapotranspiration and flux estimates during 15-minute intervals were calculated at a 0.1-second execution interval using the eddy covariance method. Data files included in this report contain the complete micrometeorological, soil-moisture, and evapotranspiration field data sets. These data files are presented in tabular Excel spreadsheet format. This report highlights selected data contained in the computer generated data files using figures, tables, and brief discussions. Instrumentation used for data collection also is described. Water-content profiles are shown to demonstrate variability of water content with depth. Time-series data are plotted to illustrate temporal variations in micrometeorological, soil-water content, and evapotranspiration data.

Nevada↗
USGS1996

Great Basin geoscience data base

This CD-ROM serves as the archive for 73 digital GIS data set for the Great Basin. The data sets cover Nevada, eastern California, southeastern Oregon, southern Idaho, and western Utah. Some of the data sets are incomplete for the total area. On the CD-ROM, the data are provided in three formats, a prototype Federal Data Exchange standard format, the ESRI PC ARCVIEW1 format for viewing the data, and the ESRI ARC/INFO export format. Extensive documentation is provided to describe the data, the sources, and data enhancements. The following data are provided. One group of coverages comes primarily from 1:2,000,000-scale National Atlas data and can be assembled for use as base maps. These various forms of topographic information. In addition, public land system data sets are provided from the 1:2,500,000-scale Geologic Map of the United States and 1:500,000-scale geologic maps of Nevada, Oregon, and Utah. Geochemical data from the National Uranium Resource Evaluation (NURE) program are provided for most of the Great Basin. Geophysical data are provided for most of the Great Basin, typically gridded data with a spacing of 1 km. The geophysical data sets include aeromagnetics, gravity, radiometric data, and several derivative products. The thematic data sets include geochronology, calderas, pluvial lakes, tectonic extension domains, distribution of pre-Cenozoic terranes, limonite anomalies, Landsat linear features, mineral sites, and Bureau of Land Management exploration and mining permits.

Data Series↗
USGS2014

Gravity, magnetic, and radiometric data for Newberry Volcano, Oregon, and vicinity

Newberry Volcano in central Oregon is a 3,100-square-kilometer (1,200-square-mile) shield-shaped composite volcano, occupying a location east of the main north-south trend of the High Cascades volcanoes and forming a transition between the High Lava Plains subprovince of the Basin and Range Province to the east and the Cascade Range to the west. Magnetic, gravity, and radiometric data have been gathered and assessed for the region around the volcano. These data have widely varying quality and resolution, even within a given dataset, and these limitations are evaluated and described in this release. Publicly available gravity data in general are too sparse to permit detailed modeling except along a few roads with high-density coverage. Likewise, magnetic data are also unsuitable for all but very local modeling, primarily because available data consist of a patchwork of datasets with widely varying line-spacing. Gravity data show only the broadest correlation with mapped geology, whereas magnetic data show moderate correlation with features only in the vicinity of Newberry Caldera. At large scales, magnetic data correlate poorly with both geologic mapping and gravity data. These poor correlations are largely due to the different sensing depths of the two potential fields methods, which respond to physical properties deeper than the surficial geology. Magnetic data derive from rocks no deeper than the Curie-point isotherm depth (10 to 15 kilometers, km, maximum), whereas gravity data reflect density-contrasts to 100 to 150 km depths. Radiometric data from the National Uranium Resource Evaluation (NURE) surveys of the 1980s have perhaps the coarsest line-spacing of all (as much as 10 km between lines) and are extremely “noisy” for several reasons inherent to this kind of data. Despite its shallow-sensing character, only a few larger anomalies in the NURE data correlate well with geologic mapping. The purpose of this data series release is to collect and place the available geophysical data in the hands of other investigators in a readily comprehensible form. All data-compilation, splicing, filtering, and overlay-map displays were accomplished with the commercial Geosoft™ system, Advanced Option. Images are provided in both JPG and PDF formats.

Oregon↗
USGS2006

Quality-Assurance Data for Routine Water Analyses by the U.S. Geological Survey Laboratory in Troy, New York-July 1997 through June 1999

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/quality-control data for the time period addressed in this report were stored in the laboratory's SAS 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 1997 through June 1999. Results for the quality-control samples for 18 analytical procedures were evaluated for bias and precision. Control charts indicate that data for eight of the analytical procedures were occasionally biased for either high-concentration and (or) low-concentration samples but were within control limits; these procedures were: acid-neutralizing capacity, total monomeric aluminum, total aluminum, ammonium, calcium, chloride, specific conductance, and sulfate. The data from the potassium and sodium analytical procedures are insufficient for evaluation. Results from the filter-blank and analytical-blank analyses indicate that the procedures for 11 of 13 analytes were within control limits, although the concentrations for blanks were occasionally outside the control limits. Blank analysis results for chloride showed that 22 percent of blanks did not meet data-quality objectives and results for dissolved organic carbon showed that 31 percent of the blanks did not meet data-quality objectives. Sampling and analysis precision are evaluated herein in terms of the coefficient of variation obtained for triplicate samples in the procedures for 14 of the 18 analytes. At least 90 percent of the samples met data-quality objectives for all analytes except total aluminum (70 percent of samples met objectives) and potassium (83 percent of samples met objectives). Results of the USGS interlaboratory Standard Reference Sample (SRS) Project indicated good data quality for most constituents over the time period. The P-sample (low-ionic-strength constituents) analysis had good ratings in two of these studies and a satisfactory rating in the third. The results of the T-sample (trace constituents) analysis indicated high data quality with good ratings in all three studies. The N-sample (nutrient constituents) studies had one each of excellent, good, and satisfactory ratings. Results of Environment Canada's National Water Research Institute (NWRI) program indicated that at least 80 percent of the samples met data-quality objectives for 9 of the 13 analytes; the exceptions were dissolved organic carbon, ammonium, chloride, and specific conductance. Data-quality objectives were not met for dissolved organic carbon in two NWRI studies, but all of the samples were within control limits for the last study. Data-quality objectives were not met in 41 percent of samples analyzed for ammonium, 25 percent of samples analyzed for chloride, and 30 percent of samples analyzed for specific conductance. Results from blind reference-sample analyses indicated that data-quality objectives were met by at least 84 percent of the samples analyzed for calcium, chloride, magnesium, pH, and potassium. Data-quality objectives were met by 73 percent of those analyzed for sulfate. The data-quality objective was not met for sodium. The data are insufficient for evaluation of the specific conductance results.

Open-File Report↗
USGS2015

Archiving California’s historical duck nesting data

The U.S. Geological Survey (USGS), in partnership with the California Waterfowl Association (CWA) and other organizations, have compiled large datasets on the nesting ecology and management of dabbling ducks and associated upland nesting birds (Northern Harriers [ Circus cyaneus ], Short-eared Owls [ Asio flammeus ], Ring-necked Pheasants [ Phasianus colchicus ], and American Bitterns [ Botaurus lentiginosus ]) throughout California on Federal Refuges, State Wildlife Areas, and private lands, some participating in State and Federal habitat programs. These datasets encompass several long-term monitoring programs at multiple sites throughout California, and include data from more than 26,000 nests and span nearly 30 years. These historical datasets represent some of the longest term datasets on nesting ducks in North America, if not the world. They are extremely valuable for ongoing waterfowl management and habitat conservation efforts in California, as well as throughout the world. However, without organization and electronic access, these data are an untapped resource and are not being used to the full extent possible. Prior to this project, these datasets were scattered among various agencies and organizations, and original paper nest cards were being stored in cardboard boxes in attics and storage containers that were not suitable for long-term archival storage. In addition, most of these data had not been entered into a computerized database and thus were at high risk for permanent data loss. To protect this irreplaceable dataset, we submitted a series of proposals to obtain funds to complete this data archival project over the past 5 years. The Central Valley Joint Venture, USGS Data Rescue Program, and USGS Ecosystems Mission Area funded this data archival project. In addition, we leveraged other USGS projects on nesting shorebirds, songbirds, and seabirds to use further resources to more fully develop the nest database structure for use on nesting waterfowl. Specifically, this large dataset on ducks was archived by USGS, but the dataset is owned and managed by a consortium of organizations. Therefore, any access and use of this data must occur through the principal investigators, who contributed data and resources to this archival project, as detailed in section, “Data Availability.” With the conclusion of this project, most duck nest data have been entered, but all nest-captured hen data and other breeding waterfowl data that were outside the scope of this project have still not been entered and electronically archived. Maintaining an up-to-date archive will require additional resources to archive and enter the new duck nest data each year in an iterative process. Further, data proofing should be conducted whenever possible, and also should be considered an iterative process as there was sometimes missing data that could not be filled in without more direct knowledge of specific projects. Despite these disclaimers, this duck data archive represents a massive and useful dataset to inform future research and management questions.

California↗
USGS1985

Satellite data-relay activities in Arizona

The U.S. Geological Survey (USGS) Arizona District collects data from automated streamflow stations for a wide variety of uses. Data from these stations are provided to Federal, State, and local agencies that have a responsibility to issue flood warnings; to generate forecasts of water availability; to monitor flow to insure compliance with treaties and other legal mandates; and to manage reservoirs for hydropower, flood abatement, and municipal and irrigation water supply. In the mid-1970's, the escalation of data collection costs and a need for more timely data led the Arizona District to examine alternatives for remote data acquisition. On the basis of successful data communications experiments with NASA 's Landsat satellite, an operational system for satellite-data relay was developed in 1976 using the National Oceanic and Atmospheric Administrations 's (NOAA) Geostationary Operational Environmental Satellite (GOES). A total of 62 data collection platforms (DCP's) was operated in 1983. Satellite telemetry operations are controlled at the remote data-collection stations by small battery-operated data collection platforms. The DCP 's periodically collect data from the sensors, store the data in computer memory, and at preset times transmit the data to the GOES satellite. The satellite retransmits the data to Earth where a ground-receive station transmits or transfers the data by land communications to the USGS computer in Reston, Virginia, for processing. The satellite relay transfers the data from sensor to computer in minutes; therefore, the data are available to users on a near real-time basis. (Author 's abstract)

Water-Resources Investigations Report↗
USGS1995

Database of well and areal data, South San Francisco Bay and Peninsula area, California

A database was developed to organize and manage data compiled for a regional assessment of geohydrologic and water-quality conditions in the south San Francisco Bay and Peninsula area in California. Available data provided by local, State, and Federal agencies and private consultants was utilized in the assessment. The database consists of geographicinformation system data layers and related tables and American Standard Code for Information Interchange files. Documentation of the database is necessary to avoid misinterpretation of the data and to make users aware of potential errors and limitations. Most of the data compiled were collected from wells and boreholes (collectively referred to as wells in this report). This point-specific data, including construction, water-level, waterquality, pumping test, and lithologic data, are contained in tables and files that are related to a geographic information system data layer that contains the locations of the wells. There are 1,014 wells in the data layer and the related tables contain 35,845 water-level measurements (from 293 of the wells) and 9,292 water-quality samples (from 394 of the wells). Calculation of hydraulic heads and gradients from the water levels can be affected adversely by errors in the determination of the altitude of land surface at the well. Cation and anion balance computations performed on 396 of the water-quality samples indicate high cation and anion balance errors for 51 (13 percent) of the samples. Well drillers' reports were interpreted for 762 of the wells, and digital representations of the lithology of the formations are contained in files following the American Standard Code for Information Interchange. The usefulness of drillers' descriptions of the formation lithology is affected by the detail and thoroughness of the drillers' descriptions, as well as the knowledge, experience, and vocabulary of the individual who described the drill cuttings. Additional data layers were created that contain political, geohydrologic, and other geographic data. These layers contain features represented by areas and lines rather than discrete points. The layers consist of data representing the thickness of alluvium, surficial geology, physiographic subareas, watershed boundaries, land use, water-supply districts, wastewater treatment districts, and recharge basins. The layers manually digitizing paper maps, acquisition of data already in digital form, or creation of new layers from available layers. The scale of the source data affects the accurate representation of real-world features with the data layer, and, therefore, the scale of the source data must be considered when the data are analyzed and plotted.

Water-Resources Investigations Report↗
USGS2017

Seven recommendations to make your invasive alien species data more useful

Science-based strategies to tackle biological invasions depend on recent, accurate, well-documented, standardized and openly accessible information on alien species. Currently and historically, biodiversity data are scattered in numerous disconnected data silos that lack interoperability. The situation is no different for alien species data, and this obstructs efficient retrieval, combination, and use of these kinds of information for research and policy-making. Standardization and interoperability are particularly important as many alien species related research and policy activities require pooling data. We describe seven ways that data on alien species can be made more accessible and useful, based on the results of a European Cooperation in Science and Technology (COST) workshop: (1) Create data management plans; (2) Increase interoperability of information sources; (3) Document data through metadata; (4) Format data using existing standards; (5) Adopt controlled vocabularies; (6) Increase data availability; and (7) Ensure long-term data preservation. We identify four properties specific and integral to alien species data (species status, introduction pathway, degree of establishment, and impact mechanism) that are either missing from existing data standards or lack a recommended controlled vocabulary. Improved access to accurate, real-time and historical data will repay the long-term investment in data management infrastructure, by providing more accurate, timely and realistic assessments and analyses. If we improve core biodiversity data standards by developing their relevance to alien species, it will allow the automation of common activities regarding data processing in support of environmental policy. Furthermore, we call for considerable effort to maintain, update, standardize, archive, and aggregate datasets, to ensure proper valorization of alien species data and information before they become obsolete or lost.

Frontiers in Applied Mathematics and Statistics↗
USGS2011

Alaska Geochemical Database (AGDB)-Geochemical data for rock, sediment, soil, mineral, and concentrate sample media

The Alaska Geochemical Database (AGDB) was created and designed to compile and integrate geochemical data from Alaska in order to facilitate geologic mapping, petrologic studies, mineral resource assessments, definition of geochemical baseline values and statistics, environmental impact assessments, and studies in medical geology. This Microsoft Access database serves as a data archive in support of present and future Alaskan geologic and geochemical projects, and contains data tables describing historical and new quantitative and qualitative geochemical analyses. The analytical results were determined by 85 laboratory and field analytical methods on 264,095 rock, sediment, soil, mineral and heavy-mineral concentrate samples. Most samples were collected by U.S. Geological Survey (USGS) personnel and analyzed in USGS laboratories or, under contracts, in commercial analytical laboratories. These data represent analyses of samples collected as part of various USGS programs and projects from 1962 to 2009. In addition, mineralogical data from 18,138 nonmagnetic heavy mineral concentrate samples are included in this database. The AGDB includes historical geochemical data originally archived in the USGS Rock Analysis Storage System (RASS) database, used from the mid-1960s through the late 1980s and the USGS PLUTO database used from the mid-1970s through the mid-1990s. All of these data are currently maintained in the Oracle-based National Geochemical Database (NGDB). Retrievals from the NGDB were used to generate most of the AGDB data set. These data were checked for accuracy regarding sample location, sample media type, and analytical methods used. This arduous process of reviewing, verifying and, where necessary, editing all USGS geochemical data resulted in a significantly improved Alaska geochemical dataset. USGS data that were not previously in the NGDB because the data predate the earliest USGS geochemical databases, or were once excluded for programmatic reasons, are included here in the AGDB and will be added to the NGDB. The AGDB data provided here are the most accurate and complete to date, and should be useful for a wide variety of geochemical studies. The AGDB data provided in the linked database may be updated or changed periodically. The data on the DVD and in the data downloads provided with this report are current as of date of publication.

Data Series↗
USGS2012

Data resources for range-wide assessment of livestock grazing across the sagebrush biome

The data contained in this series were compiled, modified, and analyzed for the U.S. Geological Survey (USGS) report "Range-Wide Assessment of Livestock Grazing Across the Sagebrush Biome." This report can be accessed through the USGS Publications Warehouse (online linkage: http://pubs.usgs.gov/of/2011/1263/). The dataset contains spatial and tabular data related to Bureau of Land Management (BLM) Grazing Allotments. We reviewed the BLM national grazing allotment spatial dataset available from the GeoCommunicator National Integrated Land System (NILS) website in 2007 (http://www.geocommunicator.gov). We identified several limitations in those data and learned that some BLM State and/or field offices had updated their spatial data to rectify these limitations, but maintained the data outside of NILS. We contacted appropriate BLM offices (State or field, 25 in all) to obtain the most recent data, assessed the data, established a data development protocol, and compiled data into a topologically enforced dataset throughout the area of interest for this project (that is, the pre-settlement distribution of Greater Sage-Grouse in the Western United States). The final database includes three spatial datasets: Allotments (BLM Grazing Allotments), OUT_Polygons (nonallotment polygons used to ensure topology), and Duplicate_Polygon_Allotments. See Appendix 1 of the aforementioned report for complete methods. The tabular data presented here consists of information synthesized by the Land Health Standard (LHS) analysis (Appendix 2), and data obtained from the BLM Rangeland Administration System (http://www.blm.gov/ras/). In 2008, available LHS data for all allotments in all regions were compiled by BLM in response to a Freedom of Information Act (FOIA) request made by a private organization. The BLM provided us with a copy of these data. These data provided three major types of information that were of interest: (1) date(s) (if any) of the most recent LHS evaluation for each allotment; (2) whether if evaluated, each region-specific standard (3–8 LHS depending on region) had been met on a given allotment; and (3) whether livestock contributed to any of these standards not being met. A description of how we processed the original data to prepare for analysis is described in Appendix 2, and the synthesized dataset can be found in the table "lhs_x_walk." Permitted use dates, livestock type (horse, sheep or cattle), number of livestock, and Animal Unit Months [the number of animal units (1,000-pound animal equivalents) that can be grazed for 31 days with the available forage in a sustainable manner] are the legal maximum grazing amounts for a given allotment, and legal adjustments to these numbers occur infrequently. We summarized permitted use by BLM allotment in the table "Permitted_Use." Billed use records are used for calculations of permittees' annual grazing bills. We summarized billed use by allotment for BLM grazing year in the table "Billed_Use." All three tables can be joined with the allotment spatial data in a geographic information system (GIS) environment, using the IDENT attribute as the primary key.

Data Series↗