Summary

Description

This digital data set defines the boundary of the ground-water flow model by D'Agnese and others (1997). This steady-state, 3-layer ground-water flow model was developed by the U.S. Geological Survey (USGS) for the U.S. Department of Energy (DOE) to support investigations at Yucca Mountain, Nevada (see "Larger Work Citation", Chapter A, pages 7-8, for details). The model area encompasses approximately 35,000 square-kilometers of southern Nevada and California, or most of the Death Valley regional ground-water flow system (DVRFS) defined by D'Agnese and others (1997). Where possible, the lateral boundary encompassing the model area is a no-flow boundary resulting from physical barriers or hydraulic separation of flow regimes (ground-water divides or regional flow lines). Three major subregional flow systems are defined within the model area and represent areas where regional ground-water flow moves from recharge areas in Nevada to discharge areas in Death Valley.

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Description

<p>Ensemble Detection is both a measurement technique and analysis tool. Like a prism that separates light into spectral bands, an ensemble detector mixes a signal with noise references that span a range of noise powers that produce multiple realizations that comprise an ensemble data set. The resulting ensemble data set represents a comprehensive stochastic description of the signal that is admissible to statistical analysis not otherwise possible with a single realization. Ensemble data sets provide time-varying probability distribution functions from which time varying statistics can be derived. The linear relationship between the reference mean and standard deviation provides a way to discriminate changes in the process mean from changes in the spread of the process’ probability distribution. Why is this important? Distinguishing between a mean state change and natural variability is a problem that spans multiple scientific disciplines. One important application is discriminating between climate change and natural variability of extreme weather events.</p>

Summary

Description

This digital dataset defines the surface traces of regional geologic structures designated as potential ground-water flow barriers in an approximately 45,000 square-kilometer area of the Death Valley regional ground-water flow system (DVRFS) in southern Nevada and California. Most geologic structures representing potential flow barriers were faults that were identified on the basis of length, offset, type of slip, orientation with respect to predominate ground-water flow directions, the location of springs, abrupt water level offsets, and hydraulic characteristics (Sweetkind and others, 2004). A subset of the potential ground-water flow barriers was incorporated into a transient ground-water flow model of the DVRFS (Faunt and others, 2004). This model is the most recent in a number of regional-scale models developed by the U.S. Geological Survey (USGS) for the U.S. Department of Energy (DOE) to support investigations at the Nevada Test Site (NTS) and at Yucca Mountain, Nevada (see "Larger Work Citation", Chapter A, page 8).

Summary

Description

Digital hydrogeologic surface of the Lower Claiborne aquifer in Alabama, Arkansas, Louisiana, and Mississippi. The hydrogeologic unit dataset contains 414 rows and 394 columns representing 1-mile grid spacing. In general, limitations of data interpolation included areas of sparse geophysical log control points, log datums not clearly defined for some logs, unknown exact extent of each hydrogeologic unit in subcrop, interpolation limitations, and values averaged over 1-mile grid spacing.

Summary

Description

HPMS compiles data on highway network extent, use, condition, and performance. The system consists of a geospatially-enabled database that is used to generate reports and provides tools for data analysis. Information from HPMS is used by many stakeholders across the US DOT, the Administration, Congress, and the transportation community.

Summary

Description

These data present a ground-water inventory of existing geospatial data and other information needed to determine the extent and characteristics of the aquifers in the Tahoe Basin. Geospatial and other data include geologic maps and soil surveys of the entire basin and for specific watersheds within the basin at the best available scales; vegetation remote-sensing datasets; well information from various local, state, and federal agencies; geophysical surveys; and results of available ground-water studies. The compilation and development of a ground-water inventory geospatial database will assist the United States Forest Service in better assessing the present and future impacts on ground-water resources within the Lake Tahoe Basin.

Summary

Description

HPMS compiles data on highway network extent, use, condition, and performance. The system consists of a geospatially-enabled database that is used to generate reports and provides tools for data analysis. Information from HPMS is used by many stakeholders across the US DOT, the Administration, Congress, and the transportation community.

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Description

This data set represents geologic structure contours for the Madison Limestone, Black Hills, South Dakota.

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Description

R&D Database provides Vehicle Crash Test data, Biomechanics Test Data, and Component Test Data to support NHTSA's motor vehicle and traffic safety goals.

Summary

Description

HPMS compiles data on highway network extent, use, condition, and performance. The system consists of a geospatially-enabled database that is used to generate reports and provides tools for data analysis. Information from HPMS is used by many stakeholders across the US DOT, the Administration, Congress, and the transportation community.

Summary

Description

This dataset is one of eight datasets produced by this study. Four of the datasets predict the probability of detecting atrazine and(or) desethyl-atrazine (a breakdown product of atrazine) in ground water in Colorado; the other four predict the probability of detecting elevated concentrations of nitrate in ground water in Colorado. The four datasets that predict the probability of atrazine and(or) desethyl-atrazine (atrazine/DEA) are differentiated by whether or not they incorporated atrazine use and whether or not they incorporated hydrogeomorphic regions. The four datasets that predict the probability of elevated concentrations of nitrate are differentiated by whether or not they incorporated fertilizer use and whether or not they incorporated hydrogeomorphic regions. Each of the eight datasets has its own unique strengths and weaknesses. The user is cautioned to read Rupert (2003, Probability of detecting atrazine/desethyl-atrazine and elevated concentrations of nitrate in ground water in Colorado: U.S. Geological Survey Water-Resources Investigations Report 02-4269, 35 p., http://water.usgs.gov/pubs/wri/wri02-4269/) to determine if he(she) is using the most appropriate dataset for his(her) particular needs. This dataset specifically predicts the probability of detecting elevated concentrations of nitrate in ground water in Colorado with hydrogeomorphic regions and fertilizer use included. The following text was extracted from Rupert (2003). Draft Federal regulations may require that each State develop a State Pesticide Management Plan for the herbicides atrazine, alachlor, metolachlor, and simazine. Maps were developed that the State of Colorado could use to predict the probability of detecting atrazine/DEA in ground water in Colorado. These maps can be incorporated into the State Pesticide Management Plan and can help provide a sound hydrogeologic basis for atrazine management in Colorado. Maps showing the probability of detecting elevated nitrite plus nitrate as nitrogen (nitrate) concentrations in ground water in Colorado also were developed because nitrate is a contaminant of concern in many areas of Colorado. Maps showing the probability of detecting atrazine/DEA at or greater than concentrations of 0.1 microgram per liter and nitrate concentrations in ground water greater than 5 milligrams per liter were developed as follows: (1) Ground-water quality data were overlaid with anthropogenic and hydrogeologic data by using a geographic information system (GIS) to produce a dataset in which each well had corresponding data on atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well construction. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Relations were observed between ground-water quality and the percentage of land-cover categories within circular regions (buffers) around wells. Several buffer sizes were evaluated; the buffer size that provided the strongest relation was selected for use in the logistic regression models. (3) Relations between concentrations of atrazine/DEA and nitrate in ground water and atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well-construction data were evaluated, and several preliminary multivariate models with various combinations of independent variables were constructed. (4) The multivariate models that best predicted the presence of atrazine/DEA and elevated concentrations of nitrate in ground water were selected. (5) The accuracy of the multivariate models was confirmed by validating the models with an independent set of ground-water quality data. (6) The multivariate models were entered into a geographic information system and the probability GRIDS were constructed.

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Description

This data set consists of digital polygons of constant hydraulic conductivity values for the High Plains aquifer in Oklahoma. This area encompasses the panhandle counties of Cimarron, Texas, and Beaver, and the western counties of Harper, Ellis, Woodward, Dewey, and Roger Mills. The High Plains aquifer underlies approximately 7,000 square miles of Oklahoma and is used extensively for irrigation. The High Plains aquifer is a water-table aquifer and consists predominately of the Tertiary-age Ogallala Formation and overlying Quaternary-age alluvial and terrace deposits. In some areas the aquifer is absent and the underlying Triassic, Jurassic, or Cretaceous-age rocks are exposed at the surface. These rocks are hydraulically connected with the aquifer in some areas. The High Plains aquifer is composed of interbedded sand, siltstone, clay, gravel, thin limestones, and caliche. The proportion of various lithological materials changes rapidly from place to place, but poorly sorted sand and gravel predominate. The rocks are poorly to moderately well cemented by calcium carbonate. The High Plains aquifer was divided into three zones with each zone having an assigned hydraulic conductivity that was used as input to a ground-water flow model on the High Plains aquifer. These values are 8.3 feet per day for the west zone, 16.2 feet per day for the central zone, and 19.3 feet per day for the east zone. The polygon boundaries and constant hydraulic conductivity values were constructed by extracting lines from digital surficial geology data sets based on a scale of 1:125,000 for the panhandle counties and 1:250,000 for the western counties. Some of the lines were digitized from maps in a published water-level elevation map for 1980. Ground-water flow models are numerical representations that simplify and aggregate natural systems. Models are not unique; different combinations of aquifer characteristics may produce similar results. Therefore, values of hydraulic conductivity used in the model and presented in this data set are not precise, but are within a reasonable range when compared to independently collected data.

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Description

This dataset allows students, graduates of the U.S. Merchant Marine Academy and participants/graduates of the Student Incentive Payment (SIP) Program at the State Maritime Academies (SMA) to complete the required annual Compliance Report for the period of their service obligation following graduation. The related application also assists MARAD in monitoring and documenting student's enrollment status while attending the maritime academies, making subsidy payments to SMA SIP students, and maintaining a record of the maritime academy graduates fulfillment of their service obligations. The MSCS also contains the graduate's employment determination waivers

Summary

Description

High resolution vegetation polygons mapped by the National Park Service. To produce the digital map, 1:12,000-scale true color digital ortho-imagery acquired in 2004 and 2006 by the U.S. Department of Agriculture - Farm Service Agencys Aerial Photography Field Office and the National Agriculture Imagery Program (NAIP) were used. In the end, 38 map units (21 vegetated and 17 land use) were developed and directly cross-walked or matched to their corresponding plant associations and land use classes. Draft maps were printed, field tested, reviewed, and revised.

Summary

Description

This metadata is for all coverages associated with the vegetation land cover and land use geospatial database for Badlands National Park and surrounding areas. The project is authorized as part of the USGS/NPS Vegetation Mapping Program http://biology.usgs.gov/npsveg. The program is being administered by the Biological Resources Division (BRD) of the United States Geological Survey (USGS). The USGS/BRD is responsible for overall management and oversight of all ongoing mapping efforts. This mapping effort was performed by the US Bureau of Reclamation's (USBR) Remote Sensing and GIS Group, Technical Service Center, Denver, CO. The vegetation mapping program is part of a larger Inventory and Monitoring (I&M) program started by the National Park Service (NPS) Their website is: http://science.nature.nps.gov/im/index.cfm

Summary

Description

The Tillamook Bay subbasins and Nehalem River basins encompass 1,369 and 2,207 respective square kilometers of northwestern Oregon and drain to the Pacific Ocean. The Tillamook, Trask, Wilson, Kilchis, and Miami Rivers flow into Tillamook Bay near the towns of Tillamook and Garibaldi. The Wilson and Trask River basins cover the largest areas (500 and 451 square kilometers, respectively) whereas the Tillamook and Kilchis Rivers encompass similar sized areas (156 and 169 square kilometers, respectively) and the Miami River the smallest area (94 square kilometers). In cooperation with the U.S. Army Corps of Engineers, the U.S. Geological Survey completed a reconnaissance-level assessment of channel condition and bed-material transport relevant to the permitting of in-stream gravel extraction along the the major alluvial portions of six river systems, including the lowermost 14.1 km of the Tillamook River, 16.3 km of the Trask River, 15.2 km of the Wilson River, 7.8 km of the Kilchis River, 11.6 km of the Miami River, and 31.4 km of the Nehalem River. To support these analyses, digital channel maps were produced to depict channel and floodplain conditions in the Tillamook Bay sub-basins and Nehalem River basin from different time periods. GIS layers defining the wetted channel and bar features and channel centerline in the study area were developed for four time periods: 1939, 1967, 2005, and 2009. For this project, the active channel was defined as area typically inundated during annual high flows, and includes the low-flow channel as well as side channels, islands, and channel-flanking gravel bars. The wetted channel and bar feature datasets were developed by digitizing from aerial photographs. Aerial photographs from 1939 and 1967 were scanned, rectified, and mosaicked for this project (See metadata for each photograph set for more information on the rectification process and resolution of each dataset). Digital orthophotographs from 2005 and 2009 are publicly available.

Summary

Description

The water and wastewater lines were compiled from utility lines collected with GPS equipment in the summer of 2003 and then merged with older water line data originating from blueprints (Potable Water and Fire Protection Lines Blueprint #381/41002A sheet 2 of 11) provided by the LIBI staff and softcopy data available from the US Census Bureau. Originally the Little Bighorn Battlefield National Monument (LIBI) GIS program was created from academic research and coursework in the Department of Economics and Geography, United States Air Force Academy (USAFA). Some of the GIS data was brought up-to-date or supplemented with GPS data in 2003 collect by NPS employees.

Summary

Description

A first-surface elevation map was produced cooperatively from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS) and National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Airborne Topographic Mapper (ATM), a scanning lidar system that measures high-resolution topography of the land surface. The ATM system is deployed on a Twin Otter or P-3 Orion aircraft and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. For more information on Lidar science and the Experimental Advanced Airborne Research Lidar (EAARL) system and surveys, see http://ngom.usgs.gov/dsp/overview/index.php and http://ngom.usgs.gov/dsp/tech/eaarl/index.php .

Summary

Description

This dataset is one of eight datasets produced by this study. Four of the datasets predict the probability of detecting atrazine and(or) desethyl-atrazine (a breakdown product of atrazine) in ground water in Colorado; the other four predict the probability of detecting elevated concentrations of nitrate in ground water in Colorado. The four datasets that predict the probability of atrazine and(or) desethyl-atrazine (atrazine/DEA) are differentiated by whether or not they incorporated atrazine use and whether or not they incorporated hydrogeomorphic regions. The four datasets that predict the probability of elevated concentrations of nitrate are differentiated by whether or not they incorporated fertilizer use and whether or not they incorporated hydrogeomorphic regions. Each of the eight datasets has its own unique strengths and weaknesses. The user is cautioned to read Rupert (2003, Probability of detecting atrazine/desethyl-atrazine and elevated concentrations of nitrate in ground water in Colorado: U.S. Geological Survey Water-Resources Investigations Report 02-4269, 35 p., http://water.usgs.gov/pubs/wri/wri02-4269/) to determine if he(she) is using the most appropriate dataset for his(her) particular needs. This dataset specifically predicts the probability of detecting elevated concentrations of nitrate in ground water in Colorado with hydrogeomorphic regions included and fertilizer use not included. The following text was extracted from Rupert (2003). Draft Federal regulations may require that each State develop a State Pesticide Management Plan for the herbicides atrazine, alachlor, metolachlor, and simazine. Maps were developed that the State of Colorado could use to predict the probability of detecting atrazine/DEA in ground water in Colorado. These maps can be incorporated into the State Pesticide Management Plan and can help provide a sound hydrogeologic basis for atrazine management in Colorado. Maps showing the probability of detecting elevated nitrite plus nitrate as nitrogen (nitrate) concentrations in ground water in Colorado also were developed because nitrate is a contaminant of concern in many areas of Colorado. Maps showing the probability of detecting atrazine/DEA at or greater than concentrations of 0.1 microgram per liter and nitrate concentrations in ground water greater than 5 milligrams per liter were developed as follows: (1) Ground-water quality data were overlaid with anthropogenic and hydrogeologic data by using a geographic information system (GIS) to produce a dataset in which each well had corresponding data on atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well construction. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Relations were observed between ground-water quality and the percentage of land-cover categories within circular regions (buffers) around wells. Several buffer sizes were evaluated; the buffer size that provided the strongest relation was selected for use in the logistic regression models. (3) Relations between concentrations of atrazine/DEA and nitrate in ground water and atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well-construction data were evaluated, and several preliminary multivariate models with various combinations of independent variables were constructed. (4) The multivariate models that best predicted the presence of atrazine/DEA and elevated concentrations of nitrate in ground water were selected. (5) The accuracy of the multivariate models was confirmed by validating the models with an independent set of ground-water quality data. (6) The multivariate models were entered into a geographic information system and the probability GRIDS were constructed.

Summary

Description

This data set consists of digital water-table contours for the Mojave River, the Morongo and the Fort Irwin Ground-Water Basins. The U.S. Geological Survey constructed a water-table map of the Mojave River, the Morongo and the Fort Irwin Ground-Water Basins for ground-water levels measured during the period January-September 1996. Water-level data were collected from 632 wells to construct the contours. The water-table contours were digitized from the paper map which was published at a scale of 1:175,512. The contour interval ranges from 3,400 to 1,550 feet above sea level.

Summary

Description

HPMS compiles data on highway network extent, use, condition, and performance. The system consists of a geospatially-enabled database that is used to generate reports and provides tools for data analysis. Information from HPMS is used by many stakeholders across the US DOT, the Administration, Congress, and the transportation community.

Summary

Description

An Innerspace 456 single-beam echosounder in conjunction with a Trimble® differential Global Positioning System (DGPS), HYPACK® navigation software, and Ashtech Z-Xtreme and Trimble® R8 Global Navigation Satellite System (GNSS) receivers was used to survey 7 chutes and 3 backwaters on the Missouri River yearly from 2011-13. These chutes and backwaters are located on the Missouri River between Newcastle, Nebraska and Rulo, Nebraska in the States of Nebraska, Iowa, and Missouri. Surveys of chutes consisted of topographic and bathymetric data collected along transects spaced 30.48 m apart from high bank to high bank. Surveys of backwaters consisted of topographic and bathymetric data collected along a transect grid of 76.2 m spacing. The data were collected by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers (USACE) Omaha District as part of the Missouri River Habitat Assessment and Monitoring Program.

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Description

Aged accounts receivable report

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Description

A part of the 2014 round of public opinion surveys implemented by LAPOP, the Guyana survey was carried out between June 4th and July 12th of 2014. It is a follow-up of the national surveys of 2006, 2009, 2010 and 2012. The 2014 survey was conducted by Vanderbilt University with the field work being carried out by Development Policy and Management Consultants (DPMC). The 2014 AmericasBarometer received generous support from many sources, including USAID, UNDP, IADB, Vanderbilt U., Princeton U., Université Laval, U. of Notre Dame, among others.

Summary

Description

HPMS compiles data on highway network extent, use, condition, and performance. The system consists of a geospatially-enabled database that is used to generate reports and provides tools for data analysis. Information from HPMS is used by many stakeholders across the US DOT, the Administration, Congress, and the transportation community.