Filters: Tags: Water Use and Availability Science (X) > partyWithName: U.S. Geological Survey (X)
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Using publicly available data for Albany and Schenectady counties, New York, a series of geospatial overlays were created at 1:24,000 scale to examine the bedrock geology, groundwater table, soils, and surficial geology. Bedrock and surficial geology were refined using extant bedrock maps, well and borehole data from water- and gas-wells, soil data, and lidar data. Groundwater data were collected from New York State Department of Environmental Conservation and U.S. Geological Survey water-well databases to estimate the groundwater table. Soil data were used to examine soil thickness over bedrock and infiltration. An inventory of closed depressions was created using reconditioned lidar-derived bare-earth digital...
Using publicly available data for Erie and Niagara counties, New York, a series of geospatial overlays were created at 1:24,000 scale to examine the bedrock geology, groundwater table, soils, and surficial geology. Bedrock and surficial geology were refined using extant bedrock maps, well and borehole data from water- and gas-wells, soil data, and lidar data. Groundwater data were collected from New York State Department of Environmental Conservation and U.S. Geological Survey water-well databases to estimate the groundwater table. Soil data were used to examine soil thickness over bedrock and infiltration. An inventory of closed depressions was created using reconditioned lidar-derived bare-earth digital elevation...
Publicly available geospatial data were identified, collated, and analyzed for a region of karst terrain extending from Albany to Buffalo, New York. A series of geospatial datasets were assembled to determine the location and extent of karstic rock; bedrock geology and depth to bedrock; average water-table configuration; surficial geology; soil type, thickness, and hydraulic conductivity; land cover; and closed depressions in the land surface First release: 2021 Revised: July 2022 (ver. 2.0) Revised: October 2022 (ver. 3.0) Revised: January 2024 (ver. 4.0)
Categories: Data Release - Revised;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Albany County,
Aquifer Mapping,
Basin & Hydrogeologic Characterization,
Buffalo,
Livingston County,
The U.S. Geological Survey in cooperation with the New York State Department of Environmental Conservation, the Tug Hill Commission, the Jefferson County Soil and Water Conservation District, the Oswego County Soil and Water Conservation District, and the Tug Hill Land Trust studied the northern and central parts of the Tug Hill glacial aquifer to help communities make sound decisions about the groundwater resource. This child item dataset contains locations of water level contours for the northern and central parts of the Tug Hill aquifer.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Aquifer,
Aquifer Mapping,
Groundwater,
Hydrogeologic Characterization,
Jefferson County,
This dataset includes spreadsheets with statistical data (mean and median absolute error) used in deciding which interpolation method best fit the corresponding dataset. All statistical data were paired with a visual inspection of the interpolation prior to determining the final raster product. All spreadsheets were generated using an automated python script (Jahn, 2020).
This dataset includes well logs used in the creation of the Cortland hydrogeologic framework. Well logs were used from multiple sources (DEC, DOT, NWIS) and were a crucial component in generating hydrogeologic layer elevations and thicknesses. Well logs are available in their original form on GeoLog Locator (https://webapps.usgs.gov/GeoLogLocator/#!/) and provided here in the digitized form (shapefiles and feature classes), which were used in the generation of the hydrogeologic framework.
Digital hydrogeologic datasets were developed for the Rondout-Neversink study area in upstate New York in cooperation with the New York State Department of Environmental Conservation. These datasets define the hydrogeologic framework of the valley-fill aquifer and surrounding till-covered uplands within the study area. Datasets include: bedrock elevation raster, lacustrine silt and clay top and bottom elevation rasters, lidar minimum elevation raster, lacustrine extent polygon, valley-fill extent polygon, and surficial geology polygons. Elevation layers were interpolated at 125-foot discretization to match the model grid cell size.
This dataset includes well logs used in the creation of the Olean hydrogeologic framework. Well logs were used from multiple sources (DEC, DOT, NWIS, ESOGIS, and recently digitized archived material) and were a crucial component in generating hydrogeologic layer elevations and thicknesses. Well logs are available in their original form on GeoLog Locator (https://webapps.usgs.gov/GeoLogLocator/#!/) and provided here in the digitized form (shapefiles and feature classes), which were used in the generation of the hydrogeologic framework.
This dataset includes "smoothing points" used in the creation of the Jamestown hydrogeologic framework. Smoothing points were manually added and were used to enhance interpolated layers using geologic assumptions and include: valley edge points, centerline bedrock points, and upland bedrock SSURGO points.
The town of Greene is located in Chenango County, New York. Previous USGS reports here include Open-File Report 2003-242 (Hetcher and others, 2003), and Scientific Investigations Map 2914 (Hetcher-Aguila and Miller, 2005). The five child pages below break the data up into georeferenced and digitized previous report data, interpreted geologic information, well logs, supplemental point data, and interpolation statistics.
This child item dataset contains a shapefile of bedrock elevation contours in the Oneonta, NY area.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Aquifer Mapping,
Basin & Hydrogeologic Characterization,
Colliersville,
Delaware County,
Emmons,
This child item dataset contains a shapefile of the project study area in parts of Otsego and Delaware Counties, New York
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Aquifer Mapping,
Basin & Hydrogeologic Characterization,
Colliersville,
Delaware County,
Emmons,
This child item dataset contains a shapefile of inferred dead-ice sink locations in the Oneonta, NY area.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Aquifer Mapping,
Basin & Hydrogeologic Characterization,
Colliersville,
Delaware County,
Emmons,
This child item dataset contains a single horizontal-to-vertical spectral ratio (HVSR) measurement from Delaware County, New York, DHVSR8. Raw and processed HVSR data for this HVSR measurement are included in a zipped directory named by the measurement site identifier. The HVSR data-collection sites are designated by a county sequential numbering system (DHVSR8, etc. where "D" indicates Delaware County).
The U.S. Geological Survey (USGS) is providing a polygon feature class delineating the extent of Glacial Lake Great Bend within the Binghamton East 1:24,000 quadrangle of south-central Broome County, New York, 2020. The shapefile was created and intended for use with geographic information system (GIS) software. A companion report, USGS Scientific Investigations Report 2021-5026 (Van Hoesen and others, 2021; https://doi.org/10.3133/sir20215026) further describes data collection and map preparation.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Aquifer Mapping,
Basin & Hydrogeologic Characterization,
Broome County,
Conklin,
Kirkwood,
The U.S. Geological Survey (USGS) is providing a polygon feature class containing the approximate locations and confining units of the unconfined and confined aquifers within the Binghamton East 1:24,000 quadrangle of south-central Broome County, New York, 2020. The shapefile was created and intended for use with geographic information system (GIS) software. A companion report, USGS Scientific Investigations Report 2021-5026 (Van Hoesen and others, 2021; https://doi.org/10.3133/sir20215026) further describes data collection and map preparation.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Aquifer Mapping,
Basin & Hydrogeologic Characterization,
Broome County,
Conklin,
Kirkwood,
This child item dataset contains a shapefile of labels for hydrogeologic sections illustrated in Heisig, 2023 (figure 3, plate 1). The "Sec_ID" attribute lists letter-number designations for the ends of each section. Hydrogeologic section labels are in the format x - x'. By convention, the x is on the west side and the x' is on the east side of generally horizontal sections. In generally vertical sections, the x is the westernmost of the section ends and the x' is the eastermost end of the section line.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Aquifer Mapping,
Basin & Hydrogeologic Characterization,
Cayuga County,
Freeville,
Groton,
This child item dataset contains a single horizontal-to-vertical spectral ratio (HVSR) measurement from Orange County, New York, for 39 measurements, OHVSR1 through OHVSR39. Raw and processed HVSR data for this HVSR measurement are included in a zipped directory named by the measurement site identifier. The HVSR data-collection sites are designated by a county sequential numbering system (OHVSR1, OHVSR2, etc. where "O" indicates Orange County).
This dataset includes spreadsheets with statistical data (mean and median absolute error) used in deciding which interpolation method best fit the corresponding dataset. All statistical data were paired with a visual inspection of the interpolation prior to determining the final raster product. All spreadsheets were generated using an automated python script (Jahn, 2020).
This dataset includes spreadsheets with statistical data (mean and median absolute error) used in deciding which interpolation method best fit the corresponding dataset. All statistical data were paired with a visual inspection of the interpolation prior to determining the final raster product. All spreadsheets were generated using an automated python script (Jahn, 2020).
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