Filters: partyWithName: Water Resources (X) > partyWithName: New York Water Science Center (X)
111 results (17ms)|
Filters
Date Range
Extensions Types
Contacts
Categories Tag Types
|
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...
This child item data set provides high-resolution, nearshore, spatial water-quality data collected from Owasco Lake, New York, on June 26 and October 8, 2019. All data are reported as raw measured values. Continuous water-quality monitors were mounted to a boat at approximately 0.5-meters below the water surface and used to measure nitrate, chlorophyll fluorescence (fChl), fluorescent dissolved organic matter (fDOM), dissolved oxygen, specific conductance, phycocyanin fluorescence (fPC), turbidity, pH, and temperature.
Categories: Data;
Tags: Contaminants, HABS,
Finger Lakes,
New York,
Owasco Lake,
Surface-Water Quality Monitoring,
This child item contains ground penetrating radar (GPR) data collected over a small alpine wetland between Mogul Mine and Cement Creek located near Silverton, Colorado. Mine-impacted water is transported to Cement Creek via surface channels and groundwater through this wetland. The GPR method transmits radar pulses into the ground and measures the returned amplitude from these pulses over time. Variations in subsurface electromagnetic (EM) properties (dielectric permittivity, electrical conductivity, and magnetic susceptibility) affect the timing and amplitude of returned radar energy. For example, variation in water or mineral content are physical properties that often influence the EM properties that are observed...
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).
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 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 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 child item dataset contains a shapefile that delineates the surficial geology of the Owasco Inlet watershed.
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 shapefile that delineates the Owasco Inlet watershed.
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 shapefile that delineates areas of known or inferred confined aquifers within the Owasco Inlet watershed.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Aquifer Mapping,
Basin & Hydrogeologic Characterization,
Cayuga County,
Freeville,
Groton,
This U.S. Geological Survey (USGS) data release contains phytoplankton classification and enumeration results from near-surface samples analyzed by imaging flow cytometry and collected as part of a harmful algae bloom (HAB) monitoring study conducted in collaboration with the New York State Department of Environmental Conservation (NYSDEC). Samples were collected biweekly from monitoring platforms in Owasco and Seneca Lakes and one bloom sample site at Emerson Park Boat Launch in Owasco Lake. The platforms were deployed from June-October in 2020. This dataset includes all routine and quality assurance/quality control samples collected at the three sampling locations. Phytoplankton were identified to the lowest possible...
Categories: Data;
Tags: Algae,
Algae,
Cayuga County,
Division,
Ecological Assessment of Human and Natural Impacts,
Using publicly available data for Ontario and Wayne 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...
This child item data set provides phytoplankton data collected from Owasco Lake, New York, on October 8, 2019. Phytoplankton were identified to the lowest possible taxonomic level, and abundance (density reported as both natural units and cells) and biovolume are reported. All data are reported as raw calculated values. This dataset includes all routine and quality assurance/quality control samples collected at twelve sampling locations on Owasco Lake.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Class,
Contaminants, HABS,
Division,
Family,
Finger Lakes,
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 georeferenced TIFF files from two separate reports for the Jamestown study area that have been digitized into feature classes within ArcGIS. Not all digitized and georeferenced data was necessarily used in the final interpolations, however they may have contributed to understanding the local hydrogeology.
|
|
