Filters: Tags: New York (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,
Site-specific multiple linear regression models were developed for one beach in Ohio (three discrete sampling sites) and one beach in Pennsylvania to estimate concentrations of Escherichia coli (E. coli) or the probability of exceeding the bathing-water standard for E. coli in recreational waters used by the public. Traditional culture-based methods are commonly used to estimate concentrations of fecal indicator bacteria, such as E. coli; however, results are obtained 18 to 24 hours post sampling and do not accurately reflect current water-quality conditions. Beach-specific mathematical models use environmental and water-quality variables that are easily and quickly measured as surrogates to estimate concentrations...
From August 2018 to October 2019, the U.S. Geological Survey collected spatially high-resolution water quality data as part of five shoreline synoptic surveys around the perimeters of Owasco, Seneca, and Skaneateles Lakes within the Finger Lakes Region of New York. Water-quality data were collected just below water surface utilizing YSI EXO2 multiparameter sondes and portable nitrate sensors paired with real-time GPS data as part of a HABs monitoring program in the Finger Lakes. In October 2019, water-quality data collection was paired with discrete phytoplankton grab samples on Owasco Lake and Seneca Lake. Phytoplankton grab samples were collected just below water surface with a peristaltic pump at twelve locations...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Aquatic Biology,
Contaminants, HABS,
Finger Lakes,
Limnology,
New York,
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,
The dwarf wedgemussel (Alasmidonta heterodon) is a federally endangered freshwater mussel that once ranged from New Brunswick to North Carolina, but now only exists in isolated populations throughout its diminished range. This study aimed to understand links between fish abundance and dwarf wedgemussel abundance and occurrence in the Connecticut and Delaware watersheds. Specifically, my study objectives were to 1) characterize fish assemblages near dwarf wedgemussel locations and unoccupied locations, 2) determine if dwarf wedgemussel occurrence and abundance are related to abundance of the known host fish species, tessellated darter and other potential host fish species per St. John White et. al. (2017). Two fish...
This U.S. Geological Survey (USGS) data release contains meteorological, water temperature, light (photosynthetically active radiation and illumination), and multichannel fluorescence sensor data from the Finger Lakes Region of New York, during the fall of 2018 and the summer and fall of 2019 and 2020. It also includes all sensor data and associated discrete sample data, at the near surface (top), mid-depth (middle) and near bottom (bottom) depths. Data were collected from three Advanced Monitoring Pilot study platforms in open water at Seneca Lake (USGS station number 425027076564401), Owasco Lake (USGS station number 425327076313601), and Skaneateles Lake (USGS station number 425606076251601) in 2018 and 2019,...
This child item dataset contains a shapefile of locations where USGS benchmarks were installed along the Old Erie Canal. This data release contains spatial datasets of bathymetry, water velocity, water quality, and infrastructure of a 30.8 mile reach of the Old Erie Canal between the Town of DeWitt and its junction with the current Erie Canal of the New York State Canal System in Verona, near Rome, New York during 2018 and 2019.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: ADCP,
Groundwater and Streamflow Information,
Madison County,
New York,
Old Erie Canal,
In cooperation with the New York City Department of Environmental Protection (NYC DEP), the U.S. Geological Survey (USGS) collected water and bed sediment samples along Alley Creek (Queens, New York) to help determine likely sources of fecal bacteria to the creek and Little Neck Bay. Potential terrestrial sources include stormwater, sewage via combined sewer overflow (CSO) and compromised infrastructure, bed-sediment resuspension, and groundwater discharge. Host sources that were targeted using microbial source tracking (MST) techniques included human, canine, waterfowl, and general Bacteroides. Routine water samples were collected and analyzed for the fecal indicator bacteria enterococci and fecal coliform, along...
Categories: Data;
Tags: Alley Creek,
Contaminants, Microbial,
Ecological Assessment of Human and Natural Impacts,
Hydrology,
New York,
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 data release contains input data used in model development and TIF raster files used to predict the probability of high arsenic (As) and high manganese (Mn) in groundwater within the glacial aquifer system in the northern United States. Input data include measured As and Mn concentrations at groundwater wells, and associated predictor variable data. The probability of high As and high Mn was predicted using boosted regression tree methods using the gbm package in R version 4.0.0. The response variables for individual models were the occurrence of: (1) As >10 µg/L, and (2) Mn >300 µg/L. Water-quality data were compiled from three sources, as described in Wilson and others (2019): a compilation of data from numerous...
Fish tissue from 203 samples collected at five locations in the Niagara River Area of Concern in 2018 were analyzed for a wide range of analytes including Polychlorinated Biphenyls (PCBs), pesticides (E1 and E2), polycyclic aromatic hydrocarbons (PAH), organochlorine and other persistent organic compounds, metals, lipid and moisture. Over 230 analytes were analyzed in the tissue samples, including 160 PCB congeners. Fish tissues from a subset of the sites (n=40) were also analyzed for Dioxins and Furans. The data set includes a variety of laboratory quality assurance data including sample replicates, laboratory blank data, laboratory spike data, matrix spike recoveries, and replicate matrix spike recoveries.
Categories: Data;
Tags: Aquatic Biology,
Aquatic Community Health,
Contaminants, Organic,
Contamination and pollution,
Dioxins,
From April through September of 2018, water-quality data were collected at 35 locations from select tributaries, embayments, and nearshore lake locations along New York's portion of Lake Ontario in support of the 2018 Cooperative Science and Monitoring Initiative, the Great Lakes Restoration Initiative, and the Lakewide Action Management Plan. These data include environmental, replicate, and blank samples of nutrients, suspended solids, sodium, and chloride, as well as field measurements of physical parameters (temperature, specific conductance, dissolved oxygen, pH, turbidity, phycocyanin relative fluorescence, chlorophyll relative fluorescence, photosynthetically active radiation, and phycocyanin:cholorphyll...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Cayuga County,
Hydrology,
Jefferson County,
Lake Ontario,
Monroe County,
A digital representation of closed depression features overlying and adjacent to New York’s carbonate-bedrock aquifers. Includes closed depressions that are both natural and anthropogenic in origin. The features were derived from a digital contour database obtained from https://topotools.cr.usgs.gov/contour_data.php. The original contour dataset was generated from the National Elevation Dataset (NED) and the National Hydrography Dataset (NHD) in a fully automated process. The process is described in U.S. Geological Survey Scientific Investigations Report 2012–5167.
From May of 2015 through September of 2018, velocity data were collected along 7 transects from select tributaries, embayments, and nearshore lake locations along New York's Lake Ontario waterfront in support of the Great Lakes Restoration Initiative and the Lakewide Action Management Plan. These data include: depth, velocity magnitude, velocity direction, navigational data, ADCP temperature, and channel profile.
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.
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