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This Benthic Invertebrate Community Analysis dataset, a conceptual subgroup of the Lake Erie Ecological Investigations (LEEI) dataset, focuses on the benthic invertebrates sampled at Areas of Concern (AOCs) on Lake Erie. Per the Quality Assurance Project Plan (QAPP), the invertebrate samples were taken from sediments remaining from the sediment analysis. Identification of the invertebrates was completed by the same invertebrate taxonomist for both the 1998-2000 evaluation and 1986-87 historical evaluation (Smith et al. 1994) for increased consistency. Oligochaetes were identified to species if possible, chironomids were identified to genus, as adult specimens are needed for specific identification, and other taxa...
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.
This dataset was created to document the natural occurrence of helium and carbon dioxide throughout the United States. This dataset is sourced primarily from publicly available data from the Bureau of Land Management (BLM) Federal Helium Program and the U.S. Geological Survey (USGS). The Federal Helium Program, which originally began in 1925 under the U.S. Bureau of Mines (USBM) has analyzed thousands of gas samples during its history. These analyses were reported in several publications (Moore and Sigler, 1987; Hamak and Gage, 1992; Hamak and Sigler, 1991, 1993; Sigler, 1994; Hamak and Driskill, 1996; Gage and Driskill, 1998, 2003, 2005; Driskill, 2008), and additional unpublished data residing in an internal BLM...
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).
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.
Individual point estimates of stream density by juvenile salmonid species in two small tributaries to the Salmon River, Lake Ontario, New York were recorded. Enumeration of salmonid species was observed using a backpack electrofisher in order to identify fish species. Stream density estimates were calculated using stream width measurements taken at equally spaced transects. Comparisons of species densities between the two streams were analyzed to infer competition or segregation.
This dataset consists of historical estimates and future projections of land use and climate data summarized within the 1:100,000 National Hydrography Dataset Version 2 (NHDPlusV2) framework for catchments and upstream accumulated watersheds. Historical land use data are for the year 2005 and future land use projections are for the years 2030, 2060, and 2090. The projections offer a unique combination of thematic detail (17 land-use and land-cover classes). Historical climate estimates are averaged over the time period 1980-1999 and future climate projections are averaged over 20-year periods centered around the years 2030, 2060, and 2090. Climate data include seasonal measures of average air temperature (℃) and...
Digital hydrogeologic datasets were developed for the Greene 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.
Digital hydrogeologic datasets were developed for the Jamestown 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 (where present), 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 what was done in previous work.
This Sediment Analysis dataset, a conceptual subgroup of the Lake Erie Ecological Investigations (LEEI) dataset, focuses on the sediments sampled at Areas of Concern (AOCs) on Lake Erie. Per the Quality Assurance Project Plan (QAPP), sediment collections were a composite of at least five randomly selected samples collected from each site. Per an internal summary report, sediment samples were collected using a stainless steel Eckman dredge. Analytical methods and QA/QC were directed by the Patuxent Analytical Control Facility (PACF) of the US Fish and Wildlife Service. Per Dora Passino-Reader, the Geochemical & Environmental Research Group at Texas A&M University, College Station performed the analytical chemistry...
This dataset includes georeferenced TIFF files from two separate reports for the Fishkill and Wappinger Falls 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.
This dataset includes georeferenced tiff files from two separate reports for the Greene study area, where appropriate data 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
This dataset includes georeferenced tiff files from two separate reports for the Cortland 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
This dataset includes georeferenced tiff files from three separate reports for the Rondout Neversink 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.
Supplementary Points for the Fishkill and Wappinger Falls sourcewater study area in upstate New York
This dataset includes "smoothing points" used in the creation of the Fishkill and Wappinger Falls hydrogeologic framework. Smoothing points were manually added and were used to enhance interpolated layers using geologic assumptions and include: valley edge points, report points, and upland bedrock SSURGO points.
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