Data

These data are comprised of measurements of elements (e.g., uranium, cobalt, nickel, copper, zinc, cadmium, lead, etc.), major anions (chloride, nitrite+nitrate as nitrogen, sulfate, etc.), dissolved organic carbon, and general water quality characteristics in Canyon Mine containment pond water, sediment, vegetation and invertebrate samples collected in calendar year 2017.

This data release contains three different datasets that were used in the Scientific Investigations Report: Spatial and Temporal Distribution of Bacterial Indicators and Microbial Source Tracking within Tumacacori National Historical Park and the Upper Santa Cruz River, Arizona, 2015-16. These datasets contain regression model data, estimated discharge data, and calculated flux and yields data. R

The data presented includes chloride concentration and specific conductance in surface water collected from 33 wetlands in the Williston Basin of Montana and North Dakota, 2015-2017 as well as count data for three species of amphibians captured at each wetland. Data also includes concentrations of metals in bed sediment and larval amphibians collected from 32 and 12 wetlands, respectively in 2015-

The monthly ET data for the Upper Rio Grande River Basin from January 1984-December 2015 were created using the operational Simplified Surface Energy Balance (SSEBop) model to quantify and map ET over irrigated fields using Landsat imagery and associated weather datasets. The data are provided in GeoTIFF format and can be downloaded per month or year. Satelite-based ET is useful for several agr

Three regression models were developed for describing variability of host-specific flux data in eight Great Lakes tributaries. Models include one for Lachnospiraceae flux, one for human bacteroides flux, and one for ruminant bacteroides flux. Models were developed using the R project for statistical computing with core functionality and the survival, smwrBase, and smwrQW packages. Predictor variab

This Data Release contains geospatially-enabled geological data to accompany the Geologic Map of the Central Beaverhead Mountains, Lemhi County, Idaho, and Beaverhead County, Montana: U.S. Geological Survey Scientific Investigations Map 3413. This map portrays detailed geology of the central Beaverhead Mountains, printable at 1:50,000 scale. These data were collected between 1997 and 2017, and syn

This dataset contains the lithologic class and topographic position index information and quality-assurance and quality-control data not available in the online National Water Information System for 72 domestic wells sampled by the U.S. Geological Survey in Bradford County, Pennsylvania, May-August 2016. The topographic position index (TPI) for each well location was computed on the basis of a 25-

In cooperation with the South Carolina Department of Transportation, the U.S. Geological Survey developed a StreamStats web application (https://water.usgs.gov/osw/streamstats/) that provides analytical tools useful for water-resources planning and management (Ries and others, 2017). This data set presents the lidar-derived flow direction, flow accumulation, streamline, and hydro-enforced digital

In 2018 The U.S. Geological Survey, in cooperation with the U.S. Bureau of Reclamation and the Oklahoma Water Resources Board, published a calibrated numerical groundwater- flow model and associated model documentation report that evaluated the effects of potential groundwater withdrawals on groundwater flow and availability in the Rush Springs aquifer in western Oklahoma. The results of gr

Monthly Mean Dissolved-Solids Concentration and Monthly Mean Dissolved-Solids Load Data Flow weighted monthly mean dissolved-solids concentrations (mg/L) data and monthly mean dissolved-solids load data from 1928-2016 were computed by USGS using raw data from the Bureau of Reclamation. These data were computed by USGS for all of the seven sites (listed below). Colorado River above Imperial Dam,

Temperature data were collected from ~40 portable data (temperature) loggers and two weather stations located in central North Carolina, USA during August 2015. In addition to temperature, solar radiation and wind speed data were recorded at one of the sites to estimate the effects of these climate variables on sensor bias.

Forest surveys were conducted in nine 20 m x 25 m study plots, split into 3 representatives each for three forest types in Great Dismal Swamp, VA and NC, USA, December 2015 - February 2018. Trees, saplings, and shrubs were identified to species and measured for estimates of standing stocks. Standing stock data include: tree diameter at breast height (dbh), height, and condition; sapling dbh; shrub