Water Resources
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The USGS Water Resources Mission Area provides water information that is fundamental to national and local economic well-being, protection of life and property, and effective management of the Nation’s water resources. Below, find data and tools relevant to a wide range of water resources and conditions including streamflow, groundwater, water quality, and water use and availability.
USGS Water Data for the Nation
Access to water data collected at approximately 1.9 million sites
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Groundwater data, predictor variables, and rasters used for predicting redox conditions in the glacial aquifer, northern continental United States
This data release contains input data used in model development and TIF raster files used to predict the probability of low dissolved oxygen (DO) and high dissolved iron (Fe) in groundwater within the glacial aquifer system in the northern continental United States. Input data include measured DO and Fe concentrations at groundwater wells, and associated predictor variable data.
Data from USGS National Water Quality Laboratory methods used to calculate and compare detection limits estimated using single- and multi-concentration spike-based and blank-based procedures
This dataset provides the expected and determined concentrations of selected inorganic and organic analytes for spiked reagent-water samples (calibration standards and limit of quantitation standards) that were used to calculate detection limits by using the United States Environmental Protection Agency's (USEPA) Method Detection Limit (MDL) version 1.11 or 2.
The Measurement of Water Column Methylmercury Production Potential Rates in Four Oxygenated Reservoirs of the San Francisco Bay Watershed
Valley Water (formerly Santa Clara Valley Water District) provides stream stewardship, wholesale water supply, and flood protection for Santa Clara County, California, in the southern San Francisco Bay Area.
Geo-referenced orthophotographs of the Snow River, Alaska, acquired September 1, 2018
This data release consists of orthophotographs of the Snow River in Alaska acquired on September 1, 2018. The orthophotographs were produced from images obtained using a Hasselblad A6D-100C 100 megapixel digital mapping camera deployed within a pod mounted on the landing gear of a Robinson R44 helicopter.
Wetland Water Quality Data for West Twin Creek, AK, Allequash Creek, WI, and Big Thompson River, CO, 2013-2019
This dataset includes discrete water quality and discharge data for three streams that flow through wetlands. There are two measurement and sampling locations on each stream: one immediately upstream from the wetland and one immediately downstream from the wetland.
Biomass accrual and trace-element concentrations in water and periphytic algae at select locations in the Clark Fork and Blackfoot Rivers, Montana, 2015.
The U.S. Geological Survey monitored algal biomass accrual and concentrations of metals and other trace elements in stream water and periphytic algae at 3-4 day intervals over a 2-week period at 3 locations within the upper and middle portions of the mining-impacted Clark Fork River, Montana, and at one location on the relatively unimpacted Blackfoot River tributary.
Priority Ecosystem Science Program: benthic community and bivalve metrics data in Grizzly Bay and San Pablo Bay (2019-20)
Sediments and sediment transport influence the physical habitat and the ecology of the San Francisco Bay estuary. Bed sediments provide habitat for benthic organisms and the transport of sediment transports nutrients and contaminants throughout the San Francisco Bay.
Field measurements of flow depth and optical image sequences acquired from the Salcha River, Alaska, on July 25, 2019
This data release includes field measurements of flow depth and optical image sequences acquired from the Salcha River in Alaska on July 25, 2019. These data were used to develop and test a spectrally based remote sensing technique for estimating water depth from passive optical image data.
Data Release for Evaluation of Six Methods for Correcting Bias in Estimates from Ensemble Tree Machine Learning Regression Models
Ensemble-tree machine learning (ML) regression models can be prone to systematic bias: small values are overestimated and large values are underestimated. Additional bias can be introduced if the dependent variable is a transform of the original data.
Regional flood skew for parts of the mid-Atlantic region (hydrologic unit 02) in eastern New York and Pennsylvania
This data release contains annual peak-flow data through the 2013 water year, specification and output files from flood-frequency analysis of the annual peak-flow data in USGS PeakFQ software, a GIS shapefile of the basin polygons with attributes of site information, basin characteristics, results of flood-frequency analysis, and results of B-WLS/B-GLS analysis of skewness of the annual peak...
Water quality of samples collected in the Russian River Watershed (2017-2019)
The Russian River watershed is an important resource for drinking water and recreation. Sonoma Water relies on the Russian River to provide drinking water to over 620,000 Sonoma County and Marin, CA residents. Nearly 1 million visitors enjoy numerous recreational opportunities on the Russian River annually.
Modeled Stream Metabolism in Boulder Creek near Boulder, CO (2016 - 2018)
The data presented here was collected adjacent to USGS stream gage 06730200 and includes both observed and modeled values. Dissolved oxygen, dissolved carbon dioxide, stream depth, water temperature, and light intensity were collected via passive water quality sensors.