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Data

The USGS Water Resources Mission Area provides water information that is fundamental to our economic well-being, protection of life and property, and effective management of our water resources. Listed below are discrete data releases and datasets produced during our science and research activities. To explore and interact with our data using online tools and products, view our web tools.

Filter Total Items: 562

Mainstem Rivers of the Conterminous United States

Mainstem rivers are the backbone of a connected network of hydrologic units that cover the landscape. A mainstem connects a headwater source area to an outlet. This data release identifies the same mainstem paths in hydrographic datasets for the conterminous US. The Mainstems dataset includes cross walks between mainstem identifiers and several hydrographic datasets. These cross walk tables do no

Data to support water quality modeling efforts in the Delaware River Basin

This data release contains information to support water quality modeling in the Delaware River Basin (DRB). These data support both process-based and machine learning approaches to water quality modeling, including the prediction of stream temperature. Reservoirs in the DRB serve an important role as a source of drinking water, but also affect downstream water quality. Therefore, this data release

Select Groundwater-Quality and Quality-Control Data from the National Water-Quality Assessment Project 2019 to Present (ver. 3.0, November 2023)

Groundwater samples were collected and analyzed from 417 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water-Quality Program and the water-quality data and quality-control data are included in this data release. The samples were collected from three types of well networks: principal aquifer study networks, which are used to assess the quality

Discrete and high frequency water quality data for Allequash Creek, Wisconsin, WY 2019-2021

This data set is a compilation of discrete and high frequency water quality data from sites on Allequash Creek in Wisconsin, and within the Allequash Creek watershed, for the water years (WY) 2019-2021.

Data release for tempest1d: Recursive Estimation of Vertical Groundwater/Surface-Water Exchange using Heat Tracing

This data release provides a recursive-estimation framework to infer groundwater/surface-water exchange based on temperature time series collected at different vertical depths below the sediment/water interface. A heat-transport problem was formulated as a state-space model (SSM), in which the spatial derivatives in the convection/conduction equation are approximated using finite differences. The

National Atmospheric Deposition Program Pollen Study Data for 2021 Pollen Season

Pollen was measured in ambient air by several methods and in wet atmospheric deposition samples at three monitoring sites in the National Atmospheric Deposition Program (NADP) National Trends Network. A method for counting pollen on filters was developed and provided pollen counts for NADP atmospheric wet-deposition samples and high-volume ambient air samplers (HVAS) for comparison with co-located

A Two-Year Water-Column Time Series of Geochemical Data During a Limnological Shift in Mono Lake, California, 2017-2018

Mono Lake is a hypersaline (approximately 85 ppt), alkaline (pH 9.8), closed-basin lake located in the eastern Sierra Nevada Mountains of California, USA (38 degrees N, 119 degrees W). Water enters the lake primarily from snowmelt and exits by evaporation (approximately 1 m/yr). This hydrological condition, plus weathering reactions in the lake's tributaries, produce the uniquely high salinity and

Aqueous and Solid Phase Chemistry of Sequestration and Re-oxidation of Chromium in Experimental Microcosms with Sand and Sediment from Hinkley, CA

Cr(VI) contaminated groundwater at Hinkley is undergoing bioremediation using added ethanol as a reductant in a volume of the aquifer defined as the In-situ Reduction Zone (IRZ). This treatment effectively reduces Cr(VI) to Cr(III) which is rapidly sequestered by sorption to aquifer particle surfaces and by co-precipitation within iron or manganese bearing minerals forming in place as reduction pr

Lake Biogeochemical Model Output for One Retrospective and 12 Future Climate Runs in Northern Wisconsin & Michigan, USA

This dataset contains modeled daily lake area, volume, constituent mass, and biogeochemical rates for 3,692 lakes in the Northern Highlands Lake District (NHLD) for one retrospective model run (1986-2010) and 12 model runs under future climate scenarios. This dataset was created using published tools developed to simulate detailed hydrological and biogeochemical fluxes for thousands of lakes and r

Mainstem Rivers of the World based on MERIT hydrography and Natural Earth names

Mainstem rivers are the backbone of a connected network of hydrologic units that cover the landscape. A mainstem connects a headwater source area to an outlet. This data release identifies the same mainstem paths in hydrographic datasets for the world based on the MERIT hydrography and the Natural Earth river names. Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com.

Data and Model Archive for Preliminary Machine Learning Models of Manganese and 1,4-Dioxane in Groundwater on Long Island, New York

Data and preliminary machine-learning models used to predict manganese and 1,4-dioxane in groundwater on Long Island are documented in this data release. Concentration data used to develop the models were from 910 wells for manganese and 553 wells for 1,4-dioxane, primarily public supply wells, from U.S. Geological Survey, U.S. Environmental Protection Agency (USEPA), and Suffolk County Water Auth

Daily streamflow performance benchmark defined by the standard statistical suite (v1.0) for the National Water Model Retrospective (v2.1) at benchmark streamflow locations (ver. 2.0, December 2022)

This data release contains the standard statistical suite (version 1.0) daily streamflow performance benchmark results for the National Water Model Retrospective (v2.1) at streamflow benchmark locations (version 1.0) as defined by Foks and others (2022). Modeled hourly timesteps were converted to mean daily timesteps. Model error was determined by evaluating predicted daily mean streamflow versus
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