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Data Releases

The data collected and the techniques used by USGS scientists should conform to or reference national and international standards and protocols if they exist and when they are relevant and appropriate. For datasets of a given type, and if national or international metadata standards exist, the data are indexed with metadata that facilitates access and integration.

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Statistical predictions of typical well depths and related spatial diagnostics for two hydrogeologic frameworks through blending cubist and generalized additive statistical models for the Chicot aquifer system, southwestern Louisiana, from the covCHICOTla Statistical predictions of typical well depths and related spatial diagnostics for two hydrogeologic frameworks through blending cubist and generalized additive statistical models for the Chicot aquifer system, southwestern Louisiana, from the covCHICOTla

This data release provides gridded predictions of “typical” well depth for the hydrogeologically complex Chicot aquifer system, southwestern Louisiana. These predictions were made using an applied statistical prediction modeling workflow named welldepmod_make.R (Asquith and Lindaman, 2025) to estimate groundwater well depths for two custom bundles (classifications) of local aquifer codes...

Land Use and Climate Covariate Values for Hexagon Tiles in the Central and Mississippi Flyways Between 1970-2019 Land Use and Climate Covariate Values for Hexagon Tiles in the Central and Mississippi Flyways Between 1970-2019

This data release contains a csv file of hexagon-tile specific summaries of several land use and climate variables that have been produced using R scripts. The hexagon tile grid spans the entire USA-portion of the Central and Mississippi Migratory Flyways and data has been extracted for the years 1979-2019.

Post-Optimization Scenarios for the Santa Barbara Groundwater Model, California Post-Optimization Scenarios for the Santa Barbara Groundwater Model, California

The city of Santa Barbara, in cooperation with the U.S. Geological Survey (USGS) California Water Science Center, developed a three-dimensional density-dependent groundwater-flow and solute-transport model (the Santa Barbara Flow and Transport Model; Paulinski and others, 2018; Nishikawa and others, 2018). The Santa Barbara Flow and Transport Model met the objectives of estimating the

Great Lakes thiamine monitoring data 2024 Great Lakes thiamine monitoring data 2024

This data release includes thiamine concentration measurements from lake trout (Salvelinus namaycush) eggs and associated biological data (e.g., fish length, weight, sex) and capture location data (e.g., lake, coordinates, date of collection). Lake trout used in this dataset were collected during 2024 from across the Great Lakes and other inland lakes such as the Finger Lakes, New York...

Sediment core data from offshore Cascadia during field activities 2020-633-FA and 2021-636-FA Sediment core data from offshore Cascadia during field activities 2020-633-FA and 2021-636-FA

This data release contains sediment core data including core imagery, multi-sensor core logger (MSCL) data, and grainsize data. As part of a multi-year project focused on characterizing offshore marine geohazards (tsunamis, earthquakes, and landslides), the U.S. Geological Survey (USGS) Coastal and Marine Hazards and Resources Program is collaborating with MBARI to conduct research along...

Data release accompanying quantitative mineral resource assessment of lithium pegmatite deposits in the Northern Appalachian Orogen, USA Data release accompanying quantitative mineral resource assessment of lithium pegmatite deposits in the Northern Appalachian Orogen, USA

The area of study is restricted to the northern Appalachian region between latitudes 38N and 48N and longitudes 66W and 77W in the U.S. states of Maine, New Hampshire, Vermont, New York, Massachusetts, Connecticut, Rhode Island, Pennsylvania, and Delaware. This study (Wintzer and others, 2025) integrates data from several sources, including geologic, geochemical, geophysical, watershed...
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