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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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Electrical resistivity tomography data collected near a groundwater replenishment and reuse project, Yucca Valley, San Bernardino County, California, 2019

Hi-Desert Water District (HDWD) is constructing a wastewater treatment plant as part of a groundwater replenishment and reuse project (GRRP) in the east hydrogeologic unit (Nishikawa, and others, 2003) of the Warren Valley Basin (7-012) (California Department of Water Resources, 2016) in Yucca Valley, CA. The HDWD plans to use reclaimed wastewater for managed aquifer recharge by spreading treated

Oil and gas development potential in the US Intermountain West

We created a probabilistic classification model using the nonparametric machine learning technique 'Random Forests' for oil and gas development potential from low (0) to high (1) across the western US. The six predictor variables used in the model were: geophysical data showing aeromagnetic, isostatic gravity, and Bouguer gravity anomalies, geology, topography and bedrock depth. Our binary respons

Riparian vegetation, topography, and ground cover constituents along the Upper Colorado River near Moab, UT (2010-2017) (ver. 1.1, Jan 2023)

The data release presents observations of riparian vegetation, topography, and ground cover in two river reaches of the Upper Colorado River within a river segment extending 208 river kilometers (rkm), from near the Colorado/Utah border to the confluence of the Green River. Methods included field observations and analysis of the plant community five times over eight years in the fall of 2010, 2012

Coastal Multibeam Bathymetry Data Collected in 2019 off of Santa Rosa Island, Florida

The U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC), collected multibeam bathymetry data off the coast of Santa Rosa Island, Florida in June of 2019. The data was collected as part of the USGS Resource Evaluation for Management Applications (CREMA) project. This USGS Data Release includes the resulting processed elevation point data (XYZ) as derived from a 1-m

Coastal Bathymetry and Backscatter Data Collected in August 2019 from Cedar Island, Virginia

Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida (USGS SPCSMC), conducted a geophysical survey of Cedar Island, Virginia, August 2019. During this study, multibeam bathymetry and backscatter data were collected aboard the R/V Sallenger, while single-beam bathymetry were collected aboard a towed seismic sled. Efforts were support

Prediction grids of pH for the Mississippi River Valley Alluvial and Claiborne Aquifers

Groundwater is a vital resource to the Mississippi embayment region of the central United States. Regional and integrated assessments of water availability that link physical flow models and water quality in principal aquifer systems provide context for the long-term availability of these water resources. An innovative approach using machine learning was employed to predict groundwater pH across d

Time Series of Aerial Imagery from Small Unmanned Aircraft Systems and Associated Ground Control Points: Madeira Beach, Florida, July 2017 to June 2018

Aerial imagery acquired with a small unmanned aircraft system (sUAS), in conjunction with surveyed ground control points (GCP) visible in the imagery, can be processed with structure-from-motion (SfM) photogrammetry techniques to produce high-resolution orthomosaics, three-dimensional (3D) point clouds and digital elevation models (DEMs). This dataset, prepared by the U.S. Geological Survey (USGS)

Combined Occurrence Frequency of Wind Speeds and Precipitation Amounts Conducive to Dust Dispersion from Disturbed Mine and Mill Sites in the United States, 2007?16

Dispersion of dust depends on many complex factors related to the nature of the disturbed materials, climate, dust control measures, and localized weather patterns. This dataset presents wind speed and rainfall as climate factors that influence dust dispersion. These two basic factors were identified as a subset of the many factors that can lead to dust dispersion. Arpacioglu and Er (2003) reviewe

Photoluminescence Imaging of Whole Zircon Grains on a Petrographic Microscope - An Underused Aide for Geochronologic Studies

The refractory nature of zircon to temperature and pressure allows even a single zircon grain to preserve a rich history of magmatic, metamorphic, and hydrothermal processes. Isotopic dating of micro-domains exposed in cross-sections of zircon grains allows us to interrogate this history. Unfortunately, our ability to select the zircon grains in a heavy mineral concentrate that records the most ge

Water quality and gas fluxes of Interior Alaska (2014-2018)

This product consists of multiple tabular datasets and associated metadata of water quality information related to rivers, streams, and lakes in the Yukon River watershed between 2014 and 2018. This data release is apart of the National Aeronautics and Space Administration (NASA) funded Arctic-Boreal Vulnerability Experiment (ABoVE) and is an assessment of water quality and greenhouse gas fluxes w

Digitized datasets of the structure of Cenozoic and late Cretaceous strata along the Atlantic and Gulf Coastal Plains from Texas to New Jersey

This dataset consists of shapefiles that are digitized contours of the structure of Cenozoic and late Cretaceous strata along the Gulf and Atlantic Coastal plains from Texas to New Jersey, not including Maryland and Delaware. Well depths and seismic profiles indicating depth to or elevation of subsurface geologic contacts present in some datasets have also been digitized. Metadata files (.xml) des

Cladophora biomass and supporting data collected in the Great Lakes, 2019 (ver. 2.0, December 2023)

This dataset records Cladophora and associated submerged aquatic vegetation (SAV) biomass collected approximately monthly during the growing season of 2019 at stations located along the U.S. shoreline of Lakes Michigan, Huron, Erie, and Ontario. It also records a variety of supporting data collected at Cladophora measurement stations. These supporting data include: - seasonal time series of light,
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