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This dataset contains an inventory of South Carolina U.S. Geological Survey (USGS) streamgages evaluated in 2017 as part of gage network gap assessment. Both continuous record and crest stage gages are included in this dataset. The data are grouped into three categories: rural streamgages with equal to or greater than 10 years of peak-flow data, rural streamgages with less than 10 years of peak-flow data, and urban streamgages.
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The natural resiliency of the New Jersey barrier island system, and the efficacy of management efforts to reduce vulnerability, depends on the ability of the system to recover and maintain equilibrium in response to storms and persistent coastal change. This resiliency is largely dependent on the availability of sand in the beach system. In an effort to better understand the system's sand budget and processes in which this system evolves, high-resolution geophysical mapping of the sea floor in Little Egg Inlet and along the southern end of Long Beach Island near Beach Haven, New Jersey was conducted from May 31 to June 10, 2018, followed by a sea floor sampling survey conducted from October 22 to 23, 2018, as part...
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These digital images were taken at select locations over the Potomac River using 3DR Solo unmanned aircraft systems (UAS) in October 2019. These images were collected for the purpose of evaluating UAS assessment of river habitat data such as water depth, substrate type, and water clarity. Each UAS was equipped with a Ricoh GRII digital camera for natural color photos, used to produce digital elevation models and ortho images, a MicaSense RedEdge multi-spectral camera that captures five specific bands of the visible spectrum (blue, green, red, rededge, and near-infrared), which can be used to classify vegetation, or FLIR Vue Pro R 640 13mm radiometric thermal camera that provides temperature data embedded in every...
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The natural resiliency of the New Jersey barrier island system, and the efficacy of management efforts to reduce vulnerability, depends on the ability of the system to recover and maintain equilibrium in response to storms and persistent coastal change. This resiliency is largely dependent on the availability of sand in the beach system. In an effort to better understand the system's sand budget and processes in which this system evolves, high-resolution geophysical mapping of the sea floor in Little Egg Inlet and along the southern end of Long Beach Island near Beach Haven, New Jersey was conducted from May 31 to June 10, 2018, followed by a sea floor sampling survey conducted from October 22 to 23, 2018, as part...
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This dataset includes audiomagnetotelluric (AMT) sounding data collected in July 2018 in the Silverton Caldera complex, Colorado, in the Southern Rocky Mountain Volcanic Field, by the U.S. Geological Survey (USGS). Along with geologic mapping, airborne magnetics, airborne electromagnetics, and magnetotellurics, the USGS collected AMT data at 24 sites along four profiles ranging from 3 to 6 kilometers in length across the north-western structural margin of the Silverton caldera in Mineral Basin (MB01-MB05), across the south-eastern margin of the caldera along Cunningham Creek (CC01-CC05), within the caldera in Eureka Graben (EG01-EG05), and within the caldera along upper Cement Creek near the Gold King mine (GK01-GK09).
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This dataset includes audiomagnetotelluric (AMT) sounding data collected in July 2018 in the Silverton Caldera complex, Colorado, in the Southern Rocky Mountain Volcanic Field, by the U.S. Geological Survey (USGS). Along with geologic mapping, airborne magnetics, airborne electromagnetics, and magnetotellurics, the USGS collected AMT data at 24 sites along four profiles ranging from 3 to 6 kilometers in length across the north-western structural margin of the Silverton caldera in Mineral Basin (MB01-MB05), across the south-eastern margin of the caldera along Cunningham Creek (CC01-CC05), within the caldera in Eureka Graben (EG01-EG05), and within the caldera along upper Cement Creek near the Gold King mine (GK01-GK09).
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This dataset includes audiomagnetotelluric (AMT) sounding data collected in July 2018 in the Silverton Caldera complex, Colorado, in the Southern Rocky Mountain Volcanic Field, by the U.S. Geological Survey (USGS). Along with geologic mapping, airborne magnetics, airborne electromagnetics, and magnetotellurics, the USGS collected AMT data at 24 sites along four profiles ranging from 3 to 6 kilometers in length across the north-western structural margin of the Silverton caldera in Mineral Basin (MB01-MB05), across the south-eastern margin of the caldera along Cunningham Creek (CC01-CC05), within the caldera in Eureka Graben (EG01-EG05), and within the caldera along upper Cement Creek near the Gold King mine (GK01-GK09).
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This dataset includes audiomagnetotelluric (AMT) sounding data collected in July 2018 in the Silverton Caldera complex, Colorado, in the Southern Rocky Mountain Volcanic Field, by the U.S. Geological Survey (USGS). Along with geologic mapping, airborne magnetics, airborne electromagnetics, and magnetotellurics, the USGS collected AMT data at 24 sites along four profiles ranging from 3 to 6 kilometers in length across the north-western structural margin of the Silverton caldera in Mineral Basin (MB01-MB05), across the south-eastern margin of the caldera along Cunningham Creek (CC01-CC05), within the caldera in Eureka Graben (EG01-EG05), and within the caldera along upper Cement Creek near the Gold King mine (GK01-GK09).
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This dataset includes magnetotelluric (MT) sounding data collected in July 2019 in the Silverton Caldera complex, Colorado, in the Southern Rocky Mountain Volcanic Field, by the U.S. Geological Survey (USGS). Along with geologic mapping, airborne magnetics, airborne electromagnetics, and audiomagnetotellurics, the USGS collected MT data at 24 sites along five profiles ranging from 2 to 5 kilometers in length: across Red Mountain of the Silverton caldera, within the caldera in Eureka Graben, across the south-eastern margin of the caldera along Arrastra Gulch, across the southern margin of the caldera along the western margin of Kendall Mountain, and across the south-western margin of the caldera along South Fork...
Tags: Animas River, Arrastra Gulch, Colorado, DOI, Department of the Interior, All tags...
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This dataset includes audiomagnetotelluric (AMT) sounding data collected in July 2019 in the Silverton Caldera complex, Colorado, in the Southern Rocky Mountain Volcanic Field, by the U.S. Geological Survey (USGS). Along with geologic mapping, airborne magnetics, airborne electromagnetics, and magnetotellurics, the USGS collected AMT data at 26 sites along five profiles ranging from 2 to 5 kilometers in length: across Red Mountain of the Silverton caldera, within the caldera in Eureka Graben, across the south-eastern margin of the caldera along Arrastra Gulch, across the southern margin of the caldera along the western margin of Kendall Mountain, and across the south-western margin of the caldera along South Fork...
Tags: AMT, Animas River, Arrastra Creek, Colorado, DOI, All tags...
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The Wetland Reserve Program (WRP) is a voluntary program administered by the NRCS. It provides technical and financial assistance to private landowners and Tribes to restore, protect, and enhance wetlands in exchange for retiring eligible land from agriculture. For a site to be a wetland eligible for restoration, it must be in a zone with sustained or frequent flooding for a period of 7 consecutive days on average at least once every 2 years (a value termed the 7MQ2). This study calculated the 7MQ2 flows for all the U.S. Geological Survey streamgages within the selected study reaches. These flows were related to the stage discharge tables for each streamgage and a corresponding elevation was determined. By use of...
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This dataset consists of 65 magnetotelluric (MT) stations collected in 2015 near Mountain Pass, California. The U.S. Geological Survey acquired these data to create a regional conductivity model near the Mountain Pass mine. This work is in support of characterizing mineral deposits.
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These data are U-Pb sensitive high-resolution ion microprobe (SHRIMP) geochronology data from quartz porphyry dikes for the study of the Butte mining district, U.S.A. Results of the study are described and interpreted in Lund and others (2018).
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This dataset consists of 102 magnetotelluric (MT) stations collected in 2012-2014 in the Rio Grande Rift and southern Rocky Mountains. The U.S. Geological Survey acquired these data to improve regional conductivity models of the western United States. This work is in support of studies of the effect of lithospheric modification on electrical resistivity structure and tectonic evolution of the western United States.
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This dataset consists of 102 magnetotelluric (MT) stations collected in 2012-2014 in the Rio Grande Rift and southern Rocky Mountains. The U.S. Geological Survey acquired these data to improve regional conductivity models of the western United States. This work is in support of studies of the effect of lithospheric modification on electrical resistivity structure and tectonic evolution of the western United States.
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This dataset consists of 102 magnetotelluric (MT) stations collected in 2012-2014 in the Rio Grande Rift and southern Rocky Mountains. The U.S. Geological Survey acquired these data to improve regional conductivity models of the western United States. This work is in support of studies of the effect of lithospheric modification on electrical resistivity structure and tectonic evolution of the western United States.
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The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color aerial orthoimagery and 2007 topographic lidar datasets obtained from the National Oceanic and Atmospheric Administration's Ocean Service, Coastal Services Center. This 2018 data release includes rates that incorporate...
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This dataset consists of 102 magnetotelluric (MT) stations collected in 2012-2014 in the Rio Grande Rift and southern Rocky Mountains. The U.S. Geological Survey acquired these data to improve regional conductivity models of the western United States. This work is in support of studies of the effect of lithospheric modification on electrical resistivity structure and tectonic evolution of the western United States.
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This dataset consists of 102 magnetotelluric (MT) stations collected in 2012-2014 in the Rio Grande Rift and southern Rocky Mountains. The U.S. Geological Survey acquired these data to improve regional conductivity models of the western United States. This work is in support of studies of the effect of lithospheric modification on electrical resistivity structure and tectonic evolution of the western United States.
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Fine-grained sediments, or “fines,” are nearly ubiquitous in natural sediments, even in the predominantly coarse-grained sediments that host gas hydrates. Fines within these sandy sediments can be mobilized and subsequently clog flow pathways while methane is being extracted from gas hydrate as an energy resource. Using two-dimensional (2D) micromodels to test the conditions in which clogging occurs provides insights for choosing production operation parameters that optimize methane recovery in the field. During methane extraction, several processes can alter the mobility and clogging potential of fines: (1) fluid flow as the formation is depressurized to release methane from gas hydrate, (2) shifting pore-fluid...


map background search result map search result map Station_rgr025 Station_rgr119 Station_rgr210 Station_rgr307 Station_rgr422 2D micromodel studies of pore-throat clogging by pure fine-grained sediments and natural sediments from NGHP-02, offshore India 1) U-Pb SHRIMP Age Data Potential Wetland Extent Along Wildcat Creek Between USGS Gaging Stations 03333450 and 03334000 Martha's Vineyard station mp346 Audiomagnetotelluric sounding data in the Silverton Caldera complex, Colorado, 2018; Station AMTCC04 Audiomagnetotelluric sounding data in the Silverton Caldera complex, Colorado, 2018; Station AMTGK01 Audiomagnetotelluric sounding data in the Silverton Caldera complex, Colorado, 2018; Station AMTGK06 Audiomagnetotelluric sounding data in the Silverton Caldera complex, Colorado, 2018; Station AMTGK07 Low-altitude aerial imagery from unmanned aerial systems (UAS) at select locations over the Potomac River, October 2019 Data for the Evaluation of the U.S. Geological Survey Streamgage Network in South Carolina, 2017 Audiomagnetotelluric sounding data in the Silverton Caldera complex, Colorado, 2019; Station AMTMB06 Station MTAG06; Magnetotelluric sounding data in the Silverton Caldera complex, Colorado, 2019 Chirp seismic reflection data from the Edgetech 512i collected in Little Egg Inlet and offshore the southern end of Long Beach Island, NJ, during USGS field activity 2018-001-FA (shotpoints point shapefile, survey trackline shapefile, PNG profile images, and SEG-Y trace data). Multibeam Echosounder, Reson T-20P tracklines collected in Little Egg Inlet and offshore the southern end of Long Beach Island, NJ, during USGS Field Activity 2018-001-FA (Esri polyline shapefile, GCS WGS 84) 1) U-Pb SHRIMP Age Data Chirp seismic reflection data from the Edgetech 512i collected in Little Egg Inlet and offshore the southern end of Long Beach Island, NJ, during USGS field activity 2018-001-FA (shotpoints point shapefile, survey trackline shapefile, PNG profile images, and SEG-Y trace data). Multibeam Echosounder, Reson T-20P tracklines collected in Little Egg Inlet and offshore the southern end of Long Beach Island, NJ, during USGS Field Activity 2018-001-FA (Esri polyline shapefile, GCS WGS 84) Martha's Vineyard 2D micromodel studies of pore-throat clogging by pure fine-grained sediments and natural sediments from NGHP-02, offshore India Data for the Evaluation of the U.S. Geological Survey Streamgage Network in South Carolina, 2017