Groundwater quality in the 8,806-square-mile Klamath Mountains (KLAM) study unit was investigated by the U.S. Geological Survey (USGS) from October to December 2010, as part of the California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring and Assessment (GAMA) Program’s Priority Basin Project (PBP). The GAMA-PBP was developed in response to the California Groundwater Quality Monitoring Act of 2001 and is being conducted in collaboration with the SWRCB and Lawrence Livermore National Laboratory (LLNL). The KLAM study unit was the thirty-third study unit to be sampled as part of the GAMA-PBP.
\n\nThe GAMA Klamath Mountains study was designed to provide a spatially unbiased assessment of untreated-groundwater quality in the primary aquifer system and to facilitate statistically consistent comparisons of untreated-groundwater quality throughout California. The primary aquifer system is defined by the perforation intervals of wells listed in the California Department of Public Health (CDPH) database for the KLAM study unit. Groundwater quality in the primary aquifer system may differ from the quality in the shallower or deeper water-bearing zones; shallower groundwater may be more vulnerable to surficial contamination.
\n\nIn the KLAM study unit, groundwater samples were collected from sites in Del Norte, Siskiyou, Humboldt, Trinity, Tehama, and Shasta Counties, California. Of the 39 sites sampled, 38 were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the primary aquifer system in the study unit (grid sites), and the remaining site was non-randomized (understanding site).
\n\nThe groundwater samples were analyzed for basic field parameters, organic constituents (volatile organic compounds [VOCs] and pesticides and pesticide degradates), inorganic constituents (trace elements, nutrients, major and minor ions, total dissolved solids [TDS]), radon-222, gross alpha and gross beta radioactivity, and microbial indicators (total coliform and Escherichia coli [E. coli]). Isotopic tracers (stable isotopes of hydrogen and oxygen in water, isotopic ratios of dissolved strontium in water, and stable isotopes of carbon in dissolved inorganic carbon), dissolved noble gases, and age-dating tracers (tritium and carbon-14) were measured to help identify sources and ages of sampled groundwater.
\n\nQuality-control samples (field blanks, replicate sample pairs, and matrix spikes) were collected at 13 percent of the sites in the KLAM study unit, and the results were used to evaluate the quality of the data from the groundwater samples. Field blank samples rarely contained detectable concentrations of any constituent, indicating that contamination from sample collection or analysis was not a significant source of bias in the data for the groundwater samples. More than 99 percent of the replicate pair samples were within acceptable limits of variability. Matrix-spike sample recoveries were within the acceptable range (70 to 130 percent) for approximately 91 percent of the compounds.
\n\nThis study did not evaluate the quality of water delivered to consumers. After withdrawal, groundwater typically is treated, disinfected, and (or) blended with other waters to maintain water quality. Regulatory benchmarks apply to water that is delivered to the consumer, not to untreated groundwater. However, to provide some context for the results, concentrations of constituents measured in the untreated groundwater were compared with regulatory and non-regulatory health-based benchmarks established by the U.S. Environmental Protection Agency (USEPA) and CDPH, and to non-health-based benchmarks established for aesthetic concerns by the CDPH. Comparisons between data collected for this study and benchmarks for drinking water are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks.
\n\nAll concentrations of organic constituents from grid sites sampled in the KLAM study unit were less than health-based benchmarks. In total, VOCs were detected in 16 of the 38 grid sites sampled (approximately 42 percent), pesticides and pesticide degradates were detected in 8 grid sites (about 21 percent), and microbial indicators were detected in 14 grid sites (approximately 37 percent).
\n\nInorganic constituents (trace elements, major and minor ions, nutrients, and uranium and other radioactive constituents) and microbial indicators were sampled for at 38 grid sites, and all concentrations were less than health-based benchmarks, with the exception of one detection of boron greater than the CDPH notification level of 1,000 micrograms per liter (μg/L). Generally, concentrations of inorganic constituents with non-health-based benchmarks (iron, manganese, chloride, and TDS) were less than the CDPH secondary maximum contaminant level (SMCL-CA). Exceptions include three detections of iron greater than the SMCL-CA of 300 μg/L, four detections of manganese greater than the SMCL-CA of 50 μg/L, one detection of chloride greater than the recommended SMCL-CA of 250 μg/L, and one detection of TDS greater than the recommended SMCL-CA of 500 μg/L.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds803","collaboration":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program; Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Mathany, T., and Belitz, K., 2014, Groundwater-quality data in the Klamath Mountains study unit, 2010: results from the California GAMA Program: U.S. Geological Survey Data Series 803, x, 82 p., https://doi.org/10.3133/ds803.","productDescription":"x, 82 p.","numberOfPages":"96","ipdsId":"IP-036089","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":285119,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds803.jpg"},{"id":285117,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/803/"},{"id":285118,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/803/pdf/ds803.pdf"}],"projection":"Albers Equal Area Conic Projection","country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -0.01611111111111111,8.333333333333334E-4 ], [ -0.01611111111111111,0.0011111111111111111 ], [ -0.01638888888888889,0.0011111111111111111 ], [ -0.01638888888888889,8.333333333333334E-4 ], [ -0.01611111111111111,8.333333333333334E-4 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517044e4b05569d805a245","contributors":{"authors":[{"text":"Mathany, Timothy M. 0000-0002-4747-5113","orcid":"https://orcid.org/0000-0002-4747-5113","contributorId":99949,"corporation":false,"usgs":true,"family":"Mathany","given":"Timothy M.","affiliations":[],"preferred":false,"id":485868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":485867,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70099991,"text":"sir20145036 - 2014 - Simulation of zones of contribution to wells at site GM–38, Naval Weapons Industrial Reserve Plant, Bethpage, New York","interactions":[],"lastModifiedDate":"2014-03-28T14:36:01","indexId":"sir20145036","displayToPublicDate":"2014-03-28T14:23:03","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5036","title":"Simulation of zones of contribution to wells at site GM–38, Naval Weapons Industrial Reserve Plant, Bethpage, New York","docAbstract":"A three-dimensional groundwater-flow model is coupled with the particle-tracking program MODPATH to delineate zones of contribution to wells pumping from the Magothy aquifer and supplying water to a chlorinated volatile organic compound removal plant at site GM–38, Naval Weapons Industrial Reserve Plant, Bethpage, New York. By use of driller’s logs, a transitional probability approach generated three alternative realizations of heterogeneity within the Magothy aquifer to assess uncertainty in model representation. Finer-grained sediments with low hydraulic conductivity were realized as laterally discontinuous, thickening towards the south, and comprising about 17 percent of the total aquifer volume.
\n\nParticle-tracking evaluations of a steady state present conditions model with alternative heterogeneity realizations were used to develop zones of contribution of remedial pumping wells. Because of heterogeneity and high rates of advection within the coarse-grained sediments, transport by dispersion and (or) diffusion was assumed to be negligible. Resulting zones of contribution of existing remedial wells are complex shapes, influenced by heterogeneity of each realization and other nearby hydrologic stresses. The use of two particle tracking techniques helped identify zones of contribution to wells. Backtracking techniques and observations of points of intersection of backward-tracked particles at shells of the GM–38 Hot Spot, as defined by surfaces of equal total volatile organic compound concentration, identified the source of water within the GM–38 Hot Spot to simulated wells. Forward-tracking techniques identified the fate of water within the GM–38 Hot Spot, including well capture and discharge to model constant head and drain boundaries. The percentage of backward-tracked particles, started at GM–38 wells that were sourced from within the Hot Spot, varied from 72.0 to 98.2, depending on the Hot Spot delineation used (present steady state model and Magothy aquifer heterogeneity realization A). The percentage of forward-tracked particles that were captured by GM–38 wells varied from 81.1 to 94.6, depending on the Hot Spot delineation used, with the remainder primarily captured by Bethpage Water District Plant 4 production wells (present steady state model and Magothy aquifer heterogeneity realization A). Less than 1 percent of forward-tracked particles ultimately discharge at model constant head and drain boundaries. The differences between forward- and backward-tracked particle percentage ranges are due to some forward-tracked particles not being captured by GM–38 wells, and some backward-tracked particles not intersecting specific regions of the Hot Spot.
\n\nDuring 2013, an aquifer test generated detailed time series of well pumping rates and corresponding water-level responses were recorded at numerous locations. These data were used to verify the present conditions steady state model and demonstrate the sensitivity of model results to transient-state changes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145036","collaboration":"Prepared in cooperation with the Naval Facilities Engineering Command","usgsCitation":"Misut, P., 2014, Simulation of zones of contribution to wells at site GM–38, Naval Weapons Industrial Reserve Plant, Bethpage, New York: U.S. Geological Survey Scientific Investigations Report 2014-5036, vii, 58 p., https://doi.org/10.3133/sir20145036.","productDescription":"vii, 58 p.","numberOfPages":"70","onlineOnly":"Y","ipdsId":"IP-053917","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":285106,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5036/pdf/sir2014-5036.pdf"},{"id":285107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145036.jpg"},{"id":285104,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5036/"}],"country":"United States","state":"New York","otherGeospatial":"Bethpage","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -73.506,40.731 ], [ -73.506,40.769 ], [ -73.464,40.769 ], [ -73.464,40.731 ], [ -73.506,40.731 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517063e4b05569d805a3b7","contributors":{"authors":[{"text":"Misut, Paul","contributorId":93822,"corporation":false,"usgs":true,"family":"Misut","given":"Paul","affiliations":[],"preferred":false,"id":492102,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70095234,"text":"ofr20131020 - 2014 - High-resolution geophysical data collected aboard the U.S. Geological Survey research vessel Rafael to supplement existing datasets from Buzzards Bay and Vineyard Sound, Massachusetts","interactions":[],"lastModifiedDate":"2014-03-28T13:46:51","indexId":"ofr20131020","displayToPublicDate":"2014-03-28T13:34:34","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1020","title":"High-resolution geophysical data collected aboard the U.S. Geological Survey research vessel Rafael to supplement existing datasets from Buzzards Bay and Vineyard Sound, Massachusetts","docAbstract":"Geophysical and geospatial data were collected in Buzzards Bay, in the shallow-water areas of Vineyard Sound, and in the nearshore areas off the eastern Elizabeth Islands and northern coast of Martha's Vineyard, Massachusetts, on the U.S. Geological Survey research vessel Rafael between 2007 and 2011, in a collaborative effort between the U.S. Geological Survey and the Massachusetts Office of Coastal Zone Management. This report describes results of this collaborative effort, which include mapping the geology of the inner shelf zone of the Elizabeth Islands and the sand shoals of Vineyard Sound and studying geologic processes that contribute to the evolution of this area. Data collected during these surveys include: bathymetry, acoustic backscatter, seismic-reflection profiles, sound velocity profiles, and navigation. The long-term goals of this project are (1) to provide high-resolution geophysical data that will support research on the influence of sea-level change and sediment supply on coastal evolution and (2) to inventory subtidal marine habitats and their distribution within the coastal zone of Massachusetts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131020","collaboration":"Prepared in cooperation with the Massachusetts Office of Coastal Zone Management","usgsCitation":"Pendleton, E., Andrews, B., Danforth, W.W., and Foster, D.S., 2014, High-resolution geophysical data collected aboard the U.S. Geological Survey research vessel Rafael to supplement existing datasets from Buzzards Bay and Vineyard Sound, Massachusetts: U.S. Geological Survey Open-File Report 2013-1020, HTML Document, https://doi.org/10.3133/ofr20131020.","productDescription":"HTML 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As such, water-resource managers that oversee these water supplies require monitoring of the quantity and quality of the resource. Monitoring information can be used to assess the basic conditions within the reservoir and to establish a reliable estimate of storage capacity. In April and May 2013, a global navigation satellite system receiver and fathometer were used to collect bathymetric data, and an autonomous underwater vehicle was used to collect water-quality and bathymetric data at Table Rock Reservoir and North Saluda Reservoir in Greenville County, South Carolina. These bathymetric data were used to create a bathymetric contour map and stage-area and stage-volume relation tables for each reservoir. Additionally, statistical summaries of the water-quality data were used to provide a general description of water-quality conditions in the reservoirs.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3289","issn":"2329-132X","collaboration":"Prepared in cooperation with Greenville Water","usgsCitation":"Clark, J.M., Journey, C.A., Nagle, D.D., and Lanier, T.H., 2014, Bathymetric maps and water-quality profiles of Table Rock and North Saluda Reservoirs, Greenville County, South Carolina: U.S. Geological Survey Scientific Investigations Map 3289, Map: 36.00 x 32.00 inches, https://doi.org/10.3133/sim3289.","productDescription":"Map: 36.00 x 32.00 inches","onlineOnly":"Y","ipdsId":"IP-052115","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":285090,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3289.jpg"},{"id":285088,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3289/"},{"id":285089,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3289/pdf/sim3289.pdf"}],"scale":"4000","projection":"Lambert Conformal Conic projection","datum":"North American Datum of 1983","country":"United States","state":"South Carolina","county":"Greenville County","otherGeospatial":"North Saluda Reservoirs, Table Rock","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -82.75,35.0 ], [ -82.75,35.25 ], [ -82.25,35.25 ], [ -82.25,35.0 ], [ -82.75,35.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517027e4b05569d805a176","contributors":{"authors":[{"text":"Clark, Jimmy M. 0000-0002-3138-5738 jmclark@usgs.gov","orcid":"https://orcid.org/0000-0002-3138-5738","contributorId":4773,"corporation":false,"usgs":true,"family":"Clark","given":"Jimmy","email":"jmclark@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":490446,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nagle, Doug D. ddnagle@usgs.gov","contributorId":2697,"corporation":false,"usgs":true,"family":"Nagle","given":"Doug","email":"ddnagle@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":490447,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lanier, Timothy H. 0000-0001-5104-3308 thlanier@usgs.gov","orcid":"https://orcid.org/0000-0001-5104-3308","contributorId":4171,"corporation":false,"usgs":true,"family":"Lanier","given":"Timothy","email":"thlanier@usgs.gov","middleInitial":"H.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490448,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70142794,"text":"70142794 - 2014 - Great Lakes prey fish populations: a cross-basin overview of status and trends based on bottom trawl surveys, 1978-2013","interactions":[],"lastModifiedDate":"2018-03-23T14:24:18","indexId":"70142794","displayToPublicDate":"2014-03-28T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"Great Lakes prey fish populations: a cross-basin overview of status and trends based on bottom trawl surveys, 1978-2013","docAbstract":"The assessment of Great Lakes prey fish stocks have been conducted annually with bottom trawls since the 1970s by the Great Lakes Science Center, sometimes assisted by partner agencies. These stock assessments provide data on the status and trends of prey fish that are consumed by important commercial and recreational fishes. Although all these annual surveys are conducted using bottom trawls, they differ among the lakes in the proportion of the lake covered, seasonal timing, trawl gear used, and the manner in which the trawl is towed (across or along bottom contours). Because each assessment is unique, population indices were standardized to the highest value for a time series within each lake for the following prey species: Cisco (Coregonus artedi), Bloater (C. hoyi), Rainbow Smelt (Osmerus mordax), Alewife (Alosa pseudoharengus), and Round Goby (Neogobius melanostomus). In this report, standardized indices are presented in graphical form along with synopses to provide a short, informal cross-basin summary of the status and trends of principal prey fishes. There was basin-wide agreement in the trends of age-1 and older biomass for all prey species, with the highest concordance occurring for coregonids and Rainbow Smelt, and weaker concordance for Alewife. For coregonids, the highest biomass occurred from the mid-1980s to the mid-1990s. Rainbow Smelt biomass declined slowly and erratically during the last quarter century. Alewife biomass was generally higher from the early 1980s through 1990s across the Great Lakes, but since the early 1990s, trends have been divergent across the lakes, though there has been a downward trend in all lakes since 2005. Recently, Lake Huron has shown resurgence in biomass of Bloater, achieving 75% of its maximum record in 2012 due to recruitment of a succession of strong and moderate year classes that appeared in 2005-2011. Also, strong recruitment of the 2010 year class of Alewife has led to a sharp increase in biomass of Alewife in Lake Michigan. In general, trends in year-class strengths were less concordant across the basin and only coregonids showed statistical agreement across the upper Great Lakes. The appearance of strong and moderate year-classes of Bloater in Lake Huron in 2005- 2011 countered the trend of continuing weak year-classes of coregonids in Lakes Michigan and Superior. Not shown in our analysis is the appearance of the 2013 year-class of Bloater in Huron, the largest to date. There was no agreement in cross-basin trends in year-class strengths for Rainbow Smelt and Alewife, although there was agreement between pairs of lakes. Although there was statistical agreement in trends of age-0 and older Round Goby biomass among lakes where this species has successfully invaded (Michigan, Huron, Erie and Ontario), temporal patterns of biomass in each lake were different. Round Goby may be approaching equilibrium in Lake Erie, peaking in Lake Huron, and expanding in Lake Michigan. The trend in Lake Ontario remains unclear. Declining abundance in Lake Erie has corresponded with evidence that Round Goby have become increasingly incorporated into piscivore diets, e.g., Lake Trout, Walleye, Smallmouth Bass, Yellow Perch, and Burbot in Lakes Michigan, Huron, Erie, and Ontario. Round Goby continue to be absent from spring bottom trawl assessments in Lake Superior, but their presence in the harbors and embayments of Duluth and Thunder Bay (U.S. Geological Survey and Ontario Ministry of Natural Resources, unpublished data), suggests that there is potential for future colonization.
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,{"id":70099932,"text":"ofr20141065 - 2014 - Preliminary interpretation of pre-2014 landslide deposits in the vicinity of Oso, Washington","interactions":[],"lastModifiedDate":"2023-05-26T15:30:08.282033","indexId":"ofr20141065","displayToPublicDate":"2014-03-27T16:12:50","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1065","title":"Preliminary interpretation of pre-2014 landslide deposits in the vicinity of Oso, Washington","docAbstract":"High-resolution topographic surveys allow fairly precise mapping of landslide deposits and their relative ages. Relative ages are determined by cross-cutting relations and the amount of smoothing—more smoothed slide deposits are older—of these deposits. The Tulalip Tribes, in partnership with the Puget Sound Lidar Consortium, acquired a high-resolution lidar (light detection and ranging) survey of the North Fork Stillaguamish River valley in 2013. This report presents a preliminary interpretation of the topography of this area using the lidar data at a scale of 1:24,000.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141065","usgsCitation":"Haugerud, R.A., 2014, Preliminary interpretation of pre-2014 landslide deposits in the vicinity of Oso, Washington: U.S. Geological Survey Open-File Report 2014-1065, Report: 4 pages; GIS Data Zip File, https://doi.org/10.3133/ofr20141065.","productDescription":"Report: 4 pages; GIS Data Zip File","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-055838","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":417505,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_99750.htm","linkFileType":{"id":5,"text":"html"}},{"id":285073,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1065/","linkFileType":{"id":5,"text":"html"}},{"id":285075,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1065/pdf/ofr2014-1065.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":285077,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141065.png"},{"id":285076,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1065/downloads/ofr2014-1065_GIS.zip"}],"country":"United States","state":"Washington","city":"Oso","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.940536,48.258349 ], [ -121.940536,48.297727 ], [ -121.880529,48.297727 ], [ -121.880529,48.258349 ], [ -121.940536,48.258349 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5351705be4b05569d805a371","contributors":{"authors":[{"text":"Haugerud, Ralph A. 0000-0001-7302-4351 rhaugerud@usgs.gov","orcid":"https://orcid.org/0000-0001-7302-4351","contributorId":2691,"corporation":false,"usgs":true,"family":"Haugerud","given":"Ralph","email":"rhaugerud@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":492070,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70073968,"text":"ofr20141003 - 2014 - Hydrologic Drought Decision Support System (HyDroDSS)","interactions":[],"lastModifiedDate":"2014-03-27T14:22:43","indexId":"ofr20141003","displayToPublicDate":"2014-03-27T14:06:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1003","title":"Hydrologic Drought Decision Support System (HyDroDSS)","docAbstract":"The hydrologic drought decision support system (HyDroDSS) was developed by the U.S. Geological Survey (USGS) in cooperation with the Rhode Island Water Resources Board (RIWRB) for use in the analysis of hydrologic variables that may indicate the risk for streamflows to be below user-defined flow targets at a designated site of interest, which is defined herein as data-collection site on a stream that may be adversely affected by pumping. Hydrologic drought is defined for this study as a period of lower than normal streamflows caused by precipitation deficits and (or) water withdrawals. The HyDroDSS is designed to provide water managers with risk-based information for balancing water-supply needs and aquatic-habitat protection goals to mitigate potential effects of hydrologic drought.
\nThis report describes the theory and methods for retrospective streamflow-depletion analysis, rank correlation analysis, and drought-projection analysis. All three methods are designed to inform decisions made by drought steering committees and decisionmakers on the basis of quantitative risk assessment. All three methods use estimates of unaltered streamflow, which is the measured or modeled flow without major withdrawals or discharges, to approximate a natural low-flow regime.
\nRetrospective streamflow-depletion analysis can be used by water-resource managers to evaluate relations between withdrawal plans and the potential effects of withdrawal plans on streams at one or more sites of interest in an area. Retrospective streamflow-depletion analysis indicates the historical risk of being below user-defined flow targets if different pumping plans were implemented for the period of record. Retrospective streamflow-depletion analysis also indicates the risk for creating hydrologic drought conditions caused by use of a pumping plan. Retrospective streamflow-depletion analysis is done by calculating the net streamflow depletions from withdrawals and discharges and applying these depletions to a simulated record of unaltered streamflow.
\nRank correlation analysis in the HyDroDSS indicates the persistence of hydrologic measurements from month to month for the prediction of developing hydrologic drought conditions and quantitatively indicates which hydrologic variables may be used to indicate the onset of hydrologic drought conditions. Rank correlation analysis also indicates the potential use of each variable for estimating the monthly minimum unaltered flow at a site of interest for use in the drought-projection analysis. Rank correlation analysis in the HyDroDSS is done by calculating Spearman’s rho for paired samples and the 95-percent confidence limits of this rho value. Rank correlation analysis can be done by using precipitation, groundwater levels, measured streamflows, and estimated unaltered streamflows. Serial correlation analysis, which indicates relations between current and future values, can be done for a single site. Cross correlation analysis, which indicates relations among current values at one site and current and future values at a second site, also can be done.
\nDrought-projection analysis in the HyDroDSS indicates the risk for being in a hydrologic drought condition during the current month and the five following months with and without pumping. Drought-projection analysis also indicates the potential effectiveness of water-conservation methods for mitigating the effect of withdrawals in the coming months on the basis of the amount of depletion caused by different pumping plans and on the risk of unaltered flows being below streamflow targets. Drought-projection analysis in the HyDroDSS is done with Monte Carlo methods by using the position analysis method. In this method the initial value of estimated unaltered streamflows is calculated by correlation to a measured hydrologic variable (monthly precipitation, groundwater levels, or streamflows from an index station identified with the rank correlation analysis). Then a pseudorandom number generator is used to create 251 six-month-long flow traces by using a bootstrap method. Serial correlation of the estimated unaltered monthly minimum streamflows determined from the rank correlation analysis is preserved within each flow trace. The sample of unaltered streamflows indicates the risk of being below flow targets in the coming months under simulated natural conditions (without historic withdrawals). The streamflow-depletion algorithms are then used to estimate risks of flow being below targets if selected pumping plans are used.
\nThis report also describes the implementation of the HyDroDSS. The HyDroDSS was developed as a Microsoft Access® database application to facilitate storage, handling, and use of hydrologic datasets with a simple graphical user interface. The program is implemented in the database by using the Visual Basic for Applications® (VBA) programming language. Program source code for the analytical techniques is provided in the HyDroDSS and in electronic text files accompanying this report. Program source code for the graphical user interface and for data-handling code, which is specific to Microsoft Access® and the HyDroDSS, is provided in the database. An installation package with a run-time version of the software is available with this report for potential users who do not have a compatible copy of Microsoft Access®. Administrative rights are needed to install this version of the HyDroDSS.
\nA case study, to demonstrate the use of HyDroDSS and interpretation of results for a site of interest, is detailed for the USGS streamgage on the Hunt River (station 01117000) near East Greenwich in central Rhode Island. The Hunt River streamgage was used because it has a long record of streamflow and is in a well-studied basin with a substantial amount of hydrologic and water-use data including groundwater pumping for municipal water supply.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141003","collaboration":"Prepared in cooperation with the Rhode Island Water Resources Board","usgsCitation":"Granato, G., 2014, Hydrologic Drought Decision Support System (HyDroDSS): U.S. Geological Survey Open-File Report 2014-1003, Report: x, 91 p.; Make CD by ISO package, https://doi.org/10.3133/ofr20141003.","productDescription":"Report: x, 91 p.; Make CD by ISO package","numberOfPages":"118","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-042923","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":285061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141003.jpg"},{"id":285059,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1003/ofr2014-1003_CDROM.iso"},{"id":285057,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1003/"},{"id":285058,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1003/pdf/ofr2014-1003.pdf"}],"projection":"Rhode Island state plane projection","country":"United States","state":"Rhode Island","city":"East Greenwich","otherGeospatial":"Hunt River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.575284,41.507592 ], [ -71.575284,41.674953 ], [ -71.426104,41.674953 ], [ -71.426104,41.507592 ], [ -71.575284,41.507592 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517047e4b05569d805a262","contributors":{"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913 ggranato@usgs.gov","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":1692,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory E.","email":"ggranato@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":489307,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70094492,"text":"fs20143015 - 2014 - Estimating flood magnitude and frequency for urban and small, rural streams in Georgia, South Carolina, and North Carolina, 2011","interactions":[],"lastModifiedDate":"2016-12-07T11:42:39","indexId":"fs20143015","displayToPublicDate":"2014-03-27T13:03:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3015","title":"Estimating flood magnitude and frequency for urban and small, rural streams in Georgia, South Carolina, and North Carolina, 2011","docAbstract":"Reliable estimates of the magnitude and frequency of floods are essential for the design of transportation and water-conveyance structures, flood insurance studies, and flood-plain management. Flood-frequency estimates are particularly important in densely populated urban areas. The U.S. Geological Survey (USGS) used a multistate approach to update methods for determining the magnitude and frequency of floods in urban and small, rural streams that are not substantially affected by regulation or tidal fluctuations in Georgia, South Carolina, and North Carolina (Feaster and others, 2014). The multistate approach has the advantage over a single state approach of increasing the number of streamflow-gaging station (streamgages) available for analysis, expanding the geographical coverage that would allow for application of regional regression equations across state boundaries, and building on a previous flood-frequency investigation of rural streamgages in the Southeastern United States. This investigation was funded as part of a cooperative program of water-resources investigations between the USGS, the South Carolina Department of Transportation, and the North Carolina Department of Transportation. In addition, much of the data and information for the Georgia streamgages was funded through a similar cooperative program with the Georgia Department of Transportation.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143015","collaboration":"Prepared in cooperation with the South Carolina Department of Transportation, Office of Materials and Research, and the North Carolina Department of Transportation, Division of Highways (Hydraulics Unit)","usgsCitation":"Feaster, T., Gotvald, A.J., and Weaver, J., 2014, Estimating flood magnitude and frequency for urban and small, rural streams in Georgia, South Carolina, and North Carolina, 2011: U.S. Geological Survey Fact Sheet 2014-3015, 2 p., https://doi.org/10.3133/fs20143015.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-051854","costCenters":[{"id":13634,"text":"South Atlantic Water Science 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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517037e4b05569d805a1e8","contributors":{"authors":[{"text":"Feaster, Toby D. 0000-0002-5626-5011 tfeaster@usgs.gov","orcid":"https://orcid.org/0000-0002-5626-5011","contributorId":1109,"corporation":false,"usgs":true,"family":"Feaster","given":"Toby D.","email":"tfeaster@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":490646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gotvald, Anthony J. 0000-0002-9019-750X agotvald@usgs.gov","orcid":"https://orcid.org/0000-0002-9019-750X","contributorId":1970,"corporation":false,"usgs":true,"family":"Gotvald","given":"Anthony","email":"agotvald@usgs.gov","middleInitial":"J.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weaver, J. Curtis","contributorId":42260,"corporation":false,"usgs":true,"family":"Weaver","given":"J. Curtis","affiliations":[],"preferred":false,"id":490648,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70093764,"text":"sir20145029 - 2014 - Hydrogeologic framework and salinity distribution of the Floridan aquifer system of Broward County, Florida","interactions":[],"lastModifiedDate":"2014-03-27T10:09:44","indexId":"sir20145029","displayToPublicDate":"2014-03-27T09:58:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5029","title":"Hydrogeologic framework and salinity distribution of the Floridan aquifer system of Broward County, Florida","docAbstract":"Concerns about water-level decline and seawater intrusion in the surficial Biscayne aquifer, currently the principal source of water supply to Broward County, prompted a study to refine the hydrogeologic framework of the underlying Floridan aquifer system to evaluate its potential as an alternative source of supply. This report presents cross sections that illustrate the stratigraphy and hydrogeology in eastern Broward County; maps of the upper surfaces and thicknesses of several geologic formations or units within the Floridan aquifer system; and maps of two of the potentially productive water-bearing zones within the system, the Upper Floridan aquifer and the Avon Park permeable zone.
\nAn analysis of data on rock depositional textures, associated pore networks, and flow zones in the Floridan aquifer system shows that groundwater moves through the system in two ways. These data support a conceptual, dual-porosity model of the system wherein groundwater moves either as concentrated flow in discrete, thin bedding-plane vugs or zones of vuggy megaporosity, or as diffuse flow through rocks with primarily interparticle and moldic-particle porosity. Because considerable exchange of groundwater may occur between the zones of vuggy and matrix-dominated porosity, understanding the distribution of that porosity and flow zone types is important to evaluating the suitability of the several units within the Floridan aquifer system for managing the water through practices such as aquifer storage and recovery (ASR).
\nThe salinity of the water in the Floridan aquifer system is highest in the central part of the study area, and lower toward the north and south. Although salinity generally increases with depth, in the western part of the study area a zone of relatively high saline water is perched above water of lower salinity in the underlying Avon Park permeable zone. Overall, the areas of highest salinity in the aquifer system coincide with those with the lowest estimated transmissivity, so that the occurrence of perched saline water in the system may be the consequence of incompletely flushed connate water or intruded seawater.
\nA seismic reflection profile along the Hillsboro Canal, at the northern edge of the study area, shows seven seismic-sag structures that are interpreted as downward deformation of overlying strata into collapsed deep cave systems. These structures may compromise the integrity of the confinement created by the underlying strata by allowing upconing of saline water from depth, which has implications for successful application of ASR and use of the Floridan aquifer system as an alternative water supply.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145029","collaboration":"Prepared in cooperation with Broward County, Florida","usgsCitation":"Reese, R.S., and Cunningham, K.J., 2014, Hydrogeologic framework and salinity distribution of the Floridan aquifer system of Broward County, Florida: U.S. Geological Survey Scientific Investigations Report 2014-5029, Report: vii, 60 p.; Appendix; Plate Directory, https://doi.org/10.3133/sir20145029.","productDescription":"Report: vii, 60 p.; Appendix; Plate Directory","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-026662","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"links":[{"id":285022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145029.jpg"},{"id":285020,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5029/appendix"},{"id":285021,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5029/plates"},{"id":285018,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5029/"},{"id":285019,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5029/pdf/sir2014-5029.pdf"}],"projection":"Albers Equal Area Conic Projection","datum":"North American Datum 1983","country":"United States","state":"Florida","county":"Broward County","otherGeospatial":"Hillsboro Canal","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.37981,25.949959 ], [ -80.37981,26.37992 ], [ -80.060996,26.37992 ], [ -80.060996,25.949959 ], [ -80.37981,25.949959 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517047e4b05569d805a25d","contributors":{"authors":[{"text":"Reese, Ronald S. rsreese@usgs.gov","contributorId":1090,"corporation":false,"usgs":true,"family":"Reese","given":"Ronald","email":"rsreese@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":490204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cunningham, Kevin J. 0000-0002-2179-8686 kcunning@usgs.gov","orcid":"https://orcid.org/0000-0002-2179-8686","contributorId":1689,"corporation":false,"usgs":true,"family":"Cunningham","given":"Kevin","email":"kcunning@usgs.gov","middleInitial":"J.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":490205,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70095888,"text":"ofr20141052 - 2014 - Monitoring fine-sediment volume in the Colorado River ecosystem, Arizona: construction and analysis of digital elevation models","interactions":[],"lastModifiedDate":"2014-03-27T08:31:20","indexId":"ofr20141052","displayToPublicDate":"2014-03-27T08:23:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1052","title":"Monitoring fine-sediment volume in the Colorado River ecosystem, Arizona: construction and analysis of digital elevation models","docAbstract":"Digital elevation models (DEMs) of eleven 2–5 kilometer reaches of the Colorado River ecosystem (CRE) in Grand Canyon were constructed from repeat bathymetric and topographic surveys collected between August 2000 and December 2004. The DEMs will be used by researchers to study the effects of Glen Canyon Dam (GCD) operations on the sediment resources of the CRE in Grand Canyon by quantifying morphological changes and sediment transfer within and among the study reaches.
\nAirborne surveys collected light detection and ranging (lidar) and photogrammetric data, whereas ground topographic and bathymetric data were collected simultaneously on river trips. Surveys were conducted in August 2000, September 2000, May 2002, May 2004, November 2004, and December 2004. The aerial lidar and photogrammetric data were merged with the ground topographic and bathymetric data to create DEMs of the study areas with a grid resolution of 1 meter. For each survey period, the vertical component of uncertainty (specifically, reproducibility or precision) was estimated for each data type (lidar/photogrammetry, ground surveys, bathymetry) and for two different types of bed-surface texture (smooth and rough).
\nThe resulting DEMs from this study are a valuable contribution to ongoing efforts in assessing the effects of GCD operations on the CRE. The DEMs can be used to map the spatial characteristics of geomorphic change within the study reaches and to estimate sediment budgets for different time periods by calculating the difference in sediment volume between surveys. In addition, the DEMs provide essential boundary conditions for numerical models of sediment transport and deposition, as well as help define the spatial distribution of habitat for fisheries investigations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141052","collaboration":"Prepared in cooperation with Northern Arizona University","usgsCitation":"Kaplinski, M., Hazel, J., Grams, P.E., and Davis, P.A., 2014, Monitoring fine-sediment volume in the Colorado River ecosystem, Arizona: construction and analysis of digital elevation models: U.S. Geological Survey Open-File Report 2014-1052, Report: v, 29 p.; Appendix 1; Digital products, https://doi.org/10.3133/ofr20141052.","productDescription":"Report: v, 29 p.; Appendix 1; Digital products","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-043600","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":285009,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141052.jpg"},{"id":285006,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1052/pdf/ofr2014-1052.pdf"},{"id":285008,"type":{"id":7,"text":"Companion Files"},"url":"https://www.gcmrc.gov/research_areas/sediment_geomorphology/downloads/OFR_2014_1052/"},{"id":285007,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1052/pdf/ofr2014-1052_Appendix.pdf"},{"id":285005,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1052/"}],"projection":"1983 Arizona State Plane","datum":"North American Datum 1983","country":"United States","state":"Arizona","otherGeospatial":"Colorado River;Grand Canyon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.2468,35.003 ], [ -114.2468,37.2631 ], [ -110.6625,37.2631 ], [ -110.6625,35.003 ], [ -114.2468,35.003 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517056e4b05569d805a339","contributors":{"authors":[{"text":"Kaplinski, Matt","contributorId":65817,"corporation":false,"usgs":true,"family":"Kaplinski","given":"Matt","affiliations":[],"preferred":false,"id":491465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hazel, Joseph E. Jr.","contributorId":91819,"corporation":false,"usgs":true,"family":"Hazel","given":"Joseph E.","suffix":"Jr.","affiliations":[],"preferred":false,"id":491466,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grams, Paul E. 0000-0002-0873-0708 pgrams@usgs.gov","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":1830,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","email":"pgrams@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":491464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":491463,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70048989,"text":"sir20135204 - 2014 - Acute and chronic sensitivity of white sturgeon (Acipenser transmontanus) and rainbow trout (Oncorhynchus mykiss) to cadmium, copper, lead, or zinc in laboratory water-only exposures","interactions":[],"lastModifiedDate":"2014-03-26T12:59:41","indexId":"sir20135204","displayToPublicDate":"2014-03-26T12:54:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5204","title":"Acute and chronic sensitivity of white sturgeon (Acipenser transmontanus) and rainbow trout (Oncorhynchus mykiss) to cadmium, copper, lead, or zinc in laboratory water-only exposures","docAbstract":"White sturgeon (Acipenser transmontanus) are experiencing poor recruitment in the trans boundary reach of the upper Columbia River in eastern Washington State. Limited toxicity data indicated that early life stages of white sturgeon are sensitive to metals. In acute 4-day (d) exposures with larval white sturgeon, previous studies have reported that the 4-day median lethal concentrations (LC50) based on biotic ligand model (BLM) normalization for copper were below the U.S. Environmental Protection Agency national recommended acute water-quality criterion. In previously published chronic 66-d exposures starting with newly fertilized eggs of white sturgeon, 20-percent lethal effect concentrations (LC20s) for copper, cadmium, or zinc generally were within a factor of two of the chronic values of the most sensitive fish species in the databases of the U.S. Environmental Protection Agency water-quality criteria (WQC) for the three metals. However, there were some uncertainties in the chronic exposures previously performed with white sturgeon, including (1) low control survival (37 percent), (2) more control fish tested in each replicate compared to other treatments, (3) limited replication of treatments (n=2), (4) lack of reported growth data (such as dry weight), and (5) wide dilution factors for exposure concentrations (6- to 8-fold dilutions). The U.S. Environmental Protection Agency concluded that additional studies are needed to generate more toxicity data to better define lethal and sublethal toxicity thresholds for metals for white sturgeon.
\nThe objective of the study was to further evaluate the acute and chronic toxicity of cadmium, copper, lead, or zinc to early life stages of white sturgeon in water-only exposures. Toxicity tests also were performed with commonly tested rainbow trout (Oncorhynchus mykiss) under similar test conditions to determine the relative sensitivity between white sturgeon and rainbow trout to these metals. Toxicity data generated from this study were used to evaluate the sensitivity of early life stages of white sturgeon and rainbow trout relative to data published for other test organisms. Toxicity data generated from this study also were used to evaluate the level of protection of U.S. Environmental Protection Agency WQC or Washington State water-quality standards (WQS) for copper, zinc, cadmium, or lead to white sturgeon inhabiting the upper Columbia River.
\nChapter A of this report summarizes the results of acute toxicity tests performed for 4 d with white sturgeon and rainbow trout exposed to copper, cadmium, or zinc. Chapter B of this report summarizes the results of chronic toxicity tests performed for as many as 53 days with white sturgeon or rainbow trout exposed to copper, cadmium, zinc, or lead. Appendixes to the report are available at http://pubs.usgs.gov/sir/2013/5204. Supporting documentation for chapter A toxicity testing is provided in appendix 1. Supporting documentation for chapter B toxicity testing is provided in Appendix 2. Supporting documentation on analysis of water chemistry for chapter A and chapter B is provided in appendix 3 and 4. The rationale for applying corrections to measured copper and zinc values in water samples from some of the toxicity tests performed in chapter A is provided in appendix 5. A summary of dissolved organic carbon measurement variability and implications for biotic ligand model normalization for toxicity data summarized in chapter A and chapter B are provided in appendix 6. An evaluation of an interlaboratory comparison of analyses for dissolved organic carbon in water from the U.S. Geological Survey Columbia Environmental Research Center and University of Saskatchewan is provided in appendix 7. Finally, appendix 8 provides a summary of retesting of white sturgeon in 2012 to determine if improved survival of sturgeon would affect copper effect concentrations in 24-d copper exposures started with newly hatched larvae, and to evaluate the effect of light intensity or temperature on the response of newly hatched larvae during a 25-d study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135204","issn":"2328-0328","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency and Teck American, Inc.","usgsCitation":"Ingersoll, C.G., Contributions by Wang, N., Calfee, R.D., Beahan, E., Brumbaugh, W.G., Dorman, R.A., Hardesty, D.K., Kunz, J.L., Little, E.E., Mebane, C.A., and Puglis, H.J., 2014, Acute and chronic sensitivity of white sturgeon (Acipenser transmontanus) and rainbow trout (Oncorhynchus mykiss) to cadmium, copper, lead, or zinc in laboratory water-only exposures: U.S. Geological Survey Scientific Investigations Report 2013-5204, Report: viii, 76 p.; Downloads Directory, https://doi.org/10.3133/sir20135204.","productDescription":"Report: viii, 76 p.; Downloads Directory","numberOfPages":"88","onlineOnly":"Y","ipdsId":"IP-042908","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":284956,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5204/"},{"id":284957,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5204/pdf/sir2013-5204.pdf"},{"id":284958,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5204/downloads/"},{"id":284959,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135204.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4b24e4b0b290850f02f6","contributors":{"authors":[{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":485944,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Contributions by Wang, Ning","contributorId":42131,"corporation":false,"usgs":true,"family":"Contributions by Wang","given":"Ning","email":"","affiliations":[],"preferred":false,"id":485949,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calfee, Robin D. 0000-0001-6056-7023 rcalfee@usgs.gov","orcid":"https://orcid.org/0000-0001-6056-7023","contributorId":1841,"corporation":false,"usgs":true,"family":"Calfee","given":"Robin","email":"rcalfee@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":485943,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beahan, Erinn","contributorId":13893,"corporation":false,"usgs":true,"family":"Beahan","given":"Erinn","email":"","affiliations":[],"preferred":false,"id":485947,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":485941,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dorman, Rebecca A. 0000-0002-5748-7046","orcid":"https://orcid.org/0000-0002-5748-7046","contributorId":28522,"corporation":false,"usgs":true,"family":"Dorman","given":"Rebecca","email":"","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":485948,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hardesty, Doug K.","contributorId":79344,"corporation":false,"usgs":true,"family":"Hardesty","given":"Doug","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":485950,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kunz, James L. 0000-0002-1027-158X jkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-1027-158X","contributorId":3309,"corporation":false,"usgs":true,"family":"Kunz","given":"James","email":"jkunz@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":485945,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Little, Edward E. 0000-0003-0034-3639 elittle@usgs.gov","orcid":"https://orcid.org/0000-0003-0034-3639","contributorId":1746,"corporation":false,"usgs":true,"family":"Little","given":"Edward","email":"elittle@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":485942,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485940,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Puglis, Holly J. 0000-0002-3090-6597 hpuglis@usgs.gov","orcid":"https://orcid.org/0000-0002-3090-6597","contributorId":4686,"corporation":false,"usgs":true,"family":"Puglis","given":"Holly","email":"hpuglis@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":485946,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70099649,"text":"ofr20141024 - 2014 - The 1946 Unimak Tsunami Earthquake Area: revised tectonic structure in reprocessed seismic images and a suspect near field tsunami source","interactions":[],"lastModifiedDate":"2018-01-08T12:43:53","indexId":"ofr20141024","displayToPublicDate":"2014-03-26T09:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1024","title":"The 1946 Unimak Tsunami Earthquake Area: revised tectonic structure in reprocessed seismic images and a suspect near field tsunami source","docAbstract":"In 1946 at Unimak Pass, Alaska, a tsunami destroyed the lighthouse at Scotch Cap, Unimak Island, took 159 lives on the Hawaiian Islands, damaged island coastal facilities across the south Pacific, and destroyed a hut in Antarctica. The tsunami magnitude of 9.3 is comparable to the magnitude 9.1 tsunami that devastated the Tohoku coast of Japan in 2011. Both causative earthquake epicenters occurred in shallow reaches of the subduction zone. Contractile tectonism along the Alaska margin presumably generated the far-field tsunami by producing a seafloor elevation change. However, the Scotch Cap lighthouse was destroyed by a near-field tsunami that was probably generated by a coeval large undersea landslide, yet bathymetric surveys showed no fresh large landslide scar. We investigated this problem by reprocessing five seismic lines, presented here as high-resolution graphic images, both uninterpreted and interpreted, and available for the reader to download. In addition, the processed seismic data for each line are available for download as seismic industry-standard SEG-Y files. One line, processed through prestack depth migration, crosses a 10 × 15 kilometer and 800-meter-high hill presumed previously to be basement, but that instead is composed of stratified rock superimposed on the slope sediment. This image and multibeam bathymetry illustrate a slide block that could have sourced the 1946 near-field tsunami because it is positioned within a distance determined by the time between earthquake shaking and the tsunami arrival at Scotch Cap and is consistent with the local extent of high runup of 42 meters along the adjacent Alaskan coast. The Unimak/Scotch Cap margin is structurally similar to the 2011 Tohoku tsunamigenic margin where a large landslide at the trench, coeval with the Tohoku earthquake, has been documented. Further study can improve our understanding of tsunami sources along Alaska’s erosional margins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141024","usgsCitation":"Miller, J.J., von Huene, R.E., and Ryan, H.F., 2014, The 1946 Unimak Tsunami Earthquake Area: revised tectonic structure in reprocessed seismic images and a suspect near field tsunami source: U.S. Geological Survey Open-File Report 2014-1024, Report: iii, 19 p.; Downloads Directory, https://doi.org/10.3133/ofr20141024.","productDescription":"Report: iii, 19 p.; Downloads Directory","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051311","costCenters":[],"links":[{"id":284924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141024.jpg"},{"id":284922,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1024/pdf/ofr2014-1024.pdf"},{"id":284923,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1024/downloads"},{"id":284914,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1024/"}],"country":"United States","state":"Alaska","otherGeospatial":"Unimak Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -166.36596679687497,\n 52.05924589011585\n ],\n [\n -166.36596679687497,\n 55.084655921502\n ],\n [\n -159.609375,\n 55.084655921502\n ],\n [\n -159.609375,\n 52.05924589011585\n ],\n [\n -166.36596679687497,\n 52.05924589011585\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517066e4b05569d805a3df","contributors":{"authors":[{"text":"Miller, John J. 0000-0002-9098-0967 jmiller@usgs.gov","orcid":"https://orcid.org/0000-0002-9098-0967","contributorId":3785,"corporation":false,"usgs":true,"family":"Miller","given":"John","email":"jmiller@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":491999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"von Huene, Roland E. 0000-0003-1301-3866 rvonhuene@usgs.gov","orcid":"https://orcid.org/0000-0003-1301-3866","contributorId":191070,"corporation":false,"usgs":true,"family":"von Huene","given":"Roland","email":"rvonhuene@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":492000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ryan, Holly F. hryan@usgs.gov","contributorId":2375,"corporation":false,"usgs":true,"family":"Ryan","given":"Holly","email":"hryan@usgs.gov","middleInitial":"F.","affiliations":[],"preferred":false,"id":491998,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70099631,"text":"fs20143022 - 2014 - The 3D Elevation Program: summary for Montana","interactions":[],"lastModifiedDate":"2016-08-17T15:46:29","indexId":"fs20143022","displayToPublicDate":"2014-03-25T14:50:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3022","title":"The 3D Elevation Program: summary for Montana","docAbstract":"Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Montana, elevation data are critical for flood risk management, infrastructure and construction management, agriculture and precision farming, geologic resource assessment and hazard mitigation, natural resources conservation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.
\nThe National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The new 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.
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William J. Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":491994,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70093581,"text":"ofr20141023 - 2014 - Petrophysical properties, mineralogy, fractures, and flow tests in 25 deep boreholes at Yucca Mountain, Nevada","interactions":[],"lastModifiedDate":"2018-08-28T15:23:34","indexId":"ofr20141023","displayToPublicDate":"2014-03-25T14:48:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1023","title":"Petrophysical properties, mineralogy, fractures, and flow tests in 25 deep boreholes at Yucca Mountain, Nevada","docAbstract":"As part of a site investigation for the disposal of radioactive waste, numerous boreholes were drilled into a sequence of Miocene pyroclastic flows and related deposits at Yucca Mountain, Nevada. This report contains displays of data from 25 boreholes drilled during 1979–1984, relatively early in the site investigation program. Geophysical logs and hydrological tests were conducted in the boreholes; core and cuttings analyses yielded data on mineralogy, fractures, and physical properties; and geologic descriptions provided lithology boundaries and the degree of welding of the rock units. Porosity and water content were computed from the geophysical logs, and porosity results were combined with mineralogy from x-ray diffraction to provide whole-rock volume fractions. These data were composited on plates and used by project personnel during the 1990s. Improvements in scanning and computer technology now make it possible to publish these displays.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141023","usgsCitation":"Nelson, P.H., and Kibler, J.E., 2014, Petrophysical properties, mineralogy, fractures, and flow tests in 25 deep boreholes at Yucca Mountain, Nevada: U.S. Geological Survey Open-File Report 2014-1023, Report: vi, 19 p.; Downloads Directory, https://doi.org/10.3133/ofr20141023.","productDescription":"Report: vi, 19 p.; Downloads Directory","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051310","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":284900,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1023/"},{"id":284903,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1023/downloads/"},{"id":284902,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1023/pdf/of2014-1023.pdf"},{"id":284905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141023.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Yucca Mountain","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.500887,36.74929 ], [ -116.500887,36.919932 ], [ -116.374544,36.919932 ], [ -116.374544,36.74929 ], [ -116.500887,36.74929 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd6b1ae4b0b29085103ad2","contributors":{"authors":[{"text":"Nelson, Philip H. pnelson@usgs.gov","contributorId":862,"corporation":false,"usgs":true,"family":"Nelson","given":"Philip","email":"pnelson@usgs.gov","middleInitial":"H.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":490067,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kibler, Joyce E.","contributorId":56293,"corporation":false,"usgs":true,"family":"Kibler","given":"Joyce","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":490068,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70093765,"text":"tm11B5 - 2014 - Digital orthoimagery base specification V1.0","interactions":[],"lastModifiedDate":"2014-03-25T13:27:52","indexId":"tm11B5","displayToPublicDate":"2014-03-25T13:08:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"11-B5","title":"Digital orthoimagery base specification V1.0","docAbstract":"The resolution requirement for orthoimagery in support of the The National Map of the U.S. Geological Survey (USGS) is 1 meter. However, as the Office of Management and Budget A-16 designated Federal agency responsible for base orthoimagery, the USGS National Geospatial Program (NGP) has developed this base specification to include higher resolution orthoimagery. Many Federal, State, and local programs use high-resolution orthoimagery for various purposes including critical infrastructure management, vector data updates, land-use analysis, natural resource inventory, and extraction of data. The complex nature of large-area orthoimagery datasets, combined with the broad interest in orthoimagery, which is of consistent quality and spatial accuracy, requires high-resolution orthoimagery to meet or exceed the format and content outlined in this specification.
\n\nThe USGS intends to use this specification primarily to create consistency across all NGP funded and managed orthoimagery collections, in particular, collections in support of the National Digital Orthoimagery Program (NDOP). In the absence of other comprehensive specifications or standards, the USGS intends that this specification will, to the highest degree practical, be adopted by other USGS programs and mission areas, and by other Federal agencies.
\n\nThis base specification, defining minimum parameters for orthoimagery data collection. Local conditions in any given project area, specialized applications for the data, or the preferences of cooperators, may mandate more stringent requirements. The USGS fully supports the acquisition of more detailed, accurate, or value-added data that exceed the base specification outlined herein. A partial list of common “buy-up” options is provided in appendix 1 for those areas and projects that require more stringent or expanded specifications.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section B: U.S. Geological Survey Standards in Book 11 Collection and Delineation of Spatial Data","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm11B5","collaboration":"National Geospatial Program. This report is Chapter 5 of Section B: U.S. Geological Survey Standards in Book 11 Collection and Delineation of Spatial Data","usgsCitation":"Rufe, P.P., 2014, Digital orthoimagery base specification V1.0: U.S. Geological Survey Techniques and Methods 11-B5, Report: v, 13 p.; Downloads Directory, https://doi.org/10.3133/tm11B5.","productDescription":"Report: v, 13 p.; Downloads Directory","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-041313","costCenters":[{"id":425,"text":"National Geospatial Technical Operations Center","active":false,"usgs":true}],"links":[{"id":284883,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm11b5.jpg"},{"id":284881,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/11/b5/pdf/tm11-B5.pdf"},{"id":284882,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/11/b5/downloads/"},{"id":284880,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/11/b5/"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd550fe4b0b290850f61ad","contributors":{"authors":[{"text":"Rufe, Philip P. prufe@usgs.gov","contributorId":4048,"corporation":false,"usgs":true,"family":"Rufe","given":"Philip","email":"prufe@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":490206,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70099203,"text":"70099203 - 2014 - Advances in a distributed approach for ocean model data interoperability","interactions":[],"lastModifiedDate":"2014-03-25T08:24:40","indexId":"70099203","displayToPublicDate":"2014-03-24T16:14:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Advances in a distributed approach for ocean model data interoperability","docAbstract":"An infrastructure for earth science data is emerging across the globe based on common data models and web services. As we evolve from custom file formats and web sites to standards-based web services and tools, data is becoming easier to distribute, find and retrieve, leaving more time for science. We describe recent advances that make it easier for ocean model providers to share their data, and for users to search, access, analyze and visualize ocean data using MATLAB® and Python®. These include a technique for modelers to create aggregated, Climate and Forecast (CF) metadata convention datasets from collections of non-standard Network Common Data Form (NetCDF) output files, the capability to remotely access data from CF-1.6-compliant NetCDF files using the Open Geospatial Consortium (OGC) Sensor Observation Service (SOS), a metadata standard for unstructured grid model output (UGRID), and tools that utilize both CF and UGRID standards to allow interoperable data search, browse and access. We use examples from the U.S. Integrated Ocean Observing System (IOOS®) Coastal and Ocean Modeling Testbed, a project in which modelers using both structured and unstructured grid model output needed to share their results, to compare their results with other models, and to compare models with observed data. The same techniques used here for ocean modeling output can be applied to atmospheric and climate model output, remote sensing data, digital terrain and bathymetric data.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Marine Science and Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Multidisciplinary Digital Publishing Institute","doi":"10.3390/jmse2010194","usgsCitation":"Signell, R.P., and Snowden, D.P., 2014, Advances in a distributed approach for ocean model data interoperability: Journal of Marine Science and Engineering, v. 2, no. 1, p. 194-208, https://doi.org/10.3390/jmse2010194.","productDescription":"15 p.","startPage":"194","endPage":"208","ipdsId":"IP-054706","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":473095,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse2010194","text":"Publisher Index Page"},{"id":284419,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284348,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3390/jmse2010194"}],"volume":"2","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-03-19","publicationStatus":"PW","scienceBaseUri":"53516f2de4b05569d805a02d","contributors":{"authors":[{"text":"Signell, Richard P. rsignell@usgs.gov","contributorId":1435,"corporation":false,"usgs":true,"family":"Signell","given":"Richard","email":"rsignell@usgs.gov","middleInitial":"P.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":491858,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snowden, Derrick P.","contributorId":54112,"corporation":false,"usgs":true,"family":"Snowden","given":"Derrick","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":491859,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70099277,"text":"70099277 - 2014 - Hierarchical spatial capture-recapture models: Modeling population density from stratified populations","interactions":[],"lastModifiedDate":"2016-11-08T08:50:48","indexId":"70099277","displayToPublicDate":"2014-03-24T14:23:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchical spatial capture-recapture models: Modeling population density from stratified populations","docAbstract":"From August 26 to September 5, 2011, the U.S. Geological Survey (USGS) collected more than 600 line-kilometers of shipborne magnetic data on Mono Lake, 20 line-kilometers of ground magnetic data on Paoha Island, 50 gravity stations on Paoha and Negit Islands, and 28 rock samples on Paoha and Negit Islands, in east-central California. Magnetic and gravity investigations were undertaken in Mono Lake to study regional crustal structures and to aid in understanding the geologic framework, in particular regarding potential geothermal resources and volcanic hazards throughout Mono Basin. Furthermore, shipborne magnetic data illuminate local structures in the upper crust beneath Mono Lake where geologic exposure is absent.
\n\nMagnetic and gravity methods, which sense contrasting physical properties of the subsurface, are ideal for studying Mono Lake. Exposed rock units surrounding Mono Lake consist mainly of Quaternary alluvium, lacustrine sediment, aeolian deposits, basalt, and Paleozoic granitic and metasedimentary rocks (Bailey, 1989). At Black Point, on the northwest shore of Mono Lake, there is a mafic cinder cone that was produced by a subaqueous eruption around 13.3 ka. Within Mono Lake there are several small dacite cinder cones and flows, forming Negit Island and part of Paoha Island, which also host deposits of Quaternary lacustrine sediments. The typical density and magnetic properties of young volcanic rocks contrast with those of the lacustrine sediment, enabling us to map their subsurface extent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141043","usgsCitation":"Athens, N.D., Ponce, D.A., Jayko, A.S., Miller, M., McEvoy, B., Marcaida, M., Mangan, M.T., Wilkinson, S.K., McClain, J.S., Chuchel, B.A., and Denton, K.M., 2014, Magnetic and gravity studies of Mono Lake, east-central, California: U.S. Geological Survey Open-File Report 2014-1043, Report: iv, 14 p.; Metadata; Tables 2, 3, 4, https://doi.org/10.3133/ofr20141043.","productDescription":"Report: iv, 14 p.; Metadata; Tables 2, 3, 4","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-046411","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":284395,"rank":7,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141043.jpg"},{"id":417507,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_99713.htm","linkFileType":{"id":5,"text":"html"}},{"id":284386,"rank":5,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1043/","linkFileType":{"id":5,"text":"html"}},{"id":284390,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1043/pdf/ofr2014-1043.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":284394,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1043/downloads/ofr2014-1043_table4_gravity.xls"},{"id":284393,"rank":2,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1043/downloads/ofr2014-1043_table3_magnetic.xls"},{"id":284392,"rank":3,"type":{"id":7,"text":"Companion 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Center","active":true,"usgs":true}],"preferred":true,"id":491174,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ponce, David A. 0000-0003-4785-7354 ponce@usgs.gov","orcid":"https://orcid.org/0000-0003-4785-7354","contributorId":1049,"corporation":false,"usgs":true,"family":"Ponce","given":"David","email":"ponce@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":491169,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jayko, Angela S. 0000-0002-7378-0330 ajayko@usgs.gov","orcid":"https://orcid.org/0000-0002-7378-0330","contributorId":2531,"corporation":false,"usgs":true,"family":"Jayko","given":"Angela","email":"ajayko@usgs.gov","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":491171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Matt","contributorId":55742,"corporation":false,"usgs":true,"family":"Miller","given":"Matt","affiliations":[],"preferred":false,"id":491178,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McEvoy, Bobby","contributorId":51650,"corporation":false,"usgs":true,"family":"McEvoy","given":"Bobby","email":"","affiliations":[],"preferred":false,"id":491177,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marcaida, Mae mmarcaida@usgs.gov","contributorId":5345,"corporation":false,"usgs":true,"family":"Marcaida","given":"Mae","email":"mmarcaida@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":491176,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mangan, Margaret T. 0000-0002-5273-8053 mmangan@usgs.gov","orcid":"https://orcid.org/0000-0002-5273-8053","contributorId":3343,"corporation":false,"usgs":true,"family":"Mangan","given":"Margaret","email":"mmangan@usgs.gov","middleInitial":"T.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":491172,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wilkinson, Stuart K. swilk@usgs.gov","contributorId":3401,"corporation":false,"usgs":true,"family":"Wilkinson","given":"Stuart","email":"swilk@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":491173,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McClain, James S.","contributorId":103578,"corporation":false,"usgs":true,"family":"McClain","given":"James","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":491179,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Chuchel, Bruce A. chuchel@usgs.gov","contributorId":2415,"corporation":false,"usgs":true,"family":"Chuchel","given":"Bruce","email":"chuchel@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":491170,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Denton, Kevin M. 0000-0001-9604-4021 kmdenton@usgs.gov","orcid":"https://orcid.org/0000-0001-9604-4021","contributorId":5303,"corporation":false,"usgs":true,"family":"Denton","given":"Kevin","email":"kmdenton@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":491175,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70099756,"text":"70099756 - 2014 - The chemistry of hydrothermal magnetite: a review","interactions":[],"lastModifiedDate":"2014-03-26T09:28:56","indexId":"70099756","displayToPublicDate":"2014-03-24T09:22:45","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"The chemistry of hydrothermal magnetite: a review","docAbstract":"Magnetite (Fe3O4) is a well-recognized petrogenetic indicator and is a common accessory mineral in many ore deposits and their host rocks. Recent years have seen an increased interest in the use of hydrothermal magnetite for provenance studies and as a pathfinder for mineral exploration. A number of studies have investigated how specific formation conditions are reflected in the composition of the respective magnetite. Two fundamental questions underlie these efforts — (i) How can the composition of igneous and, more importantly, hydrothermal magnetite be used to discriminate mineralized areas from barren host rocks, and (ii) how can this assist exploration geologists to target ore deposits at greater and greater distances from the main mineralization? Similar to igneous magnetite, the most important factors that govern compositional variations in hydrothermal magnetite are (A) temperature, (B) fluid composition — element availability, (C) oxygen and sulfur fugacity, (D) silicate and sulfide activity, (E) host rock buffering, (F) re-equilibration processes, and (G) intrinsic crystallographic controls such as ionic radius and charge balance. We discuss how specific formation conditions are reflected in the composition of magnetite and review studies that investigate the chemistry of hydrothermal and igneous magnetite from various mineral deposits and their host rocks. Furthermore, we discuss the redox-related alteration of magnetite (martitization and mushketovitization) and mineral inclusions in magnetite and their effect on chemical analyses. Our database includes published and previously unpublished magnetite minor and trace element data for magnetite from (1) banded iron formations (BIF) and related high-grade iron ore deposits in Western Australia, India, and Brazil, (2) Ag–Pb–Zn veins of the Coeur d'Alene district, United States, (3) porphyry Cu–(Au)–(Mo) deposits and associated (4) calcic and magnesian skarn deposits in the southwestern United States and Indonesia, and (5) plutonic igneous rocks from the Henderson Climax-type Mo deposit, United States, and the un-mineralized Inner Zone Batholith granodiorite, Japan. These five settings represent a diverse suite of geological settings and cover a wide range of formation conditions.\n\nThe main discriminator elements for magnetite are Mg, Al, Ti, V, Cr, Mn, Co, Ni, Zn, and Ga. These elements are commonly present at detectable levels (10 to > 1000 ppm) and display systematic variations. We propose a combination of Ni/(Cr + Mn) vs. Ti + V, Al + Mn vs. Ti + V, Ti/V and Sn/Ga discriminant plots and upper threshold concentrations to discriminate hydrothermal from igneous magnetite and to fingerprint different hydrothermal ore deposits. The overall trends in upper threshold values for the different settings can be summarized as follows: (I) BIF (hydrothermal) — low Al, Ti, V, Cr, Mn, Co, Ni, Zn, Ga and Sn; (II) Ag–Pb–Zn veins (hydrothermal) — high Mn and low Ga and Sn; (III) Mg-skarn (hydrothermal) — high Mg and Mn and low Al, Ti, Cr, Co, Ni and Ga; (IV) skarn (hydrothermal) — high Mg, Al, Cr, Mn, Co, Ni and Zn and low Sn; (V) porphyry (hydrothermal) — high Ti and V and low Sn; (VI) porphyry (igneous) — high Ti, V and Cr and low Mg; and (VII) Climax-Mo (igneous) — high Al, Ga and Sn and low Mg and Cr.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ore Geology Reviews","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2013.12.013","usgsCitation":"Nadoll, P., Angerer, T., Mauk, J.L., French, D., and Walshe, J., 2014, The chemistry of hydrothermal magnetite: a review: Ore Geology Reviews, v. 61, p. 1-32, https://doi.org/10.1016/j.oregeorev.2013.12.013.","productDescription":"32 p.","startPage":"1","endPage":"32","ipdsId":"IP-045680","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":284926,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284925,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.oregeorev.2013.12.013"}],"volume":"61","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517068e4b05569d805a3f7","contributors":{"authors":[{"text":"Nadoll, Patrick","contributorId":106407,"corporation":false,"usgs":true,"family":"Nadoll","given":"Patrick","affiliations":[],"preferred":false,"id":492014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angerer, Thomas","contributorId":100737,"corporation":false,"usgs":true,"family":"Angerer","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":492013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mauk, Jeffrey L. 0000-0002-6244-2774 jmauk@usgs.gov","orcid":"https://orcid.org/0000-0002-6244-2774","contributorId":4101,"corporation":false,"usgs":true,"family":"Mauk","given":"Jeffrey","email":"jmauk@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":492010,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"French, David","contributorId":92162,"corporation":false,"usgs":true,"family":"French","given":"David","email":"","affiliations":[],"preferred":false,"id":492012,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walshe, John","contributorId":29299,"corporation":false,"usgs":true,"family":"Walshe","given":"John","email":"","affiliations":[],"preferred":false,"id":492011,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70095134,"text":"ofr20131297 - 2014 - Analysis of pharmaceutical and other organic wastewater compounds in filtered and unfiltered water samples by gas chromatography/mass spectrometry","interactions":[],"lastModifiedDate":"2014-03-25T11:02:20","indexId":"ofr20131297","displayToPublicDate":"2014-03-24T07:53:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1297","title":"Analysis of pharmaceutical and other organic wastewater compounds in filtered and unfiltered water samples by gas chromatography/mass spectrometry","docAbstract":"Research on the effects of exposure of stream biota to complex mixtures of pharmaceuticals and other organic compounds associated with wastewater requires the development of additional analytical capabilities for these compounds in water samples. Two gas chromatography/mass spectrometry (GC/MS) analytical methods used at the U.S. Geological Survey National Water Quality Laboratory (NWQL) to analyze organic compounds associated with wastewater were adapted to include additional pharmaceutical and other organic compounds beginning in 2009. This report includes a description of method performance for 42 additional compounds for the filtered-water method (hereafter referred to as the filtered method) and 46 additional compounds for the unfiltered-water method (hereafter referred to as the unfiltered method). The method performance for the filtered method described in this report has been published for seven of these compounds; however, the addition of several other compounds to the filtered method and the addition of the compounds to the unfiltered method resulted in the need to document method performance for both of the modified methods. Most of these added compounds are pharmaceuticals or pharmaceutical degradates, although two nonpharmaceutical compounds are included in each method. The main pharmaceutical compound classes added to the two modified methods include muscle relaxants, opiates, analgesics, and sedatives. These types of compounds were added to the original filtered and unfiltered methods largely in response to the tentative identification of a wide range of pharmaceutical and other organic compounds in samples collected from wastewater-treatment plants.
\nFiltered water samples are extracted by vacuum through disposable solid-phase cartridges that contain modified polystyrene-divinylbenzene resin. Unfiltered samples are extracted by using continuous liquid-liquid extraction with dichloromethane. The compounds of interest for filtered and unfiltered sample types were determined by use of the capillary-column gas chromatography/mass spectrometry.
\nThe performance of each method was assessed by using data on recoveries of compounds in fortified surface-water, wastewater, and reagent-water samples. These experiments (referred to as spike experiments) consist of fortifying (or spiking) samples with known amounts of target analytes. Surface-water-spike experiments were performed by using samples obtained from a stream in Colorado (unfiltered method) and a stream in New York (filtered method). Wastewater spike experiments for both the filtered and unfiltered methods were performed by using a treated wastewater obtained from a single wastewater treatment plant in New York. Surface water and wastewater spike experiments were fortified at both low and high concentrations and termed low- and high-level spikes, respectively. Reagent water spikes were assessed in three ways: (1) set spikes, (2) a low-concentration fortification experiment, and (3) a high-concentration fortification experiment. Set spike samples have been determined since 2009, and consist of analysis of fortified reagent water for target compounds included for each group of 10 to18 environmental samples analyzed at the NWQL. The low-concentration and high-concentration reagent spike experiments, by contrast, represent a one-time assessment of method performance. For each spike experiment, mean recoveries ranging from 60 to 130 percent indicate low bias, and relative standard deviations (RSDs) less than (<) 30 percent indicate low variability.
\nOf the compounds included in the filtered method, 21 had mean recoveries ranging from 63 to 129 percent for the low-level and high-level surface-water spikes, and had low (<15 percent) RSDs for these spikes. The remaining 21 compounds generally had high bias for the low-level or the high-level spike experiments for surface water [mean recoveries <58 percent or greater than (>)132 percent]. For wastewater spikes, 24 of the compounds included in the filtered method had recoveries ranging from 61 to 130 percent for the low-level and high-level spikes. RSDs were <29 percent for both of these spike experiments for the 24 compounds. The remaining 18 compounds in the filtered method generally had high recoveries (>130 percent) or variable recoveries (RSDs >30 percent) for low-level wastewater spikes, or low recoveries (<60 percent) for high-level wastewater spikes. Of the compounds included in the filtered method, 34 had mean set-spike recoveries between 61 and 126 percent, and RSDs <30 percent.
\nOf the compounds included in the unfiltered method, 17 had mean spike recoveries ranging from 74 to 129 percent and RSDs ranging from 5 to 25 percent for low-level and high-level surface water spikes. The remaining compounds had poor mean recoveries (<60 or >130 percent), or high RSDs (>29 percent) for these spikes. For wastewater, 14 of the compounds included in the unfiltered method had mean recoveries ranging from 62 to 127 percent and RSDs <25 percent for the low-level and high-level spikes. Most of the remaining compounds had high mean recoveries for wastewater (>130 percent), or low mean recoveries (<20 percent) or high RSDs (>33 percent) for the low-level wastewater spikes. Of the compounds found in wastewater, 24 had mean set spike recoveries ranging from 64 to 104 percent and RSDs <30 percent.
\nSeparate method detection limits (MDLs) were computed for surface water and wastewater for both the filtered and unfiltered methods. Filtered method MDLs ranged from 0.007 to 0.14 microgram per liter (μg/L) for the surface water matrix and from 0.004 to 0.62 μg/L for the wastewater matrix. Unfiltered method MDLs ranged from 0.014 to 0.33 μg/L for the surface water matrix and from 0.008 to 0.36 μg/L for the wastewater matrix.
","language":"English","publisher":"U.S Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131297","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Zaugg, S.D., Phillips, P., and Smith, S.G., 2014, Analysis of pharmaceutical and other organic wastewater compounds in filtered and unfiltered water samples by gas chromatography/mass spectrometry: U.S. Geological Survey Open-File Report 2013-1297, Report: v, 24 p.; Appendix, https://doi.org/10.3133/ofr20131297.","productDescription":"Report: v, 24 p.; Appendix","onlineOnly":"Y","ipdsId":"IP-040896","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":284375,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131297.jpg"},{"id":284374,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1297/tables/ofr2013-1297_tables1-appendix1.xlsx"},{"id":284372,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1297/"},{"id":284373,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1297/pdf/ofr2013-1297.pdf"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4ce0e4b0b290850f13b4","contributors":{"authors":[{"text":"Zaugg, Steven D. sdzaugg@usgs.gov","contributorId":768,"corporation":false,"usgs":true,"family":"Zaugg","given":"Steven","email":"sdzaugg@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":491079,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Patrick J. pjphilli@usgs.gov","contributorId":856,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick J.","email":"pjphilli@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":491080,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Steven G. sgsmith@usgs.gov","contributorId":1560,"corporation":false,"usgs":true,"family":"Smith","given":"Steven","email":"sgsmith@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":491081,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70094915,"text":"fs20143013 - 2014 - The 3D Elevation Program: summary for Maine","interactions":[],"lastModifiedDate":"2016-08-17T15:47:53","indexId":"fs20143013","displayToPublicDate":"2014-03-24T07:28:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3013","title":"The 3D Elevation Program: summary for Maine","docAbstract":"Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Maine, elevation data are critical for natural resources conservation, flood risk management, forest resources management, agriculture and precision farming, coastal zone management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.
\nThe National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.
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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":490945,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70094636,"text":"ofr20141034 - 2014 - Water-quality, bed-sediment, and biological data (October 2011 through September 2012) and statistical summaries of data for streams in the Clark Fork Basin, Montana","interactions":[],"lastModifiedDate":"2014-03-24T07:25:07","indexId":"ofr20141034","displayToPublicDate":"2014-03-24T07:16:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1034","title":"Water-quality, bed-sediment, and biological data (October 2011 through September 2012) and statistical summaries of data for streams in the Clark Fork Basin, Montana","docAbstract":"Water, bed sediment, and biota were sampled in streams from Butte to near Missoula, Montana, as part of a monitoring program in the upper Clark Fork Basin of western Montana. The sampling program was conducted by the U.S. Geological Survey in cooperation with the U.S. Environmental Protection Agency to characterize aquatic resources in the Clark Fork Basin, with emphasis on trace elements associated with historic mining and smelting activities. Sampling sites were located on the Clark Fork and selected tributaries. Water samples were collected periodically at 20 sites from October 2011 through September 2012. Bed-sediment and biota samples were collected once at 13 sites during August 2012.
\nThis report presents the analytical results and quality-assurance data for water-quality, bed-sediment, and biota samples collected at sites from October 2011 through September 2012. Water-quality data include concentrations of selected major ions, trace elements, and suspended sediment. Turbidity was analyzed for water samples collected at the four sites where seasonal daily values of turbidity were being determined. Daily values of suspended-sediment concentration and suspended-sediment discharge were determined for four sites. Bed-sediment data include trace-element concentrations in the fine-grained fraction. Biological data include trace-element concentrations in whole-body tissue of aquatic benthic insects. Statistical summaries of water-quality, bed-sediment, and biological data for sites in the upper Clark Fork Basin are provided for the period of record since 1985.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141034","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Dodge, K.A., Hornberger, M.I., and Dyke, J., 2014, Water-quality, bed-sediment, and biological data (October 2011 through September 2012) and statistical summaries of data for streams in the Clark Fork Basin, Montana: U.S. Geological Survey Open-File Report 2014-1034, vi, 121 p., https://doi.org/10.3133/ofr20141034.","productDescription":"vi, 121 p.","additionalOnlineFiles":"Y","ipdsId":"IP-049914","costCenters":[{"id":400,"text":"Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":284361,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141034.jpg"},{"id":284360,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1034/pdf/of2014-1034.pdf"},{"id":284352,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1034/"}],"scale":"1000000","datum":"NAD 27","country":"United States","state":"Montana","otherGeospatial":"Clark Fork Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.0,45.0 ], [ -114.0,47.0 ], [ -112.0,47.0 ], [ -112.0,45.0 ], [ -114.0,45.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7d35e4b0b2908510f3d4","contributors":{"authors":[{"text":"Dodge, Kent A. kdodge@usgs.gov","contributorId":1036,"corporation":false,"usgs":true,"family":"Dodge","given":"Kent","email":"kdodge@usgs.gov","middleInitial":"A.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490679,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hornberger, Michelle I. 0000-0002-7787-3446 mhornber@usgs.gov","orcid":"https://orcid.org/0000-0002-7787-3446","contributorId":1037,"corporation":false,"usgs":true,"family":"Hornberger","given":"Michelle","email":"mhornber@usgs.gov","middleInitial":"I.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":490680,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dyke, Jessica jldyke@usgs.gov","contributorId":1035,"corporation":false,"usgs":true,"family":"Dyke","given":"Jessica","email":"jldyke@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":490678,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70134498,"text":"70134498 - 2014 - Large natural pH, CO2 and O2 fluctuations in a temperate tidal salt marsh on diel, seasonal, and interannual time scales","interactions":[],"lastModifiedDate":"2020-12-23T16:21:27.378371","indexId":"70134498","displayToPublicDate":"2014-03-21T13:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Large natural pH, CO2 and O2 fluctuations in a temperate tidal salt marsh on diel, seasonal, and interannual time scales","title":"Large natural pH, CO2 and O2 fluctuations in a temperate tidal salt marsh on diel, seasonal, and interannual time scales","docAbstract":"Coastal marine organisms experience dynamic pH and dissolved oxygen (DO) conditions in their natural habitats, which may impact their susceptibility to long-term anthropogenic changes. Robust characterizations of all temporal scales of natural pH and DO fluctuations in different marine habitats are needed; however, appropriate time series of pH and DO are still scarce. We used multiyear (2008–2012), high-frequency (6 min) monitoring data to quantify diel, seasonal, and interannual scales of pH and DO variability in a productive, temperate tidal salt marsh (Flax Pond, Long Island, US). pHNBS and DO showed strong and similar seasonal patterns, with average (minimum) conditions declining from 8.2 (8.1) and 12.5 (11.4) mg l−1 at the end of winter to 7.6 (7.2) and 6.3 (2.8) mg l−1 in late summer, respectively. Concomitantly, average diel fluctuations increased from 0.22 and 2.2 mg l−1 (February) to 0.74 and 6.5 mg l−1 (August), respectively. Diel patterns were modulated by tides and time of day, eliciting the most extreme minima when low tides aligned with the end of the night. Simultaneous in situ pCO2 measurements showed striking fluctuations between ∼330 and ∼1,200 (early May), ∼2,200 (mid June), and ∼4,000 μatm (end of July) within single tidal cycles. These patterns also indicate that the marsh’s strong net heterotrophy influences its adjacent estuary by ‘outwelling’ acidified and hypoxic water during ebb tides. Our analyses emphasize the coupled and fluctuating nature of pH and DO conditions in productive coastal and estuarine environments, which have yet to be adequately represented by experiments.
","language":"English","publisher":"Springer Link","doi":"10.1007/s12237-014-9800-y","usgsCitation":"Baumann, H., Wallace, R., Tagliaferri, T.N., and Gobler, C.J., 2014, Large natural pH, CO2 and O2 fluctuations in a temperate tidal salt marsh on diel, seasonal, and interannual time scales: Estuaries and Coasts, v. 38, p. 220-231, https://doi.org/10.1007/s12237-014-9800-y.","productDescription":"12 p.","startPage":"220","endPage":"231","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052918","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":296386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Flax Pond, Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.15135002136229,\n 40.95967830900992\n ],\n [\n -73.13070774078369,\n 40.95967830900992\n ],\n [\n -73.13070774078369,\n 40.96816877082855\n ],\n [\n -73.15135002136229,\n 40.96816877082855\n ],\n [\n -73.15135002136229,\n 40.95967830900992\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","noUsgsAuthors":false,"publicationDate":"2014-03-21","publicationStatus":"PW","scienceBaseUri":"547ee2cce4b09357f05f8a5f","contributors":{"authors":[{"text":"Baumann, Hannes","contributorId":127638,"corporation":false,"usgs":false,"family":"Baumann","given":"Hannes","affiliations":[{"id":7093,"text":"Adjunct Assist Prof, School of Marine & Atmospheric Sciences, Stony Brook Univ","active":true,"usgs":false}],"preferred":false,"id":526053,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wallace, Ryan","contributorId":127639,"corporation":false,"usgs":false,"family":"Wallace","given":"Ryan","email":"","affiliations":[{"id":7094,"text":"Grad Student, School of Marine & Atmospheric Sciences, Stony Brook Univ","active":true,"usgs":false}],"preferred":false,"id":526054,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tagliaferri, Tristen N. 0000-0001-7408-7899 ttagliaferri@usgs.gov","orcid":"https://orcid.org/0000-0001-7408-7899","contributorId":5138,"corporation":false,"usgs":true,"family":"Tagliaferri","given":"Tristen","email":"ttagliaferri@usgs.gov","middleInitial":"N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":526052,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gobler, Christopher J.","contributorId":127640,"corporation":false,"usgs":false,"family":"Gobler","given":"Christopher","email":"","middleInitial":"J.","affiliations":[{"id":7095,"text":"Professor, School of Marine & Atmospheric Sciences, Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":526055,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187384,"text":"70187384 - 2014 - Transmission of chronic wasting disease in Wisconsin white-tailed deer: Implications for disease spread and management","interactions":[],"lastModifiedDate":"2017-05-01T12:47:43","indexId":"70187384","displayToPublicDate":"2014-03-21T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Transmission of chronic wasting disease in Wisconsin white-tailed deer: Implications for disease spread and management","docAbstract":"Few studies have evaluated the rate of infection or mode of transmission for wildlife diseases, and the implications of alternative management strategies. We used hunter harvest data from 2002 to 2013 to investigate chronic wasting disease (CWD) infection rate and transmission modes, and address how alternative management approaches affect disease dynamics in a Wisconsin white-tailed deer population. Uncertainty regarding demographic impacts of CWD on cervid populations, human and domestic animal health concerns, and potential economic consequences underscore the need for strategies to control CWD distribution and prevalence. Using maximum-likelihood methods to evaluate alternative multi-state deterministic models of CWD transmission, harvest data strongly supports a frequency-dependent transmission structure with sex-specific infection rates that are two times higher in males than females. As transmissible spongiform encephalopathies are an important and difficult-to-study class of diseases with major economic and ecological implications, our work supports the hypothesis of frequency-dependent transmission in wild deer at a broad spatial scale and indicates that effective harvest management can be implemented to control CWD prevalence. Specifically, we show that harvest focused on the greater-affected sex (males) can result in stable population dynamics and control of CWD within the next 50 years, given the constraints of the model. We also provide a quantitative estimate of geographic disease spread in southern Wisconsin, validating qualitative assessments that CWD spreads relatively slowly. Given increased discovery and distribution of CWD throughout North America, insights from our study are valuable to management agencies and to the general public concerned about the impacts of CWD on white-tailed deer populations.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0091043","usgsCitation":"Jennelle, C., Henaux, V., Wasserberg, G., Thiagarajan, B., Rolley, R.E., and Samuel, M.D., 2014, Transmission of chronic wasting disease in Wisconsin white-tailed deer: Implications for disease spread and management: PLoS ONE, v. 9, no. 3, p. 1-12, https://doi.org/10.1371/journal.pone.0091043.","productDescription":" e91043; 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-038460","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":473099,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0091043","text":"Publisher Index Page"},{"id":340673,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","volume":"9","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-03-21","publicationStatus":"PW","scienceBaseUri":"59084932e4b0fc4e448ffd82","contributors":{"authors":[{"text":"Jennelle, Christopher S.","contributorId":50823,"corporation":false,"usgs":true,"family":"Jennelle","given":"Christopher S.","affiliations":[],"preferred":false,"id":693757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Henaux, Viviane","contributorId":171388,"corporation":false,"usgs":false,"family":"Henaux","given":"Viviane","email":"","affiliations":[{"id":24576,"text":"University of Wisconsin, Madison, WI","active":true,"usgs":false}],"preferred":false,"id":693758,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wasserberg, Gideon","contributorId":31185,"corporation":false,"usgs":true,"family":"Wasserberg","given":"Gideon","email":"","affiliations":[],"preferred":false,"id":693759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thiagarajan, Bala","contributorId":92520,"corporation":false,"usgs":true,"family":"Thiagarajan","given":"Bala","email":"","affiliations":[],"preferred":false,"id":693760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rolley, Robert E.","contributorId":171376,"corporation":false,"usgs":false,"family":"Rolley","given":"Robert","email":"","middleInitial":"E.","affiliations":[{"id":24833,"text":"Wisconsin DNR, Madison, WI","active":true,"usgs":false}],"preferred":false,"id":693761,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Samuel, Michael D. msamuel@usgs.gov","contributorId":1419,"corporation":false,"usgs":true,"family":"Samuel","given":"Michael","email":"msamuel@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693721,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70098154,"text":"ofr20141056 - 2014 - Summary and abstracts of the Planetary Data Workshop, June 2012","interactions":[],"lastModifiedDate":"2019-02-11T10:40:55","indexId":"ofr20141056","displayToPublicDate":"2014-03-20T16:01:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1056","title":"Summary and abstracts of the Planetary Data Workshop, June 2012","docAbstract":"The recent boom in the volume of digital data returned by international planetary science missions continues to both delight and confound users of those data. In just the past decade, the Planetary Data System (PDS), NASA’s official archive of scientific results from U.S. planetary missions, has seen a nearly 50-fold increase in the amount of data and now serves nearly half a petabyte. In only a handful of years, this volume is expected to approach 1 petabyte (1,000 terabytes or 1 quadrillion bytes). Although data providers, archivists, users, and developers have done a creditable job of providing search functions, download capabilities, and analysis and visualization tools, the new wealth of data necessitates more frequent and extensive discussion among users and developers about their current capabilities and their needs for improved and new tools. A workshop to address these and other topics, “Planetary Data: A Workshop for Users and Planetary Software Developers,” was held June 25–29, 2012, at Northern Arizona University (NAU) in Flagstaff, Arizona. A goal of the workshop was to present a summary of currently available tools, along with hands-on training and how-to guides, for acquiring, processing and working with a variety of digital planetary data. The meeting emphasized presentations by data users and mission providers during days 1 and 2, and developers had the floor on days 4 and 5 using an “unconference” format for day 5. Day 3 featured keynote talks by Laurence Soderblom (U.S. Geological Survey, USGS) and Dan Crichton (Jet Propulsion Laboratory, JPL) followed by a panel discussion, and then research and technical discussions about tools and capabilities under recent or current development. Software and tool demonstrations were held in break-out sessions in parallel with the oral session. Nearly 150 data users and developers from across the globe attended, and 22 National Aeronautics and space Administration (NASA) and non-NASA data providers and missions were represented. Presentations (some in video format) and tutorials are posted on the meeting site (http://astrogeology.usgs.gov/groups/Planetary-Data-Workshop).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141056","issn":"2331-1258","usgsCitation":"Gaddis, L.R., Hare, T.M., and Beyer, R., 2014, Summary and abstracts of the Planetary Data Workshop, June 2012: U.S. Geological Survey Open-File Report 2014-1056, v, 199 p., https://doi.org/10.3133/ofr20141056.","productDescription":"v, 199 p.","onlineOnly":"Y","temporalStart":"2012-06-01","temporalEnd":"2012-06-30","ipdsId":"IP-049475","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":284345,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141056.PNG"},{"id":284344,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1056/pdf/ofr2014-1056.pdf"},{"id":284090,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1056/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7517e4b0b2908510a08c","contributors":{"authors":[{"text":"Gaddis, Lisa R. 0000-0001-9953-5483 lgaddis@usgs.gov","orcid":"https://orcid.org/0000-0001-9953-5483","contributorId":2817,"corporation":false,"usgs":true,"family":"Gaddis","given":"Lisa","email":"lgaddis@usgs.gov","middleInitial":"R.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":491648,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hare, Trent M. 0000-0001-8842-389X thare@usgs.gov","orcid":"https://orcid.org/0000-0001-8842-389X","contributorId":3188,"corporation":false,"usgs":true,"family":"Hare","given":"Trent","email":"thare@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":491649,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beyer, Ross","contributorId":71607,"corporation":false,"usgs":true,"family":"Beyer","given":"Ross","affiliations":[],"preferred":false,"id":491650,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}