This report describes a reconnaissance study of estuarine bed-sediment quality conducted June–October 2013 in New Jersey and New York after Hurricane Sandy in October 2012 to assess the extent of contamination and the potential long-term human and ecological impacts of the storm. The study, funded through the Disaster Relief Appropriations Act of 2013 (PL 113-2), was conducted by the U.S. Geological Survey in cooperation with the U.S. Environmental Protection Agency and the National Oceanographic and Atmospheric Administration. In addition to presenting the bed-sediment-quality data, the report describes the study design, documents the methods of sample collection and analysis, and discusses the steps taken to assure the quality of the data.
\nBed-sediment samples were collected from June to October 2013 from 167 estuarine sites extending from Cape May, New Jersey, to the New York Harbor and the eastern end of Long Island. Each sampling location and study region was characterized by using geographic information to identify potential contaminant sources. Characterizations included land cover, locations and types of businesses (industrial, financial, and others), spills (sewage, chemical, and others), bulk storage facilities, effluent discharges within 2 kilometers of the sampling point, and discharges within inundated and non-inundated regions near the sampling location. Samples were analyzed for particle size, total organic carbon, metals and trace elements, semivolatile organic compounds, wastewater compounds, hormones, and sediment toxicity. Samples were also screened using x-ray fluorescence, Fourier transform infrared spectroscopy, and x-ray diffraction. In addition, bioassays for endocrine disruptors and protein phosphatase 2A inhibition were conducted. The study was designed to provide the data needed to understand the extent and sources of contamination resulting from Hurricane Sandy, to compare the chemistry and toxicity of estuarine bed sediments before and after the storm, and to evaluate the usefulness of rapid screening and bioassay approaches in disaster settings.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds905","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, National Oceanic and Atmospheric Administration, New Jersey Department of Environmental Protection, New York State Department of Environmental Conservation, New York City Department of Environmental Protection, Suffolk County Department of Health Services, and Town of Hempstead","usgsCitation":"Fischer, J., Phillips, P., Reilly, T.J., Focazio, M.J., Loftin, K.A., Benzel, W., Jones, D.K., Smalling, K., Fisher, S.C., Fisher, I., Iwanowicz, L., Romanok, K., Jenkins, D.E., Bowers, L., Boehlke, A., Foreman, W., Deetz, A., Carper, L.G., Imbrigiotta, T., and Birdwell, J.E., 2015, Estuarine bed-sediment-quality data collected in New Jersey and New York after Hurricane Sandy, 2013: U.S. Geological Survey Data Series 905, Report: xiv, 42 p.; 38 Tables; Downloads Directory, 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Sea-level-rise scenarios used as model inputs are generated by using multiple sources of information, including Coupled Model Intercomparison Project Phase 5 models following representative concentration pathways 4.5 and 8.5 in the Intergovernmental Panel on Climate Change Fifth Assessment Report. A Bayesian network is used to develop a predictive coastal response model that integrates the sea-level, elevation, and land-cover data with assigned probabilities that account for interactions with coastal geomorphology as well as the corresponding ecological and societal systems it supports. The effects of sea-level rise are presented as (1) level of landscape submergence and (2) coastal response type characterized as either static (that is, inundation) or dynamic (that is, landform or landscape change). Results are produced at a spatial scale of 30 meters for four decades (the 2020s, 2030s, 2050s, and 2080s). The probabilistic predictions can be applied to landscape management decisions based on sea-level-rise effects as well as on assessments of the prediction uncertainty and need for improved data or fundamental understanding. This report describes the methods used to produce predictions, including information on input datasets; the modeling approach; model outputs; data-quality-control procedures; and information on how to access the data and metadata online.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141252","usgsCitation":"Lentz, E.E., Stippa, S.R., Thieler, E.R., Plant, N.G., Gesch, D.B., and Horton, R.M., 2015, Evaluating coastal landscape response to sea-level rise in the northeastern United States—Approach and methods (ver. 2.0, December 2015): U.S. Geological Survey Open-File Report 2014–1252, 26 p., https://dx.doi.org/10.3133/ofr20141252.","productDescription":"Report: vi, 26 p.; Dataset; Project Web Page","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-058567","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438725,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73J3B0B","text":"USGS data release","linkHelpText":"Coastal Landscape Response to Sea-Level Rise Assessment for the Northeastern United States Data Release"},{"id":297982,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1252/"},{"id":297983,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1252/pdf/ofr2014-1252.pdf","size":"4.23 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297985,"rank":5,"type":{"id":18,"text":"Project Site"},"url":"https://woodshole.er.usgs.gov/project-pages/coastal_response/","text":"Coastal Landscape Response Project","linkFileType":{"id":5,"text":"html"}},{"id":297986,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2014/1252/images/coverthb.jpg"},{"id":297984,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://woodshole.er.usgs.gov/project-pages/coastal_response/data.html","text":"Landscape change predictions for the 2020s, 2030s, 2050s, and 2080s","linkFileType":{"id":5,"text":"html"}},{"id":312642,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2014/1252/versionHist.txt"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.19238281249999,\n 45.19752230305685\n ],\n [\n -69.23583984375,\n 44.69989765840318\n ],\n [\n -71.34521484375,\n 43.59630591596548\n ],\n [\n -71.69677734375,\n 41.96765920367816\n ],\n [\n -74.72900390625,\n 41.21172151054787\n ],\n [\n -77.6953125,\n 38.993572058209466\n ],\n [\n -77.49755859375,\n 36.54494944148322\n ],\n [\n -75.89355468749999,\n 36.56260003738548\n ],\n [\n -71.7626953125,\n 40.88029480552824\n ],\n [\n -69.80712890625,\n 41.11246878918086\n ],\n [\n -69.67529296875,\n 42.09822241118974\n ],\n [\n -70.24658203125,\n 42.779275360241904\n ],\n [\n -68.8623046875,\n 43.77109381775651\n ],\n [\n -66.796875,\n 44.715513732021336\n ],\n [\n -67.19238281249999,\n 45.19752230305685\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted February 13, 2015; Version 2.0: December 21, 2015","contact":"Director, Woods Hole Coastal and Marine Science Center
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In 2011, the U.S. Geological Survey and the U.S. Army Corps of Engineers began monitoring the saltwater interface near Lake Okeechobee to evaluate changes in interface depth that could possibly be related to the repair of the Herbert Hoover Dike. A seepage barrier (or cut-off wall), installed by the U.S. Army Corps of Engineers, is a wall of grout designed to protect the Herbert Hoover Dike from internal erosion caused by the piping of water. The seepage barrier prevents water from flowing through or immediately under the dike by diverting the flow below the dike, into the surficial aquifer system. The seepage barrier extends below the saltwater interface in some areas. Monitoring consisted of collecting water samples and time series electromagnetic-induction log (TSEMIL) datasets from 10 well clusters, each of which have 1 shallow and 1 deep monitoring well, with 5- to 10-foot- (ft) long-screened intervals. The deep wells are 120 to 187 ft deep, and the shallow wells are 44 to 100 ft deep.
\nChanges in the depth of the saltwater interface were identified that correspond closely to the depth of the bottom of the seepage barrier. These changes may have been the consequence of changes in groundwater flow initiated by the seepage barrier installation. In areas of the dike where a seepage barrier had not been installed, or where the bottom of the seepage barrier is well above the saltwater interface, monitoring detected no changes in the depth of the saltwater interface.
\nAt five of the monitoring-well cluster locations, a long-screened well was also installed for monitoring and comparison purposes. These long-screened wells are 160 to 200 ft deep, and have open intervals ranging from 145 to 185 ft in length. Water samples were collected at depth intervals of about 5 to 10 ft, using 3-ft-long straddle packers to isolate each sampling interval. The results of monitoring conducted using these long-screened interval wells were generally too variable to identify any changes that might be associated with the seepage barrier. Samples from one of these long-screened interval wells failed to detect the saltwater interface evident in samples and TSEMIL datasets from a collocated well cluster. This failure may have been caused by downward flow of freshwater from above the saltwater interface in the well bore.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141256","usgsCitation":"Prinos, S.T., and Valderrama, R., 2015, Changes in the saltwater interface corresponding to the installation of a seepage barrier near Lake Okeechobee, Florida: U.S. Geological Survey Open-File Report 2014-1256, Report: vii, 24 p.; 2 Appendixes, https://doi.org/10.3133/ofr20141256.","productDescription":"Report: vii, 24 p.; 2 Appendixes","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-058177","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":297981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141256.jpg"},{"id":297979,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1256/appendix/ofr2014-1256_appendix01.xlsx","text":"Appendix 1","size":"30 kB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"Results of water samples from selected long-screened interval monitoring wells."},{"id":297978,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1256/pdf/ofr2014-1256.pdf","size":"6.90 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297980,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1256/appendix/ofr2014-1256_appendix02.xlsx","text":"Appendix 2","size":"33.6 kB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"Results of water samples from selected short-screened interval monitoring wells."},{"id":297967,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1256/"}],"country":"United States","state":"Florida","otherGeospatial":"Lake Okeechobee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.15875244140625,\n 26.674458841825206\n ],\n [\n -81.15875244140625,\n 27.21311366818236\n ],\n [\n -80.60531616210938,\n 27.21311366818236\n ],\n [\n -80.60531616210938,\n 26.674458841825206\n ],\n [\n -81.15875244140625,\n 26.674458841825206\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54df2028e4b08de9379b3a2f","contributors":{"authors":[{"text":"Prinos, Scott T. 0000-0002-5776-8956 stprinos@usgs.gov","orcid":"https://orcid.org/0000-0002-5776-8956","contributorId":4045,"corporation":false,"usgs":true,"family":"Prinos","given":"Scott","email":"stprinos@usgs.gov","middleInitial":"T.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540580,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Valderrama, Robert rvalder@usgs.gov","contributorId":5710,"corporation":false,"usgs":true,"family":"Valderrama","given":"Robert","email":"rvalder@usgs.gov","affiliations":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"preferred":false,"id":540581,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70137951,"text":"ofr20141246 - 2015 - Water-level and wave measurements in the Chandeleur Islands, Louisiana, 2012 and 2013","interactions":[],"lastModifiedDate":"2015-02-13T15:50:07","indexId":"ofr20141246","displayToPublicDate":"2015-02-13T16:45:00","publicationYear":"2015","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":"2014-1246","title":"Water-level and wave measurements in the Chandeleur Islands, Louisiana, 2012 and 2013","docAbstract":"This report documents measurements of atmospheric pressure, water levels, and waves made by the U.S. Geological Survey in the Chandeleur Islands, Louisiana, during 2012 and 2013 as part of the Barrier Island Evolution Research project. Simple, inexpensive pressure sensors mounted in shallow wells were buried in the beach and left for one hurricane season and one winter-storm season. Gauges with rapid-sampling pressure sensors that provided nondirectional wave data and water-level data were mounted on rugged mounts on the Chandeleur Sound side and at the base of a tower at the northern end of the island chain. Additionally, an atmospheric pressure sensor was mounted on the tower to provide a local atmospheric pressure measurement for correcting the submerged pressure records.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141246","usgsCitation":"Dickhudt, P., Sherwood, C.R., and DeWitt, N.T., 2015, Water-level and wave measurements in the Chandeleur Islands, Louisiana, 2012 and 2013: U.S. Geological Survey Open-File Report 2014-1246, Report: HTML Document; Report: viii, 49 p., https://doi.org/10.3133/ofr20141246.","productDescription":"Report: HTML Document; Report: viii, 49 p.","numberOfPages":"59","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2012-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-056460","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":297977,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141246.JPG"},{"id":297974,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1246/"},{"id":297975,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1246/ofr2014-1246-title_page.html","text":"Report (HTML format)","linkFileType":{"id":5,"text":"html"}},{"id":297976,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1246/pdf/ofr2014-1246.pdf","text":"Report PDF","size":"1.52 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Chandeleur Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.88763427734375,\n 30.055425546694924\n ],\n [\n -88.86703491210938,\n 30.07087666238811\n ],\n [\n -88.8196563720703,\n 30.00013836058068\n ],\n [\n -88.81004333496094,\n 29.83945268266779\n ],\n [\n -88.8519287109375,\n 29.840048293026957\n ],\n [\n -88.84025573730469,\n 29.95136495173933\n ],\n [\n -88.88763427734375,\n 30.055425546694924\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54df2032e4b08de9379b3a35","contributors":{"authors":[{"text":"Dickhudt, Patrick J. pdickhudt@usgs.gov","contributorId":5595,"corporation":false,"usgs":true,"family":"Dickhudt","given":"Patrick J.","email":"pdickhudt@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":540602,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":540603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeWitt, Nancy T. 0000-0002-2419-4087 ndewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-2419-4087","contributorId":4095,"corporation":false,"usgs":true,"family":"DeWitt","given":"Nancy","email":"ndewitt@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":540604,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70249417,"text":"70249417 - 2015 - Global land cover mapping using Earth observation satellite data: Recent progresses and challenges","interactions":[],"lastModifiedDate":"2024-06-18T14:08:22.769726","indexId":"70249417","displayToPublicDate":"2015-02-13T06:57:59","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1958,"text":"ISPRS Journal of Photogrammetry and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Global land cover mapping using Earth observation satellite data: Recent progresses and challenges","docAbstract":"Land cover is an important variable for many studies involving the Earth surface, such as climate, food security, hydrology, soil erosion, atmospheric quality, conservation biology, and plant functioning. Land cover not only changes with human caused land use changes, but also changes with nature. Therefore, the state of land cover is highly dynamic. In winter snow shields underneath various other land cover types in higher latitudes. Floods may persist for a long period in a year over low land areas in the tropical and subtropical regions. Forest maybe burnt or clear cut in a few days and changes to bare land. Within several months, the coverage of crops may vary from bare land to nearly 100% crops and then back to bare land following harvest. The highly dynamic nature of land cover creates a challenge in mapping and monitoring which remains to be adequately addressed. As economic globalization continues to intensify, there is an increasing trend of land cover/land use change, environmental pollution, land degradation, biodiversity loss at the global scale, timely and reliable information on global land cover and its changes is urgently needed to mitigate the negative impact of global environment change.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.isprsjprs.2015.01.001","usgsCitation":"Ban, Y., Gong, P., and Giri, C., 2015, Global land cover mapping using Earth observation satellite data: Recent progresses and challenges: ISPRS Journal of Photogrammetry and Remote Sensing, v. 103, p. 1-6, https://doi.org/10.1016/j.isprsjprs.2015.01.001.","productDescription":"6 p.","startPage":"1","endPage":"6","ipdsId":"IP-088485","costCenters":[],"links":[{"id":472278,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.isprsjprs.2015.01.001","text":"External Repository"},{"id":421807,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"103","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ban, Yifang","contributorId":330797,"corporation":false,"usgs":false,"family":"Ban","given":"Yifang","email":"","affiliations":[],"preferred":false,"id":885891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gong, Peng","contributorId":102393,"corporation":false,"usgs":true,"family":"Gong","given":"Peng","affiliations":[],"preferred":false,"id":885892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Giri, Chandra 0000-0001-9495-155X cgiri@usgs.gov","orcid":"https://orcid.org/0000-0001-9495-155X","contributorId":330663,"corporation":false,"usgs":true,"family":"Giri","given":"Chandra","email":"cgiri@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":885548,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70140265,"text":"ofr20151026 - 2015 - Evaluation of aquifer interconnection from aquifer characteristics computed by using specific capacity data within the vicinity of the Tremont Barrel Fill site, Clark County, Ohio","interactions":[],"lastModifiedDate":"2015-02-12T16:17:16","indexId":"ofr20151026","displayToPublicDate":"2015-02-12T17:15:00","publicationYear":"2015","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":"2015-1026","title":"Evaluation of aquifer interconnection from aquifer characteristics computed by using specific capacity data within the vicinity of the Tremont Barrel Fill site, Clark County, Ohio","docAbstract":"The Tremont Barrel Fill site is immediately north of the Tremont City Landfill near Tremont City, Clark County, Ohio. The site was an unlined pit used as a repository for disposing industrial liquid wastes and sludge from 1976 through 1979. Previous investigations led the U.S. Environmental Protection Agency (USEPA) to conclude that the site poses a contamination risk to nearby residents relying on private supply wells opened to the underlying deep sand and gravel and limestone aquifers. The USEPA also concluded there is a potential risk to the residents of the nearby Tremont City; the city obtains its municipal water supply from the Mad River Valley aquifer, which is recharged by the adjacent limestone aquifer. The U.S. Geological Survey (USGS) assessed the degree of hydraulic interconnection, and thus possible contaminant pathway(s), between the two aquifers (the sand and gravel and the limestone) underlying the Barrel Fill site, with consideration for the impact of an identified interconnection between the limestone and the Mad River Valley aquifer used for municipal supply.
\nAquifer interconnection between the sand and gravel aquifer overlying the limestone aquifer is assessed by analysis of specific capacity data from well-construction logs for derivation of estimates of transmissivity (T) and horizontal hydraulic conductivity (Kh). Data of this nature is limited in the control or knowledge about how well these data were collected and reported; therefore, the T and Kh are estimations. Similar values of T and Kh are used to infer the degree of aquifer interconnection based on the USEPA Hazard Ranking System, which states that aquifers are considered interconnected when the hydraulic conductivities are within two orders of magnitude.
\nThe results of the hydraulic analysis from 127 wells open to either the sand and gravel or the limestone aquifer indicate that the transmissivity of these aquifers is within one order of magnitude and horizontal hydraulic conductivity is within two orders of magnitude. As such, on the basis of the applied ranking system the two aquifers can be considered hydraulically interconnected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151026","usgsCitation":"Gahala, A.M., 2015, Evaluation of aquifer interconnection from aquifer characteristics computed by using specific capacity data within the vicinity of the Tremont Barrel Fill site, Clark County, Ohio: U.S. Geological Survey Open-File Report 2015-1026, 27 p., https://doi.org/10.3133/ofr20151026.","productDescription":"27 p.","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061351","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":297953,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151026.jpg"},{"id":297951,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1026/"},{"id":297952,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1026/pdf/ofr2015-1026.pdf","text":"Report","size":"1.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Ohio","otherGeospatial":"Clark County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.96987915039061,\n 39.839122664473194\n ],\n [\n -83.96987915039061,\n 40.00552775916049\n ],\n [\n -83.6334228515625,\n 40.00552775916049\n ],\n [\n -83.6334228515625,\n 39.839122664473194\n ],\n [\n -83.96987915039061,\n 39.839122664473194\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54ddcea6e4b08de9379b3932","contributors":{"authors":[{"text":"Gahala, Amy M. 0000-0003-2380-2973 agahala@usgs.gov","orcid":"https://orcid.org/0000-0003-2380-2973","contributorId":4396,"corporation":false,"usgs":true,"family":"Gahala","given":"Amy","email":"agahala@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539883,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70188571,"text":"70188571 - 2015 - Predicting locations of post-fire debris-flow erosionin the San Gabriel Mountains of southern California","interactions":[],"lastModifiedDate":"2017-06-15T14:59:07","indexId":"70188571","displayToPublicDate":"2015-02-12T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Predicting locations of post-fire debris-flow erosionin the San Gabriel Mountains of southern California","docAbstract":"Timely hazard assessments are needed to assess post-fire debris flows that may\nimpact communities located within and adjacent to recently burned areas. Implementing\nexisting models for debris-flow probability and magnitude can be time-consuming because\nthe geographic extent for applying the models is manually defined. In this study, a model is\npresented for predicting locations of post-fire debris-flow erosion. This model is further\ncalibrated to identify the geographic extent for applying post-fire hazard assessment\nmodels. Aerial photographs were used to map locations of post-fire debris-flow erosion and\ndeposition in the San Gabriel Mountains. Terrain, burn severity, and soil characteristics\nexpected to influence debris-flow erosion and deposition were calculated for each mapped\nlocation using 10-m resolution DEMs, GIS data for burn severity, and soil surveys.\nMultiple logistic regression was used to develop a model that predicts the probability of\nerosion as a function of channel slope, planform curvature, and the length of the longest\nupstream flow path. The model was validated using an independent database of mapped\nlocations of debris-flow erosion and deposition and found to make accurate and precise\npredictions. The model was further calibrated by identifying the average percentage of the\ndrainage network classified as erosion for mapped locations where debris flows transitioned\nfrom eroding to depositing material. The calibrated model provides critical information\nfor consistent and timely application of post-fire debris-flow hazard assessment\nmodels and the ability to identify locations of post-fire debris-flow erosion.","language":"English","publisher":"Springer","doi":"10.1007/s11069-015-1656-3","usgsCitation":"Gartner, J.E., Santi, P., and Cannon, S.H., 2015, Predicting locations of post-fire debris-flow erosionin the San Gabriel Mountains of southern California: Natural Hazards, v. 77, no. 2, p. 1305-1321, https://doi.org/10.1007/s11069-015-1656-3.","productDescription":"17 p. 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We developed a rule-based, piecewise regression-tree model trained on 99 points that used three data-sets – latitude, elevation, and start of season time based on remote sensing input data – to estimate cheatgrass beginning of spring growth (BOSG) in the northern Great Basin. The model was then applied to map the location and timing of cheatgrass spring growth for the entire area. The model was strong (R2 = 0.85) and predicted an average cheatgrass BOSG across the study area of 29 March–4 April. Of early cheatgrass BOSG areas, 65% occurred at elevations below 1452 m. The highest proportion of cheatgrass BOSG occurred between mid-April and late May. Predicted cheatgrass BOSG in this study matched well with previous Great Basin cheatgrass green-up studies.
","language":"English","publisher":"Taylor & Francis","publisherLocation":"Abingdon, UK","doi":"10.1080/17538947.2013.860196","usgsCitation":"Boyte, S.P., Wylie, B.K., Major, D.J., and Brown, J.F., 2015, The integration of geophysical and enhanced Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index data into a rule-based, piecewise regression-tree model to estimate cheatgrass beginning of spring growth: International Journal of Digital Earth, v. 8, no. 2, p. 116-130, https://doi.org/10.1080/17538947.2013.860196.","productDescription":"15 p.","startPage":"116","endPage":"130","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037330","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472279,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/17538947.2013.860196","text":"Publisher Index Page"},{"id":297921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.84033203125,\n 40.12849105685408\n ],\n [\n -120.66284179687499,\n 39.21523130910491\n ],\n [\n -122.03613281249999,\n 44.5278427984555\n ],\n [\n -114.686279296875,\n 45.398449976304086\n ],\n [\n -113.84033203125,\n 40.12849105685408\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2013-11-28","publicationStatus":"PW","scienceBaseUri":"54dd2abfe4b08de9379b31d2","contributors":{"authors":[{"text":"Boyte, Stephen P. 0000-0002-5462-3225 sboyte@usgs.gov","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":3463,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen","email":"sboyte@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":540443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":540450,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Major, Donald J.","contributorId":83405,"corporation":false,"usgs":false,"family":"Major","given":"Donald","email":"","middleInitial":"J.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":540451,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":3241,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":540452,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70140950,"text":"70140950 - 2015 - Mapping and monitoring cheatgrass dieoff in rangelands of the Northern Great Basin, USA","interactions":[],"lastModifiedDate":"2017-01-18T10:05:49","indexId":"70140950","displayToPublicDate":"2015-02-11T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Mapping and monitoring cheatgrass dieoff in rangelands of the Northern Great Basin, USA","docAbstract":"Understanding cheatgrass (Bromus tectorum) dynamics in the Northern Great Basin rangelands, USA, is necessary to effectively manage the region’s lands. This study’s goal was to map and monitor cheatgrass performance to identify where and when cheatgrass dieoff occurred in the Northern Great Basin and to discover how this phenomenon was affected by climatic, topographic, and edaphic variables. We also examined how fire affected cheatgrass performance. Land managers and scientists are concerned by cheatgrass dieoff because it can increase land degradation, and its causes and effects are not fully known. To better understand the scope of cheatgrass dieoff, we developed multiple ecological models that integrated remote sensing data with geophysical and biophysical data. The models’ R2 ranged from 0.71 to 0.88, and their root mean squared errors (RMSEs) ranged from 3.07 to 6.95. Validation of dieoff data showed that 41% of pixels within independently developed dieoff polygons were accurately classified as dieoff, whereas 2% of pixels outside of dieoff polygons were classified as dieoff. Site potential, a long-term spatial average of cheatgrass cover, dominated the development of the cheatgrass performance model. Fire negatively affected cheatgrass performance 1 year postfire, but by the second year postfire performance exceeded prefire levels. The landscape-scale monitoring study presented in this paper helps increase knowledge about recent rangeland dynamics, including where cheatgrass dieoffs occurred and how cheatgrass responded to fire. This knowledge can help direct further investigation and/or guide land management activities that can capitalize on, or mitigate the effects of, cheatgrass dieoff.
","language":"English","publisher":"Society for Range Management","doi":"10.1016/j.rama.2014.12.005","usgsCitation":"Boyte, S.P., Wylie, B.K., and Major, D.J., 2015, Mapping and monitoring cheatgrass dieoff in rangelands of the Northern Great Basin, USA: Rangeland Ecology and Management, v. 68, no. 1, p. 18-28, https://doi.org/10.1016/j.rama.2014.12.005.","productDescription":"11 p.","startPage":"18","endPage":"28","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053587","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":297920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northern Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.22314453124999,\n 40.1452892956766\n ],\n [\n -121.22314453124999,\n 44.85586880735725\n ],\n [\n -110.85205078124999,\n 44.85586880735725\n ],\n [\n -110.85205078124999,\n 40.1452892956766\n ],\n [\n -121.22314453124999,\n 40.1452892956766\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"68","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a94e4b08de9379b3112","contributors":{"authors":[{"text":"Boyte, Stephen P. 0000-0002-5462-3225 sboyte@usgs.gov","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":3463,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen","email":"sboyte@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":540447,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":540448,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Major, Donald J.","contributorId":83405,"corporation":false,"usgs":false,"family":"Major","given":"Donald","email":"","middleInitial":"J.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":540449,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70140818,"text":"ofr20141248 - 2015 - Magnetotelluric data collected to characterize aquifers in the San Luis Basin, New Mexico","interactions":[],"lastModifiedDate":"2015-02-11T09:38:42","indexId":"ofr20141248","displayToPublicDate":"2015-02-11T09:30:00","publicationYear":"2015","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":"2014-1248","title":"Magnetotelluric data collected to characterize aquifers in the San Luis Basin, New Mexico","docAbstract":"The U.S. Geological Survey is conducting a series of multidisciplinary studies of the San Luis Basin as part of the Geologic Framework of Rio Grande Basins project. Detailed geologic mapping, high-resolution airborne magnetic surveys, gravity surveys, magnetotelluric surveys, and hydrologic and lithologic data are being used to better understand the aquifers in the San Luis Basin. This report describes one north-south and two east-west regional magnetotelluric sounding profiles, acquired in June of 2010 and July and August of 2011, across the San Luis Basin in northern New Mexico. No interpretation of the data is included.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141248","usgsCitation":"Ailes, C.E., and Rodriguez, B.D., 2015, Magnetotelluric data collected to characterize aquifers in the San Luis Basin, New Mexico: U.S. Geological Survey Open-File Report 2014-1248, Report: iv, 9 p.; Table 2; Appendix, https://doi.org/10.3133/ofr20141248.","productDescription":"Report: iv, 9 p.; Table 2; Appendix","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-038565","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":297912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141248.jpg"},{"id":297905,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1248/"},{"id":297909,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1248/pdf/ofr2014-1248.pdf","text":"Report","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297910,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1248/downloads/ofr2014-1248_Table2.xls","text":"Table 2","size":"1.27 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 2"},{"id":297911,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1248/downloads/ofr2014-1248_Appendix.pdf","size":"79.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix"}],"country":"United States","state":"New Mexico","otherGeospatial":"San Luis Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.28036499023438,\n 36.147855714690515\n ],\n [\n -106.28036499023438,\n 36.99377838872517\n ],\n [\n -105.10345458984375,\n 36.99377838872517\n ],\n [\n -105.10345458984375,\n 36.147855714690515\n ],\n [\n -106.28036499023438,\n 36.147855714690515\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a94e4b08de9379b310e","contributors":{"authors":[{"text":"Ailes, Chad E. cailes@usgs.gov","contributorId":3995,"corporation":false,"usgs":true,"family":"Ailes","given":"Chad","email":"cailes@usgs.gov","middleInitial":"E.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":540410,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rodriguez, Brian D. 0000-0002-2263-611X brod@usgs.gov","orcid":"https://orcid.org/0000-0002-2263-611X","contributorId":836,"corporation":false,"usgs":true,"family":"Rodriguez","given":"Brian","email":"brod@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":540409,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70225727,"text":"70225727 - 2015 - Simulation of acceleration field of the Lushan earthquake (Ms7.0, April 20, 2013, China)","interactions":[],"lastModifiedDate":"2021-11-05T11:49:49.750359","indexId":"70225727","displayToPublicDate":"2015-02-11T06:45:27","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1517,"text":"Engineering Geology","active":true,"publicationSubtype":{"id":10}},"title":"Simulation of acceleration field of the Lushan earthquake (Ms7.0, April 20, 2013, China)","docAbstract":"The acceleration field of the Lushan earthquake (Ms7.0, April 20, 2013, China) is simulated using a new modified version of the stochastic finite-fault method (EXSIM) based on a dynamic corner frequency approach. To incorporate the effect of heterogeneous slip distribution on the variation of source spectrum, we adopt an empirical source spectral model and derive the corresponding dynamic parameters, which vary with the cumulative seismic moment of the ruptured area.
The new modified method is validated by: 1) comparison of the simulation results with those obtained from the EXSIM method using near-fault ground motion data of the 1994 Northridge earthquake; 2) comparison of simulated PGA contour map inferred from synthetic time histories at 315 grid locations with the observed PGA shakemap for the 2013 Lushan earthquake; 3) comparison of simulated PGA with those predicted by ground-motion prediction equations (GMPEs); and 4) comparison of simulated time histories with observed acceleration records at six strong motion stations during the mainshock of the Lushan earthquake, in which local site response is considered in the simulation. These comparisons confirm the validity of the new simulation procedure for purposes of regional strong ground motion estimation. Limitations of the procedure in modeling the phasing of different arrivals in the seismic signal and near-surface response of geologic deposits are discussed.
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H. lbiewick@usgs.gov","contributorId":1086,"corporation":false,"usgs":true,"family":"Biewick","given":"Laura","email":"lbiewick@usgs.gov","middleInitial":"R. H.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":542499,"contributorType":{"id":3,"text":"Compilers"},"rank":1}],"authors":[{"text":"U.S. Geological Survey National Assessment of Oil and Gas Resources Team","contributorId":128233,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey National Assessment of Oil and Gas Resources Team","id":542498,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70126012,"text":"ds879 - 2015 - Water- and air-quality and surficial bed-sediment monitoring of the Sweetwater Reservoir watershed, San Diego County, California, 2003-09","interactions":[],"lastModifiedDate":"2015-02-20T14:37:22","indexId":"ds879","displayToPublicDate":"2015-02-06T15:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"879","title":"Water- and air-quality and surficial bed-sediment monitoring of the Sweetwater Reservoir watershed, San Diego County, California, 2003-09","docAbstract":"In 1998, the U.S. Geological Survey, in cooperation with the Sweetwater Authority, began a study to assess the overall health of the Sweetwater watershed in San Diego County, California. This study was designed to provide a data set that could be used to evaluate potential effects from the construction and operation of State Route 125 within the broader context of the water quality and air quality in the watershed. The study included regular sampling of water, air, and surficial bed sediment at Sweetwater Reservoir (SWR) for chemical constituents, including volatile organic compounds (VOCs), base-neutral and acid- extractable organic compounds (BNAs) that include polycyclic aromatic hydrocarbons (PAHs), pesticides, and metals. Additionally, water samples were collected for anthropogenic organic indicator compounds in and around SWR. Background water samples were collected at Loveland Reservoir for VOCs, BNAs, pesticides, and metals. Surficial bed-sediment samples were collected for PAHs, organochlorine pesticides, and metals at Sweetwater and Loveland Reservoirs.
\nTo monitor changes in contaminant concentration in water and air at SWR during the construction and operation of State Route 125, this study was divided into three phases. Phase One sampling (September 1998 to September 2004) was designed to establish baseline conditions for target compounds in terms of detection frequency and concentration in air and water. Phase Two (October 2004 to September 2007) continued sampling at selected monitoring sites during construction of State Route 125 to assess any effect from the construction process and the use of heavy equipment to build the roadway. Phase Three (October 2007 to August 2009) continued sampling for 2 years after the opening of State Route 125 to assess the potential changes in water quality related to vehicle emissions from the roadway alignment. Surficial bed-sediment samples were collected three times during the study—at the beginning of the study, at the start of Phase Two, and at the end of the study.
\nThis report describes the study design and the sampling and analytical methods and presents data from water, air, and surficial bed-sediment samples collected from the sixth to eleventh years of the study (October 2003–August 2009), spanning the last year of Phase one and all of Phases Two and Three. Data collected during the first 5 years of sampling have been previously published.
\nThree types of quality-control samples were used in this study—matrix spikes, blanks, and replicates. Matrix-spike data are considered to be adequate if the recovery concentration is within 30 percent of the matrix concentration. Replicate data are considered to be adequate if the replicate sample concentration is within 30 percent of the environmental sample concentration. Additionally, surrogate compounds were added to most samples to monitor sample-specific performance of the analytical method.
\nMost VOC matrix-spike recovery data associated with water samples are within acceptable criteria, but three VOCs had recoveries below the acceptable criteria; these compounds may not have been detected in water samples if they were present at low concentrations. Data for blanks associated with water samples for VOCs and metals showed no detections above their laboratory reporting levels. Most replicate data are within acceptable criteria. Quality-control data for VOC air samples resulted in flagging several reported concentrations for acetone, benzene, ethenylbenzene, and naphthalene because they may be biased high. Acetone, benzene, and toluene were detected at low concentrations in almost every VOC air blank. Some PAH and pesticide concentrations in air samples were designated as estimated because of method performance limitations. PAHs in surficial bed sediment had 83 percent of surrogates below the acceptable criteria. No matrix-spike data for metals in surficial bed sediment were outside the acceptable criteria; only beryllium had a replicate comparison outside the acceptable criteria.
\nSampling results show concentrations of the gasoline oxygenate methyl tert-butyl ether in water and air samples declined after it was phased out by the State of California in January 2004. The largest concentrations of gasoline hydrocarbons benzene and toluene in water were detected at or near the surface of the SWR. Isophorone and phenol were the two most frequently detected BNA compounds in water. Diuron, prometon, and simazine were the most frequently detected pesticide compounds in water. Concentrations of benzene and toluene in air samples were highest during the cooler months and had a consistent seasonal pattern over time. Ten PAH compounds were detected frequently in air samples. Twelve pesticide compounds were also detected in air samples. Surficial bed-sediment samples were analyzed for 53 PAHs; 22 of the compounds had one or more detections. Surficial bed-sediment samples were analyzed for 22 organic compounds; only 6 compounds had one or more detections. Surficial bed-sediment samples were analyzed for 37 metals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds879","collaboration":"Prepared in cooperation with the Sweetwater Authority","usgsCitation":"Mendez, G.O., Majewski, M.S., Foreman, W., and Morita, A.Y., 2015, Water- and air-quality and surficial bed-sediment monitoring of the Sweetwater Reservoir watershed, San Diego County, California, 2003-09: U.S. Geological Survey Data Series 879, Report: xi, 226 p.; 5 Tables, https://doi.org/10.3133/ds879.","productDescription":"Report: xi, 226 p.; 5 Tables","numberOfPages":"242","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2003-01-01","temporalEnd":"2009-12-31","ipdsId":"IP-002295","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":297815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds879.jpg"},{"id":297808,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0879/"},{"id":297809,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0879/pdf/ds879.pdf","size":"6.2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297810,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0879/downloads/ds879_table4b_voc.xls","text":"Table 4B","size":"174 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297811,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0879/downloads/ds879_table5b_bna.xls","text":"Table 5B","size":"82 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297812,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0879/downloads/ds879_table10b_avoc.xls","text":"Table 10B","size":"240 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297813,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0879/downloads/ds879_table11b_pah.xls","text":"Table 11B","size":"313 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297814,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0879/downloads/ds879_table13_airtm.xls","text":"Table 13","size":"124 kB","linkFileType":{"id":3,"text":"xlsx"}}],"scale":"100000","projection":"Universal Transverse Mercator projection","country":"United States","state":"California","county":"San Diego County","otherGeospatial":"Sweetwater Reservoir watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.1142578125,\n 32.58963484306727\n ],\n [\n -117.1142578125,\n 32.99945000822839\n ],\n [\n -116.46606445312499,\n 32.99945000822839\n ],\n [\n -116.46606445312499,\n 32.58963484306727\n ],\n [\n -117.1142578125,\n 32.58963484306727\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2acde4b08de9379b3214","contributors":{"authors":[{"text":"Mendez, Gregory O. 0000-0002-9955-3726 gomendez@usgs.gov","orcid":"https://orcid.org/0000-0002-9955-3726","contributorId":1489,"corporation":false,"usgs":true,"family":"Mendez","given":"Gregory","email":"gomendez@usgs.gov","middleInitial":"O.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":540012,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Majewski, Michael S. majewski@usgs.gov","contributorId":440,"corporation":false,"usgs":true,"family":"Majewski","given":"Michael","email":"majewski@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foreman, William T. wforeman@usgs.gov","contributorId":1473,"corporation":false,"usgs":true,"family":"Foreman","given":"William T.","email":"wforeman@usgs.gov","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":false,"id":540014,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morita, Andrew Y. 0000-0002-8120-996X amorita@usgs.gov","orcid":"https://orcid.org/0000-0002-8120-996X","contributorId":1487,"corporation":false,"usgs":true,"family":"Morita","given":"Andrew","email":"amorita@usgs.gov","middleInitial":"Y.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540015,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70134473,"text":"sir20145220 - 2015 - Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961-2010","interactions":[],"lastModifiedDate":"2015-02-06T12:59:44","indexId":"sir20145220","displayToPublicDate":"2015-02-06T13:45:00","publicationYear":"2015","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":"2014-5220","title":"Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961-2010","docAbstract":"The lakes, rivers, and streams of New York State provide an essential water resource for the State. The information provided by time series hydrologic data is essential to understanding ways to promote healthy instream ecology and to strengthen the scientific basis for sound water management decision making in New York. The U.S. Geological Survey, in cooperation with The Nature Conservancy and the New York State Energy Research and Development Authority, has developed the New York Streamflow Estimation Tool to estimate a daily mean hydrograph for the period from October 1, 1960, to September 30, 2010, at ungaged locations across the State. The New York Streamflow Estimation Tool produces a complete estimated daily mean time series from which daily flow statistics can be estimated. In addition, the New York Streamflow Estimation Tool provides a means for quantitative flow assessments at ungaged locations that can be used to address the objectives of the Clean Water Act—to restore and maintain the chemical, physical, and biological integrity of the Nation’s waters.
\nThe New York Streamflow Estimation Tool uses data from the U.S. Geological Survey streamflow network for selected streamgages in New York (excluding Long Island) and surrounding States with shared hydrologic boundaries, and physical and climate basin characteristics to estimate the natural unaltered streamflow at ungaged stream locations. The unaltered streamflow is representative of flows that are minimally altered by regulation, diversion, or mining, and other anthropogenic activities. With the streamflow network data, flow-duration exceedance probability equations were developed to estimate unaltered streamflow exceedance probabilities at an ungaged location using a methodology that equates streamflow as a percentile from a flow-duration curve for a particular day at a hydrologically similar reference streamgage with streamflow as a percentile from the flow-duration curve for the same day at an ungaged location. The reference streamgage is selected using map correlation, a geostatistical method in which variogram models are developed that correlate streamflow at one streamgage with streamflows at all other locations in the study area. Regression equations used to predict 17 flow-duration exceedance probabilities were developed to estimate the flow-duration curves at ungaged locations for New York using geographic information system-derived basin characteristics.
\nA graphical user interface, with an integrated spreadsheet summary report, has been developed to estimate and display the daily mean streamflows and statistics and to evaluate different water management or water withdrawal scenarios with the estimated monthly data. This package of regression equations, U.S. Geological Survey streamgage data, and spreadsheet application produces an interactive tool to estimate an unaltered daily streamflow hydrograph and streamflow statistics at ungaged sites in New York. Among other uses, the New York Streamflow Estimation Tool can assist water managers with permitting water withdrawals, implementing habitat protection, estimating contaminant loads, or determining the potential affect from chemical spills.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145220","collaboration":"Prepared in cooperation with The Nature Conservancy and the New York State Energy Research and Development Authority","usgsCitation":"Gazoorian, C.L., 2015, Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961-2010: U.S. Geological Survey Scientific Investigations Report 2014-5220, Report: viii, 29 p.; Readme; 5 Appendixes; NYSET application, https://doi.org/10.3133/sir20145220.","productDescription":"Report: viii, 29 p.; Readme; 5 Appendixes; NYSET application","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1960-10-01","temporalEnd":"2010-09-30","ipdsId":"IP-055442","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":297799,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145220.jpg"},{"id":297792,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5220/"},{"id":297793,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5220/pdf/sir2014-5220.pdf"},{"id":297794,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/sir2014-5220_readme.pdf","text":"Readme Appendix 1-5","size":"58 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":297795,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/sir2014-5220_app1-4.pdf","text":"Appendix 1-4 PDF","size":"308 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":297796,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/sir2014-5220_app1-4.xlsx","text":"Appendix 1-4 XLS","size":"75 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297797,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/SIR2014-5220_app5.pdf","text":"Appendix 5","size":"696 kB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"User’s Guide for the New York Streamflow Estimation Tool (NYSET) version 1.0"},{"id":297798,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://ny.water.usgs.gov/projects/nyset/","text":"NYSET application","linkFileType":{"id":5,"text":"html"}}],"scale":"200000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"New York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.771728515625,\n 42.27730877423709\n ],\n [\n -79.7607421875,\n 42.00032514831621\n ],\n [\n -75.35522460937499,\n 42.00032514831621\n ],\n [\n -75.003662109375,\n 41.46742831254425\n ],\n [\n -73.773193359375,\n 40.863679665481676\n ],\n [\n -73.487548828125,\n 41.054501963290505\n ],\n [\n -73.2568359375,\n 42.779275360241904\n ],\n [\n -73.223876953125,\n 45.01141864227728\n ],\n [\n -75.003662109375,\n 45.034714778688624\n ],\n [\n -76.5966796875,\n 44.166444664458595\n ],\n [\n -76.201171875,\n 43.58834891179792\n ],\n [\n -79.068603515625,\n 43.29320031385282\n ],\n [\n -79.771728515625,\n 42.27730877423709\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a74e4b08de9379b3070","contributors":{"authors":[{"text":"Gazoorian, Christopher L. 0000-0002-5408-6212 cgazoori@usgs.gov","orcid":"https://orcid.org/0000-0002-5408-6212","contributorId":2929,"corporation":false,"usgs":true,"family":"Gazoorian","given":"Christopher","email":"cgazoori@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":525962,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70140094,"text":"70140094 - 2015 - Mineral commodity summaries 2015","interactions":[],"lastModifiedDate":"2015-02-09T14:21:20","indexId":"70140094","displayToPublicDate":"2015-02-06T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"seriesTitle":{"id":323,"text":"Mineral Commodity Summaries","code":"MCS","active":true,"publicationSubtype":{"id":5}},"title":"Mineral commodity summaries 2015","docAbstract":"Each chapter of the 2015 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production and resources. The MCS is the earliest comprehensive source of 2014 mineral production data for the world. More than 90 individual minerals and materials are covered by two-page synopses.
\nFor mineral commodities for which there is a Government stockpile, detailed information concerning the stockpile status is included in the two-page synopsis.
\nAbbreviations and units of measure, and definitions of selected terms used in the report, are in Appendix A and Appendix B, respectively. \"Appendix C—Reserves and Resources” includes “Part A—Resource/Reserve Classification for Minerals” and “Part B—Sources of Reserves Data.\" A directory of USGS minerals information country specialists and their responsibilities is Appendix D.
\nThe USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the MCS 2015 are welcomed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70140094","productDescription":"Report: 196 p.; 1 Appendix","numberOfPages":"199","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063093","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":297786,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/70140094.gif"},{"id":297784,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://minerals.usgs.gov/minerals/pubs/mcs/2015/mcs2015.pdf","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297785,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://minerals.usgs.gov/minerals/pubs/mcs/2015/mcsapp2015.pdf","linkFileType":{"id":1,"text":"pdf"}}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a97e4b08de9379b3124","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":539782,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70137267,"text":"sir20145237 - 2015 - Simulation of the regional groundwater-flow system of the Menominee Indian Reservation, Wisconsin","interactions":[],"lastModifiedDate":"2015-02-06T09:37:21","indexId":"sir20145237","displayToPublicDate":"2015-02-06T10:30:00","publicationYear":"2015","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":"2014-5237","title":"Simulation of the regional groundwater-flow system of the Menominee Indian Reservation, Wisconsin","docAbstract":"A regional, two-dimensional, steady-state groundwater-flow model was developed to simulate the groundwater-flow system and groundwater/surface-water interactions within the Menominee Indian Reservation. The model was developed by the U.S. Geological Survey (USGS), in cooperation with the Menominee Indian Tribe of Wisconsin, to contribute to the fundamental understanding of the region’s hydrogeology. The objectives of the regional model were to improve understanding of the groundwater-flow system, including groundwater/surface-water interactions, and to develop a tool suitable for evaluating the effects of potential regional water-management programs. The computer code GFLOW was used because of the ease with which the model can simulate groundwater/surface-water interactions, provide a framework for simulating regional groundwater-flow systems, and be refined in a stepwise fashion to incorporate new data and simulate groundwater-flow patterns at multiple scales. Simulations made with the regional model reproduce groundwater levels and stream base flows representative of recent conditions (1970–2013) and illustrate groundwater-flow patterns with maps of (1) the simulated water table and groundwater-flow directions, (2) probabilistic areas contributing recharge to high-capacity pumped wells, and (3) estimation of the extent of infiltrated wastewater from treatment lagoons.
\nThe groundwater-flow model described in this report simulates the major hydrogeologic features of the modeled area, including surficial unconsolidated aquifers, groundwater/surface-water interactions, and groundwater withdrawals from existing high-capacity production wells. Areas contributing recharge to pumped high-capacity wells on the Menominee Indian Reservation were delineated by tracking simulated water particles from the water table to wells in combination with Monte Carlo techniques, and maps of the probability of capture for each well nest were produced. Groundwater-agebased areas contributing recharge to wells were simulated by using the calibrated set of parameters and porosity values adjusted to account for bias in simulated saturated thickness. Simulations were performed for current (2013) pumping rates. The simulations show a range in sensitivity of the simulated areas contributing recharge to wells given the parameters evaluated through the Monte Carlo analysis. The areas contributing recharge to supply wells for the villages of Zoar and Neopit are long and narrow, with a sharp gradation from high to low probability of capture. The areas contributing recharge to supply wells for Middle Village and the village of Keshena exhibit a sharp gradation from high to low probability over a relatively small area between the well and a local groundwater mound. The highest probability areas contributing recharge to the supply wells for the Villages of Onekewat and Redwing are in the immediate vicinity of the wells. These wells also have an extensive area with low probability for capturing water that is likely due to a locally low hydraulic gradient and the large degree of uncertainty associated with the lakebed resistance parameters that control interaction between groundwater and local lakes. Additional field investigations and associated local model refinements would facilitate further reductions in uncertainty associated with simulated areas contributing recharge to the wells.
\nThe likely extent of the Neopit wastewater plume was simulated by using the groundwater-flow model and Monte Carlo techniques to evaluate the sensitivity of predictive simulations to a range of model parameter values. Wastewater infiltrated from the currently operating lagoons flows predominantly south toward Tourtillotte Creek. Some of the infiltrated wastewater is simulated as having a low probability of flowing beneath Tourtillotte Creek to the nearby West Branch Wolf River. Results for the probable extent of the wastewater plume are considered to be qualitative because the method only considers advective flow and does not account for processes affecting contaminant transport in porous media. Therefore, results for the probable extent of the wastewater plume are sensitive to the number of particles used to represent flow from the lagoon and the resolution of a synthetic grid used for the analysis. Nonetheless, it is expected that the qualitative results may be of use for identifying potential downgradient areas of concern that can then be evaluated using the quantitative “area contributing recharge to wells” method or traditional contaminant-transport simulations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145237","collaboration":"In cooperation with the Menominee Indian Tribe of Wisconsin","usgsCitation":"Juckem, P.F., and Dunning, C., 2015, Simulation of the regional groundwater-flow system of the Menominee Indian Reservation, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2014-5237, Report: vi, 40 p.; 1 Appendix, https://doi.org/10.3133/sir20145237.","productDescription":"Report: vi, 40 p.; 1 Appendix","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051827","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":297772,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145237.jpg"},{"id":297770,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5237/pdf/sir2014-5237.pdf","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297771,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5237/appendix/sir2014-5237_appendix1.xlsx","text":"Appendix 1","size":"43 kB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"Data from auger surveys near the Villages of Neopit, Zoar, and Keshena."},{"id":297768,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5237/"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Menominee Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.98376464843749,\n 45.11133093583214\n ],\n [\n -88.98239135742188,\n 44.94633342311665\n ],\n [\n -88.73794555664062,\n 44.94438944516438\n ],\n [\n -88.7310791015625,\n 44.85100108620397\n ],\n [\n -88.47152709960938,\n 44.8490538825394\n ],\n [\n -88.472900390625,\n 45.11326925230233\n ],\n [\n -88.98376464843749,\n 45.11133093583214\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ab4e4b08de9379b3192","contributors":{"authors":[{"text":"Juckem, Paul F. 0000-0002-3613-1761 pfjuckem@usgs.gov","orcid":"https://orcid.org/0000-0002-3613-1761","contributorId":1905,"corporation":false,"usgs":true,"family":"Juckem","given":"Paul","email":"pfjuckem@usgs.gov","middleInitial":"F.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539963,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunning, Charles P. cdunning@usgs.gov","contributorId":892,"corporation":false,"usgs":true,"family":"Dunning","given":"Charles P.","email":"cdunning@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539964,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70139975,"text":"fs20143089 - 2015 - Water resources of La Salle Parish, Louisiana","interactions":[],"lastModifiedDate":"2015-02-05T14:15:15","indexId":"fs20143089","displayToPublicDate":"2015-02-05T15:00:00","publicationYear":"2015","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":"2014-3089","title":"Water resources of La Salle Parish, Louisiana","docAbstract":"Information concerning the availability, use, and quality of water in La Salle Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. Information on the availability, past and current use, use trends, and water quality from groundwater and surface-water sources in the parish is presented. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System (http://waterdata.usgs.gov/nwis) are the primary sources of the information presented here.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143089","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"White, V.E., and Prakken, L.B., 2015, Water resources of La Salle Parish, Louisiana: U.S. Geological Survey Fact Sheet 2014-3089, 6 p., https://doi.org/10.3133/fs20143089.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056216","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":297765,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143089.jpg"},{"id":297764,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3089/pdf/fs2014-3089.pdf","text":"Report","size":"1.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297693,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3089/"}],"country":"United States","state":"Louisiana","otherGeospatial":"La Salle Parish","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.384033203125,\n 31.33252503230784\n ],\n [\n -92.384033203125,\n 31.924192605327708\n ],\n [\n -91.9940185546875,\n 31.924192605327708\n ],\n [\n -91.9940185546875,\n 31.33252503230784\n ],\n [\n -92.384033203125,\n 31.33252503230784\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2acde4b08de9379b3211","contributors":{"authors":[{"text":"White, Vincent E. 0000-0002-1660-0102 vwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-1660-0102","contributorId":5388,"corporation":false,"usgs":true,"family":"White","given":"Vincent","email":"vwhite@usgs.gov","middleInitial":"E.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prakken, Lawrence B. lprakken@usgs.gov","contributorId":2319,"corporation":false,"usgs":true,"family":"Prakken","given":"Lawrence","email":"lprakken@usgs.gov","middleInitial":"B.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539753,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70138587,"text":"ofr20151009 - 2015 - Update of the Graizer-Kalkan ground-motion prediction equations for shallow crustal continental earthquakes","interactions":[],"lastModifiedDate":"2015-02-11T09:05:10","indexId":"ofr20151009","displayToPublicDate":"2015-02-05T14:15:00","publicationYear":"2015","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":"2015-1009","title":"Update of the Graizer-Kalkan ground-motion prediction equations for shallow crustal continental earthquakes","docAbstract":"A ground-motion prediction equation (GMPE) for computing medians and standard deviations of peak ground acceleration and 5-percent damped pseudo spectral acceleration response ordinates of maximum horizontal component of randomly oriented ground motions was developed by Graizer and Kalkan (2007, 2009) to be used for seismic hazard analyses and engineering applications. This GMPE was derived from the greatly expanded Next Generation of Attenuation (NGA)-West1 database. In this study, Graizer and Kalkan’s GMPE is revised to include (1) an anelastic attenuation term as a function of quality factor (Q0) in order to capture regional differences in large-distance attenuation and (2) a new frequency-dependent sedimentary-basin scaling term as a function of depth to the 1.5-km/s shear-wave velocity isosurface to improve ground-motion predictions for sites on deep sedimentary basins. The new model (GK15), developed to be simple, is applicable to the western United States and other regions with shallow continental crust in active tectonic environments and may be used for earthquakes with moment magnitudes 5.0–8.0, distances 0–250 km, average shear-wave velocities 200–1,300 m/s, and spectral periods 0.01–5 s. Directivity effects are not explicitly modeled but are included through the variability of the data. Our aleatory variability model captures inter-event variability, which decreases with magnitude and increases with distance. The mixed-effects residuals analysis shows that the GK15 reveals no trend with respect to the independent parameters. The GK15 is a significant improvement over Graizer and Kalkan (2007, 2009), and provides a demonstrable, reliable description of ground-motion amplitudes recorded from shallow crustal earthquakes in active tectonic regions over a wide range of magnitudes, distances, and site conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151009","collaboration":"Prepared in cooperation with the U.S. Nuclear Regulatory Commission","usgsCitation":"Graizer, V., and Kalkan, E., 2015, Update of the Graizer-Kalkan ground-motion prediction equations for shallow crustal continental earthquakes: U.S. Geological Survey Open-File Report 2015-1009, vii, 79 p., https://doi.org/10.3133/ofr20151009.","productDescription":"vii, 79 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-049464","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":297762,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151009.gif"},{"id":297761,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1009/downloads/ofr2015-1009.pdf","text":"Report","size":"21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297760,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1009/"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ac7e4b08de9379b31ff","contributors":{"authors":[{"text":"Graizer, Vladimir","contributorId":138813,"corporation":false,"usgs":false,"family":"Graizer","given":"Vladimir","affiliations":[{"id":12536,"text":"U.S. Nuclear Regulatory Commission","active":true,"usgs":false}],"preferred":false,"id":539921,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalkan, Erol 0000-0002-9138-9407 ekalkan@usgs.gov","orcid":"https://orcid.org/0000-0002-9138-9407","contributorId":1218,"corporation":false,"usgs":true,"family":"Kalkan","given":"Erol","email":"ekalkan@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":539922,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70140681,"text":"70140681 - 2015 - A laboratory evaluation of tagging-related mortality and tag loss in juvenile humpback chub","interactions":[],"lastModifiedDate":"2016-06-01T14:02:05","indexId":"70140681","displayToPublicDate":"2015-02-05T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"A laboratory evaluation of tagging-related mortality and tag loss in juvenile humpback chub","docAbstract":"We quantified tag retention, survival, and growth in juvenile, captive-reared Humpback Chub Gila cypha marked with three different tag types: (1) Biomark 12.5-mm, 134.2-kHz, full duplex PIT tags injected into the body cavity with a 12-gauge needle; (2) Biomark 8.4-mm, 134.2-kHz, full duplex PIT tags injected with a 16-gauge needle; and (3) Northwest Marine Technology visible implant elastomer (VIE) tags injected under the skin with a 29-gauge needle. Estimates of tag loss, tagging-induced mortality, and growth were evaluated for 60 d with each tag type for four different size-groups of fish: 40–49 mm, 50–59 mm, 60–69 mm, and 70–79 mm TL. Total length was a significant predictor of the probability of PIT tag retention and mortality for both 8-mm and 12-mm PIT tags, and the smallest fish had the highest rates of tag loss (12.5–30.0%) and mortality (7.5–20.0%). Humpback Chub of sizes 40–49 mm TL and tagged with VIE tags had no mortality but did have a 17.5% tag loss. Growth rates of all tagged fish were similar to controls. Our data indicate Humpback Chub can be effectively tagged using either 8-mm or 12-mm PIT tags with little tag loss or mortality at sizes as low as 65 mm TL.
","language":"English","publisher":"American Fisheries Society","publisherLocation":"Lawrence, KS","doi":"10.1080/02755947.2014.986345","usgsCitation":"Ward, D.L., Persons, W.R., Young, K., Stone, D.M., Van Haverbeke, R., and Knight, W.R., 2015, A laboratory evaluation of tagging-related mortality and tag loss in juvenile humpback chub: North American Journal of Fisheries Management, v. 35, no. 1, p. 135-140, https://doi.org/10.1080/02755947.2014.986345.","productDescription":"6 p.","startPage":"135","endPage":"140","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057354","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":297892,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-05","publicationStatus":"PW","scienceBaseUri":"54dd2a4be4b08de9379b2fc7","contributors":{"authors":[{"text":"Ward, David L. 0000-0002-3355-0637 dlward@usgs.gov","orcid":"https://orcid.org/0000-0002-3355-0637","contributorId":3879,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dlward@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":540288,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Persons, William R. wpersons@usgs.gov","contributorId":4028,"corporation":false,"usgs":true,"family":"Persons","given":"William","email":"wpersons@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":540290,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Kirk","contributorId":139191,"corporation":false,"usgs":false,"family":"Young","given":"Kirk","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":540289,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stone, Dennis M.","contributorId":58237,"corporation":false,"usgs":false,"family":"Stone","given":"Dennis","email":"","middleInitial":"M.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":540291,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Van Haverbeke, Randy","contributorId":139192,"corporation":false,"usgs":false,"family":"Van Haverbeke","given":"Randy","email":"","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":540292,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knight, William R.","contributorId":35631,"corporation":false,"usgs":true,"family":"Knight","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":540293,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70058741,"text":"sim3280 - 2015 - Bedrock geologic map of the Spring Valley, West Plains, and parts of the Piedmont and Poplar Bluff 30'x60' quadrangles, Missouri, including the upper Current River and Eleven Point River drainage basins","interactions":[],"lastModifiedDate":"2016-06-14T10:22:20","indexId":"sim3280","displayToPublicDate":"2015-02-05T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3280","title":"Bedrock geologic map of the Spring Valley, West Plains, and parts of the Piedmont and Poplar Bluff 30'x60' quadrangles, Missouri, including the upper Current River and Eleven Point River drainage basins","docAbstract":"This map covers the drainage basins of the upper Current River and the Eleven Point River in the Ozark Plateaus physiographic province of southeastern Missouri. The two surface drainage basins are contiguous in their headwaters regions, but are separated in their lower reaches by the lower Black River basin in the southeast corner of the map area. Numerous dye-trace studies demonstrate that in the contiguous headwaters areas, groundwater flows from the Eleven Point River basin into the Current River basin. Much of the groundwater discharge of the Eleven Point River basin emanates from Big Spring, located on the Current River. This geologic map and cross sections were produced to help fulfill a need to understand the geologic framework of the region in which this subsurface flow occurs.
\nThe map includes all of the Ozark National Scenic Riverways, a national park created by an Act of Congress in 1964 to protect 134 miles of the Current and Jacks Fork Rivers in south-central Missouri. Located within the park are numerous large springs, including Big Spring, the largest spring in Missouri and one of the ten largest springs in the world. Also within the map area is Greer Spring, which is the main source of the Eleven Point River. Greer Spring is the largest spring on National Forest land in the United States. During flood, flow from Greer Spring is almost as large, volumetrically, as that from Big Spring. The Wild and Scenic Rivers Act in 1968 established a 44-mile section of the Eleven Point River as the Eleven Point National Scenic River, which is entirely within the boundaries of this map.
\nPotentially economic mineral resources are present in the subsurface in the map area. Exploration drill-hole data indicate that anomalously high concentrations of base-metal sulfides locally occur within the Cambrian Bonneterre Formation. The geologic setting of these anomalous concentrations is similar to that found in the Viburnum Trend, part of the largest lead-mining district in the world. The southernmost part of the Viburnum Trend extends into the northern part of the map area and is exploited by the Sweetwater Mine. Undeveloped and potentially economic occurrences of base metals are known also beneath Blair Creek, a tributary to the Current River in the north-central part of the map area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3280","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Weary, D.J., Harrison, R., Orndorff, R.C., Weems, R.E., Schindler, J.S., Repetski, J.E., and Pierce, H.A., 2015, Bedrock geologic map of the Spring Valley, West Plains, and parts of the Piedmont and Poplar Bluff 30'x60' quadrangles, Missouri, including the upper Current River and Eleven Point River drainage basins: U.S. Geological Survey Scientific Investigations Map 3280, 2 Sheets: 40.82 x 56.98 inches and 40.07 x 43.90 inches; Pamphlet: iv, 55 p., https://doi.org/10.3133/sim3280.","productDescription":"2 Sheets: 40.82 x 56.98 inches and 40.07 x 43.90 inches; Pamphlet: iv, 55 p.","numberOfPages":"62","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-033086","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":297758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3280.jpg"},{"id":297756,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3280/pdf/sim3280.pdf","text":"Text Pamphlet","size":"1.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Text Pamphlet"},{"id":297755,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3280/pdf/sim3280_sheet2.pdf","text":"Map Sheet 2","size":"14.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Map Sheet 2"},{"id":297754,"rank":2,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3280/pdf/sim3280_sheet1.pdf","text":"Map Sheet 1","size":"15.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Map Sheet 1"},{"id":297753,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3280/"},{"id":297757,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3280/downloads/","text":"Downloads Directory","description":"Downloads Directory","linkHelpText":"Contains: geospatial database. 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Stephen 0000-0001-9550-5957 sschindl@usgs.gov","orcid":"https://orcid.org/0000-0001-9550-5957","contributorId":3270,"corporation":false,"usgs":true,"family":"Schindler","given":"J.","email":"sschindl@usgs.gov","middleInitial":"Stephen","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":518417,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Repetski, John E. 0000-0002-2298-7120 jrepetski@usgs.gov","orcid":"https://orcid.org/0000-0002-2298-7120","contributorId":2596,"corporation":false,"usgs":true,"family":"Repetski","given":"John","email":"jrepetski@usgs.gov","middleInitial":"E.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":518421,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pierce, Herbert A. hpierce@usgs.gov","contributorId":5995,"corporation":false,"usgs":true,"family":"Pierce","given":"Herbert","email":"hpierce@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":false,"id":518422,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70129828,"text":"ds895 - 2015 - Geochemical and petrographic data for intrusions peripheral to the Big Timber Stock, Crazy Mountains, Montana","interactions":[],"lastModifiedDate":"2023-08-16T13:35:49.372755","indexId":"ds895","displayToPublicDate":"2015-02-05T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"895","title":"Geochemical and petrographic data for intrusions peripheral to the Big Timber Stock, Crazy Mountains, Montana","docAbstract":"The Paleocene Fort Union Formation hosts a compositionally diverse array of Eocene plugs, dikes, and sills arrayed around the Eocene Big Timber stock in the Crazy Mountains of south-central Montana. The geochemistry and petrography of the sills have not previously been characterized or interpreted. The purpose of this report is (1) to present available geochemical and petrographic data for several dozen samples of these rocks and (2) to provide a basic interpretive synthesis of these data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds895","usgsCitation":"du Bray, E.A., Wilson, A.B., and Van Gosen, B.S., 2015, Geochemical and petrographic data for intrusions peripheral to the Big Timber Stock, Crazy Mountains, Montana: U.S. Geological Survey Data Series 895, Report: iv, 19 p.; 2 Appendices, https://doi.org/10.3133/ds895.","productDescription":"Report: iv, 19 p.; 2 Appendices","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-058128","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":297749,"rank":5,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds895.jpg"},{"id":297746,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0895/pdf/ds895.pdf","text":"Report","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297748,"rank":1,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0895/downloads/DS895_Appendix2.xlsx","text":"Appendix 2","size":"170 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 2"},{"id":297747,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0895/downloads/DS895_Appendix1.xlsx","text":"Appendix 1","size":"18.6 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 1"},{"id":297745,"rank":4,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0895/"}],"country":"United States","state":"Montana","otherGeospatial":"Crazy Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.52197265625,\n 45.336701909968106\n ],\n [\n -112.52197265625,\n 47.040182144806664\n ],\n [\n -109.2919921875,\n 47.040182144806664\n ],\n [\n -109.2919921875,\n 45.336701909968106\n ],\n [\n -112.52197265625,\n 45.336701909968106\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a7de4b08de9379b30a0","contributors":{"authors":[{"text":"du Bray, Edward A. 0000-0002-4383-8394 edubray@usgs.gov","orcid":"https://orcid.org/0000-0002-4383-8394","contributorId":755,"corporation":false,"usgs":true,"family":"du Bray","given":"Edward","email":"edubray@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":539860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Anna B. 0000-0002-9737-2614 awilson@usgs.gov","orcid":"https://orcid.org/0000-0002-9737-2614","contributorId":1619,"corporation":false,"usgs":true,"family":"Wilson","given":"Anna","email":"awilson@usgs.gov","middleInitial":"B.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":880394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Gosen, Bradley S. 0000-0003-4214-3811 bvangose@usgs.gov","orcid":"https://orcid.org/0000-0003-4214-3811","contributorId":1174,"corporation":false,"usgs":true,"family":"Van Gosen","given":"Bradley","email":"bvangose@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":539878,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168499,"text":"70168499 - 2015 - A genetic discontinuity in moose (Alces alces) in Alaska corresponds with fenced transportation infrastructure","interactions":[],"lastModifiedDate":"2018-08-20T18:09:04","indexId":"70168499","displayToPublicDate":"2015-02-05T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"A genetic discontinuity in moose (Alces alces) in Alaska corresponds with fenced transportation infrastructure","docAbstract":"The strength and arrangement of movement barriers can impact the connectivity among habitat patches. Anthropogenic barriers (e.g. roads) are a source of habitat fragmentation that can disrupt these resource networks and can have an influence on the spatial genetic structure of populations. Using microsatellite data, we evaluated whether observed genetic structure of moose (Alces alces) populations were associated with human activities (e.g. roads) in the urban habitat of Anchorage and rural habitat on the Kenai Peninsula, Alaska. We found evidence of a recent genetic subdivision among moose in Anchorage that corresponds to a major highway and associated infrastructure. This subdivision is most likely due to restrictions in gene flow due to alterations to the highway (e.g. moose-resistant fencing with one-way gates) and a significant increase in traffic volume over the past 30 years; genetic subdivision was not detected on the Kenai Peninsula in an area not bisected by a major highway. This study illustrates that anthropogenic barriers can substructure wildlife populations within a few generations and highlights the value of genetic assessments to determine the effects on connectivity among habitat patches in conjunction with behavioral and ecological data..
","language":"English","publisher":"Kluwer Academic Publishers","doi":"10.1007/s10592-015-0700-x","usgsCitation":"Wilson, R.E., Farley, S.D., McDonough, T.J., Talbot, S.L., and Barboza, P.S., 2015, A genetic discontinuity in moose (Alces alces) in Alaska corresponds with fenced transportation infrastructure: Conservation Genetics, v. 16, no. 4, p. 791-800, https://doi.org/10.1007/s10592-015-0700-x.","productDescription":"10 p.","startPage":"791","endPage":"800","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061406","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":318103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Anchorage","otherGeospatial":"Chugach State Park, Joint Base Elmendorf-Richardson, Kenai Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150.15014648437497,\n 61.08485672110025\n ],\n [\n -150.15014648437497,\n 61.454521127671924\n ],\n [\n -149.44702148437497,\n 61.454521127671924\n ],\n [\n -149.44702148437497,\n 61.08485672110025\n ],\n [\n -150.15014648437497,\n 61.08485672110025\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -152.05078125,\n 59.61776916872399\n ],\n [\n -152.05078125,\n 60.45721779774397\n ],\n [\n -150.63354492187497,\n 60.45721779774397\n ],\n [\n -150.63354492187497,\n 59.61776916872399\n ],\n [\n -152.05078125,\n 59.61776916872399\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-05","publicationStatus":"PW","scienceBaseUri":"56c4563be4b0946c652184da","contributors":{"authors":[{"text":"Wilson, Robert E. 0000-0003-1800-0183 rewilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1800-0183","contributorId":5718,"corporation":false,"usgs":true,"family":"Wilson","given":"Robert","email":"rewilson@usgs.gov","middleInitial":"E.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":620638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farley, Sean D.","contributorId":27642,"corporation":false,"usgs":false,"family":"Farley","given":"Sean","email":"","middleInitial":"D.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":620671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McDonough, Thomas J.","contributorId":166994,"corporation":false,"usgs":false,"family":"McDonough","given":"Thomas","email":"","middleInitial":"J.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":620672,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":620673,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barboza, Perry S.","contributorId":36454,"corporation":false,"usgs":false,"family":"Barboza","given":"Perry","email":"","middleInitial":"S.","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":620674,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70139778,"text":"ofr20151023 - 2015 - Geologic map of the Patagonia Mountains, Santa Cruz County, Arizona","interactions":[],"lastModifiedDate":"2015-02-05T12:54:00","indexId":"ofr20151023","displayToPublicDate":"2015-02-04T13:15:00","publicationYear":"2015","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":"2015-1023","title":"Geologic map of the Patagonia Mountains, Santa Cruz County, Arizona","docAbstract":"The Patagonia Mountains contain two large porphyry Cu-Mo systems each with separate associated hypogene and supergene zones, two high-grade Cu-Mo breccia pipes, one large epithermal Ag-Pb-Zn-Mn deposit, and numerous additional areas of base- and precious-metal mineralization all zoned around a Laramide-age composite batholith of intermediate composition. Compilations and new work by Vikre and others (2014) have identified as many as eight separate intrusive phases of the batholith and five separate hydrothermal events spanning at least 16 m.y., in addition to a supergene enrichment event of middle Tertiary age. The geologic map presents a spatial context for this important new information that is intended to support further work in this highly mineralized region.
\nSeveral spatial databases provide data for the geologic map of the Patagonia Mountains in Arizona. The data can be viewed and queried in ArcGIS 10, a geographic information system; a geologic map is also available in PDF format. All products are available online only.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151023","usgsCitation":"Graybeal, F., Moyer, L.A., Vikre, P.G., Dunlap, P., and Wallis, J., 2015, Geologic map of the Patagonia Mountains, Santa Cruz County, Arizona: U.S. Geological Survey Open-File Report 2015-1023, Pamphlet: 10 p.; Mapsheet: 38.57 x 31.32 inches; Spatial database; Readme; Metadata, https://doi.org/10.3133/ofr20151023.","productDescription":"Pamphlet: 10 p.; Mapsheet: 38.57 x 31.32 inches; Spatial database; Readme; Metadata","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-056357","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":297737,"rank":5,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151023.gif"},{"id":297734,"rank":1,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1023/downloads/GIS_PatagoniaMtns.zip","text":"Spatial database","size":"8.5 MB","description":"Spatial database","linkHelpText":"Contains: geospatial database. Refer to the Readme and Metadata files (all metadata files are zipped as a single file) for more information."},{"id":297735,"rank":2,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/of/2015/1023/readme.txt"},{"id":297736,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2015/1023/Metadata.zip"},{"id":297733,"rank":4,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1023/"}],"scale":"48000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1927","country":"United States","state":"Arizona","county":"Santa Cruz County","otherGeospatial":"Patagonia Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.83934783935547,\n 31.332818285711372\n ],\n [\n -110.83934783935547,\n 31.538456424018218\n ],\n [\n -110.63060760498047,\n 31.538456424018218\n ],\n [\n -110.63060760498047,\n 31.332818285711372\n ],\n [\n -110.83934783935547,\n 31.332818285711372\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a81e4b08de9379b30ae","contributors":{"authors":[{"text":"Graybeal, Frederick","contributorId":139000,"corporation":false,"usgs":false,"family":"Graybeal","given":"Frederick","email":"","affiliations":[{"id":12586,"text":"Consultant","active":true,"usgs":false}],"preferred":true,"id":539838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moyer, Lorre A.","contributorId":106152,"corporation":false,"usgs":true,"family":"Moyer","given":"Lorre","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":539839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vikre, Peter G. 0000-0001-7895-5972 pvikre@usgs.gov","orcid":"https://orcid.org/0000-0001-7895-5972","contributorId":139033,"corporation":false,"usgs":true,"family":"Vikre","given":"Peter","email":"pvikre@usgs.gov","middleInitial":"G.","affiliations":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":539837,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunlap, Pamela pdunlap@usgs.gov","contributorId":5329,"corporation":false,"usgs":true,"family":"Dunlap","given":"Pamela","email":"pdunlap@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":539840,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wallis, John C.","contributorId":45755,"corporation":false,"usgs":true,"family":"Wallis","given":"John C.","affiliations":[],"preferred":false,"id":539841,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70134058,"text":"ofr20141241 - 2015 - Movements of wild pigs in Louisiana and Mississippi, 2011-13","interactions":[],"lastModifiedDate":"2015-02-04T11:11:07","indexId":"ofr20141241","displayToPublicDate":"2015-02-04T11:00:00","publicationYear":"2015","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":"2014-1241","title":"Movements of wild pigs in Louisiana and Mississippi, 2011-13","docAbstract":"The prolific breeding capability, behavioral adaptation, and adverse environmental impacts of invasive wild pigs (Sus scrofa) have increased efforts towards managing their populations and understanding their movements. Currently, little is known about wild pig populations and movements in Louisiana and Mississippi. From 2011 to 2013, the U.S. Geological Survey investigated spatial and temporal movements of wild pigs in both marsh and nonmarsh physiographic regions. Twenty-one Global Positioning System satellite telemetry tracking collars were installed on adult wild pigs captured with trained dogs and released. Coordinates of their locations were recorded hourly. We collected 16,674 hourly data points including date, time, air temperature, and position during a 3-year study. Solar and lunar attributes, such as sun and moon phases and azimuth angles, were not related significantly to the movements among wild pigs. Movements were significantly correlated negatively with air temperature. Differences in movements between seasons and years were observed. On average, movements of boars were significantly greater than those of sows. Average home range, determined by using a minimum convex polygon as a proxy, was 911 hectares for boars, whereas average home range for sows was 116 hectares. Wild pigs in marsh habitat traveled lesser distances relative to those from more arid, nonmarsh habitats. Overall, results of this study indicate that wild pigs in Louisiana and Mississippi have small home ranges. These small home ranges suggest that natural movements have not been a major factor in the recent broad-scale range expansion observed in this species in the United States.
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