{"pageNumber":"571","pageRowStart":"14250","pageSize":"25","recordCount":46856,"records":[{"id":70047841,"text":"ofr20131179 - 2013 - Reconnaissance investigation of the placer gold deposits in the Zarkashan Area of Interest, Ghazni Province, Afghanistan","interactions":[],"lastModifiedDate":"2013-08-27T09:20:54","indexId":"ofr20131179","displayToPublicDate":"2013-08-27T08:40:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1179","title":"Reconnaissance investigation of the placer gold deposits in the Zarkashan Area of Interest, Ghazni Province, Afghanistan","docAbstract":"This study is a reconnaissance investigation of the placer gold deposits in the Zarkashan Area of Interest (AOI) in Ghazni Province, Afghanistan. Detailed investigations of the Zarkashan gold deposits were conducted by Soviet and Afghan geologists in the 1960s and 1970s, prior to the development of satellite-based remote-sensing platforms and new methods of geomorphic mapping. The purpose of this study was to integrate new mapping techniques with previously collected concentration and borehole sampling data and geomorphologic interpretations to reassess the placer gold deposits in the Zarkashan AOI. A methodology combining the collection and analysis of historical sampling data, digital database development, hydrologic analysis, and geomorphic modeling was used. The analysis led to the reinterpretation of four gold-bearing seams along the Zarkashan River, and the calculation of an estimated gold reserve of approximately 3,000 kilograms (kg). This estimate is approximately 1,500 kg greater than the Soviet estimate. The result differs in large part due to the reinterpretation of the seams based on a much lower cutoff grade of 100 mg/m<sup>3</sup>. Because cutoff grade is dependent in part on the price of gold, the sevenfold increase in the price of gold since the undertaking of the Soviet investigation warranted our re-evaluation of their 500 mg/m<sup>3</sup> cutoff grade.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131179","collaboration":"Prepared in cooperation with the Afghan Geological Survey under the auspices of the U.S. Department of Defense Task Force for Business and Stability Operations; USGS Afghanistan Project Product No. 185","usgsCitation":"Malpeli, K., Chirico, P., and McLoughlin, I.H., 2013, Reconnaissance investigation of the placer gold deposits in the Zarkashan Area of Interest, Ghazni Province, Afghanistan: U.S. Geological Survey Open-File Report 2013-1179, iv, 12 p.; 4 Figures: 40 x 26 inches, https://doi.org/10.3133/ofr20131179.","productDescription":"iv, 12 p.; 4 Figures: 40 x 26 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":277034,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131179.gif"},{"id":277029,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1179/"},{"id":277028,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1179/pdf/of2013-1179.pdf"},{"id":277030,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1179/pdf/of2013-1179_figure1.pdf"},{"id":277031,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1179/pdf/of2013-1179_figure2.pdf"},{"id":277032,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1179/pdf/of2013-1179_figure3.pdf"},{"id":277033,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1179/pdf/of2013-1179_figure4.pdf"}],"country":"Afghanistan","otherGeospatial":"Ghazni Province","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 67.0,32.583333 ], [ 67.0,33.333333 ], [ 68.5,33.333333 ], [ 68.5,32.583333 ], [ 67.0,32.583333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52a64066e4b0a6d69588260d","contributors":{"authors":[{"text":"Malpeli, Katherine C.","contributorId":55106,"corporation":false,"usgs":true,"family":"Malpeli","given":"Katherine C.","affiliations":[],"preferred":false,"id":483113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chirico, Peter G.","contributorId":27086,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter G.","affiliations":[],"preferred":false,"id":483112,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McLoughlin, Isabel H.","contributorId":63295,"corporation":false,"usgs":true,"family":"McLoughlin","given":"Isabel","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":483114,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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These changes can have a devastating impact on coastal communities, such as the loss of homes built on retreating sea cliffs or protective dunes eroded by storm waves. Sometimes, however, the changes can be positive, such as new habitat created by storm deposits. The U.S. Geological Survey (USGS) is meeting the need for scientific understanding of how our coasts respond to different hazards with continued assessments of current and future changes along U.S. coastlines. Through the National Assessment of Coastal Change Hazards (NACCH), the USGS carries out the unique task of quantifying coastal change hazards along open-ocean coasts in the United States and its territories. 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,{"id":70047830,"text":"ofr20121219 - 2013 - Carolinas coastal change processes project data report for nearshore observations at Cape Hatteras, North Carolina","interactions":[],"lastModifiedDate":"2025-04-10T15:40:20.72464","indexId":"ofr20121219","displayToPublicDate":"2013-08-26T12:44:00","publicationYear":"2013","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":"2012-1219","title":"Carolinas coastal change processes project data report for nearshore observations at Cape Hatteras, North Carolina","docAbstract":"An oceanographic field study conducted in February 2010 investigated processes that control nearshore flow and sediment transport dynamics at Cape Hatteras, North Carolina. 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,{"id":70047177,"text":"70047177 - 2013 - Florida Panhandle","interactions":[],"lastModifiedDate":"2022-12-27T17:53:56.43368","indexId":"70047177","displayToPublicDate":"2013-08-26T11:02:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"chapter":"M","title":"Florida Panhandle","docAbstract":"Throughout the past century, emergent wetlands have been declining across the Gulf of Mexico. Emergent wetland ecosystems provide a multitude of resources, including plant and wildlife habitat, commercial and recreational economic activity, and natural barriers against storms. As emergent wetland losses increase, so does the need for information on the causes and effects of this loss; emergent wetland mapping, monitoring, and restoration efforts; and education. This report provides scientists, managers, and citizens with valuable baseline information on the status and trends of emergent wetlands along the coast of the Gulf of Mexico. The Florida Panhandle chapter provides status and trends information for the Florida Panhandle using what data is available during the 1950-2010 time period.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Emergent wetlands status and trends in the northern Gulf of Mexico: 1950-2010","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"conferenceTitle":"2013 Gulf of Mexico Alliance (GOMA) All Hands Meeting","conferenceDate":"June 25-27, 2013","conferenceLocation":"Tampa, FL","language":"English","publisher":"U.S. Geological Survey and U.S. Environmental Protection Agency","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Handley, L.R., Spear, K.A., Albrecht, B., Bruening, K., McDowell, A., Baumstark, R., Moyer, R., and Thatcher, C.A., 2013, Florida Panhandle, 22 p.","productDescription":"22 p.","ipdsId":"IP-045000","costCenters":[],"links":[{"id":276989,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340729,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://gom.usgs.gov/web/Site/EmWetStatusTrends"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Panhandle","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -87.659912109375,\n              29.54956657394792\n            ],\n            [\n              -85.2374267578125,\n              29.54956657394792\n            ],\n            [\n              -85.2374267578125,\n              30.982318643027536\n            ],\n            [\n              -87.659912109375,\n              30.982318643027536\n            ],\n            [\n              -87.659912109375,\n              29.54956657394792\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521c6adbe4b01458f78428ff","contributors":{"authors":[{"text":"Handley, Lawrence R. handleyl@usgs.gov","contributorId":3459,"corporation":false,"usgs":true,"family":"Handley","given":"Lawrence","email":"handleyl@usgs.gov","middleInitial":"R.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":481239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spear, Kathryn A. 0000-0001-8942-2856 speark@usgs.gov","orcid":"https://orcid.org/0000-0001-8942-2856","contributorId":1949,"corporation":false,"usgs":true,"family":"Spear","given":"Kathryn","email":"speark@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":481237,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Albrecht, Barbara","contributorId":108011,"corporation":false,"usgs":true,"family":"Albrecht","given":"Barbara","email":"","affiliations":[],"preferred":false,"id":481244,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bruening, Karen","contributorId":98204,"corporation":false,"usgs":true,"family":"Bruening","given":"Karen","email":"","affiliations":[],"preferred":false,"id":481243,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McDowell, Alison","contributorId":31665,"corporation":false,"usgs":true,"family":"McDowell","given":"Alison","email":"","affiliations":[],"preferred":false,"id":481241,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baumstark, René","contributorId":17903,"corporation":false,"usgs":true,"family":"Baumstark","given":"René","affiliations":[],"preferred":false,"id":481240,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moyer, Ryan","contributorId":48460,"corporation":false,"usgs":true,"family":"Moyer","given":"Ryan","affiliations":[],"preferred":false,"id":481242,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thatcher, Cindy A. 0000-0003-0331-071X thatcherc@usgs.gov","orcid":"https://orcid.org/0000-0003-0331-071X","contributorId":2868,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy","email":"thatcherc@usgs.gov","middleInitial":"A.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":481238,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70047819,"text":"sir20135065 - 2013 - Effects of surface applications of biosolids on groundwater quality and trace-element concentrations in crops near Deer Trail, Colorado, 2004-2010","interactions":[],"lastModifiedDate":"2025-05-14T19:19:14.041259","indexId":"sir20135065","displayToPublicDate":"2013-08-26T08:04:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5065","title":"Effects of surface applications of biosolids on groundwater quality and trace-element concentrations in crops near Deer Trail, Colorado, 2004-2010","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with Metro Wastewater Reclamation District (Metro District), studied biosolids composition and the effects of biosolids applications on groundwater quality and trace-element concentrations in crops of the Metro District properties near Deer Trail, Colorado, during 2004 through 2010. Priority parameters for each monitoring component included the nine trace elements regulated by Colorado for biosolids (arsenic, cadmium, copper, lead, mercury, molybdenum, nickel, selenium, and zinc); other constituents also were analyzed. All concentrations for the priority parameters in monthly biosolids samples were less than Colorado regulatory limits, and the concentrations were relatively consistent. Biosolids likely were the largest source of nitrogen and phosphorus on the Metro District properties. Plutonium isotopes were not detected in the biosolids, but many organic wastewater compounds (organic wastewater compounds: wastewater indicators, pharmaceuticals, and hormones) were detected in substantial concentrations relative to minimum reporting levels and various surface-water concentrations. Bismuth, copper, mercury, nitrogen, phosphorus, silver, biogenic sterols, detergent degradates, disinfectants, fire retardants, fragrances, pharmaceuticals, and plasticizers would be the most likely biosolids signature to indicate the presence of Metro District biosolids in soil or streambed sediment from the study area. Antimony, cadmium, cobalt, copper, molybdenum, nickel, nitrogen, phosphorus, selenium, tungsten, vanadium, zinc, detergent degradates, disinfectants, fire retardants, fragrances, pharmaceuticals or their degradates, and plasticizers would be the most likely biosolids signature for groundwater and surface water in the study area. More biosolids-signature components detected and larger concentration differences from untreated materials, baseline, and blank samples indicate more evidence of biosolids presence or effects. Although the inorganic constituent concentrations were relatively large in samples from one monitoring well, the concentrations of organic wastewater compounds in groundwater samples were not correspondingly large. Concentrations of organic wastewater compounds in the groundwater samples from all five monitoring wells were less than the minimum reporting levels with only a few detections. Some of the organic wastewater compounds detected could have anthropogenic sources that are not biosolids. Concentrations of priority parameters in groundwater varied spatially and temporally but generally were less than Colorado regulatory limits. Concentrations of dissolved nitrate, arsenic, and selenium, in addition to chloride, sulfate, total dissolved solids, boron, iron, manganese, and uranium, in samples from some wells exceeded the Colorado standards. Concentrations of dissolved nitrate (three wells), molybdenum (one well), selenium (two wells), and uranium (one well) in shallow groundwater had significant (alpha = 0.05) upward trends in some parts of the study area. The biosolids-signature results indicate that the aquifers intercepted by the five routinely sampled wells likely have received some recharge through treated (biosolids-applied) fields or biosolids-affected ponds. Adverse effects from this biosolids-related recharge range from few (if any) at one well to large and significantly (alpha = 0.05) increasing nitrate concentrations at another well. A statistical evaluation of five paired wheat-grain samples from treated (biosolids-applied) fields and untreated (control) fields did not indicate any evidence that biosolids applications significantly (alpha = 0.05 or 0.10) increased concentration of any of these constituents in wheat grain. The wheat-grain concentrations from this study were similar to those from other studies for fields in North America where no biosolids were applied. The data for the limited crop samples indicate that biosolids applications are not increasing the concentrations of arsenic, cadmium, copper, lead, mercury, molybdenum, nickel, selenium, sulfur, and zinc in mature wheat grain from the study area.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135065","collaboration":"Prepared in cooperation with the Metro Wastewater Reclamation District","usgsCitation":"Yager, T., Crock, J.G., Smith, D., Furlong, E.T., Hageman, P.L., Foreman, W., Gray, J.L., and ReVello, R., 2013, Effects of surface applications of biosolids on groundwater quality and trace-element concentrations in crops near Deer Trail, Colorado, 2004-2010: U.S. Geological Survey Scientific Investigations Report 2013-5065, vi, 119 p., https://doi.org/10.3133/sir20135065.","productDescription":"vi, 119 p.","numberOfPages":"129","onlineOnly":"Y","temporalStart":"2004-01-01","temporalEnd":"2010-12-01","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"links":[{"id":276976,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5065/SIR13-5065.pdf"},{"id":276975,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5065/"},{"id":276977,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135065.png"}],"country":"United States","state":"Colorado","city":"Deer Trail","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -105.5,38.75 ], [ -105.5,40.5 ], [ -103.0,40.5 ], [ -103.0,38.75 ], [ -105.5,38.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521c6adae4b01458f78428f7","contributors":{"authors":[{"text":"Yager, Tracy J.B.","contributorId":10861,"corporation":false,"usgs":true,"family":"Yager","given":"Tracy J.B.","affiliations":[],"preferred":false,"id":483059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crock, James G. jcrock@usgs.gov","contributorId":200,"corporation":false,"usgs":true,"family":"Crock","given":"James","email":"jcrock@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":483052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, David B. 0000-0001-8396-9105 dsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-8396-9105","contributorId":1274,"corporation":false,"usgs":true,"family":"Smith","given":"David B.","email":"dsmith@usgs.gov","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":483056,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Furlong, Edward T. 0000-0002-7305-4603 efurlong@usgs.gov","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":740,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","email":"efurlong@usgs.gov","middleInitial":"T.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":483053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hageman, Philip L. 0000-0002-3440-2150 phageman@usgs.gov","orcid":"https://orcid.org/0000-0002-3440-2150","contributorId":811,"corporation":false,"usgs":true,"family":"Hageman","given":"Philip","email":"phageman@usgs.gov","middleInitial":"L.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":483054,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":483057,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gray, James L. 0000-0002-0807-5635 jlgray@usgs.gov","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":1253,"corporation":false,"usgs":true,"family":"Gray","given":"James","email":"jlgray@usgs.gov","middleInitial":"L.","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":483055,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"ReVello, Rhiannon C. rcrevell@usgs.gov","contributorId":4128,"corporation":false,"usgs":true,"family":"ReVello","given":"Rhiannon C.","email":"rcrevell@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":483058,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70047807,"text":"ds779 - 2013 - Dissolved pesticide concentrations in the Sacramento-San Joaquin Delta and Grizzly Bay, California, 2011-12","interactions":[],"lastModifiedDate":"2026-05-20T17:06:50.702236","indexId":"ds779","displayToPublicDate":"2013-08-23T12:49:00","publicationYear":"2013","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":"779","title":"Dissolved pesticide concentrations in the Sacramento-San Joaquin Delta and Grizzly Bay, California, 2011-12","docAbstract":"Surface-water samples were collected from sites within the Sacramento-San Joaquin Delta and Grizzly Bay, California, during the spring in 2011 and 2012, and they were analyzed by the U.S. Geological Survey for a suite of 99 current-use pesticides and pesticide degradates. Samples were collected and analyzed as part of a collaborative project studying the occurrence and characteristics of phytoplankton in the San Francisco Estuary. Samples were analyzed by two separate laboratory methods employing gas chromatography/mass spectrometry or liquid chromatography with tandem mass spectrometry. Method detection limits ranged from 0.9 to 10.5 nanograms per liter (ng/L). Eighteen pesticides were detected in samples collected during 2011, and the most frequently detected compounds were the herbicides clomazone, diuron, hexazinone and metolachlor, and the diuron degradates 3,4-dichloroaniline and N-(3,4-dichlorophenyl)-N’-methylurea (DCPMU). Concentrations for all compounds were less than 75 ng/L, except for the rice herbicide clomazone and the fungicide tetraconazole, which had maximum concentrations of 535 and 511 ng/L, respectively. In samples collected in 2012, a total of 16 pesticides were detected. The most frequently detected compounds were the fungicides azoxystrobin and boscalid and the herbicides diuron, hexazinone, metolachlor, and simazine. Maximum concentrations for all compounds detected in 2012 were less than 75 ng/L, except for the fungicide azoxystrobin and the herbicides hexazinone and simazine, which were detected at up to 188, 134, and 140 ng/L, respectively.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds779","collaboration":"Prepared in cooperation with the San Luis and Delta Mendota Water Authority","usgsCitation":"Orlando, J., McWayne, M., Sanders, C., and Hladik, M., 2013, Dissolved pesticide concentrations in the Sacramento-San Joaquin Delta and Grizzly Bay, California, 2011-12: U.S. Geological Survey Data Series 779, viii, 24 p., https://doi.org/10.3133/ds779.","productDescription":"viii, 24 p.","numberOfPages":"36","temporalStart":"2011-01-01","temporalEnd":"2012-12-31","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":276960,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/779/pdf/ds779.pdf"},{"id":276959,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/779/"},{"id":276961,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds779.jpg"},{"id":504567,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98805.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"Grizzly Bay, Sacramento-San Joaquin Delta","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.5,37.75 ], [ -122.5,38.75 ], [ -121.0,38.75 ], [ -121.0,37.75 ], [ -122.5,37.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5218765de4b0e27b926cc661","contributors":{"authors":[{"text":"Orlando, James L. 0000-0002-0099-7221","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":95954,"corporation":false,"usgs":true,"family":"Orlando","given":"James L.","affiliations":[],"preferred":false,"id":483010,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McWayne, Megan 0000-0001-8069-6420","orcid":"https://orcid.org/0000-0001-8069-6420","contributorId":36038,"corporation":false,"usgs":true,"family":"McWayne","given":"Megan","affiliations":[],"preferred":false,"id":483007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sanders, Corey 0000-0001-7743-6396","orcid":"https://orcid.org/0000-0001-7743-6396","contributorId":39682,"corporation":false,"usgs":true,"family":"Sanders","given":"Corey","affiliations":[],"preferred":false,"id":483008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hladik, Michelle 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":45990,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","affiliations":[],"preferred":false,"id":483009,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70047776,"text":"fs20133053 - 2013 - The 3D Elevation Program: summary for Idaho","interactions":[],"lastModifiedDate":"2016-08-17T16:10:36","indexId":"fs20133053","displayToPublicDate":"2013-08-23T08:33:00","publicationYear":"2013","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":"2013-3053","title":"The 3D Elevation Program: summary for Idaho","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Idaho, elevation data are critical for agriculture and precision farming, natural resources conservation, infrastructure and construction management, geologic resource assessment and hazard mitigation, flood risk management, forest resources management, and other business uses. Today, high-quality light detection and ranging (lidar) data are the sources for creating elevation models and other elevation datasets. Federal, State, and local agencies work in partnership to (1) replace data, on a national basis, that are (on average) 30 years old and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The new 3D Elevation Program (3DEP) initiative, managed by the U.S. Geological Survey (USGS), responds to the growing need for high-quality topographic data and a wide range of other three-dimensional representations of the Nation&rsquo;s natural and constructed features. The Idaho LiDAR Consortium provides statewide collaboration and data sharing mechanisms that can be used as a resource by State and Federal partners implementing the 3DEP initiative.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133053","usgsCitation":"Carswell, W., 2013, The 3D Elevation Program: summary for Idaho: U.S. Geological Survey Fact Sheet 2013-3053, 2 p., https://doi.org/10.3133/fs20133053.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":276928,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133053.gif"},{"id":276926,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3053/"},{"id":276927,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3053/pdf/fs2013-3053.pdf","text":"Report","size":"225 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 \"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5218765fe4b0e27b926cc66d","contributors":{"authors":[{"text":"Carswell, William J. Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":482943,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70043513,"text":"70043513 - 2013 - Time-lapse analysis of methane quantity in Mary Lee group of coal seams using filter-based multiple-point geostatistical simulation","interactions":[],"lastModifiedDate":"2013-08-22T15:57:52","indexId":"70043513","displayToPublicDate":"2013-08-22T15:49:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2701,"text":"Mathematical Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"Time-lapse analysis of methane quantity in Mary Lee group of coal seams using filter-based multiple-point geostatistical simulation","docAbstract":"Coal seam degasification and its success are important for controlling methane, and thus for the health and safety of coal miners. During the course of degasification, properties of coal seams change. Thus, the changes in coal reservoir conditions and in-place gas content as well as methane emission potential into mines should be evaluated by examining time-dependent changes and the presence of major heterogeneities and geological discontinuities in the field. In this work, time-lapsed reservoir and fluid storage properties of the New Castle coal seam, Mary Lee/Blue Creek seam, and Jagger seam of Black Warrior Basin, Alabama, were determined from gas and water production history matching and production forecasting of vertical degasification wellbores. These properties were combined with isotherm and other important data to compute gas-in-place (GIP) and its change with time at borehole locations. Time-lapsed training images (TIs) of GIP and GIP difference corresponding to each coal and date were generated by using these point-wise data and Voronoi decomposition on the TI grid, which included faults as discontinuities for expansion of Voronoi regions. Filter-based multiple-point geostatistical simulations, which were preferred in this study due to anisotropies and discontinuities in the area, were used to predict time-lapsed GIP distributions within the study area. Performed simulations were used for mapping spatial time-lapsed methane quantities as well as their uncertainties within the study area.\nThe systematic approach presented in this paper is the first time in literature that history matching, TIs of GIPs and filter simulations are used for degasification performance evaluation and for assessing GIP for mining safety. Results from this study showed that using production history matching of coalbed methane wells to determine time-lapsed reservoir data could be used to compute spatial GIP and representative GIP TIs generated through Voronoi decomposition. Furthermore, performing filter simulations using point-wise data and TIs could be used to predict methane quantity in coal seams subjected to degasification. During the course of the study, it was shown that the material balance of gas produced by wellbores and the GIP reductions in coal seams predicted using filter simulations compared very well, showing the success of filter simulations for continuous variables in this case study. Quantitative results from filter simulations of GIP within the studied area briefly showed that GIP was reduced from an initial ∼73 Bcf (median) to ∼46 Bcf (2011), representing a 37 % decrease and varying spatially through degasification. It is forecasted that there will be an additional ∼2 Bcf reduction in methane quantity between 2011 and 2015. This study and presented results showed that the applied methodology and utilized techniques can be used to map GIP and its change within coal seams after degasification, which can further be used for ventilation design for methane control in coal mines.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Mathematical Geosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s11004-013-9474-1","usgsCitation":"Karacan, C., and Olea, R., 2013, Time-lapse analysis of methane quantity in Mary Lee group of coal seams using filter-based multiple-point geostatistical simulation: Mathematical Geosciences, v. 45, no. 6, p. 681-704, https://doi.org/10.1007/s11004-013-9474-1.","productDescription":"24 p.","startPage":"681","endPage":"704","numberOfPages":"24","ipdsId":"IP-039496","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":473591,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4503532","text":"External Repository"},{"id":276923,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276921,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s11004-013-9474-1"}],"country":"United States","state":"Alabama","otherGeospatial":"Black Warrior Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.4731,31.8421 ], [ -88.4731,35.008 ], [ -85.9759,35.008 ], [ -85.9759,31.8421 ], [ -88.4731,31.8421 ] ] ] } } ] }","volume":"45","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-06-25","publicationStatus":"PW","scienceBaseUri":"521724dee4b043bae8d2e5c1","contributors":{"authors":[{"text":"Karacan, C. 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,{"id":70047769,"text":"fs20133052 - 2013 - The 3D Elevation Program: summary for Virginia","interactions":[],"lastModifiedDate":"2016-08-17T16:11:45","indexId":"fs20133052","displayToPublicDate":"2013-08-22T14:41:00","publicationYear":"2013","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":"2013-3052","title":"The 3D Elevation Program: summary for Virginia","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the Commonwealth of Virginia, elevation data are critical for urban and regional planning, natural resources conservation, flood risk management, agriculture and precision farming, resource mining, infrastructure and construction management, and other business uses. Today, high-quality light detection and ranging (lidar) data are the sources for creating elevation models and other elevation datasets. Federal, State, and local agencies work in partnership to (1) replace data, on a national basis, that are (on average) 30 years old and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The new 3D Elevation Program (3DEP) initiative, managed by the U.S. Geological Survey (USGS), responds to the growing need for high-quality topographic data and a wide range of other three-dimensional representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133052","usgsCitation":"Carswell, W., 2013, The 3D Elevation Program: summary for Virginia: U.S. Geological Survey Fact Sheet 2013-3052, 2 p., https://doi.org/10.3133/fs20133052.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":276909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133052.jpg"},{"id":276907,"type":{"id":15,"text":"Index 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,{"id":70047762,"text":"fs20133048 - 2013 - Monitoring of green infrastructure at The Grove in Bloomington, Illinois","interactions":[],"lastModifiedDate":"2013-08-22T11:47:39","indexId":"fs20133048","displayToPublicDate":"2013-08-22T11:38:00","publicationYear":"2013","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":"2013-3048","title":"Monitoring of green infrastructure at The Grove in Bloomington, Illinois","docAbstract":"The City of Bloomington, Illinois, restored Kickapoo Creek to a more natural state by incorporating green infrastructure—specifically flood-plain reconnection, riparian wetlands, meanders, and rock riffles—at a 90-acre park within The Grove residential development. A team of State and Federal agencies and contractors are collecting data to monitor the effectiveness of this stream restoration in improving water quality and stream habitat. The U.S. Geological Survey (USGS) is collecting and analyzing water resources data; Illinois Department of Natural Resources (IDNR) is collecting fish population data; Illinois Environmental Protection Agency (IEPA) is collecting macroinvertebrates and riparian habitat data; and Prairie Engineers of Illinois, P.C., is collecting vegetation data. The data collection includes conditions upstream, within, and downstream of the development and restoration. The 480-acre development was designed by the Farnsworth Group to reduce peak stormwater flows by capturing runoff in the reconnected flood plains with shallow wetland basins. Also, an undersized park bridge was built at the downstream end of the park to pass the 20-percent annual exceedance probability flows (historically referred to as the 5-year flood), but detain larger floods. This design also helps limit sediment deposition from sediments transported in the drainage ditches in the upper 9,000 acres of agricultural row crops. Maintaining sediment-transport capacity minimizes sediment deposition in the restored stream segments, which reduces the loss of riparian and wetland-plant communities and instream habitat. Two additional goals of the restoration were to reduce nutrient loads and maintain water quality to support a diverse community of biotic species. Overall, 2 miles of previously managed agricultural-drainage ditches of Kickapoo Creek were restored, and the park landscape maximizes the enhancement of native riparian, wetland, and aquatic species for the park’s trail system. The purpose of this fact sheet is to give an overview and examples of the data being collected.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133048","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, Illinois Environmental Protection Agency, City of Bloomington, Illinois, Illinois Department of Natural Resources, U.S. Department of Agriculture, Natural Resources Conservation Service, Prairie Engineers of Illinois, P.C.","usgsCitation":"Roseboom, D., and Straub, T., 2013, Monitoring of green infrastructure at The Grove in Bloomington, Illinois: U.S. Geological Survey Fact Sheet 2013-3048, 4 p., https://doi.org/10.3133/fs20133048.","productDescription":"4 p.","onlineOnly":"Y","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":276896,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133048.gif"},{"id":276894,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3048/"},{"id":276895,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3048/pdf/fs2013-3048.pdf"}],"country":"United States","state":"Illinois","city":"Bloomington","otherGeospatial":"Kickapoo Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.88,40.45 ], [ -88.88,40.475 ], [ -88.85,40.475 ], [ -88.85,40.45 ], [ -88.88,40.45 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521724dde4b043bae8d2e5ad","contributors":{"authors":[{"text":"Roseboom, Donald P.","contributorId":94747,"corporation":false,"usgs":true,"family":"Roseboom","given":"Donald P.","affiliations":[],"preferred":false,"id":482917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Straub, Timothy D. 0000-0002-5896-0851 tdstraub@usgs.gov","orcid":"https://orcid.org/0000-0002-5896-0851","contributorId":2273,"corporation":false,"usgs":true,"family":"Straub","given":"Timothy D.","email":"tdstraub@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":482916,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047760,"text":"ofr20121157 - 2013 - Shallow geology, seafloor texture, and physiographic zones of the Inner Continental Shelf from Nahant to northern Cape Cod Bay, Massachusetts","interactions":[],"lastModifiedDate":"2017-11-10T18:29:52","indexId":"ofr20121157","displayToPublicDate":"2013-08-22T10:42:47","publicationYear":"2013","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":"2012-1157","title":"Shallow geology, seafloor texture, and physiographic zones of the Inner Continental Shelf from Nahant to northern Cape Cod Bay, Massachusetts","docAbstract":"The Massachusetts inner continental shelf between Nahant and northern Cape Cod Bay has been profoundly affected by the occupation and retreat of glacial ice sheets and relative sea-level change during the Quaternary. Marine geologic mapping of this area is a component of a statewide cooperative effort involving the U.S. Geological Survey and the Massachusetts Office of Coastal Zone Management. Interpretation of high-resolution geophysical data (interferometric and multibeam swath bathymetry, lidar, backscatter, and seismic reflection), sediment samples, and bottom photographs was used to produce a series of maps that describe the distribution and texture of seafloor sediments, shallow geologic framework, and physiographic zones of this inner-shelf region. These data and interpretations are intended to aid efforts to inventory and manage coastal and marine resources, and provide baseline information for research focused on coastal evolution and environmental change.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121157","usgsCitation":"Pendleton, E., Baldwin, W.E., Barnhardt, W., Ackerman, S.D., Foster, D.S., Andrews, B., and Schwab, W.C., 2013, Shallow geology, seafloor texture, and physiographic zones of the Inner Continental Shelf from Nahant to northern Cape Cod Bay, Massachusetts: U.S. Geological Survey Open-File Report 2012-1157, HTML Document, https://doi.org/10.3133/ofr20121157.","productDescription":"HTML Document","onlineOnly":"Y","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science 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,{"id":70047757,"text":"70047757 - 2013 - Hybrid modeling of spatial continuity for application to numerical inverse problems","interactions":[],"lastModifiedDate":"2013-08-22T10:02:03","indexId":"70047757","displayToPublicDate":"2013-08-22T09:56:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Hybrid modeling of spatial continuity for application to numerical inverse problems","docAbstract":"A novel two-step modeling approach is presented to obtain optimal starting values and geostatistical constraints for numerical inverse problems otherwise characterized by spatially-limited field data. First, a type of unsupervised neural network, called the self-organizing map (SOM), is trained to recognize nonlinear relations among environmental variables (covariates) occurring at various scales. The values of these variables are then estimated at random locations across the model domain by iterative minimization of SOM topographic error vectors. Cross-validation is used to ensure unbiasedness and compute prediction uncertainty for select subsets of the data. Second, analytical functions are fit to experimental variograms derived from original plus resampled SOM estimates producing model variograms. Sequential Gaussian simulation is used to evaluate spatial uncertainty associated with the analytical functions and probable range for constraining variables. The hybrid modeling of spatial continuity is demonstrated using spatially-limited hydrologic measurements at different scales in Brazil: (1) physical soil properties (sand, silt, clay, hydraulic conductivity) in the 42 km<sup>2</sup> Vargem de Caldas basin; (2) well yield and electrical conductivity of groundwater in the 132 km<sup>2</sup> fractured crystalline aquifer; and (3) specific capacity, hydraulic head, and major ions in a 100,000 km<sup>2</sup> transboundary fractured-basalt aquifer. These results illustrate the benefits of exploiting nonlinear relations among sparse and disparate data sets for modeling spatial continuity, but the actual application of these spatial data to improve numerical inverse modeling requires testing.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Modelling and Software","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2013.01.009","usgsCitation":"Friedel, M.J., and Iwashita, F., 2013, Hybrid modeling of spatial continuity for application to numerical inverse problems: Environmental Modelling and Software, v. 43, p. 60-79, https://doi.org/10.1016/j.envsoft.2013.01.009.","productDescription":"20 p.","startPage":"60","endPage":"79","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":276885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276884,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.envsoft.2013.01.009"}],"volume":"43","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521724dae4b043bae8d2e5a5","contributors":{"authors":[{"text":"Friedel, Michael J. 0000-0002-5060-3999 mfriedel@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-3999","contributorId":595,"corporation":false,"usgs":true,"family":"Friedel","given":"Michael","email":"mfriedel@usgs.gov","middleInitial":"J.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":482903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iwashita, Fabio","contributorId":72287,"corporation":false,"usgs":true,"family":"Iwashita","given":"Fabio","email":"","affiliations":[],"preferred":false,"id":482904,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047727,"text":"ds747 - 2013 - Groundwater-quality data in the Bear Valley and Selected Hard Rock Areas study unit, 2010: Results from the California GAMA Program","interactions":[],"lastModifiedDate":"2026-05-18T16:47:20.056927","indexId":"ds747","displayToPublicDate":"2013-08-20T14:42:00","publicationYear":"2013","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":"747","subseriesTitle":"California Groundwater Ambient Monitoring and Assessment (GAMA) Program","title":"Groundwater-quality data in the Bear Valley and Selected Hard Rock Areas study unit, 2010: Results from the California GAMA Program","docAbstract":"Groundwater quality in the 112-square-mile Bear Valley and Selected Hard Rock Areas (BEAR) study unit was investigated by the U.S. Geological Survey (USGS) from April to August 2010, as part of the California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring and Assessment (GAMA) Program’s Priority Basin Project (PBP). The GAMA-PBP was developed in response to the California Groundwater Quality Monitoring Act of 2001 and is being conducted in collaboration with the SWRCB and Lawrence Livermore National Laboratory (LLNL). The BEAR study unit was the thirty-first study unit to be sampled as part of the GAMA-PBP. The GAMA Bear Valley and Selected Hard Rock Areas study was designed to provide a spatially unbiased assessment of untreated-groundwater quality in the primary aquifer system and to facilitate statistically consistent comparisons of untreated groundwater quality throughout California. The primary aquifer system is defined as the zones corresponding to the perforation intervals of wells listed in the California Department of Public Health (CDPH) database for the BEAR study unit. Groundwater quality in the primary aquifer system may differ from the quality in the shallow or deep water-bearing zones; shallow groundwater may be more vulnerable to surficial contamination. In the BEAR study unit, groundwater samples were collected from two study areas (Bear Valley and Selected Hard Rock Areas) in San Bernardino County. Of the 38 sampling sites, 27 were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the primary aquifer system in the study unit (grid sites), and the remaining 11 sites were selected to aid in the understanding of the potential groundwater-quality issues associated with septic tank use and with ski areas in the study unit (understanding sites). The groundwater samples were analyzed for organic constituents (volatile organic compounds [VOCs], pesticides and pesticide degradates, pharmaceutical compounds, and wastewater indicator compounds [WICs]), constituents of special interest (perchlorate, N-nitrosodimethylamine [NDMA], and 1,2,3-trichloropropane [1,2,3-TCP]), and inorganic constituents (trace elements, nutrients, dissolved organic carbon [DOC], major and minor ions, silica, total dissolved solids [TDS], alkalinity, and arsenic and iron species), and uranium and other radioactive constituents (radon-222 and activities of tritium and carbon-14). Isotopic tracers (of hydrogen and oxygen in water, of nitrogen and oxygen in dissolved nitrate, of dissolved boron, isotopic ratios of strontium in water, and of carbon in dissolved inorganic carbon) and dissolved noble gases (argon, helium-4, krypton, neon, and xenon) were measured to help identify the sources and ages of sampled groundwater. In total, groundwater samples were analyzed for 289 unique constituents and 8 water-quality indicators in the BEAR study unit. Quality-control samples (blanks, replicate pairs, or matrix spikes) were collected at 13 percent of the sites in the BEAR study unit, and the results for these samples were used to evaluate the quality of the data from the groundwater samples. Blank samples rarely contained detectable concentrations of any constituent, indicating that contamination from sample collection or analysis was not a significant source of bias in the data for the groundwater samples. Replicate pair samples all were within acceptable limits of variability. Matrix-spike sample recoveries were within the acceptable range (70 to 130 percent) for approximately 84 percent of the compounds. This study did not evaluate the quality of water delivered to consumers. After withdrawal, groundwater typically is treated, disinfected, and (or) blended with other waters to maintain water quality. Regulatory benchmarks apply to water that is delivered to the consumer, not to untreated groundwater. However, to provide some context for the results, concentrations of constituents measured in the untreated groundwater were compared with regulatory and non-regulatory health-based benchmarks established by the U.S. Environmental Protection Agency (USEPA) and CDPH, and to non-health-based benchmarks established for aesthetic concerns by CDPH. Comparisons between data collected for this study and benchmarks for drinking water are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks. All concentrations of organic and special-interest constituents from grid sites sampled in the BEAR study unit were less than health-based benchmarks. In total, VOCs were detected in 17 of the 27 grid sites sampled (approximately 63 percent), pesticides and pesticide degradates were detected in 4 grid sites (approximately 15 percent), and perchlorate was detected in 21 grid sites (approximately 78 percent). Inorganic constituents (trace elements, major and minor ions, nutrients, and uranium and other radioactive constituents) were sampled for at 27 grid sites; most concentrations were less than health-based benchmarks. Exceptions include one detection of arsenic greater than the USEPA maximum contaminant level (MCL-US) of 10 micrograms per liter (μg/L), three detections of uranium greater than the MCL-US of 30 μg/L, nine detections of radon-222 greater than the proposed MCL-US of 4,000 picocuries per liter (pCi/L), and one detection of fluoride greater than the CDPH maximum contaminant level (MCL-CA) of 2 milligrams per liter. Concentrations of inorganic constituents with non-health-based benchmarks (iron, manganese, chloride, and TDS) were less than the CDPH secondary maximum contaminant level (SMCL-CA) in most grid sites. Exceptions include two detections of iron greater than the SMCL-CA of 300 μg/L and one detection of manganese greater than the SMCL-CA of 50 μg/L.","language":"English","publisher":"U.S Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds747","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Mathany, T., and Belitz, K., 2013, Groundwater-quality data in the Bear Valley and Selected Hard Rock Areas study unit, 2010: Results from the California GAMA Program: U.S. Geological Survey Data Series 747, x, 86 p., https://doi.org/10.3133/ds747.","productDescription":"x, 86 p.","numberOfPages":"100","additionalOnlineFiles":"N","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":504492,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98794.htm","linkFileType":{"id":5,"text":"html"}},{"id":276822,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds747.jpg"},{"id":276820,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/747/pdf/ds747.pdf"},{"id":276821,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/747/"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.26738,33.898917 ], [ -117.26738,34.530318 ], [ -116.368561,34.530318 ], [ -116.368561,33.898917 ], [ -117.26738,33.898917 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521481e0e4b06d85e08fb4bf","contributors":{"authors":[{"text":"Mathany, Timothy M. 0000-0002-4747-5113","orcid":"https://orcid.org/0000-0002-4747-5113","contributorId":99949,"corporation":false,"usgs":true,"family":"Mathany","given":"Timothy M.","affiliations":[],"preferred":false,"id":482833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":482832,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047726,"text":"ds742 - 2013 - Groundwater-quality data in the Santa Barbara study unit, 2011: Results from the California GAMA Program","interactions":[],"lastModifiedDate":"2026-05-19T13:22:12.177843","indexId":"ds742","displayToPublicDate":"2013-08-20T14:42:00","publicationYear":"2013","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":"742","subseriesTitle":"California Groundwater Ambient Monitoring and Assessment (GAMA) Program","title":"Groundwater-quality data in the Santa Barbara study unit, 2011: Results from the California GAMA Program","docAbstract":"Groundwater quality in the 48-square-mile Santa Barbara study unit was investigated by the U.S. Geological Survey (USGS) from January to February 2011, as part of the California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring and Assessment (GAMA) Program’s Priority Basin Project (PBP). The GAMA-PBP was developed in response to the California Groundwater Quality Monitoring Act of 2001 and is being conducted in collaboration with the SWRCB and Lawrence Livermore National Laboratory (LLNL). The Santa Barbara study unit was the thirty-fourth study unit to be sampled as part of the GAMA-PBP.\n\nThe GAMA Santa Barbara study was designed to provide a spatially unbiased assessment of untreated-groundwater quality in the primary aquifer system, and to facilitate statistically consistent comparisons of untreated-groundwater quality throughout California. The primary aquifer system is defined as those parts of the aquifers corresponding to the perforation intervals of wells listed in the California Department of Public Health (CDPH) database for the Santa Barbara study unit. Groundwater quality in the primary aquifer system may differ from the quality in the shallower or deeper water-bearing zones; shallow groundwater may be more vulnerable to surficial contamination.\n\nIn the Santa Barbara study unit located in Santa Barbara and Ventura Counties, groundwater samples were collected from 24 wells. Eighteen of the wells were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the study unit (grid wells), and six wells were selected to aid in evaluation of water-quality issues (understanding wells).\n\nThe groundwater samples were analyzed for organic constituents (volatile organic compounds [VOCs], pesticides and pesticide degradates, and pharmaceutical compounds); constituents of special interest (perchlorate and N-nitrosodimethylamine [NDMA]); naturally occurring inorganic constituents (trace elements, nutrients, major and minor ions, silica, total dissolved solids [TDS], alkalinity, and arsenic, chromium, and iron species); and radioactive constituents (radon-222 and gross alpha and gross beta radioactivity). Naturally occurring isotopes (stable isotopes of hydrogen and oxygen in water, stables isotopes of inorganic carbon and boron dissolved in water, isotope ratios of dissolved strontium, tritium activities, and carbon-14 abundances) and dissolved noble gases also were measured to help identify the sources and ages of the sampled groundwater. In total, 281 constituents and water-quality indicators were measured.\n\nThree types of quality-control samples (blanks, replicates, and matrix spikes) were collected at up to 12 percent of the wells in the Santa Barbara study unit, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. Blanks rarely contained detectable concentrations of any constituent, suggesting that contamination from sample collection procedures was not a significant source of bias in the data for the groundwater samples. Replicate samples generally were within the limits of acceptable analytical reproducibility. Matrix-spike recoveries were within the acceptable range (70 to 130 percent) for approximately 82 percent of the compounds.\n\nThis study did not attempt to evaluate the quality of water delivered to consumers; after withdrawal from the ground, untreated groundwater typically is treated, disinfected, and (or) blended with other waters to maintain water quality. Regulatory benchmarks apply to water that is served to the consumer, not to untreated groundwater. However, to provide some context for the results, concentrations of constituents measured in the untreated groundwater were compared with regulatory and non-regulatory health-based benchmarks established by the U.S. Environmental Protection Agency (USEPA) and CDPH and to non-regulatory benchmarks established for aesthetic concerns by CDPH. Comparisons between data collected for this study and benchmarks for drinking water are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks. All organic constituents and most inorganic constituents that were detected in groundwater samples from the 18 grid wells in the Santa Barbara study unit were detected at concentrations less than drinking-water benchmarks.\n\nOf the 220 organic and special-interest constituents sampled for at the 18 grid wells, 13 were detected in groundwater samples; concentrations of all detected constituents were less than regulatory and non-regulatory health-based benchmarks. In total, VOCs were detected in 61 percent of the 18 grid wells sampled, pesticides and pesticide degradates were detected in 11 percent, and perchlorate was detected in 67 percent. Polar pesticides and their degradates, pharmaceutical compounds, and NDMA were not detected in any of the grid wells sampled in the Santa Barbara study unit.\n\nEighteen grid wells were sampled for trace elements, major and minor ions, nutrients, and radioactive constituents; most detected concentrations were less than health-based benchmarks. Exceptions are one detection of boron greater than the CDPH notification level (NL-CA) of 1,000 micrograms per liter (μg/L) and one detection of fluoride greater than the CDPH maximum contaminant level (MCL-CA) of 2 milligrams per liter (mg/L).\n\nResults for constituents with non-regulatory benchmarks set for aesthetic concerns from the grid wells showed that iron concentrations greater than the CDPH secondary maximum contaminant level (SMCL-CA) of 300 μg/L were detected in three grid wells. Manganese concentrations greater than the SMCL-CA of 50 μg/L were detected in seven grid wells. Chloride was detected at a concentration greater than the SMCL-CA recommended benchmark of 250 mg/L in four grid wells. Sulfate concentrations greater than the SMCL-CA recommended benchmark of 250 mg/L were measured in eight grid wells, and the concentration in one of these wells was also greater than the SMCL-CA upper benchmark of 500 mg/L. TDS concentrations greater than the SMCL-CA recommended benchmark of 500 mg/L were measured in 17 grid wells, and concentrations in six of these wells were also greater than the SMCL-CA upper benchmark of 1,000 mg/L.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds742","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Davis, T., Kulongoski, J., and Belitz, K., 2013, Groundwater-quality data in the Santa Barbara study unit, 2011: results from the California GAMA Program: U.S. Geological Survey Data Series 742, ix, 72 p., https://doi.org/10.3133/ds742.","productDescription":"ix, 72 p.","numberOfPages":"86","temporalStart":"2011-01-01","temporalEnd":"2011-02-28","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":504489,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98795.htm","linkFileType":{"id":5,"text":"html"}},{"id":276819,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds742.PNG"},{"id":276818,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/742/pdf/ds742.pdf"},{"id":276817,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/742/"}],"country":"United States","state":"California","county":"Santa Barbara County, Ventura County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.916667,34.333333 ], [ -119.916667,34.5 ], [ -119.416667,34.5 ], [ -119.416667,34.333333 ], [ -119.916667,34.333333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521481e1e4b06d85e08fb4c3","contributors":{"authors":[{"text":"Davis, Tracy A. 0000-0003-0253-6661","orcid":"https://orcid.org/0000-0003-0253-6661","contributorId":59339,"corporation":false,"usgs":true,"family":"Davis","given":"Tracy A.","affiliations":[],"preferred":false,"id":482830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":94750,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin T.","affiliations":[],"preferred":false,"id":482831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482829,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70047719,"text":"ofr20131133 - 2013 - Salton Sea ecosystem monitoring and assessment plan","interactions":[],"lastModifiedDate":"2013-08-20T13:02:40","indexId":"ofr20131133","displayToPublicDate":"2013-08-20T12:55:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1133","title":"Salton Sea ecosystem monitoring and assessment plan","docAbstract":"The Salton Sea, California’s largest lake, provides essential habitat for several fish and wildlife species and is an important cultural and recreational resource. It has no outlet, and dissolved salts contained in the inflows concentrate in the Salton Sea through evaporation. The salinity of the Salton Sea, which is currently nearly one and a half times the salinity of ocean water, has been increasing as a result of evaporative processes and low freshwater inputs. Further reductions in inflows from water conservation, recycling, and transfers will lower the level of the Salton Sea and accelerate the rate of salinity increases, reduce the suitability of fish and wildlife habitat, and affect air quality by exposing lakebed playa that could generate dust.\n\nLegislation enacted in 2003 to implement the Quantification Settlement Agreement (QSA) stated the Legislature’s intent for the State of California to undertake the restoration of the Salton Sea ecosystem. As required by the legislation, the California Resources Agency (now California Natural Resources Agency) produced the Salton Sea Ecosystem Restoration Study and final Programmatic Environmental Impact Report (PEIR; California Resources Agency, 2007) with the stated purpose to “develop a preferred alternative by exploring alternative ways to restore important ecological functions of the Salton Sea that have existed for about 100 years.” A decision regarding a preferred alternative currently resides with the California State Legislature (Legislature), which has yet to take action.\n\nAs part of efforts to identify an ecosystem restoration program for the Salton Sea, and in anticipation of direction from the Legislature, the California Department of Water Resources (DWR), California Department of Fish and Wildlife (CDFW), U.S. Bureau of Reclamation (Reclamation), and U.S. Geological Survey (USGS) established a team to develop a monitoring and assessment plan (MAP). This plan is the product of that effort.\n\nThe goal of the MAP is to provide a guide for data collection, analysis, management, and reporting to inform management actions for the Salton Sea ecosystem. Monitoring activities are directed at species and habitats that could be affected by or drive future restoration activities. The MAP is not intended to be a prescriptive document. Rather, it is envisioned to be a flexible, program-level guide that articulates high-level goals and objectives, and establishes broad sideboards within which future project-level investigations and studies will be evaluated and authorized. As such, the MAP, by design, does not, for example, include detailed protocols describing how investigations will be implemented. It is anticipated that detailed study proposals will be prepared as part of an implementation plan that will include such things as specific sampling objectives, sampling schemes, and statistical and spatial limits.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131133","collaboration":"Prepared for the California Department of Water Resources, Salton Sea Ecosystem Restoration Program Kent Nelson, Program Manager","usgsCitation":"Case(compiler), H., Boles, J., Delgado, A., Nguyen, T., Osugi, D., Barnum, D.A., Decker, D., Steinberg, S., Steinberg, S., Keene, C., White, K., Lupo, T., Gen, S., and Baerenklau, K.A., 2013, Salton Sea ecosystem monitoring and assessment plan: U.S. Geological Survey Open-File Report 2013-1133, iv, 220 p., https://doi.org/10.3133/ofr20131133.","productDescription":"iv, 220 p.","numberOfPages":"241","additionalOnlineFiles":"N","costCenters":[{"id":550,"text":"Salton Sea Science Office","active":true,"usgs":true}],"links":[{"id":276810,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131133.jpg"},{"id":276808,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1133/"},{"id":276809,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1133/pdf/ofr20131133.pdf"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.28,32.95 ], [ -116.28,33.67 ], [ -115.31,33.67 ], [ -115.31,32.95 ], [ -116.28,32.95 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521481e1e4b06d85e08fb4c7","contributors":{"authors":[{"text":"Case(compiler), H. L. III","contributorId":69461,"corporation":false,"usgs":true,"family":"Case(compiler)","given":"H. L.","suffix":"III","affiliations":[],"preferred":false,"id":482806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boles, Jerry","contributorId":102374,"corporation":false,"usgs":true,"family":"Boles","given":"Jerry","email":"","affiliations":[],"preferred":false,"id":482810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Delgado, Arturo","contributorId":101176,"corporation":false,"usgs":true,"family":"Delgado","given":"Arturo","email":"","affiliations":[],"preferred":false,"id":482809,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nguyen, Thang","contributorId":45997,"corporation":false,"usgs":true,"family":"Nguyen","given":"Thang","email":"","affiliations":[],"preferred":false,"id":482802,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Osugi, Doug","contributorId":66163,"corporation":false,"usgs":true,"family":"Osugi","given":"Doug","email":"","affiliations":[],"preferred":false,"id":482805,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barnum, Douglas A. doug_barnum@usgs.gov","contributorId":3566,"corporation":false,"usgs":true,"family":"Barnum","given":"Douglas","email":"doug_barnum@usgs.gov","middleInitial":"A.","affiliations":[{"id":550,"text":"Salton Sea Science Office","active":true,"usgs":true}],"preferred":true,"id":482798,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Decker, Drew ddecker@usgs.gov","contributorId":5513,"corporation":false,"usgs":true,"family":"Decker","given":"Drew","email":"ddecker@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":482799,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Steinberg, Steven","contributorId":71872,"corporation":false,"usgs":true,"family":"Steinberg","given":"Steven","email":"","affiliations":[],"preferred":false,"id":482808,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Steinberg, Sheila","contributorId":36449,"corporation":false,"usgs":true,"family":"Steinberg","given":"Sheila","email":"","affiliations":[],"preferred":false,"id":482801,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Keene, Charles","contributorId":70279,"corporation":false,"usgs":true,"family":"Keene","given":"Charles","email":"","affiliations":[],"preferred":false,"id":482807,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"White, Kristina","contributorId":11933,"corporation":false,"usgs":true,"family":"White","given":"Kristina","email":"","affiliations":[],"preferred":false,"id":482800,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lupo, Tom","contributorId":59338,"corporation":false,"usgs":true,"family":"Lupo","given":"Tom","email":"","affiliations":[],"preferred":false,"id":482804,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Gen, Sheldon","contributorId":46406,"corporation":false,"usgs":true,"family":"Gen","given":"Sheldon","email":"","affiliations":[],"preferred":false,"id":482803,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Baerenklau, Ken A.","contributorId":108020,"corporation":false,"usgs":true,"family":"Baerenklau","given":"Ken","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":482811,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70047718,"text":"fs20133057 - 2013 - The 3D Elevation Program: summary for Washington","interactions":[],"lastModifiedDate":"2016-08-17T16:12:52","indexId":"fs20133057","displayToPublicDate":"2013-08-20T12:47:00","publicationYear":"2013","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":"2013-3057","title":"The 3D Elevation Program: summary for Washington","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Washington, elevation data are critical for natural resources conservation, agriculture and precision farming, infrastructure and construction management, flood risk management, geologic resource assessment and hazards mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.</p>\n<p>The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A&ndash;16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133057","usgsCitation":"Carswell, W., 2013, The 3D Elevation Program: summary for Washington (Originally posted August 20, 2013; Revised and reposted August 14, 2014, version 1.1): U.S. Geological Survey Fact Sheet 2013-3057, 2 p., https://doi.org/10.3133/fs20133057.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":423,"text":"National Geospatial 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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":482797,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70047707,"text":"70047707 - 2013 - The 2011 Mw 7.1 Van (Eastern Turkey) earthquake","interactions":[],"lastModifiedDate":"2013-08-20T08:37:42","indexId":"70047707","displayToPublicDate":"2013-08-20T08:19:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"The 2011 Mw 7.1 Van (Eastern Turkey) earthquake","docAbstract":"We use interferometric synthetic aperture radar (InSAR), body wave seismology, satellite imagery, and field observations to constrain the fault parameters of the M<sub>w</sub> 7.1 2011 Van (Eastern Turkey) reverse-slip earthquake, in the Turkish-Iranian plateau. Distributed slip models from elastic dislocation modeling of the InSAR surface displacements from ENVISAT and COSMO-SkyMed interferograms indicate up to 9 m of reverse and oblique slip on a pair of en echelon NW 40 &deg;–54 &deg; dipping fault planes which have surface extensions projecting to just 10 km north of the city of Van. The slip remained buried and is relatively deep, with a centroid depth of 14 km, and the rupture reaching only within 8–9 km of the surface, consistent with the lack of significant ground rupture. The up-dip extension of this modeled WSW striking fault plane coincides with field observations of weak ground deformation seen on the western of the two fault segments and has a dip consistent with that seen at the surface in fault gouge exposed in Quaternary sediments. No significant coseismic slip is found in the upper 8 km of the crust above the main slip patches, except for a small region on the eastern segment potentially resulting from the M<sub>w</sub> 5.9 aftershock on the same day. We perform extensive resolution tests on the data to confirm the robustness of the observed slip deficit in the shallow crust. We resolve a steep gradient in displacement at the point where the planes of the two fault segments ends are inferred to abut at depth, possibly exerting some structural control on rupture extent.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/jgrb.50117","usgsCitation":"Elliot, J., Copley, A.C., Holley, R., Scharer, K.M., and Parsons, B., 2013, The 2011 Mw 7.1 Van (Eastern Turkey) earthquake: Journal of Geophysical Research, v. 118, no. 4, p. 1619-1637, https://doi.org/10.1002/jgrb.50117.","productDescription":"19 p.","startPage":"1619","endPage":"1637","numberOfPages":"19","ipdsId":"IP-038911","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":276789,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276788,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrb.50117"}],"country":"Turkey","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 33.0,33.0 ], [ 33.0,44.0 ], [ 52.0,44.0 ], [ 52.0,33.0 ], [ 33.0,33.0 ] ] ] } } ] }","volume":"118","issue":"4","noUsgsAuthors":false,"publicationDate":"2013-04-04","publicationStatus":"PW","scienceBaseUri":"521481e2e4b06d85e08fb4cb","contributors":{"authors":[{"text":"Elliot, John R.","contributorId":26612,"corporation":false,"usgs":true,"family":"Elliot","given":"John R.","affiliations":[],"preferred":false,"id":482782,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Copley, Alex C.","contributorId":90630,"corporation":false,"usgs":true,"family":"Copley","given":"Alex","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":482785,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holley, R.","contributorId":85874,"corporation":false,"usgs":true,"family":"Holley","given":"R.","email":"","affiliations":[],"preferred":false,"id":482784,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scharer, Katherine M. 0000-0003-2811-2496 kscharer@usgs.gov","orcid":"https://orcid.org/0000-0003-2811-2496","contributorId":3385,"corporation":false,"usgs":true,"family":"Scharer","given":"Katherine","email":"kscharer@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":482781,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parsons, Barry","contributorId":56966,"corporation":false,"usgs":true,"family":"Parsons","given":"Barry","affiliations":[],"preferred":false,"id":482783,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70047697,"text":"ofr20131190 - 2013 - Knowledge and understanding of dissolved solids in the Rio Grande–San Acacia, New Mexico, to Fort Quitman, Texas, and plan for future studies and monitoring","interactions":[],"lastModifiedDate":"2013-08-19T15:16:39","indexId":"ofr20131190","displayToPublicDate":"2013-08-19T15:02:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1190","title":"Knowledge and understanding of dissolved solids in the Rio Grande–San Acacia, New Mexico, to Fort Quitman, Texas, and plan for future studies and monitoring","docAbstract":"Availability of water in the Rio Grande Basin has long been a primary concern for water-resource managers. The transport and delivery of water in the basin have been engineered by using reservoirs, irrigation canals and drains, and transmountain-water diversions to meet the agricultural, residential, and industrial demand. In contrast, despite the widespread recognition of critical water-quality problems, there have been minimal management efforts to improve water quality in the Rio Grande. Of greatest concern is salinization (concentration of dissolved solids approaching 1,000 mg/L), a water-quality problem that has been recognized and researched for more than 100 years because of the potential to limit both agricultural and municipal use. To address the issue of salinization, water-resource managers need to have a clear conceptual understanding of the sources of salinity and the factors that control storage and transport, identify critical knowledge gaps in this conceptual understanding, and develop a research plan to address these gaps and develop a salinity management program. In 2009, the U.S. Geological Survey (USGS) in cooperation with the U.S. Army Corps of Engineers (USACE), New Mexico Interstate Stream Commission (NMISC), and New Mexico Environment Department (NMED) initiated a project to summarize the current state of knowledge regarding the transport of dissolved solids in the Rio Grande between San Acacia, New Mexico, and Fort Quitman, Texas. The primary objective is to provide hydrologic information pertaining to the spatial and temporal variability present in the concentrations and loads of dissolved solids in the Rio Grande, the source-specific budget for the mass of dissolved solids transported along the Rio Grande, and the locations at which dissolved solids enter the Rio Grande. Dissolved-solids concentration data provide a good indicator of the general quality of surface water and provide information on the factors governing salinization within the Rio Grande study area. The pattern in dissolved-solids concentrations along the Rio Grande is one of increasing concentration with increasing distance downstream from Elephant Butte and Caballo Reservoirs. The concentration of dissolved solids in the Rio Grande doubles (approximately 500 to 1,000 mg/L) from below Elephant Butte Reservoir to El Paso and increases by more than a factor of 5 (approximately 500 to 3,200 mg/L) from below Elephant Butte Reservoir to Fort Quitman. Marked increases in the concentration of dissolved solids commonly coincide with contributions from agricultural drains, wastewater-treatment plants, regional groundwater, and upward-flowing saline groundwater.  The greatest factor, from the surface-water system, in controlling dissolved solids in the Rio Grande is the amount of water that is being transported or stored. Annual variation in streamflow is influenced primarily by climate (precipitation and evaporation) and management of Elephant Butte and Caballo Reservoirs (water storage and release cycles). Seasonal variation in streamflow within the Rio Grande study area is generally categorized generally as irrigation (March–September) and nonirrigation (October–February) seasons; with streamflow in the Rio Grande is highest during the irrigation season and lowest during the nonirrigation season. Dissolved-solids loads during the irrigation season decrease between Leasburg and Fort Quitman primarily because of irrigation diversions and losses to the underlying alluvial aquifer. Conversely, dissolved-solids loads during the nonirrigation season increase between Caballo Dam and Fort Quitman primarily because of the inflow of dissolved solids from agricultural drains, wastewater-treatment plants, and groundwater with elevated concentrations of dissolved solids.  Many studies have mass-balance budgets that account for the mass of dissolved solids transported along the Rio Grande. Results from mass-balance budgets developed for dissolved solids indicated that (1) the inflow of saline groundwater, inflow of regional groundwater, and chemical reactions between mineral phases are the primary sources controlling dissolved solids in the Rio Grande, and (2) groundwater pumping and mineral precipitation are causing a net storage of dissolved solids in the Leasburg to El Paso and El Paso to Fort Quitman reaches of the Rio Grande.  Looking forward, multiple water-resource managers from State and local agencies in New Mexico and Texas and Federal agencies formed the Rio Grande Salinity Management Coalition with the goal to reduce the amount of dissolved solids that are transported and stored in the Rio Grande study area. The recommendations for additional monitoring to assist the coalition are as follows:\n-Monitoring: Couple water-quality and streamflow monitoring in the Rio Grande and agricultural drains; perform groundwater-seepage investigations in the Rio Grande and major agricultural drains; nonitor groundwater water-quality conditions in the Mesilla and Hueco Basins.\n-Focused Hydrogeology Studies at Inflow Sources: Map dissolved-solids concentrations in the Rio Grande and underlying alluvial aquifer; perform hydrogeologic characterization of subsurface areas containing unusually high concentrations of dissolved solids. \n-Modeling of Dissolved Solids: Develop models to simulate the transport and storage of dissolved solids in both surface-water and groundwater systems.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131190","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, New Mexico Interstate Stream Commission, and New Mexico Environment Department","usgsCitation":"Moyer, D., Anderholm, S.K., Hogan, J., Phillips, F.M., Hibbs, B.J., Witcher, J.C., Matherne, A.M., and Falk, S.E., 2013, Knowledge and understanding of dissolved solids in the Rio Grande–San Acacia, New Mexico, to Fort Quitman, Texas, and plan for future studies and monitoring: U.S. Geological Survey Open-File Report 2013-1190, vii, 55 p., https://doi.org/10.3133/ofr20131190.","productDescription":"vii, 55 p.","numberOfPages":"67","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":276776,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1190/"},{"id":276777,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1190/pdf/ofr2013-1190.pdf"},{"id":276779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131190.gif"}],"country":"Mexico;United States","state":"New Mexico;Texas","otherGeospatial":"Rio Grande Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -108,31 ], [ -108,34.15 ], [ -105.15,34.15 ], [ -105.15,31 ], [ -108,31 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52136df9e4b0b08f4461988f","contributors":{"authors":[{"text":"Moyer, Douglas 0000-0001-6330-478X dlmoyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6330-478X","contributorId":2670,"corporation":false,"usgs":true,"family":"Moyer","given":"Douglas","email":"dlmoyer@usgs.gov","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":false,"id":482745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderholm, Scott K.","contributorId":94270,"corporation":false,"usgs":true,"family":"Anderholm","given":"Scott","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":482749,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hogan, James F.","contributorId":30533,"corporation":false,"usgs":true,"family":"Hogan","given":"James F.","affiliations":[],"preferred":false,"id":482746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phillips, Fred M.","contributorId":57957,"corporation":false,"usgs":true,"family":"Phillips","given":"Fred","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":482748,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hibbs, Barry J.","contributorId":55327,"corporation":false,"usgs":true,"family":"Hibbs","given":"Barry","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":482747,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Witcher, James C.","contributorId":99456,"corporation":false,"usgs":true,"family":"Witcher","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":482750,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Matherne, Anne Marie 0000-0002-5873-2226 matherne@usgs.gov","orcid":"https://orcid.org/0000-0002-5873-2226","contributorId":303,"corporation":false,"usgs":true,"family":"Matherne","given":"Anne","email":"matherne@usgs.gov","middleInitial":"Marie","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482743,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Falk, Sarah E. sefalk@usgs.gov","contributorId":1056,"corporation":false,"usgs":true,"family":"Falk","given":"Sarah","email":"sefalk@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":482744,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70047694,"text":"ds784 - 2013 - Velocity, water-quality, and bathymetric surveys of the Grays Landing and Maxwell Navigation Pools, and Selected Tributaries to the Monongahela River, Pennsylvania, 2010–11","interactions":[],"lastModifiedDate":"2017-06-27T11:12:50","indexId":"ds784","displayToPublicDate":"2013-08-19T14:39:00","publicationYear":"2013","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":"784","title":"Velocity, water-quality, and bathymetric surveys of the Grays Landing and Maxwell Navigation Pools, and Selected Tributaries to the Monongahela River, Pennsylvania, 2010–11","docAbstract":"The U.S. Geological Survey (USGS) conducted velocity, water-quality, and bathymetric surveys from spring 2010 to summer 2011 in the Grays Landing and Maxwell navigation pools of the Monongahela River, Pennsylvania, and selected tributaries in response to elevated levels of total dissolved solids (TDS) recorded in early September 2009. Velocity data were collected using an Acoustic Doppler Current Profiler. Water-quality surveys included the in-situ collection of specific-conductance, water-temperature, and turbidity data using a water-quality sonde. Additionally, discrete water samples were collected and analyzed for TDS, chloride, and sulfate. Bathymetric data were collected using an echo sounder, and the shoreline was delineated using a laser range finder and electronic compass. The data were geo-referenced using a differential global positioning system and navigational software. Horizontal (x, y) coordinates were referenced to the North American Datum of 1983. Depth (z) elevations were referenced to the North American Vertical Datum of 1988. The data are provided in electronic format (appendix 1) and may be downloaded and can be used in a geographic information system for cartographic display and data analysis.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds784","collaboration":"Prepared in cooperation with the Pennsylvania Department of Environmental Protection","usgsCitation":"Hoffman, S.A., Roland, M.A., Schalk, L., and Fulton, J.W., 2013, Velocity, water-quality, and bathymetric surveys of the Grays Landing and Maxwell Navigation Pools, and Selected Tributaries to the Monongahela River, Pennsylvania, 2010–11: U.S. Geological Survey Data Series 784, Report: vi, 12 p.; Downloads Directory, https://doi.org/10.3133/ds784.","productDescription":"Report: vi, 12 p.; Downloads Directory","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":276769,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds784.gif"},{"id":276766,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/784/"},{"id":276768,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/784/downloads"},{"id":276767,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/784/pdf/ds784.pdf"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Monongahela River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.1,39.7 ], [ -80.1,40.083 ], [ -79.75,40.083 ], [ -79.75,39.7 ], [ -80.1,39.7 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52136dfbe4b0b08f446198a3","contributors":{"authors":[{"text":"Hoffman, Scott A. shoffman@usgs.gov","contributorId":2634,"corporation":false,"usgs":true,"family":"Hoffman","given":"Scott","email":"shoffman@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482734,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roland, Mark A. 0000-0002-0268-6507 mroland@usgs.gov","orcid":"https://orcid.org/0000-0002-0268-6507","contributorId":2116,"corporation":false,"usgs":true,"family":"Roland","given":"Mark","email":"mroland@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schalk, Luther 0000-0003-3957-1794 lschalk@usgs.gov","orcid":"https://orcid.org/0000-0003-3957-1794","contributorId":4366,"corporation":false,"usgs":true,"family":"Schalk","given":"Luther","email":"lschalk@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482735,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fulton, John W. 0000-0002-5335-0720 jwfulton@usgs.gov","orcid":"https://orcid.org/0000-0002-5335-0720","contributorId":2298,"corporation":false,"usgs":true,"family":"Fulton","given":"John","email":"jwfulton@usgs.gov","middleInitial":"W.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482733,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70047674,"text":"ofr20131157 - 2013 - Land change in the Central Corn Belt Plains Ecoregion and hydrologic consequences in developed areas: 1939-2000","interactions":[],"lastModifiedDate":"2013-10-30T13:22:12","indexId":"ofr20131157","displayToPublicDate":"2013-08-19T09:51:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1157","title":"Land change in the Central Corn Belt Plains Ecoregion and hydrologic consequences in developed areas: 1939-2000","docAbstract":"This report emphasizes the importance of a multi-disciplinary understanding of how land use and land cover can affect regional hydrology by collaboratively investigating how increases in developed land area may affect stream discharge by evaluating land-cover change from 1939 to 2000, urban housing density data from 1940 to 2010, and changes in annual peak streamflow from water years 1945 to 2009. The results and methods crosscut two mission areas of the U.S. Geological Survey (Climate and Land Use, Water) and can be used to better assess developed land change and hydrologic consequences, which can be used to better assess future management and mitigation strategies.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131157","usgsCitation":"Karstensen, K., Shaver, D., Alexander, R., Over, T., and Soong, D.T., 2013, Land change in the Central Corn Belt Plains Ecoregion and hydrologic consequences in developed areas: 1939-2000: U.S. Geological Survey Open-File Report 2013-1157, vi, 21 p., https://doi.org/10.3133/ofr20131157.","productDescription":"vi, 21 p.","numberOfPages":"32","onlineOnly":"Y","temporalStart":"1939-01-01","temporalEnd":"2000-12-31","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":276739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131157.png"},{"id":276737,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1157/"},{"id":276738,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1157/pdf/ofr2013-1157.pdf"}],"country":"United States","state":"Illinois;Indiana;Wisconsin","otherGeospatial":"Central Corn Belt Plains Ecoregion","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.0,38.0 ], [ -92.0,43.0 ], [ -86.0,43.0 ], [ -86.0,38.0 ], [ -92.0,38.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52136df9e4b0b08f44619893","contributors":{"authors":[{"text":"Karstensen, Krista","contributorId":97758,"corporation":false,"usgs":true,"family":"Karstensen","given":"Krista","affiliations":[],"preferred":false,"id":482693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shaver, David","contributorId":24265,"corporation":false,"usgs":true,"family":"Shaver","given":"David","affiliations":[],"preferred":false,"id":482691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alexander, Randal","contributorId":14285,"corporation":false,"usgs":true,"family":"Alexander","given":"Randal","email":"","affiliations":[],"preferred":false,"id":482690,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Over, Thomas","contributorId":31294,"corporation":false,"usgs":true,"family":"Over","given":"Thomas","affiliations":[],"preferred":false,"id":482692,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Soong, David T. dsoong@usgs.gov","contributorId":2230,"corporation":false,"usgs":true,"family":"Soong","given":"David","email":"dsoong@usgs.gov","middleInitial":"T.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":482689,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70047671,"text":"70047671 - 2013 - Surface electric fields for North America during historical geomagnetic storms","interactions":[],"lastModifiedDate":"2013-09-09T11:17:44","indexId":"70047671","displayToPublicDate":"2013-08-19T09:08:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3456,"text":"Space Weather","active":true,"publicationSubtype":{"id":10}},"title":"Surface electric fields for North America during historical geomagnetic storms","docAbstract":"To better understand the impact of geomagnetic disturbances on the electric grid, we recreate surface electric fields from two historical geomagnetic storms—the 1989 “Quebec” storm and the 2003 “Halloween” storms. Using the Spherical Elementary Current Systems method, we interpolate sparsely distributed magnetometer data across North America. We find good agreement between the measured and interpolated data, with larger RMS deviations at higher latitudes corresponding to larger magnetic field variations. The interpolated magnetic field data are combined with surface impedances for 25 unique physiographic regions from the United States Geological Survey and literature to estimate the horizontal, orthogonal surface electric fields in 1 min time steps. The induced horizontal electric field strongly depends on the local surface impedance, resulting in surprisingly strong electric field amplitudes along the Atlantic and Gulf Coast. The relative peak electric field amplitude of each physiographic region, normalized to the value in the Interior Plains region, varies by a factor of 2 for different input magnetic field time series. The order of peak electric field amplitudes (largest to smallest), however, does not depend much on the input. These results suggest that regions at lower magnetic latitudes with high ground resistivities are also at risk from the effect of geomagnetically induced currents. The historical electric field time series are useful for estimating the flow of the induced currents through long transmission lines to study power flow and grid stability during geomagnetic disturbances.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Space Weather","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/swe.20073","usgsCitation":"Wei, L.H., Homeier, N., and Gannon, J.L., 2013, Surface electric fields for North America during historical geomagnetic storms: Space Weather, v. 11, no. 8, p. 451-462, https://doi.org/10.1002/swe.20073.","startPage":"451","endPage":"462","ipdsId":"IP-050044","costCenters":[{"id":415,"text":"National Earthquake Information Center","active":false,"usgs":true}],"links":[{"id":473595,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/swe.20073","text":"Publisher Index Page"},{"id":276730,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276728,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/swe.20073"}],"country":"United States","volume":"11","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52136dfae4b0b08f4461989b","contributors":{"authors":[{"text":"Wei, Lisa H.","contributorId":29726,"corporation":false,"usgs":true,"family":"Wei","given":"Lisa","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":482680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Homeier, Nichole","contributorId":40881,"corporation":false,"usgs":true,"family":"Homeier","given":"Nichole","email":"","affiliations":[],"preferred":false,"id":482681,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gannon, Jennifer L.","contributorId":40882,"corporation":false,"usgs":true,"family":"Gannon","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":482682,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70047660,"text":"70047660 - 2013 - No trespassing: using a biofence to manipulate wolf movements","interactions":[],"lastModifiedDate":"2013-08-16T13:30:01","indexId":"70047660","displayToPublicDate":"2013-08-16T13:27:26","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"title":"No trespassing: using a biofence to manipulate wolf movements","docAbstract":"Context: Conserving large carnivores can be challenging because of conflicts with human land use and competition with humans for resources. Predation on domestic stock can have negative economic impacts particularly for owners of small herds, and tools for minimising carnivore depredation of livestock are needed. Canids use scent marking to establish territories and avoid intraspecific conflict. Exploiting scent-marking behaviour may provide a means for manipulating canid movements. Aims: We hypothesised that human-deployed scent marks (i.e. ‘biofence’) could be used to manipulate the movements of grey wolves (Canis lupus) in Idaho, USA. Methods: We deployed 65 km of biofence within three wolf-pack territories during summer 2010 and 2011 and used location data from satellite-collared wolves and sign surveys to assess the effectiveness of biofencing. Key results: Location data provided by satellite-collared wolves and sign surveys in 2010 showed little to no trespass of the biofence, even though the excluded areas were used by the packs in previous summers. We also opportunistically deployed a biofence in between a rendezvous site of a resident pack and a nearby sheep grazing allotment; the pack was not implicated in any depredations in summer 2010, even though they had killed sheep every year since 2006. Location data provided by satellite-collared wolves in summer 2011 showed that wolves did trespass biofences. Conclusions: Biofencing effectively manipulated the movements of wolves in the first year of our study, but not the second. Implications: Our work suggests that biofencing may be most limited by the apparent necessity to maintain a continuous presence once the biofence is established. The inherent labour and costs associated with such efforts may limit the usefulness of biofencing. Our work can be improved on through further testing that maintains biofencing over a longer timeframe (>3 months), samples several animals per treatment pack, and uses a treatment and control design.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Wildlife Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WR12176","usgsCitation":"Ausband, D., Mitchell, M.S., Bassing, S.B., and White, C., 2013, No trespassing: using a biofence to manipulate wolf movements: Wildlife Research, v. 40, no. 3, p. 207-216, https://doi.org/10.1071/WR12176.","productDescription":"10 p.","startPage":"207","endPage":"216","ipdsId":"IP-048940","costCenters":[{"id":399,"text":"Montana Cooperative Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":276695,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276694,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1071/WR12176"}],"volume":"40","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"520f3bebe4b0fc50304bc48c","contributors":{"authors":[{"text":"Ausband, David E.","contributorId":51441,"corporation":false,"usgs":true,"family":"Ausband","given":"David E.","affiliations":[],"preferred":false,"id":482662,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitchell, Michael S. 0000-0002-0773-6905 mmitchel@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-6905","contributorId":3716,"corporation":false,"usgs":true,"family":"Mitchell","given":"Michael","email":"mmitchel@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":482661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bassing, Sarah B.","contributorId":81006,"corporation":false,"usgs":true,"family":"Bassing","given":"Sarah","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":482663,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"White, Craig","contributorId":94203,"corporation":false,"usgs":true,"family":"White","given":"Craig","email":"","affiliations":[],"preferred":false,"id":482664,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70047647,"text":"ofr20131229 - 2013 - Review of a model to assess stranding of juvenile salmon by ship wakes along the Lower Columbia River, Oregon and Washington","interactions":[],"lastModifiedDate":"2013-08-16T11:13:18","indexId":"ofr20131229","displayToPublicDate":"2013-08-16T11:05:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1229","title":"Review of a model to assess stranding of juvenile salmon by ship wakes along the Lower Columbia River, Oregon and Washington","docAbstract":"Long period wake waves from deep draft vessels have been shown to strand small fish, particularly juvenile Chinook salmon Oncorhynchus tschawytcha, in the lower Columbia River (LCR). The U.S. Army Corps of Engineers is responsible for maintaining the shipping channel in the LCR and recently conducted dredging operations to deepen the shipping channel from an authorized depth of 40 feet(ft) to an authorized depth of 43 ft (in areas where rapid shoaling was expected, dredging operations were used to increase the channel depth to 48 ft). A model was developed to estimate stranding probabilities for juvenile salmon under the 40- and 43-ft channel scenarios, to determine if channel deepening was going to affect wake stranding (Assessment of potential stranding of juvenile salmon by ship wakes along the Lower Columbia River under scenarios of ship traffic and channel depth: Report prepared for the Portland District U.S. Army Corps of Engineers, Portland, Oregon). The U.S. Army Corps of Engineers funded the U.S. Geological Survey to review this model. A total of 30 review questions were provided to guide the review process, and these questions are addressed in this report. In general, we determined that the analyses by Pearson (2011) were appropriate given the data available. We did identify two areas where additional information could have been provided: (1) a more thorough description of model diagnostics and model selection would have been useful for the reader to better understand the model framework; and (2) model uncertainty should have been explicitly described and reported in the document. Stranding probability estimates between the 40- and 43-ft channel depths were minimally different under most of the scenarios that were examined by Pearson (2011), and a discussion of the effects of uncertainty given these minimal differences would have been useful. Ultimately, however, a stochastic (or simulation) model would provide the best opportunity to illustrate uncertainty within a given set of model predictions, but such an approach would require a substantial amount of additional data collection. Several review questions focused on the accuracy and precision of the model estimates, but we were unable to address these questions because of the limited data that currently exists regarding wake stranding in the LCR. Additional field studies will be required to validate findings from Pearson (2011), if concerns regarding accuracy and precision remain a priority. Although the Pearson (2011) model provided a useful examination of stranding under pre-construction and post-construction conditions, future research will be required to better understand the effects of wake stranding on juvenile salmonids throughout the entire LCR. If additional information on wake stranding is desired in the future, the following topics may be of interest: (1) spatial examination of wake stranding throughout the entire LCR; (2) additional evaluation of juvenile salmonid behavior and population dynamics; (3) assessing and integrating predicted changes in ship development; and (4) assessing and integrating predicted changes in climate on environmental factors known to cause stranding.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131229","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Kock, T.J., Plumb, J.M., and Adams, N.S., 2013, Review of a model to assess stranding of juvenile salmon by ship wakes along the Lower Columbia River, Oregon and Washington: U.S. Geological Survey Open-File Report 2013-1229, iv, 20 p., https://doi.org/10.3133/ofr20131229.","productDescription":"iv, 20 p.","numberOfPages":"28","onlineOnly":"Y","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":276680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131229.jpg"},{"id":276678,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1229/"},{"id":276679,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1229/pdf/ofr20131229.pdf"}],"country":"United States","state":"Oregon;Washington","otherGeospatial":"Columbia River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.1739,45.5391 ], [ -124.1739,48.9995 ], [ -117.6306,48.9995 ], [ -117.6306,45.5391 ], [ -124.1739,45.5391 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"520f3bece4b0fc50304bc494","contributors":{"authors":[{"text":"Kock, Tobias J. 0000-0001-8976-0230 tkock@usgs.gov","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":3038,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","email":"tkock@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":482625,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John M. 0000-0003-4255-1612 jplumb@usgs.gov","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":3569,"corporation":false,"usgs":true,"family":"Plumb","given":"John","email":"jplumb@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":482627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":482626,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70047635,"text":"fs20133040 - 2013 - The 3D Elevation Program: summary for Rhode Island","interactions":[],"lastModifiedDate":"2016-08-17T16:14:28","indexId":"fs20133040","displayToPublicDate":"2013-08-15T14:09:00","publicationYear":"2013","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":"2013-3040","title":"The 3D Elevation Program: summary for Rhode Island","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Rhode Island, elevation data are critical for flood risk management, natural resources conservation, coastal zone management, sea level rise and subsidence, agriculture and precision farming, and other business uses. Today, high-quality light detection and ranging (lidar) data are the sources for creating elevation models and other elevation datasets. Federal, State, and local agencies work in partnership to (1) replace data, on a national basis, that are (on average) 30 years old and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The new 3D Elevation Program (3DEP) initiative (Snyder, 2012a,b), managed by the U.S. Geological Survey (USGS), responds to the growing need for high-quality topographic data and a wide range of other three-dimensional representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133040","usgsCitation":"Carswell, W., 2013, The 3D Elevation Program: summary for Rhode Island: U.S. Geological Survey Fact Sheet 2013-3040, 2 p., https://doi.org/10.3133/fs20133040.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":423,"text":"National Geospatial 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