{"pageNumber":"47","pageRowStart":"1150","pageSize":"25","recordCount":36988,"records":[{"id":70185117,"text":"ofr20171031 - 2017 - Correction of elevation offsets in multiple co-located lidar datasets","interactions":[],"lastModifiedDate":"2017-04-07T14:20:13","indexId":"ofr20171031","displayToPublicDate":"2017-04-07T14:15:00","publicationYear":"2017","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":"2017-1031","title":"Correction of elevation offsets in multiple co-located lidar datasets","docAbstract":"<h1>Introduction</h1><p>Topographic elevation data collected with airborne light detection and ranging (lidar) can be used to analyze short- and long-term changes to beach and dune systems. Analysis of multiple lidar datasets at Dauphin Island, Alabama, revealed systematic, island-wide elevation differences on the order of 10s of centimeters (cm) that were not attributable to real-world change and, therefore, were likely to represent systematic sampling offsets. These offsets vary between the datasets, but appear spatially consistent within a given survey. This report describes a method that was developed to identify and correct offsets between lidar datasets collected over the same site at different times so that true elevation changes over time, associated with sediment accumulation or erosion, can be analyzed.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171031","usgsCitation":"Thompson, D.M., Dalyander, P.S., Long, J.W., and Plant, N.G., 2017, Correction of elevation offsets in multiple co-located lidar datasets: U.S. Geological Survey Open-File Report 2017–1031, 10 p., https://doi.org/10.3133/ofr20171031.  ","productDescription":"iv, 10 p.","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-079032","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":339143,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1031/ofr20171031.pdf","text":"Report","size":"546 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1031"},{"id":339142,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1031/coverthb.jpg"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.21369171142578,\n              30.217541849095714\n            ],\n            [\n              -88.06949615478516,\n              30.217541849095714\n            ],\n            [\n              -88.06949615478516,\n              30.28575280701959\n            ],\n            [\n              -88.21369171142578,\n              30.28575280701959\n            ],\n            [\n              -88.21369171142578,\n              30.217541849095714\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>St. Petersburg Coastal and Marine Science Center<br> U.S. Geological Survey<br> 600 4th Street South<br> St. Petersburg, FL 33701<br> <a href=\"http://coastal.er.usgs.gov/\" data-mce-href=\"http://coastal.er.usgs.gov/\">http://coastal.er.usgs.gov/</a></p>","tableOfContents":"<ul><li>Introduction</li><li>Background</li><li>Method</li><li>Discussion</li><li>Summary&nbsp;</li><li>References Cited&nbsp;</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2017-04-07","noUsgsAuthors":false,"publicationDate":"2017-04-07","publicationStatus":"PW","scienceBaseUri":"58e8a53ee4b09da6799d6397","contributors":{"authors":[{"text":"Thompson, David M. 0000-0002-7103-5740 dthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-7103-5740","contributorId":3502,"corporation":false,"usgs":true,"family":"Thompson","given":"David","email":"dthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":684414,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dalyander, P. Soupy 0000-0001-9583-0872 sdalyander@usgs.gov","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":149892,"corporation":false,"usgs":true,"family":"Dalyander","given":"P. Soupy","email":"sdalyander@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":684415,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, Joseph W. 0000-0003-2912-1992 jwlong@usgs.gov","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":3303,"corporation":false,"usgs":true,"family":"Long","given":"Joseph","email":"jwlong@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":684416,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":684417,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70184446,"text":"ofr20171024 - 2017 - Nearshore sediment thickness, Fire Island, New York","interactions":[],"lastModifiedDate":"2023-10-30T18:34:37.420969","indexId":"ofr20171024","displayToPublicDate":"2017-04-03T14:30:00","publicationYear":"2017","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":"2017-1024","title":"Nearshore sediment thickness, Fire Island, New York","docAbstract":"<p>Investigations of coastal change at Fire Island, New York (N.Y.), sought to characterize sediment budgets and determine geologic framework controls on coastal processes. Nearshore sediment thickness is critical for assessing coastal system sediment availability, but it is largely unquantified due to the difficulty of conducting geological or geophysical surveys across the nearshore. This study used an amphibious vessel to acquire chirp subbottom profiles. These profiles were used to characterize nearshore geology and provide an assessment of nearshore sediment volume. Two resulting sediment-thickness maps are provided: total Holocene sediment thickness and the thickness of the active shoreface. The Holocene sediment section represents deposition above the maximum flooding surface that is related to the most recent marine transgression. The active shoreface section is the uppermost Holocene sediment, which is interpreted to represent the portion of the shoreface thought to contribute to present and future coastal behavior. The sediment distribution patterns correspond to previously defined zones of erosion, accretion, and stability along the island, demonstrating the importance of sediment availability in the coastal response to storms and seasonal variability. The eastern zone has a thin nearshore sediment thickness, except for an ebb-tidal deposit at the wilderness breach caused by Hurricane Sandy. Thicker sediment is found along a central zone that includes shoreface-attached sand ridges, which is consistent with a stable or accretional coastline in this area. The thickest overall Holocene section is found in the western zone of the study, where a thicker lower section of Holocene sediment appears related to the westward migration of Fire Island Inlet over several hundred years. </p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171024","usgsCitation":"Locker, S.D., Miselis, J.L., Buster, N.A., Hapke, C.J., Wadman, H.M., McNinch, J.E., Forde, A.S., and Stalk, C.A., 2017, Nearshore sediment thickness, Fire Island, New York: U.S. Geological Survey Open-File Report 2017–1024, 21 p., https://doi.org/10.3133/ofr20171024.","productDescription":"vii, 21 p.","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-079609","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":338703,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1024/ofr20171024.pdf","text":"Report","size":"6.61 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1024"},{"id":338702,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1024/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -72.87986755371094,\n              40.77534183237267\n            ],\n            [\n              -72.87986755371094,\n              40.77534183237267\n            ],\n            [\n              -72.87986755371094,\n              40.77534183237267\n            ],\n            [\n              -72.87986755371094,\n              40.77534183237267\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -72.87574768066406,\n              40.77534183237267\n            ],\n            [\n              -73.27743530273438,\n              40.65563874006118\n            ],\n            [\n              -73.24447631835938,\n              40.59674926086908\n            ],\n            [\n              -72.84210205078125,\n              40.7202010588415\n            ],\n            [\n              -72.87574768066406,\n              40.77534183237267\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, St. Petersburg Coastal and Marine Science Center<br> U.S. Geological Survey<br> 600 4th Street South<br> St. Petersburg, FL 33701<br> <a href=\"https://coastal.er.usgs.gov/\" data-mce-href=\"https://coastal.er.usgs.gov/\">https://coastal.er.usgs.gov/</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Setting</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Summary</li><li>References</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2017-04-03","noUsgsAuthors":false,"publicationDate":"2017-04-03","publicationStatus":"PW","scienceBaseUri":"58e35f7ce4b09da67997ec9d","contributors":{"authors":[{"text":"Locker, Stanley D.  slocker@usgs.gov","contributorId":187736,"corporation":false,"usgs":true,"family":"Locker","given":"Stanley D. ","email":"slocker@usgs.gov","affiliations":[],"preferred":false,"id":681526,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":681527,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buster, Noreen A. 0000-0001-5069-9284 nbuster@usgs.gov","orcid":"https://orcid.org/0000-0001-5069-9284","contributorId":3750,"corporation":false,"usgs":true,"family":"Buster","given":"Noreen","email":"nbuster@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":681528,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":681529,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wadman, Heidi M.","contributorId":187737,"corporation":false,"usgs":false,"family":"Wadman","given":"Heidi","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":681530,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McNinch, Jesse E.","contributorId":187738,"corporation":false,"usgs":false,"family":"McNinch","given":"Jesse","email":"","middleInitial":"E.","affiliations":[{"id":34410,"text":"USACE-Coastal Hydraulic Lab, Duck, NC","active":true,"usgs":false}],"preferred":false,"id":681531,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Forde, Arnell S. 0000-0002-5581-2255 aforde@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-2255","contributorId":376,"corporation":false,"usgs":true,"family":"Forde","given":"Arnell","email":"aforde@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":681532,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stalk, Chelsea A.","contributorId":181865,"corporation":false,"usgs":false,"family":"Stalk","given":"Chelsea A.","affiliations":[],"preferred":false,"id":681533,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70179858,"text":"ofr20171007 - 2017 - Semiautomatic approaches to account for 3-D distortion of the electric field from local, near-surface structures in 3-D resistivity inversions of 3-D regional magnetotelluric data","interactions":[],"lastModifiedDate":"2017-03-31T10:53:51","indexId":"ofr20171007","displayToPublicDate":"2017-03-31T10:15:00","publicationYear":"2017","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":"2017-1007","title":"Semiautomatic approaches to account for 3-D distortion of the electric field from local, near-surface structures in 3-D resistivity inversions of 3-D regional magnetotelluric data","docAbstract":"<p>This report summarizes the results of three-dimensional (3-D) resistivity inversion simulations that were performed to account for local 3-D distortion of the electric field in the presence of 3-D regional structure, without any a priori information on the actual 3-D distribution of the known subsurface geology. The methodology used a 3-D geologic model to create a 3-D resistivity forward (“known”) model that depicted the subsurface resistivity structure expected for the input geologic configuration. The calculated magnetotelluric response of the modeled resistivity structure was assumed to represent observed magnetotelluric data and was subsequently used as input into a 3-D resistivity inverse model that used an iterative 3-D algorithm to estimate 3-D distortions without any a priori geologic information. A publicly available inversion code, WSINV3DMT, was used for all of the simulated inversions, initially using the default parameters, and subsequently using adjusted inversion parameters. A semiautomatic approach of accounting for the static shift using various selections of the highest frequencies and initial models was also tested. The resulting 3-D resistivity inversion simulation was compared to the “known” model and the results evaluated. The inversion approach that produced the lowest misfit to the various local 3-D distortions was an inversion that employed an initial model volume resistivity that was nearest to the maximum resistivities in the near-surface layer.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171007","usgsCitation":"Rodriguez, B.D., 2017, Semiautomatic approaches to account for 3-D distortion of the electric field from local, near-surface structures in 3-D resistivity inversions of 3-D regional magnetotelluric data: U.S. Geological Survey Open-File Report 2017–1007, 25 p., https://doi.org/10.3133/ofr20171007.","productDescription":"iii, 25 p.","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-068212","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":338862,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1007/coverthb.jpg"},{"id":338863,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1007/ofr20171007.pdf","text":"Report","size":"20.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1007"}],"contact":"<p>Director,&nbsp;Crustal Geophysics and Geochemistry Science Center<br>U.S. Geological Survey<br>Box 25046, MS 964<br>Denver, CO 80225</p><p><a href=\"http://crustal.usgs.gov/\" target=\"_blank\" data-mce-href=\"http://crustal.usgs.gov/\">http://crustal.usgs.gov/</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Electrical Properties of Rock</li><li>Magnetotelluric Method</li><li>3-D Resistivity Model Build</li><li>3-D Resistivity Inversion Approaches</li><li>3-D Resistivity Inversion Results</li><li>Conclusions</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2017-03-31","noUsgsAuthors":false,"publicationDate":"2017-03-31","publicationStatus":"PW","scienceBaseUri":"58df6abde4b02ff32c6aea23","contributors":{"authors":[{"text":"Rodriguez, Brian D. 0000-0002-2263-611X brod@usgs.gov","orcid":"https://orcid.org/0000-0002-2263-611X","contributorId":836,"corporation":false,"usgs":true,"family":"Rodriguez","given":"Brian","email":"brod@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":658967,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70185601,"text":"ofr20171034 - 2017 - Landsat and agriculture—Case studies on the uses and benefits of Landsat imagery in agricultural monitoring and production","interactions":[],"lastModifiedDate":"2017-03-30T12:15:26","indexId":"ofr20171034","displayToPublicDate":"2017-03-29T17:45:00","publicationYear":"2017","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":"2017-1034","title":"Landsat and agriculture—Case studies on the uses and benefits of Landsat imagery in agricultural monitoring and production","docAbstract":"<h1>Executive Summary</h1><p>The use of Landsat satellite imagery for global agricultural monitoring began almost immediately after the launch of Landsat 1 in 1972, making agricultural monitoring one of the longest-standing operational applications for the Landsat program. More recently, Landsat imagery has been used in domestic agricultural applications as an input for field-level production management. The enactment of the U.S. Geological Survey’s free and open data policy in 2008 and the launch of Landsat 8 in 2013 have both influenced agricultural applications. This report presents two primary sets of case studies on the applications and benefits of Landsat imagery use in agriculture. The first set examines several operational applications within the U.S. Department of Agriculture (USDA) and the second focuses on private sector applications for agronomic management. &nbsp;</p><p>Information on the USDA applications is provided in the U.S. Department of Agriculture Uses of Landsat Imagery for Global and Domestic Agricultural Monitoring section of the report in the following subsections:</p><ul><li><i>Estimating Crop Production</i>.—Provides an overview of how Landsat satellite imagery is used to estimate crop production, including the spectral bands most frequently utilized in this application.</li><li><i>Monitoring Consumptive Water Use</i>.—Highlights the role of Landsat imagery in monitoring consumptive water use for agricultural production. Globally, a significant amount of agricultural production relies on irrigation, so monitoring water resources is a critical component of agricultural monitoring. <br></li><li><i>National Agricultural Statistics Service</i>—Cropland Data Layer.—Highlights the use of Landsat imagery in developing the annual Cropland Data Layer, a crop-specific land cover classification product that provides information on more than 100 crop categories grown in the United States.&nbsp;</li><li><i>Foreign Agricultural Service</i>—Global Agricultural Monitoring.—Highlights Landsat’s role in monitoring global agricultural production. The USDA has been using Landsat imagery to monitor global agricultural production since the launch of Landsat 1 in 1972. Landsat imagery provides objective, global input for a number of USDA agricultural programs and plays an important role in economic and food security forecasting.</li><li><i>U.S. Department of Agriculture</i>—Satellite Imagery Archive.—Highlights a number of the experiences of the USDA in acquiring, sharing, and managing moderate resolution imagery to support the diversity of USDA operational programs.&nbsp;</li></ul><p>Private sector applications using Landsat imagery for agricultural management are discussed in the Landsat Imagery Use and Benefits in Field-Level Agricultural Production Management section of the report in the following subsections:</p><ul><li><i>Field-Level Management</i>.—Provides an introduction to what field-level production management is and how it can be applied to agricultural management. This section explores the concept of zone mapping and how Landsat imagery can be used to identify different conditions within a field. The section also provides a case study of zone-mapping software, developed by GK Technology, Inc., that is used by numerous agricultural consultants.</li><li><i>Putting Zone Maps to Work</i>.—Highlights several case studies of private agricultural consultants who have been using Landsat imagery to develop zone maps for farmers. Landsat imagery is helping consultants and farmers optimize agricultural inputs, including fertilizer and seed, which leads to higher yield and economic return for the farmer.</li><li><i>Increasing Yield</i>.—Highlights the primary benefit of zone mapping using Landsat imagery. Using 5-year market average prices for a number of commodities, this section provides examples of how yield increases translate into higher returns for farmers.</li></ul>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171034","usgsCitation":"Leslie, C.R., Serbina, L.O., and Miller, H.M., 2017, Landsat and agriculture—Case studies on the uses and benefits of Landsat imagery in agricultural monitoring and production: U.S. Geological Survey Open-File Report 2017–1034, 27 p., https://doi.org/10.3133/ofr20171034. ","productDescription":"vi, 27 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-074917","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":338573,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1034/coverthb.jpg"},{"id":338574,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1034/ofr20171034.pdf","text":"Report","size":"6.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1034"}],"contact":"<p>Director, Fort Collins Science Center&nbsp;<br>U.S. Geological Survey<br>2150 Centre Ave., Bldg. C<br>Fort Collins, CO 80526-8118</p><p><a href=\"http://www.fort.usgs.gov/\" data-mce-href=\"http://www.fort.usgs.gov/\">http://www.fort.usgs.gov/</a></p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>U.S. Department of Agriculture Uses of Landsat Imagery for Global and Domestic Agricultural Monitoring</li><li>Landsat Imagery Use and Benefits in Field-Level Agricultural Production Management</li><li>Conclusion</li><li>References</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2017-03-29","noUsgsAuthors":false,"publicationDate":"2017-03-29","publicationStatus":"PW","scienceBaseUri":"58dcc7cfe4b02ff32c68565b","contributors":{"authors":[{"text":"Leslie, Colin R.","contributorId":167359,"corporation":false,"usgs":false,"family":"Leslie","given":"Colin","email":"","middleInitial":"R.","affiliations":[{"id":24700,"text":"Student contractor","active":true,"usgs":false}],"preferred":false,"id":686079,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Serbina, Larisa O.","contributorId":189807,"corporation":false,"usgs":false,"family":"Serbina","given":"Larisa O.","affiliations":[],"preferred":false,"id":686080,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Holly M. 0000-0003-0914-7570 millerh@usgs.gov","orcid":"https://orcid.org/0000-0003-0914-7570","contributorId":29544,"corporation":false,"usgs":true,"family":"Miller","given":"Holly","email":"millerh@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":false,"id":686078,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70181024,"text":"ofr20171016 - 2017 - Numerical modeling of the effects of Hurricane Sandy and potential future hurricanes on spatial patterns of salt marsh morphology in Jamaica Bay, New York City","interactions":[],"lastModifiedDate":"2017-03-29T15:19:26","indexId":"ofr20171016","displayToPublicDate":"2017-03-29T00:00:00","publicationYear":"2017","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":"2017-1016","title":"Numerical modeling of the effects of Hurricane Sandy and potential future hurricanes on spatial patterns of salt marsh morphology in Jamaica Bay, New York City","docAbstract":"<p>The salt marshes of Jamaica Bay, managed by the New York City Department of Parks &amp; Recreation and the Gateway National Recreation Area of the National Park Service, serve as a recreational outlet for New York City residents, mitigate flooding, and provide habitat for critical wildlife species. Hurricanes and extra-tropical storms have been recognized as one of the critical drivers of coastal wetland morphology due to their effects on hydrodynamics and sediment transport, deposition, and erosion processes. However, the magnitude and mechanisms of hurricane effects on sediment dynamics and associated coastal wetland morphology in the northeastern United States are poorly understood. In this study, the depth-averaged version of the Delft3D modeling suite, integrated with field measurements, was utilized to examine the effects of Hurricane Sandy and future potential hurricanes on salt marsh morphology in Jamaica Bay, New York City. Hurricane Sandy-induced wind, waves, storm surge, water circulation, sediment transport, deposition, and erosion were simulated by using the modeling system in which vegetation effects on flow resistance, surge reduction, wave attenuation, and sedimentation were also incorporated. Observed marsh elevation change and accretion from a rod surface elevation table and feldspar marker horizons and cesium-137- and lead-210-derived long-term accretion rates were used to calibrate and validate the wind-waves-surge-sediment transport-morphology coupled model.</p><p>The model results (storm surge, waves, and marsh deposition and erosion) agreed well with field measurements. The validated modeling system was then used to detect salt marsh morphological change due to Hurricane Sandy across the entire Jamaica Bay over the short-term (for example, 4 days and 1 year) and long-term (for example, 5 and 10 years). Because Hurricanes Sandy (2012) and Irene (2011) were two large and destructive tropical cyclones which hit the northeast coast, the validated coupled model was run to predict the effects of Sandy-like and Irene-like hurricanes with different storm tracks and wind intensities on wetland morphology in Jamaica Bay. Model results indicate that, in Jamaica Bay salt marshes, the morphological changes (greater than 5 millimeters [mm] determined by the long-term marsh accretion rate) caused by Hurricane Sandy were complex and spatially heterogeneous. Most of the erosion (5–40 mm) and deposition (5–30 mm) were mainly characterized by fine sand for channels and bay bottoms and by mud for marsh areas. Hurricane Sandy-generated deposition and erosion were generated locally. The storm-induced net sediment input through Rockaway Inlet was only about 1 percent of the total amount of the sediment reworked by the hurricane. Salt marshes inside the western part of the bay showed erosion overall while marshes inside the eastern part showed deposition from Hurricane Sandy. Model results indicated that most of the marshes could recover from Hurricane Sandy-induced erosion after 1 year and demonstrated continued marsh accretion after the hurricane over the course of long simulation periods although the effect (accretion) was diminished. Local waves and currents generated by Hurricane Sandy appeared to play a critical role in sediment transport and associated wetland morphological change in Jamaica Bay. Hypothetical hurricanes, depending on their track and intensity, cause variable responses in spatial patterns of sediment deposition and erosion compared to simulations without the hurricane. In general, hurricanes passing west of the Jamaica Bay estuary appear to be more destructive to the salt marshes than those passing the east. Consequently, marshes inside the western part of the bay were likely to be more vulnerable to hurricanes than marshes inside the eastern part of the bay.</p><p>&nbsp;</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171016","usgsCitation":"Wang, H., Chen, Q., Hu, K., Snedden, G.A., Hartig, E.K., Couvillion, B.R., Johnson, C.L., and Orton, P.M., 2017, Numerical modeling of the effects of Hurricane Sandy and potential future hurricanes on spatial patterns of salt marsh morphology in Jamaica Bay, New York City: U.S. Geological Survey Open-File Report 2017–1016, 43 p., https://doi.org/10.3133/ofr20171016.","productDescription":"vii, 43 p.","numberOfPages":"56","onlineOnly":"Y","ipdsId":"IP-079827","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":338515,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1016/coverthb.jpg"},{"id":338516,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1016/ofr20171016.pdf","text":"Report","size":"30.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1016"}],"country":"United States","state":"New York","city":"New York City","otherGeospatial":"Jamaica Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.95687103271484,\n              40.539112438263516\n            ],\n            [\n              -73.72684478759766,\n              40.539112438263516\n            ],\n            [\n              -73.72684478759766,\n              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PSC"},"publishedDate":"2017-03-29","noUsgsAuthors":false,"publicationDate":"2017-03-29","publicationStatus":"PW","scienceBaseUri":"58dcc7d5e4b02ff32c68566f","contributors":{"authors":[{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":140432,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":663344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Q. 0000-0002-6540-8758","orcid":"https://orcid.org/0000-0002-6540-8758","contributorId":56532,"corporation":false,"usgs":false,"family":"Chen","given":"Q.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":true,"id":663345,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hu, Kelin","contributorId":177218,"corporation":false,"usgs":false,"family":"Hu","given":"Kelin","email":"","affiliations":[],"preferred":false,"id":663346,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Snedden, Gregg A. 0000-0001-7821-3709 sneddeng@usgs.gov","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":3894,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","email":"sneddeng@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":663347,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartig, Ellen K.","contributorId":179351,"corporation":false,"usgs":false,"family":"Hartig","given":"Ellen K.","affiliations":[],"preferred":false,"id":663348,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Couvillion, Brady R. 0000-0001-5323-1687 couvillionb@usgs.gov","orcid":"https://orcid.org/0000-0001-5323-1687","contributorId":3829,"corporation":false,"usgs":true,"family":"Couvillion","given":"Brady","email":"couvillionb@usgs.gov","middleInitial":"R.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":663350,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Cody L.","contributorId":179353,"corporation":false,"usgs":false,"family":"Johnson","given":"Cody","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":663351,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Orton, Philip M.","contributorId":179354,"corporation":false,"usgs":false,"family":"Orton","given":"Philip","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":663352,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70180979,"text":"ofr20171017 - 2017 - Geophysical logging and thermal imaging near the Hemphill Road TCE National Priorities List Superfund site near Gastonia, North Carolina","interactions":[],"lastModifiedDate":"2017-03-31T11:03:39","indexId":"ofr20171017","displayToPublicDate":"2017-03-27T16:30:00","publicationYear":"2017","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":"2017-1017","title":"Geophysical logging and thermal imaging near the Hemphill Road TCE National Priorities List Superfund site near Gastonia, North Carolina","docAbstract":"<p>Borehole geophysical logs and thermal imaging data were collected by the U.S. Geological Survey near the Hemphill Road TCE (trichloroethylene) National Priorities List Superfund site near Gastonia, North Carolina, during August 2014 through February 2015. In an effort to assist the U.S. Environmental Protection Agency in the development of a conceptual groundwater model for the assessment of current contaminant distribution and future migration of contaminants, surface geological mapping and borehole geophysical log and thermal imaging data collection, which included the delineation of more than 600 subsurface features (primarily fracture orientations), was completed in five open borehole wells and two private supply bedrock wells. In addition, areas of possible groundwater discharge within a nearby creek downgradient of the study site were determined based on temperature differences between the stream and bank seepage using thermal imagery.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171017","issn":"2331-1258","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency Region 4 Superfund Section","usgsCitation":"Antolino, D.J., and Chapman, M.J., 2017, Geophysical logging and thermal imaging near the Hemphill Road TCE National Priorities List Superfund site near Gastonia, North Carolina (ver. 1.1, March 2017): U.S. Geological Survey Open-File Report 2017–1017, 47 p., https://doi.org/10.3133/ofr20171017.","productDescription":"Report: v, 47 p.; Data Release","numberOfPages":"57","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079978","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":337458,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1017/coverthb2.jpg"},{"id":337459,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1017/ofr20171017.pdf","text":"Report","size":"19.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1017"},{"id":337460,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71R6NPM","text":"USGS data release ","description":"USGS data release","linkHelpText":"Geophysical logging and thermal imaging at the Hemphill Road TCE NPL Superfund site near Gastonia, North Carolina"},{"id":338827,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2017/1017/versionHist.txt","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"North Carolina","county":"Gaston County","city":"Gastonia","otherGeospatial":"Hemphill Road trichloroethylene National Priorities List Superfund site","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-81.4535,35.4201],[-81.2581,35.4132],[-81.0069,35.4038],[-80.9549,35.4006],[-80.9554,35.3925],[-80.9632,35.3901],[-80.9761,35.3828],[-80.9806,35.3823],[-80.9846,35.3822],[-80.9868,35.38],[-80.9844,35.3695],[-80.9776,35.3646],[-80.9742,35.3642],[-80.9697,35.3669],[-80.9669,35.3688],[-80.9647,35.3738],[-80.9625,35.3756],[-80.9597,35.3756],[-80.9563,35.3738],[-80.9505,35.3675],[-80.9432,35.3658],[-80.9296,35.3636],[-80.9268,35.3627],[-80.9285,35.3614],[-80.9374,35.3572],[-80.9442,35.3521],[-80.9537,35.3521],[-80.9593,35.3489],[-80.9656,35.3506],[-80.9706,35.3501],[-80.9818,35.3446],[-80.984,35.3373],[-80.9823,35.3341],[-80.9805,35.3287],[-80.9844,35.3237],[-80.9894,35.3205],[-80.9938,35.3132],[-80.9961,35.3113],[-81.0022,35.3045],[-81.0033,35.3017],[-81.0105,35.2944],[-81.0133,35.293],[-81.0143,35.2876],[-81.0152,35.2685],[-81.0139,35.2585],[-81.0082,35.2509],[-81.012,35.2349],[-81.0113,35.2309],[-81.0129,35.2231],[-81.0071,35.2109],[-81.0054,35.2055],[-81.0064,35.1973],[-81.0063,35.1923],[-81.0046,35.1864],[-81.0045,35.1814],[-81.0049,35.1728],[-81.0088,35.165],[-81.0076,35.1569],[-81.0109,35.1532],[-81.0176,35.1536],[-81.0238,35.1486],[-81.0448,35.1494],[-81.0682,35.1507],[-81.1814,35.1568],[-81.2141,35.1586],[-81.3277,35.1637],[-81.3163,35.1906],[-81.3209,35.2609],[-81.355,35.2796],[-81.3548,35.2946],[-81.3594,35.3022],[-81.3675,35.314],[-81.3659,35.3181],[-81.3565,35.3309],[-81.3986,35.3531],[-81.4535,35.4201]]]},\"properties\":{\"name\":\"Gaston\",\"state\":\"NC\"}}]}","edition":"Version 1.0: Originally posted March 27, 2017; Version 1.1: March 30, 2017","contact":"<p><a href=\"mailto:dc_sc@usgs.gov\" data-mce-href=\"mailto:dc_sc@usgs.gov\">Director,</a> South Atlantic Water Science Center <br> U.S. Geological Survey <br> 720 Gracern Road<br> Stephenson Center, Suite 129 <br> Columbia, SC 29210<br> <a href=\"https://www2.usgs.gov/water/southatlantic/\" data-mce-href=\"https://www2.usgs.gov/water/southatlantic/\">https://www2.usgs.gov/water/southatlantic/</a></p>","tableOfContents":"<ul><li>Abstract&nbsp;</li><li>Introduction</li><li>Methods of Data Collection</li><li>Surface Measurements</li><li>Borehole Geophysical Logging and Imaging Data&nbsp;</li><li>Inherent Sampling Biases in Measurements</li><li>Thermal Imaging Data</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li><li>Appendix 1. Borehole Geophysical Image Logs Showing Orientations of Subsurface Structural Features&nbsp;</li><li>Appendix 2. Borehole Geophysical Logs Showing Depth of Fracture Zones and Measured Borehole Flow&nbsp;</li><li>Appendix 3. Infrared Images Captured by Forward-Looking Infrared Camera at Sites to Measure Stream Surface and Bank Seepage Temperature Differences</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2017-03-27","revisedDate":"2017-03-30","noUsgsAuthors":false,"publicationDate":"2017-03-27","publicationStatus":"PW","scienceBaseUri":"58da2515e4b0543bf7fda7e4","contributors":{"authors":[{"text":"Antolino, Dominick J. 0000-0001-7838-5279 dantolin@usgs.gov","orcid":"https://orcid.org/0000-0001-7838-5279","contributorId":179174,"corporation":false,"usgs":true,"family":"Antolino","given":"Dominick","email":"dantolin@usgs.gov","middleInitial":"J.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":663035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chapman, Melinda J. 0000-0003-4021-0320 mjchap@usgs.gov","orcid":"https://orcid.org/0000-0003-4021-0320","contributorId":1597,"corporation":false,"usgs":true,"family":"Chapman","given":"Melinda","email":"mjchap@usgs.gov","middleInitial":"J.","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":663036,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70185554,"text":"ofr20171021 - 2017 - County-level estimates of nitrogen and phosphorus from animal manure for the conterminous United States, 2007 and 2012","interactions":[],"lastModifiedDate":"2017-08-29T09:31:10","indexId":"ofr20171021","displayToPublicDate":"2017-03-24T00:00:00","publicationYear":"2017","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":"2017-1021","title":"County-level estimates of nitrogen and phosphorus from animal manure for the conterminous United States, 2007 and 2012","docAbstract":"<p>County-level estimates of nitrogen and phosphorus inputs from animal manure for the conterminous United States were calculated from animal population inventories in the 2007 and 2012 Census of Agriculture, using previously published methods. These estimates of non-point nitrogen and phosphorus inputs from animal manure were compiled in support of the U.S. Geological Survey’s National Water-Quality Assessment Project of the National Water Quality Program and are needed to support national-scale investigations of stream and groundwater water quality. The estimates published in this report are comparable with older estimates which can be compared to show changes in nitrogen and phosphorus inputs from manure over time.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171021","issn":"2331-1258","usgsCitation":"Gronberg, J.M., and Arnold, T.L., 2017, County-level estimates of nitrogen and phosphorus from animal manure for the conterminous United States, 2007 and 2012: U.S. Geological Survey Open-File Report 2017–1021, 6 p., https://doi.org/10.3133/ofr20171021.","productDescription":"iii, 6 p.","numberOfPages":"14","onlineOnly":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":438408,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7X34VMZ","text":"USGS data release","linkHelpText":"County-level estimates of nitrogen and phosphorus from animal manure (2007 and 2012) and 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 \"}}]}\n","contact":"<div>Director, California Water Science Center</div><div>U.S. Geological Survey</div><div>6000 J Street, Placer Hall</div><div>Sacramento, California 95819</div><div><a href=\"http://ca.water.usgs.gov/\" target=\"_blank\" data-mce-href=\"http://ca.water.usgs.gov/\">http://ca.water.usgs.gov</a></div>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Estimating Nitrogen and Phosphorus from Animal Manure<br></li><li>Description of the County-Level Nutrient-Input Dataset<br></li><li>Summary<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2017-03-24","noUsgsAuthors":false,"publicationDate":"2017-03-24","publicationStatus":"PW","scienceBaseUri":"58d63035e4b05ec7991310d5","contributors":{"authors":[{"text":"Gronberg, JoAnn M. 0000-0003-4822-7434 jmgronbe@usgs.gov","orcid":"https://orcid.org/0000-0003-4822-7434","contributorId":3548,"corporation":false,"usgs":true,"family":"Gronberg","given":"JoAnn","email":"jmgronbe@usgs.gov","middleInitial":"M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":685942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arnold, Terri 0000-0003-1406-6054 tlarnold@usgs.gov","orcid":"https://orcid.org/0000-0003-1406-6054","contributorId":1598,"corporation":false,"usgs":false,"family":"Arnold","given":"Terri","email":"tlarnold@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":false,"id":685943,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70185133,"text":"ofr20171030 - 2017 - Channel mapping river miles 29–62 of the Colorado River in Grand Canyon National Park, Arizona, May 2009","interactions":[],"lastModifiedDate":"2018-01-25T18:58:27","indexId":"ofr20171030","displayToPublicDate":"2017-03-23T00:00:00","publicationYear":"2017","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":"2017-1030","title":"Channel mapping river miles 29–62 of the Colorado River in Grand Canyon National Park, Arizona, May 2009","docAbstract":"<p class=\"p1\">Bathymetric, topographic, and grain-size data were collected in May 2009 along a 33-mi reach of the Colorado River in Grand Canyon National Park, Arizona. The study reach is located from river miles 29 to 62 at the confluence of the Colorado and Little Colorado Rivers. Channel bathymetry was mapped using multibeam and singlebeam echosounders, subaerial topography was mapped using ground-based total-stations, and bed-sediment grain-size data were collected using an underwater digital microscope system. These data were combined to produce digital elevation models, spatially variable estimates of digital elevation model uncertainty, georeferenced grain-size data, and bed-sediment distribution maps. This project is a component of a larger effort to monitor the status and trends of sand storage along the Colorado River in Grand Canyon National Park. This report documents the survey methods and post-processing procedures, digital elevation model production and uncertainty assessment, and procedures for bed-sediment classification, and presents the datasets resulting from this study.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171030","collaboration":"Prepared in cooperation with Northern Arizona University","usgsCitation":"Kaplinski, M., Hazel, J.E., Jr., Grams, P.E., Kohl, Keith, Buscombe, D.D., and Tusso, R.B., 2017, Channel mapping river miles 29–62 of the Colorado River in Grand Canyon National Park, Arizona, May 2009: U.S. Geological Survey Open-File Report 2017–1030, 35 p., https://doi.org/10.3133/ofr20171030.","productDescription":"vi, 35 p.","onlineOnly":"Y","ipdsId":"IP-079813","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":438410,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7930RCG","text":"USGS data release","linkHelpText":"Channel Mapping of the Colorado River in Grand Canyon National Park, Arizona - May 2009, river miles 29 to 62Data"},{"id":338081,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1030/coverthb.jpg"},{"id":338082,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1030/ofr20171030.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1030"},{"id":350633,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7930RCG","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Channel Mapping of the Colorado River in Grand Canyon National Park, Arizona, May 2009, river miles 29 to 62—Data"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.7,\n              36.541667\n            ],\n            [\n              -112,\n              36.541667\n            ],\n            [\n              -112,\n              36.125\n            ],\n            [\n              -111.7,\n              36.125\n            ],\n            [\n              -111.7,\n              36.541667\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>GCMRC Staff, Southwest Biological Science Center<br> U.S. Geological Survey<br> Grand Canyon Monitoring and Research Center<br> 2255 N. Gemini Drive<br> Flagstaff, Arizona 86001<br> <a href=\"https://www.gcmrc.gov/\" target=\"blank\" data-mce-href=\"https://www.gcmrc.gov/\">https://www.gcmrc.gov/</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Data Collection and Processing</li><li>Digital Elevation Models</li><li>Digital Elevation Model Uncertainty</li><li>Results</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-03-23","noUsgsAuthors":false,"publicationDate":"2017-03-23","publicationStatus":"PW","scienceBaseUri":"58d4df00e4b05ec79911d19c","contributors":{"authors":[{"text":"Kaplinski, Matt","contributorId":22709,"corporation":false,"usgs":true,"family":"Kaplinski","given":"Matt","email":"","affiliations":[],"preferred":false,"id":684471,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hazel, Joseph E. Jr.","contributorId":19500,"corporation":false,"usgs":true,"family":"Hazel","given":"Joseph","suffix":"Jr.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":684472,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grams, Paul E. 0000-0002-0873-0708 pgrams@usgs.gov","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":1830,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","email":"pgrams@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":684470,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kohl, Keith 0000-0001-6812-0373 kkohl@usgs.gov","orcid":"https://orcid.org/0000-0001-6812-0373","contributorId":1323,"corporation":false,"usgs":true,"family":"Kohl","given":"Keith","email":"kkohl@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":684473,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buscombe, Daniel D. 0000-0001-6217-5584 dbuscombe@usgs.gov","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":5020,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","email":"dbuscombe@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":684474,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tusso, Robert B. 0000-0001-7541-3713 rtusso@usgs.gov","orcid":"https://orcid.org/0000-0001-7541-3713","contributorId":4079,"corporation":false,"usgs":true,"family":"Tusso","given":"Robert","email":"rtusso@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":685710,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70180160,"text":"ofr20171011 - 2017 - Methods used to characterize the chemical composition and biological activity of environmental waters throughout the United States, 2012-14","interactions":[],"lastModifiedDate":"2017-03-22T14:39:41","indexId":"ofr20171011","displayToPublicDate":"2017-03-22T14:45:00","publicationYear":"2017","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":"2017-1011","title":"Methods used to characterize the chemical composition and biological activity of environmental waters throughout the United States, 2012-14","docAbstract":"<p>A vast array of chemical compounds are in wide commercial use in the United States, and the potential ecological and human-health effect of exposure to chemical mixtures has been identified as a high priority in environment health science. Awareness of the potential effects of low-level chemical exposures is rising. The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, conducted a study in which samples were collected from 38 streams in 25 States to provide an overview of contaminants found in stream water across the Nation. Additionally, biological screening assays were used to help determine any potential ecological and human-health effects of these chemical mixtures and to prioritize target chemicals for future toxicological studies. This report describes the site locations and the sampling and analytical methods and quality-assurance procedures used in the study.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171011","issn":"2331-1258","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Romanok, K.M., Reilly, T.J., Barber, Larry, Boone, Scott, Buxton, H.T., Foreman, W.T., Furlong, E.T., Hladik, Michelle, Iwanowicz, L.R., Journey, Celeste, Kolpin, D.W., Kuivila, Kathryn, Loftin, K.A., Mills, M.A., Meyer, M.T., Orlando, J.L., Smalling, K.L., Villeneuve, D.L., and Bradley, P.M., 2017, Methods used to characterize the chemical composition and biological activity of environmental waters throughout the United States, 2012–14: U.S. Geological Survey Open-File Report 2017–1011, 105 p., https://doi.org/10.3133/ofr20171011.","productDescription":"Report: x, 105 p.; 1 Table; Data 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erties\":{\"name\":\"Alabama\",\"nation\":\"USA  \"}}]}","contact":"<p><a href=\"mailto:dc_sc@usgs.gov\" data-mce-href=\"mailto:dc_sc@usgs.gov\">Director</a>, South Atlantic Water Science Center<br> U.S. Geological Survey<br> 720 Gracern Road<br> Stephenson Center, Suite 129<br> Columbia, SC 29210<br> <a href=\"https://www.usgs.gov/water/southatlantic/\" data-mce-href=\"https://www.usgs.gov/water/southatlantic/\">https:www.usgs.gov/water/southatlantic/</a></p>","tableOfContents":"<ul><li>Acknowledgments&nbsp;</li><li>Abstract&nbsp;</li><li>Introduction</li><li>Methods</li><li>Quality Assurance/Quality Control&nbsp;</li><li>Results</li><li>References Cited</li><li>Appendix 1. Example of protocols provided to field personnel for the preparation, collection, processing, and shipping of samples collected for the Toxic Substances Hydrology Program, Chemical Mixtures Pilot Study, November 2012–June 2014.&nbsp;</li><li>Appendix 2. Site-specific pages containing site, sampling, and other basin information as well as physical parameter and inorganic chemical data collected at each site.</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2017-03-22","noUsgsAuthors":false,"publicationDate":"2017-03-22","publicationStatus":"PW","scienceBaseUri":"58d38d37e4b0236b68f98ed8","contributors":{"authors":[{"text":"Romanok, Kristin M.  0000-0002-8472-8765 kromanok@usgs.gov","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":169543,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M. ","email":"kromanok@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":660540,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reilly, Timothy J. 0000-0002-2939-3050 tjreilly@usgs.gov","orcid":"https://orcid.org/0000-0002-2939-3050","contributorId":1858,"corporation":false,"usgs":true,"family":"Reilly","given":"Timothy","email":"tjreilly@usgs.gov","middleInitial":"J.","affiliations":[{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":660555,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barber, Larry B. 0000-0002-0561-0831 lbbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":921,"corporation":false,"usgs":true,"family":"Barber","given":"Larry","email":"lbbarber@usgs.gov","middleInitial":"B.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":660541,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boone, J. Scott","contributorId":178697,"corporation":false,"usgs":false,"family":"Boone","given":"J.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":660542,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buxton, Herbert T.","contributorId":178698,"corporation":false,"usgs":false,"family":"Buxton","given":"Herbert","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":660543,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foreman, William T.  0000-0002-2530-3310 wforeman@usgs.gov","orcid":"https://orcid.org/0000-0002-2530-3310","contributorId":169108,"corporation":false,"usgs":true,"family":"Foreman","given":"William T. ","email":"wforeman@usgs.gov","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":false,"id":660544,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":660545,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hladik, Michelle 0000-0002-0891-2712 mhladik@usgs.gov","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":784,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","email":"mhladik@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":660546,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Iwanowicz, Luke R.  0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":150383,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R. ","email":"liwanowicz@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":660547,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":660548,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":660549,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kuivila, Kathryn  0000-0001-7940-489X kkuivila@usgs.gov","orcid":"https://orcid.org/0000-0001-7940-489X","contributorId":1367,"corporation":false,"usgs":true,"family":"Kuivila","given":"Kathryn ","email":"kkuivila@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":660550,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Loftin, Keith A. 0000-0001-5291-876X kloftin@usgs.gov","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":868,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","email":"kloftin@usgs.gov","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":660551,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Mills, Marc A.","contributorId":141085,"corporation":false,"usgs":false,"family":"Mills","given":"Marc","email":"","middleInitial":"A.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":660552,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Meyer, Michael T. 0000-0001-6006-7985 mmeyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6006-7985","contributorId":866,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael","email":"mmeyer@usgs.gov","middleInitial":"T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":660553,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Orlando, James L. 0000-0002-0099-7221 jorlando@usgs.gov","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":1368,"corporation":false,"usgs":true,"family":"Orlando","given":"James","email":"jorlando@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":660554,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Smalling, Kelly L.  0000-0002-1214-4920 ksmall@usgs.gov","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":149769,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L. ","email":"ksmall@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":660556,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Villeneuve, Daniel L.","contributorId":141084,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Daniel","email":"","middleInitial":"L.","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":660557,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":660539,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}}
,{"id":70185291,"text":"ofr20171035 - 2017 - Distribution, nesting activities, and age-class of territorial pairs of golden eagles at the Altamont Pass Wind Resource Area, California, 2014–16","interactions":[],"lastModifiedDate":"2017-11-22T15:51:58","indexId":"ofr20171035","displayToPublicDate":"2017-03-22T00:00:00","publicationYear":"2017","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":"2017-1035","title":"Distribution, nesting activities, and age-class of territorial pairs of golden eagles at the Altamont Pass Wind Resource Area, California, 2014–16","docAbstract":"<p>The substantial numbers of golden eagles (<i>Aquila chrysaetos</i>) killed by collisions with oldgeneration wind turbines each year at the Altamont Pass Wind Resource Area (APWRA) in California has been well documented from previous studies. Few eagle nests have been documented in the APWRA, however, and adults and subadults 3+ years of age killed by turbines were generally not associated with nearby territories. We searched a subset of randomly selected survey plots for territorial pairs of golden eagles and associated nesting attempts within the APWRA as part of a broader investigation of population dynamics in the surrounding northern Diablo Range. In contrast to limited historical observations from 1988 to 2013, our surveys documented up to 15 territorial pairs within 3.2 kilometers (km) of wind turbines at the APWRA annually, 9 of which were not previously documented or only observed intermittently during historical surveys. We found evidence of nesting activity by adult pairs at least once during our study at six of these territories. We also determined that 23–36 percent of territories identified within 3.2 km of the APWRA had a subadult pair member, but that no pairs with a subadult member attempted to nest. These data will be useful to developers, wildlife managers, and future raptor studies in the area to evaluate and minimize the potential effects of wind energy or other development activities on previously unknown territorial pairs in the area.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171035","collaboration":"Prepared in cooperation with Next Era Energy, Inc., U.S. Fish and Wildlife Service, East Bay Regional Park District, and The Peregrine Fund, Inc.","usgsCitation":"Kolar, P.S., and Wiens, J.D., 2017, Distribution, nesting activities, and age-class of territorial pairs of golden\neagles at the Altamont Pass Wind Resource Area, California, 2014–16: U.S. Geological Survey Open-File\nReport 2017–1035, 18 p., https://doi.org/10.3133/ofr20171035.","productDescription":"iv, 18 p.","onlineOnly":"Y","ipdsId":"IP-081674","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":338092,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1035/ofr20171035.pdf","text":"Report","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1035"},{"id":338091,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1035/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Altamont Pass Wind Resource Area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.8,\n              37.866667\n            ],\n            [\n              -121.366667,\n              37.866667\n            ],\n            [\n              -121.366667,\n              37.533333\n            ],\n            [\n              -121.8,\n              37.533333\n            ],\n            [\n              -121.8,\n              37.866667\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, Forest and Rangeland Ecosystem Science Center<br> U.S. Geological Survey<br> 777 NW 9th St., Suite 400<br> Corvallis, Oregon 97330<br> <a href=\"http://fresc.usgs.gov/\" target=\"blank\" data-mce-href=\"http://fresc.usgs.gov/\">http://fresc.usgs.gov/</a></p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Methods<br></li><li>Survey Results<br></li><li>Discussion<br></li><li>Acknowledgments<br></li><li>References Cited<br></li><li>Appendix 1. Number of Completed Individual Surveys for Focal Sample Plots Overlapping with the Altamont Pass Wind Resource Area, California, 2014–16<br></li><li>Appendix 2. Observations of Territorial and Nesting Activities of Golden Eagles at the Altamont Pass Wind Resource Area, California, 2014–16<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2017-03-22","noUsgsAuthors":false,"publicationDate":"2017-03-22","publicationStatus":"PW","scienceBaseUri":"58d38d3ae4b0236b68f98ee2","contributors":{"authors":[{"text":"Kolar, Patrick S. 0000-0002-0076-7565","orcid":"https://orcid.org/0000-0002-0076-7565","contributorId":139543,"corporation":false,"usgs":true,"family":"Kolar","given":"Patrick","email":"","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":685043,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wiens, J. David 0000-0002-2020-038X jwiens@usgs.gov","orcid":"https://orcid.org/0000-0002-2020-038X","contributorId":468,"corporation":false,"usgs":true,"family":"Wiens","given":"J.","email":"jwiens@usgs.gov","middleInitial":"David","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":685042,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70184442,"text":"ofr20171027 - 2017 - Age of the youngest volcanism at Eagle Lake, northeastern California—<sup>40</sup>Ar/<sup>39</sup>Ar and paleomagnetic results","interactions":[],"lastModifiedDate":"2017-03-23T08:56:29","indexId":"ofr20171027","displayToPublicDate":"2017-03-22T00:00:00","publicationYear":"2017","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":"2017-1027","title":"Age of the youngest volcanism at Eagle Lake, northeastern California—<sup>40</sup>Ar/<sup>39</sup>Ar and paleomagnetic results","docAbstract":"<p>The age of the youngest volcanism at Eagle Lake, California, was investigated using stratigraphic, paleomagnetic, and <sup>40</sup>Ar/<sup>39</sup>Ar techniques. The three youngest volcanic lava flows at Eagle Lake yielded ages of 130.0±5.1, 127.5±3.2 and 123.6±18.7 ka, and are statistically indistinguishable. Paleomagnetic results demonstrate that two of the lava flows are very closely spaced in time, whereas the third is different by centuries to at most a few millennia. These results indicate that the basalt lava flows at Eagle Lake are not Holocene in age, and were erupted during an episode of volcanism at about 130–125 ka that is unlikely to have spanned more than a few thousand years. Thus, the short-term potential for subsequent volcanism at Eagle Lake is considered low.&nbsp;</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171027","usgsCitation":"Clynne, M.A., Calvert, A.T., Champion, D.E., Muffler, L.J.P., Sawlan, M.G., and Downs, D.T., 2017, Age of the youngest volcanism at Eagle Lake, northeastern California—<sup>40</sup>Ar/<sup>39</sup>Ar and paleomagnetic results: U.S. Geological Survey Open-File Report 2017–1027, 24 p., https://doi.org/10.3133/ofr20171027.","productDescription":"iii, 24 p.","onlineOnly":"Y","ipdsId":"IP-081567","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":338131,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1027/ofr20171027.pdf","text":"Report","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1027"},{"id":338130,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1027/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Eagle Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.95,\n              40.75\n            ],\n            [\n              -120.625,\n              40.75\n            ],\n            [\n              -120.625,\n              40.525\n            ],\n            [\n              -120.95,\n              40.525\n            ],\n            [\n              -120.95,\n              40.75\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://volcanoes.usgs.gov/observatories/calvo/\" target=\"_blank\" data-mce-href=\"https://volcanoes.usgs.gov/observatories/calvo/\">Volcano Science Center—Menlo Park</a><br> U.S. Geological Survey<br> 345 Middlefield Road, MS 910<br> Menlo Park, CA 94025<br> <a href=\"http://volcanoes.usgs.gov/\" target=\"_blank\" data-mce-href=\"http://volcanoes.usgs.gov/\">https://volcanoes.usgs.gov/</a></p>","tableOfContents":"<p>Abstract<br> Introduction<br> General Geology of the Eagle Lake Area<br> Previous Map Depiction of the Young Basalts at Eagle Lake<br> Unit Descriptions<br> Paleomagnetic Secular Variation<br> <sup>40</sup>Ar/<sup>39</sup>Ar Results<br> Discussion<br> Conclusions<br> Acknowledgments<br> References<br> Appendix 1. <sup>40</sup>Ar/<sup>39</sup>Ar Analytical Techniques<br> Appendix 2. Tabulated <sup>40</sup>Ar/<sup>39</sup>Ar data for basaltic flows of Eagle Lake</p>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-03-22","noUsgsAuthors":false,"publicationDate":"2017-03-22","publicationStatus":"PW","scienceBaseUri":"58d38d3ae4b0236b68f98ee4","contributors":{"authors":[{"text":"Clynne, Michael A. 0000-0002-4220-2968 mclynne@usgs.gov","orcid":"https://orcid.org/0000-0002-4220-2968","contributorId":2032,"corporation":false,"usgs":true,"family":"Clynne","given":"Michael","email":"mclynne@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":681508,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Calvert, Andrew T. 0000-0001-5237-2218 acalvert@usgs.gov","orcid":"https://orcid.org/0000-0001-5237-2218","contributorId":2694,"corporation":false,"usgs":true,"family":"Calvert","given":"Andrew","email":"acalvert@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":681510,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Champion, Duane E. 0000-0001-7854-9034 dchamp@usgs.gov","orcid":"https://orcid.org/0000-0001-7854-9034","contributorId":2912,"corporation":false,"usgs":true,"family":"Champion","given":"Duane","email":"dchamp@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":681511,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muffler, L.J.P.","contributorId":63383,"corporation":false,"usgs":true,"family":"Muffler","given":"L.J.P.","affiliations":[],"preferred":false,"id":681513,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sawlan, Michael G. 0000-0003-0637-2051 msawlan@usgs.gov","orcid":"https://orcid.org/0000-0003-0637-2051","contributorId":2291,"corporation":false,"usgs":true,"family":"Sawlan","given":"Michael","email":"msawlan@usgs.gov","middleInitial":"G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":681512,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Downs, Drew T.","contributorId":189714,"corporation":false,"usgs":true,"family":"Downs","given":"Drew T.","affiliations":[],"preferred":false,"id":681509,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70184404,"text":"ofr20171025 - 2017 - Natural resource inventory and monitoring for Ulaan Taiga Specially Protected Areas—An assessment of needs and opportunities in northern Mongolia","interactions":[],"lastModifiedDate":"2017-03-14T09:45:46","indexId":"ofr20171025","displayToPublicDate":"2017-03-10T00:00:00","publicationYear":"2017","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":"2017-1025","title":"Natural resource inventory and monitoring for Ulaan Taiga Specially Protected Areas—An assessment of needs and opportunities in northern Mongolia","docAbstract":"<p class=\"p1\">Between 1997 and 2011, Mongolia established three specially protected areas in the north-central part of the country to protect various high-value resources. These areas are jointly referred to as the Ulaan Taiga Specially Protected Areas. In accordance with the goals of the draft general management plan, this report identifies options for initiating an inventory and monitoring program for the three protected areas. Together, the three areas comprise over 1.5 million hectares of mountainous terrain west of Lake Hovsgol and bordering the Darkhad Valley. The area supports numerous rare ungulates, endangered fish, and over 40 species of threatened plants. Illegal mining, illegal logging, and poaching pose the most immediate threats to resources. As a first step, a review of published literature would inform natural resource management at the Ulaan Taiga Specially Protected Areas because it would inform other inventories.</p><p class=\"p1\">Vegetation classification and mapping also would inform other inventory efforts because the process incorporates geographic analysis to identify environmental gradients, fine-scale sampling that captures species composition and structure, and landscape-scale results that represent the variety and extent of habitats for various organisms. Mapping using satellite imagery reduces the cost per hectare.</p><p class=\"p1\">Following a determination of existing knowledge, field surveys of vertebrates and vascular plants would serve to build species lists and fill in gaps in existing knowledge. For abiotic resources, a focus on monitoring air quality, evaluating and monitoring water quality, and assembling and storing weather data would provide information for correlating resource response status with changing environmental conditions.</p><p class=\"p1\">Finally, we identify datasets that, if incorporated into a geographic information system, would inform resource management. They include political boundaries, infrastructure, topography, surficial geology, hydrology, fire history, and soils.</p><p class=\"p1\">In terms of tracking high-value resources, vegetation monitoring at the plot scale would provide a basis for detecting change in such characteristics as plant species composition, vegetation structure, and productivity that are associated with landscape-scale factors such as climate change or biotic interactions. Continued population monitoring of rare ungulates, particularly argali or wild sheep (<i>Ovis ammon</i>), would provide information on how populations are responding to natural and anthropogenic stressors. Siberian taimen (<i>Hucho taimen</i>) also is an important monitoring target given ongoing threats of poaching and climate change.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171025","usgsCitation":"Moore, P.E., Meyer, J.B., and Chow, L.S., 2017, Natural resource inventory and monitoring for Ulaan Taiga Specially Protected Areas—An assessment of needs and opportunities in northern Mongolia: U.S. Geological Survey Open-File Report 2017–1025, 35 p., https://doi.org/10.3133/ofr20171025.","productDescription":"viii, 35 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-082861","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":337345,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1025/coverthb.jpg"},{"id":337346,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1025/ofr20171025.pdf","text":"Report","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1025"}],"country":"Mongolia","otherGeospatial":"Ulaan Taiga Specially Protected Areas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              97.55859375,\n              49.89463439573421\n            ],\n            [\n              102.48046875,\n              49.89463439573421\n            ],\n            [\n              102.48046875,\n              52.24125614966341\n            ],\n            [\n              97.55859375,\n              52.24125614966341\n            ],\n            [\n              97.55859375,\n              49.89463439573421\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, Western Ecological Research Center<br> U.S. Geological Survey<br> 3020 State University Drive East<br> Sacramento, California 95819<br> <a href=\"http://www.werc.usgs.gov/\" target=\"blank\" data-mce-href=\"http://www.werc.usgs.gov/\">http://www.werc.usgs.gov/</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Protected Areas</li><li>Natural Resource Inventories</li><li>Monitoring</li><li>Research to Inform Natural Resource Inventory and Monitoring</li><li>Conclusions</li><li>References Cited</li><li>Glossary</li><li>Appendixes 1–4</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2017-03-10","noUsgsAuthors":false,"publicationDate":"2017-03-10","publicationStatus":"PW","scienceBaseUri":"58c3c932e4b0f37a93ee9adb","contributors":{"authors":[{"text":"Moore, Peggy E. 0000-0002-8481-2617 peggy_moore@usgs.gov","orcid":"https://orcid.org/0000-0002-8481-2617","contributorId":3365,"corporation":false,"usgs":true,"family":"Moore","given":"Peggy","email":"peggy_moore@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":681337,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meyer, Joseph B.","contributorId":175028,"corporation":false,"usgs":false,"family":"Meyer","given":"Joseph","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":681338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chow, Leslie S.","contributorId":187689,"corporation":false,"usgs":false,"family":"Chow","given":"Leslie","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":681339,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70182911,"text":"ofr20171013 - 2017 - Assessment of continuous oil resources in the Wolfcamp shale of the Midland Basin, Permian Basin Province, Texas, 2016","interactions":[],"lastModifiedDate":"2017-03-06T15:56:17","indexId":"ofr20171013","displayToPublicDate":"2017-03-06T13:00:00","publicationYear":"2017","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":"2017-1013","title":"Assessment of continuous oil resources in the Wolfcamp shale of the Midland Basin, Permian Basin Province, Texas, 2016","docAbstract":"<p>The U.S. Geological Survey completed a geology-based assessment of undiscovered, technically recoverable continuous petroleum resources in the Wolfcamp shale in the Midland Basin part of the Permian Basin Province of west Texas. This is the first U.S. Geological Survey evaluation of continuous resources in the Wolfcamp shale in the Midland Basin. Since the 1980s, the Wolfcamp shale in the Midland Basin has been part of the “Wolfberry” play. This play has traditionally been developed using vertical wells that are completed and stimulated in multiple productive stratigraphic intervals that include the Wolfcamp shale and overlying Spraberry Formation. Since the shift to horizontal wells targeting the organic-rich shale of the Wolfcamp, more than 3,000 horizontal wells have been drilled and completed in the Midland Basin Wolfcamp section. The U.S. Geological Survey assessed technically recoverable mean resources of 20 billion barrels of oil and 16 trillion cubic feet of associated gas in the Wolfcamp shale in the Midland Basin.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171013","usgsCitation":"Gaswirth, S.B., 2017, Assessment of continuous oil resources in the Wolfcamp shale of the Midland Basin, Permian Basin Province, Texas, 2016: U.S. Geological Survey Open File-Report 2017–1013, 14 p., https://doi.org/10.3133/ofr20171013.\n","productDescription":"14 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-081644","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":336741,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1013/ofr20171013.pdf","text":"Report","size":"14.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1013"},{"id":336740,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1013/coverthb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Midland Basin, Permian Basin Province","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103,\n              30.5\n            ],\n            [\n              -103,\n              33.8\n            ],\n            [\n              -100,\n              33.8\n            ],\n            [\n              -100,\n              30.5\n            ],\n            [\n              -103,\n              30.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Center Director, USGS Central Energy Resources Science Center<br>Box 25046, Mail Stop 939<br>Denver, CO 80225</p><p><a href=\"http://energy.usgs.gov/\" data-mce-href=\"http://energy.usgs.gov/\">http://energy.usgs.gov/</a></p>","tableOfContents":"<ul><li>Assessment of the Wolfcamp Shale</li><li>Wolfcamp Production</li><li>Wolfcamp by the Numbers</li><li>Conventional versus Continuous Resources</li><li>USGS Assessment Methodology For Continuous-Type Accumulations</li><li>Stratigraphy and Assessment Units</li><li>Wolfcamp Shale Assessment Units</li><li>Wolfcamp Shale Mean Assessment Results Per Assessment Unit</li><li>Midland Basin Wolfcamp Shale Assessment Summary</li><li>Wolfcamp Shale of the Midland Basin: Largest Continuous Oil Accumulation Assessed by the USGS</li><li>References</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2017-03-06","noUsgsAuthors":false,"publicationDate":"2017-03-06","publicationStatus":"PW","scienceBaseUri":"58be8335e4b014cc3a3a99c9","contributors":{"authors":[{"text":"Gaswirth, Stephanie B. 0000-0001-5821-6347 sgaswirth@usgs.gov","orcid":"https://orcid.org/0000-0001-5821-6347","contributorId":140068,"corporation":false,"usgs":true,"family":"Gaswirth","given":"Stephanie B.","email":"sgaswirth@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":674340,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70180978,"text":"ofr20171019 - 2017 - Water-quality sampling plan for evaluating the distribution of bigheaded carps in the Illinois Waterway","interactions":[],"lastModifiedDate":"2017-05-25T16:05:01","indexId":"ofr20171019","displayToPublicDate":"2017-02-27T08:45:00","publicationYear":"2017","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":"2017-1019","title":"Water-quality sampling plan for evaluating the distribution of bigheaded carps in the Illinois Waterway","docAbstract":"<p>The two nonnative invasive <strong>bigheaded carp</strong> species (bighead carp <i>Hypophthalmichthys nobilis</i> and silver carp <i>H. molitrix</i>) that were accidentally released in the 1970s have spread widely into the rivers and waterways of the Mississippi River Basin. First detected in the lower reaches of the Illinois Waterway (IWW, the combined Illinois River-Des Plaines River-Chicago Area Waterway System) in the 1990s, bighead and silver carps moved quickly upstream, approaching the Chicago Area Waterway System. The potential of substantial negative ecological and economic impact to the Great Lakes from the presence of these species is a concern. However, since 2006, the population front of bigheaded carps has remained in the vicinity of Joliet, Illinois, near river mile 278. This reach of the IWW is characterized by stark changes in habitat, water quality, and food resources as the waterway transitions from a primarily agricultural landscape to a metropolitan and industrial canal system. This report describes a 2015 plan for sampling the IWW to establish water-quality conditions that might be contributing to the apparent stalling of the population front of bigheaded carps in this reach. A detailed description of the study plan, <strong>Lagrangian-style sampling</strong> approach, selected analytes, sampling methods and protocols are provided. Hydrographs from streamflow-gaging stations show IWW conditions during the 2015 sampling runs.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171019","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency- Great Lakes Restoration Initiative","usgsCitation":"Duncker, J.J., and Terrio, P.J., 2017, Water-quality sampling plan for evaluating the distribution of bigheaded carps in the Illinois Waterway: U.S. Geological Survey Open File Report 2017–1019, 9 p., https://doi.org/10.3133/ofr20171019.\n\n","productDescription":"iv, 9 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-077191","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":336228,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1019/coverthb.jpg"},{"id":336229,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1019/ofr20171019.pdf","text":"Report","size":"7.68 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1019"}],"country":"United States","state":"Illinois","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.527099609375,\n              38.64261790634527\n            ],\n            [\n              -87.506103515625,\n              38.64261790634527\n            ],\n            [\n              -87.506103515625,\n              42.48830197960227\n            ],\n            [\n              -91.527099609375,\n              42.48830197960227\n            ],\n            [\n              -91.527099609375,\n              38.64261790634527\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_il@usgs.gov\" data-mce-href=\"mailto:dc_il@usgs.gov\">Director</a>, Illinois Water Science Center<br> 405 N. Goodwin Avenue<br> Urbana, IL 61801-2347<br> Phone: (217) 328-8747 <br> <a href=\"http://il.water.usgs.gov/\" data-mce-href=\"http://il.water.usgs.gov/\">http://il.water.usgs.gov/</a></p>","tableOfContents":"<ul><li>Abstract&nbsp;</li><li>Introduction</li><li>Plan of Study</li><li>Summary</li><li>References Cited</li><li>Glossary</li></ul>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2017-02-27","noUsgsAuthors":false,"publicationDate":"2017-02-27","publicationStatus":"PW","scienceBaseUri":"58b548bce4b01ccd54fddfa0","contributors":{"authors":[{"text":"Duncker, James J. 0000-0001-5464-7991 jduncker@usgs.gov","orcid":"https://orcid.org/0000-0001-5464-7991","contributorId":4316,"corporation":false,"usgs":true,"family":"Duncker","given":"James","email":"jduncker@usgs.gov","middleInitial":"J.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":663034,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terrio, Paul J. 0000-0002-1515-9570 pjterrio@usgs.gov","orcid":"https://orcid.org/0000-0002-1515-9570","contributorId":3313,"corporation":false,"usgs":true,"family":"Terrio","given":"Paul","email":"pjterrio@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":671715,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70179691,"text":"ofr20171003 - 2017 - USA National Phenology Network gridded products documentation","interactions":[],"lastModifiedDate":"2017-02-24T09:11:49","indexId":"ofr20171003","displayToPublicDate":"2017-02-23T17:15:00","publicationYear":"2017","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":"2017-1003","title":"USA National Phenology Network gridded products documentation","docAbstract":"<p>The goals of the USA National Phenology Network (<a href=\"https://www.usanpn.org/\" data-mce-href=\"https://www.usanpn.org/\">USA-NPN, www.usanpn.org</a>) are to advance science, inform decisions, and communicate and connect with the public regarding phenology and species’ responses to environmental variation and climate change. The USA-NPN seeks to facilitate informed ecosystem stewardship and management by providing phenological information freely and openly. One way the USA-NPN is endeavoring to accomplish these goals is by providing data and data products in a wide range of formats, including gridded real-time, short-term forecasted, and historical maps of phenological events, patterns and trends. This document describes the suite of gridded phenologically relevant data products produced and provided by the USA National Phenology Network, which can be accessed at <a href=\"https://www.usanpn.org/data/phenology_maps\" data-mce-href=\"https://www.usanpn.org/data/phenology_maps\">www.usanpn.org/data/phenology_maps</a> and also through web services at <a href=\"http://geoserver.usanpn.org/geoserver/wms?request=GetCapabilities\" data-mce-href=\"http://geoserver.usanpn.org/geoserver/wms?request=GetCapabilities\">geoserver.usanpn.org/geoserver/wms?request=GetCapabilities</a>.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171003","collaboration":"Prepared in cooperation with the University of Arizona","usgsCitation":"Crimmins, T.M., Marsh, R.L., Switzer, J.R., Crimmins, M.A., Gerst, K.L., Rosemartin, A.H., and Weltzin, J.F., 2017, USA National Phenology Network gridded products documentation: U.S. Geological Survey Open-File Report 2017–1003, 27 p., https://doi.org/10.3133/ofr20171003.","productDescription":"vi, 27 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076553","costCenters":[{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"links":[{"id":334617,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1003/ofr20171003.pdf","text":"Report","size":"432 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1003"},{"id":334616,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1003/coverthb.jpg"}],"contact":"<p>Executive Director<br> USA National Phenology Network<br> <a href=\"http://www.usanpn.org\" data-mce-href=\"http://www.usanpn.org\">http://www.usanpn.org</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>1.0 Introduction</li><li>2.0 Data Product Descriptions</li><li>3.0 Additional Layer Features</li><li>4.0 Production Workflow</li><li>5.0 Web Services: Geoserver&nbsp;</li><li>6.0 Changes to the Extended Spring Index Implementation</li><li>7.0 Uncertainty and Quality Control Checks on Gridded Products</li><li>References Cited&nbsp;</li><li>Appendix. USA-NPN Geoserver Documentation</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-02-23","noUsgsAuthors":false,"publicationDate":"2017-02-23","publicationStatus":"PW","scienceBaseUri":"58b002c2e4b01ccd54fb27b9","contributors":{"authors":[{"text":"Crimmins, Theresa M.","contributorId":178236,"corporation":false,"usgs":false,"family":"Crimmins","given":"Theresa","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":658270,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marsh, R. Lee","contributorId":146211,"corporation":false,"usgs":false,"family":"Marsh","given":"R.","email":"","middleInitial":"Lee","affiliations":[{"id":16629,"text":"USA National Phenology Network, SNRE University of Arizona","active":true,"usgs":false}],"preferred":false,"id":658271,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Switzer, Jeff R.","contributorId":178237,"corporation":false,"usgs":false,"family":"Switzer","given":"Jeff","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":658272,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crimmins, Michael A.","contributorId":178238,"corporation":false,"usgs":false,"family":"Crimmins","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":658273,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gerst, Katharine L.","contributorId":175227,"corporation":false,"usgs":false,"family":"Gerst","given":"Katharine","email":"","middleInitial":"L.","affiliations":[{"id":27543,"text":"National Phenology Network, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":658274,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rosemartin, Alyssa H.","contributorId":178239,"corporation":false,"usgs":false,"family":"Rosemartin","given":"Alyssa","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":658275,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weltzin, Jake F. 0000-0001-8641-6645 jweltzin@usgs.gov","orcid":"https://orcid.org/0000-0001-8641-6645","contributorId":149648,"corporation":false,"usgs":true,"family":"Weltzin","given":"Jake F.","email":"jweltzin@usgs.gov","affiliations":[{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"preferred":false,"id":658269,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70179952,"text":"ofr20171008 - 2017 - Processing and review interface for strong motion data (PRISM) software, version 1.0.0—Methodology and automated processing","interactions":[],"lastModifiedDate":"2017-02-24T08:53:40","indexId":"ofr20171008","displayToPublicDate":"2017-02-23T00:00:00","publicationYear":"2017","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":"2017-1008","title":"Processing and review interface for strong motion data (PRISM) software, version 1.0.0—Methodology and automated processing","docAbstract":"<p class=\"p1\">A continually increasing number of high-quality digital strong-motion records from stations of the National Strong-Motion Project (NSMP) of the U.S. Geological Survey (USGS), as well as data from regional seismic networks within the United States, call for automated processing of strong-motion records with human review limited to selected significant or flagged records. The NSMP has developed the Processing and Review Interface for Strong Motion data (PRISM) software to meet this need. In combination with the Advanced National Seismic System Quake Monitoring System (AQMS), PRISM automates the processing of strong-motion records. When used without AQMS, PRISM provides batch-processing capabilities. The PRISM version 1.0.0 is platform independent (coded in Java), open source, and does not depend on any closed-source or proprietary software. The software consists of two major components: a record processing engine and a review tool that has a graphical user interface (GUI) to manually review, edit, and process records. To facilitate use by non-NSMP earthquake engineers and scientists, PRISM (both its processing engine and review tool) is easy to install and run as a stand-alone system on common operating systems such as Linux, OS X, and Windows. PRISM was designed to be flexible and extensible in order to accommodate new processing techniques. This report provides a thorough description and examples of the record processing features supported by PRISM. All the computing features of PRISM have been thoroughly tested.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171008","usgsCitation":"Jones, J., Kalkan, E., and Stephens, C., 2017, Processing and review interface for strong motion data (PRISM) software, version 1.0.0—Methodology and automated processing: U.S. Geological Survey Open-File Report 2017–1008, 81 p., https://doi.org/10.3133/ofr20171008.","productDescription":"x, 81 p.","onlineOnly":"Y","ipdsId":"IP-065005","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":335779,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1008/ofr20171008.pdf","text":"Report","size":"14.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1008"},{"id":335778,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1008/coverthb.jpg"}],"contact":"<p>Earthquake Science Center—<a href=\"http://earthquake.usgs.gov/contactus/menlo/\" target=\"_blank\" data-mce-href=\"http://earthquake.usgs.gov/contactus/menlo/\">Menlo Park, Calif. Office</a><br>U.S. Geological Survey&nbsp;<br>345 Middlefield Road, MS 977&nbsp;<br>Menlo Park, CA 94025&nbsp;<br><a href=\"http://earthquake.usgs.gov/\" target=\"_blank\" data-mce-href=\"http://earthquake.usgs.gov/\">http://earthquake.usgs.gov/</a></p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Input/Output Files<br></li><li>Automated Processing Workflow<br></li><li>Configuration File Parameters<br></li><li>Example V2 and V3 Products<br></li><li>Run-Time Performance Assessment<br></li><li>Systematic Comparisons among PRISM, BAP, and CSMIP Processing<br></li><li>Running PRISM<br></li><li>Output Directory Structure<br></li><li>Concluding Remarks<br></li><li>Data and Resources<br></li><li>References Cited<br></li><li>Appendixes 1–4<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-02-23","noUsgsAuthors":false,"publicationDate":"2017-02-23","publicationStatus":"PW","scienceBaseUri":"58b002c6e4b01ccd54fb27c5","contributors":{"authors":[{"text":"Jones, Jeanne","contributorId":50444,"corporation":false,"usgs":true,"family":"Jones","given":"Jeanne","affiliations":[],"preferred":false,"id":659272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalkan, Erol 0000-0002-9138-9407 ekalkan@usgs.gov","orcid":"https://orcid.org/0000-0002-9138-9407","contributorId":1218,"corporation":false,"usgs":true,"family":"Kalkan","given":"Erol","email":"ekalkan@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":659271,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stephens, Christopher","contributorId":33582,"corporation":false,"usgs":true,"family":"Stephens","given":"Christopher","affiliations":[],"preferred":false,"id":659273,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70182272,"text":"ofr20171020 - 2017 - Systematic comparisons between PRISM version 1.0.0, BAP, and CSMIP ground-motion processing","interactions":[],"lastModifiedDate":"2017-02-24T08:43:12","indexId":"ofr20171020","displayToPublicDate":"2017-02-23T00:00:00","publicationYear":"2017","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":"2017-1020","title":"Systematic comparisons between PRISM version 1.0.0, BAP, and CSMIP ground-motion processing","docAbstract":"<p class=\"p1\">A series of benchmark tests was run by comparing results of the Processing and Review Interface for Strong Motion data (PRISM) software version 1.0.0 to Basic Strong-Motion Accelerogram Processing Software (BAP; Converse and Brady, 1992), and to California Strong Motion Instrumentation Program (CSMIP) processing (Shakal and others, 2003, 2004). These tests were performed by using the MatLAB implementation of PRISM, which is equivalent to its public release version in Java language. Systematic comparisons were made in time and frequency domains of records processed in PRISM and BAP, and in CSMIP, by using a set of representative input motions with varying resolutions, frequency content, and amplitudes. Although the details of strong-motion records vary among the processing procedures, there are only minor differences among the waveforms for each component and within the frequency passband common to these procedures. A comprehensive statistical evaluation considering more than 1,800 ground-motion components demonstrates that differences in peak amplitudes of acceleration, velocity, and displacement time series obtained from PRISM and CSMIP processing are equal to or less than 4 percent for 99 percent of the data, and equal to or less than 2 percent for 96 percent of the data. Other statistical measures, including the Euclidian distance (L<sup>2 </sup>norm) and the windowed root mean square level of processed time series, also indicate that both processing schemes produce statistically similar products.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171020","usgsCitation":"Kalkan, E., and Stephens, C., 2017, Systematic comparisons between PRISM version 1.0.0, BAP, and CSMIP ground-motion processing: U.S. Geological Survey Open-File Report 2017–1020, 108 p., https://doi.org/10.3133/ofr20171020.","productDescription":"xv, 108 p.","onlineOnly":"Y","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":335955,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1020/coverthb.jpg"},{"id":335956,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1020/ofr20171020.pdf","text":"Report","size":"34.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1020"}],"contact":"<p>Earthquake Science Center—<a href=\"http://earthquake.usgs.gov/contactus/menlo/\" target=\"_blank\" data-mce-href=\"http://earthquake.usgs.gov/contactus/menlo/\">Menlo Park, Calif. Office</a><br>U.S. Geological Survey&nbsp;<br>345 Middlefield Road, MS 977&nbsp;<br>Menlo Park, CA 94025&nbsp;<br><a href=\"http://earthquake.usgs.gov/\" target=\"_blank\" data-mce-href=\"http://earthquake.usgs.gov/\">http://earthquake.usgs.gov/</a></p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Integration and Filtering<br></li><li>Central-Difference Formula<br></li><li>Measuring Time-Series Similarities<br></li><li>Statistical Evaluation of PRISM and CSMIP Processed Records<br></li><li>Concluding Remarks<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-02-23","noUsgsAuthors":false,"publicationDate":"2017-02-23","publicationStatus":"PW","scienceBaseUri":"58b002c5e4b01ccd54fb27bf","contributors":{"authors":[{"text":"Kalkan, Erol 0000-0002-9138-9407 ekalkan@usgs.gov","orcid":"https://orcid.org/0000-0002-9138-9407","contributorId":1218,"corporation":false,"usgs":true,"family":"Kalkan","given":"Erol","email":"ekalkan@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":670328,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stephens, Christopher","contributorId":33582,"corporation":false,"usgs":true,"family":"Stephens","given":"Christopher","affiliations":[],"preferred":false,"id":670329,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70182161,"text":"ofr20171022 - 2017 - Record-high specific conductance and water temperature in San Francisco Bay during water year 2015","interactions":[],"lastModifiedDate":"2017-10-30T09:38:04","indexId":"ofr20171022","displayToPublicDate":"2017-02-22T00:00:00","publicationYear":"2017","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":"2017-1022","title":"Record-high specific conductance and water temperature in San Francisco Bay during water year 2015","docAbstract":"<p>The San Francisco estuary is commonly defined to include San Francisco Bay (bay) and the adjacent Sacramento–San Joaquin River Delta (delta). The U.S. Geological Survey (USGS) has operated a high-frequency (15-minute sampling interval) water-quality monitoring network in San Francisco Bay since the late 1980s (Buchanan and others, 2014). This network includes 19 stations at which sustained measurements have been made in the bay; currently, 8 stations are in operation (fig. 1). All eight stations are equipped with specific conductance (which can be related to salinity) and water-temperature sensors. Water quality in the bay constantly changes as ocean tides force seawater in and out of the bay, and river inflows—the most significant coming from the delta—vary on time scales ranging from those associated with storms to multiyear droughts. This monitoring network was designed to observe and characterize some of these changes in the bay across space and over time. The data demonstrate a high degree of variability in both specific conductance and temperature at time scales from tidal to annual and also reveal longer-term changes that are likely to influence overall environmental health in the bay.<br></p><p>In water year (WY) 2015 (October 1, 2014, through September 30, 2015), as in the preceding water year (Downing-Kunz and others, 2015), the high-frequency measurements revealed record-high values of specific conductance and water temperature at several stations during a period of reduced freshwater inflow from the delta and other tributaries because of persistent, severe drought conditions in California. This report briefly summarizes observations for WY 2015 and compares them to previous years that had different levels of freshwater inflow.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171022","issn":"2331-1258 (online)","usgsCitation":"Work, P.A., Downing-Kunz, M.A., and Livsey, D., 2017, Record-high specific conductance and water temperature in San Francisco Bay during water year 2015: U.S. Geological Survey Open-File Report 2017–1022, 4 p., https://doi.org/10.3133/ofr20171022.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","ipdsId":"IP-079162","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":335947,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1022/coverthb.jpg"},{"id":335948,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1022/ofr20171022.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1022"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin River Delta, San Francisco Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.9,\n              37.4\n            ],\n            [\n              -122.5,\n              37.4\n            ],\n            [\n              -122.5,\n              38.1\n            ],\n            [\n              -121.9,\n              38.1\n            ],\n            [\n              -121.9,\n              37.4\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://mail.google.com/mail/?view=cm&amp;fs=1&amp;tf=1&amp;to=dc_ca@usgs.gov\" data-mce-href=\"https://mail.google.com/mail/?view=cm&amp;fs=1&amp;tf=1&amp;to=dc_ca@usgs.gov\">Director</a>, California Water Science Center<br>U.S. Geological Survey<br>6000 J Street, Placer Hall<br>Sacramento, CA 95819</p><p><a href=\"http://ca.water.usgs.gov/\" data-mce-href=\"http://ca.water.usgs.gov\">http://ca.water.usgs.gov</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Instrumentation and Data Collection<br></li><li>Water Year 2015 Records<br></li><li>Annual Mean Values and Relation to Freshwater Inflow</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2017-02-22","noUsgsAuthors":false,"publicationDate":"2017-02-22","publicationStatus":"PW","scienceBaseUri":"58aeb139e4b01ccd54f9ee12","contributors":{"authors":[{"text":"Work, Paul A. 0000-0002-2815-8040 pwork@usgs.gov","orcid":"https://orcid.org/0000-0002-2815-8040","contributorId":168561,"corporation":false,"usgs":true,"family":"Work","given":"Paul","email":"pwork@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669845,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Downing-Kunz, Maureen A. 0000-0002-4879-0318 mdowning-kunz@usgs.gov","orcid":"https://orcid.org/0000-0002-4879-0318","contributorId":3690,"corporation":false,"usgs":true,"family":"Downing-Kunz","given":"Maureen","email":"mdowning-kunz@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669846,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Livsey, Daniel N. 0000-0002-2028-6128 dlivsey@usgs.gov","orcid":"https://orcid.org/0000-0002-2028-6128","contributorId":181870,"corporation":false,"usgs":true,"family":"Livsey","given":"Daniel","email":"dlivsey@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669847,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70180166,"text":"ofr20171010 - 2017 - Saltwater intrusion in the Floridan aquifer system near downtown Brunswick, Georgia, 1957–2015","interactions":[],"lastModifiedDate":"2017-02-17T09:15:57","indexId":"ofr20171010","displayToPublicDate":"2017-02-16T16:45:00","publicationYear":"2017","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":"2017-1010","title":"Saltwater intrusion in the Floridan aquifer system near downtown Brunswick, Georgia, 1957–2015","docAbstract":"<h1>Introduction</h1><p>The Floridan aquifer system (FAS) consists of the Upper Floridan aquifer (UFA), an intervening confining unit of highly variable properties, and the Lower Floridan aquifer (LFA). The UFA and LFA are primarily composed of Paleocene- to Oligocene-age carbonate rocks that include, locally, Upper Cretaceous rocks. The FAS extends from coastal areas in southeastern South Carolina and continues southward and westward across the coastal plain of Georgia and Alabama, and underlies all of Florida. The thickness of the FAS varies from less than 100 feet (ft) in aquifer outcrop areas of South Carolina to about 1,700 ft near the city of Brunswick, Georgia.</p><p>Locally, in southeastern Georgia and the Brunswick– Glynn County area, the UFA consists of an upper water-bearing zone (UWBZ) and a lower water-bearing zone (LWBZ), as identified by Wait and Gregg (1973), with aquifer test data indicating the upper zone has higher productivity than the lower zone. Near the city of Brunswick, the LFA is composed of two permeable zones: an early middle Eocene-age upper permeable zone (UPZ) and a highly permeable lower zone of limestone (LPZ) of Paleocene and Late Cretaceous age that includes a deeply buried, cavernous, saline water-bearing unit known as the Fernandina permeable zone. Maslia and Prowell (1990) inferred the presence of major northeast–southwest trending faults through the downtown Brunswick area based on structural analysis of geophysical data, northeastward elongation of the potentiometric surface of the UFA, and breaches in the local confining unit that influence the area of chloride contamination. Pronounced horizontal and vertical hydraulic head gradients, caused by pumping in the UFA, allow saline water from the FPZ to migrate upward into the UFA through this system of faults and conduits.</p><p>Saltwater was first detected in the FAS in wells completed in the UFA near the southern part of the city of Brunswick in late 1957. By the 1970s, a plume of groundwater with high chloride concentrations had migrated northward toward two major industrial pumping centers, and since 1965, chloride concentrations have steadily increased in the northern part of the city. In 1978, data obtained from a 2,720-ft-deep test well (33H188) drilled south of the city showed water with a chloride concentration of 33,000 milligrams per liter (mg/L), suggesting the saltwater source was located below the UFA in the Fernandina permeable zone (FPZ) of the LFA.</p><p>All U.S. Geological Survey (USGS) data collected for this study, including groundwater levels in wells and water-chemistry data, are available in the USGS National Water Information System.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171010","collaboration":"In cooperation with the Brunswick-Glynn County Joint Water and Sewer Commission","usgsCitation":"Cherry, G.S., and Peck, M.F., 2017, Saltwater intrusion in the Floridan aquifer system near downtown Brunswick, Georgia, 1957–2015: U.S. Geological Survey Open-File Report 2017–2010, 10 p., https://doi.org/10.3133/ofr20171010.","productDescription":"10 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-075326","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":334883,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1010/ofr20171010.pdf","text":"Report","size":"1.61 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1010"},{"id":334882,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1010/coverthb1.jpg"}],"country":"United States","state":"Georgia","city":"Brunswick","otherGeospatial":"Floridan Aquifer System","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.53263092041016,\n              31.11262192177511\n            ],\n            [\n              -81.46190643310547,\n              31.11262192177511\n            ],\n            [\n              -81.46190643310547,\n              31.207516037787602\n            ],\n            [\n              -81.53263092041016,\n              31.207516037787602\n            ],\n            [\n              -81.53263092041016,\n              31.11262192177511\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_sc@usgs.gov\" data-mce-href=\"mailto:dc_sc@usgs.gov\">Director</a>, South Atlantic Water Science Center <br> U.S. Geological Survey<br> 720 Gracern Road<br> Stephenson Center, Suite 129<br> Columbia, SC 29210</p><p>Or visit the South Atlantic Water Science Center Website at<br><a href=\"https://www.usgs.gov/water/southatlantic/\" data-mce-href=\"https://www.usgs.gov/water/southatlantic/\">https://www.usgs.gov/water/southatlantic/</a></p>","tableOfContents":"<ul><li>Introduction</li><li>Groundwater Levels, Groundwater Pumping, and Flow in the Floridan Aquifer System</li><li>Chloride Concentrations in the Upper Floridan Aquifer</li><li>Water Chemistry of the Upper Floridan Aquifer</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2017-02-16","noUsgsAuthors":false,"publicationDate":"2017-02-16","publicationStatus":"PW","scienceBaseUri":"58a6c823e4b025c46428624c","contributors":{"authors":[{"text":"Cherry, Gregory S. 0000-0002-5567-1587 gccherry@usgs.gov","orcid":"https://orcid.org/0000-0002-5567-1587","contributorId":1567,"corporation":false,"usgs":true,"family":"Cherry","given":"Gregory","email":"gccherry@usgs.gov","middleInitial":"S.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":660590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peck, Michael mfpeck@usgs.gov","contributorId":178707,"corporation":false,"usgs":true,"family":"Peck","given":"Michael","email":"mfpeck@usgs.gov","affiliations":[],"preferred":true,"id":660591,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70180894,"text":"ofr20171009 - 2017 - A methodology for modeling barrier island storm-impact scenarios","interactions":[],"lastModifiedDate":"2017-03-29T14:44:29","indexId":"ofr20171009","displayToPublicDate":"2017-02-16T12:00:00","publicationYear":"2017","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":"2017-1009","title":"A methodology for modeling barrier island storm-impact scenarios","docAbstract":"<p>A methodology for developing a representative set of storm scenarios based on historical wave buoy and tide gauge data for a region at the Chandeleur Islands, Louisiana, was developed by the U.S. Geological Survey. The total water level was calculated for a 10-year period and analyzed against existing topographic data to identify when storm-induced wave action would affect island morphology. These events were categorized on the basis of the threshold of total water level and duration to create a set of storm scenarios that were simulated, using a high-fidelity, process-based, morphologic evolution model, on an idealized digital elevation model of the Chandeleur Islands. The simulated morphological changes resulting from these scenarios provide a range of impacts that can help coastal managers determine resiliency of proposed or existing coastal structures and identify vulnerable areas within those structures.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171009","usgsCitation":"Mickey, R.C., Long, J.W., Plant, N.G., Thompson, D.M., and Dalyander, P.S., 2017, A methodology for modeling barrier island storm-impact scenarios (ver. 1.1, March 2017): U.S. Geological Survey Open-File Report 2017–1009, 17 p.,  https://doi.org/10.3133/ofr20171009.","productDescription":"iv, 17 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":337876,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2017/1009/versionHist.txt","linkFileType":{"id":2,"text":"txt"}},{"id":334864,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1009/coverthb2.jpg"},{"id":334865,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1009/ofr20171009.pdf","text":"Report","size":"2.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1009"},{"id":334866,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72F7KJK","text":"USGS data release","description":"USGS data release","linkHelpText":"Storm-Impact Scenario XBeach Model Input and Results"}],"country":"United States","state":"Louisiana","otherGeospatial":"Chandeleur Islands","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.116667,\n              31\n            ],\n            [\n              -86.95,\n              31\n            ],\n            [\n              -86.95,\n              28.583333\n            ],\n            [\n              -89.116667,\n              28.583333\n            ],\n            [\n              -89.116667,\n              31\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.0: Originally posted February 16, 2017; Version 1.1: March 29, 2017","contact":"<p>Director, St. Petersburg Coastal and Marine Science Center<br> U.S. Geological Survey<br> 600 4th Street South<br> St. Petersburg, FL 33701<br> <a href=\"http://coastal.er.usgs.gov/\" data-mce-href=\"http://coastal.er.usgs.gov/\">http://coastal.er.usgs.gov/</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results&nbsp;</li><li>Discussion</li><li>Summary</li><li>Acknowledgments</li><li>Information Statement</li><li>References Cited&nbsp;</li><li>Appendix 1. Example Model Input Files&nbsp;</li></ul>","publishedDate":"2017-02-16","revisedDate":"2017-03-29","noUsgsAuthors":false,"publicationDate":"2017-02-16","publicationStatus":"PW","scienceBaseUri":"58a6c824e4b025c46428624e","contributors":{"authors":[{"text":"Mickey, Rangley C. rmickey@usgs.gov","contributorId":5741,"corporation":false,"usgs":true,"family":"Mickey","given":"Rangley C.","email":"rmickey@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":662748,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Joseph W. 0000-0003-2912-1992 jwlong@usgs.gov","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":3303,"corporation":false,"usgs":true,"family":"Long","given":"Joseph","email":"jwlong@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":662749,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":662750,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, David M. 0000-0002-7103-5740 dthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-7103-5740","contributorId":3502,"corporation":false,"usgs":true,"family":"Thompson","given":"David","email":"dthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":662751,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dalyander, P. Soupy 0000-0001-9583-0872 sdalyander@usgs.gov","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":141015,"corporation":false,"usgs":true,"family":"Dalyander","given":"P.","email":"sdalyander@usgs.gov","middleInitial":"Soupy","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":662752,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70181798,"text":"ofr20171014 - 2017 - Hurricane Sandy washover deposits on Fire Island, New York","interactions":[],"lastModifiedDate":"2017-02-17T08:26:09","indexId":"ofr20171014","displayToPublicDate":"2017-02-16T00:00:00","publicationYear":"2017","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":"2017-1014","title":"Hurricane Sandy washover deposits on Fire Island, New York","docAbstract":"<p><span>Washover deposits on Fire Island, New York, from Hurricane Sandy in 2012 were investigated a year after the storm to document the sedimentary characteristics of hurricane washover features. Sediment data collected in the field includes stratigraphic descriptions and photos from trenches, bulk sediment samples, U-channels, and gouge and push cores. Samples and push cores were further analyzed in the laboratory for grain size, density variations using x-ray computed tomography (CT), and surface microtexture using a scanning electron microscope (SEM). Elevation profiles of washover features were measured using Differential Global Positioning System (DGPS) with Real Time Kinematic processing. The DGPS elevations were compared to lidar (light detection and ranging) data from pre- and post-Sandy surveys to assess the degree to which washover deposit thicknesses changed within the year following deposition. Hurricane Sandy washover deposits as much as 1 meter thick were observed in trenches. Initial results show that the upper parts of the deposits have been reworked significantly in some places by wind, but there are still areas where the deposits are almost entirely intact. Where mostly intact, the washover deposits consist of massive or weakly laminated sand near the base, overlain by more strongly laminated sands.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171014","usgsCitation":"La Selle, S.M., Lunghino, B.D., Jaffe, B.E., Gelfenbaum, G., and Costa, P.J.M., 2017, Hurricane Sandy washover deposits on Fire Island, New York: U.S. Geological Survey Open-File Report 2017–1014, 30 p., https://doi.org/10.3133/ofr20171014.","productDescription":"v, 30 p.","onlineOnly":"Y","ipdsId":"IP-059939","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":335669,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1014/ofr20171014.pdf","text":"Report","size":"7.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1014"},{"id":335668,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1014/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.333333,\n              40.916667\n            ],\n            [\n              -72.45,\n              40.916667\n            ],\n            [\n              -72.45,\n              40.583333\n            ],\n            [\n              -73.333333,\n              40.583333\n            ],\n            [\n              -73.333333,\n              40.916667\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://walrus.wr.usgs.gov/infobank/programs/html/staff2html/staff.html\" target=\"_blank\" data-mce-href=\"https://walrus.wr.usgs.gov/infobank/programs/html/staff2html/staff.html\">Contact Information</a>, Pacific Coastal and Marine Science Center&nbsp;<br>U.S. Geological Survey <br>Pacific Science Center <br>2885 Mission Street <br>Santa Cruz, CA 95060 <br><a href=\"https://walrus.wr.usgs.gov/\" target=\"_blank\" data-mce-href=\"https://walrus.wr.usgs.gov/\">https://walrus.wr.usgs.gov/</a></p>","tableOfContents":"<ul><li>Acknowledgments<br></li><li>Abstract<br></li><li>Introduction<br></li><li>Methods and Data Collected<br></li><li>Results<br></li><li>Summary<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-02-16","noUsgsAuthors":false,"publicationDate":"2017-02-16","publicationStatus":"PW","scienceBaseUri":"58a6c829e4b025c46428625c","contributors":{"authors":[{"text":"La Selle, SeanPaul M. slaselle@usgs.gov","contributorId":5317,"corporation":false,"usgs":true,"family":"La Selle","given":"SeanPaul M.","email":"slaselle@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":668609,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lunghino, Brent D.","contributorId":181566,"corporation":false,"usgs":false,"family":"Lunghino","given":"Brent D.","affiliations":[],"preferred":false,"id":668610,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":668611,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gelfenbaum, Guy","contributorId":79844,"corporation":false,"usgs":true,"family":"Gelfenbaum","given":"Guy","affiliations":[],"preferred":false,"id":668612,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Costa, Pedro J.M.","contributorId":181772,"corporation":false,"usgs":true,"family":"Costa","given":"Pedro","email":"","middleInitial":"J.M.","affiliations":[],"preferred":false,"id":669498,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70181877,"text":"ofr20171012 - 2017 - Mapping land cover through time with the Rapid Land Cover Mapper—Documentation and user manual","interactions":[],"lastModifiedDate":"2017-05-31T16:18:07","indexId":"ofr20171012","displayToPublicDate":"2017-02-15T10:45:00","publicationYear":"2017","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":"2017-1012","title":"Mapping land cover through time with the Rapid Land Cover Mapper—Documentation and user manual","docAbstract":"<p>The Rapid Land Cover Mapper is an Esri ArcGIS® Desktop add-in, which was created as an alternative to automated or semiautomated mapping methods. Based on a manual photo interpretation technique, the tool facilitates mapping over large areas and through time, and produces time-series raster maps and associated statistics that characterize the changing landscapes. The Rapid Land Cover Mapper add-in can be used with any imagery source to map various themes (for instance, land cover, soils, or forest) at any chosen mapping resolution. The user manual contains all essential information for the user to make full use of the Rapid Land Cover Mapper add-in. This manual includes a description of the add-in functions and capabilities, and step-by-step procedures for using the add-in. The Rapid Land Cover Mapper add-in was successfully used by the U.S. Geological Survey West Africa Land Use Dynamics team to accurately map land use and land cover in 17 West African countries through time (1975, 2000, and 2013).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171012","usgsCitation":"Cotillon, S.E., and Mathis, M.L., 2017, Mapping land cover through time with the Rapid Land Cover Mapper—Documentation and user manual: U.S. Geological Survey Open File Report 2017–1012, 23 p., https://doi.org/10.3133/ofr20171012.","productDescription":"Report: vi, 23; Appendix","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":335429,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1012/ofr20171012.pdf","text":"Report","size":"13.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1012"},{"id":335428,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1012/coverthb.jpg"},{"id":335432,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1012/ofr20171012_appendixtable1-1.xlsx","text":"Appendix Table 1–1","size":"18.8 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2017–1012 Appendix Table 1–1"}],"contact":"<p>Director, Earth Resources Observation and Science (EROS) Center <br>U.S. Geological Survey<br>47914 252nd Street <br>Sioux Falls, SD 57198<br></p><p><a href=\"https://eros.usgs.gov/\" data-mce-href=\"https://eros.usgs.gov/\">https://eros.usgs.gov/</a></p>","tableOfContents":"<ul><li>Abstract<br></li><li>Disclaimer<br></li><li>Introduction<br></li><li>Overview<br></li><li>System Requirements<br></li><li>Rapid Land Cover Mapper Installation<br></li><li>Setup and Description of the Rapid Land Cover Mapper<br></li><li>Rapid Land Cover Mapper Tips<br></li><li>Frequently Asked Questions<br></li><li>References Cited<br></li><li>Appendix 1. Classification Systems Included in the Rapid Land Cover Mapper Add-In<br></li><li>Appendix 2. List of the Rapid Land Cover Mapper Projection Files<br></li><li>Appendix 3. Description of the XML File<br></li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2017-02-15","noUsgsAuthors":false,"publicationDate":"2017-02-15","publicationStatus":"PW","scienceBaseUri":"58a576b7e4b057081a24ed08","contributors":{"authors":[{"text":"Cotillon, Suzanne E. 0000-0003-3103-8944 scotillon@usgs.gov","orcid":"https://orcid.org/0000-0003-3103-8944","contributorId":169088,"corporation":false,"usgs":true,"family":"Cotillon","given":"Suzanne","email":"scotillon@usgs.gov","middleInitial":"E.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":668895,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mathis, Melissa L. 0000-0003-4967-4770 mlmathis@usgs.gov","orcid":"https://orcid.org/0000-0003-4967-4770","contributorId":5461,"corporation":false,"usgs":true,"family":"Mathis","given":"Melissa","email":"mlmathis@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":668896,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70178724,"text":"ofr20161199 - 2017 -  Geologic assessment of undiscovered oil and gas resources—Lower Cretaceous Albian to Upper Cretaceous Cenomanian carbonate rocks of the Fredericksburg and Washita Groups, United States Gulf of Mexico Coastal Plain and State Waters","interactions":[],"lastModifiedDate":"2017-02-13T10:46:43","indexId":"ofr20161199","displayToPublicDate":"2017-02-10T15:30:00","publicationYear":"2017","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":"2016-1199","title":" Geologic assessment of undiscovered oil and gas resources—Lower Cretaceous Albian to Upper Cretaceous Cenomanian carbonate rocks of the Fredericksburg and Washita Groups, United States Gulf of Mexico Coastal Plain and State Waters","docAbstract":"<p>In 2010, the U.S. Geological Survey (USGS) assessed Lower Cretaceous Albian to Upper Cretaceous Cenomanian carbonate rocks of the Fredericksburg and Washita Groups and their equivalent units for technically recoverable, undiscovered hydrocarbon resources underlying onshore lands and State Waters of the Gulf Coast region of the United States. This assessment was based on a geologic model that incorporates the Upper Jurassic-Cretaceous-Tertiary Composite Total Petroleum System (TPS) of the Gulf of Mexico basin; the TPS was defined previously by the USGS assessment team in the assessment of undiscovered hydrocarbon resources in Tertiary strata of the Gulf Coast region in 2007. One conventional assessment unit (AU), which extends from south Texas to the Florida panhandle, was defined: the Fredericksburg-Buda Carbonate Platform-Reef Gas and Oil AU. The assessed stratigraphic interval includes the Edwards Limestone of the Fredericksburg Group and the Georgetown and Buda Limestones of the Washita Group. The following factors were evaluated to define the AU and estimate oil and gas resources: potential source rocks, hydrocarbon migration, reservoir porosity and permeability, traps and seals, structural features, paleoenvironments (back-reef lagoon, reef, and fore-reef environments), and the potential for water washing of hydrocarbons near outcrop areas.</p><p>In Texas and Louisiana, the downdip boundary of the AU was defined as a line that extends 10 miles downdip of the Lower Cretaceous shelf margin to include potential reef-talus hydrocarbon reservoirs. In Mississippi, Alabama, and the panhandle area of Florida, where the Lower Cretaceous shelf margin extends offshore, the downdip boundary was defined by the offshore boundary of State Waters. Updip boundaries of the AU were drawn based on the updip extent of carbonate rocks within the assessed interval, the presence of basin-margin fault zones, and the presence of producing wells. Other factors evaluated were the middle Cenomanian sea-level fall and erosion that removed large portions of platform and platform-margin carbonate sediments in the Washita Group of central Louisiana. The production history of discovered reservoirs and well data within the AU were examined to estimate the number and size of undiscovered oil and gas reservoirs within the AU. Using the USGS National Oil and Gas Assessment resource assessment methodology, mean volumes of 40 million barrels of oil, 622 billion cubic feet of gas, and 14 million barrels of natural gas liquids are the estimated technically recoverable undiscovered resources for the Fredericksburg-Buda Carbonate Platform-Reef Gas and Oil AU.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161199","usgsCitation":"Swanson, S.M., Enomoto, C.B., Dennen, K.O., Valentine, B.J., and Cahan, S.M., 2017, Geologic assessment of undiscovered oil and gas resources—Lower Cretaceous Albian to Upper Cretaceous Cenomanian carbonate rocks of the Fredericksburg and Washita Groups, United States Gulf of Mexico Coastal Plain and State Waters: U.S. Geological Survey Open-File Report 2016–1199, 69 p., https://doi.org/10.3133/ofr20161199.","productDescription":"Report: vii, 68 p.; Appendix 1: 2 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064618","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":335075,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1199/ofr20161199.pdf","text":"Report","size":"10.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1199"},{"id":335074,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1199/coverthb.jpg"},{"id":335076,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1199/ofr20161199_appendix1.pdf","text":"Appendix 1 - ","size":"446 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"Input data form for the Fredericksburg-Buda  Carbonate Platform-Reef Gas and Oil Assessment  Unit (50490127)"}],"country":"United States","state":"Alabama, Arkansas, Florida, Louisiana, Mississippi, Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  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       37.78808138412046\n            ],\n            [\n              -89.20898437499999,\n              37.996162679728116\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, Eastern Energy Resources Science Center<br> U.S. Geological Survey<br> Mail Stop 956<br> 12201 Sunrise Valley Drive<br> Reston, VA 20192<br> <a href=\"http://energy.usgs.gov/\" data-mce-href=\"http://energy.usgs.gov/\">http://energy.usgs.gov/</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Stratigraphy of the Fredericksburg and Washita Groups</li><li>Structural Features</li><li>Depositional Framework</li><li>Hydrocarbon Source Rocks</li><li>Reservoir Rocks</li><li>Seals and Traps</li><li>Geologic Model for Assessment of Undiscovered Hydrocarbons</li><li>Boundaries Used to Define Assessment Units</li><li>Estimates of the Numbers and Sizes of Undiscovered Reservoirs</li><li>Assessment Results</li><li>Acknowledgments</li><li>References Cited</li><li>Appendix 1. Input data form for the Fredericksburg-Buda Carbonate Platform-Reef Gas and Oil Assessment Unit (50490127)</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2017-02-10","noUsgsAuthors":false,"publicationDate":"2017-02-10","publicationStatus":"PW","scienceBaseUri":"589edf23e4b099f50d3dc588","contributors":{"authors":[{"text":"Swanson, Sharon M. 0000-0002-4235-1736 smswanson@usgs.gov","orcid":"https://orcid.org/0000-0002-4235-1736","contributorId":590,"corporation":false,"usgs":true,"family":"Swanson","given":"Sharon","email":"smswanson@usgs.gov","middleInitial":"M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":654980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Enomoto, Catherine B. 0000-0002-4119-1953 cenomoto@usgs.gov","orcid":"https://orcid.org/0000-0002-4119-1953","contributorId":2126,"corporation":false,"usgs":true,"family":"Enomoto","given":"Catherine","email":"cenomoto@usgs.gov","middleInitial":"B.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":654981,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dennen, Kristin O. kdennen@usgs.gov","contributorId":177202,"corporation":false,"usgs":true,"family":"Dennen","given":"Kristin","email":"kdennen@usgs.gov","middleInitial":"O.","affiliations":[],"preferred":false,"id":654982,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Valentine, Brett J. 0000-0002-8678-2431 bvalentine@usgs.gov","orcid":"https://orcid.org/0000-0002-8678-2431","contributorId":3846,"corporation":false,"usgs":true,"family":"Valentine","given":"Brett","email":"bvalentine@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":654983,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cahan, Steven M. 0000-0002-4776-3668 scahan@usgs.gov","orcid":"https://orcid.org/0000-0002-4776-3668","contributorId":4529,"corporation":false,"usgs":true,"family":"Cahan","given":"Steven","email":"scahan@usgs.gov","middleInitial":"M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":662920,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70179809,"text":"ofr20171002 - 2017 - Forested floristic quality index: An assessment tool for forested wetland habitats using the quality and quantity of woody vegetation at Coastwide Reference Monitoring System (CRMS) vegetation monitoring stations","interactions":[],"lastModifiedDate":"2017-02-08T11:49:54","indexId":"ofr20171002","displayToPublicDate":"2017-02-08T00:00:00","publicationYear":"2017","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":"2017-1002","title":"Forested floristic quality index: An assessment tool for forested wetland habitats using the quality and quantity of woody vegetation at Coastwide Reference Monitoring System (CRMS) vegetation monitoring stations","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the Coastal Protection and Restoration Authority of Louisiana and the Coastal Wetlands Planning, Protection and Restoration Act, developed the Forested Floristic Quality Index (FFQI) for the Coastwide Reference Monitoring System (CRMS). The FFQI will help evaluate forested wetland sites on a continuum from severely degraded to healthy and will assist in defining areas where forested wetland restoration can be successful by projecting the trajectories of change. At each CRMS forested wetland site there are stations for quantifying the overstory, understory, and herbaceous vegetation layers. Rapidly responding overstory canopy cover and herbaceous layer composition are measured annually, while gradually changing overstory basal area and species composition are collected on a 3-year cycle.</p><p>A CRMS analytical team has tailored these data into an index much like the Floristic Quality Index (FQI) currently used for herbaceous marsh and for the herbaceous layer of the swamp vegetation. The core of the FFQI uses basal area by species to assess the quality and quantity of the overstory at each of three stations within each CRMS forested wetland site. Trees that are considered by experts to be higher quality swamp species like <i>Taxodium distichum</i> (bald cypress) and <i>Nyssa aquatica</i> (water tupelo) are scored higher than tree species like <i>Triadica sebifera</i> (Chinese tallow) and <i>Salix nigra</i> (black willow) that are indicators of recent disturbance. This base FFQI is further enhanced by the percent canopy cover in the overstory and the presence of indicator species at the forest floor. This systemic approach attempts to differentiate between locations with similar basal areas that are on different ecosystem trajectories. Because of these varying states of habitat degradation, paired use of the FQI and the FFQI is useful to interpret the vegetative data in transitional locations. There is often an inverse relation between the health of the overstory and health of the herbaceous community beneath it because of resource competition (for example, light) and differing environmental preferences between the two communities. The herbaceous layer vegetation responds rapidly to basic environmental factors such as flooding, salinity, and nutrients and can offer insight into the sustainability of swamps on a temporal scale shorter than tha of the slowly growing woody vegetation.</p><p>The FFQI will be available via the CRMS spatial viewer (<a href=\"http://lacoast.gov/crms2/home.aspx\" data-mce-href=\"http://lacoast.gov/crms2/home.aspx\">http://lacoast.gov/crms2/home.aspx</a>), and a new score will be calculated annually for each CRMS forested wetland site as data are collected to establish trends, to compare among sites, and to evaluate specific restoration projects when applicable. The FFQI will identify forested wetland areas in need of restoration and conservation and will help define targets and trajectories for restoration planning.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171002","collaboration":"Prepared in cooperation with the Coastal Protection and Restoration Authority of Louisiana and the Coastal Wetlands Planning, Protection and Restoration Act","usgsCitation":"Wood, W.B., Shaffer, G.P., Visser, J.M., Krauss, K.W., Piazza, S.C., Sharp, L.A., and Cretini, K.F., 2017, Forested Floristic Quality Index—An assessment tool for forested wetland habitats using the quality and quantity of woody vegetation at Coastwide Reference Monitoring System (CRMS) vegetation monitoring stations: U.S. Geological Survey Open-File Report 2017–1002, 15 p., https://doi.org/10.3133/ofr20171002.","productDescription":"iv, 15 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PSC"},"publishedDate":"2017-02-08","noUsgsAuthors":false,"publicationDate":"2017-02-08","publicationStatus":"PW","scienceBaseUri":"589c3c39e4b0efcedb740ffd","contributors":{"authors":[{"text":"Wood, William B.","contributorId":149675,"corporation":false,"usgs":false,"family":"Wood","given":"William","email":"","middleInitial":"B.","affiliations":[{"id":17778,"text":"Coastal Protection and Restoration Authority of Louisiana","active":true,"usgs":false}],"preferred":false,"id":658784,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shaffer, Gary P.","contributorId":178419,"corporation":false,"usgs":false,"family":"Shaffer","given":"Gary","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":658788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Visser, Jenneke 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,{"id":70180215,"text":"ofr20161213 - 2017 - Updated operational protocols for the U.S. Geological Survey Precipitation Chemistry Quality Assurance Project in support of the National Atmospheric Deposition Program","interactions":[],"lastModifiedDate":"2019-06-05T07:38:31","indexId":"ofr20161213","displayToPublicDate":"2017-02-06T11:00:00","publicationYear":"2017","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":"2016-1213","title":"Updated operational protocols for the U.S. Geological Survey Precipitation Chemistry Quality Assurance Project in support of the National Atmospheric Deposition Program","docAbstract":"<p>The U.S. Geological Survey Branch of Quality Systems operates the Precipitation Chemistry Quality Assurance Project (PCQA) for the National Atmospheric Deposition Program/National Trends Network (NADP/NTN) and National Atmospheric Deposition Program/Mercury Deposition Network (NADP/MDN). Since 1978, various programs have been implemented by the PCQA to estimate data variability and bias contributed by changing protocols, equipment, and sample submission schemes within NADP networks. These programs independently measure the field and laboratory components which contribute to the overall variability of NADP wet-deposition chemistry and precipitation depth measurements. The PCQA evaluates the quality of analyte-specific chemical analyses from the two, currently (2016) contracted NADP laboratories, Central Analytical Laboratory and Mercury Analytical Laboratory, by comparing laboratory performance among participating national and international laboratories. Sample contamination and stability are evaluated for NTN and MDN by using externally field-processed blank samples provided by the Branch of Quality Systems. A colocated sampler program evaluates the overall variability of NTN measurements and bias between dissimilar precipitation gages and sample collectors.</p><p>This report documents historical PCQA operations and general procedures for each of the external quality-assurance programs from 2007 to 2016.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161213","usgsCitation":"Wetherbee, G.A., and Martin, RoseAnn, 2017, Updated operational protocols for the U.S. Geological Survey Precipitation Chemistry Quality Assurance Project in support of the National Atmospheric Deposition Program: U.S. Geological  Survey Open-File Report 2016–1213, 18 p., https://doi.org/10.3133/ofr20161213.","productDescription":"v, 18 p.","onlineOnly":"Y","ipdsId":"IP-071130","costCenters":[{"id":143,"text":"Branch of Quality 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USGS Branch of Quality Systems<br>Box 25046, Mail Stop 401<br>Denver, CO 80225</p><p><a href=\"http://bqs.usgs.gov/\" data-mce-href=\"http://bqs.usgs.gov/\">http://bqs.cr.usgs.gov/</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Background</li><li>Field Quality-Assurance Programs</li><li>Interlaboratory-Comparison Programs</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2017-02-06","noUsgsAuthors":false,"publicationDate":"2017-02-06","publicationStatus":"PW","scienceBaseUri":"58999942e4b0efcedb71a085","contributors":{"authors":[{"text":"Wetherbee, Gregory A. 0000-0002-6720-2294 wetherbe@usgs.gov","orcid":"https://orcid.org/0000-0002-6720-2294","contributorId":1044,"corporation":false,"usgs":true,"family":"Wetherbee","given":"Gregory","email":"wetherbe@usgs.gov","middleInitial":"A.","affiliations":[{"id":143,"text":"Branch of Quality Systems","active":true,"usgs":true}],"preferred":true,"id":660789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, RoseAnn ramartin@usgs.gov","contributorId":5367,"corporation":false,"usgs":true,"family":"Martin","given":"RoseAnn","email":"ramartin@usgs.gov","affiliations":[{"id":143,"text":"Branch of Quality Systems","active":true,"usgs":true}],"preferred":true,"id":660790,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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