{"pageNumber":"1414","pageRowStart":"35325","pageSize":"25","recordCount":165227,"records":[{"id":70047814,"text":"70047814 - 2013 - Landscape-level estimation of nitrogen removal in coastal Louisiana wetlands: potential sinks under different restoration scenarios","interactions":[],"lastModifiedDate":"2017-01-12T11:40:25","indexId":"70047814","displayToPublicDate":"2013-08-26T08:32:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Landscape-level estimation of nitrogen removal in coastal Louisiana wetlands: potential sinks under different restoration scenarios","docAbstract":"<p><span>Coastal eutrophication in the northern Gulf of Mexico (GOM) is the primary anthropogenic contributor to the largest zone of hypoxic bottom waters in North America. Although biologically mediated processes such as denitrification (Dn) are known to act as sinks for inorganic nitrogen, it is unknown what contribution denitrification makes to landscape-scale nitrogen budgets along the coast. As the State of Louisiana plans the implementation of a 2012 Coastal Master Plan (MP) to help restore its wetlands and protect its coast, it is critical to understand what effect potential restoration projects may have in altering nutrient budgets. As part of the MP, a spatial statistical approach was developed to estimate nitrogen removal under varying scenarios of future conditions and coastal restoration project implementation. In every scenario of future conditions under which MP implementation was modeled, more nitrogen (</span><span class=\"NLM_inline-graphic\"><img src=\"http://www.bioone.org/na101/home/literatum/publisher/bioone/journals/content/coas/2013/15515036-67.sp1/si_67_6/20130814/images/medium/i1551-5036-67-sp1-75-ilm01.gif\" alt=\"\" data-mce-src=\"http://www.bioone.org/na101/home/literatum/publisher/bioone/journals/content/coas/2013/15515036-67.sp1/si_67_6/20130814/images/medium/i1551-5036-67-sp1-75-ilm01.gif\"></span><span>) was removed from coastal waters when compared with conditions under which no action is taken. Overall, the MP increased coast-wide average nitrogen removal capacity (NRC) rates by up to 0.55 g N m</span><sup>−2</sup><span> y</span><sup>−1</sup><span> compared with the “future without action” (FWOA) scenario, resulting in a conservative estimate of up to 25% removal of the annual</span><span class=\"NLM_inline-graphic\"><img src=\"http://www.bioone.org/na101/home/literatum/publisher/bioone/journals/content/coas/2013/15515036-67.sp1/si_67_6/20130814/images/medium/i1551-5036-67-sp1-75-ilm12.gif\" alt=\"\" data-mce-src=\"http://www.bioone.org/na101/home/literatum/publisher/bioone/journals/content/coas/2013/15515036-67.sp1/si_67_6/20130814/images/medium/i1551-5036-67-sp1-75-ilm12.gif\"></span><span> +</span><span class=\"NLM_inline-graphic\"><img src=\"http://www.bioone.org/na101/home/literatum/publisher/bioone/journals/content/coas/2013/15515036-67.sp1/si_67_6/20130814/images/medium/i1551-5036-67-sp1-75-ilm23.gif\" alt=\"\" data-mce-src=\"http://www.bioone.org/na101/home/literatum/publisher/bioone/journals/content/coas/2013/15515036-67.sp1/si_67_6/20130814/images/medium/i1551-5036-67-sp1-75-ilm23.gif\"></span><span> load of the Mississippi-Atchafalaya rivers (956,480 t y</span><sup>−1</sup><span>). These results are spatially correlated, with the lower Mississippi River and Chenier Plain exhibiting the greatest change in NRC. Since the implementation of the MP can maintain, and in some regions increase the NRC, our results show the need to preserve the functionality of wetland habitats and use this ecosystem service (</span><i>i.e</i><span>. Dn) to decrease eutrophication of the GOM.</span></p>","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/SI_67_6","usgsCitation":"Rivera-Monroy, V., Branoff, B., Meselhe, E., McCorquodale, A., Dortch, M., Steyer, G.D., Visser, J., and Wang, H., 2013, Landscape-level estimation of nitrogen removal in coastal Louisiana wetlands: potential sinks under different restoration scenarios: Journal of Coastal Research, v. Summer 2013, p. 75-87, https://doi.org/10.2112/SI_67_6.","productDescription":"13 p.","startPage":"75","endPage":"87","numberOfPages":"13","ipdsId":"IP-042639","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":276978,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.0434,28.9254 ], [ -94.0434,30.8379 ], [ -88.8162,30.8379 ], [ -88.8162,28.9254 ], [ -94.0434,28.9254 ] ] ] } } ] }","volume":"Summer 2013","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521c6adde4b01458f7842907","contributors":{"authors":[{"text":"Rivera-Monroy, Victor H.","contributorId":34198,"corporation":false,"usgs":true,"family":"Rivera-Monroy","given":"Victor H.","affiliations":[],"preferred":false,"id":483034,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Branoff, Benjamin","contributorId":99874,"corporation":false,"usgs":true,"family":"Branoff","given":"Benjamin","affiliations":[],"preferred":false,"id":483038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meselhe, Ehab","contributorId":95333,"corporation":false,"usgs":true,"family":"Meselhe","given":"Ehab","email":"","affiliations":[],"preferred":false,"id":483037,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCorquodale, Alex","contributorId":53685,"corporation":false,"usgs":true,"family":"McCorquodale","given":"Alex","email":"","affiliations":[],"preferred":false,"id":483036,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dortch, Mark","contributorId":15507,"corporation":false,"usgs":true,"family":"Dortch","given":"Mark","email":"","affiliations":[],"preferred":false,"id":483033,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Steyer, Gregory D. 0000-0001-7231-0110 steyerg@usgs.gov","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":2856,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","email":"steyerg@usgs.gov","middleInitial":"D.","affiliations":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":483031,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Visser, Jenneke","contributorId":40504,"corporation":false,"usgs":true,"family":"Visser","given":"Jenneke","affiliations":[],"preferred":false,"id":483035,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":4421,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":483032,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70047819,"text":"sir20135065 - 2013 - Effects of surface applications of biosolids on groundwater quality and trace-element concentrations in crops near Deer Trail, Colorado, 2004-2010","interactions":[],"lastModifiedDate":"2025-05-14T19:19:14.041259","indexId":"sir20135065","displayToPublicDate":"2013-08-26T08:04:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5065","title":"Effects of surface applications of biosolids on groundwater quality and trace-element concentrations in crops near Deer Trail, Colorado, 2004-2010","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with Metro Wastewater Reclamation District (Metro District), studied biosolids composition and the effects of biosolids applications on groundwater quality and trace-element concentrations in crops of the Metro District properties near Deer Trail, Colorado, during 2004 through 2010. Priority parameters for each monitoring component included the nine trace elements regulated by Colorado for biosolids (arsenic, cadmium, copper, lead, mercury, molybdenum, nickel, selenium, and zinc); other constituents also were analyzed. All concentrations for the priority parameters in monthly biosolids samples were less than Colorado regulatory limits, and the concentrations were relatively consistent. Biosolids likely were the largest source of nitrogen and phosphorus on the Metro District properties. Plutonium isotopes were not detected in the biosolids, but many organic wastewater compounds (organic wastewater compounds: wastewater indicators, pharmaceuticals, and hormones) were detected in substantial concentrations relative to minimum reporting levels and various surface-water concentrations. Bismuth, copper, mercury, nitrogen, phosphorus, silver, biogenic sterols, detergent degradates, disinfectants, fire retardants, fragrances, pharmaceuticals, and plasticizers would be the most likely biosolids signature to indicate the presence of Metro District biosolids in soil or streambed sediment from the study area. Antimony, cadmium, cobalt, copper, molybdenum, nickel, nitrogen, phosphorus, selenium, tungsten, vanadium, zinc, detergent degradates, disinfectants, fire retardants, fragrances, pharmaceuticals or their degradates, and plasticizers would be the most likely biosolids signature for groundwater and surface water in the study area. More biosolids-signature components detected and larger concentration differences from untreated materials, baseline, and blank samples indicate more evidence of biosolids presence or effects. Although the inorganic constituent concentrations were relatively large in samples from one monitoring well, the concentrations of organic wastewater compounds in groundwater samples were not correspondingly large. Concentrations of organic wastewater compounds in the groundwater samples from all five monitoring wells were less than the minimum reporting levels with only a few detections. Some of the organic wastewater compounds detected could have anthropogenic sources that are not biosolids. Concentrations of priority parameters in groundwater varied spatially and temporally but generally were less than Colorado regulatory limits. Concentrations of dissolved nitrate, arsenic, and selenium, in addition to chloride, sulfate, total dissolved solids, boron, iron, manganese, and uranium, in samples from some wells exceeded the Colorado standards. Concentrations of dissolved nitrate (three wells), molybdenum (one well), selenium (two wells), and uranium (one well) in shallow groundwater had significant (alpha = 0.05) upward trends in some parts of the study area. The biosolids-signature results indicate that the aquifers intercepted by the five routinely sampled wells likely have received some recharge through treated (biosolids-applied) fields or biosolids-affected ponds. Adverse effects from this biosolids-related recharge range from few (if any) at one well to large and significantly (alpha = 0.05) increasing nitrate concentrations at another well. A statistical evaluation of five paired wheat-grain samples from treated (biosolids-applied) fields and untreated (control) fields did not indicate any evidence that biosolids applications significantly (alpha = 0.05 or 0.10) increased concentration of any of these constituents in wheat grain. The wheat-grain concentrations from this study were similar to those from other studies for fields in North America where no biosolids were applied. The data for the limited crop samples indicate that biosolids applications are not increasing the concentrations of arsenic, cadmium, copper, lead, mercury, molybdenum, nickel, selenium, sulfur, and zinc in mature wheat grain from the study area.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135065","collaboration":"Prepared in cooperation with the Metro Wastewater Reclamation District","usgsCitation":"Yager, T., Crock, J.G., Smith, D., Furlong, E.T., Hageman, P.L., Foreman, W., Gray, J.L., and ReVello, R., 2013, Effects of surface applications of biosolids on groundwater quality and trace-element concentrations in crops near Deer Trail, Colorado, 2004-2010: U.S. Geological Survey Scientific Investigations Report 2013-5065, vi, 119 p., https://doi.org/10.3133/sir20135065.","productDescription":"vi, 119 p.","numberOfPages":"129","onlineOnly":"Y","temporalStart":"2004-01-01","temporalEnd":"2010-12-01","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"links":[{"id":276976,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5065/SIR13-5065.pdf"},{"id":276975,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5065/"},{"id":276977,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135065.png"}],"country":"United States","state":"Colorado","city":"Deer Trail","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -105.5,38.75 ], [ -105.5,40.5 ], [ -103.0,40.5 ], [ -103.0,38.75 ], [ -105.5,38.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521c6adae4b01458f78428f7","contributors":{"authors":[{"text":"Yager, Tracy J.B.","contributorId":10861,"corporation":false,"usgs":true,"family":"Yager","given":"Tracy J.B.","affiliations":[],"preferred":false,"id":483059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crock, James G. jcrock@usgs.gov","contributorId":200,"corporation":false,"usgs":true,"family":"Crock","given":"James","email":"jcrock@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":483052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, David B. 0000-0001-8396-9105 dsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-8396-9105","contributorId":1274,"corporation":false,"usgs":true,"family":"Smith","given":"David B.","email":"dsmith@usgs.gov","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":483056,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Furlong, Edward T. 0000-0002-7305-4603 efurlong@usgs.gov","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":740,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","email":"efurlong@usgs.gov","middleInitial":"T.","affiliations":[{"id":191,"text":"Colorado Water Science Center","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":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":483053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hageman, Philip L. 0000-0002-3440-2150 phageman@usgs.gov","orcid":"https://orcid.org/0000-0002-3440-2150","contributorId":811,"corporation":false,"usgs":true,"family":"Hageman","given":"Philip","email":"phageman@usgs.gov","middleInitial":"L.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":483054,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foreman, William T. wforeman@usgs.gov","contributorId":1473,"corporation":false,"usgs":true,"family":"Foreman","given":"William T.","email":"wforeman@usgs.gov","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":false,"id":483057,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gray, James L. 0000-0002-0807-5635 jlgray@usgs.gov","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":1253,"corporation":false,"usgs":true,"family":"Gray","given":"James","email":"jlgray@usgs.gov","middleInitial":"L.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":483055,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"ReVello, Rhiannon C. rcrevell@usgs.gov","contributorId":4128,"corporation":false,"usgs":true,"family":"ReVello","given":"Rhiannon C.","email":"rcrevell@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":483058,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70177027,"text":"70177027 - 2013 - Predicting the toxicity of metal mixtures","interactions":[],"lastModifiedDate":"2016-10-19T15:36:08","indexId":"70177027","displayToPublicDate":"2013-08-25T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Predicting the toxicity of metal mixtures","docAbstract":"The toxicity of single and multiple metal (Cd, Cu, Pb, and Zn) solutions to trout is predicted using an approach that combines calculations of: (1) solution speciation; (2) competition and accumulation of cations (H, Ca, Mg, Na, Cd, Cu, Pb, and Zn) on low abundance, high affinity and high abundance, low affinity biotic ligand sites; (3) a toxicity function that accounts for accumulation and potency of individual toxicants; and (4) biological response.  The approach is evaluated by examining water composition from single metal toxicity tests of trout at 50% mortality, results of theoretical calculations of metal accumulation on fish gills and associated mortality for single, binary, ternary, and quaternary metal solutions, and predictions for a field site impacted by acid rock drainage.  These evaluations indicate that toxicity of metal mixtures depends on the relative affinity and potency of toxicants for a given aquatic organism, suites of metals in the mixture, dissolved metal concentrations and ratios, and background solution composition (temperature, pH, and concentrations of major ions and dissolved organic carbon).  A composite function that incorporates solution composition, affinity and competition of cations for two types of biotic ligand sites, and potencies of hydrogen and individual metals is proposed as a tool to evaluate potential toxicity of environmental solutions to trout.","language":"English","publisher":"Elsevier B.V.","doi":"10.1016/j.scitotenv.2013.07.034","usgsCitation":"Balistrieri, L.S., and Mebane, C.A., 2013, Predicting the toxicity of metal mixtures: Science of the Total Environment, v. 466-467, p. 788-799, https://doi.org/10.1016/j.scitotenv.2013.07.034.","productDescription":"12 p.","startPage":"788","endPage":"799","ipdsId":"IP-049206","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":329770,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"466-467","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58088688e4b0f497e78e24d5","contributors":{"authors":[{"text":"Balistrieri, Laurie S. 0000-0002-6359-3849 balistri@usgs.gov","orcid":"https://orcid.org/0000-0002-6359-3849","contributorId":1406,"corporation":false,"usgs":true,"family":"Balistrieri","given":"Laurie","email":"balistri@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":651035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":651036,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047813,"text":"ofr20131122 - 2013 - User’s guide and reference to Ash3d—A three-dimensional model for Eulerian atmospheric tephra transport and deposition","interactions":[],"lastModifiedDate":"2021-04-16T11:44:27.105677","indexId":"ofr20131122","displayToPublicDate":"2013-08-23T16:19:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1122","displayTitle":"User’s Guide and Reference to Ash3d—A Three-Dimensional Model for Eulerian Atmospheric Tephra Transport and Deposition","title":"User’s guide and reference to Ash3d—A three-dimensional model for Eulerian atmospheric tephra transport and deposition","docAbstract":"<p>Ash3d is a three-dimensional Eulerian atmospheric model for tephra transport, dispersal, and deposition to study and forecast hazards of volcanic ash clouds and tephra fall. In this report, we explain how to set up simulations using a web interface, and how to view and interpret model output. We also summarize the architecture of the model and some of its properties.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131122","usgsCitation":"Mastin, L.G., Randall, M.J., Schwaiger, H.F., and Denlinger, R.P., 2021, User’s guide and reference to the web interface of Ash3d—A three-dimensional model for Eulerian atmospheric tephra transport and deposition (ver. 2.0, April 2021): U.S. Geological Survey Open-File Report 2013–1122, 25 p., https://doi.org/10.3133/ofr20131122.","productDescription":"Report: viii, 25 p.; Version History","numberOfPages":"25","onlineOnly":"Y","ipdsId":"IP-112934","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":276973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2013/1122/covrthb.jpg"},{"id":276972,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1122/ofr20131122.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":385065,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2013/1122/versionHist.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"}}],"edition":"Version 1.0:May 2013; Version 2.0: April 2021","contact":"<p><a href=\"mailto:yvowebteam@usgs.gov\" data-mce-href=\"mailto:yvowebteam@usgs.gov\">Contact YVO</a><br><a href=\"https://volcanoes.usgs.gov/yvo/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://volcanoes.usgs.gov/yvo/\">Volcano Science Center, Yellowstone Volcano Observatory</a><br>U.S. Geological Survey<br>345 Middlefield Road, MS 910<br>Menlo Park, CA 94025</p>","tableOfContents":"<ul><li>Abstract&nbsp;&nbsp;</li><li>Introduction&nbsp;&nbsp;</li><li>Model Overview&nbsp;&nbsp;</li><li>Examples of Model Output&nbsp;&nbsp;</li><li>The Web Interface&nbsp;&nbsp;</li><li>Accessing the Interface&nbsp;&nbsp;</li><li>Creating a New Job&nbsp;&nbsp;</li><li>Entering Source Parameters&nbsp;&nbsp;</li><li>Running the Model&nbsp;&nbsp;</li><li>Model Results Page&nbsp;&nbsp;</li><li>Model Output Files&nbsp;&nbsp;</li><li>Limitations of the Graphical User Interface (GUI)&nbsp;&nbsp;</li><li>Concluding Remarks&nbsp;&nbsp;&nbsp;</li><li>References Cited&nbsp;&nbsp;</li><li>Appendix</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2013-08-23","revisedDate":"2021-04-13","noUsgsAuthors":false,"publicationDate":"2013-08-23","publicationStatus":"PW","scienceBaseUri":"5218765fe4b0e27b926cc671","contributors":{"authors":[{"text":"Mastin, Larry G. 0000-0002-4795-1992 lgmastin@usgs.gov","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":555,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"lgmastin@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":483027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Randall, Michael J. 0000-0001-7750-9612","orcid":"https://orcid.org/0000-0001-7750-9612","contributorId":44819,"corporation":false,"usgs":true,"family":"Randall","given":"Michael J.","affiliations":[],"preferred":false,"id":483030,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwaiger, Hans F. 0000-0001-7397-8833 hschwaiger@usgs.gov","orcid":"https://orcid.org/0000-0001-7397-8833","contributorId":4108,"corporation":false,"usgs":true,"family":"Schwaiger","given":"Hans","email":"hschwaiger@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":483029,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Denlinger, Roger P. 0000-0003-0930-0635 roger@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-0635","contributorId":2679,"corporation":false,"usgs":true,"family":"Denlinger","given":"Roger","email":"roger@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":483028,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70047811,"text":"70047811 - 2013 - Leaf gas exchange and nutrient use efficiency help explain the distribution of two Neotropical mangroves under contrasting flooding and salinity","interactions":[],"lastModifiedDate":"2013-08-23T16:16:31","indexId":"70047811","displayToPublicDate":"2013-08-23T15:34:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2043,"text":"International Journal of Forestry Research","active":true,"publicationSubtype":{"id":10}},"title":"Leaf gas exchange and nutrient use efficiency help explain the distribution of two Neotropical mangroves under contrasting flooding and salinity","docAbstract":"Rhizophora mangle and Laguncularia racemosa co-occur along many intertidal floodplains in the Neotropics. Their patterns of dominance shift along various gradients, coincident with salinity, soil fertility, and tidal flooding. We used leaf gas exchange metrics to investigate the strategies of these two species in mixed culture to simulate competition under different salinity concentrations and hydroperiods. Semidiurnal tidal and permanent flooding hydroperiods at two constant salinity regimes (10 g L<sup>−1</sup> and 40 g L<sup>−1</sup>) were simulated over 10 months. Assimilation (A), stomatal conductance (g<sub>w</sub>), intercellular CO<sub>2</sub> concentration (C<sub>i</sub>), instantaneous photosynthetic water use efficiency (PWUE), and photosynthetic nitrogen use efficiency (PNUE) were determined at the leaf level for both species over two time periods. Rhizophora mangle had significantly higher PWUE than did L. racemosa seedlings at low salinities; however, L. racemosa had higher PNUE and stomatal conductance and g<sub>w</sub>, accordingly, had greater intercellular CO<sub>2</sub> (calculated) during measurements. Both species maintained similar capacities for assimilation at 10 and 40 g L−1 salinity and during both permanent and tidal hydroperiod treatments. Hydroperiod alone had no detectable effect on leaf gas exchange. However, PWUE increased and PNUE decreased for both species at 40 g L<sup>−1</sup> salinity compared to 10 g L<sup>−1</sup>. At 40 g L<sup>−1</sup> salinity, PNUE was higher for L. racemosa than R. mangle with tidal flooding. These treatments indicated that salinity influences gas exchange efficiency, might affect how gases are apportioned intercellularly, and accentuates different strategies for distributing leaf nitrogen to photosynthesis for these two species while growing competitively.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Forestry Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Hindawi Publishing Corporation","doi":"10.1155/2013/524625","usgsCitation":"Cardona-Olarte, P., Krauss, K.W., and Twilley, R.R., 2013, Leaf gas exchange and nutrient use efficiency help explain the distribution of two Neotropical mangroves under contrasting flooding and salinity: International Journal of Forestry Research, 10 p., https://doi.org/10.1155/2013/524625.","productDescription":"10 p.","numberOfPages":"10","ipdsId":"IP-045543","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":473589,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1155/2013/524625","text":"Publisher Index Page"},{"id":276970,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276969,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1155/2013/524625"}],"country":"United States","state":"Florida;Louisiana","city":"Lafayette","otherGeospatial":"Terra Ceia Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.2134,27.2767 ], [ -92.2134,30.4332 ], [ -82.3077,30.4332 ], [ -82.3077,27.2767 ], [ -92.2134,27.2767 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5218765ee4b0e27b926cc669","contributors":{"authors":[{"text":"Cardona-Olarte, Pablo","contributorId":48081,"corporation":false,"usgs":true,"family":"Cardona-Olarte","given":"Pablo","email":"","affiliations":[],"preferred":false,"id":483026,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","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":483024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Twilley, Robert R.","contributorId":34585,"corporation":false,"usgs":false,"family":"Twilley","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":483025,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70047810,"text":"70047810 - 2013 - Forecasting the effects of coastal protection and restoration projects on wetland morphology in coastal Louisiana under multiple environmental uncertainty scenarios","interactions":[],"lastModifiedDate":"2019-06-05T14:53:28","indexId":"70047810","displayToPublicDate":"2013-08-23T14:13:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting the effects of coastal protection and restoration projects on wetland morphology in coastal Louisiana under multiple environmental uncertainty scenarios","docAbstract":"Few landscape scale models have assessed the effects of coastal protection and restoration projects on wetland morphology while taking into account important uncertainties in environmental factors such as sea-level rise (SLR) and subsidence. In support of Louisiana's 2012 Coastal Master Plan, we developed a spatially explicit wetland morphology model and coupled it with other predictive models. The model is capable of predicting effects of protection and restoration projects on wetland area, landscape configuration, surface elevation, and soil organic carbon (SOC) storage under multiple environmental uncertainty scenarios. These uncertainty scenarios included variability in parameters such as eustatic SLR (ESLR), subsidence rate, and Mississippi River discharge. Models were run for a 2010–2060 simulation period. Model results suggest that under a “future-without-action” condition (FWOA), coastal Louisiana is at risk of losing between 2118 and 4677 km<sup>2</sup> of land over the next 50 years, but with protection and restoration projects proposed in the Master Plan, between 40% and 75% of that loss could be mitigated. Moreover, model results indicate that under a FWOA condition, SOC storage (to a depth of 1 m) could decrease by between 108 and 250 million metric tons, a loss of 12% to 30% of the total coastwide SOC, but with the Master Plan implemented, between 35% and 74% of the SOC loss could be offset. Long-term maintenance of project effects was best attained in areas of low SLR and subsidence, with a sediment source to support marsh accretion. Our findings suggest that despite the efficacy of restoration projects in mitigating losses in certain areas, net loss of wetlands in coastal Louisiana is likely to continue. Model results suggest certain areas may eventually be lost regardless of proposed restoration investment, and, as such, other techniques and strategies of adaptation may have to be utilized in these areas.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Coastal Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Coastal Restoration and Research Foundation","doi":"10.2112/SI_67_3","usgsCitation":"Couvillion, B.R., Steyer, G.D., Wang, H., Beck, H.J., and Rybczyk, J.M., 2013, Forecasting the effects of coastal protection and restoration projects on wetland morphology in coastal Louisiana under multiple environmental uncertainty scenarios: Journal of Coastal Research, p. 29-50, https://doi.org/10.2112/SI_67_3.","productDescription":"23 p.","startPage":"29","endPage":"50","numberOfPages":"23","ipdsId":"IP-042243","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":276965,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2112/SI_67_3"},{"id":276968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.0434,28.9254 ], [ -94.0434,30.8191 ], [ -88.8162,30.8191 ], [ -88.8162,28.9254 ], [ -94.0434,28.9254 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5218765ee4b0e27b926cc665","contributors":{"authors":[{"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":483020,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Steyer, Gregory D. 0000-0001-7231-0110 steyerg@usgs.gov","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":2856,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","email":"steyerg@usgs.gov","middleInitial":"D.","affiliations":[{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"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":483019,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":4421,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":483021,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beck, Holly J. 0000-0002-0567-9329 hbeck@usgs.gov","orcid":"https://orcid.org/0000-0002-0567-9329","contributorId":5454,"corporation":false,"usgs":true,"family":"Beck","given":"Holly","email":"hbeck@usgs.gov","middleInitial":"J.","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":483022,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rybczyk, John M.","contributorId":89794,"corporation":false,"usgs":true,"family":"Rybczyk","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":483023,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70047807,"text":"ds779 - 2013 - Dissolved pesticide concentrations in the Sacramento-San Joaquin Delta and Grizzly Bay, California, 2011-12","interactions":[],"lastModifiedDate":"2017-10-30T12:18:48","indexId":"ds779","displayToPublicDate":"2013-08-23T12:49:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"779","title":"Dissolved pesticide concentrations in the Sacramento-San Joaquin Delta and Grizzly Bay, California, 2011-12","docAbstract":"Surface-water samples were collected from sites within the Sacramento-San Joaquin Delta and Grizzly Bay, California, during the spring in 2011 and 2012, and they were analyzed by the U.S. Geological Survey for a suite of 99 current-use pesticides and pesticide degradates. Samples were collected and analyzed as part of a collaborative project studying the occurrence and characteristics of phytoplankton in the San Francisco Estuary. Samples were analyzed by two separate laboratory methods employing gas chromatography/mass spectrometry or liquid chromatography with tandem mass spectrometry. Method detection limits ranged from 0.9 to 10.5 nanograms per liter (ng/L). Eighteen pesticides were detected in samples collected during 2011, and the most frequently detected compounds were the herbicides clomazone, diuron, hexazinone and metolachlor, and the diuron degradates 3,4-dichloroaniline and N-(3,4-dichlorophenyl)-N’-methylurea (DCPMU). Concentrations for all compounds were less than 75 ng/L, except for the rice herbicide clomazone and the fungicide tetraconazole, which had maximum concentrations of 535 and 511 ng/L, respectively. In samples collected in 2012, a total of 16 pesticides were detected. The most frequently detected compounds were the fungicides azoxystrobin and boscalid and the herbicides diuron, hexazinone, metolachlor, and simazine. Maximum concentrations for all compounds detected in 2012 were less than 75 ng/L, except for the fungicide azoxystrobin and the herbicides hexazinone and simazine, which were detected at up to 188, 134, and 140 ng/L, respectively.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds779","collaboration":"Prepared in cooperation with the San Luis and Delta Mendota Water Authority","usgsCitation":"Orlando, J., McWayne, M., Sanders, C., and Hladik, M., 2013, Dissolved pesticide concentrations in the Sacramento-San Joaquin Delta and Grizzly Bay, California, 2011-12: U.S. Geological Survey Data Series 779, viii, 24 p., https://doi.org/10.3133/ds779.","productDescription":"viii, 24 p.","numberOfPages":"36","temporalStart":"2011-01-01","temporalEnd":"2012-12-31","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":276961,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds779.jpg"},{"id":276959,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/779/"},{"id":276960,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/779/pdf/ds779.pdf"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin Delta;Grizzly Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.5,37.75 ], [ -122.5,38.75 ], [ -121.0,38.75 ], [ -121.0,37.75 ], [ -122.5,37.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5218765de4b0e27b926cc661","contributors":{"authors":[{"text":"Orlando, James L. 0000-0002-0099-7221","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":95954,"corporation":false,"usgs":true,"family":"Orlando","given":"James L.","affiliations":[],"preferred":false,"id":483010,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McWayne, Megan 0000-0001-8069-6420","orcid":"https://orcid.org/0000-0001-8069-6420","contributorId":36038,"corporation":false,"usgs":true,"family":"McWayne","given":"Megan","affiliations":[],"preferred":false,"id":483007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sanders, Corey 0000-0001-7743-6396","orcid":"https://orcid.org/0000-0001-7743-6396","contributorId":39682,"corporation":false,"usgs":true,"family":"Sanders","given":"Corey","affiliations":[],"preferred":false,"id":483008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hladik, Michelle 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":45990,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","affiliations":[],"preferred":false,"id":483009,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70047776,"text":"fs20133053 - 2013 - The 3D Elevation Program: summary for Idaho","interactions":[],"lastModifiedDate":"2016-08-17T16:10:36","indexId":"fs20133053","displayToPublicDate":"2013-08-23T08:33:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3053","title":"The 3D Elevation Program: summary for Idaho","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Idaho, elevation data are critical for agriculture and precision farming, natural resources conservation, infrastructure and construction management, geologic resource assessment and hazard mitigation, flood risk management, forest resources management, and other business uses. Today, high-quality light detection and ranging (lidar) data are the sources for creating elevation models and other elevation datasets. Federal, State, and local agencies work in partnership to (1) replace data, on a national basis, that are (on average) 30 years old and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The new 3D Elevation Program (3DEP) initiative, managed by the U.S. Geological Survey (USGS), responds to the growing need for high-quality topographic data and a wide range of other three-dimensional representations of the Nation&rsquo;s natural and constructed features. The Idaho LiDAR Consortium provides statewide collaboration and data sharing mechanisms that can be used as a resource by State and Federal partners implementing the 3DEP initiative.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133053","usgsCitation":"Carswell, W., 2013, The 3D Elevation Program: summary for Idaho: U.S. Geological Survey Fact Sheet 2013-3053, 2 p., https://doi.org/10.3133/fs20133053.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":276928,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133053.gif"},{"id":276926,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3053/"},{"id":276927,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3053/pdf/fs2013-3053.pdf","text":"Report","size":"225 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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":482943,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70047771,"text":"70047771 - 2013 - Analysis of long-term trends (1950–2009) in precipitation, runoff and runoff coefficient in major urban watersheds in the United States","interactions":[],"lastModifiedDate":"2013-08-23T08:01:31","indexId":"70047771","displayToPublicDate":"2013-08-23T07:47:33","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Analysis of long-term trends (1950–2009) in precipitation, runoff and runoff coefficient in major urban watersheds in the United States","docAbstract":"This study investigates the long-term trends in precipitation, runoff and runoff coefficient in major urban watersheds in the United States. The seasonal Mann–Kendall trend test was performed on monthly precipitation, runoff and runoff coefficient data from 1950 to 2009 obtained from 62 urban watersheds covering 21 major urban centers in the United States. The results indicate that only five out of 21 urban centers in the United States showed an uptrend in precipitation. Twelve urban centers showed an uptrend in runoff coefficient. However, six urban centers did not show any trend in runoff coefficient, and three urban centers showed a significant downtrend. The highest rate of change in precipitation, runoff and runoff coefficient was observed in the Houston urban watershed. Based on the results obtained, we also attributed plausible causes for the trends. Our analysis indicated that while a human only influence is observed in most of the urban watersheds, a combined climate and human influence is observed in the central United States.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/8/2/024020","usgsCitation":"Velpuri, N., and Senay, G., 2013, Analysis of long-term trends (1950–2009) in precipitation, runoff and runoff coefficient in major urban watersheds in the United States: Environmental Research Letters, v. 8, no. 2, Article number 024020, https://doi.org/10.1088/1748-9326/8/2/024020.","productDescription":"Article number 024020","ipdsId":"IP-042785","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473590,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/8/2/024020","text":"Publisher Index Page"},{"id":276912,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1088/1748-9326/8/2/024020"},{"id":276925,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 173.0,16.916667 ], [ 173.0,71.833333 ], [ -66.95,71.833333 ], [ -66.95,16.916667 ], [ 173.0,16.916667 ] ] ] } } ] }","volume":"8","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-05-09","publicationStatus":"PW","scienceBaseUri":"5218764fe4b0e27b926cc65d","contributors":{"authors":[{"text":"Velpuri, N.M. 0000-0002-6370-1926","orcid":"https://orcid.org/0000-0002-6370-1926","contributorId":66495,"corporation":false,"usgs":true,"family":"Velpuri","given":"N.M.","affiliations":[],"preferred":false,"id":482937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, G.B. 0000-0002-8810-8539","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":17741,"corporation":false,"usgs":true,"family":"Senay","given":"G.B.","affiliations":[],"preferred":false,"id":482936,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70043513,"text":"70043513 - 2013 - Time-lapse analysis of methane quantity in Mary Lee group of coal seams using filter-based multiple-point geostatistical simulation","interactions":[],"lastModifiedDate":"2013-08-22T15:57:52","indexId":"70043513","displayToPublicDate":"2013-08-22T15:49:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2701,"text":"Mathematical Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"Time-lapse analysis of methane quantity in Mary Lee group of coal seams using filter-based multiple-point geostatistical simulation","docAbstract":"Coal seam degasification and its success are important for controlling methane, and thus for the health and safety of coal miners. During the course of degasification, properties of coal seams change. Thus, the changes in coal reservoir conditions and in-place gas content as well as methane emission potential into mines should be evaluated by examining time-dependent changes and the presence of major heterogeneities and geological discontinuities in the field. In this work, time-lapsed reservoir and fluid storage properties of the New Castle coal seam, Mary Lee/Blue Creek seam, and Jagger seam of Black Warrior Basin, Alabama, were determined from gas and water production history matching and production forecasting of vertical degasification wellbores. These properties were combined with isotherm and other important data to compute gas-in-place (GIP) and its change with time at borehole locations. Time-lapsed training images (TIs) of GIP and GIP difference corresponding to each coal and date were generated by using these point-wise data and Voronoi decomposition on the TI grid, which included faults as discontinuities for expansion of Voronoi regions. Filter-based multiple-point geostatistical simulations, which were preferred in this study due to anisotropies and discontinuities in the area, were used to predict time-lapsed GIP distributions within the study area. Performed simulations were used for mapping spatial time-lapsed methane quantities as well as their uncertainties within the study area.\nThe systematic approach presented in this paper is the first time in literature that history matching, TIs of GIPs and filter simulations are used for degasification performance evaluation and for assessing GIP for mining safety. Results from this study showed that using production history matching of coalbed methane wells to determine time-lapsed reservoir data could be used to compute spatial GIP and representative GIP TIs generated through Voronoi decomposition. Furthermore, performing filter simulations using point-wise data and TIs could be used to predict methane quantity in coal seams subjected to degasification. During the course of the study, it was shown that the material balance of gas produced by wellbores and the GIP reductions in coal seams predicted using filter simulations compared very well, showing the success of filter simulations for continuous variables in this case study. Quantitative results from filter simulations of GIP within the studied area briefly showed that GIP was reduced from an initial ∼73 Bcf (median) to ∼46 Bcf (2011), representing a 37 % decrease and varying spatially through degasification. It is forecasted that there will be an additional ∼2 Bcf reduction in methane quantity between 2011 and 2015. This study and presented results showed that the applied methodology and utilized techniques can be used to map GIP and its change within coal seams after degasification, which can further be used for ventilation design for methane control in coal mines.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Mathematical Geosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s11004-013-9474-1","usgsCitation":"Karacan, C., and Olea, R., 2013, Time-lapse analysis of methane quantity in Mary Lee group of coal seams using filter-based multiple-point geostatistical simulation: Mathematical Geosciences, v. 45, no. 6, p. 681-704, https://doi.org/10.1007/s11004-013-9474-1.","productDescription":"24 p.","startPage":"681","endPage":"704","numberOfPages":"24","ipdsId":"IP-039496","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":473591,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4503532","text":"External Repository"},{"id":276923,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276921,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s11004-013-9474-1"}],"country":"United States","state":"Alabama","otherGeospatial":"Black Warrior Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.4731,31.8421 ], [ -88.4731,35.008 ], [ -85.9759,35.008 ], [ -85.9759,31.8421 ], [ -88.4731,31.8421 ] ] ] } } ] }","volume":"45","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-06-25","publicationStatus":"PW","scienceBaseUri":"521724dee4b043bae8d2e5c1","contributors":{"authors":[{"text":"Karacan, C. Özgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":96571,"corporation":false,"usgs":true,"family":"Karacan","given":"C. Özgen","affiliations":[],"preferred":false,"id":473748,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":47873,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":473747,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047769,"text":"fs20133052 - 2013 - The 3D Elevation Program: summary for Virginia","interactions":[],"lastModifiedDate":"2016-08-17T16:11:45","indexId":"fs20133052","displayToPublicDate":"2013-08-22T14:41:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3052","title":"The 3D Elevation Program: summary for Virginia","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the Commonwealth of Virginia, elevation data are critical for urban and regional planning, natural resources conservation, flood risk management, agriculture and precision farming, resource mining, infrastructure and construction management, and other business uses. Today, high-quality light detection and ranging (lidar) data are the sources for creating elevation models and other elevation datasets. Federal, State, and local agencies work in partnership to (1) replace data, on a national basis, that are (on average) 30 years old and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The new 3D Elevation Program (3DEP) initiative, managed by the U.S. Geological Survey (USGS), responds to the growing need for high-quality topographic data and a wide range of other three-dimensional representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133052","usgsCitation":"Carswell, W., 2013, The 3D Elevation Program: summary for Virginia: U.S. Geological Survey Fact Sheet 2013-3052, 2 p., https://doi.org/10.3133/fs20133052.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":276909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133052.jpg"},{"id":276907,"type":{"id":15,"text":"Index 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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":482934,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70047766,"text":"sir20135089 - 2013 - Method to support Total Maximum Daily Load development using hydrologic alteration as a surrogate to address aquatic life impairment in New Jersey streams","interactions":[],"lastModifiedDate":"2018-11-01T12:06:18","indexId":"sir20135089","displayToPublicDate":"2013-08-22T13:36:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5089","title":"Method to support Total Maximum Daily Load development using hydrologic alteration as a surrogate to address aquatic life impairment in New Jersey streams","docAbstract":"<p>More than 300 ambient monitoring sites in New Jersey have been identified by the New Jersey Department of Environmental Protection (NJDEP) in its integrated water-quality monitoring and assessment report (that is, the 305(b) Report on general water quality and 303(d) List of waters that do not support their designated uses) as being impaired with respect to aquatic life; however, no unambiguous stressors (for example, nutrients or bacteria) have been identified. Because of the indeterminate nature of the broad range of possible impairments, surrogate measures that more holistically encapsulate the full suite of potential environmental stressors need to be developed. Streamflow alteration resulting from anthropogenic changes in the landscape is one such surrogate. For example, increases in impervious surface cover (ISC) commonly cause increases in surface runoff, which can result in “flashy” hydrology and other changes in the stream corridor that are associated with streamflow alteration. The NJDEP has indicated that methodologies to support a hydrologically based Total Maximum Daily Load (hydro-TMDL) need to be developed in order to identify hydrologic targets that represent a minimal percent deviation from a baseline condition (“minimally altered”) as a surrogate measure to meet criteria in support of designated&nbsp;uses.</p><p>The primary objective of this study was to develop an applicable hydro-TMDL approach to address aquatic-life impairments associated with hydrologic alteration for New Jersey streams. The U.S. Geological Survey, in cooperation with the NJDEP, identified 51 non- to moderately impaired gaged streamflow sites in the Raritan River Basin for evaluation. Quantile regression (QR) analysis was used to compare flow and precipitation records and identify baseline hydrographs at 37 of these sites. At sites without an appropriately long period of record (POR) or where a baseline hydrograph could not be identified with QR, a rainfall-runoff model was used to develop simulated baseline hydrographs. The hydro-TMDL approach provided an opportunity to evaluate proportional differences in flow attributes between observed and baseline hydrographs and to develop complementary flow-ecology response relations at a subset of Raritan River Basin sites where available flow and ecological information&nbsp;overlapped.</p><p>The New Jersey Stream Classification Tool (NJSCT) was used to determine the stream class of all 51 study sites by using either an observed or a simulated baseline hydrograph. Two New Jersey stream classes (A and C) were evaluated to help characterize the unique hydrology of the Raritan River Basin. In general, class C streams (1.99–40.7&nbsp;square miles) had smaller drainage areas than class A streams (0.7–785&nbsp;square miles). Many of the non-impaired and moderately impaired class A and C streams in the Raritan River Basin were found to have significant hydrologic alteration as indicated by numerous flow values that fell outside the established 25th-to-75th- and the more conservative 40th-to-60th-percentile boundaries. However, percent deviations for the class C streams (defined as moderately stable streams with moderately high base-flow contributions) were, in general, much larger than those for the class A streams (defined as semiflashy streams characterized by moderately low base flow). The greater deviations for class C streams in the hydro-TMDL assessments likely resulted from comparisons that were based solely on simulated baseline hydrographs, which were developed without considering any anthropogenic influences in the basin. In contrast, comparisons for many of the class A streams were made by using an observed baseline, which already includes an implicit level of ISC and other human influences on the&nbsp;landscape.</p><p>By using the hydro-TMDL approach, numerous flow deviations were identified that were indicative of streams that are highly regulated by reservoirs or dams, streams that are affected by increasing amounts of surface runoff resulting from ISC, and streams that are affected by water abstraction (that is, groundwater or surface-water withdrawals used for agricultural and human supply). Eight of the reservoir- and (or) dam-affected sites showed flow deviations that are indicative of flow-managed systems. For example, indices that account for the timing and magnitude of high and low flows were often found to fall outside the 25th-to-75th-percentile range. In general, at regulated class C streams, annual summer low flows are arriving later and tend to be lower, and high flows are arriving earlier with higher magnitudes of longer duration. At class A streams, high and low flows are arriving later with an overall increase in discharge with respect to the prereservoir baseline&nbsp;conditions.</p><p>The drainage basins of eight of the study sites had large values of ISC (&gt;10 percent), most likely as a result of expanding urban development. In general, the magnitude and frequency of high flows at class A and C sites with high ISC are increasing and were commonly found to fall outside the 25th-to-75th-percentile range. Additionally, magnitudes of low flows are becoming lower and, although the timing of high flows was highly variable, low-flow events appeared to be arriving earlier than would be expected under normal low-flow conditions. Three of the study sites appeared to be affected by hydrologic changes associated with water abstraction. At these sites, the timing of flows appeared to be altered. For example, low flows tended to arrive earlier and high flows arrived later at two of the three sites. Additionally, the magnitude and duration of low flows were commonly less than the 25th-percentile value and the duration of high flows appeared to&nbsp;increase.</p><p>A reduced set of hydrologic and ecological variables was used to develop univariate and multivariate flow-ecology response models for the aquatic-invertebrate assemblage. Many hydrologic variables accounting for the duration, magnitude, frequency, and timing of flows were significantly correlated with ecological response. Multiple linear regression (MLR) models were developed to provide a more holistic evaluation of the combined effects of hydrologic alteration and to identify models with two or three hydrologic variables that account for a significant proportion of the variability in invertebrate-assemblage condition as represented by assemblage metric scores. MLR models, derived on the basis of hydrologic attributes, accounted for 35 to 75 percent of the variability in assemblage&nbsp;condition.</p><p>The hydro-TMDL method developed herein for non- to moderately impaired Raritan River Basin streams utilizes a “surrogate” approach in place of the traditional “pollutant of concern” approach commonly used for TMDL development. Managers can use the results obtained by using the hydro-TMDL method to offset the effects of impervious-surface runoff and altered streamflow and to implement measures designed to achieve the necessary load reductions for the “pollutant of concern” (that is, percentage deviations of stream-class-specific flow-index values outside the established 25th-to-75th-percentile range). In this case, such deviations could represent all or a subset of the altered flow indices that prevent the stream from meeting designated aquatic-life criteria. This hydro-TMDL uses a reference, or attainment stream approach for developing the TMDL endpoint. That is, either observed or simulated baseline hydrographs were selected as appropriate reference conditions on the basis of results of QR analysis and watershed modeling procedures, respectively. For any stream in the Raritan River Basin evaluated as part of this study, the hydro-TMDL can be expressed as the greatest amount of deviation in flow a stream can exhibit without violating the stream’s designated aquatic-life criteria. Use of this surrogate approach is appropriate because flows that fall outside the established percentile ranges are ultimately a function of many anthropogenic modifications of the landscape, including the amount of stormwater runoff generated from impervious surfaces within a given basin, the presence of manmade structures designed to retain or divert water, the magnitude of ground- and surface-water abstraction, and the presence of water-supply processes implemented to support human needs. In addition, the stream-type-specific flow indices used as the basis for the hydro-TMDL approach are useful for representing the hydrologic conditions of class A and C streams/basins because they incorporate the full spectrum of flow conditions (very low to very high) that occur in the stream system over a long period of time, as well as those flow properties that change as a result of seasonal&nbsp;variation.</p><p>Ultimately, an estimate of the maximum percentage flow reduction that could be allowed will be needed to address the aquatic-life impairments in many of the study streams in the Raritan River Basin and will be necessary for identifying appropriate target flow conditions for hydro-TMDL implementation. As described in this report, a target flow value equal to the 25th- or 75th-percentile flow rate could be selected as the point useful for setting specific hydrologic targets. This selection, however, is a management decision that could vary depending on the designated use of the stream or other regulatory factors (for example, water-supply protection, trout production, antidegradation policies, or special protection designations). In New Jersey streams where no unambiguous stressors can be identified, State monitoring agencies, such as the NJDEP, could choose to require the implementation of a flow-based TMDL that not only supports designated uses, but meets the regulatory requirements under the Clean Water Act, and represents a balance between water supply intended to meet human needs and the conservation of ecosystem&nbsp;integrity.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135089","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Kennen, J., Riskin, M.L., Reilly, P.A., and Colarullo, S.J., 2013, Method to support Total Maximum Daily Load development using hydrologic alteration as a surrogate to address aquatic life impairment in New Jersey streams: U.S. Geological Survey Scientific Investigations Report 2013-5089, viii, 86 p., https://doi.org/10.3133/sir20135089.","productDescription":"viii, 86 p.","numberOfPages":"98","onlineOnly":"Y","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":276906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135089.png"},{"id":276904,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5089/","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":276905,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5089/pdf/sir2013-5089.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"New Jersey","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.25,\n              40\n            ],\n            [\n              -74.25,\n              40\n            ],\n            [\n              -74.25,\n              41\n            ],\n            [\n              -75.25,\n              41\n            ],\n            [\n              -75.25,\n              40\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521724dae4b043bae8d2e5a9","contributors":{"authors":[{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riskin, Melissa L. 0000-0001-6499-3775 mriskin@usgs.gov","orcid":"https://orcid.org/0000-0001-6499-3775","contributorId":654,"corporation":false,"usgs":true,"family":"Riskin","given":"Melissa","email":"mriskin@usgs.gov","middleInitial":"L.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reilly, Pamela A. 0000-0002-2937-4490 jankowsk@usgs.gov","orcid":"https://orcid.org/0000-0002-2937-4490","contributorId":653,"corporation":false,"usgs":true,"family":"Reilly","given":"Pamela","email":"jankowsk@usgs.gov","middleInitial":"A.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Colarullo, Susan J. 0000-0003-4504-0068 colarull@usgs.gov","orcid":"https://orcid.org/0000-0003-4504-0068","contributorId":652,"corporation":false,"usgs":true,"family":"Colarullo","given":"Susan","email":"colarull@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482926,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70047763,"text":"sir20135091 - 2013 - A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suites","interactions":[{"subject":{"id":70047763,"text":"sir20135091 - 2013 - A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suites","indexId":"sir20135091","publicationYear":"2013","noYear":false,"title":"A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suites"},"predicate":"SUPERSEDED_BY","object":{"id":70116317,"text":"sir20105070K - 2013 - A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suite","indexId":"sir20105070K","publicationYear":"2013","noYear":false,"chapter":"K","title":"A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suite"},"id":1}],"supersededBy":{"id":70116317,"text":"sir20105070K - 2013 - A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suite","indexId":"sir20105070K","publicationYear":"2013","noYear":false,"title":"A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suite"},"lastModifiedDate":"2018-11-26T09:35:39","indexId":"sir20135091","displayToPublicDate":"2013-08-22T11:55:07","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5091","title":"A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suites","docAbstract":"This descriptive model for magmatic iron-titanium-oxide (Fe-Ti-oxide) deposits hosted by Proterozoic age massif-type anorthosite and related rock types presents their geological, mineralogical, geochemical, and geoenvironmental attributes. Although these Proterozoic rocks are found worldwide, the majority of known deposits are found within exposed rocks of the Grenville Province, stretching from southwestern United States through eastern Canada; its extension into Norway is termed the Rogaland Anorthosite Province. This type of Fe-Ti-oxide deposit dominated by ilmenite rarely contains more than 300 million tons of ore, with between 10- to 45-percent titanium dioxide (TiO<sub>2</sub>), 32- to 45-percent iron oxide (FeO), and less than 0.2-percent vanadium (V).  The origin of these typically discordant ore deposits remains as enigmatic as the magmatic evolution of their host rocks. The deposits clearly have a magmatic origin, hosted by an age-constrained unique suite of rocks that likely are the consequence of a particular combination of tectonic circumstances, rather than any a priori temporal control. Principal ore minerals are ilmenite and hemo-ilmenite (ilmenite with extensive hematite exsolution lamellae); occurrences of titanomagnetite, magnetite, and apatite that are related to this deposit type are currently of less economic importance. Ore-mineral paragenesis is somewhat obscured by complicated solid solution and oxidation behavior within the Fe-Ti-oxide system. Anorthosite suites hosting these deposits require an extensive history of voluminous plagioclase crystallization to develop plagioclase-melt diapirs with entrained Fe-Ti-rich melt rising from the base of the lithosphere to mid- and upper-crustal levels. Timing and style of oxide mineralization are related to magmatic and dynamic evolution of these diapiric systems and to development and movement of oxide cumulates and related melts.  Active mines have developed large open pits with extensive waste-rock piles, but because of the nature of the ore and waste rock, the major environmental impacts documented at the mine sites are reported to be waste disposal issues and somewhat degraded water quality.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135091","usgsCitation":"Woodruff, L.G., Nicholson, S.W., and Fey, D.L., 2013, A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suites: U.S. Geological Survey Scientific Investigations Report 2013-5091, vii, 47 p., https://doi.org/10.3133/sir20135091.","productDescription":"vii, 47 p.","numberOfPages":"58","onlineOnly":"Y","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":276898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135091.gif"},{"id":276897,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5091/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521724cfe4b043bae8d2e59d","contributors":{"authors":[{"text":"Woodruff, Laurel G. 0000-0002-2514-9923 woodruff@usgs.gov","orcid":"https://orcid.org/0000-0002-2514-9923","contributorId":2224,"corporation":false,"usgs":true,"family":"Woodruff","given":"Laurel","email":"woodruff@usgs.gov","middleInitial":"G.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":482920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nicholson, Suzanne W. 0000-0002-9365-1894 swnich@usgs.gov","orcid":"https://orcid.org/0000-0002-9365-1894","contributorId":880,"corporation":false,"usgs":true,"family":"Nicholson","given":"Suzanne","email":"swnich@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":true,"id":482919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fey, David L. dfey@usgs.gov","contributorId":713,"corporation":false,"usgs":true,"family":"Fey","given":"David","email":"dfey@usgs.gov","middleInitial":"L.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":482918,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70047762,"text":"fs20133048 - 2013 - Monitoring of green infrastructure at The Grove in Bloomington, Illinois","interactions":[],"lastModifiedDate":"2013-08-22T11:47:39","indexId":"fs20133048","displayToPublicDate":"2013-08-22T11:38:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3048","title":"Monitoring of green infrastructure at The Grove in Bloomington, Illinois","docAbstract":"The City of Bloomington, Illinois, restored Kickapoo Creek to a more natural state by incorporating green infrastructure—specifically flood-plain reconnection, riparian wetlands, meanders, and rock riffles—at a 90-acre park within The Grove residential development. A team of State and Federal agencies and contractors are collecting data to monitor the effectiveness of this stream restoration in improving water quality and stream habitat. The U.S. Geological Survey (USGS) is collecting and analyzing water resources data; Illinois Department of Natural Resources (IDNR) is collecting fish population data; Illinois Environmental Protection Agency (IEPA) is collecting macroinvertebrates and riparian habitat data; and Prairie Engineers of Illinois, P.C., is collecting vegetation data. The data collection includes conditions upstream, within, and downstream of the development and restoration. The 480-acre development was designed by the Farnsworth Group to reduce peak stormwater flows by capturing runoff in the reconnected flood plains with shallow wetland basins. Also, an undersized park bridge was built at the downstream end of the park to pass the 20-percent annual exceedance probability flows (historically referred to as the 5-year flood), but detain larger floods. This design also helps limit sediment deposition from sediments transported in the drainage ditches in the upper 9,000 acres of agricultural row crops. Maintaining sediment-transport capacity minimizes sediment deposition in the restored stream segments, which reduces the loss of riparian and wetland-plant communities and instream habitat. Two additional goals of the restoration were to reduce nutrient loads and maintain water quality to support a diverse community of biotic species. Overall, 2 miles of previously managed agricultural-drainage ditches of Kickapoo Creek were restored, and the park landscape maximizes the enhancement of native riparian, wetland, and aquatic species for the park’s trail system. The purpose of this fact sheet is to give an overview and examples of the data being collected.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133048","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, Illinois Environmental Protection Agency, City of Bloomington, Illinois, Illinois Department of Natural Resources, U.S. Department of Agriculture, Natural Resources Conservation Service, Prairie Engineers of Illinois, P.C.","usgsCitation":"Roseboom, D., and Straub, T., 2013, Monitoring of green infrastructure at The Grove in Bloomington, Illinois: U.S. Geological Survey Fact Sheet 2013-3048, 4 p., https://doi.org/10.3133/fs20133048.","productDescription":"4 p.","onlineOnly":"Y","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":276896,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133048.gif"},{"id":276894,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3048/"},{"id":276895,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3048/pdf/fs2013-3048.pdf"}],"country":"United States","state":"Illinois","city":"Bloomington","otherGeospatial":"Kickapoo Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.88,40.45 ], [ -88.88,40.475 ], [ -88.85,40.475 ], [ -88.85,40.45 ], [ -88.88,40.45 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521724dde4b043bae8d2e5ad","contributors":{"authors":[{"text":"Roseboom, Donald P.","contributorId":94747,"corporation":false,"usgs":true,"family":"Roseboom","given":"Donald P.","affiliations":[],"preferred":false,"id":482917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Straub, Timothy D. 0000-0002-5896-0851 tdstraub@usgs.gov","orcid":"https://orcid.org/0000-0002-5896-0851","contributorId":2273,"corporation":false,"usgs":true,"family":"Straub","given":"Timothy D.","email":"tdstraub@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":482916,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047520,"text":"70047520 - 2013 - Chromosome rearrangements, recombination suppression, and limited segregation distortion in hybrids between Yellowstone cutthroat trout (<i>Oncorhynchus clarkii bouvieri</i>) and rainbow trout (<i>O. mykiss</i>)","interactions":[],"lastModifiedDate":"2016-05-17T09:03:12","indexId":"70047520","displayToPublicDate":"2013-08-22T11:28:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":956,"text":"BMC Genomics","active":true,"publicationSubtype":{"id":10}},"title":"Chromosome rearrangements, recombination suppression, and limited segregation distortion in hybrids between Yellowstone cutthroat trout (<i>Oncorhynchus clarkii bouvieri</i>) and rainbow trout (<i>O. mykiss</i>)","docAbstract":"<div id=\"ASec1\" class=\"AbstractSection\">\n<h3 class=\"Heading\">Background</h3>\n<p class=\"Para\">Introgressive hybridization is an important evolutionary process that can lead to the creation of novel genome structures and thus potentially new genetic variation for selection to act upon. On the other hand, hybridization with introduced species can threaten native species, such as cutthroat trout (<i class=\"EmphasisTypeItalic\">Oncorhynchus clarkii</i>) following the introduction of rainbow trout (<i class=\"EmphasisTypeItalic\">O. mykiss</i>). Neither the evolutionary consequences nor conservation implications of rainbow trout introgression in cutthroat trout is well understood. Therefore, we generated a genetic linkage map for rainbow-Yellowstone cutthroat trout (<i class=\"EmphasisTypeItalic\">O. clarkii bouvieri</i>) hybrids to evaluate genome processes that may help explain how introgression affects hybrid genome evolution.</p>\n</div>\n<div id=\"ASec2\" class=\"AbstractSection\">\n<h3 class=\"Heading\">Results</h3>\n<p class=\"Para\">The hybrid map closely aligned with the rainbow trout map (a cutthroat trout map does not exist), sharing all but one linkage group. This linkage group (RYHyb20) represented a fusion between an acrocentric (Omy28) and a metacentric chromosome (Omy20) in rainbow trout. Additional mapping in Yellowstone cutthroat trout indicated the two rainbow trout homologues were fused in the Yellowstone genome. Variation in the number of hybrid linkage groups (28 or 29) likely depended on a Robertsonian rearrangement polymorphism within the rainbow trout stock. Comparison between the female-merged F<span>1</span>&nbsp;map and a female consensus rainbow trout map revealed that introgression suppressed recombination across large genomic regions in 5 hybrid linkage groups. Two of these linkage groups (RYHyb20 and RYHyb25_29) contained confirmed chromosome rearrangements between rainbow and Yellowstone cutthroat trout indicating that rearrangements may suppress recombination. The frequency of allelic and genotypic segregation distortion varied among parents and families, suggesting few incompatibilities exist between rainbow and Yellowstone cutthroat trout genomes.</p>\n</div>\n<div id=\"ASec3\" class=\"AbstractSection\">\n<h3 class=\"Heading\">Conclusions</h3>\n<p class=\"Para\">Chromosome rearrangements suppressed recombination in the hybrids. This result supports several previous findings demonstrating that recombination suppression restricts gene flow between chromosomes that differ by arrangement. Conservation of synteny and map order between the hybrid and rainbow trout maps and minimal segregation distortion in the hybrids suggest rainbow and Yellowstone cutthroat trout genomes freely introgress across chromosomes with similar arrangement. Taken together, these results suggest that rearrangements impede introgression. Recombination suppression across rearrangements could enable large portions of non-recombined chromosomes to persist within admixed populations.</p>\n</div>","language":"English","publisher":"BMC Genomics","doi":"10.1186/1471-2164-14-570","usgsCitation":"Ostberg, C.O., Hauser, L., Pritchard, V.L., Garza, J., and Naish, K., 2013, Chromosome rearrangements, recombination suppression, and limited segregation distortion in hybrids between Yellowstone cutthroat trout (<i>Oncorhynchus clarkii bouvieri</i>) and rainbow trout (<i>O. mykiss</i>): BMC Genomics, v. 14, 16 p., https://doi.org/10.1186/1471-2164-14-570.","productDescription":"16 p.","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044308","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":473592,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/1471-2164-14-570","text":"Publisher Index Page"},{"id":277375,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"522af95fe4b08fd0132e796e","contributors":{"authors":[{"text":"Ostberg, Carl O. 0000-0003-1479-8458 costberg@usgs.gov","orcid":"https://orcid.org/0000-0003-1479-8458","contributorId":3031,"corporation":false,"usgs":true,"family":"Ostberg","given":"Carl","email":"costberg@usgs.gov","middleInitial":"O.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":482242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hauser, Lorenz","contributorId":62510,"corporation":false,"usgs":true,"family":"Hauser","given":"Lorenz","email":"","affiliations":[],"preferred":false,"id":482245,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pritchard, Victoria L.","contributorId":6750,"corporation":false,"usgs":true,"family":"Pritchard","given":"Victoria","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":482243,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garza, John C.","contributorId":97806,"corporation":false,"usgs":true,"family":"Garza","given":"John C.","affiliations":[],"preferred":false,"id":482246,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Naish, Kerry A.","contributorId":20243,"corporation":false,"usgs":true,"family":"Naish","given":"Kerry A.","affiliations":[],"preferred":false,"id":482244,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70047760,"text":"ofr20121157 - 2013 - Shallow geology, seafloor texture, and physiographic zones of the Inner Continental Shelf from Nahant to northern Cape Cod Bay, Massachusetts","interactions":[],"lastModifiedDate":"2017-11-10T18:29:52","indexId":"ofr20121157","displayToPublicDate":"2013-08-22T10:42:47","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1157","title":"Shallow geology, seafloor texture, and physiographic zones of the Inner Continental Shelf from Nahant to northern Cape Cod Bay, Massachusetts","docAbstract":"The Massachusetts inner continental shelf between Nahant and northern Cape Cod Bay has been profoundly affected by the occupation and retreat of glacial ice sheets and relative sea-level change during the Quaternary. Marine geologic mapping of this area is a component of a statewide cooperative effort involving the U.S. Geological Survey and the Massachusetts Office of Coastal Zone Management. Interpretation of high-resolution geophysical data (interferometric and multibeam swath bathymetry, lidar, backscatter, and seismic reflection), sediment samples, and bottom photographs was used to produce a series of maps that describe the distribution and texture of seafloor sediments, shallow geologic framework, and physiographic zones of this inner-shelf region. These data and interpretations are intended to aid efforts to inventory and manage coastal and marine resources, and provide baseline information for research focused on coastal evolution and environmental change.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121157","usgsCitation":"Pendleton, E., Baldwin, W.E., Barnhardt, W., Ackerman, S.D., Foster, D.S., Andrews, B., and Schwab, W.C., 2013, Shallow geology, seafloor texture, and physiographic zones of the Inner Continental Shelf from Nahant to northern Cape Cod Bay, Massachusetts: U.S. Geological Survey Open-File Report 2012-1157, HTML Document, https://doi.org/10.3133/ofr20121157.","productDescription":"HTML Document","onlineOnly":"Y","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science 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,{"id":70047754,"text":"70047754 - 2013 - The quest for extraterrestrial life: what about the viruses?","interactions":[],"lastModifiedDate":"2013-08-22T10:13:57","indexId":"70047754","displayToPublicDate":"2013-08-22T10:11:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":912,"text":"Astrobiology","active":true,"publicationSubtype":{"id":10}},"title":"The quest for extraterrestrial life: what about the viruses?","docAbstract":"Recently, viruses have been recognized as the most numerous entities and the primary drivers of evolution on Earth. Historically, viruses have been mostly ignored in the field of astrobiology due to the view that they are not alive in the classical sense and if encountered would not present risk due to their host-specific nature. What we currently know of viruses is that we are most likely to encounter them on other life-bearing planets; that while some are exquisitely host-specific, many viruses can utilize hundreds of different host species; that viruses are known to exist in our planet's most extreme environments; and that while many do not survive long outside their hosts, some can survive for extended periods, especially in the cold. In our quest for extraterrestrial life, we should be looking for viruses; and while any encountered may pose no risk, the possibility of an encounter with a virus capable of accessing multiple cell types exists, and any prospective contact with such an organism should be treated accordingly.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Astrobiology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Mary Ann Liebert, Inc.","doi":"10.1089/ast.2012.0959","usgsCitation":"Griffin, D.W., 2013, The quest for extraterrestrial life: what about the viruses?: Astrobiology, v. 13, no. 8, p. 774-783, https://doi.org/10.1089/ast.2012.0959.","productDescription":"10 p.","startPage":"774","endPage":"783","ipdsId":"IP-035856","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":276888,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276878,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1089/ast.2012.0959"}],"volume":"13","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521724dee4b043bae8d2e5bd","contributors":{"authors":[{"text":"Griffin, Dale Warren","contributorId":38052,"corporation":false,"usgs":true,"family":"Griffin","given":"Dale","email":"","middleInitial":"Warren","affiliations":[],"preferred":false,"id":482895,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70047757,"text":"70047757 - 2013 - Hybrid modeling of spatial continuity for application to numerical inverse problems","interactions":[],"lastModifiedDate":"2013-08-22T10:02:03","indexId":"70047757","displayToPublicDate":"2013-08-22T09:56:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Hybrid modeling of spatial continuity for application to numerical inverse problems","docAbstract":"A novel two-step modeling approach is presented to obtain optimal starting values and geostatistical constraints for numerical inverse problems otherwise characterized by spatially-limited field data. First, a type of unsupervised neural network, called the self-organizing map (SOM), is trained to recognize nonlinear relations among environmental variables (covariates) occurring at various scales. The values of these variables are then estimated at random locations across the model domain by iterative minimization of SOM topographic error vectors. Cross-validation is used to ensure unbiasedness and compute prediction uncertainty for select subsets of the data. Second, analytical functions are fit to experimental variograms derived from original plus resampled SOM estimates producing model variograms. Sequential Gaussian simulation is used to evaluate spatial uncertainty associated with the analytical functions and probable range for constraining variables. The hybrid modeling of spatial continuity is demonstrated using spatially-limited hydrologic measurements at different scales in Brazil: (1) physical soil properties (sand, silt, clay, hydraulic conductivity) in the 42 km<sup>2</sup> Vargem de Caldas basin; (2) well yield and electrical conductivity of groundwater in the 132 km<sup>2</sup> fractured crystalline aquifer; and (3) specific capacity, hydraulic head, and major ions in a 100,000 km<sup>2</sup> transboundary fractured-basalt aquifer. These results illustrate the benefits of exploiting nonlinear relations among sparse and disparate data sets for modeling spatial continuity, but the actual application of these spatial data to improve numerical inverse modeling requires testing.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Modelling and Software","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2013.01.009","usgsCitation":"Friedel, M.J., and Iwashita, F., 2013, Hybrid modeling of spatial continuity for application to numerical inverse problems: Environmental Modelling and Software, v. 43, p. 60-79, https://doi.org/10.1016/j.envsoft.2013.01.009.","productDescription":"20 p.","startPage":"60","endPage":"79","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":276885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276884,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.envsoft.2013.01.009"}],"volume":"43","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521724dae4b043bae8d2e5a5","contributors":{"authors":[{"text":"Friedel, Michael J. 0000-0002-5060-3999 mfriedel@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-3999","contributorId":595,"corporation":false,"usgs":true,"family":"Friedel","given":"Michael","email":"mfriedel@usgs.gov","middleInitial":"J.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":482903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iwashita, Fabio","contributorId":72287,"corporation":false,"usgs":true,"family":"Iwashita","given":"Fabio","email":"","affiliations":[],"preferred":false,"id":482904,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047755,"text":"70047755 - 2013 - Seismic detection of increased degassing before Kīlauea's 2008 summit explosion","interactions":[],"lastModifiedDate":"2013-08-22T09:50:10","indexId":"70047755","displayToPublicDate":"2013-08-22T09:43:26","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Seismic detection of increased degassing before Kīlauea's 2008 summit explosion","docAbstract":"The 2008 explosion that started a new eruption at the summit of Kīlauea Volcano, Hawai‘i, was not preceded by a dramatic increase in earthquakes nor inflation, but was associated with increases in SO<sub>2</sub> emissions and seismic tremor. Here we perform shear wave splitting analysis on local earthquakes spanning the onset of the eruption. Shear wave splitting measures seismic anisotropy and is traditionally used to infer changes in crustal stress over time. We show that shear wave splitting may also vary due to changes in volcanic degassing. The orientation of fast shear waves at Kīlauea is usually controlled by structure, but in 2008 showed changes with increased SO<sub>2</sub> emissions preceding the start of the summit eruption. This interpretation for changing anisotropy is supported by corresponding decreases in V<sub>p</sub>/V<sub>s<sub> ratio. Our result demonstrates a novel method for detecting changes in gas flux using seismic observations and provides a new tool for monitoring under-instrumented volcanoes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Nature Communications","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Nature Publishing Group","doi":"10.1038/ncomms2703","usgsCitation":"Johnson, J.H., and Poland, M., 2013, Seismic detection of increased degassing before Kīlauea's 2008 summit explosion: Nature Communications, v. 4, Article number 1668, https://doi.org/10.1038/ncomms2703.","productDescription":"Article number 1668","ipdsId":"IP-042373","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473593,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/ncomms2703","text":"Publisher Index Page"},{"id":276883,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276879,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1038/ncomms2703"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kilauea Volcano","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -155.323951,19.377839 ], [ -155.323951,19.447759 ], [ -155.217641,19.447759 ], [ -155.217641,19.377839 ], [ -155.323951,19.377839 ] ] ] } } ] }","volume":"4","noUsgsAuthors":false,"publicationDate":"2013-04-09","publicationStatus":"PW","scienceBaseUri":"521724dde4b043bae8d2e5b1","contributors":{"authors":[{"text":"Johnson, Jessica H. jessjohnson@usgs.gov","contributorId":3523,"corporation":false,"usgs":true,"family":"Johnson","given":"Jessica","email":"jessjohnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":482897,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":635,"corporation":false,"usgs":true,"family":"Poland","given":"Michael P.","email":"mpoland@usgs.gov","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":false,"id":482896,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047751,"text":"70047751 - 2013 - Aspects of embryonic and larval development in bighead carp Hypophthalmichthys nobilis and silver carp Hypophthalmichthys molitrix","interactions":[],"lastModifiedDate":"2016-10-13T11:21:26","indexId":"70047751","displayToPublicDate":"2013-08-22T09:13:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Aspects of embryonic and larval development in bighead carp Hypophthalmichthys nobilis and silver carp Hypophthalmichthys molitrix","docAbstract":"As bighead carp Hypophthalmichthys nobilis and silver carp H. molitrix (the bigheaded carps) are poised to enter the Laurentian Great Lakes and potentially damage the region’s economically important fishery, information on developmental rates and behaviors of carps is critical to assessing their ability to establish sustainable populations within the Great Lakes basin. In laboratory experiments, the embryonic and larval developmental rates, size, and behaviors of bigheaded carp were tracked at two temperature treatments, one “cold” and one “warm”. Developmental rates were computed using previously described stages of development and the cumulative thermal unit method. Both species have similar thermal requirements, with a minimum developmental temperature for embryonic stages of 12.1° C for silver carp and 12.9° C for bighead carp, and 13.3° C for silver carp larval stages and 13.4° C for bighead carp larval stages. Egg size differed among species and temperature treatments, as egg size was larger in bighead carp, and “warm\" temperature treatments. The larvae started robust upwards vertical swimming immediately after hatching, interspersed with intervals of sinking. Vertical swimming tubes were used to measure water column distribution, and ascent and descent rates of vertically swimming fish. Water column distribution and ascent and descent rates changed with ontogeny. Water column distribution also showed some diel periodicity. Developmental rates, size, and behaviors contribute to the drift distance needed to fulfill the early life history requirements of bigheaded carps and can be used in conjunction with transport information to assess invasibility of a river.","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0073829","usgsCitation":"George, A.E., and Chapman, D., 2013, Aspects of embryonic and larval development in bighead carp Hypophthalmichthys nobilis and silver carp Hypophthalmichthys molitrix: PLoS ONE, v. 8, no. 8, e73829; 11 p., https://doi.org/10.1371/journal.pone.0073829.","productDescription":"e73829; 11 p.","ipdsId":"IP-038088","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":473594,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0073829","text":"Publisher Index Page"},{"id":276882,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276881,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0073829"}],"volume":"8","issue":"8","noUsgsAuthors":false,"publicationDate":"2013-08-14","publicationStatus":"PW","scienceBaseUri":"521724dae4b043bae8d2e5a1","contributors":{"authors":[{"text":"George, Amy E. 0000-0003-1150-8646 ageorge@usgs.gov","orcid":"https://orcid.org/0000-0003-1150-8646","contributorId":3950,"corporation":false,"usgs":true,"family":"George","given":"Amy","email":"ageorge@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":482891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":482890,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047730,"text":"sim3238 - 2013 - Geologic strip map along the Hines Creek Fault showing evidence for Cenozoic displacement in the western Mount Hayes and northeastern Healy quadrangles, eastern Alaska Range, Alaska","interactions":[],"lastModifiedDate":"2023-06-05T14:47:53.967479","indexId":"sim3238","displayToPublicDate":"2013-08-21T06:55:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3238","title":"Geologic strip map along the Hines Creek Fault showing evidence for Cenozoic displacement in the western Mount Hayes and northeastern Healy quadrangles, eastern Alaska Range, Alaska","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3238","usgsCitation":"Nokleberg, W.J., Aleinikoff, J.N., Bundtzen, T., and Hanshaw, M.N., 2013, Geologic strip map along the Hines Creek Fault showing evidence for Cenozoic displacement in the western Mount Hayes and northeastern Healy quadrangles, eastern Alaska Range, Alaska: U.S. Geological Survey Scientific Investigations Map 3238, Pamphlet: iv, 31 p.; Map: 1 Sheet: 72 x 41 inches; Readme; Metadata; GIS Data, https://doi.org/10.3133/sim3238.","productDescription":"Pamphlet: iv, 31 p.; Map: 1 Sheet: 72 x 41 inches; Readme; Metadata; GIS Data","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-034191","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":276834,"rank":7,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3238.png"},{"id":276833,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3238/sim3238_data.zip"},{"id":276831,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3238/1_Hines_Creek_Fault_Map_readme.txt"},{"id":276829,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3238/sim3238_pamphlet.pdf"},{"id":276832,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3238/Hines_Creek_Fault_Map_GDB_metadata.txt"},{"id":276830,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3238/sim3238_map.pdf"},{"id":276825,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3238/"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -147.583333,63.25 ], [ -147.583333,64.0 ], [ -145.5,64.0 ], [ -145.5,63.25 ], [ -147.583333,63.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5215d351e4b02034073ad3e4","contributors":{"authors":[{"text":"Nokleberg, Warren J. 0000-0002-1574-8869 wnokleberg@usgs.gov","orcid":"https://orcid.org/0000-0002-1574-8869","contributorId":2077,"corporation":false,"usgs":true,"family":"Nokleberg","given":"Warren","email":"wnokleberg@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":482838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aleinikoff, John N. 0000-0003-3494-6841 jaleinikoff@usgs.gov","orcid":"https://orcid.org/0000-0003-3494-6841","contributorId":1478,"corporation":false,"usgs":true,"family":"Aleinikoff","given":"John","email":"jaleinikoff@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":482837,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bundtzen, Thomas K.","contributorId":83560,"corporation":false,"usgs":true,"family":"Bundtzen","given":"Thomas K.","affiliations":[],"preferred":false,"id":482840,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanshaw, Maiana N.","contributorId":54505,"corporation":false,"usgs":true,"family":"Hanshaw","given":"Maiana","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":482839,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70047726,"text":"ds742 - 2013 - Groundwater-quality data in the Santa Barbara study unit, 2011: results from the California GAMA Program","interactions":[],"lastModifiedDate":"2013-08-20T14:54:49","indexId":"ds742","displayToPublicDate":"2013-08-20T14:42:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"742","subseriesTitle":"California Groundwater Ambient Monitoring and Assessment (GAMA) Program","title":"Groundwater-quality data in the Santa Barbara study unit, 2011: results from the California GAMA Program","docAbstract":"Groundwater quality in the 48-square-mile Santa Barbara study unit was investigated by the U.S. Geological Survey (USGS) from January to February 2011, as part of the California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring and Assessment (GAMA) Program’s Priority Basin Project (PBP). The GAMA-PBP was developed in response to the California Groundwater Quality Monitoring Act of 2001 and is being conducted in collaboration with the SWRCB and Lawrence Livermore National Laboratory (LLNL). The Santa Barbara study unit was the thirty-fourth study unit to be sampled as part of the GAMA-PBP.\n\nThe GAMA Santa Barbara study was designed to provide a spatially unbiased assessment of untreated-groundwater quality in the primary aquifer system, and to facilitate statistically consistent comparisons of untreated-groundwater quality throughout California. The primary aquifer system is defined as those parts of the aquifers corresponding to the perforation intervals of wells listed in the California Department of Public Health (CDPH) database for the Santa Barbara study unit. Groundwater quality in the primary aquifer system may differ from the quality in the shallower or deeper water-bearing zones; shallow groundwater may be more vulnerable to surficial contamination.\n\nIn the Santa Barbara study unit located in Santa Barbara and Ventura Counties, groundwater samples were collected from 24 wells. Eighteen of the wells were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the study unit (grid wells), and six wells were selected to aid in evaluation of water-quality issues (understanding wells).\n\nThe groundwater samples were analyzed for organic constituents (volatile organic compounds [VOCs], pesticides and pesticide degradates, and pharmaceutical compounds); constituents of special interest (perchlorate and N-nitrosodimethylamine [NDMA]); naturally occurring inorganic constituents (trace elements, nutrients, major and minor ions, silica, total dissolved solids [TDS], alkalinity, and arsenic, chromium, and iron species); and radioactive constituents (radon-222 and gross alpha and gross beta radioactivity). Naturally occurring isotopes (stable isotopes of hydrogen and oxygen in water, stables isotopes of inorganic carbon and boron dissolved in water, isotope ratios of dissolved strontium, tritium activities, and carbon-14 abundances) and dissolved noble gases also were measured to help identify the sources and ages of the sampled groundwater. In total, 281 constituents and water-quality indicators were measured.\n\nThree types of quality-control samples (blanks, replicates, and matrix spikes) were collected at up to 12 percent of the wells in the Santa Barbara study unit, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. Blanks rarely contained detectable concentrations of any constituent, suggesting that contamination from sample collection procedures was not a significant source of bias in the data for the groundwater samples. Replicate samples generally were within the limits of acceptable analytical reproducibility. Matrix-spike recoveries were within the acceptable range (70 to 130 percent) for approximately 82 percent of the compounds.\n\nThis study did not attempt to evaluate the quality of water delivered to consumers; after withdrawal from the ground, untreated groundwater typically is treated, disinfected, and (or) blended with other waters to maintain water quality. Regulatory benchmarks apply to water that is served to the consumer, not to untreated groundwater. However, to provide some context for the results, concentrations of constituents measured in the untreated groundwater were compared with regulatory and non-regulatory health-based benchmarks established by the U.S. Environmental Protection Agency (USEPA) and CDPH and to non-regulatory benchmarks established for aesthetic concerns by CDPH. Comparisons between data collected for this study and benchmarks for drinking water are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks. All organic constituents and most inorganic constituents that were detected in groundwater samples from the 18 grid wells in the Santa Barbara study unit were detected at concentrations less than drinking-water benchmarks.\n\nOf the 220 organic and special-interest constituents sampled for at the 18 grid wells, 13 were detected in groundwater samples; concentrations of all detected constituents were less than regulatory and non-regulatory health-based benchmarks. In total, VOCs were detected in 61 percent of the 18 grid wells sampled, pesticides and pesticide degradates were detected in 11 percent, and perchlorate was detected in 67 percent. Polar pesticides and their degradates, pharmaceutical compounds, and NDMA were not detected in any of the grid wells sampled in the Santa Barbara study unit.\n\nEighteen grid wells were sampled for trace elements, major and minor ions, nutrients, and radioactive constituents; most detected concentrations were less than health-based benchmarks. Exceptions are one detection of boron greater than the CDPH notification level (NL-CA) of 1,000 micrograms per liter (μg/L) and one detection of fluoride greater than the CDPH maximum contaminant level (MCL-CA) of 2 milligrams per liter (mg/L).\n\nResults for constituents with non-regulatory benchmarks set for aesthetic concerns from the grid wells showed that iron concentrations greater than the CDPH secondary maximum contaminant level (SMCL-CA) of 300 μg/L were detected in three grid wells. Manganese concentrations greater than the SMCL-CA of 50 μg/L were detected in seven grid wells. Chloride was detected at a concentration greater than the SMCL-CA recommended benchmark of 250 mg/L in four grid wells. Sulfate concentrations greater than the SMCL-CA recommended benchmark of 250 mg/L were measured in eight grid wells, and the concentration in one of these wells was also greater than the SMCL-CA upper benchmark of 500 mg/L. TDS concentrations greater than the SMCL-CA recommended benchmark of 500 mg/L were measured in 17 grid wells, and concentrations in six of these wells were also greater than the SMCL-CA upper benchmark of 1,000 mg/L.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds742","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Davis, T., Kulongoski, J., and Belitz, K., 2013, Groundwater-quality data in the Santa Barbara study unit, 2011: results from the California GAMA Program: U.S. Geological Survey Data Series 742, ix, 72 p., https://doi.org/10.3133/ds742.","productDescription":"ix, 72 p.","numberOfPages":"86","temporalStart":"2011-01-01","temporalEnd":"2011-02-28","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":276819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds742.PNG"},{"id":276817,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/742/"},{"id":276818,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/742/pdf/ds742.pdf"}],"country":"United States","state":"California","county":"Santa Barbara County;Ventura County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.916667,34.333333 ], [ -119.916667,34.5 ], [ -119.416667,34.5 ], [ -119.416667,34.333333 ], [ -119.916667,34.333333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521481e1e4b06d85e08fb4c3","contributors":{"authors":[{"text":"Davis, Tracy A. 0000-0003-0253-6661","orcid":"https://orcid.org/0000-0003-0253-6661","contributorId":59339,"corporation":false,"usgs":true,"family":"Davis","given":"Tracy A.","affiliations":[],"preferred":false,"id":482830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":94750,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin T.","affiliations":[],"preferred":false,"id":482831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":482829,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70047727,"text":"ds747 - 2013 - Groundwater-quality data in the Bear Valley and Selected Hard Rock Areas study unit, 2010: Results from the California GAMA Program","interactions":[],"lastModifiedDate":"2013-08-20T15:27:33","indexId":"ds747","displayToPublicDate":"2013-08-20T14:42:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"747","subseriesTitle":"California Groundwater Ambient Monitoring and Assessment (GAMA) Program","title":"Groundwater-quality data in the Bear Valley and Selected Hard Rock Areas study unit, 2010: Results from the California GAMA Program","docAbstract":"Groundwater quality in the 112-square-mile Bear Valley and Selected Hard Rock Areas (BEAR) study unit was investigated by the U.S. Geological Survey (USGS) from April to August 2010, as part of the California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring and Assessment (GAMA) Program’s Priority Basin Project (PBP). The GAMA-PBP was developed in response to the California Groundwater Quality Monitoring Act of 2001 and is being conducted in collaboration with the SWRCB and Lawrence Livermore National Laboratory (LLNL). The BEAR study unit was the thirty-first study unit to be sampled as part of the GAMA-PBP. The GAMA Bear Valley and Selected Hard Rock Areas study was designed to provide a spatially unbiased assessment of untreated-groundwater quality in the primary aquifer system and to facilitate statistically consistent comparisons of untreated groundwater quality throughout California. The primary aquifer system is defined as the zones corresponding to the perforation intervals of wells listed in the California Department of Public Health (CDPH) database for the BEAR study unit. Groundwater quality in the primary aquifer system may differ from the quality in the shallow or deep water-bearing zones; shallow groundwater may be more vulnerable to surficial contamination. In the BEAR study unit, groundwater samples were collected from two study areas (Bear Valley and Selected Hard Rock Areas) in San Bernardino County. Of the 38 sampling sites, 27 were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the primary aquifer system in the study unit (grid sites), and the remaining 11 sites were selected to aid in the understanding of the potential groundwater-quality issues associated with septic tank use and with ski areas in the study unit (understanding sites). The groundwater samples were analyzed for organic constituents (volatile organic compounds [VOCs], pesticides and pesticide degradates, pharmaceutical compounds, and wastewater indicator compounds [WICs]), constituents of special interest (perchlorate, N-nitrosodimethylamine [NDMA], and 1,2,3-trichloropropane [1,2,3-TCP]), and inorganic constituents (trace elements, nutrients, dissolved organic carbon [DOC], major and minor ions, silica, total dissolved solids [TDS], alkalinity, and arsenic and iron species), and uranium and other radioactive constituents (radon-222 and activities of tritium and carbon-14). Isotopic tracers (of hydrogen and oxygen in water, of nitrogen and oxygen in dissolved nitrate, of dissolved boron, isotopic ratios of strontium in water, and of carbon in dissolved inorganic carbon) and dissolved noble gases (argon, helium-4, krypton, neon, and xenon) were measured to help identify the sources and ages of sampled groundwater. In total, groundwater samples were analyzed for 289 unique constituents and 8 water-quality indicators in the BEAR study unit. Quality-control samples (blanks, replicate pairs, or matrix spikes) were collected at 13 percent of the sites in the BEAR study unit, and the results for these samples were used to evaluate the quality of the data from the groundwater samples. Blank samples rarely contained detectable concentrations of any constituent, indicating that contamination from sample collection or analysis was not a significant source of bias in the data for the groundwater samples. Replicate pair samples all were within acceptable limits of variability. Matrix-spike sample recoveries were within the acceptable range (70 to 130 percent) for approximately 84 percent of the compounds. This study did not evaluate the quality of water delivered to consumers. After withdrawal, groundwater typically is treated, disinfected, and (or) blended with other waters to maintain water quality. Regulatory benchmarks apply to water that is delivered to the consumer, not to untreated groundwater. However, to provide some context for the results, concentrations of constituents measured in the untreated groundwater were compared with regulatory and non-regulatory health-based benchmarks established by the U.S. Environmental Protection Agency (USEPA) and CDPH, and to non-health-based benchmarks established for aesthetic concerns by CDPH. Comparisons between data collected for this study and benchmarks for drinking water are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks. All concentrations of organic and special-interest constituents from grid sites sampled in the BEAR study unit were less than health-based benchmarks. In total, VOCs were detected in 17 of the 27 grid sites sampled (approximately 63 percent), pesticides and pesticide degradates were detected in 4 grid sites (approximately 15 percent), and perchlorate was detected in 21 grid sites (approximately 78 percent). Inorganic constituents (trace elements, major and minor ions, nutrients, and uranium and other radioactive constituents) were sampled for at 27 grid sites; most concentrations were less than health-based benchmarks. Exceptions include one detection of arsenic greater than the USEPA maximum contaminant level (MCL-US) of 10 micrograms per liter (μg/L), three detections of uranium greater than the MCL-US of 30 μg/L, nine detections of radon-222 greater than the proposed MCL-US of 4,000 picocuries per liter (pCi/L), and one detection of fluoride greater than the CDPH maximum contaminant level (MCL-CA) of 2 milligrams per liter. Concentrations of inorganic constituents with non-health-based benchmarks (iron, manganese, chloride, and TDS) were less than the CDPH secondary maximum contaminant level (SMCL-CA) in most grid sites. Exceptions include two detections of iron greater than the SMCL-CA of 300 μg/L and one detection of manganese greater than the SMCL-CA of 50 μg/L.","language":"English","publisher":"U.S Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds747","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Mathany, T., and Belitz, K., 2013, Groundwater-quality data in the Bear Valley and Selected Hard Rock Areas study unit, 2010: Results from the California GAMA Program: U.S. Geological Survey Data Series 747, x, 86 p., https://doi.org/10.3133/ds747.","productDescription":"x, 86 p.","numberOfPages":"100","additionalOnlineFiles":"N","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":276822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds747.jpg"},{"id":276820,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/747/pdf/ds747.pdf"},{"id":276821,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/747/"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.26738,33.898917 ], [ -117.26738,34.530318 ], [ -116.368561,34.530318 ], [ -116.368561,33.898917 ], [ -117.26738,33.898917 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521481e0e4b06d85e08fb4bf","contributors":{"authors":[{"text":"Mathany, Timothy M. 0000-0002-4747-5113","orcid":"https://orcid.org/0000-0002-4747-5113","contributorId":99949,"corporation":false,"usgs":true,"family":"Mathany","given":"Timothy M.","affiliations":[],"preferred":false,"id":482833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482832,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047719,"text":"ofr20131133 - 2013 - Salton Sea ecosystem monitoring and assessment plan","interactions":[],"lastModifiedDate":"2013-08-20T13:02:40","indexId":"ofr20131133","displayToPublicDate":"2013-08-20T12:55:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1133","title":"Salton Sea ecosystem monitoring and assessment plan","docAbstract":"The Salton Sea, California’s largest lake, provides essential habitat for several fish and wildlife species and is an important cultural and recreational resource. It has no outlet, and dissolved salts contained in the inflows concentrate in the Salton Sea through evaporation. The salinity of the Salton Sea, which is currently nearly one and a half times the salinity of ocean water, has been increasing as a result of evaporative processes and low freshwater inputs. Further reductions in inflows from water conservation, recycling, and transfers will lower the level of the Salton Sea and accelerate the rate of salinity increases, reduce the suitability of fish and wildlife habitat, and affect air quality by exposing lakebed playa that could generate dust.\n\nLegislation enacted in 2003 to implement the Quantification Settlement Agreement (QSA) stated the Legislature’s intent for the State of California to undertake the restoration of the Salton Sea ecosystem. As required by the legislation, the California Resources Agency (now California Natural Resources Agency) produced the Salton Sea Ecosystem Restoration Study and final Programmatic Environmental Impact Report (PEIR; California Resources Agency, 2007) with the stated purpose to “develop a preferred alternative by exploring alternative ways to restore important ecological functions of the Salton Sea that have existed for about 100 years.” A decision regarding a preferred alternative currently resides with the California State Legislature (Legislature), which has yet to take action.\n\nAs part of efforts to identify an ecosystem restoration program for the Salton Sea, and in anticipation of direction from the Legislature, the California Department of Water Resources (DWR), California Department of Fish and Wildlife (CDFW), U.S. Bureau of Reclamation (Reclamation), and U.S. Geological Survey (USGS) established a team to develop a monitoring and assessment plan (MAP). This plan is the product of that effort.\n\nThe goal of the MAP is to provide a guide for data collection, analysis, management, and reporting to inform management actions for the Salton Sea ecosystem. Monitoring activities are directed at species and habitats that could be affected by or drive future restoration activities. The MAP is not intended to be a prescriptive document. Rather, it is envisioned to be a flexible, program-level guide that articulates high-level goals and objectives, and establishes broad sideboards within which future project-level investigations and studies will be evaluated and authorized. As such, the MAP, by design, does not, for example, include detailed protocols describing how investigations will be implemented. It is anticipated that detailed study proposals will be prepared as part of an implementation plan that will include such things as specific sampling objectives, sampling schemes, and statistical and spatial limits.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131133","collaboration":"Prepared for the California Department of Water Resources, Salton Sea Ecosystem Restoration Program Kent Nelson, Program Manager","usgsCitation":"Case(compiler), H., Boles, J., Delgado, A., Nguyen, T., Osugi, D., Barnum, D.A., Decker, D., Steinberg, S., Steinberg, S., Keene, C., White, K., Lupo, T., Gen, S., and Baerenklau, K.A., 2013, Salton Sea ecosystem monitoring and assessment plan: U.S. Geological Survey Open-File Report 2013-1133, iv, 220 p., https://doi.org/10.3133/ofr20131133.","productDescription":"iv, 220 p.","numberOfPages":"241","additionalOnlineFiles":"N","costCenters":[{"id":550,"text":"Salton Sea Science Office","active":true,"usgs":true}],"links":[{"id":276810,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131133.jpg"},{"id":276808,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1133/"},{"id":276809,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1133/pdf/ofr20131133.pdf"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.28,32.95 ], [ -116.28,33.67 ], [ -115.31,33.67 ], [ -115.31,32.95 ], [ -116.28,32.95 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521481e1e4b06d85e08fb4c7","contributors":{"authors":[{"text":"Case(compiler), H. L. III","contributorId":69461,"corporation":false,"usgs":true,"family":"Case(compiler)","given":"H. L.","suffix":"III","affiliations":[],"preferred":false,"id":482806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boles, Jerry","contributorId":102374,"corporation":false,"usgs":true,"family":"Boles","given":"Jerry","email":"","affiliations":[],"preferred":false,"id":482810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Delgado, Arturo","contributorId":101176,"corporation":false,"usgs":true,"family":"Delgado","given":"Arturo","email":"","affiliations":[],"preferred":false,"id":482809,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nguyen, Thang","contributorId":45997,"corporation":false,"usgs":true,"family":"Nguyen","given":"Thang","email":"","affiliations":[],"preferred":false,"id":482802,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Osugi, Doug","contributorId":66163,"corporation":false,"usgs":true,"family":"Osugi","given":"Doug","email":"","affiliations":[],"preferred":false,"id":482805,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barnum, Douglas A. doug_barnum@usgs.gov","contributorId":3566,"corporation":false,"usgs":true,"family":"Barnum","given":"Douglas","email":"doug_barnum@usgs.gov","middleInitial":"A.","affiliations":[{"id":550,"text":"Salton Sea Science Office","active":true,"usgs":true}],"preferred":true,"id":482798,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Decker, Drew ddecker@usgs.gov","contributorId":5513,"corporation":false,"usgs":true,"family":"Decker","given":"Drew","email":"ddecker@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":482799,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Steinberg, Steven","contributorId":71872,"corporation":false,"usgs":true,"family":"Steinberg","given":"Steven","email":"","affiliations":[],"preferred":false,"id":482808,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Steinberg, Sheila","contributorId":36449,"corporation":false,"usgs":true,"family":"Steinberg","given":"Sheila","email":"","affiliations":[],"preferred":false,"id":482801,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Keene, Charles","contributorId":70279,"corporation":false,"usgs":true,"family":"Keene","given":"Charles","email":"","affiliations":[],"preferred":false,"id":482807,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"White, Kristina","contributorId":11933,"corporation":false,"usgs":true,"family":"White","given":"Kristina","email":"","affiliations":[],"preferred":false,"id":482800,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lupo, Tom","contributorId":59338,"corporation":false,"usgs":true,"family":"Lupo","given":"Tom","email":"","affiliations":[],"preferred":false,"id":482804,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Gen, Sheldon","contributorId":46406,"corporation":false,"usgs":true,"family":"Gen","given":"Sheldon","email":"","affiliations":[],"preferred":false,"id":482803,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Baerenklau, Ken A.","contributorId":108020,"corporation":false,"usgs":true,"family":"Baerenklau","given":"Ken","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":482811,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70047718,"text":"fs20133057 - 2013 - The 3D Elevation Program: summary for Washington","interactions":[],"lastModifiedDate":"2016-08-17T16:12:52","indexId":"fs20133057","displayToPublicDate":"2013-08-20T12:47:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3057","title":"The 3D Elevation Program: summary for Washington","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Washington, elevation data are critical for natural resources conservation, agriculture and precision farming, infrastructure and construction management, flood risk management, geologic resource assessment and hazards mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.</p>\n<p>The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A&ndash;16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133057","usgsCitation":"Carswell, W., 2013, The 3D Elevation Program: summary for Washington (Originally posted August 20, 2013; Revised and reposted August 14, 2014, version 1.1): U.S. Geological Survey Fact Sheet 2013-3057, 2 p., https://doi.org/10.3133/fs20133057.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":423,"text":"National Geospatial 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