{"pageNumber":"631","pageRowStart":"15750","pageSize":"25","recordCount":40807,"records":[{"id":70048852,"text":"ds769 - 2013 - Topobathymetric model of Mobile Bay, Alabama","interactions":[],"lastModifiedDate":"2017-03-27T15:27:07","indexId":"ds769","displayToPublicDate":"2013-11-08T11:35:00","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":"769","title":"Topobathymetric model of Mobile Bay, Alabama","docAbstract":"Topobathymetric Digital Elevation Models (DEMs) are a merged rendering of both topography (land elevation) and bathymetry (water depth) that provides a seamless elevation product useful for inundation mapping, as well as for other earth science applications, such as the development of sediment-transport, sea-level rise, and storm-surge models. This 1/9-arc-second (approximately 3 meters) resolution model of Mobile Bay, Alabama was developed using multiple topographic and bathymetric datasets, collected on different dates. The topographic data were obtained primarily from the U.S. Geological Survey (USGS) National Elevation Dataset (NED) (http://ned.usgs.gov/) at 1/9-arc-second resolution; USGS Experimental Advanced Airborne Research Lidar (EAARL) data (2 meters) (http://pubs.usgs.gov/ds/400/); and topographic lidar data (2 meters) and Compact Hydrographic Airborne Rapid Total Survey (CHARTS) lidar data (2 meters) from the U.S. Army Corps of Engineers (USACE) (http://www.csc.noaa.gov/digitalcoast/data/coastallidar/). Bathymetry was derived from digital soundings obtained from the National Oceanic and Atmospheric Administration’s (NOAA) National Geophysical Data Center (NGDC) (http://www.ngdc.noaa.gov/mgg/geodas/geodas.html) and from water-penetrating lidar sources, such as EAARL and CHARTS.\n\nMobile Bay is ecologically important as it is the fourth largest estuary in the United States. The Mobile and Tensaw Rivers drain into the bay at the northern end with the bay emptying into the Gulf of Mexico at the southern end. Dauphin Island (a barrier island) and the Fort Morgan Peninsula form the mouth of Mobile Bay. Mobile Bay is 31 miles (50 kilometers) long by a maximum width of 24 miles (39 kilometers) with a total area of 413 square miles (1,070 square kilometers).\n\nThe vertical datum of the Mobile Bay topobathymetric model is the North American Vertical Datum of 1988 (NAVD 88). All the topographic datasets were originally referenced to NAVD 88 and no transformations were made to these input data. The NGDC hydrographic, multibeam, and trackline surveys were transformed from mean low water (MLW) or mean lower low water (MLLW) to NAVD 88 using VDatum (http://vdatum.noaa.gov). VDatum is a tool developed by the National Geodetic Survey (NGS) that performs transformations among tidal, ellipsoid-based, geoid-based, and orthometric datums using calibrated hydrodynamic models. The vertical accuracy of the input topographic data varied depending on the input source. Because the input elevation data were derived primarily from lidar, the vertical accuracy ranges from 6 to 20 centimeters in root mean square error (RMSE).\n\nhe horizontal datum of the Mobile Bay topobathymetric model is the North American Datum of 1983 (NAD 83), geographic coordinates. All the topographic and bathymetric datasets were originally referenced to NAD 83, and no transformations were made to the input data. The bathymetric surveys were downloaded referenced to NAD 83 geographic, and therefore no horizontal transformations were required. The topbathymetric model of Mobile Bay and detailed metadata can be obtained from the USGS Web sites: http://nationalmap.gov/.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds769","usgsCitation":"Danielson, J.J., Brock, J., Howard, D., Gesch, D.B., Bonisteel-Cormier, J.M., and Travers, L.J., 2013, Topobathymetric model of Mobile Bay, Alabama: U.S. Geological Survey Data Series 769, 6 Plates: 38.17 x 33.59 inches; Downloads Directory, https://doi.org/10.3133/ds769.","productDescription":"6 Plates: 38.17 x 33.59 inches; Downloads Directory","ipdsId":"IP-038535","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":278975,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds769.gif"},{"id":278892,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/769/"},{"id":278972,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/769/pdf/mapsheets/ds769_nw-mobilebay-mapsheet.pdf","text":"Sheet 1: Topobathymetric Model of Mobile Bay, Alabama"},{"id":278969,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/769/pdf/mapsheets/ds769_5-SCtr_Mobile_Bay_mapsheet-opt-Aug_12.pdf","text":"Sheet 5: Topobathymetric Model of Mobile Bay, Alabama"},{"id":278970,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/769/pdf/mapsheets/ds769_6-SE_Mobile_Bay_mapsheet-opt-Aug_12.pdf","text":"Sheet 6: Topobathymetric Model of Mobile Bay, Alabama"},{"id":278968,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/769/pdf/mapsheets/ds769_4-SW_Mobile_Bay_mapsheet-opt-Aug_12.pdf","text":"Sheet 4: Topobathymetric Model of Mobile Bay, Alabama"},{"id":278971,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/769/pdf/mapsheets/ds769_nctr-mobilebay-mapsheet.pdf","text":"Sheet 2: Topobathymetric Model of Mobile Bay, Alabama"},{"id":278973,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/769/pdf/mapsheets/ds769_3-NE_Mobile_Bay_mapsheet-opt-Aug_12.pdf","text":"Sheet 3: Topobathymetric Model of Mobile Bay, Alabama"},{"id":278974,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/769/Downloads/"}],"country":"United States","state":"Alabama","otherGeospatial":"Mobile Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.230932,30.203506 ], [ -88.230932,30.858225 ], [ -87.80086,30.858225 ], [ -87.80086,30.203506 ], [ -88.230932,30.203506 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"527e0805e4b02d2057dcf1be","contributors":{"authors":[{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":485742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":485739,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howard, Daniel M. 0000-0002-7563-7538","orcid":"https://orcid.org/0000-0002-7563-7538","contributorId":97795,"corporation":false,"usgs":true,"family":"Howard","given":"Daniel M.","affiliations":[],"preferred":false,"id":485744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":485740,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bonisteel-Cormier, Jamie M.","contributorId":18085,"corporation":false,"usgs":true,"family":"Bonisteel-Cormier","given":"Jamie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":485743,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Travers, Laurinda J. ltravers@usgs.gov","contributorId":3002,"corporation":false,"usgs":true,"family":"Travers","given":"Laurinda","email":"ltravers@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":485741,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70048695,"text":"70048695 - 2013 - Dissolved oxygen fluctuations in karst spring flow and implications for endemic species: Barton Springs, Edwards aquifer, Texas, USA","interactions":[],"lastModifiedDate":"2017-10-12T20:18:05","indexId":"70048695","displayToPublicDate":"2013-11-08T09:46:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Dissolved oxygen fluctuations in karst spring flow and implications for endemic species: Barton Springs, Edwards aquifer, Texas, USA","docAbstract":"Karst aquifers and springs provide the dissolved oxygen critical for survival of endemic stygophiles worldwide, but little is known about fluctuations of dissolved oxygen concentrations (DO) and factors that control those concentrations. We investigated temporal variation in DO at Barton Springs, Austin, Texas, USA. During 2006–2012, DO fluctuated by as much as a factor of 2, and at some periods decreased to concentrations that adversely affect the Barton Springs salamander (Eurycea sorosum) (&le;4.4 mg/L), a federally listed endangered species endemic to Barton Springs. DO was lowest (&le;4.4 mg/L) when discharge was low (&le;1 m<sup>3</sup>/s) and spring water temperature was >21 °C, although not at a maximum; the minimum DO recorded was 4.0 mg/L. Relatively low DO (<6 mg/L) also was measured at relatively high discharge (3.2 m<sup>3</sup>/s) and maximum T (22.2 °C). A four-segment linear regression model with daily data for discharge and spring water temperature as explanatory variables provided an excellent fit for mean daily DO (Nash–Sutcliffe coefficient for the validation period of 0.90). DO also fluctuated at short-term timescales in response to storms, and DO measured at 15-min intervals could be simulated with a combination of discharge, spring temperature, and specific conductance as explanatory variables. On the basis of the daily-data regression model, we hypothesize that more frequent low DO corresponding to salamander mortality could result from (i) lower discharge from Barton Springs resulting from increased groundwater withdrawals or decreased recharge as a result of climate change, and (or) (ii) higher groundwater temperature as a result of climate change.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2013.10.004","usgsCitation":"Mahler, B., and Bourgeais, R., 2013, Dissolved oxygen fluctuations in karst spring flow and implications for endemic species: Barton Springs, Edwards aquifer, Texas, USA: Journal of Hydrology, v. 505, p. 291-298, https://doi.org/10.1016/j.jhydrol.2013.10.004.","productDescription":"8 p.","startPage":"291","endPage":"298","ipdsId":"IP-043691","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":278958,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Barton Springs, Edwards Aquifer","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -100.47,29.2 ], [ -100.47,30.76 ], [ -97.57,30.76 ], [ -97.57,29.2 ], [ -100.47,29.2 ] ] ] } } ] }","volume":"505","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"527e07e1e4b02d2057dcf0ef","contributors":{"authors":[{"text":"Mahler, Barbara 0000-0002-9150-9552 bjmahler@usgs.gov","orcid":"https://orcid.org/0000-0002-9150-9552","contributorId":1249,"corporation":false,"usgs":true,"family":"Mahler","given":"Barbara","email":"bjmahler@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":485449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bourgeais, Renan","contributorId":13522,"corporation":false,"usgs":true,"family":"Bourgeais","given":"Renan","email":"","affiliations":[],"preferred":false,"id":485450,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70048860,"text":"ofr20131251 - 2013 - Estimation of missing water-level data for the Everglades Depth Estimation Network (EDEN), 2013 update","interactions":[],"lastModifiedDate":"2013-11-14T17:26:26","indexId":"ofr20131251","displayToPublicDate":"2013-11-07T10:19:00","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":"2013-1251","title":"Estimation of missing water-level data for the Everglades Depth Estimation Network (EDEN), 2013 update","docAbstract":"The Everglades Depth Estimation Network is an integrated network of real-time water-level gaging stations, a \nground-elevation model, and a water-surface elevation model \ndesigned to provide scientists, engineers, and water-resource \nmanagers with water-level and water-depth information \n(1991-2013) for the entire freshwater portion of the Greater \nEverglades. The U.S. Geological Survey Greater Everglades \nPriority Ecosystems Science provides support for the Everglades Depth Estimation Network in order for the Network \nto provide quality-assured monitoring data for the U.S. Army \nCorps of Engineers Comprehensive Everglades Restoration \nPlan. In a previous study, water-level estimation equations \nwere developed to fill in missing data to increase the accuracy of the daily water-surface elevation model. During this \nstudy, those equations were updated because of the addition \nand removal of water-level gaging stations, the consistent use \nof water-level data relative to the North American Vertical \nDatum of 1988, and availability of recent data (March 1, 2006, \nto September 30, 2011). Up to three linear regression equations were developed for each station by using three different \ninput stations to minimize the occurrences of missing data \nfor an input station. Of the 667 water-level estimation equations developed to fill missing data at 223 stations, more than \n72 percent of the equations have coefficients of determination \ngreater than 0.90, and 97 percent have coefficients of determination greater than 0.70.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131251","collaboration":"Prepared in cooperation with the U.S. Geological Survey Greater Everglades Priority Ecosystems Science","usgsCitation":"Petkewich, M.D., and Conrads, P., 2013, Estimation of missing water-level data for the Everglades Depth Estimation Network (EDEN), 2013 update: U.S. Geological Survey Open-File Report 2013-1251, iv, 45 p., https://doi.org/10.3133/ofr20131251.","productDescription":"iv, 45 p.","numberOfPages":"49","onlineOnly":"Y","costCenters":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"links":[{"id":278909,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1251/"},{"id":278910,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131251.jpg"},{"id":278908,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1251/pdf/of2013-1251.pdf"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.8106,25.1872 ], [ -81.8106,26.3864 ], [ -80.0415,26.3864 ], [ -80.0415,25.1872 ], [ -81.8106,25.1872 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"527cb931e4b0850ea050a8cf","contributors":{"authors":[{"text":"Petkewich, Matthew D. 0000-0002-5749-6356 mdpetkew@usgs.gov","orcid":"https://orcid.org/0000-0002-5749-6356","contributorId":982,"corporation":false,"usgs":true,"family":"Petkewich","given":"Matthew","email":"mdpetkew@usgs.gov","middleInitial":"D.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":485756,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70048826,"text":"70048826 - 2013 - Hyperspectral versus multispectral crop-productivity modeling and type discrimination for the HyspIRI mission","interactions":[],"lastModifiedDate":"2021-04-22T19:32:37.892102","indexId":"70048826","displayToPublicDate":"2013-11-07T09:32:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Hyperspectral <i>versus</i> multispectral crop-productivity modeling and type discrimination for the HyspIRI mission","title":"Hyperspectral versus multispectral crop-productivity modeling and type discrimination for the HyspIRI mission","docAbstract":"<p id=\"sp0005\">Precise monitoring of agricultural crop biomass and yield quantities is critical for crop production management and prediction. The goal of this study was to compare hyperspectral narrowband (HNB)<span>&nbsp;</span><i>versus</i><span>&nbsp;</span>multispectral broadband (MBB) reflectance data in studying irrigated cropland characteristics of five leading world crops (cotton, wheat, maize, rice, and alfalfa) with the objectives of: 1. Modeling crop productivity, and 2. Discriminating crop types. HNB data were obtained from Hyperion hyperspectral imager and field ASD spectroradiometer, and MBB data were obtained from five broadband sensors: Landsat-7 Enhanced Thematic Mapper Plus (ETM&nbsp;+), Advanced Land Imager (ALI), Indian Remote Sensing (IRS), IKONOS, and QuickBird. A large collection of field spectral and biophysical variables were gathered for the 5 crops in Central Asia throughout the growing seasons of 2006 and 2007. Overall, the HNB and hyperspectral vegetation index (HVI) crop biophysical models explained about 25% greater variability when compared with corresponding MBB models. Typically, 3 to 7 HNBs, in multiple linear regression models of a given crop variable, explained more than 93% of variability in crop models. The evaluation of λ<sub>1</sub><span>&nbsp;</span>(400–2500&nbsp;nm)<span>&nbsp;</span><i>versus</i><span>&nbsp;</span>λ<sub>2</sub><span>&nbsp;</span>(400–2500&nbsp;nm) plots of various crop biophysical variables showed that the best two-band normalized difference HVIs involved HNBs centered at: (i) 742&nbsp;nm and 1175&nbsp;nm (HVI742-1175), (ii) 1296&nbsp;nm and 1054&nbsp;nm (HVI1296-1054), (iii) 1225&nbsp;nm and 697&nbsp;nm (HVI1225-697), and (iv) 702&nbsp;nm and 1104&nbsp;nm (HVI702-1104). Among the most frequently occurring HNBs in various crop biophysical models, 74% were located in the 1051–2331&nbsp;nm spectral range, followed by 10% in the moisture sensitive 970&nbsp;nm, 6% in the red and red-edge (630–752&nbsp;nm), and the remaining 10% distributed between blue (400–500&nbsp;nm), green (501–600&nbsp;nm), and NIR (760–900&nbsp;nm).</p><p id=\"sp0010\">Discriminant models, used for discriminating 3 or 4 or 5 crop types, showed significantly higher accuracies when using HNBs (&gt;&nbsp;90%) over MBBs data (varied between 45 and 84%).</p><p id=\"sp0015\">Finally, the study highlighted 29 HNBs of Hyperion that are optimal in the study of agricultural crops and potentially significant to the upcoming NASA HyspIRI mission. Determining optimal and redundant bands for a given application will help overcoming the Hughes' phenomenon (or curse of high dimensionality of data).</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2013.08.002","usgsCitation":"Mariotto, I., Thenkabail, P.S., Huete, A., Slonecker, E.T., and Platonov, A., 2013, Hyperspectral versus multispectral crop-productivity modeling and type discrimination for the HyspIRI mission: Remote Sensing of Environment, v. 139, p. 291-305, https://doi.org/10.1016/j.rse.2013.08.002.","productDescription":"15 p.","startPage":"291","endPage":"305","ipdsId":"IP-037397","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":36171,"text":"National Civil Applications Center","active":true,"usgs":true}],"links":[{"id":278897,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Uzbekistan","otherGeospatial":"Syr Darya River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 68.704655,40.8555 ], [ 68.704655,40.885405 ], [ 68.719804,40.885405 ], [ 68.719804,40.8555 ], [ 68.704655,40.8555 ] ] ] } } ] }","volume":"139","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"527cb952e4b0850ea050a8d2","contributors":{"authors":[{"text":"Mariotto, Isabella","contributorId":14140,"corporation":false,"usgs":true,"family":"Mariotto","given":"Isabella","email":"","affiliations":[],"preferred":false,"id":485722,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":485721,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huete, Alfredo","contributorId":48337,"corporation":false,"usgs":true,"family":"Huete","given":"Alfredo","affiliations":[],"preferred":false,"id":485724,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Slonecker, E. Terrence 0000-0002-5793-0503","orcid":"https://orcid.org/0000-0002-5793-0503","contributorId":67175,"corporation":false,"usgs":true,"family":"Slonecker","given":"E.","email":"","middleInitial":"Terrence","affiliations":[{"id":36171,"text":"National Civil Applications Center","active":true,"usgs":true}],"preferred":false,"id":485725,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Platonov, Alexander","contributorId":39965,"corporation":false,"usgs":true,"family":"Platonov","given":"Alexander","email":"","affiliations":[],"preferred":false,"id":485723,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70132334,"text":"70132334 - 2013 - Odor-conditioned rheotaxis of the sea lamprey: Modeling, analysis and validation","interactions":[],"lastModifiedDate":"2020-12-21T13:05:20.074686","indexId":"70132334","displayToPublicDate":"2013-11-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1013,"text":"Bioinspiration and Biomimetics","active":true,"publicationSubtype":{"id":10}},"title":"Odor-conditioned rheotaxis of the sea lamprey: Modeling, analysis and validation","docAbstract":"<p><span>Mechanisms for orienting toward and locating an odor source are sought in both biology and engineering. Chemical ecology studies have demonstrated that adult female sea lamprey show rheotaxis in response to a male pheromone with dichotomous outcomes: sexually mature females locate the source of the pheromone whereas immature females swim by the source and continue moving upstream. Here we introduce a simple switching mechanism modeled after odor-conditioned rheotaxis for the sea lamprey as they search for the source of a pheromone in a one-dimensional riverine environment. In this strategy, the females move upstream only if they detect that the pheromone concentration is higher than a threshold value and drifts down (by turning off control action to save energy) otherwise. In addition, we propose various uncertainty models such as measurement noise, actuator disturbance, and a probabilistic model of a concentration field in turbulent flow. Based on the proposed model with uncertainties, a convergence analysis showed that with this simplistic switching mechanism, the lamprey converges to the source location on average in spite of all such uncertainties. Furthermore, a slightly modified model and its extensive simulation results explain the behaviors of immature female lamprey near the source location.</span></p>","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-3182/8/4/046011","usgsCitation":"Choi, J., Jean, S., Johnson, N.S., Brant, C.O., and Li, W., 2013, Odor-conditioned rheotaxis of the sea lamprey: Modeling, analysis and validation: Bioinspiration and Biomimetics, v. 8, no. 4, 046011, https://doi.org/10.1088/1748-3182/8/4/046011.","productDescription":"046011","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051395","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":498914,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-3182/8/4/046011","text":"Publisher Index Page"},{"id":381516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"4","noUsgsAuthors":false,"publicationDate":"2013-11-07","publicationStatus":"PW","scienceBaseUri":"546727c1e4b04d4b7dbde88e","contributors":{"authors":[{"text":"Choi, Jongeun","contributorId":126764,"corporation":false,"usgs":false,"family":"Choi","given":"Jongeun","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":522801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jean, Soo","contributorId":126765,"corporation":false,"usgs":false,"family":"Jean","given":"Soo","email":"","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":522802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":597,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas","email":"njohnson@usgs.gov","middleInitial":"S.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":522800,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brant, Cory O.","contributorId":126746,"corporation":false,"usgs":false,"family":"Brant","given":"Cory","email":"","middleInitial":"O.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":522803,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Li, Weiming","contributorId":126748,"corporation":false,"usgs":false,"family":"Li","given":"Weiming","email":"","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":522804,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70048808,"text":"70048808 - 2013 - Recent lake ice-out phenology within and among lake districts of Alaska, U.S.A.","interactions":[],"lastModifiedDate":"2013-11-06T10:24:19","indexId":"70048808","displayToPublicDate":"2013-11-06T10:14:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Recent lake ice-out phenology within and among lake districts of Alaska, U.S.A.","docAbstract":"The timing of ice-out in high latitudes is a fundamental threshold for lake ecosystems and an indicator of climate change. In lake-rich regions, the loss of ice cover also plays a key role in landscape and climatic processes. Thus, there is a need to understand lake ice phenology at multiple scales. In this study, we observed ice-out timing on 55 large lakes in 11 lake districts across Alaska from 2007 to 2012 using satellite imagery. Sensor networks in two lake districts validated satellite observations and provided comparison with smaller lakes. Over this 6 yr period, the mean lake ice-out for all lakes was 27 May and ranged from 07 May in Kenai to 06 July in Arctic Coastal Plain lake districts with relatively low inter-annual variability. Approximately 80% of the variation in ice-out timing was explained by the date of 0°C air temperature isotherm and lake area. Shoreline irregularity, watershed area, and river connectivity explained additional variation in some districts. Coherence in ice-out timing within the lakes of each district was consistently strong over this 6 yr period, ranging from r-values of 0.5 to 0.9. Inter-district analysis of coherence also showed synchronous ice-out patterns with the exception of the two arctic coastal districts where ice-out occurs later (June–July) and climatology is sea-ice influenced. These patterns of lake ice phenology provide a spatially extensive baseline describing short-term temporal variability, which will help decipher longer term trends in ice phenology and aid in representing the role of lake ice in land and climate models in northern landscapes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Limnology and Oceanography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Association for the Sciences of Limnology and Oceonography","doi":"10.4319/lo.2013.58.6.2013","usgsCitation":"Arp, C.D., Jones, B.M., and Grosse, G., 2013, Recent lake ice-out phenology within and among lake districts of Alaska, U.S.A.: Limnology and Oceanography, v. 58, no. 6, p. 2013-2028, https://doi.org/10.4319/lo.2013.58.6.2013.","productDescription":"16 p.","startPage":"2013","endPage":"2028","numberOfPages":"16","ipdsId":"IP-049175","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":473451,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4319/lo.2013.58.6.2013","text":"Publisher Index Page"},{"id":278877,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278876,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.4319/lo.2013.58.6.2013"}],"country":"United States","state":"Alaska","otherGeospatial":"Ahtna;Arctic Coastal Plain;Beringia;Denali;Kenai;Koyukuk;Matanuska-susitna;Minto Flats;Tetlin;Yukon Flats;Yukon-kuskokwim Delta","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -179.91,53.93 ], [ -179.91,72.18 ], [ -129.9,72.18 ], [ -129.9,53.93 ], [ -179.91,53.93 ] ] ] } } ] }","volume":"58","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-10-21","publicationStatus":"PW","scienceBaseUri":"527b6510e4b0a7295d9b55f0","contributors":{"authors":[{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":485684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":485683,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grosse, Guido","contributorId":101475,"corporation":false,"usgs":true,"family":"Grosse","given":"Guido","affiliations":[{"id":34291,"text":"University of Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":485685,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048864,"text":"70048864 - 2013 - On the correct name of <i>Icterus bullockii</i> (Passeriformes: Icteridae)","interactions":[],"lastModifiedDate":"2016-06-03T12:05:22","indexId":"70048864","displayToPublicDate":"2013-11-06T08:57:55","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3814,"text":"Zootaxa","onlineIssn":"1175-5334","printIssn":"1175-5326","active":true,"publicationSubtype":{"id":10}},"title":"On the correct name of <i>Icterus bullockii</i> (Passeriformes: Icteridae)","docAbstract":"<p>William Bullock was an Englishman who owned the Egyptian Hall (also known as the London Museum or Bullock&rsquo;s Museum) at Piccadilly in London, a museum opened in 1812 to display his collection of antiquities, artifacts, and natural history specimens. Following the sale of Bullock&rsquo;s collection in 1819, the Egyptian Hall served as an exhibition space. Bullock and his son, William Bullock, Jr., both enthusiastic naturalists, travelled in Mexico in 1822&ndash;1823, spending some six months together collecting natural history specimens and other artifacts for exhibition and investigating mining and other business opportunities (Costeloe 2006). The elder Bullock returned to London with the collections in 1823, but his son, while ostensibly managing the silver mine his father had purchased in Temascaltepec, outside of Mexico City, continued to travel in Mexico and collect specimens, often in the company of German naturalist Ferdinand Deppe (Costeloe 2006). William Bullock, Sr., meanwhile prepared the Mexican collection for exhibition at the Egyptian Hall. Twin exhibitions on ancient and modern Mexico opened, with much fanfare, in April 1824, and were a great success, remaining open until September 1825 (Costeloe 2006). Afterwards, the contents of the exhibitions were dispersed via auction, but not before Bullock had made the bird specimens available to English naturalist William Swainson for &ldquo;recording this portion of his discoveries&rdquo; (Swainson 1827: 365).</p>","language":"English","publisher":"Magnolia Press","doi":"10.11646/zootaxa.3718.3.6","usgsCitation":"Chesser, R., 2013, On the correct name of <i>Icterus bullockii</i> (Passeriformes: Icteridae): Zootaxa, v. 3718, no. 3, p. 295-296, https://doi.org/10.11646/zootaxa.3718.3.6.","productDescription":"2 p.","startPage":"295","endPage":"296","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051325","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":487406,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://zenodo.org/record/5275785","text":"External Repository"},{"id":278952,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3718","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-10-04","publicationStatus":"PW","scienceBaseUri":"527e586de4b02d2057dd95ed","contributors":{"authors":[{"text":"Chesser, R. Terry 0000-0003-4389-7092","orcid":"https://orcid.org/0000-0003-4389-7092","contributorId":87669,"corporation":false,"usgs":true,"family":"Chesser","given":"R. Terry","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":485765,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70048809,"text":"ds792 - 2013 - Hydrographic surveys of four narrows within the Namakan reservoir system, Voyageurs National Park, Minnesota, 2011","interactions":[],"lastModifiedDate":"2013-11-21T10:36:55","indexId":"ds792","displayToPublicDate":"2013-11-06T08:07:00","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":"792","title":"Hydrographic surveys of four narrows within the Namakan reservoir system, Voyageurs National Park, Minnesota, 2011","docAbstract":"The U.S. Geological Survey performed multibeam echosounder hydrographic surveys of four narrows in the Namakan reservoir system in August 2011, in cooperation with the International Joint Commission and Environment Canada. The data-collection effort was completed to provide updated and detailed hydrographic data to Environment Canada for inclusion in a Hydrologic Engineering Centers River Analysis System hydraulic model. The Namakan reservoir system is composed of Namakan, Kabetogama, Sand Point, Crane, and Little Vermilion Lakes. Water elevations in the Namakan reservoir system are regulated according to rule curves, or guidelines for water-level management based on the time of year, established by the International Joint Commission. Water levels are monitored by established gages on Crane Lake and the outlet of Namakan Lake at Kettle Falls, but water elevations throughout the system may deviate from these measured values by as much as 0.3 meters, according to lake managers and residents. Deviations from expected water elevations may be caused by between-lake constrictions (narrows). According to the 2000 Rule Curve Assessment Workgroup, hydrologic models of the reservoir system are needed to better understand the system and to evaluate the recent changes made to rule curves in 2000. \nHydrographic surveys were performed using a RESON SeaBat™7125 multibeam echosounder system. Surveys were completed at Namakan Narrows, Harrison Narrows, King Williams Narrows, and Little Vermilion Narrows. Hydrographic survey data were processed using Caris HIPS<sup>TM</sup> and SIPS<sup>TM</sup> software that interpolated a combined uncertainty and bathymetric estimator (CUBE) surface. Quality of the survey results was evaluated in relation to standards set by the International Hydrographic Organization (IHO) for describing the uncertainty of hydrographic surveys. More than 90 percent of the surveyed areas at the four narrows have resulting bed elevations that meet the IHO “Special Order” quality. Survey datasets published in this report are formatted as text files of x-y-z coordinates and as CARIS Spatial Archive<sup>TM</sup> (CSAR<sup>TM</sup>) files with corresponding metadata.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds792","collaboration":"Prepared in cooperation with the International Joint Commission and Environment Canada","usgsCitation":"Densmore, B.K., Strauch, K.R., and Ziegeweid, J.R., 2013, Hydrographic surveys of four narrows within the Namakan reservoir system, Voyageurs National Park, Minnesota, 2011: U.S. Geological Survey Data Series 792, Report: iv, 12 p.; Downloads Directory, https://doi.org/10.3133/ds792.","productDescription":"Report: iv, 12 p.; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-041944","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":278872,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds792.gif"},{"id":278871,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/792/downloads/"},{"id":278869,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/792/pdf/ds792.pdf"},{"id":278870,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/792/"}],"country":"United States","state":"Minnesota","otherGeospatial":"Voyageurs National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.760315,48.145931 ], [ -92.760315,48.466548 ], [ -92.397766,48.466548 ], [ -92.397766,48.145931 ], [ -92.760315,48.145931 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"527b650fe4b0a7295d9b55e6","contributors":{"authors":[{"text":"Densmore, Brenda K. 0000-0003-2429-638X bdensmore@usgs.gov","orcid":"https://orcid.org/0000-0003-2429-638X","contributorId":4896,"corporation":false,"usgs":true,"family":"Densmore","given":"Brenda","email":"bdensmore@usgs.gov","middleInitial":"K.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485688,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Strauch, Kellan R. 0000-0002-7218-2099 kstrauch@usgs.gov","orcid":"https://orcid.org/0000-0002-7218-2099","contributorId":1006,"corporation":false,"usgs":true,"family":"Strauch","given":"Kellan","email":"kstrauch@usgs.gov","middleInitial":"R.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ziegeweid, Jeffrey R. 0000-0001-7797-3044 jrziege@usgs.gov","orcid":"https://orcid.org/0000-0001-7797-3044","contributorId":4166,"corporation":false,"usgs":true,"family":"Ziegeweid","given":"Jeffrey","email":"jrziege@usgs.gov","middleInitial":"R.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485687,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70145850,"text":"70145850 - 2013 - Plant invasions in protected areas of tropical pacific islands, with special reference to Hawaii","interactions":[],"lastModifiedDate":"2018-01-05T12:36:12","indexId":"70145850","displayToPublicDate":"2013-11-06T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Plant invasions in protected areas of tropical pacific islands, with special reference to Hawaii","docAbstract":"<p>Isolated tropical islands are notoriously vulnerable to plant invasions. Serious management for protection of native biodiversity in Hawaii began in the 1970s, arguably at Hawaii Volcanoes National Park. Concerted alien plant management began there in the 1980s and has in a sense become a model for protected areas throughout Hawaii and Pacific Island countries and territories. We review the relative successes of their strategies and touch upon how their experience has been applied elsewhere. Protected areas in Hawaii are fortunate in having relatively good resources for addressing plant invasions, but many invasions remain intractable, and invasions from outside the boundaries continue from a highly globalised society with a penchant for horticultural novelty. There are likely few efforts in most Pacific Islands to combat alien plant invasions in protected areas, but such areas may often have fewer plant invasions as a result of their relative remoteness and/or socio-economic development status. The greatest current needs for protected areas in this region may be for establishment of yet more protected areas, for better resources to combat invasions in Pacific Island countries and territories, for more effective control methods including biological control programme to contain intractable species, and for meaningful efforts to address prevention and early detection of potential new invaders.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Plant Invasions in Protected Areas","language":"English","publisher":"Springer Netherlands","doi":"10.1007/978-94-007-7750-7_15","usgsCitation":"Hughes, R.F., Meyer, J., and Loope, L.L., 2013, Plant invasions in protected areas of tropical pacific islands, with special reference to Hawaii, chap. <i>of</i> Plant Invasions in Protected Areas, p. 313-348, https://doi.org/10.1007/978-94-007-7750-7_15.","productDescription":"35 p.","startPage":"313","endPage":"348","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-040712","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":311391,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.80810546875,\n              20.29311344754411\n            ],\n            [\n              -155.10498046875,\n              19.98367396609249\n            ],\n            [\n              -154.775390625,\n              19.559790136497398\n            ],\n            [\n              -154.852294921875,\n              19.34224499677179\n            ],\n   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Flint","contributorId":140151,"corporation":false,"usgs":false,"family":"Hughes","given":"R.","email":"","middleInitial":"Flint","affiliations":[{"id":13397,"text":"USDA Forest Service, fhughes@fs.fed.us","active":true,"usgs":false}],"preferred":false,"id":544461,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meyer, Jean-Yves","contributorId":120858,"corporation":false,"usgs":true,"family":"Meyer","given":"Jean-Yves","affiliations":[],"preferred":false,"id":544460,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loope, Lloyd L.","contributorId":107848,"corporation":false,"usgs":true,"family":"Loope","given":"Lloyd","email":"","middleInitial":"L.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":false,"id":579905,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048795,"text":"sir20135185 - 2013 - Reconnaissance investigation of the rough diamond resource potential and production capacity of Côte d’Ivoire","interactions":[],"lastModifiedDate":"2018-03-23T14:16:38","indexId":"sir20135185","displayToPublicDate":"2013-11-05T14:07:00","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":"2013-5185","title":"Reconnaissance investigation of the rough diamond resource potential and production capacity of Côte d’Ivoire","docAbstract":"Ethnic and political conflict developed into open civil war in Côte d’Ivoire in 2002, leading to a de facto partitioning of the country into the government-controlled south and the rebel-controlled north. Côte d’Ivoire’s two main diamond mining areas, Séguéla and Tortiya, are located in the north, under what was, until recently, rebel-controlled territory. In an effort to prevent proceeds from diamond mining from funding the conflict, the United Nations (UN) placed an embargo on the export of rough diamonds from Côte d’Ivoire in 2005. That same year, the Kimberley Process (KP), the international initiative charged with stemming the flow of conflict diamonds, acted to enforce this ban by adopting the Moscow Resolution on Côte d’Ivoire, which contained measures to prevent the infiltration of Ivorian diamonds into the legitimate global rough diamond trade. Though under scrutiny by the international community, diamond mining activities continued in Côte d’Ivoire, with artisanal miners exploiting both alluvial deposits in fluvial systems and primary kimberlitic dike deposits. However, because of the embargo, there has been no official record of diamond production since the conflict began in 2002. This lack of production statistics represents a significant data gap and hinders efforts by the KP to understand how illicitly produced diamonds may be entering the legitimate trade.\n\nThis study presents the results of a multiyear effort to monitor the diamond mining activities of Côte d’Ivoire’s two main diamond mining areas, Séguéla and Tortiya. An innovative approach was developed that integrates data acquired from archival reports and maps, high-resolution satellite imagery, and digital terrain modeling to assess the total diamond endowment of the Séguéla and Tortiya deposits and to calculate annual diamond production from 2006 to 2013. On the basis of currently available data, this study estimates that a total of 10,100,000 carats remain in Séguéla and a total of 1,100,000 carats remain in Tortiya. Production capacity was calculated for the two study areas for the years 2006–2010 and 2012–2013. Production capacity was found to range from between 38,000 carats and 375,000 carats in Séguéla and from 13,000 carats and 20,000 carats in Tortiya. Further, this study demonstrates that artisanal mining activities can be successfully monitored by using remote sensing and geologic modeling techniques. The production capacity estimates presented here fill a significant data gap and provide policy makers, the UN, and the KP with important information not otherwise available.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135185","collaboration":"Prepared under the auspices of the U.S. Department of State","usgsCitation":"Chirico, P., and Malpeli, K., 2013, Reconnaissance investigation of the rough diamond resource potential and production capacity of Côte d’Ivoire: U.S. Geological Survey Scientific Investigations Report 2013-5185, vi, 45 p., https://doi.org/10.3133/sir20135185.","productDescription":"vi, 45 p.","numberOfPages":"55","onlineOnly":"Y","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":278819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135185.jpg"},{"id":278810,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5185/pdf/sir2013-5185.pdf"},{"id":278809,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5185/"}],"projection":"Geographic Coordinate System","datum":"World Geodetic System 1984 Daturm","country":"Côte d’Ivoire","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -8.6064,4.1642 ], [ -8.6064,10.74 ], [ -2.4878,10.74 ], [ -2.4878,4.1642 ], [ -8.6064,4.1642 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"527a1368e4b051792d0148a2","contributors":{"authors":[{"text":"Chirico, Peter G.","contributorId":27086,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter G.","affiliations":[],"preferred":false,"id":485660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malpeli, Katherine C.","contributorId":55106,"corporation":false,"usgs":true,"family":"Malpeli","given":"Katherine C.","affiliations":[],"preferred":false,"id":485661,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70101798,"text":"70101798 - 2013 - Large scale snow water status monitoring: Comparison of different snow water products in the upper Colorado basins","interactions":[],"lastModifiedDate":"2022-04-13T17:03:52.638666","indexId":"70101798","displayToPublicDate":"2013-11-05T13:53:58","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Large scale snow water status monitoring: Comparison of different snow water products in the upper Colorado basins","docAbstract":"<p><span>We illustrate the ability to monitor the status of snow water content over large areas by using a spatially distributed snow accumulation and ablation model that uses data from a weather forecast model in the upper Colorado Basin. The model was forced with precipitation fields from the National Weather Service (NWS) Multi-sensor Precipitation Estimator (MPE) and the Tropical Rainfall Measuring Mission (TRMM) data-sets; remaining meteorological model input data were from NOAA's Global Forecast System (GFS) model output fields. The simulated snow water equivalent (SWE) was compared to SWEs from the Snow Data Assimilation System (SNODAS) and SNOwpack TELemetry system (SNOTEL) over a region of the western US that covers parts of the upper Colorado Basin. We also compared the SWE product estimated from the special sensor microwave imager (SSM/I) and scanning multichannel microwave radiometer (SMMR) to the SNODAS and SNOTEL SWE data-sets. Agreement between the spatial distributions of the simulated SWE with MPE data was high with both SNODAS and SNOTEL. Model-simulated SWE with TRMM precipitation and SWE estimated from the passive microwave imagery were not significantly correlated spatially with either SNODAS or the SNOTEL SWE. Average basin-wide SWE simulated with the MPE and the TRMM data were highly correlated with both SNODAS (</span><i>r</i><span>&nbsp;= 0.94 and&nbsp;</span><i>r</i><span>&nbsp;= 0.64; d.f. = 14 – d.f. = degrees of freedom) and SNOTEL (</span><i>r</i><span>&nbsp;= 0.93 and&nbsp;</span><i>r</i><span>&nbsp;= 0.68; d.f. = 14). The SWE estimated from the passive microwave imagery was significantly correlated with the SNODAS SWE (</span><i>r</i><span>&nbsp;= 0.55, d.f. = 9,&nbsp;</span><i>p</i><span>&nbsp;= 0.05) but was not significantly correlated with the SNOTEL-reported SWE values (</span><i>r</i><span>&nbsp;= 0.45, d.f. = 9,&nbsp;</span><i>p</i><span>&nbsp;= 0.05).The results indicate the applicability of the snow energy balance model for monitoring snow water content at regional scales when coupled with meteorological data of acceptable quality. The two snow water contents from the microwave imagery (SMMR and SSM/I) and the Utah Energy Balance forced with the TRMM precipitation data were found to be unreliable sources for mapping SWE in the study area; both data sets lacked discernible variability of snow water content between sites as seen in the SNOTEL and SNODAS SWE data. This study will contribute to better understanding the adequacy of data from weather forecast models, TRMM, and microwave imagery for monitoring status of the snow water content.</span></p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-17-5127-2013","usgsCitation":"Artan, G.A., Verdin, J., and Lietzow, R., 2013, Large scale snow water status monitoring: Comparison of different snow water products in the upper Colorado basins: Hydrology and Earth System Sciences, v. 17, p. 5127-5139, https://doi.org/10.5194/hess-17-5127-2013.","productDescription":"13 p.","startPage":"5127","endPage":"5139","ipdsId":"IP-018769","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473452,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-17-5127-2013","text":"Publisher Index Page"},{"id":286361,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Utah, Wyoming","otherGeospatial":"Colorado basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.8740234375,\n              37.16031654673677\n            ],\n            [\n              -105.1171875,\n              37.16031654673677\n            ],\n            [\n              -105.1171875,\n              44.11914151643737\n            ],\n            [\n              -110.8740234375,\n              44.11914151643737\n            ],\n            [\n              -110.8740234375,\n              37.16031654673677\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"17","noUsgsAuthors":false,"publicationDate":"2013-12-18","publicationStatus":"PW","scienceBaseUri":"535594a9e4b0120853e8c044","contributors":{"authors":[{"text":"Artan, G. A.","contributorId":50733,"corporation":false,"usgs":false,"family":"Artan","given":"G.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":492762,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Verdin, J. P. 0000-0003-0238-9657","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":33033,"corporation":false,"usgs":true,"family":"Verdin","given":"J. P.","affiliations":[],"preferred":false,"id":492761,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lietzow, R.","contributorId":89648,"corporation":false,"usgs":true,"family":"Lietzow","given":"R.","email":"","affiliations":[],"preferred":false,"id":492763,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70073846,"text":"70073846 - 2013 - Surface water quality in streams and rivers: Scaling, and climate change","interactions":[],"lastModifiedDate":"2022-12-13T16:52:57.590293","indexId":"70073846","displayToPublicDate":"2013-11-05T11:45:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"4.5","title":"Surface water quality in streams and rivers: Scaling, and climate change","docAbstract":"<p><span>This chapter explores spatial and temporal scaling and the impact of climate change on four basic water quality parameters: temperature, pH, dissolved oxygen, and suspended sediment. An introduction describing the conditions and changes in these water quality parameters is presented. Temporal scaling of water quality parameters is discussed on diel (24</span><span>&nbsp;</span><span>h), precipitation event, and seasonal time scales. Discussion of longitudinal scaling of these parameters is included as well. Effects of climate change are presented here with a focus on observed trends, modeling results, and confounding factors in predicting climate change-induced shifts in water quality. This review highlights how factors such as geographic location, land cover, and human perturbations can alter water quality trends in rivers and streams.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Comprehensive water quality and purification","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-382182-9.00064-5","usgsCitation":"Loperfido, J., 2013, Surface water quality in streams and rivers: Scaling, and climate change, chap. 4.5 <i>of</i> Comprehensive water quality and purification, v. 4, p. 87-105, https://doi.org/10.1016/B978-0-12-382182-9.00064-5.","productDescription":"20 p.","startPage":"87","endPage":"105","ipdsId":"IP-033755","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":284309,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7577e4b0b2908510a42b","contributors":{"authors":[{"text":"Loperfido, John","contributorId":74667,"corporation":false,"usgs":true,"family":"Loperfido","given":"John","email":"","affiliations":[],"preferred":false,"id":489132,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70048792,"text":"sir20135150 - 2013 - Estimating nitrate concentrations in groundwater at selected wells and springs in the surficial aquifer system and Upper Floridan aquifer, Dougherty Plain and Marianna Lowlands, Georgia, Florida, and Alabama, 2002-50","interactions":[],"lastModifiedDate":"2017-01-17T20:49:03","indexId":"sir20135150","displayToPublicDate":"2013-11-05T11:31:00","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":"2013-5150","title":"Estimating nitrate concentrations in groundwater at selected wells and springs in the surficial aquifer system and Upper Floridan aquifer, Dougherty Plain and Marianna Lowlands, Georgia, Florida, and Alabama, 2002-50","docAbstract":"Groundwater from the surficial aquifer system and Upper Floridan aquifer in the Dougherty Plain and Marianna Lowlands in southwestern Georgia, northwestern Florida, and southeastern Alabama is affected by elevated nitrate concentrations as a result of the vulnerability of the aquifer, irrigation water-supply development, and intensive agricultural land use. The region relies primarily on groundwater from the Upper Floridan aquifer for drinking-water and irrigation supply. Elevated nitrate concentrations in drinking water are a concern because infants under 6 months of age who drink water containing nitrate concentrations above the U.S. Environmental Protection Agency maximum contaminant level of 10 milligrams per liter as nitrogen can become seriously ill with blue baby syndrome.\n\nIn response to concerns about water quality in domestic wells and in springs in the lower Apalachicola–Chattahoochee–Flint River Basin, the Florida Department of Environmental Protection funded a study in cooperation with the U.S. Geological Survey to examine water quality in groundwater and springs that provide base flow to the Chipola River. A three-dimensional, steady-state, regional-scale groundwater-flow model and two local-scale models were used in conjunction with particle tracking to identify travel times and areas contributing recharge to six groundwater sites—three long-term monitor wells (CP-18A, CP-21A, and RF-41) and three springs (Jackson Blue Spring, Baltzell Springs Group, and Sandbag Spring) in the lower Apalachicola–Chattahoochee–Flint River Basin. Estimated nitrate input to groundwater at land surface, based on previous studies of nitrogen fertilizer sales and atmospheric nitrate deposition data, were used in the advective transport models for the period 2002 to 2050. Nitrate concentrations in groundwater samples collected from the six sites during 1993 to 2007 and groundwater age tracer data were used to calibrate the transport aspect of the simulations.\n\nMeasured nitrate concentrations (as nitrogen) in wells and springs sampled during the study ranged from 0.37 to 12.73 milligrams per liter. Average apparent ages of groundwater calculated from measurements of chlorofluorocarbon, sulfur hexafluoride, and tritium from wells CP-18A, CP-21A,and RF-41 were about 23, 29, and 32 years, respectively. Average apparent ages of groundwater from Baltzell Springs Group, Sandbag Spring, and Jackson Blue Spring were about 16, 18, and 19 years, respectively. Simulated travel times of particles from the six selected sites ranged from less than 1 day to 511 years; both the minimum and maximum particle travel times were estimated for water from Jackson Blue Spring. Median simulated travel times of particles were about 30, 38, and 62 years for Jackson Blue Spring, Sandbag Spring, and Baltzell Springs Group, respectively. Study results indicated that travel times for approximately 50 percent of the particles from all spring sites were less than 50 years. The median simulated travel times of particles arriving at receptor wells CP-18A, CP-21A, and RF-41 were about 50, 35, and 36 years, respectively. All particle travel times were within the same order of magnitude as the tracer-derived average apparent ages for water, although slightly older than the measured ages. Travel time estimates were substantially greater than the measured age for groundwater reaching well CP-18A, as confirmed by the average apparent age of water determined from tracers.\n\nLocal-scale particle-tracking models were used to predict nitrate concentrations in the three monitor wells and three springs from 2002 to 2050 for three nitrogen management scenarios: (1) fixed input of nitrate at the 2001 level, (2) reduction of nitrate inputs of 4 percent per year (from the previous year) from 2002 to 2050, and (3) elimination of nitrate input after 2001. Simulated nitrate concentrations in well CP-21A peaked at 7.82 milligrams per liter in 2030, and concentrations in background well RF-41 peaked at 1.10 milligrams per liter in 2020. The simulated particle travel times were longer than indicated by age dating analysis for groundwater in well CP-18A; to account for the poor calibration fit at this well, nitrate concentrations were shifted 21 years. With the shift, simulated nitrate concentrations in groundwater at CP-18A peaked at 13.76 milligrams per liter in 2026. For groundwater in Baltzell Springs Group, Jackson Blue Spring, and Sandbag Spring, simulated nitrate concentrations peaked at 3.77 milligrams per liter in 2006, 3.51 milligrams per liter in 2011, and 0.81 milligram per liter in 2018, respectively, under the three management scenarios. In management scenario 3 (elimination of nitrate input after 2001), simulated nitrate concentrations in Baltzell Springs Group decreased to less than background concentrations (0.10 milligram per liter) by 2033, and in Sandbag Spring concentrations decreased to less than background by 2041. Simulations using nitrate management scenarios 1 (fixed input of nitrate at 2001 levels) and 2 (reduction of 4.0 percent per year) indicate that nitrate concentrations in groundwater may remain above background concentrations through 2050 at all sites.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135150","collaboration":"National Water-Quality Assessment Program; Prepared in cooperation with the Florida Department of Environmental Protection","usgsCitation":"Crandall, C.A., Katz, B.G., and Berndt, M., 2013, Estimating nitrate concentrations in groundwater at selected wells and springs in the surficial aquifer system and Upper Floridan aquifer, Dougherty Plain and Marianna Lowlands, Georgia, Florida, and Alabama, 2002-50: U.S. Geological Survey Scientific Investigations Report 2013-5150, ix, 65 p., https://doi.org/10.3133/sir20135150.","productDescription":"ix, 65 p.","numberOfPages":"80","onlineOnly":"Y","temporalStart":"2002-01-01","temporalEnd":"2050-12-31","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":278706,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5150/"},{"id":278707,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5150/pdf/sir2013-5150.pdf"},{"id":278708,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135150.gif"}],"scale":"24000","projection":"Albers Equal-Area Conic Projection","country":"United States","state":"Alabama, Florida, Georgia","otherGeospatial":"Apalachicola River Basin, Chattahoochee River Basin, Flint River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -85.8626,29.8562 ], [ -85.8626,32.2922 ], [ -83.6061,32.2922 ], [ -83.6061,29.8562 ], [ -85.8626,29.8562 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"527a1367e4b051792d014898","contributors":{"authors":[{"text":"Crandall, Christy A. crandall@usgs.gov","contributorId":1091,"corporation":false,"usgs":true,"family":"Crandall","given":"Christy","email":"crandall@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":485654,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katz, Brian G. bkatz@usgs.gov","contributorId":1093,"corporation":false,"usgs":true,"family":"Katz","given":"Brian","email":"bkatz@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":485655,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berndt, Marian P.","contributorId":45296,"corporation":false,"usgs":true,"family":"Berndt","given":"Marian P.","affiliations":[],"preferred":false,"id":485656,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048789,"text":"ofr20131165 - 2013 - Uniform California earthquake rupture forecast, version 3 (UCERF3): the time-independent model","interactions":[],"lastModifiedDate":"2014-01-14T14:46:38","indexId":"ofr20131165","displayToPublicDate":"2013-11-05T10:36:00","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":"2013-1165","title":"Uniform California earthquake rupture forecast, version 3 (UCERF3): the time-independent model","docAbstract":"In this report we present the time-independent component of the Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3), which provides authoritative estimates of the magnitude, location, and time-averaged frequency of potentially damaging earthquakes in California. The primary achievements have been to relax fault segmentation assumptions and to include multifault ruptures, both limitations of the previous model (UCERF2). The rates of all earthquakes are solved for simultaneously, and from a broader range of data, using a system-level \"grand inversion\" that is both conceptually simple and extensible. The inverse problem is large and underdetermined, so a range of models is sampled using an efficient simulated annealing algorithm. The approach is more derivative than prescriptive (for example, magnitude-frequency distributions are no longer assumed), so new analysis tools were developed for exploring solutions. Epistemic uncertainties were also accounted for using 1,440 alternative logic tree branches, necessitating access to supercomputers. The most influential uncertainties include alternative deformation models (fault slip rates), a new smoothed seismicity algorithm, alternative values for the total rate of M≥5 events, and different scaling relationships, virtually all of which are new. As a notable first, three deformation models are based on kinematically consistent inversions of geodetic and geologic data, also providing slip-rate constraints on faults previously excluded because of lack of geologic data. The grand inversion constitutes a system-level framework for testing hypotheses and balancing the influence of different experts. For example, we demonstrate serious challenges with the Gutenberg-Richter hypothesis for individual faults. UCERF3 is still an approximation of the system, however, and the range of models is limited (for example, constrained to stay close to UCERF2). Nevertheless, UCERF3 removes the apparent UCERF2 overprediction of M6.5–7 earthquake rates and also includes types of multifault ruptures seen in nature. Although UCERF3 fits the data better than UCERF2 overall, there may be areas that warrant further site-specific investigation. Supporting products may be of general interest, and we list key assumptions and avenues for future model improvements.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131165","collaboration":"CGS Special Report 228, Southern California Earthquake Center Publication 1792","usgsCitation":"Field, E.H., Biasi, G.P., Bird, P., Dawson, T.E., Felzer, K., Jackson, D.D., Johnson, K.M., Jordan, T.H., Madden, C., Michael, A.J., Milner, K.R., Page, M.T., Parsons, T., Powers, P.M., Shaw, B., Thatcher, W.R., Weldon, R.J., Zeng, Y., and Working Group on California Earthquake Probabilities, 2013, Uniform California earthquake rupture forecast, version 3 (UCERF3): the time-independent model: U.S. Geological Survey Open-File Report 2013-1165, Report: xvi, 97 p.; Appendixes A-T; Table B1; Earthquake Catalog; 3 Supplemental Materials; Fault Section Data; Pre-inversion Analysis, https://doi.org/10.3133/ofr20131165.","productDescription":"Report: xvi, 97 p.; Appendixes A-T; Table B1; Earthquake Catalog; 3 Supplemental Materials; Fault Section Data; Pre-inversion Analysis","numberOfPages":"115","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":278709,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131165.jpg"},{"id":278704,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1165/"},{"id":278705,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1165/pdf/ofr2013-1165.pdf"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125.02,30.97 ], [ -125.02,42.98 ], [ -113.49,42.98 ], [ -113.49,30.97 ], [ -125.02,30.97 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"527a1368e4b051792d0148a8","contributors":{"authors":[{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":52242,"corporation":false,"usgs":true,"family":"Field","given":"Edward","email":"field@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":485644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biasi, Glenn P.","contributorId":20436,"corporation":false,"usgs":true,"family":"Biasi","given":"Glenn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":485638,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bird, Peter","contributorId":78643,"corporation":false,"usgs":true,"family":"Bird","given":"Peter","affiliations":[],"preferred":false,"id":485648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dawson, Timothy E.","contributorId":24429,"corporation":false,"usgs":false,"family":"Dawson","given":"Timothy","email":"","middleInitial":"E.","affiliations":[{"id":7099,"text":"Calif. 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Survey","active":true,"usgs":false}],"preferred":false,"id":485639,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Felzer, Karen R.","contributorId":40680,"corporation":false,"usgs":true,"family":"Felzer","given":"Karen R.","affiliations":[],"preferred":false,"id":485641,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jackson, David D.","contributorId":94762,"corporation":false,"usgs":true,"family":"Jackson","given":"David","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":485651,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Kaj M.","contributorId":92526,"corporation":false,"usgs":true,"family":"Johnson","given":"Kaj","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":485649,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jordan, Thomas H.","contributorId":75055,"corporation":false,"usgs":true,"family":"Jordan","given":"Thomas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":485647,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Madden, Christopher","contributorId":47280,"corporation":false,"usgs":true,"family":"Madden","given":"Christopher","affiliations":[],"preferred":false,"id":485642,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Michael, Andrew J. 0000-0002-2403-5019 michael@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-5019","contributorId":1280,"corporation":false,"usgs":true,"family":"Michael","given":"Andrew","email":"michael@usgs.gov","middleInitial":"J.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":485633,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Milner, Kevin R.","contributorId":63494,"corporation":false,"usgs":true,"family":"Milner","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":485645,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":485636,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Parsons, Thomas 0000-0002-0582-4338","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":26583,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","affiliations":[],"preferred":false,"id":485640,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Powers, Peter M. pmpowers@usgs.gov","contributorId":4434,"corporation":false,"usgs":true,"family":"Powers","given":"Peter","email":"pmpowers@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":485637,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Shaw, Bruce E.","contributorId":93810,"corporation":false,"usgs":true,"family":"Shaw","given":"Bruce E.","affiliations":[],"preferred":false,"id":485650,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Thatcher, Wayne R. 0000-0001-6324-545X thatcher@usgs.gov","orcid":"https://orcid.org/0000-0001-6324-545X","contributorId":2599,"corporation":false,"usgs":true,"family":"Thatcher","given":"Wayne","email":"thatcher@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":485635,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Weldon, Ray J. II","contributorId":47859,"corporation":false,"usgs":true,"family":"Weldon","given":"Ray","suffix":"II","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":485643,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Zeng, Yuehua zeng@usgs.gov","contributorId":1623,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuehua","email":"zeng@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":485634,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Working Group on California Earthquake Probabilities","contributorId":128141,"corporation":true,"usgs":false,"organization":"Working Group on California Earthquake Probabilities","id":535606,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}}
,{"id":70048772,"text":"fs20133056 - 2013 - The 3D Elevation Program: summary for California","interactions":[],"lastModifiedDate":"2016-08-17T16:03:05","indexId":"fs20133056","displayToPublicDate":"2013-11-04T08:57:00","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":"2013-3056","title":"The 3D Elevation Program: summary for California","docAbstract":"<p><span>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 California, elevation data are critical for infrastructure and construction management; natural resources conservation; flood risk management; wildfire management, planning, and response; agriculture and precision farming; geologic resource assessment and hazard mitigation; 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.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133056","usgsCitation":"Carswell, W., 2013, The 3D Elevation Program: summary for California: U.S. Geological Survey Fact Sheet 2013-3056, 2 p., https://doi.org/10.3133/fs20133056.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":278674,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133056.gif"},{"id":278672,"type":{"id":15,"text":"Index 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 \"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5278c216e4b0c04ac3417aa4","contributors":{"authors":[{"text":"Carswell, William J. Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":485603,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70136362,"text":"70136362 - 2013 - Genetics, recruitment, and migration patterns of Arctic Cisco (Coregonus autumnalis) in the Colville River, Alaska and Mackenzie River, Canada","interactions":[],"lastModifiedDate":"2014-12-30T16:03:57","indexId":"70136362","displayToPublicDate":"2013-11-01T16:15:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3093,"text":"Polar Biology","active":true,"publicationSubtype":{"id":10}},"title":"Genetics, recruitment, and migration patterns of Arctic Cisco (Coregonus autumnalis) in the Colville River, Alaska and Mackenzie River, Canada","docAbstract":"<p>Arctic cisco Coregonus autumnalis have a complex anadromous life history, many aspects of which remain poorly understood. Some life history traits of Arctic cisco from the Colville River, Alaska, and Mackenzie River basin, Canada, were investigated using molecular genetics, harvest data, and otolith microchemistry. The Mackenzie hypothesis, which suggests that Arctic cisco found in Alaskan waters originate from the Mackenzie River system, was tested using 11 microsatellite loci and a single mitochondrial DNA gene. No genetic differentiation was found among sample collections from the Colville River and the Mackenzie River system using molecular markers (P &gt; 0.19 in all comparisons). Model-based clustering methods also supported genetic admixture between sample collections from the Colville River and Mackenzie River basin. A reanalysis of recruitment patterns to Alaska, which included data from recent warm periods and suspected changes in atmospheric circulation patterns, still finds that recruitment is correlated to wind conditions. Otolith microchemistry (Sr/Ca ratios) confirmed repeated, annual movements of Arctic cisco between low-salinity habitats in winter and marine waters in summer.</p>","language":"English","publisher":"Springer-Verlag","publisherLocation":"Heidelberg","doi":"10.1007/s00300-013-1372-y","usgsCitation":"Zimmerman, C.E., Ramey, A.M., Turner, S., Mueter, F.J., Murphy, S., and Nielsen, J.L., 2013, Genetics, recruitment, and migration patterns of Arctic Cisco (Coregonus autumnalis) in the Colville River, Alaska and Mackenzie River, Canada: Polar Biology, v. 36, no. 11, p. 1543-1555, https://doi.org/10.1007/s00300-013-1372-y.","productDescription":"13 p.","startPage":"1543","endPage":"1555","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-022648","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":296953,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":296938,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1007/s00300-013-1372-y"}],"volume":"36","issue":"11","noUsgsAuthors":false,"publicationDate":"2013-07-12","publicationStatus":"PW","scienceBaseUri":"54dd2ba7e4b08de9379b345e","contributors":{"authors":[{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":537436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":537437,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Turner, S.","contributorId":18947,"corporation":false,"usgs":true,"family":"Turner","given":"S.","email":"","affiliations":[],"preferred":false,"id":537466,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mueter, Franz J.","contributorId":131144,"corporation":false,"usgs":false,"family":"Mueter","given":"Franz","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":537467,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murphy, S.","contributorId":91384,"corporation":false,"usgs":true,"family":"Murphy","given":"S.","email":"","affiliations":[],"preferred":false,"id":537468,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nielsen, Jennifer L.","contributorId":43722,"corporation":false,"usgs":true,"family":"Nielsen","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":537469,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70094485,"text":"70094485 - 2013 - Factors controlling floc settling velocity along a longitudinal estuarine transect","interactions":[],"lastModifiedDate":"2020-06-05T14:20:10.591306","indexId":"70094485","displayToPublicDate":"2013-11-01T15:14:12","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Factors controlling floc settling velocity along a longitudinal estuarine transect","docAbstract":"A 147 km longitudinal transect of flocculated cohesive sediment properties in San Francisco Bay (SFB) was conducted on June 17th, 2008. Our aim was to determine the factors that control floc settling velocity along the longitudinal axis of the estuary. The INSSEV-LF video system was used to measure floc diameters and settling velocities at 30 stations at a distance of 0.7 m above the estuary bed. Floc sizes (D) ranged from 22 μm to 639 μm and settling velocities (Ws) ranged between 0.04 mm·s<sup>− 1</sup> and 15.8 mm·s<sup>− 1</sup> during the longitudinal transect. Nearbed turbulent shear stresses throughout the transect duration were within the 0.2–0.5 Pa range which typically stimulates flocculation growth. The individual D–Ws–floc density plots suggest the suspended sediments encountered throughout SFB were composed of both muddy cohesive sediment and mixed sediments flocs. Mass-weighted population mean settling velocity (Ws<sub>mass</sub>) ranged from 0.5 mm·s<sup>− 1</sup> to 10 mm·s<sup>− 1</sup>. The macrofloc and microfloc (demarcation at 160 μm) sub-populations demonstrated parameterised settling velocities which spanned nearly double the range of the sample mean settling velocities (Ws<sub>mean</sub>). The macroflocs tended to dominate the suspended mass (up to 77% of the ambient suspended solid concentration; SSC) from San Pablo Bay to Carquinez Strait (the vicinity of the turbidity maximum zone). Microfloc mass was particularly significant (typically 60–100% of the SSC) in the northern section of South Bay and most of Central Bay. The transect took eleven hours to complete and was not fully synoptic. During slack tide, larger and faster settling flocs deposited, accounting for most of the longitudinal variability. The best single predictor of settling velocity was water velocity 39 min prior to sampling, not suspended-sediment concentration or salinity. Resuspension and settling lags are likely responsible for the lagged response of settling velocity to water velocity. The distribution of individual floc diameters and settling velocities indicates that floc density for a given floc diameter varies greatly. A small portion (a few percent) of suspended sediment mass in SFB is sand-sized and inclusion of sand in flocs appears likely. Fractal theory for cohesive sediment assumes that there is a single primary particle size that flocculates, which is not the case for these types of mixed sediment flocs. The wide variability in the physical, biological and chemical processes which contribute to flocculation within SFB means that spatial floc data is required in order to accurately represent the diverse floc dynamics present in the Bay system. The importance in determining accurate estimates of floc density has been highlighted by the SFB data, as these provide the basis for realistic distributions of floc dry mass and the mass settling flux across a floc population. However, although video floc sampling devices can produce the various floc property trends observed in SFB, good survey practice is still paramount. One can see that if the sampling coverage (i.e. data collection frequency) is poor, this could lead to potential mis-interpretations of the data and only limited conclusions may be drawn from such a restricted survey. For example, a limited survey (i.e. only 3 stations, compared to the 10 stations in the full survey) in South Bay produces an under-estimate in both the macrofloc SSC<sub>macro</sub> distribution by a factor of four and the Ws<sub>macro</sub> by a factor of two. To develop sediment transport numerical models for SFB, high quality floc size and settling data are needed to understand and simulate the depositional qualities of both suspended cohesive sediment and mixed sediments in San Francisco Bay. This study has shown that the most pragmatic solution is a physically-based approach, whereby the detailed flocs D vs. Ws spectra are parameterised in terms of their macrofloc and microfloc properties. This aids in model calibration, whilst retaining more of the dynamical aspects of the floc populations. All forms of flocculation are dynamically active processes, therefore it is important to also include both SSC and turbulence functions together with the floc data.","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2013.06.018","usgsCitation":"Manning, A., and Schoellhamer, D., 2013, Factors controlling floc settling velocity along a longitudinal estuarine transect: Marine Geology, v. 345, p. 266-280, https://doi.org/10.1016/j.margeo.2013.06.018.","productDescription":"15 p.","startPage":"266","endPage":"280","numberOfPages":"15","ipdsId":"IP-011207","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":282591,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.6349,37.4225 ], [ -122.6349,38.277 ], [ -121.6324,38.277 ], [ -121.6324,37.4225 ], [ -122.6349,37.4225 ] ] ] } } ] }","volume":"345","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd58fbe4b0b290850f86f5","contributors":{"editors":[{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":790422,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":790423,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":790424,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Manning, A.J.","contributorId":54106,"corporation":false,"usgs":true,"family":"Manning","given":"A.J.","email":"","affiliations":[],"preferred":false,"id":490618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490619,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70111902,"text":"70111902 - 2013 - A landscape-based assessment of climate change vulnerability for all native Hawaiian plants","interactions":[],"lastModifiedDate":"2014-07-01T15:05:56","indexId":"70111902","displayToPublicDate":"2013-11-01T14:54:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"TR HCSU-044","title":"A landscape-based assessment of climate change vulnerability for all native Hawaiian plants","docAbstract":"<p>In Hawaiʽi and elsewhere, research efforts have focused on two main approaches to determine the potential impacts of climate change on individual species: estimating species vulnerabilities and projecting responses of species to expected changes. We integrated these approaches by defining vulnerability as the inability of species to exhibit any of the responses necessary for persistence under climate change (i.e., tolerate projected changes, endure in microrefugia, or migrate to new climate-compatible areas, but excluding evolutionary adaptation).</p>\n<br/>\n<p>To operationalize this response-based definition of species vulnerability within a landscape-based analysis, we used current and future climate envelopes for each species to define zones across the landscape: the toleration zone; the microrefugia zone; and the migration zone. Using these response zones we calculated a diverse set of factors related to habitat area, quality, and distribution for each species, including the amount of habitat protection and fragmentation and areas projected to be lost to sea-level rise. We then calculated the probabilities of each species exhibiting these responses using a Bayesian network model and determined the overall climate change vulnerability of each species by using a vulnerability index. As a first iteration of a response-based species vulnerability assessment (VA), our landscape-based analysis effectively integrates species-distribution models into a Bayesian network-based VA that can be updated with improved models and data for more refined analyses in the future.</p>\n<br/>\n<p>Our results show that the species most vulnerable to climate change also tend to be species of conservation concern due to non-climatic threats (e.g., competition and predation from invasive species, land-use change). Also, many of Hawaiʽi’s taxa that are most vulnerable to climate change share characteristics with species that in the past were found to be at risk of extinction due to non-climatic threats (e.g., archipelago endemism, single-island endemism). Of particular concern are the numerous species that have no compatible-climate areas remaining by the year 2100. Species primarily associated with dry forests have higher vulnerability scores than species from any other habitat type. When examined at taxonomic levels above species, low vulnerabilities are concentrated in families and genera of generalists (e.g., ferns or sedges) and typically associated with mid-elevation wet habitats. Our results replicate findings from other regions that link higher species vulnerability with decreasing range size.</p>\n<br/>\n<p>This species VA is possibly the largest in scope ever conducted in the United States with over 1000 species considered, 319 of which are listed as endangered or threatened under the U.S. Endangered Species Act, filling a critical knowledge gap for resource managers in the region. The information in this assessment can help prioritize species for special conservation actions, guide the management of conservation areas, inform the selection of research and monitoring priorities, and support adaptive management planning and implementation.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Hawaii Cooperative Studies Unit Technical Report","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"University of Hawaii","publisherLocation":"Hilo, HI","usgsCitation":"Fortini, L.B., Price, J., Jacobi, J., Vorsino, A., Burgett, J., Brinck, K., Amidon, F., Miller, S., `Ohukani`ohi`a Gon, S., Koob, G., and Paxton, E., 2013, A landscape-based assessment of climate change vulnerability for all native Hawaiian plants, v, 134 p.","productDescription":"v, 134 p.","numberOfPages":"141","ipdsId":"IP-052457","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":289344,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288195,"type":{"id":15,"text":"Index Page"},"url":"https://hilo.hawaii.edu/hcsu/publications.php"}],"country":"United States","state":"Hawai'i","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -178.31,18.91 ], [ -178.31,28.4 ], [ -154.81,28.4 ], [ -154.81,18.91 ], [ -178.31,18.91 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53b3d860e4b07c5f79a7f324","contributors":{"authors":[{"text":"Fortini, Lucas B. 0000-0002-5781-7295 lfortini@usgs.gov","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":4645,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas","email":"lfortini@usgs.gov","middleInitial":"B.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":false,"id":494521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Price, Jonathan","contributorId":27789,"corporation":false,"usgs":true,"family":"Price","given":"Jonathan","affiliations":[],"preferred":false,"id":494524,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jacobi, James","contributorId":21073,"corporation":false,"usgs":true,"family":"Jacobi","given":"James","affiliations":[],"preferred":false,"id":494523,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vorsino, Adam","contributorId":29740,"corporation":false,"usgs":true,"family":"Vorsino","given":"Adam","affiliations":[],"preferred":false,"id":494525,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burgett, Jeff","contributorId":40132,"corporation":false,"usgs":true,"family":"Burgett","given":"Jeff","affiliations":[],"preferred":false,"id":494526,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brinck, Kevin W. 0000-0001-7581-2482 kbrinck@usgs.gov","orcid":"https://orcid.org/0000-0001-7581-2482","contributorId":3847,"corporation":false,"usgs":true,"family":"Brinck","given":"Kevin W.","email":"kbrinck@usgs.gov","affiliations":[],"preferred":false,"id":494520,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Amidon, Fred","contributorId":62934,"corporation":false,"usgs":false,"family":"Amidon","given":"Fred","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":494528,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, Steve","contributorId":77461,"corporation":false,"usgs":true,"family":"Miller","given":"Steve","email":"","affiliations":[],"preferred":false,"id":494529,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"`Ohukani`ohi`a Gon, Sam III","contributorId":60961,"corporation":false,"usgs":true,"family":"`Ohukani`ohi`a Gon","given":"Sam","suffix":"III","email":"","affiliations":[],"preferred":false,"id":494527,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Koob, Gregory","contributorId":12377,"corporation":false,"usgs":true,"family":"Koob","given":"Gregory","affiliations":[],"preferred":false,"id":494522,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Paxton, Eben H. 0000-0001-5578-7689 epaxton@usgs.gov","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":438,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben H.","email":"epaxton@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":false,"id":494519,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70094488,"text":"70094488 - 2013 - Comparison of sediment supply to San Francisco Bay from watersheds draining the Bay Area and the Central Valley of California","interactions":[],"lastModifiedDate":"2020-06-05T14:23:39.123768","indexId":"70094488","displayToPublicDate":"2013-11-01T14:39:58","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of sediment supply to San Francisco Bay from watersheds draining the Bay Area and the Central Valley of California","docAbstract":"Quantifying suspended sediment loads is important for managing the world's estuaries in the context of navigation, pollutant transport, wetland restoration, and coastal erosion. To address these needs, a comprehensive analysis was completed on sediment supply to San Francisco Bay from fluvial sources. Suspended sediment, optical backscatter, velocity data near the head of the estuary, and discharge data obtained from the output of a water balance model were used to generate continuous suspended sediment concentration records and compute loads to the Bay from the large Central Valley watershed. Sediment loads from small tributary watersheds around the Bay were determined using 235 station-years of suspended sediment data from 38 watershed locations, regression analysis, and simple modeling. Over 16 years, net annual suspended sediment load to the head of the estuary from its 154,000 km<sup>2</sup> Central Valley watershed varied from 0.13 to 2.58 (mean = 0.89) million metric t of suspended sediment, or an average yield of 11 metric t/km<sup>2</sup>/yr. Small tributaries, totaling 8145 km<sup>2</sup>, in the nine-county Bay Area discharged between 0.081 and 4.27 (mean = 1.39) million metric t with a mean yield of 212 metric t/km<sup>2</sup>/yr. The results indicate that the hundreds of urbanized and tectonically active tributaries adjacent to the Bay, which together account for just 5% of the total watershed area draining to the Bay and provide just 7% of the annual average fluvial flow, supply 61% of the suspended sediment. The small tributary loads are more variable (53-fold between years compared to 21-fold for the inland Central Valley rivers) and dominated fluvial sediment supply to the Bay during 10 out of 16 yr. If San Francisco Bay is typical of other estuaries in active tectonic or climatically variable coastal regimes, managers responsible for water quality, dredging and reusing sediment accumulating in shipping channels, or restoring wetlands in the world's estuaries may need to more carefully account for proximal small urbanized watersheds that may dominate sediment supply.","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2013.03.003","usgsCitation":"McKee, L., Lewicki, M., Schoellhamer, D., and Ganju, N., 2013, Comparison of sediment supply to San Francisco Bay from watersheds draining the Bay Area and the Central Valley of California: Marine Geology, v. 345, p. 47-62, https://doi.org/10.1016/j.margeo.2013.03.003.","productDescription":"16 p.","startPage":"47","endPage":"62","numberOfPages":"16","ipdsId":"IP-039414","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":282589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley, San Francisco Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.5303,37.0069 ], [ -123.5303,38.6941 ], [ -120.8716,38.6941 ], [ -120.8716,37.0069 ], [ -123.5303,37.0069 ] ] ] } } ] }","volume":"345","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd5213e4b0b290850f44fc","contributors":{"editors":[{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":2880,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":790428,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":790429,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":790430,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"McKee, L.J.","contributorId":84562,"corporation":false,"usgs":true,"family":"McKee","given":"L.J.","email":"","affiliations":[],"preferred":false,"id":490629,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lewicki, M.","contributorId":65379,"corporation":false,"usgs":true,"family":"Lewicki","given":"M.","email":"","affiliations":[],"preferred":false,"id":490628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490630,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ganju, Neil K. 0000-0002-1096-0465 nganju@usgs.gov","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":140088,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","email":"nganju@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":490627,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70041881,"text":"70041881 - 2013 - Identifying the dynamic characteristics of a dual core-wall and frame building in Chile using aftershocks of the 27 February 2010 (M<sub>w</sub>=8.8) Maule, Chile, earthquake","interactions":[],"lastModifiedDate":"2014-01-14T14:35:44","indexId":"70041881","displayToPublicDate":"2013-11-01T14:30:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Identifying the dynamic characteristics of a dual core-wall and frame building in Chile using aftershocks of the 27 February 2010 (M<sub>w</sub>=8.8) Maule, Chile, earthquake","docAbstract":"Following the 27 February 2010 (M<sub>w</sub> = 8.8) Offshore Maule, Chile earthquake, a temporary, 16-channel, real-time data streaming array was installed in a recently constructed building in Viña del Mar to capture its responses to aftershocks. The cast-in-place, reinforced concrete building is 16 stories high, with 3 additional basement levels, and has dual system comprising multiple structural walls and perimeter frames. This building was not damaged during the main-shock, but other buildings of similar design in Viña del Mar and other parts of Chile were damaged, although none collapsed. Dynamic characteristics of the building identified from the low-amplitude (PGA of about 2 Gal) response recordings of aftershocks are found to compare well with those determined from modal analyses using a design level FEM model. Distinct “major-axes” translational and torsional fundamental frequencies, as well as frequencies of secondary modes, are identified. Evidence of beating is consistently observed in the response data for each earthquake. Results do not match well with U.S. code formulas.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Earthquake Spectra","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1193/011812EQS012M","usgsCitation":"Çelebi, M., Sereci, M., Boroschek, R., Carreno, R., and Bonelli, P., 2013, Identifying the dynamic characteristics of a dual core-wall and frame building in Chile using aftershocks of the 27 February 2010 (M<sub>w</sub>=8.8) Maule, Chile, earthquake: Earthquake Spectra, v. 29, no. 4, p. 1233-1254, https://doi.org/10.1193/011812EQS012M.","productDescription":"22 p.","startPage":"1233","endPage":"1254","numberOfPages":"22","ipdsId":"IP-028467","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":281042,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281041,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1193/011812EQS012M"}],"country":"Chile","state":"Talca Province","city":"Maule","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -72.7899,-36.5457 ], [ -72.7899,-34.7119 ], [ -70.326,-34.7119 ], [ -70.326,-36.5457 ], [ -72.7899,-36.5457 ] ] ] } } ] }","volume":"29","issue":"4","noUsgsAuthors":false,"publicationDate":"2013-11-01","publicationStatus":"PW","scienceBaseUri":"53cd61fce4b0b290850fde02","contributors":{"authors":[{"text":"Çelebi, Mehmet","contributorId":27493,"corporation":false,"usgs":true,"family":"Çelebi","given":"Mehmet","affiliations":[],"preferred":false,"id":470289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sereci, Mark","contributorId":92969,"corporation":false,"usgs":true,"family":"Sereci","given":"Mark","email":"","affiliations":[],"preferred":false,"id":470291,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boroschek, Ruben","contributorId":32826,"corporation":false,"usgs":true,"family":"Boroschek","given":"Ruben","email":"","affiliations":[],"preferred":false,"id":470290,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carreno, Rodrigo","contributorId":21460,"corporation":false,"usgs":true,"family":"Carreno","given":"Rodrigo","email":"","affiliations":[],"preferred":false,"id":470288,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bonelli, Patricio","contributorId":14731,"corporation":false,"usgs":true,"family":"Bonelli","given":"Patricio","email":"","affiliations":[],"preferred":false,"id":470287,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70112524,"text":"70112524 - 2013 - Influence of history and environment on the sediment dynamics of intertidal flats","interactions":[],"lastModifiedDate":"2014-06-16T14:59:09","indexId":"70112524","displayToPublicDate":"2013-11-01T14:26:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Influence of history and environment on the sediment dynamics of intertidal flats","docAbstract":"<p>Morphological trends of three distinct intertidal environments in South San Francisco Bay were investigated using a combination of measurement and modeling tools. Because of the inherent relationship between the physical environment and the sediment properties, the sediment properties provide a good indicator of morphologic trends. A significant finding of this study is that surface sediment erodibility increases as the energy level in the environment increases. Conversely subsurface sediment erodibility shows a strong relationship to the long-term history of the site. The combination of the measured sediment properties, the history of deposition and erosion, and simple modeling of the physical environment illustrate the interaction of these properties such that an understanding of intertidal flat behavior is developed.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2013.05.011","usgsCitation":"Jones, C.A., and Jaffe, B.E., 2013, Influence of history and environment on the sediment dynamics of intertidal flats: Marine Geology, v. 345, p. 294-303, https://doi.org/10.1016/j.margeo.2013.05.011.","productDescription":"10 p.","startPage":"294","endPage":"303","numberOfPages":"10","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288652,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288650,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.margeo.2013.05.011"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.6229,37.333 ], [ -122.6229,38.2598 ], [ -121.1534,38.2598 ], [ -121.1534,37.333 ], [ -122.6229,37.333 ] ] ] } } ] }","volume":"345","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae774de4b0abf75cf2c0e7","contributors":{"editors":[{"text":"Barnard, P.L.","contributorId":20527,"corporation":false,"usgs":true,"family":"Barnard","given":"P.L.","email":"","affiliations":[],"preferred":false,"id":509892,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Jaffe, B.E.","contributorId":112487,"corporation":false,"usgs":true,"family":"Jaffe","given":"B.E.","email":"","affiliations":[],"preferred":false,"id":509894,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Schoellhamer, D. H. 0000-0001-9488-7340","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":85624,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"D. H.","affiliations":[],"preferred":false,"id":509893,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Jones, Craig A.","contributorId":92972,"corporation":false,"usgs":true,"family":"Jones","given":"Craig","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":494834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":494833,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70112523,"text":"70112523 - 2013 - Does centennial morphodynamic evolution lead to higher channel efficiency in San Pablo Bay, California?","interactions":[],"lastModifiedDate":"2020-06-05T14:44:42.854024","indexId":"70112523","displayToPublicDate":"2013-11-01T14:21:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Does centennial morphodynamic evolution lead to higher channel efficiency in San Pablo Bay, California?","docAbstract":"<p>Measured bathymetries on 30 year interval over the past 150 years show that San Pablo Bay experienced periods of considerable deposition followed by periods of net erosion. However, the main channel in San Pablo Bay has continuously narrowed. The underlying mechanisms and consequences of this tidal channel evolution are not well understood.</p>\n<br/>\n<p>The central question of this study is whether tidal channels evolve towards a geometry that leads to more efficient hydraulic conveyance and sediment throughput. We applied a hydrodynamic process-based, numerical model (Delft3D), which was run on 5 San Pablo Bay bathymetries measured between 1856 and 1983.</p>\n<br/>\n<p>Model results shows increasing energy dissipation levels for lower water flows leading to an approximately 15% lower efficiency in 1983 compared to 1856. During the same period the relative seaward sediment throughput through the San Pablo Bay main channel increased by 10%. A probable explanation is that San Pablo Bay is still affected by the excessive historic sediment supply. Sea level rise and Delta surface water area variations over 150 years have limited effect on the model results. With expected lower sediment concentrations in the watershed and less impact of wind waves due to erosion of the shallow flats, it is possible that energy dissipations levels will decrease again in future decades. Our study suggests that the morphodynamic adaptation time scale to excessive variations in sediment supply to estuaries may be on the order of centuries.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2013.06.020","usgsCitation":"van der Wegen, M., and Jaffe, B.E., 2013, Does centennial morphodynamic evolution lead to higher channel efficiency in San Pablo Bay, California?: Marine Geology, v. 345, p. 254-265, https://doi.org/10.1016/j.margeo.2013.06.020.","productDescription":"12 p.","startPage":"254","endPage":"265","numberOfPages":"12","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay, San Pablo Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.6229,37.333 ], [ -122.6229,38.2598 ], [ -121.1534,38.2598 ], [ -121.1534,37.333 ], [ -122.6229,37.333 ] ] ] } } ] }","volume":"345","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae768ae4b0abf75cf2bf93","contributors":{"editors":[{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":509889,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":509891,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":509890,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"van der Wegen, M.","contributorId":106720,"corporation":false,"usgs":true,"family":"van der Wegen","given":"M.","affiliations":[],"preferred":false,"id":494832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":494831,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70112522,"text":"70112522 - 2013 - Changes in surfzone morphodynamics driven by multi-decadal contraction of a large ebb-tidal delta","interactions":[],"lastModifiedDate":"2020-06-05T13:55:39.88378","indexId":"70112522","displayToPublicDate":"2013-11-01T14:16:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Changes in surfzone morphodynamics driven by multi-decadal contraction of a large ebb-tidal delta","docAbstract":"<p>The impact of multi-decadal, large-scale deflation (76 million m<sup>3</sup> of sediment loss) and contraction (~ 1 km) of a 150 km<sup>2</sup> ebb-tidal delta on hydrodynamics and sediment transport at adjacent Ocean Beach in San Francisco, CA (USA), is examined using a coupled wave and circulation model. The model is forced with representative wave and tidal conditions using recent (2005) and historic (1956) ebb-tidal delta bathymetry data sets. Comparison of the simulations indicates that along north/south trending Ocean Beach the contraction and deflation of the ebb-tidal delta have resulted in significant differences in the flow and sediment dynamics. Between 1956 and 2005 the transverse bar (the shallow attachment point of the ebb-tidal delta to the shoreline) migrated northward ~ 1 km toward the inlet while a persistent alongshore flow and transport divergence point migrated south by ~ 500 m such that these features now overlap. A reduction in tidal prism and sediment supply over the last century has resulted in a net decrease in offshore tidal current-generated sediment transport at the mouth of San Francisco Bay, and a relative increase in onshore-directed wave-driven transport toward the inlet, accounting for the observed contraction of the ebb-tidal delta. Alongshore migration of the transverse bar and alongshore flow divergence have resulted in an increasing proportion of onshore migrating sediment from the ebb-tidal delta to be transported north along the beach in 2005 versus south in 1956. The northerly migrating sediment is then trapped by Pt. Lobos, a rocky headland at the northern extreme of the beach, consistent with the observed shoreline accretion in this area. Conversely, alongshore migration of the transverse bar and divergence point has decreased the sediment supply to southern Ocean Beach, consistent with the observed erosion of the shoreline in this area. This study illustrates the utility of applying a high-resolution coupled circulation-wave model for understanding coastal response to large-scale bathymetric changes over multi-decadal timescales, common to many coastal systems adjacent to urbanized estuaries and watersheds worldwide.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2013.07.005","usgsCitation":"Hansen, J., Elias, E., and Barnard, P., 2013, Changes in surfzone morphodynamics driven by multi-decadal contraction of a large ebb-tidal delta: Marine Geology, v. 345, p. 221-234, https://doi.org/10.1016/j.margeo.2013.07.005.","productDescription":"14 p.","startPage":"221","endPage":"234","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.2546,37.333 ], [ -123.2546,38.2598 ], [ -121.9279,38.2598 ], [ -121.9279,37.333 ], [ -123.2546,37.333 ] ] ] } } ] }","volume":"345","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7652e4b0abf75cf2bf24","contributors":{"editors":[{"text":"Barnard, P.L.","contributorId":20527,"corporation":false,"usgs":true,"family":"Barnard","given":"P.L.","email":"","affiliations":[],"preferred":false,"id":509886,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Jaffe, B.E.","contributorId":112487,"corporation":false,"usgs":true,"family":"Jaffe","given":"B.E.","email":"","affiliations":[],"preferred":false,"id":509888,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Schoellhamer, D. H. 0000-0001-9488-7340","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":85624,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"D. H.","affiliations":[],"preferred":false,"id":509887,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Hansen, Jeff E.","contributorId":60339,"corporation":false,"usgs":true,"family":"Hansen","given":"Jeff E.","affiliations":[],"preferred":false,"id":494830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elias, Edwin","contributorId":50615,"corporation":false,"usgs":true,"family":"Elias","given":"Edwin","affiliations":[],"preferred":false,"id":494828,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick L.","contributorId":54936,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","affiliations":[],"preferred":false,"id":494829,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70112515,"text":"70112515 - 2013 - Understanding processes controlling sediment transports at the mouth of a highly energetic inlet system (San Francisco Bay, CA)","interactions":[],"lastModifiedDate":"2020-06-05T14:37:04.752704","indexId":"70112515","displayToPublicDate":"2013-11-01T14:12:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Understanding processes controlling sediment transports at the mouth of a highly energetic inlet system (San Francisco Bay, CA)","docAbstract":"<p>San Francisco Bay is one of the largest estuaries along the U.S. West Coast and is linked to the Pacific Ocean through the Golden Gate, a 100 m deep bedrock inlet. A coupled wave, flow and sediment transport model is used to quantify the sediment linkages between San Francisco Bay, the Golden Gate, and the adjacent open coast. Flow and sediment transport processes are investigated using an ensemble average of 24 climatologically derived wave cases and a 24.8 h representative tidal cycle. The model simulations show that within the inlet, flow and sediment transport is tidally dominated and driven by asymmetry of the ebb and flood tides. Peak ebb velocities exceed the peak flood velocities in the narrow Golden Gate channel as a result of flow convergence and acceleration. Persistent flow and sediment gyres at the headland tips are formed that limit sediment transfer from the ebb-tidal delta to the inlet and into the bay. The residual transport pattern in the inlet is dominated by a lateral segregation with a large ebb-dominant sediment transport (and flow) prevailing along the deeper north side of the Golden Gate channel, and smaller flood dominant transports along the shallow southern margin. The seaward edge of the ebb-tidal delta largely corresponds to the seaward extent of strong tidal flows. On the ebb-tidal delta, both waves and tidal forcing govern flow and sediment transport. Wave focusing by the ebb-tidal delta leads to strong patterns of sediment convergence and divergence along the adjacent Ocean Beach.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2012.07.003","usgsCitation":"Elias, E.P., and Hansen, J., 2013, Understanding processes controlling sediment transports at the mouth of a highly energetic inlet system (San Francisco Bay, CA): Marine Geology, v. 345, p. 207-220, https://doi.org/10.1016/j.margeo.2012.07.003.","productDescription":"14 p.","startPage":"207","endPage":"220","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":288645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.47695922851562,\n              37.80327385185868\n            ],\n            [\n              -122.47695922851562,\n              38.381498197198816\n            ],\n            [\n              -121.48818969726561,\n              38.591113776147445\n            ],\n            [\n              -121.05697631835938,\n              38.052416771864834\n            ],\n            [\n              -121.53762817382814,\n              37.80327385185868\n            ],\n            [\n              -122.47695922851562,\n              37.80327385185868\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"345","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7881e4b0abf75cf2d7f7","contributors":{"editors":[{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":509883,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":509885,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":509884,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Elias, Edwin P.L.","contributorId":47295,"corporation":false,"usgs":true,"family":"Elias","given":"Edwin","email":"","middleInitial":"P.L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":494821,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Jeff E.","contributorId":60339,"corporation":false,"usgs":true,"family":"Hansen","given":"Jeff E.","affiliations":[],"preferred":false,"id":494822,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70048764,"text":"fs20133070 - 2013 - Coastal processes influencing water quality at Great Lakes beaches","interactions":[],"lastModifiedDate":"2013-11-14T17:35:04","indexId":"fs20133070","displayToPublicDate":"2013-11-01T14:09:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3070","title":"Coastal processes influencing water quality at Great Lakes beaches","docAbstract":"In a series of studies along the Great Lakes, U.S. Geological Survey scientists are examining the physical processes that influence concentrations of fecal indicator bacteria and related pathogens at recreational beaches. These studies aim to estimate human health risk, improve management strategies, and understand the fate and transport of microbes in the nearshore area. It was determined that embayed beaches act as traps, accumulating <i>Escherichia coli (E. coli)</i> and other bacteria in the basin and even in beach sand. Further, shear stress and wave run-up could resuspend accumulated bacteria, leading to water-contamination events. These findings are being used to target beach design and circulation projects. In previous research, it was determined that <i>E. coli</i> followed a diurnal pattern, with concentrations decreasing throughout the day, largely owing to solar inactivation, but rebounding overnight. Studies at a Chicago beach identified the impact of wave-induced mass transport on this phenomenon, a finding that will extend our understanding of bacterial fate in the natural environment. In another series of studies, scientists examined the impact of river outfalls on bacteria concentrations, using mechanistic and empirical modeling. Through these studies, the models can indicate range and extent of impact, given <i>E. coli</i> concentration in the source water. These findings have been extended to extended lengths of coastlines and have been applied in beach management using empirical predictive modeling. Together, these studies are helping scientists identify and eliminate threats to human and coastal health.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133070","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2013, Coastal processes influencing water quality at Great Lakes beaches: U.S. Geological Survey Fact Sheet 2013-3070, 4 p., https://doi.org/10.3133/fs20133070.","productDescription":"4 p.","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":278649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133070.gif"},{"id":278647,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3070/pdf/fs2013-3070.pdf"},{"id":278648,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3070/"}],"country":"United States","otherGeospatial":"Great Lakes Beaches","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5274c67de4b089748f071324","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":535604,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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