The Colorado River and its tributaries supply water to more than 35 million people in the United States and 3 million people in Mexico, irrigating over 4.5 million acres of farmland, and annually generating about 12 billion kilowatt hours of hydroelectric power. The Upper Colorado River Basin, part of the Colorado River Basin, encompasses more than 110,000 mi2 and is the source of much of more than 9 million tons of dissolved solids that annually flows past the Hoover Dam. High dissolved-solids concentrations in the river are the cause of substantial economic damages to users, primarily in reduced agricultural crop yields and corrosion, with damages estimated to be greater than 300 million dollars annually. In 1974, the Colorado River Basin Salinity Control Act created the Colorado River Basin Salinity Control Program to investigate and implement a broad range of salinity control measures. A 2009 study by the U.S. Geological Survey, supported by the Salinity Control Program, used the Spatially Referenced Regressions on Watershed Attributes surface-water quality model to examine dissolved-solids supply and transport within the Upper Colorado River Basin. Dissolved-solids loads developed for 218 monitoring sites were used to calibrate the 2009 Upper Colorado River Basin Spatially Referenced Regressions on Watershed Attributes dissolved-solids model. This study updates and develops new dissolved-solids loading estimates for 323 Upper Colorado River Basin monitoring sites using streamflow and dissolved-solids concentration data through 2012, to support a planned Spatially Referenced Regressions on Watershed Attributes modeling effort that will investigate the contributions to dissolved-solids loads from irrigation and rangeland practices.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141148","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Tillman, F., and Anning, D.W., 2014, Updated estimates of long-term average dissolved-solids loading in streams and rivers of the Upper Colorado River Basin: U.S. Geological Survey Open-File Report 2014-1148, Report: v, 10 p.; Appendixes 1-2, https://doi.org/10.3133/ofr20141148.","productDescription":"Report: v, 10 p.; Appendixes 1-2","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051915","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":291789,"type":{"id":15,"text":"Index 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Water Science Center","active":true,"usgs":true}],"preferred":false,"id":495814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anning, David W. dwanning@usgs.gov","contributorId":432,"corporation":false,"usgs":true,"family":"Anning","given":"David","email":"dwanning@usgs.gov","middleInitial":"W.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":495813,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70110586,"text":"sim3300 - 2014 - An expanded model: flood-inundation maps for the Leaf River at Hattiesburg, Mississippi, 2013","interactions":[],"lastModifiedDate":"2014-08-08T14:12:01","indexId":"sim3300","displayToPublicDate":"2014-08-06T11:21:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3300","title":"An expanded model: flood-inundation maps for the Leaf River at Hattiesburg, Mississippi, 2013","docAbstract":"Digital flood-inundation maps for a 6.8-mile reach of the Leaf River at Hattiesburg, Mississippi (Miss.), were created by the U.S. Geological Survey (USGS) in cooperation with the City of Hattiesburg, City of Petal, Forrest County, Mississippi Emergency Management Agency, Mississippi Department of Homeland Security, and the Emergency Management District. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Leaf River at Hattiesburg, Miss. (station no. 02473000). Current conditions for estimating near-real-time areas of inundation by use of USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/. In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http://water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that are often colocated with USGS streamgages. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.
\nIn this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated by using the most current stage-discharge relations at the Leaf River at Hattiesburg, Miss. streamgage (02473000) and documented high-water marks from recent and historical floods. The hydraulic model was then used to determine 13 water-surface profiles for flood stages at 1.0-foot intervals referenced to the streamgage datum and ranging from bankfull to approximately the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM, derived from light detection and ranging (lidar) data having a 0.6-foot vertical and 9.84-foot horizontal resolution) in order to delineate the area flooded at each water level.
\nDevelopment of the estimated flood inundation maps as described in this report update previously published inundation estimates by including reaches of the Bouie and Leaf Rivers above their confluence. The availability of these maps along with Internet information regarding current stage from USGS streamgages and forecasted stream stages from the NWS provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3300","collaboration":"Prepared in cooperation with the City of Hattiesburg, City of Petal, Forrest County, Mississippi Emergency Management Agency, Mississippi Department of Homeland Security, and the Emergency Management District and Prepared in collaboration with the National Weather Service","usgsCitation":"Storm, J.B., 2014, An expanded model: flood-inundation maps for the Leaf River at Hattiesburg, Mississippi, 2013: U.S. Geological Survey Scientific Investigations Map 3300, Report: vi, 8 p.; 13 Plates: 18.00 x 22.83 inches; Downloads Directory, https://doi.org/10.3133/sim3300.","productDescription":"Report: vi, 8 p.; 13 Plates: 18.00 x 22.83 inches; Downloads Directory","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-045674","costCenters":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true}],"links":[{"id":291773,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3300.jpg"},{"id":291775,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3300/pdf/mapsheets/sim3300_sheet11.pdf"},{"id":291774,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3300/pdf/mapsheets/sim3300_sheet1.pdf"},{"id":291779,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3300/pdf/mapsheets/sim3300_sheet2.pdf"},{"id":291780,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3300/pdf/mapsheets/sim3300_sheet3.pdf"},{"id":291781,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3300/pdf/mapsheets/sim3300_sheet4.pdf"},{"id":291782,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3300/pdf/mapsheets/sim3300_sheet5.pdf"},{"id":291776,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3300/pdf/mapsheets/sim3300_sheet10.pdf"},{"id":291777,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3300/pdf/mapsheets/sim3300_sheet12.pdf"},{"id":291778,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3300/pdf/mapsheets/sim3300_sheet13.pdf"},{"id":291783,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3300/pdf/mapsheets/sim3300_sheet6.pdf"},{"id":291784,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3300/pdf/mapsheets/sim3300_sheet7.pdf"},{"id":291785,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3300/pdf/mapsheets/sim3300_sheet9.pdf"},{"id":291786,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3300/pdf/mapsheets/sim3300_sheet8.pdf"},{"id":291770,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3300/"},{"id":291771,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3300/pdf/sim3300_pamphlet.pdf"},{"id":291772,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3300/downloads"}],"projection":"Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Mississippi","city":"Hattiesburg","otherGeospatial":"Leaf River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.314293,31.295882 ], [ -89.314293,31.363778 ], [ -89.243122,31.363778 ], [ -89.243122,31.295882 ], [ -89.314293,31.295882 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e3332ee4b0567f276f7cf8","contributors":{"authors":[{"text":"Storm, John B. 0000-0002-5657-536X jbstorm@usgs.gov","orcid":"https://orcid.org/0000-0002-5657-536X","contributorId":3684,"corporation":false,"usgs":true,"family":"Storm","given":"John","email":"jbstorm@usgs.gov","middleInitial":"B.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494070,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70175906,"text":"70175906 - 2014 - Seismicity, faulting, and structure of the Koyna-Warna seismic region, Western India from local earthquake tomography and hypocenter locations","interactions":[],"lastModifiedDate":"2016-08-20T15:32:00","indexId":"70175906","displayToPublicDate":"2014-08-06T10:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Seismicity, faulting, and structure of the Koyna-Warna seismic region, Western India from local earthquake tomography and hypocenter locations","docAbstract":"Although seismicity near Koyna Reservoir (India) has persisted for ~50 years and includes the largest induced earthquake (M 6.3) reported worldwide, the seismotectonic framework of the area is not well understood. We recorded ~1800 earthquakes from 6 January 2010 to 28 May 2010 and located a subset of 343 of the highest-quality earthquakes using the tomoDD code of Zhang and Thurber (2003) to better understand the framework. We also inverted first arrivals for 3-D Vp, Vs, and Vp/Vs and Poisson's ratio tomography models of the upper 12 km of the crust. Epicenters for the recorded earthquakes are located south of the Koyna River, including a high-density cluster that coincides with a shallow depth (<1.5 km) zone of relatively high Vp and low Vs (also high Vp/Vs and Poisson's ratios) near Warna Reservoir. This anomalous zone, which extends near vertically to at least 8 km depth and laterally northward at least 15 km, is likely a water-saturated zone of faults under high pore pressures. Because many of the earthquakes occur on the periphery of the fault zone, rather than near its center, the observed seismicity-velocity correlations are consistent with the concept that many of the earthquakes nucleate in fractures adjacent to the main fault zone due to high pore pressure. We interpret our velocity images as showing a series of northwest trending faults locally near the central part of Warna Reservoir and a major northward trending fault zone north of Warna Reservoir.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014JB010950","usgsCitation":"Dixit, M.M., Kumar, S., Catchings, R.D., Suman, K., Sarkar, D., and Sen, M., 2014, Seismicity, faulting, and structure of the Koyna-Warna seismic region, Western India from local earthquake tomography and hypocenter locations: Journal of Geophysical Research B: Solid Earth, v. 119, no. 8, p. 6372-6398, https://doi.org/10.1002/2014JB010950.","productDescription":"27 p.","startPage":"6372","endPage":"6398","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042844","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":472826,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014jb010950","text":"Publisher Index Page"},{"id":327121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India","state":"Maharashtra","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 73.7,\n 17.7\n ],\n [\n 73.7,\n 16.8\n ],\n [\n 74.2,\n 16.8\n ],\n [\n 74.2,\n 17.7\n ],\n [\n 73.7,\n 17.7\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"119","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-08-06","publicationStatus":"PW","scienceBaseUri":"57b97f29e4b03fd6b7db87d9","contributors":{"authors":[{"text":"Dixit, Madan M.","contributorId":173893,"corporation":false,"usgs":false,"family":"Dixit","given":"Madan","email":"","middleInitial":"M.","affiliations":[{"id":27315,"text":"National Geophysical Research Institute, India","active":true,"usgs":false}],"preferred":false,"id":646527,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kumar, Sanjay","contributorId":173894,"corporation":false,"usgs":false,"family":"Kumar","given":"Sanjay","email":"","affiliations":[{"id":27315,"text":"National Geophysical Research Institute, India","active":true,"usgs":false}],"preferred":false,"id":646528,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Catchings, Rufus D. 0000-0002-5191-6102 catching@usgs.gov","orcid":"https://orcid.org/0000-0002-5191-6102","contributorId":1519,"corporation":false,"usgs":true,"family":"Catchings","given":"Rufus","email":"catching@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":646524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Suman, K.","contributorId":173892,"corporation":false,"usgs":false,"family":"Suman","given":"K.","email":"","affiliations":[{"id":27315,"text":"National Geophysical Research Institute, India","active":true,"usgs":false}],"preferred":false,"id":646554,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sarkar, Dipankar","contributorId":173891,"corporation":false,"usgs":false,"family":"Sarkar","given":"Dipankar","email":"","affiliations":[{"id":27315,"text":"National Geophysical Research Institute, India","active":true,"usgs":false}],"preferred":false,"id":646525,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sen, M.K.","contributorId":94482,"corporation":false,"usgs":true,"family":"Sen","given":"M.K.","email":"","affiliations":[],"preferred":false,"id":646526,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70112364,"text":"sir20105090R - 2014 - Sandstone copper assessment of the Teniz Basin, Kazakhstan","interactions":[{"subject":{"id":70112364,"text":"sir20105090R - 2014 - Sandstone copper assessment of the Teniz Basin, Kazakhstan","indexId":"sir20105090R","publicationYear":"2014","noYear":false,"chapter":"R","title":"Sandstone copper assessment of the Teniz Basin, Kazakhstan"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2020-07-01T19:58:33.657374","indexId":"sir20105090R","displayToPublicDate":"2014-08-06T09:16:00","publicationYear":"2014","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":"2010-5090","chapter":"R","title":"Sandstone copper assessment of the Teniz Basin, Kazakhstan","docAbstract":"The U.S. Geological Survey (USGS) conducts national and global resource assessments (mineral, energy, water, and biological) to provide data and scientific analyses to support decision making. Three-part mineral resource assessments result in informed, unbiased, quantitative, and probabilistic estimates of undiscovered mineral resources and deposits. In particular, mineral assessment results inform decisions concerning land-use and mineral-resource development. A probabilistic mineral resource assessment of the sandstone subtype of sediment-hosted stratabound copper deposits in the Teniz Basin, Kazakhstan, was undertaken by the USGS.
\nThe Teniz Basin is located in Akmola Oblast, central and western Kazakhstan. With an areal extent of almost 78,000 km2, the basin contains many sediment-hosted stratabound copper prospects, none of which are well described, and the majority of which may belong to the sandstone subtype of sediment-hosted copper deposits. There are no known locations within the Teniz Basin currently mined for copper. Within the basin, however, map units permissive for the sandstone subtype of sediment-hosted stratabound copper deposits include (from oldest to youngest): the Middle Carboniferous Kiery Suite; the Middle to Upper Carboniferous Vladimirov Suite (a stratigraphic equivalent of the Dzhezkazgan Suite, Chu-Sarysu Basin); and the Upper Carboniferous or lowest Permian Kayraktin Suite. The multicolored sedimentary rocks of the Vladimirov Suite, in which 14 potentially ore-bearing horizons of gray beds have been recorded, have the greatest potential for undiscovered, sandstone subtype, sediment-hosted stratabound copper deposits.
\nA quantitative mineral resource assessment has been completed that (1) delineates one 49,714 km2 tract permissive for undiscovered, sandstone subtype, sediment-hosted stratabound copper deposits, and (2) provides probabilistic estimates of numbers of undiscovered deposits and probable amounts of copper resource contained in those deposits. The permissive tract delineated in this assessment encompasses no previously known sandstone subtype, sediment-hosted stratabound copper deposits. However, this assessment estimates (with 30 percent probability) that a mean of nine undiscovered sandstone subtype copper deposits may be present in the Teniz Basin and could contain a mean total of 8.9 million metric tons of copper and 7,500 metric tons of silver.
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hydraulic conductivity measurements","docAbstract":"Soil Survey Geographic Database (SSURGO) data are available for the entire United States, so are incorporated in many regional and national models of hydrology and environmental management. However, SSURGO does not provide an understanding of spatial variability and only includes saturated hydraulic conductivity (Ksat) values estimated from particle size analysis (PSA). This study showed model sensitivity to the substitution of SSURGO data with locally described soil properties or alternate methods of measuring Ksat. Incorporation of these different soil data sets significantly changed the results of hydrologic modeling as a consequence of the amount of space available to store soil water and how this soil water is moved downslope. Locally described soil profiles indicated a difference in Ksat when measured in the field vs. being estimated from PSA. This, in turn, caused a difference in which soil layers were incorporated in the hydrologic simulations using TOPMODEL, ultimately affecting how soil water storage was simulated. Simulations of free-flowing soil water, the amount of water traveling through pores too large to retain water against gravity, were compared with field observations of water in wells at five slope positions along a catena. Comparison of the simulated data with the observed data showed that the ability to model the range of conditions observed in the field varied as a function of three soil data sets (SSURGO and local field descriptions using PSA-derived Ksat or field-measured Ksat) and that comparison of absolute values of soil water storage are not valid if different characterizations of soil properties are used.
","language":"English","publisher":"Soil Science Society of America","doi":"10.2136/sssaj2014.01.0045","usgsCitation":"Williamson, T., Lee, B.D., Schoeneberger, P.J., McCauley, W.M., Indorante, S.J., and Owens, P.R., 2014, Simulating soil-water movement through loess-veneered landscapes using nonconsilient saturated hydraulic conductivity measurements: Soil Science Society of America Journal, v. 78, no. 4, p. 1320-1331, https://doi.org/10.2136/sssaj2014.01.0045.","productDescription":"12 p.","startPage":"1320","endPage":"1331","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051268","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":297589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","issue":"4","noUsgsAuthors":false,"publicationDate":"2014-08-06","publicationStatus":"PW","scienceBaseUri":"54dd2c58e4b08de9379b373e","contributors":{"authors":[{"text":"Williamson, Tanja N. tnwillia@usgs.gov","contributorId":452,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja N.","email":"tnwillia@usgs.gov","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":false,"id":518851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Brad D.","contributorId":138937,"corporation":false,"usgs":false,"family":"Lee","given":"Brad","email":"","middleInitial":"D.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":539372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schoeneberger, Philip J.","contributorId":138938,"corporation":false,"usgs":false,"family":"Schoeneberger","given":"Philip","email":"","middleInitial":"J.","affiliations":[{"id":6688,"text":"National Soil Survey Center, Natural Resources Conservation Service – United States Department of Agriculture. 100 Centennial Mall North, Lincoln, NE 68508, USA","active":true,"usgs":false}],"preferred":false,"id":539373,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCauley, W. M.","contributorId":138939,"corporation":false,"usgs":false,"family":"McCauley","given":"W.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":539374,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Indorante, Samuel J.","contributorId":138940,"corporation":false,"usgs":false,"family":"Indorante","given":"Samuel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":539375,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Owens, Phillip R.","contributorId":119740,"corporation":false,"usgs":false,"family":"Owens","given":"Phillip","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":518854,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70100418,"text":"fs20143029 - 2014 - Simulation of groundwater flow in the Edwards-Trinity and related aquifers in the Pecos County region, Texas","interactions":[],"lastModifiedDate":"2016-08-05T12:19:58","indexId":"fs20143029","displayToPublicDate":"2014-08-05T16:59:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3029","title":"Simulation of groundwater flow in the Edwards-Trinity and related aquifers in the Pecos County region, Texas","docAbstract":"The Edwards-Trinity aquifer, a major aquifer in the Pecos County region of western Texas, is a vital groundwater resource for agricultural, industrial, and public supply uses. Resource managers would like to better understand the future availability of water in the Edwards-Trinity aquifer in the Pecos County region and the effects of the possible increase or temporal redistribution of groundwater withdrawals. To that end, the U.S. Geological Survey (USGS), in cooperation with the Middle Pecos Groundwater Conservation District, Pecos County, City of Fort Stockton, Brewster County, and Pecos County Water Control and Improvement District No. 1, completed a comprehensive, integrated analysis of available hydrogeologic data to develop a groundwater-flow model of the Edwards-Trinity and related aquifers in parts of Brewster, Jeff Davis, Pecos, and Reeves Counties. Following calibration, the model was used to evaluate the sustainability of recent (2008) and projected water-use demands on groundwater resources in the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143029","collaboration":"Prepared in cooperation with Middle Pecos Groundwater Conservation District, Pecos County, City of Fort Stockton, Brewster County, and Pecos County Water Control and Improvement District No. 1","usgsCitation":"Thomas, J.V., 2014, Simulation of groundwater flow in the Edwards-Trinity and related aquifers in the Pecos County region, Texas: U.S. Geological Survey Fact Sheet 2014-3029, 6 p., https://doi.org/10.3133/fs20143029.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054256","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":291744,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143029.jpg"},{"id":291742,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3029/pdf/fs2014-3029.pdf"},{"id":291743,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3029/"}],"scale":"2000000","projection":"Albers Equal-Area Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Texas","county":"Pecos County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.50,30.25 ], [ -104.50,31.50 ], [ -101.50,31.50 ], [ -101.50,30.25 ], [ -104.50,30.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e1e1b5e4b0fe532be24a97","contributors":{"authors":[{"text":"Thomas, Jonathan V. 0000-0003-0903-9713 jvthomas@usgs.gov","orcid":"https://orcid.org/0000-0003-0903-9713","contributorId":2194,"corporation":false,"usgs":true,"family":"Thomas","given":"Jonathan","email":"jvthomas@usgs.gov","middleInitial":"V.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492194,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70099988,"text":"fs20143025 - 2014 - A multiphased approach to groundwater investigations for the Edwards-Trinity and related aquifers in the Pecos County region, Texas","interactions":[],"lastModifiedDate":"2016-08-05T12:21:45","indexId":"fs20143025","displayToPublicDate":"2014-08-05T16:54:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3025","title":"A multiphased approach to groundwater investigations for the Edwards-Trinity and related aquifers in the Pecos County region, Texas","docAbstract":"The Edwards-Trinity aquifer is a vital groundwater resource for agricultural, industrial, and public supply uses in the Pecos County region of western Texas. Resource managers would like to understand the future availability of water in the Edwards-Trinity aquifer in the Pecos County region and the effects of the possible increase or temporal redistribution of groundwater withdrawals. To provide resource managers with that information, the U.S. Geological Survey (USGS), in cooperation with the Middle Pecos Groundwater Conservation District, Pecos County, City of Fort Stockton, Brewster County, and Pecos County Water Control and Improvement District No. 1, completed a three-phase study of the Edwards-Trinity and related aquifers in parts of Brewster, Jeff Davis, Pecos, and Reeves Counties. The first phase was to collect groundwater, surface-water, geochemical, geophysical, and geologic data in the study area and develop a geodatabase of historical and collected data. Data compiled in the first phase of the study were used to develop the conceptual model in the second phase of the study. The third phase of the study involved the development and calibration of a numerical groundwater-flow model of the Edwards-Trinity aquifer to simulate groundwater conditions based on various groundwater-withdrawal scenarios. Analysis of well, geophysical, geochemical, and hydrologic data contributed to the development of the conceptual model in phase 1. Lithologic information obtained from well reports and geophysical data was used to describe the hydrostratigraphy and structural features of the groundwater-flow system, and aquifer-test data were used to estimate aquifer hydraulic properties. Geochemical data were used to evaluate groundwater-flow paths, water-rock interaction, aquifer interaction, and the mixing of water from different sources in phase 2. Groundwater-level data also were used to evaluate aquifer interaction, as well as to develop a potentiometric-surface map, delineate regional groundwater divides, and describe regional groundwater-flow paths. During phase 3, the data collected and compiled along with the conceptual information in the study area were incorporated into a numerical groundwater-flow model to evaluate the sustainability of recent (2008) and projected water-use demands on groundwater resources in the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143025","collaboration":"Prepared in cooperation with the Middle Pecos Groundwater Conservation District, Pecos County, City of Fort Stockton, Brewster County, and Pecos County Water Control and Improvement District No. 1","usgsCitation":"Thomas, J.V., 2014, A multiphased approach to groundwater investigations for the Edwards-Trinity and related aquifers in the Pecos County region, Texas: U.S. Geological Survey Fact Sheet 2014-3025, 6 p., https://doi.org/10.3133/fs20143025.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054855","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":291741,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143025.jpg"},{"id":291739,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3025/"},{"id":291740,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3025/pdf/fs2014-3025.pdf"}],"scale":"2000000","projection":"Albers Equal-Area Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Texas","county":"Pecos County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.00,30.25 ], [ -104.00,31.50 ], [ -102.00,31.50 ], [ -102.00,30.25 ], [ -104.00,30.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e1e1aee4b0fe532be24a4e","contributors":{"authors":[{"text":"Thomas, Jonathan V. 0000-0003-0903-9713 jvthomas@usgs.gov","orcid":"https://orcid.org/0000-0003-0903-9713","contributorId":2194,"corporation":false,"usgs":true,"family":"Thomas","given":"Jonathan","email":"jvthomas@usgs.gov","middleInitial":"V.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492101,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70119241,"text":"70119241 - 2014 - Remote sensing with simulated unmanned aircraft imagery for precision agriculture applications","interactions":[],"lastModifiedDate":"2015-01-13T09:23:45","indexId":"70119241","displayToPublicDate":"2014-08-05T15:48:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1942,"text":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Remote sensing with simulated unmanned aircraft imagery for precision agriculture applications","docAbstract":"An important application of unmanned aircraft systems (UAS) may be remote-sensing for precision agriculture, because of its ability to acquire images with very small pixel sizes from low altitude flights. The objective of this study was to compare information obtained from two different pixel sizes, one about a meter (the size of a small vegetation plot) and one about a millimeter. Cereal rye (Secale cereale) was planted at the Beltsville Agricultural Research Center for a winter cover crop with fall and spring fertilizer applications, which produced differences in biomass and leaf chlorophyll content. UAS imagery was simulated by placing a Fuji IS-Pro UVIR digital camera at 3-m height looking nadir. An external UV-IR cut filter was used to acquire true-color images; an external red cut filter was used to obtain color-infrared-like images with bands at near-infrared, green, and blue wavelengths. Plot-scale Green Normalized Difference Vegetation Index was correlated with dry aboveground biomass ( ${mbi {r}} = 0.58$ ), whereas the Triangular Greenness Index (TGI) was not correlated with chlorophyll content. We used the SamplePoint program to select 100 pixels systematically; we visually identified the cover type and acquired the digital numbers. The number of rye pixels in each image was better correlated with biomass ( ${mbi {r}} = 0.73$ ), and the average TGI from only leaf pixels was negatively correlated with chlorophyll content ( ${mbi {r}} = -0.72$ ). Thus, better information for crop requirements may be obtained using very small pixel sizes, but new algorithms based on computer vision are needed for analysis. It may not be necessary to geospatially register large numbers of photographs with very small pixel sizes. Instead, images could be analyzed as single plots along field transects.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Institute of Electrical and Electronics Engineers","publisherLocation":"New York, NY","doi":"10.1109/JSTARS.2014.2317876","usgsCitation":"Hunt, E.R., Daughtry, C.S., Mirsky, S.B., and Hively, W., 2014, Remote sensing with simulated unmanned aircraft imagery for precision agriculture applications: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, v. 7, no. 11, 6 p., https://doi.org/10.1109/JSTARS.2014.2317876.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056175","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":291733,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291680,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1109/JSTARS.2014.2317876"}],"volume":"7","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e1e1b5e4b0fe532be24a8f","contributors":{"authors":[{"text":"Hunt, E. Raymond Jr.","contributorId":60557,"corporation":false,"usgs":true,"family":"Hunt","given":"E.","suffix":"Jr.","email":"","middleInitial":"Raymond","affiliations":[],"preferred":false,"id":497598,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daughtry, Craig S.T.","contributorId":75863,"corporation":false,"usgs":true,"family":"Daughtry","given":"Craig","email":"","middleInitial":"S.T.","affiliations":[],"preferred":false,"id":497599,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mirsky, Steven B.","contributorId":88662,"corporation":false,"usgs":true,"family":"Mirsky","given":"Steven","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":497600,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":9391,"corporation":false,"usgs":true,"family":"Hively","given":"W. 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Many researchers have speculated on the origin and evolution of Cat Island in Mississippi, but uncertainty remains about whether or not the island is underlain completely or in part by deposits associated with the past growth of the Mississippi River delta. In part, this is due to a lack of comprehensive geological information offshore of the island that could augment previous stratigraphic interpretations based on terrestrial borings. An extensive survey of Cat Island and its surrounding waters was conducted, including shallow-water geophysics (e.g., high-resolution chirp seismic, side-scan sonar, and swath and single-beam bathymetry) and both terrestrial and marine vibracoring. High-resolution seismic data and vibracores from south and east of the island show two horizontally laminated silt units; marine radiocarbon dates indicate that they are St. Bernard delta complex (SBDC) deposits. Furthermore, seismic data reveal that the SBDC deposits taper off toward the southern shoreline of Cat Island and to the west, morphology consistent with the distal edge of a delta complex. The sedimentology and extent of each unit suggest that the lower unit may have been deposited during an earlier period of continuous river flow while the upper unit may represent reduced or sporadic river flow. OSL dates from the island platform (beneath beach ridge complexes) indicate three stages of terrestrial evolution: island emergence resulting from relative sea-level rise (~ 5400 ybp) island aggradation via littoral transport (~ 2500–4000 ybp) and island degradation due to delta-mediated changes in wave direction (present– ~ 3600 ybp). Finally, the combination of terrestrial and marine data shows that portions of Cat Island that are lower in elevation than the central part of the island are younger and are likely underlain by a thin layer of deltaic sediments. This underscores the potential for increased future vulnerability of barrier islands that develop adjacent to major river delta complexes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2014.05.021","usgsCitation":"Miselis, J.L., Buster, N.A., and Kindinger, J.L., 2014, Refining the link between the Holocene development of the Mississippi River Delta and the geologic evolution of Cat Island, MS: implications for delta-associated barrier islands: Marine Geology, v. 355, p. 274-290, https://doi.org/10.1016/j.margeo.2014.05.021.","productDescription":"17 p.","startPage":"274","endPage":"290","numberOfPages":"17","ipdsId":"IP-053421","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":291730,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291722,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.margeo.2014.05.021"}],"country":"United States","state":"Mississippi","otherGeospatial":"Cat Island;Mississippi River Delta","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.2,30.183333 ], [ -89.2,30.266667 ], [ -89.041667,30.266667 ], [ -89.041667,30.183333 ], [ -89.2,30.183333 ] ] ] } } ] }","volume":"355","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e1e1b4e4b0fe532be24a89","contributors":{"authors":[{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":497629,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buster, Noreen A. 0000-0001-5069-9284 nbuster@usgs.gov","orcid":"https://orcid.org/0000-0001-5069-9284","contributorId":3750,"corporation":false,"usgs":true,"family":"Buster","given":"Noreen","email":"nbuster@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":497628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kindinger, Jack L. jkindinger@usgs.gov","contributorId":815,"corporation":false,"usgs":true,"family":"Kindinger","given":"Jack","email":"jkindinger@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":497627,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70119244,"text":"70119244 - 2014 - Monitoring Everglades freshwater marsh water level using L-band synthetic aperture radar backscatter","interactions":[],"lastModifiedDate":"2014-08-05T15:15:12","indexId":"70119244","displayToPublicDate":"2014-08-05T15:06:00","publicationYear":"2014","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}},"title":"Monitoring Everglades freshwater marsh water level using L-band synthetic aperture radar backscatter","docAbstract":"The Florida Everglades plays a significant role in controlling floods, improving water quality, supporting ecosystems, and maintaining biodiversity in south Florida. Adaptive restoration and management of the Everglades requires the best information possible regarding wetland hydrology. We developed a new and innovative approach to quantify spatial and temporal variations in wetland water levels within the Everglades, Florida. We observed high correlations between water level measured at in situ gages and L-band SAR backscatter coefficients in the freshwater marsh, though C-band SAR backscatter has no close relationship with water level. Here we illustrate the complementarity of SAR backscatter coefficient differencing and interferometry (InSAR) for improved estimation of high spatial resolution water level variations in the Everglades. This technique has a certain limitation in applying to swamp forests with dense vegetation cover, but we conclude that this new method is promising in future applications to wetland hydrology research.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2014.03.031","usgsCitation":"Kim, J., Lu, Z., Jones, J., Shum, C., Lee, H., and Jia, Y., 2014, Monitoring Everglades freshwater marsh water level using L-band synthetic aperture radar backscatter: Remote Sensing of Environment, v. 150, p. 66-81, https://doi.org/10.1016/j.rse.2014.03.031.","productDescription":"16 p.","startPage":"66","endPage":"81","numberOfPages":"16","ipdsId":"IP-046291","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":291726,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291700,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2014.03.031"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -83.0,23.5 ], [ -83.0,27.5 ], [ -78.0,27.5 ], [ -78.0,23.5 ], [ -83.0,23.5 ] ] ] } } ] }","volume":"150","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e1e1b4e4b0fe532be24a83","contributors":{"authors":[{"text":"Kim, Jin-Woo","contributorId":69486,"corporation":false,"usgs":true,"family":"Kim","given":"Jin-Woo","affiliations":[],"preferred":false,"id":497614,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lu, Zhong 0000-0001-9181-1818 lu@usgs.gov","orcid":"https://orcid.org/0000-0001-9181-1818","contributorId":901,"corporation":false,"usgs":true,"family":"Lu","given":"Zhong","email":"lu@usgs.gov","affiliations":[],"preferred":true,"id":497610,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, John 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":497611,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shum, C. K.","contributorId":85373,"corporation":false,"usgs":true,"family":"Shum","given":"C. K.","affiliations":[],"preferred":false,"id":497615,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lee, Hyongki","contributorId":14748,"corporation":false,"usgs":true,"family":"Lee","given":"Hyongki","email":"","affiliations":[],"preferred":false,"id":497612,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jia, Yuanyuan","contributorId":35660,"corporation":false,"usgs":true,"family":"Jia","given":"Yuanyuan","email":"","affiliations":[],"preferred":false,"id":497613,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70119249,"text":"70119249 - 2014 - Density-stratified flow events in Great Salt Lake, Utah, USA: implications for mercury and salinity cycling","interactions":[],"lastModifiedDate":"2018-09-14T16:03:01","indexId":"70119249","displayToPublicDate":"2014-08-05T14:53:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":866,"text":"Aquatic Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Density-stratified flow events in Great Salt Lake, Utah, USA: implications for mercury and salinity cycling","docAbstract":"Density stratification in saline and hypersaline water bodies from throughout the world can have large impacts on the internal cycling and loading of salinity, nutrients, and trace elements. High temporal resolution hydroacoustic and physical/chemical data were collected at two sites in Great Salt Lake (GSL), a saline lake in the western USA, to understand how density stratification may influence salinity and mercury (Hg) distributions. The first study site was in a causeway breach where saline water from GSL exchanges with less saline water from a flow restricted bay. Near-surface-specific conductance values measured in water at the breach displayed a good relationship with both flow and wind direction. No diurnal variations in the concentration of dissolved (<0.45 μm) methylmercury (MeHg) were observed during the 24-h sampling period; however, the highest proportion of particulate Hgtotal and MeHg loadings was observed during periods of elevated salinity. The second study site was located on the bottom of GSL where movement of a high-salinity water layer, referred to as the deep brine layer (DBL), is restricted to a naturally occurring 1.5-km-wide “spillway” structure. During selected time periods in April/May, 2012, wind-induced flow reversals in a railroad causeway breach, separating Gunnison and Gilbert Bays, were coupled with high-velocity flow pulses (up to 55 cm/s) in the DBL at the spillway site. These flow pulses were likely driven by a pressure response of highly saline water from Gunnison Bay flowing into the north basin of Gilbert Bay. Short-term flow reversal events measured at the railroad causeway breach have the ability to move measurable amounts of salt and Hg from Gunnison Bay into the DBL. Future disturbance to the steady state conditions currently imposed by the railroad causeway infrastructure could result in changes to the existing chemical balance between Gunnison and Gilbert Bays. Monitoring instruments were installed at six additional sites in the DBL during October 2012 to assess impacts from any future modifications to the railroad causeway.","language":"English","publisher":"Springer","doi":"10.1007/s10498-014-9237-8","usgsCitation":"Naftz, D.L., Carling, G.T., Angeroth, C., Freeman, M., Rowland, R., and Pazmino, E., 2014, Density-stratified flow events in Great Salt Lake, Utah, USA: implications for mercury and salinity cycling: Aquatic Geochemistry, v. 20, no. 6, p. 547-571, https://doi.org/10.1007/s10498-014-9237-8.","productDescription":"25 p.","startPage":"547","endPage":"571","ipdsId":"IP-042028","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":291724,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291721,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10498-014-9237-8"}],"country":"United States","state":"Utah","otherGeospatial":"Great Salt Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -112.9012,40.6237 ], [ -112.9012,41.299 ], [ -111.8002,41.299 ], [ -111.8002,40.6237 ], [ -112.9012,40.6237 ] ] ] } } ] }","volume":"20","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-07-26","publicationStatus":"PW","scienceBaseUri":"53e1e1b3e4b0fe532be24a70","contributors":{"authors":[{"text":"Naftz, David L. 0000-0003-1130-6892 dlnaftz@usgs.gov","orcid":"https://orcid.org/0000-0003-1130-6892","contributorId":1041,"corporation":false,"usgs":true,"family":"Naftz","given":"David","email":"dlnaftz@usgs.gov","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":497621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carling, Gregory T.","contributorId":11964,"corporation":false,"usgs":true,"family":"Carling","given":"Gregory","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":497622,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Angeroth, Cory","contributorId":75070,"corporation":false,"usgs":true,"family":"Angeroth","given":"Cory","affiliations":[],"preferred":false,"id":497626,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Freeman, Michael","contributorId":51222,"corporation":false,"usgs":true,"family":"Freeman","given":"Michael","affiliations":[],"preferred":false,"id":497624,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rowland, Ryan","contributorId":43685,"corporation":false,"usgs":true,"family":"Rowland","given":"Ryan","affiliations":[],"preferred":false,"id":497623,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pazmino, Eddy","contributorId":62531,"corporation":false,"usgs":true,"family":"Pazmino","given":"Eddy","email":"","affiliations":[],"preferred":false,"id":497625,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70119129,"text":"70119129 - 2014 - Lateral baroclinic forcing enhances sediment transport from shallows to channel in an estuary","interactions":[],"lastModifiedDate":"2017-10-30T11:25:10","indexId":"70119129","displayToPublicDate":"2014-08-05T14:39:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Lateral baroclinic forcing enhances sediment transport from shallows to channel in an estuary","docAbstract":"We investigate the dynamics governing exchange of sediment between estuarine shallows and the channel based on field measurements at eight stations spanning the interface between the channel and the extensive eastern shoals of South San Francisco Bay. The study site is characterized by longitudinally homogeneous bathymetry and a straight channel, with friction more important than the Coriolis forcing. Data were collected for 3 weeks in the winter and 4 weeks in the late summer of 2009, to capture a range of hydrologic and meteorologic conditions. The greatest sediment transport from shallows to channel occurred during a pair of strong, late-summer wind events, with westerly winds exceeding 10 m/s for more than 24 h. A combination of wind-driven barotropic return flow and lateral baroclinic circulation caused the transport. The lateral density gradient was produced by differences in temperature and suspended sediment concentration (SSC). During the wind events, SSC-induced vertical density stratification limited turbulent mixing at slack tides in the shallows, increasing the potential for two-layer exchange. The temperature- and SSC-induced lateral density gradient was comparable in strength to salinity-induced gradients in South Bay produced by seasonal freshwater inflows, but shorter in duration. In the absence of a lateral density gradient, suspended sediment flux at the channel slope was directed towards the shallows, both in winter and during summer sea breeze conditions, indicating the importance of baroclinically driven exchange to supply of sediment from the shallows to the channel in South San Francisco Bay and systems with similar bathymetry.","language":"English","publisher":"Springer","doi":"10.1007/s12237-013-9748-3","usgsCitation":"Lacy, J.R., Gladding, S., Brand, A., Collignon, A., and Stacey, M., 2014, Lateral baroclinic forcing enhances sediment transport from shallows to channel in an estuary: Estuaries and Coasts, v. 37, no. 5, p. 1058-1077, https://doi.org/10.1007/s12237-013-9748-3.","productDescription":"20 p.","startPage":"1058","endPage":"1077","ipdsId":"IP-044083","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":291723,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"South San Francisco Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.262079,37.550057 ], [ -122.262079,37.610474 ], [ -122.16324,37.610474 ], [ -122.16324,37.550057 ], [ -122.262079,37.550057 ] ] ] } } ] }","volume":"37","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-01-15","publicationStatus":"PW","scienceBaseUri":"53e1e1b4e4b0fe532be24a7d","contributors":{"authors":[{"text":"Lacy, Jessica R. 0000-0002-2797-6172 jlacy@usgs.gov","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":3158,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"jlacy@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":497576,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gladding, Steve","contributorId":54481,"corporation":false,"usgs":false,"family":"Gladding","given":"Steve","email":"","affiliations":[{"id":12776,"text":"Department of Civil and Environmental Engineering, University of California, Berkeley, California, USA","active":true,"usgs":false}],"preferred":false,"id":497579,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brand, Andreas","contributorId":32415,"corporation":false,"usgs":false,"family":"Brand","given":"Andreas","email":"","affiliations":[{"id":12775,"text":"Department of Surface Waters – Research and Management, Swiss Federal Institute of Aquatic Science and Technology (Eawag), Kastanienbaum, Switzerland","active":true,"usgs":false}],"preferred":false,"id":497577,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collignon, Audric","contributorId":42895,"corporation":false,"usgs":true,"family":"Collignon","given":"Audric","email":"","affiliations":[],"preferred":false,"id":497578,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stacey, Mark T.","contributorId":94531,"corporation":false,"usgs":false,"family":"Stacey","given":"Mark T.","affiliations":[{"id":12776,"text":"Department of Civil and Environmental Engineering, University of California, Berkeley, California, USA","active":true,"usgs":false}],"preferred":false,"id":497580,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70119243,"text":"70119243 - 2014 - Comparison of surficial CO2 efflux to other measures of subsurface crude oil degradation","interactions":[],"lastModifiedDate":"2018-09-14T16:10:08","indexId":"70119243","displayToPublicDate":"2014-08-05T13:42:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Comparison of surficial CO2 efflux to other measures of subsurface crude oil degradation","title":"Comparison of surficial CO2 efflux to other measures of subsurface crude oil degradation","docAbstract":"At a spill site near Bemidji, Minnesota, crude oil at the water table has been undergoing anaerobic biodegradation for over 30 years. Previous work at this site has shown that methane produced from biodegradation of the oil migrates upward and is oxidized in a methanotrophic zone midway between the water table and the surface. To compare microbial activity measurement methods from multiple locations in the oil body, surficial carbon dioxide efflux, methanogen and methanotroph concentrations, and oil degradation state were collected. Carbon dioxide effluxes over the oil body averaged more than four times those at the background site. Methanotrophic bacteria concentrations measured using pmoA were over 105 times higher above the oil-contaminated sediments compared with the background site. Methanogenic archaea measured using mcrA ranged from 105 to over 107 in the oil and were below detection in the background. Methanogens correlated very well with methanotroph concentrations (r = 0.99), n-alkylcyclohexane losses as a proxy for degradation state (r = − 0.96), and somewhat less well with carbon dioxide efflux (r = 0.92). Carbon dioxide efflux similarly correlated to methanotroph concentrations (r = 0.90) and n-alkylcyclohexane losses (r = − 0.91).","language":"English","publisher":"Elsevier","doi":"10.1016/j.jconhyd.2014.06.006","usgsCitation":"Warren, E., Sihota, N.J., Hostettler, F.D., and Bekins, B.A., 2014, Comparison of surficial CO2 efflux to other measures of subsurface crude oil degradation: Journal of Contaminant Hydrology, v. 164, p. 275-284, https://doi.org/10.1016/j.jconhyd.2014.06.006.","productDescription":"10 p.","startPage":"275","endPage":"284","numberOfPages":"10","ipdsId":"IP-057108","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":291716,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291715,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jconhyd.2014.06.006"}],"projection":"Universal Transverse Mercator projection, Zone 15 N","datum":"North American Datum 1983","country":"United States","state":"Minnesota","city":"Bemidji","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.119972,47.559731 ], [ -95.119972,47.582258 ], [ -95.072165,47.582258 ], [ -95.072165,47.559731 ], [ -95.119972,47.559731 ] ] ] } } ] }","volume":"164","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e1e1b1e4b0fe532be24a66","contributors":{"authors":[{"text":"Warren, Ean ewarren@usgs.gov","contributorId":1351,"corporation":false,"usgs":true,"family":"Warren","given":"Ean","email":"ewarren@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":497607,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sihota, Natasha J.","contributorId":46431,"corporation":false,"usgs":true,"family":"Sihota","given":"Natasha","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":497609,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hostettler, Frances D. fdhostet@usgs.gov","contributorId":3383,"corporation":false,"usgs":true,"family":"Hostettler","given":"Frances","email":"fdhostet@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":497608,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bekins, Barbara A. 0000-0002-1411-6018 babekins@usgs.gov","orcid":"https://orcid.org/0000-0002-1411-6018","contributorId":1348,"corporation":false,"usgs":true,"family":"Bekins","given":"Barbara","email":"babekins@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":497606,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70119141,"text":"70119141 - 2014 - Bayesian historical earthquake relocation: an example from the 1909 Taipei earthquake","interactions":[],"lastModifiedDate":"2014-08-05T13:37:34","indexId":"70119141","displayToPublicDate":"2014-08-05T13:31:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Bayesian historical earthquake relocation: an example from the 1909 Taipei earthquake","docAbstract":"Locating earthquakes from the beginning of the modern instrumental period is complicated by the fact that there are few good-quality seismograms and what traveltimes do exist may be corrupted by both large phase-pick errors and clock errors. Here, we outline a Bayesian approach to simultaneous inference of not only the hypocentre location but also the clock errors at each station and the origin time of the earthquake. This methodology improves the solution for the source location and also provides an uncertainty analysis on all of the parameters included in the inversion. As an example, we applied this Bayesian approach to the well-studied 1909 Mw 7 Taipei earthquake. While our epicentre location and origin time for the 1909 Taipei earthquake are consistent with earlier studies, our focal depth is significantly shallower suggesting a higher seismic hazard to the populous Taipei metropolitan area than previously supposed.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Journal International","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Oxford University Press","publisherLocation":"Oxford, United Kingdom","doi":"10.1093/gji/ggu201","usgsCitation":"Minson, S.E., and Lee, W.H., 2014, Bayesian historical earthquake relocation: an example from the 1909 Taipei earthquake: Geophysical Journal International, v. 198, no. 3, p. 1419-1430, https://doi.org/10.1093/gji/ggu201.","productDescription":"12 p.","startPage":"1419","endPage":"1430","numberOfPages":"12","ipdsId":"IP-055022","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":472827,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggu201","text":"Publisher Index Page"},{"id":291706,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291626,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1093/gji/ggu201"}],"country":"Taiwan","city":"Taipei","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 119.0,21.0 ], [ 119.0,27.0 ], [ 124.0,27.0 ], [ 124.0,21.0 ], [ 119.0,21.0 ] ] ] } } ] }","volume":"198","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-07-03","publicationStatus":"PW","scienceBaseUri":"53e1e1b0e4b0fe532be24a5d","contributors":{"authors":[{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":497589,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, William H.K.","contributorId":76836,"corporation":false,"usgs":true,"family":"Lee","given":"William","email":"","middleInitial":"H.K.","affiliations":[],"preferred":false,"id":497590,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70111856,"text":"ofr20141111 - 2014 - Report of the River Master of the Delaware River for the period December 1, 2007-November 30, 2008","interactions":[],"lastModifiedDate":"2014-08-05T12:55:00","indexId":"ofr20141111","displayToPublicDate":"2014-08-05T12:43:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1111","title":"Report of the River Master of the Delaware River for the period December 1, 2007-November 30, 2008","docAbstract":"A Decree of the Supreme Court of the United States, entered June 7, 1954, established the position of Delaware River Master within the U.S. Geological Survey (USGS). In addition, the Decree authorizes diversions of water from the Delaware River Basin and requires compensating releases from certain reservoirs, owned by New York City, to be made under the supervision and direction of the River Master. The Decree stipulates that the River Master will furnish reports to the Court, not less frequently than annually. This report is the 55th Annual Report of the River Master of the Delaware River. It covers the 2008 River Master report year, the period from December 1, 2007, to November 30, 2008.
\nDuring the report year, precipitation in the upper Delaware River Basin was 49.79 inches (in.) or 114 percent of the 67 report-year average. Combined storage in Pepacton, Cannonsville, and Neversink Reservoirs remained high from December 2007 to May 2008. Reservoir storage decreased seasonally from June to late October, then increased gradually through the end of November. Delaware River operations during the year were conducted as stipulated by the Decree.
\nDiversions from the Delaware River Basin by New York City and New Jersey were in full compliance with the Decree. Reservoir releases were made as directed by the River Master at rates designed to meet the flow objective for the Delaware River at Montague, New Jersey, on 107 days during the report year. Releases were made at conservation rates—rates designed to relieve thermal stress and protect the fishery and aquatic habitat in the tailwaters of the reservoirs—on all other days.
\nDuring the report year, New York City and New Jersey complied fully with the terms of the Decree, and directives and requests of the River Master.
\nAs part of a long-term program, the quality of water in the Delaware Estuary between Trenton, New Jersey, and Reedy Island Jetty, Delaware, was monitored at various locations. Data on water temperature, specific conductance, dissolved oxygen, and pH were collected continuously by electronic instruments at four sites. Data on water temperature and specific conductance were collected intermittently at one site. In addition, selected water-quality data were collected at 19 sites on a twice-monthly basis and at 3 sites on a monthly basis.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141111","usgsCitation":"Krejmas, B.E., Paulachok, G.N., and Blanchard, S.F., 2014, Report of the River Master of the Delaware River for the period December 1, 2007-November 30, 2008: U.S. Geological Survey Open-File Report 2014-1111, vi, 78 p., https://doi.org/10.3133/ofr20141111.","productDescription":"vi, 78 p.","numberOfPages":"88","onlineOnly":"N","temporalStart":"2007-12-01","temporalEnd":"2008-11-30","ipdsId":"IP-053666","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":291694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141111.jpg"},{"id":291692,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1111/"},{"id":291693,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1111/pdf/of2014-1111.pdf"}],"country":"United States","state":"Delaware;New Jersey;New York;Pennsylvania","city":"New York City","otherGeospatial":"Delaware River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76.5,39.75 ], [ -76.5,42.5 ], [ -74.0,42.5 ], [ -74.0,39.75 ], [ -76.5,39.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e1e1b5e4b0fe532be24a92","contributors":{"authors":[{"text":"Krejmas, Bruce E.","contributorId":102501,"corporation":false,"usgs":true,"family":"Krejmas","given":"Bruce","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":494485,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paulachok, Gary N. gnpaulac@usgs.gov","contributorId":3500,"corporation":false,"usgs":true,"family":"Paulachok","given":"Gary","email":"gnpaulac@usgs.gov","middleInitial":"N.","affiliations":[],"preferred":true,"id":494483,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blanchard, Stephen F.","contributorId":54966,"corporation":false,"usgs":true,"family":"Blanchard","given":"Stephen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":494484,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70119135,"text":"70119135 - 2014 - Autonomous bed-sediment imaging-systems for revealing temporal variability of grain size","interactions":[],"lastModifiedDate":"2014-08-05T11:53:44","indexId":"70119135","displayToPublicDate":"2014-08-05T11:31:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2622,"text":"Limnology and Oceanography: Methods","active":true,"publicationSubtype":{"id":10}},"title":"Autonomous bed-sediment imaging-systems for revealing temporal variability of grain size","docAbstract":"We describe a remotely operated video microscope system, designed to provide high-resolution images of seabed sediments. Two versions were developed, which differ in how they raise the camera from the seabed. The first used hydraulics and the second used the energy associated with wave orbital motion. Images were analyzed using automated frequency-domain methods, which following a rigorous partially supervised quality control procedure, yielded estimates to within 20% of the true size as determined by on-screen manual measurements of grains. Long-term grain-size variability at a sandy inner shelf site offshore of Santa Cruz, California, USA, was investigated using the hydraulic system. Eighteen months of high frequency (min to h), high-resolution (μm) images were collected, and grain size distributions compiled. The data constitutes the longest known high-frequency record of seabed-grain size at this sample frequency, at any location. Short-term grain-size variability of sand in an energetic surf zone at Praa Sands, Cornwall, UK was investigated using the ‘wave-powered’ system. The data are the first high-frequency record of grain size at a single location of a highly mobile and evolving bed in a natural surf zone. Using this technology, it is now possible to measure bed-sediment-grain size at a time-scale comparable with flow conditions. Results suggest models of sediment transport at sandy, wave-dominated, nearshore locations should allow for substantial changes in grain-size distribution over time-scales as short as a few hours.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Limnology and Oceanography: Methods","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society of Limnology and Oceanography","publisherLocation":"Waco, TX","doi":"10.4319/lom.2014.12.390","usgsCitation":"Buscombe, D., Rubin, D.M., Lacy, J.R., Storlazzi, C., Hatcher, G., Chezar, H., Wyland, R., and Sherwood, C.R., 2014, Autonomous bed-sediment imaging-systems for revealing temporal variability of grain size: Limnology and Oceanography: Methods, v. 12, p. 390-406, https://doi.org/10.4319/lom.2014.12.390.","productDescription":"17 p.","startPage":"390","endPage":"406","numberOfPages":"17","ipdsId":"IP-045183","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":291683,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291617,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.4319/lom.2014.12.390"}],"country":"United Kingdom;United States","state":"California","county":"Cornwall","city":"Praa Sands;Santa Cruz","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.033333,36.933333 ], [ -122.033333,50.111704 ], [ -5.369593,50.111704 ], [ -5.369593,36.933333 ], [ -122.033333,36.933333 ] ] ] } } ] }","volume":"12","noUsgsAuthors":false,"publicationDate":"2014-06-24","publicationStatus":"PW","scienceBaseUri":"53e1e1b0e4b0fe532be24a55","contributors":{"authors":[{"text":"Buscombe, Daniel","contributorId":99414,"corporation":false,"usgs":true,"family":"Buscombe","given":"Daniel","affiliations":[],"preferred":false,"id":497587,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rubin, David M. 0000-0003-1169-1452 drubin@usgs.gov","orcid":"https://orcid.org/0000-0003-1169-1452","contributorId":3159,"corporation":false,"usgs":true,"family":"Rubin","given":"David","email":"drubin@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":497584,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lacy, Jessica R. 0000-0002-2797-6172 jlacy@usgs.gov","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":3158,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"jlacy@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":497583,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":77889,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt D.","affiliations":[],"preferred":false,"id":497586,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hatcher, Gerald","contributorId":10346,"corporation":false,"usgs":true,"family":"Hatcher","given":"Gerald","email":"","affiliations":[],"preferred":false,"id":497585,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chezar, Henry hchezar@usgs.gov","contributorId":2964,"corporation":false,"usgs":true,"family":"Chezar","given":"Henry","email":"hchezar@usgs.gov","affiliations":[],"preferred":true,"id":497582,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wyland, Robert","contributorId":99485,"corporation":false,"usgs":true,"family":"Wyland","given":"Robert","email":"","affiliations":[],"preferred":false,"id":497588,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":497581,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70112363,"text":"sir20145112 - 2014 - Historical channel-planform change of the Little Colorado River near Winslow, Arizona","interactions":[],"lastModifiedDate":"2023-05-26T15:22:05.63425","indexId":"sir20145112","displayToPublicDate":"2014-08-05T08:17:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5112","title":"Historical channel-planform change of the Little Colorado River near Winslow, Arizona","docAbstract":"This study evaluates channel-planform adjustment on an alluvial reach of the Little Colorado River and documents the geomorphic evolution of the channel through an analysis of aerial photographs and orthophotographs for the period 1936–2010. The Little Colorado River has adjusted to the effects of an extreme flood in 1923 and a subsequent decline in peak discharge and mean annual flow by channel narrowing: the channel width and area of the river have decreased by approximately 90 percent over the study period. Although deposition historically exceeds erosion, lateral migration exacerbates localized erosion, particularly near hydraulic controls. Despite repeated cutoff and avulsion, the Little Colorado River has steadily increased in length and sinuosity over a period of 74 years.
\nChanges in temperature and precipitation are likely affecting the discharge of the Little Colorado River near and downstream of Winslow, Ariz. Nonparametric methods of trend detection determine whether the probability distribution of temperature, precipitation, and peak streamflow has changed over time. Time-series plots of temperature and precipitation show statistically significant trends at the 99-percent-confidence level when evaluated with a Mann-Kendall test. An increasing trend was indicated in mean daily minimum air temperature (Tmin), whereas decreasing trends were indicated in both annual precipitation (Pann) and monsoon-seasonal precipitation (Pjas), as well as in peak discharge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145112","collaboration":"Prepared in cooperation with the Navajo Nation","usgsCitation":"Block, D.L., 2014, Historical channel-planform change of the Little Colorado River near Winslow, Arizona: U.S. Geological Survey Scientific Investigations Report 2014-5112, Report: v, 24 p.; 2 Plates: 26.0 x 44.0 inches and 21.85 x 16.67 inches; Database; Metadata: XML; Metadata: HTML, https://doi.org/10.3133/sir20145112.","productDescription":"Report: v, 24 p.; 2 Plates: 26.0 x 44.0 inches and 21.85 x 16.67 inches; Database; Metadata: XML; Metadata: HTML","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-049442","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":417501,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_100483.htm","linkFileType":{"id":5,"text":"html"}},{"id":291644,"rank":8,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145112.jpg"},{"id":291639,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2014/5112/pdf/sir2014-5112_plate1.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":291642,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2014/5112/downloads/sir2014-5112_metadata.xml"},{"id":291643,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2014/5112/downloads/sir2014-5112_metadata.html"},{"id":291640,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2014/5112/pdf/sir2014-5112_plate2.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":291637,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5112/","linkFileType":{"id":5,"text":"html"}},{"id":291641,"rank":1,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sir/2014/5112/downloads/sir2014-5112_database.zip"},{"id":291638,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5112/pdf/sir2014-5112.pdf","linkFileType":{"id":1,"text":"pdf"}}],"scale":"24000","projection":"Universal Transverse Mercator projection, zone 12","datum":"North American Datum 1983","country":"United States","state":"Arizona","otherGeospatial":"Little Colorado River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.0,35.0 ], [ -111.0,35.3 ], [ -110.6,35.3 ], [ -110.6,35.0 ], [ -111.0,35.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e1e1b4e4b0fe532be24a75","contributors":{"authors":[{"text":"Block, Debra L. 0000-0001-7348-3064 dblock@usgs.gov","orcid":"https://orcid.org/0000-0001-7348-3064","contributorId":3587,"corporation":false,"usgs":true,"family":"Block","given":"Debra","email":"dblock@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":494716,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70113233,"text":"sir20145090 - 2014 - Methods and equations for estimating peak streamflow per square mile in Virginia’s urban basins","interactions":[],"lastModifiedDate":"2014-08-04T15:59:07","indexId":"sir20145090","displayToPublicDate":"2014-08-04T15:35:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5090","title":"Methods and equations for estimating peak streamflow per square mile in Virginia’s urban basins","docAbstract":"Models are presented that describe Virginia urban area annual peak streamflow per square mile based on basin percent urban area and basin drainage area. Equations are provided to estimate Virginia urban peak flow per square mile of basin drainage area in each of the following annual exceedance probability categories: 0.995, 0.99, 0.95, 0.9, 0.8, 0.67, 0.5, 0.43, 0.2, 0.1, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 1.005, 1.01, 1.05, 1.11, 1.25, 1.49, 2.0, 2.3, 5, 10, 25, 50, 100, 200, and 500 years, respectively). Equations apply to Virginia drainage basins ranging in size from no less than 1.2 mi2 to no more than 2,400 mi2 containing at least 10 percent urban area, and not more than 96 percent urban area. A total of 115 Virginia drainage basins were analyzed. Actual-by-predicted plots and leverage plots for response variables and explanatory variables in each peak-flow annual exceedance probability category indicate robust model fits and significant explanatory power. Equations for 8 of 15 urban peak-flow response surface models yield R-square values greater than 0.8. Relations identified in statistical models, describing significant increases in urban peak stream discharges as basin urban area increases, affirm empirical relations reported in past studies of change in stream discharge, lag times, and physical streamflow processes, most notably those detailed for urban areas in northern Virginia.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145090","collaboration":"Prepared in cooperation with the Virginia Department of Transportation","usgsCitation":"Austin, S.H., 2014, Methods and equations for estimating peak streamflow per square mile in Virginia’s urban basins: U.S. Geological Survey Scientific Investigations Report 2014-5090, vii, 25 p., https://doi.org/10.3133/sir20145090.","productDescription":"vii, 25 p.","numberOfPages":"38","onlineOnly":"N","ipdsId":"IP-044243","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":291634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145090.jpg"},{"id":291633,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5090/pdf/sir2014-5090.pdf"},{"id":291632,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5090/"}],"projection":"Albers Equal Area projection","datum":"North American Datum 1983","country":"United States","state":"Virginia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.00,36.00 ], [ -84.00,40.00 ], [ -75.00,40.00 ], [ -75.00,36.00 ], [ -84.00,36.00 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e09030e4b0beb42bdc040e","contributors":{"authors":[{"text":"Austin, Samuel H. 0000-0001-5626-023X saustin@usgs.gov","orcid":"https://orcid.org/0000-0001-5626-023X","contributorId":153,"corporation":false,"usgs":true,"family":"Austin","given":"Samuel","email":"saustin@usgs.gov","middleInitial":"H.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":495008,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70117791,"text":"sir20145141 - 2014 - Watershed characteristics and water-quality trends and loads in 12 watersheds in Gwinnett County, Georgia","interactions":[],"lastModifiedDate":"2017-01-18T13:13:47","indexId":"sir20145141","displayToPublicDate":"2014-08-04T11:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5141","title":"Watershed characteristics and water-quality trends and loads in 12 watersheds in Gwinnett County, Georgia","docAbstract":"The U.S. Geological Survey, in cooperation with Gwinnett County Department of Water Resources, established a Long-Term Trend Monitoring (LTTM) program in 1996. The LTTM program is a comprehensive, long-term, water-quantity and water-quality monitoring program designed to document and analyze the hydrologic and water-quality conditions of selected watersheds of Gwinnett County, Georgia. Water-quality monitoring initially began in six watersheds and was expanded to another six watersheds in 2001.
\nAs part of the LTTM program, streamflow, precipitation, water temperature, specific conductance, and turbidity were measured continuously at the 12 watershed monitoring stations for water years 2004–09. In addition, discrete water-quality samples were collected seasonally from May through October (summer) and November through April (winter), including one base-flow and three stormflow event composite samples, during the study period. Samples were analyzed for nutrients (nitrogen and phosphorus), total organic carbon, trace elements (total lead and total zinc), total dissolved solids, and total suspended sediment (total suspended solids and suspended-sediment concentrations). The sampling scheme was designed to identify variations in water quality both hydrologically and seasonally.
\nThe 12 watersheds were characterized for basin slope, population density, land use for 2009, and the percentage of impervious area from 2000 to 2009. Precipitation in water years 2004–09 was about 18 percent below average, and the county experienced exceptional drought conditions and below average runoff in water years 2007 and 2008. Watershed water yields, the percentage of precipitation that results in runoff, typically are lower in low precipitation years and are higher for watersheds with the highest percentages of impervious areas.
\nA comparison of base-flow and stormflow water-quality samples indicates that turbidity and concentrations of total ammonia plus organic nitrogen, total nitrogen, total phosphorus, total organic carbon, total lead, total zinc, total suspended solids, and suspended-sediment concentrations increased with increasing discharge at all watersheds. Specific conductance, however, decreased during stormflow at all watersheds, and total dissolved solids concentrations decreased during stormflow at a few of the watersheds. Total suspended solids and suspended-sediment concentrations typically were two orders of magnitude higher in stormflow samples, turbidities were about 1.5 orders of magnitude higher, total phosphorus and total zinc were about one order of magnitude higher, and total ammonia plus organic nitrogen, total nitrogen, total organic carbon, and total lead were about twofold higher than in base-flow samples.
\nSeasonal patterns and long-term trends in flow-adjusted water-quality concentrations were identified for five representative constituents—total nitrogen, total phosphorus, total zinc, total dissolved solids, and total suspended solids. Seasonal patterns for all five constituents were fairly similar, with higher concentrations in the summer and lower concentrations in the winter. Significant linear long-term trends in stormflow composite concentrations were identified for 36 of the 60 constituent-watershed combinations (5 constituents multiplied by 12 watersheds) for the period of record through water year 2011. Significant trends typically were decreasing for total nitrogen, total phosphorus, total suspended solids, and total zinc and increasing for total dissolved solids. Total dissolved solids and total suspended solids trends had the largest magnitude changes per year.
\nStream water loads were estimated for 10 water-quality constituents. These estimates represent the cumulative effects of watershed characteristics, hydrologic processes, biogeochemical processes, climatic variability, and human influences on watershed water quality. Yields, in load per unit area, were used to compare loads from watersheds with different sizes. A load estimation approach developed for the Gwinnett County LTTM program that incorporates storm-event composited samples was used with some minor modifications. This approach employs the commonly used regression-model method. Concentrations were modeled as a function of discharge, time, season, and turbidity to improve model predictions and reduce errors in load estimates. Total suspended solids annual loads have been identified in Gwinnett County’s Watershed Protection Plan for target performance criterion.
\nThe amount of annual runoff is the primary factor in determining the amount of annual constituent loads. Below average runoff during water years 2004–09, especially during water years 2006–08, resulted in corresponding below average loads. Variations in constituent yields between watersheds appeared to be related to various watershed characteristics. Suspended sediment (total suspended solids and suspended-sediment concentrations) along with constituents transported predominately in solid phase (total phosphorus, total organic carbon, total lead, and total zinc) and total dissolved solids typically had higher yields from watersheds that had high percentages of impervious areas or high basin slope. High total nitrogen yields were also associated with watersheds with high percentages of impervious areas. Low total nitrogen, total suspended solids, total lead, and total zinc yields appear to be associated with watersheds that have a low percentage of high-density development. Total suspended solids yields were lower in drought years, water years 2007–08, from the combined effects of less runoff and the result of fewer, lower magnitude storms, which likely resulted in less surface erosion and lower stream sediment transport.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145141","isbn":"9781411338159","collaboration":"Prepared in cooperation with Gwinnett County Department of Water Resources","usgsCitation":"Joiner, J.K., Aulenbach, B.T., and Landers, M.N., 2014, Watershed characteristics and water-quality trends and loads in 12 watersheds in Gwinnett County, Georgia: U.S. Geological Survey Scientific Investigations Report 2014-5141, viii, 79 p., https://doi.org/10.3133/sir20145141.","productDescription":"viii, 79 p.","numberOfPages":"92","onlineOnly":"N","ipdsId":"IP-057246","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":291595,"type":{"id":15,"text":"Index 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Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5049","title":"Comparability among four invertebrate sampling methods, Fountain Creek Basin, Colorado, 2010-2012","docAbstract":"The U.S. Geological Survey, in cooperation with Colorado Springs City Engineering and Colorado Springs Utilities, designed a study to determine if sampling method and sample timing resulted in comparable samples and assessments of biological condition. To accomplish this task, annual invertebrate samples were collected concurrently using four sampling methods at 15 U.S. Geological Survey streamflow gages in the Fountain Creek basin from 2010 to 2012. Collectively, the four methods are used by local (U.S. Geological Survey cooperative monitoring program) and State monitoring programs (Colorado Department of Public Health and Environment) in the Fountain Creek basin to produce two distinct sample types for each program that target single-and multiple-habitats. This study found distinguishable differences between single-and multi-habitat sample types using both community similarities and multi-metric index values, while methods from each program within sample type were comparable. This indicates that the Colorado Department of Public Health and Environment methods were compatible with the cooperative monitoring program methods within multi-and single-habitat sample types. Comparisons between September and October samples found distinguishable differences based on community similarities for both sample types, whereas only differences were found for single-habitat samples when multi-metric index values were considered. At one site, differences between September and October index values from single-habitat samples resulted in opposing assessments of biological condition. Direct application of the results to inform the revision of the existing Fountain Creek basin U.S. Geological Survey cooperative monitoring program are discussed.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145049","collaboration":"Prepared in cooperation with Colorado Springs City Engineering and Colorado Springs Utilities","usgsCitation":"Zuellig, R.E., Bruce, J.F., Stogner, and Brown, K.D., 2014, Comparability among four invertebrate sampling methods, Fountain Creek Basin, Colorado, 2010-2012: U.S. Geological Survey Scientific Investigations Report 2014-5049, Report: iv, 13 p.; Appendix 1, https://doi.org/10.3133/sir20145049.","productDescription":"Report: iv, 13 p.; Appendix 1","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053356","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":291587,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145049.jpg"},{"id":291585,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5049/pdf/sir2014-5049.pdf"},{"id":291586,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5049/appendix/sir2014-5049_tables.xlsx"},{"id":291584,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5049/"}],"projection":"Albers Equal-area projection","country":"United States","state":"Colorado","otherGeospatial":"Fountain Creek Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -105.00,38.25 ], [ -105.00,39.00 ], [ -104.50,39.00 ], [ -104.50,38.25 ], [ -105.00,38.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e0902fe4b0beb42bdc0408","contributors":{"authors":[{"text":"Zuellig, Robert E. 0000-0002-4784-2905 rzuellig@usgs.gov","orcid":"https://orcid.org/0000-0002-4784-2905","contributorId":1620,"corporation":false,"usgs":true,"family":"Zuellig","given":"Robert","email":"rzuellig@usgs.gov","middleInitial":"E.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bruce, James F. 0000-0003-3125-2932 jbruce@usgs.gov","orcid":"https://orcid.org/0000-0003-3125-2932","contributorId":916,"corporation":false,"usgs":true,"family":"Bruce","given":"James","email":"jbruce@usgs.gov","middleInitial":"F.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":493100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stogner 0000-0002-3185-1452 rstogner@usgs.gov","orcid":"https://orcid.org/0000-0002-3185-1452","contributorId":938,"corporation":false,"usgs":true,"family":"Stogner","email":"rstogner@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":493101,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Krystal D. kdtezak@usgs.gov","contributorId":5587,"corporation":false,"usgs":true,"family":"Brown","given":"Krystal","email":"kdtezak@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":493103,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70110608,"text":"ds854 - 2014 - A comprehensive list and photographic collection of the vascular flora of Caddo Lake National Wildlife Refuge, Texas, March 2011-March 2012","interactions":[],"lastModifiedDate":"2014-08-04T10:02:27","indexId":"ds854","displayToPublicDate":"2014-08-04T09:51:00","publicationYear":"2014","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":"854","title":"A comprehensive list and photographic collection of the vascular flora of Caddo Lake National Wildlife Refuge, Texas, March 2011-March 2012","docAbstract":"A floristics inventory was conducted to identify and photograph the vascular plants occurring at Caddo Lake National Wildlife Refuge (NWR), Texas, from March 2011 to March 2012 by the U.S. Geological Survey in cooperation with the U.S. Fish and Wildlife Service. This research resulted in the identification of 511 taxa of vascular plants representing 111 families and 317 genera. Despite the degree of development of the refuge at the time it was transferred to the U.S. Fish and Wildlife Service, plant diversity was high. Of the 511 species identified in this study, 346 species are new records for Harrison County, and 3 species are new discoveries for Texas. Caddo Lake NWR is primarily forested with 55 tree species and 35 shrub species identified in this study. Of the species identified, 289 are associated with wetlands having a wetland classification of facultative or wetter, possibly reflecting the proximity of Caddo Lake to the refuge and the three streams that intersect the refuge. Sixty-two of the species found on the refuge are introduced. Chinese tallow tree (Triadica sebifera) is one of the more common invasive tree species on the refuge and is actively controlled by refuge staff. Chinese privet (Ligustrum sinense), sacred bamboo (Nandina domestica), and King’s Ranch bluestem (Bothriochloa ischaemum var. songarica) are present on the refuge and have the potential to become invasive. More than 10,000 photographs were taken of the plants found on the refuge in an effort to document general appearance and capture diagnostic characters of each plant species. Photographs were also taken of many of the animals and landscapes encountered during the project. Select images of each of the plants and animals are included in the collection of more than 1,600 photographs (all photographs by Larry Allain).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds854","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Allain, L., 2014, A comprehensive list and photographic collection of the vascular flora of Caddo Lake National Wildlife Refuge, Texas, March 2011-March 2012: U.S. Geological Survey Data Series 854, Report: iv, 41 p.; Photograph collection, https://doi.org/10.3133/ds854.","productDescription":"Report: iv, 41 p.; Photograph collection","numberOfPages":"49","onlineOnly":"Y","temporalStart":"2011-03-01","temporalEnd":"2012-03-01","ipdsId":"IP-042560","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":291570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds854.jpg"},{"id":291567,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/854/pdf/ds854.pdf"},{"id":291569,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/854/Photograph_collection/"},{"id":291566,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/854/"}],"scale":"24000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Texas","otherGeospatial":"Caddo Lake National Wildlife Refuge","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.5,32.5 ], [ -94.5,33.0 ], [ -94.0,33.0 ], [ -94.0,32.5 ], [ -94.5,32.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e0902ee4b0beb42bdc0406","contributors":{"authors":[{"text":"Allain, Larry 0000-0002-7717-9761","orcid":"https://orcid.org/0000-0002-7717-9761","contributorId":63108,"corporation":false,"usgs":true,"family":"Allain","given":"Larry","affiliations":[],"preferred":false,"id":494095,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70119003,"text":"70119003 - 2014 - Mapping and monitoring Mount Graham red squirrel habitat with Lidar and Landsat imagery","interactions":[],"lastModifiedDate":"2016-04-26T10:02:52","indexId":"70119003","displayToPublicDate":"2014-08-04T09:27:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Mapping and monitoring Mount Graham red squirrel habitat with Lidar and Landsat imagery","docAbstract":"The Mount Graham red squirrel (Tamiasciurus hudsonicus grahamensis) is an endemic subspecies located in the Pinaleño Mountains of southeast Arizona. Living in a conifer forest on a sky-island surrounded by desert, the Mount Graham red squirrel is one of the rarest mammals in North America. Over the last two decades, drought, insect infestations, and fire destroyed much of its habitat. A federal recovery team is working on a plan to recover the squirrel and detailed information is necessary on its habitat requirements and population dynamics. Toward that goal I developed and compared three probabilistic models of Mount Graham red squirrel habitat with a geographic information system and logistic regression. Each model contained the same topographic variables (slope, aspect, elevation), but the Landsat model contained a greenness variable (Normalized Difference Vegetation Index) extracted from Landsat, the Lidar model contained three forest-inventory variables extracted from lidar, while the Hybrid model contained Landsat and lidar variables. The Hybrid model produced the best habitat classification accuracy, followed by the Landsat and Lidar models, respectively. Landsat-derived forest greenness was the best predictor of habitat, followed by topographic (elevation, slope, aspect) and lidar (tree height, canopy bulk density, and live basal area) variables, respectively. The Landsat model's probabilities were significantly correlated with all 12 lidar variables, indicating its utility for habitat mapping. While the Hybrid model produced the best classification results, only the Landsat model was suitable for creating a habitat time series or habitat–population function between 1986 and 2013. The techniques I highlight should prove valuable in the development of Landsat- or lidar-based habitat models range wide.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2014.07.004","usgsCitation":"Hatten, J.R., 2014, Mapping and monitoring Mount Graham red squirrel habitat with Lidar and Landsat imagery: Ecological Modelling, v. 289, p. 106-123, https://doi.org/10.1016/j.ecolmodel.2014.07.004.","productDescription":"18 p.","startPage":"106","endPage":"123","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053195","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":291561,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291556,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolmodel.2014.07.004"}],"country":"United States","state":"Arizona","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.859696,32.631505 ], [ -109.859696,32.650297 ], [ -109.827681,32.650297 ], [ -109.827681,32.631505 ], [ -109.859696,32.631505 ] ] ] } } ] }","volume":"289","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e09030e4b0beb42bdc040c","contributors":{"authors":[{"text":"Hatten, James R. 0000-0003-4676-8093 jhatten@usgs.gov","orcid":"https://orcid.org/0000-0003-4676-8093","contributorId":3431,"corporation":false,"usgs":true,"family":"Hatten","given":"James","email":"jhatten@usgs.gov","middleInitial":"R.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":497568,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70118992,"text":"70118992 - 2014 - Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices","interactions":[],"lastModifiedDate":"2014-08-04T09:26:36","indexId":"70118992","displayToPublicDate":"2014-08-04T09:03:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1958,"text":"ISPRS Journal of Photogrammetry and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices","docAbstract":"In the past 40 years, many spectral vegetation indices have been developed to quantify vegetation biophysical parameters. An ideal vegetation index should contain the maximum level of signal related to specific biophysical characteristics and the minimum level of noise such as background soil influences and atmospheric effects. However, accurate quantification of signal and noise in a vegetation index remains a challenge, because it requires a large number of field measurements or laboratory experiments. In this study, we applied a geostatistical method to estimate signal-to-noise ratio (S/N) for spectral vegetation indices. Based on the sample semivariogram of vegetation index images, we used the standardized noise to quantify the noise component of vegetation indices. In a case study in the grasslands and shrublands of the western United States, we demonstrated the geostatistical method for evaluating S/N for a series of soil-adjusted vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The soil-adjusted vegetation indices were found to have higher S/N values than the traditional normalized difference vegetation index (NDVI) and simple ratio (SR) in the sparsely vegetated areas. This study shows that the proposed geostatistical analysis can constitute an efficient technique for estimating signal and noise components in vegetation indices.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"ISPRS Journal of Photogrammetry and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.isprsjprs.2014.06.013","usgsCitation":"Ji, L., Zhang, L., Rover, J.R., Wylie, B.K., and Chen, X., 2014, Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices: ISPRS Journal of Photogrammetry and Remote Sensing, v. 96, p. 20-27, https://doi.org/10.1016/j.isprsjprs.2014.06.013.","productDescription":"8 p.","startPage":"20","endPage":"27","ipdsId":"IP-033481","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":291559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291558,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.isprsjprs.2014.06.013"}],"volume":"96","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e09030e4b0beb42bdc040a","contributors":{"authors":[{"text":"Ji, Lei 0000-0002-6133-1036 lji@usgs.gov","orcid":"https://orcid.org/0000-0002-6133-1036","contributorId":2832,"corporation":false,"usgs":true,"family":"Ji","given":"Lei","email":"lji@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":497564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Li","contributorId":98139,"corporation":false,"usgs":true,"family":"Zhang","given":"Li","affiliations":[],"preferred":false,"id":497567,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rover, Jennifer R. 0000-0002-3437-4030 jrover@usgs.gov","orcid":"https://orcid.org/0000-0002-3437-4030","contributorId":2941,"corporation":false,"usgs":true,"family":"Rover","given":"Jennifer","email":"jrover@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":false,"id":497565,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":497563,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chen, Xuexia","contributorId":14213,"corporation":false,"usgs":true,"family":"Chen","given":"Xuexia","affiliations":[],"preferred":false,"id":497566,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193618,"text":"70193618 - 2014 - Holocene sea surface temperature and sea ice extent in the Okhotsk and Bering Seas","interactions":[],"lastModifiedDate":"2017-11-02T14:20:01","indexId":"70193618","displayToPublicDate":"2014-08-04T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3194,"text":"Progress in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Holocene sea surface temperature and sea ice extent in the Okhotsk and Bering Seas","docAbstract":"Accurate prediction of future climate requires an understanding of the mechanisms of the Holocene climate; however, the driving forces, mechanisms, and processes of climate change in the Holocene associated with different time scales remain unclear. We investigated the drivers of Holocene sea surface temperature (SST) and sea ice extent in the North Pacific Ocean, and the Okhotsk and Bering Seas, as inferred from sediment core records, by using the alkenone unsaturation index as a biomarker of SST and abundances of sea ice-related diatoms (F. cylindrus and F. oceanica) as an indicator of sea ice extent to explore controlling mechanisms in the high-latitude Pacific. Temporal changes in alkenone content suggest that alkenone production was relatively high during the middle Holocene in the Okhotsk Sea and the western North Pacific, but highest in the late Holocene in the eastern Bering Sea and the eastern North Pacific. The Holocene variations of alkenone-SSTs at sites near Kamchatka in the Northwest Pacific, as well as in the western and eastern regions of the Bering Sea, and in the eastern North Pacific track the changes of Holocene summer insolation at 50°N, but at other sites in the western North Pacific, in the southern Okhotsk Sea, and the eastern Bering Sea they do not. In addition to insolation, other atmosphere and ocean climate drivers, such as sea ice distribution and changes in the position and activity of the Aleutian Low, may have systematically influenced the timing and magnitude of warming and cooling during the Holocene within the subarctic North Pacific. Periods of high sea ice extent in both the Okhotsk and Bering Seas may correspond to some periods of frequent or strong winter–spring dust storms in the Mongolian Gobi Desert, particularly one centered at ∼4–3 thousand years before present (kyr BP). Variation in storm activity in the Mongolian Gobi Desert region may reflect changes in the strength and positions of the Aleutian Low and Siberian High. We suggest that periods of eastward displacement or increased intensity of the Aleutian Low correspond with times of increased extent of sea ice in the western Okhotsk Sea and eastern Bering Sea.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.pocean.2014.04.017","usgsCitation":"Harada, N., Katsuki, K., Nakagawa, M., Matsumoto, A., Seki, O., Addison, J.A., Finney, B.P., and Sato, M., 2014, Holocene sea surface temperature and sea ice extent in the Okhotsk and Bering Seas: Progress in Oceanography, v. 126, p. 242-253, https://doi.org/10.1016/j.pocean.2014.04.017.","productDescription":"12 p.","startPage":"242","endPage":"253","ipdsId":"IP-052685","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":348105,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Okhotsk Sea, Bering Sea, North Pacific Ocean","volume":"126","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fc2eaae4b0531197b27fa3","contributors":{"authors":[{"text":"Harada, Naomi","contributorId":199653,"corporation":false,"usgs":false,"family":"Harada","given":"Naomi","email":"","affiliations":[],"preferred":false,"id":719645,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katsuki, Kota","contributorId":199654,"corporation":false,"usgs":false,"family":"Katsuki","given":"Kota","email":"","affiliations":[],"preferred":false,"id":719646,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nakagawa, Mitsuhiro","contributorId":199655,"corporation":false,"usgs":false,"family":"Nakagawa","given":"Mitsuhiro","email":"","affiliations":[],"preferred":false,"id":719647,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matsumoto, Akiko","contributorId":199656,"corporation":false,"usgs":false,"family":"Matsumoto","given":"Akiko","email":"","affiliations":[],"preferred":false,"id":719648,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seki, Osamu","contributorId":199657,"corporation":false,"usgs":false,"family":"Seki","given":"Osamu","email":"","affiliations":[],"preferred":false,"id":719649,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Addison, Jason A. 0000-0003-2416-9743 jaddison@usgs.gov","orcid":"https://orcid.org/0000-0003-2416-9743","contributorId":4192,"corporation":false,"usgs":true,"family":"Addison","given":"Jason","email":"jaddison@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719644,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Finney, Bruce P.","contributorId":199658,"corporation":false,"usgs":false,"family":"Finney","given":"Bruce","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":719650,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sato, Miyako","contributorId":199659,"corporation":false,"usgs":false,"family":"Sato","given":"Miyako","email":"","affiliations":[],"preferred":false,"id":719651,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}