Geologic evidence of past events and inundation modeling of potential events suggest that lahars associated with Mount Rainier, Washington, are significant threats to downstream development. To mitigate potential impacts of future lahars and educate at-risk populations, officials need to understand how communities are vulnerable to these fast-moving debris flows and which individuals and communities may need assistance in preparing for and responding to an event. To support local risk-reduction planning for future Mount Rainier lahars, this study documents the variations among communities in King, Lewis, Pierce, and Thurston Counties in the amount and types of developed land, human populations, economic assets, and critical facilities in a lahar-hazard zone. The lahar-hazard zone in this study is based on the behavior of the Electron Mudflow, a lahar that traveled along the Puyallup River approximately 500 years ago and was due to a slope failure on the west flank of Mount Rainier. This lahar-hazard zone contains 78,049 residents, of which 11 percent are more than 65 years in age, 21 percent do not live in cities or unincorporated towns, and 39 percent of the households are renter occupied. The lahar-hazard zone contains 59,678 employees (4 percent of the four-county labor force) at 3,890 businesses that generate $16 billion in annual sales (4 and 7 percent, respectively, of totals in the four-county area) and tax parcels with a combined total value of $8.8 billion (2 percent of the study-area total). Employees in the lahar-hazard zone are primarily in businesses related to manufacturing, retail trade, transportation and warehousing, wholesale trade, and construction. Key road and rail corridors for the region are in the lahar-hazard zone, which could result in significant indirect economic losses for businesses that rely on these networks, such as the Port of Tacoma. Although occupancy values are not known for each site, the lahar-hazard zone contains numerous dependent-population facilities (for example, schools and child day-care centers), public venues (for example, religious organizations and hotels), and critical facilities (for example, police and fire stations). The lahar-hazard zone also includes high-volume tourist sites, such as Mount Rainier National Park and the Puyallup Fairgrounds. Community exposure to lahars associated with Mount Rainier varies considerably among 27 communities and four counties—some may experience great losses that reflect only a small portion of their community and others may experience relatively small losses that devastate them. Among 27 communities, the City of Puyallup has the highest number of people and assets in the lahar-hazard zone, whereas the communities of Carbonado, Fife, Orting, and Sumner have the highest percentages of people and assets in this zone. Based on a composite index, the cities of Puyallup, Sumner, and Fife have the highest combinations of the number and percentage of people and assets in lahar-prone areas.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095211","collaboration":"Prepared in cooperation with the State of Washington Military Department Emergency Management Division","usgsCitation":"Wood, N.J., and Soulard, C.E., 2009, Community exposure to lahar hazards from Mount Rainier, Washington: U.S. Geological Survey Scientific Investigations Report 2009-5211, iv, 27 p., https://doi.org/10.3133/sir20095211.","productDescription":"iv, 27 p.","numberOfPages":"34","onlineOnly":"Y","costCenters":[{"id":157,"text":"Cascades Volcano Observatory","active":false,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":118498,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5211.jpg"},{"id":13103,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5211/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Washington","otherGeospatial":"Mount Rainier","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.83333333333333,46.416666666666664 ], [ -122.83333333333333,47.416666666666664 ], [ -121.41666666666667,47.416666666666664 ], [ -121.41666666666667,46.416666666666664 ], [ -122.83333333333333,46.416666666666664 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b24e4b07f02db6ae5b6","contributors":{"authors":[{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":303621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soulard, Christopher E. 0000-0002-5777-9516 csoulard@usgs.gov","orcid":"https://orcid.org/0000-0002-5777-9516","contributorId":2642,"corporation":false,"usgs":true,"family":"Soulard","given":"Christopher","email":"csoulard@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":303620,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70156475,"text":"70156475 - 2009 - Defining fish nursery habitats: An application of otolith elemental fingerprinting in Tampa Bay, Florida","interactions":[],"lastModifiedDate":"2021-11-09T16:37:23.44025","indexId":"70156475","displayToPublicDate":"2009-10-20T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Defining fish nursery habitats: An application of otolith elemental fingerprinting in Tampa Bay, Florida","docAbstract":"Fishing in Tampa Bay enhances the quality of life of the area's residents and visitors. However, people's desire to settle along the Bay's shorelines and tributaries has been detrimental to the very habitat believed to be crucial to prime target fishery species. Common snook (Centropomus undecimalis) and red drum (Sciaenops ocellatus) are part of the suite of estuarine fishes that 1) are economically or ecologically prominent, and 2) have complex life cycles involving movement between open coastal waters and estuarine nursery habitats, including nursery habitats that are located within upstream, low-salinity portions of the Bay?s tidal tributaries. We are using an emerging microchemical technique -- elemental fingerprinting of fish otoliths -- to determine the degree to which specific estuarine locations contribute to adult fished populations in Tampa Bay. In ongoing monitoring surveys, over 1,000 young-of-the-year common snook and red drum have already been collected from selected Tampa Bay tributaries. Using laser ablation-inductively coupled plasma - mass spectrometry (LA-ICP-MS), we are currently processing a subsample of these archived otoliths to identify location-specific fingerprints based on elemental microchemistry. We will then analyze older fish from the local fishery in order to match them to their probable nursery areas, as defined by young-of-the-year otoliths. We expect to find that some particularly favorable nursery locations contribute disproportionately to the fished population. In contrast, other nursery areas may be degraded, or act as 'sinks', thereby decreasing their contribution to the fish population. Habitat managers can direct strategic efforts to protect any nursery locations that are found to be of prime importance in contributing to adult stocks.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the fifth Tampa Bay area scientific information symposium basis 5","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Fifth Tampa Bay Area Scientific Information Symposium Basis 5","conferenceDate":"October 20-23 2009","language":"English","publisher":"Tampa Bay Estuary Program","usgsCitation":"Ley, J.A., McIvor, C., Peebles, E.B., Rolls, H., and Cooper, S.T., 2009, Defining fish nursery habitats: An application of otolith elemental fingerprinting in Tampa Bay, Florida, in Proceedings of the fifth Tampa Bay area scientific information symposium basis 5, October 20-23 2009, p. 331-346.","productDescription":"15 p.","startPage":"331","endPage":"346","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-019847","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":307181,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Tampa Bay estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.803955078125,\n 27.520451064122113\n ],\n [\n -82.078857421875,\n 27.520451064122113\n ],\n [\n -82.078857421875,\n 28.125283321961756\n ],\n [\n -82.803955078125,\n 28.125283321961756\n ],\n [\n -82.803955078125,\n 27.520451064122113\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57fe8400e4b0824b2d148de9","contributors":{"authors":[{"text":"Ley, Janet A.","contributorId":56563,"corporation":false,"usgs":true,"family":"Ley","given":"Janet","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":569274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McIvor, Carole C.","contributorId":33641,"corporation":false,"usgs":true,"family":"McIvor","given":"Carole C.","affiliations":[],"preferred":false,"id":569275,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peebles, Ernst B","contributorId":127813,"corporation":false,"usgs":false,"family":"Peebles","given":"Ernst","email":"","middleInitial":"B","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":569276,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rolls, Holly","contributorId":146877,"corporation":false,"usgs":false,"family":"Rolls","given":"Holly","email":"","affiliations":[],"preferred":false,"id":569277,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cooper, Suzanne T.","contributorId":146878,"corporation":false,"usgs":false,"family":"Cooper","given":"Suzanne","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":569278,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":97920,"text":"pp1727 - 2009 - Late Cenozoic geology and lacustrine history of Searles Valley, Inyo and San Bernardino Counties, California","interactions":[],"lastModifiedDate":"2015-09-14T14:48:21","indexId":"pp1727","displayToPublicDate":"2009-10-17T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1727","title":"Late Cenozoic geology and lacustrine history of Searles Valley, Inyo and San Bernardino Counties, California","docAbstract":"Searles Valley is an arid, closed basin lying 70 km east of the south end of the Sierra Nevada, California. It is bounded on the east and northeast by the Slate Range, on the west by the Argus Range and Spangler Hills, and on the south by the Lava Mountains; Searles (dry) Lake occupies the north-central part of the valley. During those parts of late Pliocene and Pleistocene time when precipitation and runoff from the east side of the Sierra Nevada into the Owens River were much greater than at present, a chain of as many as five large lakes was created, of which Searles Lake was third. The stratigraphic record left in Searles Valley when that lake expanded, contracted, or desiccated, is fully revealed by cores from beneath the surface of Searles (dry) Lake and partly recorded by sediments cropping out around the edge of the valley. The subsurface record is described elsewhere. This volume includes six geologic maps (scales: 1:50,000 and 1:10,000) and a text that describes the outcrop record, most of which represents sedimentation since 150 ka. Although this outcrop record is discontinuous, it provides evidence indicating the lake's water depths during each expansion, which the subsurface record does not. Maximum-depth lakes rose to the 2,280-ft (695 m) contour, the level of the spillway that led overflowing waters to Panamint Valley; that spillway is about 660 ft (200 m) above the present dry-lake surface. Several rock units of Tertiary and early Quaternary ages crop out in Searles Valley. Siltstone and sandstone of Tertiary age, mostly lacustrine in nature and locally deformed to near-vertical dips, are exposed in the southern part of the valley, as is the younger(?) upper Miocene Bedrock Spring Formation. Unnamed, mostly mafic volcanic rocks of probable Miocene or Pliocene age are exposed along the north and south edges of the basin. Slightly deformed lacustrine sandstones are mapped in the central-southwestern and southern parts of the study area. The Christmas Canyon Formation and deposits mapped as older gravel and older tufa are extensively exposed over much of the basin floor. The older gravel unit and the gravel facies of the Christmas Canyon Formation are boulder alluvial gravels; parts of these units are probably correlative. The lacustrine facies of the Christmas Canyon Formation includes the Lava Creek ash, which is dated at 0.64 Ma; the older tufa deposits may be equivalent in age to those sediments. Most of this study concerns sediments of the newly described Searles Lake Formation, whose deposition spanned the period between about 150 ka and 2 ka. Most of this formation is lacustrine in origin, but it includes interbedded alluvium. To extract as much geologic detail as possible, criteria were developed that permitted (1) intrabasin correlation of some thin outcrop units representative of only a few thousand years (or less), (2) identification of unconformities produced by subaerial erosion, (3) identification of unconformities produced by sublacustrine erosion, and (4) correlation of outcrop units with subsurface units. The Searles Lake Formation is divided into seven main units, many of which are subdivided on the five larger scale geologic maps. Units A (oldest), B, C, and D are dominantly lacustrine in origin. The Pleistocene-Holocene boundary is placed at the top of unit C. In areas that were a kilometer or more from shore at the time of deposition, deposits of units A,B, and C consist of fine, highly calcareous sand, silt, or clay; nearer to shore they consist of well-sorted coarse sand and gravel. Unit A has been locally subdivided into as many as four subunits, unit B into six subunits, and unit C into six subunits. The finer facies of units A, B, and C contain such high percentages of Caco3 that they are best described as marl. Sediments of unit C, and to a lesser extent those of unit B, are laminated with light- to white-colored layers of aragonite, calcite, or dolomite(?) that may repre
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/pp1727","usgsCitation":"Smith, G.I., 2009, Late Cenozoic geology and lacustrine history of Searles Valley, Inyo and San Bernardino Counties, California: U.S. Geological Survey Professional Paper 1727, Report: viii, 117 p.; 4 Plates: 33 x 40 inches or smaller; Readme; Metadata; Database; Shapefiles, https://doi.org/10.3133/pp1727.","productDescription":"Report: viii, 117 p.; 4 Plates: 33 x 40 inches or smaller; Readme; Metadata; Database; Shapefiles","numberOfPages":"128","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":227,"text":"Earth Surface Dynamics Program","active":true,"usgs":true}],"links":[{"id":125530,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp_1727.jpg"},{"id":266880,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/pp/1727/SearlesValley_metadata.txt"},{"id":266879,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/pp/1727/1_readme.txt"},{"id":266881,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/pp/1727/pp1727searles_valley_db.zip"},{"id":266882,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/pp/1727/pp1727searles_valley_shape.zip"},{"id":13092,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1727/","linkFileType":{"id":5,"text":"html"}},{"id":266875,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/pp/1727/pp1727_plate1.pdf"},{"id":266876,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/pp/1727/pp1727_plate2.pdf"},{"id":266877,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/pp/1727/pp1727_plate3.pdf"},{"id":266874,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1727/pp1727_text.pdf"},{"id":266878,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/pp/1727/pp1727_plate4.pdf"}],"projection":"Polyconic","country":"United States","state":"California","county":"Inyo County, San Bernadino County","otherGeospatial":"Searless Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.5,35.5 ], [ -117.5,36 ], [ -117,36 ], [ -117,35.5 ], [ -117.5,35.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b1be4b07f02db6a8d40","contributors":{"authors":[{"text":"Smith, George I.","contributorId":92637,"corporation":false,"usgs":true,"family":"Smith","given":"George","email":"","middleInitial":"I.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":303587,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":97922,"text":"ofr20091229 - 2009 - A method for creating a three dimensional model from published geologic maps and cross sections","interactions":[],"lastModifiedDate":"2022-09-23T14:44:41.084811","indexId":"ofr20091229","displayToPublicDate":"2009-10-17T00:00:00","publicationYear":"2009","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":"2009-1229","title":"A method for creating a three dimensional model from published geologic maps and cross sections","docAbstract":"This brief report presents a relatively inexpensive and rapid method for creating a 3D model of geology from published quadrangle-scale maps and cross sections using Google Earth and Google SketchUp software. An example from the Green Mountains of Vermont, USA, is used to illustrate the step by step methods used to create such a model. A second example is provided from the Jebel Saghro region of the Anti-Atlas Mountains of Morocco. The report was published to help enhance the public's ability to use and visualize geologic map data.
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In addition, the Washington State Department of Transportation would like to identify the standard operating procedures and quality assurance protocols that must be adopted so that their monitoring program will meet the requirements of the new National Pollutant Discharge Elimination System municipal stormwater permit. As a result, in March 2009, the Washington State Department of Transportation asked the U.S. Geological Survey to assess their pre-2009 municipal stormwater monitoring program. This report presents guidelines developed for the Washington State Department of Transportation to meet new permit requirements and regional/national stormwater monitoring standards to ensure that adequate processes and procedures are identified to collect high-quality, scientifically defensible municipal stormwater monitoring data. These include: (1) development of coherent vision and cooperation among all elements of the program; (2) a comprehensive approach for site selection; (3) an effective quality assurance program for field, laboratory, and data management; and (4) an adequate database and data management system.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091236","collaboration":"Prepared in cooperation with the Washington State Department of Transportation","usgsCitation":"Sheibley, R., Kelly, V., and Wagner, R.J., 2009, Scientific Framework for Stormwater Monitoring by the Washington State Department of Transportation: U.S. Geological Survey Open-File Report 2009-1236, iv, 23 p., https://doi.org/10.3133/ofr20091236.","productDescription":"iv, 23 p.","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":125510,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1236.jpg"},{"id":13096,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1236/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125.75,45.5 ], [ -125.75,49 ], [ -116.91666666666667,49 ], [ -116.91666666666667,45.5 ], [ -125.75,45.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a0de4b07f02db5fd265","contributors":{"authors":[{"text":"Sheibley, R.W. 0000-0003-1627-8536 sheibley@usgs.gov","orcid":"https://orcid.org/0000-0003-1627-8536","contributorId":43066,"corporation":false,"usgs":true,"family":"Sheibley","given":"R.W.","email":"sheibley@usgs.gov","affiliations":[],"preferred":false,"id":303602,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelly, V.J.","contributorId":14009,"corporation":false,"usgs":true,"family":"Kelly","given":"V.J.","email":"","affiliations":[],"preferred":false,"id":303600,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wagner, R. 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This new USGS VMS deposit model provides a comprehensive review of deposit occurrence and ore genesis, and fully integrates recent advances in the understanding of active seafloor VMS-forming environments, and integrates consideration of geoenvironmental consequences of mining VMS deposits.\r\n\r\nBecause VMS deposits exhibit a broad range of geological and geochemical characteristics, a suitable classification system is required to incorporate these variations into the mineral deposit model. We classify VMS deposits based on compositional variations in volcanic and sedimentary host rocks. The advantage of the classification method is that it provides a closer linkage between tectonic setting and lithostratigraphic assemblages, and an increased predictive capability during field-based studies.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091235","usgsCitation":"Shanks, W.P., Dusel-Bacon, C., Koski, R., Morgan, L.A., Mosier, D., Piatak, N., Ridley, I., Seal, R., Schulz, K.J., Slack, J.F., and Thurston, R., 2009, A New Occurrence Model for National Assessment of Undiscovered Volcanogenic Massive Sulfide Deposits: U.S. Geological Survey Open-File Report 2009-1235, iv, 27 p., https://doi.org/10.3133/ofr20091235.","productDescription":"iv, 27 p.","onlineOnly":"Y","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":125509,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1235.jpg"},{"id":13093,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1235/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd495ee4b0b290850ef1b7","contributors":{"authors":[{"text":"Shanks, W.C. Pat III","contributorId":93949,"corporation":false,"usgs":true,"family":"Shanks","given":"W.C.","suffix":"III","email":"","middleInitial":"Pat","affiliations":[],"preferred":false,"id":303598,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dusel-Bacon, Cynthia 0000-0001-8481-739X cdusel@usgs.gov","orcid":"https://orcid.org/0000-0001-8481-739X","contributorId":2797,"corporation":false,"usgs":true,"family":"Dusel-Bacon","given":"Cynthia","email":"cdusel@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":303591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koski, Randolph","contributorId":88049,"corporation":false,"usgs":true,"family":"Koski","given":"Randolph","affiliations":[],"preferred":false,"id":303597,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morgan, Lisa A.","contributorId":66300,"corporation":false,"usgs":true,"family":"Morgan","given":"Lisa","email":"","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":false,"id":303595,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mosier, Dan","contributorId":36246,"corporation":false,"usgs":true,"family":"Mosier","given":"Dan","affiliations":[],"preferred":false,"id":303594,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Piatak, Nadine M.","contributorId":23621,"corporation":false,"usgs":true,"family":"Piatak","given":"Nadine M.","affiliations":[],"preferred":false,"id":303593,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ridley, Ian","contributorId":23244,"corporation":false,"usgs":true,"family":"Ridley","given":"Ian","email":"","affiliations":[],"preferred":false,"id":303592,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Seal, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":397,"corporation":false,"usgs":true,"family":"Seal","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[],"preferred":false,"id":303588,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schulz, Klaus J. 0000-0003-2967-4765 kschulz@usgs.gov","orcid":"https://orcid.org/0000-0003-2967-4765","contributorId":2438,"corporation":false,"usgs":true,"family":"Schulz","given":"Klaus","email":"kschulz@usgs.gov","middleInitial":"J.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":303590,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":303589,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Thurston, Roland","contributorId":69261,"corporation":false,"usgs":true,"family":"Thurston","given":"Roland","affiliations":[],"preferred":false,"id":303596,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":97919,"text":"fs20093077 - 2009 - U.S. Geological Survey (USGS) Western Region; Santa Barbara Channel Coastal and Ocean Science","interactions":[],"lastModifiedDate":"2012-02-10T00:11:54","indexId":"fs20093077","displayToPublicDate":"2009-10-17T00:00:00","publicationYear":"2009","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":"2009-3077","title":"U.S. Geological Survey (USGS) Western Region; Santa Barbara Channel Coastal and Ocean Science","docAbstract":"USGS coastal and ocean science in the Western United States and the Pacific integrates scientific expertise in geology, water resources, biology, and geography. Operating from 10 major science centers in the Western Region, the USGS is addressing a broad geographic and thematic range of important coastal and marine issues. In California, the Santa Barbara Channel represents one area of focus.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/fs20093077","usgsCitation":"Johnson, S.Y., 2009, U.S. Geological Survey (USGS) Western Region; Santa Barbara Channel Coastal and Ocean Science: U.S. Geological Survey Fact Sheet 2009-3077, 4 p., https://doi.org/10.3133/fs20093077.","productDescription":"4 p.","costCenters":[{"id":645,"text":"Western Coastal and Marine Geology","active":false,"usgs":true}],"links":[{"id":125416,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2009_3077.jpg"},{"id":13091,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2009/3077/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.5,33.8 ], [ -120.5,34.5 ], [ -119,34.5 ], [ -119,33.8 ], [ -120.5,33.8 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49e5e4b07f02db5e6d88","contributors":{"authors":[{"text":"Johnson, Samuel Y. 0000-0001-7972-9977 sjohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-7972-9977","contributorId":2607,"corporation":false,"usgs":true,"family":"Johnson","given":"Samuel","email":"sjohnson@usgs.gov","middleInitial":"Y.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":303586,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70200432,"text":"70200432 - 2009 - Inference of distributional parameters from compositional samples containing nondetects","interactions":[],"lastModifiedDate":"2018-11-29T09:33:12","indexId":"70200432","displayToPublicDate":"2009-10-15T11:25:05","publicationYear":"2009","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Inference of distributional parameters from compositional samples containing nondetects","docAbstract":"Low concentrations of elements in geochemical analyses have the peculiarity of being compositional data and, for a given level of significance, are likely to be beyond the capabilities of laboratories to distinguish between minute concentrations and complete absence, thus preventing laboratories from reporting extremely low concentrations of the analyte. Instead, what is reported is the detection limit, which is the minimum concentration that conclusively differentiates between presence and absence of the element. A spatially distributed exhaustive sample is employed in this study to generate unbiased sub-samples, which are further censored to observe the effect that different detection limits and sample sizes have on the inference of population distributions starting from geochemical analyses having specimens below detection limit (nondetects). The isometric logratio transformation is used to convert the compositional data in the simplex to samples in real space, thus allowing the practitioner to properly borrow from the large source of statistical techniques valid only in real space. The bootstrap method is used to numerically investigate the reliability of inferring several distributional parameters employing different forms of imputation for the censored data. The case study illustrates that, in general, best results are obtained when imputations are made using the distribution best fitting the readings above detection limit and exposes the problems of other more widely used practices. When the sample is spatially correlated, it
is necessary to combine the bootstrap with stochastic simulation.
Coastal wetlands provide valued ecosystem functions but the sustainability of those functions often is threatened by artificial hydrologic conditions. It is widely recognized that increased flooding and salinity can stress emergent plants, but there are few measurements to guide restoration, management, and mitigation. Marsh flooding can be estimated over large areas with few data where winds have little effect on water levels, but quantifying flooding requires hourly measurements over long time periods where tides are wind-dominated such as the northern Gulf of Mexico. Estimating salinity of flood water requires direct daily measurements because coastal marshes are characterized by dynamic salinity gradients. We analyzed 399,772 hourly observations of water depth and 521,561 hourly observations of water salinity from 14 sites in Louisiana coastal marshes dominated by Spartina patens (Ait.) Muhl. Unlike predicted water levels, observed water levels varied monthly and annually. We attributed those observed variations to variations in river runoff and winds. In stable marshes with slow wetland loss rates, we found that marsh elevation averaged 1 cm above mean high water, 15 cm above mean water, and 32 cm above mean low water levels. Water salinity averaged 3.7 ppt during April, May, and June, and 5.4 ppt during July, August, and September. The daily, seasonal, and annual variation in water levels and salinity that were evident would support the contention that such variation be retained when designing and operating coastal wetland management and restoration projects. Our findings might be of interest to scientists, engineers, and managers involved in restoration, management, and restoration in other regions where S. patens or similar species are common but local data are unavailable.
","language":"English","publisher":"European Geophysical Society","publisherLocation":"Amsterdam","doi":"10.1016/j.jhydrol.2009.06.001","usgsCitation":"Nyman, J., LaPeyre, M.K., Caldwell, A.W., Piazza, S.C., Thom, C., and Winslow, C., 2009, Defining restoration targets for water depth and salinity in wind-dominated Spartina patens (Ait.) Muhl. coastal marshes: Journal of Hydrology, v. 376, no. 3-4, p. 327-336, https://doi.org/10.1016/j.jhydrol.2009.06.001.","productDescription":"10 p.","startPage":"327","endPage":"336","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-007506","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":301340,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"376","issue":"3-4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55853d39e4b023124e8f5afb","contributors":{"authors":[{"text":"Nyman, J.A.","contributorId":56835,"corporation":false,"usgs":true,"family":"Nyman","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":548991,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":548979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell, Andral W. 0000-0003-1269-5463 acaldwel@usgs.gov","orcid":"https://orcid.org/0000-0003-1269-5463","contributorId":3228,"corporation":false,"usgs":true,"family":"Caldwell","given":"Andral","email":"acaldwel@usgs.gov","middleInitial":"W.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548992,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Piazza, Sarai C. 0000-0001-6962-9008 piazzas@usgs.gov","orcid":"https://orcid.org/0000-0001-6962-9008","contributorId":466,"corporation":false,"usgs":true,"family":"Piazza","given":"Sarai","email":"piazzas@usgs.gov","middleInitial":"C.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":548993,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thom, C.","contributorId":56479,"corporation":false,"usgs":true,"family":"Thom","given":"C.","email":"","affiliations":[],"preferred":false,"id":548994,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Winslow, C.","contributorId":57693,"corporation":false,"usgs":true,"family":"Winslow","given":"C.","email":"","affiliations":[],"preferred":false,"id":548995,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70037866,"text":"70037866 - 2009 - Wildfire risk in the wildland-urban interface: A simulation study in northwestern Wisconsin","interactions":[],"lastModifiedDate":"2021-03-02T13:48:16.175386","indexId":"70037866","displayToPublicDate":"2009-10-10T12:53:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Wildfire risk in the wildland-urban interface: A simulation study in northwestern Wisconsin","docAbstract":"The rapid growth of housing in and near the wildland–urban interface (WUI) increases wildfire risk to lives and structures. To reduce fire risk, it is necessary to identify WUI housing areas that are more susceptible to wildfire. This is challenging, because wildfire patterns depend on fire behavior and spread, which in turn depend on ignition locations, weather conditions, the spatial arrangement of fuels, and topography. The goal of our study was to assess wildfire risk to a 60,000 ha WUI area in northwestern Wisconsin while accounting for all of these factors. We conducted 6000 simulations with two dynamic fire models: Fire Area Simulator (FARSITE) and Minimum Travel Time (MTT) in order to map the spatial pattern of burn probabilities. Simulations were run under normal and extreme weather conditions to assess the effect of weather on fire spread, burn probability, and risk to structures. The resulting burn probability maps were intersected with maps of structure locations and land cover types. The simulations revealed clear hotspots of wildfire activity and a large range of wildfire risk to structures in the study area. As expected, the extreme weather conditions yielded higher burn probabilities over the entire landscape, as well as to different land cover classes and individual structures. Moreover, the spatial pattern of risk was significantly different between extreme and normal weather conditions. The results highlight the fact that extreme weather conditions not only produce higher fire risk than normal weather conditions, but also change the fine-scale locations of high risk areas in the landscape, which is of great importance for fire management in WUI areas. In addition, the choice of weather data may limit the potential for comparisons of risk maps for different areas and for extrapolating risk maps to future scenarios where weather conditions are unknown. Our approach to modeling wildfire risk to structures can aid fire risk reduction management activities by identifying areas with elevated wildfire risk and those most vulnerable under extreme weather conditions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2009.07.051","usgsCitation":"Massada, A.B., Radeloff, V., Stewart, S.I., and Hawbaker, T., 2009, Wildfire risk in the wildland-urban interface: A simulation study in northwestern Wisconsin: Forest Ecology and Management, v. 258, no. 9, p. 1990-1999, https://doi.org/10.1016/j.foreco.2009.07.051.","productDescription":"10 p.","startPage":"1990","endPage":"1999","costCenters":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"links":[{"id":383711,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"northern Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.791015625,\n 46.9502622421856\n ],\n [\n -92.1533203125,\n 46.70973594407157\n ],\n [\n -92.4169921875,\n 46.01222384063236\n ],\n [\n -92.92236328125,\n 45.5679096098613\n ],\n [\n -92.6806640625,\n 45.38301927899065\n ],\n [\n -92.83447265624999,\n 44.824708282300236\n ],\n [\n -91.20849609375,\n 43.8028187190472\n ],\n [\n -87.73681640625,\n 43.58039085560784\n ],\n [\n -87.03369140625,\n 45.213003555993964\n ],\n [\n -87.64892578125,\n 45.07352060670971\n ],\n [\n -87.86865234374999,\n 45.537136680398596\n ],\n [\n -88.06640625,\n 45.81348649679973\n ],\n [\n -88.72558593749999,\n 46.057985244793024\n ],\n [\n -90.263671875,\n 46.558860303117164\n ],\n [\n -90.791015625,\n 46.9502622421856\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"258","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bd0d0e4b08c986b32f092","contributors":{"authors":[{"text":"Massada, Avi Bar","contributorId":93744,"corporation":false,"usgs":true,"family":"Massada","given":"Avi","email":"","middleInitial":"Bar","affiliations":[],"preferred":false,"id":462914,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Radeloff, Volker C.","contributorId":76169,"corporation":false,"usgs":true,"family":"Radeloff","given":"Volker C.","affiliations":[],"preferred":false,"id":462912,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stewart, Susan I.","contributorId":78973,"corporation":false,"usgs":true,"family":"Stewart","given":"Susan","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":462913,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":462911,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":97914,"text":"ds440 - 2009 - Groundwater quality data in the Mojave study unit, 2008: Results from the California GAMA Program","interactions":[],"lastModifiedDate":"2022-07-19T20:16:33.323921","indexId":"ds440","displayToPublicDate":"2009-10-10T00:00:00","publicationYear":"2009","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":"440","title":"Groundwater quality data in the Mojave study unit, 2008: Results from the California GAMA Program","docAbstract":"Groundwater quality in the approximately 1,500 square-mile Mojave (MOJO) study unit was investigated from February to April 2008, as part of the Priority Basin Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA Priority Basin Project was developed in response to the Groundwater Quality Monitoring Act of 2001 and is being conducted by the U.S. Geological Survey (USGS) in cooperation with the California State Water Resources Control Board (SWRCB). MOJO was the 23rd of 37 study units to be sampled as part of the GAMA Priority Basin Project.
The MOJO study was designed to provide a spatially unbiased assessment of the quality of untreated ground water used for public water supplies within MOJO, and to facilitate statistically consistent comparisons of groundwater quality throughout California. Samples were collected from 59 wells in San Bernardino and Los Angeles Counties. Fifty-two of the wells were selected using a spatially distributed, randomized grid-based method to provide statistical representation of the study area (grid wells), and seven were selected to aid in evaluation of specific water-quality issues (understanding wells).
The groundwater samples were analyzed for a large number of organic constituents [volatile organic compounds (VOCs), pesticides and pesticide degradates, and pharmaceutical compounds], constituents of special interest (perchlorate and N-nitrosodimethylamine [NDMA]) naturally occurring inorganic constituents (nutrients, dissolved organic carbon [DOC], major and minor ions, silica, total dissolved solids [TDS], and trace elements), and radioactive constituents (gross alpha and gross beta radioactivity, radium isotopes, and radon-222). Naturally occurring isotopes (stable isotopes of hydrogen, oxygen, and carbon, stable isotopes of nitrogen and oxygen in nitrate, and activities of tritium and carbon-14), and dissolved noble gases also were measured to help identify the sources and ages of the sampled ground water. In total, over 230 constituents and water-quality indicators (field parameters) were investigated.
Three types of quality-control samples (blanks, replicates, and matrix spikes) each were collected at approximately 5–8 percent of the wells, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. Field blanks rarely contained detectable concentrations of any constituent, suggesting that contamination was not a significant source of bias in the data for the groundwater samples. Differences between replicate samples generally were within acceptable ranges, indicating acceptable analytical reproducibility. Matrix spike recoveries were within acceptable ranges for most compounds.
This study did not attempt to evaluate the quality of water delivered to consumers; after withdrawal from the ground, untreated groundwater typically is treated, disinfected, or blended with other waters to maintain water quality. Regulatory thresholds apply to water that is served to the consumer, not to untreated ground water. However, to provide some context for the results, concentrations of constituents measured in the untreated ground water were compared with regulatory and non-regulatory health-based thresholds established by the U.S. Environmental Protection Agency (USEPA) and California Department of Public Health (CDPH) and thresholds established for aesthetic and technical concerns by CDPH. Comparisons between data collected for this study and thresholds for drinking-water are for illustrative purposes only, and are not indicative of compliance or non-compliance with those thresholds.
Most constituents that were detected in groundwater samples in the 59 wells in MOJO were found at concentrations below drinking-water thresholds. In MOJO’s 52 grid wells, volatile organic compounds (VOCs) were detected in 40 percent of the wells, and pesticides and pesticide degradates were detected in 23 percent of the grid wells. Results for health-based thresholds in MOJO grid wells showed that all of the detections of organic compounds in samples from MOJO grid wells were below health-based thresholds, with the exception of a single detection of NDMA above the California Department of Public Health notification level (NL-CA).
Trace elements and radioactive constituents were sampled for at 19 MOJO grid wells and most detections were below health-based thresholds. Exceptions include: six detections of arsenic above the USEPA maximum contaminant level (MCL-US), two detections of boron and one detection of vanadium above the NL-CA, one detection each of molybdenum and strontium that were above the USEPA lifetime health advisory level (HAL-US), and one detection of fluoride just above the MCL-CA of 2 µg/L. Most detections of radioactive constituents in the MOJO grid wells were below health-based thresholds, with the exception of one detection of gross alpha radioactivity (72-hour count and 30-day count) above the MCL-CA, and 17 grid wells (of 19 sampled) that had activities of radon-222 above the proposed MCL-US of 300 pCi/L, but all were below the proposed alternative MCL-US of 4,000 pCi/L.
All of the samples collected from the 19 MOJO grid wells for trace elements, and most of the samples for major ions and total dissolved solids (TDS), had measured concentrations below the non-enforceable thresholds set for aesthetic concerns. Four grid wells had TDS concentrations above the California Department of Public Health secondary maximum contaminant level (SMCL-CA) recommended threshold of 500 mg/L, and three of these wells were also above the SMCL-CA upper threshold of 1,000 mg/L. Four grid wells (of 19 sampled) had sulfate measured at concentrations above the recommended SMCL-CA threshold of 250 mg/L, and one of these detections was also above the upper SMCL-CA threshold of 500 mg/L. One grid well had chloride levels at a concentration above the upper SMCL-CA threshold of 500 mg/L. Eleven grid wells (of 52 sampled) had pH values outside of the SMCL-US range for pH.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ds440","collaboration":"Prepared in cooperation with the California State Water Resources Control Board; A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program","usgsCitation":"Mathany, T., and Belitz, K., 2009, Groundwater quality data in the Mojave study unit, 2008: Results from the California GAMA Program: U.S. Geological Survey Data Series 440, x, 81 p., https://doi.org/10.3133/ds440.","productDescription":"x, 81 p.","temporalStart":"2008-02-01","temporalEnd":"2008-04-30","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":118585,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_440.jpg"},{"id":13086,"rank":100,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/440/","text":"Index page","linkFileType":{"id":5,"text":"html"}},{"id":360778,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/440/pdf/ds440.pdf","text":"Report","size":"12.3 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"Mojave study unit","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.7333,\n 34.2833\n ],\n [\n -116.35,\n 34.2833\n ],\n [\n -116.35,\n 35.0708\n ],\n [\n -117.7333,\n 35.0708\n ],\n [\n -117.7333,\n 34.2833\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a95e4b07f02db659f54","contributors":{"authors":[{"text":"Mathany, Timothy M. 0000-0002-4747-5113","orcid":"https://orcid.org/0000-0002-4747-5113","contributorId":99949,"corporation":false,"usgs":true,"family":"Mathany","given":"Timothy M.","affiliations":[],"preferred":false,"id":303577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":303576,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":97915,"text":"ofr20091118 - 2009 - Chronology and references of volcanic eruptions and selected unrest in the United States, 1980-2008","interactions":[],"lastModifiedDate":"2021-02-11T20:48:21.828029","indexId":"ofr20091118","displayToPublicDate":"2009-10-10T00:00:00","publicationYear":"2009","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":"2009-1118","title":"Chronology and references of volcanic eruptions and selected unrest in the United States, 1980-2008","docAbstract":"The United States ranks as one of the top countries in the world in the number of young, active volcanoes within its borders. The United States, including the Commonwealth of the Northern Mariana Islands, is home to approximately 170 geologically active (age <10,000 years) volcanoes. As our review of the record shows, 30 of these volcanoes have erupted since 1980, many repeatedly. In addition to producing eruptions, many U.S. volcanoes exhibit periods of anomalous activity, unrest, that do not culminate in eruptions. \r\n\r\nMonitoring volcanic activity in the United States is the responsibility of the U.S. Geological Survey (USGS) Volcano Hazards Program (VHP) and is accomplished with academic, Federal, and State partners. The VHP supports five Volcano Observatories - the Alaska Volcano Observatory (AVO), Cascades Volcano Observatory (CVO), Yellowstone Volcano Observatory (YVO), Long Valley Observatory (LVO), and Hawaiian Volcano Observatory (HVO). With the exception of HVO, which was established in 1912, the U.S. Volcano Observatories have been established in the past 27 years in response to specific volcanic eruptions or sustained levels of unrest. As understanding of volcanic activity and hazards has grown over the years, so have the extent and types of monitoring networks and techniques available to detect early signs of anomalous volcanic behavior. This increased capability is providing us with a more accurate gauge of volcanic activity in the United States. \r\n\r\nThe purpose of this report is to (1) document the range of volcanic activity that U.S. Volcano Observatories have dealt with, beginning with the 1980 eruption of Mount St. Helens, (2) describe some overall characteristics of the activity, and (3) serve as a quick reference to pertinent published literature on the eruptions and unrest documented in this report.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091118","usgsCitation":"Diefenbach, A., Guffanti, M., and Ewert, J.W., 2009, Chronology and references of volcanic eruptions and selected unrest in the United States, 1980-2008 (Version 1.0): U.S. Geological Survey Open-File Report 2009-1118, 85 p., https://doi.org/10.3133/ofr20091118.","productDescription":"85 p.","onlineOnly":"Y","temporalStart":"1980-01-01","temporalEnd":"2008-12-31","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":125528,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1118.jpg"},{"id":13087,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1118/","linkFileType":{"id":5,"text":"html"}}],"country":"Commonwealth of the Northern Mariana Islands, United States","state":"Alaska, Washington","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49dae4b07f02db5e041b","contributors":{"authors":[{"text":"Diefenbach, Angela K. 0000-0003-0214-7818","orcid":"https://orcid.org/0000-0003-0214-7818","contributorId":36650,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Angela K.","affiliations":[],"preferred":false,"id":303579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guffanti, Marianne","contributorId":68257,"corporation":false,"usgs":true,"family":"Guffanti","given":"Marianne","affiliations":[],"preferred":false,"id":303580,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ewert, John W. 0000-0003-2819-4057 jwewert@usgs.gov","orcid":"https://orcid.org/0000-0003-2819-4057","contributorId":642,"corporation":false,"usgs":true,"family":"Ewert","given":"John","email":"jwewert@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":303578,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":97917,"text":"ofr20091076 - 2009 - Water Use in Wisconsin, 2005","interactions":[],"lastModifiedDate":"2015-06-01T11:34:37","indexId":"ofr20091076","displayToPublicDate":"2009-10-10T00:00:00","publicationYear":"2009","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":"2009-1076","title":"Water Use in Wisconsin, 2005","docAbstract":"The U.S. Geological Survey (USGS) Wisconsin Water Science Center is responsible for presenting data collected or estimated for water withdrawals and diversions every 5 years to the National Water-Use Information Program (NWUIP). This program serves many purposes such as quantifying how much, where, and for what purpose water is used; tracking and documenting water-use trends and changes; and providing these data to other agencies to support hydrologic projects. In 2005, data at both the county and subbasin levels were compiled into the USGS national water-use database system; these data are published in a statewide summary report and a national circular. This publication, Water Use in Wisconsin, 2005, presents the water-use estimates for 2005; this publication also describes how these water-use data were determined (including assumptions used), limitations of using these data, and trends in water-use data presented to the NWUIP. Estimates of water use in Wisconsin indicate that about 8,608 million gallons per day (Mgal/d) were withdrawn during 2005. Of this amount, about 7,622 Mgal/d (89 percent) were from surface-water sources and about 986 Mgal/d (11 percent) were from ground-water sources. Surface water used for cooling at thermoelectric-power plants constituted the largest portion of daily use at 6,898 Mgal/d. Water provided by public-supply water utilities is the second largest use of water and totaled 552 Mgal/d. Public supply served approximately 71 percent of the estimated 2005 Wisconsin population of 5.54 million people; two counties - Milwaukee and Dane - accounted for more than one-third of the public-supply withdrawal. Industrial and irrigation were the next major water uses at 471 and 402 Mgal/d, respectively. Non-irrigational agricultural (livestock and aquaculture) accounted for approximately 155 Mgal/d and is similar to the combined withdrawal for the remaining water-use categories of domestic, commercial, and mining (131 Mgal/d). Data on water use in Wisconsin by source of water and category of use have been compiled at 5-year intervals since 1950. During the past 55 years (1950-2005), water withdrawn to meet demands for public supply and self-supplied irrigation, industrial, commercial, domestic, and livestock increased 333 percent (1,117 Mgal/d). The greatest increases were for public supply, industrial, and irrigation, and are reflected in the increasing total per-capita water-use values. In recent (2000 and 2005) water-use estimation years, both public-supply and self-supplied domestic per-capita-use values have been declining. This can be attributed, at least in part, to a reduction in industrial-water deliveries, increased water-efficiency standards, and the implementation of leak-detection programs and water-conservation practices. However, when making comparisons to evaluate trends among other Wisconsin water-use estimation years, it is important to be aware of changes that may have occurred in estimation methods or objectives that create differences. Some changes that have occurred are the availability of data and information about water use, changes in data sources and estimation methods, and the inclusion and exclusion of certain water-use categories. These differences may have an effect on apparent trends and make comparing trends difficult.
","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091076","usgsCitation":"Buchwald, C.A., 2009, Water Use in Wisconsin, 2005: U.S. Geological Survey Open-File Report 2009-1076, viii, 75 p., https://doi.org/10.3133/ofr20091076.","productDescription":"viii, 75 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2005-01-01","temporalEnd":"2005-12-31","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":118476,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1076.jpg"},{"id":13089,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1076/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{\"type\":\"FeatureCollection\",\n\"features\":[\n{\"type\":\"Feature\",\n\"id\":\"3055\",\n\"properties\":{\"name\":\"Dane\",\"state\":\"WI\"},\n\"geometry\":{\"type\":\"Polygon\",\n\"coordinates\":[\n[[-89.0094,43.286],[-89.0084,43.2555],[-89.0094,43.2],[-89.01,43.1131],[-89.0109,43.0849],[-89.0107,43.0271],[-89.0132,42.9353],[-89.013,42.8762],[-89.0119,42.8471],[-89.132,42.8479],[-89.2488,42.8478],[-89.3689,42.8484],[-89.3688,42.8575],[-89.4832,42.858],[-89.6026,42.8575],[-89.7196,42.8587],[-89.8377,42.8598],[-89.8375,42.9471],[-89.8386,43.0317],[-89.8384,43.1181],[-89.8394,43.205],[-89.8325,43.2123],[-89.825,43.2187],[-89.8175,43.226],[-89.8125,43.2342],[-89.8088,43.2369],[-89.8012,43.2365],[-89.7874,43.2356],[-89.771,43.237],[-89.7579,43.2379],[-89.7529,43.2443],[-89.7485,43.2507],[-89.7391,43.2548],[-89.7259,43.2644],[-89.7171,43.2739],[-89.714,43.2821],[-89.7165,43.2867],[-89.7235,43.2935],[-89.7209,43.2935],[-89.6008,43.2932],[-89.4819,43.2942],[-89.3617,43.2954],[-89.3624,43.2832],[-89.246,43.2834],[-89.1271,43.2827],[-89.0094,43.286]]]}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49d1e4b07f02db5db903","contributors":{"authors":[{"text":"Buchwald, Cheryl A. 0000-0001-8968-5023 cabuchwa@usgs.gov","orcid":"https://orcid.org/0000-0001-8968-5023","contributorId":1943,"corporation":false,"usgs":true,"family":"Buchwald","given":"Cheryl","email":"cabuchwa@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":303585,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":97916,"text":"ofr20091200 - 2009 - Multivariate Statistical Models for Predicting Sediment Yields from Southern California Watersheds","interactions":[],"lastModifiedDate":"2012-02-02T00:14:29","indexId":"ofr20091200","displayToPublicDate":"2009-10-10T00:00:00","publicationYear":"2009","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":"2009-1200","title":"Multivariate Statistical Models for Predicting Sediment Yields from Southern California Watersheds","docAbstract":"Debris-retention basins in Southern California are frequently used to protect communities and infrastructure from the hazards of flooding and debris flow. Empirical models that predict sediment yields are used to determine the size of the basins. Such models have been developed using analyses of records of the amount of material removed from debris retention basins, associated rainfall amounts, measures of watershed characteristics, and wildfire extent and history. In this study we used multiple linear regression methods to develop two updated empirical models to predict sediment yields for watersheds located in Southern California. The models are based on both new and existing measures of volume of sediment removed from debris retention basins, measures of watershed morphology, and characterization of burn severity distributions for watersheds located in Ventura, Los Angeles, and San Bernardino Counties. The first model presented reflects conditions in watersheds located throughout the Transverse Ranges of Southern California and is based on volumes of sediment measured following single storm events with known rainfall conditions. The second model presented is specific to conditions in Ventura County watersheds and was developed using volumes of sediment measured following multiple storm events. To relate sediment volumes to triggering storm rainfall, a rainfall threshold was developed to identify storms likely to have caused sediment deposition. A measured volume of sediment deposited by numerous storms was parsed among the threshold-exceeding storms based on relative storm rainfall totals.\r\n\r\nThe predictive strength of the two models developed here, and of previously-published models, was evaluated using a test dataset consisting of 65 volumes of sediment yields measured in Southern California. The evaluation indicated that the model developed using information from single storm events in the Transverse Ranges best predicted sediment yields for watersheds in San Bernardino, Los Angeles, and Ventura Counties. This model predicts sediment yield as a function of the peak 1-hour rainfall, the watershed area burned by the most recent fire (at all severities), the time since the most recent fire, watershed area, average gradient, and relief ratio. The model that reflects conditions specific to Ventura County watersheds consistently under-predicted sediment yields and is not recommended for application. Some previously-published models performed reasonably well, while others either under-predicted sediment yields or had a larger range of errors in the predicted sediment yields.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091200","usgsCitation":"Gartner, J.E., Cannon, S.H., Helsel, D., and Bandurraga, M., 2009, Multivariate Statistical Models for Predicting Sediment Yields from Southern California Watersheds: U.S. Geological Survey Open-File Report 2009-1200, Report: v, 42 p.; Downloads Directory, https://doi.org/10.3133/ofr20091200.","productDescription":"Report: v, 42 p.; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":118541,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1200.jpg"},{"id":13088,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1200/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b32e4b07f02db6b473f","contributors":{"authors":[{"text":"Gartner, Joseph E. jegartner@usgs.gov","contributorId":1876,"corporation":false,"usgs":true,"family":"Gartner","given":"Joseph","email":"jegartner@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":303582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cannon, Susan H. cannon@usgs.gov","contributorId":1019,"corporation":false,"usgs":true,"family":"Cannon","given":"Susan","email":"cannon@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":303581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Helsel, Dennis R.","contributorId":85569,"corporation":false,"usgs":true,"family":"Helsel","given":"Dennis R.","affiliations":[],"preferred":false,"id":303584,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bandurraga, Mark","contributorId":57974,"corporation":false,"usgs":true,"family":"Bandurraga","given":"Mark","email":"","affiliations":[],"preferred":false,"id":303583,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204956,"text":"70204956 - 2009 - Erratum to Sources and temporal dynamics of arsenic in a New Jersey watershed, USA","interactions":[],"lastModifiedDate":"2019-08-27T08:03:15","indexId":"70204956","displayToPublicDate":"2009-10-09T15:35:38","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Erratum to Sources and temporal dynamics of arsenic in a New Jersey watershed, USA","docAbstract":"No abstract available
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Jersey\",\"nation\":\"USA \"}}]}","volume":"408","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Barringer, Julia jbarring@usgs.gov","contributorId":169542,"corporation":false,"usgs":true,"family":"Barringer","given":"Julia","email":"jbarring@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":769261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonin, Jennifer L. 0000-0002-7631-9734","orcid":"https://orcid.org/0000-0002-7631-9734","contributorId":59404,"corporation":false,"usgs":true,"family":"Bonin","given":"Jennifer L.","affiliations":[],"preferred":false,"id":769262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeLuca, Michael J.","contributorId":82008,"corporation":false,"usgs":true,"family":"DeLuca","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":769263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Romagna, T.","contributorId":37155,"corporation":false,"usgs":true,"family":"Romagna","given":"T.","email":"","affiliations":[],"preferred":false,"id":769264,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cenno, K.","contributorId":66919,"corporation":false,"usgs":true,"family":"Cenno","given":"K.","email":"","affiliations":[],"preferred":false,"id":769265,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alebus, Marzooq","contributorId":15497,"corporation":false,"usgs":true,"family":"Alebus","given":"Marzooq","email":"","affiliations":[],"preferred":false,"id":769266,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kratzer, T.","contributorId":105532,"corporation":false,"usgs":true,"family":"Kratzer","given":"T.","email":"","affiliations":[],"preferred":false,"id":769267,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hirst, B.","contributorId":78555,"corporation":false,"usgs":true,"family":"Hirst","given":"B.","email":"","affiliations":[],"preferred":false,"id":769268,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70003497,"text":"70003497 - 2009 - A case study of carbon fluxes from land change in the Southwest Brazilian Amazon","interactions":[],"lastModifiedDate":"2021-03-05T17:41:20.934657","indexId":"70003497","displayToPublicDate":"2009-10-08T14:46:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2367,"text":"Journal of Land Use Science","active":true,"publicationSubtype":{"id":10}},"title":"A case study of carbon fluxes from land change in the Southwest Brazilian Amazon","docAbstract":"Worldwide, land change is responsible for one-fifth of anthropogenic carbon emissions. In Brazil, three-quarters of carbon emissions originate from land change. This study represents a municipal-scale study of carbon fluxes from vegetation in Rio Branco, Brazil. Land-cover maps of pasture, forest, and secondary growth from 1993, 1996, 1999, and 2003 were produced using an unsupervised classification method (overall accuracy = 89%). Carbon fluxes from land change over the decade of imagery were estimated from transitions between land-cover categories for each time interval. This article presents new methods for estimating emissions reductions from carbon stored in the vegetation that replaces forests (e.g., pasture) and sequestration by new (>10–15 years) forests, which reduced gross emissions by 16, 15, and 22% for the period of 1993–1996, 1996–1999, and 1999–2003, respectively. The methods used in the analysis are broadly applicable and provide a comprehensive characterization of regional-scale carbon fluxes from land change.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/17474230903222481","usgsCitation":"Barrett, K., Rogan, J., and Eastman, J., 2009, A case study of carbon fluxes from land change in the Southwest Brazilian Amazon: Journal of Land Use Science, v. 4, no. 4, p. 233-248, https://doi.org/10.1080/17474230903222481.","productDescription":"16 p.","startPage":"233","endPage":"248","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":476055,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/17474230903222481","text":"Publisher Index Page"},{"id":384095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","otherGeospatial":"Southwest Brazilian Amazon Rainforest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -50.5810546875,\n -0.17578097424708533\n ],\n [\n -69.8291015625,\n -3.425691524418062\n ],\n [\n -72.861328125,\n -5.134714634014442\n ],\n [\n -73.95996093749999,\n -7.318881730366743\n ],\n [\n -73.212890625,\n -9.535748998133615\n ],\n [\n -72.0703125,\n -9.96885060854611\n ],\n [\n -70.57617187499999,\n -9.579084335882534\n ],\n [\n -70.48828125,\n -11.049038346537094\n ],\n [\n -68.37890625,\n -12.46876014482322\n ],\n [\n -69.12597656249999,\n -14.434680215297268\n ],\n [\n -60.55664062499999,\n -14.349547837185362\n ],\n [\n -55.37109374999999,\n -14.562317701914843\n ],\n [\n -49.833984375,\n -12.983147716796566\n ],\n [\n -44.736328125,\n -10.833305983642491\n ],\n [\n -41.1767578125,\n -8.49410453755187\n ],\n [\n -39.5068359375,\n -5.747174076651375\n ],\n [\n -39.287109375,\n -3.3818237353282767\n ],\n [\n -40.341796875,\n -2.6357885741666065\n ],\n [\n -43.41796875,\n -2.2406396093827206\n ],\n [\n -45.0439453125,\n -1.5818302639606454\n ],\n [\n -48.47167968749999,\n -0.21972602392080884\n ],\n [\n -50.5810546875,\n -0.17578097424708533\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b28e4b07f02db6b1117","contributors":{"authors":[{"text":"Barrett, K.","contributorId":40318,"corporation":false,"usgs":true,"family":"Barrett","given":"K.","affiliations":[],"preferred":false,"id":347517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rogan, J.","contributorId":80386,"corporation":false,"usgs":true,"family":"Rogan","given":"J.","email":"","affiliations":[],"preferred":false,"id":347518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eastman, J.R.","contributorId":18876,"corporation":false,"usgs":true,"family":"Eastman","given":"J.R.","email":"","affiliations":[],"preferred":false,"id":347516,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":97908,"text":"sir20095188 - 2009 - Application guide for AFINCH (Analysis of Flows in Networks of Channels) described by NHDPlus","interactions":[],"lastModifiedDate":"2016-10-06T14:46:50","indexId":"sir20095188","displayToPublicDate":"2009-10-08T00:00:00","publicationYear":"2009","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":"2009-5188","title":"Application guide for AFINCH (Analysis of Flows in Networks of Channels) described by NHDPlus","docAbstract":"AFINCH (Analysis of Flows in Networks of CHannels) is a computer application that can be used to generate a time series of monthly flows at stream segments (flowlines) and water yields for catchments defined in the National Hydrography Dataset Plus (NHDPlus) value-added attribute system. AFINCH provides a basis for integrating monthly flow data from streamgages, water-use data, monthly climatic data, and land-cover characteristics to estimate natural monthly water yields from catchments by user-defined regression equations. Images of monthly water yields for active streamgages are generated in AFINCH and provide a basis for detecting anomalies in water yields, which may be associated with undocumented flow diversions or augmentations. Water yields are multiplied by the drainage areas of the corresponding catchments to estimate monthly flows. Flows from catchments are accumulated downstream through the streamflow network described by the stream segments. For stream segments where streamgages are active, ratios of measured to accumulated flows are computed. These ratios are applied to upstream water yields to proportionally adjust estimated flows to match measured flows. Flow is conserved through the NHDPlus network. A time series of monthly flows can be generated for stream segments that average about 1-mile long, or monthly water yields from catchments that average about 1 square mile. Estimated monthly flows can be displayed within AFINCH, examined for nonstationarity, and tested for monotonic trends. Monthly flows also can be used to estimate flow-duration characteristics at stream segments. AFINCH generates output files of monthly flows and water yields that are compatible with ArcMap, a geographical information system analysis and display environment. Chloropleth maps of monthly water yield and flow can be generated and analyzed within ArcMap by joining NHDPlus data structures with AFINCH output. Matlab code for the AFINCH application is presented.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20095188","usgsCitation":"Holtschlag, D.J., 2009, Application guide for AFINCH (Analysis of Flows in Networks of Channels) described by NHDPlus: U.S. Geological Survey Scientific Investigations Report 2009-5188, xii, 106 p., https://doi.org/10.3133/sir20095188.","productDescription":"xii, 106 p.","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":125680,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5188.jpg"},{"id":13081,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5188/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac7e4b07f02db67abcb","contributors":{"authors":[{"text":"Holtschlag, David J. 0000-0001-5185-4928 dholtschlag@usgs.gov","orcid":"https://orcid.org/0000-0001-5185-4928","contributorId":5447,"corporation":false,"usgs":true,"family":"Holtschlag","given":"David","email":"dholtschlag@usgs.gov","middleInitial":"J.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":303556,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70047118,"text":"70047118 - 2009 - Introduction to the High Resolution Imaging Science Experiment (HiRISE)","interactions":[],"lastModifiedDate":"2018-11-20T11:01:40","indexId":"70047118","displayToPublicDate":"2009-10-08T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Introduction to the High Resolution Imaging Science Experiment (HiRISE)","docAbstract":"No abstract available.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Icarus","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2009.10.003","usgsCitation":"McEwen, A.S., Herkenhoff, K.E., and Keszthelyi, L., 2009, Introduction to the High Resolution Imaging Science Experiment (HiRISE): Icarus, v. 205, no. 1, p. 1-1, https://doi.org/10.1016/j.icarus.2009.10.003.","productDescription":"1 p.","startPage":"1","endPage":"1","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-017047","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":278712,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"205","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"527a218be4b051792d01955c","contributors":{"editors":[{"text":"Herkenhoff, Kenneth E. 0000-0002-3153-6663 kherkenhoff@usgs.gov","orcid":"https://orcid.org/0000-0002-3153-6663","contributorId":2275,"corporation":false,"usgs":true,"family":"Herkenhoff","given":"Kenneth","email":"kherkenhoff@usgs.gov","middleInitial":"E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":569815,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Keszthelyi, Laszlo","contributorId":107593,"corporation":false,"usgs":true,"family":"Keszthelyi","given":"Laszlo","email":"","affiliations":[],"preferred":false,"id":569816,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"McEwen, Alfred S.","contributorId":61657,"corporation":false,"usgs":false,"family":"McEwen","given":"Alfred","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":481108,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herkenhoff, Kenneth E. 0000-0002-3153-6663 kherkenhoff@usgs.gov","orcid":"https://orcid.org/0000-0002-3153-6663","contributorId":2275,"corporation":false,"usgs":true,"family":"Herkenhoff","given":"Kenneth","email":"kherkenhoff@usgs.gov","middleInitial":"E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":750968,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keszthelyi, Laszlo P. 0000-0003-1879-4331 laz@usgs.gov","orcid":"https://orcid.org/0000-0003-1879-4331","contributorId":52802,"corporation":false,"usgs":true,"family":"Keszthelyi","given":"Laszlo P.","email":"laz@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":750969,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70041609,"text":"70041609 - 2009 - Detection and characterization of benthic filamentous algal stands (Cladophora sp.) on rocky substrata using a high-frequency echosounder","interactions":[],"lastModifiedDate":"2022-07-25T18:12:31.139221","indexId":"70041609","displayToPublicDate":"2009-10-08T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Detection and characterization of benthic filamentous algal stands (Cladophora sp.) on rocky substrata using a high-frequency echosounder","docAbstract":"A high-frequency echosounder was used to detect and characterize percent cover and stand height of the benthic filamentous green alga Cladophora sp. on rocky substratum of the Laurentian Great Lakes. Comparisons between in situ observations and estimates of the algal stand characteristics (percent cover, stand height) derived from the acoustic data show good agreement for algal stands that exceeded the height threshold for detection by acoustics (~7.5 cm). Backscatter intensity and volume scattering strength were unable to provide any predictive power for estimating algal biomass. A comparative analysis between the only current commercial software (EcoSAV™) and an alternate method using a graphical user interface (GUI) written in MATLAB® confirmed previous findings that EcoSAV functions poorly in conditions where the substrate is uneven and bottom depth changes rapidly. The GUI method uses a signal processing algorithm similar to that of EcoSAV but bases bottom depth classification and algal stand height classification on adjustable thresholds that can be visualized by a trained analyst. This study documents the successful characterization of nuisance quantities of filamentous algae on hard substrate using an acoustic system and demonstrates the potential to significantly increase the efficiency of collecting information on the distribution of nuisance macroalgae. This study also highlights the need for further development of more flexible classification algorithms that can be used in a variety of aquatic ecosystems.","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","publisherLocation":"Waco, TX","doi":"10.4319/lom.2009.7.693","usgsCitation":"Depew, D.C., Stevens, A., Smith, R.E., and Hecky, R.E., 2009, Detection and characterization of benthic filamentous algal stands (Cladophora sp.) on rocky substrata using a high-frequency echosounder: Limnology and Oceanography, v. 7, p. 693-705, https://doi.org/10.4319/lom.2009.7.693.","productDescription":"13 p.","startPage":"693","endPage":"705","ipdsId":"IP-014197","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":476056,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4319/lom.2009.7.693","text":"Publisher Index Page"},{"id":263933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.11,41.3971 ], [ -92.11,48.88 ], [ -76.0002,48.88 ], [ -76.0002,41.3971 ], [ -92.11,41.3971 ] ] ] } } ] }","volume":"7","noUsgsAuthors":false,"publicationDate":"2009-10-08","publicationStatus":"PW","scienceBaseUri":"50c86413e4b03bc63bd679e4","contributors":{"authors":[{"text":"Depew, David C.","contributorId":79772,"corporation":false,"usgs":true,"family":"Depew","given":"David","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":469980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stevens, Andrew W.","contributorId":89093,"corporation":false,"usgs":true,"family":"Stevens","given":"Andrew W.","affiliations":[],"preferred":false,"id":469982,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Ralph E.H.","contributorId":107586,"corporation":false,"usgs":true,"family":"Smith","given":"Ralph","email":"","middleInitial":"E.H.","affiliations":[],"preferred":false,"id":469983,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hecky, Robert E.","contributorId":88628,"corporation":false,"usgs":true,"family":"Hecky","given":"Robert","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":469981,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":97912,"text":"ofr20091220 - 2009 - Preliminary vitrinite and bitumen reflectance, total organic carbon, and pyrolysis data for samples from Upper and Lower Cretaceous strata, Maverick Basin, south Texas","interactions":[],"lastModifiedDate":"2012-02-02T00:15:03","indexId":"ofr20091220","displayToPublicDate":"2009-10-08T00:00:00","publicationYear":"2009","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":"2009-1220","title":"Preliminary vitrinite and bitumen reflectance, total organic carbon, and pyrolysis data for samples from Upper and Lower Cretaceous strata, Maverick Basin, south Texas","docAbstract":"The Lower Cretaceous Pearsall Formation, a regionally occurring limestone and shale interval of 500-600-ft maximum thickness (Rose, 1986), is being evaluated as part of an ongoing U.S. Geological Survey (USGS) assessment of undiscovered hydrocarbon resources in onshore Lower Cretaceous strata of the northern Gulf of Mexico.\r\n\r\nThe purpose of this report is to release preliminary vitrinite and bitumen reflectance, total organic carbon, and pyrolysis data for Pearsall Formation, Glen Rose Formation, Hosston Formation, Austin Group, and Eagle Ford Group samples from the Maverick Basin in south Texas in order to aid in the characterization of these strata in this area. The preliminary nature of this report and the data contained herein reflect that the assessment and characterization of these samples is a work currently in progress.\r\n\r\nPearsall Formation subdivisions are, in ascending stratigraphic order, the Pine Island Shale, James Limestone, and Bexar Shale Members (Loucks, 2002). The Lower Cretaceous Glen Rose Formation is also part of the USGS Lower Cretaceous assessment and produces oil in the Maverick Basin (Loucks and Kerans, 2003). The Hosston Formation was assessed by the USGS for undiscovered oil and gas resources in 2006 (Dyman and Condon, 2006), but not in south Texas.\r\n\r\nThe Upper Cretaceous Austin Group is being assessed as part of the USGS assessment of undiscovered hydrocarbon resources in the Upper Cretaceous strata of the northern Gulf of Mexico and, along with the Upper Cretaceous Eagle Ford Group, is considered to be an important source rock in the Smackover-Austin-Eagleford Total Petroleum System (Condon and Dyman, 2006). Both the Austin Group and the Eagle Ford Group are present in the Maverick Basin in south Texas (Rose, 1986).","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091220","usgsCitation":"Hackley, P.C., Dennen, K., Gesserman, R.M., and Ridgley, J.L., 2009, Preliminary vitrinite and bitumen reflectance, total organic carbon, and pyrolysis data for samples from Upper and Lower Cretaceous strata, Maverick Basin, south Texas: U.S. Geological Survey Open-File Report 2009-1220, Report: iii, 3 p.; Table (xls), https://doi.org/10.3133/ofr20091220.","productDescription":"Report: iii, 3 p.; Table (xls)","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":118560,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1220.jpg"},{"id":13085,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1220/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4aaae4b07f02db6695cc","contributors":{"authors":[{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":303568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dennen, Kristin O.","contributorId":61437,"corporation":false,"usgs":true,"family":"Dennen","given":"Kristin O.","affiliations":[],"preferred":false,"id":303571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gesserman, Rachel M.","contributorId":34229,"corporation":false,"usgs":true,"family":"Gesserman","given":"Rachel","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":303570,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ridgley, Jennie L. ridgley@usgs.gov","contributorId":1248,"corporation":false,"usgs":true,"family":"Ridgley","given":"Jennie","email":"ridgley@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":303569,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":97907,"text":"sir20095134 - 2009 - Dendrogeomorphic Assessment of the Rattlesnake Gulf Landslide in the Tully Valley, Onondaga County, New York","interactions":[],"lastModifiedDate":"2012-03-08T17:16:27","indexId":"sir20095134","displayToPublicDate":"2009-10-08T00:00:00","publicationYear":"2009","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":"2009-5134","title":"Dendrogeomorphic Assessment of the Rattlesnake Gulf Landslide in the Tully Valley, Onondaga County, New York","docAbstract":"Dendrogeomorphic techniques were used to assess soil movement within the Rattlesnake Gulf landslide in the Tully Valley of central New York during the last century. This landslide is a postglacial, slow-moving earth slide that covers 23 acres and consists primarily of rotated, laminated, glaciolacustrine silt and clay. Sixty-two increment cores were obtained from 30 hemlock (Tsuga canadensis) trees across the active part of the landslide and from 3 control sites to interpret the soil-displacement history. Annual growth rings were measured and reaction wood was identified to indicate years in which ring growth changed from concentric to eccentric, on the premise that soil movement triggered compensatory growth in displaced trees. These data provided a basis for an 'event index' to identify years of landslide activity over the 108 years of record represented by the oldest trees. Event-index values and total annual precipitation increased during this time, but years with sudden event-index increases did not necessarily correspond to years with above-average precipitation. Multiple-regression and residual-values analyses indicated a possible correlation between precipitation and movement within the landslide and a possible cyclic (decades-long) tree-ring response to displacement within the landslide area from the toe upward to, and possibly beyond, previously formed landslide features. The soil movement is triggered by a sequence of factors that include (1) periods of several months with below-average precipitation followed by persistent above-average precipitation, (2) the attendant increase in streamflow, which erodes the landslide toe and results in an upslope propagation of slumping, and (3) the harvesting of mature trees within this landslide during the last century and continuing to the present.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095134","isbn":"9781411326026","collaboration":"Prepared in cooperation with Onondaga Lake Partnership and Onondaga Environmental Institute","usgsCitation":"Tamulonis, K.L., and Kappel, W.M., 2009, Dendrogeomorphic Assessment of the Rattlesnake Gulf Landslide in the Tully Valley, Onondaga County, New York: U.S. Geological Survey Scientific Investigations Report 2009-5134, iv, 17 p., https://doi.org/10.3133/sir20095134.","productDescription":"iv, 17 p.","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":118660,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5134.jpg"},{"id":13080,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5134/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76.18333333333334,42.8 ], [ -76.18333333333334,42.916666666666664 ], [ -76.11666666666666,42.916666666666664 ], [ -76.11666666666666,42.8 ], [ -76.18333333333334,42.8 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ab2e4b07f02db66ecc4","contributors":{"authors":[{"text":"Tamulonis, Kathryn L.","contributorId":75234,"corporation":false,"usgs":true,"family":"Tamulonis","given":"Kathryn","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":303555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kappel, William M. 0000-0002-2382-9757 wkappel@usgs.gov","orcid":"https://orcid.org/0000-0002-2382-9757","contributorId":1074,"corporation":false,"usgs":true,"family":"Kappel","given":"William","email":"wkappel@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":303554,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}