{"pageNumber":"676","pageRowStart":"16875","pageSize":"25","recordCount":46883,"records":[{"id":70004605,"text":"70004605 - 2011 - Geology and geochemistry of volcanic centers within the eastern half of the Sonoma volcanic field, northern San Francisco Bay region, California","interactions":[],"lastModifiedDate":"2021-02-25T21:56:02.954513","indexId":"70004605","displayToPublicDate":"2011-07-25T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Geology and geochemistry of volcanic centers within the eastern half of the Sonoma volcanic field, northern San Francisco Bay region, California","docAbstract":"

Volcanic rocks in the Sonoma volcanic field in the northern California Coast Ranges contain heterogeneous assemblages of a variety of compositionally diverse volcanic rocks. We have used field mapping, new and existing age determinations, and 343 new major and trace element analyses of whole-rock samples from lavas and tuff to define for the first time volcanic source areas for many parts of the Sonoma volcanic field. Geophysical data and models have helped to define the thickness of the volcanic pile and the location of caldera structures. Volcanic rocks of the Sonoma volcanic field show a broad range in eruptive style that is spatially variable and specific to an individual eruptive center. Major, minor, and trace-element geochemical data for intracaldera and outflow tuffs and their distal fall equivalents suggest caldera-related sources for the Pinole and Lawlor Tuffs in southern Napa Valley and for the tuff of Franz Valley in northern Napa Valley. Stratigraphic correlations based on similarity in eruptive sequence and style coupled with geochemical data allow an estimate of 30 km of right-lateral offset across the West Napa-Carneros fault zones since ∼5 Ma.

The volcanic fields in the California Coast Ranges north of San Francisco Bay are temporally and spatially associated with the northward migration of the Mendocino triple junction and the transition from subduction and associated arc volcanism to a slab window tectonic environment. Our geochemical analyses from the Sonoma volcanic field highlight the geochemical diversity of these volcanic rocks, allowing us to clearly distinguish these volcanic rocks from those of the roughly coeval ancestral Cascades magmatic arc to the west, and also to compare rocks of the Sonoma volcanic field to rocks from other slab window settings.

","language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","doi":"10.1130/GES00625.1","usgsCitation":"Sweetkind, D., Rytuba, J.J., Langenheim, V., and Fleck, R.J., 2011, Geology and geochemistry of volcanic centers within the eastern half of the Sonoma volcanic field, northern San Francisco Bay region, California: Geosphere, v. 7, no. 3, p. 629-657, https://doi.org/10.1130/GES00625.1.","productDescription":"19 p.","startPage":"629","endPage":"657","numberOfPages":"29","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":474959,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges00625.1","text":"Publisher Index Page"},{"id":204092,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sonoma Volcanic Field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.92053222656249,\n 38.11727165830543\n ],\n [\n -122.10205078125,\n 38.11727165830543\n ],\n [\n -122.10205078125,\n 38.74551518488265\n ],\n [\n -122.92053222656249,\n 38.74551518488265\n ],\n [\n -122.92053222656249,\n 38.11727165830543\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4adbe4b07f02db6860ea","contributors":{"authors":[{"text":"Sweetkind, Donald S.","contributorId":18732,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald S.","affiliations":[],"preferred":false,"id":350837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rytuba, James J. jrytuba@usgs.gov","contributorId":3043,"corporation":false,"usgs":true,"family":"Rytuba","given":"James","email":"jrytuba@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":350836,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langenheim, Victoria E. 0000-0003-2170-5213 zulanger@usgs.gov","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":1526,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria E.","email":"zulanger@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":350835,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fleck, Robert J. 0000-0002-3149-8249 fleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3149-8249","contributorId":1048,"corporation":false,"usgs":true,"family":"Fleck","given":"Robert","email":"fleck@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":350834,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70004948,"text":"ofr20111114 - 2011 - Fort Collins Science Center fiscal year 2010 science accomplishments","interactions":[],"lastModifiedDate":"2012-02-02T00:15:54","indexId":"ofr20111114","displayToPublicDate":"2011-07-25T00:00:00","publicationYear":"2011","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":"2011-1114","title":"Fort Collins Science Center fiscal year 2010 science accomplishments","docAbstract":"The scientists and technical professionals at the U.S. Geological Survey (USGS), Fort Collins Science Center (FORT), apply their diverse ecological, socioeconomic, and technological expertise to investigate complicated ecological problems confronting managers of the Nation's biological resources. FORT works closely with U.S. Department of the Interior (DOI) agency scientists, the academic community, other USGS science centers, and many other partners to provide critical information needed to help answer complex natural-resource management questions. In Fiscal Year 2010 (FY10), FORT's scientific and technical professionals conducted ongoing, expanded, and new research vital to the science needs and management goals of DOI, other Federal and State agencies, and nongovernmental organizations in the areas of aquatic systems and fisheries, climate change, data and information integration and management, invasive species, science support, security and technology, status and trends of biological resources (including the socioeconomic aspects), terrestrial and freshwater ecosystems, and wildlife resources, including threatened and endangered species. This report presents selected FORT science accomplishments for FY10 by the specific USGS mission area or science program with which each task is most closely associated, though there is considerable overlap. The report also includes all FORT publications and other products published in FY10, as well as staff accomplishments, appointments, committee assignments, and invited presentations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111114","usgsCitation":"Wilson, J.T., 2011, Fort Collins Science Center fiscal year 2010 science accomplishments: U.S. Geological Survey Open-File Report 2011-1114, v, 62 p., https://doi.org/10.3133/ofr20111114.","productDescription":"v, 62 p.","startPage":"i","endPage":"62","numberOfPages":"67","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2009-10-01","temporalEnd":"2010-09-30","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":116169,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1114.gif"},{"id":24438,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1114/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b23e4b07f02db6ae35b","contributors":{"authors":[{"text":"Wilson, Juliette T.","contributorId":86439,"corporation":false,"usgs":true,"family":"Wilson","given":"Juliette","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":351713,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70004944,"text":"sir20115095 - 2011 - Development of a precipitation-runoff model to simulate unregulated streamflow in the South Fork Flathead River Basin, Montana","interactions":[],"lastModifiedDate":"2012-03-08T17:16:41","indexId":"sir20115095","displayToPublicDate":"2011-07-25T00:00:00","publicationYear":"2011","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":"2011-5095","title":"Development of a precipitation-runoff model to simulate unregulated streamflow in the South Fork Flathead River Basin, Montana","docAbstract":"This report documents the development of a precipitation-runoff model for the South Fork Flathead River Basin, Mont. The Precipitation-Runoff Modeling System model, developed in cooperation with the Bureau of Reclamation, can be used to simulate daily mean unregulated streamflow upstream and downstream from Hungry Horse Reservoir for water-resources planning. Two input files are required to run the model. The time-series data file contains daily precipitation data and daily minimum and maximum air-temperature data from climate stations in and near the South Fork Flathead River Basin. The parameter file contains values of parameters that describe the basin topography, the flow network, the distribution of the precipitation and temperature data, and the hydrologic characteristics of the basin soils and vegetation.\r\n\r\nA primary-parameter file was created for simulating streamflow during the study period (water years 1967-2005). The model was calibrated for water years 1991-2005 using the primary-parameter file. This calibration was further refined using snow-covered area data for water years 2001-05. The model then was tested for water years 1967-90. Calibration targets included mean monthly and daily mean unregulated streamflow upstream from Hungry Horse Reservoir, mean monthly unregulated streamflow downstream from Hungry Horse Reservoir, basin mean monthly solar radiation and potential evapotranspiration, and daily snapshots of basin snow-covered area. \r\n\r\nSimulated streamflow generally was in better agreement with observed streamflow at the upstream gage than at the downstream gage. Upstream from the reservoir, simulated mean annual streamflow was within 0.0 percent of observed mean annual streamflow for the calibration period and was about 2 percent higher than observed mean annual streamflow for the test period. Simulated mean April-July streamflow upstream from the reservoir was about 1 percent lower than observed streamflow for the calibration period and about 4 percent higher than observed for the test period. Downstream from the reservoir, simulated mean annual streamflow was 17 percent lower than observed streamflow for the calibration period and 12 percent lower than observed streamflow for the test period. Simulated mean April-July streamflow downstream from the reservoir was 13 percent lower than observed streamflow for the calibration period and 6 percent lower than observed streamflow for the test period. \r\n\r\nCalibrating to solar radiation, potential evapotranspiration, and snow-covered area improved the model representation of evapotranspiration, snow accumulation, and snowmelt processes. Simulated basin mean monthly solar radiation values for both the calibration and test periods were within 9 percent of observed values except during the month of December (28 percent different). Simulated basin potential evapotranspiration values for both the calibration and test periods were within 10 percent of observed values except during the months of January (100 percent different) and February (13 percent different). The larger percent errors in simulated potential evaporation occurred in the winter months when observed potential evapotranspiration values were very small; in January the observed value was 0.000 inches and in February the observed value was 0.009 inches. Simulated start of melting of the snowpack occurred at about the same time as observed start of melting. The simulated snowpack accumulated to 90-100 percent snow-covered area 1 to 3 months earlier than observed snowpack. This overestimated snowpack during the winter corresponded to underestimated streamflow during the same period. \r\n\r\nIn addition to the primary-parameter file, four other parameter files were created: for a \"recent\" period (1991-2005), a historical period (1967-90), a \"wet\" period (1989-97), and a \"dry\" period (1998-2005). For each data file of projected precipitation and air temperature, a single parameter file can be used to simulate a s","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115095","usgsCitation":"Chase, K., 2011, Development of a precipitation-runoff model to simulate unregulated streamflow in the South Fork Flathead River Basin, Montana: U.S. Geological Survey Scientific Investigations Report 2011-5095, viii, 38 p., https://doi.org/10.3133/sir20115095.","productDescription":"viii, 38 p.","costCenters":[{"id":400,"text":"Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":116156,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5095.gif"},{"id":24435,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5095/","linkFileType":{"id":5,"text":"html"}}],"scale":"100000","country":"United States","state":"Montana;Idaho","otherGeospatial":"South Fork Flathead River Basin;Hungry Horse Reservoir;Clark Fort Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116,45 ], [ -116,49 ], [ -111,49 ], [ -111,45 ], [ -116,45 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a9be4b07f02db65e459","contributors":{"authors":[{"text":"Chase, K.J.","contributorId":43093,"corporation":false,"usgs":true,"family":"Chase","given":"K.J.","email":"","affiliations":[],"preferred":false,"id":351698,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70004935,"text":"ofr20111178 - 2011 - Evaluation of angler effort and harvest of rainbow trout (Oncorhynchus mykiss), Lake Scanewa, Washington, 2010","interactions":[],"lastModifiedDate":"2012-02-10T00:11:59","indexId":"ofr20111178","displayToPublicDate":"2011-07-22T00:00:00","publicationYear":"2011","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":"2011-1178","title":"Evaluation of angler effort and harvest of rainbow trout (Oncorhynchus mykiss), Lake Scanewa, Washington, 2010","docAbstract":"A creel evaluation was conducted in Lake Scanewa, a reservoir on the Cowlitz River, to monitor catch rates of rainbow trout (Oncorhynchus mykiss) and determine if the trout fishery was having negative impacts on juvenile anadromous salmon (Oncorhynchus spp.) in the system. The trout fishery, which is supported by releases of 20,000 fish (2 fish per pound) per year from June to August, was developed to mitigate for the construction of the Cowlitz Falls Dam in 1994. The trout fishery has a target catch rate of at least 0.50 fish per hour. Interviews with 1,214 anglers during the creel evaluation found that most anglers targeted rainbow trout (52 percent) or Chinook and coho salmon (48 percent). The interviewed anglers caught a total of 1,866 fish, most of which were rainbow trout (1,213 fish; 78 percent) or coho salmon (311 fish; 20 percent). We estimated that anglers spent 17,365 hours fishing in Lake Scanewa from June to November 2010. Catch rates for boat anglers (1.39 fish per hour) exceeded the 0.50 fish per hour target, whereas catch rates for shore anglers (0.35 fish per hour) fell short of the goal. The combined catch rates for all trout anglers in the reservoir were 0.96 fish per hour. We estimated that anglers harvested 7,584 (95 percent confidence interval = 2,795-12,372 fish) rainbow trout during the study period and boat anglers caught more fish than shore anglers (5,975 and 1,609 fish, respectively). This estimate suggests that more than 12,000 of the 20,000 rainbow trout released into Lake Scanewa during 2010 were not harvested, and could negatively impact juvenile salmon in the reservoir through predation or competition. We examined 1,236 stomach samples from rainbow trout and found that 2.1 percent (26 fish) of these samples contained juvenile fish. Large trout (greater than 300 millimeters) had a higher incidence of predation than small trout (less than 300 millimeters; 8.50 and 0.06 percent, respectively). A total of 39 fish were found in rainbow trout stomachs and 13 (33 percent) of these were juvenile salmon. These data and uncertainties associated with movement patterns and survival rates of rainbow trout in Lake Scanewa suggest that future evaluations would be helpful to better understand the potential effects of the mitigation trout fishery on juvenile salmon in the reservoir.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111178","usgsCitation":"Liedtke, T.L., Kock, T.J., Ekstrom, B.K., Tomka, R.G., and Rondorf, D.W., 2011, Evaluation of angler effort and harvest of rainbow trout (Oncorhynchus mykiss), Lake Scanewa, Washington, 2010: U.S. Geological Survey Open-File Report 2011-1178, iv, 12 p.; Figures; Tables, https://doi.org/10.3133/ofr20111178.","productDescription":"iv, 12 p.; Figures; Tables","startPage":"i","endPage":"24","numberOfPages":"28","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":116163,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1178.bmp"},{"id":24425,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1178/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Washington","otherGeospatial":"Lake Scanewa","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.10194444444444,46.45027777777778 ], [ -122.10194444444444,46.50083333333333 ], [ -122.00194444444445,46.50083333333333 ], [ -122.00194444444445,46.45027777777778 ], [ -122.10194444444444,46.45027777777778 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a4be4b07f02db625794","contributors":{"authors":[{"text":"Liedtke, Theresa L. 0000-0001-6063-9867 tliedtke@usgs.gov","orcid":"https://orcid.org/0000-0001-6063-9867","contributorId":2999,"corporation":false,"usgs":true,"family":"Liedtke","given":"Theresa","email":"tliedtke@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":351677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kock, Tobias J. 0000-0001-8976-0230 tkock@usgs.gov","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":3038,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","email":"tkock@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":351678,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ekstrom, Brian K. 0000-0002-1162-1780 bekstrom@usgs.gov","orcid":"https://orcid.org/0000-0002-1162-1780","contributorId":3704,"corporation":false,"usgs":true,"family":"Ekstrom","given":"Brian","email":"bekstrom@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":351679,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tomka, Ryan G. 0000-0003-1078-6089 rtomka@usgs.gov","orcid":"https://orcid.org/0000-0003-1078-6089","contributorId":3706,"corporation":false,"usgs":true,"family":"Tomka","given":"Ryan","email":"rtomka@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":351680,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rondorf, Dennis W. drondorf@usgs.gov","contributorId":2970,"corporation":false,"usgs":true,"family":"Rondorf","given":"Dennis","email":"drondorf@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":351676,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70004893,"text":"cir1368 - 2011 - Development of industrial minerals in Colorado","interactions":[],"lastModifiedDate":"2012-02-10T00:12:00","indexId":"cir1368","displayToPublicDate":"2011-07-22T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1368","title":"Development of industrial minerals in Colorado","docAbstract":"Technology and engineering have helped make mining safer and cleaner for both humans and the environment. Inevitably, mineral development entails costs as well as benefits. Developing a mine is an environmental, engineering, and planning challenge that must conform to many Federal, State, and local regulations. Community collaboration, creative design, and best management practices of sustainability and biodiversity can be positive indicators for the mining industry. A better understanding of aesthetics, culture, economics, geology, climate, vegetation and wildlife, topography, historical significance, and regional land planning is important in resolving land-use issues and managing mineral resources wisely. Ultimately, the consuming public makes choices about product use (including water, food, highways, housing, and thousands of other items) that influence operations of the mineral industry. Land planners, resource managers, earth scientists, designers, and public groups have a responsibility to consider sound scientific information, society's needs, and community appeals in making smart decisions concerning resource use and how complex landscapes should change. \n\nAn effort to provide comprehensive geosciences data for land management agencies in central Colorado was undertaken in 2003 by scientists of the U.S. Geological Survey and the Colorado Geological Survey. This effort, the Central Colorado Assessment Project, addressed a variety of land-use issues: an understanding of the availability of industrial and metallic rocks and minerals, the geochemical and environmental effects of historic mining activity on surface water and groundwater, and the geologic controls on the availability and quality of groundwater. \n\nThe USDA Forest Service and other land management agencies have the opportunity to contribute to the sustainable management of natural aggregate and other mineral resources through the identification and selective development of mineral resources and the reclamation of mines on lands that they administer. The information in this Circular will help them carry out that task.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1368","usgsCitation":"Arbogast, B.F., Knepper, D.H., Langer, W.H., Cappa, J.A., Keller, J.W., Widmann, B.L., Ellefsen, K.J., Klein, T.L., Lucius, J.E., and Dersch, J.S., 2011, Development of industrial minerals in Colorado: U.S. Geological Survey Circular 1368, vii, 87 p., https://doi.org/10.3133/cir1368.","productDescription":"vii, 87 p.","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":116164,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir_1368.gif"},{"id":24427,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/circ/1368/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Colorado","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -107,37 ], [ -107,41 ], [ -104.5,41 ], [ -104.5,37 ], [ -107,37 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a9be4b07f02db65de9f","contributors":{"authors":[{"text":"Arbogast, Belinda F.","contributorId":89124,"corporation":false,"usgs":true,"family":"Arbogast","given":"Belinda","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":351614,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knepper, Daniel H. dknepper@usgs.gov","contributorId":1242,"corporation":false,"usgs":true,"family":"Knepper","given":"Daniel","email":"dknepper@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":351610,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langer, William H. blanger@usgs.gov","contributorId":1241,"corporation":false,"usgs":true,"family":"Langer","given":"William","email":"blanger@usgs.gov","middleInitial":"H.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":false,"id":351609,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cappa, James A.","contributorId":47844,"corporation":false,"usgs":true,"family":"Cappa","given":"James","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":351612,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Keller, John W.","contributorId":48687,"corporation":false,"usgs":true,"family":"Keller","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":351613,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Widmann, Beth L.","contributorId":104613,"corporation":false,"usgs":true,"family":"Widmann","given":"Beth","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":351616,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ellefsen, Karl J. 0000-0003-3075-4703 ellefsen@usgs.gov","orcid":"https://orcid.org/0000-0003-3075-4703","contributorId":789,"corporation":false,"usgs":true,"family":"Ellefsen","given":"Karl","email":"ellefsen@usgs.gov","middleInitial":"J.","affiliations":[{"id":82803,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":false}],"preferred":true,"id":351607,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Klein, Terry L. tklein@usgs.gov","contributorId":1244,"corporation":false,"usgs":true,"family":"Klein","given":"Terry","email":"tklein@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":351611,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lucius, Jeffrey E. lucius@usgs.gov","contributorId":817,"corporation":false,"usgs":true,"family":"Lucius","given":"Jeffrey","email":"lucius@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":351608,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dersch, John S.","contributorId":89500,"corporation":false,"usgs":true,"family":"Dersch","given":"John","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":351615,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70003896,"text":"70003896 - 2011 - Genetic landscapes GIS Toolbox: Tools to map patterns of genetic divergence and diversity.","interactions":[],"lastModifiedDate":"2021-05-18T15:37:19.294974","indexId":"70003896","displayToPublicDate":"2011-07-20T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2776,"text":"Molecular Ecology Resources","active":true,"publicationSubtype":{"id":10}},"title":"Genetic landscapes GIS Toolbox: Tools to map patterns of genetic divergence and diversity.","docAbstract":"

The Landscape Genetics GIS Toolbox contains tools that run in the Geographic Information System software, ArcGIS®, to map genetic landscapes and to summarize multiple genetic landscapes as average and variance surfaces. These tools can be used to visualize the distribution of genetic diversity across geographic space and to study associations between patterns of genetic diversity and geographic features or other geo‐referenced environmental data sets. Together, these tools create genetic landscape surfaces directly from tables containing genetic distance or diversity data and sample location coordinates, greatly reducing the complexity of building and analyzing these raster surfaces in a Geographic Information System.

","language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1755-0998.2010.02904.x","usgsCitation":"Vandergast, A.G., Perry, W.M., Lugo, R.V., and Hathaway, S.A., 2011, Genetic landscapes GIS Toolbox: Tools to map patterns of genetic divergence and diversity.: Molecular Ecology Resources, v. 11, no. 1, p. 158-161, https://doi.org/10.1111/j.1755-0998.2010.02904.x.","productDescription":"4 p.","startPage":"158","endPage":"161","numberOfPages":"4","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":474961,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1755-0998.2010.02904.x","text":"Publisher Index Page"},{"id":203900,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationDate":"2010-08-16","publicationStatus":"PW","scienceBaseUri":"4f4e4b24e4b07f02db6aeb27","contributors":{"authors":[{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":97617,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","email":"","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":349361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, William M. 0000-0002-6180-8180 wmperry@usgs.gov","orcid":"https://orcid.org/0000-0002-6180-8180","contributorId":5124,"corporation":false,"usgs":true,"family":"Perry","given":"William","email":"wmperry@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":349360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lugo, Roberto V. rlugo@usgs.gov","contributorId":4011,"corporation":false,"usgs":true,"family":"Lugo","given":"Roberto","email":"rlugo@usgs.gov","middleInitial":"V.","affiliations":[],"preferred":true,"id":349359,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hathaway, Stacie A. 0000-0002-4167-8059 sahathaway@usgs.gov","orcid":"https://orcid.org/0000-0002-4167-8059","contributorId":3420,"corporation":false,"usgs":true,"family":"Hathaway","given":"Stacie","email":"sahathaway@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":349358,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70004931,"text":"sir20095219 - 2011 - Application of a watershed model (HSPF) for evaluating sources and transport of pathogen indicators in the Chino Basin drainage area, San Bernardino County, California","interactions":[],"lastModifiedDate":"2012-03-08T17:16:41","indexId":"sir20095219","displayToPublicDate":"2011-07-20T00:00:00","publicationYear":"2011","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":"2009-5219","title":"Application of a watershed model (HSPF) for evaluating sources and transport of pathogen indicators in the Chino Basin drainage area, San Bernardino County, California","docAbstract":"A watershed model using Hydrologic Simulation Program-FORTRAN (HSPF) was developed for the urbanized Chino Basin in southern California to simulate the transport of pathogen indicator bacteria, evaluate the flow-component and land-use contributions to bacteria contamination and water-quality degradation throughout the basin, and develop a better understanding of the potential effects of climate and land-use change on water quality. The calibration of the model for indicator bacteria was supported by historical data collected before this study and by samples collected by the U.S. Geological Survey from targeted land-use areas during storms in water-year 2004. The model was successfully calibrated for streamflow at 5 gage locations representing the Chino Creek and Mill Creek drainages. Although representing pathogens as dissolved constituents limits the model's ability to simulate the transport of pathogen indicator bacteria, the bacteria concentrations measured over the period 1998-2004 were well represented by the simulated concentrations for most locations. Hourly concentrations were more difficult to predict because of high variability in measured bacteria concentrations. In general, model simulations indicated that the residential and commercial land uses were the dominant sources for most of the pathogen indicator bacteria during low streamflows. However, simulations indicated that land used for intensive livestock (dairies and feedlots) and mixed agriculture contributed the most bacteria during storms. \r\n\r\nThe calibrated model was used to evaluate how various land use, air temperature, and precipitation scenarios would affect flow and transport of bacteria. Results indicated that snow pack formation and melt were sensitive to changes in air temperature in the northern, mountainous part of the Chino Basin, causing the timing and magnitude of streamflow to shift in the natural drainages and impact the urbanized areas of the central Chino Basin. The relation between bacteria concentrations and air temperature was more complicated, and did not substantially affect the quality of water discharging from the Chino Basin into the Santa Ana River. Changes in precipitation had a greater basin-wide affect on bacteria concentrations than changes in air temperature, and varied according to location. Drainages representing natural conditions had a decrease in bacteria concentrations in correlation with an increase in precipitation, whereas drainages in the central and southern part of the Chino Basin had an increase in bacteria concentrations. Drier climate conditions tended to result in higher sensitivity of simulated bacteria concentrations to changes in precipitation. Simulated bacteria concentrations in wetter climates were usually less sensitive to changes in precipitation because bacteria transport becomes more dependent on the land-use specified bacteria loading rates and the storage limits. Bacteria contamination from impervious-area runoff is affected to a greater degree by drier climates, whereas contamination from pervious-area runoff is affected to a greater degree by wetter climates. Model results indicated that the relation between precipitation, runoff, and bacteria contamination is complicated because after the initial bacteria washoff and transport from the land surfaces during the beginning of a storm period, subsequent runoff has fewer bacteria available for washoff, which then dilutes the concentrations of bacteria in the downstream reach. It was illustrated that pathogen indicator bacteria transport depends most significantly on the relation of imperviousness to runoff, which controls the frequency, and often the magnitude, of transport, and on the contribution of higher bacteria loading rates used for pervious land areas, especially intensive feedlots, to the infrequent, but very high, peaks of bacteria contamination.\r\n\r\nThe indicator bacteria transport model for the Chino Basin was based on the assumption that no","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20095219","usgsCitation":"Hevesi, J.A., Flint, L.E., Church, C.D., and Mendez, G.O., 2011, Application of a watershed model (HSPF) for evaluating sources and transport of pathogen indicators in the Chino Basin drainage area, San Bernardino County, California: U.S. Geological Survey Scientific Investigations Report 2009-5219, xiv, 142 p.; Appendices, https://doi.org/10.3133/sir20095219.","productDescription":"xiv, 142 p.; Appendices","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":116159,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5219.jpg"},{"id":24423,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5219/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","county":"San Bernardino County;Orange County;Los Angeles County;Riverside County","otherGeospatial":"Chino Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119,33 ], [ -119,35 ], [ -116.5,35 ], [ -116.5,33 ], [ -119,33 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac6e4b07f02db67aa97","contributors":{"authors":[{"text":"Hevesi, Joseph 0000-0003-2898-1800 jhevesi@usgs.gov","orcid":"https://orcid.org/0000-0003-2898-1800","contributorId":1507,"corporation":false,"usgs":true,"family":"Hevesi","given":"Joseph","email":"jhevesi@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":351673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":351671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Church, Clinton D.","contributorId":8189,"corporation":false,"usgs":true,"family":"Church","given":"Clinton","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":351674,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mendez, Gregory O. 0000-0002-9955-3726 gomendez@usgs.gov","orcid":"https://orcid.org/0000-0002-9955-3726","contributorId":1489,"corporation":false,"usgs":true,"family":"Mendez","given":"Gregory","email":"gomendez@usgs.gov","middleInitial":"O.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":351672,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70004919,"text":"gip131 - 2011 - The international charter for space and major disasters--project manager training","interactions":[],"lastModifiedDate":"2017-03-27T11:20:18","indexId":"gip131","displayToPublicDate":"2011-07-19T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"131","title":"The international charter for space and major disasters--project manager training","docAbstract":"Regional Project Managers for the Charter are developed through training courses, which typically last between 3 and 5 days and are held in a central location for participants. These courses have resulted in increased activations and broader use of Charter data and information by local emergency management authorities. Project Managers are nominated according to either their regional affiliation or their specific areas of expertise. A normal activation takes 2 to 3 weeks to complete, with all related expenses the responsibility of the PM's home agency.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip131","usgsCitation":"Jones, B., 2011, The international charter for space and major disasters--project manager training: U.S. Geological Survey General Information Product 131, 1 p., https://doi.org/10.3133/gip131.","productDescription":"1 p.","startPage":"1","endPage":"1","numberOfPages":"1","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":116172,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/gip_131.jpg"},{"id":24412,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/gip/131/","linkFileType":{"id":5,"text":"html"}},{"id":19162,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/BF01032928"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a85e4b07f02db64d3fc","contributors":{"authors":[{"text":"Jones, Brenda 0000-0003-4941-5349 bkjones@usgs.gov","orcid":"https://orcid.org/0000-0003-4941-5349","contributorId":2994,"corporation":false,"usgs":true,"family":"Jones","given":"Brenda","email":"bkjones@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":351661,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70004920,"text":"fs20113077 - 2011 - Mapping perennial vegetation cover in the Mojave Desert","interactions":[],"lastModifiedDate":"2012-02-10T00:11:59","indexId":"fs20113077","displayToPublicDate":"2011-07-19T00:00:00","publicationYear":"2011","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":"2011-3077","title":"Mapping perennial vegetation cover in the Mojave Desert","docAbstract":"Scientists with the U.S. Geological Survey's Western Geographic Science Center have recently created a regional map of perennial vegetation cover for the Mojave Desert. The scientists used existing field data collected for a variety of previous studies and satellite data available for free through USGS archives to create a calibrated model of percent vegetation cover, an important attribute of desert ecosystems. This map is being used to inform ongoing scientific investigations and land-management efforts, including endangered species habitat mapping and vulnerability and recoverability studies of desert landscapes in the arid Southwest.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20113077","collaboration":"RESEARCH AT THE USGS WESTERN GEOGRAPHIC SCIENCE CENTER","usgsCitation":"Wallace, C., 2011, Mapping perennial vegetation cover in the Mojave Desert: U.S. Geological Survey Fact Sheet 2011-3077, 2 p., https://doi.org/10.3133/fs20113077.","productDescription":"2 p.","startPage":"1","endPage":"2","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":116189,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2011_3077.gif"},{"id":24413,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2011/3077/","linkFileType":{"id":5,"text":"html"}},{"id":19163,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/BF01032927"}],"country":"United States","state":"California;Nevada;Utah;Arizona","otherGeospatial":"Mojave Desert","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -118,33.5 ], [ -118,37.5 ], [ -113,37.5 ], [ -113,33.5 ], [ -118,33.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b0be4b07f02db69de0a","contributors":{"authors":[{"text":"Wallace, Cynthia S.A. cwallace@usgs.gov","contributorId":3335,"corporation":false,"usgs":true,"family":"Wallace","given":"Cynthia S.A.","email":"cwallace@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":351662,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70118549,"text":"70118549 - 2011 - Three types of gas hydrate reservoirs in the Gulf of Mexico identified in LWD data","interactions":[],"lastModifiedDate":"2014-07-29T11:19:35","indexId":"70118549","displayToPublicDate":"2011-07-17T11:16:55","publicationYear":"2011","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":12,"text":"Conference publication"},"title":"Three types of gas hydrate reservoirs in the Gulf of Mexico identified in LWD data","docAbstract":"High quality logging-while-drilling (LWD) well logs were acquired in seven wells drilled during the Gulf of Mexico Gas Hydrate Joint Industry Project Leg II in the spring of 2009. These data help to identify three distinct types of gas hydrate reservoirs: isotropic reservoirs in sands, vertical fractured reservoirs in shale, and horizontally layered reservoirs in silty shale. In general, most gas hydratebearing sand reservoirs exhibit isotropic elastic velocities and formation resistivities, and gas hydrate saturations estimated from the P-wave velocity agree well with those from the resistivity. However, in highly gas hydrate-saturated sands, resistivity-derived gas hydrate-saturation estimates appear to be systematically higher by about 5% over those estimated by P-wave velocity, possibly because of the uncertainty associated with the consolidation state of gas hydrate-bearing sands. Small quantities of gas hydrate were observed in vertical fractures in shale. These occurrences are characterized by high formation resistivities with P-wave velocities close to those of water-saturated sediment. Because the formation factor varies significantly with respect to the gas hydrate saturation for vertical fractures at low saturations, an isotropic analysis of formation factor highly overestimates the gas hydrate saturation. Small quantities of gas hydrate in horizontal layers in shale are characterized by moderate increase in P-wave velocities and formation resistivities and either measurement can be used to estimate gas hydrate saturations.","largerWorkTitle":"Proceedings of the 7th International Conference on Gas Hydrates","conferenceTitle":"7th International Conference on Gas Hydrates","conferenceDate":"2011-07-17T00:00:00","conferenceLocation":"Edinburgh, Scotland","language":"English","publisher":"ICGH","publisherLocation":"Edinburgh, Scotland","usgsCitation":"Lee, M.W., and Collett, T.S., 2011, Three types of gas hydrate reservoirs in the Gulf of Mexico identified in LWD data, 12 p.","productDescription":"12 p.","numberOfPages":"12","costCenters":[],"links":[{"id":291282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57fe7f2ee4b0824b2d1476c5","contributors":{"authors":[{"text":"Lee, Myung Woong","contributorId":15114,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","email":"","middleInitial":"Woong","affiliations":[],"preferred":false,"id":496985,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":496984,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70156455,"text":"70156455 - 2011 - Beaufort Sea deep-water gas hydrate recovery from a seafloor mound in a region of widespread BSR occurrence","interactions":[],"lastModifiedDate":"2022-11-08T20:00:32.399138","indexId":"70156455","displayToPublicDate":"2011-07-17T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Beaufort Sea deep-water gas hydrate recovery from a seafloor mound in a region of widespread BSR occurrence","docAbstract":"

Gas hydrate was recovered from the Alaskan Beaufort Sea slope north of Camden Bay in August 2010 during a U.S. Coast Guard Cutter Healy expedition (USCG cruise ID HLY1002) under the direction of the U.S. Geological Survey (USGS). Interpretation of multichannel seismic (MCS) reflection data collected in 1977 by the USGS across the Beaufort Sea continental margin identified a regional bottom simulating reflection (BSR), indicating that a large segment of the Beaufort Sea slope is underlain by gas hydrate. During HLY1002, gas hydrate was sampled by serendipity with a piston core targeting a steep-sided bathymetric high originally thought to be an outcrop of older, exposed strata. The feature cored is an approximately 1100m diameter, 130 m high conical mound, referred to here as the Canning Seafloor Mound (CSM), which overlies the crest of a buried anticline in a region of sub-parallel compressional folds beneath the eastern Beaufort outer slope. An MCS profile shows a prominent BSR upslope and downslope from the mound. The absence of a BSR beneath the CSM and occurrence of gas hydrate near the summit indicates that free gas has migrated via deep-rooted thrust faults or by structural focusing up the flanks of the anticline to the seafloor. Gas hydrate recovered from near the CSM summit at a subbottom depth of about 5.7 meters in a water depth of 2538 m was of nodular and vein-filling morphology. Although the hydrate was not preserved, residual gas from the core liner contained >95% methane by volume when corrected for atmospheric contamination. The presence of trace C4+hydrocarbons (<0.1% by volume) confirms at least a minor thermogenic component. Authigenic carbonates and mollusk shells found throughout the core indicate sustained methane-rich fluid advection and possible sediment extrusion contributing to the development of the mound. Blister-like inflation of the seafloor caused by formation and accumulation of shallow hydrate lenses is also a likely factor in CSM growth. Pore water analysis shows the sulfate-methane transition to be very shallow (0-1 mbsf), also supporting an active high-flux interpretation. Pore water with chloride concentrations as low as 160 mM suggest fluid migration pathways may extend to the mound from buried non-marine sediments containing low-salinity fluids.

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It comprises functions, dialogs, and datasets used in the U.S. Geological Survey for the analysis of water-resources data. This version does not contain ESTREND, which was in version 2.1. See Release 2.1 for information and access to that version.\n\nThis library requires Release 8.1 or later of S-PLUS for Windows. S-PLUS is a commercial statistical and graphical analysis software package produced by TIBCO corporation(http://www.tibco.com/).\n\nThe USGS library is not supported by TIBCO or its technical support staff.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111130","usgsCitation":"Lorenz, D.L., Ahearn, E.A., Carter, J.M., Cohn, T., Danchuk, W.J., Frey, J.W., Helsel, D., Lee, K., Leeth, D.C., Martin, J.D., McGuire, V.L., Neitzert, K.M., Robertson, D.M., Slack, J.R., Starn, J., Vecchia, A.V., Wilkison, D.H., and Williamson, J., 2011, USGS library for S-PLUS for Windows -- Release 4.0 (4.0): U.S. Geological Survey Open-File Report 2011-1130, HTML Document; ZIP Download of S-Plus, https://doi.org/10.3133/ofr20111130.","productDescription":"HTML Document; ZIP Download of S-Plus","additionalOnlineFiles":"Y","costCenters":[{"id":392,"text":"Minnesota Water Science 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Jeffrey","email":"jjstarn@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":false,"id":351637,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Vecchia, Aldo V. 0000-0002-2661-4401","orcid":"https://orcid.org/0000-0002-2661-4401","contributorId":41810,"corporation":false,"usgs":true,"family":"Vecchia","given":"Aldo","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":351642,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Wilkison, Donald H. wilkison@usgs.gov","contributorId":3824,"corporation":false,"usgs":true,"family":"Wilkison","given":"Donald","email":"wilkison@usgs.gov","middleInitial":"H.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":351641,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Williamson, Joyce E. jewillia@usgs.gov","contributorId":1964,"corporation":false,"usgs":true,"family":"Williamson","given":"Joyce E.","email":"jewillia@usgs.gov","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":351638,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70003619,"text":"70003619 - 2011 - Developing seismogenic source models based on geologic fault data","interactions":[],"lastModifiedDate":"2021-05-21T17:40:36.908792","indexId":"70003619","displayToPublicDate":"2011-07-15T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Developing seismogenic source models based on geologic fault data","docAbstract":"Calculating seismic hazard usually requires input that includes seismicity associated with known faults, historical earthquake catalogs, geodesy, and models of ground shaking. This paper will address the input generally derived from geologic studies that augment the short historical catalog to predict ground shaking at time scales of tens, hundreds, or thousands of years (e.g., SSHAC 1997). A seismogenic source model, terminology we adopt here for a fault source model, includes explicit three-dimensional faults deemed capable of generating ground motions of engineering significance within a specified time frame of interest. In tectonically active regions of the world, such as near plate boundaries, multiple seismic cycles span a few hundred to a few thousand years. In contrast, in less active regions hundreds of kilometers from the nearest plate boundary, seismic cycles generally are thousands to tens of thousands of years long. Therefore, one should include sources having both longer recurrence intervals and possibly older times of most recent rupture in less active regions of the world rather than restricting the model to include only Holocene faults (i.e., those with evidence of large-magnitude earthquakes in the past 11,500 years) as is the practice in tectonically active regions with high deformation rates. \r\n\r\nDuring the past 15 years, our institutions independently developed databases to characterize seismogenic sources based on geologic data at a national scale. Our goal here is to compare the content of these two publicly available seismogenic source models compiled for the primary purpose of supporting seismic hazard calculations by the Istituto Nazionale di Geofisica e Vulcanologia (INGV) and the U.S. Geological Survey (USGS); hereinafter we refer to the two seismogenic source models as INGV and USGS, respectively. This comparison is timely because new initiatives are emerging to characterize seismogenic sources at the continental scale (e.g., SHARE in the Euro-Mediterranean, http://www.share-eu.org/; EMME in the Middle East, http://www.emme-gem.org/) and global scale (e.g., GEM, http://www.globalquakemodel.org/; Anonymous 2008). To some extent, each of these efforts is still trying to resolve the level of optimal detail required for this type of compilation. The comparison we provide defines a common standard for consideration by the international community for future regional and global seismogenic source models by identifying the necessary parameters that capture the essence of geological fault data in order to characterize seismogenic sources. In addition, we inform potential users of differences in our usage of common geological/seismological terms to avoid inappropriate use of the data in our models and provide guidance to convert the data from one model to the other (for detailed instructions, see the electronic supplement to this article). Applying our recommendations will permit probabilistic seismic hazard assessment codes to run seamlessly using either seismogenic source input. \r\n\r\nThe USGS and INGV database schema compare well at a first-level inspection. Both databases contain a set of fields representing generalized fault three-dimensional geometry and additional fields that capture the essence of past earthquake occurrences. Nevertheless, there are important differences. When we further analyze supposedly comparable fields, many are defined differently. These differences would cause anomalous results in hazard prediction if one assumes the values are similarly defined. The data, however, can be made fully compatible using simple transformations.","language":"English","publisher":"Seismological Society of America","publisherLocation":"El Cerrito, CA","doi":"10.1785/gssrl.82.4.519","usgsCitation":"Haller, K., and Basili, R., 2011, Developing seismogenic source models based on geologic fault data: Seismological Research Letters, v. 82, no. 4, p. 519-525, https://doi.org/10.1785/gssrl.82.4.519.","productDescription":"7 p.","startPage":"519","endPage":"525","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":204124,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"82","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-07-05","publicationStatus":"PW","scienceBaseUri":"4f4e4aa8e4b07f02db6672f8","contributors":{"authors":[{"text":"Haller, Kathleen M. haller@usgs.gov","contributorId":1331,"corporation":false,"usgs":true,"family":"Haller","given":"Kathleen M.","email":"haller@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":347978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Basili, Roberto","contributorId":9760,"corporation":false,"usgs":true,"family":"Basili","given":"Roberto","affiliations":[],"preferred":false,"id":347979,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70157178,"text":"70157178 - 2011 - Unravelling long-term vegetation change patterns in a binational watershed using multitemporal land cover data and historical photography","interactions":[],"lastModifiedDate":"2015-09-10T17:31:24","indexId":"70157178","displayToPublicDate":"2011-07-14T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Unravelling long-term vegetation change patterns in a binational watershed using multitemporal land cover data and historical photography","docAbstract":"

A significant amount of research conducted in the Sonoran Desert of North America has documented, both anecdotally and empirically, major vegetation changes over the past century due to human land use activities. However, many studies lack coincidental landscape-scale data characterizing the spatial and temporal manifestation of these changes. Vegetation changes in a binational (USA and Mexico) watershed were documented using a series of four land cover maps (1979-2009) derived from multispectral satellite imagery. Cover changes are compared to georeferenced, repeat oblique photographs dating from the late 19th century to present. Results indicate the expansion of grassland over the past 20 years following nearly a century of decline. Historical repeat photography documents early-mid 20th century mesquite invasions, but recent land cover data and rephotography demonstrate declines in xeroriparian/riparian mesquite communities in recent decades. These vegetation changes are variable over the landscape and influenced by topography and land management.

","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Proceedings of MULTITEMP 2011, 6th International Workshop on the Analysis of Multitemporal Remote Sensing Images","conferenceTitle":"MULTITEMP 2011, 6th International Workshop on the Analysis of Multitemporal Remote Sensing Images","conferenceDate":"July 12-14 2011","conferenceLocation":"Trento, Italy","language":"English","publisher":"World Scientific","usgsCitation":"Villarreal, M., Norman, L.M., Webb, R., Boyer, D.E., and Turner, R., 2011, Unravelling long-term vegetation change patterns in a binational watershed using multitemporal land cover data and historical photography, in Proceedings of MULTITEMP 2011, 6th International Workshop on the Analysis of Multitemporal Remote Sensing Images, Trento, Italy, July 12-14 2011.","productDescription":"4 p.","endPage":"101","numberOfPages":"104","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":308081,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"560bb718e4b058f706e53f68","contributors":{"authors":[{"text":"Villarreal, Miguel L.","contributorId":107012,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel L.","affiliations":[],"preferred":false,"id":572154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406 lnorman@usgs.gov","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":967,"corporation":false,"usgs":true,"family":"Norman","given":"Laura","email":"lnorman@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":572155,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webb, Robert H. rhwebb@usgs.gov","contributorId":1573,"corporation":false,"usgs":false,"family":"Webb","given":"Robert H.","email":"rhwebb@usgs.gov","affiliations":[{"id":12625,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA","active":true,"usgs":false}],"preferred":false,"id":572156,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boyer, Diane E.","contributorId":22018,"corporation":false,"usgs":true,"family":"Boyer","given":"Diane","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":572157,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Turner, Raymond M.","contributorId":7383,"corporation":false,"usgs":true,"family":"Turner","given":"Raymond M.","affiliations":[],"preferred":false,"id":572158,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70004888,"text":"sir20115105 - 2011 - Modeling hydrodynamics, water temperature, and water quality in the Klamath River upstream of Keno Dam, Oregon, 2006-09","interactions":[],"lastModifiedDate":"2022-12-23T17:04:02.596722","indexId":"sir20115105","displayToPublicDate":"2011-07-14T00:00:00","publicationYear":"2011","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":"2011-5105","title":"Modeling hydrodynamics, water temperature, and water quality in the Klamath River upstream of Keno Dam, Oregon, 2006-09","docAbstract":"A hydrodynamic, water temperature, and water-quality model was constructed for a 20-mile reach of the Klamath River downstream of Upper Klamath Lake, from Link River to Keno Dam, for calendar years 2006-09. The two-dimensional, laterally averaged model CE-QUAL-W2 was used to simulate water velocity, ice cover, water temperature, specific conductance, dissolved and suspended solids, dissolved oxygen, total nitrogen, ammonia, nitrate, total phosphorus, orthophosphate, dissolved and particulate organic matter, and three algal groups. The Link-Keno model successfully simulated the most important spatial and temporal patterns in the measured data for this 4-year time period. The model calibration process provided critical insights into water-quality processes and the nature of those inputs and processes that drive water quality in this reach. The model was used not only to reproduce and better understand water-quality conditions that occurred in 2006-09, but also to test several load-reduction scenarios that have implications for future water-resources management in the river basin. The model construction and calibration process provided results concerning water quality and transport in the Link-Keno reach of the Klamath River, ranging from interesting circulation patterns in the Lake Ewauna area to the nature and importance of organic matter and algae. These insights and results include: * Modeled segment-average water velocities ranged from near 0.0 to 3.0 ft/s in 2006 through 2009. Travel time through the model reach was about 4 days at 2,000 ft3/s and 12 days at 700 ft3/s flow. Flow direction was aligned with the upstream-downstream channel axis for most of the Link-Keno reach, except for Lake Ewauna. Wind effects were pronounced at Lake Ewauna during low-flow conditions, often with circulation in the form of a gyre that rotated in a clockwise direction when winds were towards the southeast and in a counterclockwise direction when winds were towards the northwest. * Water temperatures ranged from near freezing in winter to near 30 degrees C at some locations and periods in summer; seasonal water temperature patterns were similar at the inflow and outflow. Although vertical temperature stratification was not present at most times and locations, weak stratification could persist for periods up to 1-2 weeks, especially in the downstream parts of the reach. Thermal stratification was important in controlling vertical variations in water quality. * The specific conductance, and thus density, of tributaries within the reach usually was higher than that of the river itself, so that inflows tended to sink below the river surface. This was especially notable for inflows from the Klamath Straits Drain, which tended to sink to the bottom of the Klamath River at its confluence and not mix vertically for several miles downstream. * The model was able to capture most of the seasonal changes in the algal population by modeling that population with three algal groups: blue-green algae, diatoms, and other algae. The blooms of blue-green algae, consisting mostly of Aphanizomenon flos aquae that entered from Upper Klamath Lake, were dominant, dwarfing the populations of the other two algae groups in summer. A large part of the blue-green algae population that entered this reach from upstream tended to settle out, die, and decompose, especially in the upper part of the Link-Keno reach. Diatoms reached a maximum in spring and other algae in midsummer. * Organic matter, occurring in both dissolved and particulate forms, was critical to the water quality of this reach of the Klamath River, and was strongly tied to nutrient and dissolved-oxygen dynamics. Dissolved and particulate organic matter were subdivided into labile (quickly decaying) and refractory (slowing decaying) groups for modeling purposes. The particulate matter in summer, consisting largely of dead blue-green algae, decayed quickly. Consequently, this particulate matt","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115105","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Sullivan, A.B., Rounds, S.A., Deas, M., Asbill, J.R., Wellman, R.E., Stewart, M.A., Johnston, M.W., and Sogutlugil, I.E., 2011, Modeling hydrodynamics, water temperature, and water quality in the Klamath River upstream of Keno Dam, Oregon, 2006-09: U.S. Geological Survey Scientific Investigations Report 2011-5105, viii, 70 p., https://doi.org/10.3133/sir20115105.","productDescription":"viii, 70 p.","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":116150,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5105.jpg"},{"id":24397,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5105/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon","otherGeospatial":"Keno Dam, Klamath River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.98333333333333,42.05 ], [ -121.98333333333333,42.28333333333333 ], [ -121.73333333333333,42.28333333333333 ], [ -121.73333333333333,42.05 ], [ -121.98333333333333,42.05 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a2de4b07f02db6146fa","contributors":{"authors":[{"text":"Sullivan, Annett B. 0000-0001-7783-3906 annett@usgs.gov","orcid":"https://orcid.org/0000-0001-7783-3906","contributorId":56317,"corporation":false,"usgs":true,"family":"Sullivan","given":"Annett","email":"annett@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":351605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":351599,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deas, Michael L.","contributorId":98830,"corporation":false,"usgs":true,"family":"Deas","given":"Michael L.","affiliations":[],"preferred":false,"id":351606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Asbill, Jessica R.","contributorId":39896,"corporation":false,"usgs":true,"family":"Asbill","given":"Jessica","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":351603,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wellman, Roy E. 0000-0003-4460-8918 rwellman@usgs.gov","orcid":"https://orcid.org/0000-0003-4460-8918","contributorId":1706,"corporation":false,"usgs":true,"family":"Wellman","given":"Roy","email":"rwellman@usgs.gov","middleInitial":"E.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":351600,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stewart, Marc A. 0000-0003-1140-6316 mastewar@usgs.gov","orcid":"https://orcid.org/0000-0003-1140-6316","contributorId":2277,"corporation":false,"usgs":true,"family":"Stewart","given":"Marc","email":"mastewar@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":351601,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnston, Matthew W. mattj@usgs.gov","contributorId":3066,"corporation":false,"usgs":true,"family":"Johnston","given":"Matthew","email":"mattj@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":351602,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sogutlugil, I. Ertugrul","contributorId":50277,"corporation":false,"usgs":true,"family":"Sogutlugil","given":"I.","email":"","middleInitial":"Ertugrul","affiliations":[],"preferred":false,"id":351604,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70189033,"text":"70189033 - 2011 - Hydrogeophysical investigations at Hidden Dam, Raymond, California","interactions":[],"lastModifiedDate":"2017-06-29T13:48:41","indexId":"70189033","displayToPublicDate":"2011-07-14T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3928,"text":"Journal of Environmental & Engineering Geophysics","printIssn":"1083-1363","active":true,"publicationSubtype":{"id":10}},"title":"Hydrogeophysical investigations at Hidden Dam, Raymond, California","docAbstract":"

Self-potential and direct current resistivity surveys are carried out at the Hidden Dam site in Raymond, California to assess present-day seepage patterns and better understand the hydrogeologic mechanisms that likely influence seepage. Numerical modeling is utilized in conjunction with the geophysical measurements to predict variably-saturated flow through typical two-dimensional dam cross-sections as a function of reservoir elevation. Several different flow scenarios are investigated based on the known hydrogeology, as well as information about typical subsurface structures gained from the resistivity survey. The flow models are also used to simulate the bulk electrical resistivity in the subsurface under varying saturation conditions, as well as the self-potential response using petrophysical relationships and electrokinetic coupling equations.

The self-potential survey consists of 512 measurements on the downstream area of the dam, and corroborates known seepage areas on the northwest side of the dam. Two direct-current resistivity profiles, each approximately 2,500 ft (762 m) long, indicate a broad sediment channel under the northwest side of the dam, which may be a significant seepage pathway through the foundation. A focusing of seepage in low-topography areas downstream of the dam is confirmed from the numerical flow simulations, which is also consistent with past observations. Little evidence of seepage is identified from the self-potential data on the southeast side of the dam, also consistent with historical records, though one possible area of focused seepage is identified near the outlet works. Integration of the geophysical surveys, numerical modeling, and observation well data provides a framework for better understanding seepage at the site through a combined hydrogeophysical approach.

","language":"English","publisher":"Environmental and Engineering Geophysical Society","doi":"10.2113/JEEG16.4.145","usgsCitation":"Minsley, B.J., Burton, B.L., Ikard, S., and Powers, M.H., 2011, Hydrogeophysical investigations at Hidden Dam, Raymond, California: Journal of Environmental & Engineering Geophysics, v. 16, no. 4, p. 145-164, https://doi.org/10.2113/JEEG16.4.145.","productDescription":"20 p.","startPage":"145","endPage":"164","ipdsId":"IP-022264","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":343136,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Raymond","otherGeospatial":"Hidden Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.89240407943724,\n 37.11503755152569\n ],\n [\n -119.89349842071533,\n 37.11428466832454\n ],\n [\n -119.89163160324095,\n 37.11158107148775\n ],\n [\n -119.8788857460022,\n 37.103743517498586\n ],\n [\n -119.87809181213377,\n 37.10437671245446\n ],\n [\n -119.87950801849364,\n 37.10625915268512\n ],\n [\n -119.88178253173828,\n 37.10898005178678\n ],\n [\n -119.8827052116394,\n 37.10993833259634\n ],\n [\n -119.88624572753906,\n 37.112385316076114\n ],\n [\n -119.88764047622679,\n 37.113172440806665\n ],\n [\n -119.89240407943724,\n 37.11503755152569\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595611c7e4b0d1f9f05067e5","contributors":{"authors":[{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burton, Bethany L. 0000-0001-5011-7862 blburton@usgs.gov","orcid":"https://orcid.org/0000-0001-5011-7862","contributorId":138925,"corporation":false,"usgs":true,"family":"Burton","given":"Bethany","email":"blburton@usgs.gov","middleInitial":"L.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702493,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ikard, Scott 0000-0002-8304-4935 sikard@usgs.gov","orcid":"https://orcid.org/0000-0002-8304-4935","contributorId":171751,"corporation":false,"usgs":true,"family":"Ikard","given":"Scott","email":"sikard@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":702603,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powers, Michael H. 0000-0002-4480-7856 mhpowers@usgs.gov","orcid":"https://orcid.org/0000-0002-4480-7856","contributorId":851,"corporation":false,"usgs":true,"family":"Powers","given":"Michael","email":"mhpowers@usgs.gov","middleInitial":"H.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702495,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190222,"text":"70190222 - 2011 - Ictalurids in Iowa’s streams and rivers: Status, distribution, and relationships with biotic integrity","interactions":[],"lastModifiedDate":"2017-08-20T10:16:35","indexId":"70190222","displayToPublicDate":"2011-07-14T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":718,"text":"American Fisheries Society Symposium","active":true,"publicationSubtype":{"id":10}},"title":"Ictalurids in Iowa’s streams and rivers: Status, distribution, and relationships with biotic integrity","docAbstract":"

Anthropogenic alterations to Iowa’s landscape have greatly altered lotic systems with consequent effects on the biodiversity of freshwater fauna. Ictalurids are a diverse group of fishes and play an important ecological role in aquatic ecosystems. However, little is known about their distribution and status in lotic systems throughout Iowa. The purpose of this study was to describe the distribution of ictalurids in Iowa and examine their relationship with ecological integrity of streams and rivers. Historical data (i.e., 1884–2002) compiled for the Iowa Aquatic Gap Analysis Project (IAGAP) were used to detect declines in the distribution of ictalurids in Iowa streams and rivers at stream segment and watershed scales. Eight variables characterizing ictalurid assemblages were used to evaluate relationships with index of biotic integrity (IBI) ratings. Comparisons of recent and historic data from the IAGAP database indicated that 9 of Iowa’s 10 ictalurid species experienced distribution declines at one or more spatial scales. Analysis of variance indicated that ictalurid assemblages differed among samples with different IBI ratings. Specifically, total ictalurid, sensitive ictalurid, and Noturus spp. richness increased as IBI ratings increased. Results indicate declining ictalurid species distributions and biotic integrity are related, and management strategies aimed to improve habitat and increase biotic integrity will benefit ictalurid species.

","language":"English","publisher":"American Fisheries Society","usgsCitation":"Sindt, A.R., Fischer, J., Quist, M.C., and Pierce, C., 2011, Ictalurids in Iowa’s streams and rivers: Status, distribution, and relationships with biotic integrity: American Fisheries Society Symposium, v. 77, p. 335-347.","productDescription":"13 p.","startPage":"335","endPage":"347","ipdsId":"IP-024856","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":344976,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"77","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"599a9fb8e4b0b589267d58c3","contributors":{"authors":[{"text":"Sindt, Anthony R.","contributorId":171503,"corporation":false,"usgs":false,"family":"Sindt","given":"Anthony","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":708094,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fischer, Jesse R.","contributorId":86618,"corporation":false,"usgs":true,"family":"Fischer","given":"Jesse R.","affiliations":[],"preferred":false,"id":708095,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quist, Michael C. mquist@usgs.gov","contributorId":4042,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","email":"mquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":350,"text":"Iowa Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":708096,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pierce, Clay 0000-0001-5088-5431 cpierce@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-5431","contributorId":150492,"corporation":false,"usgs":true,"family":"Pierce","given":"Clay","email":"cpierce@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":708024,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70004872,"text":"ofr20111003 - 2011 - Combined multibeam and LIDAR bathymetry data from eastern Long Island Sound and westernmost Block Island Sound-A regional perspective","interactions":[],"lastModifiedDate":"2012-02-02T00:15:56","indexId":"ofr20111003","displayToPublicDate":"2011-07-13T00:00:00","publicationYear":"2011","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":"2011-1003","title":"Combined multibeam and LIDAR bathymetry data from eastern Long Island Sound and westernmost Block Island Sound-A regional perspective","docAbstract":"Detailed bathymetric maps of the sea floor in Long Island Sound are of great interest to the Connecticut and New York research and management communities because of this estuary's ecological, recreational, and commercial importance. The completed, geologically interpreted digital terrain models (DTMs), ranging in area from 12 to 293 square kilometers, provide important benthic environmental information, yet many applications require a geographically broader perspective. For example, individual surveys are of limited use for the planning and construction of cross-sound infrastructure, such as cables and pipelines, or for the testing of regional circulation models. To address this need, we integrated 12 multibeam and 2 LIDAR (Light Detection and Ranging) contiguous bathymetric DTMs, produced by the National Oceanic and Atmospheric Administration during charting operations, into one dataset that covers much of eastern Long Island Sound and extends into westernmost Block Island Sound. The new dataset is adjusted to mean lower low water, is gridded to 4-meter resolution, and is provided in UTM Zone 18 NAD83 and geographic WGS84 projections. This resolution is adequate for sea floor-feature and process interpretation but is small enough to be queried and manipulated with standard Geographic Information System programs and to allow for future growth. Natural features visible in the grid include exposed bedrock outcrops, boulder lag deposits of submerged moraines, sand-wave fields, and scour depressions that reflect the strength of the oscillating and asymmetric tidal currents. Bedform asymmetry allows interpretations of net sediment transport. Anthropogenic artifacts visible in the bathymetric data include a dredged channel, shipwrecks, dredge spoils, mooring anchors, prop-scour depressions, buried cables, and bridge footings. Together the merged data reveal a larger, more continuous perspective of bathymetric topography than previously available, providing a fundamental framework for research and resource management activities in this major east-coast estuary.","language":"English","publisher":"U. S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111003","usgsCitation":"Poppe, L., Danforth, W.W., McMullen, K., Parker, C.E., and Doran, E.F., 2011, Combined multibeam and LIDAR bathymetry data from eastern Long Island Sound and westernmost Block Island Sound-A regional perspective: U.S. Geological Survey Open-File Report 2011-1003, HTML Page, https://doi.org/10.3133/ofr20111003.","productDescription":"HTML Page","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":116654,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1003.png"},{"id":24384,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1003/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{\"crs\": {\"type\": \"name\", \"properties\": {\"name\": \"urn:ogc:def:crs:OGC:1.3:CRS84\"}}, \"geometry\": {\"type\": \"Polygon\", \"coordinates\": [[[-72.64578435384327, 41.21420149913303], [-72.4009181372618, 41.21869445723546], [-72.34196176021061, 41.23431022624995], [-72.34190696803863, 41.262582986991944], [-72.3244830573488, 41.257596899341706], [-72.30026491733334, 41.27606186129919], [-72.25999267092757, 41.28055481940162], [-72.24503440797686, 41.29847185963929], [-72.22481609651601, 41.29666371796391], [-72.22103543664933, 41.30937550186342], [-72.21955604800584, 41.29337618764508], [-72.20448820071117, 41.28625320528759], [-72.2032827729276, 41.31255344783832], [-72.1848178109701, 41.32762129513297], [-72.17533876521745, 41.32679941255328], [-72.16744869245224, 41.30570442634073], [-72.15035353479428, 41.31551222512526], [-72.14761392619523, 41.32548440042575], [-72.14394285067254, 41.30274564905378], [-72.11249214395565, 41.29891019701514], [-72.09030131430347, 41.31551222512526], [-72.08843695748531, 41.32339903350462], [-72.0998899444001, 41.336935964369715], [-72.09210945597884, 41.34438769975909], [-72.09923243833633, 41.34937378740931], [-72.08597273271701, 41.367729165022844], [-72.07868537384358, 41.32838838554074], [-72.06652151166386, 41.31529305643735], [-72.05550828509575, 41.31748474331659], [-72.0551755981885, 41.3286508270778], [-72.0526042999808, 41.318306625896305], [-72.04367317594794, 41.322909168342676], [-72.03539955797886, 41.33622366613397], [-72.03682415445036, 41.323731050922376], [-72.0466319532349, 41.32016955974362], [-72.0347420519151, 41.31271782435429], [-72.01589354475375, 41.32258041531079], [-72.01161975533925, 41.30712902281224], [-72.00526386338949, 41.30636193240452], [-71.9995654775035, 41.31737515897261], [-71.99940110098754, 41.301649805614176], [-72.01331831267065, 41.30038958565863], [-72.01320872832669, 41.28619841311561], [-71.99929151664361, 41.28817093130693], [-71.99457938985327, 41.26992513803737], [-72.0077295111286, 41.26017213142484], [-72.0126060144349, 41.26384320694752], [-72.00729117375278, 41.27085660496103], [-72.020824840232, 41.276116653471206], [-72.02235902104745, 41.262254233960086], [-72.02871491299722, 41.263459661743646], [-72.03854491854008, 41.24899862455118], [-72.0029077999943, 41.25261081169149], [-71.99123706736245, 41.260994014004524], [-71.99918193229963, 41.24756993186928], [-71.99923672447161, 41.19354485029635], [-72.1901326516522, 41.189764190429685], [-72.21226868913239, 41.17825783431373], [-72.20777573102997, 41.17086089109635], [-72.21298098736813, 41.16346394787899], [-72.2682662888966, 41.15502595339394], [-72.28486831700674, 41.159628495840316], [-72.32311325304923, 41.14012248261521], [-72.35450916759413, 41.14072519650701], [-72.38990491069363, 41.103959649107956], [-72.65044168846163, 41.106206128159165], [-72.65126357104135, 41.11749331558719], [-72.65729070995921, 41.11743852341521], [-72.65093481800946, 41.118369990338884], [-72.65082523366549, 41.153108227374624], [-72.64512684777951, 41.15886140543259], [-72.64578435384327, 41.21420149913303]]]}, \"properties\": {\"extentType\": \"Custom\", \"code\": \"\", \"name\": \"\", \"notes\": \"\", \"promotedForReuse\": false, \"abbreviation\": \"\", \"shortName\": \"\", \"description\": \"\"}, \"bbox\": [-72.65729070995921, 41.10330214304421, -71.99112748301849, 41.367729165022844], \"type\": \"Feature\", \"id\": \"3091921\"}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b24e4b07f02db6ae707","contributors":{"authors":[{"text":"Poppe, L. J.","contributorId":72782,"corporation":false,"usgs":true,"family":"Poppe","given":"L.","middleInitial":"J.","affiliations":[],"preferred":false,"id":351538,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Danforth, W. W.","contributorId":16386,"corporation":false,"usgs":true,"family":"Danforth","given":"W.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":351534,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McMullen, K. Y.","contributorId":51857,"corporation":false,"usgs":true,"family":"McMullen","given":"K.","middleInitial":"Y.","affiliations":[],"preferred":false,"id":351537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parker, Castle E.","contributorId":28684,"corporation":false,"usgs":false,"family":"Parker","given":"Castle","email":"","middleInitial":"E.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":351535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doran, E. F.","contributorId":31066,"corporation":false,"usgs":true,"family":"Doran","given":"E.","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":351536,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70004542,"text":"70004542 - 2011 - Density estimation in a wolverine population using spatial capture-recapture models","interactions":[],"lastModifiedDate":"2021-05-18T14:29:16.586796","indexId":"70004542","displayToPublicDate":"2011-07-13T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Density estimation in a wolverine population using spatial capture-recapture models","docAbstract":"Classical closed-population capture-recapture models do not accommodate the spatial information inherent in encounter history data obtained from camera-trapping studies. As a result, individual heterogeneity in encounter probability is induced, and it is not possible to estimate density objectively because trap arrays do not have a well-defined sample area. We applied newly-developed, capture-recapture models that accommodate the spatial attribute inherent in capture-recapture data to a population of wolverines (Gulo gulo) in Southeast Alaska in 2008. We used camera-trapping data collected from 37 cameras in a 2,140-km2 area of forested and open habitats largely enclosed by ocean and glacial icefields. We detected 21 unique individuals 115 times. Wolverines exhibited a strong positive trap response, with an increased tendency to revisit previously visited traps. Under the trap-response model, we estimated wolverine density at 9.7 individuals/1,000-km2(95% Bayesian CI: 5.9-15.0). Our model provides a formal statistical framework for estimating density from wolverine camera-trapping studies that accounts for a behavioral response due to baited traps. Further, our model-based estimator does not have strict requirements about the spatial configuration of traps or length of trapping sessions, providing considerable operational flexibility in the development of field studies.","language":"English","publisher":"The Wildlife Society","publisherLocation":"Bethesda, MD","doi":"10.1002/jwmg.79","usgsCitation":"Royle, J., Magoun, A.J., Gardner, B., Valkenbury, P., and Lowell, R.E., 2011, Density estimation in a wolverine population using spatial capture-recapture models: Journal of Wildlife Management, v. 75, no. 3, p. 604-611, https://doi.org/10.1002/jwmg.79.","productDescription":"8 p.","startPage":"604","endPage":"611","numberOfPages":"7","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":204059,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Southeast Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 173,54.666666666666664 ], [ 173,71.83333333333333 ], [ -130,71.83333333333333 ], [ -130,54.666666666666664 ], [ 173,54.666666666666664 ] ] ] } } ] }","volume":"75","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-05-11","publicationStatus":"PW","scienceBaseUri":"4f4e4ab2e4b07f02db66eb17","contributors":{"editors":[{"text":"McKelvey, Kevin","contributorId":112036,"corporation":false,"usgs":true,"family":"McKelvey","given":"Kevin","affiliations":[],"preferred":false,"id":508242,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":80808,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":350664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoun, Audrey J.","contributorId":34249,"corporation":false,"usgs":true,"family":"Magoun","given":"Audrey","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":350663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":350665,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Valkenbury, Patrick","contributorId":25279,"corporation":false,"usgs":true,"family":"Valkenbury","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":350662,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowell, Richard E.","contributorId":8214,"corporation":false,"usgs":true,"family":"Lowell","given":"Richard","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":350661,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208567,"text":"70208567 - 2011 - Treatment of anchor pixels in the METRIC model for improved estimation of sensible and latent heat fluxes","interactions":[],"lastModifiedDate":"2020-02-20T10:00:34","indexId":"70208567","displayToPublicDate":"2011-07-12T10:23:50","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1927,"text":"Hydrological Sciences Journal","active":true,"publicationSubtype":{"id":10}},"title":"Treatment of anchor pixels in the METRIC model for improved estimation of sensible and latent heat fluxes","docAbstract":"

Reliable estimation of sensible heat flux (H) is important in energy balance models for quantifying evapotranspiration (ET). This study was conducted to evaluate the value of adding the Priestley-Taylor (PT) equation to the METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model. METRIC was used to estimate energy fluxes for 10 Landsat images from the 2005, 2006 and 2007 crop growing seasons in south-central Nebraska, USA, where each image owing to recent rainfall exhibited high residual moisture content even at the hot pixel. The METRIC model performed satisfactorily for net radiation (Rn ) and soil heat flux (G) estimation with a root mean square error (RMSE) of 52 and 24 W m-2, respectively. A RMSE of 122 W m-2 for H indicated the limitation of the METRIC model in estimating H for high residual moisture content of the hot pixel (Alfalfa reference ET fraction, ET r F > 0.15). The modified METRIC model (wet METRIC or wMETRIC) incorporating the PT equation was applied to calculate H at the anchor pixels (hot and cold) for high residual moisture content of the hot pixel. The α coefficient of the PT equation was locally calibrated using hourly meteorological data from an automatic weather station and Rn and G data from a Bowen ratio flux tower. The mean α coefficient value was 1.14. The wMETRIC model reduced the RMSE of H from 122 to 64 W m-2 and that of latent heat flux, LE, from 163 to 106 W m-2. The RMSE of daily ET decreased from 1.7 to 1.1 mm d-1 with wMETRIC. The results indicate that treatment of anchor pixels for high residual moisture content with the PT approach gives improved estimation of H, LE and daily ET. It is recommended that the wMETRIC model be used for estimating ET if the hot pixel has high residual moisture (i.e. reference ET fraction > 0.15).

","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02626667.2011.587424","usgsCitation":"Singh, R.K., and Irmak, A., 2011, Treatment of anchor pixels in the METRIC model for improved estimation of sensible and latent heat fluxes: Hydrological Sciences Journal, v. 56, no. 5, p. 895-906, https://doi.org/10.1080/02626667.2011.587424.","productDescription":"12 p.","startPage":"895","endPage":"906","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":372386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"South Central Agricultural Laboratory","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.13434600830078,\n 40.53859061142965\n ],\n [\n -98.06156158447266,\n 40.53859061142965\n ],\n [\n -98.06156158447266,\n 40.57563021524945\n ],\n [\n -98.13434600830078,\n 40.57563021524945\n ],\n [\n -98.13434600830078,\n 40.53859061142965\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"5","noUsgsAuthors":false,"publicationDate":"2011-07-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Singh, Ramesh K. 0000-0002-8164-3483 rsingh@usgs.gov","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":3895,"corporation":false,"usgs":true,"family":"Singh","given":"Ramesh","email":"rsingh@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":782549,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irmak, A.","contributorId":101473,"corporation":false,"usgs":true,"family":"Irmak","given":"A.","email":"","affiliations":[],"preferred":false,"id":782550,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70004843,"text":"ofr20111164 - 2011 - Macondo-1 well oil in sediment and tarballs from the northern Gulf of Mexico shoreline","interactions":[],"lastModifiedDate":"2012-02-10T00:11:59","indexId":"ofr20111164","displayToPublicDate":"2011-07-12T00:00:00","publicationYear":"2011","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":"2011-1164","title":"Macondo-1 well oil in sediment and tarballs from the northern Gulf of Mexico shoreline","docAbstract":"From April 20 through July 15, 2010, an estimated 4.4 million barrels (1 barrel = 42 gallons [~700,000 cu m]) of crude oil spilled into the northern Gulf of Mexico (nGOM) from the ruptured British Petroleum (BP) Macondo-1 (M-1) well after the explosion of the drilling platform Deepwater Horizon. In addition, ~1.84 million gallons (~7,000 cu m) of hydrocarbon-based Corexit dispersants were applied to the oil both on and below the sea surface (Operational Science Advisory Team, 2010). An estimate of the total extent of the surface oil slick, derived from wind, ocean currents, aerial photography, and satellite imagery, was 68,000 square miles (~180,000 sq km; Amos and Norse, 2010). Spilled oil from this event impacted sensitive habitat along the shores of the nGOM.\n\nIn response to this environmental catastrophe, the U.S. Geological Survey (USGS) collected coastal sediment and tarball samples along the shores of the nGOM from Texas to Florida before and after oil made landfall. These sites included priority areas of the nGOM at highest risk for oil contamination. These areas included coastal wetlands, shorelines, and barrier islands that could suffer severe environmental damage if a significant amount of oil came ashore.\n\nSamples were collected before oil reached land from 69 sites; 49 were revisited to collect samples after oil landfall. This poster focuses on the samples from locations that were sampled on both occasions. The USGS samples and one M-1 well-oil sample provided by BP were analyzed for a suite of diagnostic geochemical biomarkers. Aided by multivariate statistical analysis, the M-1 well oil was not detected in the samples collected before landfall but have been identified in sediment and tarballs collected from Louisiana, Alabama, Mississippi, and Florida after landfall. None of the sediment hydrocarbon extracts from Texas correlated with the M-1 well oil. Oil-impacted sediment is confined to the shoreline adjacent to the cumulative oil slick of the Deepwater Horizon oil spill and no impact was observed outside of this area. Incorporation of the analytical data in geographical information systems (GIS) offers querying capabilities and visualizations such as those demonstrated here.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111164","usgsCitation":"Wong, F.L., Rosenbauer, R.J., Campbell, P.L., Lam, A., Lorenson, T., Hostettler, F.D., and Thomas, B., 2011, Macondo-1 well oil in sediment and tarballs from the northern Gulf of Mexico shoreline: U.S. Geological Survey Open-File Report 2011-1164, Poster; 1 Sheet: 60.00 x 36.00 inches, https://doi.org/10.3133/ofr20111164.","productDescription":"Poster; 1 Sheet: 60.00 x 36.00 inches","startPage":"1","endPage":"1","numberOfPages":"1","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":116125,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1164.gif"},{"id":24363,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1164/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96,27.5 ], [ -96,31.5 ], [ -82,31.5 ], [ -82,27.5 ], [ -96,27.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a53e4b07f02db62bb06","contributors":{"authors":[{"text":"Wong, Florence L. 0000-0002-3918-5896 fwong@usgs.gov","orcid":"https://orcid.org/0000-0002-3918-5896","contributorId":1990,"corporation":false,"usgs":true,"family":"Wong","given":"Florence","email":"fwong@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":351460,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenbauer, Robert J. brosenbauer@usgs.gov","contributorId":204,"corporation":false,"usgs":true,"family":"Rosenbauer","given":"Robert","email":"brosenbauer@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":351459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell, Pamela L.","contributorId":76719,"corporation":false,"usgs":true,"family":"Campbell","given":"Pamela","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":351464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lam, Angela","contributorId":37312,"corporation":false,"usgs":true,"family":"Lam","given":"Angela","email":"","affiliations":[],"preferred":false,"id":351463,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lorenson, T.D. tlorenson@usgs.gov","contributorId":2622,"corporation":false,"usgs":true,"family":"Lorenson","given":"T.D.","email":"tlorenson@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":false,"id":351461,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hostettler, Frances D. fdhostet@usgs.gov","contributorId":3383,"corporation":false,"usgs":true,"family":"Hostettler","given":"Frances","email":"fdhostet@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":351462,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thomas, Burt","contributorId":95454,"corporation":false,"usgs":true,"family":"Thomas","given":"Burt","affiliations":[],"preferred":false,"id":351465,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70004819,"text":"fs20113079 - 2011 - USGS Emergency Response Resources","interactions":[],"lastModifiedDate":"2012-02-02T00:15:53","indexId":"fs20113079","displayToPublicDate":"2011-07-12T00:00:00","publicationYear":"2011","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":"2011-3079","title":"USGS Emergency Response Resources","docAbstract":"Every day, emergency responders are confronted with worldwide natural and manmade disasters, including earthquakes, floods, hurricanes, landslides, tsunami, volcanoes, wildfires, terrorist attacks, and accidental oil spills.The U.S. Geological Survey (USGS) is ready to coordinate the provisioning and deployment of USGS staff, equipment, geospatial data, products, and services in support of national emergency response requirements.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20113079","usgsCitation":"Bewley, R.D., 2011, USGS Emergency Response Resources: U.S. Geological Survey Fact Sheet 2011-3079, 2 p., https://doi.org/10.3133/fs20113079.","productDescription":"2 p.","additionalOnlineFiles":"N","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":116770,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2011_3079.gif"},{"id":22739,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2011/3079/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49e2e4b07f02db5e49b1","contributors":{"authors":[{"text":"Bewley, Robert D. rbewley@usgs.gov","contributorId":4026,"corporation":false,"usgs":true,"family":"Bewley","given":"Robert","email":"rbewley@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":351407,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70004714,"text":"ds603 - 2011 - Discrete and continuous water-quality data and hydrologic parameters from seven agricultural watersheds in the United States, 2002-09","interactions":[],"lastModifiedDate":"2012-03-08T17:16:40","indexId":"ds603","displayToPublicDate":"2011-07-12T00:00:00","publicationYear":"2011","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":"603","title":"Discrete and continuous water-quality data and hydrologic parameters from seven agricultural watersheds in the United States, 2002-09","docAbstract":"Field and analytical methods; discrete organic and non-organic water-quality data and associated quality-control data; and continuous hydrologic and water-quality parameters are reported for sites in California, Indiana, Iowa, Maryland, Mississippi, Nebraska, and Washington. The sites were sampled as part of the U.S. Geological Survey National Water-Quality Assessment Program?s Agricultural Chemicals Team study to better understand how environmental processes and agricultural practices interact to determine the transport and fate of agricultural chemicals in the environment.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ds603","collaboration":"National Water-Quality Assessment Program?","usgsCitation":"McCarthy, K.A., Lampe, D.C., and Capel, P.D., 2011, Discrete and continuous water-quality data and hydrologic parameters from seven agricultural watersheds in the United States, 2002-09: U.S. Geological Survey Data Series 603, iv, 7 p.; Appendices; Abstract; Table of Contents; List of Figures; List of Tables; Appendices ZIP; Appendix 1; Appendix 2; Appendices 3-9, https://doi.org/10.3133/ds603.","productDescription":"iv, 7 p.; Appendices; Abstract; Table of Contents; List of Figures; List of Tables; Appendices ZIP; Appendix 1; Appendix 2; Appendices 3-9","additionalOnlineFiles":"Y","temporalStart":"2002-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":116115,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_603.bmp"},{"id":21932,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/603/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a81e4b07f02db64a94c","contributors":{"authors":[{"text":"McCarthy, Kathleen A. mccarthy@usgs.gov","contributorId":1159,"corporation":false,"usgs":true,"family":"McCarthy","given":"Kathleen","email":"mccarthy@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":351211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lampe, David C. 0000-0002-8904-0337 dclampe@usgs.gov","orcid":"https://orcid.org/0000-0002-8904-0337","contributorId":2441,"corporation":false,"usgs":true,"family":"Lampe","given":"David","email":"dclampe@usgs.gov","middleInitial":"C.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":351212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Capel, Paul D. 0000-0003-1620-5185 capel@usgs.gov","orcid":"https://orcid.org/0000-0003-1620-5185","contributorId":1002,"corporation":false,"usgs":true,"family":"Capel","given":"Paul","email":"capel@usgs.gov","middleInitial":"D.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":351210,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70003745,"text":"70003745 - 2011 - Abundance of introduced species at home predicts abundance away in herbaceous communities","interactions":[],"lastModifiedDate":"2013-02-19T16:56:34","indexId":"70003745","displayToPublicDate":"2011-07-12T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Abundance of introduced species at home predicts abundance away in herbaceous communities","docAbstract":"Many ecosystems worldwide are dominated by introduced plant species, leading to loss of biodiversity and ecosystem function. A common but rarely tested assumption is that these plants are more abundant in introduced vs. native communities, because ecological or evolutionary-based shifts in populations underlie invasion success. Here, data for 26 herbaceous species at 39 sites, within eight countries, revealed that species abundances were similar at native (home) and introduced (away) sites - grass species were generally abundant home and away, while forbs were low in abundance, but more abundant at home. Sites with six or more of these species had similar community abundance hierarchies, suggesting that suites of introduced species are assembling similarly on different continents. Overall, we found that substantial changes to populations are not necessarily a pre-condition for invasion success and that increases in species abundance are unusual. Instead, abundance at home predicts abundance away, a potentially useful additional criterion for biosecurity programmes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley-Blackwell","publisherLocation":"Malden, MA","doi":"10.1111/j.1461-0248.2010.01584.x","usgsCitation":"Firn, J., Moore, J.L., MacDougall, A.S., Borer, E.T., Seabloom, E.W., HilleRisLambers, J., Harpole, W., Cleland, E., Brown, C.S., Knops, J.M., Prober, S.M., Pyke, D.A., Farrell, K.A., Bakker, J.D., O’Halloran, L.R., Adler, P.B., Collins, S., D'Antonio, C., Crawley, M.J., Wolkovich, E., La Pierre, K.J., Melbourne, B.A., Hautier, Y., Morgan, J.W., Leakey, A.D., Kay, A., McCulley, R., Davies, K.F., Stevens, C.J., Chu, C., Holl, K.D., Klein, J.A., Fay, P.A., Hagenah, N., Kirkman, K.P., and Buckley, Y.M., 2011, Abundance of introduced species at home predicts abundance away in herbaceous communities: Ecology Letters, v. 14, no. 3, p. 274-281, https://doi.org/10.1111/j.1461-0248.2010.01584.x.","productDescription":"8 p.","startPage":"274","endPage":"281","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":474972,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://ir.lzu.edu.cn/handle/262010/114990","text":"External Repository"},{"id":267801,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1461-0248.2010.01584.x"},{"id":204144,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":22511,"rank":9999,"type":{"id":9,"text":"Database"},"url":"https://onlinelibrary.wiley.com/doi/10.1111/j.1461-0248.2010.01584.x/abstract;jsessionid=710BF47CFA6E976692208EC0C5C53768.d02t02?systemMessage=Wiley+Online+Library+will+be+disrupted+2+July+from+10-12+BST+for+monthly+maintenance","linkFileType":{"id":5,"text":"html"}}],"country":"United States","volume":"14","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-02-01","publicationStatus":"PW","scienceBaseUri":"4f4e4b05e4b07f02db699d36","contributors":{"authors":[{"text":"Firn, Jennifer","contributorId":66405,"corporation":false,"usgs":false,"family":"Firn","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":348650,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Joslin L.","contributorId":90456,"corporation":false,"usgs":true,"family":"Moore","given":"Joslin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":348663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"MacDougall, Andrew S.","contributorId":39509,"corporation":false,"usgs":true,"family":"MacDougall","given":"Andrew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":348640,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borer, Elizabeth T.","contributorId":45049,"corporation":false,"usgs":false,"family":"Borer","given":"Elizabeth","email":"","middleInitial":"T.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":348642,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seabloom, Eric W.","contributorId":60762,"corporation":false,"usgs":false,"family":"Seabloom","given":"Eric","email":"","middleInitial":"W.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":348647,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"HilleRisLambers, Janneke","contributorId":47649,"corporation":false,"usgs":true,"family":"HilleRisLambers","given":"Janneke","email":"","affiliations":[],"preferred":false,"id":348644,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harpole, W. 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Assessment using numerical groundwater models","docAbstract":"Widespread use of dry wells to dispose of roadside runoff has raised concern about the potential effects on the quality of groundwater on the Island of Hawai‘i. This study used semi-generic numerical models of groundwater flow and contaminant transport to assess the potential effect of dry wells on groundwater quality on the Island of Hawai‘i. The semi-generic models are generalized numerical groundwater-flow and solute-transport models that have a range of aquifer properties and regional groundwater gradients that are characteristic for the island. Several semi-generic models were created to study the effect of dry wells in different hydrogeologic conditions, such as different unsaturated-zone thicknesses or different aquifer characteristics. Results indicate that mixing of contaminated water from the surface with contaminant-free water in the saturated aquifer immediately reduces the contaminant concentration. The amount the concentration is reduced depends on the hydraulic properties of the aquifer in a given area, the thickness of the unsaturated zone, and whether the infiltration is focused in a small area of a dry well or spread naturally over a larger area. Model simulations indicate that focusing infiltration of contaminated runoff through a dry well can substantially increase contaminant concentrations in the underlying saturated aquifer relative to infiltration under natural conditions. Simulated concentrations directly beneath a dry well were nearly 8 times higher than the simulated concentrations directly beneath a broad infiltration area representing the natural condition. Where dry wells are present, contaminant concentrations in the underlying saturated aquifer are lower when the unsaturated zone is thicker and higher when the unsaturated zone is thinner. Contaminant concentrations decline quickly as the contaminant plume migrates, with the regional groundwater flow, away from the dry well. The differences among concentrations resulting from the various unsaturated-zone thicknesses also diminish with distance from the dry well. At a horizontal distance of about 700 ft downgradient from the dry well, all simulated maximum concentrations were less than 1 percent of the concentration in the infiltration water; at about 0.5 mi downgradient from the dry well, all simulated concentrations were equal to or less than 0.1 percent. Actual concentrations may be even lower than indicated by the models because of processes such as decay and reaction that were not simulated. Hydrologic and geologic differences from one location to the next also affect contaminant concentrations—simulations using models with properties representative of aquifers in the Hilo area resulted in lower overall concentrations than models with properties representative of aquifers in the Kona area. Results from this study can be used to assess how contaminants entering a dry well may affect receiving waters in a variety of situations on the Island of Hawai‘i. Better assessment would be obtained by using results from models having the most similar conditions (such as climate, hydraulic properties, regional groundwater gradient) to the dry well in question. 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