{"pageNumber":"661","pageRowStart":"16500","pageSize":"25","recordCount":46883,"records":[{"id":70224979,"text":"70224979 - 2011 - DDT, DDD, and DDE in birds","interactions":[],"lastModifiedDate":"2021-10-11T18:38:01.49406","indexId":"70224979","displayToPublicDate":"2011-12-31T13:29:51","publicationYear":"2011","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"12","title":"DDT, DDD, and DDE in birds","docAbstract":"<p><span>This chapter summarizes residue levels of dichlorodiphenyltrichloroethane (DDT), DDD, and DDE three compounds in birds that are diagnostic for or are associated with mortality and important sublethal effects and suggests improvements in design of contemporary field studies that will result in maximum usefulness in interpreting residue data. Heath et al. first documented eggshell thinning and associated lowered reproductive success of experimental birds on DDE diets. Although there were several studies of eggshell thinning of birds that were given diets containing technical DDT, most did not list residues in eggs, and DDE-not DDT-comprises most of dietary exposure of wild birds with significant eggshell thinning. Although DDE was responsible for most reproductive failure in birds, very high levels of DDT in ring-necked pheasant eggs in California may have caused reproductive problems, such as crippling and mortality of young. Residues in tissues, particularly brain, have proven to be diagnostic of lethality in animals on dietary dosages of DDT, DDD, and DDE in experiments.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Environmental contaminants in biota: Interpreting tissue concentrations","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Taylor & Francis","doi":"10.1201/b10598-13","usgsCitation":"Blus, L.J., 2011, DDT, DDD, and DDE in birds, chap. 12 <i>of</i> Environmental contaminants in biota: Interpreting tissue concentrations, p. 425-444, https://doi.org/10.1201/b10598-13.","productDescription":"20 p.","startPage":"425","endPage":"444","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":474830,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1201/b10598-13","text":"Publisher Index Page"},{"id":390401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Beyer, W. Nelson 0000-0002-8911-9141 nbeyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8911-9141","contributorId":3301,"corporation":false,"usgs":true,"family":"Beyer","given":"W.","email":"nbeyer@usgs.gov","middleInitial":"Nelson","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":825008,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Meador, James P.","contributorId":174075,"corporation":false,"usgs":false,"family":"Meador","given":"James P.","affiliations":[],"preferred":false,"id":825009,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Blus, Lawrence J.","contributorId":35199,"corporation":false,"usgs":true,"family":"Blus","given":"Lawrence","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":825007,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70224978,"text":"70224978 - 2011 - Environmental contaminants in biota: Interpreting tissue concentrations","interactions":[],"lastModifiedDate":"2021-10-11T18:07:15.061438","indexId":"70224978","displayToPublicDate":"2011-12-31T13:02:02","publicationYear":"2011","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":15,"text":"Monograph"},"title":"Environmental contaminants in biota: Interpreting tissue concentrations","docAbstract":"<p><span>Discussing the interpretation of tissue concentrations of contaminants in wildlife, this updated edition of a bestseller draws on current scientific research and includes new chapters and greater emphasis on aquatic organisms. Each chapter provides a summary and review of a specific chemical along with direction on research methods and the interpretation of conflicting or insufficient data. Chapters include a comprehensive history of contaminant interpretation in wildlife and fish, the use of tissue residues in ecological risk assessment, and detailed coverage of all bioaccumulative contaminants and their physiologic affects.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1201/b10598","usgsCitation":"Beyer, W.N., and Meador, J., 2011, Environmental contaminants in biota: Interpreting tissue concentrations, 768 p., https://doi.org/10.1201/b10598.","productDescription":"768 p.","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":474831,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.doabooks.org/doab?func=search&query=rid:48368","text":"Publisher Index Page"},{"id":390400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2011-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Beyer, W. Nelson 0000-0002-8911-9141 nbeyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8911-9141","contributorId":3301,"corporation":false,"usgs":true,"family":"Beyer","given":"W.","email":"nbeyer@usgs.gov","middleInitial":"Nelson","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":825004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meador, James P.","contributorId":174075,"corporation":false,"usgs":false,"family":"Meador","given":"James P.","affiliations":[],"preferred":false,"id":825005,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70209241,"text":"70209241 - 2011 - The role of backbarrier infilling in the formation of barrier island systems","interactions":[],"lastModifiedDate":"2020-03-27T06:31:57","indexId":"70209241","displayToPublicDate":"2011-12-31T11:35:31","publicationYear":"2011","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"The role of backbarrier infilling in the formation of barrier island systems","docAbstract":"<p><span>Barrier islands develop through a variety of processes, including spit accretion, barrier elongation, and inlet filling. New geophysical and sedimentological data provide a means of documenting the presence of a paleoinlet within a barrier lithosome in the western Gulf of Maine, illuminating the process of backbarrier infilling and its effect on barrier and tidal inlet morphodynamics. The transport of sediment into the backbarrier through tidal inlets as well as sediment contribution from nearby rivers led to bay infilling, formation of tidal flats and marshes, and a vast reduction in the bay tidal prism. Using existing marsh stratigraphy and high resolution imaging of a paleo inlet, this study investigates the effects of this diminishing tidal prism and inlet closure process. Chronostratigraphic reconstructions and digital backstripping of the backbarrier explain rates and timing of infilling and eventual conversion of an open water lagoon to the modern high marsh and tidal creek system.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The Proceedings of the Coastal Sediments 2011","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Coastal Sediments 2011","conferenceDate":"May 2-6, 2011","conferenceLocation":"Miami, FL","language":"English","publisher":"World Scientific","doi":"10.1142/9789814355537_0091","usgsCitation":"Hein, C.J., FitzGerald, D.M., Carruthers, E.A., Stone, B.D., and Gontz, A.M., 2011, The role of backbarrier infilling in the formation of barrier island systems, <i>in</i> The Proceedings of the Coastal Sediments 2011, v. 2011, Miami, FL, May 2-6, 2011, p. 1203-1216, https://doi.org/10.1142/9789814355537_0091.","productDescription":"14 p.","startPage":"1203","endPage":"1216","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":373510,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Maine","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -71.54296874999999,\n              41.77131167976407\n            ],\n            [\n              -70.4443359375,\n              41.21172151054787\n            ],\n            [\n              -66.70898437499999,\n              42.8115217450979\n            ],\n            [\n              -64.6875,\n              44.213709909702054\n            ],\n            [\n              -64.8193359375,\n              45.706179285330855\n            ],\n            [\n              -67.3681640625,\n              45.213003555993964\n            ],\n            [\n              -71.05957031249999,\n              43.83452678223682\n            ],\n            [\n              -71.54296874999999,\n              41.77131167976407\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"2011","noUsgsAuthors":false,"publicationDate":"2012-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Hein, Christopher J.","contributorId":39893,"corporation":false,"usgs":true,"family":"Hein","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":785520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"FitzGerald, Duncan M.","contributorId":48077,"corporation":false,"usgs":true,"family":"FitzGerald","given":"Duncan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":785521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carruthers, Emily A.","contributorId":59709,"corporation":false,"usgs":true,"family":"Carruthers","given":"Emily","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":785522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stone, Byron D. 0000-0001-6092-0798 bdstone@usgs.gov","orcid":"https://orcid.org/0000-0001-6092-0798","contributorId":1702,"corporation":false,"usgs":true,"family":"Stone","given":"Byron","email":"bdstone@usgs.gov","middleInitial":"D.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":785523,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gontz, Allen M.","contributorId":79784,"corporation":false,"usgs":true,"family":"Gontz","given":"Allen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":785524,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70190488,"text":"70190488 - 2011 - Novel primers for complete mitochondrial cytochrome b genesequencing in mammals","interactions":[],"lastModifiedDate":"2017-09-05T08:53:32","indexId":"70190488","displayToPublicDate":"2011-12-31T00:00:00","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}},"displayTitle":"Novel primers for complete mitochondrial cytochrome <i>b</i> genesequencing in mammals","title":"Novel primers for complete mitochondrial cytochrome b genesequencing in mammals","docAbstract":"<p>Sequence-based species identification relies on the extent and integrity of sequence data available in online databases such as GenBank. When identifying species from a sample of unknown origin, partial DNA sequences obtained from the sample are aligned against existing sequences in databases. When the sequence from the matching species is not present in the database, high-scoring alignments with closely related sequences might produce unreliable results on species identity. For species identification in mammals, the cytochrome <i>b</i> (cyt <i>b</i>) gene has been identified to be highly informative; thus, large amounts of reference sequence data from the cyt <i>b</i> gene are much needed. To enhance availability of cyt <i>b</i> gene sequence data on a large number of mammalian species in GenBank and other such publicly accessible online databases, we identified a primer pair for complete cyt <i>b</i> gene sequencing in mammals. Using this primer pair, we successfully PCR amplified and sequenced the complete cyt<i> b</i> gene from 40 of 44 mammalian species representing 10 orders of mammals. We submitted 40 complete, correctly annotated, cyt <i>b</i> protein coding sequences to GenBank. To our knowledge, this is the first single primer pair to amplify the complete cyt <i>b</i> gene in a broad range of mammalian species. This primer pair can be used for the addition of new cyt <i>b</i> gene sequences and to enhance data available on species represented in GenBank. The availability of novel and complete gene sequences as high-quality reference data can improve the reliability of sequence-based species identification.</p>","language":"English","publisher":"Wiley","doi":"10.1111/j.1755-0998.2011.03078.x","usgsCitation":"Naidu, A., Fitak, R.R., Munguia-Vega, A., and Culver, M., 2011, Novel primers for complete mitochondrial cytochrome b genesequencing in mammals: Molecular Ecology Resources, v. 12, no. 2, p. 191-196, https://doi.org/10.1111/j.1755-0998.2011.03078.x.","productDescription":"6 p.","startPage":"191","endPage":"196","ipdsId":"IP-058046","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":506142,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1755-0998.2011.03078.x","text":"Publisher Index Page"},{"id":345448,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2011-10-04","publicationStatus":"PW","scienceBaseUri":"59afb7a0e4b0e9bde1351143","contributors":{"authors":[{"text":"Naidu, Ashwin","contributorId":170000,"corporation":false,"usgs":false,"family":"Naidu","given":"Ashwin","email":"","affiliations":[{"id":17653,"text":"School of Natural Resources & the Environment, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":709444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fitak, Robert R.","contributorId":169991,"corporation":false,"usgs":false,"family":"Fitak","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":32413,"text":"University of Arizona, Tucson, AZ, USA, 85721","active":true,"usgs":false},{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":709445,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Munguia-Vega, Adrian","contributorId":56909,"corporation":false,"usgs":false,"family":"Munguia-Vega","given":"Adrian","email":"","affiliations":[],"preferred":false,"id":709446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Culver, Melanie 0000-0001-5380-3059 mculver@usgs.gov","orcid":"https://orcid.org/0000-0001-5380-3059","contributorId":4327,"corporation":false,"usgs":true,"family":"Culver","given":"Melanie","email":"mculver@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":12625,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA","active":true,"usgs":false},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":127,"text":"Arizona Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":709443,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70193077,"text":"70193077 - 2011 - Using regional-scale pre- and post Hurricane Katrina lidar for monitoring and modeling: Chapter 30","interactions":[],"lastModifiedDate":"2018-04-23T09:14:52","indexId":"70193077","displayToPublicDate":"2011-12-31T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Using regional-scale pre- and post Hurricane Katrina lidar for monitoring and modeling: Chapter 30","docAbstract":"Hurricane Katrina was one of the largest natural disasters in U.S. history. Due to the sheer\nsize of the affected areas, an unprecedented regional analysis at very high resolution and\naccuracy was needed to properly quantify and understand the effects of the hurricane and\nthe storm tide. Many disparate sources of lidar data were acquired and processed for\nvarying environmental reasons by pre- and post-Katrina projects. The datasets were in\nseveral formats and projections and were processed to varying phases of completion, and as\na result the task of producing a seamless digital elevation dataset required a high level of\ncoordination, research, and revision. This completed integration allowed for regional-scale\nstorm surge modeling based on very high-resolution elevation information.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Recent Hurricane Research - Climate, Dynamics, and Societal Impacts","language":"English","publisher":"InTech","doi":"10.5772/14127","usgsCitation":"Stoker, J.M., Turnipseed, D.P., and Wilson, K.V., 2011, Using regional-scale pre- and post Hurricane Katrina lidar for monitoring and modeling: Chapter 30, chap. <i>of</i> Recent Hurricane Research - Climate, Dynamics, and Societal Impacts, p. 575-592, https://doi.org/10.5772/14127.","productDescription":"13 p.","startPage":"575","endPage":"592","ipdsId":"IP-087647","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":474835,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5772/14127","text":"Publisher Index 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,{"id":70043157,"text":"70043157 - 2011 - Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin","interactions":[],"lastModifiedDate":"2013-02-15T16:51:02","indexId":"70043157","displayToPublicDate":"2011-12-31T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2289,"text":"Journal of Flood Risk Management","active":true,"publicationSubtype":{"id":10}},"title":"Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin","docAbstract":"In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32 000 km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC_RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC_RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC_RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Flood Risk Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/j.1753-318X.2011.01121.x","usgsCitation":"Artan, G.A., Tokar, S., Gautam, D., Bajracharya, S., and Shrestha, M., 2011, Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin: Journal of Flood Risk Management, v. 4, no. 4, p. 360-373, https://doi.org/10.1111/j.1753-318X.2011.01121.x.","startPage":"360","endPage":"373","ipdsId":"IP-021744","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":267584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":267583,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1753-318X.2011.01121.x"}],"country":"United States","volume":"4","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-09-13","publicationStatus":"PW","scienceBaseUri":"511f6705e4b03b29402c5d90","contributors":{"authors":[{"text":"Artan, Guleid A. 0000-0001-8409-6182 gartan@usgs.gov","orcid":"https://orcid.org/0000-0001-8409-6182","contributorId":2938,"corporation":false,"usgs":true,"family":"Artan","given":"Guleid","email":"gartan@usgs.gov","middleInitial":"A.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":473074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tokar, S.A.","contributorId":67331,"corporation":false,"usgs":true,"family":"Tokar","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":473077,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gautam, D.K.","contributorId":90568,"corporation":false,"usgs":true,"family":"Gautam","given":"D.K.","email":"","affiliations":[],"preferred":false,"id":473078,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bajracharya, S.R.","contributorId":25387,"corporation":false,"usgs":true,"family":"Bajracharya","given":"S.R.","email":"","affiliations":[],"preferred":false,"id":473075,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shrestha, M.S.","contributorId":45547,"corporation":false,"usgs":true,"family":"Shrestha","given":"M.S.","email":"","affiliations":[],"preferred":false,"id":473076,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70006368,"text":"ofr20111308 - 2011 - Postwildfire preliminary debris flow hazard assessment for the area burned by the 2011 Las Conchas Fire in north-central New Mexico","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"ofr20111308","displayToPublicDate":"2011-12-30T14:32:00","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":"2011-1308","title":"Postwildfire preliminary debris flow hazard assessment for the area burned by the 2011 Las Conchas Fire in north-central New Mexico","docAbstract":"<p>The Las Conchas Fire during the summer of 2011 was the largest in recorded history for the state of New Mexico, burning 634 square kilometers in the Jemez Mountains of north-central New Mexico. The burned landscape is now at risk of damage from postwildfire erosion, such as that caused by debris flows and flash floods. This report presents a preliminary hazard assessment of the debris-flow potential from 321 basins burned by the Las Conchas Fire. A pair of empirical hazard-assessment models developed using data from recently burned basins throughout the intermountain western United States was used to estimate the probability of debris-flow occurrence and volume of debris flows at the outlets of selected drainage basins within the burned area. The models incorporate measures of burn severity, topography, soils, and storm rainfall to estimate the probability and volume of debris flows following the fire.</p> <p>In response to a design storm of 28.0 millimeters of rain in 30 minutes (10-year recurrence interval), the probabilities of debris flows estimated for basins burned by the Las Conchas Fire were greater than 80 percent for two-thirds (67 percent) of the modeled basins. Basins with a high (greater than 80 percent) probability of debris-flow occurrence were concentrated in tributaries to Santa Clara and Rio del Oso Canyons in the northeastern part of the burned area; some steep areas in the Valles Caldera National Preserve, Los Alamos, and Guaje Canyons in the east-central part of the burned area; tributaries to Peralta, Colle, Bland, and Cochiti canyons in the southwestern part of the burned area; and tributaries to Frijoles, Alamo, and Capulin Canyons in the southeastern part of the burned area (within Bandelier National Monument). Estimated debris-flow volumes ranged from 400 cubic meters to greater than 72,000 cubic meters. The largest volumes (greater than 40,000 cubic meters) were estimated for basins in Santa Clara, Los Alamos, and Water Canyons, and for two basins at the northeast edge of the burned area tributary to Rio del Oso and Vallecitos Creek.</p> <p>The Combined Relative Debris-Flow Hazard Rankings identify the areas of highest probability of the largest debris flows. Basins with high Combined Relative Debris-Flow Hazard Rankings include upper Santa Clara Canyon in the northern section of the burn scar, and portions of Peralta, Colle, Bland, Cochiti, Capulin, Alamo, and Frijoles Canyons in the southern section of the burn scar. Three basins with high Combined Relative Debris-Flow Hazard Rankings also occur in areas upstream from the city of Los Alamos&mdash;the city is home to and surrounded by numerous technical sites for the Los Alamos National Laboratory.</p> <p>Potential debris flows in the burned area could affect the water supply for Santa Clara Pueblo and several recreational lakes, as well as recreational and archeological resources in Bandelier National Monument. Debris flows could damage bridges and culverts along State Highway 501 and other roadways. Additional assessment is necessary to determine if the estimated volume of material is sufficient to travel into areas downstream from the modeled basins along the valley floors, where they could affect human life, property, agriculture, and infrastructure in those areas. Additionally, further investigation is needed to assess the potential for debris flows to affect structures at or downstream from basin outlets and to increase the threat of flooding downstream by damaging or blocking flood mitigation structures. The maps presented here may be used to prioritize areas where erosion mitigation or other protective measures may be necessary within a 2- to 3-year window of vulnerability following the Las Conchas Fire.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111308","usgsCitation":"Tillery, A.C., Darr, M.J., Cannon, S.H., and Michael, J.A., 2011, Postwildfire preliminary debris flow hazard assessment for the area burned by the 2011 Las Conchas Fire in north-central New Mexico: U.S. Geological Survey Open-File Report 2011-1308, v, 11 p.; 3 Plates - Plate 1: 20.35 x 32.35 inches, Plate 2: 20.21 x 32.41 inches, Plate 3: 20.41 x 32.41 inches, https://doi.org/10.3133/ofr20111308.","productDescription":"v, 11 p.; 3 Plates - Plate 1: 20.35 x 32.35 inches, Plate 2: 20.21 x 32.41 inches, Plate 3: 20.41 x 32.41 inches","onlineOnly":"Y","temporalStart":"2011-06-01","temporalEnd":"2011-08-31","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":116198,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1308.png"},{"id":112410,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1308/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.61749999999999,35.6 ], [ -106.61749999999999,36.08416666666667 ], [ -106.25083333333333,36.08416666666667 ], [ -106.25083333333333,35.6 ], [ -106.61749999999999,35.6 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a7ea0e4b0c8380cd7a65e","contributors":{"authors":[{"text":"Tillery, Anne C. 0000-0002-9508-7908 atillery@usgs.gov","orcid":"https://orcid.org/0000-0002-9508-7908","contributorId":2549,"corporation":false,"usgs":true,"family":"Tillery","given":"Anne","email":"atillery@usgs.gov","middleInitial":"C.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":354396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Darr, Michael J. mjdarr@usgs.gov","contributorId":4239,"corporation":false,"usgs":true,"family":"Darr","given":"Michael","email":"mjdarr@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":354397,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cannon, Susan H. cannon@usgs.gov","contributorId":1019,"corporation":false,"usgs":true,"family":"Cannon","given":"Susan","email":"cannon@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":354394,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Michael, John A. jmichael@usgs.gov","contributorId":1877,"corporation":false,"usgs":true,"family":"Michael","given":"John","email":"jmichael@usgs.gov","middleInitial":"A.","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":354395,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70006364,"text":"ofr20111310 - 2011 - Summary of November 2010 meeting to evaluate turbidite data for constraining the recurrence parameters of great Cascadia earthquakes for the update of national seismic hazard maps","interactions":[],"lastModifiedDate":"2012-02-10T00:12:01","indexId":"ofr20111310","displayToPublicDate":"2011-12-30T00:00:00","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":"2011-1310","title":"Summary of November 2010 meeting to evaluate turbidite data for constraining the recurrence parameters of great Cascadia earthquakes for the update of national seismic hazard maps","docAbstract":"This report summarizes a meeting of geologists, marine sedimentologists, geophysicists, and seismologists that was held on November 18&ndash;19, 2010 at Oregon State University in Corvallis, Oregon. The overall goal of the meeting was to evaluate observations of turbidite deposits to provide constraints on the recurrence time and rupture extent of great Cascadia subduction zone (CSZ) earthquakes for the next update of the U.S. national seismic hazard maps (NSHM). The meeting was convened at Oregon State University because this is the major center for collecting and evaluating turbidite evidence of great Cascadia earthquakes by Chris Goldfinger and his colleagues. We especially wanted the participants to see some of the numerous deep sea cores this group has collected that contain the turbidite deposits. Great earthquakes on the CSZ pose a major tsunami, ground-shaking, and ground-failure hazard to the Pacific Northwest. Figure 1 shows a map of the Pacific Northwest with a model for the rupture zone of a moment magnitude M<sub>w</sub> 9.0 earthquake on the CSZ and the ground shaking intensity (in ShakeMap format) expected from such an earthquake, based on empirical ground-motion prediction equations. The damaging effects of such an earthquake would occur over a wide swath of the Pacific Northwest and an accompanying tsunami would likely cause devastation along the Pacifc Northwest coast and possibly cause damage and loss of life in other areas of the Pacific. A magnitude 8 earthquake on the CSZ would cause damaging ground shaking and ground failure over a substantial area and could also generate a destructive tsunami. The recent tragic occurrence of the 2011 M<sub>w</sub> 9.0 Tohoku-Oki, Japan, earthquake highlights the importance of having accurate estimates of the recurrence times and magnitudes of great earthquakes on subduction zones. For the U.S. national seismic hazard maps, estimating the hazard from the Cascadia subduction zone has been based on coastal paleoseismic evidence of great earthquakes over the past 5,000 years. The instrumental catalog of earthquakes is of little use for constraining the hazard of the CSZ, because there are virtually no recorded earthquakes on most of the plate interface of the CSZ. There are no historical accounts in the past 150 years of large earthquakes on most of the CSZ. Until about 20 years ago, some interpreted this lack of recent and historical earthquakes as an indicator that the subduction zone was slipping aseismically and could not produce a great earthquake. The work of Brian Atwater and others, in the late 1980s and the 1990s (Atwater, 1987, 1992; Atwater and others, 1995; Nelson and others, 1996; Clague, 1997; Atwater and Hemphill-Haley, 1997; Atwater and others, 2004) demonstrated that submerged forests, buried soils, tsunami deposits, and liquefaction along and near the coast were compelling evidence of repeated great Cascadia earthquakes over at least the past 5,000 years. Atwater and Hemphill-Haley (1997) concluded from paleoseismic evidence at Willapa Bay, Washington, that great earthquakes ruptured the CSZ with an average recurrence time of about 500 years. The date of the last great CSZ earthquake, January 26, 1700, was established from historical records of the so-called orphan tsunami in Japan that is inferred to have been produced by this earthquake (Satake and others, 1996, 2003; Atwater and others, 2005) and is consistent with tree-ring data from drowned forests in Washington and Oregon. From modeling the observations of the tsunami, Satake and others (2003) estimated a moment magnitude of about 9.0 for this earthquake. Many other paleoseismic sites have been investigated along the Pacific Northwest coast from Vancouver Island to northern California and show evidence of great CSZ earthquakes. Nelson and others (2006) summarized the dates found from these studies and proposed correlations between sites indicating the extent of rupture for individual events. Dating of inferred tsunami deposits in Bradley Lake, Oregon by Kelsey and others (2005), as well as tsunami and subsidence evidence from Six Rivers, Oregon (Kelsey and others, 2002) and Coquille River (Witter and others, 2003), indicates that there were probably M<sub>w</sub> 8 ruptures in the southern portion of the CSZ in addition to the M<sub>w</sub> 9 events that rupture the whole length of the CSZ (Nelson and others, 2006). A parallel development over the past 20 years or more is the use of deep-sea turbidite deposits for identifying and dating great Cascadia earthquakes over the past 10,000 years (Adams, 1990; Goldfinger and others, 2003, 2008, in press; Goldfinger, 2011). Turbidites are sediment deposits in the deep ocean from turbidity currents, which are energetic flows of sediment and water along the continental shelf and slope. Adams (1990), using the counts of turbidites in deep-sea cores off the coast of Oregon and Washington collected and analyzed by Griggs (1969) and Griggs and others (1969), proposed that these turbidites were caused by the shaking of great Cascadia earthquakes. Part of his reasoning was that the number (13) of turbidite deposits that occurred since deposition of the Mazama Ash 7,000 years ago gave a recurrence time of about 500 years, consistent with that derived from the coastal submergence data. Adams (1990) also proposed the &ldquo;confluence test&rdquo; which evaluates the number of turbidites for submarine channels that form a confluence. He reported that the number of turbidites in the single downstream channel equaled the number in each of the tributary channels. He reasoned that this indicated that the turbidites in each tributary were simultaneously triggered and were, therefore, caused by a common forcing agent. He concluded that shaking from extended ruptures of great Cascadia earthquakes was the most likely cause of these turbidites. Based on the paleoseismic evidence of past great earthquakes, the hazard from the Cascadia subduction zone was included in the 1996 U.S. NSHM (Frankel and others, 1996), which were the basis for seismic provisions in the 2000 International Building Code. These hazard maps used the paleoseismic studies to constrain the recurrence rate of great CSZ earthquakes. Goldfinger and his colleagues have since collected many more deep ocean cores and done extensive analysis on the turbidite deposits that they identified in the cores (Goldfinger and others, 2003, 2008, in press; Goldfinger, 2011). Using their dating of the sediments and correlation of features in the logs of density and magnetic susceptibility between cores, they developed a detailed chronology of great earthquakes along the CSZ for the past 10,000 years (Goldfinger and others, in press). These correlations consist of attempting to match the peaks and valleys in logs of density and magnetic susceptibility between cores separated, in some cases, by hundreds of kilometers. Based on this work, Goldfinger and others (2003, 2008, in press) proposed that the turbidite evidence indicated the occurrence of great earthquakes (M<sub>w</sub> 8) that only ruptured the southern portion of the CSZ, as well as earthquakes with about M<sub>w</sub> 9 that ruptured the entire length of the CSZ. For the southernmost portion of the CSZ, Goldfinger and others (in press) proposed a recurrence time of M<sub>w</sub> 8 or larger earthquakes of about 230 years. This proposed recurrence time was shorter than the 500 year time that was incorporated in one scenario in the NSHM&rsquo;s. It is important to note that the hazard maps of 1996 and later also included a scenario or set of scenarios with a shorter recurrence time for M<sub>w</sub> 8 earthquakes, using rupture zones that are distributed along the length of the CSZ (Frankel and others, 1996; Petersen and others, 2008). Originally, this scenario was meant to correspond to the idea that some of the 500-year averaged ruptures seen in the paleoseismic evidence could have been a series of M<sub>w</sub> 8 earthquakes that occurred over a short period of time (a few decades), rather than M<sub>w</sub> 9 earthquakes. Figure 2 shows the logic tree for the CSZ used in the 2008 NSHM&rsquo;s (Petersen and others, 2008). This logic tree includes whole CSZ rupture earthquakes (M<sub>w</sub> 8.8&ndash;9.2) and partial CSZ rupture earthquakes (M<sub>w</sub> 8.0&ndash;8.7). In this latest version of the NSHM&rsquo;s, the effective recurrence time of earthquakes on the CSZ with moment magnitudes greater than or equal to 8.0 over the various models is about 270 years (Petersen and others, 2008). This recurrence time applies to the entire CSZ, so that the hazard from great earthquakes was approximately equal along the whole zone, although the hazard estimates taper on the northern and southern ends of the CSZ, because of the way rupture zones of M<sub>w</sub> 8 earthquakes were distributed along the strike of the CSZ. The NSHM will be updated in 2013, as part of the standard update cycle that corresponds to the update cycle of the national model building codes that are based on the seismic hazard maps. A meeting was necessary to assemble a wide group of experts to hear Dr. Goldfinger explain his methodology for dating and correlating the turbidites and for developing the earthquake chronology. The overall goal of the workshop was to evaluate observations of turbidite deposits to provide constraints on the recurrence times and rupture extents of great Cascadia subduction zone earthquakes for the next update of the NSHM. Before the meeting, participants were supplied with the U.S. Geological Survey (USGS) Professional Paper of Goldfinger and others (in press), as well as material from Brian Atwater and Alan Nelson. The agenda of the meeting was developed by Art Frankel, with assistance from Chris Goldfinger, Brian Atwater, Alan Nelson, Mark Petersen, and Craig Weaver. The meeting was hosted by Chris Goldfinger of Oregon State University. We stress that it is difficult to evaluate in a two-day meeting the large amount of work that Goldfinger and his colleagues have done over the past 15 years or more. This meeting is the first step in a process that develops the inputs to the update of the national maps. The conclusions of this workshop will be discussed and possibly modified at the regional Pacific Northwest workshop for the hazard maps to be held in early 2012. Vetting new research results using informed expert opinion is an integral part of updating the national maps and does not reflect on the veracity of these results.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111310","usgsCitation":"Frankel, A.D., 2011, Summary of November 2010 meeting to evaluate turbidite data for constraining the recurrence parameters of great Cascadia earthquakes for the update of national seismic hazard maps: U.S. Geological Survey Open-File Report 2011-1310, iii, 10 p.; Appendix; Figures, https://doi.org/10.3133/ofr20111310.","productDescription":"iii, 10 p.; Appendix; Figures","startPage":"i","endPage":"13","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":116324,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1310.gif"},{"id":112398,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1310/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Cascadia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -130,40 ], [ -130,50 ], [ -118,50 ], [ -118,40 ], [ -130,40 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b9e3de4b08c986b31dd97","contributors":{"authors":[{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":1363,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":354391,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70007061,"text":"sim3194 - 2011 - Geologic map of the Cochiti Dam quadrangle, Sandoval County, New Mexico","interactions":[],"lastModifiedDate":"2022-04-15T19:17:01.779818","indexId":"sim3194","displayToPublicDate":"2011-12-30T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3194","title":"Geologic map of the Cochiti Dam quadrangle, Sandoval County, New Mexico","docAbstract":"<p>The Cochiti Dam quadrangle is located in the southern part of the Espa&#241;ola Basin and contains sedimentary and volcanic deposits that record alluvial, colluvial, eolian, tectonic and volcanic processes over the past seventeen million years. The geology was mapped from 1997 to 1999 and modified in 2004 to 2008. The primary mapping responsibilities were as follows: Dethier mapped the surficial deposits, basin-fill sedimentary deposits, Miocene to Quaternary volcanic deposits of the Jemez volcanic field, and a preliminary version of fault distribution. Thompson and Hudson mapped the Pliocene and Quaternary volcanic deposits of the Cerros del Rio volcanic field. Thompson, Minor, and Hudson mapped surface exposures of faults and Hudson conducted paleomagnetic studies for stratigraphic correlations. Thompson prepared the digital compilation of the geologic map.</p>\n<p>The mapped distribution of units is based primarily on interpretation of 1:16,000-scale, color aerial photographs taken in 1992, and 1:40,000-scale, black-and-white, aerial photographs taken in 1996. Most of the contacts on the map were transferred from the aerial photographs using a photogrammetric stereo-plotter and subsequently field checked for accuracy and revised based on field determination of allostratigraphic and lithostratigraphic units. Determination of lithostratigraphic units in volcanic deposits was aided by geochemical data, <sup>40</sup>Ar/<sup>39</sup>Ar geochronology, aeromagnetic and paleomagnetic data. Supplemental revision of mapped contacts was based on interpretation of USGS 1-meter orthoimagery.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3194","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Dethier, D., Thompson, R.A., Hudson, M., Minor, S.A., and Sawyer, D.A., 2011, Geologic map of the Cochiti Dam quadrangle, Sandoval County, New Mexico: U.S. Geological Survey Scientific Investigations Map 3194, 1 Plate: 58.06 x 42.00 inches; Metadata; Data Files, https://doi.org/10.3133/sim3194.","productDescription":"1 Plate: 58.06 x 42.00 inches; Metadata; Data Files","costCenters":[{"id":308,"text":"Geology and Environmental Change Science Center","active":false,"usgs":true}],"links":[{"id":116196,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3194.png"},{"id":398858,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_96374.htm"},{"id":112411,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3194/","linkFileType":{"id":5,"text":"html"}}],"scale":"24000","country":"United States","state":"New Mexico","county":"Sandoval County","otherGeospatial":"Cochiti Dam","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.375,\n              35.625\n            ],\n            [\n              -106.25,\n              35.625\n            ],\n            [\n              -106.25,\n              35.75\n            ],\n            [\n              -106.375,\n              35.75\n            ],\n            [\n              -106.375,\n              35.625\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a1b73e4b0c8380cd55ed8","contributors":{"authors":[{"text":"Dethier, David P.","contributorId":35285,"corporation":false,"usgs":true,"family":"Dethier","given":"David P.","affiliations":[],"preferred":false,"id":355761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Ren A. 0000-0002-3044-3043 rathomps@usgs.gov","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":1265,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren","email":"rathomps@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":355760,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hudson, Mark R. 0000-0003-0338-6079 mhudson@usgs.gov","orcid":"https://orcid.org/0000-0003-0338-6079","contributorId":1236,"corporation":false,"usgs":true,"family":"Hudson","given":"Mark R.","email":"mhudson@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":355758,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Minor, Scott A. 0000-0002-6976-9235 sminor@usgs.gov","orcid":"https://orcid.org/0000-0002-6976-9235","contributorId":765,"corporation":false,"usgs":true,"family":"Minor","given":"Scott","email":"sminor@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":355757,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sawyer, David A. dsawyer@usgs.gov","contributorId":1262,"corporation":false,"usgs":true,"family":"Sawyer","given":"David","email":"dsawyer@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":355759,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70006361,"text":"ofr20111316 - 2011 - Geochemical data from waters in Prospect Gulch, San Juan County, Colorado, that span pre- and post-Lark Mine remediation","interactions":[],"lastModifiedDate":"2012-02-10T00:12:01","indexId":"ofr20111316","displayToPublicDate":"2011-12-30T00:00:00","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":"2011-1316","title":"Geochemical data from waters in Prospect Gulch, San Juan County, Colorado, that span pre- and post-Lark Mine remediation","docAbstract":"In San Juan County, Colorado, the effects of historical mining continue to contribute dissolved metals to groundwater and surface water. Water samples in Prospect Gulch near Silverton, Colorado, were collected at selected locations that span pre- and post-reclamation activities at the Lark Mine, located in the Prospect Gulch watershed. Geochemical results from those water samples are presented in this report. Water samples were analyzed for specific conductance, pH, temperature, and dissolved oxygen with handheld field meters, and metals were analyzed using inductively coupled plasma-mass spectrometry.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111316","usgsCitation":"Johnson, R.H., Yager, D.B., and Johnson, H.D., 2011, Geochemical data from waters in Prospect Gulch, San Juan County, Colorado, that span pre- and post-Lark Mine remediation: U.S. Geological Survey Open-File Report 2011-1316, vii, 4 p.; XLS Downloads of Tables 1-3, https://doi.org/10.3133/ofr20111316.","productDescription":"vii, 4 p.; XLS Downloads of Tables 1-3","startPage":"i","endPage":"4","numberOfPages":"11","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":116325,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1316.png"},{"id":112396,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1316/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Colorado","county":"San Juan County","otherGeospatial":"Prospect Gulch","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -107.68416666666667,37.86666666666667 ], [ -107.68416666666667,37.9 ], [ -107.66666666666667,37.9 ], [ -107.66666666666667,37.86666666666667 ], [ -107.68416666666667,37.86666666666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a161de4b0c8380cd55053","contributors":{"authors":[{"text":"Johnson, Raymond H. rhjohnso@usgs.gov","contributorId":707,"corporation":false,"usgs":true,"family":"Johnson","given":"Raymond","email":"rhjohnso@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":354382,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yager, Douglas B. 0000-0001-5074-4022 dyager@usgs.gov","orcid":"https://orcid.org/0000-0001-5074-4022","contributorId":798,"corporation":false,"usgs":true,"family":"Yager","given":"Douglas","email":"dyager@usgs.gov","middleInitial":"B.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":354383,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Hugh D.","contributorId":69701,"corporation":false,"usgs":true,"family":"Johnson","given":"Hugh","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":354384,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70136237,"text":"70136237 - 2011 - Development of a pan-Arctic monitoring plan for polar bears: Background paper","interactions":[],"lastModifiedDate":"2018-07-14T13:24:53","indexId":"70136237","displayToPublicDate":"2011-12-30T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Development of a pan-Arctic monitoring plan for polar bears: Background paper","docAbstract":"<div class=\"textLayer\">Polar bears (Ursus maritimus), by their very nature, and the extreme, remote environment in which they live, are inherently difficult to study and monitor. Monitoring polar bear populations is both arduous and costly and, to be effective, must be a long-term commitment. There are few jurisdictional governments and management boards with a mandate for polar bear research and management, and many have limited resources. Although population monitoring of polar bears has been a focus to some degree within most jurisdictions around the Arctic, of the 19 subpopulations recognised by the IUCN/Species Survival Commission Polar Bear Specialist Group (PBSG), adequate scientific trend data exist for only three of the subpopulations, fair trend data for five and poor or no trend data for the remaining 11 subpopulations (PBSG 2010a). There are especially critical knowledge gaps for the subpopulations in East Greenland, in the Russian Kara and Laptev seas, and in the Chukchi Sea, which is shared between Russia and the United States. The range covered by these subpopulations represents a third of the total area (approx. 23 million km2) of polar bears’ current range, and more than half if the Arctic Basin is included. If we use popular terms, we know close to nothing about polar bears in this portion of their range.</div><div class=\"textLayer\"><div><br data-mce-bogus=\"1\"></div><div>As summer sea-ice extent, and to a lesser degree, spring-time extent, continues to retreat, outpacing model forecasts (Stroeve et al. 2007, Pedersen et al. 2009), polar bears face the challenge of adapting to rapidly changing habitats. There is a need to use current and synthesised information across the Arctic, and to develop new methods that will facilitate monitoring to generate new knowledge at a pan-Arctic scale. The circumpolar dimension can be lost when efforts are channelled into regional monitoring. Developing and implementing a plan that harmonises local, regional and global efforts will increase our power to detect and understand important trends for polar bears, with particular emphasis on how climate warming may differentially affect populations and habitats. Current knowledge is inadequate for a comprehensive understanding of the present and future impact of climate warming and its interaction with other stressors. The cumulative effects are unknown (Laidre et al. 2008). An integrated pan-Arctic research and monitoring plan will improve the ability to detect future trends, identify the most vulnerable subpopulations and guide effective conservation. There is a need to direct attention and resources where data are deficient to understand the mechanisms that drive trends, and to facilitate more effective and timely conservation response.</div></div>","language":"English","publisher":"CAFF Monitoring Series Report No. 1","isbn":"978-9935-431-01-1","usgsCitation":"Vongraven, D., and Peacock, E.L., 2011, Development of a pan-Arctic monitoring plan for polar bears: Background paper, 31 p. .","productDescription":"31 p. ","startPage":"1","endPage":"47","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-027368","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":342413,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":296880,"type":{"id":15,"text":"Index Page"},"url":"https://alaska.usgs.gov/science/biology/polar_bears/pdfs/Vongraven_Peacock_2011_PBCircumpolarMonitor.pdf"}],"otherGeospatial":"Arctic","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -42.09960937499999,\n              59.489726035537075\n            ],\n            [\n              -38.935546875,\n              63.430860212678105\n            ],\n            [\n              -31.025390625,\n              65.83877570688918\n            ],\n            [\n              -19.072265624999996,\n              69.25614923150724\n            ],\n            [\n              -14.853515624999996,\n              74.98218270428187\n            ],\n            [\n              -12.216796874999996,\n              78.47300170046985\n            ],\n            [\n              -8.876953124999998,\n              80.83090675124559\n            ],\n            [\n              -10.634765624999996,\n              82.52918486654664\n            ],\n            [\n              -25.400390625,\n              83.7825325736073\n            ],\n            [\n              -41.39648437499999,\n              83.68661544472062\n            ],\n            [\n              -67.236328125,\n              83.66725589385207\n            ],\n            [\n              -84.638671875,\n              82.97265897888354\n            ],\n            [\n              -98.701171875,\n              81.63414891575125\n            ],\n            [\n              -97.822265625,\n              79.20430943611333\n            ],\n            [\n              -97.64648437499999,\n              77.01969153517521\n            ],\n            [\n              -97.998046875,\n              75.67219739055291\n            ],\n            [\n              -97.119140625,\n              73.403337662912\n            ],\n            [\n              -87.97851562499999,\n              70.34831755984781\n            ],\n            [\n              -79.541015625,\n              66.5482634621744\n            ],\n            [\n              -50.009765625,\n              56.413901376006734\n            ],\n            [\n              -42.09960937499999,\n              59.489726035537075\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5940f9b6e4b0764e6c63eaec","contributors":{"authors":[{"text":"Vongraven, Dag","contributorId":131092,"corporation":false,"usgs":false,"family":"Vongraven","given":"Dag","email":"","affiliations":[{"id":7238,"text":"Norwegian Polar Institute","active":true,"usgs":false}],"preferred":false,"id":537228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peacock, Elizabeth L. 0000-0001-7279-0329 lpeacock@usgs.gov","orcid":"https://orcid.org/0000-0001-7279-0329","contributorId":3361,"corporation":false,"usgs":true,"family":"Peacock","given":"Elizabeth","email":"lpeacock@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":false,"id":537227,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70006345,"text":"sim3195 - 2011 - Seismic-Hazard Maps for the Conterminous United States, 2008","interactions":[],"lastModifiedDate":"2012-02-10T00:12:01","indexId":"sim3195","displayToPublicDate":"2011-12-27T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3195","title":"Seismic-Hazard Maps for the Conterminous United States, 2008","docAbstract":"Probabilistic seismic-hazard maps were prepared for the conterminous United States portraying peak horizontal acceleration and horizontal spectral response acceleration for 0.2- and 1.0-second periods with probabilities of exceedance of 10 percent in 50 years and 2 percent in 50 years. All of the maps were prepared by combining the hazard derived from spatially smoothed historic seismicity with the hazard from fault-specific sources. The acceleration values contoured are the random horizontal component. The reference site condition is firm rock, defined as having an average shear-wave velocity of 760 m/s in the top 30 meters corresponding to the boundary between NEHRP (National Earthquake Hazards Reduction program) site classes B and C.\nThis data set represents the results of calculations of hazard curves for a grid of points with a spacing of 0.05 degrees in latitude and longitude. The grid of points were contoured to produce the final representation of the seismic-hazard.\nThese maps are intended to summarize the available quantitative information about seismic ground motion hazard for the conterminous United States from geologic and geophysical source.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3195","collaboration":"Prepared in cooperation with the California Geological Survey","usgsCitation":"Petersen, M.D., Frankel, A.D., Harmsen, S., Mueller, C.S., Haller, K., Wheller, R.L., Wesson, R.L., Zeng, Y., Boyd, O.S., Perkins, D.M., Luco, N., Field, E.H., Wills, C.J., and Rukstales, K.S., 2011, Seismic-Hazard Maps for the Conterminous United States, 2008: U.S. Geological Survey Scientific Investigations Map 3195, Sheets 1-6: 31 inches x 24 inches, Map PDF, GIS data zip; Metadata; Geologic map database, https://doi.org/10.3133/sim3195.","productDescription":"Sheets 1-6: 31 inches x 24 inches, Map PDF, GIS data zip; Metadata; Geologic map database","additionalOnlineFiles":"Y","costCenters":[{"id":414,"text":"National Earthquake Hazards Reduction Program","active":false,"usgs":true}],"links":[{"id":116799,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3195.png"},{"id":112364,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3195/","linkFileType":{"id":5,"text":"html"}}],"scale":"7000000","projection":"Albers eaul-area conic","country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125,22 ], [ -125,50 ], [ -65,50 ], [ -65,22 ], [ -125,22 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b8b79e4b08c986b31786d","contributors":{"authors":[{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":354346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":1363,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":354349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harmsen, Stephen C. harmsen@usgs.gov","contributorId":1795,"corporation":false,"usgs":true,"family":"Harmsen","given":"Stephen C.","email":"harmsen@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":354351,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mueller, Charles S. 0000-0002-1868-9710 cmueller@usgs.gov","orcid":"https://orcid.org/0000-0002-1868-9710","contributorId":955,"corporation":false,"usgs":true,"family":"Mueller","given":"Charles","email":"cmueller@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":354344,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":354348,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wheller, Russel L.","contributorId":75263,"corporation":false,"usgs":true,"family":"Wheller","given":"Russel","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":354355,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wesson, Robert L. 0000-0003-2702-0012 rwesson@usgs.gov","orcid":"https://orcid.org/0000-0003-2702-0012","contributorId":850,"corporation":false,"usgs":true,"family":"Wesson","given":"Robert","email":"rwesson@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":354343,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zeng, Yuehua zeng@usgs.gov","contributorId":1623,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuehua","email":"zeng@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":354350,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Boyd, Oliver S. olboyd@usgs.gov","contributorId":956,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":354345,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Perkins, David M. perkins@usgs.gov","contributorId":2114,"corporation":false,"usgs":true,"family":"Perkins","given":"David","email":"perkins@usgs.gov","middleInitial":"M.","affiliations":[{"id":301,"text":"Geologic Hazards Team","active":false,"usgs":true}],"preferred":true,"id":354352,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Luco, Nicolas 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":1188,"corporation":false,"usgs":true,"family":"Luco","given":"Nicolas","email":"nluco@usgs.gov","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":false,"id":354347,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":52242,"corporation":false,"usgs":true,"family":"Field","given":"Edward","email":"field@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":354353,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Wills, Christopher J.","contributorId":58013,"corporation":false,"usgs":true,"family":"Wills","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":354354,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Rukstales, Kenneth S. 0000-0003-2818-078X rukstales@usgs.gov","orcid":"https://orcid.org/0000-0003-2818-078X","contributorId":775,"corporation":false,"usgs":true,"family":"Rukstales","given":"Kenneth","email":"rukstales@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":354342,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70003691,"text":"70003691 - 2011 - The U.S. Geological Survey mapping and cartographic database activities, 2006-2010","interactions":[],"lastModifiedDate":"2012-02-02T00:15:58","indexId":"70003691","displayToPublicDate":"2011-12-25T15:47:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1191,"text":"Cartography and Geographic Information Science","active":true,"publicationSubtype":{"id":10}},"title":"The U.S. Geological Survey mapping and cartographic database activities, 2006-2010","docAbstract":"The U.S. Geological Survey (USGS) began systematic topographic mapping of the United States in the 1880s, beginning with scales of 1:250,000 and 1:125,000 in support of geological mapping. Responding to the need for higher resolution and more detail, the 1:62,500-scale, 15-minute, topographic map series was begun in the beginning of the 20th century. Finally, in the 1950s the USGS adopted the 1:24,000-scale, 7.5-minute topographic map series to portray even more detail, completing the coverage of the conterminous 48 states of the United States with this series in 1992. In 2001, the USGS developed the vision and concept of <i>The National Map</i>, a topographic database for the 21st century and the source for a new generation of topographic maps (http://nationalmap.gov/). In 2008, the initial production of those maps began with a 1:24,000-scale digital product. In a separate, but related project, the USGS began scanning the existing inventory of historical topographic maps at all scales to accompany the new topographic maps. The USGS also had developed a digital database of <i>The National Atlas of the United States</i>. The digital version of Atlas is now Web-available and supports a mapping engine for small scale maps of the United States and North America. These three efforts define topographic mapping activities of the USGS during the last few years and are discussed below.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Cartography and Geographic Information Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Cartography and Geographic Information Society","doi":"10.1559/15230406382326","usgsCitation":"Craun, K.J., Donnelly, J.P., and Allord, G.J., 2011, The U.S. Geological Survey mapping and cartographic database activities, 2006-2010: Cartography and Geographic Information Science, v. 38, no. 3, p. 326-329, https://doi.org/10.1559/15230406382326.","productDescription":"4 p.","startPage":"326","endPage":"329","temporalStart":"2006-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":204393,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":112422,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1559/15230406382326","linkFileType":{"id":5,"text":"html"}}],"country":"United States","volume":"38","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505ba93fe4b08c986b322138","contributors":{"authors":[{"text":"Craun, Kari J. 0000-0001-7875-2809 kcraun@usgs.gov","orcid":"https://orcid.org/0000-0001-7875-2809","contributorId":3526,"corporation":false,"usgs":true,"family":"Craun","given":"Kari","email":"kcraun@usgs.gov","middleInitial":"J.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":348354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donnelly, John P. jpdonnelly@usgs.gov","contributorId":4461,"corporation":false,"usgs":true,"family":"Donnelly","given":"John","email":"jpdonnelly@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":348355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allord, Gregory J. gjallord@usgs.gov","contributorId":2714,"corporation":false,"usgs":true,"family":"Allord","given":"Gregory","email":"gjallord@usgs.gov","middleInitial":"J.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":348353,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70003793,"text":"70003793 - 2011 - The U.S. Geological Survey cartographic and geographic information science research activities 2006-2010","interactions":[],"lastModifiedDate":"2012-02-02T00:15:59","indexId":"70003793","displayToPublicDate":"2011-12-25T15:33:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1191,"text":"Cartography and Geographic Information Science","active":true,"publicationSubtype":{"id":10}},"title":"The U.S. Geological Survey cartographic and geographic information science research activities 2006-2010","docAbstract":"The U.S. Geological Survey (USGS) produces geospatial databases and topographic maps for the United States of America. A part of that mission includes conducting research in geographic information science (GIScience) and cartography to support mapping and improve the design, quality, delivery, and use of geospatial data and topographic maps. The Center of Excellence for Geospatial Information Science (CEGIS) was established by the USGS in January 2006 as a part of the National Geospatial Program Office. CEGIS (http://cegis.usgs.gov) evolved from a team of cartographic researchers at the Mid-Continent Mapping Center. The team became known as the Cartographic Research group and was supported by the Cooperative Topographic Mapping, Geographic Analysis and Monitoring, and Land Remote Sensing programs of the Geography Discipline of the USGS from 1999-2005. In 2006, the Cartographic Research group and its projects (http://carto-research.er.usgs.gov/) became the core of CEGIS staff and research. In 2006, CEGIS research became focused on The National Map (http://nationalmap.gov).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Cartography and Geographic Information Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1559/15230406382302","usgsCitation":"Usery, E.L., 2011, The U.S. Geological Survey cartographic and geographic information science research activities 2006-2010: Cartography and Geographic Information Science, v. 38, no. 3, p. 302-309, https://doi.org/10.1559/15230406382302.","productDescription":"8 p.","startPage":"302","endPage":"309","temporalStart":"2006-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":112421,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1559/15230406382302","linkFileType":{"id":5,"text":"html"}},{"id":204416,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505ba93ae4b08c986b322119","contributors":{"authors":[{"text":"Usery, E. Lynn 0000-0002-2766-2173 usery@usgs.gov","orcid":"https://orcid.org/0000-0002-2766-2173","contributorId":231,"corporation":false,"usgs":true,"family":"Usery","given":"E.","email":"usery@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":348886,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70006363,"text":"sir20115204 - 2011 - Quality of volatile organic compound data from groundwater and surface water for the National Water-Quality Assessment Program, October 1996&ndash;December 2008","interactions":[],"lastModifiedDate":"2017-10-14T11:36:25","indexId":"sir20115204","displayToPublicDate":"2011-12-25T09:47:00","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":"2011-5204","title":"Quality of volatile organic compound data from groundwater and surface water for the National Water-Quality Assessment Program, October 1996&ndash;December 2008","docAbstract":"<p>This report describes the quality of volatile organic compound (VOC) data collected from October 1996 to December 2008 from groundwater and surface-water sites for the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) Program. The VOC data described were collected for three NAWQA site types: (1) domestic and public-supply wells, (2) monitoring wells, and (3) surface-water sites. Contamination bias, based on the 90-percent upper confidence limit (UCL) for the 90th percentile of concentrations in field blanks, was determined for VOC samples from the three site types. A way to express this bias is that there is 90-percent confidence that this amount of contamination would be exceeded in no more than 10 percent of all samples (including environmental samples) that were collected, processed, shipped, and analyzed in the same manner as the blank samples. This report also describes how important native water rinsing may be in decreasing carryover contamination, which could be affecting field blanks.</p> <p>The VOCs can be classified into four contamination categories on the basis of the 90-percent upper confidence limit (90-percent UCL) concentration distribution in field blanks. Contamination category 1 includes compounds that were not detected in any field blanks. Contamination category 2 includes VOCs that have a 90-percent UCL concentration distribution in field blanks that is about an order of magnitude lower than the concentration distribution of the environmental samples. Contamination category 3 includes VOCs that have a 90-percent UCL concentration distribution in field blanks that is within an order of magnitude of the distribution in environmental samples. Contamination category 4 includes VOCs that have a 90-percent UCL concentration distribution in field blanks that is at least an order of magnitude larger than the concentration distribution of the environmental samples.</p> <p>Fifty-four of the 87 VOCs analyzed in samples from domestic and public-supply wells were not detected in field blanks (contamination category 1), and 33 VOC were detected in field blanks. Ten of the 33 VOCs had a 90-percent UCL concentration distribution in field blanks that was at least an order of magnitude lower than the concentration distribution in environmental samples (contamination category 2). These 10 VOCs may have had some contamination bias associated with the environmental samples, but the potential contamination bias was negligible in comparison to the environmental data; therefore, the field blanks were assumed to be representative of the sources of contamination bias affecting the environmental samples for these 10 VOCs. Seven VOCs had a 90-percent UCL concentration distribution of the field blanks that was within an order of magnitude of the concentration distribution of the environmental samples (contamination category 3). Sixteen VOCs had a 90-percent UCL concentration distribution in the field blanks that was at least an order of magnitude greater than the concentration distribution of the environmental samples (contamination category 4). Field blanks for these 16 VOCs appear to be nonrepresentative of the sources of contamination bias affecting the environmental samples because of the larger concentration distributions (and sometimes higher frequency of detection) in field blanks than in environmental samples.</p> <p>Forty-three of the 87 VOCs analyzed in samples from monitoring wells were not detected in field blanks (contamination category 1), and 44 VOCs were detected in field blanks. Eight of the 44 VOCs had a 90-percent UCL concentration distribution in field blanks that was at least an order of magnitude lower than concentrations in environmental samples (contamination category 2). These eight VOCs may have had some contamination bias associated with the environmental samples, but the potential contamination bias was negligible in comparison to the environmental data; therefore, the field blanks were assumed to be representative. Seven VOCs had a 90-percent UCL concentration distribution in field blanks that was of the same order of magnitude as the concentration distribution of the environmental samples (contamination category 3). Twenty-nine VOCs had a 90-percent UCL concentration distribution in the field blanks that was an order of magnitude greater than the distribution of the environmental samples (contamination category 4). Field blanks for these 29 VOCs appear to be nonrepresentative of the sources of contamination bias to the environmental samples.</p> <p>Fifty-four of the 87 VOCs analyzed in surface-water samples were not detected in field blanks (category 1), and 33 VOC were detected in field blanks. Sixteen of the 33 VOCs had a 90-percent UCL concentration distribution in field blanks that was at least an order of magnitude lower than the concentration distribution in environmental samples (contamination category 2). These 16 VOCs may have had some contamination bias associated with the environmental samples, but the potential contamination bias was negligible in comparison to the environmental data; therefore, the field blanks were assumed to be representative. Ten VOCs had a 90-percent UCL concentration distribution in field blanks that was similar to the concentration distribution of environmental samples (contamination category 3). Seven VOCs had a 90-percent UCL concentration distribution in the field blanks that was greater than the concentration distribution in environmental samples (contamination category 4). Field-blank samples for these seven VOCs appear to be nonrepresentative of the sources of contamination bias to the environmental samples.</p> <p>The relation between the detection of a compound in field blanks and the detection in subsequent environmental samples appears to be minimal. The median minimum percent effectiveness of native water rinsing is about 79 percent for the 19 VOCs detected in more than 5 percent of field blanks from all three site types. The minimum percent effectiveness of native water rinsing (10 percent) was for toluene in surface-water samples, likely because of the large detection frequency of toluene in surface-water samples (about 79 percent) and in the associated field-blank samples (46.5 percent).</p> <p>The VOCs that were not detected in field blanks (contamination category 1) from the three site types can be considered free of contamination bias, and various interpretations for environmental samples, such as VOC detection frequency at multiple assessment levels and comparisons of concentrations to benchmarks, are not limited for these VOCs. A censoring level for making comparisons at different assessment levels among environmental samples could be applied to concentrations of 9 VOCs in samples from domestic and public-supply wells, 16 VOCs in samples from monitoring wells, and 9 VOCs in surface-water samples to account for potential low-level contamination bias associated with these selected VOCs. Bracketing the potential contamination by comparing the detection and concentration statistics with no censoring applied to the potential for contamination bias on the basis of the 90-percent UCL for the 90th-percentile concentrations in field blanks may be useful when comparisons to benchmarks are done in a study.</p> <p>The VOCs that were not detected in field blanks (contamination category 1) from the three site types can be considered free of contamination bias, and various interpretations for environmental samples, such as VOC detection frequency at multiple assessment levels and comparisons of concentrations to benchmarks, are not limited for these VOCs. A censoring level for making comparisons at different assessment levels among environmental samples could be applied to concentrations of 9 VOCs in samples from domestic and public-supply wells, 16 VOCs in samples from monitoring wells, and 9 VOCs in surface-water samples to account for potential low-level contamination bias associated with these selected VOCs. Bracketing the potential contamination by comparing the detection and concentration statistics with no censoring applied to the potential for contamination bias on the basis of the 90-percent UCL for the 90th-percentile concentrations in field blanks may be useful when comparisons to benchmarks are done in a study.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115204","collaboration":"Prepared in cooperation with the National Water-Quality Assessment Program","usgsCitation":"Bender, D.A., Zogorski, J.S., Mueller, D.K., Rose, D.L., Martin, J.D., and Brenner, C.K., 2011, Quality of volatile organic compound data from groundwater and surface water for the National Water-Quality Assessment Program, October 1996&ndash;December 2008: U.S. Geological Survey Scientific Investigations Report 2011-5204, viii, 57 p.; Glossary; Appendices, https://doi.org/10.3133/sir20115204.","productDescription":"viii, 57 p.; Glossary; Appendices","onlineOnly":"Y","temporalStart":"1996-10-01","temporalEnd":"2008-12-31","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":116322,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5204.jpg"},{"id":112397,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5204/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a9148e4b0c8380cd801be","contributors":{"authors":[{"text":"Bender, David A. 0000-0002-1269-0948 dabender@usgs.gov","orcid":"https://orcid.org/0000-0002-1269-0948","contributorId":985,"corporation":false,"usgs":true,"family":"Bender","given":"David","email":"dabender@usgs.gov","middleInitial":"A.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":354386,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zogorski, John S. jszogors@usgs.gov","contributorId":189,"corporation":false,"usgs":true,"family":"Zogorski","given":"John","email":"jszogors@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":354385,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mueller, David K. mueller@usgs.gov","contributorId":1585,"corporation":false,"usgs":true,"family":"Mueller","given":"David","email":"mueller@usgs.gov","middleInitial":"K.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":354388,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rose, Donna L. 0000-0003-1216-9914 dlrose@usgs.gov","orcid":"https://orcid.org/0000-0003-1216-9914","contributorId":4546,"corporation":false,"usgs":true,"family":"Rose","given":"Donna","email":"dlrose@usgs.gov","middleInitial":"L.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":354389,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martin, Jeffrey D. 0000-0003-1994-5285 jdmartin@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-5285","contributorId":1066,"corporation":false,"usgs":true,"family":"Martin","given":"Jeffrey","email":"jdmartin@usgs.gov","middleInitial":"D.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":354387,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brenner, Cassandra K.","contributorId":24235,"corporation":false,"usgs":true,"family":"Brenner","given":"Cassandra","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":354390,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70171509,"text":"70171509 - 2011 - The Hydrogeology of the San Juan Mountains Chapter 5","interactions":[],"lastModifiedDate":"2019-06-21T14:55:24","indexId":"70171509","displayToPublicDate":"2011-12-23T23:45:00","publicationYear":"2011","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"Chapter 5","title":"The Hydrogeology of the San Juan Mountains Chapter 5","docAbstract":"<p>Knowledge of the occurrence, storage, and flow of groundwater in mountainous regions is limited by the lack of integrated data from wells, streams, springs, and climate. In his comprehensive treatment of the hydrogeology of the San Luis Valley, Huntley (1979) hypothesized that the underlying, fractured volcanic bedrock of the San Juan Mountains has relatively high bulk permeability and a regional-scale water table with a low hydraulic gradient. Other (some more recent) studies of fractured crystalline bedrock in mountainous terrain indicate that these rock units can act as aquifers (Kahn et al. 2008; Manning and Caine 2007; Robinson 1978; Stober and Bucher 2005). The body of recent work also suggests that the conception that fractured crystalline bedrock is of such low permeability that it constitutes a “no-flow zone” may be inappropriate. In addition to establishing a new baseline, the data presented here are used to test Huntley’s (1979) hypotheses that suggest that the San Juan Mountains may be underlain by a substantial groundwater system. With the advent of computers and digital databases, many types of publicly available data can be used to test hypotheses and provide new insights into mountain hydrogeology at the regional scale in the San Juan Mountains. Plate 16 illustrates processes that suggest several fundamental questions arising from our lack of knowledge of mountain hydrogeology. These questions include: What are the&nbsp;dynamic interrelationships among the tectonics of mountain building, climate, and groundwater, and what are the time scales over which associated processes operate? How does extreme topographic relief allow for groundwater recharge along steep surfaces rather than simply causing precipitation to run off ? How does extreme relief translate into hydraulic gradients that drive groundwater flow? Can extreme gradients drive large volumes of meteoric water deep into the Earth’s upper crust? Once in the subsurface, what are the residence times of these waters? Finally, how does complex geology, commonly associated with mountainous terrain, influence these processes and control potentially heterogeneous and tortuous flow pathways? This chapter presents a synthesis of hydrogeological data, in a reconnaissance style, at the regional scale for the San Juan Mountains. Analyses of these data shed some light on the questions posed earlier for the San Juan Mountains and on mountain hydrogeologic processes in general. These analyses are based on public digital data from geologic and topographic maps, precipitation networks, stream gauges, groundwater wells, and springs. These data can be integrated using the hydrologic cycle expressed as a mass balance between inputs and outputs. The data types noted earlier form the basic set of measurements used to explore, characterize, and quantify elements of the hydrologic cycle. This exploration at a variety of scales yields insight into the relationships among the physical geological framework, climatological and hydrological budgets, and the hydraulic properties of the major aquifers in the San Juan Mountains. Each of these factors has been broken down and investigated separately and then integrated at the end of the chapter, using a conceptual model. Although the San Juan Mountains contain extensive precious- and base-metal deposits that have led to natural and mining-related groundwater contamination, this topic is not addressed here. Interested readers should refer to the extensive body of US Geological Survey work in Gray et al. (1994), Plumlee et al. (1995), Wirt et al. (1999), Johnson and Yager (2006), Johnson et al. (2007), and Church, von Guerard, and Finger (2007). Huntley (1979) also provided a large database for regional hydro-geochemistry of the San Juan Mountains (SJM).</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The Eastern San Juan Mountains Their Ecology, Geology, and Human History","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"University Press of Colorado","publisherLocation":"Boulder, CO","isbn":"978-1-60732-084-5","usgsCitation":"Caine, J.S., and Wilson, A.B., 2011, The Hydrogeology of the San Juan Mountains Chapter 5, chap. Chapter 5 <i>of</i> The Eastern San Juan Mountains Their Ecology, Geology, and Human History, p. 79-98.","productDescription":"20 p.","startPage":"79","endPage":"98","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-003416","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":322074,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":322070,"type":{"id":15,"text":"Index Page"},"url":"https://www.upcolorado.com/university-press-of-colorado/item/1923-the-eastern-san-juan-mountains","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Colorado","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.91276550292969,\n              37.421980615353675\n            ],\n            [\n              -106.91276550292969,\n              37.496652341233364\n            ],\n            [\n              -106.75758361816406,\n              37.496652341233364\n            ],\n            [\n              -106.75758361816406,\n              37.421980615353675\n            ],\n            [\n              -106.91276550292969,\n              37.421980615353675\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","tableOfContents":"<p><br data-mce-bogus=\"1\"></p>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"575158bbe4b053f0edd03c93","contributors":{"editors":[{"text":"Blair, Robert","contributorId":70008,"corporation":false,"usgs":true,"family":"Blair","given":"Robert","affiliations":[],"preferred":false,"id":631559,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Bracksieck, George","contributorId":169938,"corporation":false,"usgs":false,"family":"Bracksieck","given":"George","email":"","affiliations":[],"preferred":false,"id":631560,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Caine, Jonathan S. 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":1272,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan","email":"jscaine@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":631533,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Anna B. 0000-0002-9737-2614 awilson@usgs.gov","orcid":"https://orcid.org/0000-0002-9737-2614","contributorId":1619,"corporation":false,"usgs":true,"family":"Wilson","given":"Anna","email":"awilson@usgs.gov","middleInitial":"B.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":631532,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70006336,"text":"sir20115222 - 2011 - Assessing controls on perched saturated zones beneath the Idaho Nuclear Technology and Engineering Center, Idaho","interactions":[],"lastModifiedDate":"2012-03-08T17:16:42","indexId":"sir20115222","displayToPublicDate":"2011-12-23T00:00:00","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":"2011-5222","title":"Assessing controls on perched saturated zones beneath the Idaho Nuclear Technology and Engineering Center, Idaho","docAbstract":"Waste byproducts associated with operations at the Idaho Nuclear Technology and Engineering Center (INTEC) have the potential to contaminate the eastern Snake River Plain (ESRP) aquifer. Recharge to the ESRP aquifer is controlled largely by the alternating stratigraphy of fractured volcanic rocks and sedimentary interbeds within the overlying vadose zone and by the availability of water at the surface. Beneath the INTEC facilities, localized zones of saturation perched on the sedimentary interbeds are of particular concern because they may facilitate accelerated transport of contaminants. The sources and timing of natural and anthropogenic recharge to the perched zones are poorly understood. Simple approaches for quantitative characterization of this complex, variably saturated flow system are needed to assess potential scenarios for contaminant transport under alternative remediation strategies. During 2009-2011, the U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Energy, employed data analysis and numerical simulations with a recently developed model of preferential flow to evaluate the sources and quantity of recharge to the perched zones. Piezometer, tensiometer, temperature, precipitation, and stream-discharge data were analyzed, with particular focus on the possibility of contributions to the perched zones from snowmelt and flow in the neighboring Big Lost River (BLR). Analysis of the timing and magnitude of subsurface dynamics indicate that streamflow provides local recharge to the shallow, intermediate, and deep perched saturated zones within 150 m of the BLR; at greater distances from the BLR the influence of streamflow on recharge is unclear. Perched water-level dynamics in most wells analyzed are consistent with findings from previous geochemical analyses, which suggest that a combination of annual snowmelt and anthropogenic sources (for example, leaky pipes and drainage ditches) contribute to recharge of shallow and intermediate perched zones throughout much of INTEC. The source-responsive fluxes model was parameterized to simulate recharge via preferential flow associated with intermittent episodes of streamflow in the BLR. The simulations correspond reasonably well to the observed hydrologic response within the shallow perched zone. Good model performance indicates that source-responsive flow through a limited number of connected fractures contributes substantially to the perched-zone dynamics. The agreement between simulated and observed perched-zone dynamics suggest that the source-responsive fluxes model can provide a valuable tool for quantifying rapid preferential flow processes that may result from different land management scenarios.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115222","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Mirus, B.B., Perkins, K.S., and Nimmo, J.R., 2011, Assessing controls on perched saturated zones beneath the Idaho Nuclear Technology and Engineering Center, Idaho: U.S. Geological Survey Scientific Investigations Report 2011-5222, vi, 20 p., https://doi.org/10.3133/sir20115222.","productDescription":"vi, 20 p.","onlineOnly":"Y","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":116400,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5222.gif"},{"id":112312,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5222/","linkFileType":{"id":5,"text":"html"}}],"state":"Idaho","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059edd0e4b0c8380cd49a0f","contributors":{"authors":[{"text":"Mirus, Benjamin B. 0000-0001-5550-014X bbmirus@usgs.gov","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":4064,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin","email":"bbmirus@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":354320,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perkins, Kim S.","contributorId":106963,"corporation":false,"usgs":true,"family":"Perkins","given":"Kim","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":354321,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nimmo, John R. 0000-0001-8191-1727 jrnimmo@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-1727","contributorId":757,"corporation":false,"usgs":true,"family":"Nimmo","given":"John","email":"jrnimmo@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":354319,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70006339,"text":"sir20115225 - 2011 - Toxicity of nickel-spiked freshwater sediments to benthic invertebrates-Spiking methodology, species sensitivity, and nickel bioavailability","interactions":[],"lastModifiedDate":"2019-07-19T08:42:43","indexId":"sir20115225","displayToPublicDate":"2011-12-23T00:00:00","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":"2011-5225","title":"Toxicity of nickel-spiked freshwater sediments to benthic invertebrates-Spiking methodology, species sensitivity, and nickel bioavailability","docAbstract":"This report summarizes data from studies of the toxicity and bioavailability of nickel in nickel-spiked freshwater sediments. The goal of these studies was to generate toxicity and chemistry data to support development of broadly applicable sediment quality guidelines for nickel. The studies were conducted as three tasks, which are presented here as three chapters: Task 1, Development of methods for preparation and toxicity testing of nickel-spiked freshwater sediments; Task 2, Sensitivity of benthic invertebrates to toxicity of nickel-spiked freshwater sediments; and Task 3, Effect of sediment characteristics on nickel bioavailability. Appendices with additional methodological details and raw chemistry and toxicity data for the three tasks are available online at http://pubs.usgs.gov/sir/2011/5225/downloads/.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115225","collaboration":"Prepared in cooperation with the Nickel Producers Environmental Research Association","usgsCitation":"Besser, J.M., Brumbaugh, W.G., Kemble, N.E., Ivey, C.D., Kunz, J.L., Ingersoll, C.G., and Rudel, D., 2011, Toxicity of nickel-spiked freshwater sediments to benthic invertebrates-Spiking methodology, species sensitivity, and nickel bioavailability: U.S. Geological Survey Scientific Investigations Report 2011-5225, Report: x, 51 p.; Appendixes: 1-3, https://doi.org/10.3133/sir20115225.","productDescription":"Report: x, 51 p.; Appendixes: 1-3","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":332257,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2011/5225/downloads/appendix-1.xls","text":"Appendix 1"},{"id":332258,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2011/5225/downloads/appendix-2.xls","text":"Appendix 2"},{"id":332256,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5225/pdf/sir2011-5225.pdf"},{"id":332259,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2011/5225/downloads/appendix-3.xls","text":"Appendix 3"},{"id":112313,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5225/","linkFileType":{"id":5,"text":"html"}},{"id":116786,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5225.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bb608e4b08c986b326a0c","contributors":{"authors":[{"text":"Besser, John M. 0000-0002-9464-2244 jbesser@usgs.gov","orcid":"https://orcid.org/0000-0002-9464-2244","contributorId":2073,"corporation":false,"usgs":true,"family":"Besser","given":"John","email":"jbesser@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":354327,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":354325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kemble, Nile E. 0000-0002-3608-0538 nkemble@usgs.gov","orcid":"https://orcid.org/0000-0002-3608-0538","contributorId":2626,"corporation":false,"usgs":true,"family":"Kemble","given":"Nile","email":"nkemble@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":354328,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":354329,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kunz, James L. 0000-0002-1027-158X jkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-1027-158X","contributorId":3309,"corporation":false,"usgs":true,"family":"Kunz","given":"James","email":"jkunz@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":354330,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":354326,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rudel, David","contributorId":12181,"corporation":false,"usgs":true,"family":"Rudel","given":"David","email":"","affiliations":[],"preferred":false,"id":354331,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70006343,"text":"70006343 - 2011 - Spatial capture-recapture models for search-encounter data","interactions":[],"lastModifiedDate":"2021-05-18T15:12:59.888696","indexId":"70006343","displayToPublicDate":"2011-12-22T12:30:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Spatial capture-recapture models for search-encounter data","docAbstract":"<p><b>1.</b> Spatial capture&ndash;recapture models make use of auxiliary data on capture location to provide density estimates for animal populations. Previously, models have been developed primarily for fixed trap arrays which define the observable locations of individuals by a set of discrete points.</p> <p><b>2.</b> Here, we develop a class of models for 'search-encounter' data, i.e. for detections of recognizable individuals in continuous space, not restricted to trap locations. In our hierarchical model, detection probability is related to the average distance between individual location and the survey path. The locations are allowed to change over time owing to movements of individuals, and individual locations are related formally by a model describing individual activity or home range centre which is itself regarded as a latent variable in the model. We provide a Bayesian analysis of the model in WinBUGS, and develop a custom MCMC algorithm in the R language.</p> <p><b>3.</b> The model is applied to simulated data and to territory mapping data for the Willow Tit from the Swiss Breeding Bird Survey MHB. While the observed density was 15 territories per nominal 1 km<sup>2</sup> plot of unknown effective sample area, the model produced a density estimate of 21&#8729;12 territories per square km (95% posterior interval: 17&ndash;26).</p> <p><b>4.</b> Spatial capture&ndash;recapture models are relevant to virtually all animal population studies that seek to estimate population size or density, yet existing models have been proposed mainly for conventional sampling using arrays of traps. Our model for search-encounter data, where the spatial pattern of searching can be arbitrary and may change over occasions, greatly expands the scope and utility of spatial capture&ndash;recapture models.</p>","language":"English","publisher":"British Ecological Society","publisherLocation":"London, England","doi":"10.1111/j.2041-210X.2011.00116.x","usgsCitation":"Royle, J., Kery, M., and Guelat, J., 2011, Spatial capture-recapture models for search-encounter data: Methods in Ecology and Evolution, v. 2, no. 6, p. 602-611, https://doi.org/10.1111/j.2041-210X.2011.00116.x.","productDescription":"10 p.","startPage":"602","endPage":"611","numberOfPages":"10","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":474840,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.2041-210x.2011.00116.x","text":"Publisher Index Page"},{"id":204258,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"6","noUsgsAuthors":false,"publicationDate":"2011-05-18","publicationStatus":"PW","scienceBaseUri":"505b945de4b08c986b31aa2f","contributors":{"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":354340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kery, Marc","contributorId":38680,"corporation":false,"usgs":true,"family":"Kery","given":"Marc","affiliations":[],"preferred":false,"id":354339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guelat, Jerome","contributorId":27991,"corporation":false,"usgs":true,"family":"Guelat","given":"Jerome","email":"","affiliations":[],"preferred":false,"id":354338,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70006328,"text":"sir20115223 - 2011 - Collection, processing, and interpretation of ground-penetrating radar data to determine sediment thickness at selected locations in Deep Creek Lake, Garrett County, Maryland, 2007","interactions":[],"lastModifiedDate":"2023-03-09T20:20:25.971114","indexId":"sir20115223","displayToPublicDate":"2011-12-22T00:00:00","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":"2011-5223","title":"Collection, processing, and interpretation of ground-penetrating radar data to determine sediment thickness at selected locations in Deep Creek Lake, Garrett County, Maryland, 2007","docAbstract":"The U.S. Geological Survey collected geophysical data in Deep Creek Lake in Garrett County, Maryland, between September 17 through October 4, 2007 to assist the Maryland Department of Natural Resources to better manage resources of the Lake. The objectives of the geophysical surveys were to provide estimates of sediment thickness in shallow areas around the Lake and to test the usefulness of three geophysical methods in this setting. Ground-penetrating radar (GPR), continuous seismic-reflection profiling (CSP), and continuous resistivity profiling (CRP) were attempted. Nearly 90 miles of GPR radar data and over 70 miles of CSP data were collected throughout the study area. During field deployment and testing, CRP was determined not to be practical and was not used on a large scale. Sediment accumulation generally could be observed in the radar profiles in the shallow coves. In some seismic profiles, a thin layer of sediment could be observed at the water bottom. The radar profiles appeared to be better than the seismic profiles for the determination of sediment thickness. Although only selected data profiles were processed, all data were archived for future interpretation.\nThis investigation focused on selected regions of the study area, particularly in the coves where sediment accumulations were presumed to be thickest. GPR was the most useful tool for interpreting sediment thickness, especially in these shallow coves. The radar profiles were interpreted for two surfaces of interest-the water bottom, which was defined as the \"2007 horizon,\" and the interface between Lake sediments and the original Lake bottom, which was defined as the \"1925 horizon\"-corresponding to the year the Lake was impounded. The ground-penetrating radar data were interpreted on the basis of characteristics of the reflectors. The sediments that had accumulated in the impounded Lake were characterized by laminated, parallel reflections, whereas the subsurface below the original Lake bottom was characterized by more discontinuous and chaotic reflections, often with diffractions indicating cobbles or boulders. The reflectors were picked manually along the water bottom and along the interface between the Lake sediments and the pre-Lake sediments. A simple graphic approach was used to convert traveltimes to depth through water and depth through saturated sediments using velocities of the soundwaves through the water and the saturated sediments. Nineteen cross sections were processed and interpreted in 9 coves around Deep Creek Lake, and the difference between the 2007 horizon and the 1925 horizon was examined. In most areas, GPR data indicate a layer of sediment between 1 and 7 feet thick. When multiple cross sections from a single cove were compared, the cross sections indicated that sediment thickness decreased toward the center of the Lake.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115223","collaboration":"Prepared in cooperation with the Maryland Department of Natural Resources","usgsCitation":"Banks, W.S., and Johnson, C.D., 2011, Collection, processing, and interpretation of ground-penetrating radar data to determine sediment thickness at selected locations in Deep Creek Lake, Garrett County, Maryland, 2007: U.S. Geological Survey Scientific Investigations Report 2011-5223, v, 16 p.; Appendix A, https://doi.org/10.3133/sir20115223.","productDescription":"v, 16 p.; Appendix A","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":116864,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5223.gif"},{"id":112310,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5223/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Maryland","county":"Garrett County","otherGeospatial":"Deep Creek Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -79.43416666666667,39.43333333333333 ], [ -79.43416666666667,39.61666666666667 ], [ -79.18333333333334,39.61666666666667 ], [ -79.18333333333334,39.43333333333333 ], [ -79.43416666666667,39.43333333333333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f7b3e4b0c8380cd4cc66","contributors":{"authors":[{"text":"Banks, William S.L.","contributorId":35281,"corporation":false,"usgs":true,"family":"Banks","given":"William","email":"","middleInitial":"S.L.","affiliations":[],"preferred":false,"id":354313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Carole D. 0000-0001-6941-1578 cjohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-6941-1578","contributorId":1891,"corporation":false,"usgs":true,"family":"Johnson","given":"Carole","email":"cjohnson@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":354312,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70006326,"text":"ofr20111299 - 2011 - Results of time-domain electromagnetic soundings in Miami-Dade and southern Broward Counties, Florida","interactions":[],"lastModifiedDate":"2013-01-28T15:52:17","indexId":"ofr20111299","displayToPublicDate":"2011-12-21T00:00:00","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":"2011-1299","title":"Results of time-domain electromagnetic soundings in Miami-Dade and southern Broward Counties, Florida","docAbstract":"<p>Time-domain electromagnetic (TEM) soundings were made in Miami-Dade and southern Broward Counties to aid in mapping the landward extent of saltwater in the Biscayne aquifer. A total of 79 soundings were collected in settings ranging from urban to undeveloped land, with some of the former posing problems of land access and interference from anthropogenic features. TEM soundings combined with monitoring-well data were used to determine if the saltwater front had moved since the last time it was mapped, to provide additional spatial coverage where existing monitoring wells were insufficient, and to help interpret a previously collected helicopter electromagnetic (HEM) survey flown in the southernmost portion of the study area.</p> <p>TEM soundings were interpreted as layered resistivity-depth models. Using information from well logs and water-quality data, the resistivity of the freshwater saturated Biscayne aquifer is expected to be above 30 ohm-meters, and the saltwater-saturated aquifer will have resistivities of less than 10 ohm-meters allowing determination of water quality from the TEM interpretations. TEM models from 29 soundings were compared to electromagnetic induction logs collected in nearby monitoring wells. In general, the agreement of these results was very good, giving confidence in the use of the TEM data for mapping saltwater encroachment.</p>","language":"English","publisher":"U.S. Geological Society","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111299","usgsCitation":"Fitterman, D.V., and Prinos, S.T., 2011, Results of time-domain electromagnetic soundings in Miami-Dade and southern Broward Counties, Florida: U.S. Geological Survey Open-File Report 2011-1299, ix, 289 p.; Supplemental Files Download, https://doi.org/10.3133/ofr20111299.","productDescription":"ix, 289 p.; Supplemental Files Download","onlineOnly":"Y","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":116863,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1299.png"},{"id":112309,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1299/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","city":"Miami-dade;Broward","otherGeospatial":"Biscayne Aquifer","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505aabf0e4b0c8380cd86a81","contributors":{"authors":[{"text":"Fitterman, David V. dfitterman@usgs.gov","contributorId":1106,"corporation":false,"usgs":true,"family":"Fitterman","given":"David","email":"dfitterman@usgs.gov","middleInitial":"V.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":354310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prinos, Scott T. 0000-0002-5776-8956 stprinos@usgs.gov","orcid":"https://orcid.org/0000-0002-5776-8956","contributorId":4045,"corporation":false,"usgs":true,"family":"Prinos","given":"Scott","email":"stprinos@usgs.gov","middleInitial":"T.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"preferred":true,"id":354311,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70006295,"text":"sir20115154 - 2011 - Status and understanding of groundwater quality in the San Diego Drainages Hydrogeologic Province, 2004: California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"sir20115154","displayToPublicDate":"2011-12-20T00:00:00","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":"2011-5154","title":"Status and understanding of groundwater quality in the San Diego Drainages Hydrogeologic Province, 2004: California GAMA Priority Basin Project","docAbstract":"Groundwater quality in the approximately 3,900-square-mile (mi<sup>2</sup>) San Diego Drainages Hydrogeologic Province (hereinafter San Diego) study unit was investigated from May through July 2004 as part of the Priority Basin Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The study unit is located in southwestern California in the counties of San Diego, Riverside, and Orange. The GAMA Priority Basin Project is being conducted by the California State Water Resources Control Board in collaboration with the U.S. Geological Survey (USGS) and the Lawrence Livermore National Laboratory.  The GAMA San Diego study was designed to provide a statistically robust assessment of untreated-groundwater quality within the primary aquifer systems. The assessment is based on water-quality and ancillary data collected by the USGS from 58 wells in 2004 and water-quality data from the California Department of Public Health (CDPH) database. The primary aquifer systems (hereinafter referred to as the primary aquifers) were defined by the depth interval of the wells listed in the California Department of Public Health (CDPH) database for the San Diego study unit. The San Diego study unit consisted of four study areas: Temecula Valley (140 mi<sup>2</sup>), Warner Valley (34 mi<sup>2</sup>), Alluvial Basins (166 mi<sup>2</sup>), and Hard Rock (850 mi<sup>2</sup>). The quality of groundwater in shallow or deep water-bearing zones may differ from that in the primary aquifers. For example, shallow groundwater may be more vulnerable to surficial contamination than groundwater in deep water-bearing zones.  This study had two components: the status assessment and the understanding assessment. The first component of this study-the status assessment of the current quality of the groundwater resource-was assessed by using data from samples analyzed for volatile organic compounds (VOC), pesticides, and naturally occurring inorganic constituents, such as major ions and trace elements. The status assessment is intended to characterize the quality of groundwater resources within the primary aquifers of the San Diego study unit, not the treated drinking water delivered to consumers by water purveyors. The second component of this study-the understanding assessment-identified the natural and human factors that affect groundwater quality by evaluating land use, well construction, and geochemical conditions of the aquifer. Results from these evaluations were used to help explain the occurrence and distribution of selected constituents in the study unit.  Relative-concentrations (sample concentration divided by benchmark concentration) were used as the primary metric for relating concentrations of constituents in groundwater samples to water-quality benchmarks for those constituents that have Federal and (or) California benchmarks. For organic and special-interest constituents, relative-concentrations were classified as high (> 1.0), moderate (> 0.1 and &le;1.0), and low (&le;0.1). For inorganic constituents, relative concentrations were classified as high (> 1.0), moderate (> 0.5 and &le;1.0), and low (&le;0.5). Grid-based and spatially weighted approaches were then used to evaluate the proportion of the primary aquifers (aquifer-scale proportions) with high, moderate, and low relative-concentrations for individual compounds and classes of constituents.  One or more of the inorganic constituents with health-based benchmarks were high (relative to those benchmarks) in 17.6 percent of the primary aquifers in the Temecula Valley, Warner Valley, and Alluvial Basins study areas (hereinafter also collectively referred to as the Alluvial Fill study areas because they are composed of alluvial fill aquifers), and in 25.0 percent of the Hard Rock study area. Inorganic constituents with health-based benchmarks that were frequently detected at high relative-concentrations included vanadium (V), arsenic (As), and boron (B). Vanadium and As concentrations were not significantly correlated to either urban or agricultural land use indicating natural sources as the primary contributors of these constituents to groundwater. The positive correlation of B concentration to urban land-use was significant which indicates that anthropogenic activities are a contributing source of B to groundwater. The correlation of V, As and B concentrations to pH was positive, indicating that in alkaline groundwater these constituents are being desorbed from, or being inhibited from adsorbing to, particle surfaces.  Inorganic constituents with aesthetic benchmarks that were detected at high relative-concentrations include manganese (Mn), iron (Fe), and total dissolved solids (TDS). In the Alluvial Fill study areas, Mn and TDS were detected at high relative-concentrations in 13.7 percent of the primary aquifers, and Fe in 6.9 percent. In the Hard Rock study area, Mn was detected at high relative-concentrations in 33.3 percent of the primary aquifers, and TDS in 16.7 percent; Fe was not detected at high relative-concentrations. Total dissolved solids concentrations were significantly correlated to agricultural land use suggesting that agricultural practices are a contributing source of TDS to groundwater. Manganese and Fe concentrations were highest in groundwater with low dissolved oxygen and pH indicating that the reductive dissolution of oxyhydroxides may be an important mechanism for the mobilization of Mn and Fe in groundwater. TDS concentrations were highest in shallow wells and in modern (< 50 yrs) groundwater which indicates anthropogenic activities as a source of TDS concentrations in groundwater.  The relative-concentrations of organic constituents with health-based benchmarks were high in 3.0 percent of the primary aquifers in the Alluvial Fill study areas. A single detection in the Alluvial Basins study area of the discontinued gasoline oxygenate methyl tert-butyl ether (MTBE) was the only organic constituent detected at a high relative-concentration; high relative-concentrations of these constituents were not detected in the Hard Rock study area. Twelve of 88 VOCs and 14 of 123 pesticides and pesticide degradates analyzed in grid wells were detected. Chloroform was the only VOC detected in more than 10 percent of the grid wells. The herbicides simazine, atrazine, and prometon were each detected in greater than 10 percent of the grid wells. Perchlorate was detected in 22 percent of the grid wells sampled.  The understanding assessment showed a significant correlation of trihalomethanes (THMs) and solvents to urban land-use, indicating that detections of these constituents are more likely to occur in groundwater underlying urbanized areas of the study unit. MTBE concentrations were negatively correlated to the distance from the nearest leaking underground fuel tank, indicating that point sources are the most significant contributing factor for MTBE concentrations to groundwater in the study unit. The positive correlation of THM and herbicide concentrations to modern groundwater was significant, as was the negative correlation of herbicide concentrations to pH and anoxic groundwater. The negative correlation of herbicides to pH and anoxic groundwater was likely due to the fact that these constituents were detected more frequently in shallow wells where groundwater conditions tend to be oxic with relatively low pH.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115154","collaboration":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program, prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Wright, M.T., and Belitz, K., 2011, Status and understanding of groundwater quality in the San Diego Drainages Hydrogeologic Province, 2004: California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2011-5154, x, 71 p.; Appendices, https://doi.org/10.3133/sir20115154.","productDescription":"x, 71 p.; Appendices","temporalStart":"2004-05-01","temporalEnd":"2004-07-31","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":116784,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5154.jpg"},{"id":112133,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5154/","linkFileType":{"id":5,"text":"html"}}],"projection":"Albers Equal Area Conic Projection","country":"United States","state":"California","county":"Orange;Riverside;And San Diego","city":"San Diego","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125,32 ], [ -125,42 ], [ -114,42 ], [ -114,32 ], [ -125,32 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b979be4b08c986b31bb70","contributors":{"authors":[{"text":"Wright, Michael T. 0000-0003-0653-6466 mtwright@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-6466","contributorId":1508,"corporation":false,"usgs":true,"family":"Wright","given":"Michael","email":"mtwright@usgs.gov","middleInitial":"T.","affiliations":[],"preferred":false,"id":354249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":354248,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70006303,"text":"70006303 - 2011 - Groundwater quality in the San Diego Drainages Hydrogeologic Province, California","interactions":[],"lastModifiedDate":"2022-04-19T21:14:52.589233","indexId":"70006303","displayToPublicDate":"2011-12-20T00:00:00","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":"2011-3111","title":"Groundwater quality in the San Diego Drainages Hydrogeologic Province, California","docAbstract":"More than 40 percent of California's drinking water is from groundwater. To protect this vital resource, the State of California created the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The Priority Basin Project of the GAMA Program provides a comprehensive assessment of the State's groundwater quality and increases public access to groundwater-quality information. The San Diego Drainages Hydrogeologic Province (hereinafter referred to as San Diego) is one of the study units being evaluated.  The San Diego study unit is approximately 3,900 square miles and consists of the Temecula Valley, Warner Valley, and 12 other alluvial basins (California Department of Water Resources, 2003). The study unit also consists of all areas outside defined groundwater basins that are within 3 kilometers of a public-supply well. The study unit was separated, based primarily on hydrogeologic settings, into four study areas: Temecula Valley, Warner Valley, Alluvial Basins, and Hard Rock (Wright and others, 2005). The sampling density for the Hard Rock study area, which consists of areas outside of groundwater basins, was much lower than for the other study areas. Consequently, aquifer proportions for the Hard Rock study area are not used to calculate the aquifer proportions shown by the pie charts. An assessment of groundwater quality for the Hard Rock study area can be found in Wright and Belitz, 2011.  The temperatures in the coastal part of the study unit are mild with dry summers, moist winters, and an average annual rainfall of about 10 inches. The temperatures in the mountainous eastern part of the study unit are cooler than in the coastal part, with an annual precipitation of about 45 inches that occurs mostly in the winter. The primary aquifers consist of Quaternary-age alluvium and weathered bedrock in the Temecula Valley, Warner Valley, and Alluvial Basins study areas, whereas in the Hard Rock study area the primary aquifers consist mainly of fractured and decomposed granite of Mesozoic age. The primary aquifers are defined as those parts of the aquifers corresponding to the perforated intervals of wells listed in the California Department of Public Health (CDPH) database. Public-supply wells typically are drilled to depths between 200 and 700 feet, consist of solid casing from the land surface to a depth of about 60 to 170 feet, and are perforated, or consist of an open hole, below the solid casing. Water quality in the shallow and deep parts of the aquifer system may differ from water quality in the primary aquifers.  Municipal water use accounts for approximately 70 percent of water used in the study unit; the majority of the remainder is used for agriculture, industry, and commerce. Groundwater accounts for approximately 8 percent of the municipal supply, and surface water, the majority of which is imported, accounts for the rest. Recharge to groundwater occurs through stream-channel infiltration from rivers and their tributaries, infiltration in engineered recharge basins, and infiltration of water from precipitation and irrigation. The primary source of discharge is water pumped from wells.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70006303","collaboration":"U.S. Geological Survey and the California State Water Resources Control Board","usgsCitation":"Wright, M.T., and Belitz, K., 2011, Groundwater quality in the San Diego Drainages Hydrogeologic Province, California: U.S. Geological Survey Fact Sheet 2011-3111, 4 p., https://doi.org/10.3133/70006303.","productDescription":"4 p.","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":116882,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2011_3111.png"},{"id":112173,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2011/3111/","linkFileType":{"id":5,"text":"html"}},{"id":399135,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_96350.htm"}],"country":"United States","state":"California","county":"Orange County, Riverside County, San Diego County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.8053,\n              32.5344\n            ],\n            [\n              -116.2964,\n              32.5344\n            ],\n            [\n              -116.2964,\n              33.7053\n            ],\n            [\n              -117.8053,\n              33.7053\n            ],\n            [\n              -117.8053,\n              32.5344\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a2db7e4b0c8380cd5bfca","contributors":{"authors":[{"text":"Wright, Michael T. 0000-0003-0653-6466 mtwright@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-6466","contributorId":1508,"corporation":false,"usgs":true,"family":"Wright","given":"Michael","email":"mtwright@usgs.gov","middleInitial":"T.","affiliations":[],"preferred":false,"id":354259,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":354258,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70004815,"text":"70004815 - 2011 - Tamarisk biocontrol using tamarisk beetles: Potential consequences for riparian birds in the southwestern United States","interactions":[],"lastModifiedDate":"2021-05-21T18:28:26.440416","indexId":"70004815","displayToPublicDate":"2011-12-18T14:25:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Tamarisk biocontrol using tamarisk beetles: Potential consequences for riparian birds in the southwestern United States","docAbstract":"<p>The tamarisk beetle (<i>Diorhabda</i> spp.), a non-native biocontrol agent, has been introduced to eradicate tamarisk (<i>Tamarix</i> spp.), a genus of non-native tree that has become a dominant component of riparian woodlands in the southwestern United States. Tamarisk beetles have the potential to spread widely and defoliate large expanses of tamarisk habitat, but the effects of such a widespread loss of riparian vegetation on birds remains unknown. We reviewed literature on the effects of other defoliating insects on birds to investigate the potential for tamarisk beetles to affect birds positively or negatively by changing food abundance and vegetation structure. We then combined data on the temporal patterns of tamarisk defoliation by beetles with nest productivity of a well-studied riparian obligate, the Southwestern Willow Flycatcher (<i>Empidonax traillii extimus</i>), to simulate the potential demographic consequences of beetle defoliation on breeding riparian birds in both the short and long term. Our results highlight that the effects of tamarisk biocontrol on birds will likely vary by species and population, depending upon its sensitivity to seasonal defoliation by beetles and net loss of riparian habitat due to tamarisk mortality. Species with restricted distributions that include areas dominated by tamarisk may be negatively affected both in the short and long term. The rate of regeneration and/or restoration of native cottonwoods (<i>Populus</i> spp.) and willows (<i>Salix</i> spp.) relative to the rate of tamarisk loss will be critical in determining the long-term effect of this large-scale ecological experiment.</p>","language":"English","publisher":"University of California Press","publisherLocation":"Berkeley, CA","doi":"10.1525/cond.2011.090226","usgsCitation":"Paxton, E.H., Theimer, T.C., and Sogge, M.K., 2011, Tamarisk biocontrol using tamarisk beetles: Potential consequences for riparian birds in the southwestern United States: The Condor, v. 113, no. 2, p. 255-265, https://doi.org/10.1525/cond.2011.090226.","productDescription":"11 p.","startPage":"255","endPage":"265","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":474848,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1525/cond.2011.090226","text":"Publisher Index Page"},{"id":204390,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.85107421875,\n              32.54681317351514\n            ],\n            [\n              -110.98388671874999,\n              31.259769987394286\n            ],\n            [\n              -108.17138671875,\n              31.3348710339506\n            ],\n            [\n              -108.1494140625,\n              31.74685416292141\n            ],\n            [\n              -102.919921875,\n              32.02670629333614\n            ],\n            [\n              -102.98583984374999,\n              37.03763967977139\n            ],\n            [\n              -101.84326171875,\n              37.020098201368114\n            ],\n            [\n              -101.97509765625,\n              41.09591205639546\n            ],\n            [\n              -110.98388671874999,\n              41.04621681452063\n            ],\n            [\n              -111.07177734375,\n              42.08191667830631\n            ],\n            [\n              -114.19189453125,\n              42.01665183556825\n            ],\n            [\n              -114.0380859375,\n              36.26199220445664\n            ],\n            [\n              -114.2138671875,\n              35.99578538642032\n            ],\n            [\n              -114.63134765625001,\n              36.13787471840729\n            ],\n            [\n              -114.6533203125,\n              35.04798673426734\n            ],\n            [\n              -114.2578125,\n              34.30714385628804\n            ],\n            [\n              -114.6533203125,\n              33.17434155100208\n            ],\n            [\n              -114.85107421875,\n              32.54681317351514\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"113","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505ba3c8e4b08c986b31feb8","contributors":{"authors":[{"text":"Paxton, Eben H. 0000-0001-5578-7689","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":19640,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben","email":"","middleInitial":"H.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":351402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Theimer, Tad C.","contributorId":72073,"corporation":false,"usgs":true,"family":"Theimer","given":"Tad","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":351403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sogge, Mark K. 0000-0002-8337-5689 mark_sogge@usgs.gov","orcid":"https://orcid.org/0000-0002-8337-5689","contributorId":3710,"corporation":false,"usgs":true,"family":"Sogge","given":"Mark","email":"mark_sogge@usgs.gov","middleInitial":"K.","affiliations":[{"id":5079,"text":"Pacific Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":351401,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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