{"pageNumber":"672","pageRowStart":"16775","pageSize":"25","recordCount":46670,"records":[{"id":70004524,"text":"sir20115069 - 2011 - Geologic framework and hydrogeologic characteristics in the southern part of the Rancho Diana Natural Area, northern Bexar County, Texas, 2008-10","interactions":[],"lastModifiedDate":"2017-03-29T16:07:20","indexId":"sir20115069","displayToPublicDate":"2011-05-31T10:01:04","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":"2011-5069","title":"Geologic framework and hydrogeologic characteristics in the southern part of the Rancho Diana Natural Area, northern Bexar County, Texas, 2008-10","docAbstract":"<p>The area designated by the city of San Antonio as the Rancho Diana Natural Area is in northern Bexar County, near San Antonio, Texas. During 2008-10, the U.S. Geological Survey, in cooperation with the city of San Antonio, documented the geologic framework and mapped the hydrogeologic characteristics for the southern part of the Rancho Diana Natural Area. The geologic framework of the study area and its hydrogeologic characteristics were documented using field observations and information from previously published reports. Many of the geologic and hydrogeologic features were found by making field observations through the dense vegetation along gridlines spaced approximately 25 feet apart and documenting the features as they were located. Surface geologic features were identified and hydrogeologic features such as caves, sinkholes, and areas of solutionally enlarged porosity were located using hand-held Global Positioning System units. The location data were used to create a map of the hydrogeologic subdivisions and the location of karst features. The outcrops of the Edwards and Trinity aquifer recharge zones were mapped by using hydrogeologic subdivisions modified from previous reports. All rocks exposed within the study area are of sedimentary origin and Lower Cretaceous in age. The valley floor is formed in the cavernous member of the upper Glen Rose Limestone of the Trinity Group. The hills are composed of the basal nodular member, dolomitic member, Kirschberg evaporite member, and grainstone member of the Kainer Formation of the Edwards Group. Field observations made during this study of the exposed formations and members indicate that the formations and members typically are composed of mudstones, wackestones, packstones, grainstones, and argillaceous limestones, along with marls. The upper Glen Rose Limestone is approximately 410 to 450 feet thick but only the upper 70 feet is exposed in the study area. The Kainer Formation is approximately 255 feet thick in the study area and is composed of, in ascending order, the basal nodular member, dolomitic member, Kirschberg evaporite member, and grainstone member. The Edwards and Trinity aquifers contain a combination of fabric-selective and not-fabric-selective porosities. Porosity types observed in the study area that can increase the effective porosity and increase permeability include solutionally enlarged caves, sinkholes, fractures, bedding planes, channels, molds and vugs. Caves found during hydrogeologic mapping might have been spring discharge points, but sufficient downcutting over geologic time in the rocks has occurred so that springs discharge at lower elevations near the creek channel. The mapped caves, sinkholes, and other areas of solutionally enlarged porosity might facilitate recharge during large storm events when runoff occurs on the hillsides; additional areally distributed recharge in the study area occurs as a result of infiltration.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115069","collaboration":"In cooperation with the City of San Antonio","usgsCitation":"Clark, A.K., and Morris, R., 2011, Geologic framework and hydrogeologic characteristics in the southern part of the Rancho Diana Natural Area, northern Bexar County, Texas, 2008-10: U.S. Geological Survey Scientific Investigations Report 2011-5069, v, 19 p., https://doi.org/10.3133/sir20115069.","productDescription":"v, 19 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2008-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":116841,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5069.jpg"},{"id":21820,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5069/","linkFileType":{"id":5,"text":"html"}},{"id":338706,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5069/pdf/sir2011-5069.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Texas","county":"Bexar","otherGeospatial":"Rancho Diana Natural Area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -98.67679595947266,\n              29.61763959537609\n            ],\n            [\n              -98.68091583251953,\n              29.61465489947712\n            ],\n            [\n              -98.68640899658203,\n              29.608685242542364\n            ],\n            [\n              -98.68881225585938,\n              29.59883453582689\n            ],\n            [\n              -98.68331909179688,\n              29.59077415103838\n            ],\n            [\n              -98.67610931396484,\n              29.585997322833492\n            ],\n            [\n              -98.66546630859375,\n              29.58629588122112\n            ],\n            [\n              -98.65585327148438,\n              29.5922668634766\n            ],\n            [\n              -98.6517333984375,\n              29.602118211647333\n            ],\n            [\n              -98.64212036132812,\n              29.612267079123548\n            ],\n            [\n              -98.64280700683592,\n              29.622713375554916\n            ],\n            [\n              -98.64967346191406,\n              29.626891590943814\n            ],\n            [\n              -98.65791320800781,\n              29.62629471363916\n            ],\n            [\n              -98.66752624511719,\n              29.62539939105201\n            ],\n            [\n              -98.67233276367188,\n              29.622414924968727\n            ],\n            [\n              -98.67679595947266,\n              29.61763959537609\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b15e4b07f02db6a4819","contributors":{"authors":[{"text":"Clark, Allan K. 0000-0003-0099-1521 akclark@usgs.gov","orcid":"https://orcid.org/0000-0003-0099-1521","contributorId":1279,"corporation":false,"usgs":true,"family":"Clark","given":"Allan","email":"akclark@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":350563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morris, Robert R. 0000-0001-7504-3732","orcid":"https://orcid.org/0000-0001-7504-3732","contributorId":106213,"corporation":false,"usgs":true,"family":"Morris","given":"Robert R.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":350564,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70173540,"text":"70173540 - 2011 - Trends in marine debris in the U.S. Caribbean and the Gulf of Mexico, 1996-2003","interactions":[],"lastModifiedDate":"2016-06-22T15:46:15","indexId":"70173540","displayToPublicDate":"2011-05-31T05:30:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2358,"text":"Journal of Integrative Plant Biology","active":true,"publicationSubtype":{"id":10}},"title":"Trends in marine debris in the U.S. Caribbean and the Gulf of Mexico, 1996-2003","docAbstract":"<p>Marine debris is a widespread and globally recognized problem. Sound information is necessary to understand the extent of the problem and to inform resource managers and policy makers about potential mitigation strategies. Although there are many short-term studies on marine debris, a longer-term perspective and the ability to compare among regions has heretofore been missing in the U.S. Caribbean and the Gulf of Mexico. We used data from a national beach monitoring program to evaluate and compare amounts, composition, and trends of indicator marine debris in the U.S. Caribbean (Puerto Rico and the U.S. Virgin Islands) and the Gulf of Mexico from 1996 to 2003. Indicator items provided a standardized set that all surveys collected; each was assigned a probable source: ocean-based, land-based, or general-source. Probable ocean-based debris was related to activities such as recreational boating/fishing, commercial fishing and activities on oil/gas platforms. Probable land-based debris was related to land-based recreation and sewer systems. General-source debris represented plastic items that can come from either ocean- or land-based sources; these items were plastic bags, strapping bands, and plastic bottles (excluding motor oil containers). Debris loads were similar between the U.S. Caribbean and the western Gulf of Mexico; however, debris composition on U.S. Caribbean beaches was dominated by land-based indicators while the western Gulf of Mexico was dominated by ocean-based indicators. Beaches along the eastern Gulf of Mexico had the lowest counts of debris; composition was dominated by land-based indicators, similar to that found for the U.S. Caribbean. Debris loads on beaches in the Gulf of Mexico are likely affected by Gulf circulation patterns, reducing loads in the eastern Gulf and increasing loads in the western Gulf. Over the seven years of monitoring, we found a large linear decrease in total indicator debris, as well as all source categories, for the U.S. Caribbean. Lower magnitude decreases were seen in indicator debris along the eastern Gulf of Mexico. In contrast, only land-based indicators declined in the western Gulf of Mexico; total, ocean-based and general-source indicators remained unchanged. Decreases in land-based indicators were not related to human population in the coastal regions; human population increased in all regions over the time of the study. Significant monthly patterns for indicator debris were found only in the Gulf of Mexico; counts were highest during May through September, with peaks occurring in July. Inclement weather conditions before the time of the survey also accounted for some of the variation in the western Gulf of Mexico; fewer items were found when there were heavy seas or cold fronts in the weeks prior to the survey, while tropical storms (including hurricanes) increased the amount of debris. With the development around the globe of long-term monitoring programs using standardized methodology, there is the potential to help management at individual sites, as well as generate larger-scale perspectives (from regional to global) to inform decision makers. Incorporating mechanisms producing debris into marine debris programs would be a fruitful area for future research.</p>","language":"English","publisher":"Universidade do Vale do Itajai, Brazil","publisherLocation":"Itajaí, Brazil","doi":"10.5894/rgci181","usgsCitation":"Ribic, C., Sheavly, S.B., and Rugg, D.J., 2011, Trends in marine debris in the U.S. Caribbean and the Gulf of Mexico, 1996-2003: Journal of Integrative Plant Biology, v. 11, no. 1, p. 7-19, https://doi.org/10.5894/rgci181.","productDescription":"13 p.","startPage":"7","endPage":"19","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1996-01-01","ipdsId":"IP-018231","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":474998,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.5894/rgci181","text":"External 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Leetown","active":true,"usgs":true}],"preferred":true,"id":637279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheavly, Seba B.","contributorId":171391,"corporation":false,"usgs":false,"family":"Sheavly","given":"Seba","email":"","middleInitial":"B.","affiliations":[{"id":26885,"text":"Sheavly Consultants, Virginia Beach, VA","active":true,"usgs":false}],"preferred":false,"id":640311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rugg, David J.","contributorId":171931,"corporation":false,"usgs":false,"family":"Rugg","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":640312,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70004496,"text":"ofr20111095 - 2011 - Assessment of Soil-Gas and Soil Contamination at the Former Military Police Range, Fort Gordon, Georgia, 2009-2010","interactions":[],"lastModifiedDate":"2012-03-08T17:16:40","indexId":"ofr20111095","displayToPublicDate":"2011-05-27T19:09:29","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":"2011-1095","title":"Assessment of Soil-Gas and Soil Contamination at the Former Military Police Range, Fort Gordon, Georgia, 2009-2010","docAbstract":"Soil gas and soil were assessed for organic and inorganic contaminants at the former military police range at Fort Gordon, Georgia, from May to September 2010. The assessment evaluated organic contaminants in soil-gas samplers and inorganic contaminants in soil samples. This assessment was conducted to provide environmental contamination data to Fort Gordon pursuant to requirements of the Resource Conservation and Recovery Act Part B Hazardous Waste Permit process. Soil-gas samplers deployed and collected from May 20 to 24, 2010, identified masses above method detection level for total petroleum hydrocarbons, gasoline-related and diesel-related compounds, and chloroform. Most of these detections were in the southwestern quarter of the study area and adjacent to the road on the eastern boundary of the site. Nine of the 11 chloroform detections were in the southern half of the study area. One soil-gas sampler deployed adjacent to the road on the southern boundary of the site detected a mass of tetrachloroethene greater than, but close to, the method detection level of 0.02 microgram. For soil-gas samplers deployed and collected from September 15 to 22, 2010, none of the selected organic compounds classified as chemical agents and explosives were detected above method detection levels. Inorganic concentrations in the five soil samples collected at the site did not exceed the U.S. Environmental Protection Agency regional screening levels for industrial soil and were at or below background levels for similar rocks and strata in South Carolina.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111095","collaboration":"Prepared in cooperation with the U.S. Department of the Army Environmental and Natural Resources Management Office of the U.S. Army Signal Center and Fort Gordon","usgsCitation":"Falls, W.F., Caldwell, A.W., Guimaraes, W.B., Ratliff, W.H., Wellborn, J.B., and Landmeyer, J., 2011, Assessment of Soil-Gas and Soil Contamination at the Former Military Police Range, Fort Gordon, Georgia, 2009-2010: U.S. Geological Survey Open-File Report 2011-1095, vi, 24 p., https://doi.org/10.3133/ofr20111095.","productDescription":"vi, 24 p.","costCenters":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"links":[{"id":116608,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1095.bmp"},{"id":21814,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1095/","linkFileType":{"id":5,"text":"html"}},{"id":204787,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/BF02509922"}],"country":"United States","state":"Georgia","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4aafe4b07f02db66d313","contributors":{"authors":[{"text":"Falls, W. Fred 0000-0003-2928-9795 wffalls@usgs.gov","orcid":"https://orcid.org/0000-0003-2928-9795","contributorId":107754,"corporation":false,"usgs":true,"family":"Falls","given":"W.","email":"wffalls@usgs.gov","middleInitial":"Fred","affiliations":[],"preferred":false,"id":350505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caldwell, Andral W. 0000-0003-1269-5463 acaldwel@usgs.gov","orcid":"https://orcid.org/0000-0003-1269-5463","contributorId":3228,"corporation":false,"usgs":true,"family":"Caldwell","given":"Andral","email":"acaldwel@usgs.gov","middleInitial":"W.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":350500,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guimaraes, Wladmir B. wbguimar@usgs.gov","contributorId":3818,"corporation":false,"usgs":true,"family":"Guimaraes","given":"Wladmir","email":"wbguimar@usgs.gov","middleInitial":"B.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":350502,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ratliff, W. Hagan","contributorId":60347,"corporation":false,"usgs":true,"family":"Ratliff","given":"W.","email":"","middleInitial":"Hagan","affiliations":[],"preferred":false,"id":350504,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wellborn, John B.","contributorId":24822,"corporation":false,"usgs":true,"family":"Wellborn","given":"John","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":350503,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Landmeyer, James 0000-0002-5640-3816 jlandmey@usgs.gov","orcid":"https://orcid.org/0000-0002-5640-3816","contributorId":3257,"corporation":false,"usgs":true,"family":"Landmeyer","given":"James","email":"jlandmey@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":350501,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70004506,"text":"ds604 - 2011 - Davis Pond freshwater diversion biomonitoring: Prediversion and postdiversion freshwater fish data","interactions":[],"lastModifiedDate":"2022-01-19T12:24:00.249716","indexId":"ds604","displayToPublicDate":"2011-05-27T19:09:29","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"604","title":"Davis Pond freshwater diversion biomonitoring: Prediversion and postdiversion freshwater fish data","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ds604","usgsCitation":"Jenkins, J.A., Olivier, H.M., Draugelis-Dale, R., and Kaller, M.D., 2011, Davis Pond freshwater diversion biomonitoring: Prediversion and postdiversion freshwater fish data: U.S. Geological Survey Data Series 604, HTML Document, https://doi.org/10.3133/ds604.","productDescription":"HTML Document","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":116610,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_604.png"},{"id":21815,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/604/","linkFileType":{"id":5,"text":"html"}},{"id":394469,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_95207.htm"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -90.4708,\n              29.3089\n            ],\n            [\n              -90.03,\n              29.3089\n            ],\n            [\n              -90.03,\n              30\n            ],\n            [\n              -90.4708,\n              30\n            ],\n            [\n              -90.4708,\n              29.3089\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4abbe4b07f02db67292b","contributors":{"authors":[{"text":"Jenkins, Jill A. 0000-0002-5087-0894 jenkinsj@usgs.gov","orcid":"https://orcid.org/0000-0002-5087-0894","contributorId":2710,"corporation":false,"usgs":true,"family":"Jenkins","given":"Jill","email":"jenkinsj@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":350521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olivier, Heather M.","contributorId":23245,"corporation":false,"usgs":true,"family":"Olivier","given":"Heather","email":"","middleInitial":"M.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":350522,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Draugelis-Dale, Rassa 0000-0001-8532-3287","orcid":"https://orcid.org/0000-0001-8532-3287","contributorId":47069,"corporation":false,"usgs":true,"family":"Draugelis-Dale","given":"Rassa","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":350523,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kaller, Michael D.","contributorId":58005,"corporation":false,"usgs":true,"family":"Kaller","given":"Michael","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":350524,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70004515,"text":"ds580 - 2011 - Groundwater environmental tracer data collected from the Chicot, Evangeline, and Jasper aquifers in Montgomery County and adjacent counties, Texas, 2008","interactions":[],"lastModifiedDate":"2016-08-11T15:40:29","indexId":"ds580","displayToPublicDate":"2011-05-27T19:09:29","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"580","title":"Groundwater environmental tracer data collected from the Chicot, Evangeline, and Jasper aquifers in Montgomery County and adjacent counties, Texas, 2008","docAbstract":"<p>The Gulf Coast aquifer system is the primary water supply for Montgomery County in southeastern Texas, including part of the Houston metropolitan area and the cities of Magnolia, Conroe, and The Woodlands Township, Texas. The U.S. Geological Survey, in cooperation with the Lone Star Groundwater Conservation District, collected environmental tracer data in the Gulf Coast aquifer system, primarily in Montgomery County. Forty existing groundwater wells screened in the Gulf Coast aquifer system were selected for sampling in Montgomery County (38 wells), Waller County (1 well), and Walker County (1 well). Groundwater-quality samples, physicochemical properties, and water-level data were collected once from each of the 40 wells during March-September 2008. Groundwater-quality samples were analyzed for dissolved gases and the environmental tracers sulfur hexafluoride, chlorofluorocarbons, tritium, helium-4, and helium-3/tritium. Water samples were collected and processed onsite using methods designed to minimize changes to the water-sample chemistry or contamination from the atmosphere. Replicate samples for quality assurance and quality control were collected with each environmental sample. Well-construction information and environmental tracer data for March-September 2008 are presented.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds580","usgsCitation":"Oden, T., 2011, Groundwater environmental tracer data collected from the Chicot, Evangeline, and Jasper aquifers in Montgomery County and adjacent counties, Texas, 2008: U.S. Geological Survey Data Series 580, iv, 8 p.; Appendices; Download of Appendices in Excel Format, https://doi.org/10.3133/ds580.","productDescription":"iv, 8 p.; Appendices; Download of Appendices in Excel Format","startPage":"iv","endPage":"37","numberOfPages":"41","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":116606,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_580.gif"},{"id":21818,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/580/","linkFileType":{"id":5,"text":"html"}}],"scale":"100000","projection":"Universal Transverse Mercator projection","state":"Texas","county":"Montgomery","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96.25,30 ], [ -96.25,30.75 ], [ -95.08333333333333,30.75 ], [ -95.08333333333333,30 ], [ -96.25,30 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a80e4b07f02db649701","contributors":{"authors":[{"text":"Oden, Timothy D. toden@usgs.gov","contributorId":1284,"corporation":false,"usgs":true,"family":"Oden","given":"Timothy D.","email":"toden@usgs.gov","affiliations":[],"preferred":true,"id":350542,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70004514,"text":"sir20115008 - 2011 - Precipitation-runoff relations and water-quality characteristics at edge-of-field stations, Discovery Farms and Pioneer Farm, Wisconsin, 2003-8","interactions":[],"lastModifiedDate":"2015-12-23T11:51:14","indexId":"sir20115008","displayToPublicDate":"2011-05-27T19:09:29","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":"2011-5008","title":"Precipitation-runoff relations and water-quality characteristics at edge-of-field stations, Discovery Farms and Pioneer Farm, Wisconsin, 2003-8","docAbstract":"A cooperative study between the U.S. Geological Survey, the University of Wisconsin (UW)-Madison Discovery Farms program (Discovery Farms), and the UW-Platteville Pioneer Farm program (Pioneer Farm) was developed to identify typical ranges and magnitudes, temporal distributions, and principal factors affecting concentrations and yields of sediment, nutrients, and other selected constituents in runoff from agricultural fields. Hydrologic and water-quality data were collected year-round at 23 edge-of-field monitoring stations on 5 privately owned Discovery Farms and on Pioneer Farm during water years 2003-8. The studied farms represented landscapes, soils, and farming systems typical of livestock farms throughout southern Wisconsin. Each farm employed a variety of soil, nutrient, and water-conservation practices to help minimize sediment and nutrient losses from fields and to improve crop productivity. This report summarizes the precipitation-runoff relations and water-quality characteristics measured in edge-of-field runoff for 26 \"farm years\" (aggregate years of averaged station data from all 6 farms for varying monitoring periods). A relatively wide range of constituents typically found in agricultural runoff were measured: suspended sediment, phosphorus (total, particulate, dissolved reactive, and total dissolved), and nitrogen (total, nitrate plus nitrite, organic, ammonium, total Kjeldahl and total Kjeldahl-dissolved), chloride, total solids, total suspended solids, total volatile suspended solids, and total dissolved solids.\n\nMean annual precipitation was 32.8 inches for the study period, about 3 percent less than the 30-year mean. Overall mean annual runoff was 2.55 inches per year (about 8 percent of precipitation) and the distribution was nearly equal between periods of frozen ground (54 percent) and unfrozen ground (46 percent). Mean monthly runoff was highest during two periods: February to March and May to June. Ninety percent of annual runoff occurred between January and the end of June.\n\nEvent mean concentrations of suspended sediment in runoff during unfrozen-ground periods were significantly higher (p<0.05) than those during frozen-ground periods. Mean annual suspended-sediment yields ranged from about 3 to nearly 5,000 pounds per acre (lb/acre), with a mean yield of 667 lb/acre. Ninety percent of suspended sediment was yielded in runoff during unfrozen-ground periods. May and June alone contributed more than 80 percent of the overall yield.\n\nPhosphorus concentrations and yields were also affected by the ground conditions at the time of runoff; however, unlike suspended sediment, phosphorus was usually available for transport in runoff regardless of ground condition. Mean annual total-phosphorus yields ranged from 0.03 to 7.0 lb/acre, with a mean yield of about 2.0 lb/acre. Nitrogen in runoff followed similar patterns to phosphorus in that concentrations were highest during unfrozen-ground periods, yields were highest during months of highest runoff, and speciation was affected by the ground conditions at the time of runoff. Mean annual total-nitrogen yields ranged from 0.11 to 19.2 lb/acre, and the mean was 7.2 lb/acre. Mean monthly total-nitrogen yields were strongly correlated with mean monthly total-phosphorus yields (r<sup>2</sup>= 0.92), indicating that the sources of nitrogen and phosphorus in runoff were likely similar.\n\nAnalysis of runoff, concentration, and yield data on annual, monthly, and seasonal time scales, when combined with precipitation, soil moisture, soil temperature, and on-farm field-activity information, revealed conditions in which runoff was most likely. The analysis also revealed the effects that field conditions and the timing of field-management activities-most notably, manure applications and tillage-had on the quantity and quality of surface runoff from agricultural fields.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115008","usgsCitation":"Stuntebeck, T.D., Komiskey, M.J., Peppler, M.C., Owens, D., and Frame, D.R., 2011, Precipitation-runoff relations and water-quality characteristics at edge-of-field stations, Discovery Farms and Pioneer Farm, Wisconsin, 2003-8: U.S. Geological Survey Scientific Investigations Report 2011-5008, vii, 46 p.; Appendices 1-5 in Excel format and Excel Comma Separated Values format, https://doi.org/10.3133/sir20115008.","productDescription":"vii, 46 p.; Appendices 1-5 in Excel format and Excel Comma Separated Values format","startPage":"i","endPage":"46","numberOfPages":"53","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":116609,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5008.jpg"},{"id":21817,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5008/","linkFileType":{"id":5,"text":"html"}}],"state":"Wisconsin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -93,42 ], [ -93,48 ], [ -87,48 ], [ -87,42 ], [ -93,42 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ad0e4b07f02db680852","contributors":{"authors":[{"text":"Stuntebeck, Todd D. 0000-0002-8405-7295 tdstunte@usgs.gov","orcid":"https://orcid.org/0000-0002-8405-7295","contributorId":902,"corporation":false,"usgs":true,"family":"Stuntebeck","given":"Todd","email":"tdstunte@usgs.gov","middleInitial":"D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":350538,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Komiskey, Matthew J. 0000-0003-2962-6974 mjkomisk@usgs.gov","orcid":"https://orcid.org/0000-0003-2962-6974","contributorId":1776,"corporation":false,"usgs":true,"family":"Komiskey","given":"Matthew","email":"mjkomisk@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":350540,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peppler, Marie C. 0000-0002-1120-9673 mpeppler@usgs.gov","orcid":"https://orcid.org/0000-0002-1120-9673","contributorId":825,"corporation":false,"usgs":true,"family":"Peppler","given":"Marie","email":"mpeppler@usgs.gov","middleInitial":"C.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":350537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Owens, David W. dwowens@usgs.gov","contributorId":3745,"corporation":false,"usgs":true,"family":"Owens","given":"David W.","email":"dwowens@usgs.gov","affiliations":[{"id":676,"text":"Wisconsin Water Resource Division","active":false,"usgs":true}],"preferred":false,"id":350539,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frame, Dennis R.","contributorId":77282,"corporation":false,"usgs":true,"family":"Frame","given":"Dennis","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":350541,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70004508,"text":"ds605 - 2011 - Photographic images captured while sampling for bald eagles near the Davis Pond freshwater diversion structure in Barataria Bay, Louisiana (2009-10)","interactions":[],"lastModifiedDate":"2012-02-02T00:15:50","indexId":"ds605","displayToPublicDate":"2011-05-27T19:09:29","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"605","title":"Photographic images captured while sampling for bald eagles near the Davis Pond freshwater diversion structure in Barataria Bay, Louisiana (2009-10)","docAbstract":"The implementation of freshwater diversions in large-scale coastal restoration schemes presents several scientific and management considerations. Large-scale environmental restructuring necessitates aquatic biomonitoring, and during such field studies, photographs that document animals and habitat may be captured. Among the biomonitoring studies performed in conjunction with the Davis Pond freshwater diversion structure south of New Orleans, Louisiana, only postdiversion study images are readily available, and these are presented here.","language":"ENGLISH","doi":"10.3133/ds605","usgsCitation":"Jenkins, J.A., Jeske, C.W., and Allain, L.K., 2011, Photographic images captured while sampling for bald eagles near the Davis Pond freshwater diversion structure in Barataria Bay, Louisiana (2009-10): U.S. Geological Survey Data Series 605, iii, 19 p., https://doi.org/10.3133/ds605.","productDescription":"iii, 19 p.","additionalOnlineFiles":"Y","temporalStart":"2009-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":116607,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_605.png"},{"id":21816,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/605/","linkFileType":{"id":5,"text":"html"}}],"state":"Louisiana","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4adbe4b07f02db685e5d","contributors":{"authors":[{"text":"Jenkins, Jill A. 0000-0002-5087-0894 jenkinsj@usgs.gov","orcid":"https://orcid.org/0000-0002-5087-0894","contributorId":2710,"corporation":false,"usgs":true,"family":"Jenkins","given":"Jill","email":"jenkinsj@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":350526,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jeske, Clinton W. jeskec@usgs.gov","contributorId":2982,"corporation":false,"usgs":true,"family":"Jeske","given":"Clinton","email":"jeskec@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":true,"id":350527,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allain, Larry K. 0000-0002-7717-9761 allainl@usgs.gov","orcid":"https://orcid.org/0000-0002-7717-9761","contributorId":2414,"corporation":false,"usgs":true,"family":"Allain","given":"Larry","email":"allainl@usgs.gov","middleInitial":"K.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":350525,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70004516,"text":"ofr20111076 - 2011 - Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2010","interactions":[],"lastModifiedDate":"2012-03-08T17:16:40","indexId":"ofr20111076","displayToPublicDate":"2011-05-27T19:09:00","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":"2011-1076","title":"Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2010","docAbstract":"Streamflow and water-quality data were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board (PWSB), Rhode Island's largest drinking-water supplier. Streamflow was measured or estimated by the USGS following standard methods at 23 streamgages; 14 of these stations were also equipped with instrumentation capable of continuously monitoring specific conductance and water temperature. Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2010 (October 1, 2009, to September 30, 2010). Water-quality samples also were collected at 37 sampling stations by the PWSB and at 14 monitoring stations by the USGS during WY 2010 as part of a long sampling program; all stations are in the Scituate Reservoir drainage area. Waterquality data collected by PWSB are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2010. The largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed a mean streamflow of about 39 cubic feet per second (ft<sup>3</sup>/s) to the reservoir during WY 2010. For the same time period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.7 to 27 ft<sup>3</sup>/s. Together, tributary streams (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,500,000 kilograms (kg) of sodium and 2,500,000 kg of chloride to the Scituate Reservoir during WY 2010; sodium and chloride yields for the tributaries ranged from 11,000 to 66,000 kilograms per square mile (kg/mi<sup>2</sup>) and from 18,000 to 110,000 kg/mi<sup>2</sup>, respectively. At the stations where water-quality samples were collected by the PWSB, the median of the median chloride concentrations was 20.2 milligrams per liter (mg/L), median nitrite concentration was 0.002 mg/L as nitrogen (N), median nitrate concentration was 0.01 mg/L as N, median orthophosphate concentration was 0.06 mg/L as phosphorus, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 93 and 16 colony forming units per 100 milliliters (CFU/100mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 170 kg/d (73 kg/d/mi<sup>2</sup>), 11 g/d (5.3 g/d/mi<sup>2</sup>), 74 g/d (39 g/d/mi<sup>2</sup>), 340 g/d (170 g/d/mi<sup>2</sup>), 5,700 million colony forming units per day (CFUx106/d) (2,300 CFUx106/d/mi<sup>2</sup>), and 620 CFUx106/d (440 CFUx106/d/mi<sup>2</sup>), respectively.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111076","usgsCitation":"Smith, K.P., and Breault, R., 2011, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2010: U.S. Geological Survey Open-File Report 2011-1076, iv, 20 p.; Tables, https://doi.org/10.3133/ofr20111076.","productDescription":"iv, 20 p.; Tables","startPage":"i","endPage":"26","numberOfPages":"30","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":116611,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1076.gif"},{"id":21819,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1076/","linkFileType":{"id":5,"text":"html"}}],"state":"Rhode Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.8,41.700833333333335 ], [ -71.8,41.93333333333333 ], [ -71,41.93333333333333 ], [ -71,41.700833333333335 ], [ -71.8,41.700833333333335 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b1fe4b07f02db6ab732","contributors":{"authors":[{"text":"Smith, Kirk P. 0000-0003-0269-474X kpsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-474X","contributorId":1516,"corporation":false,"usgs":true,"family":"Smith","given":"Kirk","email":"kpsmith@usgs.gov","middleInitial":"P.","affiliations":[{"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":350543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breault, Robert F. 0000-0002-2517-407X rbreault@usgs.gov","orcid":"https://orcid.org/0000-0002-2517-407X","contributorId":2219,"corporation":false,"usgs":true,"family":"Breault","given":"Robert F.","email":"rbreault@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":350544,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70173876,"text":"70173876 - 2011 - Interrelationships between fish tissue mercury concentrations and water quality for South Dakota natural lakes and impoundments","interactions":[],"lastModifiedDate":"2018-02-13T10:31:39","indexId":"70173876","displayToPublicDate":"2011-05-27T10:30:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3728,"text":"Water, Air, & Soil Pollution","onlineIssn":"1573-2932","printIssn":"0049-6979","active":true,"publicationSubtype":{"id":10}},"title":"Interrelationships between fish tissue mercury concentrations and water quality for South Dakota natural lakes and impoundments","docAbstract":"<p><span>The purpose of this study was to determine whether water quality parameters commonly associated with primary productivity may be used to predict the susceptibility of a specific water body to exceed proposed fish consumption advisory limitation of 0.3&nbsp;mg&nbsp;kg</span><sup><span>&minus;1</span></sup><span>. South Dakota currently has nine lakes and impoundments that exceed fish tissue mercury advisory limits of 1.0&nbsp;mg&nbsp;kg</span><sup><span>&minus;1</span></sup><span>&nbsp;total mercury, far exceeding US Environmental Protection Agency and Food and Drug Administration 0.3&nbsp;mg&nbsp;kg</span><sup><span>&minus;1</span></sup><span>&nbsp;consumption criteria. Previous studies suggest that increased aquatic productivity may mitigate the effects of biological production and subsequent uptake of methyl mercury through bio-dilution; however, it is uncertain whether these trends may exist within highly alkaline and highly productive aquatic conditions common to South Dakota lakes and impoundments. Water quality parameters and fish tissue mercury data for northern pike and walleye were collected and assessed using existing South Dakota Department of Environment and Natural Resources and Game Fish and Parks data. The data was initially screened using both parametric linear regression and non-parametric Mann&ndash;Whitney rank sum comparisons and further assessed using binary logistic regression and stepwise logistic regression methodology. Three separate phosphorus measurements (total, total dissolved, and Trophic State Index) and pH were determined to significantly correlate with increased mercury concentrations for the northern pike-in-impoundments model. However, phosphorus surprisingly was not a strong predictor for the remaining scenarios modeled. For the northern pike-in-natural lakes models, alkalinity was the most significant water quality parameter predicting increased mercury concentrations. Mercury concentrations for the walleye-in-natural lakes models were further influenced by pH and alkalinity. The water quality and fish tissue mercury interrelationships determined within this study suggest aquatic productivity, and consequential eutrophication processes appear to be reasonable indicators of fish tissue mercury susceptibility for aquatic conditions common to South Dakota and highlight the continuing need to minimize eutrophication through effective watershed management strategies.</span></p>","language":"English","publisher":"Spinger","doi":"10.1007/s11270-011-0828-3","usgsCitation":"Chipps, S.R., Stetler, L., Stone, J., and McCutcheon, C.M., 2011, Interrelationships between fish tissue mercury concentrations and water quality for South Dakota natural lakes and impoundments: Water, Air, & Soil Pollution, v. 222, no. 1, p. 337-349, https://doi.org/10.1007/s11270-011-0828-3.","productDescription":"13 p.","startPage":"337","endPage":"349","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-030403","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323705,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South 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J.","contributorId":171913,"corporation":false,"usgs":false,"family":"Stone","given":"James J.","affiliations":[],"preferred":false,"id":639094,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCutcheon, Cindy M.","contributorId":171915,"corporation":false,"usgs":false,"family":"McCutcheon","given":"Cindy","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":639095,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70157546,"text":"70157546 - 2011 - Planned updates and refinements to the Central Valley hydrologic model with an emphasis on improving the simulation of land subsidence in the San Joaquin Valley","interactions":[],"lastModifiedDate":"2021-11-09T17:55:54.596127","indexId":"70157546","displayToPublicDate":"2011-05-26T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Planned updates and refinements to the Central Valley hydrologic model with an emphasis on improving the simulation of land subsidence in the San Joaquin Valley","docAbstract":"<p><span>California's Central Valley has been one of the most productive agricultural regions in the world for more than 50 years. To better understand the groundwater availability in the valley, the U.S. Geological Survey (USGS) developed the Central Valley hydrologic model (CVHM). Because of recent water-level declines and renewed subsidence, the CVHM is being updated to better simulate the geohydrologic system. The CVHM updates and refinements can be grouped into two general categories: (1) model code changes and (2) data updates. The CVHM updates and refinements will require that the model be recalibrated. The updated CVHM will provide a detailed transient analysis of changes in groundwater availability and flow paths in relation to climatic variability, urbanization, stream flow, and changes in irrigated agricultural practices and crops. The updated CVHM is particularly focused on more accurately simulating the locations and magnitudes of land subsidence. The intent of the updated CVHM is to help scientists better understand the availability and sustainability of water resources and the interaction of groundwater levels with land subsidence.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"World environmental and water resources congress 2011: Bearing knowledge for sustainability","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"World Environmental and Water Resources Congress 2011","conferenceDate":"May 22-26 2011","conferenceLocation":"Palm Springs, California","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/41173(414)88","usgsCitation":"Faunt, C., Hanson, R.T., Martin, P., and Schmid, W., 2011, Planned updates and refinements to the Central Valley hydrologic model with an emphasis on improving the simulation of land subsidence in the San Joaquin Valley, <i>in</i> World environmental and water resources congress 2011: Bearing knowledge for sustainability, Palm Springs, California, May 22-26 2011, p. 864-870, https://doi.org/10.1061/41173(414)88.","productDescription":"7 p.","startPage":"864","endPage":"870","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-026942","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":308612,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.11376953125,\n              35.17380831799959\n            ],\n            [\n              -118.47656249999999,\n              36.35052700542763\n            ],\n            [\n              -120.76171875,\n              38.87392853923629\n            ],\n            [\n              -121.728515625,\n              40.17887331434696\n            ],\n            [\n              -122.32177734375,\n              40.48038142908172\n            ],\n            [\n              -122.56347656249999,\n              39.57182223734374\n            ],\n            [\n              -121.6845703125,\n              37.94419750075404\n            ],\n            [\n              -120.10253906249999,\n              36.01356058518153\n            ],\n            [\n              -119.11376953125,\n              35.17380831799959\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationDate":"2012-04-26","publicationStatus":"PW","scienceBaseUri":"56067036e4b058f706e51945","contributors":{"authors":[{"text":"Faunt, Claudia C. 0000-0001-5659-7529 ccfaunt@usgs.gov","orcid":"https://orcid.org/0000-0001-5659-7529","contributorId":1491,"corporation":false,"usgs":true,"family":"Faunt","given":"Claudia C.","email":"ccfaunt@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":573555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanson, Randall T. 0000-0002-9819-7141 rthanson@usgs.gov","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":801,"corporation":false,"usgs":true,"family":"Hanson","given":"Randall","email":"rthanson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":573556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Peter pmmartin@usgs.gov","contributorId":799,"corporation":false,"usgs":true,"family":"Martin","given":"Peter","email":"pmmartin@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":573557,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmid, Wolfgang","contributorId":84020,"corporation":false,"usgs":false,"family":"Schmid","given":"Wolfgang","affiliations":[{"id":13040,"text":"Department of Hydrology and Water Resources, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":573558,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":99284,"text":"ofr20111125 - 2011 - Threats of habitat and water-quality degradation to mussel diversity in the Meramec River Basin, Missouri, USA","interactions":[],"lastModifiedDate":"2019-07-09T15:47:36","indexId":"ofr20111125","displayToPublicDate":"2011-05-25T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-1125","title":"Threats of habitat and water-quality degradation to mussel diversity in the Meramec River Basin, Missouri, USA","docAbstract":"The Meramec River Basin in east-central Missouri is an important stronghold for native freshwater mussels (Order: Unionoida) in the United States. Whereas the basin supports more than 40 mussel species, previous studies indicate that the abundance and distribution of most species are declining. Therefore, resource managers have identified the need to prioritize threats to native mussel populations in the basin and to design a mussel monitoring program. The objective of this study was to identify threats of habitat and water-quality degradation to mussel diversity in the basin. Affected habitat parameters considered as the main threats to mussel conservation included excess sedimentation, altered stream geomorphology and flow, effects on riparian vegetation and condition, impoundments, and invasive non-native species. Evaluating water-quality parameters for conserving mussels was a main focus of this study. Mussel toxicity data for chemical contaminants were compared to national water quality criteria (NWQC) and Missouri water quality standards (MWQS). However, NWQC and MWQS have not been developed for many chemical contaminants and some MWQS may not be protective of native mussel populations. Toxicity data indicated that mussels are sensitive to ammonia, copper, temperature, certain pesticides, pharmaceuticals, and personal care products; these compounds were identified as the priority water-quality parameters for mussel conservation in the basin. Measures to conserve mussel diversity in the basin include expanding the species and life stages of mussels and the list of chemical contaminants that have been assessed, establishing a long term mussel monitoring program that measures physical and chemical parameters of high priority, conducting landscape scale modeling to predict mussel distributions, determining sublethal effects of primary contaminants of concern, deriving risk-based guidance values for mussel conservation, and assessing the effects of wastewater treatment plants and non-point source pollution on mussels. A critical next step to further prioritize these needs is to conduct a watershed risk assessment using local data (for example, land use, flow) when available.\r\n","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111125","collaboration":"A report to the Missouri Department of Conservation","usgsCitation":"Hinck, J.E., Ingersoll, C.G., Wang, N., Augspurger, T., Barnhart, M., McMurray, S., Roberts, A.D., and Schrader, L., 2011, Threats of habitat and water-quality degradation to mussel diversity in the Meramec River Basin, Missouri, USA: U.S. Geological Survey Open-File Report 2011-1125, vi, 18 p., https://doi.org/10.3133/ofr20111125.","productDescription":"vi, 18 p.","additionalOnlineFiles":"N","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":116647,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1125.jpg"},{"id":204783,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1125/","linkFileType":{"id":5,"text":"html"}},{"id":334505,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2011/1125/pdf/of2011_1125.pdf","size":"529 kB","linkFileType":{"id":1,"text":"pdf"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92,37.25 ], [ -92,38.75 ], [ -90,38.75 ], [ -90,37.25 ], [ -92,37.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a54e4b07f02db62bc58","contributors":{"authors":[{"text":"Hinck, Jo Ellen 0000-0002-4912-5766","orcid":"https://orcid.org/0000-0002-4912-5766","contributorId":38507,"corporation":false,"usgs":true,"family":"Hinck","given":"Jo","email":"","middleInitial":"Ellen","affiliations":[],"preferred":false,"id":307998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":307995,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":307996,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Augspurger, Tom","contributorId":63921,"corporation":false,"usgs":true,"family":"Augspurger","given":"Tom","affiliations":[],"preferred":false,"id":308001,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barnhart, M. Christopher","contributorId":78061,"corporation":false,"usgs":true,"family":"Barnhart","given":"M. Christopher","affiliations":[],"preferred":false,"id":308002,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McMurray, Stephen E.","contributorId":38687,"corporation":false,"usgs":true,"family":"McMurray","given":"Stephen E.","affiliations":[],"preferred":false,"id":307999,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roberts, Andrew D.","contributorId":52304,"corporation":false,"usgs":true,"family":"Roberts","given":"Andrew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":308000,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schrader, Lynn","contributorId":14551,"corporation":false,"usgs":true,"family":"Schrader","given":"Lynn","email":"","affiliations":[],"preferred":false,"id":307997,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70005228,"text":"70005228 - 2011 - Estimating occupancy dynamics in an anuran assemblage from Louisiana, USA","interactions":[],"lastModifiedDate":"2020-01-28T09:35:43","indexId":"70005228","displayToPublicDate":"2011-05-25T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Estimating occupancy dynamics in an anuran assemblage from Louisiana, USA","docAbstract":"Effective monitoring programs are designed to track changes in the distribution, occurrence, and abundance of species. We developed an extension of Royle and K&eacute;ry's (2007) single species model to estimate simultaneously temporal changes in probabilities of detection, occupancy, colonization, extinction, and species turnover using data on calling anuran amphibians, collected from 2002 to 2006 in the Lower Mississippi Alluvial Valley of Louisiana, USA. During our 5-year study, estimates of occurrence probabilities declined for all 12 species detected. These declines occurred primarily in conjunction with variation in estimates of local extinction probabilities (cajun chorus frog [<i>Pseudacris fouquettei</i>], spring peeper [<i>P. crucifer</i>], northern cricket frog [<i>Acris crepitans</i>], Cope's gray treefrog [<i>Hyla chrysoscelis</i>], green treefrog [<i>H. cinerea</i>], squirrel treefrog [<i>H. squirella</i>], southern leopard frog [<i>Lithobates sphenocephalus</i>], bronze frog [<i>L. clamitans</i>], American bullfrog [<i>L. catesbeianus</i>], and Fowler's toad [<i>Anaxyrus fowleri</i>]). For 2 species (eastern narrowmouthed toad [<i>Gastrophryne carolinensis</i>] and Gulf Coast toad [<i>Incilius nebulifer</i>]), declines in occupancy appeared to be a consequence of both increased local extinction and decreased colonization events. The eastern narrow-mouthed toad experienced a 2.5-fold increase in estimates of occupancy in 2004, possibly because of the high amount of rainfall received during that year, along with a decrease in extinction and increase in colonization of new sites between 2003 and 2004. Our model can be incorporated into monitoring programs to estimate simultaneously the occupancy dynamics for multiple species that show similar responses to ecological conditions. It will likely be an important asset for those monitoring programs that employ the same methods to sample assemblages of ecologically similar species, including those that are rare. By combining information from multiple species to decrease the variance on estimates of individual species, our results are advantageous compared to single-species models. This feature enables managers and researchers to use an entire community, rather than just one species, as an ecological indicator in monitoring programs.","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.97","usgsCitation":"Walls, S., Waddle, J., and Dorazio, R.M., 2011, Estimating occupancy dynamics in an anuran assemblage from Louisiana, USA: Journal of Wildlife Management, v. 75, no. 4, p. 751-761, https://doi.org/10.1002/jwmg.97.","productDescription":"11 p.","startPage":"751","endPage":"761","temporalStart":"2002-01-01","temporalEnd":"2006-12-31","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":204251,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Atchafalaya Basin, Lower Mississippi Alluvial Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.8731689453125,\n              29.89304338543419\n            ],\n            [\n              -91.8731689453125,\n              30.576450026618076\n            ],\n            [\n              -91.373291015625,\n              30.576450026618076\n            ],\n            [\n              -91.373291015625,\n              29.89304338543419\n            ],\n            [\n              -91.8731689453125,\n              29.89304338543419\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"75","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-05-25","publicationStatus":"PW","scienceBaseUri":"4f4e4a0ce4b07f02db5fc9db","contributors":{"authors":[{"text":"Walls, Susan C. 0000-0001-7391-9155","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":52284,"corporation":false,"usgs":true,"family":"Walls","given":"Susan C.","affiliations":[],"preferred":false,"id":352105,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waddle, J. Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":89982,"corporation":false,"usgs":true,"family":"Waddle","given":"J. Hardin","affiliations":[],"preferred":false,"id":352106,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dorazio, Robert M. 0000-0003-2663-0468 bob_dorazio@usgs.gov","orcid":"https://orcid.org/0000-0003-2663-0468","contributorId":1668,"corporation":false,"usgs":true,"family":"Dorazio","given":"Robert","email":"bob_dorazio@usgs.gov","middleInitial":"M.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":352104,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":99283,"text":"sim3121 - 2011 - Geologic map of the Ganiki Planitia quadrangle (V-14), Venus","interactions":[],"lastModifiedDate":"2023-03-16T10:55:03.655596","indexId":"sim3121","displayToPublicDate":"2011-05-24T00:00:00","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":"3121","title":"Geologic map of the Ganiki Planitia quadrangle (V-14), Venus","docAbstract":"The Ganiki Planitia (V-14) quadrangle on Venus, which extends from 25&deg; N. to 50&deg; N. and from 180&deg; E. to 210&deg; E., derives its name from the extensive suite of plains that dominates the geology of the northern part of the region. With a surface area of nearly 6.5 x 10<sup>6</sup> km<sup>2</sup> (roughly two-thirds that of the United States), the quadrangle is located northwest of the Beta-Atla-Themis volcanic zone and southeast of the Atalanta Planitia lowlands, areas proposed to be the result of large scale mantle upwelling and downwelling, respectively. The region immediately south of Ganiki Planitia is dominated by Atla Regio, a major volcanic rise beneath which localized upwelling appears to be ongoing, whereas the area just to the north is dominated by the orderly system of north-trending deformation belts that characterize Vinmara Planitia. The Ganiki Planitia quadrangle thus lies at the intersection between several physiographic regions where extensive mantle flow-induced tectonic and volcanic processes are thought to have occurred.\r\nThe geology of the V-14 quadrangle is characterized by a complex array of volcanic, tectonic, and impact-derived features. There are eleven impact craters with diameters from 4 to 64 km, as well as four diffuse 'splotch' features interpreted to be the product of near-surface bolide explosions. Tectonic activity has produced heavily deformed tesserae, belts of complex deformation and rifts as well as a distributed system of fractures and wrinkle ridges. Volcanic activity has produced extensive regional plains deposits, and in the northwest corner of the quadrangle these plains host the initial (or terminal) 700 km of the Baltis Vallis canali, an enigmatic volcanic feature with a net length of ~7,000 km that is the longest channel on Venus. Major volcanic centers in V-14 include eight large volcanoes and eight coronae; all but one of these sixteen features was noted during a previous global survey. The V-14 quadrangle contains an abundance of minor volcanic features including individual shield volcanoes and localized fissure eruptions as well as many small annular structures and domes, which often serve as the source for local lava flows.\r\nThe topographic and geophysical characteristics of the Ganiki Planitia quadrangle are less complex than the surface geology, but they yield equally valuable information about the region&rsquo;s formation and evolution. Referenced to the mean planetary radius of 6051.84 km, the average elevation in the quadrangle is -0.26&plusmn;0.86 km (2&sigma;) with a full range of -2.58 km to 1.85 km. The highest 2.5 percent of elevations in the quadrangle (above 0.60 km) are associated primarily with the major tessera blocks and the peaks of a few volcanic edifices, whereas the lowest 2.5 percent (below -1.12 km) mostly occur within corona interiors and in the northwest corner of the quadrangle where the plains begin to merge into the Atalanta Planitia lowlands. At the ~4.6 km/pixel scale of the topography data, the mean point-to-point topographic slope is 0.63&deg; and topographic slopes greater than 2&deg; cover less than 5 percent of the region. Overall, the topography of the Ganiki Planitia quadrangle can be characterized as flat, low lying, and nearly devoid of abrupt topographic variation. Complementing this gentle topography, the geoid anomaly has a generally linear gradient that decreases north-northwest from a high of ~20 m at the southern edge of the quadrangle (the northern border of the Atla Regio anomaly) to a low of -30 to -40 m along the northern edge (Konopliv and others, 1999). The vertical component of the gravity anomaly varies from ~50 mGal to -40 mGal, and integrated analysis of the gravity and topography data indicates that dynamically supported regions and areas of thickened crust are both present within the quadrangle.\r\nBecause the Ganiki Planitia quadrangle is a plains-dominated lowland area that lies between several major physiographic provinces (namely, Atla Regio, Atalanta Planitia, and Vinmara Planitia), a geologic map of the region may yield insight into a wide array of important problems in Venusian geology. The current mapping effort and analysis complements previous efforts to characterize aspects of the region&rsquo;s geology, for example stratigraphy near parabolic halo crater sites, volcanic plains emplacement, wrinkle ridges, volcanic feature distribution, volcano deformation, coronae characteristics, lithospheric flexure, and various features along a 30&plusmn;7.58&deg; N. geotraverse. Our current research focuses on addressing four specific questions. Has the dominant style of volcanic expression within the quadrangle varied in a systematic fashion over time? Does the tectonic deformation within the quadrangle record significant regional patterns that vary spatially or temporally, and if so what are the scales, orientations and sources of the stress fields driving this deformation? If mantle upwelling and downwelling have played a significant role in the formation of Atla Regio and Atalanta Planitia as has been proposed, does the geology of Ganiki Planitia record evidence of northwest-directed lateral mantle flow connecting the two sites? Finally, can integration of the tectonic and volcanic histories preserved within the quadrangle help constrain competing resurfacing models for Venus?","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sim3121","collaboration":"Prepared for the National Aeronautics and Space Administration","usgsCitation":"Grosfils, E.B., Long, S.M., Venechuk, E.M., Hurwitz, D.M., Richards, J.W., Drury, D.E., and Hardin, J., 2011, Geologic map of the Ganiki Planitia quadrangle (V-14), Venus: U.S. Geological Survey Scientific Investigations Map 3121, Map: 43.86 inches x 36.87 inches; Pamphlet: ii, 30 p., https://doi.org/10.3133/sim3121.","productDescription":"Map: 43.86 inches x 36.87 inches; Pamphlet: ii, 30 p.","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":116211,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3121.jpg"},{"id":204782,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3121/","linkFileType":{"id":5,"text":"html"}},{"id":414265,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://doi.org/10.5066/P9NSC8UY","text":"Interactive map","linkHelpText":"- Geologic Map of the Ganiki Planitia Quadrangle (V-14) of Venus, 1:5M. Grosfils and others (2011)"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afee4b07f02db697873","contributors":{"authors":[{"text":"Grosfils, Eric B.","contributorId":27752,"corporation":false,"usgs":true,"family":"Grosfils","given":"Eric","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":307989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Sylvan M.","contributorId":14699,"corporation":false,"usgs":true,"family":"Long","given":"Sylvan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":307988,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Venechuk, Elizabeth M.","contributorId":50053,"corporation":false,"usgs":true,"family":"Venechuk","given":"Elizabeth","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":307991,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hurwitz, Debra M.","contributorId":43614,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Debra","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":307990,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richards, Joseph W.","contributorId":94926,"corporation":false,"usgs":true,"family":"Richards","given":"Joseph","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":307994,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drury, Dorothy E.","contributorId":69425,"corporation":false,"usgs":true,"family":"Drury","given":"Dorothy","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":307993,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hardin, Johanna","contributorId":58151,"corporation":false,"usgs":true,"family":"Hardin","given":"Johanna","email":"","affiliations":[],"preferred":false,"id":307992,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70035058,"text":"70035058 - 2011 - Modelling the distribution of domestic ducks in Monsoon Asia","interactions":[],"lastModifiedDate":"2024-10-01T13:29:18.617101","indexId":"70035058","displayToPublicDate":"2011-05-24T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":682,"text":"Agriculture, Ecosystems and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Modelling the distribution of domestic ducks in Monsoon Asia","docAbstract":"<p><span>Domestic ducks are considered to be an important reservoir of highly pathogenic avian influenza (HPAI), as shown by a number of geospatial studies in which they have been identified as a significant risk factor associated with disease presence. Despite their importance in HPAI epidemiology, their large-scale distribution in Monsoon Asia is poorly understood. In this study, we created a spatial database of domestic duck census data in Asia and used it to train statistical distribution models for domestic duck distributions at a spatial resolution of 1</span><span>&nbsp;</span><span>km. The method was based on a modelling framework used by the Food and Agriculture Organisation to produce the Gridded Livestock of the World (GLW) database, and relies on stratified regression models between domestic duck densities and a set of agro-ecological explanatory variables. We evaluated different ways of stratifying the analysis and of combining the prediction to optimize the goodness of fit of the predictions. We found that domestic duck density could be predicted with reasonable accuracy (mean RMSE and correlation coefficient between log-transformed observed and predicted densities being 0.58 and 0.80, respectively), using a stratification based on&nbsp;livestock production systems. We tested the use of artificially degraded data on duck distributions in Thailand and Vietnam as training data, and compared the modelled outputs with the original high-resolution data. This showed, for these two countries at least, that these approaches could be used to accurately disaggregate provincial level (administrative level 1) statistical data to provide high resolution model distributions.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.agee.2011.04.013","issn":"01678809","usgsCitation":"Van Boeckel, T., Prosser, D.J., Franceschini, G., Biradar, C., Wint, W., Robinson, T., and Gilbert, M., 2011, Modelling the distribution of domestic ducks in Monsoon Asia: Agriculture, Ecosystems and Environment, v. 141, no. 3-4, p. 373-380, https://doi.org/10.1016/j.agee.2011.04.013.","productDescription":"8 p.","startPage":"373","endPage":"380","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":475001,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3148691","text":"External Repository"},{"id":381244,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"141","issue":"3-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5c77e4b0c8380cd6fcff","contributors":{"authors":[{"text":"Van Boeckel, T.P.","contributorId":97342,"corporation":false,"usgs":false,"family":"Van Boeckel","given":"T.P.","affiliations":[],"preferred":false,"id":449081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":449075,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Franceschini, G.","contributorId":73030,"corporation":false,"usgs":true,"family":"Franceschini","given":"G.","email":"","affiliations":[],"preferred":false,"id":449080,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Biradar, C.","contributorId":44377,"corporation":false,"usgs":true,"family":"Biradar","given":"C.","email":"","affiliations":[],"preferred":false,"id":449078,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wint, W.","contributorId":24588,"corporation":false,"usgs":true,"family":"Wint","given":"W.","affiliations":[],"preferred":false,"id":449076,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robinson, T.","contributorId":26154,"corporation":false,"usgs":true,"family":"Robinson","given":"T.","affiliations":[],"preferred":false,"id":449077,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gilbert, M.","contributorId":57810,"corporation":false,"usgs":true,"family":"Gilbert","given":"M.","affiliations":[],"preferred":false,"id":449079,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":99279,"text":"ofr20111026 - 2011 - Tectonic and metallogenic model for northeast Asia","interactions":[],"lastModifiedDate":"2012-02-10T00:11:58","indexId":"ofr20111026","displayToPublicDate":"2011-05-23T00:00:00","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":"2011-1026","title":"Tectonic and metallogenic model for northeast Asia","docAbstract":"This document describes the digital files in this report that contains a tectonic and metallogenic model for Northeast Asia. The report also contains background materials. This tectonic and metallogenic model and other materials on this report are derived from (1) an extensive USGS Professional Paper, 1765, on the metallogenesis and tectonics of Northeast Asia that is available on the Internet at http://pubs.usgs.gov/pp/1765/; and (2) the Russian Far East parts of an extensive USGS Professional Paper, 1697, on the metallogenesis and tectonics of the Russian Far East, Alaska, and the Canadian Cordillera that is available on the Internet at http://pubs.usgs.gov/pp/pp1697/. The major purpose of the tectonic and metallogenic model is to provide, in movie format, a colorful summary of the complex geology, tectonics, and metallogenesis of the region. To accomplish this goal four steps were taken: (1) 13 time-stage diagrams, from the late Neoproterozoic (850 Ma) through the present (0 Ma), were adapted, generalized, and transformed into color static time-stage diagrams; (2) the 13 time-stage diagrams were placed in a computer morphing program to produce the model; (3) the model was examined and each diagram was successively adapted to preceding and subsequent diagrams to match the size and surface expression of major geologic units; and (4) the final version of the model was produced in successive iterations of steps 2 and 3. The tectonic and metallogenic model and associated materials in this report are derived from a project on the major mineral deposits, metallogenesis, and tectonics of the Northeast Asia and from a preceding project on the metallogenesis and tectonics of the Russian Far East, Alaska, and the Canadian Cordillera. Both projects provide critical information on bedrock geology and geophysics, tectonics, major metalliferous mineral resources, metallogenic patterns, and crustal origin and evolution of mineralizing systems for this region. The major scientific goals and benefits of the projects are to: (1) provide a comprehensive international data base on the mineral resources of the region that is the first extensive knowledge available in English; (2) provide major new interpretations of the origin and crustal evolution of mineralizing systems and their host rocks, thereby enabling enhanced, broad-scale tectonic reconstructions and interpretations; and (3) promote trade and scientific and technical exchanges between North America and eastern Asia. ","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20111026","collaboration":"In cooperation with Jilin University, Changchun, People's Republic of China; Mongolian Academy of Sciences, Ulaanbaatar, Mongolia; Mongolian University of Science and Technology, Ulaanbaatar, Mongolia; Russian Academy of Sciences, Irkutsk, Russia; Russian Academy of Sciences, Khabarovsk, Russia; Russian Academy of Sciences, Magadan, Russia; Russian Academy of Sciences, Novosibirsk, Russia; Russian Academy of Sciences; Vladivostok, Russia; Russian Academy of Sciences, Yakutsk, Russia; and University of Texas, Arlington, Texas","usgsCitation":"Parfenov, L.M., Nokleberg, W.J., Berzin, N.A., Badarch, G., Dril, S.I., Gerel, O., Goryachev, N., Khanchuk, A.I., Kuz’min, M.I., Prokopiev, A.V., Ratkin, V.V., Rodionov, S.M., Scotese, C.R., Shpikerman, V.I., Timofeev, V.F., Tomurtogoo, O., and Yan, H., 2011, Tectonic and metallogenic model for northeast Asia: U.S. Geological Survey Open-File Report 2011-1026, 9 p.; Model file; Model-Figures folder; CD-ROM, https://doi.org/10.3133/ofr20111026.","productDescription":"9 p.; Model file; Model-Figures folder; CD-ROM","onlineOnly":"N","costCenters":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":116603,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1026.gif"},{"id":14680,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1026/","linkFileType":{"id":5,"text":"html"}}],"state":"Colorado","county":"Summit","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4882e4b07f02db516c22","contributors":{"editors":[{"text":"Nokleberg, Warren J. 0000-0002-1574-8869 wnokleberg@usgs.gov","orcid":"https://orcid.org/0000-0002-1574-8869","contributorId":2077,"corporation":false,"usgs":true,"family":"Nokleberg","given":"Warren","email":"wnokleberg@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":505758,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Parfenov, Leonid M.","contributorId":59112,"corporation":false,"usgs":true,"family":"Parfenov","given":"Leonid","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":307974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nokleberg, Warren J. 0000-0002-1574-8869 wnokleberg@usgs.gov","orcid":"https://orcid.org/0000-0002-1574-8869","contributorId":2077,"corporation":false,"usgs":true,"family":"Nokleberg","given":"Warren","email":"wnokleberg@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":307964,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berzin, Nikolai A.","contributorId":33793,"corporation":false,"usgs":true,"family":"Berzin","given":"Nikolai","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":307971,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Badarch, Gombosuren","contributorId":6940,"corporation":false,"usgs":true,"family":"Badarch","given":"Gombosuren","email":"","affiliations":[],"preferred":false,"id":307965,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dril, Sergy I.","contributorId":66823,"corporation":false,"usgs":true,"family":"Dril","given":"Sergy","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":307977,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gerel, Ochir","contributorId":41520,"corporation":false,"usgs":true,"family":"Gerel","given":"Ochir","email":"","affiliations":[],"preferred":false,"id":307973,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Goryachev, Nikolai A.","contributorId":7318,"corporation":false,"usgs":true,"family":"Goryachev","given":"Nikolai A.","affiliations":[],"preferred":false,"id":307966,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Khanchuk, Alexander I.","contributorId":19585,"corporation":false,"usgs":true,"family":"Khanchuk","given":"Alexander","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":307967,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kuz’min, Mikhail I. Obolenskiy Obolenskiy, Alexander A.","contributorId":28717,"corporation":false,"usgs":true,"family":"Kuz’min","given":"Mikhail","suffix":"Obolenskiy, Alexander A.","email":"","middleInitial":"I. Obolenskiy","affiliations":[],"preferred":false,"id":307969,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Prokopiev, Andrei V.","contributorId":20825,"corporation":false,"usgs":true,"family":"Prokopiev","given":"Andrei","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":307968,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ratkin, Vladimir V.","contributorId":79924,"corporation":false,"usgs":true,"family":"Ratkin","given":"Vladimir","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":307978,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Rodionov, Sergey M.","contributorId":64726,"corporation":false,"usgs":true,"family":"Rodionov","given":"Sergey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":307975,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Scotese, Christopher R.","contributorId":66357,"corporation":false,"usgs":true,"family":"Scotese","given":"Christopher","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":307976,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Shpikerman, Vladimir I.","contributorId":35766,"corporation":false,"usgs":true,"family":"Shpikerman","given":"Vladimir","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":307972,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Timofeev, Vladimir F.","contributorId":90385,"corporation":false,"usgs":true,"family":"Timofeev","given":"Vladimir","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":307980,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Tomurtogoo, Onongin","contributorId":29932,"corporation":false,"usgs":true,"family":"Tomurtogoo","given":"Onongin","email":"","affiliations":[],"preferred":false,"id":307970,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Yan, Hongquan","contributorId":81559,"corporation":false,"usgs":true,"family":"Yan","given":"Hongquan","email":"","affiliations":[],"preferred":false,"id":307979,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":99275,"text":"ofr20111123 - 2011 - Estimation of bed-material transport in the lower Chetco River, Oregon, water years 2009-2010","interactions":[],"lastModifiedDate":"2019-04-29T10:18:54","indexId":"ofr20111123","displayToPublicDate":"2011-05-20T00:00:00","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":"2011-1123","title":"Estimation of bed-material transport in the lower Chetco River, Oregon, water years 2009-2010","docAbstract":"This assessment of bed-material transport uses methods developed in a previous study (Wallick and others, 2010) to estimate bed-material flux at the USGS Chetco River streamflow gaging station located at flood-plain kilometer 15 (14400000). On the basis of regressions between daily mean flow and transport capacity, daily bed-material flux was calculated for the period October 1, 2008 to March 30, 2011. The daily flux estimates were then aggregated by water year (WY) for WY 2009 and WY 2010 and the period April 1-March 31 during 2008-09, 2009-10 and 2010-11. The main findings were: \n\n*Estimated bed-material flux for WY 2009 (October 1, 2008 to September 30, 2009) was 87,300 metric tons as calculated by the Parker (1990a, b) equation (hereinafter \\'the Parker equation\\') and 116,900 metric tons as calculated by the Wilcock and Crowe (2003) equation (hereinafter \\'the Wilcock-Crowe equation\\'). \n*Estimated bed-material flux for water year 2010 (October 1, 2008 to September 30, 2009) was 56,800 metric tons as calculated by the Parker equation and 96,700 metric tons as calculated by the Wilcock-Crowe equation. \n*Estimated bed-material flux for April 1, 2008, to March 31, 2009, was 84,700 metric tons as calculated by the Parker equation and 111,700 metric tons as calculated by the Wilcock-Crowe equation. Flux values from April 1 to September 30, 2008, are from Wallick and others (2010). \n*Estimated bed-material flux for April 1, 2009, to March 31, 2010, was 45,500 metric tons as calculated by the Parker equation and 79,100 metric tons as calculated by the Wilcock-Crowe equation. \n*Estimated bed-material flux for April 1, 2010, to March 31, 2011, was 67,100 metric tons as calculated by the Parker equation and 134,300 metric tons as calculated by the Wilcock-Crowe equation. These calculations used provisional flow data for December 29, 2010, to March 31, 2011, and may be subject to revision. \n*Water years 2009 and 2010 both had less bed-material transport than the average annual transport values of 105,300 and 152,300 metric tons for the period 1970-2010 as calculated by the Parker and Wilcock-Crowe equations, respectively.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20111123","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers and the Oregon Department of State Lands\r\n","usgsCitation":"Wallick, J., and O'Connor, J., 2011, Estimation of bed-material transport in the lower Chetco River, Oregon, water years 2009-2010: U.S. Geological Survey Open-File Report 2011-1123, vi, 12 p., https://doi.org/10.3133/ofr20111123.","productDescription":"vi, 12 p.","numberOfPages":"21","additionalOnlineFiles":"N","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":116908,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1123.gif"},{"id":204777,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1123/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon","otherGeospatial":"Chetco River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.30240631103514,\n              42.03679931146698\n            ],\n            [\n              -124.1513442993164,\n              42.03679931146698\n            ],\n            [\n              -124.1513442993164,\n              42.14125958838083\n            ],\n            [\n              -124.30240631103514,\n              42.14125958838083\n            ],\n            [\n              -124.30240631103514,\n              42.03679931146698\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49e0e4b07f02db5e4788","contributors":{"authors":[{"text":"Wallick, J. Rose 0000-0002-9392-272X rosewall@usgs.gov","orcid":"https://orcid.org/0000-0002-9392-272X","contributorId":3583,"corporation":false,"usgs":true,"family":"Wallick","given":"J. Rose","email":"rosewall@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":307955,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":307956,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":99271,"text":"ofr20111073 - 2011 - Global multi-resolution terrain elevation data 2010 (GMTED2010)","interactions":[],"lastModifiedDate":"2012-02-10T00:11:58","indexId":"ofr20111073","displayToPublicDate":"2011-05-20T00:00:00","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":"2011-1073","title":"Global multi-resolution terrain elevation data 2010 (GMTED2010)","docAbstract":"In 1996, the U.S. Geological Survey (USGS) developed a global topographic elevation model designated as GTOPO30 at a horizontal resolution of 30 arc-seconds for the entire Earth. Because no single source of topographic information covered the entire land surface, GTOPO30 was derived from eight raster and vector sources that included a substantial amount of U.S. Defense Mapping Agency data. The quality of the elevation data in GTOPO30 varies widely; there are no spatially-referenced metadata, and the major topographic features such as ridgelines and valleys are not well represented. Despite its coarse resolution and limited attributes, GTOPO30 has been widely used for a variety of hydrological, climatological, and geomorphological applications as well as military applications, where a regional, continental, or global scale topographic model is required. These applications have ranged from delineating drainage networks and watersheds to using digital elevation data for the extraction of topographic structure and three-dimensional (3D) visualization exercises (Jenson and Domingue, 1988; Verdin and Greenlee, 1996; Lehner and others, 2008). Many of the fundamental geophysical processes active at the Earth's surface are controlled or strongly influenced by topography, thus the critical need for high-quality terrain data (Gesch, 1994). U.S. Department of Defense requirements for mission planning, geographic registration of remotely sensed imagery, terrain visualization, and map production are similarly dependent on global topographic data.\r\n\r\nSince the time GTOPO30 was completed, the availability of higher-quality elevation data over large geographic areas has improved markedly. New data sources include global Digital Terrain Elevation Data (DTEDRegistered) from the Shuttle Radar Topography Mission (SRTM), Canadian elevation data, and data from the Ice, Cloud, and land Elevation Satellite (ICESat). Given the widespread use of GTOPO30 and the equivalent 30-arc-second DTEDRegistered level 0, the USGS and the National Geospatial-Intelligence Agency (NGA) have collaborated to produce an enhanced replacement for GTOPO30, the Global Land One-km Base Elevation (GLOBE) model and other comparable 30-arc-second-resolution global models, using the best available data. The new model is called the Global Multi-resolution Terrain Elevation Data 2010, or GMTED2010 for short. This suite of products at three different resolutions (approximately 1,000, 500, and 250 meters) is designed to support many applications directly by providing users with generic products (for example, maximum, minimum, and median elevations) that have been derived directly from the raw input data that would not be available to the general user or would be very costly and time-consuming to produce for individual applications. The source of all the elevation data is captured in metadata for reference purposes. It is also hoped that as better data become available in the future, the GMTED2010 model will be updated.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20111073","usgsCitation":"Danielson, J.J., and Gesch, D.B., 2011, Global multi-resolution terrain elevation data 2010 (GMTED2010): U.S. Geological Survey Open-File Report 2011-1073, iv, 23 p.; Appendix, https://doi.org/10.3133/ofr20111073.","productDescription":"iv, 23 p.; Appendix","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":116894,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1073.jpg"},{"id":204774,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1073/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4abee4b07f02db674b19","contributors":{"authors":[{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":307951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":307950,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":99276,"text":"ofr20101077 - 2011 - Geochemical and stable isotopic data on barren and mineralized drill core in the Devonian Popovich Formation, Screamer sector of the Betze-Post gold deposit, northern Carlin trend, Nevada","interactions":[],"lastModifiedDate":"2022-09-29T21:11:15.454446","indexId":"ofr20101077","displayToPublicDate":"2011-05-20T00:00:00","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":"2010-1077","title":"Geochemical and stable isotopic data on barren and mineralized drill core in the Devonian Popovich Formation, Screamer sector of the Betze-Post gold deposit, northern Carlin trend, Nevada","docAbstract":"The Devonian Popovich Formation is the major host for Carlin-type gold deposits in the northern Carlin trend of Nevada. The Popovich is composed of gray to black, thin-bedded, calcareous to dolomitic mudstone and limestone deposited near the carbonate platform margin. Carlin-type gold deposits are Eocene, disseminated, auriferous pyrite deposits characterized by acid leaching, sulfidation, and silicification that are typically hosted in Paleozoic calcareous sedimentary rocks exposed in windows through siliceous sedimentary rocks of the Roberts Mountains allochthon. The Carlin trend currently is the largest gold producer in the United States. The Screamer ore zone is a tabular body on the periphery of the huge Betze-Post gold deposit. Screamer is a good place to study both the original lithogeochemistry of the Popovich Formation and the effects of subsequent alteration and mineralization because it is below the level of supergene oxidation, mostly outside the contact metamorphic aureole of the Jurassic Goldstrike stock, has small, high-grade ore zones along fractures and Jurassic dikes, and has intervening areas with lower grade mineralization and barren rock. In 1997, prior to mining at Screamer, drill core intervals from barren and mineralized Popovich Formation were selected for geochemical and stable isotope analysis. The 332, five-foot core samples analyzed are from five holes separated by as much as 2000 feet (600 meters). The samples extend from the base of the Wispy unit up through the Planar and Soft sediment deformation units into the lower part of the upper Mud unit of the Popovich Formation.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20101077","usgsCitation":"Christiansen, W., Hofstra, A.H., Zohar, P.B., and Tousignant, G., 2011, Geochemical and stable isotopic data on barren and mineralized drill core in the Devonian Popovich Formation, Screamer sector of the Betze-Post gold deposit, northern Carlin trend, Nevada: U.S. Geological Survey Open-File Report 2010-1077, Report: iii, 11 p.; 2 Tables, https://doi.org/10.3133/ofr20101077.","productDescription":"Report: iii, 11 p.; 2 Tables","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":407658,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_95203.htm","linkFileType":{"id":5,"text":"html"}},{"id":204778,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1077/","linkFileType":{"id":5,"text":"html"}},{"id":116907,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1077.png"}],"country":"United States","state":"Nevada","otherGeospatial":"northern Carlin trend","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.4458,\n              40.5744\n            ],\n            [\n              -115.8958,\n              40.5744\n            ],\n            [\n              -115.8958,\n              41.1833\n            ],\n            [\n              -116.4458,\n              41.1833\n            ],\n            [\n              -116.4458,\n              40.5744\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b24e4b07f02db6ae69d","contributors":{"authors":[{"text":"Christiansen, William D.","contributorId":69688,"corporation":false,"usgs":true,"family":"Christiansen","given":"William D.","affiliations":[],"preferred":false,"id":307960,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hofstra, Albert H. 0000-0002-2450-1593 ahofstra@usgs.gov","orcid":"https://orcid.org/0000-0002-2450-1593","contributorId":1302,"corporation":false,"usgs":true,"family":"Hofstra","given":"Albert","email":"ahofstra@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":307957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zohar, Pamela B.","contributorId":24070,"corporation":false,"usgs":true,"family":"Zohar","given":"Pamela","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":307958,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tousignant, Gilles","contributorId":24071,"corporation":false,"usgs":true,"family":"Tousignant","given":"Gilles","affiliations":[],"preferred":false,"id":307959,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":99273,"text":"ti2H1 - 2011 - Computational considerations for collecting and using data in the equidistant cylindrical map projection and the bounds of sampling geographic data at progressively higher resolution","interactions":[],"lastModifiedDate":"2012-02-02T00:05:16","indexId":"ti2H1","displayToPublicDate":"2011-05-20T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2-H1","title":"Computational considerations for collecting and using data in the equidistant cylindrical map projection and the bounds of sampling geographic data at progressively higher resolution","docAbstract":"The Equidistant Cylindrical Map projection is popular with digital modelers and others for storing and processing worldwide data sets because of the simple association of latitude and longitude to cell values or pixels in the resulting grid. This projection does not accurately display area, and the diminished geographic area represented by cells at high latitudes is not often carefully considered. A simple mathematical analysis quantifies the discrepancy in area sampled by cells at different latitudes. The presence of this discrepancy indicates that the use of this projection can induce bias in data sets when both sampling and reporting data. It is demonstrated that as the resolution requirements of input data for models increase, the necessity of providing data to accurately describe smaller cells, particularly at high latitude, will be a challenge. ","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ti2H1","usgsCitation":"Foley, K.M., 2011, Computational considerations for collecting and using data in the equidistant cylindrical map projection and the bounds of sampling geographic data at progressively higher resolution: U.S. Geological Survey Techniques and Methods 2-H1, iii, 5 p., https://doi.org/10.3133/ti2H1.","productDescription":"iii, 5 p.","costCenters":[{"id":308,"text":"Geology and Environmental Change Science Center","active":false,"usgs":true}],"links":[{"id":116909,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_2_h1.gif"},{"id":204775,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/tm2h1/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a6be4b07f02db63d86f","contributors":{"authors":[{"text":"Foley, Kevin M. 0000-0003-1013-462X kfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-1013-462X","contributorId":2543,"corporation":false,"usgs":true,"family":"Foley","given":"Kevin","email":"kfoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":307952,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":99274,"text":"ofr20111116 - 2011 - Rapid estimation of the economic consequences of global earthquakes","interactions":[],"lastModifiedDate":"2022-11-29T20:24:57.519343","indexId":"ofr20111116","displayToPublicDate":"2011-05-20T00:00:00","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":"2011-1116","title":"Rapid estimation of the economic consequences of global earthquakes","docAbstract":"The U.S. Geological Survey's (USGS) Prompt Assessment of Global Earthquakes for Response (PAGER) system, operational since mid 2007, rapidly estimates the most affected locations and the population exposure at different levels of shaking intensities. The PAGER system has significantly improved the way aid agencies determine the scale of response needed in the aftermath of an earthquake. For example, the PAGER exposure estimates provided reasonably accurate assessments of the scale and spatial extent of the damage and losses following the 2008 Wenchuan earthquake (Mw 7.9) in China, the 2009 L'Aquila earthquake (Mw 6.3) in Italy, the 2010 Haiti earthquake (Mw 7.0), and the 2010 Chile earthquake (Mw 8.8).\r\n\r\nNevertheless, some engineering and seismological expertise is often required to digest PAGER's exposure estimate and turn it into estimated fatalities and economic losses. This has been the focus of PAGER's most recent development.\r\n\r\nWith the new loss-estimation component of the PAGER system it is now possible to produce rapid estimation of expected fatalities for global earthquakes (Jaiswal and others, 2009). While an estimate of earthquake fatalities is a fundamental indicator of potential human consequences in developing countries (for example, Iran, Pakistan, Haiti, Peru, and many others), economic consequences often drive the responses in much of the developed world (for example, New Zealand, the United States, and Chile), where the improved structural behavior of seismically resistant buildings significantly reduces earthquake casualties.\r\n\r\nRapid availability of estimates of both fatalities and economic losses can be a valuable resource. The total time needed to determine the actual scope of an earthquake disaster and to respond effectively varies from country to country. It can take days or sometimes weeks before the damage and consequences of a disaster can be understood both socially and economically. The objective of the U.S. Geological Survey's PAGER system is to reduce this time gap to more rapidly and effectively mobilize response.\r\n\r\nWe present here a procedure to rapidly and approximately ascertain the economic impact immediately following a large earthquake anywhere in the world. In principle, the approach presented is similar to the empirical fatality estimation methodology proposed and implemented by Jaiswal and others (2009). In order to estimate economic losses, we need an assessment of the economic exposure at various levels of shaking intensity. The economic value of all the physical assets exposed at different locations in a given area is generally not known and extremely difficult to compile at a global scale. In the absence of such a dataset, we first estimate the total Gross Domestic Product (GDP) exposed at each shaking intensity by multiplying the per-capita GDP of the country by the total population exposed at that shaking intensity level. We then scale the total GDP estimated at each intensity by an exposure correction factor, which is a multiplying factor to account for the disparity between wealth and/or economic assets to the annual GDP. The economic exposure obtained using this procedure is thus a proxy estimate for the economic value of the actual inventory that is exposed to the earthquake. The economic loss ratio, defined in terms of a country-specific lognormal cumulative distribution function of shaking intensity, is derived and calibrated against the losses from past earthquakes. This report describes the development of a country or region-specific economic loss ratio model using economic loss data available for global earthquakes from 1980 to 2007. The proposed model is a potential candidate for directly estimating economic losses within the currently-operating PAGER system. PAGER's other loss models use indirect methods that require substantially more data (such as building/asset inventories, vulnerabilities, and the asset values exposed at the time of earthquake) to implement on a global basis and will thus take more time to develop and implement within the PAGER system.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20111116","usgsCitation":"Jaiswal, K., and Wald, D.J., 2011, Rapid estimation of the economic consequences of global earthquakes: U.S. Geological Survey Open-File Report 2011-1116, iv, 47 p.; 2 Appendixes, https://doi.org/10.3133/ofr20111116.","productDescription":"iv, 47 p.; 2 Appendixes","costCenters":[{"id":301,"text":"Geologic Hazards Team","active":false,"usgs":true}],"links":[{"id":116906,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1116.png"},{"id":204776,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1116/","linkFileType":{"id":5,"text":"html"}},{"id":409813,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_95202.htm","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a80e4b07f02db649616","contributors":{"authors":[{"text":"Jaiswal, Kishor kjaiswal@usgs.gov","contributorId":861,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":false,"id":307954,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":307953,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70157170,"text":"70157170 - 2011 - Well log characterization of natural gas hydrates","interactions":[],"lastModifiedDate":"2021-10-26T16:41:33.343365","indexId":"70157170","displayToPublicDate":"2011-05-18T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Well log characterization of natural gas hydrates","docAbstract":"<p><span>In the last 25 years we have seen significant advancements in the use of downhole well logging tools to acquire detailed information on the occurrence of gas hydrate in nature: From an early start of using wireline electrical resistivity and acoustic logs to identify gas hydrate occurrences in wells drilled in Arctic permafrost environments to today where wireline and advanced logging-while-drilling tools are routinely used to examine the petrophysical nature of gas hydrate reservoirs and the distribution and concentration of gas hydrates within various complex reservoir systems. The most established and well known use of downhole log data in gas hydrate research is the use of electrical resistivity and acoustic velocity data (both compressional- and shear-wave data) to make estimates of gas hydrate content (i.e., reservoir saturations) in various sediment types and geologic settings. New downhole logging tools designed to make directionally oriented acoustic and propagation resistivity log measurements have provided the data needed to analyze the acoustic and electrical anisotropic properties of both highly inter-bedded and fracture dominated gas hydrate reservoirs. Advancements in nuclear-magnetic-resonance (NMR) logging and wireline formation testing have also allowed for the characterization of gas hydrate at the pore scale. Integrated NMR and formation testing studies from northern Canada and Alaska have yielded valuable insight into how gas hydrates are physically distributed in sediments and the occurrence and nature of pore fluids (i.e., free-water along with clay and capillary bound water) in gas-hydrate-bearing reservoirs. Information on the distribution of gas hydrate at the pore scale has provided invaluable insight on the mechanisms controlling the formation and occurrence of gas hydrate in nature along with data on gas hydrate reservoir properties (i.e., permeabilities) needed to accurately predict gas production rates for various gas hydrate production schemes.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"SPWLA 52nd Annual Logging Symposium","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SPWLA 52nd Annual Logging Symposium","conferenceDate":"May 14-18 2011","conferenceLocation":"Colorado Springs, CO","language":"English","publisher":"Society of Petrophysicists and Well-Log Analysts","usgsCitation":"Collett, T.S., and Lee, M.W., 2011, Well log characterization of natural gas hydrates, <i>in</i> SPWLA 52nd Annual Logging Symposium, Colorado Springs, CO, May 14-18 2011, 16 p.","productDescription":"16 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-028902","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":308073,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"560bb720e4b058f706e53fa6","contributors":{"authors":[{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":572120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Myung W. mlee@usgs.gov","contributorId":779,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","email":"mlee@usgs.gov","middleInitial":"W.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":572121,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":99270,"text":"sir20115046 - 2011 - Gulkana Glacier, Alaska-Mass balance, meteorology, and water measurements-1997-2001","interactions":[],"lastModifiedDate":"2024-01-16T22:51:26.939831","indexId":"sir20115046","displayToPublicDate":"2011-05-17T00:00:00","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":"2011-5046","title":"Gulkana Glacier, Alaska-Mass balance, meteorology, and water measurements-1997-2001","docAbstract":"The measured winter snow, maximum winter snow, net, and annual balances for 1997-2001 in the Gulkana Glacier basin are determined at specific points and over the entire glacier area using the meteorological, hydrological, and glaciological data. We provide descriptions of glacier geometry to aid in estimation of conventional and reference surface mass balances and descriptions of ice motion to aid in the understanding of the glacier's response to its changing geometry. These data provide annual estimates for area altitude distribution, equilibrium line altitude, and accumulation area ratio during the study interval. New determinations of historical area altitude distributions are given for 1900 and annually from 1966 to 2001. As original weather instrumentation is nearing the end of its deployment lifespan, we provide new estimates of overlap comparisons and precipitation catch efficiency.\n\nDuring 1997-2001, Gulkana Glacier showed a continued and accelerated negative mass balance trend, especially below the equilibrium line altitude where thinning was pronounced. Ice motion also slowed, which combined with the negative mass balance, resulted in glacier retreat under a warming climate. Average annual runoff augmentation by glacier shrinkage for 1997-2001 was 25 percent compared to the previous average of 13 percent, in accordance with the measured glacier volume reductions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115046","usgsCitation":"March, R.S., and O’Neel, S., 2011, Gulkana Glacier, Alaska-Mass balance, meteorology, and water measurements-1997-2001: U.S. Geological Survey Scientific Investigations Report 2011-5046, viii, 70 p., https://doi.org/10.3133/sir20115046.","productDescription":"viii, 70 p.","additionalOnlineFiles":"N","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":424458,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_95192.htm","linkFileType":{"id":5,"text":"html"}},{"id":115729,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5046/","linkFileType":{"id":5,"text":"html"}},{"id":116114,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5046.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulkana Glacier","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -145.33928137695307,\n              63.2999444760608\n            ],\n            [\n              -145.5156977043993,\n              63.2999444760608\n            ],\n            [\n              -145.5156977043993,\n              63.25130158823154\n            ],\n            [\n              -145.33928137695307,\n              63.25130158823154\n            ],\n            [\n              -145.33928137695307,\n              63.2999444760608\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ae5e4b07f02db68a792","contributors":{"authors":[{"text":"March, Rod S. rsmarch@usgs.gov","contributorId":416,"corporation":false,"usgs":true,"family":"March","given":"Rod","email":"rsmarch@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":307948,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Neel, Shad 0000-0002-9185-0144 soneel@usgs.gov","orcid":"https://orcid.org/0000-0002-9185-0144","contributorId":166740,"corporation":false,"usgs":true,"family":"O’Neel","given":"Shad","email":"soneel@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":307949,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":99264,"text":"fs20113014 - 2011 - Using models for the optimization of hydrologic monitoring","interactions":[],"lastModifiedDate":"2012-03-08T17:16:13","indexId":"fs20113014","displayToPublicDate":"2011-05-17T00:00:00","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":"2011-3014","title":"Using models for the optimization of hydrologic monitoring","docAbstract":"Hydrologists are often asked what kind of monitoring network can most effectively support science-based water-resources management decisions. Currently (2011), hydrologic monitoring locations often are selected by addressing observation gaps in the existing network or non-science issues such as site access. A model might then be calibrated to available data and applied to a prediction of interest (regardless of how well-suited that model is for the prediction). However, modeling tools are available that can inform which locations and types of data provide the most 'bang for the buck' for a specified prediction. Put another way, the hydrologist can determine which observation data most reduce the model uncertainty around a specified prediction.\r\n\r\nAn advantage of such an approach is the maximization of limited monitoring resources because it focuses on the difference in prediction uncertainty with or without additional collection of field data. Data worth can be calculated either through the addition of new data or subtraction of existing information by reducing monitoring efforts (Beven, 1993). The latter generally is not widely requested as there is explicit recognition that the worth calculated is fundamentally dependent on the prediction specified. If a water manager needs a new prediction, the benefits of reducing the scope of a monitoring effort, based on an old prediction, may be erased by the loss of information important for the new prediction.\r\n\r\nThis fact sheet focuses on the worth or value of new data collection by quantifying the reduction in prediction uncertainty achieved be adding a monitoring observation. This calculation of worth can be performed for multiple potential locations (and types) of observations, which then can be ranked for their effectiveness for reducing uncertainty around the specified prediction. This is implemented using a Bayesian approach with the PREDUNC utility in the parameter estimation software suite PEST (Doherty, 2010).\r\n\r\nThe techniques briefly described earlier are described in detail in a U.S. Geological Survey Scientific Investigations Report available on the Internet (Fienen and others, 2010; http://pubs.usgs.gov/sir/2010/5159/). This fact sheet presents a synopsis of the techniques as applied to a synthetic model based on a model constructed using properties from the Lake Michigan Basin (Hoard, 2010).","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/fs20113014","collaboration":"National Water Availability and Use Pilot Program","usgsCitation":"Fienen, M., Hunt, R.J., Doherty, J.E., and Reeves, H.W., 2011, Using models for the optimization of hydrologic monitoring: U.S. Geological Survey Fact Sheet 2011-3014, 6 p., https://doi.org/10.3133/fs20113014.","productDescription":"6 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":116954,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2011_3014.jpg"},{"id":204768,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2011/3014/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a14e4b07f02db602eb1","contributors":{"authors":[{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":893,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","email":"mnfienen@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":307929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":307930,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doherty, John E.","contributorId":8817,"corporation":false,"usgs":false,"family":"Doherty","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":7046,"text":"Watermark Numerical Computing","active":true,"usgs":false}],"preferred":false,"id":307932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reeves, Howard W. 0000-0001-8057-2081 hwreeves@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-2081","contributorId":2307,"corporation":false,"usgs":true,"family":"Reeves","given":"Howard","email":"hwreeves@usgs.gov","middleInitial":"W.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":307931,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":99267,"text":"sir20115037 - 2011 - Sedimentation and occurrence and trends of selected nutrients, other chemical constituents, and cyanobacteria in bottom sediment, Clinton Lake, northeast Kansas, 1977-2009","interactions":[],"lastModifiedDate":"2012-03-08T17:16:13","indexId":"sir20115037","displayToPublicDate":"2011-05-17T00:00:00","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":"2011-5037","title":"Sedimentation and occurrence and trends of selected nutrients, other chemical constituents, and cyanobacteria in bottom sediment, Clinton Lake, northeast Kansas, 1977-2009","docAbstract":"A combination of available bathymetric-survey information and bottom-sediment coring was used to investigate sedimentation and the occurrence of selected nutrients (total nitrogen and total phosphorus), organic and total carbon, 25 trace elements, cyanobacterial akinetes, and the radionuclide cesium-137 in the bottom sediment of Clinton Lake, northeast Kansas. The total estimated volume and mass of bottom sediment deposited from 1977 through 2009 in the conservation (multi-purpose) pool of the reservoir was 438 million cubic feet and 18 billion pounds, respectively. The estimated sediment volume occupied about 8 percent of the conservation-pool, water-storage capacity of the reservoir. Sedimentation in the conservation pool has occurred about 70 percent faster than originally projected at the time the reservoir was completed. Water-storage capacity in the conservation pool has been lost to sedimentation at a rate of about 0.25 percent annually. Mean annual net sediment deposition since 1977 in the conservation pool of the reservoir was estimated to be 563 million pounds per year. Mean annual net sediment yield from the Clinton Lake Basin was estimated to be 1.5 million pounds per square mile per year. Typically, the bottom sediment sampled in Clinton Lake was at least 99 percent silt and clay.\n\nThe mean annual net loads of total nitrogen and total phosphorus deposited in the bottom sediment of Clinton Lake were estimated to be 1.29 million pounds per year and 556,000 pounds per year, respectively. The estimated mean annual net yields of total nitrogen and total phosphorus from the Clinton Lake Basin were 3,510 pounds per square mile per year and 1,510 pounds per square mile per year, respectively. Throughout the history of Clinton Lake, total nitrogen concentrations in the deposited sediment generally were uniform and indicated consistent inputs to the reservoir over time. Likewise, total phosphorus concentrations in the deposited sediment generally were uniform. Although, for two of three coring sites, a possible positive trend in phosphorus deposition was indicated. The Wakarusa River possibly was a larger contributor of nitrogen and phosphorus to Clinton Lake than was Rock Creek. As a principal limiting factor for primary production in most freshwater environments, phosphorus is of particular importance because increased inputs can contribute to accelerated reservoir eutrophication and the production of algal toxins and taste-and-odor compounds.\n\nTrace-element concentrations in the bottom sediment of Clinton Lake generally were uniform over time. As is typical for eastern Kansas reservoirs, arsenic, chromium, and nickel concentrations typically exceeded the threshold-effects guidelines, which represent the concentrations above which toxic biological effects occasionally occur. Zinc concentrations frequently exceeded the threshold-effects guideline. Trace-element concentrations did not exceed the probable-effects guidelines (available for eight trace elements), which represent the concentrations above which toxic biological effects usually or frequently occur.\n\nCyanobacterial akinetes (cyanobacteria resting stage) in the bottom sediment of Clinton Lake, combined with historical water-quality data on chlorophyll-a and total phosphorus concentrations, indicated that the reservoir likely has been eutrophic throughout most of its history. A statistically significant increase in cyanobacterial akinetes in the bottom sediment indicated that Clinton Lake may have become more eutrophic over the life of the reservoir. The increase in cyanobacterial akinetes may, in part, be related to a possible increase in total phosphorus concentrations.","language":"ENGLISH","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115037","collaboration":"Prepared in cooperation with the Kansas Department of Health and Environment","usgsCitation":"Juracek, K.E., 2011, Sedimentation and occurrence and trends of selected nutrients, other chemical constituents, and cyanobacteria in bottom sediment, Clinton Lake, northeast Kansas, 1977-2009: U.S. Geological Survey Scientific Investigations Report 2011-5037, v, 28 p., https://doi.org/10.3133/sir20115037.","productDescription":"v, 28 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":116953,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5037.jpg"},{"id":115730,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5037/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49f6e4b07f02db5f1a32","contributors":{"authors":[{"text":"Juracek, Kyle E. 0000-0002-2102-8980 kjuracek@usgs.gov","orcid":"https://orcid.org/0000-0002-2102-8980","contributorId":2022,"corporation":false,"usgs":true,"family":"Juracek","given":"Kyle","email":"kjuracek@usgs.gov","middleInitial":"E.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":307940,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":99268,"text":"ds593 - 2011 - Suspended-sediment and suspended-sand concentrations and loads for selected streams in the Mississippi River Basin, 1940-2009","interactions":[],"lastModifiedDate":"2012-03-08T17:16:14","indexId":"ds593","displayToPublicDate":"2011-05-17T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"593","title":"Suspended-sediment and suspended-sand concentrations and loads for selected streams in the Mississippi River Basin, 1940-2009","docAbstract":"This report presents suspended-sediment concentration and streamflow data, describes load-estimation techniques used in the computation of annual suspended-sediment loads, and presents annual suspended-sediment loads for 48 streamgaging stations within the Mississippi River Basin. Available published, unpublished, and computed annual total suspended-sediment and suspended-sand loads are presented for water years 1940 through 2009. When previously published annual loads were not available, total suspended-sediment and sand loads were computed using available data for water years 1949 through 2009. A table of suspended-sediment concentration and daily mean streamflow data used in the computation of annual loads is presented along with a table of compiled and computed annual suspended-sediment and suspended-sand loads, annual streamflows, and flow-weighted concentrations for the 48 stations.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ds593","usgsCitation":"Heimann, D.C., Cline, T.L., and Glaspie, L.M., 2011, Suspended-sediment and suspended-sand concentrations and loads for selected streams in the Mississippi River Basin, 1940-2009: U.S. Geological Survey Data Series 593, vi, 6 p.; Downloads Directory, https://doi.org/10.3133/ds593.","productDescription":"vi, 6 p.; Downloads Directory","additionalOnlineFiles":"Y","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":116112,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_593.jpg"},{"id":204771,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/593/","linkFileType":{"id":5,"text":"html"}}],"scale":"2000000","projection":"Albers Equal-Area Conic","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120,25 ], [ -120,48 ], [ -70,48 ], [ -70,25 ], [ -120,25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ae0e4b07f02db687fc8","contributors":{"authors":[{"text":"Heimann, David C. 0000-0003-0450-2545 dheimann@usgs.gov","orcid":"https://orcid.org/0000-0003-0450-2545","contributorId":3822,"corporation":false,"usgs":true,"family":"Heimann","given":"David","email":"dheimann@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":307941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cline, Teri L.","contributorId":80220,"corporation":false,"usgs":true,"family":"Cline","given":"Teri","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":307942,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glaspie, Lori M.","contributorId":98256,"corporation":false,"usgs":true,"family":"Glaspie","given":"Lori","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":307943,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
]}