{"pageNumber":"625","pageRowStart":"15600","pageSize":"25","recordCount":46883,"records":[{"id":70039848,"text":"ds701 - 2012 - Classifications for Coastal Wetlands Planning, Protection and Restoration Act site-specific projects: 2008 and 2009","interactions":[],"lastModifiedDate":"2012-09-08T17:16:16","indexId":"ds701","displayToPublicDate":"2012-09-08T00:00:00","publicationYear":"2012","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":"701","title":"Classifications for Coastal Wetlands Planning, Protection and Restoration Act site-specific projects: 2008 and 2009","docAbstract":"The Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) funds over 100 wetland restoration projects across Louisiana. Integral to the success of CWPPRA is its long-term monitoring program, which enables State and Federal agencies to determine the effectiveness of each restoration effort. One component of this monitoring program is the analysis of high-resolution, color-infrared aerial photography at the U.S. Geological Survey's National Wetlands Research Center in Lafayette, Louisiana. Color-infrared aerial photography (9- by 9-inch) is obtained before project construction and several times after construction. Each frame is scanned on a photogrametric scanner that produces a high-resolution image in Tagged Image File Format (TIFF). By using image-processing software, these TIFF files are then orthorectified and mosaicked to produce a seamless image of a project area and its associated reference area (a control site near the project that has common environmental features, such as marsh type, soil types, and water salinities.) The project and reference areas are then classified according to pixel value into two distinct classes, land and water. After initial land and water ratios have been established by using photography obtained before and after project construction, subsequent comparisons can be made over time to determine land-water change. Several challenges are associated with the land-water interpretation process. Primarily, land-water classifications are often complicated by the presence of floating aquatic vegetation that occurs throughout the freshwater systems of coastal Louisiana and that is sometimes difficult to differentiate from emergent marsh. Other challenges include tidal fluctuations and water movement from strong winds, which may result in flooding and inundation of emergent marsh during certain conditions. Compensating for these events is difficult but possible by using other sources of imagery to verify marsh conditions for other dates in time.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds701","collaboration":"Prepared in cooperation with Coastal Protection and Restoration Authority of Louisiana,  U.S. Army Corps of Engineers, U.S. Environmental Protection Agency, U.S. Fish and Wildlife Service, Natural Resources Conservation Service, and National Oceanic and Atmospheric Administration","usgsCitation":"Jones, W.R., and Garber, A., 2012, Classifications for Coastal Wetlands Planning, Protection and Restoration Act site-specific projects: 2008 and 2009: U.S. Geological Survey Data Series 701, iv, 8 p.; 2008 CWPPRA Map PDF: 17 x 11 inches; 2009 CWPPRA Maps (13 Maps) PDF: 54 x 42 inches or smaller, https://doi.org/10.3133/ds701.","productDescription":"iv, 8 p.; 2008 CWPPRA Map PDF: 17 x 11 inches; 2009 CWPPRA Maps (13 Maps) PDF: 54 x 42 inches or smaller","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":261779,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_701.gif"},{"id":261777,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/701/","linkFileType":{"id":5,"text":"html"}},{"id":261778,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/701/CWPPRA_DS_701.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Louisiana","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94,29 ], [ -94,33 ], [ -89,33 ], [ -89,29 ], [ -94,29 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f631e4b0c8380cd4c5e9","contributors":{"authors":[{"text":"Jones, William R. 0000-0002-5493-4138 jonesb@usgs.gov","orcid":"https://orcid.org/0000-0002-5493-4138","contributorId":463,"corporation":false,"usgs":true,"family":"Jones","given":"William","email":"jonesb@usgs.gov","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":467055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garber, Adrienne 0000-0003-1139-8256 garbera@usgs.gov","orcid":"https://orcid.org/0000-0003-1139-8256","contributorId":464,"corporation":false,"usgs":true,"family":"Garber","given":"Adrienne","email":"garbera@usgs.gov","affiliations":[],"preferred":true,"id":467056,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70039839,"text":"ofr20121178 - 2012 - Profile measurements and data from the 2011 Optics, Acoustics, and Stress In Situ (OASIS) project at the Martha's Vineyard Coastal Observatory","interactions":[],"lastModifiedDate":"2012-09-07T17:16:30","indexId":"ofr20121178","displayToPublicDate":"2012-09-07T00:00:00","publicationYear":"2012","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":"2012-1178","title":"Profile measurements and data from the 2011 Optics, Acoustics, and Stress In Situ (OASIS) project at the Martha's Vineyard Coastal Observatory","docAbstract":"This report documents data collected by the U.S. Geological Survey (USGS) for the Coastal Model Applications and Field Measurements project under the auspices of the U.S. Navy Office of Naval Research Optics, Acoustics, and Stress In Situ (OASIS) Project. The objective of the measurements was to relate optical and acoustic properties of suspended particles to changes in particle size, concentration, and vertical distribution in the bottom boundary layer near the seafloor caused by wave- and current-induced stresses. This information on the physics of particle resuspension and aggregation and light penetration and water clarity will help improve models of sediment transport, benthic primary productivity, and underwater visibility. There is well-established technology for acoustic profiling, but optical profiles are more difficult to obtain because of the rapid attenuation of light in water. A specially modified tripod with a moving arm was designed to solve this problem by moving instruments vertically in the bottom boundary layer, between the bottom and about 2 meters above the seafloor. The profiling arm was designed, built, and tested during spring and summer 2011 by a team of USGS scientists, engineers, and technicians. To accommodate power requirements and the large data files recorded by some of the optical instruments, the tripod was connected via underwater cable to the Martha's Vineyard Coastal Observatory, operated by the Woods Hole Oceanographic Institution (WHOI). This afforded real-time Internet communication with the embedded computers aboard the tripod. Instruments were mounted on the profiling arm, and additional instruments were mounted elsewhere on the tripod and nearby on the seafloor. The tripod and a small mooring for a profiling current meter were deployed on September 17, 2011, at the Martha's Vineyard Coastal Observatory 12-meter-deep underwater node about 2 kilometers south of Martha's Vineyard, Massachusetts. Divers assisted in the deployment and cleaned the instrument surfaces on the tripod approximately once per week until the tripod and current meter were recovered on October 23, 2011. There was a range of wave and current conditions during the 36-day deployment, including the distant passage of Hurricane Ophelia, several moderate wave events, and a significant local gale that generated wave heights greater than 4 meters at the 12-meter site and knocked over the tripod 3 days before it was recovered. All but one of the instruments functioned well and provided complete datasets. The details of these data and the location of files containing the best basic version of the data are described in this report.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121178","usgsCitation":"Sherwood, C.R., Dickhudt, P., Martini, M.A., Montgomery, E., and Boss, E.S., 2012, Profile measurements and data from the 2011 Optics, Acoustics, and Stress In Situ (OASIS) project at the Martha's Vineyard Coastal Observatory: U.S. Geological Survey Open-File Report 2012-1178, HTML Document, https://doi.org/10.3133/ofr20121178.","productDescription":"HTML Document","onlineOnly":"Y","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":261706,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1178.jpg"},{"id":261704,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1178/","linkFileType":{"id":5,"text":"html"}},{"id":261705,"rank":200,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1178/title_page.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Massachusetts","otherGeospatial":"Martha's Vineyard","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -70.83333333333333,41.25 ], [ -70.83333333333333,41.5 ], [ -70.33333333333333,41.5 ], [ -70.33333333333333,41.25 ], [ -70.83333333333333,41.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a8dffe4b0c8380cd7ef6a","contributors":{"authors":[{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":467027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dickhudt, Patrick J.","contributorId":48302,"corporation":false,"usgs":true,"family":"Dickhudt","given":"Patrick J.","affiliations":[],"preferred":false,"id":467028,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martini, Marinna A. 0000-0002-7757-5158 mmartini@usgs.gov","orcid":"https://orcid.org/0000-0002-7757-5158","contributorId":2456,"corporation":false,"usgs":true,"family":"Martini","given":"Marinna","email":"mmartini@usgs.gov","middleInitial":"A.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":467026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Montgomery, Ellyn T.","contributorId":78038,"corporation":false,"usgs":true,"family":"Montgomery","given":"Ellyn T.","affiliations":[],"preferred":false,"id":467030,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boss, Emmanuel S.","contributorId":48811,"corporation":false,"usgs":true,"family":"Boss","given":"Emmanuel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":467029,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70039841,"text":"ds697 - 2012 - Digital spatial data for observed, predicted, and misclassification errors for observations in the training dataset for nitrate and arsenic concentrations in basin-fill aquifers in the Southwest Principal Aquifers study area","interactions":[],"lastModifiedDate":"2017-09-20T12:17:59","indexId":"ds697","displayToPublicDate":"2012-09-07T00:00:00","publicationYear":"2012","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":"697","title":"Digital spatial data for observed, predicted, and misclassification errors for observations in the training dataset for nitrate and arsenic concentrations in basin-fill aquifers in the Southwest Principal Aquifers study area","docAbstract":"This product \"Digital spatial data for observed, predicted, and misclassification errors for observations in the training dataset for nitrate and arsenic concentrations in basin-fill aquifers in the Southwest Principal Aquifers study area\" is a 1:250,000-scale point spatial dataset developed as part of a regional Southwest Principal Aquifers (SWPA) study (Anning and others, 2012). The study examined the vulnerability of basin-fill aquifers in the southwestern United States to nitrate contamination and arsenic enrichment. Statistical models were developed by using the random forest classifier algorithm to predict concentrations of nitrate and arsenic across a model grid that represents local- and basin-scale measures of source, aquifer susceptibility, and geochemical conditions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds697","collaboration":"National Water-Quality Assessment Program","usgsCitation":"McKinney, T., and Anning, D.W., 2012, Digital spatial data for observed, predicted, and misclassification errors for observations in the training dataset for nitrate and arsenic concentrations in basin-fill aquifers in the Southwest Principal Aquifers study area: U.S. Geological Survey Data Series 697, Report: iv, 2 p.; Metadata, https://doi.org/10.3133/ds697.","productDescription":"Report: iv, 2 p.; Metadata","numberOfPages":"10","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":261756,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_697.jpg"},{"id":273229,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/ds697_SWPA_NO3_As_training.xml"},{"id":261748,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/697/","linkFileType":{"id":5,"text":"html"}},{"id":261749,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/697/pdf/ds697.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Nevada, New Mexico, Oregon, Utah","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.4,31.333333333333332 ], [ -124.4,43 ], [ -105,43 ], [ -105,31.333333333333332 ], [ -124.4,31.333333333333332 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a018ae4b0c8380cd4fc4a","contributors":{"authors":[{"text":"McKinney, Tim S.","contributorId":66792,"corporation":false,"usgs":true,"family":"McKinney","given":"Tim S.","affiliations":[],"preferred":false,"id":467033,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anning, David W. dwanning@usgs.gov","contributorId":432,"corporation":false,"usgs":true,"family":"Anning","given":"David","email":"dwanning@usgs.gov","middleInitial":"W.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":467032,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70039844,"text":"sir20125065 - 2012 - Predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwestern United States","interactions":[],"lastModifiedDate":"2019-12-30T14:29:12","indexId":"sir20125065","displayToPublicDate":"2012-09-07T00:00:00","publicationYear":"2012","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":"2012-5065","title":"Predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwestern United States","docAbstract":"<p>The National Water-Quality Assessment (NAWQA) Program of the U.S. Geological Survey (USGS) is conducting a regional analysis of water quality in the principal aquifer systems across the United States. The Southwest Principal Aquifers (SWPA) study is building a better understanding of the susceptibility and vulnerability of basin-fill aquifers in the region to groundwater contamination by synthesizing baseline knowledge of groundwater-quality conditions in 16 basins previously studied by the NAWQA Program. The improved understanding of aquifer susceptibility and vulnerability to contamination is assisting in the development of tools that water managers can use to assess and protect the quality of groundwater resources.</p><p>Human-health concerns and economic considerations associated with meeting drinking-water standards motivated a study of the vulnerability of basin-fill aquifers to nitrate con­tamination and arsenic enrichment in the southwestern United States. Statistical models were developed by using the random forest classifier algorithm to predict concentrations of nitrate and arsenic across a model grid that represents about 190,600 square miles of basin-fill aquifers in parts of Arizona, California, Colorado, Nevada, New Mexico, and Utah. The statistical models, referred to as classifiers, reflect natural and human-related factors that affect aquifer vulnerability to contamina­tion and relate nitrate and arsenic concentrations to explana­tory variables representing local- and basin-scale measures of source, aquifer susceptibility, and geochemical conditions. The classifiers were unbiased and fit the observed data well, and misclassifications were primarily due to statistical sampling error in the training datasets.</p><p>The classifiers were designed to predict concentrations to be in one of six classes for nitrate, and one of seven classes for arsenic. Each classification scheme allowed for identification of areas with concentrations that were equal to or exceeding the U.S. Environmental Protection Agency drinking-water standard. Whereas 2.4 percent of the area underlain by basin-fill aquifers in the study area was predicted to equal or exceed this standard for nitrate (10 milligrams per liter as N; mg/L), 42.7 percent was predicted to equal or exceed the standard for arsenic (10 micrograms per liter; μg/L). Areas predicted to equal or exceed the drinking-water standard for nitrate include basins in central Arizona near Phoenix; the San Joaquin, Inland, and San Jacinto basins of California; and the San Luis Valley of Colorado. Much of the area predicted to equal or exceed the drinking-water standard for arsenic is within a belt of basins along the western portion of the Basin and Range Physiographic Province in Nevada, California, and Arizona. Predicted nitrate and arsenic concentrations are substantially lower than the drinking-water standards in much of the study area—about 93.0 percent of the area underlain by basin-fill aquifers was less than one-half the standard for nitrate (5.0 mg/L), and 50.2 percent was less than one-half the standard for arsenic (5.0 μg/L).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125065","usgsCitation":"Anning, D.W., Paul, A.P., McKinney, T., Huntington, J.M., Bexfield, L.M., and Thiros, S.A., 2012, Predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwestern United States: U.S. Geological Survey Scientific Investigations Report 2012-5065, Report: viii, 115 p.; Metadata; Appendices 1, 2, 8-17, https://doi.org/10.3133/sir20125065.","productDescription":"Report: viii, 115 p.; Metadata; Appendices 1, 2, 8-17","numberOfPages":"128","costCenters":[{"id":128,"text":"Arizona Water Science 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MB","linkFileType":{"id":1,"text":"pdf"}},{"id":332848,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5065/pdf/sir20125065Geology.pdf","text":"Appendix 13","size":"8.2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":332850,"rank":13,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5065/pdf/sir20125065Soil.pdf","text":"Appendix 15","size":"11 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":261753,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5065/pdf/sir20125065.pdf","size":"9.6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":273232,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/ds698_SWPA_NO3_As_prediction.xml"},{"id":332842,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5065/pdf/sir20125065Appendix1and2.xlsx","text":"Appendixes 1 and 2","size":"36 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Center","active":true,"usgs":true}],"preferred":true,"id":467041,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thiros, Susan A. 0000-0002-8544-553X sthiros@usgs.gov","orcid":"https://orcid.org/0000-0002-8544-553X","contributorId":965,"corporation":false,"usgs":true,"family":"Thiros","given":"Susan","email":"sthiros@usgs.gov","middleInitial":"A.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":467040,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70039840,"text":"sir20125137 - 2012 - Development of a flood-warning system and flood-inundation mapping in Licking County, Ohio","interactions":[],"lastModifiedDate":"2012-09-07T17:16:30","indexId":"sir20125137","displayToPublicDate":"2012-09-07T00:00:00","publicationYear":"2012","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":"2012-5137","title":"Development of a flood-warning system and flood-inundation mapping in Licking County, Ohio","docAbstract":"Digital flood-inundation maps for selected reaches of South Fork Licking River, Raccoon Creek, North Fork Licking River, and the Licking River in Licking County, Ohio, were created by the U.S. Geological Survey (USGS), in cooperation with the Ohio Department of Transportation; U.S. Department of Transportation, Federal Highway Administration; Muskingum Watershed Conservancy District; U.S. Department of Agriculture, Natural Resources Conservation Service; and the City of Newark and Village of Granville, Ohio. The inundation maps depict estimates of the areal extent of flooding corresponding to water levels (stages) at the following USGS streamgages: South Fork Licking River at Heath, Ohio (03145173); Raccoon Creek below Wilson Street at Newark, Ohio (03145534); North Fork Licking River at East Main Street at Newark, Ohio (03146402); and Licking River near Newark, Ohio (03146500). The maps were provided to the National Weather Service (NWS) for incorporation into a Web-based flood-warning system that can be used in conjunction with NWS flood-forecast data to show areas of predicted flood inundation associated with forecasted flood-peak stages. As part of the flood-warning streamflow network, the USGS re-installed one streamgage on North Fork Licking River, and added three new streamgages, one each on North Fork Licking River, South Fork Licking River, and Raccoon Creek. Additionally, the USGS upgraded a lake-level gage on Buckeye Lake. Data from the streamgages and lake-level gage can be used by emergency-management personnel, in conjunction with the flood-inundation maps, to help determine a course of action when flooding is imminent. Flood profiles for selected reaches were prepared by calibrating steady-state step-backwater models to selected, established streamgage rating curves. The step-backwater models then were used to determine water-surface-elevation profiles for up to 10 flood stages at a streamgage with corresponding streamflows ranging from approximately the 50 to 0.2-percent chance annual-exceedance probabilities for each of the 4 streamgages that correspond to the flood-inundation maps. The computed flood profiles were used in combination with digital elevation data to delineate flood-inundation areas. Maps of Licking County showing flood-inundation areas overlain on digital orthophotographs are presented for the selected floods. The USGS also developed an unsteady-flow model for a reach of South Fork Licking River for use by the NWS to enhance their ability to provide advanced flood warning in the region north of Buckeye Lake, Ohio. The unsteady-flow model was calibrated based on data from four flooding events that occurred from June 2008 to December 2011. Model calibration was approximate due to the fact that there were unmeasured inflows to the river that were not able to be considered during the calibration. Information on unmeasured inflow derived from NWS hydrologic models and additional flood-event data could enable the NWS to further refine the unsteady-flow model.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125137","collaboration":"39 plates (PDF and JPEG formats) available through the index page link displayed at the top of this record. Prepared in cooperation with the Ohio Department of Transportation; U.S. Department of Transportation, Federal Highway Administration; Muskingum Watershed Conservancy District; U.S. Department of Agriculture, Natural Resources Conservation Service; and the City of Newark and Village of Granville, Ohio","usgsCitation":"Ostheimer, C.J., 2012, Development of a flood-warning system and flood-inundation mapping in Licking County, Ohio: U.S. Geological Survey Scientific Investigations Report 2012-5137, vii, 13 p.; 39 Plates (PDF and JPEG format): 13 x 13 inches or smaller; Downloads Directory, https://doi.org/10.3133/sir20125137.","productDescription":"vii, 13 p.; 39 Plates (PDF and JPEG format): 13 x 13 inches or smaller; Downloads Directory","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":513,"text":"Ohio Water Science 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States","state":"Ohio","county":"Licking","city":"Newark","otherGeospatial":"Buckeye Lake;Licking River;Raccoon Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -82.7675,40 ], [ -82.7675,40.26777777777777 ], [ -82.18333333333334,40.26777777777777 ], [ -82.18333333333334,40 ], [ -82.7675,40 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0039e4b0c8380cd4f651","contributors":{"authors":[{"text":"Ostheimer, Chad J. ostheime@usgs.gov","contributorId":2160,"corporation":false,"usgs":true,"family":"Ostheimer","given":"Chad","email":"ostheime@usgs.gov","middleInitial":"J.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":467031,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70039842,"text":"ds698 - 2012 - Digital spatial data for predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwest Principal Aquifers study area","interactions":[],"lastModifiedDate":"2017-09-20T12:18:45","indexId":"ds698","displayToPublicDate":"2012-09-07T00:00:00","publicationYear":"2012","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":"698","title":"Digital spatial data for predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwest Principal Aquifers study area","docAbstract":"This product \"Digital spatial data for predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwest Principal Aquifers study area\" is a 1:250,000-scale vector spatial dataset developed as part of a regional Southwest Principal Aquifers (SWPA) study (Anning and others, 2012). The study examined the vulnerability of basin-fill aquifers in the southwestern United States to nitrate contamination and arsenic enrichment. Statistical models were developed by using the random forest classifier algorithm to predict concentrations of nitrate and arsenic across a model grid that represents local- and basin-scale measures of source, aquifer susceptibility, and geochemical conditions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds698","collaboration":"National Water-Quality Assessment Program","usgsCitation":"McKinney, T., and Anning, D.W., 2012, Digital spatial data for predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwest Principal Aquifers study area: U.S. Geological Survey Data Series 698, iv, 2 p., https://doi.org/10.3133/ds698.","productDescription":"iv, 2 p.","numberOfPages":"10","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":261757,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_698.jpg"},{"id":261750,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/698/","linkFileType":{"id":5,"text":"html"}},{"id":261751,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/698/pdf/ds698.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Nevada, New Mexico, Oregon, Utah","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.4,31.333333333333332 ], [ -124.4,43 ], [ -105,43 ], [ -105,31.333333333333332 ], [ -124.4,31.333333333333332 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a018be4b0c8380cd4fc4d","contributors":{"authors":[{"text":"McKinney, Tim S.","contributorId":66792,"corporation":false,"usgs":true,"family":"McKinney","given":"Tim S.","affiliations":[],"preferred":false,"id":467035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anning, David W. dwanning@usgs.gov","contributorId":432,"corporation":false,"usgs":true,"family":"Anning","given":"David","email":"dwanning@usgs.gov","middleInitial":"W.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":467034,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70039819,"text":"sir20125150 - 2012 - Comparison of streamflow and water-quality data collection techniques for the Saginaw River, Michigan","interactions":[],"lastModifiedDate":"2012-09-07T01:01:55","indexId":"sir20125150","displayToPublicDate":"2012-09-06T00:00:00","publicationYear":"2012","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":"2012-5150","title":"Comparison of streamflow and water-quality data collection techniques for the Saginaw River, Michigan","docAbstract":"In 2009, the Michigan Department of Environmental Quality and the U.S. Geological Survey developed a plan to compare the effect of various streamgaging and water-quality collection techniques on streamflow and stream water-quality data for the Saginaw River, Michigan. The Saginaw River is the primary contributor of surface runoff to Saginaw Bay, Lake Huron, draining approximately 70 percent of the Saginaw Bay watershed. The U.S. Environmental Protection Agency has listed the Saginaw Bay system as an \"Area of Concern\" due to many factors, including excessive sediment and nutrient concentrations in the water. Current efforts to estimate loading of sediment and nutrients to Saginaw Bay utilize water-quality samples collected using a surface-grab technique and flow data that are uncertain during specific conditions. Comparisons of current flow and water-quality sampling techniques to alternative techniques were assessed between April 2009 and September 2009 at two locations in the Saginaw River. Streamflow estimated using acoustic Doppler current profiling technology was compared to a traditional stage-discharge technique. Complex conditions resulting from the influence of Saginaw Bay on the Saginaw River were able to be captured using the acoustic technology, while the traditional stage-discharge technique failed to quantify these effects. Water-quality samples were collected at two locations and on eight different dates, utilizing both surface-grab and depth-integrating multiple-vertical techniques. Sixteen paired samples were collected and analyzed for suspended sediment, turbidity, total phosphorus, total nitrogen, orthophosphate, nitrite, nitrate, and ammonia. Results indicate that concentrations of constituents associated with suspended material, such as suspended sediment, turbidity, and total phosphorus, are underestimated when samples are collected using the surface-grab technique. The median magnitude of the relative percent difference in concentration based on sampling technique was 37 percent for suspended sediment, 26 percent for turbidity, and 9.7 percent for total phosphorus samples collected at both. Acoustic techniques were also used to assist in the determination of the effectiveness of using acoustic-backscatter information for estimating the suspended-sediment concentration of the river water. Backscatter data was collected by use of an acoustic Doppler current profiler, and a Van Dorn manual sampler was simultaneously used to collect discrete water samples at 10 depths (3.5, 7.5, 11, 14, 15.5, 17.5, 19.5, 20.5, 22, and 24.5 ft below the water surface) along two vertical profiles near the center of the Saginaw River near Bay City. The Van Dorn samples were analyzed for suspended-sediment concentrations, and these data were then used to develop a relationship between acoustic-backscatter data. Acoustic-backscatter data was strongly correlated to sediment concentrations and, by using a linear regression, was able to explain 89 percent of the variability. Although this regression technique showed promise for using acoustic backscatter to estimate suspended-sediment concentration, attempts to compare suspended-sediment concentrations to the acoustic signal-to-noise ratio estimates, recorded at the fixed acoustic streamflow-gaging station near Bay City (04157061), resulted in a poor correlation.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125150","collaboration":"Prepared in cooperation with the Michigan Department of Environmental Quality","usgsCitation":"Hoard, C.J., Holtschlag, D., Duris, J., James, D., and Obenauer, D., 2012, Comparison of streamflow and water-quality data collection techniques for the Saginaw River, Michigan: U.S. Geological Survey Scientific Investigations Report 2012-5150, vi, 28 p.; col. ill.; maps (col.), https://doi.org/10.3133/sir20125150.","productDescription":"vi, 28 p.; col. ill.; maps (col.)","startPage":"i","endPage":"28","numberOfPages":"38","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":260246,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5150.gif"},{"id":260245,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5150/pdf/SIR2012-5150.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260244,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5150/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Michigan","otherGeospatial":"Saginaw River","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f892e4b0c8380cd4d1c0","contributors":{"authors":[{"text":"Hoard, C. J.","contributorId":37436,"corporation":false,"usgs":true,"family":"Hoard","given":"C.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":466994,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holtschlag, D. J. 0000-0001-5185-4928","orcid":"https://orcid.org/0000-0001-5185-4928","contributorId":102493,"corporation":false,"usgs":true,"family":"Holtschlag","given":"D. J.","affiliations":[],"preferred":false,"id":466997,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duris, J.W.","contributorId":62835,"corporation":false,"usgs":true,"family":"Duris","given":"J.W.","email":"","affiliations":[],"preferred":false,"id":466996,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"James, D.A.","contributorId":108225,"corporation":false,"usgs":true,"family":"James","given":"D.A.","email":"","affiliations":[],"preferred":false,"id":466998,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Obenauer, D.J.","contributorId":50768,"corporation":false,"usgs":true,"family":"Obenauer","given":"D.J.","email":"","affiliations":[],"preferred":false,"id":466995,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70039828,"text":"ofr20121200 - 2012 - Survival and migration route probabilities of juvenile Chinook salmon in the Sacramento-San Joaquin River Delta during the winter of 2009-10","interactions":[],"lastModifiedDate":"2016-05-03T16:12:39","indexId":"ofr20121200","displayToPublicDate":"2012-09-06T00:00:00","publicationYear":"2012","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":"2012-1200","title":"Survival and migration route probabilities of juvenile Chinook salmon in the Sacramento-San Joaquin River Delta during the winter of 2009-10","docAbstract":"<p>Juvenile Chinook salmon (<i>Oncorhynchus tshawytscha</i>) emigrating from natal tributaries of the Sacramento River may use a number of migration routes to negotiate the Sacramento-San Joaquin River Delta (hereafter, \"the Delta\"), each of which may influence their probability of surviving. We applied a mark-recapture model to data from acoustically tagged juvenile late-fall Chinook salmon that migrated through the Delta during the winter of 2009-10 (hereafter, 2010). This report presents findings from our fourth year of research. We estimated route-specific survival for four release groups: two release groups that migrated through the Delta in December 2009 and January 2010, and two release groups that migrated during February 2010. Population-level survival through the Delta (<i>S</i><sub>Delta</sub>) ranged from 0.374 (SE = 0.040) to 0.524 (SE = 0.034) among releases. Although river flows for the February release groups were substantially higher (20,000-40,000 ft<sup>3</sup>/s at Freeport) than for the December release groups (about 10,000 ft<sup>3</sup>/s), <i>S</i><sub>Delta</sub> did not differ considerably between release groups. Among migration routes, fish migrating through the Sacramento River exhibited the highest survival, and fish entering the interior Delta exhibited the lowest survival. Fish entering Sutter and Steamboat Sloughs had lower survival than fish entering the Sacramento River during December, but similar survival during February. These patterns were consistent among release groups, and strikingly similar to patterns observed in previous years. Migration routing varied among release groups partly because of differences in river discharge between releases. For the two December release groups, 26.5 and 28.9 percent of fish entered the interior Delta; for the two February release groups, 10.4 and 17.9 percent of fish entered the interior Delta. Differences in routing probabilities between December and February are partly related to the inverse relationship between flow and the fraction of discharge entering the interior Delta. The proportion of fish diverted into the interior Delta also can be affected by the status of the Delta Cross Channel's gates. The fraction of fish entering Sutter and Steamboat Sloughs also varied considerably among release groups from 22.1 to 44.7 percent, and did not appear correlated to river discharge. For example, the lowest and highest proportion of fish entering Sutter and Steamboat Sloughs occurred during February. Because fish entering Sutter and Steamboat Sloughs bypass the entrance to the interior Delta, a high proportion of fish migrating into this route reduces the proportion of fish entering the interior Delta.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121200","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service. Other contributors: U.S. Army Corps of Engineers and University of California at Davis","usgsCitation":"Perry, R.W., Romine, J.G., Brewer, S.J., LaCivita, P.E., Brostoff, W.N., and Chapman, E.D., 2012, Survival and migration route probabilities of juvenile Chinook salmon in the Sacramento-San Joaquin River Delta during the winter of 2009-10: U.S. Geological Survey Open-File Report 2012-1200, iv, 30 p., https://doi.org/10.3133/ofr20121200.","productDescription":"iv, 30 p.","numberOfPages":"38","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":261696,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1200.jpg"},{"id":261691,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1200/","linkFileType":{"id":5,"text":"html"}},{"id":261692,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1200/pdf/ofr20121200.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"California","city":"Sacramento","otherGeospatial":"Sacramento-San Joaquin River Delta","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.25,37.75 ], [ -122.25,38.583333333333336 ], [ -121.36666666666666,38.583333333333336 ], [ -121.36666666666666,37.75 ], [ -122.25,37.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505ba2b3e4b08c986b31f8c8","contributors":{"authors":[{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":467006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romine, Jason G. 0000-0002-6938-1185 jromine@usgs.gov","orcid":"https://orcid.org/0000-0002-6938-1185","contributorId":2823,"corporation":false,"usgs":true,"family":"Romine","given":"Jason","email":"jromine@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":467007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Scott J. sbrewer@usgs.gov","contributorId":4407,"corporation":false,"usgs":true,"family":"Brewer","given":"Scott","email":"sbrewer@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":467008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LaCivita, Peter E.","contributorId":101507,"corporation":false,"usgs":true,"family":"LaCivita","given":"Peter","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":467011,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brostoff, William N.","contributorId":52828,"corporation":false,"usgs":true,"family":"Brostoff","given":"William","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":467010,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chapman, Eric D.","contributorId":34377,"corporation":false,"usgs":true,"family":"Chapman","given":"Eric","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":467009,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70039813,"text":"sim3222 - 2012 - Earthquakes and faults in southern California (1970-2010)","interactions":[],"lastModifiedDate":"2014-04-24T15:37:33","indexId":"sim3222","displayToPublicDate":"2012-09-05T00:00:00","publicationYear":"2012","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":"3222","title":"Earthquakes and faults in southern California (1970-2010)","docAbstract":"The map depicts both active and inactive faults and earthquakes magnitude 1.5 to 7.3 in southern California (1970&ndash;2010). The bathymetry was generated from digital files from the California Department of Fish And Game, Marine Region, Coastal Bathymetry Project. Elevation data are from the U.S. Geological Survey National Elevation Database. Landsat satellite image is from fourteen Landsat 5 Thematic Mapper scenes collected between 2009 and 2010. Fault data are reproduced with permission from 2006 California Geological Survey and U.S. Geological Survey data. The earthquake data are from the U.S. Geological Survey National Earthquake Information Center.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3222","usgsCitation":"Sleeter, B.M., Calzia, J.P., and Walter, S.R., 2012, Earthquakes and faults in southern California (1970-2010): U.S. Geological Survey Scientific Investigations Map 3222, Map: 1 Sheet: 48 x 36 inches, https://doi.org/10.3133/sim3222.","productDescription":"Map: 1 Sheet: 48 x 36 inches","numberOfPages":"1","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1970-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":260172,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3222.png"},{"id":260170,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3222/","linkFileType":{"id":5,"text":"html"}},{"id":260171,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3222/sim3222_poster.pdf","linkFileType":{"id":1,"text":"pdf"}}],"scale":"450000","projection":"Albers Conical Equal Area Projection","datum":"North American Horizontal Datum of 1983; National Geodetic Vertical Datum of 1929","country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121,32.75 ], [ -121,35.083333333333336 ], [ -115,35.083333333333336 ], [ -115,32.75 ], [ -121,32.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a050fe4b0c8380cd50c48","contributors":{"authors":[{"text":"Sleeter, Benjamin M. 0000-0003-2371-9571 bsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-2371-9571","contributorId":3479,"corporation":false,"usgs":true,"family":"Sleeter","given":"Benjamin","email":"bsleeter@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":466977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Calzia, James P. jcalzia@usgs.gov","contributorId":2801,"corporation":false,"usgs":true,"family":"Calzia","given":"James","email":"jcalzia@usgs.gov","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":466976,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walter, Stephen R.","contributorId":34954,"corporation":false,"usgs":true,"family":"Walter","given":"Stephen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":466978,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70039805,"text":"ofr20121154 - 2012 - Landscape consequences of natural gas extraction in Bradford and Washington Counties, Pennsylvania, 2004-2010","interactions":[],"lastModifiedDate":"2016-08-19T17:19:54","indexId":"ofr20121154","displayToPublicDate":"2012-09-05T00:00:00","publicationYear":"2012","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":"2012-1154","title":"Landscape consequences of natural gas extraction in Bradford and Washington Counties, Pennsylvania, 2004-2010","docAbstract":"<p>Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is undergoing extensive drilling and production. The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in the area of Pennsylvania. Coalbed methane, which is sometimes extracted using the same technique, is often located in the same general area as the Marcellus Shale and is frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Bradford County and Washington County, Pennsylvania, between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics is used to quantify these changes and are included in this publication.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121154","usgsCitation":"Slonecker, E., Milheim, L., Roig-Silva, C., Malizia, A., Marr, D., and Fisher, G., 2012, Landscape consequences of natural gas extraction in Bradford and Washington Counties, Pennsylvania, 2004-2010: U.S. Geological Survey Open-File Report 2012-1154, v, 36 p., https://doi.org/10.3133/ofr20121154.","productDescription":"v, 36 p.","numberOfPages":"41","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":242,"text":"Eastern Geographic Science 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A.R.","contributorId":98991,"corporation":false,"usgs":true,"family":"Malizia","given":"A.R.","email":"","affiliations":[],"preferred":false,"id":466958,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marr, D.A.","contributorId":32772,"corporation":false,"usgs":true,"family":"Marr","given":"D.A.","email":"","affiliations":[],"preferred":false,"id":466954,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fisher, G.B.","contributorId":70238,"corporation":false,"usgs":true,"family":"Fisher","given":"G.B.","email":"","affiliations":[],"preferred":false,"id":466957,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70039818,"text":"sim3229 - 2012 - Bathymetry and capacity of Blackfoot Reservoir, Caribou County, Idaho, 2011","interactions":[],"lastModifiedDate":"2019-08-28T09:24:18","indexId":"sim3229","displayToPublicDate":"2012-09-05T00:00:00","publicationYear":"2012","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":"3229","title":"Bathymetry and capacity of Blackfoot Reservoir, Caribou County, Idaho, 2011","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the Shoshone-Bannock Tribes, surveyed the bathymetry and selected above-water sections of Blackfoot Reservoir, Caribou County, Idaho, in 2011. Reservoir operators manage releases from Government Dam on Blackfoot Reservoir based on a stage-capacity relation developed about the time of dam construction in the early 1900s. Reservoir operation directly affects the amount of water that is available for irrigation of agricultural land on the Fort Hall Indian Reservation and surrounding areas. The USGS surveyed the below-water sections of the reservoir using a multibeam echosounder and real-time kinematic global positioning system (RTK-GPS) equipment at full reservoir pool in June 2011, covering elevations from 6,090 to 6,119 feet (ft) above the North American Vertical Datum of 1988 (NAVD 88). The USGS used data from a light detection and ranging (LiDAR) survey performed in 2000 to map reservoir bathymetry from 6,116 to 6,124 ft NAVD 88, which were mostly in depths too shallow to measure with the multibeam echosounder, and most of the above-water section of the reservoir (above 6,124 ft NAVD 88). Selected points and bank erosional features were surveyed by the USGS using RTK-GPS and a total station at low reservoir pool in September 2011 to supplement and verify the LiDAR data. The stage-capacity relation was revised and presented in a tabular format. The datasets show a 2.0-percent decrease in capacity from the original survey, due to sedimentation or differences in accuracy between surveys. A 1.3-percent error also was detected in the previously used capacity table and measured water-level elevation because of questionable reference elevation at monitoring stations near Government Dam. Reservoir capacity in 2011 at design maximum pool of 6,124 ft above NAVD 88 was 333,500 acre-ft.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3229","collaboration":"Prepared in cooperation with the Shoshone-Bannock Tribes","usgsCitation":"Wood, M.S., Skinner, K.D., and Fosness, R.L., 2012, Bathymetry and capacity of Blackfoot Reservoir, Caribou County, Idaho, 2011: U.S. Geological Survey Scientific Investigations Map 3229, 1 Plate: 44 x 34 inches, https://doi.org/10.3133/sim3229.","productDescription":"1 Plate: 44 x 34 inches","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":260235,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3229.jpg"},{"id":366919,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5d3f5385e4b01d82ce8d93a3","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Bathymetry of Blackfoot Reservoir, Caribou County, Idaho, 2011"},{"id":260211,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3229/","linkFileType":{"id":5,"text":"html"}},{"id":260213,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3229/pdf/sim3229.pdf","linkFileType":{"id":1,"text":"pdf"}}],"datum":"North American Vertical Datum of 1988","country":"United States","state":"Idaho","county":"Caribou","city":"Idaho Falls, Soda Springs","otherGeospatial":"Blackfoot Reservoir","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.75,42.81666666666667 ], [ -111.75,43.03333333333333 ], [ -111.5,43.03333333333333 ], [ -111.5,42.81666666666667 ], [ -111.75,42.81666666666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f015e4b0c8380cd4a5b9","contributors":{"authors":[{"text":"Wood, Molly S. 0000-0002-5184-8306 mswood@usgs.gov","orcid":"https://orcid.org/0000-0002-5184-8306","contributorId":788,"corporation":false,"usgs":true,"family":"Wood","given":"Molly","email":"mswood@usgs.gov","middleInitial":"S.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466991,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skinner, Kenneth D. 0000-0003-1774-6565 kskinner@usgs.gov","orcid":"https://orcid.org/0000-0003-1774-6565","contributorId":1836,"corporation":false,"usgs":true,"family":"Skinner","given":"Kenneth","email":"kskinner@usgs.gov","middleInitial":"D.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466992,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fosness, Ryan L. 0000-0003-4089-2704 rfosness@usgs.gov","orcid":"https://orcid.org/0000-0003-4089-2704","contributorId":2703,"corporation":false,"usgs":true,"family":"Fosness","given":"Ryan","email":"rfosness@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466993,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70039806,"text":"70039806 - 2012 - Potential pollutant sources in a Choptank River (USA) subwatershed and the influence of land use and watershed characteristics","interactions":[],"lastModifiedDate":"2012-09-07T17:16:30","indexId":"70039806","displayToPublicDate":"2012-09-05T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Potential pollutant sources in a Choptank River (USA) subwatershed and the influence of land use and watershed characteristics","docAbstract":"Row-crop and poultry production have been implicated as sources of water pollution along the Choptank River, an estuary and tributary of the Chesapeake Bay. This study examined the effects of land use, subwatershed characteristics, and climatic conditions on the water quality parameters of a subwatershed in the Choptank River watershed. The catchments within the subwatershed were defined using advanced remotely-sensed data and current geographic information system processing techniques. Water and sediment samples were collected in May&ndash;October 2009 and April&ndash;June 2010 under mostly baseflow conditions and analyzed for select bacteria, nitrate-N, ammonium-N, total arsenic, total phosphorus (TP), orthophosphate (ortho-P), and particle-phase phosphorus (PP); <i>n</i> = 96 for all analytes except for arsenic, <i>n</i> = 136, and for bacteria, <i>n</i> = 89 (aqueous) and 62 (sediment). Detections of Enterococci and Escherichia coli concentrations were ubiquitous in this subwatershed and showed no correlation to location or land use, however larger bacterial counts were observed shortly after precipitation. Nitrate-N concentrations were not correlated with agricultural lands, which may reflect the small change in percent agriculture and/or the similarity of agronomic practices and crops produced between catchments. Concentration data suggested that ammonia emission and possible deposition to surface waters occurred and that these processes may be influenced by local agronomic practices and climatic conditions. The negative correlation of PP and arsenic concentrations with percent forest was explained by the stronger signal of the head waters and overland flow of particulate phase analytes versus dissolved phase inputs from groundwater. Service roadways at some poultry production facilities were found to redirect runoff from the facilities to neighboring catchment areas, which affected water quality parameters. Results suggest that in this subwatershed, catchments with poultry production facilities are possible sources for arsenic and PP as compared to catchment areas where these facilities were not present.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Science of the Total Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.scitotenv.2012.03.056","usgsCitation":"Nino de Guzman, G.T., Hapeman, C.J., Prabhakara, K., Codling, E.E., Shelton, D.R., Rice, C.P., Hively, W., McCarty, G.W., Lang, M., and Torrents, A., 2012, Potential pollutant sources in a Choptank River (USA) subwatershed and the influence of land use and watershed characteristics: Science of the Total Environment, v. 430, p. 270-279, https://doi.org/10.1016/j.scitotenv.2012.03.056.","productDescription":"10 p.","startPage":"270","endPage":"279","numberOfPages":"9","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":260179,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.scitotenv.2012.03.056","linkFileType":{"id":5,"text":"html"}},{"id":260187,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Choptank River","volume":"430","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a7f52e4b0c8380cd7aa76","contributors":{"authors":[{"text":"Nino de Guzman, Gabriela T.","contributorId":44785,"corporation":false,"usgs":true,"family":"Nino de Guzman","given":"Gabriela","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":466963,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hapeman, Cathleen J.","contributorId":63154,"corporation":false,"usgs":true,"family":"Hapeman","given":"Cathleen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":466966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prabhakara, Kusuma","contributorId":6313,"corporation":false,"usgs":true,"family":"Prabhakara","given":"Kusuma","email":"","affiliations":[],"preferred":false,"id":466960,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Codling, Eton E.","contributorId":18616,"corporation":false,"usgs":true,"family":"Codling","given":"Eton","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":466962,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shelton, Daniel R.","contributorId":66112,"corporation":false,"usgs":true,"family":"Shelton","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":466967,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rice, Clifford P.","contributorId":56594,"corporation":false,"usgs":true,"family":"Rice","given":"Clifford","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":466964,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":9391,"corporation":false,"usgs":true,"family":"Hively","given":"W. Dean","affiliations":[],"preferred":false,"id":466961,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCarty, Gregory W.","contributorId":78861,"corporation":false,"usgs":true,"family":"McCarty","given":"Gregory","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":466968,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lang, Megan W.","contributorId":58014,"corporation":false,"usgs":true,"family":"Lang","given":"Megan W.","affiliations":[],"preferred":false,"id":466965,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Torrents, Alba","contributorId":94906,"corporation":false,"usgs":true,"family":"Torrents","given":"Alba","email":"","affiliations":[],"preferred":false,"id":466969,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70039814,"text":"sir20125161 - 2012 - Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida","interactions":[{"subject":{"id":70038861,"text":"ofr20121132 - 2012 - Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida","indexId":"ofr20121132","publicationYear":"2012","noYear":false,"title":"Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida"},"predicate":"SUPERSEDED_BY","object":{"id":70039814,"text":"sir20125161 - 2012 - Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida","indexId":"sir20125161","publicationYear":"2012","noYear":false,"title":"Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida"},"id":1}],"lastModifiedDate":"2018-04-02T15:33:30","indexId":"sir20125161","displayToPublicDate":"2012-09-05T00:00:00","publicationYear":"2012","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":"2012-5161","title":"Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida","docAbstract":"A numerical transient model of the surficial and Floridan aquifer systems in east-central Florida was developed to (1) increase the understanding of water exchanges between the surficial and the Floridan aquifer systems, (2) assess the recharge rates to the surficial aquifer system from infiltration through the unsaturated zone and (3) obtain a simulation tool that could be used by water-resource managers to assess the impact of changes in groundwater withdrawals on spring flows and on the potentiometric surfaces of the hydrogeologic units composing the Floridan aquifer system. The hydrogeology of east-central Florida was evaluated and used to develop and calibrate the groundwater flow model, which simulates the regional fresh groundwater flow system. The U.S. Geological Survey three-dimensional groundwater flow model, MODFLOW-2005, was used to simulate transient groundwater flow in the surficial, intermediate, and Floridan aquifer systems from 1995 to 2006. The East-Central Florida Transient model encompasses an actively simulated area of about 9,000 square miles. Although the model includes surficial processes-rainfall, irrigation, evapotranspiration (ET), runoff, infiltration, lake water levels, and stream water levels and flows-its primary purpose is to characterize and refine the understanding of groundwater flow in the Floridan aquifer system. Model-independent estimates of the partitioning of rainfall into ET, streamflow, and aquifer recharge are provided from a water-budget analysis of the surficial aquifer system. The interaction of the groundwater flow system with the surface environment was simulated using the Green-Ampt infiltration method and the MODFLOW-2005 Unsaturated-Zone Flow, Lake, and Streamflow-Routing Packages. The model is intended to simulate the part of the groundwater system that contains freshwater. The bottom and lateral boundaries of the model were established at the estimated depths where the chloride concentration is 5,000 milligrams per liter in the Floridan aquifer system. Potential flow across the interface represented by this chloride concentration is simulated by the General Head Boundary Package. During 1995 through 2006, there were no major groundwater withdrawals near the freshwater and saline-water interface, making the general head boundary a suitable feature to estimate flow through the interface.  The east-central Florida transient model was calibrated using the inverse parameter estimation code, PEST. Steady-state models for 1999 and 2003 were developed to estimate hydraulic conductivity (K) using average annual heads and spring flows as observations. The spatial variation of K was represented using zones of constant values in some layers, and pilot points in other layers. Estimated K values were within one order of magnitude of aquifer performance test data. A simulation of the final two years (2005-2006) of the 12-year model, with the K estimates from the steady-state calibration, was used to guide the estimation of specific yield and specific storage values. The final model yielded head and spring-flow residuals that met the calibration criteria for the 12-year transient simulation. The overall mean residual for heads, defining residual as simulated minus measured value, was -0.04 foot. The overall root-mean square residual for heads was less than 3.6 feet for each year in the 1995 to 2006 simulation period. The overall mean residual for spring flows was -0.3 cubic foot per second. The spatial distribution of head residuals was generally random, with some minor indications of bias. Simulated average ET over the 1995 to 2006 period was 34.47 inches per year, compared to the calculated average ET rate of 36.39 inches per year from the model-independent water-budget analysis. Simulated average net recharge to the surficial aquifer system was 3.58 inches per year, compared with the calculated average of 3.39 inches per year from the model-independent water-budget analysis. Groundwater withdrawals from the Floridan aquifer system averaged about 920 million gallons per day, which is equivalent to about 2 inches per year over the model area and slightly more than half of the simulated average net recharge to the surficial aquifer system over the same period. Annual net simulated recharge rates to the surficial aquifer system were less than the total groundwater withdrawals from the Floridan aquifer system only during the below-average rainfall years of 2000 and 2006.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125161","collaboration":"Prepared in cooperation with the St. Johns River Water Management District, South Florida Water Management District, and Southwest Florida Water Management District","usgsCitation":"Sepulveda, N., Tiedeman, C.R., O’Reilly, A.M., Davis, J.B., and Burger, P., 2012, Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida: U.S. Geological Survey Scientific Investigations Report 2012-5161, xiii, 214 p., https://doi.org/10.3133/sir20125161.","productDescription":"xiii, 214 p.","onlineOnly":"Y","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"links":[{"id":260178,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5161.jpg"},{"id":260176,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5161/pdf/2012-5161.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260177,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5161/","linkFileType":{"id":5,"text":"html"}}],"projection":"Universal Transverse Mercator, zone 17","country":"United States","state":"Florida","county":"Lake;Osceola;Orange;Polk;Seminole","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -82,27.5 ], [ -82,29 ], [ -80.5,29 ], [ -80.5,27.5 ], [ -82,27.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a2da0e4b0c8380cd5bf67","contributors":{"authors":[{"text":"Sepulveda, Nicasio 0000-0002-6333-1865 nsepul@usgs.gov","orcid":"https://orcid.org/0000-0002-6333-1865","contributorId":1454,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Nicasio","email":"nsepul@usgs.gov","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":466979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tiedeman, Claire R. 0000-0002-0128-3685 tiedeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0128-3685","contributorId":196777,"corporation":false,"usgs":true,"family":"Tiedeman","given":"Claire","email":"tiedeman@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":466982,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Reilly, Andrew M. 0000-0003-3220-1248 aoreilly@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-1248","contributorId":2184,"corporation":false,"usgs":true,"family":"O’Reilly","given":"Andrew","email":"aoreilly@usgs.gov","middleInitial":"M.","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":466980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Jeffrey B.","contributorId":50168,"corporation":false,"usgs":true,"family":"Davis","given":"Jeffrey","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":466981,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burger, Patrick","contributorId":90976,"corporation":false,"usgs":true,"family":"Burger","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":466983,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70040327,"text":"ds709B - 2012 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Balkhab mineral district in Afghanistan: Chapter B in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","interactions":[],"lastModifiedDate":"2013-02-01T11:14:10","indexId":"ds709B","displayToPublicDate":"2012-09-05T00:00:00","publicationYear":"2012","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":"709","chapter":"B","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Balkhab mineral district in Afghanistan: Chapter B in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Balkhab mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (&copy;JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Balkhab) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the Balkhab area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Balkhab study area, one subarea was designated for detailed field investigations (that is, the Balkhab Prospect subarea); this subarea was extracted from the area's image mosaic and is provided as separate embedded geotiff images.","largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709B","collaboration":"Prepared in cooperation with the U.S. Department of Defense <a href=\"http://tfbso.defense.gov/www/\" target=\"_blank\">Task Force for Business and Stability Operations</a> and the <a href=\"http://www.bgs.ac.uk/AfghanMinerals/\" target=\"_blank\">Afghanistan Geological Survey</a>. This report is Chapter B in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>. For more information, see: <a href=\"http://pubs.er.usgs.gov/publication/ds709\" target=\"_blank\">DS 709</a>.","usgsCitation":"Davis, P.A., and Cagney, L.E., 2012, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Balkhab mineral district in Afghanistan: Chapter B in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>: U.S. Geological Survey Data Series 709, Readme; 2 Maps: 11 x 8.5 inches and 46.68 x 35.61 inches; 6 Image Files; 6 Metadata Files; Shapefiles; DS 709, https://doi.org/10.3133/ds709B.","productDescription":"Readme; 2 Maps: 11 x 8.5 inches and 46.68 x 35.61 inches; 6 Image Files; 6 Metadata Files; Shapefiles; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":262587,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_B.jpg"},{"id":262584,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/b/","linkFileType":{"id":5,"text":"html"}},{"id":262586,"rank":400,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/b/index_maps/Balkhab_Image_Index_Map.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262585,"rank":400,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/b/index_maps/Balkhab_Area-of-Interest_Index_Map.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":263621,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/b/image_files/image_files.html"},{"id":263620,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/b/1_readme.txt"},{"id":263622,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/b/metadata/metadata.html"},{"id":263623,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/b/shapefiles/shapefiles.html"},{"id":263624,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/"}],"country":"Afghanistan","state":"Balkh;Samangan;Sari-Pul","otherGeospatial":"Balkhab Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 66.25,35.25 ], [ 66.25,35.916667 ], [ 67.25,35.916667 ], [ 67.25,35.25 ], [ 66.25,35.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"507d2378e4b0905c2a76c025","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":468095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":468096,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70039809,"text":"ofr20121102 - 2012 - Groundwater, surface-water, and water-chemistry data, Black Mesa area, northeastern Arizona - 2010-2011","interactions":[],"lastModifiedDate":"2012-09-06T01:02:24","indexId":"ofr20121102","displayToPublicDate":"2012-09-05T00:00:00","publicationYear":"2012","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":"2012-1102","title":"Groundwater, surface-water, and water-chemistry data, Black Mesa area, northeastern Arizona - 2010-2011","docAbstract":"The Navajo (N) aquifer is an extensive aquifer and the primary source of groundwater in the 5,400-square-mile Black Mesa area in northeastern Arizona. Availability of water is an important issue in northeastern Arizona because of continued water requirements for industrial and municipal use by a growing population and because of low precipitation in the arid climate of the Black Mesa area. Precipitation in the area is typically between 6 to 14 inches per year. The U.S. Geological Survey water-monitoring program in the Black Mesa area began in 1971 and provides information about the long-term effects of groundwater withdrawals from the N aquifer for industrial and municipal uses. This report presents results of data collected as part of the monitoring program in the Black Mesa area from January 2010 to September 2011. The monitoring program includes measurements of (1) groundwater withdrawals, (2) groundwater levels, (3) spring discharge, (4) surface-water discharge, and (5) groundwater chemistry. In 2010, total groundwater withdrawals were 4,040 acre-ft, industrial withdrawals were 1,170 acre-ft, and municipal withdrawals were 2,870 acre-ft. Total withdrawals during 2010 were about 42 percent less than total withdrawals in 2005 because of Peabody Western Coal Company's discontinued use of water to transport coal in a slurry. From 2009 to 2010 total withdrawals decreased by 5 percent; industrial withdrawals decreased by approximately 16 percent, and total municipal withdrawals increased by 1 percent. From 2010 to 2011, annually measured water levels in the Black Mesa area declined in 7 of 15 wells that were available for comparison in the unconfined areas of the N aquifer, and the median change was 0.0 foot. Water levels declined in 11 of 18 wells measured in the confined area of the aquifer. The median change for the confined area of the aquifer was -0.7 foot. From the prestress period (prior to 1965) to 2011, the median water-level change for 33 wells in both the confined and unconfined areas was -15.0 feet. Also, from the prestress period to 2011, the median water-level changes were -1.2 foot for 15 wells measured in the unconfined areas and -41.2 feet for 18 wells measured in the confined area. Spring flow was measured at three springs in 2011. Flow fluctuated during the period of record, but a decreasing trend was apparent at Moenkopi School Spring and Pasture Canyon Spring. Discharge at Burro Spring has remained relatively constant since it was first measured in the 1980s. Continuous records of surface-water discharge in the Black Mesa area were collected from streamflow-gaging stations at the following sites: Moenkopi Wash at Moenkopi 09401260 (1976 to 2010), Dinnebito Wash near Sand Springs 09401110 (1993 to 2010), Polacca Wash near Second Mesa 09400568 (1994 to 2010), and Pasture Canyon Springs 09401265 (2004 to 2010). Median winter flows (November through February) of each water year were used as an index of the amount of groundwater discharge at the above-named sites. For the period of record of each streamflow-gaging station, the median winter flows have generally remained constant, which suggests no change in groundwater discharge. In 2011, water samples collected from 11 wells and 4 springs in the Black Mesa area were analyzed for selected chemical constituents, and the results were compared with previous analyses. Concentrations of dissolved solids, chloride, and sulfate have varied at all 11 wells for the period of record, but neither increasing nor decreasing trends over time were found. Dissolved-solids, chloride, and sulfate concentrations increased at Moenkopi School Spring during the more than 12 years of record at that site. Concentrations of dissolved solids, chloride, and sulfate at Pasture Canyon Spring have not varied much since the early 1980s, and there is no increasing or decreasing trend in those data. Concentrations of dissolved solids, chloride, and sulfate at Burro Spring and Unnamed Spring near Dennehotso have varied for the period of record, but there is no increasing or decreasing trend in the data.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121102","usgsCitation":"Macy, J.P., Brown, C.R., and Anderson, J., 2012, Groundwater, surface-water, and water-chemistry data, Black Mesa area, northeastern Arizona - 2010-2011: U.S. Geological Survey Open-File Report 2012-1102, viii, 41 p., https://doi.org/10.3133/ofr20121102.","productDescription":"viii, 41 p.","numberOfPages":"50","onlineOnly":"Y","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":260175,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1102.gif"},{"id":260165,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1102/of2012-1102.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260163,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1102/","linkFileType":{"id":5,"text":"html"}}],"scale":"100000","projection":"Lambert Conformal Conic projection","country":"United States","state":"Arizona","otherGeospatial":"Black Mesa","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.5,35.5 ], [ -111.5,37 ], [ -109.5,37 ], [ -109.5,35.5 ], [ -111.5,35.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a2dc6e4b0c8380cd5c009","contributors":{"authors":[{"text":"Macy, Jamie P. 0000-0003-3443-0079 jpmacy@usgs.gov","orcid":"https://orcid.org/0000-0003-3443-0079","contributorId":2173,"corporation":false,"usgs":true,"family":"Macy","given":"Jamie","email":"jpmacy@usgs.gov","middleInitial":"P.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466971,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Christopher R. crbrown@usgs.gov","contributorId":4751,"corporation":false,"usgs":true,"family":"Brown","given":"Christopher","email":"crbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466972,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Jessica R.","contributorId":58132,"corporation":false,"usgs":true,"family":"Anderson","given":"Jessica R.","affiliations":[],"preferred":false,"id":466973,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70039768,"text":"ofr20121172 - 2012 - Radioisotopic data of sediment collected in Mobile and Bon Secour Bays, Alabama","interactions":[],"lastModifiedDate":"2025-05-14T13:57:04.415594","indexId":"ofr20121172","displayToPublicDate":"2012-09-04T00:00:00","publicationYear":"2012","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":"2012-1172","title":"Radioisotopic data of sediment collected in Mobile and Bon Secour Bays, Alabama","docAbstract":"The focus of this study was to determine the extent of natural and (or) anthropogenic impacts on the sedimentary records of Mobile and Bon Secour Bays, Alabama during the last 150 years. These bays are unique in that anthropogenic activities are generally widespread and span both the eastern and western shorelines. However, there is a clear distinction in the types of human development and infrastructure between the western and eastern shorelines. These activities and the differences in land-use and -change influence the overall supply and remobilization of sediment to and within the bay. These factors could subsequently threaten the health and integrity of these environments and their ability to mitigate against long-term processes associated with climate change. In an attempt to characterize long-term accretion rates within the Mobile Bay Estuarine System (MBES), seven box cores were collected and analyzed for excess lead-210 (<sup>210</sup>Pb<sub>xs</sub>, the difference between total and supported <sup>210</sup>Pb) and cesium-137 (<sup>137</sup>Cs) activities. The MBES receives sediment and water from the Alabama and Tombigbee River watersheds, which converge into the Mobile-Tensaw River (MTR) system just prior to discharging into Mobile Bay. Riverine discharge from the MTR system to the bay is second only to the Mississippi River discharge to the Gulf of Mexico for the conterminous United States.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121172","usgsCitation":"Marot, M.E., and Smith, C.G., 2012, Radioisotopic data of sediment collected in Mobile and Bon Secour Bays, Alabama: U.S. Geological Survey Open-File Report 2012-1172, iv, 15 p., https://doi.org/10.3133/ofr20121172.","productDescription":"iv, 15 p.","numberOfPages":"19","onlineOnly":"Y","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":260047,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1172.jpg"},{"id":260037,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1172/","linkFileType":{"id":5,"text":"html"}},{"id":260038,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1172/pdf/2012-1172.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Alabama","otherGeospatial":"Bon Secour Bay, Mobile Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.16666666666667,30.166666666666668 ], [ -88.16666666666667,30.666666666666668 ], [ -87.66666666666667,30.666666666666668 ], [ -87.66666666666667,30.166666666666668 ], [ -88.16666666666667,30.166666666666668 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a93fee4b0c8380cd81138","contributors":{"authors":[{"text":"Marot, Marci E. 0000-0003-0504-315X mmarot@usgs.gov","orcid":"https://orcid.org/0000-0003-0504-315X","contributorId":2078,"corporation":false,"usgs":true,"family":"Marot","given":"Marci","email":"mmarot@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":466901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Christopher G. 0000-0002-8075-4763 cgsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":3410,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher","email":"cgsmith@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466902,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70039792,"text":"ofr20121162 - 2012 - Dissolved methane in New York groundwater, 1999-2011","interactions":[],"lastModifiedDate":"2012-09-11T17:16:26","indexId":"ofr20121162","displayToPublicDate":"2012-09-04T00:00:00","publicationYear":"2012","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":"2012-1162","title":"Dissolved methane in New York groundwater, 1999-2011","docAbstract":"New York State is underlain by numerous bedrock formations of Cambrian to Devonian age that produce natural gas and to a lesser extent oil. The first commercial gas well in the United States was dug in the early 1820s in Fredonia, south of Buffalo, New York, and produced methane from Devonian-age black shale. Methane naturally discharges to the land surface at some locations in New York. At Chestnut Ridge County Park in Erie County, just south of Buffalo, N.Y., several surface seeps of natural gas occur from Devonian black shale, including one behind a waterfall. Methane occurs locally in the groundwater of New York; as a result, it may be present in drinking-water wells, in the water produced from those wells, and in the associated water-supply systems (Eltschlager and others, 2001). The natural gas in low-permeability bedrock formations has not been accessible by traditional extraction techniques, which have been used to tap more permeable sandstone and carbonate bedrock reservoirs. However, newly developed techniques involving horizontal drilling and high-volume hydraulic fracturing have made it possible to extract previously inaccessible natural gas from low-permeability bedrock such as the Marcellus and Utica Shales. The use of hydraulic fracturing to release natural gas from these shale formations has raised concerns with water-well owners and water-resource managers across the Marcellus and Utica Shale region (West Virginia, Pennsylvania, New York and parts of several other adjoining States). Molofsky and others (2011) documented the widespread natural occurrence of methane in drinking-water wells in Susquehanna County, Pennsylvania. In the same county, Osborn and others (2011) identified elevated methane concentrations in selected drinking-water wells in the vicinity of Marcellus gas-development activities, although pre-development samples were not available for comparison. In order to manage water resources in areas of gas-well drilling and hydraulic fracturing in New York, the natural occurrence of methane in the State's aquifers needs to be documented. This brief report presents a compilation of data on dissolved methane concentrations in the groundwater of New York available from the U.S. Geological Survey (USGS) National Water Information System (NWIS) (http://waterdata.usgs.gov/nwis).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121162","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Kappel, W.M., and Nystrom, E.A., 2012, Dissolved methane in New York groundwater, 1999-2011: U.S. Geological Survey Open-File Report 2012-1162, 6 p., https://doi.org/10.3133/ofr20121162.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":260130,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1162.gif"},{"id":260133,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1162/pdf/ofr2012-1162_508_09072012.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260054,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1162","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -79.75138888888888,40.48444444444444 ], [ -79.75138888888888,45.00111111111111 ], [ -71.95055555555555,45.00111111111111 ], [ -71.95055555555555,40.48444444444444 ], [ -79.75138888888888,40.48444444444444 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0236e4b0c8380cd4ff4d","contributors":{"authors":[{"text":"Kappel, William M. 0000-0002-2382-9757 wkappel@usgs.gov","orcid":"https://orcid.org/0000-0002-2382-9757","contributorId":1074,"corporation":false,"usgs":true,"family":"Kappel","given":"William","email":"wkappel@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nystrom, Elizabeth A. 0000-0002-0886-3439 nystrom@usgs.gov","orcid":"https://orcid.org/0000-0002-0886-3439","contributorId":1072,"corporation":false,"usgs":true,"family":"Nystrom","given":"Elizabeth","email":"nystrom@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466929,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70039807,"text":"sim3226 - 2012 - Flood-inundation maps for Suwanee Creek from the confluence of Ivy Creek to the Noblin Ridge Drive bridge, Gwinnett County, Georgia","interactions":[],"lastModifiedDate":"2017-01-13T09:40:31","indexId":"sim3226","displayToPublicDate":"2012-09-04T00:00:00","publicationYear":"2012","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":"3226","title":"Flood-inundation maps for Suwanee Creek from the confluence of Ivy Creek to the Noblin Ridge Drive bridge, Gwinnett County, Georgia","docAbstract":"Digital flood-inundation maps for a 6.9-mile reach of Suwanee Creek, from the confluence of Ivy Creek to the Noblin Ridge Drive bridge, were developed by the U.S. Geological Survey (USGS) in cooperation with Gwinnett County, Georgia. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at <a href=\"http://water.usgs.gov/osw/flood_inundation/\">http://water.usgs.gov/osw/flood_inundation/</a>, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Suwanee Creek at Suwanee, Georgia (02334885). Current stage at this USGS streamgage may be obtained at <a href=\"http://waterdata.usgs.gov/\">http://waterdata.usgs.gov/</a> and can be used in conjunction with these maps to estimate near real-time areas of inundation. The National Weather Service (NWS) is incorporating results from this study into the Advanced Hydrologic Prediction Service (AHPS) flood-warning system (<a href=\"http://water.weather.gov/ahps/\">http://water.weather.gov/ahps/</a>). The NWS forecasts flood hydrographs at many places that commonly are collocated at USGS streamgages. The forecasted peak-stage information for the USGS streamgage at Suwanee Creek at Suwanee (02334885), available through the AHPS Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers HEC-RAS software for Suwanee Creek and was used to compute flood profiles for a 6.9-mile reach of the creek. The model was calibrated using the most current stage-discharge relations at the Suwanee Creek at Suwanee streamgage (02334885). The hydraulic model was then used to determine 19 water-surface profiles for flood stages at the Suwanee Creek streamgage at 0.5-foot intervals referenced to the streamgage. The profiles ranged from just above bankfull stage (7.0 feet) to approximately 1.7 feet above the highest recorded water level at the streamgage (16.0 feet). The simulated water-surface profiles were then combined with a geographic information system digital elevation model - derived from light detection and ranging (LiDAR) data having a 5.0-foot horizontal resolution - to delineate the area flooded for each 0.5-foot increment of stream stage. The availability of these maps, when combined with real-time stage information from USGS streamgages and forecasted stream stage from the NWS, provides emergency management personnel and residents with critical information during flood-response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3226","collaboration":"Prepared in cooperation with Gwinnett County, Georgia","usgsCitation":"Musser, J.W., 2012, Flood-inundation maps for Suwanee Creek from the confluence of Ivy Creek to the Noblin Ridge Drive bridge, Gwinnett County, Georgia: U.S. Geological Survey Scientific Investigations Map 3226, Report: v, 8 p.; 19 Sheets: 34 x 24 inches; Downloads Directory, https://doi.org/10.3133/sim3226.","productDescription":"Report: v, 8 p.; 19 Sheets: 34 x 24 inches; Downloads Directory","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":260164,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3226.jpg"},{"id":260158,"rank":416,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet17_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260143,"rank":401,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet2_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260141,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3226/pdf/sim3226.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260142,"rank":400,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet1_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260140,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3226/","linkFileType":{"id":5,"text":"html"}},{"id":260144,"rank":402,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet3_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260145,"rank":403,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet4_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260146,"rank":404,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet5_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260147,"rank":405,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet6_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260148,"rank":406,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet7_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260149,"rank":407,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet8_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260150,"rank":408,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet9_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260151,"rank":409,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet10_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260152,"rank":410,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet11_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260153,"rank":411,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet12_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260154,"rank":412,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet13_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260155,"rank":413,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet14_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260156,"rank":414,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet15_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260157,"rank":415,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet16_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260159,"rank":417,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet18_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260160,"rank":418,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet19_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}}],"scale":"24000","country":"United States","state":"Georgia","county":"Gwinnett County","otherGeospatial":"Suwanee Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.11666666666666,34 ], [ -84.11666666666666,34.083333333333336 ], [ -84.03333333333333,34.083333333333336 ], [ -84.03333333333333,34 ], [ -84.11666666666666,34 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a1166e4b0c8380cd53fa0","contributors":{"authors":[{"text":"Musser, Jonathan W. 0000-0002-3543-0807 jwmusser@usgs.gov","orcid":"https://orcid.org/0000-0002-3543-0807","contributorId":2266,"corporation":false,"usgs":true,"family":"Musser","given":"Jonathan","email":"jwmusser@usgs.gov","middleInitial":"W.","affiliations":[{"id":13634,"text":"South Atlantic Water Science 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,{"id":70039874,"text":"ofr20121193 - 2012 - Demographics and run timing of adult Lost River (<i>Deltistes luxatus</i>) and shortnose (<i>Chasmistes brevirostris</i>) suckers in Upper Klamath Lake, Oregon, 2011","interactions":[],"lastModifiedDate":"2016-05-03T13:24:05","indexId":"ofr20121193","displayToPublicDate":"2012-09-03T15:56:00","publicationYear":"2012","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":"2012-1193","title":"Demographics and run timing of adult Lost River (<i>Deltistes luxatus</i>) and shortnose (<i>Chasmistes brevirostris</i>) suckers in Upper Klamath Lake, Oregon, 2011","docAbstract":"<h1>Executive Summary</h1>\n<p>Data from a long-term capture-recapture program were used to assess the status and dynamics of populations of two long-lived, federally endangered catostomids in Upper Klamath Lake, Oregon. Lost River suckers (<i>Deltistes luxatus</i>) and shortnose suckers (<i>Chasmistes brevirostris</i>) have been captured and tagged with passive integrated transponder (PIT) tags during their spawning migrations in each year since 1995. In addition, beginning in 2005, individuals that had been previously PIT-tagged were re-encountered on remote underwater antennas deployed throughout sucker spawning areas. Captures and remote encounters during spring 2011 were used to describe the spawning migrations in that year and also were incorporated into capture-recapture analyses of population dynamics.</p>\n<p>Cormack-Jolly-Seber (CJS) open population capture-recapture models were used to estimate annual survival probabilities, and a reverse-time analog of the CJS model was used to estimate recruitment of new individuals into the spawning populations. In addition, data on the size composition of captured fish was examined to provide corroborating evidence of recruitment. Survival and recruitment estimates were used to derive estimates of changes in population size over time and to determine the status of the populations in 2010. Separate analyses were conducted for each species and also for each subpopulation of Lost River suckers (LRS). One subpopulation of LRS migrates into tributaries to spawn, similar to shortnose suckers (SNS), whereas the other subpopulation spawns at upwelling areas along the eastern shoreline of the lake.</p>\n<p>In 2011, we captured, tagged, and released 806 LRS at four lakeshore spawning areas and recaptured an additional 1,006 individuals that had been tagged in previous years. Across all four areas, the remote antennas detected 6,547 individual LRS during the spawning season. Spawning activity peaked in April and most individuals were encountered at Sucker Springs and Cinder Flats. In the Williamson River, we captured, tagged, and released 2,742 LRS and 123 SNS, and recaptured 376 LRS and 58 SNS that had been tagged in previous years. Remote PIT tag antennas in the traps at the weir on the Williamson River and remote antenna systems that spanned the river at four different locations on the Williamson and Sprague Rivers detected a total of 16,494 LRS and 5,450 SNS. Most LRS passed upstream between mid-April and mid-May when water temperatures were rising and near or greater than 10 &deg;C. In contrast, the largest peaks in upstream passage of SNS occurred in early and mid-May when water temperatures were rising and near or greater than 12 &deg;C. Finally, an additional 875 LRS and 1,600 SNS were captured in trammel net sampling at pre-spawn staging areas in the northeastern portion of the lake. Of these, 191of the LRS and 571 of the SNS had been PIT-tagged in previous years. For LRS, encounter histories showed that more than 90 percent of the fish captured at the staging areas were members of the subpopulation that spawns in the tributaries.</p>\n<p>Capture-recapture analyses for the LRS subpopulation that spawns at the shoreline areas included encounter histories for more than 10,500 individuals, and analyses for the subpopulation that spawns in the tributaries included more than 22,000 encounter histories. With a few exceptions, the survival of males and females in both subpopulations was high (greater than 0.9) between 1999 and 2009. Notably lower survival occurred for both sexes from the tributaries in 2000, for both sexes from the shoreline areas in 2002, and for males from the tributaries in 2006. Between 2001 and 2010, the abundance of males in the lakeshore spawning subpopulation decreased by 50&ndash;60 percent and the abundance of females decreased by 29&ndash;44 percent. Capture-recapture models suggested that the abundance of the river spawning subpopulation of LRS has increased substantially since 2006. The increase over this period was largely due to large estimated recruitment events in 2003, 2006, and 2008. We know that the estimate in 2006 is substantially biased in favor of recruitment due to a sampling issue. We are skeptical of the magnitude of recruitment indicated by the 2003 and 2008 estimates as well because very few small individuals that would indicate the presence of new recruits were captured in those years. If we assume that little or no recruitment has occurred, the abundance of both sexes in the river spawning subpopulation decreased by more than 40 percent between 2002 and 2010.</p>\n<p>Capture-recapture analyses for SNS included encounter histories for more than 15,500 individuals. The majority of annual survival estimates between 2001 and 2009 were high (greater than 0.8), but SNS did experience more years of low survival than either LRS subpopulation. The survival of both sexes was particularly low in both 2001 and 2004, and male survival also was somewhat low in 2002 and 2006. Capture-recapture models and size composition data indicated that recruitment of new individuals into the SNS spawning population was trivial in nearly all years between 2001 and 2009. As a result, the abundance of males decreased by 64&ndash;82 percent and the abundance of females decreased by 62&ndash;76 percent between 2001 and 2010.</p>\n<p>Despite relatively high survival in most years, both species have experienced substantial declines in the abundance of spawning fish because losses from mortality have not been balanced by recruitment of new individuals. Although capture-recapture data indicate substantial recruitment of new individuals into the adult spawning populations for SNS and river spawning LRS in some years, size data do not corroborate these estimates. In fact, fork length data indicate that all populations are largely comprised of fish that were present in the late 1990s and early 2000s. As a result, the status of the endangered sucker populations in Upper Klamath Lake remains worrisome, and the situation is most dire for shortnose suckers. Future investigations should explore the connections between sucker recruitment and survival and various environmental factors, such as water quality and disease. Our monitoring program provides a robust platform for estimating vital population parameters, evaluating the status of the populations, and assessing the effectiveness of conservation and recovery efforts.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121193","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hewitt, D.A., Janney, E.C., Hayes, B., and Harris, A., 2012, Demographics and run timing of adult Lost River (<i>Deltistes luxatus</i>) and shortnose (<i>Chasmistes brevirostris</i>) suckers in Upper Klamath Lake, Oregon, 2011: U.S. Geological Survey Open-File Report 2012-1193, vii, 42 p., https://doi.org/10.3133/ofr20121193.","productDescription":"vii, 42 p.","numberOfPages":"52","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":261836,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1193.jpg"},{"id":261832,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1193/pdf/ofr20121193.pdf","text":"Report","size":"2.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":261831,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1193/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.16666666666667,42.166666666666664 ], [ -122.16666666666667,42.666666666666664 ], [ -121.75,42.666666666666664 ], [ -121.75,42.166666666666664 ], [ -122.16666666666667,42.166666666666664 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059fe86e4b0c8380cd4ed8b","contributors":{"authors":[{"text":"Hewitt, David A. 0000-0002-5387-0275 dhewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-5387-0275","contributorId":3767,"corporation":false,"usgs":false,"family":"Hewitt","given":"David","email":"dhewitt@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":467113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janney, Eric C. 0000-0002-0228-2174","orcid":"https://orcid.org/0000-0002-0228-2174","contributorId":83629,"corporation":false,"usgs":true,"family":"Janney","given":"Eric","email":"","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":467115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Brian S. 0000-0001-8229-4070","orcid":"https://orcid.org/0000-0001-8229-4070","contributorId":37022,"corporation":false,"usgs":true,"family":"Hayes","given":"Brian S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":467114,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harris, Alta C. 0000-0002-2123-3028 aharris@usgs.gov","orcid":"https://orcid.org/0000-0002-2123-3028","contributorId":3490,"corporation":false,"usgs":true,"family":"Harris","given":"Alta C.","email":"aharris@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":467112,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70133432,"text":"70133432 - 2012 - Ontogenetic and among-individual variation in foraging strategies of northeast Pacific white sharks based on stable isotope analysis","interactions":[],"lastModifiedDate":"2021-01-05T17:46:49.701126","indexId":"70133432","displayToPublicDate":"2012-09-01T10:45:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Ontogenetic and among-individual variation in foraging strategies of northeast Pacific white sharks based on stable isotope analysis","docAbstract":"<p>There is growing evidence for individuality in dietary preferences and foraging behaviors within populations of various species. This is especially important for apex predators, since they can potentially have wide dietary niches and a large impact on trophic dynamics within ecosystems. We evaluate the diet of an apex predator, the white shark (<em>Carcharodon carcharias</em>), by measuring the stable carbon and nitrogen isotope composition of vertebral growth bands to create lifetime records for 15 individuals from California. Isotopic variations in white shark diets can reflect within-region differences among prey (most importantly related to trophic level), as well as differences in baseline values among the regions in which sharks forage, and both prey and habitat preferences may shift with age. The magnitude of isotopic variation among sharks in our study (&gt;5&permil; for both elements) is too great to be explained solely by geographic differences, and so must reflect differences in prey choice that may vary with sex, size, age and location. Ontogenetic patterns in &delta;<sup>15</sup>N values vary considerably among individuals, and one third of the population fit each of these descriptions: 1) &delta;<sup>15</sup>N values increased throughout life, 2) &delta;<sup>15</sup>N values increased to a plateau at ~5 years of age, and 3) &delta;<sup>15</sup>N values remained roughly constant values throughout life. Isotopic data for the population span more than one trophic level, and we offer a qualitative evaluation of diet using shark-specific collagen discrimination factors estimated from a 3+ year captive feeding experiment (&Delta;<sup>13</sup>C<sub>shark-diet</sub> and &Delta;<sup>15</sup>N<sub>shark-diet</sub> equal 4.2&permil; and 2.5&permil;, respectively). We assess the degree of individuality with a proportional similarity index that distinguishes specialists and generalists. The isotopic variance is partitioned among differences between-individual (48%), within-individuals (40%), and by calendar year of sub-adulthood (12%). Our data reveal substantial ontogenetic and individual dietary variation within a white shark population.</p>","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0045068","usgsCitation":"Kim, S., Tinker, M.T., Estes, J.A., and Koch, P., 2012, Ontogenetic and among-individual variation in foraging strategies of northeast Pacific white sharks based on stable isotope analysis: PLoS ONE, v. 7, no. 9, p. 1-11, https://doi.org/10.1371/journal.pone.0045068.","productDescription":"11 p.","startPage":"1","endPage":"11","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-029024","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":474369,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0045068","text":"Publisher Index Page"},{"id":381881,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"9","noUsgsAuthors":false,"publicationDate":"2012-09-28","publicationStatus":"PW","scienceBaseUri":"546c7623e4b0f4a3478a6176","contributors":{"authors":[{"text":"Kim, S.L.","contributorId":127452,"corporation":false,"usgs":false,"family":"Kim","given":"S.L.","email":"","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":525199,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tinker, M. Tim 0000-0002-3314-839X ttinker@usgs.gov","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":2796,"corporation":false,"usgs":true,"family":"Tinker","given":"M.","email":"ttinker@usgs.gov","middleInitial":"Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":525197,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Estes, J. A.","contributorId":53319,"corporation":false,"usgs":true,"family":"Estes","given":"J.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":525198,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koch, P.L.","contributorId":101878,"corporation":false,"usgs":true,"family":"Koch","given":"P.L.","email":"","affiliations":[],"preferred":false,"id":525200,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70040984,"text":"70040984 - 2012 - Bias from false-positive detections and strategies for their removal in studies using telemetry","interactions":[{"subject":{"id":70040984,"text":"70040984 - 2012 - Bias from false-positive detections and strategies for their removal in studies using telemetry","indexId":"70040984","publicationYear":"2012","noYear":false,"chapter":"9.5","title":"Bias from false-positive detections and strategies for their removal in studies using telemetry"},"predicate":"IS_PART_OF","object":{"id":70198150,"text":"70198150 - 2012 - Telemetry techniques: A user guide for fisheries research","indexId":"70198150","publicationYear":"2012","noYear":false,"title":"Telemetry techniques: A user guide for fisheries research"},"id":1}],"isPartOf":{"id":70198150,"text":"70198150 - 2012 - Telemetry techniques: A user guide for fisheries research","indexId":"70198150","publicationYear":"2012","noYear":false,"title":"Telemetry techniques: A user guide for fisheries research"},"lastModifiedDate":"2022-12-21T15:56:25.925847","indexId":"70040984","displayToPublicDate":"2012-09-01T09:45:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"9.5","title":"Bias from false-positive detections and strategies for their removal in studies using telemetry","docAbstract":"<p>The use of radio and acoustic telemetry to study aquatic animals has flourished since the 1950s and 1960s (see Section 1). Electronic data-logging receivers are commonly used in both types of active telemetry to record the presence of transmitters in the detection field formed by one or more antennas or hydrophones. As described in Sections 5.1 and 7.1, the path of a transmitter signal to a telemetry receiver can be influenced by many factors and the received signal is not always detected or correctly assigned. It should be of no surprise to users of active telemetry systems that not all records in telemetry receivers are from tagged fish and not all tagged fish are recorded when present.</p><p>Four types of observations are possible in data from telemetry receiving systems based on the binary nature of presence and absence (Table 1). True positives and true negatives are what one ideally expects from telemetry systems, but in most studies they are accompanied by false negatives (not recorded when present) and false positives (recorded when absent). False negatives arise due to a variety of causes, including insufficient detection area relative to transmitter pulse rate and fish travel speed, collisions between transmitters in the detection area, interference from ambient noise, or a received signal too weak to be recorded (see Sections 3, 5, and 7). The probability of false negatives can be calculated as (1–detection probability) and can be estimated with proper study design and incorporated into estimates of fish presence (see Sections 7.2 and 9.2).</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Telemetry techniques: A user guide for fisheries research","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.47886/9781934874264.ch22","usgsCitation":"Beeman, J.W., and Perry, R.W., 2012, Bias from false-positive detections and strategies for their removal in studies using telemetry, chap. 9.5 <i>of</i> Telemetry techniques: A user guide for fisheries research, https://doi.org/10.47886/9781934874264.ch22.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037562","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":319605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56fcf9d4e4b0a6037df2b9b6","contributors":{"editors":[{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625592,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Beeman, John W. jbeeman@usgs.gov","contributorId":2646,"corporation":false,"usgs":true,"family":"Beeman","given":"John","email":"jbeeman@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625593,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Eiler, John H.","contributorId":146952,"corporation":false,"usgs":false,"family":"Eiler","given":"John","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":625594,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Beeman, John W. jbeeman@usgs.gov","contributorId":2646,"corporation":false,"usgs":true,"family":"Beeman","given":"John","email":"jbeeman@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625591,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70040981,"text":"70040981 - 2012 - Developing a quality assurance plan for telemetry studies: A necessary management tool for an effective study","interactions":[{"subject":{"id":70040981,"text":"70040981 - 2012 - Developing a quality assurance plan for telemetry studies: A necessary management tool for an effective study","indexId":"70040981","publicationYear":"2012","noYear":false,"chapter":"9.3","title":"Developing a quality assurance plan for telemetry studies: A necessary management tool for an effective study"},"predicate":"IS_PART_OF","object":{"id":70198150,"text":"70198150 - 2012 - Telemetry techniques: A user guide for fisheries research","indexId":"70198150","publicationYear":"2012","noYear":false,"title":"Telemetry techniques: A user guide for fisheries research"},"id":1}],"isPartOf":{"id":70198150,"text":"70198150 - 2012 - Telemetry techniques: A user guide for fisheries research","indexId":"70198150","publicationYear":"2012","noYear":false,"title":"Telemetry techniques: A user guide for fisheries research"},"lastModifiedDate":"2022-12-20T17:56:33.587977","indexId":"70040981","displayToPublicDate":"2012-09-01T09:15:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"chapter":"9.3","title":"Developing a quality assurance plan for telemetry studies: A necessary management tool for an effective study","docAbstract":"<p>Telemetry has been used to answer various questions associated with research, management, and monitoring programs and to monitor animal behavior and population dynamics throughout the world. Many telemetry projects have been developed to study the passage, behavior, and survival of migrating adult and juvenile salmonids at hydroelectric projects on the mainstem Columbia and Snake rivers (Skalski et al. 2001a, 2001b; Skalski et al. 2002; Keefer et al. 2004; Goniea et al. 2006; Plumb et al. 2006). Telemetry based field evaluations of the survival of salmon through hydroelectric projects are costly because of the technology (tags, telemetry systems, infrastructure, etc.) and personnel required to conduct the evaluations. Given the cost of implementing these projects, and the financial and conservation implications of the decisions made from the research results (e.g., forgone electricity production and conservation of threatened and endangered animals), ensuring quality data are collected by documenting all procedures, training, data checks, and that sound protocols and quality assurance and control procedures are in place is paramount.</p><p>Telemetry studies can pose unique data collection, processing, and analysis challenges. For instance, inferences about entire populations of animals are made from study animals that are captured, held, and tagged at disparate locations. Consequently great care must be taken to ensure that any potential biases that could arise from field procedures must be minimized (Peven et al. 2005). Interrogations of released study animals are remotely conducted by telemetry systems throughout the study area. The continuous recording of telemetry systems can result in large numbers of detections over a short time frame and the potential for false positive detections from records that are weak or erroneous. Thus, there is the potential to generate large data sets (many thousands of lines) that require significant postprocessing. Data reduction can be done using software or programming code within a software package or manually to discern noise from valid data and pull out the pertinent information for analysis. In either case, consistent well-documented procedures need to be in place to ensure quality results and allow for repeatability of study methods.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Telemetry techniques: A user guide for fisheries research","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.47886/9781934874264.ch20","usgsCitation":"Hardiman, J.M., Walker, C.E., and Counihan, T.D., 2012, Developing a quality assurance plan for telemetry studies: A necessary management tool for an effective study, chap. 9.3 <i>of</i> Telemetry techniques: A user guide for fisheries research, https://doi.org/10.47886/9781934874264.ch20.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-031751","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":319645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56fcfad1e4b0a6037df2bbcb","contributors":{"editors":[{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625665,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Beeman, John W. jbeeman@usgs.gov","contributorId":2646,"corporation":false,"usgs":true,"family":"Beeman","given":"John","email":"jbeeman@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625666,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Eiler, John H.","contributorId":146952,"corporation":false,"usgs":false,"family":"Eiler","given":"John","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":625667,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Hardiman, Jill M. 0000-0002-3661-9695 jhardiman@usgs.gov","orcid":"https://orcid.org/0000-0002-3661-9695","contributorId":2672,"corporation":false,"usgs":true,"family":"Hardiman","given":"Jill","email":"jhardiman@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625662,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, Christopher E.","contributorId":65938,"corporation":false,"usgs":true,"family":"Walker","given":"Christopher","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":625663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Counihan, Timothy D. 0000-0003-4967-6514 tcounihan@usgs.gov","orcid":"https://orcid.org/0000-0003-4967-6514","contributorId":4211,"corporation":false,"usgs":true,"family":"Counihan","given":"Timothy","email":"tcounihan@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625664,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70040983,"text":"70040983 - 2012 - Using mark-recapture models to estimate survival from telemetry data: Chapter 9.2","interactions":[{"subject":{"id":70040983,"text":"70040983 - 2012 - Using mark-recapture models to estimate survival from telemetry data: Chapter 9.2","indexId":"70040983","publicationYear":"2012","noYear":false,"title":"Using mark-recapture models to estimate survival from telemetry data: Chapter 9.2"},"predicate":"IS_PART_OF","object":{"id":70198150,"text":"70198150 - 2012 - Telemetry techniques: A user guide for fisheries research","indexId":"70198150","publicationYear":"2012","noYear":false,"title":"Telemetry techniques: A user guide for fisheries research"},"id":1}],"isPartOf":{"id":70198150,"text":"70198150 - 2012 - Telemetry techniques: A user guide for fisheries research","indexId":"70198150","publicationYear":"2012","noYear":false,"title":"Telemetry techniques: A user guide for fisheries research"},"lastModifiedDate":"2022-12-21T15:24:29.732869","indexId":"70040983","displayToPublicDate":"2012-09-01T09:15:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Using mark-recapture models to estimate survival from telemetry data: Chapter 9.2","docAbstract":"<p>Analyzing telemetry data within a mark–recapture framework is a powerful approach for estimating demographic parameters (e.g., survival and movement probabilities) that might otherwise be difficult to measure. Yet many studies using telemetry techniques focus on fish behavior and fail to recognize the potential of telemetry data to provide information about fish survival. The sophistication of both mark–recapture modeling and telemetry has dramatically improved since the 1980s, largely due to technological advancements in computing power (for mark–recapture models) and electronic components (for telemetry). Such advances now allow mark–recapture models to take advantage of the detailed information that telemetry techniques can provide.</p><p>The key feature of mark–recapture models is simultaneous estimation of detection and survival probabilities. With telemetry, a “capture” event consists of detecting a given tag code one or more times at a specific location or time. By contrast, in some studies interest may focus on the probability of detecting a single tag transmission (see Sections 7.2 and 9.1). Compared to conventional mark and recapture methods, telemetry methods often have greater detection probabilities due to large detection ranges, increased “effort” (i.e., continuous monitoring with autonomous receivers), and ability to simultaneously monitor multiple locations. Nonetheless, perfect detectability is rare in telemetry studies because both random (e.g., from electronic noise) and nonrandom processes (e.g., receiver loses power temporarily) can allow a fish to pass a receiver undetected. Failure to account for imperfect detection can lead to serious bias in survival estimates. When using telemetry to estimate survival, it is therefore critical to explicitly estimate detection probabilities to ensure unbiased estimates of survival (see Section 7.2). Fortunately, using telemetry techniques and mark–recapture models together yields the best of both worlds: Well-designed telemetry systems deliver high detection probabilities that result in precise estimates from small sample sizes. Mark–recapture models ensure estimates of the demographic parameters are unbiased with respect to the detection process.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Telemetry techniques: A user guide for fisheries research","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.47886/9781934874264.ch19","usgsCitation":"Perry, R.W., Castro-Santos, T.R., Holbrook, C., and Sandford, B., 2012, Using mark-recapture models to estimate survival from telemetry data: Chapter 9.2, chap. <i>of</i> Telemetry techniques: A user guide for fisheries research, p. 453-475, https://doi.org/10.47886/9781934874264.ch19.","productDescription":"23 p.","startPage":"453","endPage":"475","numberOfPages":"518","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037563","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":319642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56fd062fe4b0a6037df2d077","contributors":{"editors":[{"text":"Adams, Noah","contributorId":91604,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","affiliations":[],"preferred":false,"id":625682,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Beeman, John W. jbeeman@usgs.gov","contributorId":2646,"corporation":false,"usgs":true,"family":"Beeman","given":"John","email":"jbeeman@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625683,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Eiler, John H.","contributorId":146952,"corporation":false,"usgs":false,"family":"Eiler","given":"John","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":625684,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Castro-Santos, Theodore R. 0000-0003-2575-9120 tcastrosantos@usgs.gov","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":3321,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","email":"tcastrosantos@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":625659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holbrook, Christopher M. 0000-0001-8203-6856 cholbrook@usgs.gov","orcid":"https://orcid.org/0000-0001-8203-6856","contributorId":4198,"corporation":false,"usgs":true,"family":"Holbrook","given":"Christopher M.","email":"cholbrook@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":625660,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sandford, Benjamin P.","contributorId":118178,"corporation":false,"usgs":true,"family":"Sandford","given":"Benjamin P.","affiliations":[],"preferred":false,"id":515037,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70044110,"text":"70044110 - 2012 - Time-to-event analysis as a framework for quantifying fish passage performance","interactions":[],"lastModifiedDate":"2022-12-27T16:31:22.906306","indexId":"70044110","displayToPublicDate":"2012-09-01T09:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"chapter":"9.1","title":"Time-to-event analysis as a framework for quantifying fish passage performance","docAbstract":"<p>Fish passage is the result of a sequence of processes, whereby fish must approach, enter, and pass a structure. Each of these processes takes time, and fishway performance is best quantified in terms of the rates at which each process is completed. Optimal performance is achieved by maximizing the rates of approach, entry, and passage through safe and desirable routes. Sometimes, however, it is necessary to reduce rates of passage through less desirable routes in order to increase proportions passing through the preferred route. Effectiveness of operational or structural modifications for achieving either of these goals is best quantified by applying time-to-event analysis, commonly known as survival analysis methods, to telemetry data. This set of techniques allows for accurate estimation of passage rates and covariate effects on those rates. Importantly, it allows researchers to quantify rates that vary over time, as well as the effects of covariates that also vary over time. Finally, these methods are able to control for competing risks, i.e., the presence of alternate passage routes, failure to pass, or other fates that remove fish from the pool of candidates available to pass through a particular route. In this chapter, we present a model simulation of telemetered fish passing a hydroelectric dam, and provide step-by-step guidance and rationales for performing time-to-event analysis on the resulting data. We demonstrate how this approach removes bias from performance estimates that can result from using methods that focus only on proportions passing each route. Time-to-event analysis, coupled with multinomial models for measuring survival, provides a comprehensive set of techniques for quantifying fish passage, and a framework from which performance among different sites can be better understood.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Telemetry techniques: A user guide for fisheries research","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","usgsCitation":"Castro-Santos, T.R., and Perry, R.W., 2012, Time-to-event analysis as a framework for quantifying fish passage performance, chap. 9.1 <i>of</i> Telemetry techniques: A user guide for fisheries research, p. 427-452.","productDescription":"26 p.","startPage":"427","endPage":"452","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-032289","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":319637,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":319636,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://fisheries.org/bookstore/all-titles/professional-and-trade/55068c/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56fd0587e4b0a6037df2cf7e","contributors":{"editors":[{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625655,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Beeman, John W. jbeeman@usgs.gov","contributorId":2646,"corporation":false,"usgs":true,"family":"Beeman","given":"John","email":"jbeeman@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625656,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Eiler, John H.","contributorId":146952,"corporation":false,"usgs":false,"family":"Eiler","given":"John","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":625657,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Castro-Santos, Theodore R. 0000-0003-2575-9120 tcastrosantos@usgs.gov","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":3321,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","email":"tcastrosantos@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":625653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625654,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70043665,"text":"70043665 - 2012 - User’s guide and metada for the PICES Nonindigenous Species Information System","interactions":[],"lastModifiedDate":"2016-05-03T15:04:17","indexId":"70043665","displayToPublicDate":"2012-09-01T07:45:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"User’s guide and metada for the PICES Nonindigenous Species Information System","docAbstract":"<h1>Introduction&nbsp;</h1>\n<p>Welcome to the PICES Nonindigenous Species Information System, a Microsoft Access database that displays the biogeographic distributions, invasion status, vectors, and key life history attributes of the approximately 740 reported nonindigenous species (NIS) in the estuarine and near-coastal habitats of the North Pacific and Hawaii. This database was developed by the U.S. Environmental Protection Agency and the U.S. Geological Survey under the auspices of Working Group 21 (Invasive Species) of the North Pacific Marine Science Organization (PCIES). The PICES database contains the data used to generate the &ldquo;Atlas of Nonindigenous Marine and Estuarine Species in the North Pacific&rdquo; (Lee and Reusser, 2012; herein referred to as the &ldquo;Atlas&rdquo;). The User&rsquo;s Guide provides instructions on how to use the PICES database as well as metadata for the database and the Atlas. We note that for most users, the Atlas provides a simpler approach to accessing key information on NIS in the PICES countries than the database, though the database does provide additional information on species and sources as well as allowing users to extract information on specific taxa and/or locations (see Section 4).</p>\n<p>The PICES database also includes species reported from the PICES Rapid Assessment Surveys (RAS). PICES sponsored four rapid assessment surveys with the objective of quickly characterizing the native, non-native, and cryptogenic species present in different locations. Surveys were sponsored in Dalian, China in 2008, Jeju, Korea in 2009, Newport, Oregon, USA in 2010, and Peter the Great Bay, near Vladivostok and Nakhodka, Russia in 2011 (<a href=\"http://www.pices.int/publications/pices_press/volume19/v19_n1/pp_30-31_Kobe-WS_f.pdf\">http://www.pices.int/publications/pices_press/volume19/v19_n1/pp_30-31_Kobe-WS_f.pdf</a>, <a href=\"http://www.pices.int/publications/pices_press/volume20/v20_n1/pp_26-29_RAS-2011.pdf\">http://www.pices.int/publications/pices_press/volume20/v20_n1/pp_26-29_RAS-2011.pdf</a>). The PICES database contains the RAS species that were made available in time for inclusion. Thus, the database does not capture all the species found in these surveys. In addition, much of the information on the RAS species was provided by the experts conducting the survey, and their distributions, environmental requirements, and life history attributes were not evaluated to the same level of detail by the PICES authors as the North Pacific NIS. In lieu of the more extensive review as conduced with the Atlas species, the information on the RAS species needs to be considered preliminary. Additionally, it is important to use the &ldquo;Map All Distributions&rdquo; option (see Section 3.6.6) when mapping their distribution or conducting a query. The general reference for the RAS surveys in the PICES database is &ldquo;PICES Working Group 21, YEAR SURVEY&rdquo;.</p>\n<p>The overall goal of both the database and Atlas was to simplify and standardize the dissemination of distributional, habitat, and life history characteristics of near-coastal and estuarine nonindigenous species. This database provides a means of querying these data and displaying the information in a consistent format. The specific classes of information the database captures include:</p>\n<ul>\n<li><span>Regional and global ranges of native and nonindigenous near-coastal and estuarine species at different hierarchical spatial scales. </span></li>\n<li><span>Habitat and physiological requirements of near-coastal and estuarine species. </span></li>\n<li><span>Life history characteristics of near-coastal and estuarine species. </span></li>\n<li><span>Invasion history and vectors for nonindigenous species.</span></li>\n</ul>\n<p>This standardized and synthesized data in the database and the Atlas provide the basic information needed to address a number of managerial and scientific needs. Thus, users will be able to:</p>\n<ul>\n<li><span>Create a baseline on the extent of invasion by region in order to assess new invasions. </span></li>\n<li><span>Use existing geographical patterns of invasion to gain some insights into potential new invaders. </span></li>\n<li><span>Use existing geographical patters of invasion to gain some insights into mechanisms affecting relative invasibility of different areas. </span></li>\n<li><span>Use life history attributes and environmental requirements of the reported nonindigenous species to evaluate traits of invaders. </span></li>\n<li><span>Understand the potential spread of invaders based on their habitat and environmental requirements. </span></li>\n<li><span>Understand importance of different vectors of introduction of nonindigenous species by region.</span></li>\n</ul>\n<p>The data in the Atlas of Nonindigenous Marine and Estuarine Species in the North Pacific (Lee and Reusser, 2012) are up-to-date as of June 2012. Updates to the PICES database were made in September 2012.&nbsp;</p>","language":"English","publisher":"U.S. Environmental Protection Agengy","usgsCitation":"Lee, Reusser, D.A., Marko, K., and Ranelletti, M., 2012, User’s guide and metada for the PICES Nonindigenous Species Information System, vii, 112 p.","productDescription":"vii, 112 p.","numberOfPages":"121","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-040946","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":320913,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":320912,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://nepis.epa.gov/Exe/ZyNET.exe/P100FZ0R.txt?ZyActionD=ZyDocument&Client=EPA&Index=1995%20Thru%201999%7C1976%20Thru%201980%7C2006%20Thru%202010%7C1991%20Thru%201994%7CHardcopy%20Publications%7C2000%20Thru%202005%7C1986%20Thru%201990%7C2011%20Thru%202015%7C1981%20Thru%201985%7CPrior%20to%201976&Docs=&Query=User%27s%20Guide%20Metadata%20PICES%20Nonindigenous%20Species%20Information%20System%20&Time=&EndTime=&SearchMethod=2&TocRestrict=n&Toc=&TocEntry=&QField=&QFieldYear=&QFieldMonth=&QFieldDay=&UseQField=&IntQFieldOp=0&ExtQFieldOp=0&XmlQuery=&File=D%3A%5CZYFILES%5CINDEX%20DATA%5C11THRU15%5CTXT%5C00000006%5CP100FZ0R.txt&User=ANONYMOUS&Password=anonymous&SortMethod=-%7Ch&MaximumDocuments=15&FuzzyDegree=0&ImageQuality=r85g16/r85g16/x150y150g16/i500&Display=hpfr&DefSeekPage=x&SearchBack=ZyActionL&Back=ZyActionS&BackDesc=Results%20page&MaximumPages=1&ZyEntry=1&SeekPage=x"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5729cbbce4b0b13d3919a3df","contributors":{"authors":[{"text":"Lee, Henry II","contributorId":119739,"corporation":false,"usgs":true,"family":"Lee","suffix":"Henry II","affiliations":[],"preferred":false,"id":516728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reusser, Deborah A. dreusser@usgs.gov","contributorId":2423,"corporation":false,"usgs":true,"family":"Reusser","given":"Deborah","email":"dreusser@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":628586,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marko, Katharine Katharine","contributorId":121216,"corporation":false,"usgs":true,"family":"Marko","given":"Katharine","suffix":"Katharine","email":"","affiliations":[],"preferred":false,"id":516729,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ranelletti, Marla Marla","contributorId":117077,"corporation":false,"usgs":true,"family":"Ranelletti","given":"Marla","suffix":"Marla","email":"","affiliations":[],"preferred":false,"id":516727,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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