{"pageNumber":"661","pageRowStart":"16500","pageSize":"25","recordCount":40804,"records":[{"id":70042785,"text":"70042785 - 2013 - Accounting for non-photosynthetic vegetation in remote-sensing-based estimates of carbon flux in wetlands","interactions":[],"lastModifiedDate":"2013-03-18T17:26:55","indexId":"70042785","displayToPublicDate":"2013-03-18T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3251,"text":"Remote Sensing Letters","active":true,"publicationSubtype":{"id":10}},"title":"Accounting for non-photosynthetic vegetation in remote-sensing-based estimates of carbon flux in wetlands","docAbstract":"Monitoring productivity in coastal wetlands is important due to their high carbon sequestration rates and potential role in climate change mitigation. We tested agricultural- and forest-based methods for estimating the fraction of absorbed photosynthetically active radiation (f APAR), a key parameter for modelling gross primary productivity (GPP), in a restored, managed wetland with a dense litter layer of non-photosynthetic vegetation, and we compared the difference in canopy light transmission between a tidally influenced wetland and the managed wetland. The presence of litter reduced correlations between spectral vegetation indices and f APAR. In the managed wetland, a two-band vegetation index incorporating simulated World View-2 or Hyperion green and near-infrared bands, collected with a field spectroradiometer, significantly correlated with f APAR only when measured above the litter layer, not at the ground where measurements typically occur. Measures of GPP in these systems are difficult to capture via remote sensing, and require an investment of sampling effort, practical methods for measuring green leaf area and accounting for background effects of litter and water.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","publisherLocation":"Philadelphia, PA","doi":"10.1080/2150704X.2013.766372","usgsCitation":"Schile, L.M., Byrd, K.B., Windham-Myers, L., and Kelly, M., 2013, Accounting for non-photosynthetic vegetation in remote-sensing-based estimates of carbon flux in wetlands: Remote Sensing Letters, v. 4, no. 6, p. 542-551, https://doi.org/10.1080/2150704X.2013.766372.","productDescription":"10 p.","startPage":"542","endPage":"551","ipdsId":"IP-041455","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":269686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":269685,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/2150704X.2013.766372"}],"volume":"4","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5148294fe4b022dd171afda0","contributors":{"authors":[{"text":"Schile, Lisa M.","contributorId":105985,"corporation":false,"usgs":true,"family":"Schile","given":"Lisa","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":472264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":472262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":472261,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelly, Maggi","contributorId":14275,"corporation":false,"usgs":true,"family":"Kelly","given":"Maggi","affiliations":[],"preferred":false,"id":472263,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70044616,"text":"70044616 - 2013 - Development and characterization of 21 polymorphic microsatellite markers for the barren-ground shrew, Sorex ugyunak (Mammalia: Sorcidae), through next-generation sequencing, and cross-species amplification in the masked shrew, S. cinereus","interactions":[],"lastModifiedDate":"2018-08-20T18:08:04","indexId":"70044616","displayToPublicDate":"2013-03-18T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1325,"text":"Conservation Genetics Resources","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Development and characterization of 21 polymorphic microsatellite markers for the barren-ground shrew, <i>Sorex ugyunak</i> (Mammalia: Sorcidae), through next-generation sequencing, and cross-species amplification in the masked shrew, <i>S. cinereus</i>","title":"Development and characterization of 21 polymorphic microsatellite markers for the barren-ground shrew, Sorex ugyunak (Mammalia: Sorcidae), through next-generation sequencing, and cross-species amplification in the masked shrew, S. cinereus","docAbstract":"<p>We used next generation shotgun sequencing to develop 21 novel microsatellite markers for the barren-ground shrew (<i class=\"EmphasisTypeItalic \">Sorex ugyunak</i>), which were polymorphic among individuals from northern Alaska. The loci displayed moderate allelic diversity (averaging 6.81 alleles per locus) and heterozygosity (averaging 70&nbsp;%). Two loci deviated from Hardy–Weinberg equilibrium (HWE) due to heterozygote deficiency. While the population did not deviate from HWE overall, it showed significant linkage disequilibrium suggesting this population is not in mutation-drift equilibrium. Nineteen of 21 loci were polymorphic in masked shrews (<i class=\"EmphasisTypeItalic \">S. cinereus</i>) from interior Alaska and exhibited linkage equilibrium and HWE overall. All loci yielded sufficient variability for use in population studies.</p>","language":"English","publisher":"Springer","doi":"10.1007/s12686-012-9792-5","usgsCitation":"Sonsthagen, S.A., Sage, G.K., Fowler, M., Hope, A.G., Cook, J., and Talbot, S.L., 2013, Development and characterization of 21 polymorphic microsatellite markers for the barren-ground shrew, Sorex ugyunak (Mammalia: Sorcidae), through next-generation sequencing, and cross-species amplification in the masked shrew, S. cinereus: Conservation Genetics Resources, v. 5, no. 2, p. 315-318, https://doi.org/10.1007/s12686-012-9792-5.","productDescription":"4 p.","startPage":"315","endPage":"318","ipdsId":"IP-041585","costCenters":[{"id":115,"text":"Alaska Science Center Biology","active":false,"usgs":true}],"links":[{"id":269663,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-10-10","publicationStatus":"PW","scienceBaseUri":"5148295ae4b022dd171afda8","contributors":{"authors":[{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":476021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sage, G. Kevin 0000-0003-1431-2286 ksage@usgs.gov","orcid":"https://orcid.org/0000-0003-1431-2286","contributorId":4348,"corporation":false,"usgs":true,"family":"Sage","given":"G.","email":"ksage@usgs.gov","middleInitial":"Kevin","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":476019,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fowler, Megan C. 0000-0002-4947-0236 mfowler@usgs.gov","orcid":"https://orcid.org/0000-0002-4947-0236","contributorId":200478,"corporation":false,"usgs":false,"family":"Fowler","given":"Megan C.","email":"mfowler@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":476023,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hope, Andrew G. 0000-0003-3814-2891 ahope@usgs.gov","orcid":"https://orcid.org/0000-0003-3814-2891","contributorId":4309,"corporation":false,"usgs":true,"family":"Hope","given":"Andrew","email":"ahope@usgs.gov","middleInitial":"G.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":476024,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cook, J.A.","contributorId":60868,"corporation":false,"usgs":true,"family":"Cook","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":476022,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":476020,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70044633,"text":"ds709W - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghunday-Achin mineral district in Afghanistan, in Davis, P.A, compiler, Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-03-17T20:55:47","indexId":"ds709W","displayToPublicDate":"2013-03-17T00:00:00","publicationYear":"2013","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":"W","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghunday-Achin mineral district in Afghanistan, in Davis, P.A, compiler, Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","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 Ghunday-Achin mineral district, which has magnesite and talc deposits.\n\nALOS 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 (©JAXA,2008,2009), 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.\n\nThe 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. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was 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 500-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).\n\nAll image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Ghunday-Achin) and the WGS84 datum. The final image mosaics were subdivided into six overlapping tiles or quadrants because of the large size of the target area. The six image tiles (or quadrants) for the Ghunday-Achin 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 Ghunday-Achin study area, two subareas were designated for detailed field investigations (that is, the Achin-Magnesite and Ghunday-Mamahel subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709W","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey; This report is Chapter W in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i> (DS 709)","usgsCitation":"Davis, P.A., Arko, S.A., and Harbin, M., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghunday-Achin mineral district in Afghanistan, in Davis, P.A, compiler, Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, HTML Document; Readme; 4 Index Maps: 71 x 33 inches; 16 Image Files; 16 Metadata; Shapefiles, https://doi.org/10.3133/ds709W.","productDescription":"HTML Document; Readme; 4 Index Maps: 71 x 33 inches; 16 Image Files; 16 Metadata; Shapefiles","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":269545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds709w.png"},{"id":269539,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/w/"},{"id":269543,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/w/metadata/metadata.html"},{"id":269540,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/w/1_readme.txt"},{"id":269541,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/w/index_maps/index_maps.html"},{"id":269542,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/w/image_files/image_files.html"},{"id":269544,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/w/shapefiles/shapefiles.html"}],"country":"Afghanistan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 58.0,28.0 ], [ 58.0,40.0 ], [ 78.0,40.0 ], [ 78.0,28.0 ], [ 58.0,28.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5146d7d2e4b0694ee75ad3d0","contributors":{"editors":[{"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":509264,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"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":476086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arko, Scott A.","contributorId":101929,"corporation":false,"usgs":true,"family":"Arko","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":476088,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harbin, Michelle L.","contributorId":20590,"corporation":false,"usgs":true,"family":"Harbin","given":"Michelle L.","affiliations":[],"preferred":false,"id":476087,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70044630,"text":"ofr20131033 - 2013 - U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative: 2011 annual report","interactions":[],"lastModifiedDate":"2025-05-14T19:21:09.723237","indexId":"ofr20131033","displayToPublicDate":"2013-03-17T00:00:00","publicationYear":"2013","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":"2013-1033","title":"U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative: 2011 annual report","docAbstract":"This is the fourth report produced by the U.S. Geological Survey (USGS) for the Wyoming Landscape Conservation Initiative (WLCI) to detail annual work activities. In FY2011, there were 37 ongoing, completed, or new projects conducted under the five major multi-disciplinary science and technical-assistance activities: (1) Baseline Synthesis, (2) Targeted Monitoring and Research, (3) Data and Information Management, (4) Integration and Coordination, and (5) Decisionmaking and Evaluation. The four new work activities were (1) development of the Western Energy Citation Clearinghouse, a Web-based energy-resource database of references for literature and on-line resources focused on energy development and its effects on natural resources; (2) a study to support the Sublette County Conservation District in ascertaining potential water-quality impacts to the New Fork River from energy development in the Pinedale Anticline Project Area; (3) a study to test the efficacy of blending high-frequency temporal data provided by Moderate Resolution Imaging Spectroradiometer (MODIS) sensors and high-resolution Landsat data for providing the fine-resolution data required to evaluate habitat responses to management activities at the landscape level; and (4) a study to examine the seasonal water chemistry of Muddy Creek, including documenting salinity patterns and providing a baseline for assessing potential effects of energy and other development on water quality in the Muddy Creek watershed. Two work activities were completed in FY2011: (1) the assessment of rancher perceptions of energy development in Southwest Wyoming and (2) mapping aspen stands and conifer encroachment using classification and regression tree (CART) analysis for effectiveness monitoring. The USGS continued to compile data, develop geospatial products, and upgrade Web-based products in support of both individual and overall WLCI efforts, including (1) ranking and prioritizing proposed conservation projects, (2) developing the WLCI integrated assessment, (3) developing the WLCI 5-year Conservation Action Plan, and (4) continuing to upgrade the content and improve the functionality of the WLCI Web site. For the WLCI FY2012 annual report, a decision was made to greatly reduce the overall length of the annual report, which will be accomplished by simplifying the report format and focusing on the take-home messages of each work activity for WLCI partners.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131033","usgsCitation":"Bowen, Z.H., Aldridge, C.L., Anderson, P.J., Assal, T.J., Biewick, L., Blecker, S.W., Boughton, G.K., Carr, N.B., Chalfoun, A., Chong, G.W., Clark, M.L., Diffendorfer, J.E., Fedy, B.C., Foster, K., Garman, S.L., Germaine, S., Hethcoat, M.G., Holloway, J., Homer, C.G., Kauffman, M., Keinath, D., Latysh, N., Manier, D.J., McDougal, R., Melcher, C.P., Miller, K.A., Montag, J., Olexa, E.M., Potter, C.J., Schell, S., Shafer, S., Smith, D., Stillings, L., Sweat, M.J., Tuttle, M., and Wilson, A.B., 2013, U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative: 2011 annual report: U.S. Geological Survey Open-File Report 2013-1033, xiii, 145 p., https://doi.org/10.3133/ofr20131033.","productDescription":"xiii, 145 p.","startPage":"i","endPage":"145","numberOfPages":"162","additionalOnlineFiles":"N","ipdsId":"IP-041360","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":269528,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1033/OF13-1033_508.pdf"},{"id":269529,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131033.gif"},{"id":269527,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1033/"}],"country":"United States","state":"Wyoming","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.1,41.0 ], [ -111.1,45.0 ], [ -104.1,45.0 ], [ -104.1,41.0 ], [ -111.1,41.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5146d7dee4b0694ee75ad3dc","contributors":{"authors":[{"text":"Bowen, Zachary H. 0000-0002-8656-1831 bowenz@usgs.gov","orcid":"https://orcid.org/0000-0002-8656-1831","contributorId":821,"corporation":false,"usgs":true,"family":"Bowen","given":"Zachary","email":"bowenz@usgs.gov","middleInitial":"H.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":476044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":476070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Patrick J. 0000-0003-2281-389X andersonpj@usgs.gov","orcid":"https://orcid.org/0000-0003-2281-389X","contributorId":3590,"corporation":false,"usgs":true,"family":"Anderson","given":"Patrick","email":"andersonpj@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":476057,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Assal, Timothy J. 0000-0001-6342-2954 assalt@usgs.gov","orcid":"https://orcid.org/0000-0001-6342-2954","contributorId":2203,"corporation":false,"usgs":true,"family":"Assal","given":"Timothy","email":"assalt@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":476052,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Biewick, 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,{"id":70044626,"text":"sir20135002 - 2013 - Use of the Soil and Water Assessment Tool (SWAT) for simulating hydrology and water quality in the Cedar River Basin, Iowa, 2000--10","interactions":[],"lastModifiedDate":"2013-03-16T11:20:42","indexId":"sir20135002","displayToPublicDate":"2013-03-16T00:00:00","publicationYear":"2013","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":"2013-5002","title":"Use of the Soil and Water Assessment Tool (SWAT) for simulating hydrology and water quality in the Cedar River Basin, Iowa, 2000--10","docAbstract":"The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, used the Soil and Water Assessment Tool to simulate streamflow and nitrate loads within the Cedar River Basin, Iowa. The goal was to assess the ability of the Soil and Water Assessment Tool to estimate streamflow and nitrate loads in gaged and ungaged basins in Iowa. The Cedar River Basin model uses measured streamflow data from 12 U.S. Geological Survey streamflow-gaging stations for hydrology calibration. The U.S. Geological Survey software program, Load Estimator, was used to estimate annual and monthly nitrate loads based on measured nitrate concentrations and streamflow data from three Iowa Department of Natural Resources Storage and Retrieval/Water Quality Exchange stations, located throughout the basin, for nitrate load calibration. The hydrology of the model was calibrated for the period of January 1, 2000, to December 31, 2004, and validated for the period of January 1, 2005, to December 31, 2010. Simulated daily, monthly, and annual streamflow resulted in Nash-Sutcliffe coefficient of model efficiency (E<sub>NS</sub>) values ranging from 0.44 to 0.83, 0.72 to 0.93, and 0.56 to 0.97, respectively, and coefficient of determination (R<sup>2</sup>) values ranging from 0.55 to 0.87, 0.74 to 0.94, and 0.65 to 0.99, respectively, for the calibration period. The percent bias ranged from -19 to 10, -16 to 10, and -19 to 10 for daily, monthly, and annual simulation, respectively. The validation period resulted in daily, monthly, and annual E<sub>NS</sub> values ranging from 0.49 to 0.77, 0.69 to 0.91, and -0.22 to 0.95, respectively; R<sup>2</sup> values ranging from 0.59 to 0.84, 0.74 to 0.92, and 0.36 to 0.92, respectively; and percent bias ranging from -16 for all time steps to percent bias of 14, 15, and 15, respectively.\n\nThe nitrate calibration was based on a small subset of the locations used in the hydrology calibration with limited measured data. Model performance ranges from unsatisfactory to very good for the calibration period (January 1, 2000, to December 31, 2004). Results for the validation period (January 1, 2005, to December 31, 2010) indicate a need for an increase of measured data as well as more refined documented management practices at a higher resolution. Simulated nitrate loads resulted in monthly and annual E<sub>NS</sub> values ranging from 0.28 to 0.82 and 0.61 to 0.86, respectively, and monthly and annual R<sup>2</sup> values ranging from 0.65 to 0.81 and 0.65 to 0.88, respectively, for the calibration period. The monthly and annual calibration percent bias ranged from 4 to 7 and 5 to 7, respectively. The validation period resulted in all but two E<sub>NS</sub> values less than zero. Monthly and annual validation R<sup>2</sup> values ranged from 0.5 to 0.67 and 0.25 to 0.48, respectively. Monthly and annual validation percent bias ranged from 46 to 68 for both time steps. A daily calibration and validation for nitrate loads was not performed because of the poor monthly and annual results; measured daily nitrate data are available for intervals of time in 2009 and 2010 during which a successful monthly and annual calibration could not be achieved.\n\nThe Cedar River Basin is densely gaged relative to other basins in Iowa; therefore, an alternative hydrology scenario was created to assess the predictive capabilities of the Soil and Water Assessment Tool using fewer locations of measured data for model hydrology calibration. Although the ability of the model to reproduce measured values improves with the number of calibration locations, results indicate that the Soil and Water Assessment Tool can be used to adequately estimate streamflow in less densely gaged basins throughout the State, especially at the monthly time step. However, results also indicate that caution should be used when calibrating a subbasin that consists of physically distinct regions based on only one streamflow-gaging station.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135002","collaboration":"Prepared in cooperation with the Iowa Department of Natural Resources","usgsCitation":"Hutchinson, K.J., and Christiansen, D.E., 2013, Use of the Soil and Water Assessment Tool (SWAT) for simulating hydrology and water quality in the Cedar River Basin, Iowa, 2000--10: U.S. Geological Survey Scientific Investigations Report 2013-5002, v, 36 p., https://doi.org/10.3133/sir20135002.","productDescription":"v, 36 p.","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2000-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-029808","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":269437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135002.gif"},{"id":269435,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5002/"},{"id":269436,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5002/sir13_5002.pdf"}],"country":"United States","state":"Iowa","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96.64,40.38 ], [ -96.64,43.5 ], [ -90.14,43.5 ], [ -90.14,40.38 ], [ -96.64,40.38 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51458659e4b0c47b5d322a6f","contributors":{"authors":[{"text":"Hutchinson, Kasey J. khutchin@usgs.gov","contributorId":4223,"corporation":false,"usgs":true,"family":"Hutchinson","given":"Kasey","email":"khutchin@usgs.gov","middleInitial":"J.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christiansen, Daniel E. 0000-0001-6108-2247 dechrist@usgs.gov","orcid":"https://orcid.org/0000-0001-6108-2247","contributorId":366,"corporation":false,"usgs":true,"family":"Christiansen","given":"Daniel","email":"dechrist@usgs.gov","middleInitial":"E.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476038,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70043490,"text":"70043490 - 2013 - MODIS-informed greenness responsesto daytime land surface temperaturefluctuations and wildfire disturbancesin the Alaskan Yukon River Basin","interactions":[],"lastModifiedDate":"2024-06-13T16:31:29.714489","indexId":"70043490","displayToPublicDate":"2013-03-15T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"MODIS-informed greenness responsesto daytime land surface temperaturefluctuations and wildfire disturbancesin the Alaskan Yukon River Basin","docAbstract":"Pronounced climate warming and increased wildfire disturbances are known to modify forest composition and control the evolution of the boreal ecosystem over the Yukon River Basin (YRB) in interior Alaska. In this study, we evaluate the post-fire green-up rate using the normalized difference vegetation index (NDVI) derived from 250 m 7 day eMODIS (an alternative and application-ready type of Moderate Resolution Imaging Spectroradiometer (MODIS) data) acquired between 2000 and 2009. Our analyses indicate measureable effects on NDVI values from vegetation type, burn severity, post-fire time, and climatic variables. The NDVI observations from both fire scars and unburned areas across the Alaskan YRB showed a tendency of an earlier start to the growing season (GS); the annual variations in NDVI were significantly correlated to daytime land surface temperature (LST) fluctuations; and the rate of post-fire green-up depended mainly on burn severity and the time of post-fire succession. The higher average NDVI values for the study period in the fire scars than in the unburned areas between 1950 and 2000 suggest that wildfires enhance post-fire greenness due to an increase in post-fire evergreen and deciduous species components","language":"English","publisher":"Taylor & Francis","publisherLocation":"London, UK","doi":"10.1080/01431161.2012.742215","usgsCitation":"Tan, Z., Liu, S., Jenkerson, C.B., Oeding, J., Wylie, B.K., Rover, J.R., and Young, C.J., 2013, MODIS-informed greenness responsesto daytime land surface temperaturefluctuations and wildfire disturbancesin the Alaskan Yukon River Basin: International Journal of Remote Sensing, v. 34, no. 6, p. 2187-2199, https://doi.org/10.1080/01431161.2012.742215.","productDescription":"13 p.","startPage":"2187","endPage":"2199","numberOfPages":"13","additionalOnlineFiles":"N","ipdsId":"IP-029373","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":268264,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -163.45,62.2 ], [ -163.45,68.97 ], [ -141.26,68.97 ], [ -141.26,62.2 ], [ -163.45,62.2 ] ] ] } } ] }","volume":"34","issue":"6","noUsgsAuthors":false,"publicationDate":"2012-11-26","publicationStatus":"PW","scienceBaseUri":"512c9613e4b0855fde6697d2","contributors":{"authors":[{"text":"Tan, Zhengxi 0000-0002-4136-0921 ztan@usgs.gov","orcid":"https://orcid.org/0000-0002-4136-0921","contributorId":2945,"corporation":false,"usgs":true,"family":"Tan","given":"Zhengxi","email":"ztan@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":473702,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shu-Guang sliu@usgs.gov","contributorId":984,"corporation":false,"usgs":true,"family":"Liu","given":"Shu-Guang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":473699,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jenkerson, Calli B. 0000-0002-3780-9175 jenkerson@usgs.gov","orcid":"https://orcid.org/0000-0002-3780-9175","contributorId":469,"corporation":false,"usgs":true,"family":"Jenkerson","given":"Calli","email":"jenkerson@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":473697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oeding, Jennifer joeding@usgs.gov","contributorId":4070,"corporation":false,"usgs":true,"family":"Oeding","given":"Jennifer","email":"joeding@usgs.gov","affiliations":[],"preferred":true,"id":473703,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":473698,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rover, Jennifer R. 0000-0002-3437-4030 jrover@usgs.gov","orcid":"https://orcid.org/0000-0002-3437-4030","contributorId":2941,"corporation":false,"usgs":true,"family":"Rover","given":"Jennifer","email":"jrover@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":false,"id":473701,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Young, Claudia J. 0000-0002-0859-7206 cyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-0859-7206","contributorId":2770,"corporation":false,"usgs":true,"family":"Young","given":"Claudia","email":"cyoung@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":473700,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70044582,"text":"70044582 - 2013 - Predictive occurrence models for coastal wetland plant communities: delineating hydrologic response surfaces with multinomial logistic regression","interactions":[],"lastModifiedDate":"2013-03-14T14:16:03","indexId":"70044582","displayToPublicDate":"2013-03-14T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Predictive occurrence models for coastal wetland plant communities: delineating hydrologic response surfaces with multinomial logistic regression","docAbstract":"Understanding plant community zonation along estuarine stress gradients is critical for effective conservation and restoration of coastal wetland ecosystems. We related the presence of plant community types to estuarine hydrology at 173 sites across coastal Louisiana. Percent relative cover by species was assessed at each site near the end of the growing season in 2008, and hourly water level and salinity were recorded at each site Oct 2007–Sep 2008. Nine plant community types were delineated with k-means clustering, and indicator species were identified for each of the community types with indicator species analysis. An inverse relation between salinity and species diversity was observed. Canonical correspondence analysis (CCA) effectively segregated the sites across ordination space by community type, and indicated that salinity and tidal amplitude were both important drivers of vegetation composition. Multinomial logistic regression (MLR) and Akaike's Information Criterion (AIC) were used to predict the probability of occurrence of the nine vegetation communities as a function of salinity and tidal amplitude, and probability surfaces obtained from the MLR model corroborated the CCA results. The weighted kappa statistic, calculated from the confusion matrix of predicted versus actual community types, was 0.7 and indicated good agreement between observed community types and model predictions. Our results suggest that models based on a few key hydrologic variables can be valuable tools for predicting vegetation community development when restoring and managing coastal wetlands.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Estuarine, Coastal and Shelf Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.ecss.2012.12.002","usgsCitation":"Snedden, G., and Steyer, G.D., 2013, Predictive occurrence models for coastal wetland plant communities: delineating hydrologic response surfaces with multinomial logistic regression: Estuarine, Coastal and Shelf Science, v. 118, p. 11-23, https://doi.org/10.1016/j.ecss.2012.12.002.","productDescription":"13 p.","startPage":"11","endPage":"23","ipdsId":"IP-033792","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":269352,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":269315,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecss.2012.12.002"}],"volume":"118","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5142e35ee4b073a963ff653d","chorus":{"doi":"10.1016/j.ecss.2012.12.002","url":"http://dx.doi.org/10.1016/j.ecss.2012.12.002","publisher":"Elsevier BV","authors":"Snedden Gregg A., Steyer Gregory D.","journalName":"Estuarine, Coastal and Shelf Science","publicationDate":"2/2013","auditedOn":"11/1/2014"},"contributors":{"authors":[{"text":"Snedden, Gregg A. 0000-0001-7821-3709","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":17338,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":475910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Steyer, Gregory D. 0000-0001-7231-0110 steyerg@usgs.gov","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":2856,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","email":"steyerg@usgs.gov","middleInitial":"D.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true}],"preferred":true,"id":475909,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70044606,"text":"ds709V - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Uruzgan mineral district in Afghanistan: Chapter V in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","interactions":[],"lastModifiedDate":"2013-03-14T20:50:12","indexId":"ds709V","displayToPublicDate":"2013-03-14T00:00:00","publicationYear":"2013","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":"V","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Uruzgan mineral district in Afghanistan: Chapter V 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 Uruzgan mineral district, which has tin and tungsten deposits.\n\nALOS 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 (©JAXA, 2008, 2009), 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.\n\nThe 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 500-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).\n\nAll image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Uruzgan) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the Uruzgan 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.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709V","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey","usgsCitation":"Davis, P.A., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Uruzgan mineral district in Afghanistan: Chapter V 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, HTML Document; Readme; 4 Index Maps: 66 x 59 inches; 16 Image Files; 16 Metadata; 1 Shapefile, https://doi.org/10.3133/ds709V.","productDescription":"HTML Document; Readme; 4 Index Maps: 66 x 59 inches; 16 Image Files; 16 Metadata; 1 Shapefile","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":269393,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds709v.png"},{"id":269389,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/v/index_maps/index_maps.html"},{"id":269390,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/v/image_files/image_files.html"},{"id":269391,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/v/metadata/metadata.html"},{"id":269392,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/v/shapefiles/shapefiles.html"},{"id":269387,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/v/"},{"id":269388,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/v/1_readme.txt"}],"country":"Afghanistan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 58.0,28.0 ], [ 58.0,40.0 ], [ 78.0,40.0 ], [ 78.0,28.0 ], [ 58.0,28.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5142e35ae4b073a963ff6531","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":475992,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70044605,"text":"sir20105090D - 2013 - Porphyry copper assessment of Southeast Asia and Melanesia: Chapter D in <i>Global mineral resource assessment</i>","interactions":[{"subject":{"id":70044605,"text":"sir20105090D - 2013 - Porphyry copper assessment of Southeast Asia and Melanesia: Chapter D in <i>Global mineral resource assessment</i>","indexId":"sir20105090D","publicationYear":"2013","noYear":false,"chapter":"D","title":"Porphyry copper assessment of Southeast Asia and Melanesia: Chapter D in <i>Global mineral resource assessment</i>"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2019-12-30T14:13:54","indexId":"sir20105090D","displayToPublicDate":"2013-03-14T00:00:00","publicationYear":"2013","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":"2010-5090","chapter":"D","title":"Porphyry copper assessment of Southeast Asia and Melanesia: Chapter D in <i>Global mineral resource assessment</i>","docAbstract":"<p>The U.S. Geological Survey collaborated with member countries of the Coordinating Committee for Geoscience Programmes in East and Southeast Asia (CCOP) on an assessment of the porphyry copper resources of Southeast Asia and Melanesia as part of a global mineral resource assessment. The region hosts world-class porphyry copper deposits and underexplored areas that are likely to contain undiscovered deposits. Examples of known porphyry copper deposits include Batu Hijau and Grasberg in Indonesia; Panguna, Frieda River, and Ok Tedi in Papua New Guinea; and Namosi in Fiji.</p>\n<p>This assessment covers the countries of Cambodia, Indonesia, Lao People&rsquo;s Democratic Republic, Malaysia, Myanmar, Papua New Guinea, Singapore, Thailand, and parts of southeastern China, India, the Solomon Islands, Vanuatu, and Fiji. Twenty-two geographic areas were delineated as tracts that are permissive for porphyry copper deposits in Southeast Asia. Permissive tracts are grouped into four broadly defined geographic/geologic areas, as follows: (1) the Indochina Peninsula area, (2) Indonesian and Malaysian Islands, (3) New Guinea Island and Papuan New Guinea islands, and (4) Melanesia. Individual tracts range from less than 1,000 to more than 350,000 square kilometers in area. Permissive tracts are based on mapped and inferred subsurface (&lt;1 kilometer depth) distributions of igneous rocks of specific age ranges that define magmatic arcs and magmatic belts that are likely to contain porphyry copper deposits. Most of these magmatic arcs are subduction-related, although some have porphyry-style deposits occurring in postcollisional and (or) poorly understood tectonic settings. Although maps at a variety of different scales were used in the compilation, the final tract boundaries are intended for use at a scale of 1:1,000,000.</p>\n<p>Global grade and tonnage models for porphyry copper deposits were evaluated. Most of the known deposits are best described as fitting the copper-gold (Cu-Au) subtype of porphyry copper deposit. For some permissive tracts, a general porphyry copper-gold-molybdenum (Cu-Au-Mo) model was used. Assessment participants estimated numbers of undiscovered deposits at different levels of confidence for most of the permissive tracts. These estimates were combined with grade and tonnage models using a Monte Carlo simulation to estimate undiscovered resources. Additional resources in extensions of deposits with identified resources were not evaluated.</p>\n<p>Assessment results, presented in tables and graphs, show mean amounts of metal and mineralized rock in undiscovered deposits at different quantile levels, as well as the arithmetic mean for each tract. This assessment estimated a mean of 89 undiscovered porphyry copper deposits for the assessed permissive tracts in Southeast Asia and Melanesia. About 288 million metric tons (Mt) of copper and 18,000 metric tons (t) of gold, as well as byproduct molybdenum and silver, could be associated with undiscovered deposits. This represents about four times the number of deposits with identified resources (23) already discovered in Southeast Asia; reliable reported identified resources for those 23 deposits total 84 Mt of copper and 6,000 t of gold. Eleven permissive tracts have no known porphyry copper deposits with reported resources. Three of those 11 tracts lacked sufficient information for a probabilistic assessment and are discussed in qualitative terms.</p>\n<p>On a regional basis, both the Indochina Peninsula area and the Indonesian-Malaysian Islands area are estimated to contain about 10 times as much in place copper in undiscovered porphyry copper deposits as has been identified to date. For the New Guinea Island areas, the ratio of undiscovered to identified copper resources is about 2. Some parts of the region have a long history of porphyry exploration cycles and mine development, interrupted at times by political and social unrest, environmental concerns, and natural disasters. Changes in mining laws within the region and the recent high price of gold on the world market have prompted renewed interest in porphyry copper deposits in Southeast Asia and Melanesia. However, predicted undiscovered deposits may not be found, and if found, may not be developed.</p>\n<p>This assessment includes an overview of the assessment results with summary tables. Detailed descriptions of each tract are included in appendixes, with estimates of numbers of undiscovered deposits, and probabilistic estimates of amounts of copper, molybdenum, gold, and silver that could be contained in undiscovered deposits for each permissive tract. A geographic information system (GIS) that accompanies the report includes tract boundaries and a database of known porphyry copper deposits and significant prospects.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Global mineral resource assessment (Scientific Investigations Report 2010-5090)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105090D","collaboration":"Prepared in cooperation with the Coordinating Committee for Geoscience Programmes in East and Southeast Asia","usgsCitation":"Hammarstrom, J.M., Bookstrom, A.A., Dicken, C.L., Drenth, B.J., Ludington, S., Robinson, G.R., Setiabudi, B.T., Sukserm, W., Sunuhadi, D.N., Wah, A.Y., and Zientek, M.L., 2013, Porphyry copper assessment of Southeast Asia and Melanesia: Chapter D in <i>Global mineral resource assessment</i>: U.S. Geological Survey Scientific Investigations Report 2010-5090, 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,{"id":70044602,"text":"70044602 - 2013 - Cold-seep habitat mapping: high-resolution spatial characterization of the Blake Ridge Diapir seep field","interactions":[],"lastModifiedDate":"2013-06-17T08:56:59","indexId":"70044602","displayToPublicDate":"2013-03-14T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1371,"text":"Deep-Sea Research Part II: Topical Studies in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Cold-seep habitat mapping: high-resolution spatial characterization of the Blake Ridge Diapir seep field","docAbstract":"Relationships among seep community biomass, diversity, and physiographic controls such as underlying geology are not well understood. Previous efforts to constrain these relationships at the Blake Ridge Diapir were limited to observations from piloted deep-submergence vehicles. In August 2012, the autonomous underwater vehicle (AUV) Sentry collected geophysical and photographic data over a 0.131 km2 area at the Blake Ridge Diapir seeps. A nested survey approach was used that began with a regional or reconnaissance-style survey using sub-bottom mapping systems to locate and identify seeps and underlying conduits. This survey was followed by AUV-mounted sidescan sonar and multibeam echosounder systems mapping on a mesoscale to characterize the seabed physiography. At the most detailed survey level, digital photographic imaging was used to resolve sub-meter characteristics of the biology. Four pockmarks (25–70 m diameter) were documented, each supporting chemosynthetic communities. Concentric zonation of mussels and clams suggests the influence of chemical gradients on megafaunal distribution. Data collection and analytical techniques used here yield high-resolution habitat maps that can serve as baselines to constrain temporal evolution of seafloor seeps, and to inform ecological niche modeling and resource management.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Deep-Sea Research Part II: Topical Studies in Oceanography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr2.2013.02.008","usgsCitation":"Wagner, J.K., McEntee, M.H., Brothers, L., German, C., Kaiser, C.L., Yoerger, D.R., and Van Dover, C.L., 2013, Cold-seep habitat mapping: high-resolution spatial characterization of the Blake Ridge Diapir seep field: Deep-Sea Research Part II: Topical Studies in Oceanography, v. 92, p. 183-188, https://doi.org/10.1016/j.dsr2.2013.02.008.","productDescription":"6 p.","startPage":"183","endPage":"188","ipdsId":"IP-042820","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":269357,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":269356,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.dsr2.2013.02.008"}],"otherGeospatial":"Blake Ridge Diapir","volume":"92","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5142e34fe4b073a963ff6529","contributors":{"authors":[{"text":"Wagner, Jamie K.S.","contributorId":91766,"corporation":false,"usgs":true,"family":"Wagner","given":"Jamie","email":"","middleInitial":"K.S.","affiliations":[],"preferred":false,"id":475957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McEntee, Molly H.","contributorId":73083,"corporation":false,"usgs":true,"family":"McEntee","given":"Molly","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":475955,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brothers, Laura L.","contributorId":96132,"corporation":false,"usgs":true,"family":"Brothers","given":"Laura L.","affiliations":[],"preferred":false,"id":475958,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"German, Christopher R.","contributorId":68190,"corporation":false,"usgs":true,"family":"German","given":"Christopher R.","affiliations":[],"preferred":false,"id":475954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaiser, Carl L.","contributorId":78216,"corporation":false,"usgs":true,"family":"Kaiser","given":"Carl","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":475956,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yoerger, Dana R.","contributorId":25428,"corporation":false,"usgs":true,"family":"Yoerger","given":"Dana","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":475952,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Van Dover, Cindy Lee","contributorId":26205,"corporation":false,"usgs":true,"family":"Van Dover","given":"Cindy","email":"","middleInitial":"Lee","affiliations":[],"preferred":false,"id":475953,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70044570,"text":"70044570 - 2013 - Streams in the urban heat island: spatial and  temporal variability in temperature","interactions":[],"lastModifiedDate":"2013-03-13T18:02:20","indexId":"70044570","displayToPublicDate":"2013-03-13T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Streams in the urban heat island: spatial and  temporal variability in temperature","docAbstract":"Streams draining urban heat islands tend to be hotter than rural and forested streams at baseflow because of warmer urban air and ground temperatures, paved surfaces, and decreased riparian canopy. Urban infrastructure efficiently routes runoff over hot impervious surfaces and through storm drains directly into streams and can lead to rapid, dramatic increases in temperature. Thermal regimes affect habitat quality and biogeochemical processes, and changes can be lethal if temperatures exceed upper tolerance limits of aquatic fauna. In summer 2009, we collected continuous (10-min interval) temperature data in 60 streams spanning a range of development intensity in the Piedmont of North Carolina, USA. The 5 most urbanized streams averaged 21.1°C at baseflow, compared to 19.5°C in the 5 most forested streams. Temperatures in urban streams rose as much as 4°C during a small regional storm, whereas the same storm led to extremely small to no changes in temperature in forested streams. Over a kilometer of stream length, baseflow temperature varied by as much as 10°C in an urban stream and as little as 2°C in a forested stream. We used structural equation modeling to explore how reach- and catchment-scale attributes interact to explain maximum temperatures and magnitudes of storm-flow temperature surges. The best predictive model of baseflow temperatures (R<sup>2</sup>  =  0.461) included moderately strong pathways directly (extent of development and road density) and indirectly, as mediated by reach-scale factors (canopy closure and stream width), from catchment-scale factors. The strongest influence on storm-flow temperature surges appeared to be % development in the catchment. Reach-scale factors, such as the extent of riparian forest and stream width, had little mitigating influence (R<sup>2</sup>  =  0.448). Stream temperature is an essential, but overlooked, aspect of the urban stream syndrome and is affected by reach-scale habitat variables, catchment-scale urbanization, and stream thermal regimes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Freshwater Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Society for Freshwater Science","publisherLocation":"Wolfville, N.S.","doi":"10.1899/12-046.1","usgsCitation":"Somers, K.A., Bernhardt, E., Grace, J.B., Hassett, B.A., Sudduth, E.B., Wang, S., and Urban, D., 2013, Streams in the urban heat island: spatial and  temporal variability in temperature: Freshwater Science, v. 32, no. 1, p. 309-326, https://doi.org/10.1899/12-046.1.","productDescription":"18 p.","startPage":"309","endPage":"326","ipdsId":"IP-036981","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":473919,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.1899/12-046.1","text":"External Repository"},{"id":269266,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1899/12-046.1"},{"id":269277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"514191dfe4b0eefcba208d3f","contributors":{"authors":[{"text":"Somers, Kayleigh A.","contributorId":32422,"corporation":false,"usgs":true,"family":"Somers","given":"Kayleigh","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":475886,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernhardt, Emily S.","contributorId":92143,"corporation":false,"usgs":false,"family":"Bernhardt","given":"Emily S.","affiliations":[{"id":27331,"text":"Duke University, Durham, NC","active":true,"usgs":false}],"preferred":false,"id":475889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":475883,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hassett, Brooke A.","contributorId":57744,"corporation":false,"usgs":true,"family":"Hassett","given":"Brooke","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":475887,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sudduth, Elizabeth B.","contributorId":8747,"corporation":false,"usgs":true,"family":"Sudduth","given":"Elizabeth","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":475884,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Siyi","contributorId":68196,"corporation":false,"usgs":true,"family":"Wang","given":"Siyi","email":"","affiliations":[],"preferred":false,"id":475888,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Urban, Dean L.","contributorId":10674,"corporation":false,"usgs":true,"family":"Urban","given":"Dean L.","affiliations":[],"preferred":false,"id":475885,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70044573,"text":"sim3243 - 2013 - Flood-inundation maps for the Tippecanoe River near Delphi, Indiana","interactions":[],"lastModifiedDate":"2013-03-13T17:38:08","indexId":"sim3243","displayToPublicDate":"2013-03-13T00:00:00","publicationYear":"2013","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":"3243","title":"Flood-inundation maps for the Tippecanoe River near Delphi, Indiana","docAbstract":"Digital flood-inundation maps for an 11-mile reach of the Tippecanoe River that extends from County Road W725N to State Road 18 below Oakdale Dam, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent of flooding corresponding to selected water levels (stages) at USGS streamgage 03333050, Tippecanoe River near Delphi, Ind. Current conditions at the USGS streamgages in Indiana may be obtained online at http://waterdata.usgs.gov/in/nwis/current/?type=flow. In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http://water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that are often co-located at USGS streamgages. That forecasted peak-stage information, also available on the Internet, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.\n\nIn this study, water-surface profiles were simulated for the stream reach by means of a hydraulic one-dimensional step-backwater model. The model was calibrated by using the most current stage-discharge relation at USGS streamgage 03333050, Tippecanoe River near Delphi, Ind., and USGS streamgage 03332605, Tippecanoe River below Oakdale Dam, Ind. The hydraulic model was then used to simulate 13 water-surface profiles for flood stages at 1-foot intervals reference to the streamgage datum and ranging from bankfull to approximately the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. A flood inundation map was generated for each water-surface profile stage (13 maps in all) so that, for any given flood stage, users will be able to view the estimated area of inundation.\n\nThe availability of these maps, along with current stage from USGS streamgages and forecasted stream stages from the NWS, provides emergency management personnel and residents with information that is critical for 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/sim3243","collaboration":"Prepared in cooperation with the Indiana Department of Transportation","usgsCitation":"Menke, C.D., Bunch, A.R., and Kim, M.H., 2013, Flood-inundation maps for the Tippecanoe River near Delphi, Indiana: U.S. Geological Survey Scientific Investigations Map 3243, Maps: 13 Sheets: 17 x 22 inches; Pamphlet: vi, 9 p.; Downloads Directory, https://doi.org/10.3133/sim3243.","productDescription":"Maps: 13 Sheets: 17 x 22 inches; Pamphlet: vi, 9 p.; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":269275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3243.gif"},{"id":269273,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sim/3243/pdf/mapsheets"},{"id":269274,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3243/Downloads"},{"id":269271,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3243/"},{"id":269272,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3243/pdf/sim3243.pdf"}],"country":"United States","state":"Indiana","city":"Delphi","otherGeospatial":"Tippecanoe River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.1,37.77 ], [ -88.1,41.76 ], [ -84.78,41.76 ], [ -84.78,37.77 ], [ -88.1,37.77 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"514191dce4b0eefcba208d37","contributors":{"authors":[{"text":"Menke, Chad D. cdmenke@usgs.gov","contributorId":3209,"corporation":false,"usgs":true,"family":"Menke","given":"Chad","email":"cdmenke@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":475890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunch, Aubrey R. 0000-0002-2453-3624 aurbunch@usgs.gov","orcid":"https://orcid.org/0000-0002-2453-3624","contributorId":4351,"corporation":false,"usgs":true,"family":"Bunch","given":"Aubrey","email":"aurbunch@usgs.gov","middleInitial":"R.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":475892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kim, Moon H. 0000-0002-4328-8409 mkim@usgs.gov","orcid":"https://orcid.org/0000-0002-4328-8409","contributorId":3211,"corporation":false,"usgs":true,"family":"Kim","given":"Moon","email":"mkim@usgs.gov","middleInitial":"H.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":475891,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70044569,"text":"70044569 - 2013 - A causal examination of the effects of confounding factors on multimetric indices","interactions":[],"lastModifiedDate":"2013-03-13T17:53:38","indexId":"70044569","displayToPublicDate":"2013-03-13T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"A causal examination of the effects of confounding factors on multimetric indices","docAbstract":"The development of multimetric indices (MMIs) as a means of providing integrative measures of ecosystem condition is becoming widespread. An increasingly recognized problem for the interpretability of MMIs is controlling for the potentially confounding influences of environmental covariates. Most common approaches to handling covariates are based on simple notions of statistical control, leaving the causal implications of covariates and their adjustment unstated. In this paper, we use graphical models to examine some of the potential impacts of environmental covariates on the observed signals between human disturbance and potential response metrics. Using simulations based on various causal networks, we show how environmental covariates can both obscure and exaggerate the effects of human disturbance on individual metrics. We then examine from a causal interpretation standpoint the common practice of adjusting ecological metrics for environmental influences using only the set of sites deemed to be in reference condition. We present and examine the performance of an alternative approach to metric adjustment that uses the whole set of sites and models both environmental and human disturbance effects simultaneously. The findings from our analyses indicate that failing to model and adjust metrics can result in a systematic bias towards those metrics in which environmental covariates function to artificially strengthen the metric–disturbance relationship resulting in MMIs that do not accurately measure impacts of human disturbance. We also find that a “whole-set modeling approach” requires fewer assumptions and is more efficient with the given information than the more commonly applied “reference-set” approach.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Indicators","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.ecolind.2013.01.015","usgsCitation":"Schoolmaster, D.R., Grace, J.B., Schweiger, E.W., Mitchell, B.R., and Guntenspergen, G.R., 2013, A causal examination of the effects of confounding factors on multimetric indices: Ecological Indicators, v. 29, p. 411-419, https://doi.org/10.1016/j.ecolind.2013.01.015.","productDescription":"9 p.","startPage":"411","endPage":"419","ipdsId":"IP-032370","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":269265,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolind.2013.01.015"},{"id":269276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"514191cfe4b0eefcba208d2f","contributors":{"authors":[{"text":"Schoolmaster, Donald R. Jr. 0000-0003-0910-4458 schoolmasterd@usgs.gov","orcid":"https://orcid.org/0000-0003-0910-4458","contributorId":4746,"corporation":false,"usgs":true,"family":"Schoolmaster","given":"Donald","suffix":"Jr.","email":"schoolmasterd@usgs.gov","middleInitial":"R.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":475880,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":475878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schweiger, E. William","contributorId":53635,"corporation":false,"usgs":true,"family":"Schweiger","given":"E.","email":"","middleInitial":"William","affiliations":[],"preferred":false,"id":475882,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mitchell, Brian R.","contributorId":14683,"corporation":false,"usgs":true,"family":"Mitchell","given":"Brian","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":475881,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":475879,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70044544,"text":"cir138010 - 2013 - The Borderlands and climate change: Chapter 10 in <i>United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science</i>","interactions":[{"subject":{"id":70044544,"text":"cir138010 - 2013 - The Borderlands and climate change: Chapter 10 in <i>United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science</i>","indexId":"cir138010","publicationYear":"2013","noYear":false,"chapter":"10","title":"The Borderlands and climate change: Chapter 10 in <i>United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science</i>"},"predicate":"IS_PART_OF","object":{"id":70044525,"text":"cir1380 - 2013 - United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science","indexId":"cir1380","publicationYear":"2013","noYear":false,"title":"United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science"},"id":1}],"isPartOf":{"id":70044525,"text":"cir1380 - 2013 - United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science","indexId":"cir1380","publicationYear":"2013","noYear":false,"title":"United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science"},"lastModifiedDate":"2017-01-26T14:48:07","indexId":"cir138010","displayToPublicDate":"2013-03-12T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1380","chapter":"10","title":"The Borderlands and climate change: Chapter 10 in <i>United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science</i>","docAbstract":"The prediction of global climate change in response to both natural forces and human activity is one of the defining issues of our times. The unprecedented observational capacity of modern earth-orbiting satellites coupled with the development of robust computational representations (models) of the Earth’s weather and climate systems afford us the opportunity to observe and investigate how these systems work now, how they have worked in the past, and how they will work in the future when forced in specific ways. In the most recent report on global climate change by the Intergovernmental Panel on Climate Change (IPCC; Solomon and others, 2007), analyses using multiple climate models support recent observations that the Earth’s climate is changing in response to a combination of natural and human-induced causes. These changes will be significant in the United States–Mexican border region, where the process of climate change affects all of the Borderlands challenge themes discussed in the preceding chapters. The dual possibilities of both significantly-changed climate and increasing variability in climate make it challenging to take full measure of the potential effects because the Borderlands already experience a high degree of interannual variability and climatological extremes.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science (Circular 1380)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir138010","usgsCitation":"Fitzpatrick, J., Gray, F., Dubiel, R., Langman, J., Moring, J., Norman, L.M., Page, W.R., and Parcher, J.W., 2013, The Borderlands and climate change: Chapter 10 in <i>United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science</i>: U.S. Geological Survey Circular 1380, 37 p., https://doi.org/10.3133/cir138010.","productDescription":"37 p.","startPage":"235","endPage":"271","numberOfPages":"39","costCenters":[{"id":572,"text":"Southwest Region","active":false,"usgs":true}],"links":[{"id":269138,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir138010.gif"},{"id":269137,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/circ/1380/"},{"id":269136,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1380/downloads/Chapter10.pdf"}],"country":"Mexico, United States","otherGeospatial":"United States-Mexico Borderlands","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -97.646484375,\n              24.246964554300924\n            ],\n            [\n              -96.6796875,\n              25.918526162075153\n            ],\n            [\n             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Center","active":true,"usgs":true}],"preferred":true,"id":475857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dubiel, Russell 0000-0002-1280-0350","orcid":"https://orcid.org/0000-0002-1280-0350","contributorId":78620,"corporation":false,"usgs":true,"family":"Dubiel","given":"Russell","affiliations":[],"preferred":false,"id":475863,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Langman, Jeff","contributorId":105983,"corporation":false,"usgs":true,"family":"Langman","given":"Jeff","affiliations":[],"preferred":false,"id":475864,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moring, J. Bruce","contributorId":53372,"corporation":false,"usgs":true,"family":"Moring","given":"J. Bruce","affiliations":[],"preferred":false,"id":475861,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Norman, Laura M. 0000-0002-3696-8406 lnorman@usgs.gov","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":967,"corporation":false,"usgs":true,"family":"Norman","given":"Laura","email":"lnorman@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":475858,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Page, William R. 0000-0002-0722-9911 rpage@usgs.gov","orcid":"https://orcid.org/0000-0002-0722-9911","contributorId":1628,"corporation":false,"usgs":true,"family":"Page","given":"William","email":"rpage@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":475859,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Parcher, Jean W. jwparcher@usgs.gov","contributorId":2209,"corporation":false,"usgs":true,"family":"Parcher","given":"Jean","email":"jwparcher@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":true,"id":475860,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70042437,"text":"70042437 - 2013 - Cross-sensor comparisons between Landsat 5 TM and IRS-P6 AWiFS and disturbance detection using integrated Landsat and AWiFS time-series images","interactions":[],"lastModifiedDate":"2013-03-12T13:21:57","indexId":"70042437","displayToPublicDate":"2013-03-12T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Cross-sensor comparisons between Landsat 5 TM and IRS-P6 AWiFS and disturbance detection using integrated Landsat and AWiFS time-series images","docAbstract":"Routine acquisition of Landsat 5 Thematic Mapper (TM) data was discontinued recently and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) has an ongoing problem with the scan line corrector (SLC), thereby creating spatial gaps when covering images obtained during the process. Since temporal and spatial discontinuities of Landsat data are now imminent, it is therefore important to investigate other potential satellite data that can be used to replace Landsat data. We thus cross-compared two near-simultaneous images obtained from Landsat 5 TM and the Indian Remote Sensing (IRS)-P6 Advanced Wide Field Sensor (AWiFS), both captured on 29 May 2007 over Los Angeles, CA. TM and AWiFS reflectances were compared for the green, red, near-infrared (NIR), and shortwave infrared (SWIR) bands, as well as the normalized difference vegetation index (NDVI) based on manually selected polygons in homogeneous areas. All R<sup>2</sup> values of linear regressions were found to be higher than 0.99. The temporally invariant cluster (TIC) method was used to calculate the NDVI correlation between the TM and AWiFS images. The NDVI regression line derived from selected polygons passed through several invariant cluster centres of the TIC density maps and demonstrated that both the scene-dependent polygon regression method and TIC method can generate accurate radiometric normalization. A scene-independent normalization method was also used to normalize the AWiFS data. Image agreement assessment demonstrated that the scene-dependent normalization using homogeneous polygons provided slightly higher accuracy values than those obtained by the scene-independent method. Finally, the non-normalized and relatively normalized ‘Landsat-like’ AWiFS 2007 images were integrated into 1984 to 2010 Landsat time-series stacks (LTSS) for disturbance detection using the Vegetation Change Tracker (VCT) model. Both scene-dependent and scene-independent normalized AWiFS data sets could generate disturbance maps similar to what were generated using the LTSS data set, and their kappa coefficients were higher than 0.97. These results indicate that AWiFS can be used instead of Landsat data to detect multitemporal disturbance in the event of Landsat data discontinuity.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","publisherLocation":"Philadelphia, PA","doi":"10.1080/01431161.2012.743690","usgsCitation":"Chen, X., Vogelmann, J., Chander, G., Ji, L., Tolk, B., Huang, C., and Rollins, M., 2013, Cross-sensor comparisons between Landsat 5 TM and IRS-P6 AWiFS and disturbance detection using integrated Landsat and AWiFS time-series images: International Journal of Remote Sensing, v. 34, no. 7, p. 2432-2453, https://doi.org/10.1080/01431161.2012.743690.","productDescription":"22 p.","startPage":"2432","endPage":"2453","ipdsId":"IP-022909","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":269159,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":269158,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/01431161.2012.743690"}],"volume":"34","issue":"7","noUsgsAuthors":false,"publicationDate":"2012-12-12","publicationStatus":"PW","scienceBaseUri":"5140407ee4b089809dbf43e7","contributors":{"authors":[{"text":"Chen, Xuexia","contributorId":14213,"corporation":false,"usgs":true,"family":"Chen","given":"Xuexia","affiliations":[],"preferred":false,"id":471526,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vogelmann, James E. 0000-0002-0804-5823 vogel@usgs.gov","orcid":"https://orcid.org/0000-0002-0804-5823","contributorId":649,"corporation":false,"usgs":true,"family":"Vogelmann","given":"James E.","email":"vogel@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":471523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chander, Gyanesh gchander@usgs.gov","contributorId":3013,"corporation":false,"usgs":true,"family":"Chander","given":"Gyanesh","email":"gchander@usgs.gov","affiliations":[],"preferred":true,"id":471525,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ji, Lei 0000-0002-6133-1036 lji@usgs.gov","orcid":"https://orcid.org/0000-0002-6133-1036","contributorId":2832,"corporation":false,"usgs":true,"family":"Ji","given":"Lei","email":"lji@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":471524,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tolk, Brian 0000-0002-9060-0266","orcid":"https://orcid.org/0000-0002-9060-0266","contributorId":62426,"corporation":false,"usgs":true,"family":"Tolk","given":"Brian","affiliations":[],"preferred":false,"id":471528,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Huang, Chengquan","contributorId":25378,"corporation":false,"usgs":true,"family":"Huang","given":"Chengquan","affiliations":[],"preferred":false,"id":471527,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rollins, Matthew","contributorId":72347,"corporation":false,"usgs":true,"family":"Rollins","given":"Matthew","affiliations":[],"preferred":false,"id":471529,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70044556,"text":"ds709U - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Bakhud mineral district in Afghanistan: Chapter U in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","interactions":[],"lastModifiedDate":"2013-03-12T18:57:26","indexId":"ds709U","displayToPublicDate":"2013-03-12T00:00:00","publicationYear":"2013","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":"U","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Bakhud mineral district in Afghanistan: Chapter U 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 Bakhud mineral district, which has industrial fluorite deposits.\n\nALOS 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 (©JAXA,2006,2007, 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.\n\nThe 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).\n\nAll image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (41 for Bakhud) and the WGS84 datum. The final image mosaics were subdivided into nine overlapping tiles or quadrants because of the large size of the target area. The nine image tiles (or quadrants) for the Bakhud 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.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709U","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey; This report is Chapter U in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","usgsCitation":"Davis, P.A., and Cagney, L.E., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Bakhud mineral district in Afghanistan: Chapter U 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, HTML Document; Readme; 4 Index Maps: 37 x 39 inches; 18 Image Files; Metadata; 1 Shapefile, https://doi.org/10.3133/ds709U.","productDescription":"HTML Document; Readme; 4 Index Maps: 37 x 39 inches; 18 Image Files; Metadata; 1 Shapefile","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":269192,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds709U.png"},{"id":269187,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/u/index_maps/index_maps.html"},{"id":269188,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/u/image_files/image_files.html"},{"id":269185,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/u/"},{"id":269186,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/u/1_readme.txt"},{"id":269189,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/u/metadata/metadata.html"},{"id":269190,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/u/shapefiles/shapefiles.html"},{"id":269191,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/index.html"}],"country":"Afghanistan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 58.0,28.0 ], [ 58.0,40.0 ], [ 78.0,40.0 ], [ 78.0,28.0 ], [ 58.0,28.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5140407fe4b089809dbf43eb","contributors":{"editors":[{"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":509263,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"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":475873,"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":475874,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70044520,"text":"sir20135003 - 2013 - Hydrologic data and groundwater flow simulations in the vicinity of Long Lake, Indiana Dunes National Lakeshore, near Gary, Indiana","interactions":[],"lastModifiedDate":"2018-10-02T11:21:55","indexId":"sir20135003","displayToPublicDate":"2013-03-11T00:00:00","publicationYear":"2013","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":"2013-5003","title":"Hydrologic data and groundwater flow simulations in the vicinity of Long Lake, Indiana Dunes National Lakeshore, near Gary, Indiana","docAbstract":"<p>The U.S. Geological Survey (USGS) collected data and simulated groundwater flow to increase understanding of the hydrology and the effects of drainage alterations to the water table in the vicinity of Long Lake, near Gary, Indiana. East Long Lake and West Long Lake (collectively known as Long Lake) make up one of the largest interdunal lakes within the Indiana Dunes National Lakeshore. The National Park Service is tasked with preservation and restoration of wetlands in the Indiana Dunes National Lakeshore along the southern shoreline of Lake Michigan. Urban development and engineering have modified drainage and caused changes in the distribution of open water, streams and ditches, and groundwater abundance and flow paths. A better understanding of the effects these modifications have on the hydrologic system in the area will help the National Park Service, the Gary Sanitary District (GSD), and local stakeholders manage and protect the resources within the study area.</p><p>This study used hydrologic data and steady-state groundwater simulations to estimate directions of groundwater flow and the effects of various engineering controls and climatic conditions on the hydrology near Long Lake. Periods of relatively high and low groundwater levels were examined and simulated by using MODFLOW and companion software. Simulated hydrologic modifications examined the effects of (1) removing the beaver dams in US-12 ditch, (2) discontinuing seepage of water from the filtration pond east of East Long Lake, (3) discontinuing discharge from US-12 ditch to the GSD sewer system, (4) decreasing discharge from US-12 ditch to the GSD sewer system, (5) connecting East Long Lake and West Long Lake, (6) deepening County Line Road ditch, and (7) raising and lowering the water level of Lake Michigan.</p><p>Results from collected hydrologic data indicate that East Long Lake functioned as an area of groundwater recharge during October 2002 and a “flow-through” lake during March 2011, with the groundwater divide south of US-12. Wetlands to the south of West Long Lake act as points of recharge to the surficial aquifer in both dry- and wet-weather conditions.</p><p>Among the noteworthy results from a dry-weather groundwater flow model simulation are (1) US-12 ditch does not receive water from East Long Lake or West Long Lake, (2) the filtration pond at the east end of East Long Lake, when active, contributed approximately 10 percent of the total water entering East Long Lake, and (3) County Line Road ditch has little effect on simulated water level.</p><p>Among the noteworthy results from a wet-weather groundwater flow simulation are (1) US-12 ditch does not receive water from East Long Lake or West Long Lake, (2) when the seepage from the filtration pond to the surficial aquifer is not active, sources of inflow to East Long Lake are restricted to only precipitation (46 percent of total) and inflow from the surficial aquifer (54 percent of total), and (3) County Line Road ditch bisects the groundwater divide and creates two water-table mounds south of US-12.</p><p>The results from a series of model scenarios simulating certain engineering controls and changes in Lake Michigan levels include the following: (1) The simulated removal of beaver dams in US-12 ditch during a wet-weather simulation increased discharge from the ditch to the Gary Sanitary system by 13 percent. (2) Discontinuation of seepage from the filtration pond east of East Long Lake decreased discharge from US-12 ditch to the Gary Sanitary system by 2.3 percent. (3) Simulated discontinuation of discharge from the US-12 ditch to the GSD sewer system increased the area where the water table was estimated to be above the land surface beyond the inundated area in the initial wet-weather simulation. (4) Simulated modifications to the control structure at the discharge point of US-12 ditch to the GSD sewer system can decrease discharge by as much as 61 percent while increasing the simulated inundated area during dry weather and decrease discharge as much as 6 percent while increasing the simulated inundated area during wet weather. (5) Deepening of County Line Road ditch can decrease the discharge from US-12 ditch by 26 percent during dry weather and 24 percent during wet weather, as well as decrease the extent of flooded areas south and east of the filtration pond near Ogden Dunes. (7) The increase of the Lake Michigan water level to match the historical maximum can increase the discharge from US-12 ditch by 14 percent during dry weather and by 9.6 percent during wet weather. (8) The decrease of the Lake Michigan water level to match the historical minimum can decrease the discharge from US-12 ditch by 7.4 percent during dry weather and by 3.1 percent during wet weather.</p><p>The results of this study can be used by water-resource managers to understand how surrounding ditches affect water levels in East and West Long Lake and in the surrounding wetlands and residential areas. The groundwater model developed in this study can be applied in the future to answer questions about how alterations to the drainage system in the area will affect water levels in East and West Long Lake and surrounding areas. The modeling methods developed in this study provide a template for other studies of groundwater flow and groundwater/surface-water interactions within the shallow surficial aquifer in northern Indiana, and in similar hydrologic settings that include surficial sand aquifers in coastal settings.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135003","collaboration":"Prepared in cooperation with the Gary Sanitary District, the Lake Michigan Coastal Program, the U.S. Army Corps of Engineers, and the National Park Service","usgsCitation":"Lampe, D.C., and Bayless, E.R., 2013, Hydrologic data and groundwater flow simulations in the vicinity of Long Lake, Indiana Dunes National Lakeshore, near Gary, Indiana: U.S. Geological Survey Scientific Investigations Report 2013-5003, Report: xii, 96 p.; Data releases, https://doi.org/10.3133/sir20135003.","productDescription":"Report: xii, 96 p.; Data releases","numberOfPages":"112","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":357924,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZP45D5","text":"USGS data release","description":"USGS data release","linkHelpText":"2018 - MODFLOW-NWT model scenarios used to evaluate potential effects of proposed drainage modifications on groundwater discharge in the vicinity of Long Lake, Indiana Dunes National Lakeshore, near Gary, Indiana"},{"id":349458,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7D21VS2","text":"USGS data release","description":"USGS data release","linkHelpText":"2017 - MODFLOW-NWT model used to evaluate potential effects of alterations to the hydrologic system in the vicinity of Long Lake, Indiana Dunes National Lakeshore, near Gary, Indiana"},{"id":269068,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135003.jpg"},{"id":269066,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5003/"},{"id":269067,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5003/pdf/SIR2013-5003.pdf","text":"Report","size":"11.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2013-5003"}],"country":"United States","state":"Indiana","city":"Gary","otherGeospatial":"Indiana Dunes National Lakeshore","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.1,37.8 ], [ -88.1,41.8 ], [ -84.8,41.8 ], [ -84.8,37.8 ], [ -88.1,37.8 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"513eeee0e4b0dcc733969347","contributors":{"authors":[{"text":"Lampe, David C. 0000-0002-8904-0337 dclampe@usgs.gov","orcid":"https://orcid.org/0000-0002-8904-0337","contributorId":2441,"corporation":false,"usgs":true,"family":"Lampe","given":"David","email":"dclampe@usgs.gov","middleInitial":"C.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":475800,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bayless, E. Randall 0000-0002-0357-3635 ebayless@usgs.gov","orcid":"https://orcid.org/0000-0002-0357-3635","contributorId":1518,"corporation":false,"usgs":true,"family":"Bayless","given":"E.","email":"ebayless@usgs.gov","middleInitial":"Randall","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":475799,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70044522,"text":"70044522 - 2013 - Geological analysis of aeromagnetic data from southwestern Alaska: Implications for exploration in the area of the Pebble porphyry Cu-Au-Mo deposit","interactions":[],"lastModifiedDate":"2020-09-11T18:49:35.298265","indexId":"70044522","displayToPublicDate":"2013-03-11T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geological analysis of aeromagnetic data from southwestern Alaska: Implications for exploration in the area of the Pebble porphyry Cu-Au-Mo deposit","docAbstract":"<p>Aeromagnetic data are used to better understand the geology and mineral resources near the Late Cretaceous Pebble porphyry Cu-Au-Mo deposit in southwestern Alaska. The reduced-to-pole (RTP) transformation of regional-scale aeromagnetic data shows that the Pebble deposit is within a cluster of magnetic anomaly highs. Similar to Pebble, the Iliamna, Kijik, and Neacola porphyry copper occurrences are in magnetic highs that trend northeast along the crustal-scale Lake Clark fault. A high-amplitude, short- to moderate-wavelength anomaly is centered over the Kemuk occurrence, an Alaska-type ultramafic complex. Similar anomalies are found west and north of Kemuk. A moderate-amplitude, moderate-wavelength magnetic low surrounded by a moderate-amplitude, short-wavelength magnetic high is associated with the gold-bearing Shotgun intrusive complex.</p><p>The RTP transformation of the district-scale aeromagnetic data acquired over Pebble permits differentiation of a variety of Jurassic to Tertiary magmatic rock suites. Jurassic-Cretaceous basalt and gabbro units and Late Cretaceous biotite pyroxenite and granodiorite rocks produce magnetic highs. Tertiary basalt units also produce magnetic highs, but appear to be volumetrically minor. Eocene monzonite units have associated magnetic lows. The RTP data do not suggest a magnetite-rich hydrothermal system at the Pebble deposit.</p><p>The 10-km upward continuation transformation of the regional-scale data shows a linear northeast trend of magnetic anomaly highs. These anomalies are spatially correlated with Late Cretaceous igneous rocks and in the Pebble district are centered over the granodiorite rocks genetically related to porphyry copper systems. The spacing of these anomalies is similar to patterns shown by the numerous porphyry copper deposits in northern Chile. These anomalies are interpreted to reflect a Late Cretaceous magmatic arc that is favorable for additional discoveries of Late Cretaceous porphyry copper systems in southwestern Alaska.</p>","language":"English","publisher":"Society of Economic Geologists","publisherLocation":"Littleton, CO","doi":"10.2113/econgeo.108.3.421","usgsCitation":"Anderson, E.D., Hitzman, M., Monecke, T., Bedrosian, P.A., Shah, A.K., and Kelley, K., 2013, Geological analysis of aeromagnetic data from southwestern Alaska: Implications for exploration in the area of the Pebble porphyry Cu-Au-Mo deposit: Economic Geology, v. 108, no. 3, p. 421-436, https://doi.org/10.2113/econgeo.108.3.421.","productDescription":"16 p.","startPage":"421","endPage":"436","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-033321","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":269091,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Pebble","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -156,\n              60\n            ],\n            [\n              -156,\n              59.5\n            ],\n            [\n              -155,\n              59.5\n            ],\n            [\n              -155,\n              60\n            ],\n            [\n              -156,\n              60\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"108","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-03-07","publicationStatus":"PW","scienceBaseUri":"513eeedfe4b0dcc733969343","contributors":{"authors":[{"text":"Anderson, Eric D. 0000-0002-0138-6166 ericanderson@usgs.gov","orcid":"https://orcid.org/0000-0002-0138-6166","contributorId":1733,"corporation":false,"usgs":true,"family":"Anderson","given":"Eric","email":"ericanderson@usgs.gov","middleInitial":"D.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":475814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hitzman, Murray W.","contributorId":14682,"corporation":false,"usgs":true,"family":"Hitzman","given":"Murray W.","affiliations":[],"preferred":false,"id":475816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Monecke, Thomas","contributorId":50423,"corporation":false,"usgs":true,"family":"Monecke","given":"Thomas","affiliations":[],"preferred":false,"id":475817,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":475813,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shah, Anjana K. 0000-0002-3198-081X ashah@usgs.gov","orcid":"https://orcid.org/0000-0002-3198-081X","contributorId":2297,"corporation":false,"usgs":true,"family":"Shah","given":"Anjana","email":"ashah@usgs.gov","middleInitial":"K.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":475815,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelley, Karen D. 0000-0002-3232-5809","orcid":"https://orcid.org/0000-0002-3232-5809","contributorId":57817,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen D.","affiliations":[],"preferred":false,"id":475818,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70044502,"text":"70044502 - 2013 - Modeling variably saturated subsurface solute transport with MODFLOW-UZF and MT3DMS","interactions":[],"lastModifiedDate":"2013-03-11T20:43:16","indexId":"70044502","displayToPublicDate":"2013-03-11T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Modeling variably saturated subsurface solute transport with MODFLOW-UZF and MT3DMS","docAbstract":"The MT3DMS groundwater solute transport model was modified to simulate solute transport in the unsaturated zone by incorporating the unsaturated-zone flow (UZF1) package developed for MODFLOW. The modified MT3DMS code uses a volume-averaged approach in which Lagrangian-based UZF1 fluid fluxes and storage changes are mapped onto a fixed grid. Referred to as UZF-MT3DMS, the linked model was tested against published benchmarks solved analytically as well as against other published codes, most frequently the U.S. Geological Survey's Variably-Saturated Two-Dimensional Flow and Transport Model. Results from a suite of test cases demonstrate that the modified code accurately simulates solute advection, dispersion, and reaction in the unsaturated zone. Two- and three-dimensional simulations also were investigated to ensure unsaturated-saturated zone interaction was simulated correctly. Because the UZF1 solution is analytical, large-scale flow and transport investigations can be performed free from the computational and data burdens required by numerical solutions to Richards' equation. Results demonstrate that significant simulation runtime savings can be achieved with UZF-MT3DMS, an important development when hundreds or thousands of model runs are required during parameter estimation and uncertainty analysis. Three-dimensional variably saturated flow and transport simulations revealed UZF-MT3DMS to have runtimes that are less than one tenth of the time required by models that rely on Richards' equation. Given its accuracy and efficiency, and the wide-spread use of both MODFLOW and MT3DMS, the added capability of unsaturated-zone transport in this familiar modeling framework stands to benefit a broad user-ship.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ground Water","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1745-6584.2012.00971.x","usgsCitation":"Morway, E., Niswonger, R., Langevin, C.D., Bailey, R., and Healy, R.W., 2013, Modeling variably saturated subsurface solute transport with MODFLOW-UZF and MT3DMS: Ground Water, v. 51, no. 2, p. 237-251, https://doi.org/10.1111/j.1745-6584.2012.00971.x.","productDescription":"15 p.","startPage":"237","endPage":"251","ipdsId":"IP-034540","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":473920,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1745-6584.2012.00971.x","text":"Publisher Index Page"},{"id":269092,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1745-6584.2012.00971.x"},{"id":269093,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-07-26","publicationStatus":"PW","scienceBaseUri":"513eeee1e4b0dcc73396934b","contributors":{"authors":[{"text":"Morway, Eric D.","contributorId":72276,"corporation":false,"usgs":true,"family":"Morway","given":"Eric D.","affiliations":[],"preferred":false,"id":475755,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Niswonger, Richard G.","contributorId":45402,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard G.","affiliations":[],"preferred":false,"id":475754,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langevin, Christian D. 0000-0001-5610-9759 langevin@usgs.gov","orcid":"https://orcid.org/0000-0001-5610-9759","contributorId":1030,"corporation":false,"usgs":true,"family":"Langevin","given":"Christian","email":"langevin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":475753,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bailey, Ryan T.","contributorId":105986,"corporation":false,"usgs":true,"family":"Bailey","given":"Ryan T.","affiliations":[],"preferred":false,"id":475756,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Healy, Richard W. 0000-0002-0224-1858 rwhealy@usgs.gov","orcid":"https://orcid.org/0000-0002-0224-1858","contributorId":658,"corporation":false,"usgs":true,"family":"Healy","given":"Richard","email":"rwhealy@usgs.gov","middleInitial":"W.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":475752,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70044499,"text":"sim3244 - 2013 - Flood-inundation maps for the Saluda River from Old Easley Bridge Road to Saluda Lake Dam near Greenville, South Carolina","interactions":[],"lastModifiedDate":"2018-03-23T14:25:53","indexId":"sim3244","displayToPublicDate":"2013-03-11T00:00:00","publicationYear":"2013","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":"3244","title":"Flood-inundation maps for the Saluda River from Old Easley Bridge Road to Saluda Lake Dam near Greenville, South Carolina","docAbstract":"Digital flood-inundation maps for a 3.95-mile reach of the Saluda River from approximately 815 feet downstream from Old Easley Bridge Road to approximately 150 feet downstream from Saluda Lake Dam near Greenville, South Carolina, were developed by the U.S. Geological Survey (USGS). The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Saluda River near Greenville, South Carolina (station 02162500). Current conditions at the USGS streamgage may be obtained through the National Water Information System Web site at http://waterdata.usgs.gov/sc/nwis/uv/?site_no=02162500&PARAmeter_cd=00065,00060,00062. The National Weather Service (NWS) forecasts flood hydrographs at many places that are often collocated with USGS streamgages. Forecasted peak-stage information is available on the Internet at the NWS Advanced Hydrologic Prediction Service (AHPS) flood-warning system Web site (http://water.weather.gov/ahps/) and may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated using the most current stage-streamflow relations at USGS streamgage station 02162500, Saluda River near Greenville, South Carolina. The hydraulic model was then used to determine water-surface profiles for flood stages at 1.0-foot intervals referenced to the streamgage datum and ranging from approximately bankfull to 2 feet higher than the highest recorded water level at the streamgage. The simulated water-surface profiles were then exported to a geographic information system, ArcGIS, and combined with a digital elevation model (derived from Light Detection and Ranging [LiDAR] data with a 0.6-foot vertical Root Mean Square Error [RMSE] and a 3.0-foot horizontal RMSE), using HEC-GeoRAS tools in order to delineate the area flooded at each water level. The availability of these maps, along with real-time stage data from the USGS streamgage station 02162500 and forecasted stream stages from the NWS, can provide emergency management personnel and residents with information that is critical during flood-response and flood-recovery activities, such as evacuations, road closures, and disaster declarations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3244","usgsCitation":"Benedict, S., Caldwell, A.W., and Clark, J.M., 2013, Flood-inundation maps for the Saluda River from Old Easley Bridge Road to Saluda Lake Dam near Greenville, South Carolina: U.S. Geological Survey Scientific Investigations Map 3244, Pamphlet: v, 7 p.; 15 Sheets; Downloads directory, https://doi.org/10.3133/sim3244.","productDescription":"Pamphlet: v, 7 p.; 15 Sheets; Downloads directory","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":13634,"text":"South Atlantic Water Science 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Andral W. 0000-0003-1269-5463 acaldwel@usgs.gov","orcid":"https://orcid.org/0000-0003-1269-5463","contributorId":3228,"corporation":false,"usgs":true,"family":"Caldwell","given":"Andral","email":"acaldwel@usgs.gov","middleInitial":"W.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":475737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Jimmy M. 0000-0002-3138-5738 jmclark@usgs.gov","orcid":"https://orcid.org/0000-0002-3138-5738","contributorId":4773,"corporation":false,"usgs":true,"family":"Clark","given":"Jimmy","email":"jmclark@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":475738,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70044541,"text":"cir13807 - 2013 - Challenge theme 5: Current and future needs of energy and mineral resources in the Borderlands and the effects of their development: Chapter 7 in <i>United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science</i>","interactions":[{"subject":{"id":70044541,"text":"cir13807 - 2013 - Challenge theme 5: Current and future needs of energy and mineral resources in the Borderlands and the effects of their development: Chapter 7 in <i>United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science</i>","indexId":"cir13807","publicationYear":"2013","noYear":false,"chapter":"7","title":"Challenge theme 5: Current and future needs of energy and mineral resources in the Borderlands and the effects of their development: Chapter 7 in <i>United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science</i>"},"predicate":"IS_PART_OF","object":{"id":70044525,"text":"cir1380 - 2013 - United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science","indexId":"cir1380","publicationYear":"2013","noYear":false,"title":"United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science"},"id":1}],"isPartOf":{"id":70044525,"text":"cir1380 - 2013 - United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science","indexId":"cir1380","publicationYear":"2013","noYear":false,"title":"United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science"},"lastModifiedDate":"2017-01-26T15:02:51","indexId":"cir13807","displayToPublicDate":"2013-03-11T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1380","chapter":"7","title":"Challenge theme 5: Current and future needs of energy and mineral resources in the Borderlands and the effects of their development: Chapter 7 in <i>United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science</i>","docAbstract":"Exploration and extraction activities related to energy and mineral resources in the Borderlands—such as coal-fired power plants, offshore drilling, and mining—can create issues that have potentially major economic and environmental implications. Resource assessments and development projects, environmental studies, and other related evaluations help to understand some of these issues, such as power plant emissions and the erosion/denudation of abandoned mine lands. Information from predictive modeling, monitoring, and environmental assessments are necessary to understand the full effects of energy and mineral exploration, development, and utilization. The exploitation of these resources can negatively affect human health and the environment, its natural resources, and its ecological services (air, water, soil, recreation, wildlife, etc.). This chapter describes the major energy and mineral issues of the Borderlands and how geologic frameworks, integrated interdisciplinary (geobiologic) investigations, and other related studies can address the anticipated increases in demands on natural resources in the region.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science (Circular 1380)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir13807","usgsCitation":"Updike, R.G., Ellis, E.G., Page, W.R., Parker, M.J., Hestbeck, J.B., and Horak, W.F., 2013, Challenge theme 5: Current and future needs of energy and mineral resources in the Borderlands and the effects of their development: Chapter 7 in <i>United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science</i>: U.S. Geological Survey Circular 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rpage@usgs.gov","orcid":"https://orcid.org/0000-0002-0722-9911","contributorId":1628,"corporation":false,"usgs":true,"family":"Page","given":"William","email":"rpage@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":475849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parker, Melanie J. mparker@usgs.gov","contributorId":670,"corporation":false,"usgs":true,"family":"Parker","given":"Melanie","email":"mparker@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":475847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hestbeck, Jay B. jay_hestbeck@usgs.gov","contributorId":4247,"corporation":false,"usgs":true,"family":"Hestbeck","given":"Jay","email":"jay_hestbeck@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":true,"id":475850,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Horak, William F.","contributorId":63280,"corporation":false,"usgs":true,"family":"Horak","given":"William","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":475851,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70044489,"text":"70044489 - 2013 - Using prairie restoration to curtail invasion of Canada thistle: the importance of limiting similarity and seed mix richness","interactions":[],"lastModifiedDate":"2018-01-02T12:28:01","indexId":"70044489","displayToPublicDate":"2013-03-09T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Using prairie restoration to curtail invasion of Canada thistle: the importance of limiting similarity and seed mix richness","docAbstract":"Theory has predicted, and many experimental studies have confirmed, that resident plant species richness is inversely related to invisibility. Likewise, potential invaders that are functionally similar to resident plant species are less likely to invade than are those from different functional groups. Neither of these ideas has been tested in the context of an operational prairie restoration. Here, we tested the hypotheses that within tallgrass prairie restorations (1) as seed mix species richness increased, cover of the invasive perennial forb, Canada thistle (Cirsium arvense) would decline; and (2) guilds (both planted and arising from the seedbank) most similar to Canada thistle would have a larger negative effect on it than less similar guilds. Each hypothesis was tested on six former agricultural fields restored to tallgrass prairie in 2005; all were within the tallgrass prairie biome in Minnesota, USA. A mixed-model with repeated measures (years) in a randomized block (fields) design indicated that seed mix richness had no effect on cover of Canada thistle. Structural equation models assessing effects of cover of each planted and non-planted guild on cover of Canada thistle in 2006, 2007, and 2010 revealed that planted Asteraceae never had a negative effect on Canada thistle. In contrast, planted cool-season grasses and non-Asteraceae forbs, and many non-planted guilds had negative effects on Canada thistle cover. We conclude that early, robust establishment of native species, regardless of guild, is of greater importance in resistance to Canada thistle than is similarity of guilds in new prairie restorations.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biological Invasions","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10530-013-0432-0","usgsCitation":"Larson, D.L., Bright, J., Drobney, P., Larson, J.L., Palaia, N., Rabie, P.A., Vacek, S., and Wells, D., 2013, Using prairie restoration to curtail invasion of Canada thistle: the importance of limiting similarity and seed mix richness: Biological Invasions, v. 15, no. 9, p. 2049-2063, https://doi.org/10.1007/s10530-013-0432-0.","productDescription":"15 p.","startPage":"2049","endPage":"2063","ipdsId":"IP-032455","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":268981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268980,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10530-013-0432-0"}],"country":"United States","state":"Minnesota","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.2,43.5 ], [ -97.2,49.4 ], [ -89.5,49.4 ], [ -89.5,43.5 ], [ -97.2,43.5 ] ] ] } } ] }","volume":"15","issue":"9","noUsgsAuthors":false,"publicationDate":"2013-02-24","publicationStatus":"PW","scienceBaseUri":"520a0403e4b0026c2bc11d1b","contributors":{"authors":[{"text":"Larson, Diane L. 0000-0001-5202-0634 dlarson@usgs.gov","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":2120,"corporation":false,"usgs":true,"family":"Larson","given":"Diane","email":"dlarson@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":475712,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bright, J.B.","contributorId":53547,"corporation":false,"usgs":true,"family":"Bright","given":"J.B.","email":"","affiliations":[],"preferred":false,"id":475716,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drobney, Pauline","contributorId":67342,"corporation":false,"usgs":true,"family":"Drobney","given":"Pauline","affiliations":[],"preferred":false,"id":475717,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larson, Jennifer L. 0000-0002-6259-0101","orcid":"https://orcid.org/0000-0002-6259-0101","contributorId":68144,"corporation":false,"usgs":true,"family":"Larson","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":475718,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Palaia, Nicholas","contributorId":25051,"corporation":false,"usgs":true,"family":"Palaia","given":"Nicholas","email":"","affiliations":[],"preferred":false,"id":475714,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rabie, Paul A. 0000-0003-4364-2268","orcid":"https://orcid.org/0000-0003-4364-2268","contributorId":74328,"corporation":false,"usgs":true,"family":"Rabie","given":"Paul","email":"","middleInitial":"A.","affiliations":[],"preferred":true,"id":475719,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vacek, Sara","contributorId":37214,"corporation":false,"usgs":true,"family":"Vacek","given":"Sara","email":"","affiliations":[],"preferred":false,"id":475715,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wells, Douglas","contributorId":6346,"corporation":false,"usgs":true,"family":"Wells","given":"Douglas","email":"","affiliations":[],"preferred":false,"id":475713,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70044462,"text":"sir20135032 - 2013 - Evaluation of the groundwater-flow model for the Ohio River alluvial aquifer near Carrollton, Kentucky, updated to conditions in September 2010","interactions":[],"lastModifiedDate":"2013-03-07T09:07:36","indexId":"sir20135032","displayToPublicDate":"2013-03-07T00:00:00","publicationYear":"2013","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":"2013-5032","title":"Evaluation of the groundwater-flow model for the Ohio River alluvial aquifer near Carrollton, Kentucky, updated to conditions in September 2010","docAbstract":"The Ohio River alluvial aquifer near Carrollton, Ky., is an important water resource for the cities of Carrollton and Ghent, as well as for several industries in the area. The groundwater of the aquifer is the primary source of drinking water in the region and a highly valued natural resource that attracts various water-dependent industries because of its quantity and quality. This report evaluates the performance of a numerical model of the groundwater-flow system in the Ohio River alluvial aquifer near Carrollton, Ky., published by the U.S. Geological Survey in 1999. The original model simulated conditions in November 1995 and was updated to simulate groundwater conditions estimated for September 2010. \nThe files from the calibrated steady-state model of November 1995 conditions were imported into MODFLOW-2005 to update the model to conditions in September 2010. The model input files modified as part of this update were the well and recharge files. The design of the updated model and other input files are the same as the original model. The ability of the updated model to match hydrologic conditions for September 2010 was evaluated by comparing water levels measured in wells to those computed by the model. Water-level measurements were available for 48 wells in September 2010. Overall, the updated model underestimated the water levels at 36 of the 48 measured wells. The average difference between measured water levels and model-computed water levels was 3.4 feet and the maximum difference was 10.9 feet. The root-mean-square error of the simulation was 4.45 for all 48 measured water levels. \nThe updated steady-state model could be improved by introducing more accurate and site-specific estimates of selected field parameters, refined model geometry, and additional numerical methods. Collection of field data to better estimate hydraulic parameters, together with continued review of available data and information from area well operators, could provide the model with revised estimates of conductance values for the riverbed and valley wall, hydraulic conductivities for the model layer, and target water levels for future simulations. Additional model layers, a redesigned model grid, and revised boundary conditions could provide a better framework for more accurate simulations. Additional numerical methods would identify possible parameter estimates and determine parameter sensitivities.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135032","collaboration":"Prepared in cooperation with the City of Carrollton, Kentucky","usgsCitation":"Unthank, M.D., 2013, Evaluation of the groundwater-flow model for the Ohio River alluvial aquifer near Carrollton, Kentucky, updated to conditions in September 2010: U.S. Geological Survey Scientific Investigations Report 2013-5032, iv, 14 p., https://doi.org/10.3133/sir20135032.","productDescription":"iv, 14 p.","startPage":"i","endPage":"14","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":268882,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135032.png"},{"id":268880,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5032/"},{"id":268881,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5032/pdf/SIR2013-5032.pdf"}],"country":"United States","state":"Kentucky","otherGeospatial":"Ohio River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.5715,36.4972 ], [ -89.5715,39.1475 ], [ -81.965,39.1475 ], [ -81.965,36.4972 ], [ -89.5715,36.4972 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5139b6ede4b09608cc166b07","contributors":{"authors":[{"text":"Unthank, Michael D. 0000-0003-2483-0431 munthank@usgs.gov","orcid":"https://orcid.org/0000-0003-2483-0431","contributorId":3902,"corporation":false,"usgs":true,"family":"Unthank","given":"Michael","email":"munthank@usgs.gov","middleInitial":"D.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":475667,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70044460,"text":"ds688 - 2013 - Groundwater-quality data in the Cascade Range and Modoc Plateau study unit, 2010-Results from the California GAMA Program","interactions":[],"lastModifiedDate":"2013-03-07T08:44:55","indexId":"ds688","displayToPublicDate":"2013-03-07T00:00:00","publicationYear":"2013","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":"688","title":"Groundwater-quality data in the Cascade Range and Modoc Plateau study unit, 2010-Results from the California GAMA Program","docAbstract":"Groundwater quality in the 39,000-square-kilometer Cascade Range and Modoc Plateau (CAMP) study unit was investigated by the U.S. Geological Survey (USGS) from July through October 2010, as part of the California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring and Assessment (GAMA) Program’s Priority Basin Project (PBP). The GAMA PBP was developed in response to the California Groundwater Quality Monitoring Act of 2001 and is being conducted in collaboration with the SWRCB and Lawrence Livermore National Laboratory (LLNL). The CAMP study unit is the thirty-second study unit to be sampled as part of the GAMA PBP. The GAMA CAMP study was designed to provide a spatially unbiased assessment of untreated-groundwater quality in the primary aquifer system and to facilitate statistically consistent comparisons of untreated-groundwater quality throughout California. The primary aquifer system is defined as that part of the aquifer corresponding to the open or screened intervals of wells listed in the California Department of Public Health (CDPH) database for the CAMP study unit. The quality of groundwater in shallow or deep water-bearing zones may differ from the quality of groundwater in the primary aquifer system; shallow groundwater may be more vulnerable to surficial contamination. In the CAMP study unit, groundwater samples were collected from 90 wells and springs in 6 study areas (Sacramento Valley Eastside, Honey Lake Valley, Cascade Range and Modoc Plateau Low Use Basins, Shasta Valley and Mount Shasta Volcanic Area, Quaternary Volcanic Areas, and Tertiary Volcanic Areas) in Butte, Lassen, Modoc, Plumas, Shasta, Siskiyou, and Tehama Counties. Wells and springs were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the study unit (grid wells). Groundwater samples were analyzed for field water-quality indicators, organic constituents, perchlorate, inorganic constituents, radioactive constituents, and microbial indicators. Naturally occurring isotopes and dissolved noble gases also were measured to provide a dataset that will be used to help interpret the sources and ages of the sampled groundwater in subsequent reports. In total, 221 constituents were investigated for this study. Three types of quality-control samples (blanks, replicates, and matrix spikes) were collected at approximately 10 percent of the wells in the CAMP study unit, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. Blanks rarely contained detectable concentrations of any constituent, suggesting that contamination from sample collection procedures was not a significant source of bias in the data for the groundwater samples. Replicate samples generally were within the limits of acceptable analytical reproducibility. Matrix-spike recoveries were within the acceptable range (70 to 130 percent) for approximately 90 percent of the compounds. This study did not attempt to evaluate the quality of water delivered to consumers; after withdrawal from the ground, untreated groundwater typically is treated, disinfected, and (or) blended with other waters to maintain water quality. Regulatory benchmarks apply to water that is served to the consumer, not to untreated groundwater. However, to provide some context for the results, concentrations of constituents measured in the untreated groundwater were compared with regulatory and non-regulatory health-based benchmarks established by the U.S. Environmental Protection Agency (USEPA) and CDPH, and to non-regulatory benchmarks established for aesthetic concerns by CDPH. Comparisons between data collected for this study and benchmarks for drinking water are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks. All organic constituents and most inorganic constituents that were detected in groundwater samples from the 90 grid wells in the CAMP study unit were detected at concentrations less than drinking-water benchmarks. Of the 148 organic constituents analyzed, 27 were detected in groundwater samples; concentrations of all detected constituents were less than regulatory and nonregulatory health-based benchmarks, and all were less than 1/10 of benchmark levels. One or more organic constituents were detected in 52 percent of the grid wells in the CAMP study unit: VOCs were detected in 30 percent, and pesticides and pesticide degradates were detected in 31 percent. Trace elements, major ions, nutrients, and radioactive constituents were sampled for at 90 grid wells in the CAMP study unit, and most detected concentrations were less than health-based benchmarks. Exceptions include three detections of arsenic greater than the USEPA maximum contaminant level (MCL-US) of 10 micrograms per liter (µg/L), two detections of boron greater than the CDPH notification level (NL-CA) of 1,000 µg/L, two detections of molybdenum greater than the USEPA lifetime health advisory level (HAL-US) of 40 µg/L, two detections of vanadium greater than the CDPH notification level (NL-CA) of 50 µg/L, one detection of nitrate, as nitrogen, greater than the MCL-US of 10 milligrams per liter (mg/L), two detections of uranium greater than the MCL-US of 30 µg/L and the MCL-CA of 20 picocuries per liter (pCi/L), one detection of radon-222 greater than the proposed MCL-US of 4,000 pCi/L, and two detections of gross alpha particle activity greater than the MCL-US of 15 pCi/L. Results for inorganic constituents with non-regulatory benchmarks set for aesthetic concerns showed that iron concentrations greater than the CDPH secondary maximum contaminant level (SMCL-CA) of 300 µg/L were detected in four grid wells. Manganese concentrations greater than the SMCL-CA of 50 µg/L were detected in nine grid wells. Chloride and TDS were detected at concentrations greater than the upper SMCL-CA benchmarks of 500 mg/L and 1,000 mg/L, respectively, in one grid well. Microbial indicators (total coliform and Escherichia coli [E. coli]) were detected in 11 percent of the 83 grid wells sampled for these analyses in the CAMP study unit. The presence of total coliform was detected in nine grid wells, and the presence of E. coli was detected in one of these same grid wells.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds688","collaboration":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Shelton, J.L., Fram, M.S., and Belitz, K., 2013, Groundwater-quality data in the Cascade Range and Modoc Plateau study unit, 2010-Results from the California GAMA Program: U.S. Geological Survey Data Series 688, x, 126 p., https://doi.org/10.3133/ds688.","productDescription":"x, 126 p.","numberOfPages":"138","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":268879,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds688.jpg"},{"id":268877,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/688/"},{"id":268878,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/688/pdf/ds688.pdf"}],"projection":"Albers Equal Area Conic Projection","datum":"North American Datum of 1983","country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -0.01611111111111111,8.333333333333334E-4 ], [ -0.01611111111111111,0.0011111111111111111 ], [ -0.01638888888888889,0.0011111111111111111 ], [ -0.01638888888888889,8.333333333333334E-4 ], [ -0.01611111111111111,8.333333333333334E-4 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5139b6eee4b09608cc166b0b","contributors":{"authors":[{"text":"Shelton, Jennifer L. 0000-0001-8508-0270 jshelton@usgs.gov","orcid":"https://orcid.org/0000-0001-8508-0270","contributorId":1155,"corporation":false,"usgs":true,"family":"Shelton","given":"Jennifer","email":"jshelton@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":475661,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":475662,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":475660,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70044461,"text":"b1995CC - 2013 - Characterization of the Hosgri Fault Zone and adjacent structures in the offshore Santa Maria Basin, south-central California","interactions":[{"subject":{"id":70044461,"text":"b1995CC - 2013 - Characterization of the Hosgri Fault Zone and adjacent structures in the offshore Santa Maria Basin, south-central California","indexId":"b1995CC","publicationYear":"2013","noYear":false,"chapter":"CC","title":"Characterization of the Hosgri Fault Zone and adjacent structures in the offshore Santa Maria Basin, south-central California"},"predicate":"IS_PART_OF","object":{"id":33200,"text":"b1995 - 1991 - Evolution of sedimentary basins/onshore oil and gas investigations: Santa Maria Province","indexId":"b1995","publicationYear":"1991","noYear":false,"title":"Evolution of sedimentary basins/onshore oil and gas investigations: Santa Maria Province"},"id":1}],"isPartOf":{"id":33200,"text":"b1995 - 1991 - Evolution of sedimentary basins/onshore oil and gas investigations: Santa Maria Province","indexId":"b1995","publicationYear":"1991","noYear":false,"title":"Evolution of sedimentary basins/onshore oil and gas investigations: Santa Maria Province"},"lastModifiedDate":"2021-08-30T18:41:17.50507","indexId":"b1995CC","displayToPublicDate":"2013-03-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":306,"text":"Bulletin","code":"B","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1995","chapter":"CC","title":"Characterization of the Hosgri Fault Zone and adjacent structures in the offshore Santa Maria Basin, south-central California","docAbstract":"The Hosgri Fault Zone trends subparallel to the south-central California coast for 110 km from north of Point Estero to south of Purisima Point and forms the eastern margin of the present offshore Santa Maria Basin. Knowledge of the attributes of the Hosgri Fault Zone is important for petroleum development, seismic engineering, and environmental planning in the region. Because it lies offshore along its entire reach, our characterizations of the Hosgri Fault Zone and adjacent structures are primarily based on the analysis of over 10,000 km of common-depth-point marine seismic reflection data collected from a 5,000-km2 area of the central and eastern parts of the offshore Santa Maria Basin. We describe and illustrate the along-strike and downdip geometry of the Hosgri Fault Zone over its entire length and provide examples of interpreted seismic reflection records and a map of the structural trends of the fault zone and adjacent structures in the eastern offshore Santa Maria Basin. The seismic data are integrated with offshore well and seafloor geologic data to describe the age and seismic appearance of offshore geologic units and marker horizons. We develop a basin-wide seismic velocity model for depth conversions and map three major unconformities along the eastern offshore Santa Maria Basin. Accompanying plates include maps that are also presented as figures in the report. Appendix A provides microfossil data from selected wells and appendix B includes uninterpreted copies of the annotated seismic record sections illustrated in the chapter. Features of the Hosgri Fault Zone documented in this investigation are suggestive of both lateral and reverse slip. Characteristics indicative of lateral slip include (1) the linear to curvilinear character of the mapped trace of the fault zone, (2) changes in structural trend along and across the fault zone that diminish in magnitude toward the ends of the fault zone, (3) localized compressional and extensional structures characteristic of constraining and releasing bends and stepovers, (4) changes in the sense and magnitude of vertical separation along strike within the fault zone, and (5) changes in downdip geometry between the major traces and segments of the fault zone. Characteristics indicative of reverse slip include (1) reverse fault geometries that occur across major strands of the fault zone and (2) fault-bend folds and localized thrust faults that occur along the northern and southern reaches of the fault. Analyses of high-resolution, subbottom profiler and side-scan sonar records indicate localized Holocene activity along most of the extent of the fault zone. Collectively, these features are the basis of our characterization of the Hosgri Fault Zone as an active, 110-km-long, convergent right-oblique slip (transpressional) fault with identified northern and southern terminations. This interpretation is consistent with recently published analyses of onshore geologic data, regional tectonic kinematic models, and instrumental seismicity.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Evolution of sedimentary basins/onshore oil and gas investigations: Santa Maria Province","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/b1995CC","usgsCitation":"Willingham, C.R., Rietman, J.D., Heck, R.G., and Lettis, W.R., 2013, Characterization of the Hosgri Fault Zone and adjacent structures in the offshore Santa Maria Basin, south-central California: U.S. Geological Survey Bulletin 1995, Report: ix, 106 p.; 7 Plates: 32 x 40 inches or smaller, https://doi.org/10.3133/b1995CC.","productDescription":"Report: ix, 106 p.; 7 Plates: 32 x 40 inches or smaller","numberOfPages":"116","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":379,"text":"Menlo Park Science Center","active":false,"usgs":true}],"links":[{"id":268893,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/b1995CC.jpg"},{"id":268892,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/bul/1995/cc/pdf/bul1995cc_plate7.pdf"},{"id":268891,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/bul/1995/cc/pdf/bul1995cc_plate6.pdf"},{"id":268889,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/bul/1995/cc/pdf/bul1995cc_plate5.pdf"},{"id":268888,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/bul/1995/cc/pdf/bul1995cc_plate4.pdf"},{"id":268887,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/bul/1995/cc/pdf/bul1995cc_plate3.pdf"},{"id":268884,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/bul/1995/cc/"},{"id":268886,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/bul/1995/cc/pdf/bul1995cc_plate2.pdf"},{"id":268883,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/bul/1995/cc/pdf/bul1995cc.pdf"},{"id":268885,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/bul/1995/cc/pdf/bul1995cc_plate1.pdf"}],"country":"United States","state":"California","otherGeospatial":"Hosgri Fault Zone","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.10205078125,\n              34.252676117101515\n            ],\n            [\n              -119.70703125,\n              34.252676117101515\n            ],\n            [\n              -119.70703125,\n              36.70365959719456\n            ],\n            [\n              -122.10205078125,\n              36.70365959719456\n            ],\n            [\n              -122.10205078125,\n              34.252676117101515\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5139b6ece4b09608cc166b03","contributors":{"authors":[{"text":"Willingham, C. 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