The U.S. Geological Survey, in cooperation with the Trinity Glen Rose Groundwater Conservation District, the Edwards Aquifer Authority, and the San Antonio River Authority, developed a geodatabase of springs within and surrounding the Trinity aquifer outcrops in a 331-square-mile study area in northern Bexar County, Texas. The data used to develop the geodatabase were compiled from existing reports and databases, along with spring data collected between October 2010 and September 2011. Characteristics including the location, discharge, and water-quality properties were collected for known springs and documented in the geodatabase. A total of 141 springs were located within the study area, and 46 springs were field verified. The discharge at springs with flow ranged from 0.003 to 1.46 cubic feet per second. The specific conductance of the water discharging from the springs ranged from 167 to 1,130 microsiemens per centimeter at 25 degrees Celsius with a majority of values in the range of 500 microsiemens per centimeter at 25 degrees Celsius.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds750","collaboration":"Prepared in cooperation with Trinity Glen Rose Groundwater Conservation District, Edwards Aquifer Authority, and San Antonio River Authority","usgsCitation":"Clark, A.K., Pedraza, D.E., Morris, R., and Garcia, T.J., 2013, Geodatabase and characteristics of springs within and surrounding the Trinity aquifer outcrops in northern Bexar County, Texas, 2010--11: U.S. Geological Survey Data Series 750, Document: vi, 20 p.; Downloads Directory, https://doi.org/10.3133/ds750.","productDescription":"Document: vi, 20 p.; Downloads Directory","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":269777,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds750.gif"},{"id":269774,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/750/"},{"id":269775,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/750/pdf/ds750.pdf"},{"id":269776,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/750/downloads/"}],"country":"United States","state":"Texas","county":"Bexar County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -98.81,29.11 ], [ -98.81,29.76 ], [ -98.12,29.76 ], [ -98.12,29.11 ], [ -98.81,29.11 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"514acc5fe4b0040b38150c89","contributors":{"authors":[{"text":"Clark, Allan K. 0000-0003-0099-1521 akclark@usgs.gov","orcid":"https://orcid.org/0000-0003-0099-1521","contributorId":1279,"corporation":false,"usgs":true,"family":"Clark","given":"Allan","email":"akclark@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476196,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pedraza, Diana E. 0000-0003-4483-8094 dpedraza@usgs.gov","orcid":"https://orcid.org/0000-0003-4483-8094","contributorId":1281,"corporation":false,"usgs":false,"family":"Pedraza","given":"Diana","email":"dpedraza@usgs.gov","middleInitial":"E.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476197,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morris, Robert R. 0000-0001-7504-3732","orcid":"https://orcid.org/0000-0001-7504-3732","contributorId":106213,"corporation":false,"usgs":true,"family":"Morris","given":"Robert R.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476199,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garcia, Travis J.","contributorId":26173,"corporation":false,"usgs":true,"family":"Garcia","given":"Travis","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":476198,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70044648,"text":"ds709X - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nuristan mineral district in Afghanistan","interactions":[],"lastModifiedDate":"2013-03-19T10:25:22","indexId":"ds709X","displayToPublicDate":"2013-03-19T00:00:00","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":"X","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nuristan mineral district 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 Nuristan mineral district, which has gem, lithium, and cesium 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. All available panchromatic images for this area had significant cloud and snow cover that precluded their use for resolution enhancement of the multispectral image data. Each of the four-band images within the 10-m 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 Nuristan) and the WGS84 datum. The final image mosaics for the Nuristan 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/ds709X","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 X 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., Cagney, L.E., Arko, S.A., and Harbin, M., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nuristan mineral district in Afghanistan: U.S. Geological Survey Data Series 709, HTML Document; Readme; 4 Index Maps: 45 x 63 inches; 2 Image Files; 2 Metadata; Shapefiles, https://doi.org/10.3133/ds709X.","productDescription":"HTML Document; Readme; 4 Index Maps: 45 x 63 inches; 2 Image Files; 2 Metadata; Shapefiles","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":269695,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds709x.png"},{"id":269689,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/x/"},{"id":269690,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/x/1_readme.txt"},{"id":269691,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/x/index_maps/index_maps.html"},{"id":269692,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/x/image_files/image_files.html"},{"id":269693,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/x/metadata/metadata.html"},{"id":269694,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/x/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":"51498311e4b0971933f63654","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":509265,"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":476124,"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":476125,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arko, Scott A.","contributorId":101929,"corporation":false,"usgs":true,"family":"Arko","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":476127,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harbin, Michelle L.","contributorId":20590,"corporation":false,"usgs":true,"family":"Harbin","given":"Michelle L.","affiliations":[],"preferred":false,"id":476126,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70044615,"text":"70044615 - 2013 - Potential population-level effects of increased haulout-related mortality of Pacific walrus calves","interactions":[],"lastModifiedDate":"2013-03-18T12:47:02","indexId":"70044615","displayToPublicDate":"2013-03-18T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3093,"text":"Polar Biology","active":true,"publicationSubtype":{"id":10}},"title":"Potential population-level effects of increased haulout-related mortality of Pacific walrus calves","docAbstract":"Availability of summer sea ice has been decreasing in the Chukchi Sea during recent decades, and increasing numbers of Pacific walruses have begun using coastal haulouts in late summer during years when sea ice retreats beyond the continental shelf. Calves and yearlings are particularly susceptible to being crushed during disturbance events that cause the herd to panic and stampede at these large haulouts, but the potential population-level effects of this mortality are unknown. We used recent harvest data, along with previous assumptions about demographic parameters for this population, to estimate female population size and structure in 2009 and project these numbers forward using a range of assumptions about future harvests and haulout-related mortality that might result from increased use of coastal haulouts during late summer. We found that if demographic parameters were held constant, the levels of harvest that occurred during 1990–2008 would have allowed the population to grow during that period. Our projections indicate, however, that an increase in haulout-related mortality affecting only calves has a greater effect on the population than an equivalent increase in harvest-related mortality distributed among all age classes. Therefore, disturbance-related mortality of calves at coastal haulouts may have relatively important population consequences.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Polar Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Reston, VA","doi":"10.1007/s00300-012-1259-3","usgsCitation":"Udevitz, M.S., Taylor, R.L., Garlich-Miller, J.L., Quakenbush, L.T., and Snyder, J.A., 2013, Potential population-level effects of increased haulout-related mortality of Pacific walrus calves: Polar Biology, v. 36, no. 2, p. 291-298, https://doi.org/10.1007/s00300-012-1259-3.","productDescription":"8 p.","startPage":"291","endPage":"298","ipdsId":"IP-041758","costCenters":[{"id":115,"text":"Alaska Science Center Biology","active":false,"usgs":true}],"links":[{"id":269661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":269660,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00300-012-1259-3"}],"volume":"36","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-11-13","publicationStatus":"PW","scienceBaseUri":"51482961e4b022dd171afdb8","contributors":{"authors":[{"text":"Udevitz, Mark S. 0000-0003-4659-138X mudevitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4659-138X","contributorId":3189,"corporation":false,"usgs":true,"family":"Udevitz","given":"Mark","email":"mudevitz@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":476014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Rebecca L. 0000-0001-8459-7614 rebeccataylor@usgs.gov","orcid":"https://orcid.org/0000-0001-8459-7614","contributorId":5112,"corporation":false,"usgs":true,"family":"Taylor","given":"Rebecca","email":"rebeccataylor@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":476015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garlich-Miller, Joel L.","contributorId":10696,"corporation":false,"usgs":true,"family":"Garlich-Miller","given":"Joel","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":476016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quakenbush, Lori T.","contributorId":47262,"corporation":false,"usgs":true,"family":"Quakenbush","given":"Lori","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":476017,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Snyder, Jonathan A.","contributorId":54086,"corporation":false,"usgs":true,"family":"Snyder","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":476018,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70044641,"text":"sir20125198 - 2013 - Overview of groundwater quality in the Piceance Basin, western Colorado, 1946--2009","interactions":[],"lastModifiedDate":"2013-03-18T16:26:32","indexId":"sir20125198","displayToPublicDate":"2013-03-18T00:00:00","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":"2012-5198","title":"Overview of groundwater quality in the Piceance Basin, western Colorado, 1946--2009","docAbstract":"Groundwater-quality data from public and private sources for the period 1946 to 2009 were compiled and put into a common data repository for the Piceance Basin. The data repository is available on the web at http://rmgsc.cr.usgs.gov/cwqdr/Piceance/index.shtml. A subset of groundwater-quality data from the repository was compiled, reviewed, and checked for quality assurance for this report. The resulting dataset consists of the most recently collected sample from 1,545 wells, 1,007 (65 percent) of which were domestic wells. From those samples, the following constituents were selected for presentation in this report: dissolved oxygen, dissolved solids, pH, major ions (chloride, sulfate, fluoride), trace elements (arsenic, barium, iron, manganese, selenium), nitrate, benzene, toluene, ethylbenzene, xylene, methane, and the stable isotopic compositions of water and methane.\n\nSome portion of recharge to most of the wells for which data were available was derived from precipitation (most likely snowmelt), as indicated by δ2H [H2O] and δ18O[H2O] values that plot along the Global Meteoric Water Line and near the values for snow samples collected in the study area. Ninety-three percent of the samples were oxic, on the basis of concentrations of dissolved oxygen that were greater than or equal to 0.5 milligrams per liter.\n\nConcentration data were compared with primary and secondary drinking-water standards established by the U.S. Environmental Protection Agency. Constituents that exceeded the primary standards were arsenic (13 percent), selenium (9.2 percent), fluoride (8.4 percent), barium (4.1 percent), nitrate (1.6 percent), and benzene (0.6 percent). Concentrations of toluene, xylenes, and ethylbenzene did not exceed standards in any samples. Constituents that exceeded the secondary standard were dissolved solids (72 percent), sulfate (37 percent), manganese (21 percent), iron (16 percent), and chloride (10 percent). Drinking-water standards have not been established for methane, which was detected in 24 percent of samples. Methane concentrations were greater than or equal to 1 milligram per liter in 8.5 percent of samples. Methane isotopic data for samples collected primarily from domestic wells in Garfield County indicate that methane in samples with relative high methane concentrations were derived from both biogenic and thermogenic sources. Many of the constituents that exceeded standards, such as arsenic, fluoride, iron, and manganese, were derived from rock and sediment in aquifers. Elevated nitrate concentrations were most likely derived from human sources such as fertilizer and human or animal waste.\n\nInformation about the geologic unit or aquifer in which a well was completed generally was not provided by data sources. However, limited data indicate that Quaternary deposits in Garfield and Mesa Counties, the Wasatch Formation in Garfield County, and the Green River Formation in Rio Blanco County had some of the highest median concentrations of selected constituents. Variations in concentration with depth could not be evaluated because of the general lack of well-depth and water-level data.\n\nConcentrations of several important constituents, such as arsenic, manganese, methane, and nitrate, were related to concentrations of dissolved oxygen. Concentrations of arsenic, manganese, and methane were significantly higher in groundwater with low dissolved-oxygen concentrations than in groundwater with high dissolved-oxygen concentrations. In contrast, concentrations of nitrate were significantly higher in groundwater with high dissolved-oxygen concentrations than in groundwater with low dissolved-oxygen concentrations. These results indicate that measurements of dissolved oxygen may be a useful indicator of groundwater vulnerability to some human-derived contaminants and enrichment from some natural constituents.\n\nAssessing such a large and diverse dataset as the one available through the repository poses unique challenges for reporting on groundwater quality in the study area. The repository contains data from several studies that differed widely in purpose and scope. In addition to this variability in available data, gaps exist spatially, temporally, and analytically in the repository. For example, groundwater-quality data in the repository were not evenly distributed throughout the study area. Several key water-quality constituents or indicators, such as dissolved oxygen, were underrepresented in the repository. Ancillary information, such as well depth, depth to water, and the geologic unit or aquifer in which a well was completed, was missing for more than 50 percent of samples.\n\nFuture monitoring could avoid several limitations of the repository by making relatively minor changes to sample- collection and data-reporting protocols. Field measurements for dissolved oxygen could be added to sampling protocols, for example. Information on well construction and the geologic unit or aquifer in which a well was completed should be part of the water-quality dataset. Such changes would increase the comparability of data from different monitoring programs and also add value to each program individually and to that of the regional dataset as a whole. Other changes to monitoring programs could require greater resources, such as sampling for a basic set of constituents that is relevant to major water-quality issues in the regional study area. Creation of such a dataset for the regional study area would help to provide the kinds of information needed to characterize background conditions and the spatial and temporal variability in constituent concentrations associated with those conditions. Without such information, it is difficult to identify departures from background that might be associated with human activities.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125198","collaboration":"Prepared in cooperation with (in alphabetical order): Antero Resources, Bureau of Land Management, Bureau of Reclamation, Chevron Corporation, Cites of Grand Junction and Rifle, Colo., Colorado Department of Agriculture, Colorado Department of Natural Resources, Colorado Department of Public Health and Environment, Colorado Division of Wildlife—River Watch, Colorado Oil and Gas Conservation Commission, Colorado River Water Conservation District, Delta County, Colo., EnCana Oil & Gas (USA) Inc., Garfield County, Colo., Gunnison Energy Corp., National Park Service, Natural Soda, Inc., North Fork River Improvement Association, Oxy Petroleum Corporation, Petroleum Development Corp., Rio Blanco County, Shell Oil Company, Solvay Chemicals, Towns of Carbondale, De Beque, Palisade, Parachute, Rangely, and Silt, Colo., U.S. Forest Service, West Divide Water Conservancy District, and Williams Companies, Inc.","usgsCitation":"Thomas, J., and McMahon, P., 2013, Overview of groundwater quality in the Piceance Basin, western Colorado, 1946--2009: U.S. Geological Survey Scientific Investigations Report 2012-5198, vi, 204 p., https://doi.org/10.3133/sir20125198.","productDescription":"vi, 204 p.","numberOfPages":"213","additionalOnlineFiles":"N","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":269680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125198.gif"},{"id":269678,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5198/"},{"id":269679,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5198/SIR12-5198.pdf"}],"country":"United States","state":"Colorado","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0,37.0 ], [ -109.0,41.0 ], [ -102.0,41.0 ], [ -102.0,37.0 ], [ -109.0,37.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5148295fe4b022dd171afdb4","contributors":{"authors":[{"text":"Thomas, J.C.","contributorId":95435,"corporation":false,"usgs":true,"family":"Thomas","given":"J.C.","affiliations":[],"preferred":false,"id":476113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMahon, P.B. 0000-0001-7452-2379","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":10762,"corporation":false,"usgs":true,"family":"McMahon","given":"P.B.","affiliations":[],"preferred":false,"id":476112,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70044640,"text":"ds743 - 2013 - Lead isotope determinations from sulfide mineral occurrences--Russian Far East","interactions":[],"lastModifiedDate":"2013-03-18T15:19:48","indexId":"ds743","displayToPublicDate":"2013-03-18T00:00:00","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":"743","title":"Lead isotope determinations from sulfide mineral occurrences--Russian Far East","docAbstract":"The lead isotope database for sulfide deposits and occurrences in the Russian Far East was funded by the Mineral Resources Program, U.S. Geological Survey (USGS) in conjunction with the collaborative studies of mineral resources by the Russian Academy of Sciences and the U. S. Geological Survey (Nokleberg and others, 1996). Comparisons of these data with similar lead isotope data from Alaska published in Church, Delevaux, and others (1987) and Gaccetta and Church (1989) provide a basis for the following three-fold project objectives: 1. To utilize lead isotope signatures, in conjunction with regional mapping, to assess the relative ages and to categorize the types of mineral deposits studied, 2. To relate the lead isotope and trace-element geochemical signatures of specific deposits and occurrences to ore-forming processes, and 3. To use the lead isotope data to correlate lithotectonic terranes within the northern Cordillera (Alaska, Yukon Territories and British Columbia in Canada, and the western Cordillera of the United States). The report by Church, Gray, and others (1987) shows how this fingerprinting methodology can be applied to trace the offset of lithotectonic (or lithostratigraphic as labeled by some authors) terranes.The lead isotope data presented in table 1 represent the work completed on sulfide mineral deposits located in the Russian Far East from 1993 to 1995, when this study was terminated due to lack of funding. The lead isotope data are reported here for use by investigators who may find them of value in mineral exploration. No attempt is made to summarize the voluminous literature on these mineral deposits.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds743","usgsCitation":"Church, S.E., Goryachev, N., and Shpikerman, V.I., 2013, Lead isotope determinations from sulfide mineral occurrences--Russian Far East: U.S. Geological Survey Data Series 743, Report: iv, 4 p.; 2 Tables, Table 1: XLS file, Table 1: PDF file, https://doi.org/10.3133/ds743.","productDescription":"Report: iv, 4 p.; 2 Tables, Table 1: XLS file, Table 1: PDF file","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":269677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds743.gif"},{"id":269675,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/743/DS743_table%201.xlsx"},{"id":269673,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/743/"},{"id":269674,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/743/DS743.pdf"},{"id":269676,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/743/DS743_table%201.pdf"}],"country":"Russia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 129.20,50.96 ], [ 129.20,71.86 ], [ -163.83,71.86 ], [ -163.83,50.96 ], [ 129.20,50.96 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5148295de4b022dd171afdb0","contributors":{"authors":[{"text":"Church, Stan E. schurch@usgs.gov","contributorId":803,"corporation":false,"usgs":true,"family":"Church","given":"Stan","email":"schurch@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":false,"id":476109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goryachev, Nikolai A.","contributorId":7318,"corporation":false,"usgs":true,"family":"Goryachev","given":"Nikolai A.","affiliations":[],"preferred":false,"id":476110,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shpikerman, Vladimir I.","contributorId":35766,"corporation":false,"usgs":true,"family":"Shpikerman","given":"Vladimir","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":476111,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70041125,"text":"70041125 - 2013 - An assessment of hydrothermal alteration in the Santiaguito lava dome complex, Guatemala: implications for dome collapse hazards","interactions":[],"lastModifiedDate":"2013-03-18T17:38:19","indexId":"70041125","displayToPublicDate":"2013-03-18T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"An assessment of hydrothermal alteration in the Santiaguito lava dome complex, Guatemala: implications for dome collapse hazards","docAbstract":"A combination of field mapping, geochemistry, and remote sensing methods has been employed to determine the extent of hydrothermal alteration and assess the potential for failure at the Santiaguito lava dome complex, Guatemala. The 90-year-old complex of four lava domes has only experienced relatively small and infrequent dome collapses in the past, which were associated with lava extrusion. However, existing evidence of an active hydrothermal system coupled with intense seasonal precipitation also presents ideal conditions for instability related to weakened clay-rich edifice rocks. Mapping of the Santiaguito dome complex identified structural features related to dome growth dynamics, potential areas of weakness related to erosion, and locations of fumarole fields. X-ray diffraction and backscattered electron images taken with scanning electron microscopy of dacite and ash samples collected from around fumaroles revealed only minor clay films, and little evidence of alteration. Mineral mapping using ASTER and Hyperion satellite images, however, suggest low-temperature (<150 °C) silicic alteration on erosional surfaces of the domes, but not the type of pervasive acid-sulfate alteration implicated in collapses of other altered edifices. To evaluate the possibility of internal alteration, we re-examined existing aqueous geochemical data from dome-fed hot springs. The data indicate significant water–rock interaction, but the Na–Mg–K geoindicator suggests only a short water residence time, and δ18O/δD ratios show only minor shifts from the meteoric water line with little precipitation of secondary (alteration) minerals. Based on available data, hydrothermal alteration on the dome complex appears to be restricted to surficial deposits of hydrous silica, but the study has highlighted, importantly, that the 1902 eruption crater headwall of Santa María does show more advanced argillic alteration. We also cannot rule out the possibility of advanced alteration within the dome complex interior that is not accessible to the methods used here. 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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. 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Center","active":true,"usgs":true}],"preferred":false,"id":476055,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Sweat, Michael J. mjsweat@usgs.gov","contributorId":356,"corporation":false,"usgs":true,"family":"Sweat","given":"Michael","email":"mjsweat@usgs.gov","middleInitial":"J.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476042,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"Tuttle, Michele L. mtuttle@usgs.gov","contributorId":1028,"corporation":false,"usgs":true,"family":"Tuttle","given":"Michele L.","email":"mtuttle@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":476046,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"Wilson, Anna B. 0000-0002-9737-2614 awilson@usgs.gov","orcid":"https://orcid.org/0000-0002-9737-2614","contributorId":1619,"corporation":false,"usgs":true,"family":"Wilson","given":"Anna","email":"awilson@usgs.gov","middleInitial":"B.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":476049,"contributorType":{"id":1,"text":"Authors"},"rank":36}]}} ,{"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 Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (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":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 (ENS) values ranging from 0.44 to 0.83, 0.72 to 0.93, and 0.56 to 0.97, respectively, and coefficient of determination (R2) 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 ENS values ranging from 0.49 to 0.77, 0.69 to 0.91, and -0.22 to 0.95, respectively; R2 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 ENS values ranging from 0.28 to 0.82 and 0.61 to 0.86, respectively, and monthly and annual R2 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 ENS values less than zero. Monthly and annual validation R2 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":70043912,"text":"cir1384 - 2013 - Progress toward establishing a national assessment of water availability and use","interactions":[],"lastModifiedDate":"2017-03-29T12:08:23","indexId":"cir1384","displayToPublicDate":"2013-03-15T00:00:00","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":"1384","title":"Progress toward establishing a national assessment of water availability and use","docAbstract":"The Omnibus Public Land Management Act of 2009 (Public Law 111-11) was passed into law on March 30, 2009. Subtitle F, also known as the SECURE Water Act, calls for the establishment of a \"national water availability and use assessment program\" within the U.S. Geological Survey (USGS). A major driver for this recommendation was that national water availability and use have not been comprehensively assessed since 1978. This report fulfills a requirement to report to Congress on progress in implementing the national water availability and use assessment program, also referred to as the National Water Census. The SECURE Water Act authorized \\$20 million for each of fiscal years (FY) 2009 through 2023 for assessment of national water availability and use. The first appropriation for this effort was \\$4 million in FY 2011, followed by an appropriation of \\$6 million in FY 2012. The National Water Census synthesizes and reports information at the regional and national scales, with an emphasis on compiling and reporting the information in a way that is useful to states and others responsible for water management and natural-resource issues. The USGS works with Federal and non-Federal agencies, universities, and other organizations to ensure that the information can be aggregated with other types of water-availability and socioeconomic information, such as data on food and energy production. To maximize the utility of the information, the USGS coordinates the design and development of the effort through the Federal Advisory Committee on Water Information. A National Water Census is a complex undertaking, particularly because there are major gaps in the information needed to conduct such an assessment. To maximize progress, the USGS engaged stakeholders in a discussion of priorities and leveraged existing studies and program activities to enhance efforts toward the development of a National Water Census.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1384","usgsCitation":"Alley, W., Evenson, E.J., Barber, N.L., Bruce, B.W., Dennehy, K.F., Freeman, M., Freeman, W.O., Fischer, J., Hughes, W.B., Kennen, J., Kiang, J.E., Maloney, K.O., Musgrove, M., Ralston, B.E., Tessler, S., and Verdin, J.P., 2013, Progress toward establishing a national assessment of water availability and use: U.S. Geological Survey Circular 1384, vi, 36 p., https://doi.org/10.3133/cir1384.","productDescription":"vi, 36 p.","numberOfPages":"44","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":449,"text":"National Water 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M.","affiliations":[],"preferred":false,"id":474464,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evenson, Eric J. eevenson@usgs.gov","contributorId":4072,"corporation":false,"usgs":true,"family":"Evenson","given":"Eric","email":"eevenson@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":474461,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barber, Nancy L. 0000-0002-2952-5017 nlbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-2952-5017","contributorId":3679,"corporation":false,"usgs":true,"family":"Barber","given":"Nancy","email":"nlbarber@usgs.gov","middleInitial":"L.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":474459,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bruce, Breton W. bbruce@usgs.gov","contributorId":1127,"corporation":false,"usgs":true,"family":"Bruce","given":"Breton","email":"bbruce@usgs.gov","middleInitial":"W.","affiliations":[{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":474454,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dennehy, Kevin F. kdennehy@usgs.gov","contributorId":1128,"corporation":false,"usgs":true,"family":"Dennehy","given":"Kevin","email":"kdennehy@usgs.gov","middleInitial":"F.","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":474455,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research 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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":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":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":70044605,"text":"sir20105090D - 2013 - Porphyry copper assessment of Southeast Asia and Melanesia: Chapter D in Global mineral resource assessment","interactions":[{"subject":{"id":70044605,"text":"sir20105090D - 2013 - Porphyry copper assessment of Southeast Asia and Melanesia: Chapter D in Global mineral resource assessment","indexId":"sir20105090D","publicationYear":"2013","noYear":false,"chapter":"D","title":"Porphyry copper assessment of Southeast Asia and Melanesia: Chapter D in Global mineral resource assessment"},"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 Global mineral resource assessment","docAbstract":"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.
\nThis assessment covers the countries of Cambodia, Indonesia, Lao People’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 (<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.
\nGlobal 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.
\nAssessment 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.
\nOn 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.
\nThis 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.
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Jane M. 0000-0003-2742-3460 jhammars@usgs.gov","orcid":"https://orcid.org/0000-0003-2742-3460","contributorId":1226,"corporation":false,"usgs":true,"family":"Hammarstrom","given":"Jane","email":"jhammars@usgs.gov","middleInitial":"M.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":475981,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bookstrom, Arthur A. 0000-0003-1336-3364 abookstrom@usgs.gov","orcid":"https://orcid.org/0000-0003-1336-3364","contributorId":1542,"corporation":false,"usgs":true,"family":"Bookstrom","given":"Arthur","email":"abookstrom@usgs.gov","middleInitial":"A.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":475983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dicken, Connie L. 0000-0002-1617-8132 cdicken@usgs.gov","orcid":"https://orcid.org/0000-0002-1617-8132","contributorId":57098,"corporation":false,"usgs":true,"family":"Dicken","given":"Connie","email":"cdicken@usgs.gov","middleInitial":"L.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":475990,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science 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Jr. grobinso@usgs.gov","contributorId":3083,"corporation":false,"usgs":true,"family":"Robinson","given":"Gilpin","suffix":"Jr.","email":"grobinso@usgs.gov","middleInitial":"R.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":475985,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Setiabudi, Bambang Tjahjono","contributorId":55708,"corporation":false,"usgs":true,"family":"Setiabudi","given":"Bambang","email":"","middleInitial":"Tjahjono","affiliations":[],"preferred":false,"id":475989,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sukserm, Wudhikarn","contributorId":24250,"corporation":false,"usgs":true,"family":"Sukserm","given":"Wudhikarn","email":"","affiliations":[],"preferred":false,"id":475986,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sunuhadi, Dwi Nugroho","contributorId":46381,"corporation":false,"usgs":true,"family":"Sunuhadi","given":"Dwi","email":"","middleInitial":"Nugroho","affiliations":[],"preferred":false,"id":475988,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wah, Alexander Yan Sze","contributorId":30115,"corporation":false,"usgs":true,"family":"Wah","given":"Alexander","email":"","middleInitial":"Yan Sze","affiliations":[],"preferred":false,"id":475987,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zientek, Michael L. 0000-0002-8522-9626 mzientek@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":2420,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael","email":"mzientek@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":475984,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"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":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 Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","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 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 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 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: 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":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 (R2 = 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 (R2 = 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":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic 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":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana 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":70044550,"text":"ofr20131047 - 2013 - Miscellaneous geochemical data from waters in the Upper Animas River Watershed, Colorado","interactions":[],"lastModifiedDate":"2013-03-12T15:24:08","indexId":"ofr20131047","displayToPublicDate":"2013-03-12T00:00:00","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":"2013-1047","title":"Miscellaneous geochemical data from waters in the Upper Animas River Watershed, Colorado","docAbstract":"This report releases geochemistry data in waters from the upper Animas River watershed that have been analyzed by inductively coupled plasma–mass spectrometry. These samples were collected at various sites and at various dates (41 sites and 86 samples from 2008 to 2010). A main data table is provided and the text discusses the sampling methods and locations in relation to other published reports.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131047","usgsCitation":"Johnson, R.H., and Yager, D.B., 2013, Miscellaneous geochemical data from waters in the Upper Animas River Watershed, Colorado: U.S. Geological Survey Open-File Report 2013-1047, iii, 3 p.; Table 1, https://doi.org/10.3133/ofr20131047.","productDescription":"iii, 3 p.; Table 1","startPage":"i","endPage":"3","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":269180,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131047.gif"},{"id":269177,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1047/"},{"id":269179,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1047/table.xls"},{"id":269178,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1047/OF13-1047.pdf"}],"country":"United States","state":"Colorado","otherGeospatial":"Animas River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0,37.0 ], [ -109.0,41.0 ], [ -102.0,41.0 ], [ -102.0,37.0 ], [ -109.0,37.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51404080e4b089809dbf43ef","contributors":{"authors":[{"text":"Johnson, Raymond H. rhjohnso@usgs.gov","contributorId":707,"corporation":false,"usgs":true,"family":"Johnson","given":"Raymond","email":"rhjohnso@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":475871,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yager, Douglas B. 0000-0001-5074-4022 dyager@usgs.gov","orcid":"https://orcid.org/0000-0001-5074-4022","contributorId":798,"corporation":false,"usgs":true,"family":"Yager","given":"Douglas","email":"dyager@usgs.gov","middleInitial":"B.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":475872,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"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 Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","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 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 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 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: 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":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 R2 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":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":"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.
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.
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.
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.
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.
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.
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.
","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":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":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":"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.
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.
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.
","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":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics 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":70044525,"text":"cir1380 - 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A region of physical and cultural diversity: Chapter 2 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science"},"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":2},{"subject":{"id":70044535,"text":"cir13803 - 2013 - Challenge theme 1: Understanding and preserving ecological resources: Chapter 3 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science","indexId":"cir13803","publicationYear":"2013","noYear":false,"chapter":"3","title":"Challenge theme 1: Understanding and preserving ecological resources: Chapter 3 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science"},"predicate":"IS_PART_OF","object":{"id":70044525,"text":"cir1380 - 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2013 - Challenge theme 3: Protecting the environment and safeguarding human health: Chapter 5 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science","indexId":"cir13805","publicationYear":"2013","noYear":false,"chapter":"5","title":"Challenge theme 3: Protecting the environment and safeguarding human health: Chapter 5 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science"},"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":5},{"subject":{"id":70044540,"text":"cir13806 - 2013 - Challenge theme 4: People in the Borderlands: Chapter 6 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science","indexId":"cir13806","publicationYear":"2013","noYear":false,"chapter":"6","title":"Challenge theme 4: People in the Borderlands: Chapter 6 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science"},"predicate":"IS_PART_OF","object":{"id":70044525,"text":"cir1380 - 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2013 - Challenge theme 6: Natural hazard risks in the Borderlands: Chapter 8 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science","indexId":"cir13808","publicationYear":"2013","noYear":false,"chapter":"8","title":"Challenge theme 6: Natural hazard risks in the Borderlands: Chapter 8 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science"},"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":8},{"subject":{"id":70044543,"text":"cir13809 - 2013 - Challenge theme 7: Information support for management of border security and environmental protection: Chapter 9 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science","indexId":"cir13809","publicationYear":"2013","noYear":false,"chapter":"9","title":"Challenge theme 7: Information support for management of border security and environmental protection: Chapter 9 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science"},"predicate":"IS_PART_OF","object":{"id":70044525,"text":"cir1380 - 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2013 - An opportunity and an imperative: Chapter 11 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science","indexId":"cir138011","publicationYear":"2013","noYear":false,"chapter":"11","title":"An opportunity and an imperative: Chapter 11 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science"},"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":11}],"lastModifiedDate":"2017-01-26T14:37:35","indexId":"cir1380","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","title":"United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science","docAbstract":"Along the nearly 3,200 kilometers (almost 2,000 miles) of the United States–Mexican border, in an area known as the Borderlands, we are witnessing the expression of the challenges of the 21st century. This circular identifies several challenge themes and issues associated with life and the environment in the Borderlands, listed below. The challenges are not one-sided; they do not originate in one country only to become problems for the other. The issues and concerns of each challenge theme flow in both directions across the border, and both nations feel their effects throughout the Borderlands and beyond. The clear message is that our two nations, the United States and Mexico, face the issues in these challenge themes together, and the U.S. Geological Survey (USGS) understands it must work with its counterparts, partners, and customers in both countries.
Though the mission of the USGS is not to serve as land manager, law enforcer, or code regulator, its innovation and creativity and the scientific and technical depth of its capabilities can be directly applied to monitoring the conditions of the landscape. The ability of USGS scientists to critically analyze the monitored data in search of signals and trends, whether they lead to negative or positive results, allows us to reach significant conclusions—from providing factual conclusions to decisionmakers, to estimating how much of a natural resource exists in a particular locale, to predicting how a natural hazard phenomenon will unfold, to forecasting on a scale from hours to millennia how ecosystems will behave.
None of these challenge themes can be addressed strictly by one or two science disciplines; all require well-integrated, cross-discipline thinking, data collection, and analyses. The multidisciplinary science themes that have become the focus of the USGS mission parallel the major challenges in the border region between Mexico and the United States. Because of this multidisciplinary approach, the USGS possesses a unique set of capabilities that can address these challenges. The USGS can apply geographical, geospatial, biological, hydrological, and geological sciences to these complex issues and thereby provide insight into the area’s natural systems and their relation to human activity.
As we come to better understand the complexities of the components of these challenge themes, we discover that each part is inextricably intertwined with other overarching issues. Because of the complex interactions of the human, ecological, political, and economic exigencies associated with this area, the status of the Borderlands has become an ever-present concern for most American citizens and for Mexican and United States Federal, State, and local governments. This circular is intended to provide you - citizen, local decisionmaker, government leader, or private entrepreneur—an overview of what the USGS considers the current and future challenges in the United States–Mexican border region and examples of how the USGS can make a difference in understanding and addressing these issues.
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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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