Use of existing marine protected areas (MPAs) by far-ranging marine turtles can be determined using satellite telemetry. Because of a lack of information on MPA use by marine turtles in the Gulf of Mexico, we used satellite transmitters in 2010 and 2011 to track movements of 11 adult female breeding green turtles (Chelonia mydas) tagged in Dry Tortugas National Park (DRTO), in the Gulf of Mexico, south Florida, USA. Throughout the study period, turtles emerged every 9–18 days to nest. During the intervals between nesting episodes (i.e., inter-nesting periods), the turtles consistently used a common core-area within the DRTO boundary, determined using individual 50% kernel-density estimates (KDEs). We mapped the area in DRTO where individual turtle 50% KDEs overlapped using the USGS Along-Track Reef-Imaging System, and determined the diversity and distribution of various benthic-cover types within the mapped area. We also tracked turtles post-nesting as they transited to foraging sites 5–282 km away from tagging beaches; these sites were located both within DRTO and in the surrounding area of the Florida Keys and Florida Keys National Marine Sanctuary (FKNMS), a regional MPA. Year-round residency of 9 out of 11 individuals (82%) both within DRTO and in the FKNMS represents novel non-migratory behavior, which offers an opportunity for conservation of this imperiled species at both local and regional scales. These data comprise the first satellite-tracking results on adult nesting green turtles at this remote study site. Additional tracking could reveal whether the distinct inter-nesting and foraging sites delineated here will be repeatedly used in the future by these and other breeding green turtles.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.biocon.2013.03.019","usgsCitation":"Hart, K., Zawada, D., Fujisaki, I., and Lidz, B.H., 2013, Habitat use of breeding green turtles Chelonia mydas tagged in Dry Tortugas National Park: Making use of local and regional MPAs: Biological Conservation, v. 161, p. 142-154, https://doi.org/10.1016/j.biocon.2013.03.019.","productDescription":"13 p.","startPage":"142","endPage":"154","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":271688,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Dry Tortugas National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.76673820002982,\n 24.702032234521695\n ],\n [\n -82.80111355697035,\n 24.72611070301882\n ],\n [\n -82.86737930528973,\n 24.725734512768284\n ],\n [\n -82.90051217944944,\n 24.717834254792294\n ],\n [\n -82.96719208869578,\n 24.649344358619032\n ],\n [\n -82.96553544498762,\n 24.5665042001456\n ],\n [\n -82.89678473110656,\n 24.566880870376693\n ],\n [\n -82.80028523511646,\n 24.617720954532814\n ],\n [\n -82.76632403910288,\n 24.66891673942027\n ],\n [\n -82.76632403910288,\n 24.702032234521695\n ],\n [\n -82.76673820002982,\n 24.702032234521695\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"161","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51822b69e4b04bbc6ead26fa","chorus":{"doi":"10.1016/j.biocon.2013.03.019","url":"http://dx.doi.org/10.1016/j.biocon.2013.03.019","publisher":"Elsevier BV","authors":"Hart Kristen M., Zawada David G., Fujisaki Ikuko, Lidz Barbara H.","journalName":"Biological Conservation","publicationDate":"5/2013","auditedOn":"11/1/2014"},"contributors":{"authors":[{"text":"Hart, Kristen","contributorId":49253,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[],"preferred":false,"id":478212,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zawada, David G. 0000-0003-4547-4878 dzawada@usgs.gov","orcid":"https://orcid.org/0000-0003-4547-4878","contributorId":1898,"corporation":false,"usgs":true,"family":"Zawada","given":"David G.","email":"dzawada@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":478209,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fujisaki, Ikuko","contributorId":31108,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":478211,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lidz, Barbara H. blidz@usgs.gov","contributorId":2475,"corporation":false,"usgs":true,"family":"Lidz","given":"Barbara","email":"blidz@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":478210,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045744,"text":"ds709AA - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Bamyan mineral district in Afghanistan","interactions":[],"lastModifiedDate":"2013-05-01T21:52:05","indexId":"ds709AA","displayToPublicDate":"2013-05-01T00:00:00","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":"AA","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Bamyan 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 South Bamyan mineral district, which has areas with a spectral reflectance anomaly that require field investigation.\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 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 South Bamyan) and the WGS84 datum. The final image mosaics for the South Bamyan 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/ds709AA","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 South Bamyan mineral district in Afghanistan: U.S. Geological Survey Data Series 709, HTML Document; Readme; 4 Index Maps; 2 Image Files; 2 Metadata; Shapefiles, https://doi.org/10.3133/ds709AA.","productDescription":"HTML Document; Readme; 4 Index Maps; 2 Image Files; 2 Metadata; Shapefiles","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":271713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds709AA.png"},{"id":271709,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/aa/index_maps/index_maps.html"},{"id":271710,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/aa/image_files/image_files.html"},{"id":271711,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/aa/metadata/metadata.html"},{"id":271712,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/aa/shapefiles/shapefiles.html"},{"id":271707,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/aa/"},{"id":271708,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/aa/1_readme.txt"}],"country":"Afghanistan","otherGeospatial":"South Bamyan Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 60.52,29.38 ], [ 60.52,38.49 ], [ 74.89,38.49 ], [ 74.89,29.38 ], [ 60.52,29.38 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51822b6ce4b04bbc6ead270a","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":509320,"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":478227,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70189221,"text":"70189221 - 2013 - Community-based water-quality monitoring in the Yukon River Basin and the Kuskokwim Watershed","interactions":[],"lastModifiedDate":"2017-07-07T09:44:47","indexId":"70189221","displayToPublicDate":"2013-04-30T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5452,"text":"Witness the Arctic","active":true,"publicationSubtype":{"id":10}},"title":"Community-based water-quality monitoring in the Yukon River Basin and the Kuskokwim Watershed","docAbstract":"The unique partnership between the USGS and the YRITWC provides mutual benefits by fostering outreach efforts that have been essential for community empowerment and by generating scientific data for prohibitively large and remote regions that would be challenging for USGS scientists to sample as robustly alone. 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The Bakken and Three Forks Formations were assessed as continuous and hypothetical conventional oil accumulations using a methodology similar to that used in the assessment of other continuous- and conventional-type assessment units throughout the United States. 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tennyson@usgs.gov","orcid":"https://orcid.org/0000-0002-5166-2421","contributorId":1433,"corporation":false,"usgs":true,"family":"Tennyson","given":"Marilyn E.","email":"tennyson@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":478077,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Whidden, Katherine J. 0000-0002-7841-2553 kwhidden@usgs.gov","orcid":"https://orcid.org/0000-0002-7841-2553","contributorId":3960,"corporation":false,"usgs":true,"family":"Whidden","given":"Katherine","email":"kwhidden@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":478080,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70045695,"text":"ofr20131063 - 2013 - Air temperature, wind speed, and wind direction in the National Petroleum Reserve—Alaska and the Arctic National Wildlife Refuge, 1998–2011","interactions":[],"lastModifiedDate":"2013-04-30T08:37:02","indexId":"ofr20131063","displayToPublicDate":"2013-04-30T00:00:00","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":"2013-1063","title":"Air temperature, wind speed, and wind direction in the National Petroleum Reserve—Alaska and the Arctic National Wildlife Refuge, 1998–2011","docAbstract":"This report provides air temperature, wind speed, and wind direction data collected on Federal lands in Arctic Alaska over the period August 1998 to July 2011 by the U.S. Department of the Interior's climate monitoring array, part of the Global Terrestrial Network for Permafrost. In addition to presenting data, this report also describes monitoring, data collection, and quality control methodology. This array of 16 monitoring stations spans 68.5°N to 70.5°N and 142.5°W to 161°W, an area of roughly 150,000 square kilometers. Climate summaries are presented along with provisional quality-controlled data. Data collection is ongoing and includes several additional climate variables to be released in subsequent reports, including ground temperature and soil moisture, snow depth, rainfall, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131063","usgsCitation":"Urban, F., and Clow, G.D., 2013, Air temperature, wind speed, and wind direction in the National Petroleum Reserve—Alaska and the Arctic National Wildlife Refuge, 1998–2011: U.S. Geological Survey Open-File Report 2013-1063, HTML Document: Introduction/main text; Tunalik; Umiat; Inigok; Koluktak; Lake 145; Marsh Creek; Niquanak; Piksiksak; Red Sheep Creek; South Meade; Awuana 1; Awuana 2; Camden Bay; Drew Point; East Teshekpuk; Fish Creek; Ikpikpuk, https://doi.org/10.3133/ofr20131063.","productDescription":"HTML Document: Introduction/main text; Tunalik; Umiat; Inigok; Koluktak; Lake 145; Marsh Creek; Niquanak; Piksiksak; Red Sheep Creek; South Meade; Awuana 1; Awuana 2; Camden Bay; Drew Point; East Teshekpuk; Fish Creek; Ikpikpuk","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":271620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131063.jpg"},{"id":271619,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1063/"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -0.015,0.0016666666666666668 ], [ -0.015,0.0019444444444444444 ], [ -0.015833333333333335,0.0019444444444444444 ], [ -0.015833333333333335,0.0016666666666666668 ], [ -0.015,0.0016666666666666668 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5180d9cfe4b0df838b924d21","contributors":{"authors":[{"text":"Urban, Frank E. 0000-0002-1329-1703","orcid":"https://orcid.org/0000-0002-1329-1703","contributorId":80918,"corporation":false,"usgs":true,"family":"Urban","given":"Frank E.","affiliations":[],"preferred":false,"id":478060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clow, Gary D. 0000-0002-2262-3853 clow@usgs.gov","orcid":"https://orcid.org/0000-0002-2262-3853","contributorId":2066,"corporation":false,"usgs":true,"family":"Clow","given":"Gary","email":"clow@usgs.gov","middleInitial":"D.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":478059,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045697,"text":"sir20135042 - 2013 - Simulation of groundwater flow, effects of artificial recharge, and storage volume changes in the Equus Beds aquifer near the city of Wichita, Kansas well field, 1935–2008","interactions":[],"lastModifiedDate":"2013-04-30T10:39:05","indexId":"sir20135042","displayToPublicDate":"2013-04-30T00:00:00","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":"2013-5042","title":"Simulation of groundwater flow, effects of artificial recharge, and storage volume changes in the Equus Beds aquifer near the city of Wichita, Kansas well field, 1935–2008","docAbstract":"The Equus Beds aquifer is a primary water-supply source for Wichita, Kansas and the surrounding area because of shallow depth to water, large saturated thickness, and generally good water quality. Substantial water-level declines in the Equus Beds aquifer have resulted from pumping groundwater for agricultural and municipal needs, as well as periodic drought conditions. In March 2006, the city of Wichita began construction of the Equus Beds Aquifer Storage and Recovery project to store and later recover groundwater, and to form a hydraulic barrier to the known chloride-brine plume near Burrton, Kansas. In October 2009, the U.S. Geological Survey, in cooperation with the city of Wichita, began a study to determine groundwater flow in the area of the Wichita well field, and chloride transport from the Arkansas River and Burrton oilfield to the Wichita well field. Groundwater flow was simulated for the Equus Beds aquifer using the three-dimensional finite-difference groundwater-flow model MODFLOW-2000. The model simulates steady-state and transient conditions. The groundwater-flow model was calibrated by adjusting model input data and model geometry until model results matched field observations within an acceptable level of accuracy. The root mean square (RMS) error for water-level observations for the steady-state calibration simulation is 9.82 feet. The ratio of the RMS error to the total head loss in the model area is 0.049 and the mean error for water-level observations is 3.86 feet. The difference between flow into the model and flow out of the model across all model boundaries is -0.08 percent of total flow for the steady-state calibration. The RMS error for water-level observations for the transient calibration simulation is 2.48 feet, the ratio of the RMS error to the total head loss in the model area is 0.0124, and the mean error for water-level observations is 0.03 feet. The RMS error calculated for observed and simulated base flow gains or losses for the Arkansas River for the transient simulation is 7,916,564 cubic feet per day (91.6 cubic feet per second) and the RMS error divided by (/) the total range in streamflow (7,916,564/37,461,669 cubic feet per day) is 22 percent. The RMS error calculated for observed and simulated streamflow gains or losses for the Little Arkansas River for the transient simulation is 5,610,089 cubic feet per day(64.9 cubic feet per second) and the RMS error divided by the total range in streamflow (5,612,918/41,791,091 cubic feet per day) is 13 percent. The mean error between observed and simulated base flow gains or losses was 29,999 cubic feet per day (0.34 cubic feet per second) for the Arkansas River and -1,369,250 cubic feet per day (-15.8 cubic feet per second) for the Little Arkansas River. Cumulative streamflow gain and loss observations are similar to the cumulative simulated equivalents. Average percent mass balance difference for individual stress periods ranged from -0.46 to 0.51 percent. The cumulative mass balance for the transient calibration was 0.01 percent. Composite scaled sensitivities indicate the simulations are most sensitive to parameters with a large areal distribution. For the steady-state calibration, these parameters include recharge, hydraulic conductivity, and vertical conductance. For the transient simulation, these parameters include evapotranspiration, recharge, and hydraulic conductivity. The ability of the calibrated model to account for the additional groundwater recharged to the Equus Beds aquifer as part of the Aquifer Storage and Recovery project was assessed by using the U.S. Geological Survey subregional water budget program ZONEBUDGET and comparing those results to metered recharge for 2007 and 2008 and previous estimates of artificial recharge. The change in storage between simulations is the volume of water that estimates the recharge credit for the aquifer storage and recovery system. The estimated increase in storage of 1,607 acre-ft in the basin storage area compared to metered recharge of 1,796 acre-ft indicates some loss of metered recharge. Increased storage outside of the basin storage area of 183 acre-ft accounts for all but 6 acre-ft or 0.33 percent of the total. Previously estimated recharge credits for 2007 and 2008 are 1,018 and 600 acre-ft, respectively, and a total estimated recharge credit of 1,618 acre-ft. Storage changes calculated for this study are 4.42 percent less for 2007 and 5.67 percent more for 2008 than previous estimates. Total storage change for 2007 and 2008 is 0.68 percent less than previous estimates. The small difference between the increase in storage from artificial recharge estimated with the groundwater-flow model and metered recharge indicates the groundwater model correctly accounts for the additional water recharged to the Equus Beds aquifer as part of the Aquifer Storage and Recovery project. Small percent differences between inflows and outflows for all stress periods and all index cells in the basin storage area, improved calibration compared to the previous model, and a reasonable match between simulated and measured long-term base flow indicates the groundwater model accurately simulates groundwater flow in the study area. The change in groundwater level through recent years compared to the August 1940 groundwater level map has been documented and used to assess the change of storage volume of the Equus Beds aquifer in and near the Wichita well field for three different areas. Two methods were used to estimate changes in storage from simulation results using simulated change in groundwater levels in layer 1 between stress periods, and using ZONEBUDGET to calculate the change in storage in the same way the effects of artificial recharge were estimated within the basin storage area. The three methods indicate similar trends although the magnitude of storage changes differ. Information about the change in storage in response to hydrologic stresses is important for managing groundwater resources in the study area. The comparison between the three methods indicates similar storage change trends are estimated and each could be used to determine relative increases or decreases in storage. Use of groundwater level changes that do not include storage changes that occur in confined or semi-confined parts of the aquifer will slightly underestimate storage changes; however, use of specific yield and groundwater level changes to estimate storage change in confined or semi-confined parts of the aquifer will overestimate storage changes. Using only changes in shallow groundwater levels would provide more accurate storage change estimates for the measured groundwater levels method. The value used for specific yield is also an important consideration when estimating storage. For the Equus Beds aquifer the reported specific yield ranges between 0.08 and 0.35 and the storage coefficient (for confined conditions) ranges between 0.0004 and 0.16. Considering the importance of the value of specific yield and storage coefficient to estimates of storage change over time, and the wide range and substantial overlap for the reported values for specific yield and storage coefficient in the study area, further information on the distribution of specific yield and storage coefficient within the Equus Beds aquifer in the study area would greatly enhance the accuracy of estimated storage changes using both simulated groundwater level, simulated groundwater budget, or measured groundwater level methods.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135042","collaboration":"Prepared in cooperation with the city of Wichita, Kansas, as part of the Equus Beds Groundwater Recharge Project","usgsCitation":"Kelly, B.P., Pickett, L.L., Hansen, C.V., and Ziegler, A., 2013, Simulation of groundwater flow, effects of artificial recharge, and storage volume changes in the Equus Beds aquifer near the city of Wichita, Kansas well field, 1935–2008: U.S. Geological Survey Scientific Investigations Report 2013-5042, Report: viii, 92 p.; Downloads Directory, https://doi.org/10.3133/sir20135042.","productDescription":"Report: viii, 92 p.; Downloads Directory","numberOfPages":"102","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-042806","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":271633,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/SIR20135042.gif"},{"id":271632,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5042/downloads/"},{"id":271630,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5042/"},{"id":271631,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5042/sir2013-5042.pdf"}],"country":"United States","state":"Kansas","city":"Wichita","otherGeospatial":"Equus Beds Aquifer","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -98.3,37.6 ], [ -98.3,38.05 ], [ -97.16,38.05 ], [ -97.16,37.6 ], [ -98.3,37.6 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5180d9dce4b0df838b924d35","contributors":{"authors":[{"text":"Kelly, Brian P. 0000-0001-6378-2837 bkelly@usgs.gov","orcid":"https://orcid.org/0000-0001-6378-2837","contributorId":897,"corporation":false,"usgs":true,"family":"Kelly","given":"Brian","email":"bkelly@usgs.gov","middleInitial":"P.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pickett, Linda L.","contributorId":108377,"corporation":false,"usgs":true,"family":"Pickett","given":"Linda","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":478070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Cristi V. chansen@usgs.gov","contributorId":435,"corporation":false,"usgs":true,"family":"Hansen","given":"Cristi","email":"chansen@usgs.gov","middleInitial":"V.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":478068,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ziegler, Andrew C. aziegler@usgs.gov","contributorId":433,"corporation":false,"usgs":true,"family":"Ziegler","given":"Andrew C.","email":"aziegler@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":478067,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045702,"text":"ofr20131099 - 2013 - Differential expression profiles of microRNA in the little brown bat (Myotis lucifugus) associated with white nose syndrome affected and unaffected individuals","interactions":[],"lastModifiedDate":"2024-03-04T18:46:56.883032","indexId":"ofr20131099","displayToPublicDate":"2013-04-30T00:00:00","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":"2013-1099","title":"Differential expression profiles of microRNA in the little brown bat (Myotis lucifugus) associated with white nose syndrome affected and unaffected individuals","docAbstract":"First documented in New York State in 2006, white nose syndrome (WNS) quickly became the leading cause of mortality in hibernating bat species in the United States. WNS is caused by a psychrophilic fungus, Geomyces destructans. Clinical signs of this pathogen are expressed as a dusty white fungus predominately around the nose and on the wings of affected bats. Relatively new biomarkers, such as microRNAs (miRNAs) are being targeted as markers to predict the syndrome prior to the clinical manifestation. The primary objective of this study was to identify miRNAs that could serve as biomarkers and proxies of little brown bat health. Bats were collected from hibernacula that had tested positive and negative for WNS. Genetic sequencing was completed using the Ion Torrent platform. A number of miRNAs were identified from the liver as putative biomarkers of WNS. However, given the small sample size for each treatment, this data set has only coarsely identified miRNAs indicative of WNS, and further validation is required.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131099","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Iwanowicz, D., Iwanowicz, L., Hitt, N., and King, T., 2013, Differential expression profiles of microRNA in the little brown bat (Myotis lucifugus) associated with white nose syndrome affected and unaffected individuals: U.S. Geological Survey Open-File Report 2013-1099, iv, 11 p., https://doi.org/10.3133/ofr20131099.","productDescription":"iv, 11 p.","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":271636,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131099.png"},{"id":271635,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1099/pdf/ofr2013-1099.pdf"},{"id":271634,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1099/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5180d9dae4b0df838b924d2d","contributors":{"authors":[{"text":"Iwanowicz, D.D.","contributorId":97706,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"D.D.","email":"","affiliations":[],"preferred":false,"id":478098,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iwanowicz, L. R. 0000-0002-1197-6178","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":43864,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"L. R.","affiliations":[],"preferred":false,"id":478096,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hitt, N.P. 0000-0002-1046-4568","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":101466,"corporation":false,"usgs":true,"family":"Hitt","given":"N.P.","affiliations":[],"preferred":false,"id":478099,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"King, T.L.","contributorId":93416,"corporation":false,"usgs":true,"family":"King","given":"T.L.","email":"","affiliations":[],"preferred":false,"id":478097,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045674,"text":"sir20125290 - 2013 - Estimates of future inundation of salt marshes in response to sea-level rise in and around Acadia National Park, Maine","interactions":[],"lastModifiedDate":"2013-04-29T13:35:29","indexId":"sir20125290","displayToPublicDate":"2013-04-29T00:00:00","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":"2012-5290","title":"Estimates of future inundation of salt marshes in response to sea-level rise in and around Acadia National Park, Maine","docAbstract":"Salt marshes are ecosystems that provide many important ecological functions in the Gulf of Maine. The U.S. Geological Survey investigated salt marshes in and around Acadia National Park from Penobscot Bay to the Schoodic Peninsula to map the potential for landward migration of marshes using a static inundation model of a sea-level rise scenario of 60 centimeters (cm; 2 feet). The resulting inundation contours can be used by resource managers to proactively adapt to sea-level rise by identifying and targeting low-lying coastal areas adjacent to salt marshes for conservation or further investigation, and to identify risks to infrastructure in the coastal zone. For this study, the mapping of static inundation was based on digital elevation models derived from light detection and ranging (LiDAR) topographic data collected in October 2010. Land-surveyed control points were used to evaluate the accuracy of the LiDAR data in the study area, yielding a root mean square error of 11.3 cm. An independent accuracy assessment of the LiDAR data specific to salt-marsh land surfaces indicated a root mean square error of 13.3 cm and 95-percent confidence interval of ± 26.0 cm. LiDAR-derived digital elevation models and digital color aerial photography, taken during low tide conditions in 2008, with a pixel resolution of 0.5 meters, were used to identify the highest elevation of the land surface at each salt marsh in the study area. Inundation contours for 60-cm of sea-level rise were delineated above the highest marsh elevation for each marsh. Confidence interval contours (95-percent,± 26.0 cm) were delineated above and below the 60-cm inundation contours, and artificial structures, such as roads and bridges, that may present barriers to salt-marsh migration were mapped. This study delineated 114 salt marshes totaling 340 hectares (ha), ranging in size from 0.11 ha (marshes less than 0.2 ha were mapped only if they were on Acadia National Park property) to 52 ha, with a median size of 1.0 ha. Inundation contours were mapped at 110 salt marshes. Approximately 350 ha of low-lying upland areas adjacent to these marshes will be inundated with 60 cm of sea-level rise. Many of these areas are currently freshwater wetlands. There are potential barriers to marsh migration at 27 of the 114 marshes. Although only 23 percent of the salt marshes in the study are on ANP property, about half of the upland areas that will be inundated are within ANP; most of the predicted inundated uplands (approximately 170 ha) include freshwater wetlands in the Northeast Creek and Bass Harbor Marsh areas. Most of the salt marshes analyzed do not have a significant amount of upland area available for migration. Seventy-five percent of the salt marshes have 20 meters or less of adjacent upland that would be inundated along most of their edges. All inundation contours, salt marsh locations, potential barriers, and survey data are stored in geospatial files for use in a geographic information system and are a part of this report.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125290","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Nielsen, M.G., and Dudley, R.W., 2013, Estimates of future inundation of salt marshes in response to sea-level rise in and around Acadia National Park, Maine: U.S. Geological Survey Scientific Investigations Report 2012-5290, Report: viii, 20 p.; Appendix 1: Geospatial Data, https://doi.org/10.3133/sir20125290.","productDescription":"Report: viii, 20 p.; Appendix 1: Geospatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":271615,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125290.gif"},{"id":271612,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5290/"},{"id":271613,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5290/pdf/sir2012-5290_nielsen_508.pdf"},{"id":271614,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5290/appendix.html"}],"scale":"24000","projection":"Universe Transverse Mercator, zone 19N","datum":"North American Datum of 1983","country":"United States","state":"Maine","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -68.6598,44.0059 ], [ -68.6598,44.4314 ], [ -68.0373,44.4314 ], [ -68.0373,44.0059 ], [ -68.6598,44.0059 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"517f884fe4b0e41721f7a320","contributors":{"authors":[{"text":"Nielsen, Martha G. 0000-0003-3038-9400 mnielsen@usgs.gov","orcid":"https://orcid.org/0000-0003-3038-9400","contributorId":4169,"corporation":false,"usgs":true,"family":"Nielsen","given":"Martha","email":"mnielsen@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dudley, Robert W. 0000-0002-0934-0568 rwdudley@usgs.gov","orcid":"https://orcid.org/0000-0002-0934-0568","contributorId":2223,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert","email":"rwdudley@usgs.gov","middleInitial":"W.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478023,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187065,"text":"70187065 - 2013 - Evidence for fluid-triggered slip in the 2009 Mount Rainier, Washington earthquake swarm","interactions":[],"lastModifiedDate":"2017-04-21T09:19:10","indexId":"70187065","displayToPublicDate":"2013-04-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for fluid-triggered slip in the 2009 Mount Rainier, Washington earthquake swarm","docAbstract":"A vigorous swarm of over 1000 small, shallow earthquakes occurred 20–22 September 2009 beneath Mount Rainier, Washington, including the largest number of events ever recorded in a single day at Rainier since seismic stations were installed on the edifice in 1989. Many events were only clearly recorded on one or two stations on the edifice, or they overlapped in time with other events, and thus only ~200 were locatable by manual phase picking. To partially overcome this limitation, we applied waveform-based event detection integrated with precise double-difference relative relocation. With this procedure, detection and location goals are accomplished in tandem, using cross-correlation with continuous seismic data and waveform templates constructed from cataloged events. As a result, we obtained precise locations for 726 events, an improvement of almost a factor of 4. These event locations define a ~850 m long nearly vertical structure striking NNE, with episodic migration outward from the initial hypocenters. The activity front propagates in a manner consistent with a diffusional process. Double-couple-constrained focal mechanisms suggest dominantly near-vertical strike-slip motion on either NNW or ENE striking faults, more than 30° different than the strike of the event locations. This suggests the possibility of en echelon faulting, perhaps with a component of fault opening in a fracture-mesh-type geometry. We hypothesize that the swarm was initiated by a sudden release of high-pressure fluid into preexisting fractures, with subsequent activity triggered by diffusing fluid pressure in combination with stress transfer from the preceding events.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/grl.50354","usgsCitation":"Shelly, D.R., Moran, S.C., and Thelen, W.A., 2013, Evidence for fluid-triggered slip in the 2009 Mount Rainier, Washington earthquake swarm: Geophysical Research Letters, v. 40, no. 8, p. 1506-1512, https://doi.org/10.1002/grl.50354.","productDescription":"7 p.","startPage":"1506","endPage":"1512","ipdsId":"IP-044737","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473859,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/grl.50354","text":"Publisher Index Page"},{"id":340068,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Rainier","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122,\n 46.7\n ],\n [\n -121.5,\n 46.7\n ],\n [\n -121.5,\n 46.95\n ],\n [\n -122,\n 46.95\n ],\n [\n -122,\n 46.7\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2013-04-27","publicationStatus":"PW","scienceBaseUri":"58fb1a4fe4b0c3010a8087d9","contributors":{"authors":[{"text":"Shelly, David R. dshelly@usgs.gov","contributorId":2978,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":692282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moran, Seth C. 0000-0001-7308-9649 smoran@usgs.gov","orcid":"https://orcid.org/0000-0001-7308-9649","contributorId":548,"corporation":false,"usgs":true,"family":"Moran","given":"Seth","email":"smoran@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":692283,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thelen, Weston A. 0000-0003-2534-5577 wthelen@usgs.gov","orcid":"https://orcid.org/0000-0003-2534-5577","contributorId":4126,"corporation":false,"usgs":true,"family":"Thelen","given":"Weston","email":"wthelen@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":692284,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045614,"text":"sir20135022 - 2013 - Salmonids, stream temperatures, and solar loading--modeling the shade provided to the Klamath River by vegetation and geomorphology","interactions":[],"lastModifiedDate":"2013-04-26T09:14:32","indexId":"sir20135022","displayToPublicDate":"2013-04-26T00:00:00","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":"2013-5022","title":"Salmonids, stream temperatures, and solar loading--modeling the shade provided to the Klamath River by vegetation and geomorphology","docAbstract":"The U.S. Geological Survey is studying approaches to characterize the thermal regulation of water and the dynamics of cold water refugia. High temperatures have physiological impacts on anadromous fish species. Factors affecting the presence, variability, and quality of thermal refugia are known, such as riverine and watershed processes, hyporheic flows, deep pools and bathymetric factors, thermal stratification of reservoirs, and other broader climatic considerations. This research develops a conceptual model and methodological techniques to quantify the change in solar insolation load to the Klamath River caused by riparian and floodplain vegetation, the morphology of the river, and the orientation and topographic characteristics of its watersheds. Using multiple scales of input data from digital elevation models and airborne light detection and ranging (LiDAR) derivatives, different analysis methods yielded three different model results. These models are correlated with thermal infrared imagery for ground-truth information at the focal confluence with the Scott River. Results from nonparametric correlation tests, geostatistical cross-covariograms, and cross-correlograms indicate that statistical relationships between the insolation models and the thermal infrared imagery exist and are significant. Furthermore, the use of geostatistics provides insights to the spatial structure of the relationships that would not be apparent otherwise. To incorporate a more complete representation of the temperature dynamics in the river system, other variables including the factors mentioned above, and their influence on solar loading, are discussed. With similar datasets, these methods could be applied to any river in the United States—especially those listed as temperature impaired under Section 303(d) of the Clean Water Act—or international riverine systems. Considering the importance of thermal refugia for aquatic species, these methods can help investigate opportunities for riparian restoration, identify problematic reaches unlikely to provide good habitat, and simulate changes to solar loading estimates from alternative landscape configurations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135022","usgsCitation":"Forney, W.M., Soulard, C.E., and Chickadel, C.C., 2013, Salmonids, stream temperatures, and solar loading--modeling the shade provided to the Klamath River by vegetation and geomorphology: U.S. Geological Survey Scientific Investigations Report 2013-5022, iv, 26 p., https://doi.org/10.3133/sir20135022.","productDescription":"iv, 26 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":271506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135022.gif"},{"id":271504,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5022/"},{"id":271505,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5022/sir2013-5022.pdf"}],"country":"United States","state":"California","otherGeospatial":"Klamath River;Scott River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.85,41.36 ], [ -122.85,41.37 ], [ -122.82,41.37 ], [ -122.82,41.36 ], [ -122.85,41.36 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"517b93d7e4b09d6a5f9a2ea6","contributors":{"authors":[{"text":"Forney, William M.","contributorId":43490,"corporation":false,"usgs":true,"family":"Forney","given":"William","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":477957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soulard, Christopher E. 0000-0002-5777-9516 csoulard@usgs.gov","orcid":"https://orcid.org/0000-0002-5777-9516","contributorId":2642,"corporation":false,"usgs":true,"family":"Soulard","given":"Christopher","email":"csoulard@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":477956,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chickadel, C. Christopher","contributorId":106337,"corporation":false,"usgs":true,"family":"Chickadel","given":"C.","email":"","middleInitial":"Christopher","affiliations":[],"preferred":false,"id":477958,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70118244,"text":"70118244 - 2013 - A new data set for estimating organic carbon storage to 3 m depth in soils of the northern circumpolar permafrost region","interactions":[],"lastModifiedDate":"2014-07-28T09:21:37","indexId":"70118244","displayToPublicDate":"2013-04-25T09:16:52","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1426,"text":"Earth System Science Data","active":true,"publicationSubtype":{"id":10}},"title":"A new data set for estimating organic carbon storage to 3 m depth in soils of the northern circumpolar permafrost region","docAbstract":"High-latitude terrestrial ecosystems are key components in the global carbon cycle. The Northern Circumpolar Soil Carbon Database (NCSCD) was developed to quantify stocks of soil organic carbon (SOC) in the northern circumpolar permafrost region (a total area of 18.7 × 106 km2). The NCSCD is a geographical information system (GIS) data set that has been constructed using harmonized regional soil classification maps together with pedon data from the northern permafrost region. Previously, the NCSCD has been used to calculate SOC storage to the reference depths 0–30 cm and 0–100 cm (based on 1778 pedons). It has been shown that soils of the northern circumpolar permafrost region also contain significant quantities of SOC in the 100–300 cm depth range, but there has been no circumpolar compilation of pedon data to quantify this deeper SOC pool and there are no spatially distributed estimates of SOC storage below 100 cm depth in this region. Here we describe the synthesis of an updated pedon data set for SOC storage (kg C m-2) in deep soils of the northern circumpolar permafrost regions, with separate data sets for the 100–200 cm (524 pedons) and 200–300 cm (356 pedons) depth ranges. These pedons have been grouped into the North American and Eurasian sectors and the mean SOC storage for different soil taxa (subdivided into Gelisols including the sub-orders Histels, Turbels, Orthels, permafrost-free Histosols, and permafrost-free mineral soil orders) has been added to the updated NCSCDv2. The updated version of the data set is freely available online in different file formats and spatial resolutions that enable spatially explicit applications in GIS mapping and terrestrial ecosystem models. While this newly compiled data set adds to our knowledge of SOC in the 100–300 cm depth range, it also reveals that large uncertainties remain. Identified data gaps include spatial coverage of deep (> 100 cm) pedons in many regions as well as the spatial extent of areas with thin soils overlying bedrock and the quantity and distribution of massive ground ice. An open access data-portal for the pedon data set and the GIS-data sets is available online at http://bolin.su.se/data/ncscd/.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Earth System Science Data","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Copernicus","publisherLocation":"Katlenberg-Lindau, Germany","doi":"10.5194/essd-5-393-2013","usgsCitation":"Hugelius, G., Bockheim, J.G., Camill, P., Elberling, B., Grosse, G., Harden, J., Johnson, K., Jorgenson, T., Koven, C., Kuhry, P., Michaelson, G., Mishra, U., Palmtag, J., Ping, C., O'Donnell, J., Schirrmeister, L., Schuur, E., Sheng, Y., Smith, L., Strauss, J., and Yu, Z., 2013, A new data set for estimating organic carbon storage to 3 m depth in soils of the northern circumpolar permafrost region: Earth System Science Data, v. 5, no. 2, p. 393-402, https://doi.org/10.5194/essd-5-393-2013.","productDescription":"10 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0000-0002-6570-8259","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":38585,"corporation":false,"usgs":true,"family":"Harden","given":"J.W.","affiliations":[],"preferred":false,"id":496516,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Kevin","contributorId":83287,"corporation":false,"usgs":true,"family":"Johnson","given":"Kevin","affiliations":[],"preferred":false,"id":496526,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jorgenson, T.","contributorId":19769,"corporation":false,"usgs":true,"family":"Jorgenson","given":"T.","email":"","affiliations":[],"preferred":false,"id":496510,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Koven, C.D.","contributorId":34017,"corporation":false,"usgs":true,"family":"Koven","given":"C.D.","affiliations":[],"preferred":false,"id":496514,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kuhry, P.","contributorId":57277,"corporation":false,"usgs":false,"family":"Kuhry","given":"P.","affiliations":[],"preferred":false,"id":496519,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Michaelson, G.","contributorId":30851,"corporation":false,"usgs":true,"family":"Michaelson","given":"G.","affiliations":[],"preferred":false,"id":496512,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mishra, U.","contributorId":99906,"corporation":false,"usgs":true,"family":"Mishra","given":"U.","email":"","affiliations":[],"preferred":false,"id":496528,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Palmtag, J.","contributorId":62532,"corporation":false,"usgs":true,"family":"Palmtag","given":"J.","email":"","affiliations":[],"preferred":false,"id":496521,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Ping, C.-L.","contributorId":60843,"corporation":false,"usgs":true,"family":"Ping","given":"C.-L.","email":"","affiliations":[],"preferred":false,"id":496520,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"O'Donnell, J.","contributorId":34785,"corporation":false,"usgs":true,"family":"O'Donnell","given":"J.","affiliations":[],"preferred":false,"id":496515,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Schirrmeister, L.","contributorId":41355,"corporation":false,"usgs":true,"family":"Schirrmeister","given":"L.","affiliations":[],"preferred":false,"id":496517,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Schuur, E.A.G.","contributorId":106679,"corporation":false,"usgs":true,"family":"Schuur","given":"E.A.G.","affiliations":[],"preferred":false,"id":496529,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Sheng, Y.","contributorId":66611,"corporation":false,"usgs":true,"family":"Sheng","given":"Y.","email":"","affiliations":[],"preferred":false,"id":496522,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Smith, L.C.","contributorId":88561,"corporation":false,"usgs":true,"family":"Smith","given":"L.C.","email":"","affiliations":[],"preferred":false,"id":496527,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Strauss, J.","contributorId":8770,"corporation":false,"usgs":true,"family":"Strauss","given":"J.","affiliations":[],"preferred":false,"id":496509,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Yu, Z.","contributorId":32696,"corporation":false,"usgs":true,"family":"Yu","given":"Z.","email":"","affiliations":[],"preferred":false,"id":496513,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":70045602,"text":"ofr20131057 - 2013 - Landsat ecosystem disturbance adaptive processing system (LEDAPS) algorithm description","interactions":[],"lastModifiedDate":"2013-04-25T14:02:16","indexId":"ofr20131057","displayToPublicDate":"2013-04-25T00:00:00","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":"2013-1057","title":"Landsat ecosystem disturbance adaptive processing system (LEDAPS) algorithm description","docAbstract":"The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from LandsatThematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product.The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record.This report discusses the LEDAPS algorithm, which was implemented by the USGS.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131057","usgsCitation":"Schmidt, G., Jenkerson, C.B., Masek, J., Vermote, E., and Gao, F., 2013, Landsat ecosystem disturbance adaptive processing system (LEDAPS) algorithm description: U.S. Geological Survey Open-File Report 2013-1057, vi, 19 p., https://doi.org/10.3133/ofr20131057.","productDescription":"vi, 19 p.","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":271479,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131057.gif"},{"id":271477,"type":{"id":15,"text":"Index 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Agriculture","active":true,"usgs":false}],"preferred":false,"id":477945,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70045575,"text":"ofr20131077 - 2013 - Tidal flow dynamics and background fluorescence of the Atlantic Intracoastal Waterway in the vicinity of Sullivan’s Island and the Isle of Palms, South Carolina, 2011-12","interactions":[],"lastModifiedDate":"2017-01-31T08:26:02","indexId":"ofr20131077","displayToPublicDate":"2013-04-24T00:00:00","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":"2013-1077","title":"Tidal flow dynamics and background fluorescence of the Atlantic Intracoastal Waterway in the vicinity of Sullivan’s Island and the Isle of Palms, South Carolina, 2011-12","docAbstract":"To effectively plan site-specific studies to understand the connection between wastewater effluent and shellfish beds, data are needed concerning flow dynamics and background fluorescence in the Atlantic Intracoastal Waterway near the effluent outfalls on Sullivan’s Island and the Isle of Palms. Tidal flows were computed by the U.S. Geological Survey for three stations and longitudinal water-quality profiles were collected at high and low tide. Flows for the three U.S. Geological Survey stations, the Atlantic Intracoastal Waterway by the Isle of Palms Marina, the Atlantic Intracoastal Waterway by the Ben M. Sawyer Memorial Bridge at Sullivan’s Island, and Breach Inlet, were computed for the 53-day period from December 4, 2011, to January 26, 2012. The largest flows occurred at Breach Inlet and ranged from -58,600 cubic feet per second (ft3/s) toward the Atlantic Intracoastal Waterway to 63,300 ft3/s toward the Atlantic Ocean. Of the two stations on the Atlantic Intracoastal Waterway, the Sullivan’s Island station had the larger flows and ranged from -6,360 ft3/s to the southwest (toward Charleston Harbor) to 8,930 ft3/s to the northeast. Computed tidal flow at the Isle of Palms station ranged from -3,460 ft3/s toward the southwest to 6,410 ft3/s toward the northeast. The synoptic water-quality study showed that the stations were well mixed vertically and horizontally. All fluorescence measurements (recorded as rhodamine concentration) were below the accuracy of the sensor and the background fluorescence would not likely interfere with a dye-tracer study.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131077","collaboration":"Prepared in cooperation with the South Carolina Department of Health and Environmental Control","usgsCitation":"Conrads, P., Journey, C.A., Clark, J.M., and Levesque, V.A., 2013, Tidal flow dynamics and background fluorescence of the Atlantic Intracoastal Waterway in the vicinity of Sullivan’s Island and the Isle of Palms, South Carolina, 2011-12: U.S. Geological Survey Open-File Report 2013-1077, v, 20 p., https://doi.org/10.3133/ofr20131077.","productDescription":"v, 20 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2011-12-04","temporalEnd":"2012-01-26","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":271412,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1077/"},{"id":271414,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":271413,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1077/pdf/ofr2013-1077.pdf"}],"projection":"Universal Transverse Mercator projection, Zone 17","country":"United States","state":"South Carolina","otherGeospatial":"Isle of Palms, Sullivan's Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.96192932128906,\n 32.70757783494157\n ],\n [\n -79.96192932128906,\n 32.87901051714101\n ],\n [\n -79.64401245117188,\n 32.87901051714101\n ],\n [\n -79.64401245117188,\n 32.70757783494157\n ],\n [\n -79.96192932128906,\n 32.70757783494157\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5178f0dfe4b0d842c705f6c4","contributors":{"authors":[{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":517762,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":517763,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Jimmy M. 0000-0002-3138-5738 jmclark@usgs.gov","orcid":"https://orcid.org/0000-0002-3138-5738","contributorId":4773,"corporation":false,"usgs":true,"family":"Clark","given":"Jimmy","email":"jmclark@usgs.gov","middleInitial":"M.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":517765,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Levesque, Victor A. levesque@usgs.gov","contributorId":4335,"corporation":false,"usgs":true,"family":"Levesque","given":"Victor","email":"levesque@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":517764,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045584,"text":"70045584 - 2013 - Estimating floodplain sedimentation in the Laguna de Santa Rosa, Sonoma County, CA","interactions":[],"lastModifiedDate":"2013-04-24T16:57:38","indexId":"70045584","displayToPublicDate":"2013-04-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Estimating floodplain sedimentation in the Laguna de Santa Rosa, Sonoma County, CA","docAbstract":"We present a conceptual and analytical framework for predicting the spatial distribution of floodplain sedimentation for the Laguna de Santa Rosa, Sonoma County, CA. We assess the role of the floodplain as a sink for fine-grained sediment and investigate concerns regarding the potential loss of flood storage capacity due to historic sedimentation. We characterized the spatial distribution of sedimentation during a post-flood survey and developed a spatially distributed sediment deposition potential map that highlights zones of floodplain sedimentation. The sediment deposition potential map, built using raster files that describe the spatial distribution of relevant hydrologic and landscape variables, was calibrated using 2 years of measured overbank sedimentation data and verified using longer-term rates determined using dendrochronology. The calibrated floodplain deposition potential relation was used to estimate an average annual floodplain sedimentation rate (3.6 mm/year) for the ~11 km2 floodplain. This study documents the development of a conceptual model of overbank sedimentation, describes a methodology to estimate the potential for various parts of a floodplain complex to accumulate sediment over time, and provides estimates of short and long-term overbank sedimentation rates that can be used for ecosystem management and prioritization of restoration activities.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Wetlands","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s13157-012-0350-4","usgsCitation":"Curtis, J.A., Flint, L.E., and Hupp, C.R., 2013, Estimating floodplain sedimentation in the Laguna de Santa Rosa, Sonoma County, CA: Wetlands, v. 33, no. 1, p. 29-45, https://doi.org/10.1007/s13157-012-0350-4.","productDescription":"17 p.","startPage":"29","endPage":"45","ipdsId":"IP-018988","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":271425,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271424,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s13157-012-0350-4"}],"country":"United States","state":"California","county":"Sonoma County","city":"Santa Rosa","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.8341,38.3637 ], [ -122.8341,38.5074 ], [ -122.573,38.5074 ], [ -122.573,38.3637 ], [ -122.8341,38.3637 ] ] ] } } ] }","volume":"33","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-12-20","publicationStatus":"PW","scienceBaseUri":"5178f0dee4b0d842c705f6b8","contributors":{"authors":[{"text":"Curtis, Jennifer A. 0000-0001-7766-994X jacurtis@usgs.gov","orcid":"https://orcid.org/0000-0001-7766-994X","contributorId":927,"corporation":false,"usgs":true,"family":"Curtis","given":"Jennifer","email":"jacurtis@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hupp, Cliff R. 0000-0003-1853-9197 crhupp@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-9197","contributorId":2344,"corporation":false,"usgs":true,"family":"Hupp","given":"Cliff","email":"crhupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":477876,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70044223,"text":"70044223 - 2013 - Spatial segregation of spawning habitat limits hybridization between sympatric native Steelhead and Coastal Cutthroat Trout","interactions":[],"lastModifiedDate":"2016-05-03T11:58:47","indexId":"70044223","displayToPublicDate":"2013-04-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Spatial segregation of spawning habitat limits hybridization between sympatric native Steelhead and Coastal Cutthroat Trout","docAbstract":"Native Coastal Cutthroat Trout Oncorhynchus clarkii clarkii and Coastal Steelhead O. mykiss irideus hybridize naturally in watersheds of the Pacific Northwest yet maintain species integrity. Partial reproductive isolation due to differences in spawning habitat may limit hybridization between these species, but this process is poorly understood. We used a riverscape approach to determine the spatial distribution of spawning habitats used by native Coastal Cutthroat Trout and Steelhead as evidenced by the distribution of recently emerged fry. Molecular genetic markers were used to classify individuals as pure species or hybrids, and individuals were assigned to age-classes based on length. Fish and physical habitat data were collected in a spatially continuous framework to assess the relationship between habitat and watershed features and the spatial distribution of parental species and hybrids. Sampling occurred in 35 reaches from tidewaters to headwaters in a small (20 km2) coastal watershed in Washington State. Cutthroat, Steelhead, and hybrid trout accounted for 35%, 42%, and 23% of the fish collected, respectively. Strong segregation of spawning areas between Coastal Cutthroat Trout and Steelhead was evidenced by the distribution of age-0 trout. Cutthroat Trout were located farther upstream and in smaller tributaries than Steelhead were. The best predictor of species occurrence at a site was the drainage area of the watershed that contributed to the site. This area was positively correlated with the occurrence of age-0 Steelhead and negatively with the presence of Cutthroat Trout, whereas hybrids were found in areas occupied by both parental species. A similar pattern was observed in older juveniles of both species but overlap was greater, suggesting substantial dispersal of trout after emergence. Our results offer support for spatial reproductive segregation as a factor limiting hybridization between Steelhead and Coastal Cutthroat Trout.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/00028487.2012.728165","usgsCitation":"Buehrens, T., Glasgow, J., Ostberg, C.O., and Quinn, T., 2013, Spatial segregation of spawning habitat limits hybridization between sympatric native Steelhead and Coastal Cutthroat Trout: Transactions of the American Fisheries Society, v. 142, no. 1, p. 221-233, https://doi.org/10.1080/00028487.2012.728165.","productDescription":"13 p.","startPage":"221","endPage":"233","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037064","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":271795,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Ellsworth Creek, Willapa Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.05,46.37 ], [ -124.05,46.70 ], [ -123.94,46.70 ], [ -123.94,46.37 ], [ -124.05,46.37 ] ] ] } } ] }","volume":"142","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-12-21","publicationStatus":"PW","scienceBaseUri":"5184dc65e4b04d6ec94d62bd","contributors":{"authors":[{"text":"Buehrens, T.W.","contributorId":9149,"corporation":false,"usgs":true,"family":"Buehrens","given":"T.W.","email":"","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":475133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glasgow, J.","contributorId":17116,"corporation":false,"usgs":true,"family":"Glasgow","given":"J.","email":"","affiliations":[],"preferred":false,"id":475134,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ostberg, Carl O. 0000-0003-1479-8458 costberg@usgs.gov","orcid":"https://orcid.org/0000-0003-1479-8458","contributorId":3031,"corporation":false,"usgs":true,"family":"Ostberg","given":"Carl","email":"costberg@usgs.gov","middleInitial":"O.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":475132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quinn, T.P.","contributorId":64535,"corporation":false,"usgs":false,"family":"Quinn","given":"T.P.","email":"","affiliations":[{"id":13190,"text":"School of Aquatic and Fishery Sciences, University of Washington","active":true,"usgs":false}],"preferred":false,"id":475135,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188332,"text":"70188332 - 2013 - Radiometric cross-calibration of EO-1 ALI with L7 ETM+ and Terra MODIS sensors using near-simultaneous desert observations","interactions":[],"lastModifiedDate":"2017-06-06T14:29:04","indexId":"70188332","displayToPublicDate":"2013-04-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1942,"text":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Radiometric cross-calibration of EO-1 ALI with L7 ETM+ and Terra MODIS sensors using near-simultaneous desert observations","docAbstract":"The Earth Observing-1 (EO-1) satellite was launched on November 21, 2000, as part of a one-year technology demonstration mission. The mission was extended because of the value it continued to add to the scientific community. EO-1 has now been operational for more than a decade, providing both multispectral and hyperspectral measurements. As part of the EO-1 mission, the Advanced Land Imager (ALI) sensor demonstrates a potential technological direction for the next generation of Landsat sensors. To evaluate the ALI sensor capabilities as a precursor to the Operational Land Imager (OLI) onboard the Landsat Data Continuity Mission (LDCM, or Landsat 8 after launch), its measured top-of-atmosphere (TOA) reflectances were compared to the well-calibrated Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors in the reflective solar bands (RSB). These three satellites operate in a near-polar, sun-synchronous orbit 705 km above the Earth's surface. EO-1 was designed to fly one minute behind L7 and approximately 30 minutes in front of Terra. In this configuration, all the three sensors can view near-identical ground targets with similar atmospheric, solar, and viewing conditions. However, because of the differences in the relative spectral response (RSR), the measured physical quantities can be significantly different while observing the same target. The cross-calibration of ALI with ETM+ and MODIS was performed using near-simultaneous surface observations based on image statistics from areas observed by these sensors over four desert sites (Libya 4, Mauritania 2, Arabia 1, and Sudan 1). The differences in the measured TOA reflectances due to RSR mismatches were compensated by using a spectral band adjustment factor (SBAF), which takes into account the spectral profile of the target and the RSR of each sensor. For this study, the spectral profile of the target comes from the near-simultaneous EO-1 Hyperion data over these sites. 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Taeyoung","contributorId":146955,"corporation":false,"usgs":false,"family":"Choi","given":"Taeyoung","email":"","affiliations":[],"preferred":false,"id":697314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xiong, Xiaoxiong","contributorId":15088,"corporation":false,"usgs":true,"family":"Xiong","given":"Xiaoxiong","email":"","affiliations":[],"preferred":false,"id":697315,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70042643,"text":"70042643 - 2013 - Descriptors of natural thermal regimes in streams and their responsiveness to change in the Pacific Northwest of North America","interactions":[],"lastModifiedDate":"2013-04-23T14:17:42","indexId":"70042643","displayToPublicDate":"2013-04-23T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Descriptors of natural thermal regimes in streams and their responsiveness to change in the Pacific Northwest of North America","docAbstract":"1. Temperature is a major driver of ecological processes in stream ecosystems, yet the dynamics of thermal regimes remain poorly described. Most work has focused on relatively simple descriptors that fail to capture the full range of conditions that characterise thermal regimes of streams across seasons or throughout the year.\n\n2. To more completely describe thermal regimes, we developed several descriptors of magnitude, variability, frequency, duration and timing of thermal events throughout a year. We evaluated how these descriptors change over time using long-term (1979–2009), continuous temperature data from five relatively undisturbed cold-water streams in western Oregon, U.S.A. In addition to trends for each descriptor, we evaluated similarities among them, as well as patterns of spatial coherence, and temporal synchrony.\n\n3. Using different groups of descriptors, we were able to more fully capture distinct aspects of the full range of variability in thermal regimes across space and time. A subset of descriptors showed both higher coherence and synchrony and, thus, an appropriate level of responsiveness to examine evidence of regional climatic influences on thermal regimes. Most notably, daily minimum values during winter–spring were the most responsive descriptors to potential climatic influences.\n\n4. Overall, thermal regimes in streams we studied showed high frequency and low variability of cold temperatures during the cold-water period in winter and spring, and high frequency and high variability of warm temperatures during the warm-water period in summer and autumn. The cold and warm periods differed in the distribution of events with a higher frequency and longer duration of warm events in summer than cold events in winter. The cold period exhibited lower variability in the duration of events, but showed more variability in timing.\n\n5. In conclusion, our results highlight the importance of a year-round perspective in identifying the most responsive characteristics or descriptors of thermal regimes in streams. The descriptors we provide herein can be applied across hydro-ecological regions to evaluate spatial and temporal patterns in thermal regimes. Evaluation of coherence and synchrony of different components of thermal regimes can facilitate identification of impacts of regional climate variability or local human or natural influences.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Freshwater Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/fwb.12094","usgsCitation":"Arismendi, I., Johnson, S.L., Dunham, J., and Haggerty, R., 2013, Descriptors of natural thermal regimes in streams and their responsiveness to change in the Pacific Northwest of North America: Freshwater Biology, v. 58, no. 5, p. 880-894, https://doi.org/10.1111/fwb.12094.","productDescription":"15 p.","startPage":"880","endPage":"894","ipdsId":"IP-042716","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":271407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271406,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/fwb.12094"}],"otherGeospatial":"North America","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 177.1,5.6 ], [ 177.1,85.4 ], [ -4.0,85.4 ], [ -4.0,5.6 ], [ 177.1,5.6 ] ] ] } } ] }","volume":"58","issue":"5","noUsgsAuthors":false,"publicationDate":"2013-01-15","publicationStatus":"PW","scienceBaseUri":"51779f57e4b095699adf2722","contributors":{"authors":[{"text":"Arismendi, Ivan","contributorId":70661,"corporation":false,"usgs":true,"family":"Arismendi","given":"Ivan","affiliations":[],"preferred":false,"id":471965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Sherri L.","contributorId":91757,"corporation":false,"usgs":true,"family":"Johnson","given":"Sherri","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":471966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunham, Jason B.","contributorId":64791,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason B.","affiliations":[],"preferred":false,"id":471964,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haggerty, Roy","contributorId":102631,"corporation":false,"usgs":true,"family":"Haggerty","given":"Roy","affiliations":[],"preferred":false,"id":471967,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045552,"text":"sir20135044 - 2013 - Groundwater and surface-water interactions near White Bear Lake, Minnesota, through 2011","interactions":[],"lastModifiedDate":"2015-10-16T13:47:34","indexId":"sir20135044","displayToPublicDate":"2013-04-23T00:00:00","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":"2013-5044","title":"Groundwater and surface-water interactions near White Bear Lake, Minnesota, through 2011","docAbstract":"The U.S. Geological Survey, in cooperation with the White Bear Lake Conservation District, the Minnesota Pollution Control Agency, the Minnesota Department of Natural Resources, and other State, county, municipal, and regional planning agencies, watershed organizations, and private organizations, conducted a study to characterize groundwater and surface-water interactions near White Bear Lake through 2011. During 2010 and 2011, White Bear Lake and other lakes in the northeastern part of the Twin Cities Metropolitan Area were at historically low levels. Previous periods of lower water levels in White Bear Lake correlate with periods of lower precipitation; however, recent urban expansion and increased pumping from the Prairie du Chien-Jordan aquifer have raised the question of whether a decline in precipitation is the primary cause for the recent water-level decline in White Bear Lake. Understanding and quantifying the amount of groundwater inflow to a lake and water discharge from a lake to aquifers is commonly difficult but is important in the management of lake levels. Three methods were used in the study to assess groundwater and surface-water interactions on White Bear Lake: (1) a historical assessment (1978-2011) of levels in White Bear Lake, local groundwater levels, and their relation to historical precipitation and groundwater withdrawals in the White Bear Lake area; (2) recent (2010-11) hydrologic and water-quality data collected from White Bear Lake, other lakes, and wells; and (3) water-balance assessments for White Bear Lake in March and August 2011. An analysis of covariance between average annual lake-level change and annual precipitation indicated the relation between the two variables was significantly different from 2003 through 2011 compared with 1978 through 2002, requiring an average of 4 more inches of precipitation per year to maintain the lake level. This shift in the linear relation between annual lake-level change and annual precipitation indicated the net effect of the non-precipitation terms on the water balance has changed relative to precipitation. The average amount of precipitation required each year to maintain the lake level has increased from 33 inches per year during 1978-2002 to 37 inches per year during 2003-11. The combination of lower precipitation and an increase in groundwater withdrawals can explain the change in the lake-level response to precipitation. Annual and summer groundwater withdrawals from the Prairie du Chien-Jordan aquifer have more than doubled from 1980 through 2010. Results from a regression model constructed with annual lake-level change, annual precipitation minus evaporation, and annual volume of groundwater withdrawn from the Prairie du Chien-Jordan aquifer indicated groundwater withdrawals had a greater effect than precipitation minus evaporation on water levels in the White Bear Lake area for all years since 2003. The recent (2003-11) decline in White Bear Lake reflects the declining water levels in the Prairie du Chien-Jordan aquifer; increases in groundwater withdrawals from this aquifer are a likely cause for declines in groundwater levels and lake levels. Synoptic, static groundwater-level and lake-level measurements in March/April and August 2011 indicated groundwater was potentially flowing into White Bear Lake from glacial aquifers to the northeast and south, and lake water was potentially discharging from White Bear Lake to the underlying glacial and Prairie du Chien-Jordan aquifers and glacial aquifers to the northwest. Groundwater levels in the Prairie du Chien-Jordan aquifer below White Bear Lake are approximately 0 to 19 feet lower than surface-water levels in the lake, indicating groundwater from the aquifer likely does not flow into White Bear Lake, but lake water may discharge into the aquifer. Groundwater levels from March/April to August 2011 declined more than 10 feet in the Prairie du Chien-Jordan aquifer south of White Bear Lake and to the north in Hugo, Minnesota. Water-quality analyses of pore water from nearshore lake-sediment and well-water samples, seepage-meter measurements, and hydraulic-head differences measured in White Bear Lake also indicated groundwater was potentially flowing into White Bear Lake from shallow glacial aquifers to the east and south. Negative temperature anomalies determined in shallow waters in the water-quality survey conducted in White Bear Lake indicated several shallow-water areas where groundwater may be flowing into the lake from glacial aquifers below the lake. Cool lake-sediment temperatures (less than 18 degrees Celsius) were measured in eight areas along the northeast, east, south, and southwest shores of White Bear Lake, indicating potential areas where groundwater may flow into the lake. Stable isotope analyses of well-water, precipitation, and lake-water samples indicated wells downgradient from White Bear Lake screened in the glacial buried aquifer or open to the Prairie du Chien-Jordan aquifer receive a mixture of surface water and groundwater; the largest surface-water contributions are in wells closer to White Bear Lake. A wide range in oxygen-18/oxygen-16 and deuterium/protium ratios was measured in well-water samples, indicating different sources of water are supplying water to the wells. Well water with oxygen-18/oxygen-16 and deuterium/protium ratios that plot close to the meteoric water line consisted mostly of groundwater because deuterium/protium ratios for most groundwater usually are similar to ratios for rainwater and snow, plotting close to meteoric water lines. Well water with oxygen-18/oxygen-16 and deuterium/protium ratios that plot between the meteoric water line and ratios for the surface-water samples from White Bear Lake consists of a mixture of surface water and groundwater; the percentage of each source varies relative to its ratios. White Bear Lake is the likely source of the surface water to the wells that have a mixture of surface water and groundwater because (1) it is the only large, deep lake near these wells; (2) these wells are near and downgradient from White Bear Lake; and (3) these wells obtain their water from relatively deep depths, and White Bear Lake is the deepest lake in that area. The percentages of surface-water contribution to the three wells screened in the glacial buried aquifer receiving surface water were 16, 48, and 83 percent. The percentages of surface-water contribution ranged from 5 to 79 percent for the five wells open to the Prairie du Chien-Jordan aquifer receiving surface water; wells closest to White Bear Lake had the largest percentages of surface-water contribution. Water-balance analysis of White Bear Lake in March and August 2011 indicated a potential discharge of 2.8 and 4.5 inches per month, respectively, over the area of the lake from the lake to local aquifers. Most of the sediments from a 12.4-foot lake core collected at the deepest part of White Bear Lake consisted of silts, sands, and gravels likely slumped from shallower waters, with a very low amount of low-permeability, organic material.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135044","collaboration":"Prepared in cooperation with the White Bear Lake Conservation District, Minnesota Pollution Control Agency, Minnesota Department of Natural Resources, Minnesota Board of Water and Soil Resources, Twin Cities Metropolitan Council, and the Groundwater/Surface-Water Interaction Partners","usgsCitation":"Jones, P.M., Trost, J.J., Rosenberry, D.O., Jackson, P., Bode, J.A., and O’Grady, R.M., 2013, Groundwater and surface-water interactions near White Bear Lake, Minnesota, through 2011: U.S. Geological Survey Scientific Investigations Report 2013-5044, ix, 73 p.; Downloads Directory, https://doi.org/10.3133/sir20135044.","productDescription":"ix, 73 p.; Downloads Directory","numberOfPages":"88","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-030440","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":271388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135044.gif"},{"id":271385,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5044/"},{"id":271387,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5044/downloads/"},{"id":271386,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5044/sir2013-5044.pdf"}],"country":"United States","state":"Minnesota","county":"Anoka County, Ramsey County, Washington County","city":"Minneapolis","otherGeospatial":"White Bear Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.2080078125,\n 44.92883525162427\n ],\n [\n -93.2080078125,\n 45.2004253589021\n ],\n [\n -92.80357360839842,\n 45.2004253589021\n ],\n [\n -92.80357360839842,\n 44.92883525162427\n ],\n [\n -93.2080078125,\n 44.92883525162427\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51779f59e4b095699adf272a","contributors":{"authors":[{"text":"Jones, Perry M. 0000-0002-6569-5144 pmjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6569-5144","contributorId":2231,"corporation":false,"usgs":true,"family":"Jones","given":"Perry","email":"pmjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trost, Jared J. 0000-0003-0431-2151 jtrost@usgs.gov","orcid":"https://orcid.org/0000-0003-0431-2151","contributorId":3749,"corporation":false,"usgs":true,"family":"Trost","given":"Jared","email":"jtrost@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477837,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":477835,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, P. Ryan","contributorId":68571,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","middleInitial":"Ryan","affiliations":[],"preferred":false,"id":477839,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bode, Jenifer A. jabode@usgs.gov","contributorId":3857,"corporation":false,"usgs":true,"family":"Bode","given":"Jenifer","email":"jabode@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":477838,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Grady, Ryan M.","contributorId":83433,"corporation":false,"usgs":true,"family":"O’Grady","given":"Ryan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":477840,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70045566,"text":"ds761 - 2013 - Archive of post-Hurricane Isabel coastal oblique aerial photographs collected during U.S. Geological Survey Field Activity 03CCH01 from Ocean City, Maryland, to Fort Caswell, North Carolina and Inland from Waynesboro to Redwood, Virginia, September 21 - 23, 2003","interactions":[],"lastModifiedDate":"2026-05-19T16:22:59.323633","indexId":"ds761","displayToPublicDate":"2013-04-23T00:00:00","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":"761","title":"Archive of post-Hurricane Isabel coastal oblique aerial photographs collected during U.S. Geological Survey Field Activity 03CCH01 from Ocean City, Maryland, to Fort Caswell, North Carolina and Inland from Waynesboro to Redwood, Virginia, September 21 - 23, 2003","docAbstract":"On September 21 - 23, 2003, the United States Geological Survey (USGS) conducted an oblique aerial photographic survey along the Atlantic coast from Ocean City, Md., to Fort Caswell, N.C., and inland oblique aerial photographic survey from Waynesboro to Redwood, Va., aboard a Navajo Piper twin-engine airplane. The coastal survey was conducted at an altitude of 500 feet (ft) and approximately 1,000 ft offshore. For the inland photos, the aircraft tried to stay approximately 500 ft above the terrain. These coastal photos were used to document coastal changes like beach erosion and overwash caused by Hurricane Isabel, while the inland photos looked for potential landslides caused by heavy rains. The photos may also be used as baseline data for future coastal change analysis. The USGS and the National Aeronautics and Space Administration (NASA) surveyed the impact zone of Hurricane Isabel to better understand the changes in vulnerability of the Nation’s coasts to extreme storms (Morgan, 2009). This report serves as an archive of photographs collected during the September 21 - 23, 2003, post-Hurricane Isabel coastal and inland oblique aerial survey along with associated survey maps, KML files, navigation files, digital Field Activity Collection System (FACS) logs, and Federal Geographic Data Committee (FGDC) metadata. Refer to the Acronyms page for expansions of all acronyms and abbreviations used in this report.\n\nThe USGS St. Petersburg Coastal and Marine Science Center (SPCMSC) assigns a unique identifier to each cruise or field activity. For example, 03CCH01 tells us the data were collected in 2003 for the Coastal Change Hazards (CCH) study and the data were collected during the first field activity for that project in that calendar year. Refer to http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html for a detailed description of the method used to assign the ID number.\n\nThe photographs provided here are Joint Photographic Experts Group (JPEG) scanned images of the analog 35 millimeter (mm) color positive slides. The photograph locations are estimates of the location of the plane (see the Navigation page). The metadata values for photo creation time, GPS latitude, GPS longitude, GPS position (latitude and longitude), keywords, credit, artist, caption, copyright, and contact were added to each photograph's EXIF header using EXIFtool (Subino and others, 2012). Photographs can be opened directly with any JPEG-compatible image viewer by clicking on a thumbnail on the contact sheet, or, when viewing the Google Earth KML file, by clicking on the marker and then clicking on either the thumbnail or the link below the thumbnail. Nathaniel Plant (USGS - St. Petersburg, Fla.), and Ann Marie Ascough (formerly contracted at the USGS - St. Petersburg, Fla.) helped with the creation of KML files. To view the photos and survey maps, proceed to the Photos and Maps page.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds761","collaboration":"Groundwater Resources Program","usgsCitation":"Subino, J.A., Morgan, K., Krohn, M.D., and Dadisman, S.V., 2013, Archive of post-Hurricane Isabel coastal oblique aerial photographs collected during U.S. Geological Survey Field Activity 03CCH01 from Ocean City, Maryland, to Fort Caswell, North Carolina and Inland from Waynesboro to Redwood, Virginia, September 21 - 23, 2003: U.S. Geological Survey Data Series 761, HTML Document, https://doi.org/10.3133/ds761.","productDescription":"HTML Document","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"2003-09-21","temporalEnd":"2003-09-23","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":271410,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/761/pubs761/index.html"},{"id":271409,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/761/"},{"id":504532,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98411.htm","linkFileType":{"id":5,"text":"html"}},{"id":271411,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds761.gif"}],"country":"United States","state":"Maryland, North Carolina, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.70556640625,\n 33.37641235124676\n ],\n [\n -80.70556640625,\n 39.639537564366684\n ],\n [\n -73.67431640625,\n 39.639537564366684\n ],\n [\n -73.67431640625,\n 33.37641235124676\n ],\n [\n -80.70556640625,\n 33.37641235124676\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51779f4fe4b095699adf271a","contributors":{"authors":[{"text":"Subino, Janice A.","contributorId":50386,"corporation":false,"usgs":true,"family":"Subino","given":"Janice","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":477856,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morgan, Karen L.M. 0000-0002-2994-5572","orcid":"https://orcid.org/0000-0002-2994-5572","contributorId":95553,"corporation":false,"usgs":true,"family":"Morgan","given":"Karen L.M.","affiliations":[],"preferred":false,"id":477857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krohn, M. Dennis dkrohn@usgs.gov","contributorId":3378,"corporation":false,"usgs":true,"family":"Krohn","given":"M.","email":"dkrohn@usgs.gov","middleInitial":"Dennis","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":477855,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dadisman, Shawn V. sdadisman@usgs.gov","contributorId":2207,"corporation":false,"usgs":true,"family":"Dadisman","given":"Shawn","email":"sdadisman@usgs.gov","middleInitial":"V.","affiliations":[],"preferred":true,"id":477854,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045548,"text":"ofr20131061 - 2013 - Groundwater-level trends and forecasts, and salinity trends, in the Azraq, Dead Sea, Hammad, Jordan Side Valleys, Yarmouk, and Zarqa groundwater basins, Jordan","interactions":[],"lastModifiedDate":"2013-04-22T13:18:43","indexId":"ofr20131061","displayToPublicDate":"2013-04-22T00:00:00","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":"2013-1061","title":"Groundwater-level trends and forecasts, and salinity trends, in the Azraq, Dead Sea, Hammad, Jordan Side Valleys, Yarmouk, and Zarqa groundwater basins, Jordan","docAbstract":"Changes in groundwater levels and salinity in six groundwater basins in Jordan were characterized by using linear trends fit to well-monitoring data collected from 1960 to early 2011. On the basis of data for 117 wells, groundwater levels in the six basins were declining, on average about -1 meter per year (m/yr), in 2010. The highest average rate of decline, -1.9 m/yr, occurred in the Jordan Side Valleys basin, and on average no decline occurred in the Hammad basin. The highest rate of decline for an individual well was -9 m/yr. Aquifer saturated thickness, a measure of water storage, was forecast for year 2030 by using linear extrapolation of the groundwater-level trend in 2010. From 30 to 40 percent of the saturated thickness, on average, was forecast to be depleted by 2030. Five percent of the wells evaluated were forecast to have zero saturated thickness by 2030. Electrical conductivity was used as a surrogate for salinity (total dissolved solids). Salinity trends in groundwater were much more variable and less linear than groundwater-level trends. The long-term linear salinity trend at most of the 205 wells evaluated was not increasing, although salinity trends are increasing in some areas. The salinity in about 58 percent of the wells in the Amman-Zarqa basin was substantially increasing, and the salinity in Hammad basin showed a long-term increasing trend. Salinity increases were not always observed in areas with groundwater-level declines. The highest rates of salinity increase were observed in regional discharge areas near groundwater pumping centers.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131061","collaboration":"Prepared in cooperation with the U.S. Agency for International Development and the U.S. Army Corps of Engineers","usgsCitation":"Goode, D., Senior, L.A., Subah, A., and Jaber, A., 2013, Groundwater-level trends and forecasts, and salinity trends, in the Azraq, Dead Sea, Hammad, Jordan Side Valleys, Yarmouk, and Zarqa groundwater basins, Jordan: U.S. Geological Survey Open-File Report 2013-1061, Report: viii, 80 p.; Executive Summary: 11 p.; ZIP of all files, https://doi.org/10.3133/ofr20131061.","productDescription":"Report: viii, 80 p.; Executive Summary: 11 p.; ZIP of all files","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":271361,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131061.png"},{"id":271358,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1061/"},{"id":271359,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1061/support/ofr2013-1061.zip"},{"id":271360,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1061/support/ofr2013-1061.pdf"}],"projection":"Palestine 1923 Palestine Belt, Transverse Mercator","country":"Jordan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 34.8706,29.1809 ], [ 34.8706,33.3764 ], [ 39.3036,33.3764 ], [ 39.3036,29.1809 ], [ 34.8706,29.1809 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51764ddce4b0f989f99e0096","contributors":{"authors":[{"text":"Goode, Daniel J. 0000-0002-8527-2456 djgoode@usgs.gov","orcid":"https://orcid.org/0000-0002-8527-2456","contributorId":2433,"corporation":false,"usgs":true,"family":"Goode","given":"Daniel J.","email":"djgoode@usgs.gov","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":477816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senior, Lisa A. 0000-0003-2629-1996 lasenior@usgs.gov","orcid":"https://orcid.org/0000-0003-2629-1996","contributorId":2150,"corporation":false,"usgs":true,"family":"Senior","given":"Lisa","email":"lasenior@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477815,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Subah, Ali","contributorId":66994,"corporation":false,"usgs":true,"family":"Subah","given":"Ali","email":"","affiliations":[],"preferred":false,"id":477818,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jaber, Ayman","contributorId":46398,"corporation":false,"usgs":true,"family":"Jaber","given":"Ayman","email":"","affiliations":[],"preferred":false,"id":477817,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045542,"text":"70045542 - 2013 - Comparing Laser Desorption Ionization and Atmospheric Pressure Photoionization Coupled to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry To Characterize Shale Oils at the Molecular Level","interactions":[],"lastModifiedDate":"2013-04-22T12:44:56","indexId":"70045542","displayToPublicDate":"2013-04-22T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1506,"text":"Energy & Fuels","active":true,"publicationSubtype":{"id":10}},"title":"Comparing Laser Desorption Ionization and Atmospheric Pressure Photoionization Coupled to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry To Characterize Shale Oils at the Molecular Level","docAbstract":"Laser desorption ionization (LDI) coupled to Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was used to analyze shale oils. Previous work showed that LDI is a sensitive ionization technique for assessing aromatic nitrogen compounds, and oils generated from Green River Formation oil shales are well-documented as being rich in nitrogen. The data presented here demonstrate that LDI is effective in ionizing high-double-bond-equivalent (DBE) compounds and, therefore, is a suitable method for characterizing compounds with condensed structures. Additionally, LDI generates radical cations and protonated ions concurrently, the distribution of which depends upon the molecular structures and elemental compositions, and the basicity of compounds is closely related to the generation of protonated ions. This study demonstrates that LDI FT-ICR MS is an effective ionization technique for use in the study of shale oils at the molecular level. To the best of our knowledge, this is the first time that LDI FT-ICR MS has been applied to shale oils.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Energy & Fuels","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ACS Publications (American Chemical Society)","publisherLocation":"Washington, DC","doi":"10.1021/ef3015662","usgsCitation":"Cho, Y., Jin, J.M., Witt, M., Birdwell, J.E., Na, J., Roh, N., and Kim, S., 2013, Comparing Laser Desorption Ionization and Atmospheric Pressure Photoionization Coupled to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry To Characterize Shale Oils at the Molecular Level: Energy & Fuels, v. 27, no. 4, p. 1830-1837, https://doi.org/10.1021/ef3015662.","startPage":"1830","endPage":"1837","numberOfPages":"8","additionalOnlineFiles":"N","ipdsId":"IP-041173","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":271351,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271350,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/ef3015662"}],"volume":"27","issue":"4","noUsgsAuthors":false,"publicationDate":"2012-12-27","publicationStatus":"PW","scienceBaseUri":"51764dcfe4b0f989f99e0086","contributors":{"authors":[{"text":"Cho, Yunjo","contributorId":99860,"corporation":false,"usgs":true,"family":"Cho","given":"Yunjo","email":"","affiliations":[],"preferred":false,"id":477810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jin, Jang Mi","contributorId":28877,"corporation":false,"usgs":true,"family":"Jin","given":"Jang","email":"","middleInitial":"Mi","affiliations":[],"preferred":false,"id":477805,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Witt, Matthias","contributorId":41719,"corporation":false,"usgs":true,"family":"Witt","given":"Matthias","email":"","affiliations":[],"preferred":false,"id":477806,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":477804,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Na, Jeong-Geol","contributorId":95358,"corporation":false,"usgs":true,"family":"Na","given":"Jeong-Geol","email":"","affiliations":[],"preferred":false,"id":477809,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roh, Nam-Sun","contributorId":51622,"corporation":false,"usgs":true,"family":"Roh","given":"Nam-Sun","email":"","affiliations":[],"preferred":false,"id":477808,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kim, Sunghwan","contributorId":45606,"corporation":false,"usgs":true,"family":"Kim","given":"Sunghwan","affiliations":[],"preferred":false,"id":477807,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70045470,"text":"70045470 - 2013 - Complex resistivity signatures of ethanol in sand-clay mixtures","interactions":[],"lastModifiedDate":"2013-04-21T19:27:31","indexId":"70045470","displayToPublicDate":"2013-04-21T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Complex resistivity signatures of ethanol in sand-clay mixtures","docAbstract":"We performed complex resistivity (CR) measurements on laboratory columns to investigate changes in electrical properties as a result of varying ethanol (EtOH) concentration (0% to 30% v/v) in a sand–clay (bentonite) matrix. We applied Debye decomposition, a phenomenological model commonly used to fit CR data, to determine model parameters (time constant: τ, chargeability: m, and normalized chargeability: mn). The CR data showed a significant (P ≤ 0.001) time-dependent variation in the clay driven polarization response (~ 12 mrad) for 0% EtOH concentration. This temporal variation probably results from the clay–water reaction kinetics trending towards equilibrium in the sand–clay–water system. The clay polarization is significantly suppressed (P ≤ 0.001) for both measured phase (ϕ) and imaginary conductivity (σ″) with increasing EtOH concentration. Normalized chargeability consistently decreases (by up to a factor of ~ 2) as EtOH concentration increases from 0% to 10% and 10 to 20%, respectively. We propose that such suppression effects are associated with alterations in the electrical double layer (EDL) at the clay–fluid interface due to (a) strong EtOH adsorption on clay, and (b) complex intermolecular EtOH–water interactions and subsequent changes in ionic mobility on the surface in the EDL. Changes in the CR data following a change of the saturating fluid from EtOH 20% to plain water indicate strong hysteresis effects in the electrical response, which we attribute to persistent EtOH adsorption on clay. Our results demonstrate high sensitivity of CR measurements to clay–EtOH interactions in porous media, indicating the potential application of this technique for characterization and monitoring of ethanol contamination in sediments containing clays.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Contaminant Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jconhyd.2013.03.005","usgsCitation":"Personna, Y.R., Slater, L., Ntarlagiannis, D., Werkema, D.D., and Szabo, Z., 2013, Complex resistivity signatures of ethanol in sand-clay mixtures: Journal of Contaminant Hydrology, v. 149, p. 76-87, https://doi.org/10.1016/j.jconhyd.2013.03.005.","productDescription":"12 p.","startPage":"76","endPage":"87","ipdsId":"IP-045055","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":271323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271322,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jconhyd.2013.03.005"}],"volume":"149","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5174fc5ee4b074c2b055647d","contributors":{"authors":[{"text":"Personna, Yves Robert","contributorId":77820,"corporation":false,"usgs":false,"family":"Personna","given":"Yves","email":"","middleInitial":"Robert","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":477578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slater, Lee","contributorId":55707,"corporation":false,"usgs":false,"family":"Slater","given":"Lee","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":477577,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ntarlagiannis, Dimitrios","contributorId":55303,"corporation":false,"usgs":false,"family":"Ntarlagiannis","given":"Dimitrios","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":477576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Werkema, Dale D.","contributorId":40488,"corporation":false,"usgs":false,"family":"Werkema","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":477575,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szabo, Zoltan 0000-0002-0760-9607 zszabo@usgs.gov","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":2240,"corporation":false,"usgs":true,"family":"Szabo","given":"Zoltan","email":"zszabo@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":477574,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70043239,"text":"70043239 - 2013 - Climatic trends over Ethiopia: regional signals and drivers","interactions":[],"lastModifiedDate":"2013-06-17T09:07:21","indexId":"70043239","displayToPublicDate":"2013-04-21T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2032,"text":"International Journal of Climatology","active":true,"publicationSubtype":{"id":10}},"title":"Climatic trends over Ethiopia: regional signals and drivers","docAbstract":"This study analyses observed and projected climatic trends over Ethiopia, through analysis of temperature and rainfall records and related meteorological fields. The observed datasets include gridded station records and reanalysis products; while projected trends are analysed from coupled model simulations drawn from the IPCC 4th Assessment. Upward trends in air temperature of + 0.03 °C year−1 and downward trends in rainfall of − 0.4 mm month−1 year−1 have been observed over Ethiopia's southwestern region in the period 1948-2006. These trends are projected to continue to 2050 according to the Geophysical Fluid Dynamics Lab model using the A1B scenario. Large scale forcing derives from the West Indian Ocean where significant warming and increased rainfall are found. Anticyclonic circulations have strengthened over northern and southern Africa, limiting moisture transport from the Gulf of Guinea and Congo. Changes in the regional Walker and Hadley circulations modulate the observed and projected climatic trends. Comparing past and future patterns, the key features spread westward from Ethiopia across the Sahel and serve as an early warning of potential impacts.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Climatology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/joc.3560","usgsCitation":"Jury, M.R., and Funk, C.C., 2013, Climatic trends over Ethiopia: regional signals and drivers: International Journal of Climatology, v. 33, no. 8, p. 1924-1935, https://doi.org/10.1002/joc.3560.","productDescription":"12 p.","startPage":"1924","endPage":"1935","ipdsId":"IP-021460","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":271307,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271306,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/joc.3560"}],"country":"Ethiopia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 33.0,3.4 ], [ 33.0,15.0 ], [ 48.0,15.0 ], [ 48.0,3.4 ], [ 33.0,3.4 ] ] ] } } ] }","volume":"33","issue":"8","noUsgsAuthors":false,"publicationDate":"2012-08-15","publicationStatus":"PW","scienceBaseUri":"5174fc52e4b074c2b0556471","contributors":{"authors":[{"text":"Jury, Mark R.","contributorId":28145,"corporation":false,"usgs":true,"family":"Jury","given":"Mark","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":473217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":473216,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70044145,"text":"70044145 - 2013 - CEOS visualization environment (COVE) tool for intercalibration of satellite instruments","interactions":[],"lastModifiedDate":"2013-04-20T18:19:54","indexId":"70044145","displayToPublicDate":"2013-04-20T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1944,"text":"IEEE Transactions on Geoscience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"CEOS visualization environment (COVE) tool for intercalibration of satellite instruments","docAbstract":"Increasingly, data from multiple instruments are used to gain a more complete understanding of land surface processes at a variety of scales. Intercalibration, comparison, and coordination of satellite instrument coverage areas is a critical effort of international and domestic space agencies and organizations. The Committee on Earth Observation Satellites Visualization Environment (COVE) is a suite of browser-based applications that leverage Google Earth to display past, present, and future satellite instrument coverage areas and coincident calibration opportunities. This forecasting and ground coverage analysis and visualization capability greatly benefits the remote sensing calibration community in preparation for multisatellite ground calibration campaigns or individual satellite calibration studies. COVE has been developed for use by a broad international community to improve the efficiency and efficacy of such calibration planning efforts, whether those efforts require past, present, or future predictions. This paper provides a brief overview of the COVE tool, its validation, accuracies, and limitations with emphasis on the applicability of this visualization tool for supporting ground field campaigns and intercalibration of satellite instruments.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"IEEE Transactions on Geoscience and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"IEEE","publisherLocation":"Washington, D.C.","doi":"10.1109/TGRS.2012.2235841","usgsCitation":"Kessler, P., Killough, B., Gowda, S., Williams, B., Chander, G., and Qu, M., 2013, CEOS visualization environment (COVE) tool for intercalibration of satellite instruments: IEEE Transactions on Geoscience and Remote Sensing, v. 51, no. 3, p. 1081-1087, https://doi.org/10.1109/TGRS.2012.2235841.","productDescription":"7 p.","startPage":"1081","endPage":"1087","ipdsId":"IP-043733","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":271287,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1109/TGRS.2012.2235841"},{"id":271288,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5173b164e4b0e619a5806e9d","contributors":{"authors":[{"text":"Kessler, P.D.","contributorId":9940,"corporation":false,"usgs":true,"family":"Kessler","given":"P.D.","email":"","affiliations":[],"preferred":false,"id":474890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Killough, B.D.","contributorId":48848,"corporation":false,"usgs":true,"family":"Killough","given":"B.D.","email":"","affiliations":[],"preferred":false,"id":474892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gowda, S.","contributorId":21846,"corporation":false,"usgs":true,"family":"Gowda","given":"S.","email":"","affiliations":[],"preferred":false,"id":474891,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, B.R.","contributorId":83420,"corporation":false,"usgs":true,"family":"Williams","given":"B.R.","email":"","affiliations":[],"preferred":false,"id":474895,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":474893,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Qu, Min","contributorId":79380,"corporation":false,"usgs":true,"family":"Qu","given":"Min","email":"","affiliations":[],"preferred":false,"id":474894,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70045491,"text":"sir20135083 - 2013 - Sediment transport in the lower Snake and Clearwater River Basins, Idaho and Washington, 2008–11","interactions":[],"lastModifiedDate":"2013-04-19T09:29:00","indexId":"sir20135083","displayToPublicDate":"2013-04-19T00:00:00","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":"2013-5083","title":"Sediment transport in the lower Snake and Clearwater River Basins, Idaho and Washington, 2008–11","docAbstract":"Sedimentation is an ongoing maintenance problem for reservoirs, limiting reservoir storage capacity and navigation. Because Lower Granite Reservoir in Washington is the most upstream of the four U.S. Army Corps of Engineers reservoirs on the lower Snake River, it receives and retains the largest amount of sediment. In 2008, in cooperation with the U.S. Army Corps of Engineers, the U.S. Geological Survey began a study to quantify sediment transport to Lower Granite Reservoir. Samples of suspended sediment and bedload were collected from streamgaging stations on the Snake River near Anatone, Washington, and the Clearwater River at Spalding, Idaho. Both streamgages were equipped with an acoustic Doppler velocity meter to evaluate the efficacy of acoustic backscatter for estimating suspended-sediment concentrations and transport. In 2009, sediment sampling was extended to 10 additional locations in tributary watersheds to help identify the dominant source areas for sediment delivery to Lower Granite Reservoir. Suspended-sediment samples were collected 9–15 times per year at each location to encompass a range of streamflow conditions and to capture significant hydrologic events such as peak snowmelt runoff and rain-on-snow. Bedload samples were collected at a subset of stations where the stream conditions were conducive for sampling, and when streamflow was sufficiently high for bedload transport. At most sampling locations, the concentration of suspended sediment varied by 3–5 orders of magnitude with concentrations directly correlated to streamflow. The largest median concentrations of suspended sediment (100 and 94 mg/L) were in samples collected from stations on the Palouse River at Hooper, Washington, and the Salmon River at White Bird, Idaho, respectively. The smallest median concentrations were in samples collected from the Selway River near Lowell, Idaho (11 mg/L), the Lochsa River near Lowell, Idaho (11 mg/L), the Clearwater River at Orofino, Idaho (13 mg/L), and the Middle Fork Clearwater River at Kooskia, Idaho (15 mg/L). The largest measured concentrations of suspended sediment (3,300 and 1,400 mg/L) during a rain-on-snow event in January 2011 were from samples collected at the Potlatch River near Spalding, Idaho, and the Palouse River at Hooper, Washington, respectively. Generally, samples collected from agricultural watersheds had a high percentage of silt and clay-sized suspended sediment, whereas samples collected from forested watersheds had a high percentage of sand. During water years 2009–11, Lower Granite Reservoir received about 10 million tons of suspended sediment from the combined loads of the Snake and Clearwater Rivers. The Snake River accounted for about 2.97 million tons per year (about 89 percent) of the total suspended sediment, 1.48 million tons per year (about 90 percent) of the suspended sand, and about 1.52 million tons per year (87 percent) of the suspended silt and clay. Of the suspended sediment transported to Lower Granite Reservoir, the Salmon River accounted for about 51 percent of the total suspended sediment, about 56 percent of the suspended sand, and about 44 percent of the suspended silt and clay. About 6.2 million tons (62 percent) of the sediment contributed to Lower Granite Reservoir during 2009–11 entered during water year 2011, which was characterized by an above average winter snowpack and sustained spring runoff. A comparison of historical data collected from the Snake River near Anatone with data collected during this study indicates that concentrations of total suspended sediment and suspended sand in the Snake River were significantly smaller during water years 1972–79 than during 2008–11. Most of the increased sediment content in the Snake River is attributable to an increase of sand-size material. During 1972–79, sand accounted for an average of 28 percent of the suspended-sediment load; during 2008–11, sand accounted for an average of 48 percent. Historical data from the Clearwater River at Spalding indicates that the concentrations of total suspended sediment collected during 1972–79 were not significantly different from the concentrations measured during this study. However, the suspended-sand concentrations in the Clearwater River were significantly smaller during 1972–79 than during 2008–11. The increase in suspended-sand concentrations in the Snake and Clearwater Rivers are probably attributable to numerous severe forest fires that burned large areas of central Idaho from 1980–2010. Acoustic backscatter from an acoustic Doppler velocity meter proved to be an effective method of estimating suspended-sediment concentration and load for most streamflow conditions in the Snake and Clearwater Rivers. Models based on acoustic backscatter were able to simulate most of the variability in suspended-sediment concentrations in the Clearwater River at Spalding (coefficient of determination [R2]=0.93) and the Snake River near Anatone (R2=0.92). Acoustic backscatter seems to be especially effective for estimating suspended-sediment concentration and load over short (monthly and single storm event) and long (annual) time scales when sediment load is highly variable. However, during high streamflow events acoustic surrogate tools may be unable to capture the contribution of suspended sand moving near the bottom of the water column and thus, underestimate the total load of suspended sediment. At the stations where bedload was collected, the particle-size distribution at low streamflows typically was unimodal with sand comprising the dominant particle size. At higher streamflows and during peak bedload discharge, the particle size typically was bimodal and was comprised primarily of sand and coarse gravel. About 55,000 tons of bedload was discharged from the Snake River to Lower Granite Reservoir during water years 2009–11, about 0.62 percent of the total sediment load delivered by the Snake River. About 9,500 tons of bedload was discharged from the Clearwater River to Lower Granite Reservoir during 2009–11, about 0.83 percent of the total sediment load discharged by the Clearwater River during 2009–11.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135083","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Clark, G.M., Fosness, R.L., and Wood, M.S., 2013, Sediment transport in the lower Snake and Clearwater River Basins, Idaho and Washington, 2008–11: U.S. Geological Survey Scientific Investigations Report 2013-5083, vi, 58 p., https://doi.org/10.3133/sir20135083.","productDescription":"vi, 58 p.","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":271216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135083.jpg"},{"id":271214,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5083/"},{"id":271215,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5083/pdf/sir20135083.pdf"}],"country":"United States","state":"Idaho;Washington","otherGeospatial":"Lower Snake And Clearwater River Basins","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119,44 ], [ -119,47.5 ], [ -113,47.5 ], [ -113,44 ], [ -119,44 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5172595de4b0c173799e78f2","contributors":{"authors":[{"text":"Clark, Gregory M. gmclark@usgs.gov","contributorId":1377,"corporation":false,"usgs":true,"family":"Clark","given":"Gregory","email":"gmclark@usgs.gov","middleInitial":"M.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fosness, Ryan L. 0000-0003-4089-2704 rfosness@usgs.gov","orcid":"https://orcid.org/0000-0003-4089-2704","contributorId":2703,"corporation":false,"usgs":true,"family":"Fosness","given":"Ryan","email":"rfosness@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477622,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Molly S. 0000-0002-5184-8306 mswood@usgs.gov","orcid":"https://orcid.org/0000-0002-5184-8306","contributorId":788,"corporation":false,"usgs":true,"family":"Wood","given":"Molly","email":"mswood@usgs.gov","middleInitial":"S.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":477620,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}