{"pageNumber":"371","pageRowStart":"9250","pageSize":"25","recordCount":68867,"records":[{"id":70193051,"text":"ofr20171135 - 2017 - Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2016","interactions":[],"lastModifiedDate":"2023-04-24T21:14:41.275526","indexId":"ofr20171135","displayToPublicDate":"2017-10-30T00:00:00","publicationYear":"2017","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":"2017-1135","title":"Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2016","docAbstract":"<p class=\"p1\">Trace-metal concentrations in sediment and in the clam <i>Macoma petalum </i>(formerly reported as <i>Macoma balthica</i>), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in south San Francisco Bay, Calif. This report includes the data collected by U.S. Geological Survey (USGS) scientists for the period January 2014 to December 2016. These append to long-term datasets extending back to 1974. A major focus of the report is an integrated description of the 2016 data within the context of the longer, multi-decadal dataset. This dataset supports the City of Palo Alto’s Near-Field Receiving Water Monitoring Program, initiated in 1994.</p><p class=\"p1\">Significant reductions in silver and copper concentrations in sediment and <i>M. petalum </i>occurred at the site in the 1980s following the implementation by PARWQCP of advanced wastewater treatment and source control measures. Since the 1990s, concentrations of these elements appear to have stabilized at concentrations somewhat above (silver) or near (copper) regional background concentrations Data for other metals, including chromium (Cr), mercury (Hg), nickel (Ni), selenium (Se), and zinc (Zn), have been collected since 1994. Over this period, concentrations of these elements have remained relatively constant, aside from seasonal variation that is common to all elements. In 2016, concentrations of silver and copper in <i>M. petalum </i>varied seasonally in response to a combination of site-specific metal exposures and annual growth and reproduction, as reported previously. Seasonal patterns for other elements, including Cr, Ni, Zn, Hg, and Se, were generally similar in timing and magnitude as those for Ag and Cu. This record suggests that legacy contamination and regional-scale factors now largely control sedimentary and bioavailable concentrations of silver and copper, as well as other elements of regulatory interest, at the Palo Alto site.</p><p class=\"p1\">Analyses of the benthic community structure of a mudflat in south San Francisco Bay over a 40-year period show that changes in the community have occurred concurrent with reduced concentrations of metals in the sediment and in the tissues of the biosentinel clam, <i>M. petalum</i>, from the same area. Analysis of <i>M. petalum </i>shows increases in reproductive activity concurrent with the decline in metal concentrations in the tissues of this organism. Reproductive activity is presently stable (2016), with almost all animals initiating reproduction in the fall and spawning the following spring. The entire infaunal community has shifted from being dominated by several opportunistic species to a community where the species are more similar in abundance, a pattern that indicates a more stable community that is subjected to fewer stressors. In addition, two of the opportunistic species (<i>Ampelisca abdita </i>and <i>Streblospio benedicti</i>) that brood their young and live on the surface of the sediment in tubes have shown a continual decline in dominance coincident with the decline in metals; both species had short-lived rebounds in abundance in 2008, 2009, and 2010 and showed signs of increasing abundance in 2016. <i>Heteromastus filiformis </i>(a subsurface polychaete worm that lives in the sediment, consumes sediment and organic particles residing in the sediment, and reproduces by laying its eggs on or in the sediment) showed a concurrent increase in dominance and, in the last several years before 2008, showed a stable population. <i>H. filiformis </i>abundance increased slightly in 2011–2012 and returned to pre-2011 numbers in 2016. An unidentified disturbance occurred on the mudflat in early 2008 that resulted in the loss of the benthic animals, except for deep-dwelling animals like <i>Macoma petalum</i>. However, within two months of this event animals returned to the mudflat. The resilience of the community suggested that the disturbance was not due to a persistent toxin or anoxia. The reproductive mode of most species present in 2016 is reflective of species that were available either as pelagic larvae or as mobile adults. Although oviparous species were lower in number in this group, the authors hypothesize that these species will return slowly as more species move back into the area. The use of functional ecology was highlighted in the 2016 benthic community data, which showed that the animals that have now returned to the mudflat are those that can respond successfully to a physical, nontoxic disturbance. Today, community data show a mix of species that consume the sediment, or filter feed, have pelagic larvae that must survive landing on the sediment, and those that brood their young. USGS scientists view the 2008 disturbance event as a response by the infaunal community to an episodic natural stressor (possibly sediment accretion or a pulse of freshwater), in contrast to the long-term recovery from metal contamination. We will compare this recovery to the long-term recovery observed after the 1970s when the decline in sediment pollutants was the dominating factor.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171135","collaboration":"Prepared in cooperation with the City of Palo Alto, California","usgsCitation":"Cain, D.J., Thompson, J.K., Parchaso, F., Pearson, S., Stewart, R., Turner, M., Barasch, D., and Luoma, S.N., 2017, Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2016: U.S. Geological Survey Open-File Report 2017–1135, 75 p., https://doi.org/10.3133/ofr20171135.","productDescription":"vi, 75 p.","numberOfPages":"82","onlineOnly":"Y","ipdsId":"IP-088104","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":416202,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231017","text":"Open-File Report 2023-1017","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2020"},{"id":416201,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211079","text":"Open-File Report 2021-1079","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2019"},{"id":416200,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191084","text":"Open-File Report 2019-1084","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2018"},{"id":416199,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181107","text":"Open-File Report 2018-1107","linkHelpText":"- Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2017"},{"id":416198,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20161118","text":"Open-File Report 2016-1118","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2015"},{"id":347750,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1135/coverthb_.jpg"},{"id":347751,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1135/ofr.20171135.pdf","text":"Report","size":"4.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1135"}],"country":"United States","state":"California","city":"Palo Alto","otherGeospatial":"south San Francisco bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.16590881347656,\n              37.398528132728615\n            ],\n            [\n              -121.91184997558595,\n              37.398528132728615\n            ],\n            [\n              -121.91184997558595,\n              37.54566616715801\n            ],\n            [\n              -122.16590881347656,\n              37.54566616715801\n            ],\n            [\n              -122.16590881347656,\n              37.398528132728615\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>NRP staff<br> <a href=\"http://water.usgs.gov/nrp/\" target=\"blank\" data-mce-href=\"http://water.usgs.gov/nrp/\">National Research Program</a><br> U.S. Geological Survey<br> 345 Middlefield Road, MS-435<br>Menlo Park, CA 94025</p>","tableOfContents":"<ul><li>Executive Summary of Past Findings<br></li><li>Abstract<br></li><li>Introduction<br></li><li>Methods<br></li><li>Results<br></li><li>Summary<br></li><li>Acknowledgment<br></li><li>References Cited<br></li><li>Appendixes 1–9<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-10-30","noUsgsAuthors":false,"publicationDate":"2017-10-30","publicationStatus":"PW","scienceBaseUri":"59f83a2be4b063d5d309807b","contributors":{"authors":[{"text":"Cain, Daniel J. 0000-0002-3443-0493 djcain@usgs.gov","orcid":"https://orcid.org/0000-0002-3443-0493","contributorId":1784,"corporation":false,"usgs":true,"family":"Cain","given":"Daniel","email":"djcain@usgs.gov","middleInitial":"J.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":717754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Janet K. 0000-0002-1528-8452 jthompso@usgs.gov","orcid":"https://orcid.org/0000-0002-1528-8452","contributorId":1009,"corporation":false,"usgs":true,"family":"Thompson","given":"Janet","email":"jthompso@usgs.gov","middleInitial":"K.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":717755,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parchaso, Francis 0000-0002-9471-7787 parchaso@usgs.gov","orcid":"https://orcid.org/0000-0002-9471-7787","contributorId":150620,"corporation":false,"usgs":true,"family":"Parchaso","given":"Francis","email":"parchaso@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":717756,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearson, Sarah A. spearson@usgs.gov","contributorId":152203,"corporation":false,"usgs":true,"family":"Pearson","given":"Sarah","email":"spearson@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":717952,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stewart, A. Robin 0000-0003-2918-546X arstewar@usgs.gov","orcid":"https://orcid.org/0000-0003-2918-546X","contributorId":1482,"corporation":false,"usgs":true,"family":"Stewart","given":"A.","email":"arstewar@usgs.gov","middleInitial":"Robin","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":40553,"text":"WMA - Office of the Chief Operating Officer","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":717757,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Turner, Mathew","contributorId":199031,"corporation":false,"usgs":true,"family":"Turner","given":"Mathew","email":"","affiliations":[],"preferred":false,"id":717953,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barasch, David","contributorId":199032,"corporation":false,"usgs":true,"family":"Barasch","given":"David","affiliations":[],"preferred":false,"id":717954,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Luoma, Samuel N. 0000-0001-5443-5091 snluoma@usgs.gov","orcid":"https://orcid.org/0000-0001-5443-5091","contributorId":2287,"corporation":false,"usgs":true,"family":"Luoma","given":"Samuel","email":"snluoma@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":717955,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70192947,"text":"70192947 - 2017 - Relative performance of three stream bed stability indices as indicators of stream health","interactions":[],"lastModifiedDate":"2017-10-30T13:59:28","indexId":"70192947","displayToPublicDate":"2017-10-30T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Relative performance of three stream bed stability indices as indicators of stream health","docAbstract":"<p><span>Bed stability is an important stream habitat attribute because it affects geomorphology and biotic communities. Natural resource managers desire indices of bed stability that can be used under a wide range of geomorphic conditions, are biologically meaningful, and are easily incorporated into sampling protocols. To eliminate potential bias due to presence of instream wood and increase precision of stability values, we modified a stream bed instability index (ISI) to include measurements of bankfull depth (</span><i class=\"EmphasisTypeItalic \">d</i><sub>bf</sub><span>) and median particle diameter (</span><i class=\"EmphasisTypeItalic \">D</i><sub>50</sub><span>) only in riffles and increased the pebble count to decrease variability (i.e., increase precision) in<span>&nbsp;</span></span><i class=\"EmphasisTypeItalic \">D</i><sub>50</sub><i class=\"EmphasisTypeItalic \">.</i><span>The new riffle-based instability index (RISI) was compared to two established indices: ISI and the riffle stability index (RSI). RISI and ISI were strongly associated with each other but neither was closely associated with RSI. RISI and ISI were closely associated with both a diatom- and two macrovertebrate-based stream health indices, but RSI was only weakly associated with the macroinvertebrate indices. Unexpectedly, precision of<span>&nbsp;</span></span><i class=\"EmphasisTypeItalic \">D</i><sub>50</sub><span><span>&nbsp;</span>did not differ between RISI and ISI. Results suggest that RISI is a viable alternative to both ISI and RSI for evaluating bed stability in multiple stream types. With few data requirements and a simple protocol, RISI may also better conform to riffle-based sampling methods used by some water quality practitioners.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10661-017-6291-x","usgsCitation":"Kusnierz, P., and Holbrook, C., 2017, Relative performance of three stream bed stability indices as indicators of stream health: Environmental Monitoring and Assessment, v. 189, p. 1-10, https://doi.org/10.1007/s10661-017-6291-x.","productDescription":"Article 563; 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-090619","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":347717,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.71923828124999,\n              44.4808302785626\n            ],\n            [\n              -110.61035156249999,\n              44.4808302785626\n            ],\n            [\n              -110.61035156249999,\n              49.001843917978526\n            ],\n            [\n              -114.71923828124999,\n              49.001843917978526\n            ],\n            [\n              -114.71923828124999,\n              44.4808302785626\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"189","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-16","publicationStatus":"PW","scienceBaseUri":"59f83a2ce4b063d5d3098085","contributors":{"authors":[{"text":"Kusnierz, Paul C","contributorId":198849,"corporation":false,"usgs":false,"family":"Kusnierz","given":"Paul C","affiliations":[],"preferred":false,"id":717401,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holbrook, Christopher M. 0000-0001-8203-6856 cholbrook@usgs.gov","orcid":"https://orcid.org/0000-0001-8203-6856","contributorId":139681,"corporation":false,"usgs":true,"family":"Holbrook","given":"Christopher","email":"cholbrook@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":717400,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70192827,"text":"70192827 - 2017 - Movements and habitat use of White-fronted Geese (Anser albifrons frontalis) during the remigial molt in arctic Alaska, USA","interactions":[],"lastModifiedDate":"2017-10-27T18:47:35","indexId":"70192827","displayToPublicDate":"2017-10-27T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Movements and habitat use of White-fronted Geese (<i>Anser albifrons frontalis</i>) during the remigial molt in arctic Alaska, USA","title":"Movements and habitat use of White-fronted Geese (Anser albifrons frontalis) during the remigial molt in arctic Alaska, USA","docAbstract":"<p>Proposed oil and gas leasing in the National Petroleum Reserve - Alaska has raised questions about possible impacts of development on molting Greater White-fronted Geese (<i>Anser albifrons frontalis</i>) and their habitats. We used GPS transmitters to record fine-scale location data of molting and post-molt White-fronted Geese to assess patterns of movement and resource selection relative to vegetation class, year (2012, 2013), and body mass at capture. Molting White-fronted Geese were located an average of 63.3 ± 4.9 m (SE) from lakeshores. Estimated terrestrial home range size for flightless birds differed between years (2012 = 13.2 ± 2.6 km<sup>2</sup>; 2013 = 6.5 ± 1.8 km<sup>2</sup>), but did not vary among habitat strata or with body mass. Molting White-fronted Geese used sedge (<i>Carex aquatilus</i>) dominated low centered polygons and water more frequently than expected given proportional habitat availability, but avoided tussock tundra and wet sedge vegetation classes. Upon regaining flight, individuals tended to remain in the same general area, and the center of their home range only moved an average of 6.9 km. Greater White-fronted Geese that could fly tended to forage further from lakeshores ( = 245 m), and used a larger home range ( = 44.3 ± 9.5 km<sup>2</sup>) than when flightless.</p>","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.040.0308","usgsCitation":"Flint, P.L., and Meixell, B.W., 2017, Movements and habitat use of White-fronted Geese (Anser albifrons frontalis) during the remigial molt in arctic Alaska, USA: Waterbirds, v. 40, no. 3, p. 272-281, https://doi.org/10.1675/063.040.0308.","productDescription":"10 p.","startPage":"272","endPage":"281","ipdsId":"IP-085017","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":461375,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1675/063.040.0308","text":"Publisher Index Page"},{"id":438175,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PR7TG8","text":"USGS data release","linkHelpText":"Greater White-fronted Goose (Anser albifrons) Habitat Use Data, Teshekpuk Lake Special Area, 2012-2013"},{"id":347594,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -154.22607421875,\n              70.50657489320895\n            ],\n            [\n              -151.50146484375,\n              70.50657489320895\n            ],\n            [\n              -151.50146484375,\n              70.98655968762381\n            ],\n            [\n              -154.22607421875,\n              70.98655968762381\n            ],\n            [\n              -154.22607421875,\n              70.50657489320895\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"40","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f44595e4b063d5d306f2ad","contributors":{"authors":[{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":717088,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meixell, Brandt W. 0000-0002-6738-0349 bmeixell@usgs.gov","orcid":"https://orcid.org/0000-0002-6738-0349","contributorId":138716,"corporation":false,"usgs":true,"family":"Meixell","given":"Brandt","email":"bmeixell@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":717089,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70191270,"text":"sir20175112 - 2017 - Hydrogeology and water quality of sand and gravel aquifers in McHenry County, Illinois, 2009–14, and comparison to conditions in 1979","interactions":[],"lastModifiedDate":"2026-04-01T15:55:08.73","indexId":"sir20175112","displayToPublicDate":"2017-10-26T00:00:00","publicationYear":"2017","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":"2017-5112","displayTitle":"Hydrogeology and Water Quality of Sand and Gravel Aquifers in McHenry County, Illinois, 2009–14, and Comparison to Conditions in 1979","title":"Hydrogeology and water quality of sand and gravel aquifers in McHenry County, Illinois, 2009–14, and comparison to conditions in 1979","docAbstract":"<p class=\"p1\">Baseline conditions for the sand and gravel aquifers (groundwater) in McHenry County, Illinois, were assessed using data from a countywide network of 44 monitoring wells collecting continuous water-level data from 2009–14. In 2010, water-quality data were collected from 41 of the monitoring wells, along with five additional monitoring wells available from the U.S. Geological Survey National Water Quality Assessment Program. Periodic water-quality data were collected from 2010–14 from selected monitoring wells. The continuous water-level data were used to identify the natural and anthropogenic factors that influenced the water levels at each well. The water-level responses to natural influences such as precipitation, seasonal and annual variations, barometric pressure, and geology, and to anthropogenic influences such as pumping were used to determine (1) likely hydrogeologic setting (degree of aquifer confinement and interconnections) that, in part, are related to lithostratigraphy; and (2) areas of recharge and discharge related to vertical flow directions. Water-level trends generally were determined from the 6 years of data collection (2009–14) to infer effects of weather variability (drought) on recharge.</p><p class=\"p1\">Precipitation adds an estimated 2.4 inches per year of recharge to the aquifer. Some of this recharge is subsequently discharged to streams and some is discharged to supply wells. A few areas in the eastern half of the county had higher average recharge rates, indicating a need for adequate protection of these recharge areas. Downward vertical flow gradients in upland areas indicate that recharge to the confined aquifer units occurs near upland areas. Upward vertical flow gradients in lowland areas indicate discharge at locations of surface water and groundwater interaction (wetlands, ponds, and streams).</p><p class=\"p1\">Monitoring wells were sampled for major and minor ions, metals, and nutrients and a subset of wells was sampled for trace elements, dissolved gases, pesticides, and volatile organic compounds. The results were compared to health<span class=\"s1\">‑</span>based and aesthetically based standards, which include the U.S. Environmental Protection Agency Maximum Contaminant Level (EPA MCL), and EPA Secondary Maximum Contaminant Levels (SMCL), as well as EPA Health-based Standards Drinking Water Advisories. Health‑based standards were exceeded for arsenic in 22 percent, sodium in 20 percent, and nitrates in 2 percent of the monitoring wells sampled. Aesthetically based standards were exceeded for total dissolved solids in 33 percent, chloride in 11 percent, iron in 85 percent, and manganese in 30 percent of the wells sampled. Many of these same constituents, such as arsenic, iron, and manganese, are naturally occurring but become elevated in areas that have anoxic, mixed, and suboxic conditions. Some areas of potential vulnerability to anthropogenic-sourced constituents in the sand and gravel aquifers were evidenced by trace amounts of volatile organic compounds and pesticides detected in water-quality samples from shallow wells (total depth less of than 46 feet below land surface) near urban settings, and by the detection of elevated major ions (chloride, sodium, magnesium, and calcium) associated, in part, with road-salt applications. Source analysis for chloride indicates mixtures of road salt, water softeners, and sewage.</p><p class=\"p2\">Continuously measured specific conductance values were used as a surrogate for continuously measured chloride concentrations in the groundwater. The estimated chloride concentrations generally were highest in spring and lowest in summer, and occasionally peak during spring melt. Overall, the range of concentrations varied depending on the local thickness and hydraulic conductivity of the aquifer.</p><p class=\"p2\">Water levels and water quality from the countywide groundwater monitoring network were compared to water levels and water-quality results in 1979 from a previous U.S. Geological Survey study. Potentiometric surface maps show areas with inferred decreases of water levels near the southern and southeastern areas of McHenry County. Significant increases were noted for total dissolved solids and specific conductance. Chloride concentrations increased as much as 521 percent in three of six wells resampled in 2015 from the previous study.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175112","collaboration":"Prepared in cooperation with McHenry County, Illinois","usgsCitation":"Gahala, A.M., 2017, Hydrogeology and water quality of sand and gravel aquifers in McHenry County, Illinois, 2009–14, and comparison to conditions in 1979 (ver. 1.1, August 2022): U.S. Geological Survey Scientific Investigations Report 2017–5112, 91 p.,  https://doi.org/10.3133/sir20175112.","productDescription":"ix, 91 p.","numberOfPages":"106","onlineOnly":"Y","ipdsId":"IP-067438","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":404906,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2017/5112/versionHist.txt","text":"Version History","size":"1.36 kB","linkFileType":{"id":2,"text":"txt"}},{"id":404904,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5112/coverthb2.jpg"},{"id":347422,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5112/sir20175112.pdf","text":"Report","size":"6.67 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5112"},{"id":501947,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_106395.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Illinois","county":"McHenry County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-88.3016,42.4979],[-88.1971,42.4981],[-88.1979,42.4562],[-88.1974,42.4167],[-88.1966,42.3286],[-88.1994,42.2432],[-88.1992,42.1555],[-88.2382,42.155],[-88.3539,42.1547],[-88.4703,42.1552],[-88.5891,42.1556],[-88.7061,42.1564],[-88.7057,42.2418],[-88.7041,42.329],[-88.705,42.4167],[-88.7059,42.4972],[-88.6737,42.4977],[-88.6288,42.4985],[-88.5047,42.4981],[-88.4099,42.4977],[-88.3016,42.4979]]]},\"properties\":{\"name\":\"McHenry\",\"state\":\"IL\"}}]}","edition":"Version 1.0: October 26, 2017; Version 1.1: August 17, 2022","contact":"<p><a href=\"mailto:dc_il@usgs.gov\" data-mce-href=\"mailto:dc_il@usgs.gov\">Director</a>, <a href=\"https://il.water.usgs.gov\" target=\"blank\" data-mce-href=\"https://il.water.usgs.gov\">Illinois Water Science Center</a><br>U.S. Geological Survey<br>405 N Goodwin<br>Urbana, IL 61801</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Description of Study Area<br></li><li>Previous Investigations<br></li><li>Methods<br></li><li>Hydrogeology<br></li><li>Water Quality of Sand and Gravel Aquifers in McHenry County<br></li><li>Comparisons to Conditions in 1979<br></li><li>Summary and Conclusions<br></li><li>Acknowledgments<br></li><li>References Cited<br></li><li>Appendix A. Well Log Lithology of National Water-Quality Assessment (NAWQA) Monitoring Well 44N9E-20.7c<br></li></ul>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2017-10-26","revisedDate":"2022-08-17","noUsgsAuthors":false,"publicationDate":"2017-10-26","publicationStatus":"PW","scienceBaseUri":"5a07e85ce4b09af898c8cb60","contributors":{"authors":[{"text":"Gahala, Amy M. 0000-0003-2380-2973 agahala@usgs.gov","orcid":"https://orcid.org/0000-0003-2380-2973","contributorId":4396,"corporation":false,"usgs":true,"family":"Gahala","given":"Amy","email":"agahala@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711789,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70192122,"text":"70192122 - 2017 - Plastic ingestion by Black-footed Albatross Phoebastria nigripes from Kure Atoll, Hawai'i: Linking chick diet remains and parental at-sea foraging distributions","interactions":[],"lastModifiedDate":"2017-10-26T09:33:29","indexId":"70192122","displayToPublicDate":"2017-10-25T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2675,"text":"Marine Ornithology: Journal of Seabird Research and Conservation","onlineIssn":"2074-1235","printIssn":"1018-3337","active":true,"publicationSubtype":{"id":10}},"title":"Plastic ingestion by Black-footed Albatross Phoebastria nigripes from Kure Atoll, Hawai'i: Linking chick diet remains and parental at-sea foraging distributions","docAbstract":"We quantified the incidence (percentage of samples with plastic) and loads (mass, volume) of four plastic types (fragments, line, sheet, foam) ingested by Black-footed Albatross Phoebastria nigripes chicks raised on Kure Atoll, the westernmost Hawaiian colony. All 25 samples contained plastic, mostly in the form of foam and line. On average (± SD), boluses and stomachs contained 28.2 ± 14.3 g and 40.3 ± 29.0 g of plastic, respectively. Plastic was the dominant indigestible material in the boluses and the stomach samples, accounting for 48.8%-89.7% of the bolus mass (mean 67.4 ± 12.1%, median 67.5%, n = 20), and for 18.2%-94.1% of the stomach content mass (mean 70.0 ± 30.3%, median 75.6%, n = 5). Although the ingested plastic fragments ranged widely in size, most (92% in boluses, 91% in stomachs) were mesoplastics (5-25 mm), followed by macroplastics (>25 mm; 7% in boluses, 6% in stomachs), and microplastics (1-5 mm; 1% in boluses, 4% in stomachs). Yet the two fragment size distributions were significantly different, with more small-sized items (3-8 mm) in stomachs and with more large-sized items (46-72 mm) in boluses. To investigate where albatross parents collect this material, we tracked seven provisioning adults during 14 foraging trips using satellite-linked transmitters. The tracked birds foraged west of Kure Atoll (180–150°E, 30-40°N) and spent most of their time over pelagic waters (>2000 m deep; averaging 89 ± 9%), with substantial time over seamounts (averaging 11 ± 7%). Together, these results indicate that Black-footed Albatross chicks at Kure Atoll ingest plastics sourced by their parents foraging in waters of the western North Pacific. Provisioning adults forage within an area of surface convergence, downstream from the Kuroshio Current, and frequently visit seamounts northwest of the Hawaiian archipelago.","language":"English","publisher":"Marine Ornithology","usgsCitation":"Hyrenbach, K.D., Hester, M.M., Adams, J., Titmus, A.J., Michael, P., Wahl, T., Chang, C., Marie, A., and Vanderlip, C., 2017, Plastic ingestion by Black-footed Albatross Phoebastria nigripes from Kure Atoll, Hawai'i: Linking chick diet remains and parental at-sea foraging distributions: Marine Ornithology: Journal of Seabird Research and Conservation, v. 45, no. 2, p. 225-236.","productDescription":"12 p.","startPage":"225","endPage":"236","ipdsId":"IP-087030","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":347367,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347032,"type":{"id":15,"text":"Index Page"},"url":"https://www.marineornithology.org/content/get.cgi?rn=1232"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kure Atoll","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {\n        \"stroke\": \"#555555\",\n        \"stroke-width\": 2,\n        \"stroke-opacity\": 1,\n        \"fill\": \"#555555\",\n        \"fill-opacity\": 0.5\n      },\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -178.35565567016602,\n              28.376599976934674\n            ],\n            [\n              -178.2773780822754,\n              28.376599976934674\n            ],\n            [\n              -178.2773780822754,\n              28.440468539620316\n            ],\n            [\n              -178.35565567016602,\n              28.440468539620316\n            ],\n            [\n              -178.35565567016602,\n              28.376599976934674\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"45","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f1a2a1e4b0220bbd9d9f19","contributors":{"authors":[{"text":"Hyrenbach, K. David","contributorId":96173,"corporation":false,"usgs":true,"family":"Hyrenbach","given":"K.","email":"","middleInitial":"David","affiliations":[],"preferred":false,"id":714313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hester, Michelle M. 0000-0002-0769-5904","orcid":"https://orcid.org/0000-0002-0769-5904","contributorId":197785,"corporation":false,"usgs":false,"family":"Hester","given":"Michelle","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":714314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Josh 0000-0003-3056-925X josh_adams@usgs.gov","orcid":"https://orcid.org/0000-0003-3056-925X","contributorId":2422,"corporation":false,"usgs":true,"family":"Adams","given":"Josh","email":"josh_adams@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":714312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Titmus, Andrew J.","contributorId":197786,"corporation":false,"usgs":false,"family":"Titmus","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":714315,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Michael, Pam","contributorId":197787,"corporation":false,"usgs":false,"family":"Michael","given":"Pam","email":"","affiliations":[],"preferred":false,"id":714316,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wahl, Travis","contributorId":197788,"corporation":false,"usgs":false,"family":"Wahl","given":"Travis","email":"","affiliations":[],"preferred":false,"id":714317,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chang, Chih-Wei","contributorId":197789,"corporation":false,"usgs":false,"family":"Chang","given":"Chih-Wei","email":"","affiliations":[],"preferred":false,"id":714318,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Marie, Amarisa","contributorId":197790,"corporation":false,"usgs":false,"family":"Marie","given":"Amarisa","email":"","affiliations":[],"preferred":false,"id":714319,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Vanderlip, Cynthia","contributorId":197791,"corporation":false,"usgs":false,"family":"Vanderlip","given":"Cynthia","email":"","affiliations":[],"preferred":false,"id":714320,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70192331,"text":"70192331 - 2017 - Partial polygon pruning of hydrographic features in automated generalization","interactions":[],"lastModifiedDate":"2017-10-25T10:06:11","indexId":"70192331","displayToPublicDate":"2017-10-25T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3618,"text":"Transactions in GIS","active":true,"publicationSubtype":{"id":10}},"title":"Partial polygon pruning of hydrographic features in automated generalization","docAbstract":"This paper demonstrates a working method to automatically detect and prune portions of waterbody polygons to support creation of a multi-scale hydrographic database. Water features are known to be sensitive to scale change; and thus multiple representations are required to maintain visual and geographic logic at smaller scales. Partial pruning of polygonal features—such as long and sinuous reservoir arms, stream channels that are too narrow at the target scale, and islands that begin to coalesce—entails concurrent management of the length and width of polygonal features as well as integrating pruned polygons with other generalized point and linear hydrographic features to maintain stream network connectivity. The implementation follows data representation standards developed by the U.S. Geological Survey (USGS) for the National Hydrography Dataset (NHD). Portions of polygonal rivers, streams, and canals are automatically characterized for width, length, and connectivity. This paper describes an algorithm for automatic detection and subsequent processing, and shows results for a sample of NHD subbasins in different landscape conditions in the United States.","language":"English","publisher":"John Wiley & Sons, Ltd.","doi":"10.1111/tgis.12270","usgsCitation":"Stum, A.K., Buttenfield, B.P., and Stanislawski, L.V., 2017, Partial polygon pruning of hydrographic features in automated generalization: Transactions in GIS, v. 21, no. 5, p. 1061-1078, https://doi.org/10.1111/tgis.12270.","productDescription":"18 p.","startPage":"1061","endPage":"1078","ipdsId":"IP-078637","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":347314,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-08","publicationStatus":"PW","scienceBaseUri":"59f1a29ee4b0220bbd9d9ef8","contributors":{"authors":[{"text":"Stum, Alexander K.","contributorId":198209,"corporation":false,"usgs":false,"family":"Stum","given":"Alexander","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":715372,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buttenfield, Barbara P.","contributorId":184069,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":715373,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stanislawski, Larry V. 0000-0002-9437-0576 lstan@usgs.gov","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":3386,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","email":"lstan@usgs.gov","middleInitial":"V.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":715371,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191853,"text":"70191853 - 2017 - Selective transport of palynomorphs in marine turbiditic deposits: An example from the Ascension-Monterey Canyon system offshore central California","interactions":[],"lastModifiedDate":"2018-04-27T16:52:31","indexId":"70191853","displayToPublicDate":"2017-10-25T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3217,"text":"Quaternary International","active":true,"publicationSubtype":{"id":10}},"title":"Selective transport of palynomorphs in marine turbiditic deposits: An example from the Ascension-Monterey Canyon system offshore central California","docAbstract":"The pollen assemblage of a deep-sea core (15G) collected at lower bathyal depths (3491 m) on a levee of Monterey Canyon off central California was investigated to gain insights into the delivery processes of terrigenous material to submarine fans and the effect this transport has on the palynological record. Thirty-two samples were obtained down the length of the core, 19 from hemipelagic and mixed mud deposits considered to be the background record, and 13 others from displaced flow deposits. The pollen record obtained from the background samples documents variations in the terrestrial flora as it adapted to changing climatic conditions over the last 19,000 cal yrs BP. A Q-mode cluster analysis defined three pollen zones: a Glacial Pollen Zone (ca. 20,000–17,000 cal yr BP), an overlying Transitional Pollen Zone (ca. 17,000–11,500 cal yr BP), and an Interglacial Pollen Zone (ca. 11,500 cal yr BP to present). Another Q-mode cluster analysis, of both the background mud and flow deposits, also defined these three pollen zones, but four of the 13 turbiditic deposits were assigned to pollen zones older than expected by their stratigraphic position. This was due to these samples containing statistically significant fewer palynomorphs than the background muds as well as being enriched (∼10–35% in some cases) in hydraulically-efficient Pinus pollen. A selective bias in the pollen assemblage, such as demonstrated here, may result in incorrect interpretations (e.g., climatic shifts or environmental perturbations) based on the floral record, indicating turbiditic deposits should be avoided in marine palynological studies. Particularly in the case of fine-grained flow deposits that may not be visually distinct, granulometry and grain size frequency distribution curves may not be enough to identify these biased deposits. Determining the relative abundance and source of displaced shallow-water benthic foraminifera entrained in these sediments serves as an excellent additional tool to do so.","language":"English","publisher":"Elsevier","doi":"10.1016/j.quaint.2016.11.003","usgsCitation":"McGann, M., 2017, Selective transport of palynomorphs in marine turbiditic deposits: An example from the Ascension-Monterey Canyon system offshore central California: Quaternary International, v. 469, no. B, p. 120-140, https://doi.org/10.1016/j.quaint.2016.11.003.","productDescription":"21 p.","startPage":"120","endPage":"140","ipdsId":"IP-074347","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469403,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quaint.2016.11.003","text":"Publisher Index Page"},{"id":438178,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74F1NW7","text":"USGS data release","linkHelpText":"Grain-size data from core S3-15G, Monterey Fan, Central California"},{"id":347355,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Monterey Canyon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.6676025390625,\n              36.029110596631874\n            ],\n            [\n              -121.6241455078125,\n              36.029110596631874\n            ],\n            [\n              -121.6241455078125,\n              37.483576550426996\n            ],\n            [\n              -123.6676025390625,\n              37.483576550426996\n            ],\n            [\n              -123.6676025390625,\n              36.029110596631874\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"469","issue":"B","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f1a2a2e4b0220bbd9d9f25","contributors":{"authors":[{"text":"McGann, Mary 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":169540,"corporation":false,"usgs":true,"family":"McGann","given":"Mary","email":"mmcgann@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":713403,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70192372,"text":"70192372 - 2017 - Assessing models of arsenic occurrence in drinking water from bedrock aquifers in New Hampshire","interactions":[],"lastModifiedDate":"2017-10-25T09:37:46","indexId":"70192372","displayToPublicDate":"2017-10-25T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2234,"text":"Journal of Contemporary Water Research and Education","active":true,"publicationSubtype":{"id":10}},"title":"Assessing models of arsenic occurrence in drinking water from bedrock aquifers in New Hampshire","docAbstract":"Three existing multivariate logistic regression models were assessed using new data to evaluate the capacity of the models to correctly predict the probability of groundwater arsenic concentrations exceeding the threshold values of 1, 5, and 10 micrograms per liter (µg/L) in New Hampshire, USA. A recently released testing dataset includes arsenic concentrations from groundwater samples collected in 2004–2005 from a mix of 367 public-supply and private domestic wells. The use of this dataset to test three existing logistic regression models demonstrated enhanced overall predictive accuracy for the 5 and 10 μg/L models. Overall accuracies of 54.8, 76.3, and 86.4 percent were reported for the 1, 5, and 10 μg/L models, respectively. The state was divided by counties into northwest and southeast regions. Regional differences in accuracy were identified; models had an average accuracy of 83.1 percent for the counties in the northwest and 63.7 percent in the southeast. This is most likely due to high model specificity in the northwest and regional differences in arsenic occurrence. Though these models have limitations, they allow for arsenic hazard assessment across the region. The introduction of well-type (public or private), well depth, and casing length as explanatory variables may be appropriate measures to improve model performance. Our findings indicate that the original models generalize to the testing dataset, and should continue to serve as an important vehicle of preventative public health that may be applied to other groundwater contaminants in New Hampshire.","language":"English","publisher":"Wiley","doi":"10.1111/j.1936-704X.2017.03238.x","usgsCitation":"Andy, C., Fahnestock, M.F., Lombard, M.A., Hayes, L., Bryce, J., and Ayotte, J.D., 2017, Assessing models of arsenic occurrence in drinking water from bedrock aquifers in New Hampshire: Journal of Contemporary Water Research and Education, v. 160, no. 1, p. 25-41, https://doi.org/10.1111/j.1936-704X.2017.03238.x.","productDescription":"17 p.","startPage":"25","endPage":"41","ipdsId":"IP-078863","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":469389,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1936-704x.2017.03238.x","text":"Publisher Index 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,{"id":70192341,"text":"70192341 - 2017 - Groundwater-level trends in the U.S. glacial aquifer system, 1964-2013","interactions":[],"lastModifiedDate":"2017-11-06T15:23:39","indexId":"70192341","displayToPublicDate":"2017-10-25T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Groundwater-level trends in the U.S. glacial aquifer system, 1964-2013","docAbstract":"The glacial aquifer system in the United States is a major source of water supply but previous work on historical groundwater trends across the system is lacking. Trends in annual minimum, mean, and maximum groundwater levels for 205 monitoring wells were analyzed across three regions of the system (East, Central, West Central) for four time periods: 1964-2013, 1974-2013, 1984-2013, and 1994-2013. Trends were computed separately for wells in the glacial aquifer system with low potential for human influence on groundwater levels and ones with high potential influence from activities such as groundwater pumping. Generally there were more wells with significantly increasing groundwater levels (levels closer to ground surface) than wells with significantly decreasing levels. The highest numbers of significant increases for all four time periods were with annual minimum and/or mean levels. There were many more wells with significant increases from 1964 to 2013 than from more recent periods, consistent with low precipitation in the 1960s. Overall there were low numbers of wells with significantly decreasing trends regardless of time period considered; the highest number of these were generally for annual minimum groundwater levels at wells with likely human influence. There were substantial differences in the number of wells with significant groundwater-level trends over time, depending on whether the historical time series are assumed to be independent, have short-term persistence, or have long-term persistence. Mean annual groundwater levels have significant lag-one-year autocorrelation at 26.0% of wells in the East region, 65.4% of wells in the Central region, and 100% of wells in the West Central region. Annual precipitation across the glacial aquifer system, on the other hand, has significant autocorrelation at only 5.5% of stations, about the percentage expected due to chance.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2017.07.055","usgsCitation":"Hodgkins, G.A., Dudley, R.W., Nielsen, M.G., Renard, B., and Qi, S.L., 2017, Groundwater-level trends in the U.S. glacial aquifer system, 1964-2013: Journal of Hydrology, v. 553, p. 289-303, https://doi.org/10.1016/j.jhydrol.2017.07.055.","productDescription":"15 p.","startPage":"289","endPage":"303","ipdsId":"IP-081195","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":461379,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2017.07.055","text":"Publisher Index Page"},{"id":347310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70192135,"text":"sir20175091 - 2017 - Simulation of daily streamflow for 12 river basins in western Iowa using the Precipitation-Runoff Modeling System","interactions":[],"lastModifiedDate":"2017-10-24T15:14:56","indexId":"sir20175091","displayToPublicDate":"2017-10-24T14:45:00","publicationYear":"2017","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":"2017-5091","title":"Simulation of daily streamflow for 12 river basins in western Iowa using the Precipitation-Runoff Modeling System","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, constructed Precipitation-Runoff Modeling System models to estimate daily streamflow for 12 river basins in western Iowa that drain into the Missouri River. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of streamflow and general drainage basin hydrology to various combinations of climate and land use. Calibration periods for each basin varied depending on the period of record available for daily mean streamflow measurements at U.S. Geological Survey streamflow-gaging stations.</p><p>A geographic information system tool was used to delineate each basin and estimate initial values for model parameters based on basin physical and geographical features. A U.S. Geological Survey automatic calibration tool that uses a shuffled complex evolution algorithm was used for initial calibration, and then manual modifications were made to parameter values to complete the calibration of each basin model. The main objective of the calibration was to match daily discharge values of simulated streamflow to measured daily discharge values. The Precipitation-Runoff Modeling System model was calibrated at 42 sites located in the 12 river basins in western Iowa.</p><p>The accuracy of the simulated daily streamflow values at the 42 calibration sites varied by river and by site. The models were satisfactory at 36 of the sites based on statistical results. Unsatisfactory performance at the six other sites can be attributed to several factors: (1) low flow, no flow, and flashy flow conditions in headwater subbasins having a small drainage area; (2) poor representation of the groundwater and storage components of flow within a basin; (3) lack of accounting for basin withdrawals and water use; and (4) limited availability and accuracy of meteorological input data. The Precipitation-Runoff Modeling System models of 12 river basins in western Iowa will provide water-resource managers with a consistent and documented method for estimating streamflow at ungaged sites and aid in environmental studies, hydraulic design, water management, and water-quality projects.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175091","collaboration":"Prepared in cooperation with the Iowa Department of Natural Resources","usgsCitation":"Christiansen, D.E., Haj, A.E., and Risely, J.C., 2017, Simulation of daily streamflow for 12 river basins in western Iowa using the Precipitation-Runoff Modeling System: U.S. Geological Survey Scientific Investigations Report 2017–5091, 27 p., https://doi.org/10.3133/sir20175091. 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href=\"mailto:dc_ia@usgs.gov\" data-mce-href=\"mailto:dc_ia@usgs.gov\">Director</a>, <a href=\"https://ia.water.usgs.gov/\" data-mce-href=\"https://ia.water.usgs.gov/\">Iowa Water Science Center</a><br> U.S. Geological Survey<br> P.O. Box 1230<br> Iowa City, IA 52240</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Model Development</li><li>Simulation of Daily Streamflow for 12 River Basins in Western Iowa Using the Precipitation-Runoff Modeling System</li><li>Model Limitations</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2017-10-24","noUsgsAuthors":false,"publicationDate":"2017-10-24","publicationStatus":"PW","scienceBaseUri":"59f0511be4b0220bbd9a1d48","contributors":{"authors":[{"text":"Christiansen, Daniel E. 0000-0001-6108-2247 dechrist@usgs.gov","orcid":"https://orcid.org/0000-0001-6108-2247","contributorId":366,"corporation":false,"usgs":true,"family":"Christiansen","given":"Daniel","email":"dechrist@usgs.gov","middleInitial":"E.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haj, Adel E. 0000-0002-3377-7161 ahaj@usgs.gov","orcid":"https://orcid.org/0000-0002-3377-7161","contributorId":175220,"corporation":false,"usgs":true,"family":"Haj","given":"Adel E.","email":"ahaj@usgs.gov","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":false,"id":714363,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Risley, John C. 0000-0002-8206-5443 jrisley@usgs.gov","orcid":"https://orcid.org/0000-0002-8206-5443","contributorId":2698,"corporation":false,"usgs":true,"family":"Risley","given":"John","email":"jrisley@usgs.gov","middleInitial":"C.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714362,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191811,"text":"70191811 - 2017 - Riverine discharges to Chesapeake Bay: Analysis of long-term (1927–2014) records and implications for future flows in the Chesapeake Bay basin","interactions":[],"lastModifiedDate":"2017-10-24T14:07:39","indexId":"70191811","displayToPublicDate":"2017-10-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Riverine discharges to Chesapeake Bay: Analysis of long-term (1927–2014) records and implications for future flows in the Chesapeake Bay basin","docAbstract":"<p><span>The Chesapeake Bay (CB) basin is under a total maximum daily load (TMDL) mandate to reduce nitrogen, phosphorus, and sediment loads to the bay. Identifying shifts in the hydro-climatic regime may help explain observed trends in water quality. To identify potential shifts, hydrologic data (1927–2014) for 27 watersheds in the CB basin were analyzed to determine the relationships among long-term precipitation and stream discharge trends. The amount, frequency, and intensity of precipitation increased from 1910 to 1996 in the eastern U.S., with the observed increases greater in the northeastern U.S. than the southeastern U.S. The CB watershed spans the north-to-south gradient in precipitation increases, and hydrologic differences have been observed in watersheds north relative to watersheds south of the Pennsylvania—Maryland (PA-MD) border. Time series of monthly mean precipitation data specific to each of 27 watersheds were derived from the Precipitation-elevation Regression on Independent Slopes Model (PRISM) dataset, and monthly mean stream-discharge data were obtained from U.S. Geological Survey streamgage records. All annual precipitation trend slopes in the 18 watersheds north of the PA-MD border were greater than or equal to those of the nine south of that border. The magnitude of the trend slopes for 1927–2014 in both precipitation and discharge decreased in a north-to-south pattern. Distributions of the monthly precipitation and discharge datasets were assembled into percentiles for each year for each watershed. Multivariate correlation of precipitation and discharge within percentiles among the groups of northern and southern watersheds indicated only weak associations. Regional-scale average behaviors of trends in the distribution of precipitation and discharge annual percentiles differed between the northern and southern watersheds. In general, the linkage between precipitation and discharge was weak, with the linkage weaker in the northern watersheds compared to those in the south. On the basis of simple linear regression, 26 of the 27 watersheds are projected to have higher annual mean discharge in 2025, the target date for implementation of the TMDL for the CB basin.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2017.08.057","usgsCitation":"Rice, K.C., Moyer, D.L., and Mills, A., 2017, Riverine discharges to Chesapeake Bay: Analysis of long-term (1927–2014) records and implications for future flows in the Chesapeake Bay basin: Journal of Environmental Management, v. 204, no. 1, p. 246-254, https://doi.org/10.1016/j.jenvman.2017.08.057.","productDescription":"9 p.","startPage":"246","endPage":"254","ipdsId":"IP-078770","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":461383,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2017.08.057","text":"Publisher Index 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,{"id":70191347,"text":"sir20175120 - 2017 - Assessment of an in-channel redistribution technique for large woody debris management in Locust Creek, Linn County, Missouri","interactions":[],"lastModifiedDate":"2017-10-25T10:10:26","indexId":"sir20175120","displayToPublicDate":"2017-10-24T00:00:00","publicationYear":"2017","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":"2017-5120","title":"Assessment of an in-channel redistribution technique for large woody debris management in Locust Creek, Linn County, Missouri","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the Missouri Department of Conservation and Missouri Department of Natural Resources, completed a study to assess a mechanical redistribution technique used for the management of large woody debris (LWD) jams in Locust Creek within Pershing State Park and Fountain Grove Conservation Area, Linn County, Missouri. Extensive LWD jams were treated from 1996 to 2009 using a low-impact technique in which LWD from the jams was redistributed to reopen the channel and to mimic the natural geomorphic process of channel migration and adjustment to an obstruction. The scope of the study included the comparison of selected channel geometry characteristics and bed material particle-size distribution in seven LWD treatment reaches with that of adjacent untreated reaches (unaffected by LWD accumulations) of Locust Creek. A comparison of 1996 and 2015 survey cross sections in treated and untreated reaches and photograph documentation were used to assess channel geomorphic change and the stability of redistributed LWD. The physical characteristics of LWD within jams present in the study reach during 2015–16 also were documented.</p><p>Based on the general lack of differences in channel metrics between treated and untreated reaches, it can be concluded that the mechanical redistribution technique has been an effective treatment of extensive LWD jams in Locust Creek. Channel alterations, including aggradation, streamflow piracy, and diversions, have resulted in temporal and spatial changes in the Locust Creek channel that may affect future applications of the redistribution technique in Pershing State Park. The redistribution technique was used to effectively manage LWD in Locust Creek at a potentially lower financial cost and reduced environmental disturbance than the complete removal of LWD.</p><p>A comparison of four channel metrics (bankfull cross-sectional area, channel width, streamflow capacity, and width-depth ratio) for individual treatment reaches with adjacent untreated reaches indicated no statistically significant difference in most comparisons. Where statistically significant differences in channel metrics were determined between&nbsp;individual reaches, the channel metrics in treatment reaches were significantly less than adjacent untreated reaches in some comparisons, and significantly greater than adjacent untreated reaches in others. Without immediate posttreatment cross sections in treated and untreated reaches for comparison, it is impossible to say with certainty that a lack of significant differences in channel metrics is a result of posttreatment channel adjustment or, conversely, that any significant differences that remain are a result of the treatment of LWD.</p><p>Characteristics of LWD in accumulations sampled within the study area in 2015 indicate that most sampled pieces were in the 1–2 foot diameter size class, the 5–16 foot length class, and the advanced decay class. Most of documented LWD pieces were loose and not buried, about 20 percent on average had a root wad attached, and about 6.5 percent on average were sawn logs. Most of sampled material was less than one-half of the bankfull channel width, indicating it was easily transportable, and the advanced decay class of material entering the study area indicated that it was likely sourced from outside of Pershing State Park.</p><p>Redistributed LWD associated with treatment seems to be intact in the 1996 treated reaches from direct observation and from inference because there was net channel aggradation between 1996 and 2015 in comparison surveys. The change in channel area resulting from aggradation in time (1996 to 2015) in treated and untreated reaches exceeded the differences in channel characteristics between the treated and untreated channels in 2015 surveys.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175120","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources and the Missouri Department of Conservation","usgsCitation":"Heimann, D.C., 2017, Assessment of an in-channel redistribution technique for large woody debris management in Locust Creek, Linn County, Missouri: U.S. Geological Survey Scientific Investigations Report 2017–5120, 25 p., https://doi.org/10.3133/sir20175120.","productDescription":"Report: iv, 25 p.; 2 Tables","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-088058","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":347231,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5120/sir20175120_table4.xlsx","text":"Table 4","size":"64.3 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5120 Table 4"},{"id":347232,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5120/sir20175120_table6.xlsx","text":"Table 6","size":"26.3 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5120 Table 6"},{"id":347229,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5120/coverthb.jpg"},{"id":347230,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5120/sir20175120.pdf","text":"Report","size":"1.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5120"}],"country":"United States","state":"Missouri","county":"Linn County","otherGeospatial":"Locust Creek","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-92.8474,40.0392],[-92.8607,39.7009],[-92.9737,39.7033],[-93.0843,39.7069],[-93.1997,39.704],[-93.2595,39.7037],[-93.3067,39.7038],[-93.3683,39.7039],[-93.3643,39.9678],[-93.3638,40.0335],[-92.8534,40.0392],[-92.8474,40.0392]]]},\"properties\":{\"name\":\"Linn\",\"state\":\"MO\"}}]}","contact":"<p><a href=\"mailto: dc_mo@usgs.gov\" data-mce-href=\"mailto: dc_mo@usgs.gov\">Director</a>,&nbsp;<a href=\"https://mo.water.usgs.gov\" data-mce-href=\"https://mo.water.usgs.gov\">Missouri Water Science Center</a> <br>U.S. Geological Survey<br>1400 Independence Road <br>Rolla, MO 65401</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Methods<br></li><li>Assessment of In-Channel Large Woody Debris Redistribution Technique<br></li><li>Summary and Conclusions<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2017-10-24","noUsgsAuthors":false,"publicationDate":"2017-10-24","publicationStatus":"PW","scienceBaseUri":"59f05120e4b0220bbd9a1d77","contributors":{"authors":[{"text":"Heimann, David C. 0000-0003-0450-2545 dheimann@usgs.gov","orcid":"https://orcid.org/0000-0003-0450-2545","contributorId":3822,"corporation":false,"usgs":true,"family":"Heimann","given":"David","email":"dheimann@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712030,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70192253,"text":"70192253 - 2017 - A coupled metabolic-hydraulic model and calibration scheme for estimating of whole-river metabolism during dynamic flow conditions","interactions":[],"lastModifiedDate":"2017-10-26T09:38:40","indexId":"70192253","displayToPublicDate":"2017-10-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2622,"text":"Limnology and Oceanography: Methods","active":true,"publicationSubtype":{"id":10}},"title":"A coupled metabolic-hydraulic model and calibration scheme for estimating of whole-river metabolism during dynamic flow conditions","docAbstract":"Conventional methods for estimating whole-stream metabolic rates from measured dissolved oxygen dynamics do not account for the variation in solute transport times created by dynamic flow conditions.  Changes in flow at hourly time scales are common downstream of hydroelectric dams (i.e. hydropeaking), and hydrologic limitations of conventional metabolic models have resulted in a poor understanding of the controls on biological production in these highly managed river ecosystems.  To overcome these limitations, we coupled a two-station metabolic model of dissolved oxygen dynamics with a hydrologic river routing model.  We designed calibration and parameter estimation tools to infer values for hydrologic and metabolic parameters based on time series of water quality data, achieving the ultimate goal of estimating whole-river gross primary production and ecosystem respiration during dynamic flow conditions.  Our case study data for model design and calibration were collected in the tailwater of Glen Canyon Dam (Arizona, USA), a large hydropower facility where the mean discharge was 325 m3 s 1 and the average daily coefficient of variation of flow was 0.17 (i.e. the hydropeaking index averaged from 2006 to 2016).  We demonstrate the coupled model’s conceptual consistency with conventional models during steady flow conditions, and illustrate the potential bias in metabolism estimates with conventional models during unsteady flow conditions.  This effort contributes an approach to solute transport modeling and parameter estimation that allows study of whole-ecosystem metabolic regimes across a more diverse range of hydrologic conditions commonly encountered in streams and rivers.","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography (ASLO)","doi":"10.1002/lom3.10204","usgsCitation":"Payn, R.A., Hall, R.O., Kennedy, T.A., Poole, G.C., and Marshall, L.A., 2017, A coupled metabolic-hydraulic model and calibration scheme for estimating of whole-river metabolism during dynamic flow conditions: Limnology and Oceanography: Methods, v. 15, no. 10, p. 847-866, https://doi.org/10.1002/lom3.10204.","productDescription":"20 p.","startPage":"847","endPage":"866","ipdsId":"IP-083968","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469411,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lom3.10204","text":"Publisher Index Page"},{"id":438182,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76T0KG2","text":"USGS data release","linkHelpText":"Metabolic-hydraulic modelData"},{"id":347212,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Glen Canyon Dam","volume":"15","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-28","publicationStatus":"PW","scienceBaseUri":"59f0511ee4b0220bbd9a1d60","contributors":{"authors":[{"text":"Payn, Robert A.","contributorId":127363,"corporation":false,"usgs":false,"family":"Payn","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":6765,"text":"Montana State University, Department of Land Resources and Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":715019,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hall, Robert O","contributorId":198078,"corporation":false,"usgs":false,"family":"Hall","given":"Robert","email":"","middleInitial":"O","affiliations":[],"preferred":false,"id":715020,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, Theodore A. 0000-0003-3477-3629 tkennedy@usgs.gov","orcid":"https://orcid.org/0000-0003-3477-3629","contributorId":167537,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore","email":"tkennedy@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":715018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poole, Geoff C","contributorId":198079,"corporation":false,"usgs":false,"family":"Poole","given":"Geoff","email":"","middleInitial":"C","affiliations":[],"preferred":false,"id":715021,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marshall, Lucy A. 0000-0003-0450-4292","orcid":"https://orcid.org/0000-0003-0450-4292","contributorId":198080,"corporation":false,"usgs":false,"family":"Marshall","given":"Lucy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":715022,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70192267,"text":"70192267 - 2017 - Movements of Atlantic Sturgeon of the Gulf of Maine inside and outside the geographically defined Distinct Population Segment","interactions":[],"lastModifiedDate":"2017-10-24T11:07:48","indexId":"70192267","displayToPublicDate":"2017-10-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2680,"text":"Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science","active":true,"publicationSubtype":{"id":10}},"title":"Movements of Atlantic Sturgeon of the Gulf of Maine inside and outside the geographically defined Distinct Population Segment","docAbstract":"Identification of potential critical habitat, seasonal distributions, and movements within and between river systems is important for protecting the Gulf of Maine (GOM) Distinct Population Segment of Atlantic Sturgeon.  To accomplish these objectives, we captured Atlantic Sturgeon in four GOM rivers (Penobscot, Kennebec system, Saco, and Merrimack), and tagged 144 (83.3–217.4 cm TL) internally with uniquely coded acoustic transmitters.  Tagged fish were detected between 2006 to 2014 by primary receiver arrays deployed in the four GOM rivers or opportunistically on a secondary group of receivers deployed within the GOM and along the continental shelf.  Atlantic Sturgeon tagged in the four rivers were documented at three spawning areas in the Kennebec system in June and July, including one that became accessible in 1999 when the Edwards Dam was removed.  After being tagged, the majority (74%) of Atlantic sturgeon were detected in the estuaries of the four GOM rivers, primarily from May through October.  Tagged fish spent most of their time in saline water in the Saco River and Merrimack River, moved into brackish water in the Penobscot River, and were found in saline, brackish, and fresh water in the Kennebec system.  Approximately 70% of the tagged fish were detected in GOM coastal waters, and aggregated in the Bay of Fundy (May–January), offshore of the Penobscot River (September-February and May), offshore of the Kennebec River (September–February), in Saco Bay and the Scarborough River (July–November), and along the eastern Massachusetts coast between Cape Ann and Cape Cod (April–February).  Nine tagged Atlantic sturgeon (7%) left the GOM, three of which moved as far north as Halifax in Canada and six moved as far south as the James River in Virginia.  Information from this study will be used to make recommendations to avoid, reduce or mitigate the impacts of in-water projects and on Atlantic sturgeon.","language":"English","publisher":"Taylor & Francis","doi":"10.1080/19425120.2016.1271845","usgsCitation":"Wippelhauser, G.S., Sulikowski, J., Zydlewski, G.B., Altenritter, M., Kieffer, M., and Kinnison, M.T., 2017, Movements of Atlantic Sturgeon of the Gulf of Maine inside and outside the geographically defined Distinct Population Segment: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 9, p. 93-107, https://doi.org/10.1080/19425120.2016.1271845.","productDescription":"15 p.","startPage":"93","endPage":"107","ipdsId":"IP-077082","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":469408,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/19425120.2016.1271845","text":"Publisher Index Page"},{"id":347186,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine, Massachusetts, New Hampshire","otherGeospatial":"Gulf of Maine","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -71.444091796875,\n              41.17038447781618\n            ],\n            [\n              -63.10546874999999,\n              41.17038447781618\n            ],\n            [\n              -63.10546874999999,\n              46.05036097561633\n            ],\n            [\n              -71.444091796875,\n              46.05036097561633\n            ],\n            [\n              -71.444091796875,\n              41.17038447781618\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-10","publicationStatus":"PW","scienceBaseUri":"59f0511de4b0220bbd9a1d57","contributors":{"authors":[{"text":"Wippelhauser, Gail S.","contributorId":169680,"corporation":false,"usgs":false,"family":"Wippelhauser","given":"Gail","email":"","middleInitial":"S.","affiliations":[{"id":25571,"text":"Maine Department of Marine Resources, Augusta, ME","active":true,"usgs":false}],"preferred":false,"id":715067,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sulikowski, James","contributorId":197218,"corporation":false,"usgs":false,"family":"Sulikowski","given":"James","email":"","affiliations":[],"preferred":false,"id":715068,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zydlewski, Gayle B.","contributorId":169688,"corporation":false,"usgs":false,"family":"Zydlewski","given":"Gayle","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":715069,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Altenritter, Megan","contributorId":198093,"corporation":false,"usgs":false,"family":"Altenritter","given":"Megan","affiliations":[],"preferred":false,"id":715070,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kieffer, Micah 0000-0001-9310-018X mkieffer@usgs.gov","orcid":"https://orcid.org/0000-0001-9310-018X","contributorId":2641,"corporation":false,"usgs":true,"family":"Kieffer","given":"Micah","email":"mkieffer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":715066,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kinnison, Michael T.","contributorId":169617,"corporation":false,"usgs":false,"family":"Kinnison","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":715071,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70192261,"text":"70192261 - 2017 - Declines revisited: Long-term recovery and spatial population dynamics oftailed frog larvae after wildfire","interactions":[],"lastModifiedDate":"2017-10-24T10:54:06","indexId":"70192261","displayToPublicDate":"2017-10-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Declines revisited: Long-term recovery and spatial population dynamics oftailed frog larvae after wildfire","docAbstract":"<p>Drought has fueled an increased frequency and severity of large wildfires in many ecosystems. Despite an increase in research on wildfire effects on vertebrates, the vast majority of it has focused on short-term (&lt; 5 years) effects and there is still little information on the time scale of population recovery for species that decline in abundance after fire. In 2003, a large wildfire in Montana (USA) burned the watersheds of four of eight streams that we sampled for larval Rocky Mountain tailed frogs (<i>Ascaphus montanus</i>) in 2001. Surveys during 2004–2005 revealed reduced abundance of larvae in burned streams relative to unburned streams, with greater declines associated with increased fire extent. Rocky Mountain tailed frogs have low vagility and have several unusual life-history traits that could slow population recovery, including an extended larval period (4 years), delayed sexual maturity (6–8 years), and low fecundity (&lt; 50 eggs/year). To determine if abundance remained depressed since the 2003 wildfire, we repeated surveys during 2014–2015 and found relative abundance of larvae in burned and unburned streams had nearly converged to pre-fire conditions within two generations. The negative effects of burn extent on larval abundance weakened&gt; 58% within 12 years after the fire. We also found moderate synchrony among populations in unburned streams and negative spatial autocorrelation among populations in burned streams. We suspect negative spatial autocorrelation among spatially-clustered burned streams reflected increased post-fire patchiness in resources and different rates of local recovery. Our results add to a growing body of work that suggests populations in intact ecosystems tend to be resilient to habitat changes caused by wildfire. Our results also provide important insights into recovery times of populations that have been negatively affected by severe wildfire.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2017.06.022","usgsCitation":"Hossack, B.R., and Honeycutt, R.K., 2017, Declines revisited: Long-term recovery and spatial population dynamics oftailed frog larvae after wildfire: Biological Conservation, v. 212, no. A, p. 274-278, https://doi.org/10.1016/j.biocon.2017.06.022.","productDescription":"5 p.","startPage":"274","endPage":"278","ipdsId":"IP-083575","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":469407,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2017.06.022","text":"Publisher Index Page"},{"id":347204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Flathead National Forest, Glacier National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.17953491210938,\n              48.22284281261854\n            ],\n            [\n              -113.22235107421874,\n              48.22284281261854\n            ],\n            [\n              -113.22235107421874,\n              48.826757381274426\n            ],\n            [\n              -114.17953491210938,\n              48.826757381274426\n            ],\n            [\n              -114.17953491210938,\n              48.22284281261854\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"212","issue":"A","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f0511ee4b0220bbd9a1d5b","contributors":{"authors":[{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":715048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Honeycutt, R. Ken 0000-0002-7157-7195 rhoneycutt@usgs.gov","orcid":"https://orcid.org/0000-0002-7157-7195","contributorId":156282,"corporation":false,"usgs":true,"family":"Honeycutt","given":"R.","email":"rhoneycutt@usgs.gov","middleInitial":"Ken","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":715049,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70192094,"text":"70192094 - 2017 - Estimation and uncertainty of recent carbon accumulation and vertical accretion in drained and undrained forested peatlands of the southeastern USA","interactions":[],"lastModifiedDate":"2017-11-10T14:08:09","indexId":"70192094","displayToPublicDate":"2017-10-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Estimation and uncertainty of recent carbon accumulation and vertical accretion in drained and undrained forested peatlands of the southeastern USA","docAbstract":"<p><span>The purpose of this study was to determine how drainage impacts carbon densities and recent rates (past 50&nbsp;years) of vertical accretion and carbon accumulation in southeastern forested peatlands. We compared these parameters in drained maple-gum (MAPL), Atlantic white cedar (CDR), and pocosin (POC) communities in the Great Dismal Swamp National Wildlife Refuge (GDS) of Virginia/North Carolina and in an intact (undrained) CDR swamp in the Alligator River National Wildlife Refuge (AR) of North Carolina. Peat cores were analyzed for bulk density, percent organic carbon, and&nbsp;</span><sup>137</sup><span>Cs and<span>&nbsp;</span></span><sup>210</sup><span>Pb. An uncertainty analysis of both<span>&nbsp;</span></span><sup>137</sup><span>Cs and<span>&nbsp;</span></span><sup>210</sup><span>Pb approaches was used to constrain error at least partially related to mobility of both radioisotopes. GDS peats had lower porosities (89.6% (SD&nbsp;=&nbsp;1.71) versus 95.3% (0.18)) and higher carbon densities (0.082 (0.021) versus 0.037 (0.009)&nbsp;g&nbsp;C&nbsp;cm</span><sup>−3</sup><span>) than AR. Vertical accretion rates (0.10–0.56&nbsp;cm&nbsp;yr</span><sup>−1</sup><span>) were used to estimate a time period of ~84–362&nbsp;years for reestablishment of peat lost during the 2011 Lateral West fire at the GDS. Carbon accumulation rates ranged from 51 to 389&nbsp;g&nbsp;C&nbsp;m</span><sup>−2</sup><span>&nbsp;yr</span><sup>−1</sup><span><span>&nbsp;</span>for all sites. In the drained (GDS) versus intact (AR) CDR sites, carbon accumulation rates were similar with<span>&nbsp;</span></span><sup>137</sup><span>Cs (87</span><sub>GDS</sub><span><span>&nbsp;</span>versus 92</span><sub>AR</sub><span>&nbsp;g&nbsp;C&nbsp;m</span><sup>−2</sup><span>&nbsp;yr</span><sup>−1</sup><span>) and somewhat less at the GDS than AR as determined with<span>&nbsp;</span></span><sup>210</sup><span>Pb (111</span><sub>GDS</sub><span><span>&nbsp;</span>versus 159</span><sub>AR</sub><span>&nbsp;g&nbsp;C&nbsp;m</span><sup>−2</sup><span>&nbsp;yr</span><sup>−1</sup><span>). Heightened productivity and high polyphenol content of peat may be responsible for similar rates of carbon accumulation in both drained and intact CDR peatlands.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/2017JG003950","usgsCitation":"Drexler, J.Z., Fuller, C.C., Orlando, J.L., Salas, A., Wurster, F.C., and Duberstein, J., 2017, Estimation and uncertainty of recent carbon accumulation and vertical accretion in drained and undrained forested peatlands of the southeastern USA: Journal of Geophysical Research: Biogeosciences, v. 122, no. 10, p. 2563-2579, https://doi.org/10.1002/2017JG003950.","productDescription":"17 p.","startPage":"2563","endPage":"2579","ipdsId":"IP-087162","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":461381,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jg003950","text":"Publisher Index Page"},{"id":347238,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Alligator Rivers National Wildlife Refuge, Great Dismal Swamp Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.5582275390625,\n              36.43233216371692\n            ],\n            [\n              -76.34811401367188,\n              36.43233216371692\n            ],\n            [\n              -76.34811401367188,\n              36.76969233214548\n            ],\n            [\n              -76.5582275390625,\n              36.76969233214548\n            ],\n            [\n              -76.5582275390625,\n              36.43233216371692\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.9167,\n              35.8167\n            ],\n            [\n              -75.8917,\n              35.8167\n            ],\n            [\n              -75.8917,\n              35.85\n            ],\n            [\n              -75.9167,\n              35.85\n            ],\n            [\n              -75.9167,\n              35.8167\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"122","issue":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-17","publicationStatus":"PW","scienceBaseUri":"59f0511fe4b0220bbd9a1d6a","contributors":{"authors":[{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":714198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":714199,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orlando, James L. 0000-0002-0099-7221 jorlando@usgs.gov","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":190788,"corporation":false,"usgs":true,"family":"Orlando","given":"James","email":"jorlando@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714200,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Salas, Antonia 0000-0002-5163-4105 asalas@usgs.gov","orcid":"https://orcid.org/0000-0002-5163-4105","contributorId":194433,"corporation":false,"usgs":true,"family":"Salas","given":"Antonia","email":"asalas@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714201,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wurster, Frederic C. 0000-0002-5393-2878 fred_wurster@fws.gov","orcid":"https://orcid.org/0000-0002-5393-2878","contributorId":74301,"corporation":false,"usgs":true,"family":"Wurster","given":"Frederic","email":"fred_wurster@fws.gov","middleInitial":"C.","affiliations":[],"preferred":false,"id":714202,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Duberstein, Jamie A.","contributorId":91007,"corporation":false,"usgs":false,"family":"Duberstein","given":"Jamie A.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":714203,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70192262,"text":"70192262 - 2017 - Widespread legacy brine contamination from oil production reduces survival of chorus frog larvae","interactions":[],"lastModifiedDate":"2018-01-23T11:48:42","indexId":"70192262","displayToPublicDate":"2017-10-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Widespread legacy brine contamination from oil production reduces survival of chorus frog larvae","docAbstract":"<p><span>Advances in drilling techniques have facilitated a rapid increase in hydrocarbon extraction from energy shales, including the Williston Basin in central North America. This area overlaps with the Prairie Pothole Region, a region densely populated with wetlands that provide numerous ecosystem services. Historical (legacy) disposal practices often released saline co-produced waters (brines) with high chloride concentrations, affecting wetland water quality directly or persisting in sediments. Despite the potential threat of brine contamination to aquatic habitats, there has been little research into its ecological effects. We capitalized on a gradient of legacy brine-contaminated wetlands in northeast Montana to conduct laboratory experiments to assess variation in survival of larval Boreal Chorus Frogs (</span><i>Pseudacris maculata</i><span>) reared on sediments from 3 local wetlands and a control source. To help provide environmental context for the experiment, we also measured chloride concentrations in 6 brine-contaminated wetlands in our study area, including the 2 contaminated sites used for sediment exposures. Survival of frog larvae during 46- and 55-day experiments differed by up to 88% among sediment sources (Site Model) and was negatively correlated with potential chloride exposure (Chloride Model). Five of the 6 contaminated wetlands exceeded the U.S. EPA acute benchmark for chloride in freshwater (860&nbsp;mg/L) and all exceeded the chronic benchmark (230&nbsp;mg/L). However, the Wetland Site model explained more variation in survival than the Chloride Model, suggesting that chloride concentration alone does not fully reflect the threat of contamination to aquatic species. Because the profiles of brine-contaminated sediments are complex, further surveys and experiments are needed across a broad range of conditions, especially where restoration or remediation actions have reduced brine-contamination. Information provided by this study can help quantify potential ecological threats and help land managers prioritize conservation strategies as part of responsible and sustainable energy development.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2017.08.070","usgsCitation":"Hossack, B.R., Puglis, H.J., Battaglin, W.A., Anderson, C.W., Honeycutt, R.K., and Smalling, K.L., 2017, Widespread legacy brine contamination from oil production reduces survival of chorus frog larvae: Environmental Pollution, v. 231, no. 1, p. 742-751, https://doi.org/10.1016/j.envpol.2017.08.070.","productDescription":"12 p.","startPage":"742","endPage":"751","ipdsId":"IP-087168","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":469410,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2017.08.070","text":"Publisher Index Page"},{"id":438183,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74T6GVD","text":"USGS data release","linkHelpText":"Widespread Legacy Brine Contamination from Oil Shales Reduces Survival of Chorus Frog Larvae-Data"},{"id":347201,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota, South Dakota","otherGeospatial":"Prairie Pothole Region, Williston Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.939453125,\n              42.391008609205045\n            ],\n            [\n              -97.470703125,\n              42.391008609205045\n            ],\n            [\n              -97.470703125,\n              48.980216985374994\n            ],\n            [\n              -112.939453125,\n              48.980216985374994\n            ],\n            [\n              -112.939453125,\n              42.391008609205045\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"231","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f0511de4b0220bbd9a1d59","contributors":{"authors":[{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":715050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Puglis, Holly J. 0000-0002-3090-6597 hpuglis@usgs.gov","orcid":"https://orcid.org/0000-0002-3090-6597","contributorId":4686,"corporation":false,"usgs":true,"family":"Puglis","given":"Holly","email":"hpuglis@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":715051,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Battaglin, William A. 0000-0001-7287-7096 wbattagl@usgs.gov","orcid":"https://orcid.org/0000-0001-7287-7096","contributorId":1527,"corporation":false,"usgs":true,"family":"Battaglin","given":"William","email":"wbattagl@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":715052,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Chauncey W. 0000-0002-1016-3781 chauncey@usgs.gov","orcid":"https://orcid.org/0000-0002-1016-3781","contributorId":140160,"corporation":false,"usgs":true,"family":"Anderson","given":"Chauncey","email":"chauncey@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":715053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Honeycutt, R. Ken 0000-0002-7157-7195 rhoneycutt@usgs.gov","orcid":"https://orcid.org/0000-0002-7157-7195","contributorId":156282,"corporation":false,"usgs":true,"family":"Honeycutt","given":"R.","email":"rhoneycutt@usgs.gov","middleInitial":"Ken","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":715054,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smalling, Kelly L. 0000-0002-1214-4920 ksmall@usgs.gov","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":190789,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly","email":"ksmall@usgs.gov","middleInitial":"L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":715055,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70192284,"text":"70192284 - 2017 - A effective DNA vaccine against diverse genotype J infectious hematopoietic necrosis virus strains prevalent in China","interactions":[],"lastModifiedDate":"2017-10-25T09:41:01","indexId":"70192284","displayToPublicDate":"2017-10-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3673,"text":"Vaccine","active":true,"publicationSubtype":{"id":10}},"title":"A effective DNA vaccine against diverse genotype J infectious hematopoietic necrosis virus strains prevalent in China","docAbstract":"Infectious hematopoietic necrosis virus (IHNV) is the most important pathogen threatening the aquaculture of salmonid fish in China. In this study, a DNA vaccine, designated pIHNch-G, was constructed with the glycoprotein (G) gene of a Chinese IHNV isolate SD-12 (also called Sn1203) of genotype J. The minimal dose of vaccine required, the expression of the Mx-1 gene in the muscle (vaccine delivery site) and anterior kidney, and the titers of the neutralizing antibodies produced were used to evaluate the vaccine efficacy. To assess the potential utility of the vaccine in controlling IHNV throughout China, the cross protective efficacy of the vaccine was determined by challenging fish with a broad range of IHNV strains from different geographic locations in China. A single 100 ng dose of the vaccine conferred almost full protection to rainbow trout fry (3 g) against waterborne or intraperitoneal injection challenge with IHNV strain SD-12 as early as 4 days post-vaccination (d.p.v.), and significant protection was still observed at 180 d.p.v. Intragenogroup challenges showed that the DNA vaccine provided similar protection to the fish against all the Chinese IHNV isolates tested, suggesting that the vaccine can be widely used in China. Mx-1 gene expression was significantly upregulated in the muscle tissue (vaccine delivery site) and anterior kidney in the vaccinated rainbow trout at both 4 and 7 d.p.v. Similar levels of neutralizing antibodies were determined with each of the Chinese IHNV strains at 60 and 180 d.p.v. This DNA vaccine should play an important role in the control of IHN in China.","language":"English","publisher":"Elsevier","doi":"10.1016/j.vaccine.2017.03.047","usgsCitation":"Xu, L., Zhao, J., Liu, M., Kurath, G., Ren, G., LaPatra, S.E., Yin, J., Liu, H., Feng, J., and Lu, T., 2017, A effective DNA vaccine against diverse genotype J infectious hematopoietic necrosis virus strains prevalent in China: Vaccine, v. 35, no. 18, p. 2420-2426, https://doi.org/10.1016/j.vaccine.2017.03.047.","productDescription":"7 p.","startPage":"2420","endPage":"2426","ipdsId":"IP-086021","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":469413,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.vaccine.2017.03.047","text":"Publisher Index Page"},{"id":347210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[110.33919,18.6784],[109.47521,18.1977],[108.65521,18.50768],[108.62622,19.36789],[109.11906,19.82104],[110.2116,20.10125],[110.78655,20.07753],[111.01005,19.69593],[110.57065,19.25588],[110.33919,18.6784]]],[[[127.65741,49.76027],[129.39782,49.4406],[130.58229,48.72969],[130.98728,47.79013],[132.50667,47.78897],[133.3736,48.18344],[135.02631,48.47823],[134.50081,47.57844],[134.11236,47.21247],[133.76964,46.11693],[133.09713,45.14407],[131.88345,45.32116],[131.02521,44.96795],[131.28856,44.11152],[131.14469,42.92999],[130.63387,42.90301],[130.64002,42.39501],[129.99427,42.98539],[129.59667,42.42498],[128.05222,41.99428],[128.20843,41.46677],[127.34378,41.50315],[126.86908,41.81657],[126.18205,41.10734],[125.07994,40.56982],[124.26562,39.92849],[122.86757,39.63779],[122.13139,39.17045],[121.05455,38.89747],[121.58599,39.36085],[121.37676,39.75026],[122.1686,40.42244],[121.64036,40.94639],[120.76863,40.59339],[119.6396,39.89806],[119.02346,39.25233],[118.04275,39.20427],[117.5327,38.73764],[118.0597,38.06148],[118.87815,37.89733],[118.91164,37.44846],[119.7028,37.15639],[120.82346,37.87043],[121.71126,37.48112],[122.35794,37.45448],[122.51999,36.93061],[121.10416,36.65133],[120.63701,36.11144],[119.66456,35.60979],[119.15121,34.90986],[120.22752,34.36033],[120.62037,33.37672],[121.22901,32.46032],[121.90815,31.69217],[121.89192,30.94935],[121.26426,30.67627],[121.50352,30.14291],[122.09211,29.83252],[121.93843,29.01802],[121.68444,28.22551],[121.12566,28.13567],[120.39547,27.05321],[119.5855,25.74078],[118.65687,24.54739],[117.28161,23.6245],[115.89074,22.78287],[114.76383,22.66807],[114.15255,22.22376],[113.80678,22.54834],[113.24108,22.05137],[111.84359,21.55049],[110.78547,21.39714],[110.44404,20.34103],[109.88986,20.28246],[109.62766,21.00823],[109.86449,21.39505],[108.52281,21.71521],[108.05018,21.55238],[107.04342,21.8119],[106.56727,22.2182],[106.7254,22.79427],[105.81125,22.97689],[105.32921,23.35206],[104.47686,22.81915],[103.50451,22.70376],[102.70699,22.7088],[102.17044,22.46475],[101.65202,22.3182],[101.80312,21.17437],[101.27003,21.20165],[101.18001,21.43657],[101.15003,21.84998],[100.41654,21.55884],[99.98349,21.74294],[99.2409,22.11831],[99.53199,22.94904],[98.89875,23.14272],[98.66026,24.06329],[97.60472,23.8974],[97.72461,25.08364],[98.67184,25.9187],[98.71209,26.74354],[98.68269,27.50881],[98.24623,27.74722],[97.91199,28.33595],[97.32711,28.26158],[96.24883,28.41103],[96.58659,28.83098],[96.11768,29.4528],[95.4048,29.03172],[94.56599,29.27744],[93.41335,28.64063],[92.50312,27.89688],[91.69666,27.77174],[91.25885,28.04061],[90.73051,28.06495],[90.01583,28.29644],[89.47581,28.04276],[88.81425,27.29932],[88.73033,28.08686],[88.12044,27.87654],[86.95452,27.97426],[85.82332,28.20358],[85.01164,28.64277],[84.23458,28.83989],[83.89899,29.32023],[83.33712,29.46373],[82.32751,30.11527],[81.5258,30.42272],[81.11126,30.18348],[79.72137,30.88271],[78.73889,31.51591],[78.45845,32.61816],[79.17613,32.48378],[79.20889,32.99439],[78.81109,33.5062],[78.91227,34.32194],[77.83745,35.49401],[76.19285,35.8984],[75.8969,36.66681],[75.15803,37.13303],[74.98,37.41999],[74.82999,37.99001],[74.86482,38.37885],[74.25751,38.60651],[73.92885,38.50582],[73.67538,39.43124],[73.96001,39.66001],[73.82224,39.89397],[74.77686,40.36643],[75.46783,40.56207],[76.52637,40.42795],[76.90448,41.06649],[78.1872,41.18532],[78.54366,41.58224],[80.11943,42.12394],[80.25999,42.35],[80.18015,42.92007],[80.86621,43.18036],[79.96611,44.91752],[81.94707,45.31703],[82.45893,45.53965],[83.18048,47.33003],[85.16429,47.00096],[85.72048,47.45297],[85.76823,48.45575],[86.59878,48.54918],[87.35997,49.21498],[87.75126,49.2972],[88.01383,48.59946],[88.8543,48.06908],[90.28083,47.69355],[90.97081,46.88815],[90.58577,45.71972],[90.94554,45.28607],[92.13389,45.11508],[93.48073,44.97547],[94.68893,44.35233],[95.30688,44.24133],[95.76245,43.31945],[96.3494,42.72564],[97.45176,42.74889],[99.51582,42.52469],[100.84587,42.6638],[101.83304,42.51487],[103.31228,41.90747],[104.52228,41.90835],[104.96499,41.59741],[106.12932,42.13433],[107.74477,42.48152],[109.2436,42.51945],[110.4121,42.87123],[111.12968,43.40683],[111.82959,43.74312],[111.66774,44.07318],[111.34838,44.45744],[111.87331,45.10208],[112.43606,45.01165],[113.46391,44.80889],[114.46033,45.33982],[115.9851,45.72724],[116.71787,46.3882],[117.4217,46.67273],[118.87433,46.80541],[119.66327,46.69268],[119.77282,47.04806],[118.86657,47.74706],[118.06414,48.06673],[117.29551,47.69771],[116.30895,47.85341],[115.74284,47.72654],[115.48528,48.13538],[116.1918,49.1346],[116.6788,49.88853],[117.87924,49.51098],[119.28846,50.14288],[119.27937,50.58291],[120.18205,51.64357],[120.73819,51.96412],[120.72579,52.51623],[120.17709,52.75389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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f0511ce4b0220bbd9a1d4e","contributors":{"authors":[{"text":"Xu, Liming","contributorId":198109,"corporation":false,"usgs":false,"family":"Xu","given":"Liming","email":"","affiliations":[],"preferred":false,"id":715135,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhao, Jingzhuang","contributorId":198110,"corporation":false,"usgs":false,"family":"Zhao","given":"Jingzhuang","email":"","affiliations":[],"preferred":false,"id":715136,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Miao","contributorId":198111,"corporation":false,"usgs":false,"family":"Liu","given":"Miao","email":"","affiliations":[],"preferred":false,"id":715137,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kurath, Gael 0000-0003-3294-560X gkurath@usgs.gov","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":2629,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","email":"gkurath@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":715134,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ren, Guangming","contributorId":198112,"corporation":false,"usgs":false,"family":"Ren","given":"Guangming","email":"","affiliations":[],"preferred":false,"id":715138,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LaPatra, Scott E.","contributorId":179323,"corporation":false,"usgs":false,"family":"LaPatra","given":"Scott","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":715139,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yin, Jiasheng","contributorId":198113,"corporation":false,"usgs":false,"family":"Yin","given":"Jiasheng","email":"","affiliations":[],"preferred":false,"id":715140,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Liu, Hongbai","contributorId":198114,"corporation":false,"usgs":false,"family":"Liu","given":"Hongbai","email":"","affiliations":[],"preferred":false,"id":715141,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Feng, Jian","contributorId":198115,"corporation":false,"usgs":false,"family":"Feng","given":"Jian","email":"","affiliations":[],"preferred":false,"id":715142,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lu, Tongyan","contributorId":198116,"corporation":false,"usgs":false,"family":"Lu","given":"Tongyan","email":"","affiliations":[],"preferred":false,"id":715143,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70192243,"text":"70192243 - 2017 - Quantifying the effects of wildfire on changes in soil properties by surface burning of soils from the Boulder Creek Critical Zone Observatory","interactions":[],"lastModifiedDate":"2017-10-24T12:14:23","indexId":"70192243","displayToPublicDate":"2017-10-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the effects of wildfire on changes in soil properties by surface burning of soils from the Boulder Creek Critical Zone Observatory","docAbstract":"<div id=\"abst0010\"><p id=\"sect0015\"><strong>Study region</strong></p><p id=\"spar0075\">This study used intact soil cores collected at the Boulder Creek Critical Zone Observatory near Boulder, Colorado, USA to explore fire impacts on soil properties.</p></div><div id=\"abst0015\"><p id=\"sect0020\"><strong>Study focus</strong></p><p id=\"spar0080\">Three soil scenarios were considered: unburned control soils, and low- and high-temperature burned soils. We explored simulated fire impacts on field-saturated hydraulic conductivity, dry bulk density, total organic carbon, and infiltration processes during rainfall simulations.</p></div><div id=\"abst0020\"><p id=\"sect0025\"><strong>New hydrological insights for the region</strong></p><p id=\"spar0085\">Soils burned to high temperatures became more homogeneous with depth with respect to total organic carbon and bulk density, suggesting reductions in near-surface porosity. Organic matter decreased significantly with increasing soil temperature. Tension infiltration experiments suggested a decrease in infiltration rates from unburned to low-temperature burned soils, and an increase in infiltration rates in high-temperature burned soils. Non-parametric statistical tests showed that field-saturated hydraulic conductivity similarly decreased from unburned to low-temperature burned soils, and then increased with high-temperature burned soils. We interpret these changes result from the combustion of surface and near-surface organic materials, enabling water to infiltrate directly into soil instead of being stored in the litter and duff layer at the surface. Together, these results indicate that fire-induced changes in soil properties from low temperatures were not as drastic as high temperatures, but that reductions in surface soil water repellency in high temperatures may increase infiltration relative to low temperatures.</p></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2017.07.006","usgsCitation":"Wieting, C., Ebel, B.A., and Singha, K., 2017, Quantifying the effects of wildfire on changes in soil properties by surface burning of soils from the Boulder Creek Critical Zone Observatory: Journal of Hydrology: Regional Studies, v. 13, p. 43-57, https://doi.org/10.1016/j.ejrh.2017.07.006.","productDescription":"15 p.","startPage":"43","endPage":"57","ipdsId":"IP-081959","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":469409,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2017.07.006","text":"Publisher Index Page"},{"id":347220,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Boulder Creek Critical Zone Observatory","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -105.51406860351562,\n              39.97106879292145\n            ],\n            [\n              -105.33828735351562,\n              39.97106879292145\n            ],\n            [\n              -105.33828735351562,\n              40.091730433255\n            ],\n            [\n              -105.51406860351562,\n              40.091730433255\n            ],\n            [\n              -105.51406860351562,\n              39.97106879292145\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f0511ee4b0220bbd9a1d62","contributors":{"authors":[{"text":"Wieting, Celeste","contributorId":198061,"corporation":false,"usgs":false,"family":"Wieting","given":"Celeste","affiliations":[],"preferred":false,"id":714974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ebel, Brian A. 0000-0002-5413-3963 bebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":2557,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian","email":"bebel@usgs.gov","middleInitial":"A.","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":714973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Singha, Kamini 0000-0002-0605-3774","orcid":"https://orcid.org/0000-0002-0605-3774","contributorId":191366,"corporation":false,"usgs":false,"family":"Singha","given":"Kamini","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":714975,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192032,"text":"70192032 - 2017 - Arctic deep-water ferromanganese-oxide deposits reflect the unique characteristics of the Arctic Ocean","interactions":[],"lastModifiedDate":"2017-12-19T16:46:17","indexId":"70192032","displayToPublicDate":"2017-10-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Arctic deep-water ferromanganese-oxide deposits reflect the unique characteristics of the Arctic Ocean","docAbstract":"<div class=\"article-section__content mainAbstract\"><p>Little is known about marine mineral deposits in the Arctic Ocean, an ocean dominated by continental shelf and basins semi-closed to deep-water circulation. Here, we present data for ferromanganese crusts and nodules collected from the Amerasia Arctic Ocean in 2008, 2009, and 2012 (HLY0805, HLY0905, HLY1202). We determined mineral and chemical compositions of the crusts and nodules and the onset of their formation. Water column samples from the GEOTRACES program were analyzed for dissolved and particulate scandium concentrations, an element uniquely enriched in these deposits.</p><p>The Arctic crusts and nodules are characterized by unique mineral and chemical compositions with atypically high growth rates, detrital contents, Fe/Mn ratios, and low Si/Al ratios, compared to deposits found elsewhere. High detritus reflects erosion of submarine outcrops and North America and Siberia cratons, transport by rivers and glaciers to the sea, and distribution by sea ice, brines, and currents. Uniquely high Fe/Mn ratios are attributed to expansive continental shelves, where diagenetic cycling releases Fe to bottom waters, and density flows transport shelf bottom water to the open Arctic Ocean. Low Mn contents reflect the lack of a mid-water oxygen minimum zone that would act as a reservoir for dissolved Mn. The potential host phases and sources for elements with uniquely high contents are discussed with an emphasis on scandium. Scandium sorption onto Fe oxyhydroxides and Sc-rich detritus account for atypically high scandium contents. The opening of Fram Strait in the Miocene and ventilation of the deep basins initiated Fe-Mn crust growth ∼15 Myr ago.</p></div>","language":"English","publisher":"AGU","doi":"10.1002/2017GC007186","usgsCitation":"Hein, J.R., Konstantinova, N., Mikesell, M., Mizell, K., Fitzsimmons, J.N., Lam, P., Jensen, L.T., Xiang, Y., Gartman, A., Cherkashov, G., Hutchinson, D., and Till, C.P., 2017, Arctic deep-water ferromanganese-oxide deposits reflect the unique characteristics of the Arctic Ocean: Geochemistry, Geophysics, Geosystems, v. 18, no. 11, p. 3771-3800, https://doi.org/10.1002/2017GC007186.","productDescription":"30 p.","startPage":"3771","endPage":"3800","ipdsId":"IP-086546","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469414,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017gc007186","text":"Publisher Index Page"},{"id":347290,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-08","publicationStatus":"PW","scienceBaseUri":"59f0511fe4b0220bbd9a1d6e","contributors":{"authors":[{"text":"Hein, James R. 0000-0002-5321-899X jhein@usgs.gov","orcid":"https://orcid.org/0000-0002-5321-899X","contributorId":140835,"corporation":false,"usgs":true,"family":"Hein","given":"James","email":"jhein@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":713908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Konstantinova, Natalia","contributorId":197615,"corporation":false,"usgs":false,"family":"Konstantinova","given":"Natalia","affiliations":[],"preferred":false,"id":713909,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mikesell, Mariah 0000-0001-9145-2237 mmikesell@usgs.gov","orcid":"https://orcid.org/0000-0001-9145-2237","contributorId":174512,"corporation":false,"usgs":true,"family":"Mikesell","given":"Mariah","email":"mmikesell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":713910,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mizell, Kira 0000-0002-5066-787X kmizell@usgs.gov","orcid":"https://orcid.org/0000-0002-5066-787X","contributorId":4914,"corporation":false,"usgs":true,"family":"Mizell","given":"Kira","email":"kmizell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":713911,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fitzsimmons, Jessica N.","contributorId":197616,"corporation":false,"usgs":false,"family":"Fitzsimmons","given":"Jessica","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":713912,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lam, Phoebe","contributorId":197617,"corporation":false,"usgs":false,"family":"Lam","given":"Phoebe","affiliations":[],"preferred":false,"id":713913,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jensen, Laramie T.","contributorId":197618,"corporation":false,"usgs":false,"family":"Jensen","given":"Laramie","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":713914,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Xiang, Yang","contributorId":197619,"corporation":false,"usgs":false,"family":"Xiang","given":"Yang","email":"","affiliations":[],"preferred":false,"id":713915,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gartman, Amy 0000-0001-9307-3062 agartman@usgs.gov","orcid":"https://orcid.org/0000-0001-9307-3062","contributorId":177057,"corporation":false,"usgs":true,"family":"Gartman","given":"Amy","email":"agartman@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":713917,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cherkashov, Georgy","contributorId":197620,"corporation":false,"usgs":false,"family":"Cherkashov","given":"Georgy","affiliations":[],"preferred":false,"id":713916,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hutchinson, Deborah 0000-0002-2544-5466 dhutchinson@usgs.gov","orcid":"https://orcid.org/0000-0002-2544-5466","contributorId":174836,"corporation":false,"usgs":true,"family":"Hutchinson","given":"Deborah","email":"dhutchinson@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":713918,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Till, Claire P.","contributorId":198242,"corporation":false,"usgs":false,"family":"Till","given":"Claire","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":715459,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70192212,"text":"70192212 - 2017 - Seasonality of stable isotope composition of atmospheric water input at the southern slopes of Mt. Kilimanjaro, Tanzania","interactions":[],"lastModifiedDate":"2017-10-23T13:30:53","indexId":"70192212","displayToPublicDate":"2017-10-23T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Seasonality of stable isotope composition of atmospheric water input at the southern slopes of Mt. Kilimanjaro, Tanzania","docAbstract":"<p><span>To understand the moisture regime at the southern slopes of Mt. Kilimanjaro, we analysed the isotopic variability of oxygen (δ</span><sup>18</sup><span>O) and hydrogen (δD) of rainfall, throughfall, and fog from a total of 2,140 samples collected weekly over 2&nbsp;years at 9 study sites along an elevation transect ranging from 950 to 3,880&nbsp;m above sea level. Precipitation in the Kilimanjaro tropical rainforests consists of a combination of rainfall, throughfall, and fog. We defined local meteoric water lines for all 3 precipitation types individually and the overall precipitation, δD</span><sub>prec</sub><span>&nbsp;=&nbsp;7.45 (±0.05)&nbsp;×&nbsp;δ</span><sup>18</sup><span>O</span><sub>prec</sub><span>&nbsp;+&nbsp;13.61 (±0.20),<span>&nbsp;</span></span><i>n</i><span>&nbsp;=&nbsp;2,140,<span>&nbsp;</span></span><i>R</i><sup>2</sup><span>&nbsp;=&nbsp;.91,<span>&nbsp;</span></span><i>p</i><span>&nbsp;&lt;&nbsp;.001. We investigated the precipitation-type-specific stable isotope composition and analysed the effects of amount, altitude, and temperature. Aggregated annual mean values revealed isotope composition of rainfall as most depleted and fog water as most enriched in heavy isotopes at the highest elevation research site. We found an altitude effect of δ</span><sup>18</sup><span>O</span><sub>rain</sub><span>&nbsp;=&nbsp;−0.11‰&nbsp;×&nbsp;100&nbsp;m</span><sup>−1</sup><span>, which varied according to precipitation type and season. The relatively weak isotope or altitude gradient may reveal 2 different moisture sources in the research area: (a) local moisture recycling and (b) regional moisture sources. Generally, the seasonality of δ</span><sup>18</sup><span>O</span><sub>rain</sub><span><span>&nbsp;</span>values follows the bimodal rainfall distribution under the influences of south- and north-easterly trade winds. These seasonal patterns of isotopic composition were linked to different regional moisture sources by analysing Hybrid Single Particle Lagrangian Integrated Trajectory backward trajectories. Seasonality of<span>&nbsp;</span></span><i>d</i><span>excess values revealed evidence of enhanced moisture recycling after the onset of the rainy seasons. This comprehensive dataset is essential for further research using stable isotopes as a hydrological tracer of sources of precipitation that contribute to water resources of the Kilimanjaro region.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11311","usgsCitation":"Otte, I., Detsch, F., Gutlein, A., Scholl, M.A., Kiese, R., Appelhans, T., and Nauss, T., 2017, Seasonality of stable isotope composition of atmospheric water input at the southern slopes of Mt. Kilimanjaro, Tanzania: Hydrological Processes, v. 31, no. 22, p. 3932-3947, https://doi.org/10.1002/hyp.11311.","productDescription":"16 p.","startPage":"3932","endPage":"3947","ipdsId":"IP-089904","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":469417,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.11311","text":"Publisher Index Page"},{"id":347122,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Tanzania","otherGeospatial":"Mt. Kilimanjaro","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              37.14202880859375,\n              -3.2412964891479614\n            ],\n            [\n              37.57530212402344,\n              -3.2412964891479614\n            ],\n            [\n              37.57530212402344,\n              -2.956069891317356\n            ],\n            [\n              37.14202880859375,\n              -2.956069891317356\n            ],\n            [\n              37.14202880859375,\n              -3.2412964891479614\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"31","issue":"22","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-15","publicationStatus":"PW","scienceBaseUri":"59eeffa0e4b0220bbd988f4d","contributors":{"authors":[{"text":"Otte, Insa","contributorId":198023,"corporation":false,"usgs":false,"family":"Otte","given":"Insa","email":"","affiliations":[],"preferred":false,"id":714826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Detsch, Florian","contributorId":198024,"corporation":false,"usgs":false,"family":"Detsch","given":"Florian","email":"","affiliations":[],"preferred":false,"id":714827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gutlein, Adrian","contributorId":198025,"corporation":false,"usgs":false,"family":"Gutlein","given":"Adrian","email":"","affiliations":[],"preferred":false,"id":714828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scholl, Martha A. 0000-0001-6994-4614 mascholl@usgs.gov","orcid":"https://orcid.org/0000-0001-6994-4614","contributorId":1920,"corporation":false,"usgs":true,"family":"Scholl","given":"Martha","email":"mascholl@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":714825,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kiese, Ralf","contributorId":198026,"corporation":false,"usgs":false,"family":"Kiese","given":"Ralf","email":"","affiliations":[],"preferred":false,"id":714829,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Appelhans, Tim","contributorId":198027,"corporation":false,"usgs":false,"family":"Appelhans","given":"Tim","email":"","affiliations":[],"preferred":false,"id":714830,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nauss, Thomas","contributorId":198028,"corporation":false,"usgs":false,"family":"Nauss","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":714831,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70192118,"text":"70192118 - 2017 - New biotite and muscovite isotopic reference materials, USGS57 and USGS58, for δ2H measurements–A replacement for NBS 30","interactions":[],"lastModifiedDate":"2017-10-23T15:05:09","indexId":"70192118","displayToPublicDate":"2017-10-23T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"New biotite and muscovite isotopic reference materials, USGS57 and USGS58, for δ2H measurements–A replacement for NBS 30","docAbstract":"<p id=\"sp0090\">The advent of continuous-flow isotope-ratio mass spectrometry (CF-IRMS) coupled with a high temperature conversion (HTC) system enabled faster, more cost effective, and more precise<span>&nbsp;</span><i>δ</i><sup>2</sup>H analysis of hydrogen-bearing solids. Accurate hydrogen isotopic analysis by on-line or off-line techniques requires appropriate isotopic reference materials (RMs). A strategy of two-point calibrations spanning<span>&nbsp;</span><i>δ</i><sup>2</sup>H range of the unknowns using two RMs is recommended. Unfortunately, the supply of the previously widely used isotopic RM, NBS 30 biotite, is exhausted. In addition, recent measurements have shown that the determination of<span>&nbsp;</span><i>δ</i><sup>2</sup>H values of NBS 30 biotite on the VSMOW-SLAP isotope-delta scale by on-line HTC systems with CF-IRMS may be unreliable because hydrogen in this biotite may not be converted quantitatively to molecular hydrogen. The<span>&nbsp;</span><i>δ</i><sup>2</sup>H<sub>VSMOW-SLAP</sub><span>&nbsp;</span>values of NBS 30 biotite analyzed by on-line HTC systems can be as much as 21&nbsp;mUr (or ‰) too positive compared to the accepted value of −&nbsp;65.7&nbsp;mUr, determined by only a few conventional off-line measurements. To ensure accurate and traceable on-line hydrogen isotope-ratio determinations in mineral samples, we here propose two isotopically homogeneous, hydrous mineral RMs with well-characterized isotope-ratio values, which are urgently needed. The U.S. Geological Survey (USGS) has prepared two such RMs, USGS57 biotite and USGS58 muscovite. The<span>&nbsp;</span><i>δ</i><sup>2</sup>H values were determined by both glassy carbon-based on-line conversion and chromium-based on-line conversion, and results were confirmed by off-line conversion. The quantitative conversion of hydrogen from the two RMs using the on-line HTC method was carefully evaluated in this study. The isotopic compositions of these new RMs with 1-σ uncertainties and mass fractions of hydrogen are:</p><p id=\"sp0095\">USGS57 (biotite)</p><p id=\"sp0100\"><i>δ</i><sup>2</sup>H<sub>VSMOW-SLAP</sub>&nbsp;=&nbsp;−&nbsp;91.5&nbsp;±&nbsp;2.4&nbsp;mUr (<i>n</i>&nbsp;=&nbsp;24)</p><p id=\"sp0105\">Mass fraction hydrogen&nbsp;=&nbsp;0.416&nbsp;±&nbsp;0.002% (<i>n</i>&nbsp;=&nbsp;4)</p><p id=\"sp0110\">Mass fraction water&nbsp;=&nbsp;3.74&nbsp;±&nbsp;0.02% (<i>n</i>&nbsp;=&nbsp;4)</p><p id=\"sp0115\">USGS58 (muscovite)</p><p id=\"sp0120\"><i>δ</i><sup>2</sup>H<sub>VSMOW-SLAP</sub>&nbsp;=&nbsp;−&nbsp;28.4&nbsp;±&nbsp;1.6&nbsp;mUr (<i>n</i>&nbsp;=&nbsp;24)</p><p id=\"sp0125\">Mass fraction hydrogen&nbsp;=&nbsp;0.448&nbsp;±&nbsp;0.002% (<i>n</i>&nbsp;=&nbsp;4)</p><p id=\"sp0130\">Mass fraction water&nbsp;=&nbsp;4.03&nbsp;±&nbsp;0.02% (<i>n</i>&nbsp;=&nbsp;4).</p><p id=\"sp0135\">These<span>&nbsp;</span><i>δ</i><sup>2</sup>H<sub>VSMOW-SLAP</sub><span>&nbsp;</span>values encompass typical ranges for solid unknowns of crustal and mantle origin and are available to users for recommended two-point calibration.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2017.07.027","usgsCitation":"Qi, H., Coplen, T.B., Gehre, M., Vennemann, T.W., Brand, W.A., Geilmann, H., Olack, G., Bindeman, I.N., Palandri, J., Huang, L., and Longstaffe, F.J., 2017, New biotite and muscovite isotopic reference materials, USGS57 and USGS58, for δ2H measurements–A replacement for NBS 30: Chemical Geology, v. 467, p. 89-99, https://doi.org/10.1016/j.chemgeo.2017.07.027.","productDescription":"11 p.","startPage":"89","endPage":"99","ipdsId":"IP-088663","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":469416,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://iris.unil.ch/handle/iris/62344","text":"External Repository"},{"id":347148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"467","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59eeffa2e4b0220bbd988f5d","contributors":{"authors":[{"text":"Qi, Haiping 0000-0002-8339-744X haipingq@usgs.gov","orcid":"https://orcid.org/0000-0002-8339-744X","contributorId":507,"corporation":false,"usgs":true,"family":"Qi","given":"Haiping","email":"haipingq@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":714295,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":714296,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gehre, Matthias","contributorId":34004,"corporation":false,"usgs":false,"family":"Gehre","given":"Matthias","email":"","affiliations":[],"preferred":false,"id":714297,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vennemann, Torsten W.","contributorId":190168,"corporation":false,"usgs":false,"family":"Vennemann","given":"Torsten","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":714298,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brand, Willi A.","contributorId":33091,"corporation":false,"usgs":false,"family":"Brand","given":"Willi","email":"","middleInitial":"A.","affiliations":[{"id":13365,"text":"Max-Planck Institute for Biogeochemistry, Jena, Germany","active":true,"usgs":false}],"preferred":false,"id":714299,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Geilmann, Heike","contributorId":41303,"corporation":false,"usgs":false,"family":"Geilmann","given":"Heike","email":"","affiliations":[{"id":13365,"text":"Max-Planck Institute for Biogeochemistry, Jena, Germany","active":true,"usgs":false}],"preferred":false,"id":714300,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Olack, Gerard","contributorId":190167,"corporation":false,"usgs":false,"family":"Olack","given":"Gerard","email":"","affiliations":[],"preferred":false,"id":714301,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bindeman, Ilya N.","contributorId":175500,"corporation":false,"usgs":false,"family":"Bindeman","given":"Ilya","email":"","middleInitial":"N.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":714302,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Palandri, Jim","contributorId":197781,"corporation":false,"usgs":false,"family":"Palandri","given":"Jim","email":"","affiliations":[],"preferred":false,"id":714303,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Huang, Li","contributorId":197782,"corporation":false,"usgs":false,"family":"Huang","given":"Li","email":"","affiliations":[],"preferred":false,"id":714304,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Longstaffe, Fred J.","contributorId":197783,"corporation":false,"usgs":false,"family":"Longstaffe","given":"Fred","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":714305,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70192151,"text":"70192151 - 2017 - Using paired in situ high frequency nitrate measurements to better understand controls on nitrate concentrations and estimate nitrification rates in a wastewater-impacted river","interactions":[],"lastModifiedDate":"2017-11-29T16:19:22","indexId":"70192151","displayToPublicDate":"2017-10-23T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Using paired in situ high frequency nitrate measurements to better understand controls on nitrate concentrations and estimate nitrification rates in a wastewater-impacted river","docAbstract":"<p><span>We used paired continuous nitrate (&nbsp;</span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0001.png?v=1&amp;s=22c5715a6e2fdcc31e2624a9c77f43f8d1e6bc0d\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0001.png?v=1&amp;s=22c5715a6e2fdcc31e2624a9c77f43f8d1e6bc0d\"></span></span><span>) measurements along a tidally affected river receiving wastewater discharge rich in ammonium (<span>&nbsp;</span></span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0002.png?v=1&amp;s=6e850ad756ee9fc2b59f2c62cce5080ba359fec2\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0002.png?v=1&amp;s=6e850ad756ee9fc2b59f2c62cce5080ba359fec2\"></span></span><span>) to quantify rates of change in<span>&nbsp;</span></span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0003.png?v=1&amp;s=edd1801396530467a9c1886f4d85f881efc4aa35\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0003.png?v=1&amp;s=edd1801396530467a9c1886f4d85f881efc4aa35\"></span></span><span><span>&nbsp;</span>concentration (<span>&nbsp;</span></span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0004.png?v=1&amp;s=4ef983b0aa6ea4bcfbb1fd623360b8ef2f78f55e\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0004.png?v=1&amp;s=4ef983b0aa6ea4bcfbb1fd623360b8ef2f78f55e\"></span></span><span>) and estimate nitrification rates.<span>&nbsp;</span></span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0005.png?v=1&amp;s=af1ee755b266e46e4993cc3089e9949d0681738d\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0005.png?v=1&amp;s=af1ee755b266e46e4993cc3089e9949d0681738d\"></span></span><span><span>&nbsp;</span>sensors were deployed 30 km apart in the Sacramento River, California (USA), with the upstream station located immediately above the regional wastewater treatment plant (WWTP). We used a travel time model to track water transit between the stations and estimated<span>&nbsp;</span></span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0006.png?v=1&amp;s=ac569aa42fa9e978ae109f1f21fac0992034f6f5\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0006.png?v=1&amp;s=ac569aa42fa9e978ae109f1f21fac0992034f6f5\"></span></span><span><span>&nbsp;</span>every 15 min (October 2013 to September 2014). Changes in<span>&nbsp;</span></span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0007.png?v=1&amp;s=09413b94c0dbbc1520403721dc5cb821ea2bdfd8\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0007.png?v=1&amp;s=09413b94c0dbbc1520403721dc5cb821ea2bdfd8\"></span></span><span>concentration were strongly related to water temperature. In the presence of wastewater,<span>&nbsp;</span></span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0008.png?v=1&amp;s=067241a15e12389f8f6612a921f71fef905edb86\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0008.png?v=1&amp;s=067241a15e12389f8f6612a921f71fef905edb86\"></span></span><span>was generally positive, ranging from about 7 µ</span><i>M</i><span>&nbsp;d</span><sup>−1</sup><span><span>&nbsp;</span>in the summer to near zero in the winter. Numerous periods when the WWTP halted discharge allowed the<span>&nbsp;</span></span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0009.png?v=1&amp;s=5e476b3d5f1ca100f0b42c10db9f921fe2c56b52\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0009.png?v=1&amp;s=5e476b3d5f1ca100f0b42c10db9f921fe2c56b52\"></span></span><span><span>&nbsp;</span>to be estimated under no-effluent conditions and revealed that in the absence of effluent, net gains in<span>&nbsp;</span></span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0010.png?v=1&amp;s=000d3d020109a713ceae82ba1a91c88a1a0e2b7c\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0010.png?v=1&amp;s=000d3d020109a713ceae82ba1a91c88a1a0e2b7c\"></span></span><span><span>&nbsp;</span>were substantially lower but still positive in the summer and negative (net sink) in the winter. Nitrification rates of effluent-derived NH</span><sub>4</sub><span><span>&nbsp;</span>(<span>&nbsp;</span></span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0011.png?v=1&amp;s=a12b09a6bb2367ef84836d9f309f09415817e6a8\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0011.png?v=1&amp;s=a12b09a6bb2367ef84836d9f309f09415817e6a8\"></span></span><span>) were estimated from the difference between<span>&nbsp;</span></span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0012.png?v=1&amp;s=029e4f1a23b5b28155d9d510cc025f0aa221847f\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0012.png?v=1&amp;s=029e4f1a23b5b28155d9d510cc025f0aa221847f\"></span></span><span><span>&nbsp;</span>measured in the presence versus absence of effluent and ranged from 1.5 to 3.4 µ</span><i>M</i><span>&nbsp;d</span><sup>−1</sup><span>, which is within literature values but tenfold greater than recently reported for this region.<span>&nbsp;</span></span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0013.png?v=1&amp;s=10ca0a9987aff8303b86e43a344b3bdc16ffe889\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/2017WR020670/asset/equation/wrcr22895-math-0013.png?v=1&amp;s=10ca0a9987aff8303b86e43a344b3bdc16ffe889\"></span></span><span><span>&nbsp;</span>was generally lower in winter (∼2 µ</span><i>M</i><span>&nbsp;d</span><sup>−1</sup><span>) than summer (∼3 µ</span><i>M</i><span>&nbsp;d</span><sup>−1</sup><span>). This in situ, high frequency approach provides advantages over traditional discrete sampling, incubation, and tracer methods and allows measurements to be made over broad areas for extended periods of time. Incorporating this approach into environmental monitoring programs can facilitate our ability to protect and manage aquatic systems.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/2017WR020670","usgsCitation":"Kraus, T.E., O’Donnell, K., Downing, B.D., Burau, J.R., and Bergamaschi, B.A., 2017, Using paired in situ high frequency nitrate measurements to better understand controls on nitrate concentrations and estimate nitrification rates in a wastewater-impacted river: Water Resources Research, v. 53, no. 10, p. 8423-8442, https://doi.org/10.1002/2017WR020670.","productDescription":"20 p.","startPage":"8423","endPage":"8442","ipdsId":"IP-078919","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":469415,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017wr020670","text":"Publisher Index Page"},{"id":347134,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River","volume":"53","issue":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-20","publicationStatus":"PW","scienceBaseUri":"59eeffa2e4b0220bbd988f57","contributors":{"authors":[{"text":"Kraus, Tamara E. C. 0000-0002-5187-8644 tkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-5187-8644","contributorId":147560,"corporation":false,"usgs":true,"family":"Kraus","given":"Tamara","email":"tkraus@usgs.gov","middleInitial":"E. C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Donnell, Katy 0000-0003-2323-8970 kodonnell@usgs.gov","orcid":"https://orcid.org/0000-0003-2323-8970","contributorId":5640,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Katy","email":"kodonnell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714465,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Downing, Bryan D. 0000-0002-2007-5304 bdowning@usgs.gov","orcid":"https://orcid.org/0000-0002-2007-5304","contributorId":1449,"corporation":false,"usgs":true,"family":"Downing","given":"Bryan","email":"bdowning@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burau, Jon R. 0000-0002-5196-5035 jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714463,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70217866,"text":"70217866 - 2017 - A newly identified role of the deciduous forest floor in the timing of green‐up","interactions":[],"lastModifiedDate":"2021-02-08T13:38:48.640962","indexId":"70217866","displayToPublicDate":"2017-10-20T07:33:19","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6495,"text":"JGR: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"A newly identified role of the deciduous forest floor in the timing of green‐up","docAbstract":"<p><span>Plant phenology studies rarely consider controlling factors other than air temperature. We evaluate here the potential significance of physical and chemical properties of soil (edaphic factors) as additional important controls on phenology. More specifically, we investigate causal connections between satellite‐observed green‐up dates of small forest watersheds and soil properties in the Adirondack Mountains of New York, USA. Contrary to the findings of previous studies, where edaphic controls of spring phenology were found to be marginal, our analyses show that at least three factors manifest themselves as significant controls of seasonal patterns of variation in vegetated land surfaces observed from remote sensing: (1) thickness of the forest floor, (2) concentration of exchangeable soil potassium, and (3) soil acidity. For example, a thick forest floor appears to delay the onset of green‐up. Watersheds with elevated concentrations of potassium are associated with early surface greening. We also found that trees growing in strongly acidified watersheds demonstrate delayed green‐up dates. Overall, our work demonstrates that, at the scale of small forest watersheds, edaphic factors can explain a significant percentage of the observed spatial variation in land surface phenology that is comparable to the percentage that can be explained by climatic and landscape factors. We conclude that physical and chemical properties of forest soil play important roles in forest ecosystems as modulators of climatic drivers controlling the rate of spring soil warming and the transition of trees out of winter dormancy.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JG004073","usgsCitation":"Lapenis, A.G., Lawrence, G.B., Buyantuev, A., Jiang, S., Sullivan, T.J., McDonnell, T.C., and Bailey, S.W., 2017, A newly identified role of the deciduous forest floor in the timing of green‐up: JGR: Biogeosciences, v. 122, no. 11, p. 2876-2891, https://doi.org/10.1002/2017JG004073.","productDescription":"16 p.","startPage":"2876","endPage":"2891","ipdsId":"IP-080375","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":469421,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jg004073","text":"Publisher Index Page"},{"id":383087,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"New York","otherGeospatial":"central New York","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.3330078125,\n              42.65012181368022\n            ],\n            [\n              -74.970703125,\n              42.65012181368022\n            ],\n            [\n              -74.970703125,\n              43.389081939117496\n            ],\n            [\n              -76.3330078125,\n              43.389081939117496\n            ],\n            [\n              -76.3330078125,\n              42.65012181368022\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"122","issue":"11","noUsgsAuthors":false,"publicationDate":"2017-11-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Lapenis, Andrei G 0000-0002-2135-3636","orcid":"https://orcid.org/0000-0002-2135-3636","contributorId":248818,"corporation":false,"usgs":false,"family":"Lapenis","given":"Andrei","email":"","middleInitial":"G","affiliations":[{"id":50026,"text":"Dept of Geography & Planning, SUNY Albany, NY","active":true,"usgs":false}],"preferred":false,"id":809976,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":809977,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buyantuev, Alexander","contributorId":248819,"corporation":false,"usgs":false,"family":"Buyantuev","given":"Alexander","affiliations":[{"id":50027,"text":"Assistant Professor, Dept of Geography & Planning, SUNY Albany, NY","active":true,"usgs":false}],"preferred":false,"id":809978,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jiang, Shiguo 0000-0001-9088-883X","orcid":"https://orcid.org/0000-0001-9088-883X","contributorId":244799,"corporation":false,"usgs":false,"family":"Jiang","given":"Shiguo","email":"","affiliations":[{"id":48981,"text":"State University of New York","active":true,"usgs":false}],"preferred":false,"id":809979,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sullivan, Timothy J.","contributorId":196720,"corporation":false,"usgs":false,"family":"Sullivan","given":"Timothy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":809980,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDonnell, Todd C. 0000-0002-5231-105X","orcid":"https://orcid.org/0000-0002-5231-105X","contributorId":196721,"corporation":false,"usgs":false,"family":"McDonnell","given":"Todd","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":809981,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bailey, Scott W. 0000-0002-9160-156X","orcid":"https://orcid.org/0000-0002-9160-156X","contributorId":178217,"corporation":false,"usgs":false,"family":"Bailey","given":"Scott","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":809982,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70191807,"text":"sir20175097 - 2017 - Simulation of groundwater and surface-water flow in the upper Deschutes Basin, Oregon","interactions":[],"lastModifiedDate":"2017-10-23T11:30:00","indexId":"sir20175097","displayToPublicDate":"2017-10-20T00:00:00","publicationYear":"2017","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":"2017-5097","title":"Simulation of groundwater and surface-water flow in the upper Deschutes Basin, Oregon","docAbstract":"<p class=\"p1\">This report describes a hydrologic model for the upper Deschutes Basin in central Oregon developed using the U.S. Geological Survey (USGS) integrated Groundwater and Surface-Water Flow model (GSFLOW). The upper Deschutes Basin, which drains much of the eastern side of the Cascade Range in Oregon, is underlain by large areas of permeable volcanic rock. That permeability, in combination with the large annual precipitation at high elevations, results in a substantial regional aquifer system and a stream system that is heavily groundwater dominated.</p><p class=\"p1\">The upper Deschutes Basin is also an area of expanding population and increasing water demand for public supply and agriculture. Surface water was largely developed for agricultural use by the mid-20th century, and is closed to additional appropriations. Consequently, water users look to groundwater to satisfy the growing demand. The well‑documented connection between groundwater and the stream system, and the institutional and legal restrictions on streamflow depletion by wells, resulted in the Oregon Water Resources Department (OWRD) instituting a process whereby additional groundwater pumping can be permitted only if the effects to streams are mitigated, for example, by reducing permitted surface-water diversions. Implementing such a program requires understanding of the spatial and temporal distribution of effects to streams from groundwater pumping. A groundwater model developed in the early 2000s by the USGS and OWRD has been used to provide insights into the distribution of streamflow depletion by wells, but lacks spatial resolution in sensitive headwaters and spring areas.</p><p class=\"p1\">The integrated model developed for this project, based largely on the earlier model, has a much finer grid spacing allowing resolution of sensitive headwater streams and important spring areas, and simulates a more complete set of surface processes as well as runoff and groundwater flow. In addition, the integrated model includes improved representation of subsurface geology and explicitly simulates the effects of hydrologically important fault zones not included in the previous model.</p><p class=\"p2\">The upper Deschutes Basin GSFLOW model was calibrated using an iterative trial and error approach using measured water-level elevations (water levels) from 800 wells, 144 of which have time series of 10 or more measurements. Streamflow was calibrated using data from 21 gage locations. At 14 locations where measured flows are heavily influenced by reservoir operations and irrigation diversions, so called “<i>naturalized</i>” flows, with the effects of reservoirs and diversion removed, developed by the Bureau of Reclamation, were used for calibration. Surface energy and moisture processes such as solar radiation, snow accumulation and melting, and evapotranspiration were calibrated using national datasets as well as data from long-term measurement sites in the basin. The calibrated Deschutes GSFLOW model requires daily precipitation, minimum and maximum air temperature data, and monthly data describing groundwater pumping and artificial recharge from leaking irrigation canals (which are a significant source of groundwater recharge).</p><p class=\"p2\">The calibrated model simulates the geographic distribution of hydraulic head over the 5,000 ft range measured in the basin, with a median absolute residual of about 53 ft. Temporal variations in head resulting from climate cycles, pumping, and canal leakage are well simulated over the model area. Simulated daily streamflow matches gaged flows or calculated naturalized flows for streams including the Crooked and Metolius Rivers, and lower parts of the mainstem Deschutes River. Seasonal patterns of runoff are less well fit in some upper basin streams. Annual water balances of streamflow are good over most of the model domain. Model fit and overall capabilities are appropriate for the objectives of the project.</p><p class=\"p2\">The integrated model results confirm findings from other studies and models indicating that most streamflow in the upper Deschutes Basin comes directly from groundwater discharge. The integrated model provides additional insights about the components of streamflow including direct groundwater discharge to streams, interflow, groundwater discharge to the land surface (Dunnian flow), and direct runoff (Hortonian flow). The new model provides improved capability for exploring the timing and distribution of&nbsp;</p><p class=\"p1\">streamflow capture by wells, and the hydrologic response to changes in other external stresses such as canal operation, irrigation, and drought. Because the model uses basic meteorological data as the primary input; and simulates surface energy and moisture balances, groundwater recharge and flow, and all components of streamflow; it is well suited for exploring the hydrologic response to climate change, although no such simulations are included in this report.</p><p class=\"p1\">The model was developed as a tool for future application; however, example simulations are provided in this report. In the example simulations, the model is used to explore the influence of well location and geologic structure on stream capture by pumping wells. Wells were simulated at three locations within a 12-mi area close to known groundwater discharge areas and crossed by a regional fault zone. Simulations indicate that the magnitude and timing of stream capture from pumping is largely controlled by the geographic location of the wells, but that faults can have a large influence on the propagation of pumping stresses.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175097","collaboration":"Prepared in cooperation with the Oregon Water Resources Department","usgsCitation":"Gannett, M.W., Lite, K.E., Jr., Risley, J.C., Pischel, E.M., and La Marche, J.L., 2017, Simulation of groundwater and surface-water flow in the upper Deschutes Basin, Oregon: U.S. Geological Survey Scientific Investigations Report 2017-5097, 68 p., https://doi.org/10.3133/sir20175097.","productDescription":"Report: viii, 68 p.; Model Archive","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-085102","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":347011,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.5066/F7154F9K","text":"Model Archive","description":"SIR 2017-5097 Model Archive"},{"id":346984,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5097/coverthb.jpg"},{"id":346985,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5097/sir20175097.pdf","text":"Report","size":"5.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5097"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Deschutes Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.19268798828126,\n              43.395069512861355\n            ],\n            [\n              -120.7452392578125,\n              43.395069512861355\n            ],\n            [\n              -120.7452392578125,\n              44.939529212272305\n            ],\n            [\n              -122.19268798828126,\n              44.939529212272305\n            ],\n            [\n              -122.19268798828126,\n              43.395069512861355\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_or@usgs.gov\" data-mce-href=\"mailto:dc_or@usgs.gov\">Director</a>, <a href=\"https://or.water.usgs.gov\" target=\"blank\" data-mce-href=\"https://or.water.usgs.gov\">Oregon Water Science Center</a><br> U.S. Geological Survey<br> 2130 SW 5th Avenue<br> Portland, Oregon 97201</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Hydrogeology<br></li><li>Simulation Model<br></li><li>Model Calibration<br></li><li>Model Fit<br></li><li>Evaluating Effects of Proximity and Geologic Structure on Changes in Springs and Streamflow Resulting from Groundwater Pumping<br></li><li>Model Limitations<br></li><li>Summary<br></li><li>Acknowledgments<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2017-10-20","noUsgsAuthors":false,"publicationDate":"2017-10-20","publicationStatus":"PW","scienceBaseUri":"59eb0b2de4b0026a55fe2ef6","contributors":{"authors":[{"text":"Gannett, Marshall W. 0000-0003-2498-2427 mgannett@usgs.gov","orcid":"https://orcid.org/0000-0003-2498-2427","contributorId":2942,"corporation":false,"usgs":true,"family":"Gannett","given":"Marshall","email":"mgannett@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713206,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lite, Kenneth E. Jr.","contributorId":37373,"corporation":false,"usgs":true,"family":"Lite","given":"Kenneth","suffix":"Jr.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":713207,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Risley, John C. 0000-0002-8206-5443 jrisley@usgs.gov","orcid":"https://orcid.org/0000-0002-8206-5443","contributorId":2698,"corporation":false,"usgs":true,"family":"Risley","given":"John","email":"jrisley@usgs.gov","middleInitial":"C.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pischel, Esther M. 0000-0002-0393-6993 epischel@usgs.gov","orcid":"https://orcid.org/0000-0002-0393-6993","contributorId":5508,"corporation":false,"usgs":true,"family":"Pischel","given":"Esther","email":"epischel@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713208,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"La Marche, Jonathan L.","contributorId":197340,"corporation":false,"usgs":false,"family":"La Marche","given":"Jonathan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":713210,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
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