{"pageNumber":"591","pageRowStart":"14750","pageSize":"25","recordCount":40790,"records":[{"id":70114209,"text":"sir20145107 - 2014 - Occurrence and transport of nitrogen in the Big Sunflower River, northwestern Mississippi, October 2009-June 2011","interactions":[],"lastModifiedDate":"2014-07-29T08:14:25","indexId":"sir20145107","displayToPublicDate":"2014-07-28T16:29:00","publicationYear":"2014","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":"2014-5107","title":"Occurrence and transport of nitrogen in the Big Sunflower River, northwestern Mississippi, October 2009-June 2011","docAbstract":"<p>The Big Sunflower River Basin, located within the Yazoo River Basin, is subject to large annual inputs of nitrogen from agriculture, atmospheric deposition, and point sources. Understanding how nutrients are transported in, and downstream from, the Big Sunflower River is key to quantifying their eutrophying effects on the Gulf. Recent results from two Spatially Referenced Regressions on Watershed attributes (SPARROW models), which include the Big Sunflower River, indicate minimal losses of nitrogen in stream reaches typical of the main channels of major river systems. If SPARROW assumptions of relatively conservative transport of nitrogen are correct and surface-water losses through the bed of the Big Sunflower River are negligible, then options for managing nutrient loads to the Gulf of Mexico may be limited. Simply put, if every pound of nitrogen entering the Delta is eventually delivered to the Gulf, then the only effective nutrient management option in the Delta is to reduce inputs. If, on the other hand, it can be shown that processes within river channels of the Mississippi Delta act to reduce the mass of nitrogen in transport, other hydrologic approaches may be designed to further limit nitrogen transport. Direct validation of existing SPARROW models for the Delta is a first step in assessing the assumptions underlying those models.</p>\n<br/>\n<p>In order to characterize spatial and temporal variability of nitrogen in the Big Sunflower River Basin, water samples were collected at four U.S. Geological Survey gaging stations located on the Big Sunflower River between October 1, 2009, and June 30, 2011. Nitrogen concentrations were generally highest at each site during the spring of the 2010 water year and the fall and winter of the 2011 water year. Additionally, the dominant form of nitrogen varied between sites. For example, in samples collected from the most upstream site (Clarksdale), the concentration of organic nitrogen was generally higher than the concentrations of ammonia and nitrate plus nitrite; conversely, at sites farther downstream (that is, at Sunflower and Anguilla), nitrate plus nitrite concentrations were generally higher than concentrations of organic nitrogen and ammonia.</p>\n<br/>\n<p>In addition to the routinely collected samples, water samples from the Big Sunflower River Basin were collected using a Lagrangian sampling scheme, which attempts to follow a single mass of water through time in order to determine how it changes through processing or other pathways as the water moves downstream. Lagrangian sampling was conducted five times during the study period: (1) April 8–21, 2010, (2) May 12–June 3, 2010, (3) June 15–July 1, 2010, (4) August 23–30, 2010, and (5) May 16–20, 2011. Streamflow conditions were variable for each sampling event because of input from local precipitation and irrigation return flow, and streamflow losses through the streambed. Streamflow and total nitrogen flux increased with drainage area, and the dominant form of nitrogen varied with drainage area size and temporally across sampling events.</p>\n<br/>\n<p>Results from each method indicate relatively conservative transport of nitrogen within the 160 miles between Clarksdale and Anguilla, providing further validation of the SPARROW models. Furthermore, these results suggest relatively conservative transport of nitrogen from the Big Sunflower River to the Gulf of Mexico and, therefore, imply a fairly close association of nutrient application and export from the Big Sunflower River Basin to the Mississippi River. However, within the Big Sunflower River Basin, two potential nitrogen sinks were identified and include the transport and potential transformation of nitrogen through the streambed and the sequestration and potential transformation of nitrogen above the drainage control structures downstream of Anguilla. By coupling these potential loss mechanisms with nitrogen transport dynamics, it may be possible to further reduce the amount of nitrogen leaving the Big Sunflower River Basin and ultimately arriving at the Gulf of Mexico.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145107","collaboration":"Prepared in cooperation with the United States Army Corps of Engineers, Vicksburg District","usgsCitation":"Barlow, J.R., and Coupe, R.H., 2014, Occurrence and transport of nitrogen in the Big Sunflower River, northwestern Mississippi, October 2009-June 2011: U.S. Geological Survey Scientific Investigations Report 2014-5107, Report: vi, 29 p.; Appendix 1, https://doi.org/10.3133/sir20145107.","productDescription":"Report: vi, 29 p.; Appendix 1","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2009-10-01","temporalEnd":"2011-06-30","ipdsId":"IP-040979","costCenters":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true}],"links":[{"id":291229,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145107.jpg"},{"id":291226,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5107/"},{"id":291227,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5107/pdf/sir2014-5107.pdf"},{"id":291228,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5107/appendix/sir2014-5107_appendix1.xlsx"}],"country":"United States","state":"Arkansas;Louisiana;Mississippi","otherGeospatial":"Big Sunflower River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91.25,32.75 ], [ -91.25,34.75 ], [ -90.50,34.75 ], [ -90.50,32.75 ], [ -91.25,32.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f0a7e4b0bc0bec09f8af","contributors":{"authors":[{"text":"Barlow, Jeannie R.B.","contributorId":33965,"corporation":false,"usgs":true,"family":"Barlow","given":"Jeannie","email":"","middleInitial":"R.B.","affiliations":[],"preferred":false,"id":495269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coupe, Richard H. 0000-0001-8679-1015 rhcoupe@usgs.gov","orcid":"https://orcid.org/0000-0001-8679-1015","contributorId":551,"corporation":false,"usgs":true,"family":"Coupe","given":"Richard","email":"rhcoupe@usgs.gov","middleInitial":"H.","affiliations":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true}],"preferred":true,"id":495268,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70114018,"text":"ofr20141126 - 2014 - Estimation of methane concentrations and loads in groundwater discharge to Sugar Run, Lycoming County, Pennsylvania","interactions":[],"lastModifiedDate":"2014-07-28T10:24:54","indexId":"ofr20141126","displayToPublicDate":"2014-07-28T10:12:00","publicationYear":"2014","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":"2014-1126","title":"Estimation of methane concentrations and loads in groundwater discharge to Sugar Run, Lycoming County, Pennsylvania","docAbstract":"A stream-sampling study was conducted to estimate methane concentrations and loads in groundwater discharge to a small stream in an active shale-gas development area of northeastern Pennsylvania. Grab samples collected from 15 streams in Bradford, Lycoming, Susquehanna, and Tioga Counties, Pa., during a reconnaissance survey in May and June 2013 contained dissolved methane concentrations ranging from less than the minimum reporting limit (1.0) to 68.5 micrograms per liter (µg/L). The stream-reach mass-balance method of estimating concentrations and loads of methane in groundwater discharge was applied to a 4-kilometer (km) reach of Sugar Run in Lycoming County, one of the four streams with methane concentrations greater than or equal to 5 µg/L. Three synoptic surveys of stream discharge and methane concentrations were conducted during base-flow periods in May, June, and November 2013. Stream discharge at the lower end of the reach was about 0.10, 0.04, and 0.02 cubic meters per second, respectively, and peak stream methane concentrations were about 20, 67, and 29 µg/L. In order to refine estimated amounts of groundwater discharge and locations where groundwater with methane discharges to the stream, the lower part of the study reach was targeted more precisely during the successive studies, with approximate spacing between stream sampling sites of 800 meters (m), 400 m, and 200 m, in May, June, and November, respectively. Samples collected from shallow piezometers and a seep near the location of the peak methane concentration measured in streamwater had groundwater methane concentrations of 2,300 to 4,600 µg/L. These field data, combined with one-dimensional stream-methane transport modeling, indicate groundwater methane loads of 1.8 ±0.8, 0.7 ±0.3, and 0.7 ±0.2 kilograms per day, respectively, discharging to Sugar Run. Estimated groundwater methane concentrations, based on the transport modeling, ranged from 100 to 3,200 µg/L. Although total methane load and the uncertainty in calculated loads both decreased with lower streamflow conditions and finer-resolution sampling in June and November, the higher loads during May could indicate seasonal variability in base flow. This is consistent with flowmeter measurements indicating that there was less inflow occurring at lower streamflow conditions during June and November.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141126","usgsCitation":"Heilweil, V.M., Risser, D.W., Conger, R.W., Grieve, P.L., and Hynek, S.A., 2014, Estimation of methane concentrations and loads in groundwater discharge to Sugar Run, Lycoming County, Pennsylvania: U.S. Geological Survey Open-File Report 2014-1126, viii, 31 p., https://doi.org/10.3133/ofr20141126.","productDescription":"viii, 31 p.","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-055342","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":291113,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141126.jpg"},{"id":291112,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1126/"},{"id":291111,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1126/support/ofr2014-1126.pdf"}],"country":"United States","state":"Pennsylvania","county":"Lycoming County","otherGeospatial":"Sugar Run","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -77.60,41.25 ], [ -77.60,42.00 ], [ -75.50,42.00 ], [ -75.50,41.25 ], [ -77.60,41.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f0a7e4b0bc0bec09f8b3","contributors":{"authors":[{"text":"Heilweil, Victor M. heilweil@usgs.gov","contributorId":837,"corporation":false,"usgs":true,"family":"Heilweil","given":"Victor","email":"heilweil@usgs.gov","middleInitial":"M.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":495231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Risser, Dennis W. 0000-0001-9597-5406 dwrisser@usgs.gov","orcid":"https://orcid.org/0000-0001-9597-5406","contributorId":898,"corporation":false,"usgs":true,"family":"Risser","given":"Dennis","email":"dwrisser@usgs.gov","middleInitial":"W.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":495232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conger, Randall W. rwconger@usgs.gov","contributorId":2086,"corporation":false,"usgs":true,"family":"Conger","given":"Randall","email":"rwconger@usgs.gov","middleInitial":"W.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":495233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grieve, Paul L.","contributorId":45643,"corporation":false,"usgs":true,"family":"Grieve","given":"Paul","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":495234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hynek, Scott A. 0000-0002-6885-0445","orcid":"https://orcid.org/0000-0002-6885-0445","contributorId":52091,"corporation":false,"usgs":true,"family":"Hynek","given":"Scott","email":"","middleInitial":"A.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":false,"id":495235,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70118245,"text":"70118245 - 2014 - Unsupported inferences of high-severity fire in historical dry forests of the western United States: Response to Williams and Baker","interactions":[],"lastModifiedDate":"2018-01-12T15:59:01","indexId":"70118245","displayToPublicDate":"2014-07-28T09:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Unsupported inferences of high-severity fire in historical dry forests of the western United States: Response to Williams and Baker","docAbstract":"Reconstructions of dry western US forests in the late 19th century in Arizona, Colorado and Oregon based on General Land Office records were used by Williams & Baker (2012; Global Ecology and Biogeography, 21, 1042–1052; hereafter W&B) to infer past fire regimes with substantial moderate and high-severity burning. The authors concluded that present-day large, high-severity fires are not distinguishable from historical patterns. We present evidence of important errors in their study. First, the use of tree size distributions to reconstruct past fire severity and extent is not supported by empirical age–size relationships nor by studies that directly quantified disturbance history in these forests. Second, the fire severity classification of W&B is qualitatively different from most modern classification schemes, and is based on different types of data, leading to an inappropriate comparison. Third, we note that while W&B asserted ‘surprising’ heterogeneity in their reconstructions of stand density and species composition, their data are not substantially different from many previous studies which reached very different conclusions about subsequent forest and fire behaviour changes. Contrary to the conclusions of W&B, the preponderance of scientific evidence indicates that conservation of dry forest ecosystems in the western United States and their ecological, social and economic value is not consistent with a present-day disturbance regime of large, high-severity fires, especially under changing climate","language":"English","publisher":"Wiley","doi":"10.1111/geb.12136","usgsCitation":"Fule, P.Z., Swetnam, T., Brown, P.M., Falk, D., Peterson, D.L., Allen, C.D., Aplet, G.H., Battaglia, M., Binkley, D., Farris, C., Keane, R.E., Margolis, E., Grissino-Mayer, H., Miller, C., Sieg, C.H., Skinner, C., Stephens, S.L., and Taylor, A., 2014, Unsupported inferences of high-severity fire in historical dry forests of the western United States: Response to Williams and Baker: Global Ecology and Biogeography, v. 23, no. 7, p. 825-830, https://doi.org/10.1111/geb.12136.","productDescription":"6 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A.","contributorId":90230,"corporation":false,"usgs":true,"family":"Falk","given":"Donald A.","affiliations":[],"preferred":false,"id":496542,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peterson, David L.","contributorId":94643,"corporation":false,"usgs":false,"family":"Peterson","given":"David","email":"","middleInitial":"L.","affiliations":[{"id":12647,"text":"U.S. Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":496544,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science 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,{"id":70118084,"text":"70118084 - 2014 - Assessing the solubility controls on vanadium in groundwater, northeastern San Joaquin Valley, CA","interactions":[],"lastModifiedDate":"2014-07-28T10:01:01","indexId":"70118084","displayToPublicDate":"2014-07-25T14:35:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the solubility controls on vanadium in groundwater, northeastern San Joaquin Valley, CA","docAbstract":"<p>The solubility controls on vanadium (V) in groundwater were studied due to concerns over possible harmful health effects of ingesting V in drinking water. Vanadium concentrations in the northeastern San Joaquin Valley ranged from <3 μg/L to 70 μg/L with a median of 21 μg/L. Concentrations of V were highest in samples collected from oxic groundwater (49% > 25 μg/L) and lowest in samples collected from anoxic groundwater (70% < 0.8 μg/L). In oxic groundwater, speciation modeling (SM) using PHREEQC predicted that V exists primarily as the oxyanion H<sub>2</sub>VO<sub>4</sub><sup>−</sup>. Adsorption/desorption reactions with mineral surfaces and associated oxide coatings were indicated as the primary solubility control of V<sup>5+</sup> oxyanions in groundwater. Environmental data showed that V concentrations in oxic groundwater generally increased with increasing groundwater pH. However, data from adsorption isotherm experiments indicated that small variations in pH (7.4–8.2) were not likely as an important a factor as the inherent adsorption capacity of oxide assemblages coating the surface of mineral grains. In suboxic groundwater, accurate SM modeling was difficult since Eh measurements of source water were not measured in this study. Vanadium concentrations in suboxic groundwater decreased with increasing pH indicating that V may exist as an oxycationic species [e.g. V(OH)<sub>3</sub><sup>+</sup>]. Vanadium may complex with dissolved inorganic and organic ligands under suboxic conditions, which could alter the adsorption behavior of V in groundwater. Speciation modeling did not predict the existence of V-inorganic ligand complexes and organic ligands were not collected as part of this study. More work is needed to determine processes governing V solubility under suboxic groundwater conditions. Under anoxic groundwater conditions, SM predicts that aqueous V exists as the uncharged V(OH)<sub>3</sub> molecule. However, exceedingly low V concentrations show that V is sparingly soluble in anoxic conditions. Results indicated that V may be precipitating as V<sup>3+</sup>- or mixed V<sup>3+</sup>/Fe<sup>3+</sup>-oxides in anoxic groundwater, which is consistent with results of a previous study. The fact that V appears insoluble in anoxic (Fe reducing) redox conditions indicates that the behavior of V is different than arsenic (As) in aquifer systems where the reductive dissolution of Fe-oxides with As adsorbed to the surface is a well-documented mechanism for increasing As concentrations in groundwater. This hypothesis is supported by the relation of V to As concentrations in oxic versus anoxic redox conditions.</p>\n<br>\n<p>Sequential extraction procedures (SEP) applied to aquifer material showed that the greatest amount of V was recovered by the nitric acid (HNO<sub>3</sub>) extract (37–71%), followed by the oxalate-ascorbic acid extract (19–60%) and the oxalate extract (3–14%). These results indicate that V was not associated with the solid phase as an easily exchangeable fraction. Although the total amount of V recovered was greatest for the HNO<sub>3</sub> extract that targets V adsorbed to sorption sites of crystalline Al, Fe and Mn oxides, the greatest V saturation of sorption sites appeared to occur on the amorphous and poorly crystalline oxide solid phases targeted by the oxalate and oxalate-ascorbic acid extracts respectively. Adsorption isotherm experiments showed no correlation between V sorption and any of the fractions identified by the SEP. This lack of correlation indicates the application of an SEP alone is not adequate to estimate the sorption characteristics of V in an aquifer system.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Applied Geochemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2014.06.025","usgsCitation":"Wright, M.T., Stollenwerk, K.G., and Belitz, K., 2014, Assessing the solubility controls on vanadium in groundwater, northeastern San Joaquin Valley, CA: Applied Geochemistry, v. 48, p. 41-52, https://doi.org/10.1016/j.apgeochem.2014.06.025.","productDescription":"12 p.","startPage":"41","endPage":"52","numberOfPages":"12","ipdsId":"IP-045310","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":291026,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291025,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.apgeochem.2014.06.025"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.5,37.0 ], [ -121.5,38.5 ], [ -120.0,38.5 ], [ -120.0,37.0 ], [ -121.5,37.0 ] ] ] } } ] }","volume":"48","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f0a7e4b0bc0bec09f8bd","contributors":{"authors":[{"text":"Wright, Michael T. 0000-0003-0653-6466 mtwright@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-6466","contributorId":1508,"corporation":false,"usgs":true,"family":"Wright","given":"Michael","email":"mtwright@usgs.gov","middleInitial":"T.","affiliations":[],"preferred":false,"id":496245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stollenwerk, Kenneth G. kgstolle@usgs.gov","contributorId":578,"corporation":false,"usgs":true,"family":"Stollenwerk","given":"Kenneth","email":"kgstolle@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":496244,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":496243,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70118051,"text":"70118051 - 2014 - Analysis of the impact of spatial resolution on land/water classifications using high-resolution aerial imagery","interactions":[],"lastModifiedDate":"2014-07-28T09:59:28","indexId":"70118051","displayToPublicDate":"2014-07-25T13:04:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Analysis of the impact of spatial resolution on land/water classifications using high-resolution aerial imagery","docAbstract":"<p>Long-term monitoring efforts often use remote sensing to track trends in habitat or landscape conditions over time. To most appropriately compare observations over time, long-term monitoring efforts strive for consistency in methods. Thus, advances and changes in technology over time can present a challenge. For instance, modern camera technology has led to an increasing availability of very high-resolution imagery (i.e. submetre and metre) and a shift from analogue to digital photography. While numerous studies have shown that image resolution can impact the accuracy of classifications, most of these studies have focused on the impacts of comparing spatial resolution changes greater than 2 m. Thus, a knowledge gap exists on the impacts of minor changes in spatial resolution (i.e. submetre to about 1.5 m) in very high-resolution aerial imagery (i.e. 2 m resolution or less).</p>\n<br>\n<p>This study compared the impact of spatial resolution on land/water classifications of an area dominated by coastal marsh vegetation in Louisiana, USA, using 1:12,000 scale colour-infrared analogue aerial photography (AAP) scanned at four different dot-per-inch resolutions simulating ground sample distances (GSDs) of 0.33, 0.54, 1, and 2 m. Analysis of the impact of spatial resolution on land/water classifications was conducted by exploring various spatial aspects of the classifications including density of waterbodies and frequency distributions in waterbody sizes. This study found that a small-magnitude change (1–1.5 m) in spatial resolution had little to no impact on the amount of water classified (i.e. percentage mapped was less than 1.5%), but had a significant impact on the mapping of very small waterbodies (i.e. waterbodies ≤ 250 m<sup>2</sup>). These findings should interest those using temporal image classifications derived from very high-resolution aerial photography as a component of long-term monitoring programs.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2014.938181","usgsCitation":"Enwright, N.M., Jones, W.R., Garber, A., and Keller, M.J., 2014, Analysis of the impact of spatial resolution on land/water classifications using high-resolution aerial imagery: International Journal of Remote Sensing, v. 35, no. 13, p. 5280-5288, https://doi.org/10.1080/01431161.2014.938181.","productDescription":"9 p.","startPage":"5280","endPage":"5288","numberOfPages":"9","ipdsId":"IP-039101","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":291015,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":290987,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/01431161.2014.938181"}],"country":"United States","state":"Louisiana","otherGeospatial":"Lake Pontchartrain","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.9411,30.1971 ], [ -89.9411,30.3175 ], [ -89.7413,30.3175 ], [ -89.7413,30.1971 ], [ -89.9411,30.1971 ] ] ] } } ] }","volume":"35","issue":"13","noUsgsAuthors":false,"publicationDate":"2014-07-21","publicationStatus":"PW","scienceBaseUri":"57f7f0a7e4b0bc0bec09f8bf","contributors":{"authors":[{"text":"Enwright, Nicholas M. 0000-0002-7887-3261 enwrightn@usgs.gov","orcid":"https://orcid.org/0000-0002-7887-3261","contributorId":4880,"corporation":false,"usgs":true,"family":"Enwright","given":"Nicholas","email":"enwrightn@usgs.gov","middleInitial":"M.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":496187,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, William R. 0000-0002-5493-4138 jonesb@usgs.gov","orcid":"https://orcid.org/0000-0002-5493-4138","contributorId":463,"corporation":false,"usgs":true,"family":"Jones","given":"William","email":"jonesb@usgs.gov","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":496186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garber, Adrienne L. 0000-0003-1139-8256","orcid":"https://orcid.org/0000-0003-1139-8256","contributorId":10332,"corporation":false,"usgs":true,"family":"Garber","given":"Adrienne L.","affiliations":[],"preferred":false,"id":496188,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keller, Matthew J.","contributorId":63330,"corporation":false,"usgs":true,"family":"Keller","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":496189,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70159872,"text":"70159872 - 2014 - Great Apes","interactions":[],"lastModifiedDate":"2016-01-26T14:41:35","indexId":"70159872","displayToPublicDate":"2014-07-25T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Great Apes","docAbstract":"<p><span>Anesthesia of great apes is often necessary to conduct diagnostic analysis, provide therapeutics, facilitate surgical procedures, and enable transport and translocation for conservation purposes. Due to the stress of remote delivery injection of anesthetic agents, recent studies have focused on oral delivery and/or transmucosal absorption of preanesthetic and anesthetic agents. Maintenance of the airway and provision of oxygen is an important aspect of anesthesia in great ape species. The provision of analgesia is an important aspect of the anesthesia protocol for any procedure involving painful stimuli. Opioids and nonsteroidal anti-inflammatory drugs (NSAIDs) are often administered alone, or in combination to provide multi-modal analgesia. There is increasing conservation management of in situ great ape populations, which has resulted in the development of field anesthesia techniques for free-living great apes for the purposes of translocation, reintroduction into the wild, and clinical interventions.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Zoo animal and wildlife immobilization and anesthesia","language":"English","publisher":"Wiley","publisherLocation":"Ames, IA","doi":"10.1002/9781118792919.ch39","usgsCitation":"Sleeman, J.M., and Cerveny, S., 2014, Great Apes, chap. <i>of</i> Zoo animal and wildlife immobilization and anesthesia, p. 573-584, https://doi.org/10.1002/9781118792919.ch39.","productDescription":"12 p.","startPage":"573","endPage":"584","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-029867","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":314885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2014-07-25","publicationStatus":"PW","scienceBaseUri":"56a8a6c4e4b0b28f1184dbf4","contributors":{"authors":[{"text":"Sleeman, Jonathan M. 0000-0002-9910-6125 jsleeman@usgs.gov","orcid":"https://orcid.org/0000-0002-9910-6125","contributorId":128,"corporation":false,"usgs":true,"family":"Sleeman","given":"Jonathan","email":"jsleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":580838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cerveny, Shannon","contributorId":152588,"corporation":false,"usgs":false,"family":"Cerveny","given":"Shannon","email":"","affiliations":[],"preferred":false,"id":589842,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70116319,"text":"sir20145128 - 2014 - Flood-inundation maps for the North Branch Elkhart River at Cosperville, Indiana","interactions":[],"lastModifiedDate":"2014-07-24T14:02:59","indexId":"sir20145128","displayToPublicDate":"2014-07-24T13:45:00","publicationYear":"2014","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":"2014-5128","title":"Flood-inundation maps for the North Branch Elkhart River at Cosperville, Indiana","docAbstract":"<p>Digital flood-inundation maps for a reach of the North Branch Elkhart River at Cosperville, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the U.S. Army Corps of Engineers, Detroit District. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at <a href=\"http://water.usgs.gov/osw/flood_inundation/\" target=\"_blank\">http://water.usgs.gov/osw/flood_inundation/</a> depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at USGS streamgage 04100222, North Branch Elkhart River at Cosperville, Ind. Current conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the Internet at <a href=\"http://waterdata.usgs.gov/in/nwis/uv?site_no=04100222\" target=\"_blank\">http://waterdata.usgs.gov/in/nwis/uv?site_no=04100222</a>. In addition, information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (<a href=\"http:/water.weather.gov/ahps/\" target=\"_blank\">http:/water.weather.gov/ahps/</a>). The NWS AHPS forecasts flood hydrographs at many places that are often colocated with USGS streamgages, including the North Branch Elkhart River at Cosperville, Ind. NWS AHPS-forecast peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.</p>\n<br/>\n<p>For this study, flood profiles were computed for the North Branch Elkhart River reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relations at USGS streamgage 04100222, North Branch Elkhart River at Cosperville, Ind., and preliminary high-water marks from the flood of March 1982. The calibrated hydraulic model was then used to determine four water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the highest stage of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM, derived from Light Detection and Ranging [LiDAR]) in order to delineate the area flooded at each water level.</p>\n<br/>\n<p>The availability of these maps, along with Internet information regarding current stage from the USGS streamgage 04100222, North Branch Elkhart River at Cosperville, Ind., and forecast stream stages from the NWS AHPS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145128","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Detroit District","usgsCitation":"Kim, M.H., and Johnson, E.M., 2014, Flood-inundation maps for the North Branch Elkhart River at Cosperville, Indiana: U.S. Geological Survey Scientific Investigations Report 2014-5128, Report: iv, 9 p.; Downloads Directory, https://doi.org/10.3133/sir20145128.","productDescription":"Report: iv, 9 p.; Downloads Directory","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-054937","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":290943,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145128.jpg"},{"id":290941,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5128/pdf/sir2014-5128.pdf"},{"id":290942,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2014/5128/downloads"},{"id":290932,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5128/"}],"projection":"Indiana State Plane Eastern Zone","datum":"North American Datum of 1983","country":"United States","state":"Indiana","city":"Cosperville","otherGeospatial":"North Branch Elkhart River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -85.504146,41.464805 ], [ -85.504146,41.525172 ], [ -85.379777,41.525172 ], [ -85.379777,41.464805 ], [ -85.504146,41.464805 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f0a7e4b0bc0bec09f8c9","contributors":{"authors":[{"text":"Kim, Moon H. 0000-0002-4328-8409 mkim@usgs.gov","orcid":"https://orcid.org/0000-0002-4328-8409","contributorId":3211,"corporation":false,"usgs":true,"family":"Kim","given":"Moon","email":"mkim@usgs.gov","middleInitial":"H.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":495763,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Esther M.","contributorId":80199,"corporation":false,"usgs":true,"family":"Johnson","given":"Esther","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":495764,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70117643,"text":"70117643 - 2014 - Incorporation of inorganic mercury (Hg2+) in pelagic food webs of ultraoligotrophic and oligotrophic lakes: the role of different plankton size fractions and species assemblages","interactions":[],"lastModifiedDate":"2018-09-14T15:53:51","indexId":"70117643","displayToPublicDate":"2014-07-24T12:52:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Incorporation of inorganic mercury (Hg<sup>2+</sup>) in pelagic food webs of ultraoligotrophic and oligotrophic lakes: the role of different plankton size fractions and species assemblages","title":"Incorporation of inorganic mercury (Hg2+) in pelagic food webs of ultraoligotrophic and oligotrophic lakes: the role of different plankton size fractions and species assemblages","docAbstract":"In lake food webs, pelagic basal organisms such as bacteria and phytoplankton incorporate mercury (Hg<sup>2+</sup>) from the dissolved phase and pass the adsorbed and internalized Hg to higher trophic levels. This experimental investigation addresses the incorporation of dissolved Hg<sup>2+</sup> by four plankton fractions (picoplankton: 0.2–2.7 μm; pico + nanoplankton: 0.2–20 μm; microplankton: 20–50 μm; and mesoplankton: 50–200 μm) obtained from four Andean Patagonian lakes, using the radioisotope <sup>197</sup>Hg<sup>2+</sup>. Species composition and abundance were determined in each plankton fraction. In addition, morphometric parameters such as surface and biovolume were calculated using standard geometric models. The incorporation of Hg<sup>2+</sup> in each plankton fraction was analyzed through three concentration factors: BCF (bioconcentration factor) as a function of cell or individual abundance, SCF (surface concentration factor) and VCF (volume concentration factor) as functions of individual exposed surface and biovolume, respectively. Overall, this investigation showed that through adsorption and internalization, pico + nanoplankton play a central role leading the incorporation of Hg<sup>2+</sup> in pelagic food webs of Andean lakes. Larger planktonic organisms included in the micro- and mesoplankton fractions incorporate Hg<sup>2+</sup> by surface adsorption, although at a lesser extent. Mixotrophic bacterivorous organisms dominate the different plankton fractions of the lakes connecting trophic levels through microbial loops (e.g., bacteria–nanoflagellates–crustaceans; bacteria–ciliates–crustaceans; endosymbiotic algae–ciliates). These bacterivorous organisms, which incorporate Hg from the dissolved phase and through their prey, appear to explain the high incorporation of Hg<sup>2+</sup> observed in all the plankton fractions.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2014.06.138","usgsCitation":"Soto Cardenas, C., Dieguez, M.C., Ribeiro Guevara, S., Marvin-DiPasquale, M., and Queimalinos, C.P., 2014, Incorporation of inorganic mercury (Hg2+) in pelagic food webs of ultraoligotrophic and oligotrophic lakes: the role of different plankton size fractions and species assemblages: Science of the Total Environment, v. 494-495, p. 65-73, https://doi.org/10.1016/j.scitotenv.2014.06.138.","productDescription":"9 p.","startPage":"65","endPage":"73","numberOfPages":"9","ipdsId":"IP-057656","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":472859,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.scitotenv.2014.06.138","text":"External Repository"},{"id":290926,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":290922,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.scitotenv.2014.06.138"}],"country":"Argentina","otherGeospatial":"Patagonia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.599917,-41.115272 ], [ -71.599917,-41.050014 ], [ -71.460364,-41.050014 ], [ -71.460364,-41.115272 ], [ -71.599917,-41.115272 ] ] ] } } ] }","volume":"494-495","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f0a7e4b0bc0bec09f8cb","contributors":{"authors":[{"text":"Soto Cardenas, Carolina","contributorId":28535,"corporation":false,"usgs":true,"family":"Soto Cardenas","given":"Carolina","email":"","affiliations":[],"preferred":false,"id":496047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dieguez, Maria C.","contributorId":41336,"corporation":false,"usgs":true,"family":"Dieguez","given":"Maria","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":496048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ribeiro Guevara, Sergio","contributorId":11956,"corporation":false,"usgs":true,"family":"Ribeiro Guevara","given":"Sergio","affiliations":[],"preferred":false,"id":496045,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marvin-DiPasquale, Mark","contributorId":57423,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","affiliations":[],"preferred":false,"id":496049,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Queimalinos, Claudia P.","contributorId":23437,"corporation":false,"usgs":true,"family":"Queimalinos","given":"Claudia","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":496046,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70117797,"text":"70117797 - 2014 - Inference for finite-sample trajectories in dynamic multi-state site-occupancy models using hidden Markov model smoothing","interactions":[],"lastModifiedDate":"2014-07-24T12:49:41","indexId":"70117797","displayToPublicDate":"2014-07-24T12:44:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1573,"text":"Environmental and Ecological Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Inference for finite-sample trajectories in dynamic multi-state site-occupancy models using hidden Markov model smoothing","docAbstract":"Ecologists and wildlife biologists increasingly use latent variable models to study patterns of species occurrence when detection is imperfect. These models have recently been generalized to accommodate both a more expansive description of state than simple presence or absence, and Markovian dynamics in the latent state over successive sampling seasons. In this paper, we write these multi-season, multi-state models as hidden Markov models to find both maximum likelihood estimates of model parameters and finite-sample estimators of the trajectory of the latent state over time. These estimators are especially useful for characterizing population trends in species of conservation concern. We also develop parametric bootstrap procedures that allow formal inference about latent trend. We examine model behavior through simulation, and we apply the model to data from the North American Amphibian Monitoring Program.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental and Ecological Statistics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10651-013-0256-1","usgsCitation":"Fiske, I.J., Royle, J., and Gross, K., 2014, Inference for finite-sample trajectories in dynamic multi-state site-occupancy models using hidden Markov model smoothing: Environmental and Ecological Statistics, v. 21, no. 2, p. 313-328, https://doi.org/10.1007/s10651-013-0256-1.","productDescription":"16 p.","startPage":"313","endPage":"328","numberOfPages":"16","ipdsId":"IP-019312","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":290919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":290916,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10651-013-0256-1"}],"volume":"21","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-06-25","publicationStatus":"PW","scienceBaseUri":"57f7f0a7e4b0bc0bec09f8cd","contributors":{"authors":[{"text":"Fiske, Ian J.","contributorId":96411,"corporation":false,"usgs":true,"family":"Fiske","given":"Ian","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":496095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":80808,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":496094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gross, Kevin","contributorId":71483,"corporation":false,"usgs":true,"family":"Gross","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":496093,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70117794,"text":"70117794 - 2014 - Integrating land cover modeling and adaptive management to conserve endangered species and reduce catastrophic fire risk","interactions":[],"lastModifiedDate":"2014-07-24T11:23:58","indexId":"70117794","displayToPublicDate":"2014-07-24T11:06:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Integrating land cover modeling and adaptive management to conserve endangered species and reduce catastrophic fire risk","docAbstract":"Land cover modeling is used to inform land management, but most often via a two-step process, where science informs how management alternatives can influence resources, and then, decision makers can use this information to make decisions. A more efficient process is to directly integrate science and decision-making, where science allows us to learn in order to better accomplish management objectives and is developed to address specific decisions. Co-development of management and science is especially productive when decisions are complicated by multiple objectives and impeded by uncertainty. Multiple objectives can be met by the specification of tradeoffs, and relevant uncertainty can be addressed through targeted science (i.e., models and monitoring). We describe how to integrate habitat and fuel monitoring with decision-making focused on the dual objectives of managing for endangered species and minimizing catastrophic fire risk. Under certain conditions, both objectives might be achieved by a similar management policy; other conditions require tradeoffs between objectives. Knowledge about system responses to actions can be informed by developing hypotheses based on ideas about fire behavior and then applying competing management actions to different land units in the same system state. Monitoring and management integration is important to optimize state-specific management decisions and to increase knowledge about system responses. We believe this approach has broad utility and identifies a clear role for land cover modeling programs intended to inform decision-making.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Land","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"MDPI AG","publisherLocation":"Basel, Switzerland","doi":"10.3390/land3030874","usgsCitation":"Breininger, D., Duncan, B., Eaton, M.J., Johnson, F., and Nichols, J., 2014, Integrating land cover modeling and adaptive management to conserve endangered species and reduce catastrophic fire risk: Land, v. 3, no. 3, p. 874-897, https://doi.org/10.3390/land3030874.","productDescription":"24 p.","startPage":"874","endPage":"897","numberOfPages":"24","ipdsId":"IP-056595","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":472862,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/land3030874","text":"Publisher Index Page"},{"id":290894,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":290887,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3390/land3030874"}],"volume":"3","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-07-24","publicationStatus":"PW","scienceBaseUri":"57f7f0a7e4b0bc0bec09f8d1","contributors":{"authors":[{"text":"Breininger, David","contributorId":33226,"corporation":false,"usgs":true,"family":"Breininger","given":"David","affiliations":[],"preferred":false,"id":496085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duncan, Brean","contributorId":95809,"corporation":false,"usgs":true,"family":"Duncan","given":"Brean","affiliations":[],"preferred":false,"id":496087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eaton, Mitchell J. meaton@usgs.gov","contributorId":3912,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","email":"meaton@usgs.gov","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":false,"id":496083,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Fred 0000-0002-5854-3695","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":33227,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","affiliations":[],"preferred":false,"id":496086,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nichols, James","contributorId":26059,"corporation":false,"usgs":true,"family":"Nichols","given":"James","affiliations":[],"preferred":false,"id":496084,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70117795,"text":"70117795 - 2014 - Mobilization of selenium from the Mancos Shale and associated soils in the lower Uncompahgre River Basin, Colorado","interactions":[],"lastModifiedDate":"2014-07-24T10:50:58","indexId":"70117795","displayToPublicDate":"2014-07-24T10:40:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Mobilization of selenium from the Mancos Shale and associated soils in the lower Uncompahgre River Basin, Colorado","docAbstract":"This study investigates processes controlling mobilization of selenium in the lower part of the Uncompahgre River Basin in western Colorado. Selenium occurs naturally in the underlying Mancos Shale and is leached to groundwater and surface water by limited natural runoff, agricultural and domestic irrigation, and leakage from irrigation canals. Soil and sediment samples from the study area were tested using sequential extractions to identify the forms of selenium present in solid phases. Selenium speciation was characterized for nonirrigated and irrigated soils from an agricultural site and sediments from a wetland formed by a leaking canal. In nonirrigated areas, selenium was present in highly soluble sodium salts and gypsum. In irrigated soils, soluble forms of selenium were depleted and most selenium was associated with organic matter that was stable under near-surface weathering conditions. Laboratory leaching experiments and geochemical modeling confirm that selenium primarily is released to groundwater and surface water by dissolution of highly soluble selenium-bearing salts and gypsum present in soils and bedrock. Rates of selenium dissolution determined from column leachate experiments indicate that selenium is released most rapidly when water is applied to previously nonirrigated soils and sediment. High concentrations of extractable nitrate also were found in nonirrigated soils and bedrock that appear to be partially derived from weathered organic matter from the shale rather than from agricultural sources. Once selenium is mobilized, dissolved nitrate derived from natural sources appears to inhibit the reduction of dissolved selenium leading to elevated concentrations of selenium in groundwater. A conceptual model of selenium weathering is presented and used to explain seasonal variations in the surface-water chemistry of Loutzenhizer Arroyo, a major tributary contributor of selenium to the lower Uncompahgre River.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Applied Geochemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2014.06.024","usgsCitation":"Mast, M.A., Mills, T.J., Paschke, S.S., Keith, G., and Linard, J.I., 2014, Mobilization of selenium from the Mancos Shale and associated soils in the lower Uncompahgre River Basin, Colorado: Applied Geochemistry, v. 48, p. 16-27, https://doi.org/10.1016/j.apgeochem.2014.06.024.","productDescription":"12 p.","startPage":"16","endPage":"27","numberOfPages":"12","ipdsId":"IP-053874","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":290880,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":290879,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.apgeochem.2014.06.024"}],"country":"United States","state":"Colorado","otherGeospatial":"Uncompahgre River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -108.04985,38.469719 ], [ -108.04985,38.694353 ], [ -107.801285,38.694353 ], [ -107.801285,38.469719 ], [ -108.04985,38.469719 ] ] ] } } ] }","volume":"48","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f0a7e4b0bc0bec09f8d3","contributors":{"authors":[{"text":"Mast, M. Alisa 0000-0001-6253-8162 mamast@usgs.gov","orcid":"https://orcid.org/0000-0001-6253-8162","contributorId":827,"corporation":false,"usgs":true,"family":"Mast","given":"M.","email":"mamast@usgs.gov","middleInitial":"Alisa","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":496088,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mills, Taylor J. 0000-0001-7252-0521 tmills@usgs.gov","orcid":"https://orcid.org/0000-0001-7252-0521","contributorId":4658,"corporation":false,"usgs":true,"family":"Mills","given":"Taylor","email":"tmills@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":496090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paschke, Suzanne S.","contributorId":14072,"corporation":false,"usgs":true,"family":"Paschke","given":"Suzanne","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":496091,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keith, Gabrielle","contributorId":21469,"corporation":false,"usgs":true,"family":"Keith","given":"Gabrielle","affiliations":[],"preferred":false,"id":496092,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Linard, Joshua I. jilinard@usgs.gov","contributorId":1465,"corporation":false,"usgs":true,"family":"Linard","given":"Joshua","email":"jilinard@usgs.gov","middleInitial":"I.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":496089,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70117677,"text":"70117677 - 2014 - Radar analysis of fall bird migration stopover sites in the northeastern U.S.","interactions":[],"lastModifiedDate":"2014-07-25T12:29:25","indexId":"70117677","displayToPublicDate":"2014-07-24T10:10:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Radar analysis of fall bird migration stopover sites in the northeastern U.S.","docAbstract":"The national network of weather surveillance radars (WSR-88D) detects flying birds and is a useful remote-sensing tool for ornithological study. We used data collected during fall 2008 and 2009 by 16 WSR-88D radars in the northeastern U.S. to quantify the spatial distribution of landbirds during migratory stopover. We geo-referenced estimates based on radar reflectivity, of the density of migrants aloft at their abrupt evening exodus from daytime stopover sites, to the approximate locations from which they emerged. We classified bird stopover use by the magnitude and variation of radar reflectivity across nights; areas were considered “important” stopover sites for conservation if bird density was consistently high. We developed statistical models that predict potentially important stopover sites across the region, based on land cover, ground elevation, and geographic location. Large areas of regionally important stopover sites were located along the coastlines of Long Island Sound, throughout the Delmarva Peninsula, in areas surrounding Baltimore and Washington, along the western edge of the Adirondack Mountains, and within the Appalachian Mountains of southwestern Virginia and West Virginia. Locally important stopover sites generally were associated with deciduous forests embedded within landscapes dominated by developed or agricultural lands, or near the shores of major water bodies. Preserving or enhancing patches of natural habitat, particularly deciduous forests, in developed or agricultural landscapes and along major coastlines could be a priority for conservation plans addressing the stopover requirements of migratory landbirds in the northeastern U.S. Our maps of important stopover sites can be used to focus conservation efforts and can serve as a sampling frame for fieldwork to validate radar observations or for ecological studies of landbirds on migratory stopover.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"The Condor","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Cooper Ornithological Society","doi":"10.1650/CONDOR-13-162.1","usgsCitation":"Buler, J., and Dawson, D.K., 2014, Radar analysis of fall bird migration stopover sites in the northeastern U.S.: The Condor, v. 116, no. 3, p. 357-370, https://doi.org/10.1650/CONDOR-13-162.1.","productDescription":"14 p.","startPage":"357","endPage":"370","numberOfPages":"14","ipdsId":"IP-053278","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472863,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.1650/CONDOR-13-162.1","text":"External Repository"},{"id":290869,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":290829,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1650/CONDOR-13-162.1"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -83.08,35.21 ], [ -83.08,47.19 ], [ -64.93,47.19 ], [ -64.93,35.21 ], [ -83.08,35.21 ] ] ] } } ] }","volume":"116","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f0a7e4b0bc0bec09f8d7","contributors":{"authors":[{"text":"Buler, Jeffrey J.","contributorId":78431,"corporation":false,"usgs":true,"family":"Buler","given":"Jeffrey J.","affiliations":[],"preferred":false,"id":496055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dawson, Deanna K. ddawson@usgs.gov","contributorId":1257,"corporation":false,"usgs":true,"family":"Dawson","given":"Deanna","email":"ddawson@usgs.gov","middleInitial":"K.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":496054,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70119416,"text":"70119416 - 2014 - COSMO-SkyMed Spotlight interometry over rural areas: the Slumgullion landslide in Colorado, USA","interactions":[],"lastModifiedDate":"2017-06-10T11:16:08","indexId":"70119416","displayToPublicDate":"2014-07-23T15:57:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1942,"text":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"COSMO-SkyMed Spotlight interometry over rural areas: the Slumgullion landslide in Colorado, USA","docAbstract":"In the last 7 years, spaceborne synthetic aperture radar (SAR) data with resolution of better than a meter acquired by satellites in spotlight mode offered an unprecedented improvement in SAR interferometry (InSAR). Most attention has been focused on monitoring urban areas and man-made infrastructure exploiting geometric accuracy, stability, and phase fidelity of the spotlight mode. In this paper, we explore the potential application of the COSMO-SkyMed® Spotlight mode to rural areas where decorrelation is substantial and rapidly increases with time. We focus on the rapid repeat times of as short as one day possible with the COSMO-SkyMed® constellation. We further present a qualitative analysis of spotlight interferometry over the Slumgullion landslide in southwest Colorado, which moves at rates of more than 1 cm/day.","language":"English","publisher":"IEEE Geoscience and Remote Sensing Society","doi":"10.1109/JSTARS.2014.2345664","usgsCitation":"Milillo, P., Fielding, E.J., Schulz, W.H., Delbridge, B., and Burgmann, R., 2014, COSMO-SkyMed Spotlight interometry over rural areas: the Slumgullion landslide in Colorado, USA: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, v. 7, no. 7, p. 2919-2926, https://doi.org/10.1109/JSTARS.2014.2345664.","productDescription":"8 p.","startPage":"2919","endPage":"2926","ipdsId":"IP-058488","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":294389,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0603,36.9924 ], [ -109.0603,41.0034 ], [ -102.0409,41.0034 ], [ -102.0409,36.9924 ], [ -109.0603,36.9924 ] ] ] } } ] }","volume":"7","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5422bb1be4b08312ac7cef7d","contributors":{"authors":[{"text":"Milillo, Pietro","contributorId":9587,"corporation":false,"usgs":true,"family":"Milillo","given":"Pietro","email":"","affiliations":[],"preferred":false,"id":497677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fielding, Eric J.","contributorId":99837,"corporation":false,"usgs":true,"family":"Fielding","given":"Eric","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":497681,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schulz, William H.","contributorId":91927,"corporation":false,"usgs":true,"family":"Schulz","given":"William","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":497679,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Delbridge, Brent","contributorId":52093,"corporation":false,"usgs":true,"family":"Delbridge","given":"Brent","affiliations":[],"preferred":false,"id":497678,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burgmann, Roland","contributorId":95128,"corporation":false,"usgs":true,"family":"Burgmann","given":"Roland","affiliations":[],"preferred":false,"id":497680,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70112606,"text":"70112606 - 2014 - Biomass modeling of four water intensiveleading world crops using hyperspectral narrowbands in support of HyspIRI Mission","interactions":[],"lastModifiedDate":"2017-06-30T13:51:21","indexId":"70112606","displayToPublicDate":"2014-07-23T15:34:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3052,"text":"Photogrammetric Engineering and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Biomass modeling of four water intensiveleading world crops using hyperspectral narrowbands in support of HyspIRI Mission","docAbstract":"New satellite missions are expected to record high spectral resolution information globally and consistently for the first time, so it is important to identify modeling techniques that take advantage of these new data. In this paper, we estimate biomass for four major crops using ground-based hyperspectral narrowbands. The spectra and their derivatives are evaluated using three modeling techniques: two-band hyperspectral vegetation indices (HVIs), multiple band-HVIs (MB-HVIs) developed from Sequential Search Methods (SSM), and MB-HVIs developed from Principal Component Regression. Overall, the two-band HVIs and MB-HVIs developed from SSMs using first derivative transformed spectra in the visible blue and green and NIR explained more biomass variability and had lower error than the other approaches or transformations; however a better search criterion needs to be developed in order to reflect the true ability of the two-band HVI approach. Short-Wave Infrared 1 (1000 to 1700 nm) proved less effective, but still important in the final models.","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","doi":"10.14358/PERS.80.8.757","usgsCitation":"Marshall, M.T., and Thenkabail, P.S., 2014, Biomass modeling of four water intensiveleading world crops using hyperspectral narrowbands in support of HyspIRI Mission: Photogrammetric Engineering and Remote Sensing, v. 80, no. 8, p. 757-772, https://doi.org/10.14358/PERS.80.8.757.","productDescription":"16 p.","startPage":"757","endPage":"772","ipdsId":"IP-052043","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":472864,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14358/pers.80.8.757","text":"Publisher Index Page"},{"id":294385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294384,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.14358/PERS.80.8.757"}],"volume":"80","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5422bb19e4b08312ac7cef52","contributors":{"authors":[{"text":"Marshall, Michael T. mmarshall@usgs.gov","contributorId":5480,"corporation":false,"usgs":true,"family":"Marshall","given":"Michael","email":"mmarshall@usgs.gov","middleInitial":"T.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":494840,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":494839,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70117138,"text":"70117138 - 2014 - Accuracy of travel time distribution (TTD) models as affected by TTD complexity, observation errors, and model and tracer selection","interactions":[],"lastModifiedDate":"2018-09-18T10:10:50","indexId":"70117138","displayToPublicDate":"2014-07-23T14:45:00","publicationYear":"2014","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":"Accuracy of travel time distribution (TTD) models as affected by TTD complexity, observation errors, and model and tracer selection","docAbstract":"Analytical models of the travel time distribution (TTD) from a source area to a sample location are often used to estimate groundwater ages and solute concentration trends. The accuracies of these models are not well known for geologically complex aquifers. In this study, synthetic datasets were used to quantify the accuracy of four analytical TTD models as affected by TTD complexity, observation errors, model selection, and tracer selection. Synthetic TTDs and tracer data were generated from existing numerical models with complex hydrofacies distributions for one public-supply well and 14 monitoring wells in the Central Valley, California. Analytical TTD models were calibrated to synthetic tracer data, and prediction errors were determined for estimates of TTDs and conservative tracer (NO<sub>3</sub>−) concentrations. Analytical models included a new, scale-dependent dispersivity model (SDM) for two-dimensional transport from the watertable to a well, and three other established analytical models. The relative influence of the error sources (TTD complexity, observation error, model selection, and tracer selection) depended on the type of prediction. Geological complexity gave rise to complex TTDs in monitoring wells that strongly affected errors of the estimated TTDs. However, prediction errors for NO3− and median age depended more on tracer concentration errors. The SDM tended to give the most accurate estimates of the vertical velocity and other predictions, although TTD model selection had minor effects overall. Adding tracers improved predictions if the new tracers had different input histories. Studies using TTD models should focus on the factors that most strongly affect the desired predictions.","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014WR015625","usgsCitation":"Green, C.T., Zhang, Y., Jurgens, B., Starn, J.J., and Landon, M.K., 2014, Accuracy of travel time distribution (TTD) models as affected by TTD complexity, observation errors, and model and tracer selection: Water Resources Research, v. 50, no. 7, p. 6191-6213, https://doi.org/10.1002/2014WR015625.","productDescription":"23 p.","startPage":"6191","endPage":"6213","ipdsId":"IP-052071","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":472865,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014wr015625","text":"Publisher Index Page"},{"id":294376,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/2014WR015625"},{"id":294377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.7757,35.0674 ], [ -122.7757,40.7363 ], [ -118.7989,40.7363 ], [ -118.7989,35.0674 ], [ -122.7757,35.0674 ] ] ] } } ] }","volume":"50","issue":"7","noUsgsAuthors":false,"publicationDate":"2014-07-30","publicationStatus":"PW","scienceBaseUri":"5422bb0de4b08312ac7ceedd","contributors":{"authors":[{"text":"Green, Christopher T. 0000-0002-6480-8194 ctgreen@usgs.gov","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":1343,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"ctgreen@usgs.gov","middleInitial":"T.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":495946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Yong","contributorId":19029,"corporation":false,"usgs":true,"family":"Zhang","given":"Yong","affiliations":[],"preferred":false,"id":495947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":22454,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant C.","affiliations":[],"preferred":false,"id":495948,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Starn, J. Jeffrey","contributorId":101617,"corporation":false,"usgs":true,"family":"Starn","given":"J.","email":"","middleInitial":"Jeffrey","affiliations":[],"preferred":false,"id":495949,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":495945,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70117436,"text":"fs20143066 - 2014 - The 3D Elevation Program: summary for North Carolina","interactions":[],"lastModifiedDate":"2016-08-17T15:38:02","indexId":"fs20143066","displayToPublicDate":"2014-07-23T13:02:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3066","title":"The 3D Elevation Program: summary for North Carolina","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, and recreation. For the State of North Carolina, elevation data are critical for flood risk management, natural resources conservation, agriculture and precision farming, infrastructure and construction management, forest resources management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.</p>\n<p>The National Enhanced Elevation Assessment (NEEA; Dewberry, 2011) evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the use community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A&ndash;16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143066","usgsCitation":"Carswell, W., 2014, The 3D Elevation Program: summary for North Carolina: U.S. Geological Survey Fact Sheet 2014-3066, 2 p., https://doi.org/10.3133/fs20143066.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057847","costCenters":[{"id":423,"text":"National Geospatial 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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":495987,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70111715,"text":"ofr20141115 - 2014 - Timing of ore-related magmatism in the western Alaska Range, southwestern Alaska","interactions":[],"lastModifiedDate":"2014-07-23T12:57:09","indexId":"ofr20141115","displayToPublicDate":"2014-07-23T12:53:00","publicationYear":"2014","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":"2014-1115","title":"Timing of ore-related magmatism in the western Alaska Range, southwestern Alaska","docAbstract":"This report presents isotopic age data from mineralized granitic plutons in an area of the Alaska Range located approximately 200 kilometers to the west-northwest of Anchorage in southwestern Alaska. Uranium-lead isotopic data and trace element concentrations of zircons were determined for 12 samples encompassing eight plutonic bodies ranging in age from approximately 76 to 57.4 millions of years ago (Ma). Additionally, a rhenium-osmium age of molybdenite from the Miss Molly molybdenum occurrence is reported (approx. 59 Ma). All of the granitic plutons in this study host gold-, copper-, and (or) molybdenum-rich prospects. These new ages modify previous interpretations regarding the age of magmatic activity and mineralization within the study area. The new ages show that the majority of the gold-quartz vein-hosting plutons examined in this study formed in the Late Cretaceous. Further work is necessary to establish the ages of ore-mineral deposition in these deposits.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141115","usgsCitation":"Taylor, R.D., Graham, G.E., Anderson, E.D., and Selby, D., 2014, Timing of ore-related magmatism in the western Alaska Range, southwestern Alaska: U.S. Geological Survey Open-File Report 2014-1115, Report: iv, 25 p.; Tables 1-4, https://doi.org/10.3133/ofr20141115.","productDescription":"Report: iv, 25 p.; Tables 1-4","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-054073","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":290806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141115.jpg"},{"id":290803,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1115/"},{"id":290804,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1115/pdf/ofr2014-1115.pdf"},{"id":290805,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1115/downloads/ofr2014-1115_tables.xlsx"}],"country":"United States","state":"Alaska","otherGeospatial":"Alaska Range","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -154.0,61.5 ], [ -154.0,62.25 ], [ -152.0,62.25 ], [ -152.0,61.5 ], [ -154.0,61.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f0a8e4b0bc0bec09f8dd","contributors":{"authors":[{"text":"Taylor, Ryan D. 0000-0002-8845-5290 rtaylor@usgs.gov","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":3412,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan","email":"rtaylor@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":494450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graham, Garth E. 0000-0003-0657-0365 ggraham@usgs.gov","orcid":"https://orcid.org/0000-0003-0657-0365","contributorId":1031,"corporation":false,"usgs":true,"family":"Graham","given":"Garth","email":"ggraham@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":494448,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Eric D. 0000-0002-0138-6166 ericanderson@usgs.gov","orcid":"https://orcid.org/0000-0002-0138-6166","contributorId":1733,"corporation":false,"usgs":true,"family":"Anderson","given":"Eric","email":"ericanderson@usgs.gov","middleInitial":"D.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":494449,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Selby, David","contributorId":58167,"corporation":false,"usgs":true,"family":"Selby","given":"David","affiliations":[],"preferred":false,"id":494451,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70117149,"text":"ofr20141154 - 2014 - Methow River Studies, Washington: abundance estimates from Beaver Creek and the Chewuch River screw trap, methodology testing in the Whitefish Island side channel, and survival and detection estimates from hatchery fish releases, 2013","interactions":[],"lastModifiedDate":"2014-07-24T08:18:46","indexId":"ofr20141154","displayToPublicDate":"2014-07-23T09:36:00","publicationYear":"2014","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":"2014-1154","title":"Methow River Studies, Washington: abundance estimates from Beaver Creek and the Chewuch River screw trap, methodology testing in the Whitefish Island side channel, and survival and detection estimates from hatchery fish releases, 2013","docAbstract":"<p>Salmon and steelhead populations have been severely depleted in the Columbia River from factors such as the presence of tributary dams, unscreened irrigation diversions, and habitat degradation from logging, mining, grazing, and others (Raymond, 1988). The U.S. Geological Survey (USGS) has been funded by the Bureau of Reclamation (Reclamation) to provide evaluation of on-going Reclamation funded efforts to recover Endangered Species Act (ESA) listed anadromous salmonid populations in the Methow River watershed, a watershed of the Columbia River in the Upper Columbia River Basin, in north-central Washington State (fig. 1). This monitoring and evaluation program was funded to document Reclamation’s effort to partially fulfill the 2008 Federal Columbia River Power System Biological Opinion (BiOp) (National Oceanographic and Atmospheric Administration, Fisheries Division 2003). This Biological Opinion includes Reasonable and Prudent Alternatives (RPA) to protect listed salmon and steelhead across their life cycle. Species of concern in the Methow River include Upper Columbia River (UCR) spring Chinook salmon (<i>Oncorhynchus tshawytscha</i>), UCR summer steelhead (<i>O. mykiss</i>), and bull trout (<i>Salvelinus confluentus</i>), which are all listed as threatened or endangered under the ESA. The work done by the USGS since 2004 has encompassed three phases of work. The first phase started in 2004 and continued through 2012. This first phase involved the evaluation of stream colonization and fish production in Beaver Creek following the modification of several water diversions (2000–2006) that were acting as barriers to upstream fish movement. Products to date from this work include: Ruttenburg (2007), Connolly and others (2008), Martens and Connolly (2008), Connolly (2010), Connolly and others (2010), Martens and Connolly (2010), Benjamin and others (2012), Romine and others (2013a), Weigel and others (2013a, 2013b, 2013c), and Martens and others (2014). The second phase, initiated in 2008, focuses on the evaluation of the M2 reach (rkm 66– 80) of the mainstem Methow River prior to restoration actions planned by Reclamation and Yakama Nation. The M2 study was designed to help understand the inter-relationships between stream habitat and the life history of various fish species to explain potential success or limitations in response to restoration actions. To help document changes derived by restoration, two reference reaches (Upper Methow between rkm 85 and 90, and Chewuch River between rkm 4 and 11) were identified based on relative lack of disturbance, proximity to the restoration reach, and relative unconfined geomorphology. A control reach (Lower Methow between rkm 57 and 64, also referred to as “Silver Reach”) was 2 identified based on its similar disturbance as the reference reach, proximity to the restoration reach, and relatively unconfined geomorphology. Products to date include Barber and others (2011), Bellmore (2011), Tibbits and others (2012), Bellmore and others (2013), Benjamin and others (2013), Romine and others (2013b), Bellmore and other (2014), Martens and others (2014), and Martens and Connolly (2014). The third phase of work has been to help with the development and to provide data for modeling efforts.</p>\n<br/>\n<p>Most of the planned M2 reach restoration is focused on the creation or improvement of offchannel habitat, especially side channels. The pre-restoration portion of this study has been documented by Martens and Connolly (2014). Side channel restoration actions were initiated in 2012 (Whitefish Island side channel, also referred to as SC3; rkm 76) and are planned to continue over the next several years. The Whitefish Island side channel was modified to maintain hydrological connection with the mainstem throughout the year. In addition, several log structures were installed and pools were deepened to create fish habitat. Prior to restoration, this side channel would lose hydrological connection with the mainstem Methow River, leaving one large pool near the bottom of the side channel and several shallow isolated pools that may or may not go dry. In seasonally connected side channels, juvenile salmonid survival in pools less than 100 cm average depth was lower than in pools greater than 100 cm average depth (Martens and Connolly, 2014).</p>\n<br/>\n<p>In this report, we document our field work and analysis completed in 2013. During 2013, USGS sampling efforts were focused on resampling of three reaches in Beaver Creek, testing methodology in the Whitefish Island side channel, conducting hatchery survival estimates, and operating a screw trap on the Chewuch River (funded by Yakama Nation; fig. 1). The Beaver Creek sampling effort was a revisit of three index sites sampled continuously from 2004 to 2007 to look at the fish response to barrier removal. Methodology testing in Whitefish Island side channel was done to determine the best method for evaluating fish populations after restoration efforts in side channels (previous sampling methods were determined to be ineffective after pools were deepened). Hatchery survival estimates were completed to monitor fish survival in the Methow and Columbia Rivers, while the screw trap was operated to estimate migrating fish populations in the Chewuch River and track passive integrated transponder (PIT)-tagged fish. In addition, we maintained a network of PIT-tag interrogation systems (PTIS), assisted Reclamation with fish removal events associated with stream restoration (two people for 9 days; 14 percent of summer field season), and conducted a stream metabolism study designed to help parameterize and calibrate the stream productivity model (Bellmore and others, 2014) with model validation.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141154","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Martens, K.D., Fish, T.M., Watson, G.A., and Connolly, P., 2014, Methow River Studies, Washington: abundance estimates from Beaver Creek and the Chewuch River screw trap, methodology testing in the Whitefish Island side channel, and survival and detection estimates from hatchery fish releases, 2013: U.S. Geological Survey Open-File Report 2014-1154, iv, 38 p., https://doi.org/10.3133/ofr20141154.","productDescription":"iv, 38 p.","numberOfPages":"47","onlineOnly":"Y","ipdsId":"IP-055654","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":290754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141154.JPG"},{"id":290844,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1154/pdf/ofr2014-1154.pdf"},{"id":290752,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1154/"}],"country":"United States","state":"Washington","otherGeospatial":"Upper Columbia River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.09,46.73 ], [ -124.09,49.0 ], [ -117.6,49.0 ], [ -117.6,46.73 ], [ -124.09,46.73 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f0a8e4b0bc0bec09f8e1","contributors":{"authors":[{"text":"Martens, Kyle D.","contributorId":12740,"corporation":false,"usgs":true,"family":"Martens","given":"Kyle","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":495959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fish, Teresa M. tfish@usgs.gov","contributorId":5869,"corporation":false,"usgs":true,"family":"Fish","given":"Teresa","email":"tfish@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":495958,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watson, Grace A. gwatson@usgs.gov","contributorId":5435,"corporation":false,"usgs":true,"family":"Watson","given":"Grace","email":"gwatson@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":495957,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Connolly, Patrick J. 0000-0001-7365-7618 pconnolly@usgs.gov","orcid":"https://orcid.org/0000-0001-7365-7618","contributorId":2920,"corporation":false,"usgs":true,"family":"Connolly","given":"Patrick J.","email":"pconnolly@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":495956,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70156196,"text":"70156196 - 2014 - Influences of water and sediment quality and hydrologic processes on mussels in the Clinch River","interactions":[],"lastModifiedDate":"2016-07-08T12:04:40","indexId":"70156196","displayToPublicDate":"2014-07-22T13:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Influences of water and sediment quality and hydrologic processes on mussels in the Clinch River","docAbstract":"<p class=\"p1\"><span class=\"s1\">Segments of the Clinch River in Virginia have experienced declining freshwater mussel populations during the past 40&nbsp;years, while other segments of the river continue to support some of the richest mussel communities in the country. The close proximity of these contrasting reaches provides a study area where differences in climate, hydrology, and historic mussel distribution are minimal. The USGS conducted a study between 2009 and 2011 to evaluate possible causes of the mussel declines. Evaluation of mussel habitat showed no differences in physical habitat quality, leaving water and sediment quality as possible causes for declines. Three years of continuous water-quality data showed higher turbidity and specific conductance in the reaches with low-quality mussel assemblages compared to reaches with high-quality mussel assemblages. Discrete water-quality samples showed higher major ions and metals concentrations in the low-quality reach. Base-flow samples contained high major ion and metal concentrations coincident to low-quality mussel populations. These results support a conceptual model of dilution and augmentation where increased concentrations of major ions and other dissolved constituents from mined tributaries result in reaches with declining mussel populations. Tributaries from unmined basins provide water with low concentrations of dissolved constituents, diluting reaches of the Clinch River where high-quality mussel populations occur.</span></p>","language":"English","publisher":"American Water Resources Association","doi":"10.1111/jawr.12221","usgsCitation":"Johnson, G.C., Krstolic, J.L., and Ostby, B.J., 2014, Influences of water and sediment quality and hydrologic processes on mussels in the Clinch River: Journal of the American Water Resources Association, v. 50, no. 4, p. 878-897, https://doi.org/10.1111/jawr.12221.","productDescription":"20 p.","startPage":"878","endPage":"897","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-034906","costCenters":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"links":[{"id":324917,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee, Virginia","otherGeospatial":"Clinch River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.48583984375,\n              37.47485808497102\n            ],\n            [\n              -80.244140625,\n              37.21283151445594\n            ],\n            [\n              -80.48583984375,\n              36.949891786813296\n            ],\n            [\n              -81.05712890625,\n              36.73888412439431\n            ],\n            [\n              -81.71630859375,\n              36.58024660149866\n            ],\n            [\n              -82.81494140625,\n              36.03133177633189\n            ],\n            [\n              -83.56201171875,\n              35.746512259918504\n            ],\n            [\n              -84.19921875,\n              35.496456056584165\n            ],\n            [\n              -84.74853515625,\n              35.35321610123821\n            ],\n            [\n              -85.01220703125,\n              35.51434313431818\n            ],\n            [\n              -84.88037109375,\n              35.88905007936091\n            ],\n            [\n              -84.48486328124999,\n              36.20882309283712\n            ],\n            [\n              -84.26513671875,\n              36.421282443649496\n            ],\n            [\n              -83.8037109375,\n              36.54494944148322\n            ],\n            [\n              -83.232421875,\n              36.66841891894786\n            ],\n            [\n              -82.94677734375,\n              36.82687474287728\n            ],\n            [\n              -82.3974609375,\n              37.00255267215955\n            ],\n            [\n              -82.08984375,\n              37.07271048132943\n            ],\n            [\n              -81.62841796875,\n              37.19533058280065\n            ],\n            [\n              -81.298828125,\n              37.23032838760387\n            ],\n            [\n              -80.48583984375,\n              37.47485808497102\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"50","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2014-07-22","publicationStatus":"PW","scienceBaseUri":"5780cebae4b081161682236f","contributors":{"authors":[{"text":"Johnson, Gregory C. 0000-0003-3683-5010 gcjohnso@usgs.gov","orcid":"https://orcid.org/0000-0003-3683-5010","contributorId":1420,"corporation":false,"usgs":true,"family":"Johnson","given":"Gregory","email":"gcjohnso@usgs.gov","middleInitial":"C.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":568004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krstolic, Jennifer L. 0000-0003-2253-9886 jkrstoli@usgs.gov","orcid":"https://orcid.org/0000-0003-2253-9886","contributorId":3677,"corporation":false,"usgs":true,"family":"Krstolic","given":"Jennifer","email":"jkrstoli@usgs.gov","middleInitial":"L.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":568005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ostby, Brett J.K.","contributorId":146480,"corporation":false,"usgs":false,"family":"Ostby","given":"Brett","email":"","middleInitial":"J.K.","affiliations":[{"id":16709,"text":"VaTech","active":true,"usgs":false}],"preferred":false,"id":568006,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70117481,"text":"70117481 - 2014 - Human and bovine viruses in the Milwaukee River Watershed: hydrologically relevant representation and relations with environmental variables","interactions":[],"lastModifiedDate":"2015-02-16T10:30:03","indexId":"70117481","displayToPublicDate":"2014-07-22T09:50:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Human and bovine viruses in the Milwaukee River Watershed: hydrologically relevant representation and relations with environmental variables","docAbstract":"<p>To examine the occurrence, hydrologic variability, and seasonal variability of human and bovine viruses in surface water, three stream locations were monitored in the Milwaukee River watershed in Wisconsin, USA, from February 2007 through June 2008. Monitoring sites included an urban subwatershed, a rural subwatershed, and the Milwaukee River at the mouth. To collect samples that characterize variability throughout changing hydrologic periods, a process control system was developed for unattended, large-volume (56&ndash;2800 L) filtration over extended durations. This system provided flow-weighted mean concentrations during runoff and extended (24-h) low-flow periods. Human viruses and bovine viruses were detected by real-time qPCR in 49% and 41% of samples (n = 63), respectively. All human viruses analyzed were detected at least once including adenovirus (40% of samples), GI norovirus (10%), enterovirus (8%), rotavirus (6%), GII norovirus (1.6%) and hepatitis A virus (1.6%). Three of seven bovine viruses analyzed were detected including bovine polyomavirus (32%), bovine rotavirus (19%), and bovine viral diarrhea virus type 1 (5%). Human viruses were present in 63% of runoff samples resulting from precipitation and snowmelt, and 20% of low-flow samples. Maximum human virus concentrations exceeded 300 genomic copies/L. Bovine viruses were present in 46% of runoff samples resulting from precipitation and snowmelt and 14% of low-flow samples. The maximum bovine virus concentration was 11 genomic copies/L. Statistical modeling indicated that stream flow, precipitation, and season explained the variability of human viruses in the watershed, and hydrologic condition (runoff event or low-flow) and season explained the variability of the sum of human and bovine viruses; however, no model was identified that could explain the variability of bovine viruses alone. Understanding the factors that affect virus fate and transport in rivers will aid watershed management for minimizing human exposure and disease transmission.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Science of the Total Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2014.05.072","usgsCitation":"Corsi, S., Borchardt, M., Spencer, S.K., Hughes, P.E., and Baldwin, A.K., 2014, Human and bovine viruses in the Milwaukee River Watershed: hydrologically relevant representation and relations with environmental variables: Science of the Total Environment, v. 490, p. 849-860, https://doi.org/10.1016/j.scitotenv.2014.05.072.","productDescription":"12 p.","startPage":"849","endPage":"860","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056623","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":472867,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2014.05.072","text":"Publisher Index Page"},{"id":290663,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":290632,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.scitotenv.2014.05.072"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Milwaukee River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.8217,42.7954 ], [ -88.8217,43.8345 ], [ -87.7258,43.8345 ], [ -87.7258,42.7954 ], [ -88.8217,42.7954 ] ] ] } } ] }","volume":"490","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54e322b9e4b08de9379b4f89","chorus":{"doi":"10.1016/j.scitotenv.2014.05.072","url":"http://dx.doi.org/10.1016/j.scitotenv.2014.05.072","publisher":"Elsevier BV","authors":"Corsi S.R., Borchardt M.A., Spencer S.K., Hughes P.E., Baldwin A.K.","journalName":"Science of The Total Environment","publicationDate":"8/2014","auditedOn":"7/24/2015","publiclyAccessibleDate":"7/21/2014"},"contributors":{"authors":[{"text":"Corsi, Steven R. srcorsi@usgs.gov","contributorId":511,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":496017,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Borchardt, M. 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K.","contributorId":96118,"corporation":false,"usgs":true,"family":"Spencer","given":"S.","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":496018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hughes, Peter E. pehughes@usgs.gov","contributorId":876,"corporation":false,"usgs":true,"family":"Hughes","given":"Peter","email":"pehughes@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":496019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":496015,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70117566,"text":"sir20145117 - 2014 - A reconnaissance spatial and temporal assessment of methane and inorganic constituents in groundwater in bedrock aquifers, Pike County, Pennsylvania, 2012-13","interactions":[],"lastModifiedDate":"2016-08-24T12:19:10","indexId":"sir20145117","displayToPublicDate":"2014-07-22T08:40:00","publicationYear":"2014","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":"2014-5117","title":"A reconnaissance spatial and temporal assessment of methane and inorganic constituents in groundwater in bedrock aquifers, Pike County, Pennsylvania, 2012-13","docAbstract":"<p>Pike County in northeastern Pennsylvania is underlain by the Devonian-age Marcellus Shale and other shales, formations that have potential for natural gas development. During 2012&ndash;13, the U.S. Geological Survey in cooperation with the Pike County Conservation District conducted a reconnaissance study to assess baseline shallow groundwater quality in bedrock aquifers prior to possible shale-gas development in the county. For the spatial component of the assessment, 20 wells were sampled in summer 2012 to provide data on the occurrence of methane and other aspects of existing groundwater quality throughout the county, including concentrations of inorganic constituents commonly present at low levels in shallow, fresh groundwater but elevated in brines. For the temporal component of the assessment, 4 of the 20 wells sampled in summer 2012 were sampled monthly from July&nbsp;2012 through June&nbsp;2013 to provide data on seasonal variability in groundwater quality. All water samples were analyzed for major ions, nutrients, selected inorganic trace constituents (including metals and other elements), stable isotopes of water, radon-222, gross alpha- and gross beta-particle activity, dissolved gases (methane, ethane, and ethene), and, if possible, isotopic composition of methane. Additional analyses for boron and strontium isotopes, age-dating of water, and radium-226 were done on water samples collected from six wells in June&nbsp;2013.</p>\n<p>Results of the summer 2012 sampling show that water from 16 (80&nbsp;percent) of 20&nbsp;wells had detectable concentrations of methane, but concentrations were less than 0.1&nbsp;milligram per liter (mg/L) in most well-water samples; only two well-water samples had concentrations greater than 1&nbsp;mg/L. The groundwater with elevated methane also had a chemical composition that differed in some respects (pH, selected major ions, and inorganic trace constituents) from groundwater with low methane concentrations. The two well-water samples with the highest methane concentrations (about 3.7 and 5.8&nbsp;mg/L) also had the highest pH values (8.7 and 8.3, respectively) and the highest concentrations of sodium, lithium, boron, fluoride, and bromide. Elevated concentrations of some other constituents, such as barium, strontium, and chloride, were not limited to well-water samples with elevated methane, although the two samples with elevated methane also had among the highest concentrations of these&nbsp;constituents.</p>\n<p>One sample with elevated methane concentrations also had elevated arsenic concentrations, with the arsenic concentration of 30 micrograms per liter (&mu;g/L) exceeding the drinking-water standard of 10 &micro;g/L for arsenic. No other sample from the 20 wells sampled in summer 2012 had concentrations of constituents that exceeded any established primary drinking-water standards. However, radon-222 activities ranging up to 4,500 picocuries per liter (pCi/L) exceeded the proposed drinking-water standard of 300&nbsp;pCi/L in 85&nbsp;percent of the 20 well-water&nbsp;samples.</p>\n<p>The isotopic composition methane in the two high-methane samples (&delta;C<sub>CH4</sub>&nbsp;values of -64.55 and -64.41&nbsp;per&nbsp;mil and &delta;D<sub>CH4</sub>&nbsp;values of -216.9 and -201.8&nbsp;per mil, respectively) indicates a predominantly microbial source for the methane formed by a carbon dioxide reduction process. The stable isotopic composition of water (&delta;D<sub>H20</sub>&nbsp;and &delta;<sup>18</sup>O<sub>H20</sub>) in samples from all 20 wells falls on the local meteoric line, indicating water in the wells was of relatively recent meteoric origin (modern precipitation), including samples with elevated methane&nbsp;concentrations.</p>\n<p>Analytical results for 4 of the 20&nbsp;wells sampled monthly for 1 year ending June&nbsp;2013 in order to assess temporal variability in groundwater quality show that concentrations of major ions generally varied by less than 20 percent, with most differences less than 4&nbsp;mg/L. Concentrations of methane varied by less than 1&nbsp;&mu;g/L (0.001&nbsp;mg/L) in samples from three wells with low methane and by as much as 1 mg/L (1,000&nbsp;&mu;g/L) in samples from one well with relatively high methane. The isotopic composition of methane in the one well with relatively high methane varied slightly in the monthly samples, ranging from about -64.5 to -64.8&nbsp;per&nbsp;mil for &delta;<sup>13</sup>C<sub>CH4</sub>&nbsp;and from about -217 to -228&nbsp;per&nbsp;mil for &delta;D<sub>CH4</sub>. The &delta;<sup>13</sup>C values for dissolved inorganic carbon (DIC) in water from this well were consistent with microbial methane formation by carbon dioxide reduction (drift-type methane) and varied little in the temporal samples, ranging from -10.5 to -10.1&nbsp;per&nbsp;mil.</p>\n<p>Additional analyses of samples collected in late June 2013 from six wells with a range of methane and trace constituent concentrations provided baseline data on strontium and boron isotopic compositions (<sup>87</sup>Sr/<sup>86</sup>Sr ratios and &delta;<sup>11</sup>B, respectively) that potentially may be used to differentiate among sources of these constituents. The strontium and boron isotopic composition determined in the six shallow Pike County groundwater samples had&nbsp;<sup>87</sup>Sr/<sup>86</sup>Sr ratios of 0.71426 to 0.71531 and &delta;<sup>11</sup>B values of 11.7 to 27.0&nbsp;per mil, which differ from those reported for brines in Devonian-age formations in&nbsp;Pennsylvania.</p>\n<p>The&nbsp;June&nbsp;2013 samples were also analyzed for radium-226 and age-dating dissolved gases. Activities of radium-226 ranged from 0.041 to 0.29&nbsp;pCi/L in water samples from the six wells and were less than the drinking-water standard of 5&nbsp;pCi/L for combined radium-226 and radium-228. Age-dating of groundwater using a method based on the presence of anthropogenic gases (chlorofluorocarbons and sulfur hexafluoride) released into the atmosphere yielded estimated recharge dates for water from these six wells that ranged from the 1940s to early 2000s. The oldest water was in samples from wells that had the highest methane concentrations and the youngest water was in samples from a continuously pumped 300-foot deep production&nbsp;well.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145117","collaboration":"Prepared in cooperation with the Pike County Conservation District","usgsCitation":"Senior, L.A., 2014, A reconnaissance spatial and temporal assessment of methane and inorganic constituents in groundwater in bedrock aquifers, Pike County, Pennsylvania, 2012-13: U.S. Geological Survey Scientific Investigations Report 2014-5117, x, 91 p., https://doi.org/10.3133/sir20145117.","productDescription":"x, 91 p.","numberOfPages":"106","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-054516","costCenters":[{"id":532,"text":"Pennsylvania Water Science 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,{"id":70100432,"text":"sir20145046 - 2014 - Flood-inundation maps for the Susquehanna River near Harrisburg, Pennsylvania, 2013","interactions":[],"lastModifiedDate":"2014-07-21T14:49:17","indexId":"sir20145046","displayToPublicDate":"2014-07-21T14:41:00","publicationYear":"2014","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":"2014-5046","title":"Flood-inundation maps for the Susquehanna River near Harrisburg, Pennsylvania, 2013","docAbstract":"<p>A series of 28 digital flood-inundation maps was developed for an approximate 25-mile reach of the Susquehanna River in the vicinity of Harrisburg, Pennsylvania. The study was selected by the U.S. Army Corps of Engineers (USACE) national Silver Jackets program, which supports interagency teams at the state level to coordinate and collaborate on flood-risk management. This study to produce flood-inundation maps was the result of a collaborative effort between the USACE, National Weather Service (NWS), Susquehanna River Basin Commission (SRBC), The Harrisburg Authority, and the U.S. Geological Survey (USGS). These maps are accessible through Web-mapping applications associated with the NWS, SRBC, and USGS. The maps can be used in conjunction with the real-time stage data from the USGS streamgage 01570500, Susquehanna River at Harrisburg, Pa., and NWS flood-stage forecasts to help guide the general public in taking individual safety precautions and will provide local municipal officials with a tool to efficiently manage emergency flood operations and flood mitigation efforts.</p>\n<br/>\n<p>The maps were developed using the USACE HEC–RAS and HEC–GeoRAS programs to compute water-surface profiles and to delineate estimated flood-inundation areas for selected stream stages. The maps show estimated flood-inundation areas overlaid on high-resolution, georeferenced, aerial photographs of the study area for stream stages at 1-foot intervals between 11 feet and 37 feet (which include NWS flood categories Action, Flood, Moderate, and Major) and the June 24, 1972, peak-of-record flood event at a stage of 33.27 feet at the Susquehanna River at Harrisburg, Pa., streamgage.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145046","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, National Oceanic and Atmospheric Administration National Weather Service, Susquehanna River Basin Commission, and The Harrisburg Authority","usgsCitation":"Roland, M.A., Underwood, S.M., Thomas, C.M., Miller, J.F., Pratt, B.A., Hogan, L.G., and Wnek, P.A., 2014, Flood-inundation maps for the Susquehanna River near Harrisburg, Pennsylvania, 2013: U.S. Geological Survey Scientific Investigations Report 2014-5046, vi, 17 p., https://doi.org/10.3133/sir20145046.","productDescription":"vi, 17 p.","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-049553","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":290608,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145046.jpg"},{"id":290604,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5046/"},{"id":290607,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5046/pdf/sir2014-5046.pdf"}],"country":"United States","state":"Pennsylvania","city":"Harrisburg","otherGeospatial":"Susquehanna River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -77.099991,40.049694 ], [ -77.099991,40.500225 ], [ -76.673927,40.500225 ], [ -76.673927,40.049694 ], [ -77.099991,40.049694 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f0a8e4b0bc0bec09f8e9","contributors":{"authors":[{"text":"Roland, Mark A. 0000-0002-0268-6507 mroland@usgs.gov","orcid":"https://orcid.org/0000-0002-0268-6507","contributorId":2116,"corporation":false,"usgs":true,"family":"Roland","given":"Mark","email":"mroland@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Underwood, Stacey M.","contributorId":21467,"corporation":false,"usgs":true,"family":"Underwood","given":"Stacey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":492213,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Craig M.","contributorId":70292,"corporation":false,"usgs":true,"family":"Thomas","given":"Craig","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":492215,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Jason F.","contributorId":98643,"corporation":false,"usgs":true,"family":"Miller","given":"Jason","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":492217,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pratt, Benjamin A.","contributorId":89807,"corporation":false,"usgs":true,"family":"Pratt","given":"Benjamin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":492216,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hogan, Laurie G.","contributorId":8001,"corporation":false,"usgs":true,"family":"Hogan","given":"Laurie","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":492212,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wnek, Patricia A.","contributorId":68227,"corporation":false,"usgs":true,"family":"Wnek","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":492214,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70114031,"text":"sir20145116 - 2014 - Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River between Kansas City and St. Louis, Missouri, April-May, 2013","interactions":[],"lastModifiedDate":"2023-12-05T00:00:16.936765","indexId":"sir20145116","displayToPublicDate":"2014-07-21T13:57:00","publicationYear":"2014","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":"2014-5116","title":"Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River between Kansas City and St. Louis, Missouri, April-May, 2013","docAbstract":"<p>Bathymetric and velocimetric data were collected by the U.S. Geological Survey, in cooperation with the Missouri Department of Transportation, in the vicinity of 10 bridges at 9 highway crossings of the Missouri River between Lexington and Washington, Missouri, from April 22 through May 2, 2013. A multibeam echosounder mapping system was used to obtain channel-bed elevations for river reaches ranging from 1,640 to 1,840 feet longitudinally and extending laterally across the active channel between banks and spur dikes in the Missouri River during low- to moderate-flow conditions. These bathymetric surveys indicate the channel conditions at the time of the surveys and provide characteristics of scour holes that may be useful in the development of predictive guidelines or equations for scour holes. These data also may be useful to the Missouri Department of Transportation to assess the bridges for stability and integrity issues with respect to bridge scour during floods.</p>\n<br/>\n<p>Bathymetric data were collected around every pier that was in water, except those at the edge of water or in very shallow water (less than about 6 feet). Scour holes were present at most piers for which bathymetry could be obtained, except at piers on channel banks, near or embedded in lateral or longitudinal spur dikes, and on exposed bedrock outcrops. Scour holes observed at the surveyed bridges were examined with respect to depth and shape. Although exposure of parts of foundational support elements was observed at several piers, at most sites the exposure likely can be considered minimal compared to the overall substructure that remains buried in channel-bed material; however, there were several notable exceptions where the bed material thickness between the bottom of the scour hole and bedrock was less than 6 feet. Such substantial exposure of usually buried substructural elements may warrant special observation in future flood events.</p>\n<br/>\n<p>Previous bathymetric surveys had been done at all of the sites in this study during the flood of 2011. Comparisons between bathymetric surfaces from the previous surveys and those of this study generally indicate a consistent increase in the elevation of the bed and decrease in the size of scour holes at these sites, both likely caused by a substantial decrease in discharge and water-surface elevation compared to the 2011 surveys at most sites. However, multiple surveys at one of the sites indicate that the flow condition is not the sole variable in the determination of the size of scour holes at sites with a dual bridge configuration. Furthermore, another site had a smaller and shallower scour hole even though the discharge in this study was slightly greater than in 2011. Pier size, nose shape, and alignment to flow also had a substantial effect on the size of the scour hole observed.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145116","collaboration":"Prepared in cooperation with the Missouri Department of Transportation","usgsCitation":"Huizinga, R.J., 2014, Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River between Kansas City and St. Louis, Missouri, April-May, 2013: U.S. Geological Survey Scientific Investigations Report 2014-5116, viii, 79 p., https://doi.org/10.3133/sir20145116.","productDescription":"viii, 79 p.","numberOfPages":"92","onlineOnly":"Y","ipdsId":"IP-056537","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":290599,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5116/pdf/sir2014-5116.pdf"},{"id":290598,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5116/"},{"id":290600,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145116.jpg"}],"scale":"100000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Missouri","otherGeospatial":"Missouri River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96.00,38.00 ], [ -96.00,40.75 ], [ -90.00,40.75 ], [ -90.00,38.00 ], [ -96.00,38.00 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f0a8e4b0bc0bec09f8eb","contributors":{"authors":[{"text":"Huizinga, Richard J. 0000-0002-2940-2324 huizinga@usgs.gov","orcid":"https://orcid.org/0000-0002-2940-2324","contributorId":2089,"corporation":false,"usgs":true,"family":"Huizinga","given":"Richard","email":"huizinga@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":495237,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70095411,"text":"ds768 - 2014 - Key subsurface data help to refine Trinity aquifer hydrostratigraphic units, south-central Texas","interactions":[],"lastModifiedDate":"2014-07-21T13:40:56","indexId":"ds768","displayToPublicDate":"2014-07-21T13:07:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"768","title":"Key subsurface data help to refine Trinity aquifer hydrostratigraphic units, south-central Texas","docAbstract":"<p>The geologic framework and hydrologic characteristics of aquifers are important components for studying the nation’s subsurface heterogeneity and predicting its hydraulic budgets. Detailed study of an aquifer’s subsurface hydrostratigraphy is needed to understand both its geologic and hydrologic frameworks. Surface hydrostratigraphic mapping can also help characterize the spatial distribution and hydraulic connectivity of an aquifer’s permeable zones. Advances in three-dimensional (3-D) mapping and modeling have also enabled geoscientists to visualize the spatial relations between the saturated and unsaturated lithologies.</p>\n<br/>\n<p>This detailed study of two borehole cores, collected in 2001 on the Camp Stanley Storage Activity (CSSA) area, provided the foundation for revising a number of hydrostratigraphic units representing the middle zone of the Trinity aquifer. The CSSA area is a restricted military facility that encompasses approximately 4,000 acres and is located in Boerne, Texas, northwest of the city of San Antonio. Studying both the surface and subsurface geology of the CSSA area are integral parts of a U.S. Geological Survey project funded through the National Cooperative Geologic Mapping Program. This modification of hydrostratigraphic units is being applied to all subsurface data used to construct a proposed 3-D EarthVision model of the CSSA area and areas to the south and west.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds768","collaboration":"Prepared in cooperation with Camp Stanley Storage Activity, Parsons Corporation, and Weatherford Laboratories","usgsCitation":"Blome, C.D., and Clark, A.K., 2014, Key subsurface data help to refine Trinity aquifer hydrostratigraphic units, south-central Texas: U.S. Geological Survey Data Series 768, 1 p., https://doi.org/10.3133/ds768.","productDescription":"1 p.","numberOfPages":"1","onlineOnly":"Y","ipdsId":"IP-042154","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":290582,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds768.jpg"},{"id":290591,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/768/pdf/ds768.pdf"},{"id":290581,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/768/"}],"scale":"100000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Texas","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -99.75,29.00 ], [ -99.75,30.50 ], [ -97.75,30.50 ], [ -97.75,29.00 ], [ -99.75,29.00 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f0a8e4b0bc0bec09f8ed","contributors":{"authors":[{"text":"Blome, Charles D. 0000-0002-3449-9378 cblome@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-9378","contributorId":1246,"corporation":false,"usgs":true,"family":"Blome","given":"Charles","email":"cblome@usgs.gov","middleInitial":"D.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":491188,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Allan K. 0000-0003-0099-1521 akclark@usgs.gov","orcid":"https://orcid.org/0000-0003-0099-1521","contributorId":1279,"corporation":false,"usgs":true,"family":"Clark","given":"Allan","email":"akclark@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":491189,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70170985,"text":"70170985 - 2014 - Linking rapid magma reservoir assembly and eruption trigger mechanisms at evolved Yellowstone-type supervolcanoes","interactions":[],"lastModifiedDate":"2019-11-14T12:31:26","indexId":"70170985","displayToPublicDate":"2014-07-21T12:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Linking rapid magma reservoir assembly and eruption trigger mechanisms at evolved Yellowstone-type supervolcanoes","docAbstract":"<p><span>The geological record contains evidence of volcanic eruptions that were as much as two orders of magnitude larger than the most voluminous eruption experienced by modern civilizations, the A.D. 1815 Tambora (Indonesia) eruption. Perhaps nowhere on Earth are deposits of such supereruptions more prominent than in the Snake River Plain&ndash;Yellowstone Plateau (SRP-YP) volcanic province (northwest United States). While magmatic activity at Yellowstone is still ongoing, the Heise volcanic field in eastern Idaho represents the youngest complete caldera cycle in the SRP-YP, and thus is particularly instructive for current and future volcanic activity at Yellowstone. The Heise caldera cycle culminated 4.5 Ma ago in the eruption of the &sim;1800 km</span><sup>3</sup><span>&nbsp;Kilgore Tuff. Accessory zircons in the Kilgore Tuff display significant intercrystalline and intracrystalline oxygen isotopic heterogeneity, and the vast majority are&nbsp;</span><sup>18</sup><span>O depleted. This suggests that zircons crystallized from isotopically distinct magma batches that were generated by remelting of subcaldera silicic rocks previously altered by low-&delta;</span><sup>18</sup><span>O meteoric-hydrothermal fluids. Prior to eruption these magma batches were assembled and homogenized into a single voluminous reservoir. U-Pb geochronology of isotopically diverse zircons using chemical abrasion&ndash;isotope dilution&ndash;thermal ionization mass spectrometry yielded indistinguishable crystallization ages with a weighted mean&nbsp;</span><sup>206</sup><span>Pb/</span><sup>238</sup><span>U date of 4.4876 &plusmn; 0.0023 Ma (MSWD = 1.5; n = 24). These zircon crystallization ages are also indistinguishable from the sanidine&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar dates, and thus zircons crystallized close to eruption. This requires that shallow crustal melting, assembly of isolated batches into a supervolcanic magma reservoir, homogenization, and eruption occurred extremely rapidly, within the resolution of our geochronology (10</span><sup>3</sup><span>&ndash;10</span><sup>4</sup><span>&nbsp;yr). The crystal-scale image of the reservoir configuration, with several isolated magma batches, is very similar to the reservoir configurations inferred from seismic data at active supervolcanoes. The connection of magma batches vertically distributed over several kilometers in the upper crust would cause a substantial increase of buoyancy overpressure, providing an eruption trigger mechanism that is the direct consequence of the reservoir assembly process.</span></p>","language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","doi":"10.1130/G35979.1","usgsCitation":"Wotzlaw, J., Bindeman, I., Watts, K.E., Schmitt, A., Caricchi, L., and Schaltegger, U., 2014, Linking rapid magma reservoir assembly and eruption trigger mechanisms at evolved Yellowstone-type supervolcanoes: Geology, v. 42, no. 9, p. 807-810, https://doi.org/10.1130/G35979.1.","productDescription":"4 p.","startPage":"807","endPage":"810","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057603","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":321300,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.29150390625,\n              44.05601169578525\n            ],\n            [\n              -109.9072265625,\n              44.05601169578525\n            ],\n            [\n              -109.9072265625,\n              45.089035564831036\n            ],\n            [\n              -111.29150390625,\n              45.089035564831036\n            ],\n            [\n              -111.29150390625,\n              44.05601169578525\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"42","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"574d65a7e4b07e28b6684601","contributors":{"authors":[{"text":"Wotzlaw, J.F.","contributorId":169319,"corporation":false,"usgs":false,"family":"Wotzlaw","given":"J.F.","email":"","affiliations":[{"id":25472,"text":"University of Geneva","active":true,"usgs":false}],"preferred":false,"id":629330,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bindeman, I.N.","contributorId":99337,"corporation":false,"usgs":true,"family":"Bindeman","given":"I.N.","affiliations":[],"preferred":false,"id":629331,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watts, Kathryn E. 0000-0002-6110-7499 kwatts@usgs.gov","orcid":"https://orcid.org/0000-0002-6110-7499","contributorId":5081,"corporation":false,"usgs":true,"family":"Watts","given":"Kathryn","email":"kwatts@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":629329,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmitt, A.K.","contributorId":75320,"corporation":false,"usgs":true,"family":"Schmitt","given":"A.K.","email":"","affiliations":[],"preferred":false,"id":629332,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caricchi, L.","contributorId":169320,"corporation":false,"usgs":false,"family":"Caricchi","given":"L.","affiliations":[{"id":25472,"text":"University of Geneva","active":true,"usgs":false}],"preferred":false,"id":629333,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schaltegger, U.","contributorId":169321,"corporation":false,"usgs":false,"family":"Schaltegger","given":"U.","affiliations":[{"id":25472,"text":"University of Geneva","active":true,"usgs":false}],"preferred":false,"id":629334,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
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