Whether a waterway is temporary or permanent influences regulatory protection guidelines, however, classification can be subjective due to a combination of factors, including time of year, antecedent moisture conditions, and previous experience of the field investigator. Our objective was to develop a standardized protocol using publicly available spatial information to classify ephemeral, intermittent, and perennial streams. Our hypothesis was that field observations of flow along the stream channel could be compared to results from a hydrologic model, providing an objective method of how these stream reaches can be identified. Flow-state sensors were placed at ephemeral, intermittent, and perennial stream reaches from May to December 2011 in the Appalachian coal basin of eastern Kentucky. This observed flow record was then used to calibrate the simulated saturation deficit in each channel reach based on the topographic wetness index used by TOPMODEL. Saturation deficit values were categorized as flow or no-flow days, and the simulated record of streamflow was compared to the observed record. The hydrologic model was more accurate for simulating flow during the spring and fall seasons. However, the model effectively identified stream reaches as intermittent and perennial in each of the two basins.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12352","usgsCitation":"Williamson, T., Agouridis, C.T., Barton, C.D., Villines, J.A., and Lant, J.G., 2015, Classification of ephemeral, intermittent, and perennial stream reaches using a TOPMODEL-based approach: Journal of the American Water Resources Association, v. 51, no. 6, p. 1739-1759, https://doi.org/10.1111/1752-1688.12352.","productDescription":"21 p.","startPage":"1739","endPage":"1759","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051282","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":311879,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-18","publicationStatus":"PW","scienceBaseUri":"566167b7e4b06a3ea36c5655","contributors":{"authors":[{"text":"Williamson, Tanja N. tnwillia@usgs.gov","contributorId":452,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja N.","email":"tnwillia@usgs.gov","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":false,"id":581038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Agouridis, Carmen T. 0000-0001-9580-6143","orcid":"https://orcid.org/0000-0001-9580-6143","contributorId":150223,"corporation":false,"usgs":false,"family":"Agouridis","given":"Carmen","email":"","middleInitial":"T.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":581040,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barton, Christopher D.","contributorId":150222,"corporation":false,"usgs":false,"family":"Barton","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":581039,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Villines, Jonathan A.","contributorId":150224,"corporation":false,"usgs":false,"family":"Villines","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":581041,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lant, Jeremiah G. 0000-0001-6688-4820 jlant@usgs.gov","orcid":"https://orcid.org/0000-0001-6688-4820","contributorId":4912,"corporation":false,"usgs":true,"family":"Lant","given":"Jeremiah","email":"jlant@usgs.gov","middleInitial":"G.","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":581042,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159003,"text":"sir20155151 - 2015 - Regression Equations for Monthly and Annual Mean and Selected Percentile Streamflows for Ungaged Rivers in Maine","interactions":[],"lastModifiedDate":"2015-12-31T10:46:01","indexId":"sir20155151","displayToPublicDate":"2015-12-03T12:00:00","publicationYear":"2015","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":"2015-5151","title":"Regression Equations for Monthly and Annual Mean and Selected Percentile Streamflows for Ungaged Rivers in Maine","docAbstract":"In an effort to delineate hydrologic conditions in Maine, the U.S. Geological Survey, in cooperation with the Maine Department of Transportation, used streamflow data to develop dependent variables for 130 regression equations for estimating monthly and annual mean and 1, 5, 10, 25, 50, 75, 90, 95, and 99 percentile streamflows for ungaged, unregulated rivers in Maine. Daily streamflow data from 24 rural unregulated basins with drainage areas between 14.9 and 1,419 square miles in Maine and northern New Hampshire were used in the derivation of the equations. Streamflow data collected from October 1, 1982, through September 30, 2012, were used to derive the dependent variables for this study to represent current [2015] hydrologic conditions in Maine and northern New Hampshire. Weighted least squares regression techniques were used to derive the final coefficients and measures of uncertainty for the regression equations. Eight basin characteristics serve as the explanatory variables: drainage area, distance from the coast, mean and maximum basin elevation, mean basin slope, mean basin percentage of hydrologic soil group A, fraction of sand and gravel aquifers, and percentage of open water.
\nThe largest average errors of prediction are associated with regression equations for the lowest streamflows derived for months during which the lowest streamflows of the year occur (such as the 5 and 1 monthly percentiles for August and September). The regression equations have been derived on the basis of streamflow and basin characteristics data for unregulated, rural drainage basins without substantial streamflow or drainage modifications (for example, diversions and (or) regulation by dams or reservoirs, tile drainage, irrigation, channelization, and impervious paved surfaces), therefore using the equations for regulated or urbanized basins with substantial streamflow or drainage modifications will yield results of unknown error. Input basin characteristics derived using techniques or datasets other than those documented in this report or using values outside the ranges used to develop these regression equations also will yield results of unknown error.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155151","collaboration":"Prepared in cooperation with the Maine Department of Transportation","usgsCitation":"Dudley, R.W., 2015, Regression equations for monthly and annual mean and selected percentile streamflows for ungaged rivers in Maine (ver. 1.1, December 21, 2015): U.S. Geological Survey Scientific Investigations Report 2015–5151, 35 p., https://dx.doi.org/10.3133/sir20155151.","productDescription":"viii, 35 p.","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066284","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"links":[{"id":311685,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5151/sir20155151.pdf","text":"Report","size":"8.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5151"},{"id":312572,"rank":3,"type":{"id":25,"text":"Version 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\"}}]}","edition":"Version 1: Originally posted December 3, 2015; Version 1.1: December 21, 2015","contact":"Director, New England Water Science Center
U.S. Geological Survey
196 Whitten Road
Augusta, ME 04330
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As Arctic regions warm and frozen soils thaw, the large organic carbon pool stored in permafrost becomes increasingly vulnerable to decomposition or transport. The transfer of newly mobilized carbon to the atmosphere and its potential influence upon climate change will largely depend on the degradability of carbon delivered to aquatic ecosystems. Dissolved organic carbon (DOC) is a key regulator of aquatic metabolism, yet knowledge of the mechanistic controls on DOC biodegradability is currently poor due to a scarcity of long-term data sets, limited spatial coverage of available data, and methodological diversity. Here, we performed parallel biodegradable DOC (BDOC) experiments at six Arctic sites (16 experiments) using a standardized incubation protocol to examine the effect of methodological differences commonly used in the literature. We also synthesized results from 14 aquatic and soil leachate BDOC studies from across the circum-arctic permafrost region to examine pan-arctic trends in BDOC.
An increasing extent of permafrost across the landscape resulted in higher DOC losses in both soil and aquatic systems. We hypothesize that the unique composition of (yedoma) permafrost-derived DOC combined with limited prior microbial processing due to low soil temperature and relatively short flow path lengths and transport times, contributed to a higher overall terrestrial and freshwater DOC loss. Additionally, we found that the fraction of BDOC decreased moving down the fluvial network in continuous permafrost regions, i.e. from streams to large rivers, suggesting that highly biodegradable DOC is lost in headwater streams. We also observed a seasonal (January–December) decrease in BDOC in large streams and rivers, but saw no apparent change in smaller streams or soil leachates. We attribute this seasonal change to a combination of factors including shifts in carbon source, changing DOC residence time related to increasing thaw-depth, increasing water temperatures later in the summer, as well as decreasing hydrologic connectivity between soils and surface water as the thaw season progresses. Our results suggest that future climate warming-induced shifts of continuous permafrost into discontinuous permafrost regions could affect the degradation potential of thaw-released DOC, the amount of BDOC, as well as its variability throughout the Arctic summer. We lastly recommend a standardized BDOC protocol to facilitate the comparison of future work and improve our knowledge of processing and transport of DOC in a changing Arctic.
Lakes are prevalent in the Arctic and thus play a key role in regional hydrology. Since many Arctic lakes are shallow and ice grows thick (historically 2-m or greater), seasonal ice commonly freezes to the lake bed (bedfast ice) by winter's end. Bedfast ice fundamentally alters lake energy balance and melt-out processes compared to deeper lakes that exceed the maximum ice thickness (floating ice) and maintain perennial liquid water below floating ice. Our analysis of lakes in northern Alaska indicated that ice-out of bedfast ice lakes occurred on average 17 days earlier (22-June) than ice-out on adjacent floating ice lakes (9-July). Earlier ice-free conditions in bedfast ice lakes caused higher open-water evaporation, 28% on average, relative to floating ice lakes and this divergence increased in lakes closer to the coast and in cooler summers. Water isotopes (18O and 2H) indicated similar differences in evaporation between these lake types. Our analysis suggests that ice regimes created by the combination of lake depth relative to ice thickness and associated ice-out timing currently cause a strong hydrologic divergence among Arctic lakes. Thus understanding the distribution and dynamics of lakes by ice regime is essential for predicting regional hydrology. An observed regime shift in lakes to floating ice conditions due to thinner ice growth may initially offset lake drying because of lower evaporative loss from this lake type. This potential negative feedback caused by winter processes occurs in spite of an overall projected increase in evapotranspiration as the Arctic climate warms.
","language":"English","publisher":"AGU","doi":"10.1002/2015WR017362","usgsCitation":"Arp, C.D., Jones, B.M., Liljedahl, A.K., Hinkel, K., and Welker, J.A., 2015, Depth, ice thickness, and ice-out timing cause divergent hydrologic responses among Arctic lakes: Water Resources Research, v. 51, no. 12, p. 9379-9401, https://doi.org/10.1002/2015WR017362.","productDescription":"23 p.","startPage":"9379","endPage":"9401","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064849","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":471586,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr017362","text":"Publisher Index Page"},{"id":311769,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.18115234375,\n 68.4072675680943\n ],\n [\n -158.18115234375,\n 72.22210088942214\n ],\n [\n -147.8759765625,\n 72.22210088942214\n ],\n [\n -147.8759765625,\n 68.4072675680943\n ],\n [\n -158.18115234375,\n 68.4072675680943\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-07","publicationStatus":"PW","scienceBaseUri":"565ec4afe4b071e7ea54440b","contributors":{"authors":[{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":580787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":580786,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liljedahl, Anna K. 0000-0001-7114-6443","orcid":"https://orcid.org/0000-0001-7114-6443","contributorId":150135,"corporation":false,"usgs":false,"family":"Liljedahl","given":"Anna","email":"","middleInitial":"K.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":580788,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hinkel, Kenneth M.","contributorId":64170,"corporation":false,"usgs":true,"family":"Hinkel","given":"Kenneth M.","affiliations":[],"preferred":false,"id":580789,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Welker, Jeffery A.","contributorId":150136,"corporation":false,"usgs":false,"family":"Welker","given":"Jeffery","email":"","middleInitial":"A.","affiliations":[{"id":12492,"text":"UAA Alaska Natural Heritage Program & Biological Sciences Department","active":true,"usgs":false}],"preferred":false,"id":580790,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70160657,"text":"70160657 - 2015 - Non-invasive flow path characterization in a mining-impacted wetland","interactions":[],"lastModifiedDate":"2018-09-04T15:29:32","indexId":"70160657","displayToPublicDate":"2015-12-01T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Non-invasive flow path characterization in a mining-impacted wetland","docAbstract":"Time-lapse electrical resistivity (ER) was used to capture the dilution of a seasonal pulse of acid mine drainage (AMD) contamination in the subsurface of a wetland downgradient of the abandoned Pennsylvania mine workings in central Colorado. Data were collected monthly from mid-July to late October of 2013, with an additional dataset collected in June of 2014. Inversion of the ER data shows the development through time of multiple resistive anomalies in the subsurface, which corroborating data suggest are driven by changes in total dissolved solids (TDS) localized in preferential flow pathways. Sensitivity analyses on a synthetic model of the site suggest that the anomalies would need to be at least several meters in diameter to be adequately resolved by the inversions. The existence of preferential flow paths would have a critical impact on the extent of attenuation mechanisms at the site, and their further characterization could be used to parameterize reactive transport models in developing quantitative predictions of remediation strategies.
","language":"English","publisher":"Elsevier","publisherLocation":"New York","doi":"10.1016/j.jconhyd.2015.10.002","usgsCitation":"Bethune, J., Randell, J., Runkel, R.L., and Singha, K., 2015, Non-invasive flow path characterization in a mining-impacted wetland: Journal of Contaminant Hydrology, v. 183, p. 29-39, https://doi.org/10.1016/j.jconhyd.2015.10.002.","productDescription":"11 p.","startPage":"29","endPage":"39","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066981","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471587,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jconhyd.2015.10.002","text":"Publisher Index Page"},{"id":312932,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.24603271484375,\n 39.257778150283336\n ],\n [\n -106.24603271484375,\n 39.85915479295669\n ],\n [\n -105.08697509765625,\n 39.85915479295669\n ],\n [\n -105.08697509765625,\n 39.257778150283336\n ],\n [\n -106.24603271484375,\n 39.257778150283336\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"183","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56826b46e4b0a04ef4925b88","contributors":{"authors":[{"text":"Bethune, James","contributorId":150889,"corporation":false,"usgs":false,"family":"Bethune","given":"James","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":583484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Randell, Jackie","contributorId":150890,"corporation":false,"usgs":false,"family":"Randell","given":"Jackie","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":583485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":583483,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Singha, Kamini","contributorId":76733,"corporation":false,"usgs":true,"family":"Singha","given":"Kamini","affiliations":[],"preferred":false,"id":583486,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160371,"text":"70160371 - 2015 - Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain","interactions":[],"lastModifiedDate":"2015-12-23T11:00:01","indexId":"70160371","displayToPublicDate":"2015-12-01T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain","docAbstract":"Growing use of two-dimensional (2-D) hydraulic models has created a need for high resolution data to support flood volume estimates, floodplain specific engineering data, and accurate flood inundation scenarios. Elevation data are a critical input to these models that guide the flood-wave across the landscape allowing the computation of valuable engineering specific data that provides a better understanding of flooding impacts on structures, debris movement, bed scour, and direction. High resolution elevation data are becoming publicly available that can benefit the 2-D flood modeling community. Comparison of these newly available data with legacy data suggests that better modeling outcomes are achieved by using 3D Elevation Program (3DEP) lidar point data and the derived 1 m Digital Elevation Model (DEM) product relative to the legacy 3 m, 10 m, or 30 m products currently available in the U.S. Geological Survey (USGS) National Elevation Dataset. Within the low topographic relief of a coastal floodplain, the newer 3DEP data better resolved elevations within the forested and swampy areas achieving simulations that compared well with a historic flooding event. Results show that the 1 m DEM derived from 3DEP lidar source provides a more conservative estimate of specific energy, static pressure, and impact pressure for grid elements at maximum flow relative to the legacy DEM data. Better flood simulations are critically important in coastal floodplains where climate change driven storm frequency and sea level rise will contribute to more frequent flooding events.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.jhydrol.2015.10.051","usgsCitation":"Witt, E.C., 2015, Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain: Journal of Hydrology, v. 531, no. 3, p. 759-767, https://doi.org/10.1016/j.jhydrol.2015.10.051.","productDescription":"9 p.","startPage":"759","endPage":"767","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066431","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":312794,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","city":"Greenville","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.3298454284668,\n 35.628488848361336\n ],\n [\n -77.32804298400879,\n 35.60330002507124\n ],\n [\n -77.36005783081055,\n 35.604346810028304\n ],\n [\n -77.37645149230957,\n 35.61174370007563\n ],\n [\n -77.37722396850586,\n 35.62583776685229\n ],\n [\n -77.3298454284668,\n 35.628488848361336\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"531","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"567bd3bbe4b0a04ef491a1f9","contributors":{"authors":[{"text":"Witt, Emitt C. III 0000-0002-1814-7807 ecwitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1814-7807","contributorId":1612,"corporation":false,"usgs":true,"family":"Witt","given":"Emitt","suffix":"III","email":"ecwitt@usgs.gov","middleInitial":"C.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":582830,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70189516,"text":"70189516 - 2015 - The effect of natural organic matter on mercury methylation by Desulfobulbus propionicus 1pr3","interactions":[],"lastModifiedDate":"2018-09-04T15:40:41","indexId":"70189516","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1702,"text":"Frontiers in Microbiology","onlineIssn":"1664-302X","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The effect of natural organic matter on mercury methylation by Desulfobulbus propionicus 1pr3","title":"The effect of natural organic matter on mercury methylation by Desulfobulbus propionicus 1pr3","docAbstract":"Methylation of tracer and ambient mercury (200Hg and 202Hg, respectively) equilibrated with four different natural organic matter (NOM) isolates was investigated in vivo using the Hg-methylating sulfate-reducing bacterium Desulfobulbus propionicus 1pr3. Desulfobulbus cultures grown fermentatively with environmentally representative concentrations of dissolved NOM isolates, Hg[II], and HS− were assayed for absolute methylmercury (MeHg) concentration and conversion of Hg(II) to MeHg relative to total unfiltered Hg(II). Results showed the 200Hg tracer was methylated more efficiently in the presence of hydrophobic NOM isolates than in the presence of transphilic NOM, or in the absence of NOM. Different NOM isolates were associated with variable methylation efficiencies for either the 202Hg tracer or ambient 200Hg. One hydrophobic NOM, F1 HpoA derived from dissolved organic matter from the Florida Everglades, was equilibrated for different times with Hg tracer, which resulted in different methylation rates. A 5 day equilibration with F1 HpoA resulted in more MeHg production than either the 4 h or 30 day equilibration periods, suggesting a time dependence for NOM-enhanced Hg bioavailability for methylation.
","language":"English","publisher":"Frontiers","doi":"10.3389/fmicb.2015.01389","usgsCitation":"Moreau, J.W., Gionfriddo, C.M., Krabbenhoft, D.P., Ogorek, J.M., DeWild, J.F., Aiken, G.R., and Roden, E.E., 2015, The effect of natural organic matter on mercury methylation by Desulfobulbus propionicus 1pr3: Frontiers in Microbiology, v. 6, p. 1-15, https://doi.org/10.3389/fmicb.2015.01389.","productDescription":"Article 1389; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-070733","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471604,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmicb.2015.01389","text":"Publisher Index Page"},{"id":343858,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","noUsgsAuthors":false,"publicationDate":"2015-12-18","publicationStatus":"PW","scienceBaseUri":"5969d82ce4b0d1f9f060a197","contributors":{"authors":[{"text":"Moreau, John W.","contributorId":151017,"corporation":false,"usgs":false,"family":"Moreau","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":18167,"text":"University of Melbourne, Melbour","active":true,"usgs":false}],"preferred":false,"id":704997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gionfriddo, Caitlin M.","contributorId":194676,"corporation":false,"usgs":false,"family":"Gionfriddo","given":"Caitlin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":704998,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":704999,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ogorek, Jacob M. 0000-0002-6327-0740 jmogorek@usgs.gov","orcid":"https://orcid.org/0000-0002-6327-0740","contributorId":4960,"corporation":false,"usgs":true,"family":"Ogorek","given":"Jacob","email":"jmogorek@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":705000,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeWild, John F. 0000-0003-4097-2798 jfdewild@usgs.gov","orcid":"https://orcid.org/0000-0003-4097-2798","contributorId":2525,"corporation":false,"usgs":true,"family":"DeWild","given":"John","email":"jfdewild@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":705001,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":705002,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roden, Eric E.","contributorId":127525,"corporation":false,"usgs":false,"family":"Roden","given":"Eric","email":"","middleInitial":"E.","affiliations":[{"id":7009,"text":"Department of Geoscience and NASA Astrobiology Institute, University of Wisconsin, Madison","active":true,"usgs":false}],"preferred":false,"id":705003,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196071,"text":"70196071 - 2015 - Sources and transport of phosphorus to rivers in California and adjacent states, U.S., as determined by SPARROW modeling","interactions":[],"lastModifiedDate":"2018-09-13T16:50:34","indexId":"70196071","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","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":"Sources and transport of phosphorus to rivers in California and adjacent states, U.S., as determined by SPARROW modeling","docAbstract":"The SPARROW (SPAtially Referenced Regression on Watershed attributes) model was used to simulate annual phosphorus loads and concentrations in unmonitored stream reaches in California, U.S., and portions of Nevada and Oregon. The model was calibrated using de-trended streamflow and phosphorus concentration data at 80 locations. The model explained 91% of the variability in loads and 51% of the variability in yields for a base year of 2002. Point sources, geological background, and cultivated land were significant sources. Variables used to explain delivery of phosphorus from land to water were precipitation and soil clay content. Aquatic loss of phosphorus was significant in streams of all sizes, with the greatest decay predicted in small- and intermediate-sized streams. Geological sources, including volcanic rocks and shales, were the principal control on concentrations and loads in many regions. Some localized formations such as the Monterey shale of southern California are important sources of phosphorus and may contribute to elevated stream concentrations. Many of the larger point source facilities were located in downstream areas, near the ocean, and do not affect inland streams except for a few locations. Large areas of cultivated land result in phosphorus load increases, but do not necessarily increase the loads above those of geological background in some cases because of local hydrology, which limits the potential of phosphorus transport from land to streams.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12326","usgsCitation":"Domagalski, J.L., and Saleh, D., 2015, Sources and transport of phosphorus to rivers in California and adjacent states, U.S., as determined by SPARROW modeling: Journal of the American Water Resources Association, v. 51, no. 6, p. 1463-1486, https://doi.org/10.1111/1752-1688.12326.","productDescription":"24 p.","startPage":"1463","endPage":"1486","ipdsId":"IP-052538","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":352579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"6","noUsgsAuthors":false,"publicationDate":"2015-07-14","publicationStatus":"PW","scienceBaseUri":"5afeeb20e4b0da30c1bfc64a","contributors":{"authors":[{"text":"Domagalski, Joseph L. 0000-0002-6032-757X joed@usgs.gov","orcid":"https://orcid.org/0000-0002-6032-757X","contributorId":1330,"corporation":false,"usgs":true,"family":"Domagalski","given":"Joseph","email":"joed@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saleh, Dina 0000-0002-1406-9303 dsaleh@usgs.gov","orcid":"https://orcid.org/0000-0002-1406-9303","contributorId":939,"corporation":false,"usgs":true,"family":"Saleh","given":"Dina","email":"dsaleh@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731208,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70184232,"text":"70184232 - 2015 - Hydrologic implications of GRACE satellite data in the Colorado River Basin","interactions":[],"lastModifiedDate":"2018-01-30T18:44:55","indexId":"70184232","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","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":"Hydrologic implications of GRACE satellite data in the Colorado River Basin","docAbstract":"Use of GRACE (Gravity Recovery and Climate Experiment) satellites for assessing global water resources is rapidly expanding. Here we advance application of GRACE satellites by reconstructing long-term total water storage (TWS) changes from ground-based monitoring and modeling data. We applied the approach to the Colorado River Basin which has experienced multiyear intense droughts at decadal intervals. Estimated TWS declined by 94 km3 during 1986–1990 and by 102 km3 during 1998–2004, similar to the TWS depletion recorded by GRACE (47 km3) during 2010–2013. Our analysis indicates that TWS depletion is dominated by reductions in surface reservoir and soil moisture storage in the upper Colorado basin with additional reductions in groundwater storage in the lower basin. Groundwater storage changes are controlled mostly by natural responses to wet and dry cycles and irrigation pumping outside of Colorado River delivery zones based on ground-based water level and gravity data. Water storage changes are controlled primarily by variable water inputs in response to wet and dry cycles rather than increasing water use. Surface reservoir storage buffers supply variability with current reservoir storage representing ∼2.5 years of available water use. This study can be used as a template showing how to extend short-term GRACE TWS records and using all available data on storage components of TWS to interpret GRACE data, especially within the context of droughts.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015WR018090","usgsCitation":"Scanlon, B., Zhang, Z., Reedy, R.C., Pool, D.R., Save, H., Long, D., Chen, J., Wolock, D.M., Conway, B.D., and Winester, D., 2015, Hydrologic implications of GRACE satellite data in the Colorado River Basin: Water Resources Research, v. 51, no. 12, p. 9891-9903, https://doi.org/10.1002/2015WR018090.","productDescription":"13 p.","startPage":"9891","endPage":"9903","ipdsId":"IP-070650","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":471613,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr018090","text":"Publisher Index Page"},{"id":336855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Colorado River Basin","volume":"51","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-24","publicationStatus":"PW","scienceBaseUri":"58be833ce4b014cc3a3a99f3","contributors":{"authors":[{"text":"Scanlon, Bridget R.","contributorId":74093,"corporation":false,"usgs":true,"family":"Scanlon","given":"Bridget R.","affiliations":[],"preferred":false,"id":680670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Zizhan","contributorId":187508,"corporation":false,"usgs":false,"family":"Zhang","given":"Zizhan","email":"","affiliations":[],"preferred":false,"id":680671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reedy, Robert C.","contributorId":187509,"corporation":false,"usgs":false,"family":"Reedy","given":"Robert","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":680672,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pool, Donald R. drpool@usgs.gov","contributorId":1121,"corporation":false,"usgs":true,"family":"Pool","given":"Donald","email":"drpool@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":680669,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Save, Himanshu","contributorId":187510,"corporation":false,"usgs":false,"family":"Save","given":"Himanshu","email":"","affiliations":[],"preferred":false,"id":680673,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Long, Di","contributorId":187511,"corporation":false,"usgs":false,"family":"Long","given":"Di","email":"","affiliations":[],"preferred":false,"id":680674,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chen, Jianli","contributorId":187512,"corporation":false,"usgs":false,"family":"Chen","given":"Jianli","email":"","affiliations":[],"preferred":false,"id":680675,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"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":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":680676,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Conway, Brian D.","contributorId":187513,"corporation":false,"usgs":false,"family":"Conway","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":680677,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Winester, Daniel","contributorId":187514,"corporation":false,"usgs":false,"family":"Winester","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":680678,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70161741,"text":"70161741 - 2015 - Fire effects on aquatic ecosystems: An assessment of the current state of the science","interactions":[],"lastModifiedDate":"2025-06-25T13:19:04.034953","indexId":"70161741","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Fire effects on aquatic ecosystems: An assessment of the current state of the science","docAbstract":"Fire is a prevalent feature of many landscapes and has numerous and complex effects on geological, hydrological, ecological, and economic systems. In some regions, the frequency and intensity of wildfire have increased in recent years and are projected to escalate with predicted climatic and landuse changes. In addition, prescribed burns continue to be used in many parts of the world to clear vegetation for development projects, encourage desired vegetation, and reduce fuel loads. Given the prevalence of fire on the landscape, authors of papers in this special series examine the complexities of fire as a disturbance shaping freshwater ecosystems and highlight the state of the science. These papers cover key aspects of fire effects that range from vegetation loss and recovery in watersheds to effects on hydrology and water quality with consequences for communities (from algae to fish), food webs, and ecosystem processes (e.g., organic matter subsidies, nutrient cycling) across a range of scales. The results presented in this special series of articles expand our knowledge of fire effects in different biomes, water bodies, and geographic regions, encompassing aquatic population, community, and ecosystem responses. In this overview, we summarize each paper and emphasize its contributions to knowledge on fire ecology and freshwater ecosystems. This overview concludes with a list of 7 research foci that are needed to further our knowledge of fire effects on aquatic ecosystems, including research on: 1) additional biomes and geographic regions; 2) additional habitats, including wetlands and lacustrine ecosystems; 3) different fire severities, sizes, and spatial configurations; and 4) additional response variables (e.g., ecosystem processes) 5) over long (>5 y) time scales 6) with more rigorous study designs and data analyses, and 7) consideration of the effects of fire management practices and policies on aquatic ecosystems.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/684073","usgsCitation":"Bixby, R.J., Cooper, S., Gresswell, R.E., Brown, L.E., Dahm, C.N., and Dwire, K.A., 2015, Fire effects on aquatic ecosystems: An assessment of the current state of the science: Freshwater Science, v. 34, no. 4, p. 1340-1350, https://doi.org/10.1086/684073.","productDescription":"11 p.","startPage":"1340","endPage":"1350","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068454","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471611,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/5q9165nf","text":"External Repository"},{"id":381478,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"568cf741e4b0e7a44bc0f156","contributors":{"authors":[{"text":"Bixby, Rebecca J.","contributorId":147389,"corporation":false,"usgs":false,"family":"Bixby","given":"Rebecca","email":"","middleInitial":"J.","affiliations":[{"id":16834,"text":"Dept. of Biology and Museum of Southwestern Biology, Univ of NM","active":true,"usgs":false}],"preferred":false,"id":807071,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cooper, Scott D.","contributorId":152035,"corporation":false,"usgs":false,"family":"Cooper","given":"Scott D.","affiliations":[{"id":18860,"text":"Department of Ecology, Evolution, and Marine Biology and Marine Science Institute University of California","active":true,"usgs":false}],"preferred":false,"id":807072,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gresswell, Robert E. 0000-0003-0063-855X bgresswell@usgs.gov","orcid":"https://orcid.org/0000-0003-0063-855X","contributorId":152031,"corporation":false,"usgs":true,"family":"Gresswell","given":"Robert","email":"bgresswell@usgs.gov","middleInitial":"E.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":587615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Lee E.","contributorId":152036,"corporation":false,"usgs":false,"family":"Brown","given":"Lee","email":"","middleInitial":"E.","affiliations":[{"id":18861,"text":"School of Geography, University of Leeds, Leeds, LS2 9JT, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":807073,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dahm, Clifford N.","contributorId":152037,"corporation":false,"usgs":false,"family":"Dahm","given":"Clifford","email":"","middleInitial":"N.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":587619,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dwire, Kathleen A.","contributorId":225615,"corporation":false,"usgs":false,"family":"Dwire","given":"Kathleen","email":"","middleInitial":"A.","affiliations":[{"id":41171,"text":"US Forest Service, Rocky Mountain Research Station, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":807075,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70184995,"text":"70184995 - 2015 - Influence of grazing and land use on stream-channel characteristics among small dairy farms in the Eastern United States","interactions":[],"lastModifiedDate":"2017-03-13T12:52:54","indexId":"70184995","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5316,"text":"Renewable Agriculture and Food Systems","active":true,"publicationSubtype":{"id":10}},"title":"Influence of grazing and land use on stream-channel characteristics among small dairy farms in the Eastern United States","docAbstract":"Rotational grazing (RG) is a livestock management practice that rotates grazing cattle on a scale of hours to days among small pastures termed paddocks. It may beneficially affect stream channels, relative to other livestock management practices. Such effects and other beneficial effects on hydrology are important to RG's potential to provide a highly multifunctional mode of livestock farming. Previous comparisons of effects of RG and confinement dairy (CD) on adjoining streams have been restricted in scale and scope. We examined 11 stream-channel characteristics on a representative sample of 37 small dairy farms that used either RG or CD production methods. Our objectives were: (1) to compare channel characteristics on RG and CD farms, as these production methods are implemented in practice, in New York, Pennsylvania and Wisconsin, USA; and (2) to examine land use on these farms that may affect stream-channel characteristics. To help interpret channel characteristic findings, we examined on-farm land use in riparian areas 50 m in width along both sides of stream reaches and whole-farm land use. In all states, stream-channel characteristics on RG and CD farms did not differ. Whole-farm land use differed significantly between farm types; CD farms allocated more land to annual row crops, whereas RG farms allocated more land to pasture and grassland. However, land cover in 50 m riparian areas was not different between farm types within states; in particular, many RG and CD farms had continuously grazed pastures in riparian areas, typically occupied by juvenile and non-lactating cows, which may have contributed sediment and nutrients to streams. This similarity in riparian management practices may explain the observed similarity of farm types with respect to stream-channel characteristics. To realize the potential benefits of RG on streams, best management practices that affect stream-channel characteristics, such as protection of riparian areas, may improve aggregate effects of RG on stream quality and also enhance other environment, economic and social benefits of RG.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/S1742170514000362","usgsCitation":"Brand, G., Vondracek, B.C., and Jordan, N.R., 2015, Influence of grazing and land use on stream-channel characteristics among small dairy farms in the Eastern United States: Renewable Agriculture and Food Systems, v. 30, no. 6, p. 524-536, https://doi.org/10.1017/S1742170514000362.","productDescription":"13 p.","startPage":"524","endPage":"536","ipdsId":"IP-040573","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":337427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-09-30","publicationStatus":"PW","scienceBaseUri":"58c7afa4e4b0849ce9795eb8","contributors":{"authors":[{"text":"Brand, Genevieve","contributorId":189126,"corporation":false,"usgs":false,"family":"Brand","given":"Genevieve","email":"","affiliations":[],"preferred":false,"id":683905,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vondracek, Bruce C. bcv@usgs.gov","contributorId":904,"corporation":false,"usgs":true,"family":"Vondracek","given":"Bruce","email":"bcv@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":683868,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jordan, Nicholas R.","contributorId":39629,"corporation":false,"usgs":true,"family":"Jordan","given":"Nicholas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":683906,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70174840,"text":"70174840 - 2015 - Monitoring changes in seismic velocity related to an ongoing rapid inflation event at Okmok volcano, Alaska","interactions":[],"lastModifiedDate":"2022-11-02T14:52:07.249021","indexId":"70174840","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring changes in seismic velocity related to an ongoing rapid inflation event at Okmok volcano, Alaska","docAbstract":"Okmok is one of the most active volcanoes in the Aleutian Arc. In an effort to improve our ability to detect precursory activity leading to eruption at Okmok, we monitor a recent, and possibly ongoing, GPS-inferred rapid inflation event at the volcano using ambient noise interferometry (ANI). Applying this method, we identify changes in seismic velocity outside of Okmok’s caldera, which are related to the hydrologic cycle. Within the caldera, we observe decreases in seismic velocity that are associated with the GPS-inferred rapid inflation event. We also determine temporal changes in waveform decorrelation and show a continual increase in decorrelation rate over the time associated with the rapid inflation event. Themagnitude of relative velocity decreases and decorrelation rate increases are comparable to previous studies at Piton de la Fournaise that associate such changes with increased production of volatiles and/ormagmatic intrusion within the magma reservoir and associated opening of fractures and/or fissures. Notably, the largest decrease in relative velocity occurs along the intrastation path passing nearest to the center of the caldera. This observation, along with equal amplitude relative velocity decreases revealed via analysis of intracaldera autocorrelations, suggests that the inflation sourcemay be located approximately within the center of the caldera and represent recharge of shallow magma storage in this location. Importantly, there is a relative absence of seismicity associated with this and previous rapid inflation events at Okmok. Thus, these ANI results are the first seismic evidence of such rapid inflation at the volcano.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JB011939","usgsCitation":"Bennington, N., Haney, M.M., De Angelis, S., Thurber, C., and Freymueller, J., 2015, Monitoring changes in seismic velocity related to an ongoing rapid inflation event at Okmok volcano, Alaska: Journal of Geophysical Research, v. 120, no. 8, p. 5664-5676, https://doi.org/10.1002/2015JB011939.","productDescription":"13 p.","startPage":"5664","endPage":"5676","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068858","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":471603,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb011939","text":"Publisher Index Page"},{"id":325374,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Okmok Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -168.25928811603328,\n 53.48606857460288\n ],\n [\n -168.25928811603328,\n 53.35666372572206\n ],\n [\n -168.0005045660394,\n 53.35666372572206\n ],\n [\n -168.0005045660394,\n 53.48606857460288\n ],\n [\n -168.25928811603328,\n 53.48606857460288\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"120","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-18","publicationStatus":"PW","scienceBaseUri":"578dfdb4e4b0f1bea0e0f8a3","contributors":{"authors":[{"text":"Bennington, Ninfa","contributorId":49699,"corporation":false,"usgs":true,"family":"Bennington","given":"Ninfa","affiliations":[],"preferred":false,"id":642731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":642730,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De Angelis, Silvio","contributorId":172953,"corporation":false,"usgs":false,"family":"De Angelis","given":"Silvio","affiliations":[{"id":27128,"text":"Univ. of Liverpool","active":true,"usgs":false}],"preferred":false,"id":642732,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thurber, Clifford","contributorId":44067,"corporation":false,"usgs":true,"family":"Thurber","given":"Clifford","affiliations":[],"preferred":false,"id":642733,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Freymueller, Jeff","contributorId":82190,"corporation":false,"usgs":true,"family":"Freymueller","given":"Jeff","affiliations":[],"preferred":false,"id":642734,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193797,"text":"70193797 - 2015 - Determining climate change management priorities: A case study from Wisconsin ","interactions":[],"lastModifiedDate":"2017-11-10T10:32:00","indexId":"70193797","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2231,"text":"Journal of Conservation Planning","active":true,"publicationSubtype":{"id":10}},"title":"Determining climate change management priorities: A case study from Wisconsin ","docAbstract":"A burgeoning dialogue exists regarding how to allocate resources to maximize the likelihood of long-term biodiversity conservation within the context of climate change. To make effective decisions in natural resource management, an iterative, collaborative, and learning-based decision process may be more successful than a strictly consultative approach. One important, early step in a decision process is to identify priority species or systems. Although this promotes the conservation of select species or systems, it may inadvertently alter the future of non-target species and systems. We describe a process to screen terrestrial wildlife for potential sensitivity to climate change and then use the results to engage natural resource professionals in a process of identifying priorities for monitoring, research, and adaptation strategy implementation. We demonstrate this approach using a case study from Wisconsin. In Wisconsin, experts identified 23 out of 353 species with sufficient empirical research and management understanding to inform targeted action. Habitat management and management of hydrological conditions were the common strategies for targeted action. Although there may be an interest in adaptation strategy implementation for many species and systems, experts considered existing information inadequate to inform targeted action. According to experts, 40% of the vertebrate species in Wisconsin will require near-term intervention for climate adaptation. These results will inform state-wide conservation planning as well as regional efforts.
","language":"English","publisher":"The Conservation Fund","usgsCitation":"LeDee, O., and Ribic, C., 2015, Determining climate change management priorities: A case study from Wisconsin : Journal of Conservation Planning, v. 11, no. 1, p. 1-12.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-040823","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":348216,"type":{"id":15,"text":"Index Page"},"url":"https://www.journalconsplanning.org/"}],"country":"United 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,{"id":70220207,"text":"70220207 - 2015 - A comparison of thermal infrared to fiber-optic distributed temperature sensing for evaluation of groundwater discharge to surface water","interactions":[],"lastModifiedDate":"2021-04-27T14:29:52.674829","indexId":"70220207","displayToPublicDate":"2015-11-30T08:31:30","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of thermal infrared to fiber-optic distributed temperature sensing for evaluation of groundwater discharge to surface water","docAbstract":"Groundwater has a predictable thermal signature that can be used to locate discrete zones of discharge to surface water. As climate warms, surface water with strong groundwater influence will provide habitat stability and refuge for thermally stressed aquatic species, and is therefore critical to locate and protect. Alternatively, these discrete seepage locations may serve as potential point sources of contaminants from polluted aquifers. This study compares two increasingly common heat tracing methods to locate discrete groundwater discharge: direct-contact measurements made with fiber-optic distributed temperature sensing (FO-DTS) and remote sensing measurements collected with thermal infrared (TIR) cameras. FO-DTS is used to make high spatial resolution (typically m) thermal measurements through time within the water column using temperature-sensitive cables. The spatialtemporal data can be analyzed with statistical measures to reveal zones of groundwater influence, however, the personnel requirements, time to install, and time to georeference the cables can be burdensome, and the control units need constant calibration. In contrast, TIR data collection, either from handheld, airborne, or satellite platforms, can quickly capture point-in-time evaluations of groundwater seepage zones across large scales. However the remote nature of TIR measurements means they can be adversely influenced by a number of environmental and physical factors, and the measurements are limited to the surface skin temperature of water features. We present case studies from a range of lentic to lotic aquatic systems to identify capabilities and limitations of both technologies and highlight situations in which one or the other might be a better instrument choice for locating groundwater discharge. FO-DTS performs well in all systems across seasons, but data collection was limited spatially by practical considerations of cable installation. TIR is found to consistently locate groundwater seepage zones above and along the streambank, but submerged seepage zones are only well identified in shallow systems (e.g. <0.5 m depth) with moderate flow. Winter data collection, when groundwater is relatively warm and buoyant, increases the water surface expression of discharge zones in shallow systems.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2015.09.059","usgsCitation":"Hare, D.K., Briggs, M., Rosenberry, D., Boutt, D., and Lane, J., 2015, A comparison of thermal infrared to fiber-optic distributed temperature sensing for evaluation of groundwater discharge to surface water: Journal of Hydrology, v. 530, p. 153-166, https://doi.org/10.1016/j.jhydrol.2015.09.059.","productDescription":"14 p.","startPage":"153","endPage":"166","ipdsId":"IP-068976","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"links":[{"id":471620,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2015.09.059","text":"Publisher Index Page"},{"id":385322,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts, Michigan, Montana, New York, Pennsylvania","otherGeospatial":"Delaware River, Higgins, Lake, Quashnet River, Red Rocks Lake, Tidmarsh Farms","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.79179382324219,\n 44.41269287945535\n ],\n [\n -84.64210510253906,\n 44.41269287945535\n ],\n [\n -84.64210510253906,\n 44.520989167323734\n ],\n [\n -84.79179382324219,\n 44.520989167323734\n ],\n [\n -84.79179382324219,\n 44.41269287945535\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.91154479980467,\n 44.58582159355544\n ],\n [\n -111.66229248046874,\n 44.58582159355544\n ],\n [\n -111.66229248046874,\n 44.67182693970573\n ],\n [\n -111.91154479980467,\n 44.67182693970573\n ],\n [\n -111.91154479980467,\n 44.58582159355544\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.37513732910156,\n 41.83733944214672\n ],\n [\n -75.16159057617188,\n 41.83733944214672\n ],\n [\n -75.16159057617188,\n 41.99624282178583\n ],\n [\n -75.37513732910156,\n 41.99624282178583\n ],\n [\n -75.37513732910156,\n 41.83733944214672\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.64105987548828,\n 41.828386176902555\n ],\n [\n -70.54630279541016,\n 41.828386176902555\n ],\n [\n -70.54630279541016,\n 41.908664970834444\n ],\n [\n -70.64105987548828,\n 41.908664970834444\n ],\n [\n -70.64105987548828,\n 41.828386176902555\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.55746078491211,\n 41.58026831154093\n ],\n [\n -70.50750732421875,\n 41.58026831154093\n ],\n [\n -70.50750732421875,\n 41.62044728626882\n ],\n [\n -70.55746078491211,\n 41.62044728626882\n ],\n [\n -70.55746078491211,\n 41.58026831154093\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"530","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hare, Danielle K","contributorId":257636,"corporation":false,"usgs":false,"family":"Hare","given":"Danielle","email":"","middleInitial":"K","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":814761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":257637,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":814762,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":257638,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":814763,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boutt, Dave","contributorId":257639,"corporation":false,"usgs":false,"family":"Boutt","given":"Dave","affiliations":[{"id":52076,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":814764,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lane, John W. Jr. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":210076,"corporation":false,"usgs":true,"family":"Lane","given":"John W.","suffix":"Jr.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":814766,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70164522,"text":"70164522 - 2015 - Observed decrease in atmospheric mercury explained by global decline in anthropogenic emissions","interactions":[],"lastModifiedDate":"2018-08-09T12:27:41","indexId":"70164522","displayToPublicDate":"2015-11-30T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Observed decrease in atmospheric mercury explained by global decline in anthropogenic emissions","docAbstract":"Observations of elemental mercury (Hg0) at sites in North America and Europe show large decreases (∼1–2% y−1) from 1990 to present. Observations in background northern hemisphere air, including Mauna Loa Observatory (Hawaii) and CARIBIC (Civil Aircraft for the Regular Investigation of the atmosphere Based on an Instrument Container) aircraft flights, show weaker decreases (<1% y−1). These decreases are inconsistent with current global emission inventories indicating flat or increasing emissions over that period. However, the inventories have three major flaws: (i) they do not account for the decline in atmospheric release of Hg from commercial products; (ii) they are biased in their estimate of artisanal and small-scale gold mining emissions; and (iii) they do not properly account for the change in Hg0/HgII speciation of emissions from coal-fired utilities after implementation of emission controls targeted at SO2 and NOx. We construct an improved global emission inventory for the period 1990 to 2010 accounting for the above factors and find a 20% decrease in total Hg emissions and a 30% decrease in anthropogenic Hg0 emissions, with much larger decreases in North America and Europe offsetting the effect of increasing emissions in Asia. Implementation of our inventory in a global 3D atmospheric Hg simulation [GEOS-Chem (Goddard Earth Observing System-Chemistry)] coupled to land and ocean reservoirs reproduces the observed large-scale trends in atmospheric Hg0 concentrations and in HgII wet deposition. The large trends observed in North America and Europe reflect the phase-out of Hg from commercial products as well as the cobenefit from SO2 and NOx emission controls on coal-fired utilities.
\n","language":"English","publisher":"The Academy","publisherLocation":"Washington, D.C.","doi":"10.1073/pnas.1516312113","usgsCitation":"Zhang, Y., Jacob, D.J., Horowitz, H.M., Chen, L., Amos, H.M., Krabbenhoft, D.P., Slemr, F., St. Louis, V.L., and Elsie M. Sunderland, 2015, Observed decrease in atmospheric mercury explained by global decline in anthropogenic emissions: Proceedings of the National Academy of Sciences, v. 133, no. 3, p. 526-531, https://doi.org/10.1073/pnas.1516312113.","productDescription":"6 p.","startPage":"526","endPage":"531","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070993","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":471622,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.1516312113","text":"Publisher Index Page"},{"id":316735,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"133","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-04","publicationStatus":"PW","scienceBaseUri":"56bb1bc8e4b08d617f654e36","contributors":{"authors":[{"text":"Zhang, Yanxu","contributorId":156387,"corporation":false,"usgs":false,"family":"Zhang","given":"Yanxu","email":"","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":597723,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacob, Daniel J.","contributorId":156388,"corporation":false,"usgs":false,"family":"Jacob","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":597724,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Horowitz, Hannah M.","contributorId":156389,"corporation":false,"usgs":false,"family":"Horowitz","given":"Hannah","email":"","middleInitial":"M.","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":597725,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Long","contributorId":156390,"corporation":false,"usgs":false,"family":"Chen","given":"Long","email":"","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":597726,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Amos, Helen M.","contributorId":156391,"corporation":false,"usgs":false,"family":"Amos","given":"Helen","email":"","middleInitial":"M.","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":597727,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":597722,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Slemr, Franz","contributorId":156392,"corporation":false,"usgs":false,"family":"Slemr","given":"Franz","email":"","affiliations":[{"id":12534,"text":"Max-Planck-Institute for Chemistry, Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":597728,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"St. Louis, Vincent L.","contributorId":156393,"corporation":false,"usgs":false,"family":"St. Louis","given":"Vincent","email":"","middleInitial":"L.","affiliations":[{"id":12980,"text":"Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada","active":true,"usgs":false}],"preferred":false,"id":597729,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Elsie M. Sunderland","contributorId":156394,"corporation":false,"usgs":false,"family":"Elsie M. Sunderland","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":597730,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70159804,"text":"70159804 - 2015 - Changes in seasonality and timing of peak streamflow in snow and semi-arid climates of the north-central United States, 1910–2012","interactions":[],"lastModifiedDate":"2017-10-12T20:00:47","indexId":"70159804","displayToPublicDate":"2015-11-24T16:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Changes in seasonality and timing of peak streamflow in snow and semi-arid climates of the north-central United States, 1910–2012","docAbstract":"
Changes in the seasonality and timing of annual peak streamflow in the north-central USA are likely because of changes in precipitation and temperature regimes. A source of long-term information about flood events across the study area is the U.S. Geological Survey peak streamflow database. However, one challenge of answering climate-related questions with this dataset is that even in snowmelt-dominated areas, it is a mixed population of snowmelt/spring rain generated peaks and summer/fall rain generated peaks. Therefore, a process was developed to divide the annual peaks into two populations, or seasons, snowmelt/spring, and summer/fall. The two series were then tested for the hypotheses that because of changes in precipitation regimes, the odds of summer/fall peaks have increased and, because of temperature changes, snowmelt/spring peaks happen earlier. Over climatologically and geographically similar regions in the north-central USA, logistic regression was used to model the odds of getting a summer/fall peak. When controlling for antecedent wet and dry conditions and geographical differences, the odds of summer/fall peaks occurring have increased across the study area. With respect to timing within the seasons, trend analysis showed that in northern portions of the study region, snowmelt/spring peaks are occurring earlier. The timing of snowmelt/spring peaks in three regions in the northern part of the study area is earlier by 8.7– 14.3 days. These changes have implications for water interests, such as potential changes in lead-time for flood forecasting or changes in the operation of flood-control dams.
","language":"English","publisher":"John Wiley & Sons","doi":"10.1002/hyp.10693","usgsCitation":"Ryberg, K.R., Akyuz, F.A., Wiche, G.J., and Lin, W., 2015, Changes in seasonality and timing of peak streamflow in snow and semi-arid climates of the north-central United States, 1910–2012: Hydrological Processes, v. 30, no. 8, p. 1208-1218, https://doi.org/10.1002/hyp.10693.","productDescription":"11 p.","startPage":"1208","endPage":"1218","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1910-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-059283","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":311699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Iowa, Kansas, Minnesota, Missouri, Montana, Nebraska, North Dakota, South Dakota, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.7353515625,\n 48.574789910928864\n ],\n [\n -91.23046875,\n 43.45291889355465\n ],\n [\n -90.263671875,\n 42.00032514831621\n ],\n [\n -91.4501953125,\n 40.38002840251183\n ],\n [\n -90.8349609375,\n 39.13006024213511\n ],\n [\n -102.1728515625,\n 38.61687046392973\n ],\n [\n -105.77636718749999,\n 38.92522904714054\n ],\n [\n -109.4677734375,\n 45.01141864227728\n ],\n [\n -113.09326171875,\n 48.99463598353408\n ],\n [\n -95.20751953125,\n 49.009050809382046\n ],\n [\n -93.7353515625,\n 48.574789910928864\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"8","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-11","publicationStatus":"PW","scienceBaseUri":"56558a32e4b071e7ea53dedf","chorus":{"doi":"10.1002/hyp.10693","url":"http://dx.doi.org/10.1002/hyp.10693","publisher":"Wiley-Blackwell","authors":"Ryberg Karen R., Akyüz F. Adnan, Wiche Gregg J., Lin Wei","journalName":"Hydrological Processes","publicationDate":"11/11/2015","auditedOn":"4/11/2016"},"contributors":{"authors":[{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":580536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Akyuz, F. Adnan","contributorId":140760,"corporation":false,"usgs":false,"family":"Akyuz","given":"F.","email":"","middleInitial":"Adnan","affiliations":[{"id":13555,"text":"North Dakota Climate Office","active":true,"usgs":false}],"preferred":false,"id":580538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wiche, Gregg J. gjwiche@usgs.gov","contributorId":1675,"corporation":false,"usgs":true,"family":"Wiche","given":"Gregg","email":"gjwiche@usgs.gov","middleInitial":"J.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":580539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lin, Wei","contributorId":93805,"corporation":false,"usgs":true,"family":"Lin","given":"Wei","email":"","affiliations":[],"preferred":false,"id":580537,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70158939,"text":"sir20155150 - 2015 - Hydrogeology, hydrologic effects of development, and simulation of groundwater flow in the Borrego Valley, San Diego County, California","interactions":[],"lastModifiedDate":"2016-01-07T10:17:48","indexId":"sir20155150","displayToPublicDate":"2015-11-24T10:30:00","publicationYear":"2015","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":"2015-5150","title":"Hydrogeology, hydrologic effects of development, and simulation of groundwater flow in the Borrego Valley, San Diego County, California","docAbstract":"The Borrego Valley is a small valley (110 square miles) in the northeastern part of San Diego County, California. Although the valley is about 60 miles northeast of city of San Diego, it is separated from the Pacific Ocean coast by the mountains to the west and is mostly within the boundaries of Anza-Borrego Desert State Park. From the time the basin was first settled, groundwater has been the only source of water to the valley. Groundwater is used for agricultural, recreational, and municipal purposes. Over time, groundwater withdrawal through pumping has exceeded the amount of water that has been replenished, causing groundwater-level declines of more than 100 feet in some parts of the basin. Continued pumping has resulted in an increase in pumping lifts, reduced well efficiency, dry wells, changes in water quality, and loss of natural groundwater discharge. As a result, the U.S. Geological Survey began a cooperative study of the Borrego Valley with the Borrego Water District (BWD) in 2009. The purpose of the study was to develop a greater understanding of the hydrogeology of the Borrego Valley Groundwater Basin (BVGB) and to provide tools to help evaluate the potential hydrologic effects of future development. The objectives of the study were to (1) improve the understanding of groundwater conditions and land subsidence, (2) incorporate this improved understanding into a model that would assist in the management of the groundwater resources in the Borrego Valley, and (3) use this model to test several management scenarios. This model provides the capability for the BWD and regional stakeholders to quantify the relative benefits of various options for increasing groundwater storage. The study focuses on the period 1945–2010, with scenarios 50 years into the future.
\nThis report documents and presents (1) an analysis of the conceptual model, (2) a description of the hydrologic features, (3) a compilation and analysis of water-quality data, (4) the measurement and analysis of land subsidence by using geophysical and remote sensing techniques, (5) the development and calibration of a two-dimensional borehole-groundwater-flow model to estimate aquifer hydraulic conductivities, (6) the development and calibration of a three-dimensional (3-D) integrated hydrologic flow model, (7) a water-availability analysis with respect to current climate variability and land use, and (8) potential future management scenarios. The integrated hydrologic model, referred to here as the “Borrego Valley Hydrologic Model” (BVHM), is a tool that can provide results with the accuracy needed for making water-management decisions, although potential future refinements and enhancements could further improve the level of spatial and temporal resolution and model accuracy. Because the model incorporates time-varying inflows and outflows, this tool can be used to evaluate the effects of temporal changes in recharge and pumping and to compare the relative effects of different water-management scenarios on the aquifer system. Overall, the development of the hydrogeologic and hydrologic models, data networks, and hydrologic analysis provides a basis for assessing surface and groundwater availability and potential water-resource management guidelines.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155150","collaboration":"Prepared in cooperation with the Borrego Water District","usgsCitation":"Faunt, C.C., Stamos, C.L., Flint, L.E., Wright, M.T., Burgess, M.K., Sneed, Michelle, Brandt, Justin, Martin, Peter, and Coes, A.L., 2015, Hydrogeology, hydrologic effects of development, and simulation of groundwater flow in the Borrego Valley, San Diego County, California: U.S. Geological Survey Scientific Investigations Report 2015–5150, 135 p., https://dx.doi.org/10.3133/sir20155150.","productDescription":"xiv, 135 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-024573","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":311633,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5150/sir20155150.pdf","text":"Report","size":"21.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5150"},{"id":311632,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5150/coverthb.jpg"},{"id":311671,"rank":3,"type":{"id":18,"text":"Project Site"},"url":"https://dx.doi.org/10.5066/F7S180J9","text":"Borrego Valley Groundwater Conditions"},{"id":314004,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5150/sir20155150_input.zip","text":"Model Input","size":"420 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5150 Model Input files"},{"id":314005,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5150/sir20155150_output.zip","text":"Model Output","size":"45 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5150 Model Output files"}],"country":"United States","state":"California","otherGeospatial":"Borrego Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.54708862304686,\n 32.89342578969234\n ],\n [\n -116.54708862304686,\n 33.34659043589842\n ],\n [\n -115.73272705078124,\n 33.34659043589842\n ],\n [\n -115.73272705078124,\n 32.89342578969234\n ],\n [\n -116.54708862304686,\n 32.89342578969234\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
http://ca.water.usgs.gov
Drill-core samples from a sandstone-hosted uranium (U) deposit in Wyoming were characterized to determine the abundance and distribution of uranium following in-situ recovery (ISR) mining with oxygen- and carbon dioxide-enriched water. Concentrations of uranium, collected from ten depth intervals, ranged from 5 to 1920 ppm. A composite sample contained 750 ppm uranium with an average oxidation state of 54% U(VI) and 46% U(IV). Scanning electron microscopy (SEM) indicated rare high uranium (∼1000 ppm U) in spatial association with P/Ca and Si/O attributed to relict uranium minerals, possibly coffinite, uraninite, and autunite, trapped within low permeability layers bypassed during ISR mining. Fission track analysis revealed lower but still elevated concentrations of U in the clay/silica matrix and organic matter (several 10 s ppm) and yet higher concentrations associated with Fe-rich/S-poor sites, likely iron oxides, on altered chlorite or euhedral pyrite surfaces (but not on framboidal pyrite). Organic C (<1.62%), total S (<0.31%), and P (<0.03%) were in low abundance relative to the overall bulk composition. Microbial community analysis showed a diverse group of bacteria present with a wide range of putative metabolisms, and provides evidence for a variety of redox microenvironments co-existing in core samples. Although the uranium minerals persisting in low permeability areas in association with organic carbon were less affected by oxidizing solutions during mining, the likely sequestration of uranium within labile iron oxides following mining and sensitivity to changes in redox conditions requires careful attention during groundwater restoration.
\n\n
A groundwater-flow model was developed for the Bad River Watershed and surrounding area by using the U.S. Geological Survey (USGS) finite-difference code MODFLOW-NWT. The model simulates steady-state groundwater-flow and base flow in streams by using the streamflow routing (SFR) package. The objectives of this study were to: (1) develop an improved understanding of the groundwater-flow system in the Bad River Watershed at the regional scale, including the sources of water to the Bad River Band of Lake Superior Chippewa Reservation (Reservation) and groundwater/surface-water interactions; (2) provide a quantitative platform for evaluating future impacts to the watershed, which can be used as a starting point for more detailed investigations at the local scale; and (3) identify areas where more data are needed. This report describes the construction and calibration of the groundwater-flow model that was subsequently used for analyzing potential locations for the collection of additional field data, including new observations of water-table elevation for refining the conceptualization and corresponding numerical model of the hydrogeologic system.
\nThe study area can be conceptually divided into three primary hydrogeologic environments. The first encompasses the southern uplands with relatively low topographic relief, where groundwater-flow is unconfined and occurs primarily in sandy till and glacial outwash overlying Archean-aged crystalline bedrock. The second includes a transitional area of higher topographic relief and shallow depth to bedrock, in the vicinity of ridges formed by steeply dipping, early-Proterozoic aged metasedimentary units of the Marquette Range Supergroup (including the Ironwood Formation), and late-Proterozoic igneous units associated with the Midcontinent Rift System (MRS). Groundwater-flow in this area likely occurs primarily through connected networks of bedrock fractures that are not well characterized, and also in isolated pockets of Quaternary deposits. The third and last hydrogeologic environment includes lowlands along Lake Superior where a deep sandstone aquifer is confined by thick deposits of clay-rich till.
\nModel input was compiled by using both published and unpublished data. Constant flux boundary conditions for the model perimeter were developed from a regional analytic element model described in appendix 1 of this report. Pumping from 26 high-capacity wells within the model area was included. The SFR stream network was developed from the National Hydrography Dataset (NHDPlus Version 2) and hydrography from the Wisconsin Department of Natural Resources (WDNR). Hydraulic conductivity values were determined for each model cell by interpolation from a network of pilot points, within zones representing major hydrogeologic units.
\nRecharge to the groundwater system was estimated on a cell-by-cell basis by using the Soil Water Balance code (SWB), with gridded daily temperature and precipitation data for the period 1980–2011, and GIS coverages of soil and land-surface conditions. Estimated recharge varies considerably, following spatial patterns in the precipitation and soil hydrologic group inputs. The lowest recharge values occur in the Superior lowlands, whereas the highest values occur in the upland areas, especially those underlain by sandy soils, and in the vicinity of bedrock hills.
\nThe model was calibrated to groundwater-levels and base flows obtained from the USGS National Water Information System (NWIS) database, and groundwater-levels obtained from the WDNR and Band River Band well-construction databases. Calibration was performed via nonlinear regression by using the parameter-estimation software suite PEST. Groundwater levels and base-flow observations in the calibration dataset were well simulated by the calibrated model, with reasonable values of hydraulic conductivity. The pilot-point parameters that were most constrained by observations during model calibration coincided with the locations containing the most wells (head observations)—especially the population centers of Ashland, Mellen, and other communities along the major highway corridors.
\nResults from the calibrated model illustrate differences in the nature of groundwater-flow within the watershed. In the southern part of the watershed, where bedrock is shallow, groundwater flow paths are relatively short, extending from local recharge areas to adjacent first and second-order streams. In contrast, laterally continuous deposits of clay-rich till covering the Superior Lowlands isolate most smaller streams from the sandstone aquifer, allowing for longer flow paths toward larger streams such as the Bad, Marengo, and White Rivers. Approximately three-quarters of all first-order stream cells were dry in the Superior Lowlands, compared to only half of first-order stream cells in the southern bedrock uplands.
\nThe model was used to delineate the groundwatershed for the Bad and Kakagon Rivers. “Groundwatershed” is defined as the area contributing groundwater discharge to one of these streams and their tributaries. The groundwatershed was found to align closely with the surface-watershed, with the most notable exception occurring along the southwestern half of Birch Hill, where surface water drains southwest towards the Potato River, and groundwater flows north and east towards Lake Superior. Similarly, the contributing area of groundwater-flow to the Reservation was delineated. Results indicate the off-Reservation groundwater contributing area to be limited in comparison to the extent of the watershed, extending southward into the highlands underlain by MRS igneous rock units, but not further into the area underlain by the Marquette Range Supergroup.
\nStable isotope samples were collected from 54 wells within the watershed, to investigate sources of groundwater. Oxygen-18 (δ 18O) values lower than -13.0 per mil were documented in the sampling, and likely indicate the presence of recharge water from the last glacial period (>9,500 years old) beneath the northern portion of the Reservation, in the vicinity of Odanah, Wisconsin.
\nFinally, a new data-worth analysis of potential new monitoring-well locations was performed by using the model. The relative worth of new measurements was evaluated based on their ability to increase confidence in model predictions of groundwater levels and base flows at 35 locations, under the condition of a proposed open-pit iron mine. Results of the new data-worth analysis, and other inputs and outputs from the Bad River model, are available through an online dynamic web mapping service at (http://wim.usgs.gov/badriver/).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155162","collaboration":"Prepared in cooperation with the Bad River Band of Lake Superior Chippewa; U.S. Bureau of Indian Affairs","usgsCitation":"Leaf, A.T., Fienen, M.N., Hunt, R.J., and Buchwald, C.A., 2015, Groundwater/Surface-Water Interactions in the Bad\n River Watershed, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2015–5162, 110 p., https://dx.doi.org/10.3133/sir20155162.","productDescription":"viii, 110 p.","numberOfPages":"122","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061535","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":311584,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5162/coverthb.jpg"},{"id":311585,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5162/sir20155162.pdf","text":"Report","size":"24.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015=5162"},{"id":332726,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7Z0368H","text":"MODFLOW-NWT model used to evaluate groundwater/surface-water interactions in the Bad River Watershed, Wisconsin"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Bad River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.06842041015625,\n 46.36777895261494\n ],\n [\n -91.06842041015625,\n 46.76996843356982\n ],\n [\n -90.43121337890625,\n 46.76996843356982\n ],\n [\n -90.43121337890625,\n 46.36777895261494\n ],\n [\n -91.06842041015625,\n 46.36777895261494\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wisconsin Water Science Center
U.S. Geological Survey
8505 Research W
Middleton, WI USA 53562
http://wi.water.usgs.gov/
In this study, water and whole rock samples from hydraulically fractured wells in the Marcellus Shale (Middle Devonian), and water from conventional wells producing from Upper Devonian sandstones were analyzed for lithium concentrations and isotope ratios (δ7Li). The distribution of lithium concentrations in different mineral groups was determined using sequential extraction. Structurally bound Li, predominantly in clays, accounted for 75-91 wt. % of total Li, whereas exchangeable sites and carbonate cement contain negligible Li (< 3%). Up to 20% of the Li is present in the oxidizable fraction (organic matter and sulfides). The δ7Li values for whole rock shale in Greene Co., Pennsylvania, and Tioga Co., New York, ranged from -2.3 to + 4.3‰, similar to values reported for other shales in the literature. The δ7Li values in shale rocks with stratigraphic depth record progressive weathering of the source region; the most weathered and clay-rich strata with isotopically light Li are found closest to the top of the stratigraphic section. Diagenetic illite-smectite transition could also have partially affected the bulk Li content and isotope ratios of the Marcellus Shale.
\nIn Greene Co., southwest Pennsylvania, the Upper Devonian sandstone formation waters have δ7Li values of + 14.6 ± 1.2 (2SD, n = 25), and are distinct from Marcellus Shale formation waters which have δ7Li of + 10.0 ± 0.8 (2SD, n = 12). These two formation waters also maintain distinctive 87Sr/86Sr ratios suggesting hydrologic separation between these units. Applying temperature-dependent illitilization model to Marcellus Shale, we found that Li concentration in clay minerals increased with Li concentration in pore fluid during diagenetic illite-smectite transition. Samples from north central PA show a much smaller range in both δ7Li and 87Sr/86Sr than in southwest Pennsylvania. Spatial variations in Li and δ7Li values show that Marcellus formation waters are not homogeneous across the Appalachian Basin. Marcellus formation waters in the northeastern Pennsylvania portion of the basin show a much smaller range in both δ7Li and 87Sr/86Sr, suggesting long term, cross-formational fluid migration in this region. Assessing the impact of potential mixing of fresh water with deep formation water requires establishment of a geochemical and isotopic baseline in the shallow, fresh water aquifers, and site specific characterization of formation water, followed by long-term monitoring, particularly in regions of future shale gas development.
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1770 Corporate Drive, Ste. 500
Norcross, GA 30093
678-524-1544
http://water.usgs.gov/watercensus/
The Water Availability Tool for Environmental Resources (WATER) is a decision support system for the nontidal part of the Delaware River Basin that provides a consistent and objective method of simulating streamflow under historical, forecasted, and managed conditions. In order to quantify the uncertainty associated with these simulations, however, streamflow and the associated hydroclimatic variables of potential evapotranspiration, actual evapotranspiration, and snow accumulation and snowmelt must be simulated and compared to long-term, daily observations from sites. This report details model development and optimization, statistical evaluation of simulations for 57 basins ranging from 2 to 930 km2 and 11.0 to 99.5 percent forested cover, and how this statistical evaluation of daily streamflow relates to simulating environmental changes and management decisions that are best examined at monthly time steps normalized over multiple decades. The decision support system provides a database of historical spatial and climatic data for simulating streamflow for 2001–11, in addition to land-cover and general circulation model forecasts that focus on 2030 and 2060. WATER integrates geospatial sampling of landscape characteristics, including topographic and soil properties, with a regionally calibrated hillslope-hydrology model, an impervious-surface model, and hydroclimatic models that were parameterized by using three hydrologic response units: forested, agricultural, and developed land cover. This integration enables the regional hydrologic modeling approach used in WATER without requiring site-specific optimization or those stationary conditions inferred when using a statistical model.
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U.S. Geological Survey
1770 Corporate Drive, Ste. 500
Norcross, GA 30093
678-524-1544
http://water.usgs.gov/watercensus/
We have implemented the USGS National Climate Change Viewer (NCCV), which is an easy-to-use web application that displays future projections from global climate models over the United States at the state, county and watershed scales. We incorporate the NASA NEX-DCP30 statistically downscaled temperature and precipitation for 30 global climate models being used in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), and hydrologic variables we simulated using a simple water-balance model. Our application summarizes very large, complex data sets at scales relevant to resource managers and citizens and makes climate-change projection information accessible to users of varying skill levels. Tens of terabytes of high-resolution climate and water-balance data are distilled to compact binary format summary files that are used in the application. To alleviate slow response times under high loads, we developed a map caching technique that reduces the time it takes to generate maps by several orders of magnitude. The reduced access time scales to >500 concurrent users. We provide code examples that demonstrate key aspects of data processing, data exporting/importing and the caching technique used in the NCCV.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2015.02.016","usgsCitation":"Alder, J.R., and Hostetler, S.W., 2015, Web based visualization of large climate data sets: Environmental Modelling and Software, v. 68, p. 175-180, https://doi.org/10.1016/j.envsoft.2015.02.016.","productDescription":"6 p.","startPage":"175","endPage":"180","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057365","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":311437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"68","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564c4fbee4b0ebfbef0d345f","contributors":{"authors":[{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":579955,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":579956,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159608,"text":"70159608 - 2015 - Dynamic response of desert wetlands to abrupt climate change","interactions":[],"lastModifiedDate":"2015-11-30T11:25:02","indexId":"70159608","displayToPublicDate":"2015-11-17T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"Dynamic response of desert wetlands to abrupt climate change","docAbstract":"Desert wetlands are keystone ecosystems in arid environments and are preserved in the geologic record as groundwater discharge (GWD) deposits. GWD deposits are inherently discontinuous and stratigraphically complex, which has limited our understanding of how desert wetlands responded to past episodes of rapid climate change. Previous studies have shown that wetlands responded to climate change on glacial to interglacial timescales, but their sensitivity to short-lived climate perturbations is largely unknown. Here, we show that GWD deposits in the Las Vegas Valley (southern Nevada, United States) provide a detailed and nearly complete record of dynamic hydrologic changes during the past 35 ka (thousands of calibrated 14C years before present), including cycles of wetland expansion and contraction that correlate tightly with climatic oscillations recorded in the Greenland ice cores. Cessation of discharge associated with rapid warming events resulted in the collapse of entire wetland systems in the Las Vegas Valley at multiple times during the late Quaternary. On average, drought-like conditions, as recorded by widespread erosion and the formation of desert soils, lasted for a few centuries. This record illustrates the vulnerability of desert wetland flora and fauna to abrupt climate change. It also shows that GWD deposits can be used to reconstruct paleohydrologic conditions at millennial to submillennial timescales and informs conservation efforts aimed at protecting these fragile ecosystems in the face of anthropogenic warming.
","language":"English","publisher":"National Academy of Science","doi":"10.1073/pnas.1513352112","usgsCitation":"Springer, K.B., Manker, C.R., and Pigati, J., 2015, Dynamic response of desert wetlands to abrupt climate change: PNAS, v. 112, no. 47, p. 14522-14526, https://doi.org/10.1073/pnas.1513352112.","productDescription":"5 p.","startPage":"14522","endPage":"14526","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064575","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":471642,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.1513352112","text":"Publisher Index Page"},{"id":311434,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Las Vegas Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.51712036132811,\n 36.301845303684345\n ],\n [\n -115.51712036132811,\n 36.5526720732412\n ],\n [\n -115.1806640625,\n 36.5526720732412\n ],\n [\n -115.1806640625,\n 36.301845303684345\n ],\n [\n -115.51712036132811,\n 36.301845303684345\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"112","issue":"47","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-09","publicationStatus":"PW","scienceBaseUri":"564c4fb8e4b0ebfbef0d3451","chorus":{"doi":"10.1073/pnas.1513352112","url":"http://dx.doi.org/10.1073/pnas.1513352112","publisher":"Proceedings of the National Academy of Sciences","authors":"Springer Kathleen B., Manker Craig R., Pigati Jeffrey S.","journalName":"Proceedings of the National Academy of Sciences","publicationDate":"11/9/2015","auditedOn":"5/27/2016","publiclyAccessibleDate":"5/24/2016"},"contributors":{"authors":[{"text":"Springer, Kathleen B. 0000-0002-2404-0264 kspringer@usgs.gov","orcid":"https://orcid.org/0000-0002-2404-0264","contributorId":149826,"corporation":false,"usgs":true,"family":"Springer","given":"Kathleen","email":"kspringer@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":579701,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manker, Craig R. cmanker@usgs.gov","contributorId":149827,"corporation":false,"usgs":true,"family":"Manker","given":"Craig","email":"cmanker@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":579702,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pigati, Jeffrey S. 0000-0001-5843-6219 jpigati@usgs.gov","orcid":"https://orcid.org/0000-0001-5843-6219","contributorId":149825,"corporation":false,"usgs":true,"family":"Pigati","given":"Jeffrey S.","email":"jpigati@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":579700,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}