In late summer of 2008, after nearly 20 years of quiescence, Redoubt Volcano began to show signs of abnormal heat flow in its summit crater. In the months that followed, the excess heat triggered melting and ablation of Redoubt's glaciers, beginning at the summit and propagating to lower elevations as the unrest accelerated. A variety of morphological changes were observed, including the creation of ice cauldrons, areas of wide-spread subsidence, punctures in the ice carved out by steam, and deposition from debris flows. In this paper, we use visual observations, satellite data, and a high resolution digital elevation model of the volcanic edifice to calculate ice loss at Redoubt as a function of time. Our aim is to establish from this time series a proxy for heat flow that can be compared to other data sets collected along the same time interval. Our study area consists of the Drift glacier, which flows from the summit crater down the volcano's north slope, and makes up about one quarter of Redoubt's total ice volume of ~ 4 km3. The upper part of the Drift glacier covers the area of recent volcanism, making this part of ice mass most susceptible to the effect of volcanic heating. Moreover, melt water and other flows are channeled down the Drift glacier drainage by topography, leaving the remainder of Redoubt's ice mantle relatively unaffected. The rate of ice loss averaged around 0.1 m3/s over the last four months of 2008, accelerated to over twenty times this value by February 2009, and peaked at greater than 22 m3/s, just prior to the first major explosion on March 22, 2009. We estimate a cumulative ice loss over this period of about 35 million cubic meters (M m3).
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2012.10.008","usgsCitation":"Bleick, H.A., Coombs, M.L., Cervelli, P.F., Bull, K.F., and Wessels, R., 2013, Volcano–ice interactions precursory to the 2009 eruption of Redoubt Volcano, Alaska: Journal of Volcanology and Geothermal Research, v. 259, p. 373-388, https://doi.org/10.1016/j.jvolgeores.2012.10.008.","productDescription":"16 p.","startPage":"373","endPage":"388","ipdsId":"IP-037530","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":348073,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Redoubt Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -152.95989990234375,\n 60.39011239020665\n ],\n [\n -152.52731323242188,\n 60.39011239020665\n ],\n [\n -152.52731323242188,\n 60.584269526244995\n ],\n [\n -152.95989990234375,\n 60.584269526244995\n ],\n [\n -152.95989990234375,\n 60.39011239020665\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"259","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fc2eade4b0531197b27fd1","contributors":{"authors":[{"text":"Bleick, Heather A. hbleick@usgs.gov","contributorId":2484,"corporation":false,"usgs":true,"family":"Bleick","given":"Heather","email":"hbleick@usgs.gov","middleInitial":"A.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719423,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coombs, Michelle L. 0000-0002-6002-6806 mcoombs@usgs.gov","orcid":"https://orcid.org/0000-0002-6002-6806","contributorId":2809,"corporation":false,"usgs":true,"family":"Coombs","given":"Michelle","email":"mcoombs@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719424,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cervelli, Peter F. 0000-0001-6765-1009 pcervelli@usgs.gov","orcid":"https://orcid.org/0000-0001-6765-1009","contributorId":1936,"corporation":false,"usgs":true,"family":"Cervelli","given":"Peter","email":"pcervelli@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719425,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bull, Katharine F.","contributorId":42692,"corporation":false,"usgs":true,"family":"Bull","given":"Katharine","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":719427,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wessels, Rick 0000-0001-9711-6402 rwessels@usgs.gov","orcid":"https://orcid.org/0000-0001-9711-6402","contributorId":198602,"corporation":false,"usgs":true,"family":"Wessels","given":"Rick","email":"rwessels@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719426,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189351,"text":"70189351 - 2013 - Inorganic carbon loading as a primary driver of dissolved carbon dioxide concentrations in the lakes and reservoirs of the contiguous United States","interactions":[],"lastModifiedDate":"2017-07-11T15:54:09","indexId":"70189351","displayToPublicDate":"2013-06-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"Inorganic carbon loading as a primary driver of dissolved carbon dioxide concentrations in the lakes and reservoirs of the contiguous United States","docAbstract":"Accurate quantification of CO2 flux across the air-water interface and identification of the mechanisms driving CO2 concentrations in lakes and reservoirs is critical to integrating aquatic systems into large-scale carbon budgets, and to predicting the response of these systems to changes in climate or terrestrial carbon cycling. Large-scale estimates of the role of lakes and reservoirs in the carbon cycle, however, typically must rely on aggregation of spatially and temporally inconsistent data from disparate sources. We performed a spatially comprehensive analysis of CO2 concentration and air-water fluxes in lakes and reservoirs of the contiguous United States using large, consistent data sets, and modeled the relative contribution of inorganic and organic carbon loading to vertical CO2 fluxes. Approximately 70% of lakes and reservoirs are supersaturated with respect to the atmosphere during the summer (June–September). Although there is considerable interregional and intraregional variability, lakes and reservoirs represent a net source of CO2 to the atmosphere of approximately 40 Gg C d–1 during the summer. While in-lake CO2 concentrations correlate with indicators of in-lake net ecosystem productivity, virtually no relationship exists between dissolved organic carbon and pCO2,aq. Modeling suggests that hydrologic dissolved inorganic carbon supports pCO2,aq in most supersaturated systems (to the extent that 12% of supersaturated systems simultaneously exhibit positive net ecosystem productivity), and also supports primary production in most CO2-undersaturated systems. Dissolved inorganic carbon loading appears to be an important determinant of CO2concentrations and fluxes across the air-water interface in the majority of lakes and reservoirs in the contiguous United States.
","language":"English","publisher":"AGU","doi":"10.1002/gbc.20032","usgsCitation":"McDonald, C.P., Stets, E.G., Striegl, R.G., and Butman, D., 2013, Inorganic carbon loading as a primary driver of dissolved carbon dioxide concentrations in the lakes and reservoirs of the contiguous United States: Global Biogeochemical Cycles, v. 27, no. 2, p. 285-295, https://doi.org/10.1002/gbc.20032.","productDescription":"11 p.","startPage":"285","endPage":"295","ipdsId":"IP-038087","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":473803,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/gbc.20032","text":"Publisher Index Page"},{"id":343605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"27","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2013-04-03","publicationStatus":"PW","scienceBaseUri":"5965b868e4b0d1f9f05b3894","contributors":{"authors":[{"text":"McDonald, Cory P. 0000-0002-1208-8471 cmcdonald@usgs.gov","orcid":"https://orcid.org/0000-0002-1208-8471","contributorId":4238,"corporation":false,"usgs":true,"family":"McDonald","given":"Cory","email":"cmcdonald@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":704329,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stets, Edward G. 0000-0001-5375-0196 estets@usgs.gov","orcid":"https://orcid.org/0000-0001-5375-0196","contributorId":194490,"corporation":false,"usgs":true,"family":"Stets","given":"Edward","email":"estets@usgs.gov","middleInitial":"G.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":704330,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":704331,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Butman, David 0000-0003-3520-7426 dbutman@usgs.gov","orcid":"https://orcid.org/0000-0003-3520-7426","contributorId":174187,"corporation":false,"usgs":true,"family":"Butman","given":"David","email":"dbutman@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":704332,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70193292,"text":"70193292 - 2013 - Evaluation of Redoubt Volcano's sulfur dioxide emissions by the Ozone Monitoring Instrument","interactions":[],"lastModifiedDate":"2017-10-31T15:46:01","indexId":"70193292","displayToPublicDate":"2013-06-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of Redoubt Volcano's sulfur dioxide emissions by the Ozone Monitoring Instrument","docAbstract":"The 2009 eruption of Redoubt Volcano, Alaska, provided a rare opportunity to compare satellite measurements of sulfur dioxide (SO2) by the Ozone Monitoring Instrument (OMI) with airborne SO2 measurements by the Alaska Volcano Observatory (AVO). Herein we: (1) compare OMI and airborne SO2 column density values for Redoubt's tropospheric plume, (2) calculate daily SO2 masses from Mount Redoubt for the first three months of the eruption, (3) develop simple methods to convert daily measured SO2 masses into emission rates to allow satellite data to be directly integrated with the airborne SO2 emissions dataset, (4) calculate cumulative SO2 emissions from the eruption, and (5) evaluate OMI as a monitoring tool for high-latitude degassing volcanoes. A linear correlation (R2 ~ 0.75) is observed between OMI and airborne SO2 column densities. OMI daily SO2 masses for the sample period ranged from ~ 60.1 kt on 24 March to below detection limit, with an average daily SO2 mass of ~ 6.7 kt. The highest SO2 emissions were observed during the initial part of the explosive phase and the emissions exhibited an overall decreasing trend with time. OMI SO2 emission rates were derived using three methods and compared to airborne measurements. This comparison yields a linear correlation (R2 ~ 0.82) with OMI-derived emission rates consistently lower than airborne measurements. The comparison results suggest that OMI's detection limit for high latitude, springtime conditions varies from ~ 2000 to 4000 t/d. Cumulative SO2 masses calculated from daily OMI data for the sample period are estimated to range from 542 to 615 kt, with approximately half of this SO2 produced during the explosive phase of the eruption. These cumulative masses are similar in magnitude to those estimated for the 1989–90 Redoubt eruption. Strong correlations between daily OMI SO2 mass and both tephra mass and acoustic energy during the explosive phase of the eruption suggest that OMI data may be used to infer relative eruption size and explosivity. Further, when used in conjunction with complementary datasets, OMI daily SO2 masses may be used to help distinguish explosive from effusive activity and identify changes in lava extrusion rates. The results of this study suggest that OMI is a useful volcano monitoring tool to complement airborne measurements, capture explosive SO2 emissions, and provide high temporal resolution SO2 emissions data that can be used with interdisciplinary datasets to illuminate volcanic processes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2012.03.002","usgsCitation":"Lopez, T., Carn, S.A., Werner, C.A., Fee, D., Kelly, P.J., Doukas, M.P., Pfeffer, M., Webley, P., Cahill, C.F., and Schneider, D.J., 2013, Evaluation of Redoubt Volcano's sulfur dioxide emissions by the Ozone Monitoring Instrument: Journal of Volcanology and Geothermal Research, v. 259, p. 290-307, https://doi.org/10.1016/j.jvolgeores.2012.03.002.","productDescription":"18 p.","startPage":"290","endPage":"307","ipdsId":"IP-037424","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473796,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2012.03.002","text":"Publisher Index Page"},{"id":347926,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Redoubt Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.04092407226562,\n 60.36771313471161\n ],\n [\n -152.50808715820312,\n 60.36771313471161\n ],\n [\n -152.50808715820312,\n 60.61056362329555\n ],\n [\n -153.04092407226562,\n 60.61056362329555\n ],\n [\n -153.04092407226562,\n 60.36771313471161\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"259","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f98bbce4b0531197afa02b","contributors":{"authors":[{"text":"Lopez, Taryn","contributorId":146828,"corporation":false,"usgs":false,"family":"Lopez","given":"Taryn","affiliations":[{"id":16753,"text":"University of Alaska Geophysical Institute","active":true,"usgs":false}],"preferred":false,"id":718746,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carn, Simon A.","contributorId":28092,"corporation":false,"usgs":true,"family":"Carn","given":"Simon","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":718747,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Werner, Cynthia A. cwerner@usgs.gov","contributorId":2540,"corporation":false,"usgs":true,"family":"Werner","given":"Cynthia","email":"cwerner@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":718748,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fee, David","contributorId":77761,"corporation":false,"usgs":true,"family":"Fee","given":"David","affiliations":[],"preferred":false,"id":718749,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":718750,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Doukas, Michael P. mdoukas@usgs.gov","contributorId":2686,"corporation":false,"usgs":true,"family":"Doukas","given":"Michael","email":"mdoukas@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":718751,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pfeffer, Melissa","contributorId":199349,"corporation":false,"usgs":false,"family":"Pfeffer","given":"Melissa","affiliations":[],"preferred":false,"id":718752,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Webley, Peter","contributorId":34783,"corporation":false,"usgs":true,"family":"Webley","given":"Peter","affiliations":[],"preferred":false,"id":718753,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cahill, Catherine F.","contributorId":168688,"corporation":false,"usgs":false,"family":"Cahill","given":"Catherine","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":718754,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Schneider, David J. 0000-0001-9092-1054 djschneider@usgs.gov","orcid":"https://orcid.org/0000-0001-9092-1054","contributorId":198601,"corporation":false,"usgs":true,"family":"Schneider","given":"David","email":"djschneider@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":718755,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70187114,"text":"70187114 - 2013 - Application of stable isotope ratio analysis for biodegradation monitoring in groundwater","interactions":[],"lastModifiedDate":"2017-04-24T11:26:12","indexId":"70187114","displayToPublicDate":"2013-06-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5325,"text":"Current Opinion in Biotechnology","active":false,"publicationSubtype":{"id":10}},"title":"Application of stable isotope ratio analysis for biodegradation monitoring in groundwater","docAbstract":"Stable isotope ratio analysis is increasingly being applied as a tool to detect, understand, and quantify biodegradation of organic and inorganic contaminants in groundwater. An important feature of this approach is that it allows degradative losses of contaminants to be distinguished from those caused by non-destructive processes such as dilution, dispersion, and sorption. Recent advances in analytical techniques, and new approaches for interpreting stable isotope data, have expanded the utility of this method while also exposing complications and ambiguities that must be considered in data interpretations. Isotopic analyses of multiple elements in a compound, and multiple compounds in the environment, are being used to distinguish biodegradative pathways by their characteristic isotope effects. Numerical models of contaminant transport, degradation pathways, and isotopic composition are improving quantitative estimates of in situ contaminant degradation rates under realistic environmental conditions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.copbio.2012.11.010","usgsCitation":"Hatzinger, P.B., Bohlke, J., and Sturchio, N.C., 2013, Application of stable isotope ratio analysis for biodegradation monitoring in groundwater: Current Opinion in Biotechnology, v. 24, no. 3, p. 542-549, https://doi.org/10.1016/j.copbio.2012.11.010.","productDescription":"8 p.","startPage":"542","endPage":"549","ipdsId":"IP-041870","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":340176,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ff0ea7e4b006455f2d61f4","contributors":{"authors":[{"text":"Hatzinger, Paul B.","contributorId":149376,"corporation":false,"usgs":false,"family":"Hatzinger","given":"Paul","email":"","middleInitial":"B.","affiliations":[{"id":17721,"text":"Shaw Environmental, Princeton, NJ","active":true,"usgs":false}],"preferred":false,"id":692599,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bohlke, J.K. 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":191103,"corporation":false,"usgs":true,"family":"Bohlke","given":"J.K.","email":"jkbohlke@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":692600,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sturchio, Neil C.","contributorId":88188,"corporation":false,"usgs":true,"family":"Sturchio","given":"Neil","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":692601,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046206,"text":"sir20135090 - 2013 - Computed statistics at streamgages, and methods for estimating low-flow frequency statistics and development of regional regression equations for estimating low-flow frequency statistics at ungaged locations in Missouri","interactions":[],"lastModifiedDate":"2013-05-30T21:49:14","indexId":"sir20135090","displayToPublicDate":"2013-05-30T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5090","title":"Computed statistics at streamgages, and methods for estimating low-flow frequency statistics and development of regional regression equations for estimating low-flow frequency statistics at ungaged locations in Missouri","docAbstract":"The weather and precipitation patterns in Missouri vary considerably from year to year. In 2008, the statewide average rainfall was 57.34 inches and in 2012, the statewide average rainfall was 30.64 inches. This variability in precipitation and resulting streamflow in Missouri underlies the necessity for water managers and users to have reliable streamflow statistics and a means to compute select statistics at ungaged locations for a better understanding of water availability. Knowledge of surface-water availability is dependent on the streamflow data that have been collected and analyzed by the U.S. Geological Survey for more than 100 years at approximately 350 streamgages throughout Missouri. The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, computed streamflow statistics at streamgages through the 2010 water year, defined periods of drought and defined methods to estimate streamflow statistics at ungaged locations, and developed regional regression equations to compute selected streamflow statistics at ungaged locations.\n\nStreamflow statistics and flow durations were computed for 532 streamgages in Missouri and in neighboring States of Missouri. For streamgages with more than 10 years of record, Kendall’s tau was computed to evaluate for trends in streamflow data. If trends were detected, the variable length method was used to define the period of no trend. Water years were removed from the dataset from the beginning of the record for a streamgage until no trend was detected. Low-flow frequency statistics were then computed for the entire period of record and for the period of no trend if 10 or more years of record were available for each analysis.\n\nThree methods are presented for computing selected streamflow statistics at ungaged locations. The first method uses power curve equations developed for 28 selected streams in Missouri and neighboring States that have multiple streamgages on the same streams. Statistical estimates on one of these streams can be calculated at an ungaged location that has a drainage area that is between 40 percent of the drainage area of the farthest upstream streamgage and within 150 percent of the drainage area of the farthest downstream streamgage along the stream of interest. The second method may be used on any stream with a streamgage that has operated for 10 years or longer and for which anthropogenic effects have not changed the low-flow characteristics at the ungaged location since collection of the streamflow data. A ratio of drainage area of the stream at the ungaged location to the drainage area of the stream at the streamgage was computed to estimate the statistic at the ungaged location. The range of applicability is between 40- and 150-percent of the drainage area of the streamgage, and the ungaged location must be located on the same stream as the streamgage. The third method uses regional regression equations to estimate selected low-flow frequency statistics for unregulated streams in Missouri. This report presents regression equations to estimate frequency statistics for the 10-year recurrence interval and for the N-day durations of 1, 2, 3, 7, 10, 30, and 60 days.\n\nBasin and climatic characteristics were computed using geographic information system software and digital geospatial data. A total of 35 characteristics were computed for use in preliminary statewide and regional regression analyses based on existing digital geospatial data and previous studies. Spatial analyses for geographical bias in the predictive accuracy of the regional regression equations defined three low-flow regions with the State representing the three major physiographic provinces in Missouri. Region 1 includes the Central Lowlands, Region 2 includes the Ozark Plateaus, and Region 3 includes the Mississippi Alluvial Plain. A total of 207 streamgages were used in the regression analyses for the regional equations. Of the 207 U.S. Geological Survey streamgages, 77 were located in Region 1, 120 were located in Region 2, and 10 were located in Region 3. Streamgages located outside of Missouri were selected to extend the range of data used for the independent variables in the regression analyses. Streamgages included in the regression analyses had 10 or more years of record and were considered to be affected minimally by anthropogenic activities or trends. Regional regression analyses identified three characteristics as statistically significant for the development of regional equations. For Region 1, drainage area, longest flow path, and streamflow-variability index were statistically significant. The range in the standard error of estimate for Region 1 is 79.6 to 94.2 percent. For Region 2, drainage area and streamflow variability index were statistically significant, and the range in the standard error of estimate is 48.2 to 72.1 percent. For Region 3, drainage area and streamflow-variability index also were statistically significant with a range in the standard error of estimate of 48.1 to 96.2 percent.\n\nLimitations on the use of estimating low-flow frequency statistics at ungaged locations are dependent on the method used. The first method outlined for use in Missouri, power curve equations, were developed to estimate the selected statistics for ungaged locations on 28 selected streams with multiple streamgages located on the same stream. A second method uses a drainage-area ratio to compute statistics at an ungaged location using data from a single streamgage on the same stream with 10 or more years of record. Ungaged locations on these streams may use the ratio of the drainage area at an ungaged location to the drainage area at a streamgage location to scale the selected statistic value from the streamgage location to the ungaged location. This method can be used if the drainage area of the ungaged location is within 40 to 150 percent of the streamgage drainage area. The third method is the use of the regional regression equations. The limits for the use of these equations are based on the ranges of the characteristics used as independent variables and that streams must be affected minimally by anthropogenic activities.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135090","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Southard, R.E., 2013, Computed statistics at streamgages, and methods for estimating low-flow frequency statistics and development of regional regression equations for estimating low-flow frequency statistics at ungaged locations in Missouri: U.S. Geological Survey Scientific Investigations Report 2013-5090, vii, 28 p., https://doi.org/10.3133/sir20135090.","productDescription":"vii, 28 p.","numberOfPages":"40","ipdsId":"IP-042887","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":273040,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135090.gif"},{"id":273039,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5090/downloads/"},{"id":273037,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5090/"},{"id":273038,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5090/sir13-5090.pdf"}],"country":"United States","state":"Missouri","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.77,36.0 ], [ -95.77,40.61 ], [ -89.1,40.61 ], [ -89.1,36.0 ], [ -95.77,36.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a866cfe4b082d85d5ed86b","contributors":{"authors":[{"text":"Southard, Rodney E. 0000-0001-8024-9698 southard@usgs.gov","orcid":"https://orcid.org/0000-0001-8024-9698","contributorId":3880,"corporation":false,"usgs":true,"family":"Southard","given":"Rodney","email":"southard@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":479171,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70046201,"text":"sir20135115 - 2013 - Recharge sources and residence times of groundwater as determined by geochemical tracers in the Mayfield Area, southwestern Idaho, 2011–12","interactions":[],"lastModifiedDate":"2013-05-30T15:09:50","indexId":"sir20135115","displayToPublicDate":"2013-05-30T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5115","title":"Recharge sources and residence times of groundwater as determined by geochemical tracers in the Mayfield Area, southwestern Idaho, 2011–12","docAbstract":"Parties proposing residential development in the area of Mayfield, Idaho are seeking a sustainable groundwater supply. During 2011–12, the U.S. Geological Survey, in cooperation with the Idaho Department of Water Resources, used geochemical tracers in the Mayfield area to evaluate sources of aquifer recharge and differences in groundwater residence time. Fourteen groundwater wells and one surface-water site were sampled for major ion chemistry, metals, stable isotopes, and age tracers; data collected from this study were used to evaluate the sources of groundwater recharge and groundwater residence times in the area. Major ion chemistry varied along a flow path between deeper wells, suggesting an upgradient source of dilute water, and a downgradient source of more concentrated water with the geochemical signature of the Idaho Batholith. Samples from shallow wells had elevated nutrient concentrations, a more positive oxygen-18 signature, and younger carbon-14 dates than deep wells, suggesting that recharge comes from young precipitation and surface-water infiltration. Samples from deep wells generally had higher concentrations of metals typical of geothermal waters, a more negative oxygen-18 signature, and older carbon-14 values than samples from shallow wells, suggesting that recharge comes from both infiltration of meteoric water and another source. The chemistry of groundwater sampled from deep wells is somewhat similar to the chemistry in geothermal waters, suggesting that geothermal water may be a source of recharge to this aquifer. Results of NETPATH mixing models suggest that geothermal water composes 1–23 percent of water in deep wells. Chlorofluorocarbons were detected in every sample, which indicates that all groundwater samples contain at least a component of young recharge, and that groundwater is derived from multiple recharge sources. Conclusions from this study can be used to further refine conceptual hydrological models of the area.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135115","collaboration":"Prepared in cooperation with the Idaho Department of Water Resources","usgsCitation":"Hopkins, C.B., 2013, Recharge sources and residence times of groundwater as determined by geochemical tracers in the Mayfield Area, southwestern Idaho, 2011–12: U.S. Geological Survey Scientific Investigations Report 2013-5115, vi, 38 p., https://doi.org/10.3133/sir20135115.","productDescription":"vi, 38 p.","numberOfPages":"46","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":273032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135115.jpg"},{"id":273031,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5115/pdf/sir20135115.pdf"},{"id":273030,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5115/"}],"country":"United States","state":"Idaho","otherGeospatial":"Mayfield Area","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.50,43.15 ], [ -116.50,43.30 ], [ -115,43.30 ], [ -115,43.15 ], [ -116.50,43.15 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a866d9e4b082d85d5ed87b","contributors":{"authors":[{"text":"Hopkins, Candice B. 0000-0003-3207-7267 chopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-3207-7267","contributorId":1379,"corporation":false,"usgs":true,"family":"Hopkins","given":"Candice","email":"chopkins@usgs.gov","middleInitial":"B.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":479147,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70045238,"text":"70045238 - 2013 - Geospace environment modeling 2008--2009 challenge: Dst index","interactions":[],"lastModifiedDate":"2013-05-30T10:59:24","indexId":"70045238","displayToPublicDate":"2013-05-30T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3456,"text":"Space Weather","active":true,"publicationSubtype":{"id":10}},"title":"Geospace environment modeling 2008--2009 challenge: Dst index","docAbstract":"This paper reports the metrics-based results of the Dst index part of the 2008–2009 GEM Metrics Challenge. The 2008–2009 GEM Metrics Challenge asked modelers to submit results for four geomagnetic storm events and five different types of observations that can be modeled by statistical, climatological or physics-based models of the magnetosphere-ionosphere system. We present the results of 30 model settings that were run at the Community Coordinated Modeling Center and at the institutions of various modelers for these events. To measure the performance of each of the models against the observations, we use comparisons of 1 hour averaged model data with the Dst index issued by the World Data Center for Geomagnetism, Kyoto, Japan, and direct comparison of 1 minute model data with the 1 minute Dst index calculated by the United States Geological Survey. The latter index can be used to calculate spectral variability of model outputs in comparison to the index. We find that model rankings vary widely by skill score used. None of the models consistently perform best for all events. We find that empirical models perform well in general. Magnetohydrodynamics-based models of the global magnetosphere with inner magnetosphere physics (ring current model) included and stand-alone ring current models with properly defined boundary conditions perform well and are able to match or surpass results from empirical models. Unlike in similar studies, the statistical models used in this study found their challenge in the weakest events rather than the strongest events.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Space Weather","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/swe.20036","usgsCitation":"Rastatter, L., Kuznetsova, M., Glocer, A., Welling, D., Meng, X., Raeder, J., Wittberger, M., Jordanova, V., Yu, Y., Zaharia, S., Weigel, R., Sazykin, S., Boynton, R., Wei, H., Eccles, V., Horton, W., Mays, M., and Gannon, J., 2013, Geospace environment modeling 2008--2009 challenge: Dst index: Space Weather, v. 11, no. 4, p. 187-205, https://doi.org/10.1002/swe.20036.","productDescription":"19 p.","startPage":"187","endPage":"205","ipdsId":"IP-044644","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":473805,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/swe.20036","text":"Publisher Index Page"},{"id":273011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273010,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/swe.20036"}],"volume":"11","issue":"4","noUsgsAuthors":false,"publicationDate":"2013-04-11","publicationStatus":"PW","scienceBaseUri":"51a866d7e4b082d85d5ed873","contributors":{"authors":[{"text":"Rastatter, L.","contributorId":55317,"corporation":false,"usgs":true,"family":"Rastatter","given":"L.","email":"","affiliations":[],"preferred":false,"id":477096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kuznetsova, M.M.","contributorId":54495,"corporation":false,"usgs":true,"family":"Kuznetsova","given":"M.M.","email":"","affiliations":[],"preferred":false,"id":477095,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glocer, A.","contributorId":96180,"corporation":false,"usgs":true,"family":"Glocer","given":"A.","email":"","affiliations":[],"preferred":false,"id":477100,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Welling, D.","contributorId":96990,"corporation":false,"usgs":true,"family":"Welling","given":"D.","email":"","affiliations":[],"preferred":false,"id":477101,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meng, X.","contributorId":56962,"corporation":false,"usgs":true,"family":"Meng","given":"X.","email":"","affiliations":[],"preferred":false,"id":477097,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Raeder, J.","contributorId":15919,"corporation":false,"usgs":true,"family":"Raeder","given":"J.","email":"","affiliations":[],"preferred":false,"id":477087,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wittberger, M.","contributorId":105204,"corporation":false,"usgs":true,"family":"Wittberger","given":"M.","email":"","affiliations":[],"preferred":false,"id":477102,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jordanova, V.K.","contributorId":63704,"corporation":false,"usgs":true,"family":"Jordanova","given":"V.K.","email":"","affiliations":[],"preferred":false,"id":477098,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yu, Y.","contributorId":31292,"corporation":false,"usgs":true,"family":"Yu","given":"Y.","email":"","affiliations":[],"preferred":false,"id":477090,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zaharia, S.","contributorId":31663,"corporation":false,"usgs":true,"family":"Zaharia","given":"S.","email":"","affiliations":[],"preferred":false,"id":477091,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Weigel, R.S.","contributorId":34809,"corporation":false,"usgs":true,"family":"Weigel","given":"R.S.","affiliations":[],"preferred":false,"id":477092,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sazykin, S.","contributorId":28512,"corporation":false,"usgs":true,"family":"Sazykin","given":"S.","email":"","affiliations":[],"preferred":false,"id":477089,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Boynton, R.","contributorId":13887,"corporation":false,"usgs":true,"family":"Boynton","given":"R.","email":"","affiliations":[],"preferred":false,"id":477086,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Wei, H.","contributorId":18255,"corporation":false,"usgs":true,"family":"Wei","given":"H.","email":"","affiliations":[],"preferred":false,"id":477088,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Eccles, V.","contributorId":70678,"corporation":false,"usgs":true,"family":"Eccles","given":"V.","email":"","affiliations":[],"preferred":false,"id":477099,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Horton, W.","contributorId":44448,"corporation":false,"usgs":true,"family":"Horton","given":"W.","email":"","affiliations":[],"preferred":false,"id":477093,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Mays, M.L.","contributorId":10705,"corporation":false,"usgs":true,"family":"Mays","given":"M.L.","email":"","affiliations":[],"preferred":false,"id":477085,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Gannon, J.","contributorId":52869,"corporation":false,"usgs":true,"family":"Gannon","given":"J.","email":"","affiliations":[],"preferred":false,"id":477094,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70044054,"text":"70044054 - 2013 - Genomic patterns of introgression in rainbow and westslope cutthroat trout illuminated by overlapping paired-end RAD sequencing","interactions":[],"lastModifiedDate":"2013-06-17T09:43:28","indexId":"70044054","displayToPublicDate":"2013-05-29T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2774,"text":"Molecular Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Genomic patterns of introgression in rainbow and westslope cutthroat trout illuminated by overlapping paired-end RAD sequencing","docAbstract":"Rapid and inexpensive methods for genomewide single nucleotide polymorphism (SNP) discovery and genotyping are urgently needed for population management and conservation. In hybridized populations, genomic techniques that can identify and genotype thousands of species-diagnostic markers would allow precise estimates of population- and individual-level admixture as well as identification of 'super invasive' alleles, which show elevated rates of introgression above the genomewide background (likely due to natural selection). Techniques like restriction-site-associated DNA (RAD) sequencing can discover and genotype large numbers of SNPs, but they have been limited by the length of continuous sequence data they produce with Illumina short-read sequencing. We present a novel approach, overlapping paired-end RAD sequencing, to generate RAD contigs of >300–400 bp. These contigs provide sufficient flanking sequence for design of high-throughput SNP genotyping arrays and strict filtering to identify duplicate paralogous loci. We applied this approach in five populations of native westslope cutthroat trout that previously showed varying (low) levels of admixture from introduced rainbow trout (RBT). We produced 77 141 RAD contigs and used these data to filter and genotype 3180 previously identified species-diagnostic SNP loci. Our population-level and individual-level estimates of admixture were generally consistent with previous microsatellite-based estimates from the same individuals. However, we observed slightly lower admixture estimates from genomewide markers, which might result from natural selection against certain genome regions, different genomic locations for microsatellites vs. RAD-derived SNPs and/or sampling error from the small number of microsatellite loci (n = 7). We also identified candidate adaptive super invasive alleles from RBT that had excessively high admixture proportions in hybridized cutthroat trout populations.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Molecular Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/mec.12239","usgsCitation":"Hohenlohe, P.A., Day, M.D., Amish, S.J., Miller, M.R., Kamps-Hughes, N., Boyer, M.C., Muhlfeld, C.C., Allendorf, F., Johnson, E.A., and Luikart, G., 2013, Genomic patterns of introgression in rainbow and westslope cutthroat trout illuminated by overlapping paired-end RAD sequencing: Molecular Ecology, v. 22, no. 11, p. 3002-3013, https://doi.org/10.1111/mec.12239.","productDescription":"12 p.","startPage":"3002","endPage":"3013","ipdsId":"IP-039490","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":473808,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3664261","text":"External Repository"},{"id":272941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272940,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/mec.12239"}],"volume":"22","issue":"11","noUsgsAuthors":false,"publicationDate":"2013-02-21","publicationStatus":"PW","scienceBaseUri":"51a71565e4b09db86f875c77","contributors":{"authors":[{"text":"Hohenlohe, Paul A.","contributorId":46399,"corporation":false,"usgs":false,"family":"Hohenlohe","given":"Paul","email":"","middleInitial":"A.","affiliations":[{"id":12708,"text":"Institute for Bioinformatics and Evolutionary Studies, Department of Biological Sciences, University of Idaho, Moscow, ID 83844","active":true,"usgs":false}],"preferred":false,"id":474718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day, Mitch D.","contributorId":19867,"corporation":false,"usgs":true,"family":"Day","given":"Mitch","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":474716,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amish, Stephen J.","contributorId":104799,"corporation":false,"usgs":false,"family":"Amish","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":474723,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Michael R.","contributorId":45796,"corporation":false,"usgs":false,"family":"Miller","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":12709,"text":"Department of Animal Science, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA","active":true,"usgs":false}],"preferred":false,"id":474717,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kamps-Hughes, Nick","contributorId":9945,"corporation":false,"usgs":true,"family":"Kamps-Hughes","given":"Nick","email":"","affiliations":[],"preferred":false,"id":474715,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boyer, Matthew C.","contributorId":48468,"corporation":false,"usgs":false,"family":"Boyer","given":"Matthew","email":"","middleInitial":"C.","affiliations":[{"id":5133,"text":"Montana Fish Wildlife and Parks, Kalispell, Montana 59901","active":true,"usgs":false}],"preferred":false,"id":474719,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":474714,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Allendorf, Fred W.","contributorId":83432,"corporation":false,"usgs":false,"family":"Allendorf","given":"Fred W.","affiliations":[{"id":5091,"text":"Flathead Lake Biological Station, Fish and Wildlife Genomics Group, Division of Biological Sciences, University of Montana, Polson, MT 59860, USA","active":true,"usgs":false}],"preferred":false,"id":474721,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Johnson, Eric A.","contributorId":80158,"corporation":false,"usgs":false,"family":"Johnson","given":"Eric","email":"","middleInitial":"A.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":474720,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Luikart, Gordon","contributorId":97409,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","affiliations":[{"id":6580,"text":"University of Montana, Flathead Lake Biological Station, Polson, Montana 59860, USA","active":true,"usgs":false}],"preferred":false,"id":474722,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70043236,"text":"70043236 - 2013 - Geochronologic evidence for a possible MIS-11 emergent barrier/beach-ridge in southeastern Georgia, USA","interactions":[],"lastModifiedDate":"2013-05-29T10:29:19","indexId":"70043236","displayToPublicDate":"2013-05-29T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Geochronologic evidence for a possible MIS-11 emergent barrier/beach-ridge in southeastern Georgia, USA","docAbstract":"Predominantly clastic, off-lapping, transgressive, near-shore marine sediment packages that are morphologically expressed as subparallel NE-trending barriers, beach ridges, and associated back-barrier areas, characterize the near-surface stratigraphic section between the Savannah and the Ogeechee Rivers in Effingham County, southeastern Georgia. Each barrier/back-barrier (shoreline) complex is lower than and cut into a higher/older complex. Each barrier or shoreline complex overlies Miocene strata. No direct age data are available for these deposits. Previous researchers have disagreed on their age and provenance. Using luminescence and meteoric beryllium-10 (10Be) inventory analyses, we estimated a minimum age for the largest, westernmost, morphologically identifiable, and topographically-highest, barrier/beach-ridge (the Wicomico shoreline barrier) and constrained the age of a suite of younger barrier/beach-ridges that lie adjacent and seaward of the Wicomico shoreline barrier.\n\nAt the study site, the near-shore marine/estuarine deposits underlying the Wicomico shoreline barrier are overlain by eolian sand and an intervening zone-of-mixing. Optically stimulated luminescence (OSL) data indicate ages of ≤43 ka for the eolian sand and 116 ka for the zone-of-mixing. Meteoric 10Be and pedostratigraphic data indicate minimum residence times of 33.4 ka for the eolian sand, 80.6 ka for the zone-of-mixing, and 247 ka for the paleosol. The combined OSL and 10Be age data indicate that, at this locality, the barrier/beach ridge has a minimum age of about 360 ka. This age for the Wicomico shoreline-barrier deposit is the first for any Pleistocene near-shore marine/estuarine deposit in southeast Georgia that is conclusively older than 80 ka. The 360-ka minimum age is in agreement with other geochronologic data for near-coastline deposits in Georgia and South Carolina. The geomorphic position of this barrier/beach-ridge is similar to deposits in South Carolina considered to be ~450 ka to >1 Ma. The age and geomorphic data for Georgia and South Carolina possibly suggest the presence of MIS-11 (~420−360 ka) shoreline deposits between 15 m and 28 m above present sea level in the Southeastern Atlantic Coastal Plain.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Quaternary Science Reviews","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2012.10.041","usgsCitation":"Markewich, H.W., Pavich, M., Schultz, A., Mahan, S., Aleman-Gonzalez, W., and Bierman, P., 2013, Geochronologic evidence for a possible MIS-11 emergent barrier/beach-ridge in southeastern Georgia, USA: Quaternary Science Reviews, v. 60, p. 49-75, https://doi.org/10.1016/j.quascirev.2012.10.041.","productDescription":"27 p.","startPage":"49","endPage":"75","ipdsId":"IP-038366","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":272943,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272942,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.quascirev.2012.10.041"}],"country":"United States","state":"Georgia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -85.6052,30.3556 ], [ -85.6052,35.0 ], [ -80.8408,35.0 ], [ -80.8408,30.3556 ], [ -85.6052,30.3556 ] ] ] } } ] }","volume":"60","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a71566e4b09db86f875c7b","contributors":{"authors":[{"text":"Markewich, H. W.","contributorId":31426,"corporation":false,"usgs":true,"family":"Markewich","given":"H.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":473208,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pavich, M.J.","contributorId":70788,"corporation":false,"usgs":true,"family":"Pavich","given":"M.J.","email":"","affiliations":[],"preferred":false,"id":473211,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schultz, A. P.","contributorId":106139,"corporation":false,"usgs":true,"family":"Schultz","given":"A. P.","affiliations":[],"preferred":false,"id":473213,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mahan, S. A. 0000-0001-5214-7774","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":94333,"corporation":false,"usgs":true,"family":"Mahan","given":"S. A.","affiliations":[],"preferred":false,"id":473212,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aleman-Gonzalez, W. B.","contributorId":36447,"corporation":false,"usgs":true,"family":"Aleman-Gonzalez","given":"W. B.","affiliations":[],"preferred":false,"id":473209,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bierman, P.R.","contributorId":49145,"corporation":false,"usgs":true,"family":"Bierman","given":"P.R.","email":"","affiliations":[],"preferred":false,"id":473210,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70046156,"text":"sir20135061 - 2013 - Transport of nitrogen in a treated-wastewater plume to coastal discharge areas, Ashumet Valley, Cape Cod, Massachusetts","interactions":[],"lastModifiedDate":"2013-05-29T11:59:56","indexId":"sir20135061","displayToPublicDate":"2013-05-29T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5061","title":"Transport of nitrogen in a treated-wastewater plume to coastal discharge areas, Ashumet Valley, Cape Cod, Massachusetts","docAbstract":"Land disposal of treated wastewater from a treatment plant on the Massachusetts Military Reservation in operation from 1936 to 1995 has created a plume of contaminated groundwater that is migrating toward coastal discharge areas in the town of Falmouth, Massachusetts. To develop a better understanding of the potential impact of the treated-wastewater plume on coastal discharge areas, the U.S. Geological Survey, in cooperation with the Air Force Center for Engineering and the Environment, evaluated the fate of nitrogen (N) in the plume. Groundwater samples from two large sampling events in 1994 and 2007 were used to map the size and location of the plume, calculate the masses of nitrate-N and ammonium-N, evaluate changes in mass since cessation of disposal in 1995, and create a gridded dataset suitable for use in nitrogen-transport simulations. In 2007, the treated-wastewater plume was about 1,200 meters (m) wide, 30 m thick, and 7,700 m long and contained approximately 87,000 kilograms (kg) nitrate-N and 31,600 kg total ammonium-N. An analysis of previous studies and data from 1994 and 2007 sampling events suggests that most of biologically reactive nitrogen in the plume in 2007 will be transported to coastal discharge areas as either nitrate or ammonium with relatively little transformation to an environmentally nonreactive end product such as nitrogen gas.\n\nNitrogen-transport simulations were conducted with a previously calibrated regional three-dimensional MODFLOW groundwater flow model. Mass-loaded particle tracking was used to simulate the advective transport of nitrogen to discharge areas (or receptors) along the coast. In the simulations, nonreactive transport (no mass loss in the aquifer) was assumed, providing an upper-end estimate of nitrogen loads to receptors. Simulations indicate that approximately 95 percent of the nitrate-N and 99 percent of the ammonium-N in the wastewater plume will eventually discharge to the Coonamessett River, Backus River, Green Pond, and Bournes River. Approximately 76 percent of the total nitrate-N mass in the plume will discharge to these receptors within 100 years of 2007; 90 and 94 percent will discharge within 200 and 500 years, respectively. Nitrate loads will peak within about 50 years at all of the major receptors. The highest peak loads will occur at the Coonamessett River (450 kg per year (kg/yr) nitrate-N) and the Backus River (350 kg/yr nitrate-N). Because of adsorption, travel times are longer for ammonium than for nitrate; approximately 5 percent of the total ammonium-N mass in the plume will discharge to receptors within 100 years; 46 and 81 percent will discharge within 200 and 500 years, respectively. The simulations indicate that the Coonamessett River will receive the largest cumulative nitrogen mass and the highest rate of discharge (load). Ongoing discharge to Ashumet Pond is relatively minor because most of the wastewater plume mass has already migrated downgradient from the pond.\n\nTo evaluate the contribution of the nitrogen loads from the treated-wastewater plume to total nitrogen loads to the discharge areas, the simulated treated-wastewater plume loads were compared to steady-state nonpoint-source loads calculated by the Massachusetts Estuaries Project for 2005. Simulation results indicate that the total nitrogen loads from the treated-wastewater plume are much lower than corresponding steady-state nonpoint-source loads from the watersheds; peak plume loads are equal to 11 percent or less of the nonpoint-source loads.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135061","collaboration":"Toxic Substances Hydrology Program Prepared in cooperation with the Air Force Center for Engineering and the Environment","usgsCitation":"Barbaro, J.R., Walter, D.A., and LeBlanc, D.R., 2013, Transport of nitrogen in a treated-wastewater plume to coastal discharge areas, Ashumet Valley, Cape Cod, Massachusetts: U.S. Geological Survey Scientific Investigations Report 2013-5061, v, 37 p., https://doi.org/10.3133/sir20135061.","productDescription":"v, 37 p.","numberOfPages":"48","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":272958,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135061.gif"},{"id":272956,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5061/"},{"id":272957,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5061/pdf/sir2013-5061_barbaro_508.pdf"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -70.649578,41.542017 ], [ -70.649578,42.075706 ], [ -69.943322,42.075706 ], [ -69.943322,41.542017 ], [ -70.649578,41.542017 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a71567e4b09db86f875c8b","contributors":{"authors":[{"text":"Barbaro, Jeffrey R. 0000-0002-6107-2142 jrbarbar@usgs.gov","orcid":"https://orcid.org/0000-0002-6107-2142","contributorId":1626,"corporation":false,"usgs":true,"family":"Barbaro","given":"Jeffrey","email":"jrbarbar@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":479066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walter, Donald A. 0000-0003-0879-4477 dawalter@usgs.gov","orcid":"https://orcid.org/0000-0003-0879-4477","contributorId":1101,"corporation":false,"usgs":true,"family":"Walter","given":"Donald","email":"dawalter@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":479065,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LeBlanc, Denis R. 0000-0002-4646-2628 dleblanc@usgs.gov","orcid":"https://orcid.org/0000-0002-4646-2628","contributorId":1696,"corporation":false,"usgs":true,"family":"LeBlanc","given":"Denis","email":"dleblanc@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":479067,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046186,"text":"sir20135092 - 2013 - Analysis of 1997–2008 groundwater level changes in the upper Deschutes Basin, Central Oregon","interactions":[],"lastModifiedDate":"2013-05-29T21:25:07","indexId":"sir20135092","displayToPublicDate":"2013-05-29T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5092","title":"Analysis of 1997–2008 groundwater level changes in the upper Deschutes Basin, Central Oregon","docAbstract":"Groundwater-level monitoring in the upper Deschutes Basin of central Oregon from 1997 to 2008 shows water-level declines in some places that are larger than might be expected from climate variations alone, raising questions regarding the influence of groundwater pumping, canal lining (which decreases recharge), and other human influences. Between the mid-1990s and mid-2000s, water levels in the central part of the basin near Redmond steadily declined as much as 14 feet. Water levels in the Cascade Range, in contrast, rose more than 20 feet from the mid-1990s to about 2000, and then declined into the mid-2000s, with little or no net change.\n\nAn existing U.S. Geological Survey regional groundwater-flow model was used to gain insights into groundwater-level changes from 1997 to 2008, and to determine the relative influence of climate, groundwater pumping, and irrigation canal lining on observed water-level trends. To utilize the model, input datasets had to be extended to include post-1997 changes in groundwater pumping, changes in recharge from precipitation, irrigation canal leakage, and deep percolation of applied irrigation water (also known as on-farm loss). Mean annual groundwater recharge from precipitation during the 1999–2008 period was 25 percent less than during the 1979–88 period because of drying climate conditions. This decrease in groundwater recharge is consistent with measured decreases in streamflow and discharge to springs. For example, the mean annual discharge of Fall River, which is a spring-fed stream, decreased 12 percent between the 1979–88 and 1999–2008 periods. Between the mid-1990s and late 2000s, groundwater pumping for public-supply and irrigation uses increased from about 32,500 to 52,000 acre-feet per year, partially because of population growth. Between 1997 and 2008, the rate of recharge from leaking irrigation canals decreased by about 58,000 acre-feet per year as a result of lining and piping of canals. Decreases in recharge from on-farm losses over the past decade were relatively small, approaching an estimated 1,000 acre-feet per year by the late 2000s. All these changes in the hydrologic budget contributed to declines in groundwater levels.\n\nGroundwater flow model simulations indicate that climate variations have the largest influence on groundwater levels throughout the upper Deschutes Basin, and that impacts from pumping and canal lining also contribute but are largely restricted to the central part of the basin that extends north from near Benham Falls to Lower Bridge, and east from Sisters to the community of Powell Butte. Outside of this central area, the water-level response from changes in pumping and irrigation canal leakage cannot be discerned from the larger response to climate-driven changes in recharge. Within this central area, where measured water-level declines have generally ranged from about 5 to 14 feet since the mid-1990s, climate variations are still the dominant factor influencing groundwater levels, accounting for approximately 60–70 percent of the measured declines. Post-1994 increases in groundwater pumping account for about 20–30 percent of the measured declines in the central part of the basin, depending on location, and decreases in recharge due to canal lining account for about 10 percent of the measured declines. Decreases in recharge from on-farm losses were simulated, but the effects were negligible compared to climate influences, groundwater pumping, and the effects of canal lining and piping.\n\nObservation well data and model simulation results indicate that water levels in the Cascade Range rose and declined tens of feet in response to wet and dry climate cycles over the past two decades. Water levels in the central part of the basin, in contrast, steadily declined during the same period, with the rate of decline lessening during wet periods. This difference is because the water-level response from recharge is damped as water moves (diffuses) from the principal recharge area in the Cascade Range to discharge points along the main stems of the Deschutes, Crooked, and Metolius Rivers in the central part of the basin. Water levels in the central part of the basin respond more to multi-decadal climate trends than shorter term changes.\n\nGroundwater-flow simulations show that the effects from increased pumping and decreased irrigation canal leakage extend south into the Bend area. However, the only wells presently monitored in the Bend area are heavily influenced by the Deschutes River, which dampens any response of water levels to external stresses such as groundwater pumping, changes in canal leakage, or climate variations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135092","collaboration":"Prepared in cooperation with the Oregon Water Resources Department","usgsCitation":"Gannett, M.W., and Lite, K.E., 2013, Analysis of 1997–2008 groundwater level changes in the upper Deschutes Basin, Central Oregon: U.S. Geological Survey Scientific Investigations Report 2013-5092, vi, 34 p., https://doi.org/10.3133/sir20135092.","productDescription":"vi, 34 p.","numberOfPages":"44","additionalOnlineFiles":"N","temporalStart":"1997-01-01","temporalEnd":"2008-12-31","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":272990,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135092.jpg"},{"id":272988,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5092/"},{"id":272989,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5092/pdf/sir20135092.pdf"}],"country":"United States","state":"Oregon","otherGeospatial":"Deschutes Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.61,42.0 ], [ -124.61,46.29 ], [ -116.46,46.29 ], [ -116.46,42.0 ], [ -124.61,42.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a71551e4b09db86f875c5f","contributors":{"authors":[{"text":"Gannett, Marshall W. 0000-0003-2498-2427 mgannett@usgs.gov","orcid":"https://orcid.org/0000-0003-2498-2427","contributorId":2942,"corporation":false,"usgs":true,"family":"Gannett","given":"Marshall","email":"mgannett@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":479119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lite, Kenneth E. Jr.","contributorId":37373,"corporation":false,"usgs":true,"family":"Lite","given":"Kenneth","suffix":"Jr.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":479120,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046147,"text":"ds748 - 2013 - USGS Arctic Ocean carbon cruise 2011: field activity H-01-11-AR to collect carbon data in the Arctic Ocean, August - September 2011","interactions":[],"lastModifiedDate":"2013-05-29T11:10:55","indexId":"ds748","displayToPublicDate":"2013-05-29T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"748","title":"USGS Arctic Ocean carbon cruise 2011: field activity H-01-11-AR to collect carbon data in the Arctic Ocean, August - September 2011","docAbstract":"Carbon dioxide (CO2) in the atmosphere is absorbed at the surface of the ocean by reacting with seawater to form a weak, naturally occurring acid called carbonic acid. As atmospheric carbon dioxide increases, the concentration of carbonic acid in seawater also increases, causing a decrease in ocean pH and carbonate mineral saturation states, a process known as ocean acidification. The oceans have absorbed approximately 525 billion tons of carbon dioxide from the atmosphere, or about one-quarter to one-third of the anthropogenic carbon emissions released since the beginning of the Industrial Revolution (Sabine and others, 2004). Global surveys of ocean chemistry have revealed that seawater pH has decreased by about 0.1 units (from a pH of 8.2 to 8.1) since the 1700s due to absorption of carbon dioxide (Caldeira and Wickett, 2003; Orr and others, 2005; Raven and others, 2005). Modeling studies, based on Intergovernmental Panel on Climate Change (IPCC) CO2 emission scenarios, predict that atmospheric carbon dioxide levels could reach more than 500 parts per million (ppm) by the middle of this century and 800 ppm by the year 2100, causing an additional decrease in surface water pH of 0.3 pH units. Ocean acidification is a global threat and is already having profound and deleterious effects on the geology, biology, chemistry, and socioeconomic resources of coastal and marine habitats (Raven and others, 2005; Ruttiman, 2006). The polar and sub-polar seas have been identified as the bellwethers for global ocean acidification.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds748","usgsCitation":"Robbins, L.L., Yates, K.K., Knorr, P.O., Wynn, J., Lisle, J., Buczkowski, B.J., Moore, B., Mayer, L., Armstrong, A., Byrne, R., and Liu, X., 2013, USGS Arctic Ocean carbon cruise 2011: field activity H-01-11-AR to collect carbon data in the Arctic Ocean, August - September 2011: U.S. Geological Survey Data Series 748, HTML Document, https://doi.org/10.3133/ds748.","productDescription":"HTML Document","additionalOnlineFiles":"Y","temporalStart":"2011-08-01","temporalEnd":"2011-09-30","ipdsId":"IP-036976","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":272949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds748.gif"},{"id":272947,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/748/"},{"id":272948,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/748/pubs748/index.html"}],"otherGeospatial":"Arctic Ocean","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,70.0 ], [ -180.0,90.0 ], [ 180.0,90.0 ], [ 180.0,70.0 ], [ -180.0,70.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a71568e4b09db86f875c93","contributors":{"authors":[{"text":"Robbins, Lisa L. 0000-0003-3681-1094 lrobbins@usgs.gov","orcid":"https://orcid.org/0000-0003-3681-1094","contributorId":422,"corporation":false,"usgs":true,"family":"Robbins","given":"Lisa","email":"lrobbins@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":479043,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yates, Kimberly K. 0000-0001-8764-0358 kyates@usgs.gov","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":420,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","email":"kyates@usgs.gov","middleInitial":"K.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":479042,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knorr, Paul O. pknorr@usgs.gov","contributorId":3691,"corporation":false,"usgs":true,"family":"Knorr","given":"Paul","email":"pknorr@usgs.gov","middleInitial":"O.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":479045,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wynn, Jonathan","contributorId":9943,"corporation":false,"usgs":false,"family":"Wynn","given":"Jonathan","affiliations":[],"preferred":false,"id":479046,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lisle, John","contributorId":27344,"corporation":false,"usgs":true,"family":"Lisle","given":"John","affiliations":[],"preferred":false,"id":479047,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Buczkowski, Brian J. bbuczkowski@usgs.gov","contributorId":3524,"corporation":false,"usgs":true,"family":"Buczkowski","given":"Brian","email":"bbuczkowski@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":479044,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moore, Barbara","contributorId":68634,"corporation":false,"usgs":true,"family":"Moore","given":"Barbara","email":"","affiliations":[],"preferred":false,"id":479048,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mayer, Larry","contributorId":77936,"corporation":false,"usgs":true,"family":"Mayer","given":"Larry","affiliations":[],"preferred":false,"id":479049,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Armstrong, Andrew","contributorId":107175,"corporation":false,"usgs":true,"family":"Armstrong","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":479052,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Byrne, Robert H.","contributorId":83260,"corporation":false,"usgs":true,"family":"Byrne","given":"Robert H.","affiliations":[],"preferred":false,"id":479050,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Liu, Xuewu","contributorId":87676,"corporation":false,"usgs":true,"family":"Liu","given":"Xuewu","email":"","affiliations":[],"preferred":false,"id":479051,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70046181,"text":"70046181 - 2013 - Winter climate change and coastal wetland foundation species: Salt marshes vs. mangrove forests in the southeastern United States","interactions":[],"lastModifiedDate":"2019-06-06T08:03:24","indexId":"70046181","displayToPublicDate":"2013-05-29T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Winter climate change and coastal wetland foundation species: Salt marshes vs. mangrove forests in the southeastern United States","docAbstract":"We live in an era of unprecedented ecological change in which ecologists and natural resource managers are increasingly challenged to anticipate and prepare for the ecological effects of future global change. In this study, we investigated the potential effect of winter climate change upon salt marsh and mangrove forest foundation species in the southeastern United States. Our research addresses the following three questions: (1) What is the relationship between winter climate and the presence and abundance of mangrove forests relative to salt marshes; (2) How vulnerable are salt marshes to winter climate change-induced mangrove forest range expansion; and (3) What is the potential future distribution and relative abundance of mangrove forests under alternative winter climate change scenarios? We developed simple winter climate-based models to predict mangrove forest distribution and relative abundance using observed winter temperature data (1970–2000) and mangrove forest and salt marsh habitat data. Our results identify winter climate thresholds for salt marsh–mangrove forest interactions and highlight coastal areas in the southeastern United States (e.g., Texas, Louisiana, and parts of Florida) where relatively small changes in the intensity and frequency of extreme winter events could cause relatively dramatic landscape-scale ecosystem structural and functional change in the form of poleward mangrove forest migration and salt marsh displacement. The ecological implications of these marsh-to-mangrove forest conversions are poorly understood, but would likely include changes for associated fish and wildlife populations and for the supply of some ecosystem goods and services.","language":"English","publisher":"Wiley","doi":"10.1111/gcb.12126","usgsCitation":"Osland, M.J., Day, R.H., Doyle, T.W., and Enwright, N., 2013, Winter climate change and coastal wetland foundation species: Salt marshes vs. mangrove forests in the southeastern United States: Global Change Biology, v. 19, no. 5, p. 1482-1494, https://doi.org/10.1111/gcb.12126.","productDescription":"13 p.","startPage":"1482","endPage":"1494","ipdsId":"IP-041147","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":272996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272983,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/gcb.12126"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,18.9 ], [ 172.5,71.4 ], [ -67.0,71.4 ], [ -67.0,18.9 ], [ 172.5,18.9 ] ] ] } } ] }","volume":"19","issue":"5","noUsgsAuthors":false,"publicationDate":"2013-02-11","publicationStatus":"PW","scienceBaseUri":"51a71568e4b09db86f875c9b","contributors":{"authors":[{"text":"Osland, Michael J. 0000-0001-9902-8692 mosland@usgs.gov","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":3080,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","email":"mosland@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":479105,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day, Richard H. 0000-0002-5959-7054 dayr@usgs.gov","orcid":"https://orcid.org/0000-0002-5959-7054","contributorId":2427,"corporation":false,"usgs":true,"family":"Day","given":"Richard","email":"dayr@usgs.gov","middleInitial":"H.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":479104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doyle, Thomas W. 0000-0001-5754-0671 doylet@usgs.gov","orcid":"https://orcid.org/0000-0001-5754-0671","contributorId":703,"corporation":false,"usgs":true,"family":"Doyle","given":"Thomas","email":"doylet@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":479103,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Enwright, Nicholas 0000-0002-7887-3261","orcid":"https://orcid.org/0000-0002-7887-3261","contributorId":32435,"corporation":false,"usgs":true,"family":"Enwright","given":"Nicholas","affiliations":[],"preferred":false,"id":479106,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70046148,"text":"ds741 - 2013 - USGS Arctic Ocean carbon cruise 2010: field activity H-03-10-AR to collect carbon data in the Arctic Ocean, August - September 2010","interactions":[],"lastModifiedDate":"2013-05-29T11:13:42","indexId":"ds741","displayToPublicDate":"2013-05-29T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"741","title":"USGS Arctic Ocean carbon cruise 2010: field activity H-03-10-AR to collect carbon data in the Arctic Ocean, August - September 2010","docAbstract":"Carbon dioxide (CO2) in the atmosphere is absorbed at the surface of the ocean by reacting with seawater to form carbonic acid, a weak, naturally occurring acid. As atmospheric carbon dioxide increases, the concentration of carbonic acid in seawater also increases, causing a decrease in ocean pH and carbonate mineral saturation states, a process known as ocean acidification. The oceans have absorbed approximately 525 billion tons of carbon dioxide from the atmosphere, or about one-quarter to one-third of the anthropogenic carbon emissions released since the beginning of the Industrial Revolution (Sabine and others, 2004). Global surveys of ocean chemistry have revealed that seawater pH has decreased by about 0.1 units (from a pH of 8.2 to 8.1) since the 1700s due to absorption of carbon dioxide (Caldeira and Wickett, 2003; Orr and others, 2005; Raven and others, 2005). Modeling studies, based on Intergovernmental Panel on Climate Change (IPCC) CO2 emission scenarios, predict that atmospheric carbon dioxide levels could reach more than 500 parts per million (ppm) by the middle of this century and 800 ppm by the year 2100, causing an additional decrease in surface water pH of 0.3 pH units. Ocean acidification is a global threat and is already having profound and deleterious effects on the geology, biology, chemistry, and socioeconomic resources of coastal and marine habitats (Raven and others, 2005; Ruttiman, 2006). The polar and sub-polar seas have been identified as the bellwethers for global ocean acidification.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds741","usgsCitation":"Robbins, L.L., Yates, K.K., Gove, M.D., Knorr, P.O., Wynn, J., Byrne, R., and Liu, X., 2013, USGS Arctic Ocean carbon cruise 2010: field activity H-03-10-AR to collect carbon data in the Arctic Ocean, August - September 2010: U.S. Geological Survey Data Series 741, HTML Document, https://doi.org/10.3133/ds741.","productDescription":"HTML Document","additionalOnlineFiles":"Y","temporalStart":"2010-08-01","temporalEnd":"2010-09-30","ipdsId":"IP-036696","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":272946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds741.gif"},{"id":272945,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/741/"},{"id":272944,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/741/pubs741/index.html"}],"otherGeospatial":"Arctic Ocean","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,70.0 ], [ -180.0,90.0 ], [ 180.0,90.0 ], [ 180.0,70.0 ], [ -180.0,70.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a71568e4b09db86f875c8f","contributors":{"authors":[{"text":"Robbins, Lisa L. 0000-0003-3681-1094 lrobbins@usgs.gov","orcid":"https://orcid.org/0000-0003-3681-1094","contributorId":422,"corporation":false,"usgs":true,"family":"Robbins","given":"Lisa","email":"lrobbins@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":479054,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yates, Kimberly K. 0000-0001-8764-0358 kyates@usgs.gov","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":420,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","email":"kyates@usgs.gov","middleInitial":"K.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":479053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gove, Matthew D.","contributorId":21851,"corporation":false,"usgs":true,"family":"Gove","given":"Matthew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":479057,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knorr, Paul O. pknorr@usgs.gov","contributorId":3691,"corporation":false,"usgs":true,"family":"Knorr","given":"Paul","email":"pknorr@usgs.gov","middleInitial":"O.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":479055,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wynn, Jonathan","contributorId":9943,"corporation":false,"usgs":false,"family":"Wynn","given":"Jonathan","affiliations":[],"preferred":false,"id":479056,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Byrne, Robert H.","contributorId":83260,"corporation":false,"usgs":true,"family":"Byrne","given":"Robert H.","affiliations":[],"preferred":false,"id":479058,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liu, Xuewu","contributorId":87676,"corporation":false,"usgs":true,"family":"Liu","given":"Xuewu","email":"","affiliations":[],"preferred":false,"id":479059,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70046153,"text":"sir20135087 - 2013 - Hydrographic surveys of the Missouri and Yellowstone Rivers at selected bridges and through Bismarck, North Dakota, during the 2011 flood","interactions":[],"lastModifiedDate":"2013-05-29T11:29:18","indexId":"sir20135087","displayToPublicDate":"2013-05-29T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5087","title":"Hydrographic surveys of the Missouri and Yellowstone Rivers at selected bridges and through Bismarck, North Dakota, during the 2011 flood","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the North Dakota Department of Transportation and the North Dakota State Water Commission, completed hydrographic surveys at six Missouri River bridges and one Yellowstone River bridge during the 2011 flood of the Missouri River system. Bridges surveyed are located near the cities of Cartwright, Buford, Williston, Washburn, and Bismarck, N. Dak. The river in the vicinity of the bridges and the channel through the city of Bismarck, N. Dak., were surveyed. The hydrographic surveys were conducted using a high-resolution multibeam echosounder (MBES), the RESON SeaBatTM 7125, during June 6–9 and June 28–July 9, 2011. The surveyed area at each bridge site extended 820 feet upstream from the bridge to 820 feet downstream from the bridge. The surveyed reach through Bismarck consisted of 18 miles of the main channel wherever depth was sufficient. Results from these emergency surveys aided the North Dakota Department of Transportation in evaluating the structural integrity of the bridges during high-flow conditions. In addition, the sustained high flows made feasible the surveying of a large section of the normally shallow channel with the MBES.\n\nIn general, results from sequential bridge surveys showed that as discharge increased between the first and second surveys at a given site, there was a general trend of channel scour. Locally, complex responses of scour in some areas and deposition in other areas of the channel were identified. Similarly, scour around bridge piers also showed complex responses to the increase in flow between the two surveys. Results for the survey area of the river channel through Bismarck show that, in general, scour occurred around river structures or where the river has tight bends and channel narrowing. The data collected during the surveys are provided electronically in two different file formats: comma delimited text and CARIS Spatial ArchiveTM (CSARTM) format.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135087","collaboration":"Prepared in cooperation with the North Dakota Department of Transportation and the North Dakota State Water Commission","usgsCitation":"Densmore, B.K., Strauch, K.R., and Dietsch, B.J., 2013, Hydrographic surveys of the Missouri and Yellowstone Rivers at selected bridges and through Bismarck, North Dakota, during the 2011 flood: U.S. Geological Survey Scientific Investigations Report 2013-5087, vi, 59 p., https://doi.org/10.3133/sir20135087.","productDescription":"vi, 59 p.","numberOfPages":"70","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-06-06","temporalEnd":"2011-07-09","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":272953,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135087.gif"},{"id":272950,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5087/"},{"id":272952,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2013/5087/Data/"},{"id":272951,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5087/sir2013-5087.pdf"}],"country":"United States","state":"North Dakota","city":"Bismarck","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -100.845596,46.751104 ], [ -100.845596,46.867048 ], [ -100.688513,46.867048 ], [ -100.688513,46.751104 ], [ -100.845596,46.751104 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a71566e4b09db86f875c83","contributors":{"authors":[{"text":"Densmore, Brenda K. 0000-0003-2429-638X bdensmore@usgs.gov","orcid":"https://orcid.org/0000-0003-2429-638X","contributorId":4896,"corporation":false,"usgs":true,"family":"Densmore","given":"Brenda","email":"bdensmore@usgs.gov","middleInitial":"K.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":479062,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Strauch, Kellan R. 0000-0002-7218-2099 kstrauch@usgs.gov","orcid":"https://orcid.org/0000-0002-7218-2099","contributorId":1006,"corporation":false,"usgs":true,"family":"Strauch","given":"Kellan","email":"kstrauch@usgs.gov","middleInitial":"R.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":479060,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dietsch, Benjamin J. 0000-0003-1090-409X bdietsch@usgs.gov","orcid":"https://orcid.org/0000-0003-1090-409X","contributorId":1346,"corporation":false,"usgs":true,"family":"Dietsch","given":"Benjamin","email":"bdietsch@usgs.gov","middleInitial":"J.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":84311,"text":"Central Plains Water Science Center","active":true,"usgs":true}],"preferred":true,"id":479061,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046172,"text":"sir20135063 - 2013 - Reserve growth of oil and gas fields—Investigations and applications","interactions":[],"lastModifiedDate":"2013-05-30T07:42:42","indexId":"sir20135063","displayToPublicDate":"2013-05-29T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5063","title":"Reserve growth of oil and gas fields—Investigations and applications","docAbstract":"The reserve growth of fields has been a topic for ongoing discussion for over half a century and will continue to be studied well into the future. This is due to the expected size of the volumetric contribution of reserve growth to the future supply of oil and natural gas. Understanding past methods of estimating future volumes based on the data assembly methods that have been used can lead to a better understanding of their applicability. The statistical nature of past methods and the (1) possible high level of dependency on a limited number of fields, (2) assumption of an age-based correlation with effective reserve growth, and (3) assumption of long-lived and more common than not reserve growth, may be improved by employing a more geologically based approach.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135063","usgsCitation":"Cook, T.A., 2013, Reserve growth of oil and gas fields—Investigations and applications: U.S. Geological Survey Scientific Investigations Report 2013-5063, iv, 30 p., https://doi.org/10.3133/sir20135063.","productDescription":"iv, 30 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":272971,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135063.gif"},{"id":272969,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5063/"},{"id":272970,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5063/SIR13-5063_508.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a71567e4b09db86f875c87","contributors":{"authors":[{"text":"Cook, Troy A.","contributorId":52519,"corporation":false,"usgs":true,"family":"Cook","given":"Troy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":479085,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70046132,"text":"fs20133024 - 2013 - A conceptual hydrogeologic model for the hydrogeologic framework, geochemistry, and groundwater-flow system of the Edwards-Trinity and related aquifers in the Pecos County region, Texas","interactions":[],"lastModifiedDate":"2026-06-10T20:30:43.189759","indexId":"fs20133024","displayToPublicDate":"2013-05-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3024","title":"A conceptual hydrogeologic model for the hydrogeologic framework, geochemistry, and groundwater-flow system of the Edwards-Trinity and related aquifers in the Pecos County region, Texas","docAbstract":"The Edwards-Trinity aquifer is a vital groundwater resource for agricultural, industrial, and municipal uses in the Trans-Pecos region of west Texas. A conceptual model of the hydrogeologic framework, geochemistry, and groundwater-flow system in the 4,700 square-mile study area was developed by the U.S. Geological Survey (USGS) in cooperation with the Middle Pecos Groundwater Conservation District, Pecos County, City of Fort Stockton, Brewster County, and Pecos County Water Control and Improvement District No. 1. The model was developed to gain a better understanding of the groundwater system and to establish a scientific foundation for resource-management decisions. Data and information were collected or obtained from various sources to develop the model. Lithologic information obtained from well reports and geophysical data were used to describe the hydrostratigraphy and structural features of the groundwater system, and aquifer-test data were used to estimate aquifer hydraulic properties. Groundwater-quality data were used to evaluate groundwater-flow paths, water and rock interaction, aquifer interaction, and the mixing of water from different sources. Groundwater-level data also were used to evaluate aquifer interaction as well as to develop a potentiometric-surface map, delineate regional groundwater divides, and describe regional groundwater-flow paths.
\nSeveral previous studies have been done to compile or collect physical and chemical data, describe the hydrogeologic processes, and develop conceptual and numerical groundwater-flow models of the Edwards-Trinity aquifer in the Trans-Pecos region. Documented methods were used to compile and collect groundwater, surface-water, geochemical, geophysical, and geologic information that subsequently were used to develop this conceptual model.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133024","collaboration":"Prepared in cooperation with the Middle Pecos Groundwater Conservation District, Pecos County, City of Fort Stockton, Brewster County, and Pecos County Water Control and Improvement District No. 1","usgsCitation":"Thomas, J.V., Stanton, G.P., Bumgarner, J.R., Pearson, D., Teeple, A., Houston, N.A., Payne, J., and Musgrove, M., 2013, A conceptual hydrogeologic model for the hydrogeologic framework, geochemistry, and groundwater-flow system of the Edwards-Trinity and related aquifers in the Pecos County region, Texas: U.S. Geological Survey Fact Sheet 2013-3024, 6 p., https://doi.org/10.3133/fs20133024.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":505340,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98527.htm","linkFileType":{"id":5,"text":"html"}},{"id":272901,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3024/"},{"id":272902,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3024/pdf/fs2013-3024.pdf"},{"id":272903,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133024.gif"}],"projection":"Albers Equal Area","datum":"North American Datum of 1983","country":"United States","state":"Texas","county":"Pecos County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104,30.08 ], [ -104,31.30 ], [ -102,31.30 ], [ -102,30.08 ], [ -104,30.08 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a5c3d2e4b0605bc571ef52","contributors":{"authors":[{"text":"Thomas, Jonathan V. 0000-0003-0903-9713 jvthomas@usgs.gov","orcid":"https://orcid.org/0000-0003-0903-9713","contributorId":2194,"corporation":false,"usgs":true,"family":"Thomas","given":"Jonathan","email":"jvthomas@usgs.gov","middleInitial":"V.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478993,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanton, Gregory P. 0000-0001-8622-0933 gstanton@usgs.gov","orcid":"https://orcid.org/0000-0001-8622-0933","contributorId":1583,"corporation":false,"usgs":true,"family":"Stanton","given":"Gregory","email":"gstanton@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":478991,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bumgarner, Johnathan R. jbumgarner@usgs.gov","contributorId":5378,"corporation":false,"usgs":true,"family":"Bumgarner","given":"Johnathan","email":"jbumgarner@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":478994,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearson, Daniel K.","contributorId":52014,"corporation":false,"usgs":true,"family":"Pearson","given":"Daniel K.","affiliations":[],"preferred":false,"id":478996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Teeple, Andrew 0000-0003-1781-8354 apteeple@usgs.gov","orcid":"https://orcid.org/0000-0003-1781-8354","contributorId":1399,"corporation":false,"usgs":true,"family":"Teeple","given":"Andrew ","email":"apteeple@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":478990,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Houston, Natalie A. 0000-0002-6071-4545 nhouston@usgs.gov","orcid":"https://orcid.org/0000-0002-6071-4545","contributorId":1682,"corporation":false,"usgs":true,"family":"Houston","given":"Natalie","email":"nhouston@usgs.gov","middleInitial":"A.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478992,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Payne, Jason 0000-0003-4294-7924 jdpayne@usgs.gov","orcid":"https://orcid.org/0000-0003-4294-7924","contributorId":1062,"corporation":false,"usgs":true,"family":"Payne","given":"Jason ","email":"jdpayne@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":478989,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Musgrove, MaryLynn","contributorId":34878,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","affiliations":[],"preferred":false,"id":478995,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70046136,"text":"sim3252 - 2013 - Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado","interactions":[],"lastModifiedDate":"2013-05-28T14:30:22","indexId":"sim3252","displayToPublicDate":"2013-05-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3252","title":"Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado","docAbstract":"Multispectral satellite data acquired by the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) and Landsat 7 Enhanced Thematic Mapper Plus (TM) sensors are being used to populate an online Geographic Information System (GIS) of the spatial occurrence of mineral groups and green vegetation across the western conterminous United States and Alaska. These geospatial data are supporting U.S. Geological Survey national-scale mineral deposit database development and other mineral resource and geoenvironmental research as a means of characterizing mineral exposures related to mined and unmined hydrothermally altered rocks and mine waste.\n\nThis report introduces a new methodology for the automated analysis of Landsat TM data that has been applied to more than 180 scenes covering the western United States. A map of mineral groups and green vegetation produced using this new methodology that covers the western San Juan Mountains, Colorado, and the Four Corners Region is presented. The map is provided as a layered GeoPDF and in GIS-ready digital format. TM data analysis results from other well-studied and mineralogically characterized areas with strong hydrothermal alteration and (or) supergene weathering of near-surface sulfide minerals are also shown and compared with results derived from ASTER data analysis.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3252","usgsCitation":"Rockwell, B.W., 2013, Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado: U.S. Geological Survey Scientific Investigations Map 3252, iv, 25 p.; Map: 1 Sheet: 36 x 40 inches; Downloads Directory, https://doi.org/10.3133/sim3252.","productDescription":"iv, 25 p.; Map: 1 Sheet: 36 x 40 inches; Downloads Directory","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":272912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3252.gif"},{"id":272908,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3252/"},{"id":272909,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3252/downloads/pdfs/SIM3252_pamphlet.pdf"},{"id":272910,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3252/downloads/pdfs/SIM3252_map.pdf"},{"id":272911,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3252/downloads/"}],"country":"United States","state":"Colorado","otherGeospatial":"San Juan Mountains","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0,37.0 ], [ -109.0,41.0 ], [ -102.0,41.0 ], [ -102.0,37.0 ], [ -109.0,37.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a5c3e2e4b0605bc571ef5a","contributors":{"authors":[{"text":"Rockwell, Barnaby W. 0000-0002-9549-0617 barnabyr@usgs.gov","orcid":"https://orcid.org/0000-0002-9549-0617","contributorId":2195,"corporation":false,"usgs":true,"family":"Rockwell","given":"Barnaby","email":"barnabyr@usgs.gov","middleInitial":"W.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":479002,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70046111,"text":"sir20125001 - 2013 - The use of process models to inform and improve statistical models of nitrate occurrence, Great Miami River Basin, southwestern Ohio","interactions":[],"lastModifiedDate":"2014-02-27T14:56:37","indexId":"sir20125001","displayToPublicDate":"2013-05-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5001","title":"The use of process models to inform and improve statistical models of nitrate occurrence, Great Miami River Basin, southwestern Ohio","docAbstract":"Statistical models of nitrate occurrence in the glacial aquifer system of the northern United States, developed by the U.S. Geological Survey, use observed relations between nitrate concentrations and sets of explanatory variables—representing well-construction, environmental, and source characteristics— to predict the probability that nitrate, as nitrogen, will exceed a threshold concentration. However, the models do not explicitly account for the processes that control the transport of nitrogen from surface sources to a pumped well and use area-weighted mean spatial variables computed from within a circular buffer around the well as a simplified source-area conceptualization. The use of models that explicitly represent physical-transport processes can inform and, potentially, improve these statistical models. Specifically, groundwater-flow models simulate advective transport—predominant in many surficial aquifers— and can contribute to the refinement of the statistical models by (1) providing for improved, physically based representations of a source area to a well, and (2) allowing for more detailed estimates of environmental variables.
\nA source area to a well, known as a contributing recharge area, represents the area at the water table that contributes recharge to a pumped well; a well pumped at a volumetric rate equal to the amount of recharge through a circular buffer will result in a contributing recharge area that is the same size as the buffer but has a shape that is a function of the hydrologic setting. These volume-equivalent contributing recharge areas will approximate circular buffers in areas of relatively flat hydraulic gradients, such as near groundwater divides, but in areas with steep hydraulic gradients will be elongated in the upgradient direction and agree less with the corresponding circular buffers.
\nThe degree to which process-model-estimated contributing recharge areas, which simulate advective transport and therefore account for local hydrologic settings, would inform and improve the development of statistical models can be implicitly estimated by evaluating the differences between explanatory variables estimated from the contributing recharge areas and the circular buffers used to develop existing statistical models. The larger the difference in estimated variables, the more likely that statistical models would be changed, and presumably improved, if explanatory variables estimated from contributing recharge areas were used in model development. Comparing model predictions from the two sets of estimated variables would further quantify—albeit implicitly—how an improved, physically based estimate of explanatory variables would be reflected in model predictions. Differences between the two sets of estimated explanatory variables and resultant model predictions vary spatially; greater differences are associated with areas of steep hydraulic gradients. A direct comparison, however, would require the development of a separate set of statistical models using explanatory variables from contributing recharge areas.
\nArea-weighted means of three environmental variables—silt content, alfisol content, and depth to water from the U.S. Department of Agriculture State Soil Geographic (STATSGO) data—and one nitrogen-source variable (fertilizer-application rate from county data mapped to Enhanced National Land Cover Data 1992 (NLCDe 92) agricultural land use) can vary substantially between circular buffers and volume-equivalent contributing recharge areas and among contributing recharge areas for different sets of well variables. The differences in estimated explanatory variables are a function of the same factors affecting the contributing recharge areas as well as the spatial resolution and local distribution of the underlying spatial data. As a result, differences in estimated variables between circular buffers and contributing recharge areas are complex and site specific as evidenced by differences in estimated variables for circular buffers and contributing recharge areas of existing public-supply and network wells in the Great Miami River Basin. Large differences in areaweighted mean environmental variables are observed at the basin scale, determined by using the network of uniformly spaced hypothetical wells; the differences have a spatial pattern that generally is similar to spatial patterns in the underlying STATSGO data. Generally, the largest differences were observed for area-weighted nitrogen-application rate from county and national land-use data; the basin-scale differences ranged from -1,600 (indicating a larger value from within the volume-equivalent contributing recharge area) to 1,900 kilograms per year (kg/yr); the range in the underlying spatial data was from 0 to 2,200 kg/yr. Silt content, alfisol content, and nitrogen-application rate are defined by the underlying spatial data and are external to the groundwater system; however, depth to water is an environmental variable that can be estimated in more detail and, presumably, in a more physically based manner using a groundwater-flow model than using the spatial data. Model-calculated depths to water within circular buffers in the Great Miami River Basin differed substantially from values derived from the spatial data and had a much larger range.
\nDifferences in estimates of area-weighted spatial variables result in corresponding differences in predictions of nitrate occurrence in the aquifer. In addition to the factors affecting contributing recharge areas and estimated explanatory variables, differences in predictions also are a function of the specific set of explanatory variables used and the fitted slope coefficients in a given model. For models that predicted the probability of exceeding 1 and 4 milligrams per liter as nitrogen (mg/L as N), predicted probabilities using variables estimated from circular buffers and contributing recharge areas generally were correlated but differed significantly at the local and basin scale. The scale and distribution of prediction differences can be explained by the underlying differences in the estimated variables and the relative weight of the variables in the statistical models. Differences in predictions of exceeding 1 mg/L as N, which only includes environmental variables, generally correlated with the underlying differences in STATSGO data, whereas differences in exceeding 4 mg/L as N were more spatially extensive because that model included environmental and nitrogen-source variables. Using depths to water from within circular buffers derived from the spatial data and depths to water within the circular buffers calculated from the groundwater-flow model, restricted to the same range, resulted in large differences in predicted probabilities. The differences in estimated explanatory variables between contributing recharge areas and circular buffers indicate incorporation of physically based contributing recharge area likely would result in a different set of explanatory variables and an improved set of statistical models.
\nThe use of a groundwater-flow model to improve representations of source areas or to provide more-detailed estimates of specific explanatory variables includes a number of limitations and technical considerations. An assumption in these analyses is that (1) there is a state of mass balance between recharge and pumping, and (2) transport to a pumped well is under a steady state flow field. Comparison of volumeequivalent contributing recharge areas under steady-state and transient transport conditions at a location in the southeastern part of the basin shows the steady-state contributing recharge area is a reasonable approximation of the transient contributing recharge area after between 10 and 20 years of pumping. The first assumption is a more important consideration for this analysis. A gradient effect refers to a condition where simulated pumping from a well is less than recharge through the corresponding contributing recharge area. This generally takes place in areas with steep hydraulic gradients, such as near discharge locations, and can be mitigated using a finer model discretization. A boundary effect refers to a condition where recharge through the contributing recharge area is less than pumping. This indicates other sources of water to the simulated well and could reflect a real hydrologic process. In the Great Miami River Basin, large gradient and boundary effects—defined as the balance between pumping and recharge being less than half—occurred in 5 and 14 percent of the basin, respectively. The agreement between circular buffers and volume-equivalent contributing recharge areas, differences in estimated variables, and the effect on statisticalmodel predictions between the population of wells with a balance between pumping and recharge within 10 percent and the population of all wells were similar. This indicated process-model limitations did not affect the overall findings in the Great Miami River Basin; however, this would be model specific, and prudent use of a process model needs to entail a limitations analysis and, if necessary, alterations to the model.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125001","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Walter, D.A., and Starn, J.J., 2013, The use of process models to inform and improve statistical models of nitrate occurrence, Great Miami River Basin, southwestern Ohio: U.S. Geological Survey Scientific Investigations Report 2012-5001, x, 75 p., https://doi.org/10.3133/sir20125001.","productDescription":"x, 75 p.","numberOfPages":"90","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":377,"text":"Massachusetts-Rhode Island Water Science Center","active":false,"usgs":true}],"links":[{"id":272823,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125001.jpg"},{"id":272821,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5001/"},{"id":272822,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5001/pdf/sir2012-5001_report_508.pdf"}],"country":"United States","state":"Ohio","otherGeospatial":"Great Miami River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.82,38.4 ], [ -84.82,42.0 ], [ -80.52,42.0 ], [ -80.52,38.4 ], [ -84.82,38.4 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a4805fe4b064a995b7a0d0","contributors":{"authors":[{"text":"Walter, Donald A. 0000-0003-0879-4477 dawalter@usgs.gov","orcid":"https://orcid.org/0000-0003-0879-4477","contributorId":1101,"corporation":false,"usgs":true,"family":"Walter","given":"Donald","email":"dawalter@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478948,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Starn, J. Jeffrey","contributorId":101617,"corporation":false,"usgs":true,"family":"Starn","given":"J.","email":"","middleInitial":"Jeffrey","affiliations":[],"preferred":false,"id":478949,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043209,"text":"70043209 - 2013 - Gaussian process regression for sensor networks under localization uncertainty","interactions":[],"lastModifiedDate":"2013-05-28T10:14:22","indexId":"70043209","displayToPublicDate":"2013-05-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1947,"text":"IEEE Transactions on Signal Processing","active":true,"publicationSubtype":{"id":10}},"title":"Gaussian process regression for sensor networks under localization uncertainty","docAbstract":"In this paper, we formulate Gaussian process regression with observations under the localization uncertainty due to the resource-constrained sensor networks. In our formulation, effects of observations, measurement noise, localization uncertainty, and prior distributions are all correctly incorporated in the posterior predictive statistics. The analytically intractable posterior predictive statistics are proposed to be approximated by two techniques, viz., Monte Carlo sampling and Laplace's method. Such approximation techniques have been carefully tailored to our problems and their approximation error and complexity are analyzed. Simulation study demonstrates that the proposed approaches perform much better than approaches without considering the localization uncertainty properly. Finally, we have applied the proposed approaches on the experimentally collected real data from a dye concentration field over a section of a river and a temperature field of an outdoor swimming pool to provide proof of concept tests and evaluate the proposed schemes in real situations. In both simulation and experimental results, the proposed methods outperform the quick-and-dirty solutions often used in practice.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"IEEE Transactions on Signal Processing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"IEEE","doi":"10.1109/TSP.2012.2223695","usgsCitation":"Jadaliha, M., Xu, Y., Choi, J., Johnson, N., and Li, W., 2013, Gaussian process regression for sensor networks under localization uncertainty: IEEE Transactions on Signal Processing, v. 61, no. 2, p. 223-237, https://doi.org/10.1109/TSP.2012.2223695.","productDescription":"15 p.","startPage":"223","endPage":"237","ipdsId":"IP-041065","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":272859,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272857,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1109/TSP.2012.2223695"}],"volume":"61","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a5c3e4e4b0605bc571ef66","contributors":{"authors":[{"text":"Jadaliha, M.","contributorId":45210,"corporation":false,"usgs":true,"family":"Jadaliha","given":"M.","email":"","affiliations":[],"preferred":false,"id":473173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xu, Yunfei","contributorId":17513,"corporation":false,"usgs":true,"family":"Xu","given":"Yunfei","email":"","affiliations":[],"preferred":false,"id":473172,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choi, Jongeun","contributorId":84229,"corporation":false,"usgs":true,"family":"Choi","given":"Jongeun","affiliations":[],"preferred":false,"id":473176,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, N.S.","contributorId":73436,"corporation":false,"usgs":true,"family":"Johnson","given":"N.S.","email":"","affiliations":[],"preferred":false,"id":473175,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Li, Weiming","contributorId":65440,"corporation":false,"usgs":true,"family":"Li","given":"Weiming","affiliations":[],"preferred":false,"id":473174,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70046129,"text":"ofr20131081 - 2013 - Final report for sea-level rise response modeling for San Francisco Bay estuary tidal marshes","interactions":[],"lastModifiedDate":"2017-10-30T12:19:43","indexId":"ofr20131081","displayToPublicDate":"2013-05-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1081","title":"Final report for sea-level rise response modeling for San Francisco Bay estuary tidal marshes","docAbstract":"The International Panel on Climate Change has identified coastal ecosystems as areas that will be disproportionally affected by climate change. Current sea-level rise projections range widely with 0.57 to 1.9 meters increase in mea sea level by 2100. The expected accelerated rate of sea-level rise through the 21st century will put many coastal ecosystems at risk, especially those in topographically low-gradient areas.\n\nWe assessed marsh accretion and plant community state changes through 2100 at 12 tidal salt marshes around San Francisco Bay estuary with a sea-level rise response model. Detailed ground elevation, vegetation, and water level data were collected at all sites between 2008 and 2011 and used as model inputs. Sediment cores (taken by Callaway and others, 2012) at four sites around San Francisco Bay estuary were used to estimate accretion rates. A modification of the Callaway and others (1996) model, the Wetland Accretion Rate Model for Ecosystem Resilience (WARMER), was utilized to run sea-level rise response models for all sites. With a mean sea level rise of 1.24 m by 2100, WARMER projected that the vast majority, 95.8 percent (1,942 hectares), of marsh area in our study will lose marsh plant communities by 2100 and to transition to a relative elevation range consistent with mudflat habitat. Three marshes were projected to maintain marsh vegetation to 2100, but they only composed 4.2 percent (85 hectares) of the total marsh area surveyed.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131081","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service","usgsCitation":"Takekawa, J.Y., Thorne, K.M., Buffington, K., Spragens, K., Swanson, K., Drexler, J., Schoellhamer, D., Overton, C.T., and Casazza, M.L., 2013, Final report for sea-level rise response modeling for San Francisco Bay estuary tidal marshes: U.S. Geological Survey Open-File Report 2013-1081, x, 161 p., https://doi.org/10.3133/ofr20131081.","productDescription":"x, 161 p.","numberOfPages":"171","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":272882,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131081.jpg"},{"id":272881,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1081/pdf/ofr20131081.pdf"},{"id":272880,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1081/"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.498478,37.447658 ], [ -122.498478,37.964872 ], [ -122.041878,37.964872 ], [ -122.041878,37.447658 ], [ -122.498478,37.447658 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a5c3e3e4b0605bc571ef5e","contributors":{"authors":[{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":478976,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thorne, Karen M. 0000-0002-1381-0657 kthorne@usgs.gov","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":4191,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen","email":"kthorne@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":478979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buffington, Kevin J. 0000-0001-9741-1241 kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":478980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spragens, Kyle A.","contributorId":98452,"corporation":false,"usgs":true,"family":"Spragens","given":"Kyle A.","affiliations":[],"preferred":false,"id":478983,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swanson, Kathleen M.","contributorId":11289,"corporation":false,"usgs":true,"family":"Swanson","given":"Kathleen M.","affiliations":[],"preferred":false,"id":478982,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drexler, Judith Z. 0000-0002-0127-3866","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":8941,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith Z.","affiliations":[],"preferred":false,"id":478981,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478975,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":478978,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":478977,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70046138,"text":"ds759 - 2013 - Alaska Geochemical Database, Version 2.0 (AGDB2)–Including “best value” data compilations for rock, sediment, soil, mineral, and concentrate sample mediaI","interactions":[],"lastModifiedDate":"2026-05-18T18:16:36.703255","indexId":"ds759","displayToPublicDate":"2013-05-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"759","title":"Alaska Geochemical Database, Version 2.0 (AGDB2)–Including “best value” data compilations for rock, sediment, soil, mineral, and concentrate sample mediaI","docAbstract":"The Alaska Geochemical Database Version 2.0 (AGDB2) contains new geochemical data compilations in which each geologic material sample has one “best value” determination for each analyzed species, greatly improving speed and efficiency of use. Like the Alaska Geochemical Database (AGDB, http://pubs.usgs.gov/ds/637/) before it, the AGDB2 was created and designed to compile and integrate geochemical data from Alaska in order to facilitate geologic mapping, petrologic studies, mineral resource assessments, definition of geochemical baseline values and statistics, environmental impact assessments, and studies in medical geology. This relational database, created from the Alaska Geochemical Database (AGDB) that was released in 2011, serves as a data archive in support of present and future Alaskan geologic and geochemical projects, and contains data tables in several different formats describing historical and new quantitative and qualitative geochemical analyses. The analytical results were determined by 85 laboratory and field analytical methods on 264,095 rock, sediment, soil, mineral and heavy-mineral concentrate samples. Most samples were collected by U.S. Geological Survey personnel and analyzed in U.S. Geological Survey laboratories or, under contracts, in commercial analytical laboratories. These data represent analyses of samples collected as part of various U.S. Geological Survey programs and projects from 1962 through 2009. In addition, mineralogical data from 18,138 nonmagnetic heavy-mineral concentrate samples are included in this database. The AGDB2 includes historical geochemical data originally archived in the U.S. Geological Survey Rock Analysis Storage System (RASS) database, used from the mid-1960s through the late 1980s and the U.S. Geological Survey PLUTO database used from the mid-1970s through the mid-1990s. All of these data are currently maintained in the National Geochemical Database (NGDB). Retrievals from the NGDB were used to generate most of the AGDB data set. These data were checked for accuracy regarding sample location, sample media type, and analytical methods used. This arduous process of reviewing, verifying and, where necessary, editing all U.S. Geological Survey geochemical data resulted in a significantly improved Alaska geochemical dataset. USGS data that were not previously in the NGDB because the data predate the earliest U.S. Geological Survey geochemical databases, or were once excluded for programmatic reasons, are included here in the AGDB2 and will be added to the NGDB. The AGDB2 data provided here are the most accurate and complete to date, and should be useful for a wide variety of geochemical studies. The AGDB2 data provided in the linked database may be updated or changed periodically.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds759","usgsCitation":"Granitto, M., Schmidt, J.M., Shew, N.B., Gamble, B.M., and Labay, K., 2013, Alaska Geochemical Database, Version 2.0 (AGDB2)--including “best value” data compilations for rock, sediment, soil, mineral, and concentrate sample media: U.S. Geological Survey Data Series 759, Report: vi, 20 p.; Metadata Files; Data Files; Alaska Geochemical Database (AGDB), https://doi.org/10.3133/ds759.","productDescription":"Report: vi, 20 p.; Metadata Files; Data Files; Alaska Geochemical Database (AGDB)","numberOfPages":"29","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":504499,"rank":7,"type":{"id":36,"text":"NGMDB Index 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Minerals","active":true,"usgs":true}],"preferred":true,"id":479006,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shew, Nora B. 0000-0003-0025-7220 nshew@usgs.gov","orcid":"https://orcid.org/0000-0003-0025-7220","contributorId":3382,"corporation":false,"usgs":true,"family":"Shew","given":"Nora","email":"nshew@usgs.gov","middleInitial":"B.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":479005,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gamble, Bruce M. bgamble@usgs.gov","contributorId":560,"corporation":false,"usgs":true,"family":"Gamble","given":"Bruce","email":"bgamble@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":479003,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Labay, Keith A. 0000-0002-6763-3190 klabay@usgs.gov","orcid":"https://orcid.org/0000-0002-6763-3190","contributorId":2097,"corporation":false,"usgs":true,"family":"Labay","given":"Keith A.","email":"klabay@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":false,"id":479007,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70046109,"text":"ofr20131093 - 2013 - Solid-phase data from cores at the proposed Dewey Burdock uranium in-situ recovery mine, near Edgemont, South Dakota","interactions":[],"lastModifiedDate":"2013-05-27T20:31:16","indexId":"ofr20131093","displayToPublicDate":"2013-05-27T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1093","title":"Solid-phase data from cores at the proposed Dewey Burdock uranium in-situ recovery mine, near Edgemont, South Dakota","docAbstract":"This report releases solid-phase data from cores at the proposed Dewey Burdock uranium in-situ recovery site near Edgemont, South Dakota. These cores were collected by Powertech Uranium Corporation, and material not used for their analyses were given to the U.S. Geological Survey for additional sampling and analyses. These additional analyses included total carbon and sulfur, whole rock acid digestion for major and trace elements, 234U/238U activity ratios, X-ray diffraction, thin sections, scanning electron microscopy analyses, and cathodoluminescence. This report provides the methods and data results from these analyses along with a short summary of observations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131093","collaboration":"In cooperation with the Environmental Protection Agency","usgsCitation":"Johnson, R.H., Diehl, S.F., and Benzel, W., 2013, Solid-phase data from cores at the proposed Dewey Burdock uranium in-situ recovery mine, near Edgemont, South Dakota: U.S. Geological Survey Open-File Report 2013-1093, iii, 13 p.; 2 Tables; 5 Appendixes, https://doi.org/10.3133/ofr20131093.","productDescription":"iii, 13 p.; 2 Tables; 5 Appendixes","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-042233","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":272820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131093.gif"},{"id":272813,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1093/Table%201%20all%20solid%20data%20for%20pubs.xls"},{"id":272814,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1093/Table%202%20XRD%20data%20for%20pubs.xlsx"},{"id":272811,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1093/"},{"id":272812,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1093/OF13-1093.pdf"},{"id":272815,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1093/Appendix%20A%20carbon-sulfur/EPA-carbon-sulfur_final.xlsx"},{"id":272816,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1093/Appendix%20C%20Transmitted%20light"},{"id":272817,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1093/Appendix%20D%20SEM%20images"},{"id":272818,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1093/Appendix%20E%20SEM%20Elemental%20Maps"},{"id":272819,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1093/Appendix%20B%20uranium%20isotopes/KettererUrpt%2020Feb2012_final.pdf"}],"country":"United States","state":"South Dakota","city":"Edgemont","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -103.843393,43.289569 ], [ -103.843393,43.30621 ], [ -103.81689,43.30621 ], [ -103.81689,43.289569 ], [ -103.843393,43.289569 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a47259e4b064a995b7a0c3","contributors":{"authors":[{"text":"Johnson, Raymond H. rhjohnso@usgs.gov","contributorId":707,"corporation":false,"usgs":true,"family":"Johnson","given":"Raymond","email":"rhjohnso@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":478935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diehl, Sharon F. diehl@usgs.gov","contributorId":1089,"corporation":false,"usgs":true,"family":"Diehl","given":"Sharon","email":"diehl@usgs.gov","middleInitial":"F.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":478936,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Benzel, William 0000-0002-4085-1876 wbenzel@usgs.gov","orcid":"https://orcid.org/0000-0002-4085-1876","contributorId":3594,"corporation":false,"usgs":true,"family":"Benzel","given":"William","email":"wbenzel@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":478937,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045974,"text":"70045974 - 2013 - Tracking animals in freshwater with electronic tags: past, present and future","interactions":[],"lastModifiedDate":"2013-05-30T08:16:29","indexId":"70045974","displayToPublicDate":"2013-05-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":773,"text":"Animal Biotelemetry","active":true,"publicationSubtype":{"id":10}},"title":"Tracking animals in freshwater with electronic tags: past, present and future","docAbstract":"Considerable technical developments over the past half century have enabled widespread application of electronic tags to the study of animals in the wild, including in freshwater environments. We review the constraints associated with freshwater telemetry and biologging and the technical developments relevant to their use. Technical constraints for tracking animals are often influenced by the characteristics of the animals being studied and the environment they inhabit. Collectively, they influence which and how technologies can be used and their relative effectiveness. Although radio telemetry has historically been the most commonly used technology in freshwater, passive integrated transponder (PIT) technology, acoustic telemetry and biologgers are becoming more popular. Most telemetry studies have focused on fish, although an increasing number have focused on other taxa, such as turtles, crustaceans and molluscs. Key technical developments for freshwater systems include: miniaturization of tags for tracking small-size life stages and species, fixed stations and coded tags for tracking large samples of animals over long distances and large temporal scales, inexpensive PIT systems that enable mass tagging to yield population- and community-level relevant sample sizes, incorporation of sensors into electronic tags, validation of tag attachment procedures with a focus on maintaining animal welfare, incorporation of different techniques (for example, genetics, stable isotopes) and peripheral technologies (for example, geographic information systems, hydroacoustics), development of novel analytical techniques, and extensive international collaboration. Innovations are still needed in tag miniaturization, data analysis and visualization, and in tracking animals over larger spatial scales (for example, pelagic areas of lakes) and in challenging environments (for example, large dynamic floodplain systems, under ice). There seems to be a particular need for adapting various global positioning system and satellite tagging approaches to freshwater. Electronic tagging provides a mechanism to collect detailed information from imperilled animals and species that have no direct economic value. Current and future advances will continue to improve our knowledge of the natural history of aquatic animals and ecological processes in freshwater ecosystems while facilitating evidence-based resource management and conservation.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Animal Biotelemetry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1186/2050-3385-1-5","usgsCitation":"Cooke, S., Midwood, J.D., Thiem, J.D., Klimley, P., Lucas, M.C., Thorstad, E.B., Eiler, J., Holbrook, C., and Ebner, B.C., 2013, Tracking animals in freshwater with electronic tags: past, present and future: Animal Biotelemetry, v. 1, no. 5, 19 p., https://doi.org/10.1186/2050-3385-1-5.","productDescription":"19 p.","ipdsId":"IP-044813","costCenters":[{"id":332,"text":"Hammond Bay Biological Station","active":false,"usgs":true}],"links":[{"id":473812,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/2050-3385-1-5","text":"Publisher Index Page"},{"id":272997,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1186/2050-3385-1-5"},{"id":272998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"1","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a874ece4b082d85d5ed90e","contributors":{"authors":[{"text":"Cooke, Steven J.","contributorId":56132,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":36574,"text":"Carleton University, Ottawa, Ontario","active":true,"usgs":false}],"preferred":false,"id":478625,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Midwood, Jonathan D.","contributorId":74659,"corporation":false,"usgs":true,"family":"Midwood","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":478627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thiem, Jason D.","contributorId":75421,"corporation":false,"usgs":true,"family":"Thiem","given":"Jason","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":478628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klimley, Peter","contributorId":62507,"corporation":false,"usgs":true,"family":"Klimley","given":"Peter","email":"","affiliations":[],"preferred":false,"id":478626,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lucas, Martyn C.","contributorId":18725,"corporation":false,"usgs":true,"family":"Lucas","given":"Martyn","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":478623,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thorstad, Eva B.","contributorId":95367,"corporation":false,"usgs":true,"family":"Thorstad","given":"Eva","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":478630,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eiler, John","contributorId":34025,"corporation":false,"usgs":true,"family":"Eiler","given":"John","affiliations":[],"preferred":false,"id":478624,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Holbrook, Chris","contributorId":94194,"corporation":false,"usgs":true,"family":"Holbrook","given":"Chris","email":"","affiliations":[],"preferred":false,"id":478629,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ebner, Brendan C.","contributorId":9556,"corporation":false,"usgs":true,"family":"Ebner","given":"Brendan","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":478622,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70046104,"text":"ofr20131108 - 2013 - Postwildfire debris-flow hazard assessment of the area burned by the 2012 Little Bear Fire, south-central New Mexico","interactions":[],"lastModifiedDate":"2013-05-24T13:59:25","indexId":"ofr20131108","displayToPublicDate":"2013-05-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1108","title":"Postwildfire debris-flow hazard assessment of the area burned by the 2012 Little Bear Fire, south-central New Mexico","docAbstract":"A preliminary hazard assessment was developed of the debris-flow potential from 56 drainage basins burned by the Little Bear Fire in south-central New Mexico in June 2012. The Little Bear Fire burned approximately 179 square kilometers (km2) (44,330 acres), including about 143 km2 (35,300 acres) of National Forest System lands of the Lincoln National Forest. Within the Lincoln National Forest, about 72 km2 (17,664 acres) of the White Mountain Wilderness were burned. The burn area also included about 34 km2 (8,500 acres) of private lands. Burn severity was high or moderate on 53 percent of the burn area. The area burned is at risk of substantial postwildfire erosion, such as that caused by debris flows and flash floods.\n\nA postwildfire debris-flow hazard assessment of the area burned by the Little Bear Fire was performed by the U.S. Geological Survey in cooperation with the U.S. Department of Agriculture Forest Service, Lincoln National Forest. A set of two empirical hazard-assessment models developed by using data from recently burned drainage basins throughout the intermountain Western United States was used to estimate the probability of debris-flow occurrence and volume of debris flows along the burn area drainage network and for selected drainage basins within the burn area. The models incorporate measures of areal burn extent and severity, topography, soils, and storm rainfall intensity to estimate the probability and volume of debris flows following the fire. Relative hazard rankings of postwildfire debris flows were produced by summing the estimated probability and volume ranking to illustrate those areas with the highest potential occurrence of debris flows with the largest volumes.\n\nThe probability that a drainage basin could produce debris flows and the volume of a possible debris flow at the basin outlet were estimated for three design storms: (1) a 2-year-recurrence, 30-minute-duration rainfall of 27 millimeters (mm) (a 50 percent chance of occurrence in any given year); (2) a 10-year-recurrence, 30-minute-duration rainfall of 42 mm (a 10 percent chance of occurrence in any given year); and (3) a 25-year-recurrence, 30-minute-duration rainfall of 51 mm (a 4 percent chance of occurrence in any given year). Thirty-nine percent of the 56 drainage basins modeled have a high (greater than 80 percent) probability of debris flows in response to the 2-year design storm; 80 percent of the modeled drainage basins have a high probability of debris flows in response to the 25-year design storm. For debris-flow volume, 7 percent of the modeled drainage basins have an estimated debris-flow volume greater than 100,000 cubic meters (m3) in response to the 2-year design storm; 9 percent of the drainage basins are included in the greater than 100,000 m3 category for both the 10-year and the 25-year design storms. Drainage basins in the greater than 100,000 m3 volume category also received the highest combined hazard ranking.\n\nThe maps presented herein may be used to prioritize areas where emergency erosion mitigation or other protective measures may be needed prior to rainstorms within these drainage basins, their outlets, or areas downstream from these drainage basins within the 2- to 3-year period of vulnerability. This work is preliminary and is subject to revision. The assessment herein is provided on the condition that neither the U.S. Geological Survey nor the U.S. Government may be held liable for any damages resulting from the authorized or unauthorized use of the assessment.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131108","collaboration":"Prepared in cooperation with U.S. Department of Agriculture Forest Service, Lincoln National Forest","usgsCitation":"Tillery, A.C., and Matherne, A.M., 2013, Postwildfire debris-flow hazard assessment of the area burned by the 2012 Little Bear Fire, south-central New Mexico: U.S. Geological Survey Open-File Report 2013-1108, vi, 15 p.; Maps: 3 Sheets: 33 x 22 inches, https://doi.org/10.3133/ofr20131108.","productDescription":"vi, 15 p.; Maps: 3 Sheets: 33 x 22 inches","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":272806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":272803,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1108/ofr2013-1108-pl1.pdf"},{"id":272804,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1108/ofr2013-1108-pl2.pdf"},{"id":272805,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1108/ofr2013-1108-pl3.pdf"},{"id":272801,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1108/"},{"id":272802,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1108/ofr2013-1108.pdf"}],"country":"United States","state":"New Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0,31.3 ], [ -109.0,37.0 ], [ -103.0,37.0 ], [ -103.0,31.3 ], [ -109.0,31.3 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a07dd8e4b0e4245580366c","contributors":{"authors":[{"text":"Tillery, Anne C. 0000-0002-9508-7908 atillery@usgs.gov","orcid":"https://orcid.org/0000-0002-9508-7908","contributorId":2549,"corporation":false,"usgs":true,"family":"Tillery","given":"Anne","email":"atillery@usgs.gov","middleInitial":"C.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matherne, Anne Marie 0000-0002-5873-2226 matherne@usgs.gov","orcid":"https://orcid.org/0000-0002-5873-2226","contributorId":303,"corporation":false,"usgs":true,"family":"Matherne","given":"Anne","email":"matherne@usgs.gov","middleInitial":"Marie","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478924,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}