{"pageNumber":"1261","pageRowStart":"31500","pageSize":"25","recordCount":184828,"records":[{"id":70134287,"text":"cir1407 - 2015 - The water-energy nexus: An earth science perspective","interactions":[],"lastModifiedDate":"2026-04-29T17:17:38.039351","indexId":"cir1407","displayToPublicDate":"2015-04-10T09:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1407","title":"The water-energy nexus: An earth science perspective","docAbstract":"

Water availability and use are closely connected with energy development and use. Water cannot be delivered to homes, businesses, and industries without energy, and most forms of energy development require large amounts of water. The United States faces two significant and sometimes competing challenges: to provide sustainable supplies of freshwater for humans and ecosystems and to ensure adequate sources of energy for future generations. This report reviews the complex ways in which water and energy are interconnected and describes the earth science data collection and research that can help the Nation address these important challenges.

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The earth sciences have been a cornerstone in developing our current understanding of the water-energy nexus. A full understanding of the nexus, however, is limited by uncertainty in our knowledge of fundamental issues, such as the quantity of freshwater that is available, the amount of water that is used in energy development, the effects that emerging energy development technologies have on water quality and quantity, and the amount of energy required to treat and deliver freshwater. Enhanced data collection and research can improve our understanding of these important issues and thereby lay the groundwork for informed resource management.

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Relevant earth science issues analyzed and discussed herein include freshwater availability; water use; ecosystems health; assessment of saline water resources; assessment of fossil-fuel, uranium, and geothermal resources; subsurface injection of wastewater and carbon dioxide and related induced seismicity; climate change and its effect on water availability and energy production; byproducts and waste streams of energy development; emerging energy-development technologies; and energy for water treatment and delivery.

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Virginia coalfields","docAbstract":"

Large-scale land uses such as residential wastewater discharge and coal mining practices, particularly surface coal extraction and associated valley fills, are of particular ecological concern in central Appalachia. Identification and quantification of both alterations across scales are a necessary first-step to mitigate negative consequences to biota. In central Appalachian headwater streams absent of fish, salamanders are the dominant, most abundant vertebrate predator providing a significant intermediate trophic role. Stream salamander species are considered to be sensitive to aquatic stressors and environmental alterations, and past research has shown linkages among microhabitat parameters, large-scale land use such as urbanization and logging with salamander abundances. However, little is known about these linkages in the coalfields of central Appalachia. In the summer of 2013, we visited 70 sites (sampled three times each) in the southwest Virginia coalfields to survey salamanders and quantify stream and riparian microhabitat parameters. Using an information-theoretic framework we compared the effects of microhabitat and large-scale land use on salamander abundances. Our findings indicate that dusky salamander (Desmognathus spp.) abundances are more correlated to microhabitat parameters such as canopy cover than to subwatershed land uses. Brook salamander (Eurycea spp.) abundances show strong negative associations to the suspended sediments and stream substrate embeddedness. Neither Desmognathus spp. nor Eurycea spp. abundances were influenced by water conductivity. These suggest protection or restoration of riparian habitats and erosion control is an important conservation component for maintaining stream salamanders in the mined landscapes of central Appalachia.

","conferenceTitle":"Second Environmental Considerations in Energy Production Conference","conferenceDate":"September 20-23, 2015","conferenceLocation":"Pittsburgh, PA","language":"English","publisher":"Society for Mining, Mettallurgy, and Exploration, Inc.","publisherLocation":"Englewood, CO","usgsCitation":"Sweeten, S.E., and Ford, W., 2015, Effects of microhabitat and land use on stream salamander abundance in the southwest Virginia coalfields, Second Environmental Considerations in Energy Production Conference, Pittsburgh, PA, September 20-23, 2015, 19 p.","productDescription":"19 p.","ipdsId":"IP-064395","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. 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This report presents Phase 2 of the review and development of the mass balance water-quality model, originally developed in 2001, that guided establishment of the phosphorus (P) total maximum daily load (TMDL) for Upper Klamath and Agency Lakes, Oregon. The purpose of Phase 2 was to incorporate a longer (19-year) set of external phosphorus loading data into the lake TMDL model than had originally been available, and to develop a proof-of-concept method for modeling algal mortality and the consequent decrease in chlorophyll a that had not been possible with the 2001 TMDL model formulation.

\n

Using the extended 1991–2010 external phosphorus loading dataset, the lake TMDL model was recalibrated following the same procedures outlined in the Phase 1 review. The version of the model selected for further development incorporated an updated sediment initial condition, a numerical solution method for the chlorophyll a model, changes to light and phosphorus factors limiting algal growth, and a new pH-model regression, which removed Julian day dependence in order to avoid discontinuities in pH at year boundaries. This updated lake TMDL model was recalibrated using the extended dataset in order to compare calibration parameters to those obtained from a calibration with the original 7.5-year dataset. The resulting algal settling velocity calibrated from the extended dataset was more than twice the value calibrated with the original dataset, and, because the calibrated values of algal settling velocity and recycle rate are related (more rapid settling required more rapid recycling), the recycling rate also was larger than that determined with the original dataset. These changes in calibration parameters highlight the uncertainty in critical rates in the Upper Klamath Lake TMDL model and argue for their direct measurement in future data collection to increase confidence in the model predictions.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155041","usgsCitation":"Wherry, S.A., Wood, T.M., and Anderson, C.W., 2015, Revision and proposed modification for a total maximum daily load model for Upper Klamath Lake, Oregon: U.S. Geological Survey Scientific Investigations Report 2015-5041, vii, 55 p., https://doi.org/10.3133/sir20155041.","productDescription":"vii, 55 p.","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057247","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":299551,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155041.JPG"},{"id":299549,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5041/"},{"id":299550,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5041/pdf/sir2015-5041.pdf","text":"Report","size":"2.4 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0000-0002-1016-3781 chauncey@usgs.gov","orcid":"https://orcid.org/0000-0002-1016-3781","contributorId":139268,"corporation":false,"usgs":true,"family":"Anderson","given":"Chauncey","email":"chauncey@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":544543,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70140562,"text":"ofr20151004 - 2015 - A case study of data integration for aquatic resources using semantic web technologies","interactions":[],"lastModifiedDate":"2018-08-10T16:42:35","indexId":"ofr20151004","displayToPublicDate":"2015-04-09T16:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File 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Use cases, information modeling, and linked data techniques are Semantic Web technologies used to develop a prototype system that integrates scientific observations from four independent USGS and cooperator data systems. The techniques were tested with a use case goal of creating a data set for use in exploring potential relationships among freshwater fish populations and environmental factors. The resulting prototype extracts data from the BioData Retrieval System, the Multistate Aquatic Resource Information System, the National Geochemical Survey, and the National Hydrography Dataset. A prototype user interface allows a scientist to select observations from these data systems and combine them into a single data set in RDF format that includes explicitly defined relationships and data definitions. The project was funded by the USGS Community for Data Integration and undertaken by the Community for Data Integration Semantic Web Working Group in order to demonstrate use of Semantic Web technologies by scientists. This allows scientists to simultaneously explore data that are available in multiple, disparate systems beyond those they traditionally have used.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151004","usgsCitation":"Gordon, J.M., Chkhenkeli, N., Govoni, D.L., Lightsom, F.L., Ostroff, A.C., Schweitzer, P.N., Thongsavanh, P., Varanka, D.E., and Zednik, S., 2015, A case study of data integration for aquatic resources using semantic web technologies: U.S. Geological Survey Open-File Report 2015-1004, v, 55 p., https://doi.org/10.3133/ofr20151004.","productDescription":"v, 55 p.","startPage":"60","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-045446","costCenters":[{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":299545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151004.jpg"},{"id":299544,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1004/pdf/ofr2015-1004.pdf","text":"Report","size":"3.61 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":299543,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1004/"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55279498e4b026915857c836","contributors":{"authors":[{"text":"Gordon, Janice M. janicegordon@usgs.gov","contributorId":4917,"corporation":false,"usgs":true,"family":"Gordon","given":"Janice","email":"janicegordon@usgs.gov","middleInitial":"M.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":544519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chkhenkeli, Nina nchkhenkeli@usgs.gov","contributorId":5904,"corporation":false,"usgs":true,"family":"Chkhenkeli","given":"Nina","email":"nchkhenkeli@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":544522,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Govoni, David L. dgovoni@usgs.gov","contributorId":5192,"corporation":false,"usgs":true,"family":"Govoni","given":"David","email":"dgovoni@usgs.gov","middleInitial":"L.","affiliations":[{"id":5071,"text":"Office of Administration","active":true,"usgs":true}],"preferred":true,"id":544526,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lightsom, Frances L. 0000-0003-4043-3639 flightsom@usgs.gov","orcid":"https://orcid.org/0000-0003-4043-3639","contributorId":1535,"corporation":false,"usgs":true,"family":"Lightsom","given":"Frances","email":"flightsom@usgs.gov","middleInitial":"L.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":544520,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ostroff, Andrea C. 0000-0002-1632-6174 aostroff@usgs.gov","orcid":"https://orcid.org/0000-0002-1632-6174","contributorId":2756,"corporation":false,"usgs":true,"family":"Ostroff","given":"Andrea","email":"aostroff@usgs.gov","middleInitial":"C.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":544523,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schweitzer, Peter N. pschweitzer@usgs.gov","contributorId":5905,"corporation":false,"usgs":true,"family":"Schweitzer","given":"Peter","email":"pschweitzer@usgs.gov","middleInitial":"N.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":544524,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thongsavanh, Phethala thongsav@usgs.gov","contributorId":5154,"corporation":false,"usgs":true,"family":"Thongsavanh","given":"Phethala","email":"thongsav@usgs.gov","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":544525,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Varanka, Dalia E. 0000-0003-2857-9600 dvaranka@usgs.gov","orcid":"https://orcid.org/0000-0003-2857-9600","contributorId":1296,"corporation":false,"usgs":true,"family":"Varanka","given":"Dalia","email":"dvaranka@usgs.gov","middleInitial":"E.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":544521,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zednik, Stephan","contributorId":139117,"corporation":false,"usgs":false,"family":"Zednik","given":"Stephan","email":"","affiliations":[{"id":12656,"text":"Rensselaer Polytechnic Institute","active":true,"usgs":false}],"preferred":false,"id":544527,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70169233,"text":"70169233 - 2015 - Climate change and the permafrost carbon feedback","interactions":[],"lastModifiedDate":"2016-03-24T10:23:25","indexId":"70169233","displayToPublicDate":"2015-04-09T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"Climate change and the permafrost carbon feedback","docAbstract":"

Large quantities of organic carbon are stored in frozen soils (permafrost) within Arctic and sub-Arctic regions. A warming climate can induce environmental changes that accelerate the microbial breakdown of organic carbon and the release of the greenhouse gases carbon dioxide and methane. This feedback can accelerate climate change, but the magnitude and timing of greenhouse gas emission from these regions and their impact on climate change remain uncertain. Here we find that current evidence suggests a gradual and prolonged release of greenhouse gas emissions in a warming climate and present a research strategy with which to target poorly understood aspects of permafrost carbon dynamics.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Nature","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Macmillan Journals Ltd.","publisherLocation":"London","doi":"10.1038/nature14338","usgsCitation":"Schuur, E., McGuire, A.D., Schädel, C., Grosse, G., Harden, J., Hayes, D., Hugelius, G., Koven, C., Kuhry, P., Lawrence, D., Natali, S.M., Olefeldt, D., Romanovsky, V., Schaefer, K., Turetsky, M., Treat, C.C., and Vonk, J., 2015, Climate change and the permafrost carbon feedback: Nature, v. 520, p. 171-179, https://doi.org/10.1038/nature14338.","productDescription":"9 p.","startPage":"171","endPage":"179","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058181","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472152,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1038/nature14338","text":"External Repository"},{"id":319352,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Arctic and Sub-Arctic regions","volume":"520","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56f50fb2e4b0f59b85e1eab6","contributors":{"authors":[{"text":"Schuur, E.A.G.","contributorId":106679,"corporation":false,"usgs":true,"family":"Schuur","given":"E.A.G.","affiliations":[],"preferred":false,"id":623521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":623371,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schädel, C.","contributorId":167791,"corporation":false,"usgs":false,"family":"Schädel","given":"C.","affiliations":[],"preferred":false,"id":623522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grosse, G.","contributorId":82140,"corporation":false,"usgs":true,"family":"Grosse","given":"G.","affiliations":[],"preferred":false,"id":623523,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harden, J.W. 0000-0002-6570-8259","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":38585,"corporation":false,"usgs":true,"family":"Harden","given":"J.W.","affiliations":[],"preferred":false,"id":623524,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hayes, D.J.","contributorId":56074,"corporation":false,"usgs":true,"family":"Hayes","given":"D.J.","email":"","affiliations":[],"preferred":false,"id":623525,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hugelius, G.","contributorId":27338,"corporation":false,"usgs":true,"family":"Hugelius","given":"G.","affiliations":[],"preferred":false,"id":623526,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Koven, C.D.","contributorId":34017,"corporation":false,"usgs":true,"family":"Koven","given":"C.D.","affiliations":[],"preferred":false,"id":623527,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kuhry, P.","contributorId":57277,"corporation":false,"usgs":false,"family":"Kuhry","given":"P.","affiliations":[],"preferred":false,"id":623528,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lawrence, D.M.","contributorId":98608,"corporation":false,"usgs":true,"family":"Lawrence","given":"D.M.","email":"","affiliations":[],"preferred":false,"id":623529,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Natali, Susan M.","contributorId":103160,"corporation":false,"usgs":true,"family":"Natali","given":"Susan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":623530,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Olefeldt, David","contributorId":37622,"corporation":false,"usgs":true,"family":"Olefeldt","given":"David","email":"","affiliations":[],"preferred":false,"id":623531,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Romanovsky, V.E.","contributorId":54721,"corporation":false,"usgs":true,"family":"Romanovsky","given":"V.E.","email":"","affiliations":[],"preferred":false,"id":623532,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Schaefer, K.","contributorId":64127,"corporation":false,"usgs":true,"family":"Schaefer","given":"K.","email":"","affiliations":[],"preferred":false,"id":623533,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Turetsky, M.R.","contributorId":107470,"corporation":false,"usgs":true,"family":"Turetsky","given":"M.R.","email":"","affiliations":[],"preferred":false,"id":623534,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Treat, Claire C.","contributorId":96606,"corporation":false,"usgs":true,"family":"Treat","given":"Claire","email":"","middleInitial":"C.","affiliations":[{"id":25501,"text":"University of Eastern Finland","active":true,"usgs":false}],"preferred":false,"id":623535,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Vonk, J.E.","contributorId":167792,"corporation":false,"usgs":false,"family":"Vonk","given":"J.E.","affiliations":[],"preferred":false,"id":623536,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70141222,"text":"sir20155016 - 2015 - Evaluation of mean-monthly streamflow-regression equations for Colorado, 2014","interactions":[],"lastModifiedDate":"2015-04-09T09:22:23","indexId":"sir20155016","displayToPublicDate":"2015-04-09T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5016","title":"Evaluation of mean-monthly streamflow-regression equations for Colorado, 2014","docAbstract":"

The U.S. Geological Survey, in cooperation with the Colorado Water Conservation Board, evaluated the predictive uncertainty of mean-monthly streamflow-regression equations representative of natural streamflow conditions in Colorado. This study evaluates the predictive uncertainty of mean-monthly streamflow-regression equations developed in a 2009 U.S. Geological Survey study using streamflow data collected over the entire period of record at each streamgage through calendar year 2013. The study area for this report is limited to the Mountain, Northwest, Rio Grande, and Southwest hydrologic regions of Colorado.

\n

Data collected from the beginning of the period of record through calendar year 2013 were used to evaluate the mean-monthly streamflow equations using the same basin characteristics as in the 2009 study. U.S. Geological Survey and Colorado Division of Water Resources streamgages with at least 10 years of streamflow record and identified as representative of natural streamflow conditions were selected for this study. During the streamgage selection process, a total of 432 streamgages, composed of 278 from the 2009 study and 154 new streamgages, were identified.

\n

The updated standard error of prediction and adjusted coefficient of determination values that correspond to the mean-monthly streamflow equations developed in the 2009 study are in close agreement with the results of this study. The old streamgages performed slightly better than the new streamgages, with approximately 88 and 85 percent of the data within the prediction intervals, respectively. This result was expected because the streamgages used to develop the regression equations should yield a better performance than the new streamgages.

\n

For all hydrologic regions, approximately 87 percent of the data are within the 95-percent prediction intervals. The explanation for why fewer than 95 percent of the data are within the prediction intervals is that the data do not conform perfectly to the regression assumptions required to accurately estimate performance metrics. The equations for the Rio Grande hydrologic region had the best fit with the parametric prediction-interval assumptions, with approximately 91.8 percent of the data within the prediction interval (average 12 months). The Mountain, Northwest, and Southwest hydrologic regions had 87.8, 84.9, and 83.5 percent of the data contained within the prediction interval, respectively.

\n

Monthly adjusted coefficient of determination values were computed and have the same general pattern for all four hydrologic regions. The largest values usually occur in March or April, and the lowest values usually occur in August or September. Only the Rio Grande hydrologic region deviates from this seasonal pattern, exhibiting a decrease in adjusted coefficient of determination values in August and September, with the lowest values occurring in the winter months (December, January, and February). Generally, the adjusted coefficient of determination values for this report are just slightly less (0.76 compared to 0.79) than the values computed in the 2009 study. The similarity of values, even when tested with data not used to originally develop the mean-monthly streamflow-regression equations, provides confidence that the predictive uncertainty of mean-monthly regression equations in the 2009 study are accurate. The fact that the results for the two datasets are very similar provides assurance that when these equations are applied to locations not used to develop the equations, the standard error of prediction and adjusted-coefficient of determination error metrics should be similar to those established in the 2009 study for locations with natural streamflow.

\n

The median absolute differences between the observed and computed mean-monthly streamflow for Mountain, Northwest, and Southwest hydrologic regions are fairly uniform throughout the year, with the exception of late summer and early fall (July, August, and September), when each hydrologic region exhibits a substantial increase in median absolute percent difference. The greatest difference occurs in the Northwest hydrologic region, and the smallest difference occurs in the Mountain hydrologic region. The Rio Grande hydrologic region shows seasonal variation in median absolute percent difference with March, April, August, and September having a median absolute difference near or below 40 percent, and the remaining months of the year having a median absolute difference near or above 50 percent. In the Mountain, Northwest, and Southwest hydrologic regions, the mean-monthly streamflow equations perform the best during spring (March, April, and May). However, in the Rio Grande hydrologic region, the mean-monthly streamflow equations perform the best during late summer and early fall (August and September).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155016","collaboration":"Colorado Water Conservation Board","usgsCitation":"Kohn, M.S., Stevens, M.R., Bock, A.R., and Char, S.J., 2015, Evaluation of mean-monthly streamflow-regression equations for Colorado, 2014: U.S. Geological Survey Scientific Investigations Report 2015-5016, vii, 53, https://doi.org/10.3133/sir20155016.","productDescription":"vii, 53","startPage":"53","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2013-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-057631","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":299533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155016.jpg"},{"id":299532,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5016/pdf/sir2015-5016.pdf","text":"Report","size":"5.84 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":299521,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5016/"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.45654296875,\n 36.12012758978146\n ],\n [\n -110.45654296875,\n 41.78769700539063\n ],\n [\n -104.853515625,\n 41.78769700539063\n ],\n [\n -104.853515625,\n 36.12012758978146\n ],\n [\n -110.45654296875,\n 36.12012758978146\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5527949ae4b026915857c838","contributors":{"authors":[{"text":"Kohn, Michael S. 0000-0002-5989-7700 mkohn@usgs.gov","orcid":"https://orcid.org/0000-0002-5989-7700","contributorId":4549,"corporation":false,"usgs":true,"family":"Kohn","given":"Michael","email":"mkohn@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stevens, Michael R. 0000-0002-9476-6335 mrsteven@usgs.gov","orcid":"https://orcid.org/0000-0002-9476-6335","contributorId":769,"corporation":false,"usgs":true,"family":"Stevens","given":"Michael","email":"mrsteven@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bock, Andrew R. 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":4580,"corporation":false,"usgs":true,"family":"Bock","given":"Andrew","email":"abock@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544457,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Char, Stephen J. sjchar@usgs.gov","contributorId":3982,"corporation":false,"usgs":true,"family":"Char","given":"Stephen","email":"sjchar@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544458,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70141356,"text":"sir20155028 - 2015 - New argon-argon (40Ar/39Ar) radiometric age dates from selected subsurface basalt flows at the Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2015-04-09T09:06:19","indexId":"sir20155028","displayToPublicDate":"2015-04-09T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5028","title":"New argon-argon (40Ar/39Ar) radiometric age dates from selected subsurface basalt flows at the Idaho National Laboratory, Idaho","docAbstract":"

In 2011, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, collected samples for 12 new argon-argon radiometric ages from eastern Snake River Plain olivine tholeiite basalt flows in the subsurface at the Idaho National Laboratory. The core samples were collected from flows that had previously published paleomagnetic data. Samples were sent to Rutgers University for argon-argon radiometric dating analyses.

\n

Paleomagnetic and stratigraphic data were used to constrain the results of the age dating experiments to derive the preferred age for each basalt flow. Knowledge of the ages of subsurface basalt flows is needed to improve numerical models of groundwater flow and contaminant transport in the eastern Snake River Plain aquifer. This could be accomplished by increasing the ability to correlate basalt flow from corehole to corehole in the subsurface. The age of basalt flows also can be used in volcanic recurrence and landscape evolution studies that are important to better understand future hazards that could occur at the Idaho National Laboratory.

\n

Results indicate that ages ranged from 60 ± 16 thousand years ago for Quaking Aspen Butte to 621 ± 9 thousand years ago for State Butte.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155028","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Hodges, M., Turrin, B.D., Champion, D.E., and Swisher, C.C., 2015, New argon-argon (40Ar/39Ar) radiometric age dates from selected subsurface basalt flows at the Idaho National Laboratory, Idaho: U.S. Geological Survey Scientific Investigations Report 2015-5028, v, 25 p.; Appendix, https://doi.org/10.3133/sir20155028.","productDescription":"v, 25 p.; Appendix","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-044883","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":299524,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5028/"},{"id":299528,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5028/pdf/sir2015-5028.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":299529,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5028/download/sir2015-5028_AppendixA.zip","text":"Appendix A","size":"12.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix A"},{"id":299530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155028.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Idaho National Laboratory","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.345703125,\n 43.389081939117496\n ],\n [\n -114.345703125,\n 44.38669150215206\n ],\n [\n -112.5,\n 44.38669150215206\n ],\n [\n -112.5,\n 43.389081939117496\n ],\n [\n -114.345703125,\n 43.389081939117496\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5527949de4b026915857c83c","contributors":{"authors":[{"text":"Hodges, Mary K. 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The U.S. Geological Survey has completed an assessment of the potential geologic carbon dioxide storage resource in the onshore areas of the United States. To provide geological context and input data sources for the resources numbers, framework documents are being prepared for all areas that were investigated as part of the national assessment. This report is the geologic framework document for the Permian and Palo Duro Basins, the combined Bend arch-Fort Worth Basin area, and subbasins therein of Texas, New Mexico, and Oklahoma. In addition to a summarization of the geology and petroleum resources of studied basins, the individual storage assessment units (SAUs) within the basins are described and explanations for their selection are presented. Though appendixes in the national assessment publications include the input values used to calculate the available storage resource, this framework document provides only the context and source of inputs selected by the assessment geologists. Spatial files of boundaries for the SAUs herein, as well as maps of the density of known well bores that penetrate the SAU seal, are available for download with the release of this report.

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Digital surfaces and thicknesses of selected hydrogeologic units of the Floridan aquifer system were developed to define an updated hydrogeologic framework as part of the U.S. Geological Survey Groundwater Resources Program. The dataset contains structural surfaces depicting the top and base of the aquifer system, its major and minor hydrogeologic units and zones, geophysical marker horizons, and the altitude of the 10,000-milligram-per-liter total dissolved solids boundary that defines the approximate fresh and saline parts of the aquifer system. The thicknesses of selected major and minor units or zones were determined by interpolating points of known thickness or from raster surface subtraction of the structural surfaces. Additional data contained include clipping polygons; regional polygon features that represent geologic or hydrogeologic aspects of the aquifers and the minor units or zones; data points used in the interpolation; and polygon and line features that represent faults, boundaries, and other features in the aquifer system.

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Renewable energy is expanding quickly with sometimes dramatic impacts to species and ecosystems. To understand the degree to which sensitive species may be impacted by renewable energy projects, it is informative to know how much space individuals use and how that space may overlap with planned development. We used global positioning system–global system for mobile communications (GPS-GSM) telemetry to measure year-round movements of golden eagles (Aquila chrysaetos) from the Mojave Desert of California, USA. We estimated monthly space use with adaptive local convex hulls to identify the temporal and spatial scales at which eagles may encounter renewable energy projects in the Desert Renewable Energy Conservation Plan area. Mean size of home ranges was lowest and least variable from November through January and greatest in February–March and May–August. These monthly home range patterns coincided with seasonal variation in breeding ecology, habitat associations, and temperature. The expanded home ranges in hot summer months included movements to cooler, prey-dense, mountainous areas characterized by forest, grasslands, and scrublands. Breeding-season home ranges (October–May) included more lowland semi-desert and rock vegetation. Overlap of eagle home ranges and focus areas for renewable energy development was greatest when eagle home ranges were smallest, during the breeding season. Golden eagles in the Mojave Desert used more space and a wider range of habitat types than expected and renewable energy projects could affect a larger section of the regional population than was previously thought.

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The hydrogeologic framework for the Floridan aquifer system has been revised throughout its extent in Florida and parts of Georgia, Alabama, and South Carolina. The updated framework generally conforms to the original framework established by the U.S. Geological Survey in the 1980s, except for adjustments made to the internal boundaries of the Upper and Lower Floridan aquifers and the individual higher and contrasting lower permeability zones within these aquifers. The system behaves as one aquifer over much of its extent; although subdivided vertically into two aquifer units, the Upper and Lower Floridan aquifers. In the previous framework, discontinuous numbered middle confining units (MCUI–VII) were used to subdivide the system. In areas where less-permeable rocks do not occur within the middle part of the system, the system was previously considered one aquifer and named the Upper Floridan aquifer. In intervening years, more detailed data have been collected in local areas, resulting in some of the same lithostratigraphic units in the Floridan aquifer system being assigned to the Upper or Lower Floridan aquifer in different parts of the State of Florida. Additionally, some of the numbered middle confining units are found to have hydraulic properties within the same order of magnitude as the aquifers. A new term “composite unit” is introduced for lithostratigraphic units that cannot be defined as either a confining or aquifer unit over their entire extent. This naming convention is a departure from the previous framework, in that stratigraphy is used to consistently subdivide the aquifer system into upper and lower aquifers across the State of Florida. This lithostratigraphic mapping approach does not change the concept of flow within the system. The revised boundaries of the Floridan aquifer system were mapped by considering results from local studies and regional correlations of lithostratigraphic and hydrogeologic units or zones. Additional zones within the aquifers have been incorporated into the framework to allow finer delineation of permeability variations within the aquifer system. These additional zones can be used to progressively divide the system for assessing groundwater and surface-water interaction, saltwater intrusion, and offshore movement of groundwater at greater detail if necessary. The lateral extent of the updip boundary of the Floridan aquifer system is modified from previous work based on newer data and inclusion of parts of the updip clastic facies. The carbonate and clastic facies form a gradational sequence, generally characterized by limestone of successively younger units that extend progressively farther updip. Because of the gradational nature of the carbonate-clastic sequence, some of the updip clastic aquifers have been included in the Floridan aquifer system, the Southeastern Coastal Plain aquifer system, or both. Thus, the revised updip limit includes some of these clastic facies. Additionally, the updip limit of the most productive part of the Floridan aquifer system was revised and indicates the approximate updip limit of the carbonate facies. The extent and altitude of the freshwater-saltwater interface in the aquifer system has been mapped to define the freshwater part of the flow system.

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Director, South Atlantic Water Science Center
North Carolina–South Carolina–Georgia
20 Gracern Road, Suite 129
Columbia, SC 29210
http://ga.water.usgs.gov/

","publishedDate":"2015-04-08","revisedDate":"2016-03-01","noUsgsAuthors":false,"publicationDate":"2015-04-08","publicationStatus":"PW","scienceBaseUri":"5526431fe4b026915857c638","contributors":{"authors":[{"text":"Williams, Lester J. lesterw@usgs.gov","contributorId":2395,"corporation":false,"usgs":true,"family":"Williams","given":"Lester","email":"lesterw@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":544407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kuniansky, Eve L. 0000-0002-5581-0225 elkunian@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-0225","contributorId":932,"corporation":false,"usgs":true,"family":"Kuniansky","given":"Eve","email":"elkunian@usgs.gov","middleInitial":"L.","affiliations":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":544408,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148104,"text":"70148104 - 2015 - Effect of tides, river flow, and gate operations on entrainment of juvenile salmon into the interior Sacramento–San Joaquin River Delta","interactions":[],"lastModifiedDate":"2018-09-25T11:04:36","indexId":"70148104","displayToPublicDate":"2015-04-08T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Effect of tides, river flow, and gate operations on entrainment of juvenile salmon into the interior Sacramento–San Joaquin River Delta","docAbstract":"

Juvenile Chinook Salmon Oncorhynchus tshawytscha emigrating from natal tributaries of the Sacramento River, California, must negotiate the Sacramento-San Joaquin River Delta (hereafter, the Delta), a complex network of natural and man-made channels linking the Sacramento River with San Francisco Bay. Fish that enter the interior and southern Delta—the region to the south of the Sacramento River where water pumping stations are located—survive at a lower rate than fish that use alternative migration routes. Consequently, total survival decreases as the fraction of the population entering the interior Delta increases, thus spurring management actions to reduce the proportion of fish that are entrained into the interior Delta. To better inform management actions, we modeled entrainment probability as a function of hydrodynamic variables. We fitted alternative entrainment models to telemetry data that identified when tagged fish in the Sacramento River entered two river channels leading to the interior Delta (Georgiana Slough and the gated Delta Cross Channel). We found that the probability of entrainment into the interior Delta through both channels depended strongly on the river flow and tidal stage at the time of fish arrival at the river junction. Fish that arrived during ebb tides had a low entrainment probability, whereas fish that arrived during flood tides (i.e., when the river's flow was reversed) had a high probability of entering the interior Delta. We coupled our entrainment model with a flow simulation model to evaluate the effect of nighttime closures of the Delta Cross Channel gates on the daily probability of fish entrainment into the interior Delta. Relative to 24-h gate closures, nighttime closures increased daily entrainment probability by 3 percentage points on average if fish arrived at the river junction uniformly throughout the day and by only 1.3 percentage points if 85% of fish arrived at night. We illustrate how our model can be used to evaluate the effects of alternative water management actions on fish entrainment into the interior Delta.

","language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.1080/00028487.2014.1001038","usgsCitation":"Perry, R.W., Brandes, P., Burau, J.R., Sandstrom, P.T., and Skalski, J.R., 2015, Effect of tides, river flow, and gate operations on entrainment of juvenile salmon into the interior Sacramento–San Joaquin River Delta: Transactions of the American Fisheries Society, v. 144, no. 3, p. 445-455, https://doi.org/10.1080/00028487.2014.1001038.","productDescription":"11 p.","startPage":"445","endPage":"455","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056864","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":300640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.91734313964844,\n 38.05403884511629\n ],\n [\n -121.89743041992189,\n 38.053227812983906\n ],\n [\n -121.86927795410156,\n 38.07079816372681\n ],\n [\n -121.8651580810547,\n 38.07431172756913\n ],\n [\n -121.84078216552733,\n 38.079446632654914\n ],\n [\n -121.79786682128905,\n 38.06458144502031\n ],\n [\n -121.78207397460936,\n 38.05809387097575\n ],\n [\n -121.7841339111328,\n 38.04700960141592\n ],\n [\n -121.77452087402344,\n 38.037275688165614\n ],\n [\n -121.75907135009764,\n 38.03376034594566\n ],\n [\n -121.75048828124999,\n 38.02997440409721\n ],\n [\n -121.7501449584961,\n 38.01374672284207\n ],\n [\n -121.761474609375,\n 38.01834493072087\n ],\n [\n -121.77932739257812,\n 38.01320573824361\n ],\n [\n -121.8002700805664,\n 38.01618110412486\n ],\n [\n -121.80953979492188,\n 38.01428770344776\n ],\n [\n -121.83700561523438,\n 38.02240193339466\n ],\n [\n -121.8558883666992,\n 38.02727004012099\n ],\n [\n -121.87957763671874,\n 38.032137823399275\n ],\n [\n -121.88541412353514,\n 38.03348992801713\n ],\n [\n -121.89228057861328,\n 38.03889809689809\n ],\n [\n -121.90395355224608,\n 38.03700528321584\n ],\n [\n -121.92352294921874,\n 38.04160203158018\n ],\n [\n -121.91734313964844,\n 38.05403884511629\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"144","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-08","publicationStatus":"PW","scienceBaseUri":"555f01c0e4b0a92fa7eb969b","contributors":{"authors":[{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":547404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brandes, Patricia L.","contributorId":25834,"corporation":false,"usgs":true,"family":"Brandes","given":"Patricia L.","affiliations":[],"preferred":false,"id":547405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burau, Jon R. 0000-0002-5196-5035 jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sandstrom, Philip T. psandstrom@usgs.gov","contributorId":5907,"corporation":false,"usgs":true,"family":"Sandstrom","given":"Philip","email":"psandstrom@usgs.gov","middleInitial":"T.","affiliations":[],"preferred":true,"id":547407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Skalski, John R.","contributorId":94131,"corporation":false,"usgs":false,"family":"Skalski","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":13190,"text":"School of Aquatic and Fishery Sciences, University of Washington","active":true,"usgs":false}],"preferred":false,"id":547408,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70145561,"text":"70145561 - 2015 - The dynamics of avian influenza in western Arctic snow geese: implications for annual and migratory infection patterns","interactions":[],"lastModifiedDate":"2017-02-17T15:07:23","indexId":"70145561","displayToPublicDate":"2015-04-08T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"The dynamics of avian influenza in western Arctic snow geese: implications for annual and migratory infection patterns","docAbstract":"

Wild water birds are the natural reservoir for low-pathogenic avian influenza viruses (AIV). However, our ability to investigate the epizootiology of AIV in these migratory populations is challenging, and despite intensive worldwide surveillance, remains poorly understood. We conducted a cross-sectional, retrospective analysis in Pacific Flyway lesser snow geese Chen caerulescens to investigate AIV serology and infection patterns. We collected nearly 3,000 sera samples from snow geese at 2 breeding colonies in Russia and Canada during 1993-1996 and swab samples from > 4,000 birds at wintering and migration areas in the United States during 2006-2011. We found seroprevalence and annual seroconversion varied considerably among years. Seroconversion and infection rates also differed between snow goose breeding colonies and wintering areas, suggesting that AIV exposure in this gregarious waterfowl species is likely occurring during several phases (migration, wintering and potentially breeding areas) of the annual cycle. We estimated AIV antibody persistence was longer (14 months) in female geese compared to males (6 months). This relatively long period of AIV antibody persistence suggests that subtype-specific serology may be an effective tool for detection of exposure to subtypes associated with highly-pathogenic AIV. Our study provides further evidence of high seroprevalence in Arctic goose populations, and estimates of annual AIV seroconversion and antibody persistence for North American waterfowl. We suggest future AIV studies include serology to help elucidate the epizootiological dynamics of AIV in wild bird populations.

","language":"English","publisher":"Ecological Society of America","doi":"10.1890/14-1820.1","usgsCitation":"Samuel, M.D., Hall, J.S., Brown, J.D., Goldberg, D.R., Ip, S., and Baranyuk, V.V., 2015, The dynamics of avian influenza in western Arctic snow geese: implications for annual and migratory infection patterns: Ecological Applications, v. 25, no. 7, p. 1851-1859, https://doi.org/10.1890/14-1820.1.","productDescription":"9 p.","startPage":"1851","endPage":"1859","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057837","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":472155,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/14-1820.1","text":"Publisher Index Page"},{"id":299487,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Russia, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.78515624999999,\n 73.52839948765174\n ],\n [\n -118.65234374999999,\n 74.86788912917916\n ],\n [\n -182.548828125,\n 71.69129271863999\n ],\n [\n -181.58203125,\n 70.61261423801925\n ],\n [\n -124.892578125,\n 48.28319289548349\n ],\n [\n -122.56347656249999,\n 38.13455657705411\n ],\n [\n -119.61914062499999,\n 34.63320791137959\n ],\n [\n -117.99316406249999,\n 34.95799531086792\n ],\n [\n -110.21484375,\n 44.96479793033101\n ],\n [\n -114.78515624999999,\n 73.52839948765174\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"25","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55264320e4b026915857c63a","contributors":{"authors":[{"text":"Samuel, Michael D. msamuel@usgs.gov","contributorId":1419,"corporation":false,"usgs":true,"family":"Samuel","given":"Michael","email":"msamuel@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":544258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hall, Jeffrey S. 0000-0001-5599-2826 jshall@usgs.gov","orcid":"https://orcid.org/0000-0001-5599-2826","contributorId":2254,"corporation":false,"usgs":true,"family":"Hall","given":"Jeffrey","email":"jshall@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":544330,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Justin D.","contributorId":87838,"corporation":false,"usgs":false,"family":"Brown","given":"Justin","email":"","middleInitial":"D.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":544331,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goldberg, Diana R. 0000-0001-8540-8512 dgoldberg@usgs.gov","orcid":"https://orcid.org/0000-0001-8540-8512","contributorId":5739,"corporation":false,"usgs":true,"family":"Goldberg","given":"Diana","email":"dgoldberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":544332,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ip, S. 0000-0003-4844-7533 hip@usgs.gov","orcid":"https://orcid.org/0000-0003-4844-7533","contributorId":727,"corporation":false,"usgs":true,"family":"Ip","given":"S.","email":"hip@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":544333,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baranyuk, Vasily V.","contributorId":75482,"corporation":false,"usgs":false,"family":"Baranyuk","given":"Vasily","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":544334,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70154856,"text":"70154856 - 2015 - A chronicle of a killer alga in the west: Ecology, assessment, and management of Prymnesium parvum blooms","interactions":[],"lastModifiedDate":"2022-11-22T17:35:37.333821","indexId":"70154856","displayToPublicDate":"2015-04-08T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A chronicle of a killer alga in the west: Ecology, assessment, and management of Prymnesium parvum blooms","title":"A chronicle of a killer alga in the west: Ecology, assessment, and management of Prymnesium parvum blooms","docAbstract":"

Since the mid-1980s, fish-killing blooms of Prymnesium parvum spread throughout the USA. In the south central USA, P. parvum blooms have commonly spanned hundreds of kilometers. There is much evidence that physiological stress brought on by inorganic nutrient limitation enhances toxicity. Other factors influence toxin production as well, such as stress experienced at low salinity and temperature. A better understanding of toxin production by P. parvum remains elusive and the identities and functions of chemicals produced are unclear. This limits our understanding of factors that facilitated the spread of P. parvum blooms. In the south central USA, not only is there evidence that the spread of blooms was controlled, in part, by migration limitation. But there are also observations that suggest changed environmental conditions, primarily salinity, facilitated the spread of blooms. Other factors that might have played a role include altered hydrology and nutrient loading. Changes in water hardness, herbicide use, system pH, and the presence of toxin-resistant and/or P. parvum-inhibiting plankton may also have played a role. Management of P. parvum in natural systems has yet to be attempted, but may be guided by successes achieved in small impoundments and mesocosm experiments that employed various chemical and hydraulic control approaches.

","language":"English","publisher":"Springer","doi":"10.1007/s10750-015-2273-6","usgsCitation":"Roelke, D.L., Barkoh, A., Brooks, B.W., Grover, J.P., Hambright, K.D., LaClaire, J.W., Moeller, P.D., and Patino, R., 2015, A chronicle of a killer alga in the west: Ecology, assessment, and management of Prymnesium parvum blooms: Hydrobiologia, v. 764, p. 29-50, https://doi.org/10.1007/s10750-015-2273-6.","productDescription":"22 p.","startPage":"29","endPage":"50","numberOfPages":"22","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061394","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":305644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"764","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-08","publicationStatus":"PW","scienceBaseUri":"57f7ef48e4b0bc0bec09f00f","contributors":{"authors":[{"text":"Roelke, D. L.","contributorId":28342,"corporation":false,"usgs":true,"family":"Roelke","given":"D.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":564562,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barkoh, Aaron","contributorId":145542,"corporation":false,"usgs":false,"family":"Barkoh","given":"Aaron","email":"","affiliations":[],"preferred":false,"id":564563,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brooks, Bryan W. 0000-0002-6277-9852","orcid":"https://orcid.org/0000-0002-6277-9852","contributorId":198868,"corporation":false,"usgs":false,"family":"Brooks","given":"Bryan","email":"","middleInitial":"W.","affiliations":[{"id":35352,"text":"Department of Environmental Science, Baylor University, Waco, TX, USA","active":true,"usgs":false}],"preferred":false,"id":564564,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grover, J. P.","contributorId":20453,"corporation":false,"usgs":true,"family":"Grover","given":"J.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":564565,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hambright, K. D.","contributorId":25793,"corporation":false,"usgs":true,"family":"Hambright","given":"K.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":564566,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LaClaire, John W. II","contributorId":145543,"corporation":false,"usgs":false,"family":"LaClaire","given":"John","suffix":"II","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":564567,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moeller, Peter D. R.","contributorId":145544,"corporation":false,"usgs":false,"family":"Moeller","given":"Peter","email":"","middleInitial":"D. R.","affiliations":[],"preferred":false,"id":564568,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Patino, Reynaldo 0000-0002-4831-8400 r.patino@usgs.gov","orcid":"https://orcid.org/0000-0002-4831-8400","contributorId":2311,"corporation":false,"usgs":true,"family":"Patino","given":"Reynaldo","email":"r.patino@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":564276,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70148064,"text":"70148064 - 2015 - Intercontinental spread of asian-origin H5N8 to North America through Beringia by migratory birds","interactions":[],"lastModifiedDate":"2015-05-18T11:46:40","indexId":"70148064","displayToPublicDate":"2015-04-08T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2497,"text":"Journal of Virology","active":true,"publicationSubtype":{"id":10}},"title":"Intercontinental spread of asian-origin H5N8 to North America through Beringia by migratory birds","docAbstract":"

Phylogenetic network analysis and understanding of waterfowl migration patterns suggest the Eurasian H5N8 clade 2.3.4.4 avian influenza virus emerged in late 2013 in China, spread in early 2014 to South Korea and Japan, and reached Siberia and Beringia by summer 2014 via migratory birds. Three genetically distinct subgroups emerged and subsequently spread along different flyways during fall 2014 into Europe, North America, and East Asia, respectively. All three subgroups reappeared in Japan, a wintering site for waterfowl from Eurasia and parts of North America.

","language":"English","publisher":"American Society for Microbiology","publisherLocation":"Baltimore, MD","doi":"10.1128/JVI.00728-15","usgsCitation":"Lee, D., Kim Torchetti, M., Winker, K., Ip, S., Swayne, D.E., and Song, C., 2015, Intercontinental spread of asian-origin H5N8 to North America through Beringia by migratory birds: Journal of Virology, v. 89, no. 12, p. 6521-6524, https://doi.org/10.1128/JVI.00728-15.","productDescription":"4 p.","startPage":"6521","endPage":"6524","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062907","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":472153,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1128/jvi.00728-15","text":"External Repository"},{"id":300466,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"12","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"555b0d51e4b0a92fa7eac62d","contributors":{"authors":[{"text":"Lee, Dong-Hun","contributorId":140813,"corporation":false,"usgs":false,"family":"Lee","given":"Dong-Hun","email":"","affiliations":[{"id":13585,"text":"Poultry Research Laboratory, Agricultural Research Service, U.S. Department of Agriculture, Athens, Georgia, USA","active":true,"usgs":false}],"preferred":false,"id":547046,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kim Torchetti, Mia","contributorId":139355,"corporation":false,"usgs":false,"family":"Kim Torchetti","given":"Mia","email":"","affiliations":[{"id":12747,"text":"USDA APHIS VS National Veterinary Services Laboratories, Ames, IA","active":true,"usgs":false}],"preferred":false,"id":547047,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winker, Kevin","contributorId":140814,"corporation":false,"usgs":false,"family":"Winker","given":"Kevin","email":"","affiliations":[{"id":13586,"text":"University of Alaska Museum, University of Alaska Fairbanks, Fairbanks, Alaska, USA","active":true,"usgs":false}],"preferred":false,"id":547048,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ip, S. 0000-0003-4844-7533 hip@usgs.gov","orcid":"https://orcid.org/0000-0003-4844-7533","contributorId":727,"corporation":false,"usgs":true,"family":"Ip","given":"S.","email":"hip@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":547045,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swayne, David E.","contributorId":86218,"corporation":false,"usgs":true,"family":"Swayne","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":547049,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Song, Chang-Seon","contributorId":140815,"corporation":false,"usgs":false,"family":"Song","given":"Chang-Seon","email":"","affiliations":[],"preferred":false,"id":547050,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70146557,"text":"70146557 - 2015 - USGS National Wildlife Health Center quarterly mortality report","interactions":[],"lastModifiedDate":"2023-10-13T14:18:39.520524","indexId":"70146557","displayToPublicDate":"2015-04-08T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3769,"text":"Wildlife Disease Association Newsletter","active":true,"publicationSubtype":{"id":10}},"title":"USGS National Wildlife Health Center quarterly mortality report","docAbstract":"

No abstract available.

","language":"English","publisher":"Wildlife Disease Association","usgsCitation":"Chipault, J.G., Ballmann, A., Bodenstein, B., and Dusek, R., 2015, USGS National Wildlife Health Center quarterly mortality report: Wildlife Disease Association Newsletter, no. April 2015, p. 4-5.","productDescription":"2 p.","startPage":"4","endPage":"5","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064251","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":299772,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.wildlifedisease.org/PersonifyEbusiness/Resources/Publications/Newsletter/Archive"},{"id":299773,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"issue":"April 2015","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5536234be4b0b22a15807ac4","contributors":{"authors":[{"text":"Chipault, Jennifer G. 0000-0002-1368-622X jchipault@usgs.gov","orcid":"https://orcid.org/0000-0002-1368-622X","contributorId":4765,"corporation":false,"usgs":true,"family":"Chipault","given":"Jennifer","email":"jchipault@usgs.gov","middleInitial":"G.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":545142,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ballmann, Anne 0000-0002-0380-056X aballmann@usgs.gov","orcid":"https://orcid.org/0000-0002-0380-056X","contributorId":140319,"corporation":false,"usgs":true,"family":"Ballmann","given":"Anne","email":"aballmann@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":545143,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bodenstein, Barbara L. 0000-0001-7946-0103 bbodenstein@usgs.gov","orcid":"https://orcid.org/0000-0001-7946-0103","contributorId":139354,"corporation":false,"usgs":true,"family":"Bodenstein","given":"Barbara L.","email":"bbodenstein@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":545144,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dusek, Robert J. 0000-0001-6177-7479 rdusek@usgs.gov","orcid":"https://orcid.org/0000-0001-6177-7479","contributorId":140066,"corporation":false,"usgs":true,"family":"Dusek","given":"Robert J.","email":"rdusek@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":545145,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70139404,"text":"sir20145224 - 2015 - Hydrogeologic framework, hydrology, and refined conceptual model of groundwater flow for Coastal Plain aquifers at the Standard Chlorine of Delaware, Inc. Superfund Site, New Castle County, Delaware, 2005-12","interactions":[],"lastModifiedDate":"2018-03-21T15:43:13","indexId":"sir20145224","displayToPublicDate":"2015-04-08T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5224","title":"Hydrogeologic framework, hydrology, and refined conceptual model of groundwater flow for Coastal Plain aquifers at the Standard Chlorine of Delaware, Inc. Superfund Site, New Castle County, Delaware, 2005-12","docAbstract":"

From 1966 to 2002, activities at the Standard Chlorine of Delaware chemical facility in New Castle County, Delaware resulted in the contamination of groundwater, soils, and wetland sediment. In 2005, the U.S. Geological Survey (USGS), in partnership with the U.S. Environmental Protection Agency, Region 3, and the Delaware Department of Natural Resources and Environmental Control began a multi-year investigation of the hydrogeologic framework and hydrology of the confined aquifer system. The goals of the ongoing study at the site (the Potomac Aquifer Study) are to determine the hydraulic connection between the Columbia and Potomac aquifers, determine the direction of groundwater flow in the Potomac aquifer, and identify factors affecting the fate of contaminated groundwater. This report describes progress made towards these goals based on available data collected through September 2012.

\n

The regional hydrogeologic framework indicates that the site is underlain by Coastal Plain sediments of the Columbia, Merchantville, and Potomac Formations. Two primary aquifers underlying the site, the Columbia and the upper Potomac, are separated by the Merchantville Formation confining unit. Local groundwater flow in the surficial (Columbia) aquifer is controlled by topography and generally flows northward and discharges to nearby surface water. Regional flow within the Potomac aquifer is towards the southeast, and is strongly influenced by major water withdrawals locally. Previous investigations at the site indicated that contaminants, primarily benzene and chlorinated benzene compounds, were present in the Columbia aquifer in most locations; however, there were only limited detections in the upper Potomac aquifer as of 2004. From 2005 through 2012, the USGS designed a monitoring network, assisted with exploratory drilling, collected data at monitoring wells, conducted geophysical surveys, evaluated water-level responses in wells during pumping of a production well, and evaluated major aquifer withdrawals. Data collected through these efforts were used to refine the local conceptual flow system. The refined conceptual flow system for the site includes: (a) identification of gaps in confining units in the study area, (b) identification and correlation of multiple water-bearing sand intervals within the upper Potomac Formation, (c) connections between groundwater and surface water, (d) connections between shallow and deeper groundwater, (e) new water-level (or potentiometric surface) maps and inferred flow directions, and (f) identification of major local pumping well influences. The implications of the revised conceptual flow system on the occurrence and movement of site contaminants are that the resulting detection of contaminants in the upper Potomac aquifer at specific well locations can be attributed primarily to either advective lateral transport, direct vertical contaminant transport, or a combination of vertical and lateral movement resulting from changes in water withdrawal rates over time.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145224","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Brayton, M.J., Cruz, R.M., Myers, L., Degnan, J.R., and Raffensperger, J.P., 2015, Hydrogeologic framework, hydrology, and refined conceptual model of groundwater flow for Coastal Plain aquifers at the Standard Chlorine of Delaware, Inc. Superfund Site, New Castle County, Delaware, 2005-12: U.S. Geological Survey Scientific Investigations Report 2014-5224, vii, 61 p., https://doi.org/10.3133/sir20145224.","productDescription":"vii, 61 p.","numberOfPages":"74","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2005-01-01","temporalEnd":"2012-09-30","ipdsId":"IP-059549","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":299486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145224.jpg"},{"id":299484,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5224/"},{"id":299485,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5224/pdf/sir2014-5224.pdf","text":"Report","size":"3.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"projection":"State Plane Delaware Projection","datum":"North American Datum of 1983","country":"United States","state":"Delaware","county":"New Castle County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.60430526733398,\n 39.63187001350982\n ],\n [\n -75.65872192382812,\n 39.637422462817\n ],\n [\n -75.70489883422852,\n 39.60886226158157\n ],\n [\n -75.71365356445311,\n 39.59464387992515\n ],\n [\n -75.65108299255371,\n 39.55554482419571\n ],\n [\n -75.59306144714355,\n 39.571623755318214\n ],\n [\n -75.58670997619629,\n 39.579231826349016\n ],\n [\n -75.58653831481934,\n 39.5808856443388\n ],\n [\n -75.59864044189453,\n 39.58935257415456\n ],\n [\n -75.60842514038085,\n 39.59484229602979\n ],\n [\n -75.61426162719727,\n 39.60463011823322\n ],\n [\n -75.61134338378906,\n 39.6109782362526\n ],\n [\n -75.61408996582031,\n 39.617325772242175\n ],\n [\n -75.61031341552734,\n 39.625788248139436\n ],\n [\n -75.60636520385742,\n 39.6265815522009\n ],\n [\n -75.60430526733398,\n 39.63187001350982\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5526431de4b026915857c634","contributors":{"authors":[{"text":"Brayton, Michael J. mbrayton@usgs.gov","contributorId":2993,"corporation":false,"usgs":true,"family":"Brayton","given":"Michael","email":"mbrayton@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cruz, Roberto M. 0000-0003-1235-3295 rmcruz@usgs.gov","orcid":"https://orcid.org/0000-0003-1235-3295","contributorId":5757,"corporation":false,"usgs":true,"family":"Cruz","given":"Roberto","email":"rmcruz@usgs.gov","middleInitial":"M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539389,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Myers, Luke lmyers@usgs.gov","contributorId":5758,"corporation":false,"usgs":true,"family":"Myers","given":"Luke","email":"lmyers@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Degnan, James R. 0000-0002-5665-9010 jrdegnan@usgs.gov","orcid":"https://orcid.org/0000-0002-5665-9010","contributorId":498,"corporation":false,"usgs":true,"family":"Degnan","given":"James","email":"jrdegnan@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539391,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Raffensperger, Jeff P. 0000-0001-9275-6646 jpraffen@usgs.gov","orcid":"https://orcid.org/0000-0001-9275-6646","contributorId":199119,"corporation":false,"usgs":true,"family":"Raffensperger","given":"Jeff","email":"jpraffen@usgs.gov","middleInitial":"P.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539392,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70141848,"text":"sir20155024 - 2015 - Hydrologic effects of potential changes in climate, water use, and land cover in the Upper Scioto River Basin, Ohio","interactions":[],"lastModifiedDate":"2015-04-15T08:44:40","indexId":"sir20155024","displayToPublicDate":"2015-04-08T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5024","title":"Hydrologic effects of potential changes in climate, water use, and land cover in the Upper Scioto River Basin, Ohio","docAbstract":"

This report presents the results of a study to provide information on the hydrologic effects of potential 21st-century changes in climate, water use, and land cover in the Upper Scioto River Basin, Ohio (from Circleville, Ohio, to the headwaters). A precipitation-runoff model, calibrated on the basis of historical climate and streamflow data, was used to simulate the effects of climate change on streamflows and reservoir water levels at several locations in the basin. Two levels of simulations were done. The first level of simulation (level 1) accounted only for anticipated 21st-century changes in climate and operations of three City of Columbus upground reservoirs located in northwest Delaware County, Ohio. The second level of simulation (level 2) accounted for development-driven changes in land cover and water use in addition to changes in climate and reservoir operations.

\n

A statistical change-factor approach was used to construct future climate time series that were used in the precipitation-runoff model to compute time series of future streamflows and reservoir water levels. Monthly change factors were computed by determining differences or fractional changes between baseline historical climate time series and future climate time series consisting of outputs from selected global climate models that were included in the World Climate Research Programme’s Coupled Model Intercomparison Project phase 3 (CMIP3). Eight sets of change factors were determined on the basis of outputs from four global climate models, each of which was run under two greenhouse-gas scenarios (the “A1b” and “A2” scenarios from the Intergovernmental Panel on Climate Change’s 4th assessment). The 4 global climate models whose data were used in this study were selected to represent a wide range of potential climate outcomes as compared to the entire range of potential climate outcomes associated with the 16 global climate models represented in the CMIP3 multimodel dataset.

\n

Future land-cover and water-use data were estimated for use in the level-2 precipitation-runoff simulations to account for development-driven changes in land cover and water use. Future land-cover characteristics were estimated for selected future years based on population projections and zoning plans for communities in the basin. Future water-use data for major water suppliers and wastewater-treatment facilities were estimated from current per capita water use, population projections for 2035, and population projections for 2090 assuming full build-out. A statistical change-factor-based approach was used to estimate future water-use characteristics by major water suppliers and wastewater-treatment facilities on the basis of reference-period historical water uses. Annual change factors that were determined for future years other than 2035 and 2090 (when the change factors could be explicitly computed) were estimated by interpolating or extrapolating linearly in time. Water uses by entities other than major water suppliers and wastewater-treatment facilities were assumed to remain unchanged because of uncertainty about if and (or) how they might change.

\n

Results from the level-1 simulations were analyzed primarily to facilitate evaluation of climate-driven temporal changes in annual, seasonal, and monthly streamflow and water-level characteristics, as well as in maximum and minimum 7-, 30-, and 180-day average streamflow and reservoir water levels. Results from the level-2 simulations were analyzed to help evaluate and contrast (relative to level-1 results) the effects of the added development-related factors on maximums and minimum 7-, 30-, and 180-day average streamflows and reservoir water levels and duration characteristics of 7- and 30-day average streamflows and reservoir water levels. Results for 12 stream locations and 5 reservoirs in the Upper Scioto River Basin are presented primarily as a series of plots.

\n

Although it is beyond the scope of this study to address results in detail for each model-output location, selected results are discussed to illustrate potential uses and interpretations of the graph products provided in this report. In addition, general trends and patterns in streamflow and water-level characteristics are identified where possible.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155024","collaboration":"Prepared in cooperation with the Mid-Ohio Regional Planning Commission; the Ohio Water Development Authority; the City of Columbus, Ohio; and Del-Co Water Company","usgsCitation":"Ebner, A.D., Koltun, G., and Ostheimer, C., 2015, Hydrologic effects of potential changes in climate, water use, and land cover in the Upper Scioto River Basin, Ohio: U.S. Geological Survey Scientific Investigations Report 2015-5024, Report: vii, 34 p.; Appendixes A-G; Downloads Directory, https://doi.org/10.3133/sir20155024.","productDescription":"Report: vii, 34 p.; Appendixes A-G; Downloads Directory","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060946","costCenters":[{"id":513,"text":"Ohio Water Science 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quantile."},{"id":299478,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5024/appendix/sir2015-5024_appendixd.pdf","text":"Appendix D","size":"905 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix D","linkHelpText":"Plots of maximum and minimum 7-, 30-, and 180-day average streamflows and water levels as a function of plotting year."},{"id":299481,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5024/appendix/sir2015-5024_appendixg.pdf","text":"Appendix G","size":"226 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix G","linkHelpText":"Plots of simulated level-2 30-day running average streamflows and water levels as a function of exceedance quantile."},{"id":299482,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5024/downloads","text":"Downloads Directory","size":"5.44 MB","description":"Downloads Directory","linkHelpText":"Contains Appendixes A-G ZIP 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Environmental chemicals can disrupt endocrine signaling and adversely impact sexual differentiation in wildlife. Bisphenol A (BPA) is an estrogenic chemical commonly found in a variety of habitats. In this study, we used painted turtles (Chrysemys picta), which have temperature-dependent sex determination (TSD), as an animal model for ontogenetic endocrine disruption by BPA. We hypothesized that BPA would override TSD and disrupt sexual development. We incubated farm-raised turtle eggs at the male-producing temperature (26 °C), randomly assigned individuals to treatment groups: control, vehicle control, 17β-estradiol (E2, 20 ng/g-egg) or 0.01, 1.0, 100 μg BPA/g-egg and harvested tissues at hatch. Typical female gonads were present in 89% of the E2-treated “males”, but in none of the control males (n = 35). Gonads of BPA-exposed turtles had varying amounts of ovarian-like cortical (OLC) tissue and disorganized testicular tubules in the medulla. Although the percentage of males with OLCs increased with BPA dose (BPA-low = 30%, BPA-medium = 33%, BPA-high = 39%), this difference was not significant (p = 0.85). In all three BPA treatments, SOX9 patterns revealed disorganized medullary testicular tubules and β-catenin expression in a thickened cortex. Liver vitellogenin, a female-specific liver protein commonly used as an exposure biomarker, was not induced by any of the treatments. Notably, these results suggest that developmental exposure to BPA disrupts sexual differentiation in painted turtles. Further examination is necessary to determine the underlying mechanisms of sex reversal in reptiles and how these translate to EDC exposure in wild populations.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ygcen.2015.04.003","usgsCitation":"Jandegian, C.M., Deem, S.L., Bhandari, R.K., Holliday, C.M., Nicks, D., Rosenfeld, C.S., Selcer, K., Tillitt, D.E., vom Saal, F.S., Velez, V., Yang, Y., and Holliday, D.K., 2015, Developmental exposure to bisphenol A (BPA) alters sexual differentiation in painted turtles (Chrysemys picta): General and Comparative Endocrinology, v. 216, p. 77-85, https://doi.org/10.1016/j.ygcen.2015.04.003.","productDescription":"9 p.","startPage":"77","endPage":"85","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061239","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":306671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"216","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55cdbfafe4b08400b1fe13e4","contributors":{"authors":[{"text":"Jandegian, Caitlin M. cjandegian@usgs.gov","contributorId":5941,"corporation":false,"usgs":true,"family":"Jandegian","given":"Caitlin","email":"cjandegian@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":567436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deem, Sharon L.","contributorId":139277,"corporation":false,"usgs":false,"family":"Deem","given":"Sharon","email":"","middleInitial":"L.","affiliations":[{"id":12719,"text":"Whitney R. 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The increased integration of ecosystem service concepts into natural resource management places renewed emphasis on prediction and mapping of fish biomass as a major provisioning service of rivers. The goals of this study were to predict and map patterns of fish biomass as a proxy for the availability of catchable fish for anglers in rivers and to identify the strongest landscape constraints on fish productivity. We examined hypotheses about fish responses to total phosphorus (TP), as TP is a growth-limiting nutrient known to cause increases (subsidy response) and/or decreases (stress response) in fish biomass depending on its concentration and the species being considered. Boosted regression trees were used to define nonlinear functions that predicted the standing crops of Brook Trout Salvelinus fontinalis, Brown Trout Salmo trutta, Smallmouth Bass Micropterus dolomieu, panfishes (seven centrarchid species), and Walleye Sander vitreus by using landscape and modeled local-scale predictors. Fitted models were highly significant and explained 22–56% of the variation in validation data sets. Nonlinear and threshold responses were apparent for numerous predictors, including TP concentration, which had significant effects on all except the Walleye fishery. Brook Trout and Smallmouth Bass exhibited both subsidy and stress responses, panfish biomass exhibited a subsidy response only, and Brown Trout exhibited a stress response. Maps of reach-specific standing crop predictions showed patterns of predicted fish biomass that corresponded to spatial patterns in catchment area, water temperature, land cover, and nutrient availability. Maps illustrated predictions of higher trout biomass in coldwater streams draining glacial till in northern Michigan, higher Smallmouth Bass and panfish biomasses in warmwater systems of southern Michigan, and high Walleye biomass in large main-stem rivers throughout the state. Our results allow fisheries managers to examine the biomass potential of streams, describe geographic patterns of fisheries, explore possible nutrient management targets, and identify habitats that are candidates for species management.

","language":"English","publisher":"American Fisheries Society","publisherLocation":"Lawrence, KS","doi":"10.1080/02755947.2014.987887","usgsCitation":"Esselman, P.C., Stevenson, R.J., Lupi, F., Riseng, C.M., and Wiley, M., 2015, Landscape prediction and mapping of game fish biomass, an ecosystem service of Michigan rivers: North American Journal of Fisheries Management, v. 35, no. 2, p. 302-320, https://doi.org/10.1080/02755947.2014.987887.","productDescription":"19 p.","startPage":"302","endPage":"320","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057022","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":472157,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Landscape_Prediction_and_Mapping_of_Game_Fish_Biomass_an_Ecosystem_Service_of_Michigan_Rivers/1378927","text":"External Repository"},{"id":306583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.3515625,\n 46.604167162931844\n ],\n [\n -90.087890625,\n 46.45299704748289\n ],\n [\n -89.9560546875,\n 46.30140615437332\n ],\n [\n -88.79150390625,\n 46.042735653846506\n ],\n [\n -88.30810546875,\n 45.98169518512228\n ],\n [\n -88.00048828124999,\n 45.73685954736049\n ],\n [\n -87.64892578125,\n 45.166547157856016\n ],\n [\n -87.099609375,\n 45.67548217560647\n ],\n [\n -86.68212890625,\n 45.62940492064501\n ],\n [\n -85.7373046875,\n 45.935870621190546\n ],\n [\n -85.14404296875,\n 45.98169518512228\n ],\n [\n -84.9462890625,\n 45.84410779560204\n ],\n [\n -85.1220703125,\n 45.61403741135093\n ],\n [\n -85.517578125,\n 45.22848059584359\n ],\n [\n -86.28662109375,\n 44.68427737181225\n ],\n [\n -86.572265625,\n 43.77109381775651\n ],\n [\n -86.24267578125,\n 42.924251753870685\n ],\n [\n -86.37451171875,\n 42.342305278572816\n ],\n [\n -86.77001953125,\n 41.934976500546604\n ],\n [\n -86.7919921875,\n 41.80407814427237\n ],\n [\n -83.34228515625,\n 41.705728515237524\n ],\n [\n -83.056640625,\n 42.147114459220994\n ],\n [\n -82.81494140625,\n 42.48830197960227\n ],\n [\n -82.4853515625,\n 42.827638636242284\n ],\n [\n -82.44140625,\n 43.11702412135048\n ],\n [\n -82.59521484375,\n 43.78695837311561\n ],\n [\n -82.79296874999999,\n 44.05601169578525\n ],\n [\n -83.25439453125,\n 44.43377984606825\n ],\n [\n -83.27636718749999,\n 44.85586880735725\n ],\n [\n -83.38623046875,\n 45.321254361171476\n ],\n [\n -84.26513671875,\n 45.73685954736049\n ],\n [\n -84.0234375,\n 45.90529985724796\n ],\n [\n -83.6279296875,\n 46.08847179577592\n ],\n [\n -84.13330078125,\n 46.46813299215554\n ],\n [\n -84.79248046875,\n 46.81509864599243\n ],\n [\n -86.1328125,\n 46.73986059969267\n ],\n [\n -87.12158203125,\n 46.619261036171515\n ],\n [\n -87.6708984375,\n 46.90524554642923\n ],\n [\n -88.0224609375,\n 47.11499982620772\n ],\n [\n -87.5390625,\n 47.428087261714275\n ],\n [\n -88.2861328125,\n 47.56170075451973\n ],\n [\n -89.18701171875,\n 47.15984001304432\n ],\n [\n -90.3515625,\n 46.604167162931844\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-07","publicationStatus":"PW","scienceBaseUri":"55cb1caee4b08400b1fdd477","contributors":{"authors":[{"text":"Esselman, Peter C. 0000-0002-0085-903X pesselman@usgs.gov","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":5965,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter","email":"pesselman@usgs.gov","middleInitial":"C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":540045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stevenson, R. 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During 2005-8, the U.S. Geological Survey, in cooperation with the Cambridge, Massachusetts, Water Department, measured concentrations of sodium and chloride, plant nutrients, commonly used pesticides, and caffeine in base-flow and stormwater samples collected from 11 tributaries in the Cambridge drinking-water source area. These data were used to characterize current water-quality conditions, to establish a baseline for future comparisons, and to describe trends in surface-water quality. The data also were used to assess the effects of watershed characteristics on surface-water quality and to inform future watershed management.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153030","collaboration":"Prepared in cooperation with the Cambridge, Massachusetts, Water Department","usgsCitation":"Smith, K.P., and Waldron, M.C., 2015, Water quality in the Cambridge, Massachusetts, drinking-water source area, 2005-8: U.S. Geological Survey Fact Sheet 2015-3030, 6 p., https://doi.org/10.3133/fs20153030.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2005-01-01","temporalEnd":"2008-12-31","ipdsId":"IP-046036","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":299465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153030.jpg"},{"id":299464,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3030/pdf/fs2015-3030.pdf","text":"Report","size":"1.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3030 Report"},{"id":299463,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3030/"}],"country":"United States","state":"Massachusetts","city":"Cambridge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.06420516967773,\n 42.38504955243599\n ],\n [\n -71.15741729736328,\n 42.39531906359705\n ],\n [\n -71.23191833496094,\n 42.42700448967684\n ],\n [\n -71.24839782714844,\n 42.45411449876218\n ],\n [\n -71.2957763671875,\n 42.456647545121605\n ],\n [\n -71.33663177490234,\n 42.44296787761998\n ],\n [\n -71.33251190185545,\n 42.36133451106724\n ],\n [\n -71.26556396484375,\n 42.34154398944032\n ],\n [\n -71.06403350830078,\n 42.348648996207956\n ],\n [\n -71.06420516967773,\n 42.38504955243599\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5524f19fe4b027f0aee3d461","contributors":{"authors":[{"text":"Smith, Kirk P. 0000-0003-0269-474X kpsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-474X","contributorId":1516,"corporation":false,"usgs":true,"family":"Smith","given":"Kirk","email":"kpsmith@usgs.gov","middleInitial":"P.","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":543281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waldron, Marcus C. mwaldron@usgs.gov","contributorId":1867,"corporation":false,"usgs":true,"family":"Waldron","given":"Marcus","email":"mwaldron@usgs.gov","middleInitial":"C.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":543282,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70144440,"text":"fs20153033 - 2015 - The Ebola virus disease outbreak and the mineral sectors of Guinea, Liberia, and Sierra Leone","interactions":[],"lastModifiedDate":"2015-04-08T08:41:42","indexId":"fs20153033","displayToPublicDate":"2015-04-07T14:00:00","publicationYear":"2015","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":"2015-3033","title":"The Ebola virus disease outbreak and the mineral sectors of Guinea, Liberia, and Sierra Leone","docAbstract":"

The mineral sector plays a key role in the economies of Guinea, Liberia, and Sierra Leone. The onset of the Ebola virus disease (EVD) outbreak in early 2014, together with changes in mineral market conditions, raised questions regarding the status of mining operations and of mineral development and exploration projects in all three countries. Mineral projects were the underpinnings of World Bank short-term forecasts of increases in gross domestic product (GDP) for all three countries and were expected to be the basis of future economic growth. The significant delay or cancellation of these projects could result in a major economic setback for all three countries.

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In response to the uncertainty surrounding the status of mineral projects in Guinea, Liberia, and Sierra Leone, the National Minerals Information Center compiled information on the distribution of mines, mineral facilities, and mineral projects under development in the three countries. This fact sheet provides information on the role that the mineral sector plays in their respective economies, on the operating status of mining projects through yearend 2014, and on the coordinated actions by mining companies to support governments and international relief organizations in their efforts to contain the EVD outbreak.

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(v1.15)","interactions":[],"lastModifiedDate":"2017-10-12T20:04:28","indexId":"70145259","displayToPublicDate":"2015-04-07T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1818,"text":"Geoscientific Model Development","active":true,"publicationSubtype":{"id":10}},"title":"RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.15)","docAbstract":"

The Rainfall-Response Aquifer and Watershed Flow Model (RRAWFLOW) is a lumped-parameter model that simulates streamflow, spring flow, groundwater level, or solute transport for a measurement point in response to a system input of precipitation, recharge, or solute injection. I introduce the first version of RRAWFLOW available for download and public use and describe additional options. The open-source code is written in the R language and is available at http://sd.water.usgs.gov/projects/RRAWFLOW/RRAWFLOW.html along with an example model of streamflow. RRAWFLOW includes a time-series process to estimate recharge from precipitation and simulates the response to recharge by convolution, i.e., the unit-hydrograph approach. Gamma functions are used for estimation of parametric impulse-response functions (IRFs); a combination of two gamma functions results in a double-peaked IRF. A spline fit to a set of control points is introduced as a new method for estimation of nonparametric IRFs. Several options are included to simulate time-variant systems. For many applications, lumped models simulate the system response with equal accuracy to that of distributed models, but moreover, the ease of model construction and calibration of lumped models makes them a good choice for many applications (e.g., estimating missing periods in a hydrologic record). RRAWFLOW provides professional hydrologists and students with an accessible and versatile tool for lumped-parameter modeling.

","language":"English","publisher":"European Geosciences Union","publisherLocation":"Katlenburg-Lindau, Germany","doi":"10.5194/gmd-8-865-2015","usgsCitation":"Long, A.J., 2015, RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.15): Geoscientific Model Development, v. 8, p. 865-880, https://doi.org/10.5194/gmd-8-865-2015.","productDescription":"16 p.","startPage":"865","endPage":"880","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056483","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":472158,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-8-865-2015","text":"Publisher Index Page"},{"id":299446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-30","publicationStatus":"PW","scienceBaseUri":"5524f19ce4b027f0aee3d45d","contributors":{"authors":[{"text":"Long, Andrew J. 0000-0001-7385-8081 ajlong@usgs.gov","orcid":"https://orcid.org/0000-0001-7385-8081","contributorId":989,"corporation":false,"usgs":true,"family":"Long","given":"Andrew","email":"ajlong@usgs.gov","middleInitial":"J.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544130,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70140114,"text":"sir20155017 - 2015 - Physical subdivision and description of the water-bearing sediments of the Santa Clara Valley, California","interactions":[],"lastModifiedDate":"2015-04-07T08:39:02","indexId":"sir20155017","displayToPublicDate":"2015-04-07T09:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5017","title":"Physical subdivision and description of the water-bearing sediments of the Santa Clara Valley, California","docAbstract":"

A thick Quaternary alluvial section fills a sedimentary basin beneath the Santa Clara Valley, California, located within the San Andreas Fault system at the south end of San Francisco Bay. This section consists of an upper sequence about 1,000 feet thick containing eight sedimentary cycles and a lower fine-grained unit as thick as several hundred feet. Together these constitute the Quaternary Santa Clara Basin. The section overlies an irregular unconformity with more than 1,200 feet of relief cut into the underlying bedrock. This stratigraphy is determined through study of new wells and seismic reflection profiles, together with a sample of the many thousands of water wells in the valley. It represents a major change and improvement in understanding of the basin, particularly with regard to the upper cyclic sequence, which forms a large groundwater system that is an important resource in the San Francisco Bay region.

\n

Each of the eight sedimentary cycles consists of a coarse-grained bottom interval overlain by a fine-grained top, with the coarse bottom forming a permeable sheet that is more or less continuous around the basin and the fine top forming a similarly extensive, relatively impermeable confining layer. This stratigraphic organization contrasts with most previous views, which have considered the coarse sediment in the basin to occur as scattered, discrete lenses and (or) sinuous channel sands, all embedded in a predominantly fine-grained section. Temperature logs in several wells demonstrate that the fine cycle tops do limit vertical movement of groundwater, although this may not be the case where those tops are thin to perhaps locally absent around parts of the basin margin.

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Age control has been obtained from previous work, in which the sedimentary cycles were correlated with the marine oxygen isotope record and the ages of two deeper Quaternary unconformities were estimated, and from detailed paleomagnetic study of cores from the new wells by E.A. Mankinen. Despite careful search of the cores, very few fossils were found, and none that are helpful in subdividing the section. No tephra (volcanic ash) was recovered, and the few carbon samples found and dated radiometrically are limited to the upper 120 feet of the section. The upper cyclic section ranges in age from 0 to somewhat older than 718 thousand years (ka), and the lower fine-grained section lies between unconformities with estimated ages of 950 and 1500 ka.

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Reflections in the seismic profiles indicate that layering in the basin is subparallel to the ground surface, and this fact, together with the continuous stratigraphic detail provided by geophysical logs of the new wells, allows the confident interwell correlation required to delineate the sedimentary cycles. The sequence of layers within any one cycle tends to persist laterally between the wells in the dataset, which are spaced 1 to 3 km apart, with most changes occurring gradually. The eight cycles, in contrast, tend to differ from each other in the details of their internal organization.

\n

Maps and cross sections show the elevations of cycle boundaries and the underlying bedrock surface, the varying thicknesses of the cycles and of their fine tops and coarse bottoms, and the aggregate thickness of coarse layers in those bottom intervals. Coarse sediment is more abundant toward some parts of the basin margin and in the southern part of the basin. Cycle boundary surfaces are relatively smooth, and their shapes are consistent with having been intercycle topographic surfaces. The underlying bedrock surface has a relief of more than 1,200 feet and deepens toward the center of the basin and the west edge of the fault-bounded Evergreen Basin, which is concealed beneath the east side of the Quaternary basin. The absence of consistent abrupt changes in thicknesses or boundary elevations across the basin or in cross section indicates that the interior of the basin is largely unfaulted, with the Silver Creek strand of the San Andreas system at the west edge of the Evergreen Basin being the sole exception. The east and west margins of the Santa Clara Basin, in contrast, are marked by reverse and thrust fault systems.

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These remotely sensed, geographically referenced elevation measurements of light detection and ranging (lidar)-derived seamless (bare-earth and submerged) topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida.

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This project provides datasets acquired on August 7 and 8, 2012, for a portion of the Chandeleur Islands, Louisiana. An innovative airborne lidar system, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometers) lidar designed to map nearshore bathymetry, topography, and vegetation structure simultaneously.

\n

For more information about similar projects, please visit the Lidar for Science and Resource Management Web site.

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