Applications have been filed for several water-right changes and new water rights, with total withdrawals of about 1,800 acre-feet per year, in Snake Valley near Eskdale and Partoun, Utah. The Bureau of Land Management has identified 11 sites where the Bureau of Land Management holds water rights and 7 other springs of interest that could be affected by these proposed groundwater withdrawals. This report presents a hydrogeologic analysis of areas within Snake Valley to assess the potential effects on Bureau of Land Management water rights and other springs of interest resulting from existing and proposed groundwater withdrawals. A previously developed numerical groundwater-flow model was used to quantify potential groundwater drawdown and the capture, or groundwater withdrawals that results in depletion, of natural discharge resulting from existing and proposed groundwater withdrawals within Snake Valley. Existing groundwater withdrawals were simulated for a 50-year period prior to adding the newly proposed withdrawals to bring the model from pre-development conditions to the start of 2014. After this initial 50-year period, existing withdrawals, additional proposed withdrawals, and consequent effects were simulated for periods of 5, 10, 25, 50, and 100 years.
\nDownward trends in water levels measured in wells indicate that the existing groundwater withdrawals in Snake Valley are affecting water levels. The numerical model simulated similar downward trends in water levels. The largest simulated drawdowns caused by existing groundwater withdrawals ranged between 10 and 26 feet and were near the centers of the agricultural areas by Callao, Eskdale, Baker, Garrison, and along the Utah-Nevada state line in southern Snake Valley. The largest simulated water-level declines were at the Bureau of Land Management water-rights sites near Eskdale, Utah, where simulated drawdowns ranged between 2 and 8 feet at the start of 2014. These results were consistent with, but lower than, observations from several wells monitored by the U.S. Geological Survey that indicated water-level declines of 6 to 18 feet near the Eskdale area since the mid-1970s and 1980s. The model cells where the simulated capture of natural groundwater discharge resulting from the existing withdrawals was greatest were those containing Kane Spring, Caine Spring, and Unnamed Spring 5, where existing groundwater withdrawals capture 13 to 29 percent of the total simulated natural discharge in these cells.
\nSimulated drawdown and simulated capture of natural groundwater discharge resulting from the proposed withdrawals started in as few as 5 years at seven of the sites. After 100 years, four sites showed simulated drawdowns ranging between 1 and 2 feet; eight sites showed simulated drawdowns ranging between 0.1 and 0.9 feet; and five sites showed no simulated drawdown resulting from the proposed withdrawals. The largest amounts of simulated capture of natural groundwater discharge resulting from the proposed withdrawals after 100 years were in the model cells containing Coyote Spring, Kane Spring, and Caine Spring, which had capture amounts ranging between 5.5 and 9.1 percent of the total simulated natural discharge in these cells.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141176","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Masbruch, M.D., and Gardner, P.M., 2014, Potential effects of existing and proposed groundwater withdrawals on water levels and natural groundwater discharge in Snake Valley, Juab and Millard Counties, Utah, White Pine County, Nevada, and surrounding areas in Utah and Nevada: U.S. Geological Survey Open-File Report 2014-1176, Report: vi, 24 p.; Appendix Tables, https://doi.org/10.3133/ofr20141176.","productDescription":"Report: vi, 24 p.; Appendix Tables","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-055285","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":295072,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1176/pdf/ofr2014-1176.pdf"},{"id":295073,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1176/downloads/ofr2014-1176_appendixes.xlsx"},{"id":295074,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141176.jpg"},{"id":295071,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1176/"}],"projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Nevada, Utah","county":"Juab County, Millard County, White Pine County","otherGeospatial":"Snake Valley","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5434f289e4b0a4f4b46a2364","contributors":{"authors":[{"text":"Masbruch, Melissa D. 0000-0001-6568-160X mmasbruch@usgs.gov","orcid":"https://orcid.org/0000-0001-6568-160X","contributorId":1902,"corporation":false,"usgs":true,"family":"Masbruch","given":"Melissa","email":"mmasbruch@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498963,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Philip M. 0000-0003-3005-3587 pgardner@usgs.gov","orcid":"https://orcid.org/0000-0003-3005-3587","contributorId":962,"corporation":false,"usgs":true,"family":"Gardner","given":"Philip","email":"pgardner@usgs.gov","middleInitial":"M.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498962,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70124024,"text":"ofr20141197 - 2014 - An evaluation of remote sensing technologies for the detection of residual contamination at ready-for-anticipated use sites","interactions":[],"lastModifiedDate":"2014-10-07T12:55:39","indexId":"ofr20141197","displayToPublicDate":"2014-10-07T12:46:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1197","title":"An evaluation of remote sensing technologies for the detection of residual contamination at ready-for-anticipated use sites","docAbstract":"Operational problems with site access and information, XRF instrument operation, and imagery collections hampered the effective data collection and analysis process. Of the 24 sites imaged and analyzed, 17 appeared to be relatively clean with no discernible metal contamination, hydrocarbons, or asbestos in the soil. None of the samples for the sites in Louisiana had any result exceeding the appropriate industrial or residential standard for arsenic or lead. One site in South Carolina (North Street Dump) had two samples that exceeded the residential standard for lead. One site in Texas (Cadiz Street), and four sites in Florida (210 North 12th Street, Encore Retail Site, Clearwater Auto, and 22nd Street Mixed Use) were found to have some level of residual metal contamination above the applicable residential or commercial Risk-Based Concentration (RBC) standard. Three of the Florida sites showing metal contamination also showed a pattern of vegetation stress based on standard vegetation analysis techniques.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141197","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Slonecker, E., and Fisher, G.B., 2014, An evaluation of remote sensing technologies for the detection of residual contamination at ready-for-anticipated use sites: U.S. Geological Survey Open-File Report 2014-1197, v, 25 p., https://doi.org/10.3133/ofr20141197.","productDescription":"v, 25 p.","numberOfPages":"31","onlineOnly":"Y","ipdsId":"IP-057068","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":295017,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141197.jpg"},{"id":295015,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1197/"},{"id":295016,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1197/pdf/of2014-1197.pdf"}],"country":"United States","state":"Florida, Louisiana, South Carolina, Texas","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5434f285e4b0a4f4b46a2358","contributors":{"authors":[{"text":"Slonecker, E. Terrence","contributorId":20677,"corporation":false,"usgs":true,"family":"Slonecker","given":"E. Terrence","affiliations":[],"preferred":false,"id":500567,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisher, Gary B. gfisher@usgs.gov","contributorId":3034,"corporation":false,"usgs":true,"family":"Fisher","given":"Gary","email":"gfisher@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":true,"id":500566,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70126192,"text":"sir20145161 - 2014 - Potential postwildfire debris-flow hazards: a prewildfire evaluation for the Sandia and Manzano Mountains and surrounding areas, central New Mexico","interactions":[],"lastModifiedDate":"2014-10-07T12:41:49","indexId":"sir20145161","displayToPublicDate":"2014-10-07T12:34:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5161","title":"Potential postwildfire debris-flow hazards: a prewildfire evaluation for the Sandia and Manzano Mountains and surrounding areas, central New Mexico","docAbstract":"Wildfire can drastically increase the probability of debris flows, a potentially hazardous and destructive form of mass wasting, in landscapes that have otherwise been stable throughout recent history. Although there is no way to know the exact location, extent, and severity of wildfire, or the subsequent rainfall intensity and duration before it happens, probabilities of fire and debris-flow occurrence for different locations can be estimated with geospatial analysis and modeling efforts. The purpose of this report is to provide information on which watersheds might constitute the most serious, potential, debris-flow hazards in the event of a large-scale wildfire and subsequent rainfall in the Sandia and Manzano Mountains. Potential probabilities and estimated volumes of postwildfire debris flows in the unburned Sandia and Manzano Mountains and surrounding areas were estimated using empirical debris-flow models developed by the U.S. Geological Survey in combination with fire behavior and burn probability models developed by the U.S. Department of Agriculture Forest Service.
\nThe locations of the greatest debris-flow hazards correlate with the areas of steepest slopes and simulated crown-fire behavior. The four subbasins with the highest computed debris-flow probabilities (greater than 98 percent) were all in the Manzano Mountains, two flowing east and two flowing west. Volumes in sixteen subbasins were greater than 50,000 square meters and most of these were in the central Manzanos and the western facing slopes of the Sandias.
\nFive subbasins on the west-facing slopes of the Sandia Mountains, four of which have downstream reaches that lead into the outskirts of the City of Albuquerque, are among subbasins in the 98th percentile of integrated relative debris-flow hazard rankings. The bulk of the remaining subbasins in the 98th percentile of integrated relative debris-flow hazard rankings are located along the highest and steepest slopes of the Manzano Mountains. One of the subbasins is several miles upstream from the community of Tajique and another is several miles upstream from the community of Manzano, both on the eastern slopes of the Manzano Mountains.
\nThis prewildfire assessment approach is valuable to resource managers because the analysis of the debris-flow threat is made before a wildfire occurs, which facilitates prewildfire management, planning, and mitigation. In northern New Mexico, widespread watershed restoration efforts are being carried out to safeguard vital watersheds against the threat of catastrophic wildfire. This study was initiated to help select ideal locations for the restoration efforts that could have the best return on investment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145161","collaboration":"Prepared in cooperation with the Bernalillo County Natural Resources Services","usgsCitation":"Tillery, A.C., Haas, J., Miller, L.W., Scott, J.H., and Thompson, M.P., 2014, Potential postwildfire debris-flow hazards: a prewildfire evaluation for the Sandia and Manzano Mountains and surrounding areas, central New Mexico: U.S. Geological Survey Scientific Investigations Report 2014-5161, Report: v, 24 p.; Downloads Directory; Readme, https://doi.org/10.3133/sir20145161.","productDescription":"Report: v, 24 p.; Downloads Directory; Readme","numberOfPages":"34","onlineOnly":"N","ipdsId":"IP-056106","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":295009,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5161/pdf/sir2014-5161.pdf"},{"id":295010,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5161/downloads/"},{"id":295011,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2014/5161/downloads/README.TXT"},{"id":295007,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5161/"},{"id":295012,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145161.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Manzano Mountains, Sandia Mountains","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5434f28ae4b0a4f4b46a2366","contributors":{"authors":[{"text":"Tillery, Anne C. 0000-0002-9508-7908 atillery@usgs.gov","orcid":"https://orcid.org/0000-0002-9508-7908","contributorId":2549,"corporation":false,"usgs":true,"family":"Tillery","given":"Anne","email":"atillery@usgs.gov","middleInitial":"C.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":501894,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haas, Jessica R.","contributorId":10735,"corporation":false,"usgs":true,"family":"Haas","given":"Jessica R.","affiliations":[],"preferred":false,"id":501896,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Lara W.","contributorId":104833,"corporation":false,"usgs":true,"family":"Miller","given":"Lara","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":501898,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scott, Joe H.","contributorId":28913,"corporation":false,"usgs":true,"family":"Scott","given":"Joe","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":501897,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Matthew P.","contributorId":9190,"corporation":false,"usgs":true,"family":"Thompson","given":"Matthew","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":501895,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70093880,"text":"70093880 - 2014 - Potassium-argon (argon-argon), structural fabrics","interactions":[],"lastModifiedDate":"2014-10-09T08:59:33","indexId":"70093880","displayToPublicDate":"2014-10-07T11:14:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Potassium-argon (argon-argon), structural fabrics","docAbstract":"Definition: 40Ar/39Ar geochronology of structural fabrics: The application of 40Ar/39Ar methods to date development of structural fabrics in geologic samples.
\nIntroduction: \nStructural fabrics develop during rock deformation at variable pressures (P), temperatures (T), fluid compositions (X), and time (t). Structural fabrics are represented in rocks by features such as foliations and shear zones developed at the mm to km scale. In ideal cases, the P-T-X history of a given structural fabric can be constrained using stable isotope, cation exchange, and/or mineral equilibria thermobarometry (Essene 1989). The timing of structural fabric development can be assessed qualitatively using geologic field observations or quantitatively using isotope-based geochronology. High-precision geochronology of the thermal and fluid flow histories associated with structural fabric development can answer fundamental geologic questions including (1) when hydrothermal fluids transported and deposited ore minerals, ...
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of scientific dating methods","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Springer","doi":"10.1007/978-94-007-6326-5_124-1","usgsCitation":"Cosca, M.A., 2014, Potassium-argon (argon-argon), structural fabrics, chap. of Encyclopedia of scientific dating methods, p. 1-8, https://doi.org/10.1007/978-94-007-6326-5_124-1.","productDescription":"8 p.","startPage":"1","endPage":"8","numberOfPages":"8","ipdsId":"IP-052784","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":294993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294991,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/978-94-007-6326-5_124-1"}],"noUsgsAuthors":false,"publicationDate":"2014-01-08","publicationStatus":"PW","scienceBaseUri":"5434f287e4b0a4f4b46a2362","contributors":{"editors":[{"text":"Rink, W. Jack","contributorId":113377,"corporation":false,"usgs":true,"family":"Rink","given":"W.","email":"","middleInitial":"Jack","affiliations":[],"preferred":false,"id":509797,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Thompson, Jereon","contributorId":112977,"corporation":false,"usgs":true,"family":"Thompson","given":"Jereon","email":"","affiliations":[],"preferred":false,"id":509796,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Cosca, Michael A. 0000-0002-0600-7663 mcosca@usgs.gov","orcid":"https://orcid.org/0000-0002-0600-7663","contributorId":1000,"corporation":false,"usgs":true,"family":"Cosca","given":"Michael","email":"mcosca@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":490236,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70127378,"text":"70127378 - 2014 - Mountain pine beetle-caused mortality over eight years in two pine hosts in mixed conifer stands of the southern Rocky Mountains","interactions":[],"lastModifiedDate":"2014-10-07T10:35:10","indexId":"70127378","displayToPublicDate":"2014-10-07T10:31:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Mountain pine beetle-caused mortality over eight years in two pine hosts in mixed conifer stands of the southern Rocky Mountains","docAbstract":"Eruptive mountain pine beetle (Dendroctonus ponderosae, MPB) populations have caused widespread mortality of pines throughout western North America since the late 1990s. Early work by A.D. Hopkins suggested that when alternate host species are available, MPB will prefer to breed in the host to which it has become adapted. In Colorado, epidemic MPB populations that originated in lodgepole pine expanded into mixed-conifer stands containing ponderosa pine, a related host. We evaluated the susceptibility of both hosts to successful MPB colonization in a survey of 19 sites in pine-dominated mixed-conifer stands spanning 140 km of the Front Range, CO, USA. In each of three 0.2-ha plots at each site, we (1) assessed trees in the annual flights of 2008–2011 to compare MPB-caused mortality between lodgepole and ponderosa pine; (2) recorded previous MPB-caused tree mortality from 2004–2007 to establish baseline mortality levels; and (3) measured characteristics of the stands (e.g. tree basal area) and sites (e.g. elevation, aspect) that might be correlated with MPB colonization. Uninfested average live basal area of lodgepole and ponderosa pine was 74% of total basal area before 2004. We found that for both species, annual percent basal area of attacked trees was greatest in one year (2009), and was lower in all other years (2004–2007, 2008, 2010, and 2011). Both pine species had similar average total mortality of 38–39% by 2011. Significant predictors of ponderosa pine mortality in a given year were basal area of uninfested ponderosa pine and the previous year’s mortality levels in both ponderosa and lodgepole pine. Lodgepole pine mortality was predicted by uninfested basal areas of both lodgepole and ponderosa pine, and the previous year’s lodgepole pine mortality. These results indicate host selection by MPB from lodgepole pine natal hosts into ponderosa pine the following year, but not the reverse. In both species, diameters of attacked trees within each year were similar, and were progressively smaller the last four years of the study period. Our results suggest that, in contrast to previous reports, ponderosa and lodgepole pine were equally susceptible to MPB infestation in the CO Front Range during our study period. This suggests that forest managers may anticipate similar impacts in both hosts during similar environmental conditions when epidemic-level MPB populations are active in mixed-pine stands.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Forest Ecology and Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2014.09.012","usgsCitation":"West, D., Briggs, J.S., Jacobi, W., and Negron, J.F., 2014, Mountain pine beetle-caused mortality over eight years in two pine hosts in mixed conifer stands of the southern Rocky Mountains: Forest Ecology and Management, v. 334, no. 15, p. 321-330, https://doi.org/10.1016/j.foreco.2014.09.012.","productDescription":"10 p.","startPage":"321","endPage":"330","ipdsId":"IP-057980","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":294986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294985,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.foreco.2014.09.012"}],"country":"United States","state":"Colorado","otherGeospatial":"Front Range","volume":"334","issue":"15","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5434f286e4b0a4f4b46a2360","contributors":{"authors":[{"text":"West, Daniel R.","contributorId":36875,"corporation":false,"usgs":true,"family":"West","given":"Daniel R.","affiliations":[],"preferred":false,"id":502320,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Jennifer S.","contributorId":106035,"corporation":false,"usgs":true,"family":"Briggs","given":"Jennifer","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":502321,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jacobi, William R.","contributorId":8016,"corporation":false,"usgs":true,"family":"Jacobi","given":"William R.","affiliations":[],"preferred":false,"id":502318,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Negron, Jose F.","contributorId":10734,"corporation":false,"usgs":true,"family":"Negron","given":"Jose","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":502319,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70100139,"text":"70100139 - 2014 - Comparing species distribution models constructed with different subsets of environmental predictors","interactions":[],"lastModifiedDate":"2014-12-12T15:00:28","indexId":"70100139","displayToPublicDate":"2014-10-07T09:33:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Comparing species distribution models constructed with different subsets of environmental predictors","docAbstract":"Aim
\nTo assess the usefulness of combining climate predictors with additional types of environmental predictors in species distribution models for range-restricted species, using common correlative species distribution modelling approaches.
\n\n
Location
\nFlorida, USA
\n\n
Methods
\nWe used five different algorithms to create distribution models for 14 vertebrate species, using seven different predictor sets: two with bioclimate predictors only, and five ‘combination’ models using bioclimate predictors plus ‘additional’ predictors from groups representing: human influence, land cover, extreme weather or noise (spatially random data).We use a linear mixed-model approach to analyse the effects of predictor set and algorithm on model accuracy, variable importance scores and spatial predictions.
\n\n
Results
\nRegardless of modelling algorithm, no one predictor set produced significantly more accurate models than all others, though models including human influence predictors were the only ones with significantly higher accuracy than climate-only models. Climate predictors had consistently higher variable importance scores than additional predictors in combination models, though there was variation related to predictor type and algorithm. While spatial predictions varied moderately between predictor sets, discrepancies were significantly greater between modelling algorithms than between predictor sets. Furthermore, there were no differences in the level of agreement between binary ‘presence–absence’ maps and independent species range maps related to the predictor set used.
\n\n
Main conclusions
\nOur results indicate that additional predictors have relatively minor effects on the accuracy of climate-based species distribution models and minor to moderate effects on spatial predictions. We suggest that implementing species distribution models with only climate predictors may provide an effective and efficient approach for initial assessments of environmental suitability.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Diversity and Distributions","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/ddi.12247","usgsCitation":"Bucklin, D., Basille, M., Benscoter, A.M., Brandt, L., Mazzotti, F., Romañach, S., Speroterra, C., and Watling, J.I., 2014, Comparing species distribution models constructed with different subsets of environmental predictors: Diversity and Distributions, v. 21, no. 1, p. 23-35, https://doi.org/10.1111/ddi.12247.","productDescription":"13 p.","startPage":"23","endPage":"35","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051786","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":294979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294978,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/ddi.12247"}],"country":"United States","state":"Florida","volume":"21","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-08-21","publicationStatus":"PW","scienceBaseUri":"5434f285e4b0a4f4b46a235a","chorus":{"doi":"10.1111/ddi.12247","url":"http://dx.doi.org/10.1111/ddi.12247","publisher":"Wiley-Blackwell","authors":"Bucklin David N., Basille Mathieu, Benscoter Allison M., Brandt Laura A., Mazzotti Frank J., Romañach Stephanie S., Speroterra Carolina, Watling James I.","journalName":"Diversity and Distributions","publicationDate":"8/21/2014","auditedOn":"11/1/2014"},"contributors":{"authors":[{"text":"Bucklin, David N.","contributorId":58963,"corporation":false,"usgs":true,"family":"Bucklin","given":"David N.","affiliations":[],"preferred":false,"id":492121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Basille, Mathieu","contributorId":33246,"corporation":false,"usgs":true,"family":"Basille","given":"Mathieu","affiliations":[],"preferred":false,"id":492118,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Benscoter, Allison M.","contributorId":57781,"corporation":false,"usgs":true,"family":"Benscoter","given":"Allison","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":492120,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brandt, Laura A.","contributorId":23089,"corporation":false,"usgs":true,"family":"Brandt","given":"Laura A.","affiliations":[],"preferred":false,"id":492117,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mazzotti, Frank J.","contributorId":90236,"corporation":false,"usgs":true,"family":"Mazzotti","given":"Frank J.","affiliations":[],"preferred":false,"id":492122,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Romañach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":2331,"corporation":false,"usgs":true,"family":"Romañach","given":"Stephanie S.","email":"sromanach@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":492115,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Speroterra, Carolina","contributorId":34451,"corporation":false,"usgs":true,"family":"Speroterra","given":"Carolina","affiliations":[],"preferred":false,"id":492119,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Watling, James I.","contributorId":10352,"corporation":false,"usgs":true,"family":"Watling","given":"James","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":492116,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70119019,"text":"sir20145148 - 2014 - Documentation of a groundwater flow model (SJRRPGW) for the San Joaquin River Restoration Program study area, California","interactions":[],"lastModifiedDate":"2018-06-08T13:30:42","indexId":"sir20145148","displayToPublicDate":"2014-10-07T08:44:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5148","title":"Documentation of a groundwater flow model (SJRRPGW) for the San Joaquin River Restoration Program study area, California","docAbstract":"To better understand the potential effects of restoration flows on existing drainage problems, anticipated as a result of the San Joaquin River Restoration Program (SJRRP), the U.S. Geological Survey (USGS), in cooperation with the U.S. Bureau of Reclamation (Reclamation), developed a groundwater flow model (SJRRPGW) of the SJRRP study area that is within 5 miles of the San Joaquin River and adjacent bypass system from Friant Dam to the Merced River. The primary goal of the SJRRP is to reestablish the natural ecology of the river to a degree that restores salmon and other fish populations. Increased flows in the river, particularly during the spring salmon run, are a key component of the restoration effort. A potential consequence of these increased river flows is the exacerbation of existing irrigation drainage problems along a section of the river between Mendota and the confluence with the Merced River. Historically, this reach typically was underlain by a water table within 10 feet of the land surface, thus requiring careful irrigation management and (or) artificial drainage to maintain crop health. The SJRRPGW is designed to meet the short-term needs of the SJRRP; future versions of the model may incorporate potential enhancements, several of which are identified in this report.
\nThe SJRRPGW was constructed using the USGS groundwater flow model MODFLOW and was built on the framework of the USGS Central Valley Hydrologic Model (CVHM) within which the SJRRPGW model domain is embedded. The Farm Process (FMP2) was used to simulate the supply and demand components of irrigated agriculture. The Streamflow-Routing Package (SFR2) was used to simulate the streams and bypasses and their interaction with the aquifer system. The 1,300-square mile study area was subdivided into 0.25-mile by 0.25-mile cells. The sediment texture of the aquifer system, which was used to distribute hydraulic properties by model cell, was refined from that used in the CVHM to better represent the natural heterogeneity of aquifer-system materials within the model domain. In addition, the stream properties were updated from the CVHM to better simulate stream-aquifer interactions, and water-budget subregions were refined to better simulate agricultural water supply and demand. External boundary conditions were derived from the CVHM.
\nThe SJRRPGW was calibrated for April 1961 to September 2003 by using groundwater-level observations from 133 wells and streamflow observations from 19 streamgages. The model was calibrated using public-domain parameter estimation software (PEST) in a semi-automated manner. The simulated groundwater-level elevations and trends (including seasonal fluctuations) and surface-water flow magnitudes and trends reasonably matched observed data. The calibrated model is planned to be used to assess the potential effects of restoration flows on agricultural lands and the relative capabilities of proposed SJRRP actions to reduce these effects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145148","collaboration":"In cooperation with the U.S. Bureau of Reclamation","usgsCitation":"Traum, J.A., Phillips, S.P., Bennett, G.L., Zamora, C., and Metzger, L.F., 2014, Documentation of a groundwater flow model (SJRRPGW) for the San Joaquin River Restoration Program study area, California: U.S. Geological Survey Scientific Investigations Report 2014-5148, Report: xii, 151 p.; 3 Interactive Animations, https://doi.org/10.3133/sir20145148.","productDescription":"Report: xii, 151 p.; 3 Interactive Animations","numberOfPages":"167","onlineOnly":"Y","ipdsId":"IP-033499","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":294968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145148.jpg"},{"id":294965,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5148/pdf/sir2014-5148.pdf"},{"id":294967,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5148/downloads/sir2014-5148_D2GW.swf"},{"id":294966,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5148/downloads/sir2014-5148_StreamSeepage.swf"},{"id":294963,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5148/"},{"id":294964,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5148/downloads/sir2014-5148_GWE.swf"}],"datum":"North American Datum of 1983","country":"United States","state":"California","otherGeospatial":"San Joaquin River","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5434f286e4b0a4f4b46a235c","contributors":{"authors":[{"text":"Traum, Jonathan A. 0000-0002-4787-3680 jtraum@usgs.gov","orcid":"https://orcid.org/0000-0002-4787-3680","contributorId":4780,"corporation":false,"usgs":true,"family":"Traum","given":"Jonathan","email":"jtraum@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":497574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Steven P. 0000-0002-5107-868X sphillip@usgs.gov","orcid":"https://orcid.org/0000-0002-5107-868X","contributorId":1506,"corporation":false,"usgs":true,"family":"Phillips","given":"Steven","email":"sphillip@usgs.gov","middleInitial":"P.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":497572,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennett, George L. V V 0000-0002-6239-1604 georbenn@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-1604","contributorId":1373,"corporation":false,"usgs":true,"family":"Bennett","given":"George","suffix":"V","email":"georbenn@usgs.gov","middleInitial":"L. V","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":497575,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zamora, Celia 0000-0003-1456-4360 czamora@usgs.gov","orcid":"https://orcid.org/0000-0003-1456-4360","contributorId":1514,"corporation":false,"usgs":true,"family":"Zamora","given":"Celia","email":"czamora@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":497573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Metzger, Loren F. 0000-0003-2454-2966 lmetzger@usgs.gov","orcid":"https://orcid.org/0000-0003-2454-2966","contributorId":1378,"corporation":false,"usgs":true,"family":"Metzger","given":"Loren","email":"lmetzger@usgs.gov","middleInitial":"F.","affiliations":[],"preferred":true,"id":497571,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70173512,"text":"70173512 - 2014 - Post-mortem sporulation of Ceratomyxa shasta (Myxozoa) after death in adult Chinook salmon","interactions":[],"lastModifiedDate":"2016-06-22T13:11:13","indexId":"70173512","displayToPublicDate":"2014-10-07T05:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2414,"text":"Journal of Parasitology","active":true,"publicationSubtype":{"id":10}},"title":"Post-mortem sporulation of Ceratomyxa shasta (Myxozoa) after death in adult Chinook salmon","docAbstract":"Ceratomyxa shasta (Myxozoa) is a common gastrointestinal pathogen of salmonid fishes in the Pacific Northwest of the United States. We have been investigating this parasite in adult Chinook salmon (Oncorhynchus tshawytscha) in the Willamette River, Oregon. In prior work, we observed differences in the pattern of development of C. shasta in adult salmon compared to juvenile salmon. Adult salmon consistently had large numbers of prespore stages in many of the fish that survived to spawn in the fall. However, myxospores were rarely observed, even though they were exposed and presumably infected for months before spawning. We evaluated the ability of C. shasta to sporulate following fish death because it is reported that myxosores are common in carcasses of Chinook salmon. We collected the intestine from 30 adult salmon immediately after artificial spawning and death (T0). A total of 23 fish were infected with C. shasta based on histology, but only a few myxospores were observed in 1 fish by histology. Intestines of these fish were examined at T0 and T7 (latter held at 17 C for 7 days) using quantified wet mount preparations. An increase in myxospore concentrations was seen in 39% of these fish, ranging between a 1.5- to a 14.5-fold increase. The most heavily infected fish exhibited a 4.6-fold increase from 27,841 to 129,352 myxospores/cm. This indicates, supported by various statistical analyses, that under certain conditions presporogonic forms are viable and continue to sporulate after death in adult salmon. Considering the life cycle of C. shasta and anadromous salmon, the parasite may have evolved 2, non-mutually exclusive developmental strategies. In young fish (parr and smolts), the parasite sporulates shortly after infection and is released into freshwater from either live or dead fish before their migration to seawater, where the alternate host is absent. The second strategy occurs in adult salmon, particularly spring Chinook salmon, which become infected upon their return to freshwater in the spring or early summer. For several months throughout the summer, only prespore stages are observed in most fish, even at the time of spawning. But once the fish dies, environmental conditions experienced by C. shasta change and viable presporogonic stages are induced to sporulate. As the post-spawned fish occur in the upper reaches of rivers, the myxospores would be released in a freshwater environment that would provide a reasonable opportunity for them to encounter their freshwater polychaete hosts, which reside downstream.
","language":"English","publisher":"American Society of Parasitologists","doi":"10.1645/13-490.1","usgsCitation":"Kent, M., Soderlund, K., Thomann, E., Schreck, C.B., and Sharpton, T., 2014, Post-mortem sporulation of Ceratomyxa shasta (Myxozoa) after death in adult Chinook salmon: Journal of Parasitology, v. 100, no. 5, p. 679-683, https://doi.org/10.1645/13-490.1.","productDescription":"5 p.","startPage":"679","endPage":"683","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056298","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":324223,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576bb6b9e4b07657d1a22930","contributors":{"authors":[{"text":"Kent, Michael L.","contributorId":108420,"corporation":false,"usgs":true,"family":"Kent","given":"Michael L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":640340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soderlund, K.","contributorId":80883,"corporation":false,"usgs":true,"family":"Soderlund","given":"K.","email":"","affiliations":[],"preferred":false,"id":640341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomann, E.","contributorId":32801,"corporation":false,"usgs":true,"family":"Thomann","given":"E.","email":"","affiliations":[],"preferred":false,"id":640342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schreck, Carl B. 0000-0001-8347-1139 carl.schreck@usgs.gov","orcid":"https://orcid.org/0000-0001-8347-1139","contributorId":878,"corporation":false,"usgs":true,"family":"Schreck","given":"Carl","email":"carl.schreck@usgs.gov","middleInitial":"B.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":637224,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sharpton, T.J.","contributorId":172324,"corporation":false,"usgs":false,"family":"Sharpton","given":"T.J.","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":640343,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159647,"text":"70159647 - 2014 - Methane hydrates in nature - Current knowledge and challenges","interactions":[],"lastModifiedDate":"2015-11-16T12:31:13","indexId":"70159647","displayToPublicDate":"2014-10-07T05:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2209,"text":"Journal of Chemical and Engineering Data","active":true,"publicationSubtype":{"id":10}},"title":"Methane hydrates in nature - Current knowledge and challenges","docAbstract":"Recognizing the importance of methane hydrate research and the need for a coordinated effort, the United States Congress enacted the Methane Hydrate Research and Development Act of 2000. At the same time, the Ministry of International Trade and Industry in Japan launched a research program to develop plans for a methane hydrate exploratory drilling project in the Nankai Trough. India, China, the Republic of Korea, and other nations also have established large methane hydrate research and development programs. Government-funded scientific research drilling expeditions and production test studies have provided a wealth of information on the occurrence of methane hydrates in nature. Numerous studies have shown that the amount of gas stored as methane hydrates in the world may exceed the volume of known organic carbon sources. However, methane hydrates represent both a scientific and technical challenge, and much remains to be learned about their characteristics and occurrence in nature. Methane hydrate research in recent years has mostly focused on: (1) documenting the geologic parameters that control the occurrence and stability of methane hydrates in nature, (2) assessing the volume of natural gas stored within various methane hydrate accumulations, (3) analyzing the production response and characteristics of methane hydrates, (4) identifying and predicting natural and induced environmental and climate impacts of natural methane hydrates, (5) analyzing the methane hydrate role as a geohazard, (6) establishing the means to detect and characterize methane hydrate accumulations using geologic and geophysical data, and (7) establishing the thermodynamic phase equilibrium properties of methane hydrates as a function of temperature, pressure, and gas composition. The U.S. Department of Energy (DOE) and the Consortium for Ocean Leadership (COL) combined their efforts in 2012 to assess the contributions that scientific drilling has made and could continue to make to advance our understanding of methane hydrates in nature. COL assembled a Methane Hydrate Project Science Team with members from academia, industry, and government. This Science Team worked with COL and DOE to develop and host the Methane Hydrate Community Workshop, which surveyed a substantial cross section of the methane hydrate research community for input on the most important research developments in our understanding of methane hydrates in nature and their potential role as an energy resource, a geohazard, and/or as an agent of global climate change. Our understanding of how methane hydrates occur in nature is still growing and evolving, and it is known with certainty that field, laboratory, and modeling studies have contributed greatly to our understanding of hydrates in nature and will continue to be a critical source of the information needed to advance our understanding of methane hydrates.
","language":"English","publisher":"American Chemical Society","publisherLocation":"Columbus, OH","doi":"10.1021/je500604h","usgsCitation":"Collett, T.S., 2014, Methane hydrates in nature - Current knowledge and challenges: Journal of Chemical and Engineering Data, v. 60, no. 2, p. 319-329, https://doi.org/10.1021/je500604h.","productDescription":"11 p.","startPage":"319","endPage":"329","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057920","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":311365,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-07","publicationStatus":"PW","scienceBaseUri":"564b0c4ee4b0ebfbef0d3165","contributors":{"authors":[{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":579865,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70116792,"text":"sir20145136 - 2014 - Simulation of groundwater flow and the interaction of groundwater and surface water in the Willamette Basin and Central Willamette subbasin, Oregon","interactions":[],"lastModifiedDate":"2019-07-22T13:42:06","indexId":"sir20145136","displayToPublicDate":"2014-10-06T16:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5136","title":"Simulation of groundwater flow and the interaction of groundwater and surface water in the Willamette Basin and Central Willamette subbasin, Oregon","docAbstract":"Full appropriation of tributary streamflow during summer, a growing population, and agricultural needs are increasing the demand for groundwater in the Willamette Basin. Greater groundwater use could diminish streamflow and create seasonal and long-term declines in groundwater levels. The U.S. Geological Survey (USGS) and the Oregon Water Resources Department (OWRD) cooperated in a study to develop a conceptual and quantitative understanding of the groundwater-flow system of the Willamette Basin with an emphasis on the Central Willamette subbasin. This final report from the cooperative study describes numerical models of the regional and local groundwater-flow systems and evaluates the effects of pumping on groundwater and surface‑water resources. The models described in this report can be used to evaluate spatial and temporal effects of pumping on groundwater, base flow, and stream capture.
\nThe regional model covers about 6,700 square miles of the 12,000-square mile Willamette and Sandy River drainage basins in northwestern Oregon—referred to as the Willamette Basin in this report. The Willamette Basin is a topographic and structural trough that lies between the Coast Range and the Cascade Range and is divided into five sedimentary subbasins underlain and separated by basalts of the Columbia River Basalt Group (Columbia River basalt) that crop out as local uplands. From north to south, these five subbasins are the Portland subbasin, the Tualatin subbasin, the Central Willamette subbasin, the Stayton subbasin, and the Southern Willamette subbasin. Recharge in the Willamette Basin is primarily from precipitation in the uplands of the Cascade Range, Coast Range, and western Cascades areas. Groundwater moves downward and laterally through sedimentary or basalt units until it discharges locally to wells, evapotranspiration, or streams. Mean annual groundwater withdrawal for water years 1995 and 1996 was about 400 cubic feet per second; irrigation withdrawals accounted for about 80 percent of that total. The upper 180 feet of productive aquifers in the Central Willamette and Southern Willamette subbasins produced about 70 percent of the total pumped volume.
\nIn this study, the USGS constructed a three-dimensional numerical finite-difference groundwater-flow model of the Willamette Basin representing the six hydrogeologic units, defined in previous investigations, as six model layers. From youngest to oldest, and [generally] uppermost to lowermost they are the: upper sedimentary unit, Willamette silt unit, middle sedimentary unit, lower sedimentary unit, Columbia River basalt unit, and basement confining unit. The high Cascade unit is not included in the groundwater-flow model because it is not present within the model boundaries. Geographic boundaries are simulated as no-flow (no water flowing in or out of the model), except where the Columbia River is simulated as a constant hydraulic head boundary. Streams are designated as head-dependent-flux boundaries, in which the flux depends on the elevation of the stream surface. Groundwater recharge from precipitation was estimated using the Precipitation-Runoff Modeling System (PRMS), a watershed model that accounts for evapotranspiration from the unsaturated zone. Evapotranspiration from the saturated zone was not considered an important component of groundwater discharge. Well pumping was simulated as specified flux and included public supply, irrigation, and industrial pumping. Hydraulic conductivity values were estimated from previous studies through aquifer slug and permeameter tests, specific capacity data, core analysis, and modeling. Upper, middle and lower sedimentary unit horizontal hydraulic conductivity values were differentiated between the Portland subbasin and the Tualatin, Central Willamette, and Southern Willamette subbasins based on preliminary model results.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145136","collaboration":"Prepared in cooperation with Oregon Water Resources Department","usgsCitation":"Herrera, N.B., Burns, E., and Conlon, T.D., 2014, Simulation of groundwater flow and the interaction of groundwater and surface water in the Willamette Basin and Central Willamette subbasin, Oregon: U.S. Geological Survey Scientific Investigations Report 2014-5136, xvii, 152 p., https://doi.org/10.3133/sir20145136.","productDescription":"xvii, 152 p.","numberOfPages":"170","onlineOnly":"Y","ipdsId":"IP-022627","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":294957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145136.jpg"},{"id":294956,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5136/pdf/sir20145136.pdf"},{"id":294951,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5136/"}],"projection":"Universal Transverse Mercator, Zone 10N","datum":"North American Datum of 1927","country":"United States","state":"Oregon","otherGeospatial":"Willamette Basin","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5433a105e4b095098ca855a6","contributors":{"authors":[{"text":"Herrera, Nora B. 0000-0002-7744-5206","orcid":"https://orcid.org/0000-0002-7744-5206","contributorId":37666,"corporation":false,"usgs":true,"family":"Herrera","given":"Nora","email":"","middleInitial":"B.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":495842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Erick R. 0000-0002-1747-0506","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":100303,"corporation":false,"usgs":true,"family":"Burns","given":"Erick R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":495843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conlon, Terrence D. 0000-0002-5899-7187 tdconlon@usgs.gov","orcid":"https://orcid.org/0000-0002-5899-7187","contributorId":819,"corporation":false,"usgs":true,"family":"Conlon","given":"Terrence","email":"tdconlon@usgs.gov","middleInitial":"D.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":495841,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70215053,"text":"70215053 - 2014 - Seasonal weather patterns drive population vital rates and persistence in a stream fish","interactions":[],"lastModifiedDate":"2020-10-06T20:08:06.894274","indexId":"70215053","displayToPublicDate":"2014-10-06T15:02:22","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal weather patterns drive population vital rates and persistence in a stream fish","docAbstract":"Climate change affects seasonal weather patterns, but little is known about the relative importance of seasonal weather patterns on animal population vital rates. Even when such information exists, data are typically only available from intensive fieldwork (e.g., mark–recapture studies) at a limited spatial extent. Here, we investigated effects of seasonal air temperature and precipitation (fall, winter, and spring) on survival and recruitment of brook trout (Salvelinus fontinalis) at a broad spatial scale using a novel stage‐structured population model. The data were a 15‐year record of brook trout abundance from 72 sites distributed across a 170‐km‐long mountain range in Shenandoah National Park, Virginia, USA. Population vital rates responded differently to weather and site‐specific conditions. Specifically, young‐of‐year survival was most strongly affected by spring temperature, adult survival by elevation and per‐capita recruitment by winter precipitation. Low fall precipitation and high winter precipitation, the latter of which is predicted to increase under climate change for the study region, had the strongest negative effects on trout populations. Simulations show that trout abundance could be greatly reduced under constant high winter precipitation, consistent with the expected effects of gravel‐scouring flows on eggs and newly hatched individuals. However, high‐elevation sites would be less vulnerable to local extinction because they supported higher adult survival. Furthermore, the majority of brook trout populations are projected to persist if high winter precipitation occurs only intermittently (≤3 of 5 years) due to density‐dependent recruitment. Variable drivers of vital rates should be commonly found in animal populations characterized by ontogenetic changes in habitat, and such stage‐structured effects may increase population persistence to changing climate by not affecting all life stages simultaneously. Yet, our results also demonstrate that weather patterns during seemingly less consequential seasons (e.g., winter precipitation) can have major impacts on animal population dynamics.
","language":"English","publisher":"Wiley-Blackwell","doi":"10.1111/gcb.12837","usgsCitation":"Kanno, Y., Letcher, B., Hitt, N.P., Boughton, D.A., Wofford, J.E., and Zipkin, E., 2014, Seasonal weather patterns drive population vital rates and persistence in a stream fish: Global Change Biology, v. 21, no. 5, p. 1856-1870, https://doi.org/10.1111/gcb.12837.","productDescription":"15 p.","startPage":"1856","endPage":"1870","ipdsId":"IP-060225","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":472700,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.12837","text":"Publisher Index Page"},{"id":379108,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Shenandoah National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.9200439453125,\n 37.26530995561875\n ],\n [\n -79.310302734375,\n 37.54022177661216\n ],\n [\n -78.519287109375,\n 38.1777509666256\n ],\n [\n -78.1402587890625,\n 38.724090458956965\n ],\n [\n -78.2061767578125,\n 38.997841307500714\n ],\n [\n -78.387451171875,\n 39.0533181067413\n ],\n [\n -78.59069824218749,\n 38.7283759182398\n ],\n [\n -78.81591796875,\n 38.37611542403604\n ],\n [\n -79.6783447265625,\n 37.70120736474139\n ],\n [\n -79.969482421875,\n 37.45741810262938\n ],\n [\n -79.9200439453125,\n 37.26530995561875\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","issue":"5","noUsgsAuthors":false,"publicationDate":"2015-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Kanno, Yoichiro ykanno@usgs.gov","contributorId":4876,"corporation":false,"usgs":true,"family":"Kanno","given":"Yoichiro","email":"ykanno@usgs.gov","affiliations":[],"preferred":true,"id":800653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Letcher, Benjamin 0000-0003-0191-5678 bletcher@usgs.gov","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":242669,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin","email":"bletcher@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":800652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568 nhitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":4435,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"nhitt@usgs.gov","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":800654,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boughton, David A.","contributorId":172477,"corporation":false,"usgs":false,"family":"Boughton","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":800655,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wofford, John E. B.","contributorId":38951,"corporation":false,"usgs":false,"family":"Wofford","given":"John","email":"","middleInitial":"E. B.","affiliations":[],"preferred":false,"id":800656,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zipkin, Elise ezipkin@usgs.gov","contributorId":470,"corporation":false,"usgs":true,"family":"Zipkin","given":"Elise","email":"ezipkin@usgs.gov","affiliations":[],"preferred":true,"id":800657,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70128127,"text":"70128127 - 2014 - A cross-validation package driving Netica with python","interactions":[],"lastModifiedDate":"2014-10-03T16:17:23","indexId":"70128127","displayToPublicDate":"2014-10-03T16:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A cross-validation package driving Netica with python","docAbstract":"Bayesian networks (BNs) are powerful tools for probabilistically simulating natural systems and emulating process models. Cross validation is a technique to avoid overfitting resulting from overly complex BNs. Overfitting reduces predictive skill. Cross-validation for BNs is known but rarely implemented due partly to a lack of software tools designed to work with available BN packages. CVNetica is open-source, written in Python, and extends the Netica software package to perform cross-validation and read, rebuild, and learn BNs from data. Insights gained from cross-validation and implications on prediction versus description are illustrated with: a data-driven oceanographic application; and a model-emulation application. These examples show that overfitting occurs when BNs become more complex than allowed by supporting data and overfitting incurs computational costs as well as causing a reduction in prediction skill. CVNetica evaluates overfitting using several complexity metrics (we used level of discretization) and its impact on performance metrics (we used skill).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Modelling and Software","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2014.09.007","usgsCitation":"Fienen, M., and Plant, N.G., 2014, A cross-validation package driving Netica with python: Environmental Modelling and Software, v. 63, p. 14-23, https://doi.org/10.1016/j.envsoft.2014.09.007.","productDescription":"10 p.","startPage":"14","endPage":"23","numberOfPages":"10","ipdsId":"IP-058198","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":294937,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.envsoft.2014.09.007"},{"id":294950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542fac86e4b092f17df61cc2","contributors":{"authors":[{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":893,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","email":"mnfienen@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":502769,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":502770,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70118238,"text":"pp1798K - 2014 - The effects of Missouri River mainstem reservoir system operations on 2011 flooding using a Precipitation-Runoff Modeling System model","interactions":[{"subject":{"id":70118238,"text":"pp1798K - 2014 - The effects of Missouri River mainstem reservoir system operations on 2011 flooding using a Precipitation-Runoff Modeling System model","indexId":"pp1798K","publicationYear":"2014","noYear":false,"chapter":"K","title":"The effects of Missouri River mainstem reservoir system operations on 2011 flooding using a Precipitation-Runoff Modeling System model"},"predicate":"IS_PART_OF","object":{"id":70047427,"text":"pp1798 - 2013 - 2011 floods of the central United States","indexId":"pp1798","publicationYear":"2013","noYear":false,"title":"2011 floods of the central United States"},"id":1}],"isPartOf":{"id":70047427,"text":"pp1798 - 2013 - 2011 floods of the central United States","indexId":"pp1798","publicationYear":"2013","noYear":false,"title":"2011 floods of the central United States"},"lastModifiedDate":"2024-10-18T13:29:00.816756","indexId":"pp1798K","displayToPublicDate":"2014-10-03T14:32:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1798","chapter":"K","title":"The effects of Missouri River mainstem reservoir system operations on 2011 flooding using a Precipitation-Runoff Modeling System model","docAbstract":"In 2011 the Missouri River Mainstem Reservoir System (Reservoir System) experienced the largest volume of flood waters since the initiation of record-keeping in the nineteenth century. The high levels of runoff from both snowpack and rainfall stressed the Reservoir System’s capacity to control flood waters and caused massive damage and disruption along the river. The flooding and resulting damage along the Missouri River brought increased public attention to the U.S. Army Corps of Engineers (USACE) operation of the Reservoir System.
To help understand the effects of Reservoir System operation on the 2011 Missouri River flood flows, the U.S. Geological Survey Precipitation-Runoff Modeling System was used to construct a model of the Missouri River Basin to simulate flows at streamgages and dam locations with the effects of Reservoir System operation (regulation) on flow removed. Statistical tests indicate that the Missouri River Precipitation-Runoff Modeling System model is a good fit for high-flow monthly and annual stream flow estimation. A comparison of simulated unregulated flows and measured regulated flows show that regulation greatly reduced spring peak flow events, consolidated two summer peak flow events to one with a markedly decreased magnitude, and maintained higher than normal base flow beyond the end of water year 2011. Further comparison of results indicate that without regulation, flows greater than those measured would have occurred and been sustained for much longer, frequently in excess of 30 days, and flooding associated with high-flow events would have been more severe.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2011 Floods of the Central United States","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1798K","usgsCitation":"Haj, A.E., Christiansen, D.E., and Viger, R., 2014, The effects of Missouri River mainstem reservoir system operations on 2011 flooding using a Precipitation-Runoff Modeling System model: U.S. Geological Survey Professional Paper 1798, v, 33 p., https://doi.org/10.3133/pp1798K.","productDescription":"v, 33 p.","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-044498","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":294928,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1798k/"},{"id":294929,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1798k/pdf/pp1798k.pdf"},{"id":294930,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/pp1798k.jpg"}],"scale":"3000000","projection":"Albers Equal-Area Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Colorado, Iowa, Kansas, Minnesota, Missouri, Montana, Nebraska,North Dakota, South Dakota. Wyoming","otherGeospatial":"Missouri River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.791015625,\n 39.16414104768742\n ],\n [\n -93.1640625,\n 40.3130432088809\n ],\n [\n -96.7236328125,\n 44.87144275016589\n ],\n [\n -98.4375,\n 47.487513008956554\n ],\n [\n -102.65625,\n 48.545705491847464\n ],\n [\n -107.490234375,\n 49.03786794532644\n ],\n [\n -115.7080078125,\n 48.951366470947725\n ],\n [\n -113.02734374999999,\n 46.830133640447386\n ],\n [\n -113.64257812499999,\n 45.55252525134013\n ],\n [\n -112.939453125,\n 44.276671273775186\n ],\n [\n -111.26953125,\n 44.715513732021336\n ],\n [\n -109.4677734375,\n 43.644025847699496\n ],\n [\n -107.8857421875,\n 42.52069952914966\n ],\n [\n -106.3916015625,\n 41.343824581185686\n ],\n [\n -105.77636718749999,\n 40.111688665595956\n ],\n [\n -105.5126953125,\n 38.8225909761771\n ],\n [\n -90.791015625,\n 39.16414104768742\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542fac8ae4b092f17df61cd1","contributors":{"authors":[{"text":"Haj, Adel E. Jr. ahaj@usgs.gov","contributorId":4812,"corporation":false,"usgs":true,"family":"Haj","given":"Adel","suffix":"Jr.","email":"ahaj@usgs.gov","middleInitial":"E.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":496485,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christiansen, Daniel E. 0000-0001-6108-2247 dechrist@usgs.gov","orcid":"https://orcid.org/0000-0001-6108-2247","contributorId":366,"corporation":false,"usgs":true,"family":"Christiansen","given":"Daniel","email":"dechrist@usgs.gov","middleInitial":"E.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":496484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Viger, Roland J. 0000-0003-2520-714X","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":18294,"corporation":false,"usgs":true,"family":"Viger","given":"Roland J.","affiliations":[],"preferred":false,"id":496486,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70128075,"text":"70128075 - 2014 - Surveillance for zoonotic and selected pathogens in harbor seals Phoca vitulina from central California","interactions":[],"lastModifiedDate":"2016-01-26T15:51:21","indexId":"70128075","displayToPublicDate":"2014-10-03T11:05:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"title":"Surveillance for zoonotic and selected pathogens in harbor seals Phoca vitulina from central California","docAbstract":"The infection status of harbor seals Phoca vitulina in central California, USA, was evaluated through broad surveillance for pathogens in stranded and wild-caught animals from 2001 to 2008, with most samples collected in 2007 and 2008. Stranded animals from Mendocino County to San Luis Obispo County were sampled at a rehabilitation facility: The Marine Mammal Center (TMMC, n = 175); wild-caught animals were sampled at 2 locations: San Francisco Bay (SF, n = 78) and Tomales Bay (TB, n = 97), that differed in degree of urbanization. Low prevalences of Salmonella, Campylobacter, Giardia, and Cryptosporidium were detected in the feces of stranded and wild-caught seals. Clostridium perfringens and Escherichia coli were more prevalent in the feces of stranded (58% [78 out of 135] and 76% [102 out of 135]) than wild-caught (42% [45 out of 106] and 66% [68 out of 106]) seals, whereas Vibrio spp. were 16 times more likely to be cultured from the feces of seals from SF than TB or TMMC (p < 0.005). Brucella DNA was detected in 3.4% of dead stranded harbor seals (2 out of 58). Type A influenza was isolated from feces of 1 out of 96 wild-caught seals. Exposure to Toxoplasma gondii, Sarcocystis neurona, and type A influenza was only detected in the wild-caught harbor seals (post-weaning age classes), whereas antibody titers to Leptospira spp. were detected in stranded and wild-caught seals. No stranded (n = 109) or wild-caught (n = 217) harbor seals had antibodies to phocine distemper virus, although a single low titer to canine distemper virus was detected. These results highlight the role of harbor seals as sentinel species for zoonotic and terrestrial pathogens in the marine environment.
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Poisoning also has been sporadically suspected and, less often, documented in marine wildlife, often in association with an outbreak in humans. Kittlitz's Murrelet (Brachyramphus brevirostris) is a small, rare seabird of the Northern Pacific with a declining population. From 2008 to 2012, as part of a breeding ecology study, multiple Kittlitz's Murrelet nests on Kodiak Island, Alaska, were monitored by remote cameras. During the 2011 and 2012 breeding seasons, nestlings from several sites died during mild weather conditions. Remote camera observations revealed that the nestlings died shortly after consuming sand lance (Ammodytes hexapterus), a fish species known to biomagnify saxitoxin. High levels of saxitoxin were subsequently documented in crop content in 87% of nestling carcasses. Marine bird deaths from PSP may be underreported.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Diseases","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2013-11-296","usgsCitation":"Shearn-Bochsler, V.I., Lance, E., Corcoran, R., Piatt, J.F., Bodenstein, B., Frame, E., and Lawonn, J., 2014, Fatal paralytic shellfish poisoning in Kittlitz's Murrelet (Brachyramphus brevirostris) nestlings, Alaska, USA: Journal of Wildlife Diseases, v. 50, no. 4, p. 933-937, https://doi.org/10.7589/2013-11-296.","productDescription":"5 p.","startPage":"933","endPage":"937","numberOfPages":"5","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049617","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":294904,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294903,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.7589/2013-11-296"}],"country":"United States","state":"Alaska","otherGeospatial":"Kodiak Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.92919921875,\n 57.36801461845934\n ],\n [\n -154.62158203125,\n 57.68066002977235\n ],\n [\n -154.171142578125,\n 57.844750992891\n ],\n [\n -153.6328125,\n 58.12431960569377\n ],\n [\n -153.204345703125,\n 58.41322259056804\n ],\n [\n -152.86376953125,\n 58.642652516575964\n ],\n [\n -152.325439453125,\n 58.73400476743346\n ],\n [\n -151.962890625,\n 58.62549730245039\n ],\n [\n -151.732177734375,\n 58.34986596667874\n ],\n [\n -151.67724609374997,\n 58.12431960569377\n ],\n [\n -151.776123046875,\n 57.97315745102812\n ],\n [\n -151.776123046875,\n 57.73934950049299\n ],\n [\n -151.995849609375,\n 57.45677122453565\n ],\n [\n -152.33642578125,\n 57.249337594636835\n ],\n [\n -152.874755859375,\n 57.022794415389725\n ],\n [\n -153.643798828125,\n 56.64414704199467\n ],\n [\n -153.819580078125,\n 56.45034902929676\n ],\n [\n -154.302978515625,\n 56.35916436114856\n ],\n [\n -154.84130859375,\n 56.3409012041991\n ],\n [\n -154.97314453125,\n 56.511017504952136\n ],\n [\n -154.84130859375,\n 56.794862261400546\n ],\n [\n -154.8193359375,\n 57.11238500793404\n ],\n [\n -154.92919921875,\n 57.36801461845934\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542fac89e4b092f17df61cca","contributors":{"authors":[{"text":"Shearn-Bochsler, Valerie I. 0000-0002-5590-6518 vbochsler@usgs.gov","orcid":"https://orcid.org/0000-0002-5590-6518","contributorId":3234,"corporation":false,"usgs":true,"family":"Shearn-Bochsler","given":"Valerie","email":"vbochsler@usgs.gov","middleInitial":"I.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":502754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lance, Ellen W.","contributorId":15946,"corporation":false,"usgs":true,"family":"Lance","given":"Ellen W.","affiliations":[],"preferred":false,"id":502756,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Corcoran, Robin","contributorId":29750,"corporation":false,"usgs":true,"family":"Corcoran","given":"Robin","email":"","affiliations":[],"preferred":false,"id":502759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":502760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bodenstein, Barbara 0000-0001-7946-0103","orcid":"https://orcid.org/0000-0001-7946-0103","contributorId":8399,"corporation":false,"usgs":true,"family":"Bodenstein","given":"Barbara","affiliations":[],"preferred":false,"id":502755,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Frame, Elizabeth","contributorId":24710,"corporation":false,"usgs":true,"family":"Frame","given":"Elizabeth","affiliations":[],"preferred":false,"id":502757,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lawonn, James","contributorId":28185,"corporation":false,"usgs":true,"family":"Lawonn","given":"James","email":"","affiliations":[],"preferred":false,"id":502758,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70128065,"text":"70128065 - 2014 - Avian influenza virus ecology in Iceland shorebirds: intercontinental reassortment and movement","interactions":[],"lastModifiedDate":"2018-01-03T13:09:01","indexId":"70128065","displayToPublicDate":"2014-10-03T09:52:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1988,"text":"Infection, Genetics and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Avian influenza virus ecology in Iceland shorebirds: intercontinental reassortment and movement","docAbstract":"Shorebirds are a primary reservoir of avian influenza viruses (AIV). We conducted surveillance studies in Iceland shorebird populations for 3 years, documenting high serological evidence of AIV exposure in shorebirds, primarily in Ruddy Turnstones (Arenaria interpres; seroprevalence = 75%). However, little evidence of virus infection was found in these shorebird populations and only two turnstone AIVs (H2N7; H5N1) were able to be phylogenetically examined. These analyses showed that viruses from Iceland shorebirds were primarily derived from Eurasian lineage viruses, yet the H2 hemagglutinin gene segment was from a North American lineage previously detected in a gull from Iceland the previous year. The H5N1 virus was determined to be low pathogenic, however the PB2 gene was closely related to the PB2 from highly pathogenic H5N1 isolates from China. Multiple lines of evidence suggest that the turnstones were infected with at least one of these AIV while in Iceland and confirm Iceland as an important location where AIV from different continents interact and reassort, creating new virus genomes. Mounting data warrant continued surveillance for AIV in wild birds in the North Atlantic, including Canada, Greenland, and the northeast USA to determine the risks of new AI viruses and their intercontinental movement in this region.
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topography and coregistered texture (color) from an unstructured set of overlapping photographs taken from varying viewpoints, overcoming many of the cost, time, and logistical limitations of Light Detection and Ranging (LiDAR) and other topographic surveying methods. This paper provides the first investigation of SfM as a tool for mapping fault zone topography in areas of sparse or low-lying vegetation. First, we present a simple, affordable SfM workflow, based on an unmanned helium balloon or motorized glider, an inexpensive camera, and semiautomated software. Second, we illustrate the system at two sites on southern California faults covered by existing airborne or terrestrial LiDAR, enabling a comparative assessment of SfM topography resolution and precision. At the first site, an ∼0.1 km2 alluvial fan on the San Andreas fault, a colored point cloud of density mostly >700 points/m2 and a 3 cm digital elevation model (DEM) and orthophoto were produced from 233 photos collected ∼50 m above ground level. When a few global positioning system ground control points are incorporated, closest point vertical distances to the much sparser (∼4 points/m2) airborne LiDAR point cloud are mostly <3 cm. The second site spans an ∼1 km section of the 1992 Landers earthquake scarp. A colored point cloud of density mostly >530 points/m2 and a 2 cm DEM and orthophoto were produced from 450 photos taken from ∼60 m above ground level. Closest point vertical distances to existing terrestrial LiDAR data of comparable density are mostly <6 cm. Each SfM survey took ∼2 h to complete and several hours to generate the scene topography and texture. SfM greatly facilitates the imaging of subtle geomorphic offsets related to past earthquakes as well as rapid response mapping or long-term monitoring of faulted landscapes.","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01017.1","usgsCitation":"Johnson, K., Nissen, E., Saripalli, S., Arrowsmith, J.R., McGarey, P., Scharer, K.M., Williams, P., and Blisniuk, K., 2014, Rapid mapping of ultrafine fault zone topography with structure from motion: Geosphere, v. 10, no. 5, p. 969-986, https://doi.org/10.1130/GES01017.1.","productDescription":"18 p.","startPage":"969","endPage":"986","numberOfPages":"18","ipdsId":"IP-053161","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":472702,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01017.1","text":"Publisher Index Page"},{"id":294881,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.7841796875,\n 32.76880048488168\n ],\n [\n -114.43359375,\n 32.76880048488168\n ],\n [\n -114.43359375,\n 35.737595151747826\n ],\n [\n -118.7841796875,\n 35.737595151747826\n ],\n [\n -118.7841796875,\n 32.76880048488168\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542e5b0ce4b092f17df5a6db","contributors":{"authors":[{"text":"Johnson, Kendra","contributorId":94615,"corporation":false,"usgs":true,"family":"Johnson","given":"Kendra","email":"","affiliations":[],"preferred":false,"id":502556,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nissen, Edwin","contributorId":8777,"corporation":false,"usgs":true,"family":"Nissen","given":"Edwin","affiliations":[],"preferred":false,"id":502550,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saripalli, Srikanth","contributorId":53314,"corporation":false,"usgs":true,"family":"Saripalli","given":"Srikanth","email":"","affiliations":[],"preferred":false,"id":502554,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arrowsmith, J. 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Precocial birds (e.g., Galliformes and Anseriformes) are typically facultative nest parasites of both their own and other species (Lyon and Eadie 1991). This behavior increases a female’s reproductive success when she parasitizes other nests while simultaneously raising her own offspring. Both interspecific and conspecific nest parasitism have been well documented in several families of the order Galliformes, particularly the Phasianidae (Lyon and Eadie 1991, Geffen and Yom-Tov 2001, Krakauer and Kimball 2009). The Chukar (Alectoris chukar) has been widely introduced as a game bird to western North America from Eurasia and is now well established within the Great Basin from northeastern California east to Utah and north to Idaho and Oregon (Christensen 1996). Over much of this range the Chukar occurs with other phasianids, including the native Greater Sage-Grouse (Centrocercus urophasianus), within sagebrush (Artemisia spp.) steppe (Christensen 1996, Schroeder et al. 1999, Connelly et al. 2000). Chukar typically exploit a broader range of habitats than do sage-grouse, but both species use the same species of sagebrush and other shrubs for nesting cover (Christensen 1996, Schroeder et al. 1999). Chukar are known to parasitize nests of other individuals of their own species (Geffen and Yom-Tov 2001), but we are unaware of reported evidence that Chukar may parasitize nests of sage-grouse. Here we describe a case of a Chukar parasitizing a sage-grouse nest in the sagebrush steppe of western Nevada.
","language":"English","publisher":"Western Field Ornithologists","usgsCitation":"Fearon, M.L., and Coates, P.S., 2014, Interspecific nest parasitism by chukar on greater sage-grouse: Western Birds, v. 45, no. 3, p. 224-227.","productDescription":"4 p.","startPage":"224","endPage":"227","ipdsId":"IP-052116","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":294873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328987,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.westernfieldornithologists.org/archive/V45/journal-45-3.php"}],"volume":"45","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542e5b0be4b092f17df5a6c0","contributors":{"authors":[{"text":"Fearon, Michelle L. mfearon@usgs.gov","contributorId":5833,"corporation":false,"usgs":true,"family":"Fearon","given":"Michelle","email":"mfearon@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":502700,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":502699,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70127801,"text":"70127801 - 2014 - Error propagation in energetic carrying capacity models","interactions":[],"lastModifiedDate":"2018-01-04T12:50:25","indexId":"70127801","displayToPublicDate":"2014-10-02T13:34:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2231,"text":"Journal of Conservation Planning","active":true,"publicationSubtype":{"id":10}},"title":"Error propagation in energetic carrying capacity models","docAbstract":"Conservation objectives derived from carrying capacity models have been used to inform management of \nlandscapes for wildlife populations. Energetic carrying capacity models are particularly useful in conservation planning \nfor wildlife; these models use estimates of food abundance and energetic requirements of wildlife to target conservation \nactions. We provide a general method for incorporating a foraging threshold (i.e., density of food at which foraging \nbecomes unprofitable) when estimating food availability with energetic carrying capacity models. We use a hypothetical \nexample to describe how past methods for adjustment of foraging thresholds biased results of energetic carrying capacity \nmodels in certain instances. Adjusting foraging thresholds at the patch level of the species of interest provides results \nconsistent with ecological foraging theory. Presentation of two case studies suggest variation in bias which, in certain \ninstances, created large errors in conservation objectives and may have led to inefficient allocation of limited resources. \nOur results also illustrate how small errors or biases in application of input parameters, when extrapolated to large spatial \nextents, propagate errors in conservation planning and can have negative implications for target populations.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Conservation Planning","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"University of Florida Department of Urban and Regional Planning, The Conservation Fund","usgsCitation":"Pearse, A.T., and Stafford, J.D., 2014, Error propagation in energetic carrying capacity models: Journal of Conservation Planning, v. 10, p. 17-24.","productDescription":"8 p.","startPage":"17","endPage":"24","ipdsId":"IP-039972","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":294855,"type":{"id":15,"text":"Index Page"},"url":"https://www.journalconsplanning.org/2014/index.html"},{"id":294856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542e5b08e4b092f17df5a6a9","contributors":{"authors":[{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":502543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stafford, Joshua D. jstafford@usgs.gov","contributorId":4267,"corporation":false,"usgs":true,"family":"Stafford","given":"Joshua","email":"jstafford@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":502544,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70120244,"text":"sir20145152 - 2014 - Hydrogeologic framework and occurrence, movement, and chemical characterization of groundwater in Dixie Valley, west-central Nevada","interactions":[],"lastModifiedDate":"2014-10-02T13:04:53","indexId":"sir20145152","displayToPublicDate":"2014-10-02T12:58:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5152","title":"Hydrogeologic framework and occurrence, movement, and chemical characterization of groundwater in Dixie Valley, west-central Nevada","docAbstract":"Dixie Valley, a primarily undeveloped basin in west-central Nevada, is being considered for groundwater exportation. Proposed pumping would occur from the basin-fill aquifer. In response to proposed exportation, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation and Churchill County, conducted a study to improve the understanding of groundwater resources in Dixie Valley. The objective of this report is to characterize the hydrogeologic framework, the occurrence and movement of groundwater, the general water quality of the basin-fill aquifer, and the potential mixing between basin-fill and geothermal aquifers in Dixie Valley. Various types of geologic, hydrologic, and geochemical data were compiled from previous studies and collected in support of this study. Hydrogeologic units in Dixie Valley were defined to characterize rocks and sediments with similar lithologies and hydraulic properties influencing groundwater flow. Hydraulic properties of the basin-fill deposits were characterized by transmissivity estimated from aquifer tests and specific-capacity tests. Groundwater-level measurements and hydrogeologic-unit data were combined to create a potentiometric surface map and to characterize groundwater occurrence and movement. Subsurface inflow from adjacent valleys into Dixie Valley through the basin-fill aquifer was evaluated using hydraulic gradients and Darcy flux computations. The chemical signature and groundwater quality of the Dixie Valley basin-fill aquifer, and potential mixing between basin-fill and geothermal aquifers, were evaluated using chemical data collected from wells and springs during the current study and from previous investigations.
\nDixie Valley is the terminus of the Dixie Valley flow system, which includes Pleasant, Jersey, Fairview, Stingaree, Cowkick, and Eastgate Valleys. The freshwater aquifer in the study area is composed of unconsolidated basin-fill deposits of Quaternary age. The basin-fill hydrogeologic unit can be several orders of magnitude more transmissive than surrounding and underlying consolidated rocks and Dixie Valley playa deposits. Transmissivity estimates in the basin fill throughout Dixie Valley ranged from 30 to 45,500 feet squared per day; however, a single transmissivity value of 0.1 foot squared per day was estimated for playa deposits.
\nGroundwater generally flows from the mountain range uplands toward the central valley lowlands and eventually discharges near the playa edge. Potentiometric contours east and west of the playa indicate that groundwater is moving eastward from the Stillwater Range and westward from the Clan Alpine Mountains toward the playa. Similarly, groundwater flows from the southern and northern basin boundaries toward the basin center. Subsurface groundwater flow likely enters Dixie Valley from Fairview and Stingaree Valleys in the south and from Jersey and Pleasant Valleys in the north, but groundwater connections through basin-fill deposits were present only across the Fairview and Jersey Valley divides. Annual subsurface inflow from Fairview and Jersey Valleys ranges from 700 to 1,300 acre-feet per year and from 1,800 to 2,300 acre-feet per year, respectively. Groundwater flow between Dixie, Stingaree, and Pleasant Valleys could occur through less transmissive consolidated rocks, but only flow through basin fill was estimated in this study.
\nGroundwater in the playa is distinct from the freshwater, basin-fill aquifer. Groundwater mixing between basin-fill and playa groundwater systems is physically limited by transmissivity contrasts of about four orders of magnitude. Total dissolved solids in playa deposit groundwater are nearly 440 times greater than total dissolved solids in the basin-fill groundwater. These distinctive physical and chemical flow restrictions indicate that groundwater interaction between the basin fill and playa sediments was minimal during this study period (water years 2009–11).
\nGroundwater in Dixie Valley generally can be characterized as a sodium bicarbonate type, with greater proportions of chloride north of the Dixie Valley playa, and greater proportions of sulfate south of the playa. Analysis of major ion water chemistry data sampled during the study period indicates that groundwater north and south of Township 22N differ chemically. Dixie Valley groundwater quality is marginal when compared with national primary and secondary drinking-water standards. Arsenic and fluoride concentrations exceed primary drinking water standards, and total dissolved solids and manganese concentrations exceed secondary drinking water standards in samples collected during this study. High concentrations of boron and tungsten also were observed.
\nChemical comparisons between basin-fill and geothermal aquifer water indicate that most basin-fill groundwater sampled could contain 10–20 percent geothermal water. Geothermal indicators such as high temperature, lithium, boron, chloride, and silica suggest that mixing occurs in many wells that tap the basin-fill aquifer, particularly on the north, south, and west sides of the basin. Magnesium-lithium geothermometers indicate that some basin-fill aquifer water sampled for the current study likely originates from water that was heated above background mountain-block recharge temperatures (between 3 and 15 degrees Celsius), highlighting the influence of mixing with warm water that was possibly derived from geothermal sources.
","language":"English","publisher":"U. S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145152","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Huntington, J.M., Garcia, C.A., and Rosen, M.R., 2014, Hydrogeologic framework and occurrence, movement, and chemical characterization of groundwater in Dixie Valley, west-central Nevada: U.S. Geological Survey Scientific Investigations Report 2014-5152, Report: vii, 59 p.; 1 Plate 24 x 36 inches; 1 Appendix, https://doi.org/10.3133/sir20145152.","productDescription":"Report: vii, 59 p.; 1 Plate 24 x 36 inches; 1 Appendix","numberOfPages":"72","onlineOnly":"Y","ipdsId":"IP-034768","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":294838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145152.jpg"},{"id":294827,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5152/"},{"id":294829,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5152/pdf/sir2014-5152.pdf"},{"id":294832,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2014/5152/pdf/sir2014-5152_plate01.pdf"},{"id":294834,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5152/downloads/sir2014-5152_appendixA.xlsx"}],"scale":"24000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Nevada","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542e5b0ae4b092f17df5a6ba","contributors":{"authors":[{"text":"Huntington, Jena M. 0000-0002-9291-1404 jmhunt@usgs.gov","orcid":"https://orcid.org/0000-0002-9291-1404","contributorId":2294,"corporation":false,"usgs":true,"family":"Huntington","given":"Jena","email":"jmhunt@usgs.gov","middleInitial":"M.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, C. Amanda 0000-0003-3776-3565 cgarcia@usgs.gov","orcid":"https://orcid.org/0000-0003-3776-3565","contributorId":1899,"corporation":false,"usgs":true,"family":"Garcia","given":"C.","email":"cgarcia@usgs.gov","middleInitial":"Amanda","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosen, Michael R. 0000-0003-3991-0522 mrosen@usgs.gov","orcid":"https://orcid.org/0000-0003-3991-0522","contributorId":495,"corporation":false,"usgs":true,"family":"Rosen","given":"Michael","email":"mrosen@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498045,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70116634,"text":"pp1805 - 2014 - Groundwater discharge by evapotranspiration, Dixie Valley, west-central Nevada, March 2009-September 2011","interactions":[],"lastModifiedDate":"2022-05-31T20:41:43.010389","indexId":"pp1805","displayToPublicDate":"2014-10-02T12:56:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1805","title":"Groundwater discharge by evapotranspiration, Dixie Valley, west-central Nevada, March 2009-September 2011","docAbstract":"With increasing population growth and land-use change, urban communities in the desert Southwest are progressively looking toward remote basins to supplement existing water supplies. Pending applications by Churchill County for groundwater appropriations from Dixie Valley, Nevada, a primarily undeveloped basin east of the Carson Desert, have prompted a reevaluation of the quantity of naturally discharging groundwater. The objective of this study was to develop a revised, independent estimate of groundwater discharge by evapotranspiration (ETg) from Dixie Valley using a combination of eddy-covariance evapotranspiration (ET) measurements and multispectral satellite imagery. Mean annual ETg was estimated during water years 2010 and 2011 at four eddy-covariance sites. Two sites were in phreatophytic shrubland dominated by greasewood, and two sites were on a playa. Estimates of total ET and ETg were supported with vegetation cover mapping, soil physics considerations, water‑level measurements from wells, and isotopic water sourcing analyses to allow partitioning of ETg into evaporation and transpiration components. Site-based ETg estimates were scaled to the basin level by combining remotely sensed imagery with field reconnaissance. Enhanced vegetation index and brightness temperature data were compared with mapped vegetation cover to partition Dixie Valley into five discharging ET units and compute basin-scale ETg. Evapotranspiration units were defined within a delineated groundwater discharge area and were partitioned as (1) playa lake, (2) playa, (3) sparse shrubland, (4) moderate-to-dense shrubland, and (5) grassland.
Groundwater ET is influenced primarily by phreatophytic vegetative cover, salinity of soil and groundwater within the playa, depth to groundwater, solar radiation, and air temperature. The annual groundwater contribution to site‑scale ET ranged from 24 to 61 percent of total ET at vegetated sites and 4 to 15 percent of total ET at playa sites. Mean annual ETg from vegetated sites ranged from 53 millimeters (mm) (0.17 foot [ft], 7.3 percent vegetative cover) to 225 mm (0.74 ft, 24.8 percent vegetative cover). Cumulative liquid‑water fluxes in the unsaturated zone indicate that ETg at vegetated sites was influenced primarily by plant transpiration. Binary mixing analyses of oxygen-18 isotopes in groundwater and shallow soil water indicate that plants predominantly use groundwater throughout the year. Groundwater fractions in greasewood stem water varied seasonally and ranged from 0.63 to 1.0. Mean annual playa ETg ranged from about 11 mm (0.04 ft) at the inner playa site (near-surface volumetric water content of 37–53 percent) to about 20 mm (0.07 ft) at the outer playa site located within 2 kilometers of the playa edge (near-surface volumetric water content of 25–38 percent), but playa ETg estimates were within the probable error (plus or minus [±] 20–23 mm; 0.06–0.08 ft). Varying playa ETg was influenced predominantly by salinity rather than depth to groundwater. Osmotic resistance and physical impediments to ET (such as surface salt crusts and salt precipitate in the soil pore space) increased with increasing salinity toward the playa center, whereas vapor pressure decreased.
Mean annual basin-scale ETg totaled about 28 million cubic meters (Mm3) (23,000 acre-feet [acre-ft]), and represents the sum of ETg from all ET units. Annual groundwater ET from vegetated areas totaled about 26 Mm3 (21,000 acre-ft), and was dominated by the moderate-to-dense shrubland ET unit (54 percent), followed by sparse shrubland (37 percent) and grassland (9 percent) ET units. Senesced grasses observed in the northern most areas of the moderate-to-dense ET unit likely confounded the vegetation index and led to an overestimate of ETg for this ET unit. Therefore, mean annual ETg for moderate-to-dense shrubland presented here is likely an upper bound. Annual groundwater ET from the playa ET unit was 2.2 Mm3 (1,800 acre-ft), whereas groundwater ET from the playa lake ET unit was 0–0.1 Mm3 (0–100 acre-ft). Oxygen-18 and deuterium data indicate discharge from the playa center predominantly represents removal of local precipitation-derived recharge. The playa lake estimate, therefore, is considered an upper bound. Mean annual ETg estimates for Dixie Valley are assumed to represent the pre‑development, long-term ETg rates within the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1805","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Garcia, C.A., Huntington, J.M., Buto, S.G., Moreo, M.T., Smith, J.L., and Andraski, B.J., 2015, Groundwater discharge by evapotranspiration, Dixie Valley, west-central Nevada, March 2009–September 2011 (ver. 1.1, April 2015): U.S. Geological Survey Professional Paper 1805, 90 p., https://doi.org/10.3133/pp1805.","productDescription":"Report: ix, 89 p.; 8 Appendixes; Evapotranspiration units; Groundwater discharge area; Vegetation index","numberOfPages":"104","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2009-03-01","temporalEnd":"2011-12-31","ipdsId":"IP-034747","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":294843,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1805/images/covrthb.jpg"},{"id":294826,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1805/pdf/pp1805.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":294840,"type":{"id":23,"text":"Spatial Data"},"url":"https://water.usgs.gov/lookup/getspatial?pp1805_ETunits","text":"Evapotranspiration units"},{"id":294825,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1805/"},{"id":401429,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/pp/1805/versionHist.txt"},{"id":294841,"type":{"id":23,"text":"Spatial Data"},"url":"https://water.usgs.gov/lookup/getspatial?pp1805_GDA","text":"Groundwater discharge area"},{"id":294842,"type":{"id":23,"text":"Spatial Data"},"url":"https://water.usgs.gov/lookup/getspatial?pp1805_VI","text":"Vegetation index"},{"id":401430,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1805/downloads/pp1805_appendix01.xlsx","text":"Appendix 1","size":"786 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":401431,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1805/downloads/pp1805_appendix02.xlsx","text":"Appendix 2","size":"26 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":401432,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1805/downloads/pp1805_appendix03.xlsx","text":"Appendix 3","size":"25 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":401433,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1805/downloads/pp1805_appendix04.xlsx","text":"Appendix 4","size":"32 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":401434,"rank":12,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1805/downloads/pp1805_appendix05.xlsx","text":"Appendix 5","size":"15 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":401435,"rank":13,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1805/downloads/pp1805_appendix06.xlsx","text":"Appendix 6","size":"74 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":401436,"rank":14,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1805/pdf/pp1805_appendix07.pdf","text":"Appendix 7","size":"46 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":401437,"rank":15,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1805/downloads/pp1805_appendix08.xlsx","text":"Appendix 8","size":"13 KB","linkFileType":{"id":3,"text":"xlsx"}}],"scale":"24000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Nevada","otherGeospatial":"Dixie Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.2183837890625,\n 39.26203141523749\n ],\n [\n -118.2183837890625,\n 40.065460682065535\n ],\n [\n -117.23510742187501,\n 40.065460682065535\n ],\n [\n -117.23510742187501,\n 39.26203141523749\n ],\n [\n -118.2183837890625,\n 39.26203141523749\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: October 2, 2014; Version 1.1: April 7, 2015","contact":"Director,
Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Rd.
Carson City, NV 89701
Surface-water supplies are important sources of drinking water for residents in the Triangle area of North Carolina, which is located within the upper Cape Fear and Neuse River Basins. Since 1988, the U.S. Geological Survey and a consortium of governments have tracked water-quality conditions and trends in several of the area’s water-supply lakes and streams. This report summarizes data collected through this cooperative effort, known as the Triangle Area Water Supply Monitoring Project, during October 2008 through September 2009. Major findings for this period include:
\n- Annual precipitation was approximately 20 percent below the long-term mean (average) annual precipitation.
\n\n- Streamflow was below the long-term mean at the 10 project streamgages during most of the year.
\n\n- More than 7,000 individual measurements of water quality were made at a total of 26 sites—15 in the Neuse River Basin and 11 in the Cape Fear River Basin. Forty-seven water-quality properties and constituents were measured.
\n\n- All observations met North Carolina water-quality standards for water temperature, pH, hardness, chloride, fluoride, sulfate, nitrate, arsenic, cadmium, chromium, lead, nickel, and selenium.
\n\n- North Carolina water-quality standards were exceeded one or more times for dissolved oxygen, dissolved oxygen percent saturation, chlorophyll a, mercury, copper, iron, manganese, silver, and zinc. Exceedances occurred at 23 sites—13 in the Neuse River Basin and 10 in the Cape Fear River Basin.
\n\n- Stream samples collected during storm events contained elevated concentrations of 18 water-quality constituents compared to samples collected during non-storm events.
\n\n- Concentrations of nitrogen and phosphorus were within ranges observed during previous years.
\n\n- Five reservoirs had chlorophyll a concentrations in excess of 40 micrograms per liter at least once during 2009: Little River Reservoir, Falls Lake, Cane Creek Reservoir, University Lake, and Jordan Lake.
The Great Lakes (Superior, Michigan, Huron, Erie, and Ontario) are the largest group of freshwater lakes on Earth and serve as an important source of drinking water, transportation, power, and recreational opportunities for the United States and Canada. They also support an abundant commercial and recreational fishery, are crucial for agriculture, and are essential to the economic vitality of the region. The Great Lakes support a wealth of biological diversity, including over 200 globally rare plants and animals and more than 40 species that are found nowhere else in the world. However, more than a century of environmental degradation has taken a substantial toll on the Great Lakes. To stimulate and promote the goal of a healthy Great Lakes region, President Obama and Congress created the Great Lakes Restoration Initiative (GLRI) in 2009. The GLRI is an interagency collaboration that seeks to address the most significant environmental problems in the Great Lakes ecosystem. The GLRI is composed of five focus areas that address these issues:
\nAs of August 2013, the GLRI had funded more than 1,500 projects and programs of the highest priority to meet immediate cleanup, restoration, and protection needs. These projects use scientific analyses as the basis for identifying the restoration needs and priorities for the GLRI. Results from the science, monitoring, and other on-the-ground actions by the U.S. Geological Survey (USGS) provide the scientific information needed to help guide the Great Lakes restoration efforts. This document highlights a selection of USGS projects for each of the five focus areas through 2013, demonstrating the importance of science for restoration success. Additional information for these and other USGS projects that are important for Great Lakes restoration is available at http://cida.usgs.gov/glri/glri-catalog/.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1404","collaboration":"A Product of the Great Lakes Restoration Initiative","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2014, Great Lakes restoration success through science: U.S. Geological Survey accomplishments 2010 through 2013: U.S. Geological Survey Circular 1404, v, 56 p., https://doi.org/10.3133/cir1404.","productDescription":"v, 56 p.","numberOfPages":"68","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2010-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-058287","costCenters":[{"id":323,"text":"Great Lakes Restoration","active":false,"usgs":true},{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":294757,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir1404.jpg"},{"id":294756,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1404/pdf/circ1404.pdf","text":"Report","size":"35.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":294755,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/circ/1404/"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.13232421875,\n 49.06666839558117\n ],\n [\n -86.15478515625,\n 48.850258199721495\n ],\n [\n -84.638671875,\n 48.03401915864286\n ],\n [\n -83.8916015625,\n 46.46813299215554\n ],\n [\n -80.771484375,\n 46.042735653846506\n ],\n [\n -79.34326171875,\n 45.07352060670971\n ],\n [\n -78.7060546875,\n 44.071800467511565\n ],\n [\n -76.04736328125,\n 44.465151013519616\n ],\n [\n -74.99267578125,\n 45.042478050891546\n ],\n [\n -74.267578125,\n 45.089035564831036\n ],\n [\n -74.06982421875,\n 44.19795903948531\n ],\n [\n -75.08056640625,\n 42.5530802889558\n ],\n [\n -76.83837890625,\n 41.73852846935917\n ],\n [\n -80.4638671875,\n 40.81380923056961\n ],\n [\n -82.77099609375,\n 40.329795743702064\n ],\n [\n -87.51708984375,\n 41.09591205639546\n ],\n [\n -89.67041015625,\n 43.24520272203359\n ],\n [\n -92.87841796875,\n 46.42271253466717\n ],\n [\n -92.92236328125,\n 47.57652571374621\n ],\n [\n -89.97802734375,\n 48.879167148960214\n ],\n [\n -88.13232421875,\n 49.06666839558117\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542e5b08e4b092f17df5a6af","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":544977,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70121281,"text":"sir20145163 - 2014 - Assessment of the spatial extent and height of flooding in Lake Champlain during May 2011, using satellite remote sensing and ground-based information","interactions":[],"lastModifiedDate":"2014-10-02T09:02:28","indexId":"sir20145163","displayToPublicDate":"2014-10-02T08:56:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5163","title":"Assessment of the spatial extent and height of flooding in Lake Champlain during May 2011, using satellite remote sensing and ground-based information","docAbstract":"Landsat 5 and moderate resolution imaging spectro-radiometer satellite imagery were used to map the area of inundation of Lake Champlain, which forms part of the border between New York and Vermont, during May 2011. During this month, the lake’s water levels were record high values not observed in the previous 150 years. Lake inundation area determined from the satellite imagery is correlated with lake stage measured at three U.S. Geological Survey lake level gages to provide estimates of lake area at different lake levels (stage/area rating) and also compared with the levels of the high-water marks (HWMs) located on the Vermont side of the lake. The rating developed from the imagery shows a somewhat different relation than a similar stage/area rating developed from a medium-resolution digital elevation model (DEM) of the region. According to the rating derived from the imagery, the lake surface area during the peak lake level increased by about 17 percent above the average or “normal” lake level. By using a comparable rating developed from the DEM, the increase above average is estimated to be about 12 percent. The northern part of the lake (north of Burlington) showed the largest amount of flooding. Based on intersecting the inundation maps with the medium-resolution DEM, lake levels were not uniform around the lake. This is also evident from the lake level gage measurements and HWMs. The gage data indicate differences up to 0.5 feet between the northern and southern end of the lake. Additionally, the gage data show day-to-day and intradaily variation of the same range (0.5 foot). The high-water mark observations show differences up to 2 feet around the lake, with the highest level generally along the south- and west-facing shorelines. The data suggest that during most of May 2011, water levels were slightly higher and less variable in the northern part of the lake. These phenomena may be caused by wind effects as well as proximity to major river inputs to the lake. The inundation areas generated from the imagery generally coincide with flood mapping as estimated by the Federal Emergency Management Agency (FEMA) and shown on its digital flood insurance rate maps. Where areas in the flood inundation map derived from the imagery and the FEMA estimated flooded areas differ substantially, this difference may be due to differences between the flood magnitude at the time of the image and the assumed flood condition used for the FEMA modeling and mapping, wind/storage effects not accounted for by the FEMA modeling, and the resolution of the image compared to the DEM used in the FEMA mapping.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145163","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Bjerklie, D.M., Trombley, T.J., and Olson, S.A., 2014, Assessment of the spatial extent and height of flooding in Lake Champlain during May 2011, using satellite remote sensing and ground-based information: U.S. Geological Survey Scientific Investigations Report 2014-5163, Report: vii, 18 p.; 1 Plate: 24 x 27 inches, https://doi.org/10.3133/sir20145163.","productDescription":"Report: vii, 18 p.; 1 Plate: 24 x 27 inches","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-051120","costCenters":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"links":[{"id":294753,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145163.jpg"},{"id":294750,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5163/pdf/sir2014-5163.pdf"},{"id":294751,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5163/"},{"id":294752,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2014/5163/figure/sir2014-5163_fig08.pdf"}],"country":"Canada, United States","otherGeospatial":"Lake Champlain","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542e5b06e4b092f17df5a6a5","contributors":{"authors":[{"text":"Bjerklie, David M. 0000-0002-9890-4125 dmbjerkl@usgs.gov","orcid":"https://orcid.org/0000-0002-9890-4125","contributorId":3589,"corporation":false,"usgs":true,"family":"Bjerklie","given":"David","email":"dmbjerkl@usgs.gov","middleInitial":"M.","affiliations":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498914,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trombley, Thomas J. trombley@usgs.gov","contributorId":1803,"corporation":false,"usgs":true,"family":"Trombley","given":"Thomas","email":"trombley@usgs.gov","middleInitial":"J.","affiliations":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498912,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olson, Scott A. 0000-0002-1064-2125 solson@usgs.gov","orcid":"https://orcid.org/0000-0002-1064-2125","contributorId":2059,"corporation":false,"usgs":true,"family":"Olson","given":"Scott","email":"solson@usgs.gov","middleInitial":"A.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498913,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}