Pleistocene glaciations and late Cenozoic offset on the Teton fault have played central roles in shaping the scenic landscapes of the Teton Range and Jackson Hole area in Wyoming. The Teton Range harbored a system of mountain-valley glaciers that produced the striking geomorphic features in these mountains. However, the comparatively much larger southern sector of the Greater Yellowstone glacial system (GYGS) is responsible for creating the more expansive glacial landforms and deposits that dominate Jackson Hole. The glacial history is also inextricably associated with the Yellowstone hotspot, which caused two conditions that have fostered extensive glaciation: (1) uplift and consequent cold temperatures in greater Yellowstone; and (2) the lowland track of the hotspot (eastern Snake River Plain) that funneled moisture to the Yellowstone Plateau and the Yellowstone Crescent of High Terrain (YCHT).
The penultimate (Bull Lake) glaciation filled all of Jackson Hole with glacial ice. Granitic boulders on moraines beyond the south end of Jackson Hole have cosmogenic 10Be exposure ages of ~150 thousand years ago (ka) and correlate with Marine Isotope Stage 6. A thick loess mantle subdues the topography of Bull Lake moraines and caps Bull Lake outwash terraces with a reddish buried soil near the base of the loess having a Bk horizon that extends down into the outwash gravel. The Bull Lake glaciation of Jackson Hole extended 48 kilometers (km) farther south than the Pinedale, representing the largest separation of these two glacial positions in the Western United States. The Bull Lake is also more extensive than the Pinedale on the west (22 km) and southwest (23 km) margins of the GYGS but not on the north and east. This pattern is explained by uplift and subsidence on the leading and trailing “bow-wave” of the YCHT, respectively.
During the last (Pinedale) glaciation, mountain-valley glaciers of the Teton Range extended to the western edge of Jackson Hole and built bouldery moraines that commonly enclose lakes. On the southern margin of the GYGS, prominent glacial outwash terraces define three phases of the Pinedale glaciation in Jackson Hole: Pinedale-1 (Pd-1) by Antelope Flats with subdued channel patterns on the east side of Jackson Hole; Pinedale-2 (Pd-2) by a large outwash fan that includes Baseline Flat on the west side of Jackson Hole with well-defined channel patterns; and Pinedale-3 (Pd-3) by The Potholes and other outwash fans farther up the Snake River in central Jackson Hole. During Pinedale glaciation, three glacial lobes of the GYGS fed into Jackson Hole, and the relative importance of these lobes changed dramatically through time. During the Pd-1 glaciation, the eastern Buffalo Fork lobe dominated whereas in Pd-2 and Pd-3 time the northern Snake River lobe dominated. This is consistent with migration of the GYGS center of ice mass westward and southward as glaciers built up towards the moisture source provided by storms moving northeastward up the eastern Snake River Plain. The recession of the eastern Buffalo Fork lobe in Pd-2 and Pd-3 times is consistent with an enlarged ice mass on the Yellowstone Plateau that placed the eastern part of the GYGS in a precipitation or snow shadow.
In Pd-1 time, the Buffalo Fork lobe reached its maximum extent and was joined by the Pacific Creek lobe. This culmination may correlate with the ~21–18 ka ages of moraines in the Teton Range and nearby ranges. Three subdivisions of Pd-1 glaciation built moraines that are nearly or entirely covered by outwash almost 100 meters thick. In Pd-2 time, the Snake River lobe joined with the Pacific Creek lobe and built a large outwash fan south of the present-day Jackson Lake. Boulders on a moraine at the head of this fan are dated to 15.5 ± 0.5 ka. The relation between Teton glaciers and those of the GYGS is indicated by outwash from these Pd-2 moraines that partly buries outer Jenny Lake moraines dated to 15.2 ± 0.7 ka. East of the large outwash fan, Pd-2 ice advanced across the glacial-age Triangle X-2 lake sediments, perhaps in a surge. The Buffalo Fork lobe retreated more than 20 km up valley from its Pd-1 position and Pd-2 ice of the Snake River and Pacific Creek lobes advanced into the area previously occupied by the Buffalo Fork lobe. The Pd-3 position flanks the margin of Jackson Lake and represents a retreat to a stable position after the Pd-2 7-km advance that may have been a surge across the Triangle X-2 lake sediments. The Potholes and South Landing outwash fans were built in the area deglaciated by the retreat from Pd-2 to Pd-3 time. The Spalding Bay outwash fan continued to incise and a meltwater stream flowed just outside the Teton glacier that filled the present Jenny Lake and deposited the 14.4 ± 0.8 ka inner Jenny Lake moraines.
Glacial outwash terraces increase in slope toward their respective moraines of the GYGS and are complex in both north-south and east-west directions. The Pd-1 terrace slopes to the west where it is buried by the Pd-2 outwash. The post-depositional tilting of the Pd-1 outwash terrace is an order of magnitude smaller than the original westward depositional slope. The Pd-1, 2, and 3 terraces have a shingle-like geometry such that the highest terrace decreases in age down valley, and in southern Jackson Hole, the Pd-3 terrace is only 3–5 m above the Snake River.
In Pd-1 time the combined Buffalo Fork and Pacific Creek lobes scoured out four basins: (1) Emma Matilda Lake; (2) Two Ocean Lake; (3) a deep basin from lower Pacific Creek to beneath the Oxbows and Jackson Lake Dam; and (4) the largest basin from the lower Buffalo Fork to Deadmans Bar of the Snake River. These basins are largely filled with fine-grained sediment and are now marked by moist lowlands or lakes. In Pd-2 and Pd-3 time the Snake River lobe scoured the present 120-m deep Jackson Lake and possibly the 120-m deeper sediment-filled basin. Subglacial erosion of the Jackson Lake basin by confined water jets is supported by eskers that climb up to the head of the South Landing outwash fan.
Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-480
Denver, CO 80225
Digital flood-inundation maps for a 9.5-mile reach of the Patoka River in and near the city of Jasper, southwestern Indiana (Ind.), from the streamgage near County Road North 175 East, downstream to State Road 162, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science web site at https://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage Patoka River at Jasper, Ind. (station number 03375500). The Patoka streamgage is located at the upstream end of the 9.5-mile river reach. Near-real-time stages at this streamgage may be obtained from the USGS National Water Information System at https://waterdata.usgs.gov/ or the National Weather Service Advanced Hydrologic Prediction Service at http://water.weather.gov/ahps/, although flood forecasts and stages for action and minor, moderate, and major flood stages are not currently (2017) available at this site (JPRI3).
Flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relation at the Patoka River at Jasper, Ind., streamgage and the documented high-water marks from the flood of April 30, 2017. The calibrated hydraulic model was then used to compute five water-surface profiles for flood stages referenced to the streamgage datum ranging from 15 feet (ft), or near bankfull, to 19 ft. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging [lidar] data having a 0.98 ft vertical accuracy and 4.9 ft horizontal resolution) to delineate the area flooded at each water level.
The availability of these flood-inundation maps, along with real-time stage from the USGS streamgage at the Patoka River at Jasper, Ind., will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175138","collaboration":"Prepared in cooperation with the Indiana Department of Transportation","usgsCitation":"Fowler, K.K., 2018, Flood-inundation maps for the Patoka River in and near Jasper, southwestern Indiana: U.S. Geological Survey Scientific Investigations Report 2017–5138, 11 p., https://doi.org/10.3133/sir20175138.","productDescription":"Report: vii, 11 p.; Data Release","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-086512","costCenters":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":350479,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5138/coverthb.jpg"},{"id":350480,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5138/sir20175138.pdf","text":"Report","size":"34.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5138"},{"id":350481,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7862DX0","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial Datasets and Surface-Water Hydraulic Model for the Patoka River in and near Jasper, Southwest Indiana, Flood-inundation Study"}],"country":"United States","state":"Indiana","city":"Jasper","otherGeospatial":"Patoka River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.95,\n 38.360839624761944\n ],\n [\n -86.875,\n 38.360839624761944\n ],\n [\n -86.875,\n 38.425\n ],\n [\n -86.95,\n 38.425\n ],\n [\n -86.95,\n 38.360839624761944\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Blvd
Indianapolis, IN 46278
We apply linear deconvolution methods to derive mineral and glass proportions for eight field sample training sites at seven dune fields: (1) Algodones, California; (2) Big Dune, Nevada; (3) Bruneau, Idaho; (4) Great Kobuk Sand Dunes, Alaska; (5) Great Sand Dunes National Park and Preserve, Colorado; (6) Sunset Crater, Arizona; and (7) White Sands National Monument, New Mexico. These dune fields were chosen because they represent a wide range of mineral grain mixtures and allow us to gauge a better understanding of both compositional and sorting effects within terrestrial and extraterrestrial dune systems. We also use actual ASTER TIR emissivity imagery to map the spatial distribution of these minerals throughout the seven dune fields and evaluate the effects of degraded spectral resolution on the accuracy of mineral abundances retrieved. Our results show that hyperspectral data convolutions of our laboratory emissivity spectra outperformed multispectral data convolutions of the same data with respect to the mineral, glass and lithic abundances derived. Both the number and wavelength position of spectral bands greatly impacts the accuracy of linear deconvolution retrieval of feldspar proportions (e.g. K-feldspar vs. plagioclase) especially, as well as the detection of certain mafic and carbonate minerals. In particular, ASTER mapping results show that several of the dune sites display patterns such that less dense minerals typically have higher abundances near the center of the active and most evolved dunes in the field, while more dense minerals and glasses appear to be more abundant along the margins of the active dune fields.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aeolia.2017.12.001","usgsCitation":"Hubbard, B.E., Hooper, D.M., Solano, F., and Mars, J., 2018, Determining mineralogical variations of aeolian deposits using thermal infrared emissivity and linear deconvolution methods: Aeolian Research, v. 30, p. 54-96, https://doi.org/10.1016/j.aeolia.2017.12.001.","productDescription":"43 p.","startPage":"54","endPage":"96","ipdsId":"IP-080975","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":461075,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aeolia.2017.12.001","text":"Publisher Index Page"},{"id":438055,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MS3QWM","text":"USGS data release","linkHelpText":"Visible, Near Infrared, Shortwave Infrared and Thermal Infrared Laboratory Spectra of Samples of Compositionally Variable Dune Fields in the Western United States and Alaska"},{"id":438054,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CC0XTR","text":"USGS data release","linkHelpText":"Linear Deconvolution Mineral Maps of Compositionally Variable Dune Fields in the Western United States and Alaska"},{"id":350459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, Arizona, California, Colorado, Idaho, Nevada, New Mexico","otherGeospatial":"Algodones, Big Dune, Bruneau, Great Kobuk Sand Dunes, Great Sand Dunes National Park and Preserve, Sunset Crater, White Sands National Monument","volume":"30","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60e451e4b06e28e9c14067","contributors":{"authors":[{"text":"Hubbard, Bernard E. 0000-0002-9315-2032 bhubbard@usgs.gov","orcid":"https://orcid.org/0000-0002-9315-2032","contributorId":2342,"corporation":false,"usgs":true,"family":"Hubbard","given":"Bernard","email":"bhubbard@usgs.gov","middleInitial":"E.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":725517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooper, Donald M.","contributorId":197205,"corporation":false,"usgs":false,"family":"Hooper","given":"Donald","email":"","middleInitial":"M.","affiliations":[{"id":35997,"text":"Southwest Research Institute, San Antonio, TX","active":true,"usgs":false},{"id":35998,"text":"WEX Foundation","active":true,"usgs":false}],"preferred":false,"id":725518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Solano, Federico 0000-0002-0308-5850 fsolanoc@usgs.gov","orcid":"https://orcid.org/0000-0002-0308-5850","contributorId":4302,"corporation":false,"usgs":true,"family":"Solano","given":"Federico","email":"fsolanoc@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":725519,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mars, John C. jmars@usgs.gov","contributorId":127493,"corporation":false,"usgs":true,"family":"Mars","given":"John C.","email":"jmars@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":725520,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196290,"text":"70196290 - 2018 - International migration patterns of Red-throated Loons (Gavia stellata) from four breeding populations in Alaska","interactions":[],"lastModifiedDate":"2018-03-30T14:00:16","indexId":"70196290","displayToPublicDate":"2018-01-10T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"International migration patterns of Red-throated Loons (Gavia stellata) from four breeding populations in Alaska","title":"International migration patterns of Red-throated Loons (Gavia stellata) from four breeding populations in Alaska","docAbstract":"Identifying post-breeding migration and wintering distributions of migratory birds is important for understanding factors that may drive population dynamics. Red-throated Loons (Gavia stellata) are widely distributed across Alaska and currently have varying population trends, including some populations with recent periods of decline. To investigate population differentiation and the location of migration pathways and wintering areas, which may inform population trend patterns, we used satellite transmitters (n = 32) to describe migration patterns of four geographically separate breeding populations of Red-throated Loons in Alaska. On average (± SD) Red-throated Loons underwent long (6,288 ± 1,825 km) fall and spring migrations predominantly along coastlines. The most northern population (Arctic Coastal Plain) migrated westward to East Asia and traveled approximately 2,000 km farther to wintering sites than the three more southerly populations (Seward Peninsula, Yukon-Kuskokwim Delta, and Copper River Delta) which migrated south along the Pacific coast of North America. These migration paths are consistent with the hypothesis that Red-throated Loons from the Arctic Coastal Plain are exposed to contaminants in East Asia. The three more southerly breeding populations demonstrated a chain migration pattern in which the more northerly breeding populations generally wintered in more northerly latitudes. Collectively, the migration paths observed in this study demonstrate that some geographically distinct breeding populations overlap in wintering distribution while others use highly different wintering areas. Red-throated Loon population trends in Alaska may therefore be driven by a wide range of effects throughout the annual cycle.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0189954","usgsCitation":"McCloskey, S., Uher-Koch, B.D., Schmutz, J.A., and Fondell, T., 2018, International migration patterns of Red-throated Loons (Gavia stellata) from four breeding populations in Alaska: PLoS ONE, v. 13, no. 1, p. 1-15, https://doi.org/10.1371/journal.pone.0189954.","productDescription":"e0189954; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-090249","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":469099,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0189954","text":"Publisher Index Page"},{"id":438057,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TH8KVH","text":"USGS data release","linkHelpText":" Tracking data for Red-throated Loons (Gavia stellata)"},{"id":353018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"13","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-10","publicationStatus":"PW","scienceBaseUri":"5afee751e4b0da30c1bfc22c","contributors":{"authors":[{"text":"McCloskey, Sarah E. smccloskey@usgs.gov","contributorId":4850,"corporation":false,"usgs":true,"family":"McCloskey","given":"Sarah E.","email":"smccloskey@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":732175,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Uher-Koch, Brian D. 0000-0002-1885-0260 buher-koch@usgs.gov","orcid":"https://orcid.org/0000-0002-1885-0260","contributorId":5117,"corporation":false,"usgs":true,"family":"Uher-Koch","given":"Brian","email":"buher-koch@usgs.gov","middleInitial":"D.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":732174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":732176,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fondell, Thomas F. tfondell@usgs.gov","contributorId":139310,"corporation":false,"usgs":true,"family":"Fondell","given":"Thomas F.","email":"tfondell@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":732177,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227940,"text":"70227940 - 2018 - River otter distribution in Nebraska","interactions":[],"lastModifiedDate":"2022-02-02T16:47:55.910735","indexId":"70227940","displayToPublicDate":"2018-01-07T10:44:40","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"River otter distribution in Nebraska","docAbstract":"The river otter (Lontra canadensis) was extirpated from Nebraska, USA, in the early 1900s and reintroduced starting in 1986. Information is needed regarding the distribution of river otters in Nebraska before decisions can be made regarding its conservation status. Understanding distribution of a species is critically important for effective management. We investigated river otter distribution in Nebraska with occupancy modeling and maximum entropy (Maxent) modeling using 190 otter sign observations on Nebraska's navigable rivers and 380 historical otter records from November 1977 to April 2014. Both methods identified the Platte River, Elkhorn River, central and eastern Niobrara River, and southern Loup River system as core areas within the distribution of otters in Nebraska. The Maxent model provided more liberal estimates of site occupancy and identified some smaller rivers as being within the distribution of otters in Nebraska, which were not identified using occupancy modeling. We recommend that multiple data sets and analysis methods be used to estimate species distribution because this allows for the broadest geographical coverage and decreases the likelihood of overlooking areas with fewer animal records. If further reintroduction efforts or translocation efforts are to take place in the future, we recommend focusing on areas with high modeled occupancy but few historical and survey records
","language":"English","publisher":"Wildlife Society","doi":"10.1002/wsb.843","usgsCitation":"Bieber, N.R., Wilson, S.P., and Allen, C.R., 2018, River otter distribution in Nebraska: Wildlife Society Bulletin, v. 42, no. 1, p. 136-143, https://doi.org/10.1002/wsb.843.","productDescription":"8 p.","startPage":"136","endPage":"143","ipdsId":"IP-094064","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":500069,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/08bde403cf22458cbb0e4cf09a97b49e","text":"External Repository"},{"id":395281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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P.","contributorId":273159,"corporation":false,"usgs":false,"family":"Wilson","given":"S.","email":"","middleInitial":"P.","affiliations":[{"id":56368,"text":"Nebraska Game and Parks","active":true,"usgs":false}],"preferred":false,"id":832636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832637,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263443,"text":"70263443 - 2018 - River otter distribution in Nebraska","interactions":[],"lastModifiedDate":"2025-02-11T15:28:17.418219","indexId":"70263443","displayToPublicDate":"2018-01-07T09:25:34","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"River otter distribution in Nebraska","docAbstract":"The river otter (Lontra canadensis) was extirpated from Nebraska, USA, in the early 1900s and reintroduced starting in 1986. Information is needed regarding the distribution of river otters in Nebraska before decisions can be made regarding its conservation status. Understanding distribution of a species is critically important for effective management. We investigated river otter distribution in Nebraska with occupancy modeling and maximum entropy (Maxent) modeling using 190 otter sign observations on Nebraska's navigable rivers and 380 historical otter records from November 1977 to April 2014. Both methods identified the Platte River, Elkhorn River, central and eastern Niobrara River, and southern Loup River system as core areas within the distribution of otters in Nebraska. The Maxent model provided more liberal estimates of site occupancy and identified some smaller rivers as being within the distribution of otters in Nebraska, which were not identified using occupancy modeling. We recommend that multiple data sets and analysis methods be used to estimate species distribution because this allows for the broadest geographical coverage and decreases the likelihood of overlooking areas with fewer animal records. If further reintroduction efforts or translocation efforts are to take place in the future, we recommend focusing on areas with high modeled occupancy but few historical and survey records.
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\"}}]}","volume":"42","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Bieber, N.R.","contributorId":350797,"corporation":false,"usgs":false,"family":"Bieber","given":"N.R.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":927011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, S.P.","contributorId":341215,"corporation":false,"usgs":false,"family":"Wilson","given":"S.P.","email":"","affiliations":[{"id":17640,"text":"Nebraska Game and Parks Commission","active":true,"usgs":false}],"preferred":false,"id":927012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":927013,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188422,"text":"70188422 - 2018 - Extreme-event geoelectric hazard maps: Chapter 9","interactions":[],"lastModifiedDate":"2018-03-22T10:37:03","indexId":"70188422","displayToPublicDate":"2018-01-05T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Extreme-event geoelectric hazard maps: Chapter 9","docAbstract":"Maps of geoelectric amplitude covering about half the continental United States are presented that will be exceeded, on average, once per century in response to an extreme-intensity geomagnetic disturbance. These maps are constructed using an empirical parameterization of induction: convolving latitude-dependent statistical maps of extreme-value geomagnetic disturbances, obtained from decades of 1-minute magnetic observatory data, with local estimates of Earth-surface impedance obtained at discrete geographic sites from magnetotelluric surveys. Geoelectric amplitudes are estimated for geomagnetic waveforms having a 240-s (and 1200-s) sinusoidal period and amplitudes over 10 min (1 h) that exceed a once-per-century threshold. As a result of the combination of geographic differences in geomagnetic variation and Earth-surface impedance, once-per-century geoelectric amplitudes span more than two orders of magnitude and are a highly granular function of location. Specifically for north-south 240-s induction, once-per-century geoelectric amplitudes across large parts of the United States have a median value of 0.34 V/km; for east-west variation, they have a median value of 0.23 V/km. In Northern Minnesota, amplitudes exceed 14.00 V/km for north-south geomagnetic variation (23.34 V/km for east-west variation), while just over 100 km away, amplitudes are only 0.08 V/km (0.02 V/km). At some sites in the northern-central United States, once-per-century geoelectric amplitudes exceed the 2 V/km realized in Québec during the March 1989 storm.
Technological improvements in remote sensing and geographic information systems have demonstrated the abundance of artificially constructed water bodies across the landscape. Although research has shown the ubiquity of small ponds globally, and in the southeastern United States in particular, their cumulative impact in terms of evaporative alteration is less well quantified. The objectives of this study are to examine the hydrologic and evaporative importance of small artificial water bodies in the Upper Oconee watershed in the northern Georgia Piedmont, USA, by mapping their locations and modelling these small reservoirs using the Soil Water Assessment Tool. Comparative Soil Water Assessment Tool models were run with and without the inclusion of small reservoir surface area and volume. The models used meteorological inputs from 1990–2013 to represent years with drought, high precipitation, and moderate precipitation for both the calibration and evaluation periods. Statistical comparison of streamflow indicated that the calibration methodology produced results where the default model simulation without reservoirs fit observed flows more closely than the modified model with small reservoirs included (e.g., Nash–Sutcliffe efficiency of 0.72 vs. 0.64, r2 of 0.73 vs. 0.66, and percent bias of 11.4 vs. 21.6). In addition, Penman–Monteith, Hargreaves, and Priestley–Taylor evapotranspiration equations were used to estimate actual evaporation from 2,219 small water bodies identified throughout the 1,936.8 km2 watershed. Depending on the evaporation equation used, water bodies evaporated an average of 0.03–0.036 km3/year for the period 2003–2013. Using Penman–Monteith further, if the reservoirs were not considered and average actual evapotranspiration rates from the rest of the basin were applied, only 0.016 km3 of water would have left the basin as a result of evapotranspiration. This finding suggests construction of small reservoirs increased evaporation by an average of 0.017 km3 per year (approximately 46,500 m3/day). As the construction of small reservoirs continues and high resolution image data used to map these water bodies becomes increasingly available, watershed models that evolve to address the cumulative impacts of small water bodies on evaporation and other hydrologic processes will have greater potential to benefit the water resource management community.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11398","usgsCitation":"Ignatius, A., and Jones, J., 2018, High resolution water body mapping for SWAT evaporative modelling in the Upper Oconee watershed of Georgia, USA: Hydrological Processes, v. 32, no. 1, p. 51-65, https://doi.org/10.1002/hyp.11398.","productDescription":"15 p.","startPage":"51","endPage":"65","ipdsId":"IP-073606","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469108,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.11398","text":"Publisher Index Page"},{"id":358190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Upper Oconee watershed","volume":"32","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-18","publicationStatus":"PW","scienceBaseUri":"5bc0304de4b0fc368eb539ec","contributors":{"authors":[{"text":"Ignatius, Amber R. 0000-0002-2636-836X","orcid":"https://orcid.org/0000-0002-2636-836X","contributorId":193407,"corporation":false,"usgs":false,"family":"Ignatius","given":"Amber R.","affiliations":[],"preferred":false,"id":747475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, John W. 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","middleInitial":"W.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":747474,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198374,"text":"70198374 - 2018 - Barataria and Terrebonne Bays: Chapter F in Emergent wetlands status and trends in the northern Gulf of Mexico: 1950-2010","interactions":[],"lastModifiedDate":"2018-08-31T12:28:47","indexId":"70198374","displayToPublicDate":"2018-01-01T12:01:32","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"displayTitle":"Barataria and Terrebonne Bays: Chapter F in Emergent wetlands status and trends in the northern Gulf of Mexico: 1950-2010","title":"Barataria and Terrebonne Bays: Chapter F in Emergent wetlands status and trends in the northern Gulf of Mexico: 1950-2010","docAbstract":"The study area included in the Barataria and Terrebonne Bays vignette of\nsoutheastern Louisiana spans eastward from Terrebonne Bay to Barataria Bay (Figure 1)\nand includes portions of Terrebonne, Lafourche, St. Charles, Jefferson, Orleans,\nPlaquemines, and St. Bernard Parishes. This area falls between the Mississippi River on\nthe east and northeast, extends down through the western shore of Lake Salvador and the\nDixie Delta Canal, then runs west to Houma and follows Louisiana Route 315 to the\ncoast; Barataria and Terrebonne Bays are separated from each other by Bayou Lafourche.","largerWorkTitle":"Emergent Wetlands Status and Trends in the Northern Gulf of Mexico: 1950-2010 report","conferenceTitle":"2013 Gulf of Mexico Alliance (GOMA) All Hands Meeting","conferenceDate":"June 25-27, 2013","language":"English","usgsCitation":"Lawrence Handley, Spear, K.A., Zapletal, M., Thatcher, C.A., Jones, W.R., and Wilson, S.A., 2018, Barataria and Terrebonne Bays: Chapter F in Emergent wetlands status and trends in the northern Gulf of Mexico: 1950-2010, 25 p.","productDescription":"25 p.","startPage":"1","endPage":"24","ipdsId":"IP-096196","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":357000,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":356093,"type":{"id":15,"text":"Index Page"},"url":"https://gom.usgs.gov/web/documents/Chapter_F_BaratariaTerrebonneBays.pdf"}],"country":"United States","state":"Louisiana ","otherGeospatial":"Barataria Bay; Terrebonne Bay","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a317e4b0702d0e843028","contributors":{"authors":[{"text":"Lawrence Handley","contributorId":206612,"corporation":false,"usgs":false,"family":"Lawrence Handley","affiliations":[{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":741279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spear, Kathryn A. 0000-0001-8942-2856 speark@usgs.gov","orcid":"https://orcid.org/0000-0001-8942-2856","contributorId":1949,"corporation":false,"usgs":true,"family":"Spear","given":"Kathryn","email":"speark@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":741278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zapletal, Mirka","contributorId":206613,"corporation":false,"usgs":false,"family":"Zapletal","given":"Mirka","email":"","affiliations":[{"id":25340,"text":"Cherokee Nation Technologies","active":true,"usgs":false}],"preferred":false,"id":741280,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thatcher, Cindy A. 0000-0003-0331-071X thatcherc@usgs.gov","orcid":"https://orcid.org/0000-0003-0331-071X","contributorId":2868,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy","email":"thatcherc@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":741281,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jones, William R. 0000-0002-5493-4138 jonesb@usgs.gov","orcid":"https://orcid.org/0000-0002-5493-4138","contributorId":463,"corporation":false,"usgs":true,"family":"Jones","given":"William","email":"jonesb@usgs.gov","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":741282,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilson, Scott A. 0000-0001-8055-8618 wilsons@usgs.gov","orcid":"https://orcid.org/0000-0001-8055-8618","contributorId":2360,"corporation":false,"usgs":true,"family":"Wilson","given":"Scott","email":"wilsons@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":741283,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70194660,"text":"70194660 - 2018 - Strain partitioning in southeastern Alaska: Is the Chatham Strait Fault active?","interactions":[],"lastModifiedDate":"2018-03-29T16:02:02","indexId":"70194660","displayToPublicDate":"2018-01-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Strain partitioning in southeastern Alaska: Is the Chatham Strait Fault active?","docAbstract":"A 1200 km-long transform plate boundary passes through southeastern Alaska and northwestern British Columbia and represents one of the most seismically active, but poorly understood continental margins of North America. Although most of the plate motion is accommodated by the right-lateral Queen Charlotte–Fairweather Fault (QCFF) System, which has produced at least six M > 7 earthquakes since 1920, seismic hazard assessments also include the Chatham Strait Fault (CSF) as a potentially active, 400 km-long strike slip fault that cuts northward through southeastern Alaska, connecting with the Eastern Denali Fault. Nearly the entire length of the CSF is submerged beneath Chatham Strait and Lynn Canal and has never been systematically imaged using high-resolution marine geophysical approaches. In this study we present an integrated analysis of new marine seismic reflectiondata acquired across Lynn Canal and tectonic block modeling constrained by data from continuous and campaign GPS sites. Seismic profiles cross the CSF at twelve locations spanning ∼50 km of fault length; they reveal thick (up to 300 m) packages of glaciomarine sedimentary facies emplaced on an unconformity surface that formed during the Last Glacial Maximum (LGM). Localized warping of post-LGM stratigraphy (∼13.9 kyr B.P. to present) appears to correlate with sediment drape on basement topography and current-controlled deposition. There is no evidence for an active fault along the axis of Lynn Canal in the seismic reflection data. Crustal block models constrained by GPS data allow, but do not require, a maximum slip rate of 2–3 mm/yr along the CSF; higher slip rates on the CSF result in significant misfit to GPS data in the surrounding region. Based on the combined marine geophysical and GPS observations, it is plausible that the CSF has not generated resolvable coseismic deformation in the last ∼13 ka and that the modern slip-rate is <1 mm/yr. We propose that models for strain transfer between the QCFF and the Denali Fault, and seismic hazard maps in general, may need to be reevaluated.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2017.10.017","usgsCitation":"Brothers, D.S., Elliott, J.L., Conrad, J.E., Haeussler, P.J., and Kluesner, J.W., 2018, Strain partitioning in southeastern Alaska: Is the Chatham Strait Fault active?: Earth and Planetary Science Letters, v. 481, p. 362-371, https://doi.org/10.1016/j.epsl.2017.10.017.","productDescription":"10 p.","startPage":"362","endPage":"371","ipdsId":"IP-081661","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469122,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2017.10.017","text":"Publisher Index Page"},{"id":352971,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"481","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee755e4b0da30c1bfc267","contributors":{"authors":[{"text":"Brothers, Daniel S. 0000-0001-7702-157X dbrothers@usgs.gov","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":167089,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel","email":"dbrothers@usgs.gov","middleInitial":"S.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":724809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elliott, Julie L.","contributorId":201260,"corporation":false,"usgs":false,"family":"Elliott","given":"Julie","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":724810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conrad, James E. 0000-0001-6655-694X jconrad@usgs.gov","orcid":"https://orcid.org/0000-0001-6655-694X","contributorId":2316,"corporation":false,"usgs":true,"family":"Conrad","given":"James","email":"jconrad@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":724811,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haeussler, Peter J. 0000-0002-1503-6247 pheuslr@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":503,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter","email":"pheuslr@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":724813,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kluesner, Jared W. 0000-0003-1701-8832 jkluesner@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-8832","contributorId":201261,"corporation":false,"usgs":true,"family":"Kluesner","given":"Jared","email":"jkluesner@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":724812,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193307,"text":"70193307 - 2018 - Lead and strontium isotopes as monitors of anthropogenic contaminants in the surficial environment","interactions":[],"lastModifiedDate":"2020-08-20T17:00:35.524226","indexId":"70193307","displayToPublicDate":"2017-12-08T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"12","title":"Lead and strontium isotopes as monitors of anthropogenic contaminants in the surficial environment","docAbstract":"Isotopic discrimination can be an effective tool in establishing a direct link between sources of Pb contamination and the presence of anomalously high concentrations of Pb in waters, soils, and organisms. Residential wells supplying water containing up to 1600 ppb Pb to houses built on the former Mohr orchards commercial site, near Allentown, Pennsylvania, United States, were evaluated to discern anthropogenic from geogenic sources. Pb and Sr isotopic data and REE data were determined for waters from residential wells, test wells (drilled for this study), and surface waters from pond and creeks. Local soils, sediments, bedrock, Zn-Pb mineralization and coal were also analyzed, together with locally used Pb-As pesticide. Pb isotope data for residential wells, test wells, and surface waters show substantial overlap with Pb data reflecting anthropogenic actions (e.g., burning fossil fuels, industrial and urban processing activities). Limited contributions of Pb from bedrock, soils, and pesticides are evident. High Pb concentrations in the residential waters are likely related to Pb in groundwater accumulating in sediment in the residential water tanks. The Pb isotope features of waters in underlying shallow aquifers that supply residential wells in the region are best interpreted as reflecting a legacy of anthropogenic Pb rather than geogenic Pb.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Environmental Geochemistry","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-444-63763-5.00013-6","usgsCitation":"Ayuso, R.A., and Foley, N.K., 2018, Lead and strontium isotopes as monitors of anthropogenic contaminants in the surficial environment, chap. 12 of Environmental Geochemistry, p. 307-362, https://doi.org/10.1016/B978-0-444-63763-5.00013-6.","productDescription":"56 p.","startPage":"307","endPage":"362","ipdsId":"IP-082091","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":349929,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fad4e4b06e28e9c22765","contributors":{"authors":[{"text":"Ayuso, Robert A. 0000-0002-8496-9534 rayuso@usgs.gov","orcid":"https://orcid.org/0000-0002-8496-9534","contributorId":2654,"corporation":false,"usgs":true,"family":"Ayuso","given":"Robert","email":"rayuso@usgs.gov","middleInitial":"A.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":718623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foley, Nora K. 0000-0003-0124-3509 nfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-0124-3509","contributorId":4010,"corporation":false,"usgs":true,"family":"Foley","given":"Nora","email":"nfoley@usgs.gov","middleInitial":"K.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":718624,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70194558,"text":"sir20175109 - 2018 - Sequence stratigraphy, seismic stratigraphy, and seismic structures of the lower intermediate confining unit and most of the Floridan aquifer system, Broward County, Florida","interactions":[],"lastModifiedDate":"2018-01-25T09:03:53","indexId":"sir20175109","displayToPublicDate":"2017-12-08T00:00:00","publicationYear":"2018","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":"2017-5109","title":"Sequence stratigraphy, seismic stratigraphy, and seismic structures of the lower intermediate confining unit and most of the Floridan aquifer system, Broward County, Florida","docAbstract":"Deep well injection and disposal of treated wastewater into the highly transmissive saline Boulder Zone in the lower part of the Floridan aquifer system began in 1971. The zone of injection is a highly transmissive hydrogeologic unit, the Boulder Zone, in the lower part of the Floridan aquifer system. Since the 1990s, however, treated wastewater injection into the Boulder Zone in southeastern Florida has been detected at three treated wastewater injection utilities in the brackish upper part of the Floridan aquifer system designated for potential use as drinking water. At a time when usage of the Boulder Zone for treated wastewater disposal is increasing and the utilization of the upper part of the Floridan aquifer system for drinking water is intensifying, there is an urgency to understand the nature of cross-formational fluid flow and identify possible fluid pathways from the lower to upper zones of the Floridan aquifer system. To better understand the hydrogeologic controls on groundwater movement through the Floridan aquifer system in southeastern Florida, the U.S. Geological Survey and the Broward County Environmental Planning and Community Resilience Division conducted a 3.5-year cooperative study from July 2012 to December 2015. The study characterizes the sequence stratigraphy, seismic stratigraphy, and seismic structures of the lower part of the intermediate confining unit aquifer and most of the Floridan aquifer system.
Data obtained to meet the study objective include 80 miles of high-resolution, two-dimensional (2D), seismic-reflection profiles acquired from canals in eastern Broward County. These profiles have been used to characterize the sequence stratigraphy, seismic stratigraphy, and seismic structures in a 425-square-mile study area. Horizon mapping of the seismic-reflection profiles and additional data collection from well logs and cores or cuttings from 44 wells were focused on construction of three-dimensional (3D) visualizations of eight sequence stratigraphic cycles that compose the Eocene to Miocene Oldsmar, Avon Park, and Arcadia Formations. The mapping of these seismic-reflection and well data has produced a refined Cenozoic sequence stratigraphic, seismic stratigraphic, and hydrogeologic framework of southeastern Florida. The upward transition from the Oldsmar Formation to the Avon Park Formation and the Arcadia Formation embodies the evolution from (1) a tropical to subtropical, shallow-marine, carbonate platform, represented by the Oldsmar and Avon Park Formations, to (2) a broad, temperate, mixed carbonate-siliciclastic shallow marine shelf, represented by the lower part of the Arcadia Formation, and to (3) a temperate, distally steepened carbonate ramp represented by the upper part of the Arcadia Formation.
In the study area, the depositional sequences and seismic sequences have a direct correlation with hydrogeologic units. The approximate upper boundary of four principal permeable units of the Floridan aquifer system (Upper Floridan aquifer, Avon Park permeable zone, uppermost major permeable zone of the Lower Floridan aquifer, and Boulder Zone) have sequence stratigraphic and seismic-reflection signatures that were identified on cross sections, mapped, or both, and therefore the sequence stratigraphy and seismic stratigraphy were used to guide the development of a refined spatial representation of these hydrogeologic units. In all cases, the permeability of the four permeable units is related to stratiform megaporosity generated by ancient dissolution of carbonate rock associated with subaerial exposure and unconformities at the upper surfaces of carbonate depositional cycles of several hierarchical scales ranging from high-frequency cycles to depositional sequences. Additionally, interparticle porosity also contributes substantially to the stratiform permeability in much of the Upper Floridan aquifer. Information from seismic stratigraphy allowed 3D geomodeling of hydrogeologic units—an approach never before applied to this area. Notably, the 3D geomodeling provided 3D visualizations and geocellular models of the depositional sequences, hydrostratigraphy, and structural features. The geocellular data could be used to update the hydrogeologic structure inherent to groundwater flow simulations that are designed to address the sustainability of the water resources of the Floridan aquifer system.
Two kinds of pathways that could enable upward cross-formational flow of injected treated wastewater from the Boulder Zone have been identified in the 80 miles of high-resolution seismic data collected for this study: a near-vertical reverse fault and karst collapse structures. The single reverse fault, inferred to be of tectonic origin, is in extreme northeastern Broward County and has an offset of about 19 feet at the level of the Arcadia Formation. Most of the 17 karst collapse structures identified manifest as columniform, vertically stacked sagging seismic reflections that span early Eocene to Miocene age rocks equivalent to much of the Floridan aquifer system and the lower part of the overlying intermediate confining unit. In some cases, the seismic-sag structures extend upward into strata of Pliocene age. The seismic-sag structures are interpreted to have a semicircular shape in plan view on the basis of comparison to (1) other seismic-sag structures in southeastern Florida mapped with two 2D seismic cross lines or 3D data, (2) comparison to these structures located in other carbonate provinces, and (3) plausible extensional ring faults detected with multi-attribute analysis. The seismic-sag structures in the study area have heights as great as 2,500 vertical feet, though importantly, one spans about 7,800 feet. Both multi-attribute analysis and visual detection of offset of seismic reflections within the seismic-sag structures indicate faults and fractures are associated with many of the structures. Multi-attribute analysis highlighting chimney fluid pathways also indicates that the seismic-sag structures have a high probability for potential vertical cross-formational fluid flow along the faulted and fractured structures. A collapse of the seismic-sag structures within a deep burial setting evokes an origin related to hypogenic karst processes by ascending flow of subsurface fluids. In addition, paleo-epigenic karst related to major regional subaerial unconformities within the Florida Platform generated collapse structures (paleo-sinkholes) that are much smaller in scale than the cross-formational seismic-sag structures.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175109","collaboration":"Prepared in cooperation with Broward County Environmental Planning and Community Resilience Division, Florida","usgsCitation":"Cunningham, K.J., Kluesner, J.W., Westcott, R.L., Robinson, Edward, Walker, Cameron, and Khan, S.A., 2018, Sequence stratigraphy, seismic stratigraphy, and seismic structures of the lower intermediate confining unit and most of the Floridan aquifer system, Broward County, Florida (ver. 1.1, January 2018): U.S. Geological Survey Scientific Investigations Report 2017–5109, 71 p., 21 pls., https://doi.org/10.3133/sir20175109.","productDescription":"Report: ix, 71 p.; 21 Plates; 2 Data Releases","numberOfPages":"86","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066339","costCenters":[{"id":269,"text":"FLWSC-Ft. 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U.S. Geological Survey
4446 Pet Lane, Suite 108
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The salt marshes of Jamaica Bay serve as a recreational outlet for New York City residents, mitigate wave impacts during coastal storms, and provide habitat for critical wildlife species. Hurricanes have been recognized as one of the critical drivers of coastal wetland morphology due to their effects on hydrodynamics and sediment transport, deposition, and erosion processes. In this study, the Delft3D modeling suite was utilized to examine the effects of Hurricane Sandy (2012) on salt marsh morphology in Jamaica Bay. Observed marsh elevation change and accretion from rod Surface Elevation Tables and feldspar Marker Horizons (SET-MH) and hydrodynamic measurements during Hurricane Sandy were used to calibrate and validate the wind-waves-surge-sediment transport-morphology coupled model. The model results agreed well with in situ field measurements. The validated model was then used to detect salt marsh morphological change due to Sandy across Jamaica Bay. Model results indicate that the island-wide morphological changes in the bay's salt marshes due to Sandy were in the range of −30 mm (erosion) to +15 mm (deposition), and spatially complex and heterogeneous. The storm generated paired deposition and erosion patches at local scales. Salt marshes inside the west section of the bay showed erosion overall while marshes inside the east section showed deposition from Sandy. The net sediment amount that Sandy brought into the bay is only about 1% of the total amount of reworked sediment within the bay during the storm. Numerical experiments show that waves and vegetation played a critical role in sediment transport and associated wetland morphological change in Jamaica Bay. Furthermore, without the protection of vegetation, the marsh islands of Jamaica Bay would experience both more erosion and less accretion in coastal storms.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2017.11.001","usgsCitation":"Hu, K., Chen, Q., Wang, H., Hartig, E., and Orton, P.M., 2018, Numerical modeling of salt marsh morphological change induced by Hurricane Sandy: Coastal Engineering, v. 132, p. 63-81, https://doi.org/10.1016/j.coastaleng.2017.11.001.","productDescription":"19 p.","startPage":"63","endPage":"81","ipdsId":"IP-083439","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469146,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2017.11.001","text":"Publisher Index Page"},{"id":349863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Jamaica Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.81782531738281,\n 40.65147128144057\n ],\n [\n -73.85181427001953,\n 40.648085029646715\n ],\n [\n -73.87687683105469,\n 40.64079098062354\n ],\n [\n -73.90193939208984,\n 40.627763910481185\n ],\n [\n -73.91189575195312,\n 40.60092013543081\n ],\n [\n -73.89644622802734,\n 40.577977105192225\n ],\n [\n -73.86932373046875,\n 40.57093618838665\n ],\n [\n -73.81473541259766,\n 40.58814601026153\n ],\n [\n -73.76667022705078,\n 40.595706501568905\n ],\n [\n -73.75980377197266,\n 40.622291783092706\n ],\n [\n -73.81782531738281,\n 40.65147128144057\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"132","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fad5e4b06e28e9c2276e","contributors":{"authors":[{"text":"Hu, Kelin","contributorId":177218,"corporation":false,"usgs":false,"family":"Hu","given":"Kelin","email":"","affiliations":[],"preferred":false,"id":724671,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Q. 0000-0002-6540-8758","orcid":"https://orcid.org/0000-0002-6540-8758","contributorId":56532,"corporation":false,"usgs":false,"family":"Chen","given":"Q.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":true,"id":724672,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":140432,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":724670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hartig, Ellen K.","contributorId":179351,"corporation":false,"usgs":false,"family":"Hartig","given":"Ellen K.","affiliations":[],"preferred":false,"id":724673,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Orton, Philip M.","contributorId":179354,"corporation":false,"usgs":false,"family":"Orton","given":"Philip","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":724674,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208983,"text":"70208983 - 2018 - Mapping of compositional properties of coal using isometric log-ratio transformation and sequential Gaussian simulation – A comparative study for spatial ultimate analyses data","interactions":[],"lastModifiedDate":"2020-03-10T06:30:24","indexId":"70208983","displayToPublicDate":"2017-12-05T06:24:07","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2302,"text":"Journal of Geochemical Exploration","active":true,"publicationSubtype":{"id":10}},"title":"Mapping of compositional properties of coal using isometric log-ratio transformation and sequential Gaussian simulation – A comparative study for spatial ultimate analyses data","docAbstract":"Chemical properties of coal largely determine coal handling, processing, beneficiation methods, and design of coal-fired power plants. Furthermore, these properties impact coal strength, coal blending during mining, as well as coal's gas content, which is important for mining safety. In order for these processes and quantitative predictions to be successful, safer, and economically feasible, it is important to determine and map chemical properties of coals accurately in order to infer these properties prior to mining.
Ultimate analysis quantifies principal chemical elements in coal. These elements are C, H, N, S, O, and, depending on the basis, ash, and/or moisture. The basis for the data is determined by the condition of the sample at the time of analysis, with an “as-received” basis being the closest to sampling conditions and thus to the in-situ conditions of the coal. The parts determined or calculated as the result of ultimate analyses are compositions, reported in weight percent, and pose the challenges of statistical analyses of compositional data. The treatment of parts using proper compositional methods may be even more important in mapping them, as most mapping methods carry uncertainty due to partial sampling as well.
In this work, we map the ultimate analyses parts of the Springfield coal from an Indiana section of the Illinois basin, USA, using sequential Gaussian simulation of isometric log-ratio transformed compositions. We compare the results with those of direct simulations of compositional parts. We also compare the implications of these approaches in calculating other properties using correlations to identify the differences and consequences. Although the study here is for coal, the methods described in the paper are applicable to any situation involving compositional data and its mapping.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gexplo.2017.11.022","usgsCitation":"Karacan, C.O., and Olea, R.A., 2018, Mapping of compositional properties of coal using isometric log-ratio transformation and sequential Gaussian simulation – A comparative study for spatial ultimate analyses data: Journal of Geochemical Exploration, v. 186, p. 36-49, https://doi.org/10.1016/j.gexplo.2017.11.022.","productDescription":"14 p.","startPage":"36","endPage":"49","ipdsId":"IP-085076","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":469151,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5743214","text":"External Repository"},{"id":373033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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U.S. Geological Survey
Mail Stop 956
12201 Sunrise Valley Drive
Reston, VA 20192
https://energy.usgs.gov/
Identifying areas where deteriorating sewer infrastructure is in close proximity to surface waterways is needed to map likely connections between sewers and streams. We present a method to estimate sewer installation year and deterioration status using historical maps of the sewer network, parcel-scale property assessment data, and pipe material. Areas where streams were likely buried into the sewer system were mapped by intersecting the historical stream network derived from a 10-m resolution digital elevation model with sewer pipe locations. Potential sewer leakage hotspots were mapped by identifying where aging sewer pipes are in close proximity (50-m) to surface waterways. Results from Pittsburgh, Pennsylvania (USA), indicated 41% of the historical stream length was lost or buried and the potential interface between sewers and streams is great. The co-location of aging sewer infrastructure (>75 years old) near stream channels suggests that 42% of existing streams are located in areas with a high potential for sewer leakage if sewer infrastructure fails. Mapping the sewer-stream interface provides an approach to better understand areas were failing sewers may contribute a disproportional amount of nutrients and other pathogens to surface waterways.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.landurbplan.2017.04.011","usgsCitation":"Hopkins, K.G., and Bain, D., 2018, Research note: Mapping spatial patterns in sewer age, material, and proximity to surface waterways to infer sewer leakage hotspots: Landscape and Urban Planning, v. 170, p. 320-324, https://doi.org/10.1016/j.landurbplan.2017.04.011.","productDescription":"5 p.","startPage":"320","endPage":"324","ipdsId":"IP-077253","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469179,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.landurbplan.2017.04.011","text":"Publisher Index Page"},{"id":347268,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","county":" Allegheny 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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f0511fe4b0220bbd9a1d6c","contributors":{"authors":[{"text":"Hopkins, Kristina G. 0000-0003-1699-9384 khopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1699-9384","contributorId":195604,"corporation":false,"usgs":true,"family":"Hopkins","given":"Kristina","email":"khopkins@usgs.gov","middleInitial":"G.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":713958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bain, Daniel J.","contributorId":29276,"corporation":false,"usgs":true,"family":"Bain","given":"Daniel J.","affiliations":[],"preferred":false,"id":713959,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191455,"text":"70191455 - 2018 - Meteorological and environmental variables affect flight behaviour and decision-making of an obligate soaring bird, the California Condor Gymnogyps californianus","interactions":[],"lastModifiedDate":"2017-12-11T13:35:23","indexId":"70191455","displayToPublicDate":"2017-10-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1961,"text":"Ibis","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Meteorological and environmental variables affect flight behaviour and decision-making of an obligate soaring bird, the California Condor Gymnogyps californianus","title":"Meteorological and environmental variables affect flight behaviour and decision-making of an obligate soaring bird, the California Condor Gymnogyps californianus","docAbstract":"The movements of animals are limited by evolutionary constraints and ecological processes and are strongly influenced by the medium through which they travel. For flying animals, variation in atmospheric conditions is critically influential in movement. Obligate soaring birds depend on external sources of updraft more than do other flying species, as without that updraft they are unable to sustain flight for extended periods. These species are therefore good models for understanding how the environment can influence decisions about movement. We used meteorological and topographic variables to understand the environmental influences on the decision to engage in flight by obligate soaring and critically endangered California Condors Gymnogyps californianus. Condors were more likely to fly, soared at higher altitudes and flew over smoother terrain when weather conditions promoted either thermal or orographic updrafts, for example when turbulence and solar radiation were higher and when winds from the east and north were stronger. However, increased atmospheric stability, which is inconsistent with thermal development but may be associated with orographic updrafts, was correlated with a somewhat higher probability of being in flight at lower altitudes and over rougher terrain. The close and previously undescribed linkages between Condor flight and conditions that support development of thermal and orographic updrafts provide important insight into the behaviour of obligate soaring birds and into the environmental parameters that may define the currently expanding distribution of Condors within and outside the state of California.
","language":"English","publisher":"Wiley","doi":"10.1111/ibi.12531","usgsCitation":"Poessel, S.A., Brandt, J., Miller, T.A., and Katzner, T., 2018, Meteorological and environmental variables affect flight behaviour and decision-making of an obligate soaring bird, the California Condor Gymnogyps californianus: Ibis, v. 160, no. 1, p. 36-53, https://doi.org/10.1111/ibi.12531.","productDescription":"18 p.","startPage":"36","endPage":"53","ipdsId":"IP-082014","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":346626,"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 -122.10205078125,\n 34.15272698011818\n ],\n [\n -117.861328125,\n 34.15272698011818\n ],\n [\n -117.861328125,\n 36.958671131530316\n ],\n [\n -122.10205078125,\n 36.958671131530316\n ],\n [\n -122.10205078125,\n 34.15272698011818\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"160","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-06","publicationStatus":"PW","scienceBaseUri":"59e5c51be4b05fe04cd1c9cc","contributors":{"authors":[{"text":"Poessel, Sharon A. 0000-0002-0283-627X spoessel@usgs.gov","orcid":"https://orcid.org/0000-0002-0283-627X","contributorId":168465,"corporation":false,"usgs":true,"family":"Poessel","given":"Sharon","email":"spoessel@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":712338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brandt, Joseph","contributorId":127742,"corporation":false,"usgs":false,"family":"Brandt","given":"Joseph","affiliations":[{"id":7133,"text":"California Condor Recovery Program, US Fish and Wildlife Service, Ventura, CA","active":true,"usgs":false}],"preferred":false,"id":712339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Tricia A.","contributorId":190591,"corporation":false,"usgs":false,"family":"Miller","given":"Tricia","email":"","middleInitial":"A.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":712340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":712341,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191120,"text":"70191120 - 2018 - Soil base saturation combines with Beech Bark Disease to influence composition and structure of Sugar Maple-Beech forests in an acid rain-impacted region","interactions":[],"lastModifiedDate":"2018-06-04T16:21:37","indexId":"70191120","displayToPublicDate":"2017-09-27T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Soil base saturation combines with Beech Bark Disease to influence composition and structure of Sugar Maple-Beech forests in an acid rain-impacted region","docAbstract":"Sugar maple, an abundant and highly valued tree species in eastern North America, has experienced decline from soil calcium (Ca) depletion by acidic deposition, while beech, which often coexists with sugar maple, has been afflicted with beech bark disease (BBD) over the same period. To investigate how variations in soil base saturation combine with effects of BBD in influencing stand composition and structure, measurements of soils, canopy, subcanopy, and seedlings were taken in 21 watersheds in the Adirondack region of NY (USA), where sugar maple and beech were the predominant canopy species and base saturation of the upper B horizon ranged from 4.4 to 67%. The base saturation value corresponding to the threshold for Al mobilization (16.8%) helped to define the species composition of canopy trees and seedlings. Canopy vigor and diameter at breast height (DBH) were positively correlated (P < 0.05) with base saturation for sugar maple, but unrelated for beech. However, beech occupied lower canopy positions than sugar maple, and as base saturation increased, the average canopy position of beech decreased relative to sugar maple (P < 0.10). In low-base saturation soils, soil-Ca depletion and BBD may have created opportunities for gap-exploiting species such as red maple and black cherry, whereas in high-base saturation soils, sugar maple dominated the canopy. Where soils were beginning to recover from acidic deposition effects, sugar maple DBH and basal area increased progressively from 2000 to 2015, whereas for beech, average DBH did not change and basal area did not increase after 2010.","language":"English","publisher":"Springer","doi":"10.1007/s10021-017-0186-0","usgsCitation":"Lawrence, G.B., McDonnell, T.C., Sullivan, T.J., Dovciak, M., Bailey, S.W., Antidormi, M.R., and Zarfos, M.R., 2018, Soil base saturation combines with Beech Bark Disease to influence composition and structure of Sugar Maple-Beech forests in an acid rain-impacted region: Ecosystems, v. 21, no. 4, p. 795-810, https://doi.org/10.1007/s10021-017-0186-0.","productDescription":"16 p.","startPage":"795","endPage":"810","ipdsId":"IP-081770","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":346122,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","volume":"21","issue":"4","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-18","publicationStatus":"PW","scienceBaseUri":"59ccb8a4e4b017cf314383d4","contributors":{"authors":[{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711284,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McDonnell, Todd C. 0000-0002-5231-105X","orcid":"https://orcid.org/0000-0002-5231-105X","contributorId":196721,"corporation":false,"usgs":false,"family":"McDonnell","given":"Todd","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":711285,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Timothy J.","contributorId":77812,"corporation":false,"usgs":true,"family":"Sullivan","given":"Timothy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":711286,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dovciak, Martin","contributorId":196723,"corporation":false,"usgs":false,"family":"Dovciak","given":"Martin","email":"","affiliations":[],"preferred":false,"id":711287,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bailey, Scott W. 0000-0002-9160-156X","orcid":"https://orcid.org/0000-0002-9160-156X","contributorId":178217,"corporation":false,"usgs":false,"family":"Bailey","given":"Scott","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":711288,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Antidormi, Michael R. 0000-0002-3967-1173 mantidormi@usgs.gov","orcid":"https://orcid.org/0000-0002-3967-1173","contributorId":150722,"corporation":false,"usgs":true,"family":"Antidormi","given":"Michael","email":"mantidormi@usgs.gov","middleInitial":"R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711289,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zarfos, Michael R. 0000-0002-2902-4773","orcid":"https://orcid.org/0000-0002-2902-4773","contributorId":196724,"corporation":false,"usgs":false,"family":"Zarfos","given":"Michael","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":711290,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70190480,"text":"70190480 - 2018 - A detailed risk assessment of shale gas development on headwater streams in the Pennsylvania portion of the Upper Susquehanna River Basin, U.S.A.","interactions":[],"lastModifiedDate":"2017-09-01T10:07:51","indexId":"70190480","displayToPublicDate":"2017-09-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"A detailed risk assessment of shale gas development on headwater streams in the Pennsylvania portion of the Upper Susquehanna River Basin, U.S.A.","docAbstract":"The development of unconventional oil and gas (UOG) involves infrastructure development (well pads, roads and pipelines), well drilling and stimulation (hydraulic fracturing), and production; all of which have the potential to affect stream ecosystems. Here, we developed a fine-scaled (1:24,000) catchment-level disturbance intensity index (DII) that included 17 measures of UOG capturing all steps in the development process (infrastructure, water withdrawals, probabilistic spills) that could affect headwater streams (< 200 km2 in upstream catchment) in the Upper Susquehanna River Basin in Pennsylvania, U.S.A. The DII ranged from 0 (no UOG disturbance) to 100 (the catchment with the highest UOG disturbance in the study area) and it was most sensitive to removal of pipeline cover, road cover and well pad cover metrics. We related this DII to three measures of high quality streams: Pennsylvania State Exceptional Value (EV) streams, Class A brook trout streams and Eastern Brook Trout Joint Venture brook trout patches. Overall only 3.8% of all catchments and 2.7% of EV stream length, 1.9% of Class A streams and 1.2% of patches were classified as having medium to high level DII scores (> 50). Well density, often used as a proxy for development, only correlated strongly with well pad coverage and produced materials, and therefore may miss potential effects associated with roads and pipelines, water withdrawals and spills. When analyzed with a future development scenario, 91.1% of EV stream length, 68.7% of Class A streams and 80.0% of patches were in catchments with a moderate to high probability of development. Our method incorporated the cumulative effects of UOG on streams and can be used to identify catchments and reaches at risk to existing stressors or future development.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2017.07.247","usgsCitation":"Maloney, K.O., Young, J.A., Faulkner, S., Hailegiorgis, A., Slonecker, E., and Milheim, L., 2018, A detailed risk assessment of shale gas development on headwater streams in the Pennsylvania portion of the Upper Susquehanna River Basin, U.S.A.: Science of the Total Environment, v. 610-611, p. 154-166, https://doi.org/10.1016/j.scitotenv.2017.07.247.","productDescription":"13 p.","startPage":"154","endPage":"166","ipdsId":"IP-087579","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":461145,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2017.07.247","text":"Publisher Index Page"},{"id":438087,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Z036NF","text":"USGS data release","linkHelpText":"Shale gas data used in development of the Disturbance Intensity Index for the Pennsylvania portion of the Upper Susquehanna River basin in Maloney et al. 2018."},{"id":345411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Upper Susquehanna River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.046630859375,\n 40.53050177574321\n ],\n [\n -75.047607421875,\n 40.53050177574321\n ],\n [\n -75.047607421875,\n 42.00848901572399\n ],\n [\n -79.046630859375,\n 42.00848901572399\n ],\n [\n -79.046630859375,\n 40.53050177574321\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"610-611","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59aa71d8e4b0e9bde130cfe4","contributors":{"authors":[{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":709393,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":709394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Faulkner, Stephen 0000-0001-5295-1383 faulkners@usgs.gov","orcid":"https://orcid.org/0000-0001-5295-1383","contributorId":146152,"corporation":false,"usgs":true,"family":"Faulkner","given":"Stephen","email":"faulkners@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":709395,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hailegiorgis, Atesmachew","contributorId":196129,"corporation":false,"usgs":false,"family":"Hailegiorgis","given":"Atesmachew","email":"","affiliations":[],"preferred":false,"id":709396,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Slonecker, E. Terrence","contributorId":20677,"corporation":false,"usgs":true,"family":"Slonecker","given":"E. Terrence","affiliations":[],"preferred":false,"id":709398,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Milheim, Lesley lmilheim@usgs.gov","contributorId":168592,"corporation":false,"usgs":true,"family":"Milheim","given":"Lesley","email":"lmilheim@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":709397,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70190589,"text":"70190589 - 2018 - The influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware","interactions":[],"lastModifiedDate":"2018-03-29T12:51:13","indexId":"70190589","displayToPublicDate":"2017-06-30T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3751,"text":"Wetlands Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"The influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware","docAbstract":"The dependence of downstream waters on upstream ecosystems necessitates an improved understanding of watershed-scale hydrological interactions including connections between wetlands and streams. An evaluation of such connections is challenging when, (1) accurate and complete datasets of wetland and stream locations are often not available and (2) natural variability in surface-water extent influences the frequency and duration of wetland/stream connectivity. The Upper Choptank River watershed on the Delmarva Peninsula in eastern Maryland and Delaware is dominated by a high density of small, forested wetlands. In this analysis, wetland/stream surface water connections were quantified using multiple wetland and stream datasets, including headwater streams and depressions mapped from a lidar-derived digital elevation model. Surface-water extent was mapped across the watershed for spring 2015 using Landsat-8, Radarsat-2 and Worldview-3 imagery. The frequency of wetland/stream connections increased as a more complete and accurate stream dataset was used and surface-water extent was included, in particular when the spatial resolution of the imagery was finer (i.e., <10 m). Depending on the datasets used, 12–60% of wetlands by count (21–93% of wetlands by area) experienced surface-water interactions with streams during spring 2015. This translated into a range of 50–94% of the watershed contributing direct surface water runoff to streamflow. This finding suggests that our interpretation of the frequency and duration of wetland/stream connections will be influenced not only by the spatial and temporal characteristics of wetlands, streams and potential flowpaths, but also by the completeness, accuracy and resolution of input datasets.
","language":"English","publisher":"Springer","doi":"10.1007/s11273-017-9554-y","usgsCitation":"Vanderhoof, M.K., Distler, H., Lang, M.W., and Alexander, L.C., 2018, The influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware: Wetlands Ecology and Management, v. 26, no. 1, p. 63-86, https://doi.org/10.1007/s11273-017-9554-y.","productDescription":"24 p.","startPage":"63","endPage":"86","ipdsId":"IP-084257","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":469198,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9534041","text":"External Repository"},{"id":438088,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70C4T8F","text":"USGS data release","linkHelpText":"Data Release for the influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware"},{"id":352120,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland","otherGeospatial":"Delmarva Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.1,\n 38.5\n ],\n [\n -76.1,\n 39.1\n ],\n [\n -75.5,\n 39.1\n ],\n [\n -75.5,\n 38.5\n ],\n [\n -76.1,\n 38.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-08","publicationStatus":"PW","scienceBaseUri":"5afee787e4b0da30c1bfc2b6","contributors":{"authors":[{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":709917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Distler, Hayley 0000-0001-5006-1360 hdistler@usgs.gov","orcid":"https://orcid.org/0000-0001-5006-1360","contributorId":179359,"corporation":false,"usgs":true,"family":"Distler","given":"Hayley","email":"hdistler@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":709918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lang, Megan W.","contributorId":196284,"corporation":false,"usgs":false,"family":"Lang","given":"Megan","email":"","middleInitial":"W.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":709919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alexander, Laurie C.","contributorId":196285,"corporation":false,"usgs":false,"family":"Alexander","given":"Laurie","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":709920,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70260162,"text":"70260162 - 2018 - Focused seismicity triggered by flank instability on Kīlauea's Southwest Rift Zone","interactions":[],"lastModifiedDate":"2024-10-29T11:49:45.02765","indexId":"70260162","displayToPublicDate":"2017-03-17T06:47:36","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Focused seismicity triggered by flank instability on Kīlauea's Southwest Rift Zone","docAbstract":"Crystalline bedrock aquifers in New England and parts of New Jersey and New York (NECR aquifers) are a major source of drinking water. Because the quality of water in these aquifers is highly variable, the U.S. Geological Survey (USGS) statistically analyzed chemical data on samples of untreated groundwater collected from 117 domestic bedrock wells in New England, New York, and New Jersey, and from 4,775 public-supply bedrock wells in New England to characterize the quality of the groundwater. The domestic-well data were from samples collected by the USGS National Water-Quality Assessment (NAWQA) Program from 1995 through 2007. The public-supply-well data were from samples collected for the U.S. Environmental Protection Agency (USEPA) Safe Drinking Water Act (SDWA) Program from 1997 through 2007. Chemical data compiled from the domestic wells include pH, specific conductance, dissolved oxygen, alkalinity, and turbidity; 6 nitrogen and phosphorus compounds, 14 major ions, 23 trace elements, 222radon gas (radon), 48 pesticide compounds, and 82 volatile organic compounds (VOCs). Additional samples were collected from the domestic wells for the analysis of gross alpha- and gross beta-particle radioactivity, radium isotopes, chlorofluorocarbon isotopes, and the dissolved gases methane, carbon dioxide, nitrogen, and argon. Chemical data compiled from the public-supply wells include pH, specific conductance, nitrate, iron, manganese, sodium, chloride, fluoride, arsenic, uranium, radon, combined radium (226radium plus 228radium), gross alpha-particle radioactivity, and methyl tert-butyl ether (MtBE).
Patterns in fluoride, arsenic, uranium, and radon distributions were discernable when the data were compared to lithology groupings of the bedrock, indicating that the type of bedrock has an effect on the quality of groundwater from NECR aquifers. Fluoride concentrations were significantly higher in groundwater samples from the alkali granite, peraluminous granite, and metaluminous granite lithology groups than from samples in the other lithology groups. Water samples from 1.4 percent of 2,167 studied wells had fluoride concentrations that were equal to or greater than the maximum contaminant level (MCL) of 4 milligrams per liter (mg/L) and 7.5 percent of the wells had fluoride concentrations that were equal to or greater than the secondary MCL of 2 mg/L. For arsenic, groundwater samples from the calcareous metasedimentary rocks in the New Hampshire-Maine geologic province, peraluminous granite, and pelitic rocks lithology groups had higher concentrations than did samples from the other lithology groups. Water samples from 13.3 percent of 2,054 studied wells had arsenic concentrations that were equal to or greater than the MCL of 10 micrograms per liter (μg/L), about double the national rate of occurrence in community-supply systems and in domestic wells of the United States. Uranium concentrations were significantly higher in groundwater samples from the peraluminous granite, alkali granite, and calcareous metasedimentary rocks in the New Hampshire-Maine geologic province lithology groups than from samples in the other lithology groups. Water samples from 14.2 percent of 556 studied wells had uranium concentrations equal to or greater than the MCL of 30 μg/L. Radon activities were equal to or greater than the proposed MCL of 300 picocuries per liter (pCi/L) in 95 percent of 943 studied wells, and 33 percent of the wells had radon activities were equal to or greater than the proposed alternative maximum contaminant level (AMCL) of 4,000 pCi/L. Radon activities exceeded the proposed AMCL in 20 percent or more of groundwater samples in each of the studied lithology groups with a minimum of 9 samples, but radon activities were significantly higher in groundwater samples from the alkali granite, peraluminous granite, and Narragansett basin metasedimentary rocks lithology groups. Water samples from 3.2 percent of 564 studied wells had combined radium activities equal to or greater than the MCL of 5 pCi/L; however, combined radium activities were not significantly different among the studied lithology groups.
Land use and population density also were evaluated to explain patterns in water quality. Concentrations of nitrate, sodium, chloride, and MtBE from the studied wells were significantly greater in areas of high population density (≥50 persons per square kilometer) than in areas of low population density (<50 persons per square kilometer). Concentrations of sodium, chloride, and MtBE from the studied wells were significantly greater in areas classified as developed (urban lands) than in areas classified as undeveloped (forested), agricultural, or mixed (no dominant land use). Nitrate concentrations from the public-supply wells were not significantly different among the four land use categories, but nitrate concentrations from the domestic wells were significantly greater in areas classified as developed than in areas classified as undeveloped, agricultural, or mixed.
Chloride to bromide mass ratios in the domestic well samples indicate that the groundwater was probably affected by at least three halogen sources: local precipitation and recharge waters, remnant seawater and connate waters evolved from seawater, and recharge waters affected by road salt. The groundwater in the NECR aquifers generally contained low concentrations of nitrate, VOCs, and pesticides. Less than 1 percent of water samples from 4,781 studied wells had concentrations of nitrate greater than the MCL of 10 mg/L. Less than 1 percent of water samples from 1,299 studied wells exceeded the USEPA advisory level of 20 to 40 μg/L for MtBE. None of the other studied VOCs exceeded a human health benchmark. MtBE (36 percent frequency detection) and chloroform (32.9 percent frequency detection) were the most frequently detected (>0.02 μg/L) VOCs in the domestic wells. MtBE was detected more often in water samples with apparent ages of less than 25 years than in water samples with apparent ages greater than 25 years. This finding is consistent with the time period of high MtBE use in areas in the United States where reformulated gasoline was mandated. The largest pesticide concentration was an estimated concentration of 0.06 μg/L for the herbicide metolachlor. Deethylatrazine, a degradate of atrazine, (18 percent frequency detection) and atrazine (8 percent frequency detection) were the only pesticide compounds detected (>0.001 μg/L) in more than 3 percent of the domestic wells. None of the detected pesticide compounds exceeded human health benchmarks.
Concentrations of nitrate and gross alpha-particle activities were significantly greater in the water samples from the domestic wells than in samples from the public-supply wells. Concentrations of sodium, chloride, iron, manganese, and uranium were significantly greater in the water samples from the public-supply wells than in the samples from the domestic wells. One possible explanation may be related to differences in field processing (filtered samples from the domestic wells compared to unfiltered samples from the public-supply wells).
The high frequency of detections for a wide variety of manmade and naturally occurring contaminants in both domestic and public-supply wells shows the vulnerability of NECR aquifers to contamination. The highly variable water quality and the association with highly variable lithology of crystalline bedrock underscores the importance of testing individual wells to determine if concentrations for the most commonly detected contaminants exceed human health benchmarks.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115220","isbn":"ISBN 978-1-411-33417-5","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Flanagan, S.M., Ayotte, J.D., Robinson, G.R., Jr., 2018, Quality of water from crystalline rock aquifers in New England, New Jersey, and New York, 1995–2007 (ver.1.1, April 2018): U.S. Geological Survey 2011–5220, 104 p., https://doi.org/10.3133/sir20115220.\n","productDescription":"Report: xiv, 104 p.","numberOfPages":"122","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"1995-01-01","temporalEnd":"2007-12-31","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":353386,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5220/pdf/sir20115220.pdf","text":"Report","size":"9.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2011-5220"},{"id":353387,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2011/5220/versionHist.txt","size":"1.33 KB","linkFileType":{"id":2,"text":"txt"}},{"id":257873,"rank":100,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5220/index.html","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":257884,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2011/5220/images/coverthb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Rhode Island, and Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.03662109375,\n 40.56389453066509\n ],\n [\n -66.90673828125,\n 40.56389453066509\n ],\n [\n -66.90673828125,\n 47.39834920035926\n ],\n [\n -75.03662109375,\n 47.39834920035926\n ],\n [\n -75.03662109375,\n 40.56389453066509\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally released June 25, 2012; Version 1.1: April 13, 2018","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Ground water historically has been the sole source of water supply for the Town of Yucca Valley in the Warren subbasin of the Morongo ground-water basin, California. An imbalance between ground-water recharge and pumpage caused ground-water levels in the subbasin to decline by as much as 300 feet from the late 1940s through 1994. In response, the local water district, Hi-Desert Water District, instituted an artificial recharge program in February 1995 using imported surface water to replenish the ground water. The artificial recharge program resulted in water-level recoveries of as much as 250 feet in the vicinity of the recharge ponds between February 1995 and December 2001; however, nitrate concentrations in some wells also increased from a background concentration of 10 milligrams per liter to more than the U.S. Environmental Protection Agency (USEPA) maximum contaminant level (MCL) of 44 milligrams per liter (10 milligrams per liter as nitrogen).
The objectives of this study were to: (1) evaluate the sources of the high-nitrate concentrations that occurred after the start of the artificial-recharge program, (2) develop a ground-water flow and solute-transport model to better understand the source and transport of nitrates in the aquifer system, and (3) utilize the calibrated models to evaluate the possible effect of a proposed conjunctive-use project. These objectives were accomplished by collecting water-level and water-quality data for the subbasin and assessing changes that have occurred since artificial recharge began. Collected data were used to calibrate the ground-water flow and solute-transport models.
Data collected for this study indicate that the areal extent of the water-bearing deposits is much smaller (about 5.5 square miles versus 19 square miles) than that of the subbasin. These water-bearing deposits are referred to in this report as the Warren ground-water basin. Faults separate the ground-water basin into five hydrogeologic units: the west, the midwest, the mideast, the east and the northeast hydrogeologic units.
Water-quality analyses indicate that septage from septic tanks is the primary source of the high-nitrate concentrations measured in the Warren ground-water basin. Water-quality and stable-isotope data, collected after the start of the artificial recharge program, indicate that mixing occurs between imported water and native ground water, with the highest recorded nitrate concentrations in the midwest and the mideast hydrogeologic units. In general, the timing of the increase in measured nitrate concentrations in the midwest hydrogeologic unit is directly related to the distance of the monitoring well from a recharge site, indicating that the increase in nitrate concentrations is related to the artificial recharge program. Nitrate-to-chloride and nitrogen-isotope data indicate that septage is the source of the measured increase in nitrate concentrations in the midwest and the mideast hydrogeologic units. Samples from four wells in the Warren ground-water basin were analyzed for caffeine and selected human pharmaceutical products; these analyses suggest that septage is reaching the water table.
There are two possible conceptual models that explain how high-nitrate septage reaches the water table: (1) the continued downward migration of septage through the unsaturated zone to the water table and (2) rising water levels, a result of the artificial recharge program, entraining septage in the unsaturated zone. The observations that nitrate concentrations increase in ground-water samples from wells soon after the start of the artificial recharge program in 1995 and that the largest increase in nitrate concentrations occur in the midwest and mideast hydrogeologic units where the largest increase in water levels occur indicate the validity of the second conceptual model (rising water levels). The potential nitrate concentration resulting from a water-level rise in the midwest and mideast hydrogeologic units was estimated using a simple mixing-cell model. The estimated value is within the range of concentrations measured in samples from wells, further indicating the validity of the second conceptual model.
A ground-water flow model and a solute-transport model were developed for the Warren ground-water basin for the period 1956-2001. MODFLOW-96 was used for the ground-water flow model and MOC3D was used for the solute-transport model. The model cell size is about 500 feet by 500 feet and the models were discretized vertically into three layers. The models were calibrated using a trial-and-error approach using water-level and nitrate-concentration data collected between 1956-2001. In order to better match the measured data, low fault hydraulic characteristic values were required, thereby compartmentalizing the ground-water basin. In addition, it was necessary to parameterize the specific yield distribution for the top model layer where unconfined ground-water conditions occur into three homogeneous zones. Separate sets of specific- yield values were needed to simulate the drawdown and subsequent water-level recovery. In addition, the calibrated natural recharge was about 83 acre-feet per year. The entrainment of unsaturated-zone septage was simulated as recharge having an associated nitrate concentration. The volume of recharge was a function of the measured water-level rise between 1994-98 and the moisture content of the unsaturated zone. The nitrate concentration of the recharge water was a weighted function of the assumed nitrate concentration in the infiltrating water associated with the overlying land use. The simulated hydraulic head and nitrate concentration results were in good agreement with the measured data indicating that the mechanism for the increase in nitrate concentrations was rising water levels entraining high-nitrate septage in the unsaturated-zone.
The calibrated models were used to simulate the possible effects of a planned conjunctive-use project in the western part of the ground-water basin. The simulated project included the addition of a new recharge pond and a new extraction well. In addition, recharge at two existing recharge ponds was increased and three existing production wells were pumped, treated in a nitrate-removal facility, and used for water supply. The simulated hydraulic heads increased in the west, the mideast, and parts of the east hydrogeologic units; however, the simulated hydraulic heads decreased in the midwest and northeast hydrogeologic units. The simulated nitrate concentrations increased to above the MCL of 44 milligrams per liter (10 milligrams per liter as nitrogen) in parts of the west as a result of the increase in simulated hydraulic head. The simulated nitrate concentrations decreased in part of the midwest hydrogeologic unit as a result of the artificial recharge and pumping from the nitrate-removal wells. The simulated nitrate concentrations increased to above the MCL of 44 milligrams per liter in part of the mideast and parts of the east hydrogeologic units beneath commercial land-use areas.