Groundwater is the principal source of freshwater supply in most of Southern Maryland and Maryland’s Eastern Shore. It is also the source of freshwater supply used in the operation of the Calvert Cliffs, Chalk Point, and Morgantown power plants. Increased groundwater withdrawals over the last several decades have caused groundwater levels to decline. This report presents potentiometric-surface maps of the Aquia and Magothy aquifers and the Upper Patapsco, Lower Patapsco, and Patuxent aquifer systems using water levels measured during September 2013. Water-level difference maps are also presented for four of these aquifers. The water-level differences in the Aquia aquifer are shown using groundwater-level data from 1982 and 2013, while the water-level differences are presented for the Magothy aquifer using data from 1975 and 2013. Water-level difference maps for both the Upper Patapsco and Lower Patapsco aquifer systems are presented using data from 1990 and 2013.
\nThe potentiometric surface maps show water levels ranging from 165 feet above sea level to 199 feet below sea level. Water levels have declined by as much as 113 feet in the Aquia aquifer since 1982, 81 feet in the Magothy aquifer since 1975, and 61 and 95 feet in the Upper Patapsco and Lower Patapsco aquifer systems, respectively, since 1990.
","language":"English","publisher":"Maryland Geological Survey","publisherLocation":"Baltimore, MD","usgsCitation":"Staley, A., Andreasen, D., and Curtin, S.E., 2014, Potentiometric surface and water-level difference maps of selected confined aquifers in Southern Maryland and Maryland’s Eastern Shore, 1975-2013: Open-File Report 14-02-02, iii, 29 p.","productDescription":"iii, 29 p.","numberOfPages":"34","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058624","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":325168,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":324435,"type":{"id":15,"text":"Index Page"},"url":"https://www.mgs.md.gov/reports/OFR_14-02-02.pdf"}],"country":"United States","state":"Maryland, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.8111572265625,\n 39.63530729658601\n ],\n [\n -75.816650390625,\n 38.225235239076824\n ],\n [\n -76.3934326171875,\n 37.95719224376526\n ],\n [\n -76.6241455078125,\n 38.14751758025121\n ],\n [\n -76.75048828125,\n 38.16047628099622\n ],\n [\n -76.8768310546875,\n 38.16047628099622\n ],\n [\n -76.9757080078125,\n 38.24680876017446\n ],\n [\n -77.025146484375,\n 38.298559092254344\n ],\n [\n -77.2833251953125,\n 38.3287297527893\n ],\n [\n -77.32177734375,\n 38.42347008084994\n ],\n [\n -77.27783203125,\n 38.55246141354153\n ],\n [\n -77.2723388671875,\n 38.6897975322717\n ],\n [\n -76.607666015625,\n 39.279041894366785\n ],\n [\n -76.08032226562499,\n 39.592990390285024\n ],\n [\n -75.8111572265625,\n 39.63530729658601\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57876630e4b0d27deb36e19f","contributors":{"authors":[{"text":"Staley, Andrew W.","contributorId":43319,"corporation":false,"usgs":true,"family":"Staley","given":"Andrew W.","affiliations":[],"preferred":false,"id":640826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andreasen, David C.","contributorId":59003,"corporation":false,"usgs":true,"family":"Andreasen","given":"David C.","affiliations":[],"preferred":false,"id":640827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Curtin, Stephen E. securtin@usgs.gov","contributorId":3703,"corporation":false,"usgs":true,"family":"Curtin","given":"Stephen","email":"securtin@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640825,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70138540,"text":"70138540 - 2014 - Development of a portable active long-path differential optical absorption spectroscopy system for volcanic gas measurements","interactions":[],"lastModifiedDate":"2019-03-14T08:34:07","indexId":"70138540","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3855,"text":"Journal of Sensors and Sensor Systems","active":true,"publicationSubtype":{"id":10}},"title":"Development of a portable active long-path differential optical absorption spectroscopy system for volcanic gas measurements","docAbstract":" Active long-path differential optical absorption spectroscopy (LP-DOAS) has been an effective tool for measuring atmospheric trace gases for several decades. However, instruments were large, heavy and power-inefficient, making their application to remote environments extremely challenging. Recent developments in fibre-coupling telescope technology and the availability of ultraviolet light emitting diodes (UV-LEDS) have now allowed us to design and construct a lightweight, portable, low-power LP-DOAS instrument for use at remote locations and specifically for measuring degassing from active volcanic systems. The LP-DOAS was used to measure sulfur dioxide (SO2) emissions from La Fossa crater, Vulcano, Italy, where column densities of up to 1.2 × 1018 molec cm−2 (~ 500 ppmm) were detected along open paths of up to 400 m in total length. The instrument's SO2 detection limit was determined to be 2 × 1016 molec cm−2 (~ 8 ppmm), thereby making quantitative detection of even trace amounts of SO2 possible. The instrument is capable of measuring other volcanic volatile species as well. Though the spectral evaluation of the recorded data showed that chlorine monoxide (ClO) and carbon disulfide (CS2) were both below the instrument's detection limits during the experiment, the upper limits for the X / SO2 ratio (X = ClO, CS2) could be derived, and yielded 2 × 10−3 and 0.1, respectively. The robust design and versatility of the instrument make it a promising tool for monitoring of volcanic degassing and understanding processes in a range of volcanic systems.
Systematic calibration errors must be taken into account because they can substantially impact the accuracy of inverted subsurface resistivity models derived from frequency-domain electromagnetic data, resulting in potentially misleading interpretations. We have developed an approach that uses data acquired at multiple elevations over the same location to assess calibration errors. A significant advantage is that this method does not require prior knowledge of subsurface properties from borehole or ground geophysical data (though these can be readily incorporated if available), and is, therefore, well suited to remote areas. The multielevation data were used to solve for calibration parameters and a single subsurface resistivity model that are self consistent over all elevations. The deterministic and Bayesian formulations of the multielevation approach illustrate parameter sensitivity and uncertainty using synthetic- and field-data examples. Multiplicative calibration errors (gain and phase) were found to be better resolved at high frequencies and when data were acquired over a relatively conductive area, whereas additive errors (bias) were reasonably resolved over conductive and resistive areas at all frequencies. The Bayesian approach outperformed the deterministic approach when estimating calibration parameters using multielevation data at a single location; however, joint analysis of multielevation data at multiple locations using the deterministic algorithm yielded the most accurate estimates of calibration parameters. Inversion results using calibration-corrected data revealed marked improvement in misfit, lending added confidence to the interpretation of these models.
This study projects future (e.g., 2050 and 2099) grassland productivities in the Greater Platte River Basin (GPRB) using ecosystem performance (EP, a surrogate for measuring ecosystem productivity) models and future climate projections. The EP models developed from a previous study were based on the satellite vegetation index, site geophysical and biophysical features, and weather and climate drivers. The future climate data used in this study were derived from the National Center for Atmospheric Research Community Climate System Model 3.0 ‘SRES A1B’ (a ‘middle’ emissions path). The main objective of this study is to assess the future sustainability of the potential biofuel feedstock areas identified in a previous study. Results show that the potential biofuel feedstock areas (the more mesic eastern part of the GPRB) will remain productive (i.e., aboveground grassland biomass productivity >2750 kg ha−1 year−1) with a slight increasing trend in the future. The spatially averaged EPs for these areas are 3519, 3432, 3557, 3605, 3752, and 3583 kg ha−1 year−1 for current site potential (2000–2008 average), 2020, 2030, 2040, 2050, and 2099, respectively. Therefore, the identified potential biofuel feedstock areas will likely continue to be sustainable for future biofuel development. On the other hand, grasslands identified as having no biofuel potential in the drier western part of the GPRB would be expected to stay unproductive in the future (spatially averaged EPs are 1822, 1691, 1896, 2306, 1994, and 2169 kg ha−1 year−1 for site potential, 2020, 2030, 2040, 2050, and 2099). These areas should continue to be unsuitable for biofuel feedstock development in the future. These future grassland productivity estimation maps can help land managers to understand and adapt to the expected changes in future EP in the GPRB and to assess the future sustainability and feasibility of potential biofuel feedstock areas.
","language":"English","publisher":"WIley","doi":"10.1111/gcbb.12059","usgsCitation":"Gu, Y., Wylie, B.K., Boyte, S.P., and Phuyal, K.P., 2014, Projecting future grassland productivity to assess thesustainability of potential biofuel feedstock areas in theGreater Platte River Basin: GCB Bioenergy, v. 6, no. 1, p. 35-43, https://doi.org/10.1111/gcbb.12059.","productDescription":"9 p.","startPage":"35","endPage":"43","ipdsId":"IP-041312","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473288,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcbb.12059","text":"Publisher Index Page"},{"id":341965,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2013-07-17","publicationStatus":"PW","scienceBaseUri":"54faddbbe4b02419550db6df","contributors":{"authors":[{"text":"Gu, Yingxin 0000-0002-3544-1856 ygu@usgs.gov","orcid":"https://orcid.org/0000-0002-3544-1856","contributorId":139586,"corporation":false,"usgs":true,"family":"Gu","given":"Yingxin","email":"ygu@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":541945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":541944,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyte, Stephen P. 0000-0002-5462-3225 sboyte@usgs.gov","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":139238,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen","email":"sboyte@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":541943,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phuyal, Khem P.","contributorId":28517,"corporation":false,"usgs":true,"family":"Phuyal","given":"Khem","email":"","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":541946,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70161758,"text":"70161758 - 2014 - Estimating structural collapse fragility of generic building typologies using expert judgment","interactions":[],"lastModifiedDate":"2021-10-13T16:26:50.090642","indexId":"70161758","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Estimating structural collapse fragility of generic building typologies using expert judgment","docAbstract":"The structured expert elicitation process proposed by Cooke (1991), \nhereafter referred to as Cooke’s approach, is applied for the first time \nin the realm of structural collapse-fragility assessment for selected generic \nconstruction types. Cooke’s approach works on the principle of objective \ncalibration scoring of judgments coupled with hypothesis testing used in classical\n statistics. The performance-based scoring system reflects the combined \nmeasure of an expert’s informativeness about variables in the problem area \nunder consideration, and their ability to enumerate, in a statistically accurate \nway through expressing their true beliefs, the quantitative uncertainties \nassociated with their assessments. We summarize the findings of an expert \nelicitation workshop in which a dozen earthquake-engineering professionals\n from around the world were engaged to estimate seismic collapse fragility for\n generic construction types. Development of seismic collapse fragility \nfunctions was accomplished by combining their judgments using weights \nderived from Cooke’s method. Although substantial effort was needed to\n elicit the inputs of these experts successfully, we anticipate that the elicitation\n strategy described here will gain momentum in a wide variety of earthquake \nseismology and engineering hazard and risk analyses where physical model \nand data limitations are inherent and objective professional judgment can fill \ngaps.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Safety, reliability, risk, and life-cycle performance of structures and infrastructures","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"1th International Conference on Structural Safety and Reliability (ICOSSAR2013)","conferenceDate":"June 16-20, 2013","conferenceLocation":"New York, NY","language":"English","publisher":"CRC Press","doi":"10.1201/b16387-130","isbn":"9781138000865","usgsCitation":"Jaiswal, K., Perkins, D., Wald, D., Aspinall, W.P., and Kiremidjian, A.S., 2014, Estimating structural collapse fragility of generic building typologies using expert judgment, in Safety, reliability, risk, and life-cycle performance of structures and infrastructures, New York, NY, June 16-20, 2013, p. 879-886, https://doi.org/10.1201/b16387-130.","productDescription":"8 p.","startPage":"879","endPage":"886","ipdsId":"IP-045829","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":340113,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-01-13","publicationStatus":"PW","scienceBaseUri":"58fdbd18e4b0074928294487","contributors":{"editors":[{"text":"Deodatis, George","contributorId":191242,"corporation":false,"usgs":false,"family":"Deodatis","given":"George","email":"","affiliations":[],"preferred":false,"id":692458,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Ellingwood, Bruce R.","contributorId":44446,"corporation":false,"usgs":true,"family":"Ellingwood","given":"Bruce","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":692459,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Frangopol, Dan M.","contributorId":191243,"corporation":false,"usgs":false,"family":"Frangopol","given":"Dan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":692460,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Jaiswal, Kishor S. kjaiswal@usgs.gov","contributorId":145925,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor S.","email":"kjaiswal@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":692461,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wald, D.J. 0000-0002-1454-4514","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":43809,"corporation":false,"usgs":true,"family":"Wald","given":"D.J.","affiliations":[],"preferred":false,"id":692462,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perkins, D.","contributorId":83589,"corporation":false,"usgs":true,"family":"Perkins","given":"D.","affiliations":[],"preferred":false,"id":692463,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aspinall, W. P.","contributorId":82077,"corporation":false,"usgs":true,"family":"Aspinall","given":"W.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":692464,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kiremidjian, Anne S.","contributorId":60649,"corporation":false,"usgs":true,"family":"Kiremidjian","given":"Anne","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":692465,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189782,"text":"70189782 - 2014 - CyberShake-derived ground-motion prediction models for the Los Angeles region with application to earthquake early warning","interactions":[],"lastModifiedDate":"2017-07-26T11:02:38","indexId":"70189782","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"CyberShake-derived ground-motion prediction models for the Los Angeles region with application to earthquake early warning","docAbstract":"Real-time applications such as earthquake early warning (EEW) typically use empirical ground-motion prediction equations (GMPEs) along with event magnitude and source-to-site distances to estimate expected shaking levels. In this simplified approach, effects due to finite-fault geometry, directivity and site and basin response are often generalized, which may lead to a significant under- or overestimation of shaking from large earthquakes (M > 6.5) in some locations. For enhanced site-specific ground-motion predictions considering 3-D wave-propagation effects, we develop support vector regression (SVR) models from the SCEC CyberShake low-frequency (<0.5 Hz) and broad-band (0–10 Hz) data sets. CyberShake encompasses 3-D wave-propagation simulations of >415 000 finite-fault rupture scenarios (6.5 ≤ M ≤ 8.5) for southern California defined in UCERF 2.0. We use CyberShake to demonstrate the application of synthetic waveform data to EEW as a ‘proof of concept’, being aware that these simulations are not yet fully validated and might not appropriately sample the range of rupture uncertainty. Our regression models predict the maximum and the temporal evolution of instrumental intensity (MMI) at 71 selected test sites using only the hypocentre, magnitude and rupture ratio, which characterizes uni- and bilateral rupture propagation. Our regression approach is completely data-driven (where here the CyberShake simulations are considered data) and does not enforce pre-defined functional forms or dependencies among input parameters. The models were established from a subset (∼20 per cent) of CyberShake simulations, but can explain MMI values of all >400 k rupture scenarios with a standard deviation of about 0.4 intensity units. We apply our models to determine threshold magnitudes (and warning times) for various active faults in southern California that earthquakes need to exceed to cause at least ‘moderate’, ‘strong’ or ‘very strong’ shaking in the Los Angeles (LA) basin. These thresholds are used to construct a simple and robust EEW algorithm: to declare a warning, the algorithm only needs to locate the earthquake and to verify that the corresponding magnitude threshold is exceeded. The models predict that a relatively moderate M6.5–7 earthquake along the Palos Verdes, Newport-Inglewood/Rose Canyon, Elsinore or San Jacinto faults with a rupture propagating towards LA could cause ‘very strong’ to ‘severe’ shaking in the LA basin; however, warning times for these events could exceed 30 s.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggu198","usgsCitation":"Bose, M., Graves, R., Gill, D., Callaghan, S., and Maechling, P.J., 2014, CyberShake-derived ground-motion prediction models for the Los Angeles region with application to earthquake early warning: Geophysical Journal International, v. 198, no. 3, p. 1438-1457, https://doi.org/10.1093/gji/ggu198.","productDescription":"20 p.","startPage":"1438","endPage":"1457","ipdsId":"IP-054646","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":473293,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1093/gji/ggu198","text":"External Repository"},{"id":344321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Los Angeles","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119,\n 33\n ],\n [\n -117,\n 33\n ],\n [\n -117,\n 35\n ],\n [\n -119,\n 35\n ],\n [\n -119,\n 33\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"198","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-07-03","publicationStatus":"PW","scienceBaseUri":"5979aa58e4b0ec1a488b8c3f","contributors":{"authors":[{"text":"Bose, Maren","contributorId":195135,"corporation":false,"usgs":false,"family":"Bose","given":"Maren","affiliations":[],"preferred":false,"id":706331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":706330,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gill, David","contributorId":195159,"corporation":false,"usgs":false,"family":"Gill","given":"David","email":"","affiliations":[],"preferred":false,"id":706332,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Callaghan, Scott","contributorId":195136,"corporation":false,"usgs":false,"family":"Callaghan","given":"Scott","email":"","affiliations":[],"preferred":false,"id":706333,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maechling, Phillip J.","contributorId":117072,"corporation":false,"usgs":false,"family":"Maechling","given":"Phillip","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":706334,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70141751,"text":"70141751 - 2014 - Stratigraphy, structure and regional correlation of eastern Blue Ridge sequences in southern Virginia and northwestern North Carolina: an interim report from new USGS mapping","interactions":[],"lastModifiedDate":"2015-03-06T10:12:29","indexId":"70141751","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1724,"text":"GSA Field Guides","active":true,"publicationSubtype":{"id":10}},"title":"Stratigraphy, structure and regional correlation of eastern Blue Ridge sequences in southern Virginia and northwestern North Carolina: an interim report from new USGS mapping","docAbstract":"Examination of key outcrops in the eastern Blue Ridge in southern Virginia and northwestern North Carolina is used to evaluate existing stratigraphic and structural models. Recent detailed mapping along the Blue Ridge Parkway and the eastern flank of the Mount Rogers massif provides the opportunity to (1) evaluate legacy data and interpretations and (2) formulate new ideas for regional correlation of eastern Blue Ridge geology.
\nLynchburg Group rocks in central Virginia (metagraywacke, quartzite, graphitic schist, amphibolite, and ultramafic rocks) carry southward along strike where they transition with other units. Wills Ridge Formation consists of graphitic schist, metagraywacke, and metaconglomerate, and marks the western boundary of the eastern Blue Ridge. The Ashe Formation consists of conglomeratic metagraywacke in southern Virginia, and mica gneiss, mica schist, and ultramafic rocks in North Carolina. The overlying Alligator Back Formation shows characteristic compositional pin-striped layers in mica gneiss, schist, and amphibolite.
\nThe contact between eastern Blue Ridge stratified rocks above Mesoproterozoic basement rocks is mostly faulted (Gossan Lead and Red Valley). The Callaway fault juxtaposes Ashe and Lynchburg rocks above Wills Ridge Formation. Alligator Back Formation rocks overlie Ashe and Lynchburg rocks along the Rock Castle Creek fault, which juxtaposes rocks of different metamorphism. The fault separates major structural domains: rocks with one penetrative foliation in the footwall, and pin-striped recrystallized compositional layering, superposed penetrative foliations, and cleavage characterize the hanging wall. These relationships are ambiguous along strike to the southwest, where the Ashe and Alligator Back formations are recrystallized at higher metamorphic grades.
","language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","doi":"10.1130/2014.0035(07)","usgsCitation":"Carter, M.W., and Merschat, A.J., 2014, Stratigraphy, structure and regional correlation of eastern Blue Ridge sequences in southern Virginia and northwestern North Carolina: an interim report from new USGS mapping: GSA Field Guides, v. 35, p. 215-241, https://doi.org/10.1130/2014.0035(07).","productDescription":"27 p.","startPage":"215","endPage":"241","numberOfPages":"27","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054099","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":298319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.4581298828125,\n 36.45000844447082\n ],\n [\n -81.4581298828125,\n 37.13842453422676\n ],\n [\n -80.08209228515625,\n 37.13842453422676\n ],\n [\n -80.08209228515625,\n 36.45000844447082\n ],\n [\n -81.4581298828125,\n 36.45000844447082\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-04-01","publicationStatus":"PW","scienceBaseUri":"54faddbce4b02419550db6e2","contributors":{"authors":[{"text":"Carter, Mark W. 0000-0003-0460-7638 mcarter@usgs.gov","orcid":"https://orcid.org/0000-0003-0460-7638","contributorId":4808,"corporation":false,"usgs":true,"family":"Carter","given":"Mark","email":"mcarter@usgs.gov","middleInitial":"W.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":540998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Merschat, Arthur J. 0000-0002-9314-4067 amerschat@usgs.gov","orcid":"https://orcid.org/0000-0002-9314-4067","contributorId":4556,"corporation":false,"usgs":true,"family":"Merschat","given":"Arthur","email":"amerschat@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":540999,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155023,"text":"70155023 - 2014 - Seismometer Self-Noise and Measuring Methods","interactions":[],"lastModifiedDate":"2016-08-31T12:00:57","indexId":"70155023","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Seismometer Self-Noise and Measuring Methods","docAbstract":"Seismometer self-noise is usually not considered when selecting and using seismic waveform data in scientific research as it is typically assumed that the self-noise is negligibly small compared to seismic signals. However, instrumental noise is part of the noise in any seismic record, and in particular, at frequencies below a few mHz, the instrumental noise has a frequency-dependent character and may dominate the noise. When seismic noise itself is considered as a carrier of information, as in seismic interferometry (e.g., Chaput et al. 2012), it becomes extremely important to estimate the contribution of instrumental noise to the recordings.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of Earthquake Engineering","language":"English","publisher":"Springer Berlin Heidelberg","doi":"10.1007/978-3-642-36197-5_175-1","collaboration":"R. Sleeman; C. R. Hutt; L. S. Gee","usgsCitation":"Ringler, A.T., R. Sleeman, Hutt, C.R., and Gee, L.S., 2014, Seismometer Self-Noise and Measuring Methods, chap. of Encyclopedia of Earthquake Engineering, p. 1-13, https://doi.org/10.1007/978-3-642-36197-5_175-1.","productDescription":"14 p.","startPage":"1","endPage":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052770","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":328127,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":305672,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/referenceworkentry/10.1007/978-3-642-36197-5_175-1"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-09-24","publicationStatus":"PW","scienceBaseUri":"57c7ffbee4b0f2f0cebfc334","contributors":{"authors":[{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":564695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"R. Sleeman","contributorId":145584,"corporation":false,"usgs":false,"family":"R. Sleeman","affiliations":[{"id":16158,"text":"Royal Netherlands Meteorological Institute","active":true,"usgs":false}],"preferred":false,"id":564696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hutt, Charles R. 0000-0001-9033-9195 bhutt@usgs.gov","orcid":"https://orcid.org/0000-0001-9033-9195","contributorId":1622,"corporation":false,"usgs":true,"family":"Hutt","given":"Charles","email":"bhutt@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":564697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gee, Lind S. lgee@usgs.gov","contributorId":145579,"corporation":false,"usgs":true,"family":"Gee","given":"Lind","email":"lgee@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":564698,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191615,"text":"70191615 - 2014 - Using spatial resampling to assess redd count survey length requirements for Pacific Lamprey","interactions":[],"lastModifiedDate":"2017-10-17T14:37:58","indexId":"70191615","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Using spatial resampling to assess redd count survey length requirements for Pacific Lamprey","docAbstract":"Pacific Lamprey Entosphenus tridentatus has declined across its range along the West Coast of North America, and an understanding of all life history phases is needed to address population recovery. Spawning surveys (redd counts) are common tools currently used to monitor returning adult salmonids, but such methodologies are in their infancy for Pacific Lamprey. Our objective was to assess the minimum spawning survey distance required to detect the presence of Pacific Lamprey redds and obtain precise redd density estimates from these data. To do this, we statistically resampled existing spawning locations of Pacific Lamprey collected during spawning surveys in four streams of the Willamette River Basin, Oregon, during spring of 2013. We found that the minimum survey distance for Pacific Lamprey redd detection was inversely related to the observed redd density and was always less than 1.2 km. Survey distance requirements to obtain precise redd counts (±20% of observed redd densities) were also inversely related to redd density and habitat availability, and varied between 1.3 km and 13.7 km. Our results suggest that spawning surveys are a potential tool for monitoring adult Pacific Lamprey abundance, but the specific objectives of the monitoring programs and acknowledgment of unknowns must be considered prior to implementation into recovery plans.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02755947.2014.932867","usgsCitation":"Mayfield, M., Schultz, L.D., Wyss, L.A., Colvin, M., and Schreck, C.B., 2014, Using spatial resampling to assess redd count survey length requirements for Pacific Lamprey: North American Journal of Fisheries Management, v. 34, no. 5, p. 923-931, https://doi.org/10.1080/02755947.2014.932867.","productDescription":"9 p.","startPage":"923","endPage":"931","ipdsId":"IP-055637","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":346708,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.79394531249999,\n 44.257986652122426\n ],\n [\n -122.42340087890624,\n 44.257986652122426\n ],\n [\n -122.42340087890624,\n 44.89090425391711\n ],\n [\n -123.79394531249999,\n 44.89090425391711\n ],\n [\n -123.79394531249999,\n 44.257986652122426\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-08-13","publicationStatus":"PW","scienceBaseUri":"59e71694e4b05fe04cd331dc","contributors":{"authors":[{"text":"Mayfield, M.P.","contributorId":195833,"corporation":false,"usgs":false,"family":"Mayfield","given":"M.P.","email":"","affiliations":[],"preferred":false,"id":712883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schultz, L. D.","contributorId":197200,"corporation":false,"usgs":false,"family":"Schultz","given":"L.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":712884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wyss, Lance A.","contributorId":195114,"corporation":false,"usgs":false,"family":"Wyss","given":"Lance","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712885,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Colvin, M.E.","contributorId":53190,"corporation":false,"usgs":true,"family":"Colvin","given":"M.E.","affiliations":[],"preferred":false,"id":712886,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schreck, Carl B. 0000-0001-8347-1139 carl.schreck@usgs.gov","orcid":"https://orcid.org/0000-0001-8347-1139","contributorId":878,"corporation":false,"usgs":true,"family":"Schreck","given":"Carl","email":"carl.schreck@usgs.gov","middleInitial":"B.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":712869,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193752,"text":"70193752 - 2014 - Borehole radar interferometry revisited","interactions":[],"lastModifiedDate":"2018-08-06T12:40:35","indexId":"70193752","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Borehole radar interferometry revisited","docAbstract":"Single-hole, multi-offset borehole-radar reflection (SHMOR) is an effective technique for fracture detection. However, commercial radar system limitations hinder the acquisition of multi-offset reflection data in a single borehole. Transforming cross-hole transmission mode radar data to virtual single-hole, multi-offset reflection data using a wave interferometric virtual source (WIVS) approach has been proposed but not fully demonstrated. In this study, we compare WIVS-derived virtual single-hole, multi-offset reflection data to real SHMOR radar reflection profiles using cross-hole and single-hole radar data acquired in two boreholes located at the University of Connecticut (Storrs, CT USA). The field data results are similar to full-waveform numerical simulations developed for a two-borehole model. The reflection from the adjacent borehole is clearly imaged by both the real and WIVS-derived virtual reflection profiles. Reflector travel-time changes induced by deviation of the two boreholes from the vertical can also be observed on the real and virtual reflection profiles. The results of this study demonstrate the potential of the WIVS approach to improve bedrock fracture imaging for hydrogeological and petroleum reservoir development applications.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 15th International Conference on Ground Penetrating Radar","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"IEEE","doi":"10.1109/ICGPR.2014.6970491","usgsCitation":"Liu, L., Ma, C., Lane, J.W., and Joesten, P.K., 2014, Borehole radar interferometry revisited, in Proceedings of the 15th International Conference on Ground Penetrating Radar, https://doi.org/10.1109/ICGPR.2014.6970491.","ipdsId":"IP-057397","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":350807,"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":"5a71926ee4b0a9a2e9dbde0d","contributors":{"authors":[{"text":"Liu, Lanbo","contributorId":199850,"corporation":false,"usgs":false,"family":"Liu","given":"Lanbo","email":"","affiliations":[{"id":6619,"text":"University of Connecticutt","active":true,"usgs":false}],"preferred":false,"id":720201,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ma, Chunguang","contributorId":199851,"corporation":false,"usgs":false,"family":"Ma","given":"Chunguang","email":"","affiliations":[],"preferred":false,"id":720202,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lane, John W. Jr. 0000-0002-3558-243X jwlane@usgs.gov","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":189168,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":false,"id":720199,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Joesten, Peter K. pjoesten@usgs.gov","contributorId":1929,"corporation":false,"usgs":true,"family":"Joesten","given":"Peter","email":"pjoesten@usgs.gov","middleInitial":"K.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":720200,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70137757,"text":"70137757 - 2014 - Mount Rainier National Park","interactions":[],"lastModifiedDate":"2017-11-22T15:53:48","indexId":"70137757","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Mount Rainier National Park","docAbstract":"Natural Resource Condition Assessments (NRCAs) evaluate current conditions for a subset of natural resources and resource indicators in national parks. NRCAs also report on trends in resource condition (when possible), identify critical data gaps, and characterize a general level of confidence for study findings. The resources and indicators emphasized in a given project depend on the park’s resource setting, status of resource stewardship planning and science in identifying high-priority indicators, and availability of data and expertise to assess current conditions for a variety of potential study resources and indicators. Although the primary objective of NRCAs is to report on current conditions relative to logical forms of reference conditions and values, NRCAs also report on trends, when appropriate (i.e., when the underlying data and methods support such reporting), as well as influences on resource conditions. These influences may include past activities or conditions that provide a helpful context for understanding current conditions and present-day threats and stressors that are best interpreted at park, watershed, or landscape scales (though NRCAs do not report on condition status for land areas and natural resources beyond park boundaries). Intensive cause-andeffect analyses of threats and stressors, and development of detailed treatment options, are outside the scope of NRCAs. It is also important to note that NRCAs do not address resources that lack sufficient data for assessment. For Mount Rainier National Park, this includes most invertebrate species and many other animal species that are subject to significant stressors from climate change and other anthropogenic sources such as air pollutants and recreational use. In addition, we did not include an analysis of the physical hydrology associated with streams (such as riverine landforms, erosion and aggradation which is significant in MORA streams), due to a loss of staff expertise from the USGS-BRD staff conducting the work, and human disturbance landcover issues such as the effects of roads, trails, and other anthropogenic developments due to lack of funds.
","language":"English","publisher":"National Park Service","usgsCitation":"Hoffman, R., Woodward, A., Haggerty, P.K., Jenkins, K.J., Griffin, P., Adams, M.J., Hagar, J., Cummings, T., Duriscoe, D., Kopper, K., Riedel, J., Samora, B., Marin, L., Mauger, G., Bumbaco, K., and Littell, J.S., 2014, Mount Rainier National Park, xxvi., 353 p. .","productDescription":"xxvi., 353 p. ","startPage":"1","endPage":"380","ipdsId":"IP-056933","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":328462,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":297135,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/App/Reference/Profile/2218811"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d3dd3be4b0571647d19ab0","contributors":{"authors":[{"text":"Hoffman, Robert robert_hoffman@usgs.gov","contributorId":2991,"corporation":false,"usgs":true,"family":"Hoffman","given":"Robert","email":"robert_hoffman@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":538063,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woodward, Andrea 0000-0003-0604-9115 awoodward@usgs.gov","orcid":"https://orcid.org/0000-0003-0604-9115","contributorId":3028,"corporation":false,"usgs":true,"family":"Woodward","given":"Andrea","email":"awoodward@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":538064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haggerty, Patricia K. phaggerty@usgs.gov","contributorId":4602,"corporation":false,"usgs":true,"family":"Haggerty","given":"Patricia","email":"phaggerty@usgs.gov","middleInitial":"K.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":538065,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jenkins, Kurt J. 0000-0003-1415-6607 kurt_jenkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1415-6607","contributorId":3415,"corporation":false,"usgs":true,"family":"Jenkins","given":"Kurt","email":"kurt_jenkins@usgs.gov","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":538066,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Griffin, Paul C. pgriffin@usgs.gov","contributorId":3402,"corporation":false,"usgs":true,"family":"Griffin","given":"Paul C.","email":"pgriffin@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":538067,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adams, M. 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In the Salt Creek area of Durmid Hill, the San Andreas Fault coincides with a complex magnetic signature, with high-amplitude, short-wavelength magnetic anomalies superposed on a broader magnetic anomaly that is at least 5 km wide centered 2–3 km northeast of the fault. Marine magnetic data show that high-frequency magnetic anomalies extend more than 1 km west of the mapped trace of the San Andreas Fault. Modeling of magnetic data is consistent with a moderate to steep (> 50 degrees) northeast dip of the San Andreas Fault, but also suggests that the sedimentary sequence is folded west of the fault, causing the short wavelength of the anomalies west of the fault. Gravity anomalies are consistent with the previously modeled seismic velocity structure across the San Andreas Fault. Modeling of gravity data indicates a steep dip for the San Andreas Fault, but does not resolve unequivocally the direction of dip. Gravity data define a deeper basin, bounded by the Powerline and Hot Springs Faults, than imaged by the seismic experiment. This basin extends southeast of Line 7 for nearly 20 km, with linear margins parallel to the San Andreas Fault. These data suggest that the San Andreas Fault zone is wider than indicated by its mapped surface trace.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Not a drop left to drink","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2014 Desert Symposium","conferenceDate":"April 2014","language":"English","publisher":"California State University Desert Studies Center","publisherLocation":"Fullerton, CA","usgsCitation":"Langenheim, V., Athens, N.D., Scheirer, D., Fuis, G.S., Rymer, M.J., and Goldman, M.R., 2014, Width and dip of the southern San Andreas Fault at Salt Creek from modeling of geophysical data, in Not a drop left to drink, April 2014, p. 83-93.","productDescription":"11 p.","startPage":"83","endPage":"93","ipdsId":"IP-054142","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":340114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":313214,"type":{"id":15,"text":"Index Page"},"url":"https://nsm.fullerton.edu/dsc/desert-studies-center-additional-information"}],"country":"United States","state":"California","otherGeospatial":"San Andreas Fault","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58fdbd19e4b0074928294489","contributors":{"editors":[{"text":"Reynolds, Robert E.","contributorId":113220,"corporation":false,"usgs":true,"family":"Reynolds","given":"Robert E.","affiliations":[],"preferred":false,"id":692466,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Langenheim, Victoria E. 0000-0003-2170-5213 zulanger@usgs.gov","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":151042,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria E.","email":"zulanger@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":584145,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Athens, Noah D. nathens@usgs.gov","contributorId":4866,"corporation":false,"usgs":true,"family":"Athens","given":"Noah","email":"nathens@usgs.gov","middleInitial":"D.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":584146,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scheirer, Daniel S. dscheirer@usgs.gov","contributorId":2325,"corporation":false,"usgs":true,"family":"Scheirer","given":"Daniel S.","email":"dscheirer@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":584147,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fuis, Gary S. 0000-0002-3078-1544 fuis@usgs.gov","orcid":"https://orcid.org/0000-0002-3078-1544","contributorId":2639,"corporation":false,"usgs":true,"family":"Fuis","given":"Gary","email":"fuis@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":584148,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rymer, Michael J. mrymer@usgs.gov","contributorId":1522,"corporation":false,"usgs":true,"family":"Rymer","given":"Michael","email":"mrymer@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":584149,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Goldman, Mark R. 0000-0002-0802-829X goldman@usgs.gov","orcid":"https://orcid.org/0000-0002-0802-829X","contributorId":1521,"corporation":false,"usgs":true,"family":"Goldman","given":"Mark","email":"goldman@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":584150,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70191982,"text":"70191982 - 2014 - Niche restriction and conservatism in a neotropical psittacine: the case of the Puerto Rican parrot","interactions":[],"lastModifiedDate":"2018-01-25T11:17:58","indexId":"70191982","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Niche restriction and conservatism in a neotropical psittacine: the case of the Puerto Rican parrot","docAbstract":"The factors which govern species‘ distribution and abundance are myriad, and together constitute the ecological niche of a given species. Because abiotic factors are arguably the most profound of the factors influencing niche boundaries and thus, species distributions, substantial changes in either climatic or habitat-related parameters can be expected to produce interrelated and profound niche shifts. Habitat loss and degradation can also effectively induce a de facto climate change by forcing populations to relocate to environmentally suboptimal habitats. Populations experiencing niche shifts due to range restrictions and geographic isolation become subject to a suite of factors that may act synergistically to amplify deleterious ecological effects of habitat loss. These factors tend to exert a greater influence on populations of rare or endemic species with inherently restricted ranges. The Puerto Rican parrot (Amazona vittata) is an example of a tropical, insular, endemic and critically-endangered species that has suffered from extensive habitat loss and degradation over the past century, resulting in a single relict wild population restricted for more than 70 years to the montane rainforest of the Luquillo Mountains in northeastern Puerto Rico. In this chapter, we examine the current ecological situation of this geographically and demographically isolated parrot population by reviewing the history of landscape-level changes in and around the Luquillo Mountains, and concurrent biotic and abiotic limiting factors in relation to both historical population trajectory and current prognosis for species recovery. We used a decade (2000-2009) of empirical data on parrot fledgling survival together with long-term climatological data to model effects of local climate on fledgling survival and gain insights into its influence on population growth. We also modeled hypothetical survival of parrot fledglings in the lowlands surrounding the Luquillo Mountains, areas currently deforested but previously occupied by parrots, to illustrate both quantitative and qualitative losses of reproductive habitat for the species. We illustrate and systematically discuss how progressive and sustained changes in landscape composition and associated limiting factors have effectively shifted and restricted the ecological niche of this species, and how this complex suite of ecological processes affects the Puerto Rican parrot in the Luquillo Mountains. Our niche restriction hypothesis is supported by the demographic response of Puerto Rican parrots recently (2006-2009) reintroduced in the lower elevation karst forest of northwestern Puerto Rico. Based on our findings, we present conservation strategies aimed at promoting the recovery of the species both in the Luquillo Mountains and elsewhere in Puerto Rico. Finally, we address the relevance of our findings to conservation of other endangered species, particularly those threatened by both habitat loss and climate change.
","largerWorkType":{"id":4,"text":"Book"},"language":"English","publisher":"Nova Science Publishers","publisherLocation":"Habitat loss: Causes, impacts on biodiversity and reduction strategies","isbn":"978-1-63117-231-1","usgsCitation":"White, T.H., Collazo, J., Dinsmore, S., and Llerandi-Roman, I.C., 2014, Niche restriction and conservatism in a neotropical psittacine: the case of the Puerto Rican parrot, p. 1-84.","productDescription":"84 p.","startPage":"1","endPage":"84","ipdsId":"IP-052674","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":350601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350600,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.novapublishers.com/catalog/product_info.php?products_id=49029"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6afac8e4b06e28e9c9a91b","contributors":{"authors":[{"text":"White, Thomas H. Jr.","contributorId":201474,"corporation":false,"usgs":false,"family":"White","given":"Thomas","suffix":"Jr.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":725798,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collazo, Jaime A. 0000-0002-1816-7744 jaime_collazo@usgs.gov","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":173448,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime A.","email":"jaime_collazo@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":713809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dinsmore, Stephen J.","contributorId":61718,"corporation":false,"usgs":true,"family":"Dinsmore","given":"Stephen J.","affiliations":[],"preferred":false,"id":725799,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Llerandi-Roman, I. C.","contributorId":67324,"corporation":false,"usgs":true,"family":"Llerandi-Roman","given":"I.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":725800,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196084,"text":"70196084 - 2014 - Mapping advanced argillic alteration at Cuprite, Nevada, using imaging spectroscopy","interactions":[],"lastModifiedDate":"2018-03-29T15:07:37","indexId":"70196084","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Mapping advanced argillic alteration at Cuprite, Nevada, using imaging spectroscopy","docAbstract":"Mineral maps based on Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were used to study late Miocene advanced argillic alteration at Cuprite, Nevada. Distributions of Fe-bearing minerals, clays, micas, sulfates, and carbonates were mapped using the Tetracorder spectral-shape matching system. The Al content of white micas increases toward altered areas and near intrusive rocks. Alunite composition varies from pure K to intimate mixtures of Na-K endmembers with subpixel occurrences of huangite, the Ca analogue of alunite. Intimately mixed Na-K alunite marks areas of relatively lower alteration temperature, whereas co-occurring Na-alunite and dickite may delineate relict hydrothermal conduits. The presence of dickite, halloysite, and well-ordered kaolinite, but absence of disordered kaolinite, is consistent with acidic conditions during hydrothermal alteration. Partial lichen cover on opal spectrally mimics chalcedony, limiting its detection to lichen-free areas. Pods of buddingtonite are remnants of initial quartz-adularia-smectite alteration. Thus, spectral maps provide a synoptic view of the surface mineralogy, and define a previously unrecognized early steam-heated hydrothermal event.
Faulting and episodes of hydrothermal alteration at Cuprite were intimately linked to upper plate movements above the Silver Peak-Lone Mountain detachment and growth, collapse, and resurgence of the nearby Stonewall Mountain volcanic complex between 8 and 5 Ma. Isotopic dating indicates that hydrothermal activity started at least by 7.61 Ma and ended by about 6.2 Ma. Spectral and stable isotope data suggest that Cuprite is a late Miocene low-sulfidation adularia-sericite type hot spring deposit overprinted by late-stage, steam-heated advanced argillic alteration formed along the margin of the Stonewall Mountain caldera.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.2113/econgeo.109.5.1179","usgsCitation":"Swayze, G.A., Clark, R.N., Goetz, A., Livo, K., Breit, G.N., Kruse, F.A., Sutley, S.J., Snee, L., Lowers, H., Post, J.L., Stoffregen, R.E., and Ashley, R.P., 2014, Mapping advanced argillic alteration at Cuprite, Nevada, using imaging spectroscopy: Economic Geology, v. 109, no. 5, p. 1179-1221, https://doi.org/10.2113/econgeo.109.5.1179.","productDescription":"43 p.","startPage":"1179","endPage":"1221","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":352616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":352959,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://bit.ly/2J6IshC","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.25,\n 37.5\n ],\n [\n -117.15,\n 37.5\n ],\n [\n -117.15,\n 37.56666667\n ],\n [\n -117.25,\n 37.56666667\n ],\n [\n -117.25,\n 37.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"109","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-05-15","publicationStatus":"PW","scienceBaseUri":"5afeee10e4b0da30c1bfc74b","contributors":{"authors":[{"text":"Swayze, Gregg A. 0000-0002-1814-7823 gswayze@usgs.gov","orcid":"https://orcid.org/0000-0002-1814-7823","contributorId":518,"corporation":false,"usgs":true,"family":"Swayze","given":"Gregg","email":"gswayze@usgs.gov","middleInitial":"A.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":731250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Roger N. 0000-0002-7021-1220 rclark@usgs.gov","orcid":"https://orcid.org/0000-0002-7021-1220","contributorId":515,"corporation":false,"usgs":true,"family":"Clark","given":"Roger","email":"rclark@usgs.gov","middleInitial":"N.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":731251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goetz, Alexander F.H.","contributorId":89805,"corporation":false,"usgs":true,"family":"Goetz","given":"Alexander F.H.","affiliations":[],"preferred":false,"id":731252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Livo, K. Eric 0000-0001-7331-8130","orcid":"https://orcid.org/0000-0001-7331-8130","contributorId":26338,"corporation":false,"usgs":true,"family":"Livo","given":"K. Eric","affiliations":[],"preferred":false,"id":731253,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Breit, George N. 0000-0003-2188-6798 gbreit@usgs.gov","orcid":"https://orcid.org/0000-0003-2188-6798","contributorId":1480,"corporation":false,"usgs":true,"family":"Breit","given":"George","email":"gbreit@usgs.gov","middleInitial":"N.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":731254,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kruse, Fred A.","contributorId":26811,"corporation":false,"usgs":true,"family":"Kruse","given":"Fred","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":731255,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sutley, Stephen J.","contributorId":60296,"corporation":false,"usgs":true,"family":"Sutley","given":"Stephen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":731256,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Snee, Lawrence W.","contributorId":81534,"corporation":false,"usgs":true,"family":"Snee","given":"Lawrence W.","affiliations":[],"preferred":false,"id":731257,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lowers, Heather A. hlowers@usgs.gov","contributorId":149265,"corporation":false,"usgs":true,"family":"Lowers","given":"Heather A.","email":"hlowers@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":731258,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Post, James L.","contributorId":203356,"corporation":false,"usgs":false,"family":"Post","given":"James","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":731259,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Stoffregen, Roger E.","contributorId":52034,"corporation":false,"usgs":true,"family":"Stoffregen","given":"Roger","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":731260,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ashley, Roger P. ashley@usgs.gov","contributorId":2749,"corporation":false,"usgs":true,"family":"Ashley","given":"Roger","email":"ashley@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":731261,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70192195,"text":"70192195 - 2014 - Hydroclimatic regimes: a distributed water-balance framework for hydrologic assessment, classification, and management","interactions":[],"lastModifiedDate":"2018-04-03T11:40:25","indexId":"70192195","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Hydroclimatic regimes: a distributed water-balance framework for hydrologic assessment, classification, and management","docAbstract":"Runoff-based indicators of terrestrial water availability are appropriate for humid regions, but have tended to limit our basic hydrologic understanding of drylands – the dry-subhumid, semiarid, and arid regions which presently cover nearly half of the global land surface. In response, we introduce an indicator framework that gives equal weight to humid and dryland regions, accounting fully for both vertical (precipitation + evapotranspiration) and horizontal (groundwater + surface-water) components of the hydrologic cycle in any given location – as well as fluxes into and out of landscape storage. We apply the framework to a diverse hydroclimatic region (the conterminous USA) using a distributed water-balance model consisting of 53 400 networked landscape hydrologic units. Our model simulations indicate that about 21% of the conterminous USA either generated no runoff or consumed runoff from upgradient sources on a mean-annual basis during the 20th century. Vertical fluxes exceeded horizontal fluxes across 76% of the conterminous area. Long-term-average total water availability (TWA) during the 20th century, defined here as the total influx to a landscape hydrologic unit from precipitation, groundwater, and surface water, varied spatially by about 400 000-fold, a range of variation ~100 times larger than that for mean-annual runoff across the same area. The framework includes but is not limited to classical, runoff-based approaches to water-resource assessment. It also incorporates and reinterprets the green- and blue-water perspective now gaining international acceptance. Implications of the new framework for several areas of contemporary hydrology are explored, and the data requirements of the approach are discussed in relation to the increasing availability of gridded global climate, land-surface, and hydrologic data sets.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-18-3855-2014","usgsCitation":"Weiskel, P.K., Wolock, D.M., Zarriello, P.J., Vogel, R.M., Levin, S.B., and Lent, R.M., 2014, Hydroclimatic regimes: a distributed water-balance framework for hydrologic assessment, classification, and management: Hydrology and Earth System Sciences, v. 18, p. 3855-3872, https://doi.org/10.5194/hess-18-3855-2014.","productDescription":"18 p.","startPage":"3855","endPage":"3872","ipdsId":"IP-044838","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":473320,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-18-3855-2014","text":"Publisher Index Page"},{"id":347118,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-01","publicationStatus":"PW","scienceBaseUri":"59eeffade4b0220bbd988fd1","contributors":{"authors":[{"text":"Weiskel, Peter K. pweiskel@usgs.gov","contributorId":1099,"corporation":false,"usgs":true,"family":"Weiskel","given":"Peter","email":"pweiskel@usgs.gov","middleInitial":"K.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714681,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":714680,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zarriello, Phillip J. 0000-0001-9598-9904 pzarriel@usgs.gov","orcid":"https://orcid.org/0000-0001-9598-9904","contributorId":1868,"corporation":false,"usgs":true,"family":"Zarriello","given":"Phillip","email":"pzarriel@usgs.gov","middleInitial":"J.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714682,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vogel, Richard M.","contributorId":66811,"corporation":false,"usgs":true,"family":"Vogel","given":"Richard","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":714684,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Levin, Sara B. 0000-0002-2448-3129 slevin@usgs.gov","orcid":"https://orcid.org/0000-0002-2448-3129","contributorId":1870,"corporation":false,"usgs":true,"family":"Levin","given":"Sara","email":"slevin@usgs.gov","middleInitial":"B.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714685,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lent, Robert M. rmlent@usgs.gov","contributorId":284,"corporation":false,"usgs":true,"family":"Lent","given":"Robert","email":"rmlent@usgs.gov","middleInitial":"M.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714683,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70192200,"text":"70192200 - 2014 - Integrating recent land cover mapping efforts to update the National Gap Analysis Program's species habitat map","interactions":[],"lastModifiedDate":"2018-12-20T12:53:56","indexId":"70192200","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"seriesTitle":{"id":5650,"text":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","onlineIssn":"2194-9034","printIssn":"1682-1750","active":true,"publicationSubtype":{"id":19}},"title":"Integrating recent land cover mapping efforts to update the National Gap Analysis Program's species habitat map","docAbstract":"Over the past decade, great progress has been made to develop national extent land cover mapping products to address natural resource issues. One of the core products of the GAP Program is range-wide species distribution models for nearly 2000 terrestrial vertebrate species in the U.S. We rely on deductive modeling of habitat affinities using these products to create models of habitat availability. That approach requires that we have a thematically rich and ecologically meaningful map legend to support the modeling effort. In this work, we tested the integration of the Multi-Resolution Landscape Characterization Consortium's National Land Cover Database 2011 and LANDFIRE's Disturbance Products to update the 2001 National GAP Vegetation Dataset to reflect 2011 conditions. The revised product can then be used to update the species models.
We tested the update approach in three geographic areas (Northeast, Southeast, and Interior Northwest). We used the NLCD product to identify areas where the cover type mapped in 2011 was different from what was in the 2001 land cover map. We used Google Earth and ArcGIS base maps as reference imagery in order to label areas identified as \"changed\" to the appropriate class from our map legend. Areas mapped as urban or water in the 2011 NLCD map that were mapped differently in the 2001 GAP map were accepted without further validation and recoded to the corresponding GAP class. We used LANDFIRE's Disturbance products to identify changes that are the result of recent disturbance and to inform the reassignment of areas to their updated thematic label. We ran species habitat models for three species including Lewis's Woodpecker (Melanerpes lewis) and the White-tailed Jack Rabbit (Lepus townsendii) and Brown Headed nuthatch (Sitta pusilla). For each of three vertebrate species we found important differences in the amount and location of suitable habitat between the 2001 and 2011 habitat maps. Specifically, Brown headed nuthatch habitat in 2011 was −14% of the 2001 modeled habitat, whereas Lewis's Woodpecker increased by 4%. The white-tailed jack rabbit (Lepus townsendii) had a net change of −1% (11% decline, 10% gain). For that species we found the updates related to opening of forest due to burning and regenerating shrubs following harvest to be the locally important main transitions. In the Southeast updates related to timber management and urbanization are locally important.
Dissolved inorganic and organic nitrogen levels are elevated in aquatic systems due to anthropogenic activities. Dissolved organic nitrogen (DON) arises from various sources, and its impact could be more clearly constrained if specific sources were identified and if the molecular-level composition of DON were better understood. In this work, the pharmaceutical carbamazepine was used to identify septic-impacted groundwater in a coastal watershed. Using ultrahigh resolution mass spectrometry data, the nitrogen-containing features of the dissolved organic matter in septic-impacted and non-impacted samples were compared. The septic-impacted groundwater samples have a larger abundance of nitrogen-containing formulas. Impacted samples have additional DON features in the regions ascribed as ‘protein-like’ and ‘lipid-like’ in van Krevelen space and have more intense nitrogen-containing features in a specific region of a carbon versus mass plot. These features are potential indicators of dissolved organic nitrogen arising from septic effluents, and this work suggests that ultrahigh resolution mass spectrometry is a valuable tool to identify and characterize sources of DON.
","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/C4EM00289J","usgsCitation":"Arnold, W., Longnecker, K., Kroeger, K.D., and Kujawinski, E.B., 2014, Molecular signature of organic nitrogen in septic-impacted groundwater: Environmental Science: Processes and Impacts, v. 16, p. 2400-2407, https://doi.org/10.1039/C4EM00289J.","productDescription":"8 p.","startPage":"2400","endPage":"2407","ipdsId":"IP-058270","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":473298,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/6964","text":"External Repository"},{"id":328590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d9233ce4b090824ffa1adf","contributors":{"authors":[{"text":"Arnold, William A.","contributorId":31105,"corporation":false,"usgs":true,"family":"Arnold","given":"William A.","affiliations":[],"preferred":false,"id":648653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Longnecker, Krista","contributorId":174582,"corporation":false,"usgs":false,"family":"Longnecker","given":"Krista","email":"","affiliations":[{"id":27473,"text":"Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, 360 Woods Hole Rd., Woods Hole, MA","active":true,"usgs":false}],"preferred":false,"id":648654,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":648652,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kujawinski, Elizabeth B.","contributorId":174583,"corporation":false,"usgs":false,"family":"Kujawinski","given":"Elizabeth","email":"","middleInitial":"B.","affiliations":[{"id":27474,"text":"Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, 360 Woods Hole Rd., Woods Hole, MA 02543","active":true,"usgs":false}],"preferred":false,"id":648655,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193118,"text":"70193118 - 2014 - Groundwater conditions in Utah, spring of 2014","interactions":[],"lastModifiedDate":"2019-05-22T09:32:52","indexId":"70193118","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":110,"text":"Cooperative Investigations Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"55","title":"Groundwater conditions in Utah, spring of 2014","docAbstract":"This is the fifty-first in a series of annual reports that describe groundwater conditions in Utah. Reports in this series, published cooperatively by the U.S. Geological Survey and the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Environmental Quality, Division of Water Quality, provide data to enable interested parties to maintain awareness of changing groundwater conditions.
This report, like the others in the series, contains information on well construction, groundwater withdrawal from wells, water-level changes, precipitation, streamflow, and chemical quality of water. Information on well construction included in this report refers only to wells constructed for new appropriations of groundwater. Supplementary data are included in reports of this series only for those years or areas that are important to a discussion of changing groundwater conditions and for which applicable data are available.
This report includes individual discussions of selected significant areas of groundwater development in the State for calendar year 2013. Most of the reported data were collected by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Environmental Quality, Division of Water Quality. This report is also available online at http://www.waterrights.utah.gov/techinfo/ and http://ut.water. usgs.gov/publications/GW2014.pdf. Groundwater conditions in Utah for calendar year 2012 are reported in Burden and others (2013) and are available online at http://ut.water.usgs. gov/publications/GW2013.pdf
","language":"English","publisher":"Utah Department of Natural Resources","usgsCitation":"Burden, C.B., 2014, Groundwater conditions in Utah, spring of 2014: Cooperative Investigations Report 55, x, 118 p.","productDescription":"x, 118 p.","numberOfPages":"132","ipdsId":"IP-056622","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":350085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364083,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://waterrights.utah.gov/techinfo/wwwpub/GW2014.pdf"}],"country":"United 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\"}}]}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6100c9e4b06e28e9c2541d","contributors":{"authors":[{"text":"Burden, Carole B. cburden@usgs.gov","contributorId":852,"corporation":false,"usgs":true,"family":"Burden","given":"Carole","email":"cburden@usgs.gov","middleInitial":"B.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":718032,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70176404,"text":"70176404 - 2014 - Studying seafloor bedforms using autonomous stationary imaging and profiling sonars","interactions":[],"lastModifiedDate":"2020-10-19T14:08:08.110822","indexId":"70176404","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Studying seafloor bedforms using autonomous stationary imaging and profiling sonars","docAbstract":"The Sediment Transport Group at the U.S. Geological Survey, Woods Hole Coastal and Marine Science Center uses downward looking sonars deployed on seafloor tripods to assess and measure the formation and migration of bedforms. The sonars have been used in three resolution-testing experiments, and deployed autonomously to observe changes in the seafloor for up to two months in seven field experiments since 2002. The sonar data are recorded concurrently with measurements of waves and currents to: a) relate bedform geometry to sediment and flow characteristics; b) assess hydrodynamic drag caused by bedforms; and c) estimate bedform sediment transport rates, all with the goal of evaluating and improving numerical models of these processes. Our hardware, data processing methods, and test and validation procedures have evolved since 2001. We now employ a standard sonar configuration that provides reliable data for correlating flow conditions with bedform morphology. Plans for the future are to sample more rapidly and improve the precision of our tripod orientation measurements.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"OCEANS 2013: Proceedings of a meeting held 23-27 September 2013, San Diego, California, USA","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"OCEANS '13","conferenceDate":"September 23-27, 2013","conferenceLocation":"San Diego, CA","language":"English","publisher":"MTS/IEEE","usgsCitation":"Montgomery, E., and Sherwood, C.R., 2014, Studying seafloor bedforms using autonomous stationary imaging and profiling sonars, in OCEANS 2013: Proceedings of a meeting held 23-27 September 2013, San Diego, California, USA, San Diego, CA, September 23-27, 2013, p. 158-164.","productDescription":"7 p.","startPage":"158","endPage":"164","ipdsId":"IP-049686","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":339572,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":379511,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.proceedings.com/21340.html"}],"publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58edbcd4e4b0eed1ab8c6f73","contributors":{"authors":[{"text":"Montgomery, Ellyn T. emontgomery@usgs.gov","contributorId":169594,"corporation":false,"usgs":true,"family":"Montgomery","given":"Ellyn T.","email":"emontgomery@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":648614,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648615,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70194461,"text":"70194461 - 2014 - Utilizing multi-sensor fire detections to map fires in the United States","interactions":[],"lastModifiedDate":"2018-04-23T09:10:31","indexId":"70194461","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Utilizing multi-sensor fire detections to map fires in the United States","docAbstract":"In 2006, the Monitoring Trends in Burn Severity (MTBS) project began a cooperative effort between the US Forest Service (USFS) and the U.S.Geological Survey (USGS) to map and assess burn severity all large fires that have occurred in the United States since 1984. Using Landsat imagery, MTBS is mandated to map wildfire and prescribed fire that meet specific size criteria: greater than 1000 acres in the west and 500 acres in the east, regardless of ownership. Relying mostly on federal and state fire occurrence records, over 15,300 individual fires have been mapped. While mapping recorded fires, an additional 2,700 “unknown” or undocumented fires were discovered and assessed. It has become apparent that there are perhaps thousands of undocumented fires in the US that are yet to be mapped. Fire occurrence records alone are inadequate if MTBS is to provide a comprehensive accounting of fire across the US. Additionally, the sheer number of fires to assess has overwhelmed current manual procedures. To address these problems, the National Aeronautics and Space Administration (NASA) Applied Sciences Program is helping to fund the efforts of the USGS and its MTBS partners (USFS, National Park Service) to develop, and implement a system to automatically identify fires using satellite data. In near real time, USGS will combine active fire satellite detections from MODIS, AVHRR and GOES satellites with Landsat acquisitions. Newly acquired Landsat imagery will be routinely scanned to identify freshly burned area pixels, derive an initial perimeter and tag the burned area with the satellite date and time of detection. Landsat imagery from the early archive will be scanned to identify undocumented fires. Additional automated fire assessment processes will be developed. The USGS will develop these processes using open source software packages in order to provide freely available tools to local land managers providing them with the capability to assess fires at the local level.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1,","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"ISPRS Technical Commission I Symposium","conferenceDate":"November 17-20, 2014","conferenceLocation":"Denver, CO","language":"English","publisher":"ISPRS","doi":"10.5194/isprsarchives-XL-1-161-2014","usgsCitation":"Howard, S.M., Picotte, J.J., and Coan, M., 2014, Utilizing multi-sensor fire detections to map fires in the United States, in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1,, v. XL-1, Denver, CO, November 17-20, 2014, p. 161-166, https://doi.org/10.5194/isprsarchives-XL-1-161-2014.","productDescription":"6 p.","startPage":"161","endPage":"166","ipdsId":"IP-060379","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473416,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/isprsarchives-xl-1-161-2014","text":"Publisher Index Page"},{"id":350086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"XL-1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-07","publicationStatus":"PW","scienceBaseUri":"5a6100c8e4b06e28e9c2540f","contributors":{"authors":[{"text":"Howard, Stephen M. 0000-0001-5255-5882 smhoward@usgs.gov","orcid":"https://orcid.org/0000-0001-5255-5882","contributorId":3483,"corporation":false,"usgs":true,"family":"Howard","given":"Stephen","email":"smhoward@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":723939,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Picotte, Joshua J. 0000-0002-4021-4623 jpicotte@usgs.gov","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":4626,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua","email":"jpicotte@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":725216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coan, Michael mcoan@usgs.gov","contributorId":5398,"corporation":false,"usgs":true,"family":"Coan","given":"Michael","email":"mcoan@usgs.gov","affiliations":[],"preferred":true,"id":725217,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188032,"text":"70188032 - 2014 - Detecting emergence, growth, and senescence of wetland vegetation with polarimetric synthetic aperture radar (SAR) data","interactions":[],"lastModifiedDate":"2017-05-31T15:19:27","indexId":"70188032","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Detecting emergence, growth, and senescence of wetland vegetation with polarimetric synthetic aperture radar (SAR) data","docAbstract":"Wetlands provide ecosystem goods and services vitally important to humans. Land managers and policymakers working to conserve wetlands require regularly updated information on the statuses of wetlands across the landscape. However, wetlands are challenging to map remotely with high accuracy and consistency. We investigated the use of multitemporal polarimetric synthetic aperture radar (SAR) data acquired with Canada’s Radarsat-2 system to track within-season changes in wetland vegetation and surface water. We speculated, a priori, how temporal and morphological traits of different types of wetland vegetation should respond over a growing season with respect to four energy-scattering mechanisms. We used ground-based monitoring data and other ancillary information to assess the limits and consistency of the SAR data for tracking seasonal changes in wetlands. We found the traits of different types of vertical emergent wetland vegetation were detected well with the SAR data and corresponded with our anticipated backscatter responses. We also found using data from Landsat’s optical/infrared sensors in conjunction with SAR data helped remove confusion of wetland features with upland grasslands. These results suggest SAR data can provide useful monitoring information on the statuses of wetlands over time.
","language":"English","publisher":"MDPI","doi":"10.3390/w6030694","usgsCitation":"Gallant, A.L., Kaya, S.G., White, L., Brisco, B., Roth, M.F., Sadinski, W.J., and Rover, J., 2014, Detecting emergence, growth, and senescence of wetland vegetation with polarimetric synthetic aperture radar (SAR) data: Water, v. 6, no. 3, p. 694-722, https://doi.org/10.3390/w6030694.","productDescription":"29 p.","startPage":"694","endPage":"722","ipdsId":"IP-053361","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473304,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w6030694","text":"Publisher Index Page"},{"id":341958,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-03-24","publicationStatus":"PW","scienceBaseUri":"592fd640e4b0e9bd0ea8970a","contributors":{"authors":[{"text":"Gallant, Alisa L. 0000-0002-3029-6637 gallant@usgs.gov","orcid":"https://orcid.org/0000-0002-3029-6637","contributorId":2940,"corporation":false,"usgs":true,"family":"Gallant","given":"Alisa","email":"gallant@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":696252,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaya, Shannon G.","contributorId":192330,"corporation":false,"usgs":false,"family":"Kaya","given":"Shannon","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":696253,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, Lori","contributorId":192557,"corporation":false,"usgs":false,"family":"White","given":"Lori","email":"","affiliations":[],"preferred":false,"id":696254,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brisco, Brian","contributorId":37665,"corporation":false,"usgs":true,"family":"Brisco","given":"Brian","email":"","affiliations":[],"preferred":false,"id":696255,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roth, Mark F. 0000-0001-5095-1865 mroth@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-1865","contributorId":3286,"corporation":false,"usgs":true,"family":"Roth","given":"Mark","email":"mroth@usgs.gov","middleInitial":"F.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":696256,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sadinski, Walter J. wsadinski@usgs.gov","contributorId":3287,"corporation":false,"usgs":true,"family":"Sadinski","given":"Walter","email":"wsadinski@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":696257,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rover, Jennifer 0000-0002-3437-4030 jrover@usgs.gov","orcid":"https://orcid.org/0000-0002-3437-4030","contributorId":192333,"corporation":false,"usgs":true,"family":"Rover","given":"Jennifer","email":"jrover@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":696258,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70189207,"text":"70189207 - 2014 - Evaluation of statistically downscaled GCM output as input for hydrological and stream temperature simulation in the Apalachicola–Chattahoochee–Flint River Basin (1961–99)","interactions":[],"lastModifiedDate":"2017-07-05T16:20:39","indexId":"70189207","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1421,"text":"Earth Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of statistically downscaled GCM output as input for hydrological and stream temperature simulation in the Apalachicola–Chattahoochee–Flint River Basin (1961–99)","docAbstract":"The accuracy of statistically downscaled general circulation model (GCM) simulations of daily surface climate for historical conditions (1961–99) and the implications when they are used to drive hydrologic and stream temperature models were assessed for the Apalachicola–Chattahoochee–Flint River basin (ACFB). The ACFB is a 50 000 km2 basin located in the southeastern United States. Three GCMs were statistically downscaled, using an asynchronous regional regression model (ARRM), to ⅛° grids of daily precipitation and minimum and maximum air temperature. These ARRM-based climate datasets were used as input to the Precipitation-Runoff Modeling System (PRMS), a deterministic, distributed-parameter, physical-process watershed model used to simulate and evaluate the effects of various combinations of climate and land use on watershed response. The ACFB was divided into 258 hydrologic response units (HRUs) in which the components of flow (groundwater, subsurface, and surface) are computed in response to climate, land surface, and subsurface characteristics of the basin. Daily simulations of flow components from PRMS were used with the climate to simulate in-stream water temperatures using the Stream Network Temperature (SNTemp) model, a mechanistic, one-dimensional heat transport model for branched stream networks.
The climate, hydrology, and stream temperature for historical conditions were evaluated by comparing model outputs produced from historical climate forcings developed from gridded station data (GSD) versus those produced from the three statistically downscaled GCMs using the ARRM methodology. The PRMS and SNTemp models were forced with the GSD and the outputs produced were treated as “truth.” This allowed for a spatial comparison by HRU of the GSD-based output with ARRM-based output. Distributional similarities between GSD- and ARRM-based model outputs were compared using the two-sample Kolmogorov–Smirnov (KS) test in combination with descriptive metrics such as the mean and variance and an evaluation of rare and sustained events. In general, precipitation and streamflow quantities were negatively biased in the downscaled GCM outputs, and results indicate that the downscaled GCM simulations consistently underestimate the largest precipitation events relative to the GSD. The KS test results indicate that ARRM-based air temperatures are similar to GSD at the daily time step for the majority of the ACFB, with perhaps subweekly averaging for stream temperature. Depending on GCM and spatial location, ARRM-based precipitation and streamflow requires averaging of up to 30 days to become similar to the GSD-based output.
Evaluation of the model skill for historical conditions suggests some guidelines for use of future projections; while it seems correct to place greater confidence in evaluation metrics which perform well historically, this does not necessarily mean those metrics will accurately reflect model outputs for future climatic conditions. Results from this study indicate no “best” overall model, but the breadth of analysis can be used to give the product users an indication of the applicability of the results to address their particular problem. Since results for historical conditions indicate that model outputs can have significant biases associated with them, the range in future projections examined in terms of change relative to historical conditions for each individual GCM may be more appropriate.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/2013EI000554.1","usgsCitation":"Hay, L.E., LaFontaine, J.H., and Markstrom, S.L., 2014, Evaluation of statistically downscaled GCM output as input for hydrological and stream temperature simulation in the Apalachicola–Chattahoochee–Flint River Basin (1961–99): Earth Interactions, v. 18, p. 1-32, https://doi.org/10.1175/2013EI000554.1.","productDescription":"32 p.","startPage":"1","endPage":"32","ipdsId":"IP-052922","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":473306,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/2013ei000554.1","text":"Publisher Index Page"},{"id":343366,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia","otherGeospatial":"Apalachicola–Chattahoochee–Flint River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.60546875,\n 29.6594160549124\n ],\n [\n -83.7158203125,\n 29.6594160549124\n ],\n [\n -83.7158203125,\n 34.470335121217474\n ],\n [\n -85.60546875,\n 34.470335121217474\n ],\n [\n -85.60546875,\n 29.6594160549124\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-04-14","publicationStatus":"PW","scienceBaseUri":"595dfab7e4b0d1f9f056a7a6","contributors":{"authors":[{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaFontaine, Jacob H. 0000-0003-4923-2630 jlafonta@usgs.gov","orcid":"https://orcid.org/0000-0003-4923-2630","contributorId":2258,"corporation":false,"usgs":true,"family":"LaFontaine","given":"Jacob","email":"jlafonta@usgs.gov","middleInitial":"H.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":703495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":146553,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven","email":"markstro@usgs.gov","middleInitial":"L.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":703496,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}