The development of unconventional oil and gas (UOG) involves infrastructure development (well pads, roads and pipelines), well drilling and stimulation (hydraulic fracturing), and production; all of which have the potential to affect stream ecosystems. Here, we developed a fine-scaled (1:24,000) catchment-level disturbance intensity index (DII) that included 17 measures of UOG capturing all steps in the development process (infrastructure, water withdrawals, probabilistic spills) that could affect headwater streams (< 200 km2 in upstream catchment) in the Upper Susquehanna River Basin in Pennsylvania, U.S.A. The DII ranged from 0 (no UOG disturbance) to 100 (the catchment with the highest UOG disturbance in the study area) and it was most sensitive to removal of pipeline cover, road cover and well pad cover metrics. We related this DII to three measures of high quality streams: Pennsylvania State Exceptional Value (EV) streams, Class A brook trout streams and Eastern Brook Trout Joint Venture brook trout patches. Overall only 3.8% of all catchments and 2.7% of EV stream length, 1.9% of Class A streams and 1.2% of patches were classified as having medium to high level DII scores (> 50). Well density, often used as a proxy for development, only correlated strongly with well pad coverage and produced materials, and therefore may miss potential effects associated with roads and pipelines, water withdrawals and spills. When analyzed with a future development scenario, 91.1% of EV stream length, 68.7% of Class A streams and 80.0% of patches were in catchments with a moderate to high probability of development. Our method incorporated the cumulative effects of UOG on streams and can be used to identify catchments and reaches at risk to existing stressors or future development.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2017.07.247","usgsCitation":"Maloney, K.O., Young, J.A., Faulkner, S., Hailegiorgis, A., Slonecker, E., and Milheim, L., 2018, A detailed risk assessment of shale gas development on headwater streams in the Pennsylvania portion of the Upper Susquehanna River Basin, U.S.A.: Science of the Total Environment, v. 610-611, p. 154-166, https://doi.org/10.1016/j.scitotenv.2017.07.247.","productDescription":"13 p.","startPage":"154","endPage":"166","ipdsId":"IP-087579","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":461145,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2017.07.247","text":"Publisher Index Page"},{"id":438087,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Z036NF","text":"USGS data release","linkHelpText":"Shale gas data used in development of the Disturbance Intensity Index for the Pennsylvania portion of the Upper Susquehanna River basin in Maloney et al. 2018."},{"id":345411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Upper Susquehanna River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.046630859375,\n 40.53050177574321\n ],\n [\n -75.047607421875,\n 40.53050177574321\n ],\n [\n -75.047607421875,\n 42.00848901572399\n ],\n [\n -79.046630859375,\n 42.00848901572399\n ],\n [\n -79.046630859375,\n 40.53050177574321\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"610-611","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59aa71d8e4b0e9bde130cfe4","contributors":{"authors":[{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":709393,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":709394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Faulkner, Stephen 0000-0001-5295-1383 faulkners@usgs.gov","orcid":"https://orcid.org/0000-0001-5295-1383","contributorId":146152,"corporation":false,"usgs":true,"family":"Faulkner","given":"Stephen","email":"faulkners@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":709395,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hailegiorgis, Atesmachew","contributorId":196129,"corporation":false,"usgs":false,"family":"Hailegiorgis","given":"Atesmachew","email":"","affiliations":[],"preferred":false,"id":709396,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Slonecker, E. Terrence","contributorId":20677,"corporation":false,"usgs":true,"family":"Slonecker","given":"E. Terrence","affiliations":[],"preferred":false,"id":709398,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Milheim, Lesley lmilheim@usgs.gov","contributorId":168592,"corporation":false,"usgs":true,"family":"Milheim","given":"Lesley","email":"lmilheim@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":709397,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70190589,"text":"70190589 - 2018 - The influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware","interactions":[],"lastModifiedDate":"2018-03-29T12:51:13","indexId":"70190589","displayToPublicDate":"2017-06-30T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3751,"text":"Wetlands Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"The influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware","docAbstract":"The dependence of downstream waters on upstream ecosystems necessitates an improved understanding of watershed-scale hydrological interactions including connections between wetlands and streams. An evaluation of such connections is challenging when, (1) accurate and complete datasets of wetland and stream locations are often not available and (2) natural variability in surface-water extent influences the frequency and duration of wetland/stream connectivity. The Upper Choptank River watershed on the Delmarva Peninsula in eastern Maryland and Delaware is dominated by a high density of small, forested wetlands. In this analysis, wetland/stream surface water connections were quantified using multiple wetland and stream datasets, including headwater streams and depressions mapped from a lidar-derived digital elevation model. Surface-water extent was mapped across the watershed for spring 2015 using Landsat-8, Radarsat-2 and Worldview-3 imagery. The frequency of wetland/stream connections increased as a more complete and accurate stream dataset was used and surface-water extent was included, in particular when the spatial resolution of the imagery was finer (i.e., <10 m). Depending on the datasets used, 12–60% of wetlands by count (21–93% of wetlands by area) experienced surface-water interactions with streams during spring 2015. This translated into a range of 50–94% of the watershed contributing direct surface water runoff to streamflow. This finding suggests that our interpretation of the frequency and duration of wetland/stream connections will be influenced not only by the spatial and temporal characteristics of wetlands, streams and potential flowpaths, but also by the completeness, accuracy and resolution of input datasets.
","language":"English","publisher":"Springer","doi":"10.1007/s11273-017-9554-y","usgsCitation":"Vanderhoof, M.K., Distler, H., Lang, M.W., and Alexander, L.C., 2018, The influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware: Wetlands Ecology and Management, v. 26, no. 1, p. 63-86, https://doi.org/10.1007/s11273-017-9554-y.","productDescription":"24 p.","startPage":"63","endPage":"86","ipdsId":"IP-084257","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":469198,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9534041","text":"External Repository"},{"id":438088,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70C4T8F","text":"USGS data release","linkHelpText":"Data Release for the influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware"},{"id":352120,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland","otherGeospatial":"Delmarva Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.1,\n 38.5\n ],\n [\n -76.1,\n 39.1\n ],\n [\n -75.5,\n 39.1\n ],\n [\n -75.5,\n 38.5\n ],\n [\n -76.1,\n 38.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-08","publicationStatus":"PW","scienceBaseUri":"5afee787e4b0da30c1bfc2b6","contributors":{"authors":[{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":709917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Distler, Hayley 0000-0001-5006-1360 hdistler@usgs.gov","orcid":"https://orcid.org/0000-0001-5006-1360","contributorId":179359,"corporation":false,"usgs":true,"family":"Distler","given":"Hayley","email":"hdistler@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":709918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lang, Megan W.","contributorId":196284,"corporation":false,"usgs":false,"family":"Lang","given":"Megan","email":"","middleInitial":"W.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":709919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alexander, Laurie C.","contributorId":196285,"corporation":false,"usgs":false,"family":"Alexander","given":"Laurie","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":709920,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70260162,"text":"70260162 - 2018 - Focused seismicity triggered by flank instability on Kīlauea's Southwest Rift Zone","interactions":[],"lastModifiedDate":"2024-10-29T11:49:45.02765","indexId":"70260162","displayToPublicDate":"2017-03-17T06:47:36","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Focused seismicity triggered by flank instability on Kīlauea's Southwest Rift Zone","docAbstract":"Crystalline bedrock aquifers in New England and parts of New Jersey and New York (NECR aquifers) are a major source of drinking water. Because the quality of water in these aquifers is highly variable, the U.S. Geological Survey (USGS) statistically analyzed chemical data on samples of untreated groundwater collected from 117 domestic bedrock wells in New England, New York, and New Jersey, and from 4,775 public-supply bedrock wells in New England to characterize the quality of the groundwater. The domestic-well data were from samples collected by the USGS National Water-Quality Assessment (NAWQA) Program from 1995 through 2007. The public-supply-well data were from samples collected for the U.S. Environmental Protection Agency (USEPA) Safe Drinking Water Act (SDWA) Program from 1997 through 2007. Chemical data compiled from the domestic wells include pH, specific conductance, dissolved oxygen, alkalinity, and turbidity; 6 nitrogen and phosphorus compounds, 14 major ions, 23 trace elements, 222radon gas (radon), 48 pesticide compounds, and 82 volatile organic compounds (VOCs). Additional samples were collected from the domestic wells for the analysis of gross alpha- and gross beta-particle radioactivity, radium isotopes, chlorofluorocarbon isotopes, and the dissolved gases methane, carbon dioxide, nitrogen, and argon. Chemical data compiled from the public-supply wells include pH, specific conductance, nitrate, iron, manganese, sodium, chloride, fluoride, arsenic, uranium, radon, combined radium (226radium plus 228radium), gross alpha-particle radioactivity, and methyl tert-butyl ether (MtBE).
Patterns in fluoride, arsenic, uranium, and radon distributions were discernable when the data were compared to lithology groupings of the bedrock, indicating that the type of bedrock has an effect on the quality of groundwater from NECR aquifers. Fluoride concentrations were significantly higher in groundwater samples from the alkali granite, peraluminous granite, and metaluminous granite lithology groups than from samples in the other lithology groups. Water samples from 1.4 percent of 2,167 studied wells had fluoride concentrations that were equal to or greater than the maximum contaminant level (MCL) of 4 milligrams per liter (mg/L) and 7.5 percent of the wells had fluoride concentrations that were equal to or greater than the secondary MCL of 2 mg/L. For arsenic, groundwater samples from the calcareous metasedimentary rocks in the New Hampshire-Maine geologic province, peraluminous granite, and pelitic rocks lithology groups had higher concentrations than did samples from the other lithology groups. Water samples from 13.3 percent of 2,054 studied wells had arsenic concentrations that were equal to or greater than the MCL of 10 micrograms per liter (μg/L), about double the national rate of occurrence in community-supply systems and in domestic wells of the United States. Uranium concentrations were significantly higher in groundwater samples from the peraluminous granite, alkali granite, and calcareous metasedimentary rocks in the New Hampshire-Maine geologic province lithology groups than from samples in the other lithology groups. Water samples from 14.2 percent of 556 studied wells had uranium concentrations equal to or greater than the MCL of 30 μg/L. Radon activities were equal to or greater than the proposed MCL of 300 picocuries per liter (pCi/L) in 95 percent of 943 studied wells, and 33 percent of the wells had radon activities were equal to or greater than the proposed alternative maximum contaminant level (AMCL) of 4,000 pCi/L. Radon activities exceeded the proposed AMCL in 20 percent or more of groundwater samples in each of the studied lithology groups with a minimum of 9 samples, but radon activities were significantly higher in groundwater samples from the alkali granite, peraluminous granite, and Narragansett basin metasedimentary rocks lithology groups. Water samples from 3.2 percent of 564 studied wells had combined radium activities equal to or greater than the MCL of 5 pCi/L; however, combined radium activities were not significantly different among the studied lithology groups.
Land use and population density also were evaluated to explain patterns in water quality. Concentrations of nitrate, sodium, chloride, and MtBE from the studied wells were significantly greater in areas of high population density (≥50 persons per square kilometer) than in areas of low population density (<50 persons per square kilometer). Concentrations of sodium, chloride, and MtBE from the studied wells were significantly greater in areas classified as developed (urban lands) than in areas classified as undeveloped (forested), agricultural, or mixed (no dominant land use). Nitrate concentrations from the public-supply wells were not significantly different among the four land use categories, but nitrate concentrations from the domestic wells were significantly greater in areas classified as developed than in areas classified as undeveloped, agricultural, or mixed.
Chloride to bromide mass ratios in the domestic well samples indicate that the groundwater was probably affected by at least three halogen sources: local precipitation and recharge waters, remnant seawater and connate waters evolved from seawater, and recharge waters affected by road salt. The groundwater in the NECR aquifers generally contained low concentrations of nitrate, VOCs, and pesticides. Less than 1 percent of water samples from 4,781 studied wells had concentrations of nitrate greater than the MCL of 10 mg/L. Less than 1 percent of water samples from 1,299 studied wells exceeded the USEPA advisory level of 20 to 40 μg/L for MtBE. None of the other studied VOCs exceeded a human health benchmark. MtBE (36 percent frequency detection) and chloroform (32.9 percent frequency detection) were the most frequently detected (>0.02 μg/L) VOCs in the domestic wells. MtBE was detected more often in water samples with apparent ages of less than 25 years than in water samples with apparent ages greater than 25 years. This finding is consistent with the time period of high MtBE use in areas in the United States where reformulated gasoline was mandated. The largest pesticide concentration was an estimated concentration of 0.06 μg/L for the herbicide metolachlor. Deethylatrazine, a degradate of atrazine, (18 percent frequency detection) and atrazine (8 percent frequency detection) were the only pesticide compounds detected (>0.001 μg/L) in more than 3 percent of the domestic wells. None of the detected pesticide compounds exceeded human health benchmarks.
Concentrations of nitrate and gross alpha-particle activities were significantly greater in the water samples from the domestic wells than in samples from the public-supply wells. Concentrations of sodium, chloride, iron, manganese, and uranium were significantly greater in the water samples from the public-supply wells than in the samples from the domestic wells. One possible explanation may be related to differences in field processing (filtered samples from the domestic wells compared to unfiltered samples from the public-supply wells).
The high frequency of detections for a wide variety of manmade and naturally occurring contaminants in both domestic and public-supply wells shows the vulnerability of NECR aquifers to contamination. The highly variable water quality and the association with highly variable lithology of crystalline bedrock underscores the importance of testing individual wells to determine if concentrations for the most commonly detected contaminants exceed human health benchmarks.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115220","isbn":"ISBN 978-1-411-33417-5","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Flanagan, S.M., Ayotte, J.D., Robinson, G.R., Jr., 2018, Quality of water from crystalline rock aquifers in New England, New Jersey, and New York, 1995–2007 (ver.1.1, April 2018): U.S. Geological Survey 2011–5220, 104 p., https://doi.org/10.3133/sir20115220.\n","productDescription":"Report: xiv, 104 p.","numberOfPages":"122","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"1995-01-01","temporalEnd":"2007-12-31","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":353386,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5220/pdf/sir20115220.pdf","text":"Report","size":"9.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2011-5220"},{"id":353387,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2011/5220/versionHist.txt","size":"1.33 KB","linkFileType":{"id":2,"text":"txt"}},{"id":257873,"rank":100,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5220/index.html","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":257884,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2011/5220/images/coverthb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Rhode Island, and Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.03662109375,\n 40.56389453066509\n ],\n [\n -66.90673828125,\n 40.56389453066509\n ],\n [\n -66.90673828125,\n 47.39834920035926\n ],\n [\n -75.03662109375,\n 47.39834920035926\n ],\n [\n -75.03662109375,\n 40.56389453066509\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally released June 25, 2012; Version 1.1: April 13, 2018","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Ground water historically has been the sole source of water supply for the Town of Yucca Valley in the Warren subbasin of the Morongo ground-water basin, California. An imbalance between ground-water recharge and pumpage caused ground-water levels in the subbasin to decline by as much as 300 feet from the late 1940s through 1994. In response, the local water district, Hi-Desert Water District, instituted an artificial recharge program in February 1995 using imported surface water to replenish the ground water. The artificial recharge program resulted in water-level recoveries of as much as 250 feet in the vicinity of the recharge ponds between February 1995 and December 2001; however, nitrate concentrations in some wells also increased from a background concentration of 10 milligrams per liter to more than the U.S. Environmental Protection Agency (USEPA) maximum contaminant level (MCL) of 44 milligrams per liter (10 milligrams per liter as nitrogen).
The objectives of this study were to: (1) evaluate the sources of the high-nitrate concentrations that occurred after the start of the artificial-recharge program, (2) develop a ground-water flow and solute-transport model to better understand the source and transport of nitrates in the aquifer system, and (3) utilize the calibrated models to evaluate the possible effect of a proposed conjunctive-use project. These objectives were accomplished by collecting water-level and water-quality data for the subbasin and assessing changes that have occurred since artificial recharge began. Collected data were used to calibrate the ground-water flow and solute-transport models.
Data collected for this study indicate that the areal extent of the water-bearing deposits is much smaller (about 5.5 square miles versus 19 square miles) than that of the subbasin. These water-bearing deposits are referred to in this report as the Warren ground-water basin. Faults separate the ground-water basin into five hydrogeologic units: the west, the midwest, the mideast, the east and the northeast hydrogeologic units.
Water-quality analyses indicate that septage from septic tanks is the primary source of the high-nitrate concentrations measured in the Warren ground-water basin. Water-quality and stable-isotope data, collected after the start of the artificial recharge program, indicate that mixing occurs between imported water and native ground water, with the highest recorded nitrate concentrations in the midwest and the mideast hydrogeologic units. In general, the timing of the increase in measured nitrate concentrations in the midwest hydrogeologic unit is directly related to the distance of the monitoring well from a recharge site, indicating that the increase in nitrate concentrations is related to the artificial recharge program. Nitrate-to-chloride and nitrogen-isotope data indicate that septage is the source of the measured increase in nitrate concentrations in the midwest and the mideast hydrogeologic units. Samples from four wells in the Warren ground-water basin were analyzed for caffeine and selected human pharmaceutical products; these analyses suggest that septage is reaching the water table.
There are two possible conceptual models that explain how high-nitrate septage reaches the water table: (1) the continued downward migration of septage through the unsaturated zone to the water table and (2) rising water levels, a result of the artificial recharge program, entraining septage in the unsaturated zone. The observations that nitrate concentrations increase in ground-water samples from wells soon after the start of the artificial recharge program in 1995 and that the largest increase in nitrate concentrations occur in the midwest and mideast hydrogeologic units where the largest increase in water levels occur indicate the validity of the second conceptual model (rising water levels). The potential nitrate concentration resulting from a water-level rise in the midwest and mideast hydrogeologic units was estimated using a simple mixing-cell model. The estimated value is within the range of concentrations measured in samples from wells, further indicating the validity of the second conceptual model.
A ground-water flow model and a solute-transport model were developed for the Warren ground-water basin for the period 1956-2001. MODFLOW-96 was used for the ground-water flow model and MOC3D was used for the solute-transport model. The model cell size is about 500 feet by 500 feet and the models were discretized vertically into three layers. The models were calibrated using a trial-and-error approach using water-level and nitrate-concentration data collected between 1956-2001. In order to better match the measured data, low fault hydraulic characteristic values were required, thereby compartmentalizing the ground-water basin. In addition, it was necessary to parameterize the specific yield distribution for the top model layer where unconfined ground-water conditions occur into three homogeneous zones. Separate sets of specific- yield values were needed to simulate the drawdown and subsequent water-level recovery. In addition, the calibrated natural recharge was about 83 acre-feet per year. The entrainment of unsaturated-zone septage was simulated as recharge having an associated nitrate concentration. The volume of recharge was a function of the measured water-level rise between 1994-98 and the moisture content of the unsaturated zone. The nitrate concentration of the recharge water was a weighted function of the assumed nitrate concentration in the infiltrating water associated with the overlying land use. The simulated hydraulic head and nitrate concentration results were in good agreement with the measured data indicating that the mechanism for the increase in nitrate concentrations was rising water levels entraining high-nitrate septage in the unsaturated-zone.
The calibrated models were used to simulate the possible effects of a planned conjunctive-use project in the western part of the ground-water basin. The simulated project included the addition of a new recharge pond and a new extraction well. In addition, recharge at two existing recharge ponds was increased and three existing production wells were pumped, treated in a nitrate-removal facility, and used for water supply. The simulated hydraulic heads increased in the west, the mideast, and parts of the east hydrogeologic units; however, the simulated hydraulic heads decreased in the midwest and northeast hydrogeologic units. The simulated nitrate concentrations increased to above the MCL of 44 milligrams per liter (10 milligrams per liter as nitrogen) in parts of the west as a result of the increase in simulated hydraulic head. The simulated nitrate concentrations decreased in part of the midwest hydrogeologic unit as a result of the artificial recharge and pumping from the nitrate-removal wells. The simulated nitrate concentrations increased to above the MCL of 44 milligrams per liter in part of the mideast and parts of the east hydrogeologic units beneath commercial land-use areas.
The 1906 Great San Francisco earthquake (magnitude 7.8) and the 1989 Loma Prieta earthquake (magnitude 6.9) each motivated residents of the San Francisco Bay region to build countermeasures to earthquakes into the fabric of the region. Since Loma Prieta, bay-region communities, governments, and utilities have invested tens of billions of dollars in seismic upgrades and retrofits and replacements of older buildings and infrastructure. Innovation and state-of-the-art engineering, informed by science, including novel seismic-hazard assessments, have been applied to the challenge of increasing seismic resilience throughout the bay region. However, as long as people live and work in seismically vulnerable buildings or rely on seismically vulnerable transportation and utilities, more work remains to be done.
With that in mind, the U.S. Geological Survey (USGS) and its partners developed the HayWired scenario as a tool to enable further actions that can change the outcome when the next major earthquake strikes. By illuminating the likely impacts to the present-day built environment, well-constructed scenarios can and have spurred officials and citizens to take steps that change the outcomes the scenario describes, whether used to guide more realistic response and recovery exercises or to launch mitigation measures that will reduce future risk.
The HayWired scenario is the latest in a series of like-minded efforts to bring a special focus onto the impacts that could occur when the Hayward Fault again ruptures through the east side of the San Francisco Bay region as it last did in 1868. Cities in the east bay along the Richmond, Oakland, and Fremont corridor would be hit hardest by earthquake ground shaking, surface fault rupture, aftershocks, and fault afterslip, but the impacts would reach throughout the bay region and far beyond. The HayWired scenario name reflects our increased reliance on the Internet and telecommunications and also alludes to the interconnectedness of infrastructure, society, and our economy. How would this earthquake scenario, striking close to Silicon Valley, impact our interconnected world in ways and at a scale we have not experienced in any previous domestic earthquake?
The area of present-day Contra Costa, Alameda, and Santa Clara Counties contended with a magnitude-6.8 earthquake in 1868 on the Hayward Fault. Although sparsely populated then, about 30 people were killed and extensive property damage resulted. The question of what an earthquake like that would do today has been examined before and is now revisited in the HayWired scenario. Scientists have documented a series of prehistoric earthquakes on the Hayward Fault and are confident that the threat of a future earthquake, like that modeled in the HayWired scenario, is real and could happen at any time. The team assembled to build this scenario has brought innovative new approaches to examining the natural hazards, impacts, and consequences of such an event. Such an earthquake would also be accompanied by widespread liquefaction and landslides, which are treated in greater detail than ever before. The team also considers how the now-prototype ShakeAlert earthquake early warning system could provide useful public alerts and automatic actions.
Scientific Investigations Report 2017–5013 and accompanying data releases are the products of an effort led by the USGS, but this body of work was created through the combined efforts of a large team including partners who have come together to form the HayWired Coalition (see chapter A). Use of the HayWired scenario has already begun. More than a full year of intensive partner engagement, beginning in April 2017, is being directed toward producing the most in-depth look ever at the impacts and consequences of a large earthquake on the Hayward Fault. With the HayWired scenario, our hope is to encourage and support the active ongoing engagement of the entire community of the San Francisco Bay region by providing the scientific, engineering, and economic and social science inputs for use in exercises and planning well into the future.
As HayWired volumes are published, they will be made available at https://doi.org/10.3133/sir20175013.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175013","usgsCitation":"Detweiler, S.T., and Wein, A.M., eds., 2017, The HayWired earthquake scenario: U.S. Geological Survey Scientific Investigations Report 2017–5013, https://doi.org/10.3133/sir20175013.","productDescription":"3 Volumes","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":438111,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HKJU90","text":"USGS data release","linkHelpText":"Voice and data telecommunications restoration curves for 15 counties affected by the April 18, 2018, M7.0 HayWired earthquake scenario mainshock"},{"id":438110,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LMGHRV","text":"USGS data release","linkHelpText":"Fire following the Mw 7.0 HayWired earthquake scenario"},{"id":438109,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94Z8BOZ","text":"USGS data release","linkHelpText":"Estimated geospatial and tabular damages and vulnerable population distributions resulting from exposure to multiple hazards by the M7.0 HayWired scenario on April 18, 2018, for 17 counties in the San Francisco Bay region, California"},{"id":438108,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CLW518","text":"USGS data release","linkHelpText":"Economic subareas of interest data for areas containing concentrated damage resulting from the April 18, 2018, HayWired earthquake scenario in the San Francisco Bay region, California"},{"id":438107,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94HDTD8","text":"USGS data release","linkHelpText":"Results of individual and collocated lifeline exposure to hazards (and associated hazard and multi-hazard exposure surface data) resulting from the HayWired scenario earthquake sequence for counties and cities in the San Francisco Bay area, California"},{"id":438106,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UWWM0W","text":"USGS data release","linkHelpText":"Selected products of the scenario HayWired earthquake sequence Hazus analyses for 17 counties in the San Francisco Bay region, California"},{"id":353492,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20183016","text":"Fact Sheet 2018-3016","description":"FS 2018-3016","linkHelpText":"– The HayWired Earthquake Scenario—We Can Outsmart Disaster"},{"id":399529,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109753.htm"},{"id":399528,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109190.htm"},{"id":399527,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_107137.htm"},{"id":397249,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://geonarrative.usgs.gov/liquefactionandsealevelrise/","text":"Liquefaction and Sea-Level Rise","linkHelpText":"– A USGS storymap presenting the impacts of sea-level rise on liquefaction severity around the San Francisco Bay Area, California for the M7.0 ‘HayWired’ earthquake scenario along the Hayward Fault"},{"id":392896,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20213054","text":"Fact Sheet 2021-3054","linkHelpText":"– The HayWired Earthquake Scenario—Societal Consequences"},{"id":368403,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175013V3","text":"Scientific Investigations Report 2017-5013 Volume 3","description":"SIR 2017-5013 V3","linkHelpText":"– The HayWired Earthquake Scenario—Societal Consequences"},{"id":353491,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175013v2","text":"Scientific Investigations Report 2017-5013 Volume 2","description":"SIR 2017-5013 V2","linkHelpText":"– The HayWired Earthquake Scenario—Engineering Implications"},{"id":340064,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5013/coverthb1.jpg"},{"id":353442,"rank":2,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175013v1","text":"Scientific Investigations Report 2017-5013 Volume 1","description":"SIR 2017-5013 V1","linkHelpText":"– The HayWired Earthquake Scenario—Earthquake Hazards"}],"country":"United States","state":"California","otherGeospatial":"Hayward Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123,\n 37\n ],\n [\n -121,\n 37\n ],\n [\n -121,\n 38.65\n ],\n [\n -123,\n 38.65\n ],\n [\n -123,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Menlo Park, Calif.
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This 1:50,000-scale U.S. Geological Survey geologic map represents a compilation of the most recent geologic studies of the upper Arkansas River valley between Leadville and Salida, Colorado. The valley is structurally controlled by an extensional fault system that forms part of the prominent northern Rio Grande rift, an intra-continental region of crustal extension. This report also incorporates new detailed geologic mapping of previously poorly understood areas within the map area and reinterprets previously studied areas. The mapped region extends into the Proterozoic metamorphic and intrusive rocks in the Sawatch Range west of the valley and the Mosquito Range to the east. Paleozoic rocks are preserved along the crest of the Mosquito Range, but most of them have been eroded from the Sawatch Range. Numerous new isotopic ages better constrain the timing of both Proterozoic intrusive events, Late Cretaceous to early Tertiary intrusive events, and Eocene and Miocene volcanic episodes, including widespread ignimbrite eruptions. The uranium-lead ages document extensive about 1,440-million years (Ma) granitic plutonism mostly north of Buena Vista that produced batholiths that intruded an older suite of about 1,760-Ma metamorphic rocks and about 1,700-Ma plutonic rocks. As a result of extension during the Neogene and possibly latest Paleogene, the graben underlying the valley is filled with thick basin-fill deposits (Dry Union Formation and older sediments), which occupy two sub-basins separated by a bedrock high near the town of Granite. The Dry Union Formation has undergone deep erosion since the late Miocene or early Pliocene. During the Pleistocene, ongoing stream incision by the Arkansas River and its major tributaries has been interrupted by periodic aggradation. From Leadville south to Salida as many as seven mapped alluvial depositional units, that range in age from early to late Pleistocene, record periodic aggradational events along these streams that are commonly associated with deposition of glacial outwash or bouldery glacial-flood deposits. Many previously unrecognized Neogene and Quaternary faults, some of the latter with possible Holocene displacement, have been identified on lidar (light detection and ranging) imagery which covers 59 percent of the map area. This imagery has also permitted more accurate remapping of glacial, fluvial, and mass-movement deposits and aided in the determination of their relative ages. Recently published 10beryllium cosmogenic surface-exposure ages, coupled with our new geologic mapping, have revealed the timing and rates of late Pleistocene deglaciation. Glacial dams that impounded the Arkansas River at Clear Creek and possibly at Pine Creek failed at least three times during the middle and late Pleistocene, resulting in catastrophic floods and deposition of enormous boulders and bouldery alluvium downstream; at least two failures occurred during the late Pleistocene during the Pinedale glaciation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3382","usgsCitation":"Kellogg, K.S., Shroba, R.R., Ruleman, C.A., Bohannon, R.G., McIntosh, W. C., Premo, W.R., Cosca, M.A., Moscati, R.J., and Brandt, T.R., 2017, Geologic map of the upper Arkansas River valley region, north-central Colorado: U.S. Geological Survey Scientific Investigations Map 3382, pamphlet 70 p., 2 sheets, scale 1:50,000, https://doi.org/10.3133/sim3382.","productDescription":"Report: vi, 70 p.; 4 Sheets; Data Release; Read Me","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-078599","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":348012,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75B00XQ","text":"USGS Data Release","description":"USGS data release","linkHelpText":"Data release for the geologic map of the upper Arkansas River valley region, north-central Colorado"},{"id":351653,"rank":9,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3382/versionHist.txt","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3382 Version History"},{"id":348008,"rank":7,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3382/sim3382_ReadMe.txt","text":"Read Me","size":"12.0 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3382 Read Me"},{"id":348002,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3382/sim3382_sheet1_hillshade.pdf","text":"Sheet 1, with hillshade—","size":"102 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3382 Sheet 1 with hillshade","linkHelpText":"Geologic map with shaded relief"},{"id":347996,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3382/sim3382_sheet1_georeferenced.pdf","text":"Sheet 1, georeferenced—","size":"335 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3382 Sheet 1 georeferenced","linkHelpText":"Georeferenced geologic map"},{"id":348005,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3382/sim3382_sheet2.pdf","text":"Sheet 2—","size":"1.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3382 Sheet 2","linkHelpText":" Correlation and description of map units"},{"id":348004,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3382/sim3382_sheet1_no_hillshade.pdf","text":"Sheet 1, without hillshade—","size":"50.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3382 Sheet 1 without hillshade","linkHelpText":"Geologic map without shaded relief"},{"id":347995,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3382/sim3382.pdf","text":"Report","size":"17.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3382 Report"},{"id":347994,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3382/coverthb2.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Upper Arkansas River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.5,\n 38.5\n ],\n [\n -105.9,\n 38.5\n ],\n [\n -105.9,\n 39.5\n ],\n [\n -106.5,\n 39.5\n ],\n [\n -106.5,\n 38.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046
The Washington West 30’ × 60’ quadrangle covers an area of approximately 4,884 square kilometers (1,343 square miles) in and west of the Washington, D.C., metropolitan area. The eastern part of the area is highly urbanized, and more rural areas to the west are rapidly being developed. The area lies entirely within the Chesapeake Bay drainage basin and mostly within the Potomac River watershed. It contains part of the Nation's main north-south transportation corridor east of the Blue Ridge Mountains, consisting of Interstate Highway 95, U.S. Highway 1, and railroads, as well as parts of the Capital Beltway and Interstate Highway 66. Extensive Federal land holdings in addition to those in Washington, D.C., include the Marine Corps Development and Education Command at Quantico, Fort Belvoir, Vint Hill Farms Station, the Naval Ordnance Station at Indian Head, the Chesapeake and Ohio Canal National Historic Park, Great Falls Park, and Manassas National Battlefield Park. The quadrangle contains most of Washington, D.C.; part or all of Arlington, Culpeper, Fairfax, Fauquier, Loudoun, Prince William, Rappahannock, and Stafford Counties in northern Virginia; and parts of Charles, Montgomery, and Prince Georges Counties in Maryland.
The Washington West quadrangle spans four geologic provinces. From west to east these provinces are the Blue Ridge province, the early Mesozoic Culpeper basin, the Piedmont province, and the Coastal Plain province. There is some overlap in ages of rocks in the Blue Ridge and Piedmont provinces. The Blue Ridge province, which occupies the western part of the quadrangle, contains metamorphic and igneous rocks of Mesoproterozoic to Early Cambrian age. Mesoproterozoic (Grenville-age) rocks are mostly granitic gneisses, although older metaigneous rocks are found as xenoliths. Small areas of Neoproterozoic metasedimentary rocks nonconformably overlie Mesoproterozoic rocks. Neoproterozoic granitic rocks of the Robertson River Igneous Suite intruded the Mesoproterozoic rocks. The Mesoproterozoic rocks are nonconformably overlain by Neoproterozoic metasedimentary rocks of the Fauquier and Lynchburg Groups, which in turn are overlain by metabasalt of the Catoctin Formation. The Catoctin Formation is overlain by Lower Cambrian clastic metasedimentary rocks of the Chilhowee Group. The Piedmont province is exposed in the east-central part of the map area, between overlapping sedimentary units of the Culpeper basin on the west and those of the Coastal Plain province on the east. In this area, the Piedmont province contains Neoproterozoic and lower Paleozoic metamorphosed sedimentary, volcanic, and plutonic rocks. Allochthonous mélange complexes on the western side of the Piedmont are bordered on the east by metavolcanic and metasedimentary rocks of the Chopawamsic Formation, which has been interpreted as part of volcanic arc. The mélange complexes are unconformably overlain by metasedimentary rocks of the Popes Head Formation. The Silurian and Ordovician Quantico Formation is the youngest metasedimentary unit in this part of the Piedmont. Igneous rocks include the Garrisonville Mafic Complex, transported ultramafic and mafic inclusions in mélanges, monzogranite of the Dale City pluton, and Ordovician tonalitic and granitic plutons. Jurassic diabase dikes are the youngest intrusions. The fault boundary between rocks of the Blue Ridge and Piedmont provinces is concealed beneath the Culpeper basin in this area but is exposed farther south. Early Mesozoic rocks of the Culpeper basin unconformably overlie those of the Piedmont and Blue Ridge provinces in the central part of the quadrangle. The north-northeast-trending extensional basin contains Upper Triassic to Lower Jurassic nonmarine sedimentary rocks. Lower Jurassic sedimentary strata are interbedded with basalt flows, and both Upper Triassic and Lower Jurassic strata are intruded by diabase of Early Jurassic age. The Bull Run Mountain fault, a major Mesozoic normal fault characterized by down-to-the-east displacement, separates rocks of the Culpeper basin from those of the Blue Ridge province on the west. On the east, the contact between rocks of the Culpeper basin and those of the Piedmont province is an unconformity, which has been locally disrupted by normal faults. Sediments of the Coastal Plain province unconformably overlie rocks of the Piedmont province along the Fall Zone and occupy the eastern part of the quadrangle. Lower Cretaceous deposits of the Potomac Formation consist of fluvial-deltaic gravels, sands, silts, and clays. Discontinuous fluvial and estuarine terrace deposits of Pleistocene and middle- to late-Tertiary age flank the modern Potomac River valley unconformable capping these Cretaceous strata and the crystalline basement where the Cretaceous has been removed by erosion. East of the Potomac River, the Potomac Formation is onlapped and unconformably overlain by a westward thinning wedge of marine sedimentary deposits of Late Cretaceous and early- and late-Tertiary age. Basement rooted Coastal Plain faults of Tertiary to Quaternary age occur along the Fall Zone and this part of the inner Coastal Plain. These Coastal Plain faults have geomorphic expression that appear to influence river drainage patterns.
The geologic map of the Washington West quadrangle is intended to serve as a foundation for applying geologic information to problems involving land use decisions, groundwater availability and quality, earth resources such as natural aggregate for construction, assessment of natural hazards, and engineering and environmental studies for waste disposal sites and construction projects. This 1:100,000-scale map is mainly based on more detailed geologic mapping at a scale of 1:24,000.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171142","usgsCitation":"Lyttle, P.T., Aleinikoff, J.N., Burton, W.C., Crider, E.A., Jr., Drake, A.A., Jr., Froelich, A.J., Horton, J.W., Jr., Kasselas, Gregorios, Mixon, R.B., McCartan, Lucy, Nelson, A.E., Newell, W.L., Pavlides, Louis, Powars, D.S., Southworth, C.S., and Weems, R.E., 2017, Geologic map of the Washington West 30’ × 60’ quadrangle, Maryland, Virginia, and Washington D.C.: U.S. Geological Survey Open-File Report 2017–1142, 1 sheet, scale 1:100,000, https://doi.org/10.3133/ofr20171142.","productDescription":"Map: 55.30 x 60.78 inches; Database; Database Metadata; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052801","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":350265,"rank":6,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142_washington-west-geologic-map-database.zip","text":"Database","size":"102 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Washington West Geologic Map Database"},{"id":350266,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142_washingtonwestVADCMD-ArcGIS-10.0.mxd","size":"438 KB mxd","linkHelpText":"- Washington West: Maryland, Virginia, and Washington, D.C. (ArcGIS 10.0)"},{"id":350263,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142_washington-west-base-map.zip","text":"Base Map","size":"50.4 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Washington West Base Map Files"},{"id":350262,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142_washington-west-geologic-shapefiles.zip","text":"Shapefiles","size":"9.08 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Washington West Geologic Shapefiles"},{"id":350260,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1142/coverthb.jpg"},{"id":350261,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142.pdf","text":"Report","size":"35.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1142"},{"id":350264,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142_washington-west-geologic-database-metadata.zip","text":"Database Metadata","linkHelpText":"- Washington West Geologic Database Metadata"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Washington, D.C.","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78,\n 38.5\n ],\n [\n -77,\n 38.5\n ],\n [\n -77,\n 39\n ],\n [\n -78,\n 39\n ],\n [\n -78,\n 38.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate Science Center
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In river valleys, fluvial and upland landscapes are intrinsically linked through sediment exchange between the active channel, near-channel fluvial deposits, and higher elevation upland deposits. During floods, sediment is transferred from channels to low-elevation nearchannel deposits [Schmidt and Rubin, 1995]. Particularly in dryland river valleys, subsequent aeolian reworking of these flood deposits redistributes sediment to higher elevation upland sites, thus maintaining naturallyoccurring aeolian landscapes [Draut, 2012].
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"RCEM 2017 - Back to Italy: The 10th Symposium on River, Coastal and Estuarine Morphodynamics","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"University of Trento - Italy","usgsCitation":"Kasprak, A., Bangen, S.G., Buscombe, D.D., Caster, J., East, A.E., Grams, P.E., and Sankey, J.B., 2017, Linking fluvial and aeolian morphodynamics in the Grand Canyon, USA, in RCEM 2017 - Back to Italy: The 10th Symposium on River, Coastal and Estuarine Morphodynamics, p. 204-204.","productDescription":"1 p.","startPage":"204","endPage":"204","ipdsId":"IP-083761","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":351495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Grand Canyon","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee788e4b0da30c1bfc2d0","contributors":{"authors":[{"text":"Kasprak, Alan 0000-0001-8184-6128 akasprak@usgs.gov","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":190848,"corporation":false,"usgs":true,"family":"Kasprak","given":"Alan","email":"akasprak@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":717956,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bangen, Sara G.","contributorId":190858,"corporation":false,"usgs":false,"family":"Bangen","given":"Sara","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":717957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buscombe, Daniel D. 0000-0001-6217-5584","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":198817,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","middleInitial":"D.","affiliations":[],"preferred":false,"id":717958,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caster, Joshua 0000-0002-2858-1228 jcaster@usgs.gov","orcid":"https://orcid.org/0000-0002-2858-1228","contributorId":199033,"corporation":false,"usgs":true,"family":"Caster","given":"Joshua","email":"jcaster@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":717959,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":717960,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grams, Paul E. 0000-0002-0873-0708 pgrams@usgs.gov","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":1830,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","email":"pgrams@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":717961,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":717962,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70195670,"text":"70195670 - 2017 - Amplification of earthquake ground motions in Washington, DC, and implications for hazard assessments in central and eastern North America","interactions":[],"lastModifiedDate":"2018-02-27T10:04:20","indexId":"70195670","displayToPublicDate":"2018-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Amplification of earthquake ground motions in Washington, DC, and implications for hazard assessments in central and eastern North America","docAbstract":"The extent of damage in Washington, DC, from the 2011 Mw 5.8 Mineral, VA, earthquake was surprising for an epicenter 130 km away; U.S. Geological Survey “Did-You-Feel-It” reports suggest that Atlantic Coastal Plain and other unconsolidated sediments amplified ground motions in the city. We measure this amplification relative to bedrock sites using earthquake signals recorded on a temporary seismometer array. The spectral ratios show strong amplification in the 0.7 to 4 Hz frequency range for sites on sediments. This range overlaps with resonant frequencies of buildings in the city as inferred from their heights, suggesting amplification at frequencies to which many buildings are vulnerable to damage. Our results emphasize that local amplification can raise moderate ground motions to damaging levels in stable continental regions, where low attenuation extends shaking levels over wide areas and unconsolidated deposits on crystalline metamorphic or igneous bedrock can result in strong contrasts in near-surface material properties.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017GL075517","usgsCitation":"Pratt, T.L., Horton, J.W., Munoz, J., Hough, S.E., Chapman, M.C., and Olgun, C.G., 2017, Amplification of earthquake ground motions in Washington, DC, and implications for hazard assessments in central and eastern North America: Geophysical Research Letters, v. 44, no. 24, p. 12150-12160, https://doi.org/10.1002/2017GL075517.","productDescription":"11 p.","startPage":"12150","endPage":"12160","ipdsId":"IP-092357","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":352058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":352048,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1002/2017GL075517/full"}],"country":"United States","otherGeospatial":"Washington, DC","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82,\n 36\n ],\n [\n -75,\n 36\n ],\n [\n -75,\n 40\n ],\n [\n -82,\n 40\n ],\n [\n -82,\n 36\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","issue":"24","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-23","publicationStatus":"PW","scienceBaseUri":"5afee788e4b0da30c1bfc2c8","contributors":{"authors":[{"text":"Pratt, Thomas L. 0000-0003-3131-3141 tpratt@usgs.gov","orcid":"https://orcid.org/0000-0003-3131-3141","contributorId":3279,"corporation":false,"usgs":true,"family":"Pratt","given":"Thomas","email":"tpratt@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":729624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Horton, J. Wright Jr. 0000-0001-6756-6365 whorton@usgs.gov","orcid":"https://orcid.org/0000-0001-6756-6365","contributorId":173694,"corporation":false,"usgs":true,"family":"Horton","given":"J.","suffix":"Jr.","email":"whorton@usgs.gov","middleInitial":"Wright","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":729625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Munoz, Jessica","contributorId":202790,"corporation":false,"usgs":false,"family":"Munoz","given":"Jessica","email":"","affiliations":[],"preferred":false,"id":729626,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":729627,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chapman, Martin C.","contributorId":139348,"corporation":false,"usgs":false,"family":"Chapman","given":"Martin","email":"","middleInitial":"C.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":729628,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Olgun, C. Guney 0000-0001-9751-1103","orcid":"https://orcid.org/0000-0001-9751-1103","contributorId":202791,"corporation":false,"usgs":false,"family":"Olgun","given":"C.","email":"","middleInitial":"Guney","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":729629,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70220302,"text":"70220302 - 2017 - Preliminary-assessment and upgrade of a groundwater flow model of the Seacoast Bedrock Aquifer, New Hampshire","interactions":[],"lastModifiedDate":"2021-06-02T15:23:50.809272","indexId":"70220302","displayToPublicDate":"2017-12-31T10:19:40","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Preliminary-assessment and upgrade of a groundwater flow model of the Seacoast Bedrock Aquifer, New Hampshire","docAbstract":"In 2003 and 2004, the U.S. Geological Survey investigated the availability of groundwater resources in a 160-square mile area of coastal New Hampshire (Figure 1) using a regional groundwater flow model (Mack, 2009). At that time, population growth and increasing water demand prompted concern for the sustainability of the region’s groundwater resources in a fractured-crystalline bedrock-aquifer with little storage. The groundwater flow model developed for the previous study incorporated detailed water-use information for 2003-4 and simulated the effects of projected increases in water use. However, poor stream representation may reduce the effectiveness of the original model head simulations. Improvements to the model, made by incorporating the USGS’s MODLFOW-2005 Newton formulation (MODFLOW-NWT, Niswonger and others, 2011) and by more accurately representing stream characteristics, are presented in an example simulating approximate changes in water use. Groundwater heads in an area of relatively larger population change, near the center of the Seacoast’s fractured bedrock aquifer, were simulated with the upgraded model using published 2004, and approximated 2015, water use rates. This area is situated at a local topographic high point and near the junction of three towns, where drainages flow westward, toward Great Bay, and eastward, toward the Atlantic Ocean (Figure 1).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the MODFLOW and more 2017 conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"MODFLOW and More 2017","conferenceDate":"May 21-24, 2017","language":"English","usgsCitation":"Mack, T., 2017, Preliminary-assessment and upgrade of a groundwater flow model of the Seacoast Bedrock Aquifer, New Hampshire, in Proceedings of the MODFLOW and more 2017 conference, May 21-24, 2017, p. 40-44.","productDescription":"5 p.","startPage":"40","endPage":"44","ipdsId":"IP-087643","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":386128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Hampshire","otherGeospatial":"Seacoast Bedrock Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.71418762207031,\n 43.04079076668198\n ],\n [\n -70.71075439453125,\n 43.071395809535375\n ],\n [\n -70.78628540039062,\n 43.08493742707592\n ],\n [\n -70.8570098876953,\n 43.1405770781429\n ],\n [\n -70.9881591796875,\n 43.033764503405315\n ],\n [\n -70.98953247070311,\n 42.82663145362289\n ],\n [\n -70.81443786621094,\n 42.82209892875648\n ],\n [\n -70.74783325195311,\n 42.976520698105524\n ],\n [\n -70.71418762207031,\n 43.03777960950732\n ],\n [\n -70.71418762207031,\n 43.04079076668198\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mack, Thomas J. 0000-0002-0496-3918","orcid":"https://orcid.org/0000-0002-0496-3918","contributorId":218727,"corporation":false,"usgs":true,"family":"Mack","given":"Thomas J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":815071,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70196903,"text":"70196903 - 2017 - Analysis of the age and paleomagnetic orientation of the Broadwell Mesa Basalt, Bristol Mountains, CA","interactions":[],"lastModifiedDate":"2019-06-13T10:32:18","indexId":"70196903","displayToPublicDate":"2017-12-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Analysis of the age and paleomagnetic orientation of the Broadwell Mesa Basalt, Bristol Mountains, CA","docAbstract":"To add to the regional paleomagnetic data documenting block rotation in eastern California, we determined the age and paleomagnetic rotation of the Broadwell Mesa basalt, a basalt in the Bristol Mountains, CA as part of an effort to constrain the timing and rotation of blocks adjacent to the fault. The east-striking sinistral Broadwell Mesa fault cuts and separates the basalt into two outcrops. An 40Ar/39Ar date from the northern outcrop yields an age of 5.46 ± 0.04 Ma. Two sites consisting of 40 paleomagnetic cores from the basalt indicate the basalt is reversely magnetized and that there has been no significant rotation (< 11º) between the two basalt outcrops.","largerWorkTitle":"ECSZ Does It: Revisiting the Eastern California Shear Zone","conferenceTitle":"2017 Desert Symposium","conferenceDate":"April 2017","conferenceLocation":"Zzyzx, CA","language":"English","publisher":"Desert Studies Center, California State University at Fullerton","usgsCitation":"Phelps, G., Hillhouse, J., Fleck, R.J., Miller, D., Buesch, D.C., Cyr, A.J., and Schmidt, K.M., 2017, Analysis of the age and paleomagnetic orientation of the Broadwell Mesa Basalt, Bristol Mountains, CA, in ECSZ Does It: Revisiting the Eastern California Shear Zone, Zzyzx, CA, April 2017, p. 97-102.","productDescription":"6 p.","startPage":"97","endPage":"102","ipdsId":"IP-084405","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":354100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":354027,"type":{"id":15,"text":"Index Page"},"url":"https://www.desertsymposium.org/About.html"}],"country":"United States","state":"California","city":"ZZyzx","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.02783203125,\n 44.1151978766043\n ],\n [\n -109.94293212890625,\n 44.1151978766043\n ],\n [\n -109.94293212890625,\n 44.88895839978044\n ],\n [\n -111.02783203125,\n 44.88895839978044\n ],\n [\n -111.02783203125,\n 44.1151978766043\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.27243041992188,\n 35.04798673426734\n ],\n [\n -115.99777221679686,\n 35.04798673426734\n 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0000-0002-1371-4622","orcid":"https://orcid.org/0000-0002-1371-4622","contributorId":204776,"corporation":false,"usgs":true,"family":"Hillhouse","given":"John","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":734966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fleck, Robert J. 0000-0002-3149-8249 fleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3149-8249","contributorId":1048,"corporation":false,"usgs":true,"family":"Fleck","given":"Robert","email":"fleck@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":734963,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, David M. 0000-0003-3711-0441 dmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":140769,"corporation":false,"usgs":true,"family":"Miller","given":"David M.","email":"dmiller@usgs.gov","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":734964,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buesch, David C. 0000-0002-4978-5027 dbuesch@usgs.gov","orcid":"https://orcid.org/0000-0002-4978-5027","contributorId":1154,"corporation":false,"usgs":true,"family":"Buesch","given":"David","email":"dbuesch@usgs.gov","middleInitial":"C.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":734965,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cyr, Andrew J. 0000-0003-2293-5395 acyr@usgs.gov","orcid":"https://orcid.org/0000-0003-2293-5395","contributorId":3539,"corporation":false,"usgs":true,"family":"Cyr","given":"Andrew","email":"acyr@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":734961,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmidt, Kevin M. 0000-0003-2365-8035 kschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-2365-8035","contributorId":1985,"corporation":false,"usgs":true,"family":"Schmidt","given":"Kevin","email":"kschmidt@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":734962,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70197039,"text":"70197039 - 2017 - Comparison of the precision of age estimates generated from fin rays, scales, and otoliths of Blue Sucker","interactions":[],"lastModifiedDate":"2018-05-15T10:09:26","indexId":"70197039","displayToPublicDate":"2017-12-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3444,"text":"Southeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of the precision of age estimates generated from fin rays, scales, and otoliths of Blue Sucker","docAbstract":"Evaluating the precision of age estimates generated by different readers and different calcified structures is an important part of generating reliable estimations of growth, recruitment, and mortality for fish populations. Understanding the potential loss of precision associated with using structures harvested without sacrificing individuals, such as scales or fin rays, is particularly important when working with imperiled species, such as Cycleptus elongatus (Blue Sucker). We collected otoliths (lapilli), scales, and the first fin rays of the dorsal, anal, pelvic, and pectoral fins of 9 Blue Suckers. We generated age estimates from each structure by both experienced (n = 5) and novice (n = 4) readers. We found that, independent of the structure used to generate the age estimates, the mean coefficient of variation (CV) of experienced readers was approximately 29% lower than that of novice readers. Further, the mean CV of age estimates generated from pectoral-fin rays, pelvic-fin rays, and scales were statistically indistinguishable and less than those of dorsal-fin rays, anal-fin rays, and otoliths. Anal-, dorsal-, and pelvic-fin rays and scales underestimated age compared to otoliths, but age estimates from pectoral-fin rays were comparable to those from otoliths. Skill level, structure, and fish total-length influenced reader precision between subsequent reads of the same aging structure from a particular fish. Using structures that can be harvested non-lethally to estimate the age of Blue Sucker can provide reliable and reproducible results, similar to those that would be expected from using otoliths. Therefore, we recommend the use of pectoral-fin rays as a non-lethal method to obtain age estimates for Blue Suckers.
The Devonian-age Marcellus Shale and the Ordovician-age Utica Shale, which have the potential for natural gas development, underlie Pike County and neighboring counties in northeastern Pennsylvania. In 2015, the U.S. Geological Survey, in cooperation with the Pike County Conservation District, conducted a study that expanded on a previous more limited 2012 study to assess baseline shallow groundwater quality in bedrock aquifers in Pike County prior to possible extensive shale-gas development. Seventy-nine water wells ranging in depths from 80 to 610 feet were sampled during June through September 2015 to provide data on the presence of methane and other aspects of existing groundwater quality in the various bedrock geologic units throughout the county, including concentrations of inorganic constituents commonly present at low values in shallow, fresh groundwater but elevated in brines associated with fluids extracted from geologic formations during shale-gas development. All groundwater samples collected in 2015 were analyzed for bacteria, dissolved and total major ions, nutrients, selected dissolved and total inorganic trace constituents (including metals and other elements), radon-222, gross alpha- and gross beta-particle activity, dissolved gases (methane, ethane, and propane), and, if sufficient methane was present, the isotopic composition of methane. Additionally, samples from 20 wells distributed throughout the county were analyzed for selected man-made volatile organic compounds, and samples from 13 wells where waters had detectable gross alpha activity were analyzed for radium-226 on the basis of relatively elevated gross alpha-particle activity.
Results of the 2015 study show that groundwater quality generally met most drinking-water standards for constituents and properties included in analyses, but groundwater samples from some wells had one or more constituents or properties, including arsenic, iron, manganese, pH, bacteria, sodium, chloride, sulfate, total dissolved solids, and radon-222, that did not meet (commonly termed failed or exceeded) primary or secondary maximum contaminant levels (MCLs) or Health Advisories (HA) for drinking water. Except for iron, dissolved and total concentrations of major ions and most trace constituents generally were similar. Only 1 of 79 well-water samples had any constituent that exceeded a MCL, with an arsenic concentration of about 30 micrograms per liter (µg/L) that was higher than the MCL of 10 µg/L. However, total arsenic concentrations were higher than the HA of 2 µg/L in samples from another 12 of 79 wells (about 15 percent). Secondary maximum contaminant levels (SMCLs) were exceeded most frequently by pH and concentrations of iron and manganese. The pH was outside of the SMCL range of 6.5–8.5 in samples from 24 of 79 wells (30 percent), ranging from 5.5 to 9.2; more samples had pH values less than 6.5 than had pH values greater than 8.5. Total iron concentrations typically were much greater than dissolved iron concentrations, indicating substantial presence of iron in particulate phase, and exceeded the SMCL of 300 µg/L more often [35 of 79 samples (44 percent)] than dissolved iron concentrations [samples from 8 of 79 wells (10 percent)]. Total manganese concentrations exceeded the SMCL of 50 µg/L in samples from 31 of 79 wells (39 percent) and the HA of 300 µg/L in samples from 13 of 79 wells (about 16 percent). A few (1–2) samples had concentrations of sodium, chloride, sulfate, or TDS higher than the SMCLs of 60, 250, 250, and 500 mg/L, respectively. However, dissolved sodium concentrations were higher than the HA of 20 mg/L in samples from 15 of 79 wells (nearly 20 percent). Total coliform bacteria were detected in samples from 25 of 79 wells (32 percent) but Escherichia coli were not detected in any sample. Radon-222 activities ranged from 11 to 5,100 picocuries per liter (pCi/L), with a median of 1,440 pCi/L, and exceeded the proposed and the alternate proposed drinking-water standards of 300 and 4,000 pCi/L, respectively, in samples from 60 of 79 wells (75 percent) and in samples from 2 of 79 wells (3 percent), respectively.
Groundwater samples from all wells were analyzed for dissolved methane by one contract laboratory that determined water from 19 of the 79 wells (24 percent) had concentrations of methane greater than the reporting level of 0.010 milligrams per liter (mg/L) with a maximum methane concentration of 2.5 mg/L. Methane concentrations in 18 replicate samples submitted to a second laboratory for dissolved gas and isotopic analysis generally were higher by as much as a factor of 2.7 from those determined by the first laboratory, indicating potential bias related to combined sampling and analytical methods, and therefore, caution needs to be used when comparing methane results determined by different methods. The isotopic composition of methane in 9 of 10 samples with sufficient dissolved methane (about 0.3 mg/L) for isotopic analysis is consistent with values reported for methane of microbial origin produced through carbon dioxide reduction; an isotopic shift in 1 or 2 samples may indicate subsequent methane oxidation. The low concentrations of ethane relative to methane in these samples further indicate that the methane may be of microbial origin. Groundwater samples with relatively elevated methane concentrations (near or greater than 0.3 mg/L) also had chemical compositions that differed in some respects from groundwater with relatively low methane concentrations (less than 0.3 mg/L) by having higher pH (greater than 8) and higher concentrations of sodium, lithium, boron, fluoride, arsenic, and bromide and chloride/bromide ratios indicative of mixing with a small amount of brine of probable natural occurrence.
The spatial distribution of groundwater compositions differs by topographic setting and lithology and generally shows that (1) relatively dilute, slightly acidic, oxygenated, calcium-carbonate type waters tend to occur in the uplands underlain by the undivided Poplar Gap and Packerton members of the Catskill Formation in southwestern Pike County; (2) waters of near neutral pH with the highest amounts of hardness (calcium and magnesium) generally occur in areas of intermediate altitudes underlain by other members of the Catskill Formation; and (3) waters with pH values greater than 8, low oxygen concentrations, and the highest arsenic, sodium, lithium, bromide, and methane concentrations can be present in deep wells in uplands but most frequently occur in stream valleys, especially at low altitudes (less than about 1,200 feet above North American Vertical Datum of 1988) where groundwater may be discharging regionally, such as to the Delaware River in northern and eastern Pike County. Thus, the baseline assessment of groundwater quality in Pike County prior to gas-well development shows that shallow (less than about 1,000 feet deep) groundwater generally meets primary drinking-water standards for inorganic constituents but varies spatially, with methane and some constituents present in high concentrations in brine (and connate waters from gas and oil reservoirs) present at low to moderate concentrations in some parts of Pike County.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175110","collaboration":"Prepared in cooperation with the Pike County Conservation District","usgsCitation":"Senior, L.A., and Cravotta, C.A., III, 2017: Baseline assessment of groundwater quality in Pike County, Pennsylvania, 2015: U.S. Geological Survey Scientific Investigations Report 2017–5110, 181 p., https://doi.org/10.3133/sir20175110.","productDescription":"Report: xii, 181 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-088156","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":350196,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5980c3c0e4b0a38ca278a8c9","text":"USGS Data Release","linkHelpText":"Field properties and results of laboratory analysis of groundwater samples collected from 79 wells in Pike County, Pennsylvania, 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Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070-2424
http://pa.water.usgs.gov
Climate change refugia, areas buffered from climate change relative to their surroundings, are of increasing interest as natural resource managers seek to prioritize climate adaptation actions. However, evidence that refugia buffer the effects of anthropogenic climate change is largely missing.
Focusing on the climate-sensitive Belding’s ground squirrel (Urocitellus beldingi), we predicted that highly connected Sierra Nevada meadows that had warmed less or shown less precipitation change over the last century would have greater population persistence, as measured by short-term occupancy, fewer extirpations over the twentieth century, and long-term persistence measured through genetic diversity.
Across California, U. beldingi were more likely to persist over the last century in meadows with high connectivity that were defined as refugial based on a suite of temperature and precipitation factors. In Yosemite National Park, highly connected refugial meadows were more likely to be occupied by U. beldingi. More broadly, populations inhabiting Sierra Nevada meadows with colder mean winter temperatures had higher values of allelic richness at microsatellite loci, consistent with higher population persistence in temperature-buffered sites. Furthermore, both allelic richness and gene flow were higher in meadows that had higher landscape connectivity, indicating the importance of metapopulation processes. Conversely, anthropogenic refugia, sites where populations appeared to persist due to food or water supplementation, had lower connectivity, genetic diversity, and gene flow, and thus might act as ecological traps. This study provides evidence that validates the climate change refugia concept in a contemporary context and illustrates how to integrate field observations and genetic analyses to test the effectiveness of climate change refugia and connectivity.
Climate change refugia will be important for conserving populations as well as genetic diversity and evolutionary potential. Our study shows that in-depth modeling paired with rigorous fieldwork can identify functioning climate change refugia for conservation.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s40665-017-0036-5","usgsCitation":"Morelli, T.L., Maher, S.P., Lim, M.C., Kastely, C., Eastman, L.M., Flint, L.E., Flint, A.L., Beissinger, S.R., and Moritz, C., 2017, Climate change refugia and habitat connectivity promote species persistence: Climate Change Responses, v. 4, 8, 12 p., https://doi.org/10.1186/s40665-017-0036-5.","productDescription":"8, 12 p.","ipdsId":"IP-091107","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":469229,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40665-017-0036-5","text":"Publisher Index Page"},{"id":376819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.94873046875,\n 37.51844023887861\n ],\n [\n -119.2236328125,\n 37.51844023887861\n ],\n [\n -119.2236328125,\n 38.199338565983844\n ],\n [\n -119.94873046875,\n 38.199338565983844\n ],\n [\n -119.94873046875,\n 37.51844023887861\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","noUsgsAuthors":false,"publicationDate":"2017-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":794322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maher, Sean P.","contributorId":7998,"corporation":false,"usgs":true,"family":"Maher","given":"Sean","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":794323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lim, Marisa C. W.","contributorId":236825,"corporation":false,"usgs":false,"family":"Lim","given":"Marisa","email":"","middleInitial":"C. W.","affiliations":[],"preferred":false,"id":794324,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kastely, Christina","contributorId":236826,"corporation":false,"usgs":false,"family":"Kastely","given":"Christina","email":"","affiliations":[],"preferred":false,"id":794325,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eastman, Lindsey M.","contributorId":236827,"corporation":false,"usgs":false,"family":"Eastman","given":"Lindsey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":794362,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":794363,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":794364,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Beissinger, Steven R.","contributorId":100534,"corporation":false,"usgs":true,"family":"Beissinger","given":"Steven","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":794365,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Moritz, Craig","contributorId":149462,"corporation":false,"usgs":false,"family":"Moritz","given":"Craig","email":"","affiliations":[{"id":17742,"text":"Research School of Biology, The Australian Nat'l U, Acton, Australia","active":true,"usgs":false}],"preferred":false,"id":794366,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70194732,"text":"fs20173088 - 2017 - Assessment of undiscovered oil and gas resources in the Cretaceous Nanushuk and Torok Formations, Alaska North Slope, and summary of resource potential of the National Petroleum Reserve in Alaska, 2017","interactions":[],"lastModifiedDate":"2018-01-02T10:19:57","indexId":"fs20173088","displayToPublicDate":"2017-12-22T10:20:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-3088","title":"Assessment of undiscovered oil and gas resources in the Cretaceous Nanushuk and Torok Formations, Alaska North Slope, and summary of resource potential of the National Petroleum Reserve in Alaska, 2017","docAbstract":"The U.S. Geological Survey estimated mean undiscovered, technically recoverable resources of 8.7 billion barrels of oil and 25 trillion cubic feet of natural gas (associated and nonassociated) in conventional accumulations in the Cretaceous Nanushuk and Torok Formations in the National Petroleum Reserve in Alaska, adjacent State and Native lands, and State waters. The estimated undiscovered oil resources in the Nanushuk and Torok Formations are significantly higher than previous estimates, owing primarily to recent, larger than anticipated oil discoveries.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173088","usgsCitation":"Houseknecht, D.W., Lease, R.O., Schenk, C.J., Mercier, T.J., Rouse, W.A., Jarboe, P.J., Whidden, K.J., Garrity, C.P., Lewis, K.A., Heller, S.J., Craddock, W.H., Klett, T.R., Le, P.A., Smith, R.A., Tennyson, M.E., Gaswirth, S.B., Woodall, C.A., Brownfield, M.E., Leathers-Miller, H.M., and Finn, T.M., 2017, Assessment of undiscovered oil and gas resources in the Cretaceous Nanushuk and Torok Formations, Alaska North Slope, and summary of resource potential of the National Petroleum Reserve in Alaska, 2017: U.S. Geological Survey Fact Sheet 2017–3088, 4 p., https://doi.org/10.3133/fs20173088.","productDescription":"4 p.","onlineOnly":"N","ipdsId":"IP-092895","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":438122,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QSJKNF","text":"USGS data release","linkHelpText":"USGS Alaska Petroleum Systems Project: Northern Alaska Province, Nanushuk and Torok Formations Assessment Units and Assessment Input Forms"},{"id":350008,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20103102","text":"Fact Sheet 2010–3102: ","linkHelpText":"2010 Updated Assessment of Undiscovered Oil and Gas Resources of the National Petroleum Reserve in Alaska (NPRA)"},{"id":350003,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3088/coverthb.jpg"},{"id":350004,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3088/fs20173088.pdf","text":"Report","size":"4.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3088"},{"id":350009,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20053043","text":"Fact Sheet 2005–3043: ","linkHelpText":"Oil and Gas Assessment of Central North Slope, Alaska, 2005"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -170,\n 67\n ],\n [\n -145,\n 67\n ],\n [\n -145,\n 71.5\n ],\n [\n -170,\n 71.5\n ],\n [\n -170,\n 67\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Program Coordinator, Energy Resources Program
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The U.S. Geological Survey (USGS), in support of the Massachusetts Estuaries Project (MEP), delineated groundwater-contributing areas to various hydrologic receptors including ponds, streams, and coastal water bodies throughout southeastern Massachusetts, including portions of the Plymouth-Carver aquifer system and all of Cape Cod. These contributing areas were delineated over a 6-year period from 2003 through 2008 by using previously published regional USGS groundwater-flow models for the Plymouth-Carver region (Masterson and others, 2009), the Sagamore (western) and Monomoy (eastern) flow lenses of Cape Cod (Walter and Whealan, 2005), and lower Cape Cod (Masterson, 2004). The original USGS groundwater-contributing areas were subsequently revised in some locations by the MEP to remove modeling artifacts or to make the contributing areas more consistent with site-specific hydrologic conditions without further USGS review. This report describes the process used to create the USGS groundwater-contributing areas and provides these model results in their original format in a single, publicly accessible publication.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1074","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Carlson, C.S., Masterson, J.P., Walter, D.A., and Barbaro, J.R., 2017, Development of simulated groundwater-contributing areas to selected streams, ponds, coastal water bodies, and production wells in the Plymouth-Carver region and Cape Cod, Massachusetts: U.S. Geological Survey Data Series 1074, 17 p., https://doi.org/10.3133/ds1074.","productDescription":"Report: iv, 17 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087594","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":350104,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7V69H2Z","text":"USGS data release","description":"USGS data release","linkHelpText":"Simulated Groundwater-Contributing Areas to Selected Streams, Ponds, Coastal Water Bodies, and Production Wells, Plymouth-Carver Region and Cape Cod, Massachusetts"},{"id":350102,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1074/coverthb.jpg"},{"id":350103,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1074/ds1074.pdf","text":"Report","size":"5.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1074"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod, Plymouth-Carver Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.015625,\n 41.50857729743935\n ],\n [\n -69.88128662109375,\n 41.50857729743935\n ],\n [\n -69.88128662109375,\n 42.167475010395336\n ],\n [\n -71.015625,\n 42.167475010395336\n ],\n [\n -71.015625,\n 41.50857729743935\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Wastewater discharged to wells and ponds and wastes buried in shallow pits and trenches at facilities at the Idaho National Laboratory (INL) have contributed contaminants to the eastern Snake River Plain (ESRP) aquifer in the southwestern part of the INL. This report describes the correlation between subsurface stratigraphy in the southwestern part of the INL with information on the presence or absence of wastewater constituents to better understand how flow pathways in the aquifer control the movement of wastewater discharged at INL facilities. Paleomagnetic inclination was used to identify subsurface basalt flows based on similar inclination measurements, polarity, and stratigraphic position. Tritium concentrations, along with other chemical information for wells where tritium concentrations were lacking, were used as an indicator of which wells were influenced by wastewater disposal.
The basalt lava flows in the upper 150 feet of the ESRP aquifer where wastewater was discharged at the Idaho Nuclear Technology and Engineering Center (INTEC) consisted of the Central Facilities Area (CFA) Buried Vent flow and the AEC Butte flow. At the Advanced Test Reactor (ATR) Complex, where wastewater would presumably pond on the surface of the water table, the CFA Buried Vent flow probably occurs as the primary stratigraphic unit present; however, AEC Butte flow also could be present at some of the locations. At the Radioactive Waste Management Complex (RWMC), where contamination from buried wastes would presumably move down through the unsaturated zone and pond on the surface of the water table, the CFA Buried Vent; Late Basal Brunhes; or Early Basal Brunhes basalt flows are the flow unit at or near the water table in different cores.
In the wells closer to where wastewater disposal occurred at INTEC and the ATR-Complex, almost all the wells show wastewater influence in the upper part of the ESRP aquifer and wastewater is present in both the CFA Buried Vent flow and AEC Butte flow. The CFA Buried Vent flow and AEC Butte flow are also present in wells at and north of CFA and are all influenced by wastewater contamination. All wells with the AEC Butte flow present have wastewater influence and 83 percent of the wells with the more prevalent CFA Buried Vent flow have wastewater influence. South and southeast of CFA, most wells are not influenced by wastewater disposal and are completed in the Big Lost Flow and the CFA Buried Vent flow. Wells southwest of CFA are influenced by wastewater disposal and are completed in the Big Lost flow and CFA Buried Vent flow at the top of the aquifer. Basalt stratigraphy indicates that the CFA Buried Vent flow is the predominant flow in the upper part of the ESRP aquifer at and near the RWMC as it is present in all the wells in this area. The Late Basal Brunhes flow, Middle Basal Brunhes flow, Early Basal Brunhes flow, South Late Matuyama flow, and Matuyama flow are also present in various wells influenced by waste disposal.
Some wells south of RWMC do not show wastewater influence, and the lack of wastewater influence could be due to low hydraulic conductivities. Several wells south and southeast of CFA also do not show wastewater influence. Low hydraulic conductivities or ESRP subsidence are possible causes for lack of wastewater south of CFA.
Multilevel monitoring wells completed much deeper in the aquifer show influence of wastewater in numerous basalt flows. Well Middle 2051 (northwest of RWMC) does not show wastewater influence in its upper three basalt flows (CFA Buried Vent, Late Basal Brunhes, and Middle Basal Brunhes); however, wastewater is present in two deeper flows (the Matuyama and Jaramillo flows). Well USGS 131A (southwest of CFA) and USGS132 (south of RWMC) both show wastewater influence in all the basalt flows sampled in the upper 600 feet of the aquifer. Wells USGS 137A, 105, 108, and 103 completed along the southern boundary of the INL all show wastewater influence in several basalt flows including the G flow, Middle and Early Basal Brunhes flows, the South Late Matuyama flow and the Matuyama flow; however, the strongest wastewater influence appears to be in the South Late Matuyama flow. The concentrations of wastewater constituents in deeper parts of these wells support the concept of groundwater flow deepening in the southwestern part of the INL.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175148","collaboration":"DOE/ID-22245Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
This map is a compilation of aeromagnetic surveys over Yukon and eastern Alaska. Aeromagnetic surveys measure the total intensity of the earth's magnetic field. The field was measured by a magnetometer aboard an aircraft flown in parallel lines spaced at 200 m to 10000 m across the map area. The magnetic field reflects magnetic properties of bedrock and provides qualitative and quantitative information used in geological mapping. Understanding the geology will help geologists map the area, assist mineral/hydrocarbon exploration activities, and provide useful information necessary for communities, aboriginal associations, and government to make land use decisions. This survey was flown to improve our knowledge of the area. It will support ongoing geological mapping and resource assessment.
","language":"English, French","publisher":"Geological Survey of Canada","doi":"10.4095/301695","usgsCitation":"Miles, W., Saltus, R.W., Hayward, N., and Oneschuk, D., 2017, Alaska and Yukon magnetic compilation, residual total magnetic field: Open File 7862, 52.79 x 35.26 inches, https://doi.org/10.4095/301695.","productDescription":"52.79 x 35.26 inches","ipdsId":"IP-062639","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":469231,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4095/301695","text":"Publisher Index Page"},{"id":350146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"projection":"Lambert Conformal Conic Projection, zone 7N (NAD83)","country":"Canada, United States","state":"Alaska, Yukon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150,\n 68\n ],\n [\n -124,\n 68\n ],\n [\n -124,\n 60\n ],\n [\n -150,\n 60\n ],\n [\n -150,\n 68\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fae3e4b06e28e9c228f4","contributors":{"authors":[{"text":"Miles, W.","contributorId":201441,"corporation":false,"usgs":false,"family":"Miles","given":"W.","email":"","affiliations":[],"preferred":false,"id":725283,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saltus, Richard W. saltus@usgs.gov","contributorId":777,"corporation":false,"usgs":true,"family":"Saltus","given":"Richard","email":"saltus@usgs.gov","middleInitial":"W.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":719259,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayward, Nathan","contributorId":201439,"corporation":false,"usgs":false,"family":"Hayward","given":"Nathan","affiliations":[],"preferred":false,"id":725284,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oneschuk, D.","contributorId":201440,"corporation":false,"usgs":false,"family":"Oneschuk","given":"D.","email":"","affiliations":[],"preferred":false,"id":725285,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70093603,"text":"pp1802E - 2017 - Beryllium","interactions":[{"subject":{"id":70093603,"text":"pp1802E - 2017 - Beryllium","indexId":"pp1802E","publicationYear":"2017","noYear":false,"chapter":"E","title":"Beryllium"},"predicate":"IS_PART_OF","object":{"id":70158974,"text":"pp1802 - 2017 - Critical mineral resources of the United States—Economic and environmental geology and prospects for future supply","indexId":"pp1802","publicationYear":"2017","noYear":false,"title":"Critical mineral resources of the United States—Economic and environmental geology and prospects for future supply"},"id":1}],"isPartOf":{"id":70158974,"text":"pp1802 - 2017 - Critical mineral resources of the United States—Economic and environmental geology and prospects for future supply","indexId":"pp1802","publicationYear":"2017","noYear":false,"title":"Critical mineral resources of the United States—Economic and environmental geology and prospects for future supply"},"lastModifiedDate":"2017-12-19T13:43:12","indexId":"pp1802E","displayToPublicDate":"2017-12-19T09:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1802","chapter":"E","title":"Beryllium","docAbstract":"Beryllium is a mineral commodity that is used in a variety of industries to make products that are essential for the smooth functioning of a modern society. Two minerals, bertrandite (which is supplied domestically) and beryl (which is currently supplied solely by imports), are necessary to ensure a stable supply of high-purity beryllium metal, alloys, and metal-matrix composites and beryllium oxide ceramics. Although bertrandite is the source mineral for more than 90 percent of the beryllium produced globally, industrial beryl is critical for the production of the very high purity beryllium metal needed for some strategic applications. The current sole domestic source of beryllium is bertrandite ore from the Spor Mountain deposit in Utah; beryl is imported mainly from Brazil, China, Madagascar, Mozambique, and Portugal. High-purity beryllium metal is classified as a strategic and critical material by the Strategic Materials Protection Board of the U.S. Department of Defense because it is used in products that are vital to national security. Beryllium is maintained in the U.S. stockpile of strategic materials in the form of hot-pressed beryllium metal powder.
Because of its unique chemical properties, beryllium is indispensable for many important industrial products used in the aerospace, computer, defense, medical, nuclear, and telecommunications industries. For example, high-performance alloys of beryllium are used in many specialized, high-technology electronics applications, as they are energy efficient and can be used to fabricate miniaturized components. Beryllium-copper alloys are used as contacts and connectors, switches, relays, and shielding for everything from cell phones to thermostats, and beryllium-nickel alloys excel in producing wear-resistant and shape-retaining high-temperature springs. Beryllium metal composites, which combine the fabrication ability of aluminum with the thermal conductivity and highly elastic modulus of beryllium, are ideal for producing aircraft and satellite structural components that have a high stiffness-to-weight ratio and low surface vibration. Beryllium oxide ceramics are used in a wide range of applications, including missile guidance systems, radar applications, and cell phone transmitters, and they are critical to medical technologies, such as magnetic resonance imaging (MRI) machines, medical lasers, and portable defibrillators.
The United States is expected to remain self-sufficient with respect to most of its beryllium requirements, based on information available at the time this chapter was prepared (2013). The United States is one of only three countries that currently process beryllium ores and concentrate them into beryllium products, and these three countries supply most of the rest of the world with these products. Exploration for new deposits in the United States is limited because domestic beryllium production is dominated by a single producer that effectively controls the domestic beryllium market, which is relatively small and specialized, and the market cannot readily accommodate new competition on the raw material supply side.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Critical mineral resources of the United States—Economic and environmental geology and prospects for future supply","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1802E","isbn":"978-1-4113-3991-0","usgsCitation":"Foley, N.K., Jaskula, B.W., Piatak, N.M., and Schulte, R.F., 2017, Beryllium, chap. E of Schulz, K.J., DeYoung, J.H., Jr., Seal, R.R., II, and Bradley, D.C., eds., Critical mineral resources of the United States—Economic and environmental geology and prospects for future supply: U.S. Geological Survey Professional Paper 1802, p. E1–E32, https://doi.org/10.3133/pp1802E.","productDescription":"viii, 32 p.","numberOfPages":"44","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045146","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":334565,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1802/e/pp1802e.pdf","text":"Report","size":"15.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Professional Paper 1802 E"},{"id":334564,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1802/e/coverthb1.jpg"}],"contact":"Mineral Resources Program Coordinator
U.S. Geological Survey
913 National Center
Reston, VA 20192
Email: minerals@usgs.gov
https://minerals.usgs.gov
Mineral commodities are vital for economic growth, improving the quality of life, providing for national defense, and the overall functioning of modern society. Minerals are being used in larger quantities than ever before and in an increasingly diverse range of applications. With the increasing demand for a considerably more diverse suite of mineral commodities has come renewed recognition that competition and conflict over mineral resources can pose significant risks to the manufacturing industries that depend on them. In addition, production of many mineral commodities has become concentrated in relatively few countries (for example, tungsten, rare-earth elements, and antimony in China; niobium in Brazil; and platinum-group elements in South Africa and Russia), thus increasing the risk for supply disruption owing to political, social, or other factors. At the same time, an increasing awareness of and sensitivity to potential environmental and health issues caused by the mining and processing of many mineral commodities may place additional restrictions on mineral supplies. These factors have led a number of Governments, including the Government of the United States, to attempt to identify those mineral commodities that are viewed as most “critical” to the national economy and (or) security if supplies should be curtailed.
This book presents resource and geologic information on the following 23 mineral commodities currently among those viewed as important to the national economy and national security of the United States: antimony (Sb), barite (barium, Ba), beryllium (Be), cobalt (Co), fluorite or fluorspar (fluorine, F), gallium (Ga), germanium (Ge), graphite (carbon, C), hafnium (Hf), indium (In), lithium (Li), manganese (Mn), niobium (Nb), platinum-group elements (PGE), rare-earth elements (REE), rhenium (Re), selenium (Se), tantalum (Ta), tellurium (Te), tin (Sn), titanium (Ti), vanadium (V), and zirconium (Zr). For a number of these commodities—for example, graphite, manganese, niobium, and tantalum—the United States is currently wholly dependent on imports to meet its needs. The first two chapters (A and B) deal with general information pertinent to the study of mineral resources. Chapters C through V describe individual mineral commodities and include an overview of current uses of the commodity, identified resources and their distribution nationally and globally, the state of current geologic knowledge, the potential for finding additional deposits nationally and globally, and geoenvironmental issues that may be related to the production and uses of the commodity. These chapters are updates of the commodity chapters published in 1973 in U.S. Geological Survey Professional Paper 820, “United States Mineral Resources.”
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U.S. Geological Survey
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Reston, VA 20192
Email: minerals@usgs.gov
http://minerals.usgs.gov