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
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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 U.S. Geological Survey currently (2020) publishes information on concentrations and loads of water-quality constituents at 110 sites across the United States as part of the U.S. Geological Survey National Water Quality Network (NWQN). This report details historical and updated methods for computing water-quality loads at NWQN sites. The primary updates to historical load estimation methods include (1) an adaptation to methods for computing loads to the Gulf of Mexico; (2) the inclusion of loads and trends computed using the Weighted Regressions on Time, Discharge, and Season (WRTDS) and Weighted Regressions on Time, Discharge, and Season with Kalman filtering (WRTDS–K) methods; and (3) the inclusion of loads computed using continuous water-quality data. Loads computed using WRTDS and WRTDS–K and continuous water-quality data are provided along with those computed using historical methods. Various aspects of method updates are evaluated in this report to help users of water-quality loading data determine which estimation methods best suit their particular application.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171120","usgsCitation":"Lee, C.J., Murphy, J.C., Crawford, C.G., and Deacon, J.R, 2017, Methods for computing water-quality loads at sites in the U.S. Geological Survey National Water Quality Network (ver. 1.3, August 2021): U.S. Geological Survey Open-File Report 2017–1120, 20 p., https://doi.org/10.3133/ofr20171120.","productDescription":"Report: vii, 20 p.; Version History","onlineOnly":"Y","ipdsId":"IP-086966","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":438099,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93DHTRJ","text":"USGS data release","linkHelpText":"Nutrient and pesticide data collected from the USGS National Water Quality Network and previous networks, 1950-2022"},{"id":438098,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P948Z0VZ","text":"USGS data release","linkHelpText":"Nutrient and pesticide data collected from the USGS National Water Quality Network and previous networks, 1950-2021"},{"id":388566,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2017/1120/versionHist.txt","text":"Version History","size":"9.89 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2017–1120 Version History"},{"id":388565,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1120/ofr20171120.pdf","text":"Report","size":"14.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1120"},{"id":347239,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1120/coverthb4.jpg"}],"edition":"Version 1.3: August 2021; Version 1.2: November 2020; Version 1.1: January 2020; Version 1.0: October 2017","contact":"Director, Kansas Water Science Center
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Identifying and quantifying the major ecosystem processes that regulate recruitment strength of commercially and ecologically important fish species is a central goal of fisheries management research. In the Gulf of Alaska (GOA) five groundfish species are of particular interest: sablefish (Anoplopoma fimbria), Pacific cod (Gadus macrocephalus), walleye pollock (Gadus chalcogrammus), arrowtooth flounder (Atheresthes stomias), and Pacific ocean perch (Sebastes alutus). Habitat suitability models (HSM) were developed for the demersal early juvenile stage to inform survival to recruitment for these species, using catch data and seafloor habitat metrics with presence-only models. Regional-scale maps were produced that predict the probability of suitable habitat available in the GOA from settlement through residency in nursery areas. For example, the HSM for sablefish (150–399 mm) described suitable habitat as bathymetrically low-lying areas with low rocky structure within 25–300 m depth. In contrast, the HSM for Pacific ocean perch (50–200 mm) described suitable habitat as bathymetry rises with rocky structure present on north-south facing slopes within 85–270 m depth. These habitat covariates are useful to refine population estimates for North Pacific groundfish species and to inform life stage-specific definitions of Essential Fish Habitat. This application of MaxEnt models should be applicable for species with low occurrence of spatial data in other marine ecosystems globally.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr2.2017.12.005","usgsCitation":"Pirtle, J.L., Shotwell, S.K., Zimmermann, M., Reid, J.A., and Golden, N.E., 2017, Habitat suitability models for groundfish in the Gulf of Alaska: Deep Sea Research Part II: Topical Studies in Oceanography, v. 165, p. 303-321, https://doi.org/10.1016/j.dsr2.2017.12.005.","productDescription":"19 p.","startPage":"303","endPage":"321","ipdsId":"IP-076374","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":461313,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.dsr2.2017.12.005","text":"Publisher Index Page"},{"id":360155,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -165.498046875,\n 54.059387886623576\n ],\n [\n -130.2099609375,\n 54.059387886623576\n ],\n [\n -130.2099609375,\n 61.4597705702975\n ],\n [\n -165.498046875,\n 61.4597705702975\n ],\n [\n -165.498046875,\n 54.059387886623576\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"165","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10aa60e4b034bf6a7e57b9","contributors":{"authors":[{"text":"Pirtle, Jodi L.","contributorId":211305,"corporation":false,"usgs":false,"family":"Pirtle","given":"Jodi","email":"","middleInitial":"L.","affiliations":[{"id":38223,"text":"National Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":753605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shotwell, S. 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In this paper, we focus on recent trends in applying imaging spectrometer data to: 1) airborne imaging of high latitude deposits, 2) field-based imaging of outcrops, and 3) laboratory-level imaging of geologic samples. Comparing mineral information derived from imaging spectrometer data acquired at these three scales in Alaska in areas of exposed porphyry Cu-Au-Mo deposits, Orange Hill and Bond Creek, we find notable consistency in identifications of spectrally predominant minerals, including white mica, chlorite, clays, and gypsum. Variations in the wavelength position of white mica 2200 nm Al-OH absorption seen at the airborne level are echoed by finerscale field and laboratory imaging, with wavelength positions spanning the 2199 to 2207 nm range. The longerwavelength micas associated with porphyry formation are more phengitic in composition, and thus distinct from mica in plutonic and volcanic arc rocks not affected by magmatic-hydrothermal fluids. The hillside imagery, collected on a cloudy day that would have precluded aircraft survey, gave comparable result to airborne and laboratory data, indicating field-based imaging spectroscopy can be a feasible alternative to airborne survey for accessible targets. Direct spectral observation of molybdenite in rocks collected from the Orange Hill deposit demonstratesthat additional important mineral information can be revealed with laboratory level imaging spectroscopy that is difficult to obtain in coarser scale data, commonly due to low areal extent of target minerals. The spatial association of the clinochlore + white mica and long wavelength white mica spectral classes to multi-element Cu-Mo-Au anomalies from geochemical analyses of rocks and sediments support a causative relationship with magmatic-hydrothermal alteration. Mineral maps from the airborne data were used to guide field sampling that found additional CuMo-Au mineralized areas, which were previously unknown or unreported. The results from this study provide support for utilization of imaging spectroscopy for assisting mineral exploration in other portions of the state of Alaska as well as other areas at high latitudes. Imaging spectroscopy has the potential to provide targeting information for follow-up sampling and investigations, potentially reducing subsequent exploration costs.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of Exploration 17: Sixth Decennial International Conference on Mineral Exploration","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Decennial Mineral Exploration Conferences","usgsCitation":"Kokaly, R.F., Graham, G.E., Hoefen, T.M., Kelley, K.D., Johnson, M., Hubbard, B.E., Buchhorn, M., and Prakash, A., 2017, Multiscale hyperspectral imaging of the Orange Hill Porphyry Copper Deposit, Alaska, USA, with laboratory-, field-, and aircraft-based imaging spectrometers, in Proceedings of Exploration 17: Sixth Decennial International Conference on Mineral Exploration, p. 923-943.","productDescription":"21 p.","startPage":"923","endPage":"943","ipdsId":"IP-091448","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science 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kdkelley@usgs.gov","orcid":"https://orcid.org/0000-0002-3232-5809","contributorId":179012,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen","email":"kdkelley@usgs.gov","middleInitial":"D.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":752003,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Michaela R. 0000-0001-6133-0247 mrjohns@usgs.gov","orcid":"https://orcid.org/0000-0001-6133-0247","contributorId":1013,"corporation":false,"usgs":true,"family":"Johnson","given":"Michaela R.","email":"mrjohns@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":752004,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hubbard, Bernard E. 0000-0002-9315-2032 bhubbard@usgs.gov","orcid":"https://orcid.org/0000-0002-9315-2032","contributorId":2342,"corporation":false,"usgs":true,"family":"Hubbard","given":"Bernard","email":"bhubbard@usgs.gov","middleInitial":"E.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":752005,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Buchhorn, M.","contributorId":210801,"corporation":false,"usgs":false,"family":"Buchhorn","given":"M.","email":"","affiliations":[],"preferred":false,"id":752006,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prakash, A.","contributorId":81330,"corporation":false,"usgs":true,"family":"Prakash","given":"A.","email":"","affiliations":[],"preferred":false,"id":752007,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70198094,"text":"70198094 - 2017 - Emulation of long-term changes in global climate: application to the late Pliocene and future","interactions":[],"lastModifiedDate":"2018-07-16T11:35:53","indexId":"70198094","displayToPublicDate":"2018-07-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"Emulation of long-term changes in global climate: application to the late Pliocene and future","docAbstract":"Multi-millennial transient simulations of climate changes have a range of important applications, such as for investigating key geologic events and transitions for which high-resolution palaeoenvironmental proxy data are available, or for projecting the long-term impacts of future climate evolution on the performance of geological repositories for the disposal of radioactive wastes. However, due to the high computational requirements of current fully coupled general circulation models (GCMs), long-term simulations can generally only be performed with less complex models and/or at lower spatial resolution. In this study, we present novel longterm “continuous” projections of climate evolution based on the output from GCMs, via the use of a statistical emulator. The emulator is calibrated using ensembles of GCM simulations, which have varying orbital configurations and atmospheric CO2 concentrations and enables a variety of investigations of long-term climate change to be conducted, which would not be possible with other modelling techniques on the same temporal and spatial scales. To illustrate the potential applications, we apply the emulator to the late Pliocene (by modelling surface air temperature – SAT), comparing its results with palaeo-proxy data for a number of global sites, and to the next 200 kyr (thousand years) (by modelling SAT and precipitation). A range of CO2 scenarios are prescribed for each period. During the late Pliocene, we find that emulated SAT varies on an approximately precessional timescale, with evidence of increased obliquity response at times. A comparison of atmospheric CO2 concentration for this period, estimated using the proxy sea surface temperature (SST) data from different sites and emulator results, finds that relatively similar CO2 concentrations are estimated based on sites at lower latitudes, whereas higher-latitude sites show larger discrepancies. In our second illustrative application, spanning the next 200 kyr into the future, we find that SAT oscillations appear to be primarily influenced by obliquity for the first ∼ 120 kyr, whilst eccentricity is relatively low, after which precession plays a more dominant role. Conversely, variations in precipitation over the entire period demonstrate a strong precessional signal. Overall, we find that the emulator provides a useful and powerful tool for rapidly simulating the long-term evolution of climate, both past and future, due to its relatively high spatial resolution and relatively low computational cost. However, there are uncertainties associated with the approach used, including the inability of the emulator to capture deviations from a quasi-stationary response to the forcing, such as transient adjustments of the deep-ocean temperature and circulation, in addition to its limited range of fixed ice sheet configurations and its requirement for prescribed atmospheric CO2 concentrations.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/cp-2017-57","usgsCitation":"Lord, N.S., Crucifix, M., Lunt, D.J., Thorne, M.C., Bounceur, N., Dowsett, H.J., O’Brien, C.L., and Ridgwell, A., 2017, Emulation of long-term changes in global climate: application to the late Pliocene and future: Climate of the Past, v. 13, p. 1539-1571, https://doi.org/10.5194/cp-2017-57.","productDescription":"33 p.","startPage":"1539","endPage":"1571","ipdsId":"IP-083123","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":469214,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-2017-57","text":"Publisher Index Page"},{"id":355675,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc50ae4b0f5d57878eaea","contributors":{"authors":[{"text":"Lord, Natalie S.","contributorId":206300,"corporation":false,"usgs":false,"family":"Lord","given":"Natalie","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":740007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crucifix, Michel","contributorId":206301,"corporation":false,"usgs":false,"family":"Crucifix","given":"Michel","email":"","affiliations":[],"preferred":false,"id":740008,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lunt, Daniel J.","contributorId":101168,"corporation":false,"usgs":true,"family":"Lunt","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":740009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorne, Mike C.","contributorId":206302,"corporation":false,"usgs":false,"family":"Thorne","given":"Mike","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":740010,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bounceur, Nabila","contributorId":206303,"corporation":false,"usgs":false,"family":"Bounceur","given":"Nabila","email":"","affiliations":[],"preferred":false,"id":740011,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dowsett, Harry J. 0000-0003-1983-7524 hdowsett@usgs.gov","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":949,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry","email":"hdowsett@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":740012,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O’Brien, Charlotte L.","contributorId":206304,"corporation":false,"usgs":false,"family":"O’Brien","given":"Charlotte","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":740013,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ridgwell, A.","contributorId":192917,"corporation":false,"usgs":false,"family":"Ridgwell","given":"A.","email":"","affiliations":[],"preferred":false,"id":740014,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70187004,"text":"sir20175013 - 2017 - The HayWired Earthquake Scenario","interactions":[{"subject":{"id":70187003,"text":"sir20175013v1 - 2017 - The HayWired earthquake scenario—Earthquake hazards","indexId":"sir20175013v1","publicationYear":"2017","noYear":false,"chapter":"A–H","displayTitle":"The HayWired Earthquake Scenario—Earthquake Hazards","title":"The HayWired earthquake scenario—Earthquake hazards"},"predicate":"IS_PART_OF","object":{"id":70187004,"text":"sir20175013 - 2017 - The HayWired Earthquake Scenario","indexId":"sir20175013","publicationYear":"2017","noYear":false,"title":"The HayWired Earthquake Scenario"},"id":1},{"subject":{"id":70195667,"text":"sir20175013v2 - 2021 - The HayWired earthquake scenario—Engineering implications","indexId":"sir20175013v2","publicationYear":"2021","noYear":false,"chapter":"I–Q","displayTitle":"The HayWired Earthquake Scenario—Engineering Implications","title":"The HayWired earthquake scenario—Engineering implications"},"predicate":"IS_PART_OF","object":{"id":70187004,"text":"sir20175013 - 2017 - The HayWired Earthquake Scenario","indexId":"sir20175013","publicationYear":"2017","noYear":false,"title":"The HayWired Earthquake Scenario"},"id":2},{"subject":{"id":70206048,"text":"sir20175013V3 - 2019 - The HayWired earthquake scenario—Societal consequences","indexId":"sir20175013V3","publicationYear":"2019","noYear":false,"chapter":"R–W","displayTitle":"The HayWired Earthquake Scenario—Societal Consequences","title":"The HayWired earthquake scenario—Societal consequences"},"predicate":"IS_PART_OF","object":{"id":70187004,"text":"sir20175013 - 2017 - The HayWired Earthquake Scenario","indexId":"sir20175013","publicationYear":"2017","noYear":false,"title":"The HayWired Earthquake Scenario"},"id":3}],"lastModifiedDate":"2022-04-22T20:42:59.787763","indexId":"sir20175013","displayToPublicDate":"2018-04-17T12:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5013","title":"The HayWired Earthquake Scenario","docAbstract":"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.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
https://earthquake.usgs.gov/
Although the use of bird-borne data loggers has become widespread in avian field research, the effects of capture and transmitter attachment on behavior and demographic rates are not often measured. Tag- and capture-induced effects on individual behavior, survival and reproduction may limit extrapolation of transmitter data to wider populations. However, measuring individual responses to capture and tagging is a necessary step in developing research techniques that minimize negative effects. We measured the short-term behavioral effects of handling and GPS transmitter attachment on Brown Pelicans under both captive and field conditions, and followed tagged individuals through a full breeding season to assess whether capture and transmitter attachment increased rates of nest abandonment or breeding failure. We observed slight increases in preening among tagged individuals 0–2 h after capture relative to controls that had not been captured or tagged, with a corresponding reduction in time spent resting. One to three days post-capture, nesting behavior of tagged pelicans resembled that of neighbors that had not been captured or tagged. Eighty-eight percent of tagged breeders remained at the same nest location for more than 48 h after capture, attending nests and chicks for an average of 49 days, and 51% were assumed to successfully fledge young. Breeding success was driven primarily by variation in location; however, sex and handling time also influenced the probability of successful breeding in tagged pelicans, suggesting that individual characteristics and the capture process itself can confound the effects of capture and transmitter attachment. We conclude that pelicans fitted with GPS transmitters exhibit comparable behaviors to untagged individuals within a day of capture and that GPS tracking is a viable technique for studying behavior and demography in this species. We also identify measures to minimize post-capture nest abandonment rates in tracking studies, including minimizing handling time and covering nests during processing.
","language":"English","publisher":"Springer","doi":"10.1007/s10336-016-1418-3","usgsCitation":"Lamb, J.S., Satge, Y.G., Fiorello, C.V., and Jodice, P.G., 2017, Behavioral and reproductive effects of bird-borne data logger attachment on Brown Pelicans (Pelecanus occidentalis) on three temporal scales: Journal of Ornithology, v. 158, no. 2, p. 617-627, https://doi.org/10.1007/s10336-016-1418-3.","productDescription":"11 p.","startPage":"617","endPage":"627","ipdsId":"IP-073599","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469218,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10336-016-1418-3","text":"Publisher Index Page"},{"id":354546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.7783203125,\n 25\n ],\n [\n -82,\n 25\n ],\n [\n -82,\n 30.86451022625836\n ],\n [\n -97.7783203125,\n 30.86451022625836\n ],\n [\n -97.7783203125,\n 25\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"158","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-01","publicationStatus":"PW","scienceBaseUri":"5b155df4e4b092d9651e1b96","contributors":{"authors":[{"text":"Lamb, Juliet S. 0000-0003-0358-3240","orcid":"https://orcid.org/0000-0003-0358-3240","contributorId":198059,"corporation":false,"usgs":false,"family":"Lamb","given":"Juliet","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":736677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Satge, Yvan G.","contributorId":200132,"corporation":false,"usgs":false,"family":"Satge","given":"Yvan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":736678,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fiorello, Christine V.","contributorId":172678,"corporation":false,"usgs":false,"family":"Fiorello","given":"Christine","email":"","middleInitial":"V.","affiliations":[{"id":27076,"text":"Oiled Wildlife Care Network, UC Davis","active":true,"usgs":false}],"preferred":false,"id":736679,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X pjodice@usgs.gov","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":200009,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","email":"pjodice@usgs.gov","middleInitial":"G.R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":736617,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70185961,"text":"sim3378 - 2017 - Hydrogeologic characteristics and geospatial analysis of water-table changes in the alluvium of the lower Arkansas River Valley, southeastern Colorado, 2002, 2008, and 2015","interactions":[],"lastModifiedDate":"2018-03-08T14:30:44","indexId":"sim3378","displayToPublicDate":"2018-03-08T15:25:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3378","title":"Hydrogeologic characteristics and geospatial analysis of water-table changes in the alluvium of the lower Arkansas River Valley, southeastern Colorado, 2002, 2008, and 2015","docAbstract":"The U.S. Geological Survey in cooperation with the Lower Arkansas Valley Water Conservancy District measures groundwater levels periodically in about 100 wells completed in the alluvial material of the Arkansas River Valley in Pueblo, Crowley, Otero, Bent, and Prowers Counties in southeastern Colorado, of which 95 are used for the analysis in this report. The purpose of this report is to provide information to water-resource administrators, managers, planners, and users about groundwater characteristics in the alluvium of the lower Arkansas Valley extending roughly 150 miles between Pueblo Reservoir and the Colorado-Kansas State line. This report includes three map sheets showing (1) bedrock altitude at the base of the alluvium of the lower Arkansas Valley; (2) estimated spring-to-spring and fall-to-fall changes in water-table altitude between 2002, 2008, and 2015; and (3) estimated saturated thickness in the alluvium during spring and fall of 2002, 2008, and 2015, and thickness of the alluvium in the lower Arkansas Valley. Water-level changes were analyzed by geospatial interpolation methods.
Available data included all water-level measurements made between January 1, 2001, and December 31, 2015; however, only data from fall and spring of 2002, 2008, and 2015 are mapped in this report. To account for the effect of John Martin Reservoir in Bent County, Colorado, lake levels at the reservoir were assigned to points along the approximate shoreline and were included in the water-level dataset. After combining the water-level measurements and lake levels, inverse distance weighting was used to interpolate between points and calculate the altitude of the water table for fall and spring of each year for comparisons. Saturated thickness was calculated by subtracting the bedrock surface from the water-table surface. Thickness of the alluvium was calculated by subtracting the bedrock surface from land surface using a digital elevation model.
In order to analyze the response of the alluvium to varying environmental and anthropogenic conditions, the percentage of area of the lower Arkansas Valley showing an absolute change of 3 feet or less was calculated for each of the six water-table altitude change maps. For fall water-table altitude change maps, the periods between 2002 and 2008, 2008 and 2015, and 2002 and 2015 showed that 86.5 percent, 85.2 percent, and 66.3 percent of the study area, respectively, showed a net change of 3 feet or less. In the spring water-table altitude change maps these periods showed a net change of 3 feet or less in 94.4 percent, 96.1 percent, and 90.2 percent of the study area, respectively. While the estimated change in water-table altitude was slightly greater and more variable in fall-to-fall comparisons, these high percentages of area with relatively small net changes indicated that, at least in comparisons of the years presented, there was not a large amount of fluctuation in the altitude of the water table.
The saturated thickness in the lower Arkansas Valley was between 25 and 50 feet in 34.4 to 35.9 percent of the study area, depending on the season and year. Between 30.2 and 35.6 percent of the area showed saturated thicknesses between 0 and 25 feet. Less than 1 percent of the area showed a saturated thickness greater than 200 feet in all mapped seasons and years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3378","collaboration":"Prepared in cooperation with the Lower Arkansas Valley Water Conservancy District","usgsCitation":"Holmberg, M.J., 2017, Hydrogeologic characteristics and geospatial analysis of water-table changes in the alluvium of the lower Arkansas River Valley, southeastern Colorado, 2002, 2008, and 2015: U.S. Geological Survey Scientific Investigations Map 3378, pamphlet 9 p., 3 sheets, scale 1:130,000 and 1:575, 000, https://doi.org/10.3133/sim3378.","productDescription":"Report: vi, 9 p.; 3 Sheets: 43.0 x 32.0 inches or smaller; 2 Appendixes; Data Release; Read Me","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081751","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":341216,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3378/sim3378_sheet3.pdf","text":"Sheet 3","size":"17.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3378 Sheet 3","linkHelpText":" Estimated Saturated Thickness of the Alluvium, Spring 2002, 2008, and 2015; Fall, 2002, 2008, and 2015, and Estimated Thickness of the Alluvium in the Lower Arkansas River Valley, Southeast Colorado"},{"id":341219,"rank":8,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3378/sim3378Readme.txt","text":"Read Me","size":"12.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3378 Read Me"},{"id":341217,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sim/3378/sim3387_appendix1.xlsx","text":"Appendix 1","size":"36.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIM 3378 Appendix 1","linkHelpText":"Well Information and Measured Water Levels in the lower Arkansas Valley, Southeast Colorado, 2001–2015"},{"id":341213,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3378/coverthb.jpg"},{"id":341303,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71G0JF6","text":"USGS data release","description":"USGS data release","linkHelpText":"Hydrogeologic Characteristics and Geospatial Analysis of Water-Table Changes in the Alluvium of the Lower Arkansas River Valley, Southeastern Colorado, 2002, 2008, and 2015"},{"id":341215,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3378/sim3378_sheet2.pdf","text":"Sheet 2","size":"17.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3378 Sheet 2","linkHelpText":"Estimated Change in Water-Table Altitude, Spring-to-Spring, 2002–2008, 2018–2015, and 2002–2015; Fall-to-Fall, 2002–2008, 2018–2015, and 2002–2015; and Locations of Monitoring Wells in the Alluvium of the Lower Arkansas River Valley, Southeast Colorado"},{"id":341218,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sim/3378/sim3387_appendix2.pdf","text":"Appendix 2","size":"572 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3378 Appendix 2","linkHelpText":" Hydrographs Showing Water-Table Altitude in Select Monitoring Wells in the lower Arkansas Valley and Water-Surface Altitude in John Martin Reservoir, Southeast Colorado, 2001–2015"},{"id":341223,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3378/sim3378_sheet1.pdf","text":"Sheet 1","size":"8.02 MB ","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3378 Sheet 1","linkHelpText":" Bedrock Altitude at the Base of the Alluvium of the Lower Arkansas River Valley, Southeast Colorado"},{"id":341221,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3378/sim3378.pdf","text":"Report","size":"1.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3378 Report"}],"country":"United States","state":"Colorado","otherGeospatial":"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 -104.66125488281249,\n 37.93986540897977\n ],\n [\n -102.041015625,\n 37.93986540897977\n ],\n [\n -102.041015625,\n 38.29424797320529\n ],\n [\n -104.66125488281249,\n 38.29424797320529\n ],\n [\n -104.66125488281249,\n 37.93986540897977\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225-0046
We directly compare trip willingness to pay (WTP) values between 1985 and 2015 stated preference surveys of private party Grand Canyon boaters using identically designed valuation methods. The temporal gap of 30 years between these two studies is well beyond that of any tests of WTP temporal stability in the literature. Comparisons were made of mean WTP estimates for four hypothetical Colorado River flow level scenarios. WTP values from the 1985 survey were adjusted to 2015 levels using the consumer price index. Mean WTP precision was estimated through simulation. No statistically significant differences were detected between the adjusted Bishop et al. (1987) and the current study mean WTP estimates. Examination of pooled models of the data from the studies suggest that while the estimated WTP values are stable over time, the underlying valuation functions may not be, particularly when the data and models are corrected to account for differing bid structures and possible panel effects.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017WR020729","usgsCitation":"Neher, C.J., Duffield, J., Bair, L.S., Patterson, D.A., and Neher, K., 2017, Testing the limits of temporal stability: Willingness to pay values among Grand Canyon whitewater boaters across decades: Water Resources Research, v. 53, no. 12, p. 10108-10120, https://doi.org/10.1002/2017WR020729.","productDescription":"13 p.","startPage":"10108","endPage":"10120","ipdsId":"IP-084682","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":461315,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017wr020729","text":"Publisher Index Page"},{"id":438113,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7M044C9","text":"USGS data release","linkHelpText":"Grand Canyon Whitewater Boater Data, Temporal Stability of Willingness to Pay Values"},{"id":351777,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon","volume":"53","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee788e4b0da30c1bfc2be","contributors":{"authors":[{"text":"Neher, Chris J.","contributorId":202569,"corporation":false,"usgs":false,"family":"Neher","given":"Chris","email":"","middleInitial":"J.","affiliations":[{"id":36482,"text":"Department of Mathematical Sciences, University of Montana","active":true,"usgs":false}],"preferred":false,"id":728925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duffield, John","contributorId":202570,"corporation":false,"usgs":false,"family":"Duffield","given":"John","email":"","affiliations":[{"id":36482,"text":"Department of Mathematical Sciences, University of Montana","active":true,"usgs":false}],"preferred":false,"id":728926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bair, Lucas S. 0000-0002-9911-3624 lbair@usgs.gov","orcid":"https://orcid.org/0000-0002-9911-3624","contributorId":5270,"corporation":false,"usgs":true,"family":"Bair","given":"Lucas","email":"lbair@usgs.gov","middleInitial":"S.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":728924,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Patterson, David A.","contributorId":175326,"corporation":false,"usgs":false,"family":"Patterson","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":36482,"text":"Department of Mathematical Sciences, University of Montana","active":true,"usgs":false}],"preferred":false,"id":728927,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neher, Katherine","contributorId":202571,"corporation":false,"usgs":false,"family":"Neher","given":"Katherine","email":"","affiliations":[{"id":36483,"text":"Bioeconomics, Inc. Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":728928,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195159,"text":"70195159 - 2017 - Control of landslide volume and hazard by glacial stratigraphic architecture, Northwest Washington state, USA","interactions":[],"lastModifiedDate":"2018-02-08T09:31:33","indexId":"70195159","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Control of landslide volume and hazard by glacial stratigraphic architecture, Northwest Washington state, USA","docAbstract":"Landslide volumes span many orders of magnitude, but large-volume slides tend to travel\nfarther and consequently can pose a greater hazard. In northwest Washington State, USA, a\nlandscape abounding with landslides big and small, the recent occurrence of the large-volume\nand tragically deadly State Route 530 (Oso) landslide is a stark reminder of the hazards\nassociated with glacial terraces lining valleys of the western Cascade Range. What controls\nthe differences in location and size of these slope failures? Here, we examine the control on\nlandslide volume and failure style by terrace sedimentary architecture. We analyze lidar\ntopographic data in three nearby valleys and find significant variation in landslide deposit\nvolumes, morphology, and relative mobility in each valley. Geologic data show that each site\ndiffers in the thickness and position of outwash, tills, and glaciolacustrine clays. Combining\na three-dimensional limit-equilibrium slope-stability analysis (Scoops3D) with simulations\nof variably saturated groundwater flow (VS2Dt), we show that landslide volumes are highly\nsensitive both to the distribution of material strength as well as the location of perched water\ntables. Modeled landslides match observed failure sizes and depths in all valleys when the\neffects of variably saturated groundwater flow are included. The position and thickness of\nlow-strength strata act as first-order controls on landslide volume, with peak volumes for\nstratigraphic geometries similar to that of the valley containing the Oso landslide. Knowledge\nof feedbacks between lithology and hydrology is therefore critical to assess the landslide\nhazard and evolution of landscapes composed of stratigraphically layered units.","language":"English","publisher":"Geological Society of America","doi":"10.1130/G39691.1","usgsCitation":"Perkins, J., Reid, M.E., and Schmidt, K.M., 2017, Control of landslide volume and hazard by glacial stratigraphic architecture, Northwest Washington state, USA: Geology, v. 45, no. 12, p. 1139-1142, https://doi.org/10.1130/G39691.1.","productDescription":"4 p.","startPage":"1139","endPage":"1142","ipdsId":"IP-086196","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":351303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126.7822265625,\n 45.9511496866914\n ],\n [\n -119.0478515625,\n 45.9511496866914\n ],\n [\n -119.0478515625,\n 49.56797785892715\n ],\n [\n -126.7822265625,\n 49.56797785892715\n ],\n [\n -126.7822265625,\n 45.9511496866914\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-19","publicationStatus":"PW","scienceBaseUri":"5a7c1e6de4b00f54eb22929b","contributors":{"authors":[{"text":"Perkins, Jonathan","contributorId":201949,"corporation":false,"usgs":true,"family":"Perkins","given":"Jonathan","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":727247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reid, Mark E. 0000-0002-5595-1503 mreid@usgs.gov","orcid":"https://orcid.org/0000-0002-5595-1503","contributorId":1167,"corporation":false,"usgs":true,"family":"Reid","given":"Mark","email":"mreid@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":727248,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":727249,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187716,"text":"pp1824D - 2017 - Geology and assessment of undiscovered oil and gas resources of the Hope Basin Province, 2008","interactions":[{"subject":{"id":70187716,"text":"pp1824D - 2017 - Geology and assessment of undiscovered oil and gas resources of the Hope Basin Province, 2008","indexId":"pp1824D","publicationYear":"2017","noYear":false,"chapter":"D","title":"Geology and assessment of undiscovered oil and gas resources of the Hope Basin Province, 2008"},"predicate":"IS_PART_OF","object":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"id":1}],"isPartOf":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"lastModifiedDate":"2024-06-26T14:25:10.072861","indexId":"pp1824D","displayToPublicDate":"2018-01-04T00:00:00","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":"1824","chapter":"D","title":"Geology and assessment of undiscovered oil and gas resources of the Hope Basin Province, 2008","docAbstract":"The Hope Basin, an independent petroleum province that lies mostly offshore in the southern Chukchi Sea north of the Chukotka and Seward Peninsulas and south of Wrangel Island, the Herald Arch, and the Lisburne Peninsula, is the largest in a series of postorogenic (successor) basins in the East Siberian-Chukchi Sea region and the only one with exploratory-well control and extensive seismic coverage.
In spite of the seismic coverage and well data, the petroleum potential of the Hope Basin Province is poorly known. The adequacy of hydrocarbon charge, in combination with uncertainties in source-rock potential and maturation, was the greatest risk in this assessment. A single assessment unit was defined and assessed, resulting in mean estimates of undiscovered, technically recoverable resources that include ~3 million barrels of oil and 650 billion cubic feet of nonassociated gas.
Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
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Simulation models can represent complexities of the real world and serve as virtual laboratories for asking “what if…?” questions about how systems might respond to different scenarios. However, simulation models have limited relevance to real-world applications when designed without input from people who could use the simulated scenarios to inform their decisions. Here, we report on a state-and-transition simulation model of vegetation dynamics that was coupled to a scenario planning process and co-produced by researchers, resource managers, local subject-matter experts, and climate change adaptation specialists to explore potential effects of climate scenarios and management alternatives on key resources in southwest South Dakota. Input from management partners and local experts was critical for representing key vegetation types, bison and cattle grazing, exotic plants, fire, and the effects of climate change and management on rangeland productivity and composition given the paucity of published data on many of these topics. By simulating multiple land management jurisdictions, climate scenarios, and management alternatives, the model highlighted important tradeoffs between grazer density and vegetation composition, as well as between the short- and long-term costs of invasive species management. It also pointed to impactful uncertainties related to the effects of fire and grazing on vegetation. More broadly, a scenario-based approach to model co-production bracketed the uncertainty associated with climate change and ensured that the most important (and impactful) uncertainties related to resource management were addressed. This cooperative study demonstrates six opportunities for scientists to engage users throughout the modeling process to improve model utility and relevance: (1) identifying focal dynamics and variables, (2) developing conceptual model(s), (3) parameterizing the simulation, (4) identifying relevant climate scenarios and management alternatives, (5) evaluating and refining the simulation, and (6) interpreting the results. We also reflect on lessons learned and offer several recommendations for future co-production efforts, with the aim of advancing the pursuit of usable science.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2020","usgsCitation":"Miller, B., Symstad, A.J., Frid, L., Fisichelli, N.A., and Schuurman, G.W., 2017, Co-producing simulation models to inform resource management: a case study from southwest South Dakota: Ecosphere, v. 8, no. 12, e02020; 24 p., https://doi.org/10.1002/ecs2.2020.","productDescription":"e02020; 24 p.","ipdsId":"IP-086834","costCenters":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":469222,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2020","text":"Publisher Index Page"},{"id":350458,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.25,\n 43\n ],\n [\n -101.5,\n 43\n ],\n [\n -101.5,\n 44\n ],\n [\n -103.25,\n 44\n ],\n [\n -103.25,\n 43\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"12","noUsgsAuthors":false,"publicationDate":"2017-12-15","publicationStatus":"PW","scienceBaseUri":"5a60e453e4b06e28e9c1406f","contributors":{"authors":[{"text":"Miller, Brian W. 0000-0003-1716-1161 bwmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-1716-1161","contributorId":195418,"corporation":false,"usgs":true,"family":"Miller","given":"Brian W.","email":"bwmiller@usgs.gov","affiliations":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":false,"id":725512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Symstad, Amy J. 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":147543,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":725513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frid, Leonardo","contributorId":56553,"corporation":false,"usgs":true,"family":"Frid","given":"Leonardo","affiliations":[],"preferred":false,"id":725514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisichelli, Nicholas A.","contributorId":174508,"corporation":false,"usgs":false,"family":"Fisichelli","given":"Nicholas","email":"","middleInitial":"A.","affiliations":[{"id":27461,"text":"NPS, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":725515,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schuurman, Gregor W. 0000-0002-9304-7742","orcid":"https://orcid.org/0000-0002-9304-7742","contributorId":147698,"corporation":false,"usgs":false,"family":"Schuurman","given":"Gregor","email":"","middleInitial":"W.","affiliations":[{"id":16909,"text":"U.S. National Park Service, Natural Resource Stewardship and Science, Fort Collins, CO, 80525, USA","active":true,"usgs":false}],"preferred":false,"id":725516,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197620,"text":"70197620 - 2017 - A simulation method for combining hydrodynamic data and acoustic tag tracks to predict the entrainment of juvenile salmonids onto the Yolo Bypass under future engineering scenarios","interactions":[],"lastModifiedDate":"2018-06-14T10:27:56","indexId":"70197620","displayToPublicDate":"2018-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"A simulation method for combining hydrodynamic data and acoustic tag tracks to predict the entrainment of juvenile salmonids onto the Yolo Bypass under future engineering scenarios","docAbstract":"During water year 2016 the U.S. Geological Survey California Water Science Center (USGS) collaborated with the California Department of Water Resources (DWR) to conduct a joint hydrodynamic and fisheries study to acquire data that could be used to evaluate the effects of proposed modifications to the Fremont Weir on outmigrating juvenile Chinook salmon. During this study the USGS surgically implanted acoustic tags in juvenile late fall run Chinook salmon from the Coleman National Fish Hatchery, released the acoustically tagged juvenile salmon into the Sacramento River upstream of the Fremont Weir, and tracked their movements as they emigrated past the western end of the Fremont Weir.
The USGS analyzed tracking data from the acoustically tagged juvenile salmon along with detailed hydrodynamic data collected in the Sacramento River during the winter/spring of water year 2016 in the vicinity of the western end of the Fremont Weir to assess the potential for enhancing the entrainment of Sacramento River Chinook salmon onto the Yolo Bypass under six different Fremont Weir modification scenarios. Each modification scenario consists of a notch or multiple notches in the Fremont Weir which are designed to divert a portion of the Sacramento River onto the Yolo Bypass when the Sacramento River is below the crest of the Fremont Weir. The primary goal of this entrainment analysis was to investigate how the location of the notch or notches in each scenario affected the entrainment of juvenile Chinook salmon onto the Yolo Bypass, and to predict the notch location or locations that would result in maximum entrainment under each modification scenario.
Stumpner et al.’s (in review) analysis of hydraulic data collected during the 2016 study period showed that backwater effects in the Sacramento River created significant variability in the relationship between Sacramento River stage and the proportion of the Sacramento River flow that we expect to be diverted onto the Yolo Bypass under the modification scenarios. Because of this variability, accurately evaluating the entrainment potential of possible notch locations for each scenario required combining historic abundance data for juvenile Sacramento River Chinook salmon with historic hydraulic data for the Sacramento River in the vicinity of the Fremont Weir, so that the entrainment estimates would reflect the covariance between Sacramento River stage, Sacramento River discharge, and juvenile salmon abundance within the historic record.
We used a Monte Carlo simulation framework to combine the high resolution hydrodynamic data and acoustic tag track data collected in 2016 with historic juvenile salmon abundance, Sacramento River stage, and Sacramento River discharge data from a period spanning water years 1996-2010 to assess the entrainment potential of different weir modification scenarios under historic conditions. The scenarios we simulated consisted of four single notch configurations, and two multiple notch configurations in the vicinity of the western end of the Fremont Weir. For each notch configuration the 15-water-year entrainment simulation was repeated for 63 possible notch locations in the vicinity of the western end of the Fremont Weir. This approach allowed us to assess the effect of notch location on the entrainment of juvenile salmonids onto the Yolo Bypass for each of the six notch configurations that we evaluated.
The entrainment simulations showed that the location of each notch configuration had a major impact on the entrainment for each scenario; the predicted entrainment of some scenarios varied by as much as 400% based on where the notch (or notches) was (were) located in the study area. All of the single notch scenarios performed best when they were located within a 330 ft (100 meter) long section of the Sacramento River bank adjacent to the western terminus of the Fremont Weir (Table 1). Both of the multiple notch scenarios performed best when their upstream notches were located about 660 ft (200 meters) upstream of the western terminus of the Fremont Weir (Table 1). The results of the entrainment simulations indicated that for each notch configuration the same notch location produced near-maximum entrainment regardless of run abundance timing; this result suggests that there are areas within the study are where a notch (or notches) can be sited to achieve maximum entrainment for all runs (barring significant behavioral or physiological differences between runs). In addition, the simulation results indicate that for each notch configuration the same location is expected to produce nearmaximum entrainment for both wet water years and dry water years.
Based on the results of the entrainment simulation we make three general recommendations for strategies to improve the entrainment potential of a notch in the Fremont Weir:
1) Comparisons between the maximum entrainment potential for each scenario suggested that total entrainment of winter run, spring run, and fall run salmon onto the Yolo Bypass can be increased by increasing the amount of water entering a notch when the Sacramento River stage is between 19 ft and 22 ft NAVD88; this could be accomplished by lowering notch invert elevations or by adding a control section to the Sacramento River to raise stage for a given discharge.
2) The relationship between Sacramento River stage and entrainment for each scenario indicated that entrainment efficiency for each scenario declined significantly once Sacramento River stage exceeded bankfull (approximately 28.5 ft NAVD88). This effect was likely due to inundation of the floodplain between the Sacramento River and the Fremont Weir; Stumpner et. al (In Review) have documented a reduction in the strength of the secondary circulation and centralization of the downwelling zone in the Sacramento River when this floodplain is inundated. Therefore, increasing the height of the river right bank of the Sacramento River to coincide with the height of the Fremont Weir is recommended to increase entrainment at higher stages.
3) Bathymetric features upstream of notch openings appeared to have a major impact on the entrainment potential of the simulated notches. For this reason we recommend taking care to avoid siting notches immediately downstream of bank features that alter the sidewall boundary layer, and we expect that smoothing the bank bathymetry upstream of a notch will enhance entrainment.
Finally, we caution that the entrainment simulation was based on the behavior of large hatchery smolts, so it is likely that our results will be sensitive to any differences in behavior and physiology between these hatchery surrogates and naturally migrating juvenile salmon.
","language":"English","publisher":"Delta Stewardship Council","usgsCitation":"Blake, A.R., Stumpner, P., and Burau, J.R., 2017, A simulation method for combining hydrodynamic data and acoustic tag tracks to predict the entrainment of juvenile salmonids onto the Yolo Bypass under future engineering scenarios, 108 p.","productDescription":"108 p.","ipdsId":"IP-089808","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":355046,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":355027,"type":{"id":11,"text":"Document"},"url":"https://deltacouncil.ca.gov/sites/default/files/2018/04/Entrainment%20Analysis_FinalVersion_Released.pdf"}],"country":"United States","state":"California","otherGeospatial":"Yolo Bypass","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e607e4b060350a15d246","contributors":{"authors":[{"text":"Blake, Aaron R. 0000-0001-7348-2336 ablake@usgs.gov","orcid":"https://orcid.org/0000-0001-7348-2336","contributorId":5059,"corporation":false,"usgs":true,"family":"Blake","given":"Aaron","email":"ablake@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737949,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stumpner, Paul 0000-0002-0933-7895 pstump@usgs.gov","orcid":"https://orcid.org/0000-0002-0933-7895","contributorId":5667,"corporation":false,"usgs":true,"family":"Stumpner","given":"Paul","email":"pstump@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737950,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burau, Jon R. 0000-0002-5196-5035 jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737951,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70205968,"text":"70205968 - 2017 - Characterization of microsatellite loci for the Gulf Coast waterdog (Necturus beyeri) using paired-end Illumina shotgun sequencing and cross-amplification in other Necturus","interactions":[],"lastModifiedDate":"2019-10-11T17:22:03","indexId":"70205968","displayToPublicDate":"2017-12-31T17:20:04","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1898,"text":"Herpetological Review","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Characterization of microsatellite loci for the Gulf Coast waterdog (Necturus beyeri) using paired-end Illumina shotgun sequencing and cross-amplification in other Necturus","title":"Characterization of microsatellite loci for the Gulf Coast waterdog (Necturus beyeri) using paired-end Illumina shotgun sequencing and cross-amplification in other Necturus","docAbstract":"Amphibians are one of the most threatened groups of vertebrates (Stuart et al. 2004; Wake and Vredenburg 2008), and the application of molecular techniques to amphibian ecology and genetics has dramatically improved our ability to conserve species and populations (see Shaffer et al. [2015] for review). Microsatellites, tandem repeats of two to six nucleotides in the nuclear genome, are highly variable molecular markers that can be used to describe gene flow and genetic diversity, each of which is positively correlated with population persistence (Allendorf and Luikart 2007; Allentoft and O’Brien 2010; Avise 2004; Selkoe and Toonen 2006). Microsatellite loci have frequently been applied to studies involving terrestrial and pond breeding amphibians (Emel and Storfer 2012), but fewer studies have focused on taxa inhabiting lotic systems (Emel and Storfer 2012). For example, studies characterizing microsatellite loci are completely lacking for a group of permanently aquatic salamanders, the waterdogs and mudpuppies (Family Proteidae, Genus Necturus) (Rafinesque 1819).
The genus Necturus consists of several species of perennibranch salamanders that can be found throughout many freshwater streams, rivers, and lakes in North America (Petranka 1998). Some authorities recognize five species (Crother 2012; Petranka 1998), including the Mudpuppy (Necturus maculosus) (Rafinesque 1819), Gulf Coast Waterdog (N. beyeri) (Viosca 1937), Black Warrior Waterdog (N. alabamensis) (Viosca 1937), Neuse River Waterdog (N. lewisi) (Brimley 1924), and Dwarf Waterdog (N. punctatus) (Gibbes 1850). This taxonomy also recognizes two subspecies within N. maculosus, including the Common Mudpuppy (N. m. maculosus) and the Red River Waterdog (N. m. louisianensis) (Crother 2012; Petranka 1998; Schmidt 1953). Other authorities suggest that there are six or seven species within Necturus (Collins 1990; Frost 2016; Powell et al. 2016). These more diverse schemes recognize each of the aforementioned five species while also elevating the Red River Waterdog (N. louisianensis) (Collins 1990; Frost 2016; Powell et al. 2016; Viosca 1938) and Löding’s Waterdog (N. lödingi or N. cf. beyeri) (Bart et al. 1997; Guyer 2005a; Viosca 1938). Allozyme work by Guttman et al. (1990) suggests that there is at least one cryptic species of Necturus in drainages east of the Mobile Basin and south of the Alabama River, and both Bart et al. (1997) and Guyer (2005a) advise that these populations should be referred to as N. cf. beyeri. However, until range wide studies incorporating genetic and other data are published, we will follow the five species taxonomy outlined by Crother (2012) while acknowledging that certain taxa, such as N. maculosus and N. beyeri, may require systematic revision.
Nest box programs are frequently implemented for conservation of cavity-nesting birds, but their effectiveness is rarely evaluated in comparison to birds not using nest boxes. In the European Palearctic, Red-Footed Falcon (Falco vespertinus) populations are both of high conservation concern and are strongly associated with nest box programs in heavily managed landscapes. We used a 21-year monitoring dataset developed from monitoring 753 nesting attempts by Red-footed Falcons at the Naurzum Zapovednick to evaluate response of demographic parameters of Redfooted Falcons to environmental factors including use of nest boxes. Variations in lay date and in numbers of eggs were not well explained by any one model, but instead by combinations of models with terms for nest type, land cover type and degree of coloniality. In contrast, variation in both offspring loss and numbers of fledglings produced were fairly well explained by a single model including terms for nest type, land cover type, and an interaction between the two parameters (65% and 81% model weights respectively). Because, for other species, early lay dates are associated with individual fitness, this interaction highlighted a potential ecological trap where falcons using nest boxes on forest edges at Naurzum lay eggs earlier but suffer greater offspring loss and produce lower numbers of fledglings than do those in other nesting settings.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Biological diversity of Asian Steppe: Proceedings of the III international scientific conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"III International Scientific Conference: Biological Diversity of Asian Steppe","conferenceDate":"Apr 24-27, 2017","conferenceLocation":"Kostanay, Kazakhstan","language":"English","publisher":"Kostanay State Pedagogical Institute","usgsCitation":"Katzner, T., Bragin, A.E., and Bragin, E.A., 2017, Are nest boxes ecological traps for red-footed falcons Falco vespertinius at Naurzum, in Biological diversity of Asian Steppe: Proceedings of the III international scientific conference, Kostanay, Kazakhstan, Apr 24-27, 2017, p. 240-244.","productDescription":"5 p.","startPage":"240","endPage":"244","ipdsId":"IP-084190","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":375273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Kazahkstan","state":"Kostanay Oblast","otherGeospatial":"Naurzum State Nature Reserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 63.66165161132813,\n 51.24042602354956\n ],\n [\n 64.91683959960938,\n 51.24042602354956\n ],\n [\n 64.91683959960938,\n 51.931565061629236\n ],\n [\n 63.66165161132813,\n 51.931565061629236\n ],\n [\n 63.66165161132813,\n 51.24042602354956\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":782958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bragin, Alexander E.","contributorId":193027,"corporation":false,"usgs":false,"family":"Bragin","given":"Alexander","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":782959,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bragin, Evgeny A.","contributorId":194894,"corporation":false,"usgs":false,"family":"Bragin","given":"Evgeny","email":"","middleInitial":"A.","affiliations":[{"id":35656,"text":"Science Department, Naurzum National Nature Reserve, Kostanay Oblast, Naurzumski Raijon, Karamendy, Kazakhstan","active":true,"usgs":false}],"preferred":false,"id":782960,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70219001,"text":"70219001 - 2017 - Analysis of artificially matured shales with confocal laser scanning raman microscopy: Applications to organic matter characterization","interactions":[],"lastModifiedDate":"2021-04-20T11:56:57.637835","indexId":"70219001","displayToPublicDate":"2017-12-31T08:49:40","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Analysis of artificially matured shales with confocal laser scanning raman microscopy: Applications to organic matter characterization","docAbstract":"Raman spectroscopy has been suggested as a method for characterizing the thermal maturity of rocks. The literature contains many empirical correlations between thermal maturity proxies, such as vitrinite reflectance (VRo) and pyrolysis-Tmax, with spectral metrics such as Raman peak-widths, peak-center positions, peak-areas and all manner of differences and ratios of these parameters. However, while these correlations may be convincing for small data sets from limited sample series, broader application of these metrics to disparate and heterogeneous samples proves difficult and there remains no consensus.
In this extended abstract, Raman spectroscopy is introduced and the history of Raman analysis of carbonaceous material is briefly outlined, highlighting some of the latent difficulties and potential sources of bias. We suggest the organization of a community working group to establish terminology, guidelines, procedures and standards necessary for the successful development of this technique to characterize organic matter in an accessible, unbiased, and reproducible manner.
For the present multi-phase study, immature shale samples from the Bakken and Duvernay formations were subjected to hydrous pyrolysis for 72 hours at temperatures from 280°C to 360°C. Rock residues were mounted and polished for analysis via confocal laser-scanning Raman microscopy and reflectance. The maturation series from the Bakken was randomized for the Phase-I single-blind study to be presented at this conference. For the Phase-II study, solid bitumen reflectance (BRo) values for the Duvernay series will be known.
Multiple hyperspectral maps were collected from each Bakken sample, with each map consisting of a single diffraction-limited spot-size spectrum per 1 µm2 in rectangular areas several hundred micrometers on a side. Initial attempts at using basic spectral metrics on small numbers of hand-selected spectra to sort the blind series produced inconclusive results: any number of possible correlations could be found. In an improved approach, the statistics of the full spectral datasets were leveraged to: 1) objectively identify organic carbon types (OCTs) in a given map based on Raman and fluorescence spectral characteristics, 2) identify those OCTs in other maps from the same sample and determine if the heterogeneity of the sample has been adequately characterized, and 3) identify the same OCTs in maps from other samples in the maturation series. In ongoing work, our goals are to: 1) use these analyses of the blind series to develop a hypothesis for a correlation to maturation, 2) test the hypothesis by applying the same analyses to the known Duvernay series (in Phase-II), 3) if necessary refine the hypothesis based on observations from the Duvernay analysis, and 4) finally reveal the true order of the Bakken series to verify if the hypothesized correlation accurately predicts the maturity order of the samples.
In this document, we share progress to date. The analysis of one area of interest is detailed showing the differentiation of two OCTs based on Raman and fluorescence spectral features, including the use of 2-factor histograms, Principle Components Analysis (PCA), and Nonlinear Iterative Peak Fitting (NIPF).
","conferenceTitle":"Unconventional Resources Technology Conference","conferenceDate":"July 24-26, 2017","conferenceLocation":"Austin, TX","language":"English","publisher":"Curran Associates","doi":"10.15530/urtec-2017-2671253","usgsCitation":"Myers, G.A., Kehoe, K., and Hackley, P.C., 2017, Analysis of artificially matured shales with confocal laser scanning raman microscopy: Applications to organic matter characterization, Unconventional Resources Technology Conference, Austin, TX, July 24-26, 2017, 2671253, 16 p., https://doi.org/10.15530/urtec-2017-2671253.","productDescription":"2671253, 16 p.","ipdsId":"IP-086591","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":385188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Myers, Grant A.","contributorId":255533,"corporation":false,"usgs":false,"family":"Myers","given":"Grant","email":"","middleInitial":"A.","affiliations":[{"id":51579,"text":"WellDog Gas Sensing Technology Corp.","active":true,"usgs":false}],"preferred":false,"id":814475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kehoe, Kelsey","contributorId":255534,"corporation":false,"usgs":false,"family":"Kehoe","given":"Kelsey","email":"","affiliations":[{"id":51579,"text":"WellDog Gas Sensing Technology Corp.","active":true,"usgs":false}],"preferred":false,"id":814476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":812433,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196906,"text":"70196906 - 2017 - Spatial ecology and movement of reintroduced Canada lynx","interactions":[],"lastModifiedDate":"2018-05-11T14:19:18","indexId":"70196906","displayToPublicDate":"2017-12-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"Spatial ecology and movement of reintroduced Canada lynx","docAbstract":"Understanding movement behavior and identifying areas of landscape connectivity is critical for the conservation of many species. However, collecting fine‐scale movement data can be prohibitively time consuming and costly, especially for rare or endangered species, whereas existing data sets may provide the best available information on animal movement. Contemporary movement models may not be an option for modeling existing data due to low temporal resolution and large or unusual error structures, but inference can still be obtained using a functional movement modeling approach. We use a functional movement model to perform a population‐level analysis of telemetry data collected during the reintroduction of Canada lynx to Colorado. Little is known about southern lynx populations compared to those in Canada and Alaska, and inference is often limited to a few individuals due to their low densities. Our analysis of a population of Canada lynx fills significant gaps in the knowledge of Canada lynx behavior at the southern edge of its historical range. We analyzed functions of individual‐level movement paths, such as speed, residence time, and tortuosity, and identified a region of connectivity that extended north from the San Juan Mountains, along the continental divide, and terminated in Wyoming at the northern edge of the Southern Rocky Mountains. Individuals were able to traverse large distances across non‐boreal habitat, including exploratory movements to the Greater Yellowstone area and beyond. We found evidence for an effect of seasonality and breeding status on many of the movement quantities and documented a potential reintroduction effect. Our findings provide the first analysis of Canada lynx movement in Colorado and substantially augment the information available for conservation and management decisions. The functional movement framework can be extended to other species and demonstrates that information on movement behavior can be obtained using existing data sets.
","language":"English","publisher":"Wiley","doi":"10.1111/ecog.03030","usgsCitation":"Buderman, F.E., Hooten, M., Ivan, J., and Shenk, T., 2017, Spatial ecology and movement of reintroduced Canada lynx: Ecography, v. 41, no. 1, p. 126-139, https://doi.org/10.1111/ecog.03030.","productDescription":"14 p.","startPage":"126","endPage":"139","ipdsId":"IP-072342","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":354099,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","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}","volume":"41","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-22","publicationStatus":"PW","scienceBaseUri":"5afee789e4b0da30c1bfc2de","contributors":{"authors":[{"text":"Buderman, Frances E.","contributorId":171634,"corporation":false,"usgs":false,"family":"Buderman","given":"Frances","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":734972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":734971,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ivan, Jacob S.","contributorId":200243,"corporation":false,"usgs":false,"family":"Ivan","given":"Jacob S.","affiliations":[],"preferred":false,"id":734973,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shenk, Tanya","contributorId":204778,"corporation":false,"usgs":false,"family":"Shenk","given":"Tanya","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":734974,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196355,"text":"70196355 - 2017 - Long-term monitoring data provide evidence of declining species richness in a river valued for biodiversity conservation","interactions":[],"lastModifiedDate":"2018-04-03T14:24:41","indexId":"70196355","displayToPublicDate":"2017-12-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Long-term monitoring data provide evidence of declining species richness in a river valued for biodiversity conservation","docAbstract":"Free-flowing river segments provide refuges for many imperiled aquatic biota that have been extirpated elsewhere in their native ranges. These biodiversity refuges are also foci of conservation concerns because species persisting within isolated habitat fragments may be particularly vulnerable to local environmental change. We have analyzed long-term (14- and 20-y) survey data to assess evidence of fish species declines in two southeastern U.S. rivers where managers and stakeholders have identified potentially detrimental impacts of current and future land uses. The Conasauga River (Georgia and Tennessee) and the Etowah River (Georgia) form free-flowing headwaters of the extensively dammed Coosa River system. These rivers are valued in part because they harbor multiple species of conservation concern, including three federally endangered and two federally threatened fishes. We used data sets comprising annual surveys for fish species at multiple, fixed sites located at river shoals to analyze occupancy dynamics and temporal changes in species richness. Our analyses incorporated repeated site-specific surveys in some years to estimate and account for incomplete species detection, and test for species-specific (rarity, mainstem-restriction) and year-specific (elevated frequencies of low- or high-flow days) covariates on occupancy dynamics. In the Conasauga River, analysis of 26 species at 13 sites showed evidence of temporal declines in colonization rates for nearly all taxa, accompanied by declining species richness. Four taxa (including one federally endangered species) had reduced occupancy across the Conasauga study sites, with three of these taxa apparently absent for at least the last 5 y of the study. In contrast, a similar fauna of 28 taxa at 10 sites in the Etowah River showed no trends in species persistence, colonization, or occupancy. None of the tested covariates showed strong effects on persistence or colonization rates in either river. Previous studies and observations identified contaminants, nutrient loading, or changes in benthic habitat as possible causes for fish species declines in the Conasauga River. Our analysis provides baseline information that could be used to assess effectiveness of future management actions in the Conasauga or Etowah rivers, and illustrates the use of dynamic occupancy models to evaluate evidence of faunal decline from time-series data.
","language":"English","publisher":"Scientific Journals","doi":"10.3996/122016-JFWM-090","usgsCitation":"Freeman, M., Hagler, M.M., Bumpers, P.M., Wheeler, K., Wenger, S., and Freeman, B.J., 2017, Long-term monitoring data provide evidence of declining species richness in a river valued for biodiversity conservation: Journal of Fish and Wildlife Management, v. 8, no. 2, p. 418-434, https://doi.org/10.3996/122016-JFWM-090.","productDescription":"17p.","startPage":"418","endPage":"434","ipdsId":"IP-082143","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":353118,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Conasauga River, Etowah River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.49560546875,\n 33.99802726234877\n ],\n [\n -83.9959716796875,\n 33.99802726234877\n ],\n [\n -83.9959716796875,\n 35.007502842952896\n ],\n [\n -85.49560546875,\n 35.007502842952896\n ],\n [\n -85.49560546875,\n 33.99802726234877\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-01","publicationStatus":"PW","scienceBaseUri":"5afee789e4b0da30c1bfc2e2","contributors":{"authors":[{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":732551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hagler, Megan M.","contributorId":203870,"corporation":false,"usgs":false,"family":"Hagler","given":"Megan","email":"","middleInitial":"M.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":732552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bumpers, Phillip M.","contributorId":203871,"corporation":false,"usgs":false,"family":"Bumpers","given":"Phillip","email":"","middleInitial":"M.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":732553,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wheeler, Kit","contributorId":203872,"corporation":false,"usgs":false,"family":"Wheeler","given":"Kit","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":732554,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wenger, Seth J.","contributorId":177838,"corporation":false,"usgs":false,"family":"Wenger","given":"Seth J.","affiliations":[],"preferred":false,"id":732555,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Freeman, Byron J.","contributorId":49782,"corporation":false,"usgs":false,"family":"Freeman","given":"Byron","email":"","middleInitial":"J.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":732556,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197040,"text":"70197040 - 2017 - Occupancy and abundance of Eleutherodactylus wightmanae and E. brittoni along elevational gradients in west-central Puerto Rico","interactions":[],"lastModifiedDate":"2020-12-16T16:49:09.712772","indexId":"70197040","displayToPublicDate":"2017-12-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5533,"text":"Caribbean Naturalist","onlineIssn":"2326-7119","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Occupancy and abundance of Eleutherodactylus wightmanae and E. brittoni along elevational gradients in west-central Puerto Rico","title":"Occupancy and abundance of Eleutherodactylus wightmanae and E. brittoni along elevational gradients in west-central Puerto Rico","docAbstract":"Populations of Eleutherodactylus species in Puerto Rico have declined in recent decades due to habitat loss and long-term climatic changes. The conservation of these habitat specialists requires an understanding of factors influencing their abundance and distribution, which at present is scant. We estimated occupancy probability and the probability of encountering ≥2 individuals of E. wightmanae (Melodius Coqui or Wightman's Robber Frog) and E. brittoni (Grass Coqui), species with contrasting habitat affinities, using multi-season, multi-state occupancy models. These parameters also served as an index of abundance (non-presence, 1, and ≥2 individuals). We modeled parameters as a function of seasonal temperature and humidity, long-term average monthly precipitation, and habitat covariates measured at survey sites along 2 elevation gradients in the southern slopes of west-central Puerto Rico. We collected survey data using passive acoustic recorders during 3 seasonal periods between February and July 2015. Occupancy patterns of both species was unimodal, containing higher probabilities (e.g., ≥0.5) at elevations between 400 m and 700 m, where long-term monthly precipitation varied between 120 mm and 160 mm. Chances of encountering ≥2 individuals increased with ground cover for E. brittoni, and decreased with increasing canopy cover for E. wightmanae. Seasonal temperature and relative humidity did not influence occupancy or the probability of encountering ≥2 individuals, likely because covariates varied within known tolerance levels for Eleutherodactylus. Our findings help reduce local extinction probability through management of habitat conditions that increase the likelihood of encountering ≥2 individuals. We also detailed an analytical framework suitable to test hypotheses aimed at predicting potential impacts from land use and climatic changes, and species responses to conservation actions.
","language":"English","publisher":"Eagle Hill Institute","usgsCitation":"Monroe, K.D., Collazo, J., Pacifici, K., Reich, B.J., Puente-Rolon, A.R., and Terando, A.J., 2017, Occupancy and abundance of Eleutherodactylus wightmanae and E. brittoni along elevational gradients in west-central Puerto Rico: Caribbean Naturalist, v. 40, p. 1-18.","productDescription":"18 p.","startPage":"1","endPage":"18","onlineOnly":"Y","ipdsId":"IP-077348","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354159,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":381419,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.eaglehill.us/CANAonline/CANA-access-pages/CANA-regular/CANA-040-Collazo.shtml"}],"country":"United States","state":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.445068359375,\n 17.78007412664325\n ],\n [\n -65.19287109375,\n 17.78007412664325\n ],\n [\n -65.19287109375,\n 18.729501999072138\n ],\n [\n -67.445068359375,\n 18.729501999072138\n ],\n [\n -67.445068359375,\n 17.78007412664325\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee788e4b0da30c1bfc2d2","contributors":{"authors":[{"text":"Monroe, Kelen D.","contributorId":200135,"corporation":false,"usgs":false,"family":"Monroe","given":"Kelen","email":"","middleInitial":"D.","affiliations":[{"id":33914,"text":"North Carolina State University, Raleigh","active":true,"usgs":false}],"preferred":false,"id":735339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collazo, Jaime A. 0000-0002-1816-7744 jaime_collazo@usgs.gov","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":173448,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime A.","email":"jaime_collazo@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":735337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pacifici, Krishna","contributorId":26564,"corporation":false,"usgs":false,"family":"Pacifici","given":"Krishna","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":735340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reich, Brian J.","contributorId":150871,"corporation":false,"usgs":false,"family":"Reich","given":"Brian","email":"","middleInitial":"J.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":735341,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Puente-Rolon, Alberto R.","contributorId":42498,"corporation":false,"usgs":true,"family":"Puente-Rolon","given":"Alberto","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":735342,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Terando, Adam J. 0000-0002-9280-043X aterando@usgs.gov","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":173447,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","email":"aterando@usgs.gov","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":735343,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197037,"text":"70197037 - 2017 - Declining occurrence and low colonization probability in freshwater mussel assemblages: A dynamic occurrence modeling approach","interactions":[],"lastModifiedDate":"2020-12-16T16:55:45.695979","indexId":"70197037","displayToPublicDate":"2017-12-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5254,"text":"Freshwater Mollusk Biology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Declining occurrence and low colonization probability in freshwater mussel assemblages: A dynamic occurrence modeling approach","docAbstract":"Mussel monitoring data are abundant, but methods for analyzing long-term trends in these data are often uninformative or have low power to detect changes. We used a dynamic occurrence model, which accounted for imperfect species detection in surveys, to assess changes in species occurrence in a longterm data set (1986–2011) for the Tar River basin of North Carolina, USA. Occurrence of all species decreased steadily over the time period studied. Occurrence in 1986 ranged from 0.19 for Utterbackia imbecillis to 0.60 for Fusconaia masoni. Occurrence in 2010–2011 ranged from 0.10 for Lampsilis radiata to 0.40 for F. masoni. The maximum difference between occurrence in 1986 and 2011 was a decline of 0.30 for Alasmidonta undulata. Mean persistence for all species was high (0.97, 95% CI ¼ 0.95–0.99); however, mean colonization probability was very low (,0.01, 95% CI ¼ ,0.01–0.01). These results indicate that mussels persisted at sites already occupied but that they have not colonized sites where they had not occurred previously. Our findings highlight the importance of modeling approaches that incorporate imperfect detection in estimating species occurrence and revealing temporal trends to inform conservation planning.
","language":"English","publisher":"Freshwater Mollusk Conservation Society","doi":"10.31931/fmbc.v20i1.2017.13-19","usgsCitation":"Pandolfo, T.J., Kwak, T.J., Cope, W., Heise, R.J., Nichols, R.B., and Pacifici, K., 2017, Declining occurrence and low colonization probability in freshwater mussel assemblages: A dynamic occurrence modeling approach: Freshwater Mollusk Biology and Conservation, v. 20, no. 1, p. 13-19, https://doi.org/10.31931/fmbc.v20i1.2017.13-19.","productDescription":"7 p.","startPage":"13","endPage":"19","ipdsId":"IP-070553","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469227,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.31931/fmbc.v20i1.2017.13-19","text":"Publisher Index Page"},{"id":354162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Tar River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.365234375,\n 35.37113502280101\n ],\n [\n -77.6513671875,\n 35.37113502280101\n ],\n [\n -77.6513671875,\n 36.527294814546245\n ],\n [\n -79.365234375,\n 36.527294814546245\n ],\n [\n -79.365234375,\n 35.37113502280101\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee789e4b0da30c1bfc2d6","contributors":{"authors":[{"text":"Pandolfo, Tamara J.","contributorId":146388,"corporation":false,"usgs":false,"family":"Pandolfo","given":"Tamara","email":"","middleInitial":"J.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":735347,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":735325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cope, W. Gregory","contributorId":70353,"corporation":false,"usgs":true,"family":"Cope","given":"W. Gregory","affiliations":[],"preferred":false,"id":735348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heise, Ryan J.","contributorId":145789,"corporation":false,"usgs":false,"family":"Heise","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":16149,"text":"North Carolina Wildlife Resources Commission, 1003 Consolidated Rd., Elizabeth City, NC 27909","active":true,"usgs":false}],"preferred":false,"id":735349,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nichols, Robert B.","contributorId":182112,"corporation":false,"usgs":false,"family":"Nichols","given":"Robert","email":"","middleInitial":"B.","affiliations":[{"id":35598,"text":"North Carolina Wildlife Resources Commission ","active":true,"usgs":false}],"preferred":false,"id":735350,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pacifici, Krishna","contributorId":26564,"corporation":false,"usgs":false,"family":"Pacifici","given":"Krishna","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":735351,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70194814,"text":"sir20175141 - 2017 - Groundwater-flow budget for the lower Apalachicola-Chattahoochee-Flint River Basin in southwestern Georgia and parts of Florida and Alabama, 2008–12","interactions":[],"lastModifiedDate":"2018-01-02T13:28:49","indexId":"sir20175141","displayToPublicDate":"2017-12-29T15:45:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5141","title":"Groundwater-flow budget for the lower Apalachicola-Chattahoochee-Flint River Basin in southwestern Georgia and parts of Florida and Alabama, 2008–12","docAbstract":"As part of the National Water Census program in the Apalachicola-Chattahoochee-Flint (ACF) River Basin, the U.S. Geological Survey evaluated the groundwater budget of the lower ACF, with particular emphasis on recharge, characterizing the spatial and temporal relation between surface water and groundwater, and groundwater pumping. To evaluate the hydrologic budget of the lower ACF River Basin, a groundwater-flow model, constructed using MODFLOW-2005, was developed for the Upper Floridan aquifer and overlying semiconfining unit for 2008–12. Model input included temporally and spatially variable specified recharge, estimated using a Precipitation-Runoff Modeling System (PRMS) model for the ACF River Basin, and pumping, partly estimated on the basis of measured agricultural pumping rates in Georgia. The model was calibrated to measured groundwater levels and base flows, which were estimated using hydrograph separation.
The simulated groundwater-flow budget resulted in a small net cumulative loss of groundwater in storage during the study period. The model simulated a net loss in groundwater storage for all the subbasins as conditions became substantially drier from the beginning to the end of the study period. The model is limited by its conceptualization, the data used to represent and calibrate the model, and the mathematical representation of the system; therefore, any interpretations should be considered in light of these limitations. In spite of these limitations, the model provides insight regarding water availability in the lower ACF River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175141","collaboration":"U.S. Geological Survey National Water Census and Water Availability and Use Science Program","usgsCitation":"Jones, L.E., Painter, Jaime, LaFontaine, Jacob, Sepulveda, Nicasio, and Sifuentes, D.F., 2017, Groundwater-flow budget for the lower Apalachicola-Chattahoochee-Flint River Basin in southwestern Georgia and parts of \nFlorida and Alabama, 2008–12: U.S. Geological Survey Scientific Investigations Report 2017–5141, 76 p., \nhttps://doi.org/10.3133/sir20175141.","productDescription":"Report: viii, 76 p.; Data Release","numberOfPages":"88","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":350246,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5141/coverthb.jpg"},{"id":350249,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/publication/sir20175133","text":"Scientific Investigations Report 2017-5133","linkHelpText":"- Simulations of Hydrologic Response in the Apalachicola-Chattahoochee-Flint River Basin, Southeastern United States"},{"id":350247,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5141/sir20175141.pdf","text":"Report","size":"10.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5141"},{"id":350248,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DV1HCG","text":"USGS data release","description":"USGS data release"}],"country":"United States","state":"Alabama, Florida, Georgia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.5,\n 30.5\n ],\n [\n -83.75,\n 30.5\n ],\n [\n -83.75,\n 32.25\n ],\n [\n -85.5,\n 32.25\n ],\n [\n -85.5,\n 30.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
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720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
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