Watersheds recently burned by wildfires can have an increased susceptibility to debris flow, although little is known about how long this susceptibility persists, and how it changes over time. We here use a compilation of 75 debris-flow response and fire-ignition dates, vegetation and bedrock class, rainfall regime, and initiation process from throughout the western U.S. to address these issues. The great majority (85 percent) of debris flows occurred within the first 12 months following wildfire, with 71 percent within the first six months. Seven percent of the debris flows occurred between 1 and 1.5 years after a fire, or during the second rainy season to impact an area. Within the first 1.5 years following fires, all but one of the debris flows initiated through runoff-dominated processes, and debris flows occurred in similar proportions in forested and non-forested landscapes. Geologic materials affected how long debris-flow activity persisted, and the timing of debris flows varied within different rainfall regimes. A second, later period of increased debris flow susceptibility between 2.2 and 10 years after fires is indicated by the remaining 8 percent of events, which occurred primarily in forested terrains and initiated largely through landslide processes. The short time period between fire and debris-flow response within the first 1.5 years after ignition, and the longer-term response between 2.2 and 10 years after fire, demonstrate the necessity of both rapid and long-term reactions by land managers and emergency-response agencies to mitigate hazards from debris flows from recently burned areas in the western U.S.
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operations, or through drillholes for solution mining. Additionally, mineral processing can generate large quantities of waste, including mill tailings, waste rock and refinery wastes, heap leach pads, and slag. Thus, through mining and mineral processing activities, large surface areas of sulfide minerals can be exposed to oxygen, water, and microbes, resulting in accelerated oxidation of sulfide and other minerals and the potential for the generation of low-quality drainage. The oxidation of sulfide minerals in mine wastes is accelerated by microbial catalysis of the oxidation of aqueous ferrous iron and sulfide. These reactions, particularly when combined with evaporation, can lead to extremely acidic drainage and very high concentrations of dissolved constituents. Although acid mine drainage is the most prevalent and damaging environmental concern associated with mining activities, generation of saline, basic and neutral drainage containing elevated concentrations of dissolved metals, non-metals, and metalloids has recently been recognized as a potential environmental concern. Acid neutralization reactions through the dissolution of carbonate, hydroxide, and silicate minerals and formation of secondary aluminum and ferric hydroxide phases can moderate the effects of acid generation and enhance the formation of secondary hydrated iron and aluminum minerals which may lessen the concentration of dissolved metals. Numerical models provide powerful tools for assessing impacts of these reactions on water quality.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2015.02.008","usgsCitation":"Nordstrom, D.K., Blowes, D., and Ptacek, C., 2015, Hydrogeochemistry and microbiology of mine drainage: An update: Applied Geochemistry, v. 57, p. 3-16, https://doi.org/10.1016/j.apgeochem.2015.02.008.","productDescription":"14 p.","startPage":"3","endPage":"16","ipdsId":"IP-063646","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5980419ae4b0a38ca278933e","contributors":{"authors":[{"text":"Nordstrom, D. Kirk 0000-0003-3283-5136 dkn@usgs.gov","orcid":"https://orcid.org/0000-0003-3283-5136","contributorId":749,"corporation":false,"usgs":true,"family":"Nordstrom","given":"D.","email":"dkn@usgs.gov","middleInitial":"Kirk","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":706844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blowes, D.W","contributorId":195353,"corporation":false,"usgs":false,"family":"Blowes","given":"D.W","affiliations":[],"preferred":false,"id":706845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ptacek, C.J.","contributorId":195354,"corporation":false,"usgs":false,"family":"Ptacek","given":"C.J.","email":"","affiliations":[],"preferred":false,"id":706846,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70155017,"text":"ofr20151131 - 2015 - Archiving California’s historical duck nesting data","interactions":[],"lastModifiedDate":"2017-07-01T17:16:02","indexId":"ofr20151131","displayToPublicDate":"2015-07-14T19:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1131","title":"Archiving California’s historical duck nesting data","docAbstract":"The U.S. Geological Survey (USGS), in partnership with the California Waterfowl Association (CWA) and other organizations, have compiled large datasets on the nesting ecology and management of dabbling ducks and associated upland nesting birds (Northern Harriers [Circus cyaneus], Short-eared Owls [Asio flammeus], Ring-necked Pheasants [Phasianus colchicus], and American Bitterns [Botaurus lentiginosus]) throughout California on Federal Refuges, State Wildlife Areas, and private lands, some participating in State and Federal habitat programs. These datasets encompass several long-term monitoring programs at multiple sites throughout California, and include data from more than 26,000 nests and span nearly 30 years.
\nThese historical datasets represent some of the longest term datasets on nesting ducks in North America, if not the world. They are extremely valuable for ongoing waterfowl management and habitat conservation efforts in California, as well as throughout the world. However, without organization and electronic access, these data are an untapped resource and are not being used to the full extent possible. Prior to this project, these datasets were scattered among various agencies and organizations, and original paper nest cards were being stored in cardboard boxes in attics and storage containers that were not suitable for long-term archival storage. In addition, most of these data had not been entered into a computerized database and thus were at high risk for permanent data loss.
\nTo protect this irreplaceable dataset, we submitted a series of proposals to obtain funds to complete this data archival project over the past 5 years. The Central Valley Joint Venture, USGS Data Rescue Program, and USGS Ecosystems Mission Area funded this data archival project. In addition, we leveraged other USGS projects on nesting shorebirds, songbirds, and seabirds to use further resources to more fully develop the nest database structure for use on nesting waterfowl. Specifically, this large dataset on ducks was archived by USGS, but the dataset is owned and managed by a consortium of organizations. Therefore, any access and use of this data must occur through the principal investigators, who contributed data and resources to this archival project, as detailed in section, “Data Availability.”
\nWith the conclusion of this project, most duck nest data have been entered, but all nest-captured hen data and other breeding waterfowl data that were outside the scope of this project have still not been entered and electronically archived. Maintaining an up-to-date archive will require additional resources to archive and enter the new duck nest data each year in an iterative process. Further, data proofing should be conducted whenever possible, and also should be considered an iterative process as there was sometimes missing data that could not be filled in without more direct knowledge of specific projects. Despite these disclaimers, this duck data archive represents a massive and useful dataset to inform future research and management questions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151131","collaboration":"Prepared in cooperation with the California Waterfowl Association, University of California-Davis, and U.S. Fish and Wildlife Service","usgsCitation":"Ackerman, J.T., Herzog, M.P., Brady, C., Eadie, J.M., and Yarris, G.S., 2015, Archiving California’s historical duck nesting data: U.S. Geological Survey Open-File Report 2015-1131, 26 p., https://dx.doi.org/10.3133/ofr20151131.","productDescription":"vi, 26 p.; Appendix","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066560","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":305718,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1131/ofr20151131.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1131 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\"}}]}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
http://werc.usgs.gov/
As part of the U.S. Geological Survey’s Groundwater Resources Program study of the Appalachian Plateaus aquifers, annual and average estimates of water-budget components based on hydrograph separation and precipitation data from parameter-elevation regressions on independent slopes model (PRISM) were determined at 849 continuous-record streamflow-gaging stations from Mississippi to New York and covered the period of 1900 to 2011. Only complete calendar years (January to December) of streamflow record at each gage were used to determine estimates of base flow, which is that part of streamflow attributed to groundwater discharge; such estimates can serve as a proxy for annual recharge. For each year, estimates of annual base flow, runoff, and base-flow index were determined using computer programs—PART, HYSEP, and BFI—that have automated the separation procedures. These streamflow-hydrograph analysis methods are provided with version 1.0 of the U.S. Geological Survey Groundwater Toolbox, which is a new program that provides graphing, mapping, and analysis capabilities in a Windows environment. Annual values of precipitation were estimated by calculating the average of cell values intercepted by basin boundaries where previously defined in the GAGES–II dataset. Estimates of annual evapotranspiration were then calculated from the difference between precipitation and streamflow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds944","collaboration":"Groundwater Resources Program","usgsCitation":"Nelms, D.L., Messinger, Terence, and McCoy, K.J., 2015, Annual and average estimates of water-budget components based on hydrograph separation and PRISM precipitation for gaged basins in the Appalachian Plateaus Region, 1900–2011: U.S. Geological Survey Data Series 944, 10 p., https://dx.doi.org/10.3133/ds944.","productDescription":"Report: iv, 10 p.; 3 Appendices; Database; Metadata","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060622","costCenters":[{"id":614,"text":"Virginia Water Science 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KB","linkFileType":{"id":3,"text":"xlsx"},"description":"List of streamflow-gaging stations in the Appalachian Plateaus region used to estimate annual water-budget components based on hydrograph separation and PRISM precipitation, 1900-2011"},{"id":305626,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0944/ds944_appendix2.xlsx","text":"Appendix 2","size":"6.32 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"Annual estimates of water-budget components based on hydrograph separation and PRISM precipitation for gaged basins in the Appalachian Plateaus region, 1900-2011"},{"id":305627,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0944/ds944_appendix3.xlsx","text":"Appendix 3","size":"193 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Average estimates for the period of analysis of water-budget compo-nents based on hydrograph separation and PRISM precipitation for gaged basins in the Appalachian Plateaus region, 1900–2011"},{"id":305628,"rank":8,"type":{"id":9,"text":"Database"},"url":"https://water.usgs.gov/GIS/dsdl/HydrographSeparation_PMAS_DS944_mdb.zip","text":"Geodatabase","linkFileType":{"id":6,"text":"zip"},"description":"HydrographSeparation_PMAS_DS944"},{"id":305623,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0944/coverthb.jpg"}],"country":"United States","otherGeospatial":"Appalachian Plateaus Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.41796875,\n 32.175612478499325\n ],\n [\n -86.923828125,\n 31.690781806136822\n ],\n [\n -85.62744140625,\n 31.952162238024975\n ],\n [\n -85.2978515625,\n 33.50475906922606\n ],\n [\n -85.01220703125,\n 34.161818161230386\n ],\n [\n -84.83642578125,\n 34.74161249883172\n ],\n [\n -84.638671875,\n 35.0120020431607\n ],\n [\n -84.70458984375,\n 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Richmond, VA 23228
http://va.water.usgs.gov
In cooperation with the Bureau of Land Management, groundwater levels in wells located in the northern Green River Basin in Wyoming, an area of ongoing energy development, were measured by the U.S. Geological Survey from 2010 to 2014. The wells were completed in the uppermost aquifers of the Green River Basin lower Tertiary aquifer system, which is a complex regional aquifer system that provides water to most wells in the area. Except for near perennial streams, groundwater-level altitudes in most aquifers generally decreased with increasing depth, indicating a general downward potential for groundwater movement in the study area. Drilled depth of the wells was observed as a useful indicator of depth to groundwater such that deeper wells typically had a greater depth to groundwater. Comparison of a subset of wells included in this study that had historical groundwater levels that were measured during the 1960s and 1970s and again between 2012 and 2014 indicated that, overall, most of the wells showed a net decline in groundwater levels.
\nThe groundwater-level measurements were used to construct a generalized potentiometric-surface map of the Green River Basin lower Tertiary aquifer system. Groundwater-level altitudes measured in nonflowing and flowing wells used to construct the potentiometric-surface map ranged from 6,451 to 7,307 feet (excluding four unmeasured flowing wells used for contour construction purposes). The potentiometric-surface map indicates that groundwater in the study area generally moves from north to south, but this pattern of flow is altered locally by groundwater divides, groundwater discharge to the Green River, and possibly to a tributary river (Big Sandy River) and two reservoirs (Fontenelle and Big Sandy Reservoirs).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155090","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Bartos, T.T., Hallberg, L.L., and Eddy-Miller, C.A., 2015, Hydrogeology, groundwater levels, and generalized potentiometric-surface map of the Green River Basin lower Tertiary aquifer system, 2010–14, in the northern\nGreen River structural basin, Wyoming: U.S. Geological Survey Scientific Investigations Report 2015–5090, 33 p., https://dx.doi.org/10.3133/sir20155090.","productDescription":"Report: v, 33p.; 1 Plate: 11.0 x 17.0 inches","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-062549","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":305662,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5090/coverthb.jpg"},{"id":305663,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5090/sir20155090.pdf","text":"Report","size":"3.81 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5090"},{"id":305664,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2015/5090/downloads/sir20155090_figure10.pdf","text":"Figure 10","size":"349 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Generalized potentiometric surface of the Green River Basin lower Tertiary aquifer system, 2010-14, northern Green River structural basin, Wyoming"}],"country":"United States","state":"Wyoming","otherGeospatial":"Green River structural basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.335693359375,\n 41.6770148220322\n ],\n [\n -110.335693359375,\n 42.35448465106744\n ],\n [\n -109.2645263671875,\n 42.35448465106744\n ],\n [\n -109.2645263671875,\n 41.6770148220322\n ],\n [\n -110.335693359375,\n 41.6770148220322\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
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http://wy-mt.water.usgs.gov/
The primary goal of this research project was to evaluate the response of Moapa dace (Moapa coriacea) to the potential effects of changes in the amount of available habitat due to human influences such as ground water pumping, barriers to movement, and extirpation of Moapa dace from the mainstem Muddy River. To understand how these factors affect Moapa dace populations and to provide a tool to guide recovery actions, we developed a stochastic model to simulate Moapa dace population dynamics. Specifically, we developed an individual based model (IBM) to incorporate the critical components that drive Moapa dace population dynamics. Our model is composed of several interlinked submodels that describe changes in Moapa dace habitat as translated into carrying capacity, the influence of carrying capacity on demographic rates of dace, and the consequent effect on equilibrium population sizes. The model is spatially explicit and represents the stream network as eight discrete stream segments. The model operates at a monthly time step to incorporate seasonally varying reproduction. Growth rates of individuals vary among stream segments, with growth rates increasing along a headwater to mainstem gradient. Movement and survival of individuals are driven by density-dependent relationships that are influenced by the carrying capacity of each stream segment.
\nFirst, we calibrated the model to a historical time series of Moapa dace abundance estimates. The goal of the calibration was to estimate unknown parameters such as larval survival, carrying capacity of the tributary streams harboring the population of Moapa dace upstream of the gabion barrier, and carrying capacity of the mainstem Muddy River and tributaries. Based on historical abundance estimates, we found that the carrying capacity of the mainstem Muddy River was nearly twice the capacity of the tributary streams where Moapa dace have resided for the past 20 years.
\nGiven the calibrated model, we then conducted simulations to assess (1) the effect of altering migration barriers that restrict upstream and downstream movement of dace, and (2) the effect of changes in carrying capacity on equilibrium population sizes. We found that barriers to upstream movement led to extinction of subpopulations upstream of the barriers when initial population sizes were small. The probability of one or more subpopulations going extinct over a 50-year time horizon was >0.80 at initial population sizes of 10 non-larval and 70 larval dace, and was >0.40 at initial population sizes of 50 non-larval and 350 larval dace. The probability of a subpopulation going extinct decreased to zero when the initial population size exceeded 100 non-larval dace. Removal of upstream migration barriers eliminated extinctions of subpopulations, even at low initial population sizes. Compensatory mechanisms such as density-dependent survival and movement acted to buffer against local extinctions because stream segments could be quickly repopulated by dispersal when fish could access all stream segments.
\nProviding access to the mainstem Muddy River through removal of a gabion barrier that restricted upstream and downstream movement increased total population size from about 875 to 3,000 individuals. Additionally, because of higher growth rates of individuals in the mainstem Muddy River, the size structure of the population shifted towards larger individuals with higher fecundity, thereby increasing reproductive capacity of the population.
\nIncreasing or decreasing the total carrying capacity of all stream segments resulted in changes in equilibrium population size that were directly proportional to the change in capacity. However, changes in carrying capacity to some stream segments but not others could result in disproportionate changes in equilibrium population sizes by altering density-dependent movement and survival in the stream network. These simulations show how our IBM can provide a useful management tool for understanding the effect of restoration actions or reintroductions on carrying capacity, and, in turn, how these changes affect Moapa dace abundance. Such tools are critical for devising management strategies to achieve recovery goals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151126","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Perry, R.W., Jones, E.C., and Scoppettone, G.G., 2015, A stochastic population model to evaluate Moapa dace (Moapa coriacea) population growth under alternative management scenarios: U.S. Geological Survey Open-File Report 2015-1126, 46 p., https://dx.doi.org/10.3133/ofr20151126.","productDescription":"iv, 46 p.","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-062968","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":305694,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1126/coverthb.jpg"},{"id":305695,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1126/ofr20151126.pdf","text":"Report","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1126 Report"}],"country":"United States","state":"Nevada","otherGeospatial":"Muddy River System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.52423095703124,\n 36.44448503928196\n ],\n [\n -114.52423095703124,\n 36.65850456897558\n ],\n [\n -114.31686401367188,\n 36.65850456897558\n ],\n [\n -114.31686401367188,\n 36.44448503928196\n ],\n [\n -114.52423095703124,\n 36.44448503928196\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
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http://wfrc.usgs.gov/
Dust deposition onto mountain snow cover in the Upper Colorado River Basin frequently occurs in the spring when wind speeds and dust emission peaks on the nearby Colorado Plateau. Dust loading has increased since the intensive settlement in the western USA in the mid 1880s. The effects of dust-on-snow have been well studied at Senator Beck Basin Study Area (SBBSA) in the San Juan Mountains, CO, the first high-altitude area of contact for predominantly southwesterly winds transporting dust from the southern Colorado Plateau. To capture variability in dust transport from the broader Colorado Plateau and dust deposition across a larger area of the Colorado River water sources, an additional study plot was established in 2009 on Grand Mesa, 150 km to the north of SBBSA in west central, CO. Here, we compare the 4-year (2010–2013) dust source, deposition, and radiative forcing records at Grand Mesa Study Plot (GMSP) and Swamp Angel Study Plot (SASP), SBBSA's subalpine study plot. The study plots have similar site elevations/environments and differ mainly in the amount of dust deposited and ensuing impacts. At SASP, end of year dust concentrations ranged from 0.83 mg g−1 to 4.80 mg g−1, and daily mean spring dust radiative forcing ranged from 50–65 W m−2, advancing melt by 24–49 days. At GMSP, which received 1.0 mg g−1 less dust per season on average, spring radiative forcings of 32–50 W m−2 advanced melt by 15–30 days. Remote sensing imagery showed that observed dust events were frequently associated with dust emission from the southern Colorado Plateau. Dust from these sources generally passed south of GMSP, and back trajectory footprints modelled for observed dust events were commonly more westerly and northerly for GMSP relative to SASP. These factors suggest that although the southern Colorado Plateau contains important dust sources, dust contributions from other dust sources contribute to dust loading in this region, and likely account for the majority of dust loading at GMSP.
","language":"English","publisher":"John Wiley & Sons","publisherLocation":"Chichester, Sussex, England","doi":"10.1002/hyp.10569","usgsCitation":"Skiles, S.M., Painter, T.H., Belnap, J., Holland, L., Reynolds, R.L., Goldstein, H.L., and Lin, J., 2015, Regional variability in dust-on-snow processes and impacts in the Upper Colorado River Basin: Hydrological Processes, v. 29, no. 26, p. 5397-5413, https://doi.org/10.1002/hyp.10569.","productDescription":"27 p.","startPage":"5397","endPage":"5413","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066323","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":308422,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"26","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-14","publicationStatus":"PW","scienceBaseUri":"5603cd58e4b03bc34f544b37","contributors":{"authors":[{"text":"Skiles, S. McKenzie","contributorId":147878,"corporation":false,"usgs":false,"family":"Skiles","given":"S.","email":"","middleInitial":"McKenzie","affiliations":[{"id":16952,"text":"University of California- Los Angeles, Joint Intitute for Regional Earth System Science and Engineering","active":true,"usgs":false}],"preferred":false,"id":573098,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Painter, Thomas H.","contributorId":12378,"corporation":false,"usgs":true,"family":"Painter","given":"Thomas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":573099,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":573097,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holland, Lacey","contributorId":147879,"corporation":false,"usgs":false,"family":"Holland","given":"Lacey","email":"","affiliations":[{"id":16953,"text":"University of Utah, Atmospheric Sciences","active":true,"usgs":false}],"preferred":false,"id":573100,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reynolds, Richard L. 0000-0002-4572-2942 rreynolds@usgs.gov","orcid":"https://orcid.org/0000-0002-4572-2942","contributorId":147880,"corporation":false,"usgs":true,"family":"Reynolds","given":"Richard","email":"rreynolds@usgs.gov","middleInitial":"L.","affiliations":[{"id":271,"text":"Federal Center","active":false,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":573101,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Goldstein, Harland L. 0000-0002-6092-8818 hgoldstein@usgs.gov","orcid":"https://orcid.org/0000-0002-6092-8818","contributorId":147881,"corporation":false,"usgs":true,"family":"Goldstein","given":"Harland","email":"hgoldstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":573102,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lin, J.","contributorId":33065,"corporation":false,"usgs":true,"family":"Lin","given":"J.","email":"","affiliations":[],"preferred":false,"id":573103,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70154740,"text":"ofr20151123 - 2015 - User’s guide to the North Pacific Pelagic Seabird Database 2.0","interactions":[],"lastModifiedDate":"2016-08-22T15:19:27","indexId":"ofr20151123","displayToPublicDate":"2015-07-13T16:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1123","title":"User’s guide to the North Pacific Pelagic Seabird Database 2.0","docAbstract":"The North Pacific Pelagic Seabird Database (NPPSD) was created in 2005 to consolidate data on the oceanic distribution of marine bird species in the North Pacific. Most of these data were collected on surveys by counting species within defined areas and at known locations (that is, on strip transects). The NPPSD also contains observations of other bird species and marine mammals. The original NPPSD combined data from 465 surveys conducted between 1973 and 2002, primarily in waters adjacent to Alaska. These surveys included 61,195 sample transects with location, environment, and metadata information, and the data were organized in a flat-file format. In developing NPPSD 2.0, our goals were to add new datasets, to make significant improvements to database functionality and to provide the database online. NPPSD 2.0 includes data from a broader geographic range within the North Pacific, including new observations made offshore of the Russian Federation, Japan, Korea, British Columbia (Canada), Oregon, and California. These data were imported into a relational database, proofed, and structured in a common format. NPPSD 2.0 contains 351,674 samples (transects) collected between 1973 and 2012, representing a total sampled area of 270,259 square kilometers, and extends the time series of samples in some areas—notably the Bering Sea—to four decades. It contains observations of 16,988,138 birds and 235,545 marine mammals and is available on the NPPSD Web site. Supplementary materials include an updated set of standardized taxonomic codes, reference maps that show the spatial and temporal distribution of the survey efforts and a downloadable query tool.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151123","usgsCitation":"Drew, G.S., Piatt, J.F., and Renner, M., 2015, User’s guide to the North Pacific Pelagic Seabird Database 2.0:\nU.S. Geological Survey Open-File Report 2015-1123, 52 p., https://dx.doi.org/10.3133/ofr20151123.","productDescription":"iv, 52 p.","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057923","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":438690,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WQ01T3","text":"USGS data release","linkHelpText":"North Pacific Pelagic Seabird Database (NPPSD)"},{"id":305444,"rank":2,"type":{"id":9,"text":"Database"},"url":"https://dx.doi.org/10.5066/F7WQ01T3","text":"North Pacific Pelagic Seabird Database (NPPSD)","size":"67.4 MB","linkFileType":{"id":6,"text":"zip"},"description":"Database"},{"id":305552,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1123/cover.jpg"},{"id":305443,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1123/ofr20151123.pdf","text":"Report","size":"16.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1123"}],"contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Dr
Anchorage, Alaska 99508-4560
http://alaska.usgs.gov
The quantities of water and hydraulic fracturing proppant required for producing petroleum (oil, gas, and natural gas liquids) from continuous accumulations, and the quantities of water extracted during petroleum production, can be quantitatively assessed using a probabilistic approach. The water and proppant assessment methodology builds on the U.S. Geological Survey methodology for quantitative assessment of undiscovered technically recoverable petroleum resources in continuous accumulations. The U.S. Geological Survey assessment methodology for continuous petroleum accumulations includes fundamental concepts such as geologically defined assessment units, and probabilistic input values including well-drainage area, sweet- and non-sweet-spot areas, and success ratio within the untested area of each assessment unit. In addition to petroleum-related information, required inputs for the water and proppant assessment methodology include probabilistic estimates of per-well water usage for drilling, cementing, and hydraulic-fracture stimulation; the ratio of proppant to water for hydraulic fracturing; the percentage of hydraulic fracturing water that returns to the surface as flowback; and the ratio of produced water to petroleum over the productive life of each well. Water and proppant assessments combine information from recent or current petroleum assessments with water- and proppant-related input values for the assessment unit being studied, using Monte Carlo simulation, to yield probabilistic estimates of the volume of water for drilling, cementing, and hydraulic fracture stimulation; the quantity of proppant for hydraulic fracture stimulation; and the volumes of water produced as flowback shortly after well completion, and produced over the life of the well.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151117","usgsCitation":"Haines, S.S., 2015, Methodology for assessing quantities of water and proppant injection, and water production associated with development of continuous petroleum accumulations: U.S. Geological Survey Open-File Report 2015–1117, 18 p., https://dx.doi.org/10.3133/ofr20151117.","productDescription":"Report: iii, 18 p.; 3 Appendices","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-063289","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":305632,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1117/ofr20151117.pdf","text":"Report","size":"1.25","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2015-1117"},{"id":305633,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1117/App_1_Water_Proppant_Assmt_Input_Form_6.8.15.pdf","text":"Appendix 1","size":"77.4 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2015-1117 Appendix 1"},{"id":305634,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1117/App_2_Continuous_water_proppant_6.8.2015.xlsm","text":"Appendix 2","size":"55.7 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OF 2015-1117 Appendix 2"},{"id":305631,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1117/coverthb.jpg"},{"id":305635,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1117/App_4_CORE cover letter.pdf","text":"Appendix 4","size":"119 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2015-1117 Appendix 4"}],"contact":"Director, Central Energy Science Center
U.S. Geological Survey
P.O. Box 25046
Denver, CO 80225
http://energy.usgs.gov/
The Ozark aquifer is the largest aquifer, both in area of outcrop and thickness, and the most important source of freshwater in the Ozark Plateaus physiographic province, supplying water to northern Arkansas, southeastern Kansas, southern Missouri, and northeastern Oklahoma. The study area includes 16 Arkansas counties lying completely or partially within the Ozark Plateaus of the Interior Highlands major physiographic division. The U.S. Geological Survey, in cooperation with the Arkansas Natural Resources Commission and the Arkansas Geological Survey, conducted a study of water levels in the Ozark aquifer within Arkansas. This report presents a potentiometric-surface map of the Ozark aquifer within the Ozark Plateaus of northern Arkansas, representing water-level conditions for the early spring of 2013 and selected water-level hydrographs.
\nThe Ozark aquifer in Arkansas is composed of dolomites, limestones, sandstones, and shales of Late Cambrian to Middle Devonian age and ranges in thickness from approximately 1,100 feet (ft) in northwestern Arkansas to more than 4,000 ft in the west-central part of Arkansas. Most wells completed in the aquifer yield between 50 and 100 gallons per minute (gal/min), although some wells may yield as much as 600 gal/min.
\nWater-level measurements were made in wells completed in the Ozark aquifer from February to May 2013. Hydrographs were constructed for nine wells that have water-level measurements with a minimum 20-year period of record.
\nWater-level altitudes in wells used to construct the potentiometric-surface map range from about 1,159 ft to 313 ft above National Geodetic Vertical Datum of 1929 (NGVD 29). The highest water-level altitudes occur in Carroll and Washington Counties while water-level altitudes of less than 400 ft above NGVD 29 are mapped along the eastern and southeastern part of the study area in Independence, Lawrence, Randolph, and Sharp Counties. The lowest water level of 313 ft above NGVD 29 was measured in southwestern Randolph County.
\nThe direction of groundwater flow generally is affected by local topography, flowing from high altitudes toward stream valleys. In southern Baxter, eastern Fulton, Independence, eastern Izard, Lawrence, Randolph, and Sharp Counties, the groundwater flow is generally to the south and southeast. In western Fulton and Izard Counties, the groundwater flow is generally to the southwest. In Boone, Marion, Newton, Searcy, and Stone Counties, the groundwater flow is generally to the east and northeast. In eastern Benton, Carroll, Madison, and eastern Washington Counties, the groundwater flow is generally to the north and northeast. In western Benton and western Washington Counties, the groundwater flow is generally to the west and northwest.
\nThe general level and shape of the potentiometric surface has changed little since predevelopment. A comparison of the predevelopment potentiometric surface and the 2007, 2010, and 2013 potentiometric surfaces indicate general agreement between the mapped surfaces with the exception of parts of Benton, Boone, Marion, and Washington Counties. In Boone and northern Marion Counties in 2013, water levels have declined when compared to the predevelopment potentiometric surface, although the direction of flow is still to the northeast and north. In southern Marion County, water levels have declined when compared to the predevelopment, 2007, and 2010 potentiometric surfaces, although the direction of flow is towards and along the stream valleys. In western Benton and northwestern Washington Counties, water levels are similar when compared to the predevelopment potentiometric surface, and the direction of flow is to the west and northwest, similar to the predevelopment direction of flow. The mapped 2007 and 2010 potentiometric surfaces are very different from the mapped 2013 potentiometric surface in western Benton and northwestern Washington Counties. The mapped 2013 potentiometric surface in western Benton and northwestern Washington Counties follows the contours of the top of the formation, similar to the predevelopment potentiometric surface. Since 1975, water use in the Ozark aquifer has declined 45 percent, while water levels in Benton, Boone, Marion, and Washington Counties continue to decline.
\nNine hydrographs were selected as representative of the water-level conditions in their respective counties. Wells in Fulton, Izard, and Newton Counties (station names 20N08W27ABD1, 18N09W15BCB1, and 16N21W34ABC1, respectively) have water levels that are within the usual range of values for their respective counties. Wells in Boone, Marion, and Washington Counties (station names 18N19W19BCC1, 19N15W20ACC1, and 16N32W09ABD1, respectively) have water levels that have recently declined or are declining for the period of record. Wells in Benton, Carroll, and Sharp Counties (station names 19N29W07DAA1, 21N26W17BCC1, and 15N05W06DDD1, respectively) have water levels that have been rising recently.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155088","collaboration":"Prepared in cooperation with the Arkansas Natural Resources Commission and the Arkansas Geological Survey","usgsCitation":"Schrader, T.P., 2015, Water levels of the Ozark aquifer in northern Arkansas, 2013: U.S. Geological Survey Scientific Investigations Report 2015–5088, 17 p., 1 pl., https://dx.doi.org/10.3133/sir20155088.","productDescription":"Report: iv, 17 p.; 1 Plate: 17.0 x 11.0 inches","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059919","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":305590,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2015/5088/pdf/sir20155088-pl1.pdf","text":"Plate","size":"628 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5088 Plate"},{"id":305588,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5088/coverthb.jpg"},{"id":305589,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5088/pdf/sir20155088.pdf","text":"Report","size":"971 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5088"}],"country":"United States","state":"Arkansas","otherGeospatial":"Ozark Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.625244140625,\n 36.500805317604794\n ],\n [\n -90.72509765625,\n 36.474306755095206\n ],\n [\n -90.670166015625,\n 36.19995805932895\n ],\n [\n -90.7470703125,\n 36.06686213257888\n ],\n [\n -91.131591796875,\n 35.93354064249312\n ],\n [\n -91.1865234375,\n 35.755428369259626\n ],\n [\n -91.49414062499999,\n 35.639441068973916\n ],\n [\n -91.73583984374999,\n 35.7286770448517\n ],\n [\n -91.8017578125,\n 35.89795019335754\n ],\n [\n -94.537353515625,\n 35.79999392988527\n ],\n [\n -94.625244140625,\n 36.500805317604794\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
401 Hardin Road
Little Rock, Arkansas 72211-3528
http://ar.water.usgs.gov/
The relative merits of model complexity and types of observations employed in model calibration are compared. An existing groundwater flow model coupled with an advective transport simulation of the Salt Lake Valley, Utah (USA), is adapted for advective transport, and effective porosity is adjusted until simulated tritium concentrations match concentrations in samples from wells. Two calibration approaches are used: a “complex” highly parameterized porosity field and a “simple” parsimonious model of porosity distribution. The use of an atmospheric tracer (tritium in this case) and apparent ages (from tritium/helium) in model calibration also are discussed. Of the models tested, the complex model (with tritium concentrations and tritium/helium apparent ages) performs best. Although tritium breakthrough curves simulated by complex and simple models are very generally similar, and there is value in the simple model, the complex model is supported by a more realistic porosity distribution and a greater number of estimable parameters. Culling the best quality data did not lead to better calibration, possibly because of processes and aquifer characteristics that are not simulated. Despite many factors that contribute to shortcomings of both the models and the data, useful information is obtained from all the models evaluated. Although any particular prediction of tritium breakthrough may have large errors, overall, the models mimic observed trends.
","language":"English","publisher":"Springer","publisherLocation":"Berlin","doi":"10.1007/s10040-015-1289-3","usgsCitation":"Starn, J., Bagtzoglou, A., and Green, C.T., 2015, The effects of numerical-model complexity and observation type on estimated porosity values: Hydrogeology Journal, v. 23, no. 6, p. 1121-1128, https://doi.org/10.1007/s10040-015-1289-3.","productDescription":"8 p.","startPage":"1121","endPage":"1128","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059357","costCenters":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"links":[{"id":471943,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-015-1289-3","text":"Publisher Index Page"},{"id":314146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Salt Lake Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.5,\n 40\n ],\n [\n -112.5,\n 41\n ],\n [\n -112,\n 41\n ],\n [\n -112,\n 40\n ],\n [\n -112.5,\n 40\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","issue":"6","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-12","publicationStatus":"PW","scienceBaseUri":"5694e066e4b039675d005e9f","contributors":{"authors":[{"text":"Starn, Jeffrey jjstarn@usgs.gov","contributorId":149231,"corporation":false,"usgs":true,"family":"Starn","given":"Jeffrey","email":"jjstarn@usgs.gov","affiliations":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"preferred":true,"id":588090,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bagtzoglou, Amvrossios C.","contributorId":30146,"corporation":false,"usgs":true,"family":"Bagtzoglou","given":"Amvrossios C.","affiliations":[],"preferred":false,"id":588092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Green, Christopher T. 0000-0002-6480-8194 ctgreen@usgs.gov","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":1343,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"ctgreen@usgs.gov","middleInitial":"T.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":588091,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70148091,"text":"tm4C4 - 2015 - Design, analysis, and interpretation of field quality-control data for water-sampling projects","interactions":[],"lastModifiedDate":"2021-05-27T13:58:28.962369","indexId":"tm4C4","displayToPublicDate":"2015-07-10T16:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"4-C4","title":"Design, analysis, and interpretation of field quality-control data for water-sampling projects","docAbstract":"The process of obtaining and analyzing water samples from the environment includes a number of steps that can affect the reported result. The equipment used to collect and filter samples, the bottles used for specific subsamples, any added preservatives, sample storage in the field, and shipment to the laboratory have the potential to affect how accurately samples represent the environment from which they were collected. During the early 1990s, the U.S. Geological Survey implemented policies to include the routine collection of quality-control samples in order to evaluate these effects and to ensure that water-quality data were adequately representing environmental conditions. Since that time, the U.S. Geological Survey Office of Water Quality has provided training in how to design effective field quality-control sampling programs and how to evaluate the resultant quality-control data. This report documents that training material and provides a reference for methods used to analyze quality-control data.
\nQuality-control data are those generated from the collection and analysis of quality-control samples, and are used to estimate the magnitude of errors in the process of obtaining environmental data. “Bias” and “variability” are the terms used in this report for the two types of errors in environmental data that are quantified by the data from quality-control samples. Bias is the systematic error inherent in a method or measurement system. Variability is the random error that occurs in independent measurements. The types of field quality-control samples discussed in this report include blanks, spikes, and replicates. Blanks are samples prepared with water that is intended to be free of measurable constituents that will be analyzed by the laboratory; blanks are used to estimate bias caused by contamination. Spiked samples are modified by addition of specific analytes; spikes are used to determine the performance of analytical methods and to estimate the potential bias due to matrix interference or analyte degradation. Replicate samples are two or more samples that are considered to be essentially identical in composition. Replicates are used to evaluate variability in analytical results. Various sub-types of these quality-control samples are defined and discussed in this report, and guidance is provided for incorporating the proper samples into the design for a project. The concept of inference space is introduced to help determine where and when quality-control samples should be collected as well as which environmental samples are related to a set of quality-control samples. The recommended basic quality-control design incorporates project-specific considerations, such as the objectives and scale of the study, and hydrologic and chemical conditions within the study area.
\nThe report provides extensive information about statistical methods used to analyze quality-control data in order to estimate potential bias and variability in environmental data. These methods include construction of confidence intervals on various statistical measures, such as the mean, percentiles and percentages, and standard deviation. The methods are used to compare quality-control results with the larger set of environmental data in order to determine whether the effects of bias and variability might interfere with interpretation of these data. Examples from published reports are presented to illustrate how the methods are applied, how bias and variability are reported, and how the interpretation of environmental data can be qualified based on the quality-control analysis.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C in Book 4 Hydrologic analysis and interpretation","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/tm4C4","usgsCitation":"Mueller, D.K., Schertz, T.L., Martin, J.D., and Sandstrom, M.W., 2015, Design, analysis, and interpretation of field quality-control data for water-sampling projects: U.S. Geological Survey Techniques and Methods 4-C4, viii, 54 p., https://doi.org/10.3133/tm4C4.","productDescription":"viii, 54 p.","numberOfPages":"65","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056948","costCenters":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"links":[{"id":305661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm4C4.jpg"},{"id":305660,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/04/c04/pdf/tm4c4.pdf","text":"Report","size":"1.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":305622,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/04/c04/"}],"publicComments":"This report is Chapter 4 of Section C in Book 4 Hydrologic analysis and interpretation","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7eee2e4b0bc0bec09edae","contributors":{"authors":[{"text":"Mueller, David K. mueller@usgs.gov","contributorId":1585,"corporation":false,"usgs":true,"family":"Mueller","given":"David","email":"mueller@usgs.gov","middleInitial":"K.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":564508,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schertz, Terry L. tschertz@usgs.gov","contributorId":188,"corporation":false,"usgs":true,"family":"Schertz","given":"Terry","email":"tschertz@usgs.gov","middleInitial":"L.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":564509,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Jeffrey D. 0000-0003-1994-5285 jdmartin@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-5285","contributorId":1066,"corporation":false,"usgs":true,"family":"Martin","given":"Jeffrey","email":"jdmartin@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":564510,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sandstrom, Mark W. 0000-0003-0006-5675 sandstro@usgs.gov","orcid":"https://orcid.org/0000-0003-0006-5675","contributorId":706,"corporation":false,"usgs":true,"family":"Sandstrom","given":"Mark","email":"sandstro@usgs.gov","middleInitial":"W.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":564511,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70154797,"text":"70154797 - 2015 - Rapid water quality change in the Elwha River estuary complex during dam removal","interactions":[],"lastModifiedDate":"2015-09-17T13:42:56","indexId":"70154797","displayToPublicDate":"2015-07-08T14:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Rapid water quality change in the Elwha River estuary complex during dam removal","docAbstract":"Dam removal in the United States is increasing as a result of structural concerns, sedimentation of reservoirs, and declining riverine ecosystem conditions. The removal of the 32 m Elwha and 64 m Glines Canyon dams from the Elwha River in Washington, U.S.A., was the largest dam removal project in North American history. During the 3 yr of dam removal—from September 2011 to August 2014—more than ten million cubic meters of sediment was eroded from the former reservoirs, transported downstream, and deposited throughout the lower river, river delta, and nearshore waters of the Strait of Juan de Fuca. Water quality data collected in the estuary complex at the mouth of the Elwha River document how conditions in the estuary changed as a result of sediment deposition over the 3 yr the dams were removed. Rapid and large-scale changes in estuary conditions—including salinity, depth, and turbidity—occurred 1 yr into the dam removal process. Tidal propagation into the estuary ceased following a large sediment deposition event that began in October 2013, resulting in decreased salinity, and increased depth and turbidity in the estuary complex. These changes have persisted in the system through dam removal, significantly altering the structure and functioning of the Elwha River estuary ecosystem.
","language":"English","publisher":"Wiley","doi":"10.1002/lno.10129","usgsCitation":"Foley, M.M., Duda, J.J., Beirne, M., Paradis, R., Ritchie, A., and Warrick, J., 2015, Rapid water quality change in the Elwha River estuary complex during dam removal: Limnology and Oceanography, v. 60, no. 5, p. 1719-1732, https://doi.org/10.1002/lno.10129.","productDescription":"14 p.","startPage":"1719","endPage":"1732","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065467","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471946,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10129","text":"Publisher Index Page"},{"id":305620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.61679077148438,\n 47.96050238891509\n ],\n [\n -123.61679077148438,\n 48.15600899174947\n ],\n [\n -123.475341796875,\n 48.15600899174947\n ],\n [\n -123.475341796875,\n 47.96050238891509\n ],\n [\n -123.61679077148438,\n 47.96050238891509\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"60","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-06","publicationStatus":"PW","scienceBaseUri":"559e3ba5e4b0b94a64018f51","contributors":{"authors":[{"text":"Foley, Melissa M. 0000-0002-5832-6404 mfoley@usgs.gov","orcid":"https://orcid.org/0000-0002-5832-6404","contributorId":4861,"corporation":false,"usgs":true,"family":"Foley","given":"Melissa","email":"mfoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":564188,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":145486,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":564189,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beirne, Matthew M.","contributorId":66984,"corporation":false,"usgs":true,"family":"Beirne","given":"Matthew M.","affiliations":[],"preferred":false,"id":564190,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paradis, Rebecca","contributorId":145488,"corporation":false,"usgs":false,"family":"Paradis","given":"Rebecca","affiliations":[{"id":13135,"text":"Lower Elwha Klallam Tribe, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":564191,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ritchie, Andrew","contributorId":35443,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew","affiliations":[],"preferred":false,"id":564192,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":139314,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan A.","email":"jwarrick@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":564193,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70148555,"text":"sim3333 - 2015 - Geologic and hydrostratigraphic map of the Anhalt, Fischer, and Spring Branch 7.5-minute quadrangles, Blanco, Comal, and Kendall Counties, Texas","interactions":[],"lastModifiedDate":"2016-08-16T15:52:48","indexId":"sim3333","displayToPublicDate":"2015-07-08T10:30:00","publicationYear":"2015","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":"3333","title":"Geologic and hydrostratigraphic map of the Anhalt, Fischer, and Spring Branch 7.5-minute quadrangles, Blanco, Comal, and Kendall Counties, Texas","docAbstract":"This report describes the geology and hydrostratigraphy of the Edwards and Trinity Groups in the Anhalt, Fischer, and Spring Branch 7.5-minute quadrangles, Blanco, Comal, and Kendall Counties, Texas. The hydrostratigraphy was defined based on variations in the amount and type of porosity of each lithostratigraphic unit, which varies depending on the unit’s original depositional environment, lithology, structural history, and diagenesis.
\nRocks exposed in the study area are of the Lower Cretaceous Trinity Group and lower part of the Kainer Formation of the Lower Cretaceous Edwards Group. The mapped outcrops in the study area are the Pearsall Formation and Glen Rose Limestone of the Trinity Group. The Pearsall Formation consists of, in ascending order: the Hammett Shale, Cow Creek Limestone, and Hensell Sand Member. The Glen Rose Limestone is composed of the informal lower and upper members. In the study area the Edwards Group consists only of the informal basal nodular member of the Kainer Formation. The faulting and fracturing in the study area are part of the Miocene-age Balcones fault zone, an extensional system of faults that generally trends southwest to northeast in south-central Texas. An igneous dike, containing aphanitic texture, cuts through part of the Anhalt quadrangle near the confluence of Honey Creek and the Guadalupe River. The dike penetrates the Cow Creek Limestone Member and the lower part of the Hensell Sand Member outcropping at three locations.
\nThe hydrostratigraphic units of the Edwards and Trinity aquifers have been mapped and described herein using a classification system developed by Choquette and Pray (1970), which is based on porosity types being fabric or not-fabric selective. The naming of hydrostratigraphic units is also based on preexisting names and topographic or historical features that occur in outcrop. The only hydrostratigraphic unit of the Edwards aquifer present in the study area is VIII hydrostratigraphic unit. The mapped hydrostratigraphic units of the upper Trinity aquifer are, from top to bottom: the cavernous, Camp Bullis, upper evaporite, fossiliferous, and lower evaporite and they are interval equivalent to the upper member of the Glen Rose Limestone. The middle Trinity aquifer (interval equivalent to the lower member of the Glen Rose Limestone) contains, from top to bottom: the Bulverde, Little Blanco, Twin Sisters, Doeppenschmidt, Rust, and Honey Creek hydrostratigraphic units. The lower part of the middle Trinity aquifer is formed by the Hensell, Cow Creek, and Hammett hydrostratigraphic units which are interval equivalent to the Hensell Sand Member, the Cow Creek Limestone, and the Hammett Shale Member, respectively, of the Pearsall Formation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3333","usgsCitation":"Clark, A.K., and Morris, R.R., 2015, Geologic and hydrostratigraphic map of the Anhalt, Fischer, and Spring Branch 7.5-minute quadrangles, Blanco, Comal, and Kendall Counties, Texas: U.S. Geological Survey Scientific Investigations Map 3333, Pamphlet: iv, 12 p.; Map: 50 x 20 inches; Downloads Directory, https://doi.org/10.3133/sim3333.","productDescription":"Pamphlet: iv, 12 p.; Map: 50 x 20 inches; Downloads Directory","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059768","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":305612,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3333.jpg"},{"id":305610,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3333/pdf/sim3333_map.pdf","text":"Map and Summary Table","size":"85.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Map"},{"id":305609,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3333/pdf/sim3333_pamphlet.pdf","text":"Pamphlet","size":"8.06 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Pamphlet"},{"id":305587,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3333/"},{"id":305611,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3333/downloads/","text":"Downloads Directory","linkHelpText":"Contains: geospatial database. Refer to the Readme and Metadata files for more information."}],"country":"United States","state":"Texas","county":"Blanco County, Comal County, Kendall County","otherGeospatial":"Anhalt, Fischer, Spring Branch quadrangles","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.37570190429688,\n 29.869228848968312\n ],\n [\n -98.37570190429688,\n 29.983486718474694\n ],\n [\n -98.24798583984375,\n 29.983486718474694\n ],\n [\n -98.24798583984375,\n 29.869228848968312\n ],\n [\n -98.37570190429688,\n 29.869228848968312\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.5089111328125,\n 29.869228848968312\n ],\n [\n -98.5089111328125,\n 29.983486718474694\n ],\n [\n -98.37844848632811,\n 29.983486718474694\n ],\n [\n -98.37844848632811,\n 29.869228848968312\n ],\n [\n -98.5089111328125,\n 29.869228848968312\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.51028442382811,\n 29.756032197482945\n ],\n [\n -98.51028442382811,\n 29.868037972862645\n ],\n [\n -98.37570190429688,\n 29.868037972862645\n ],\n [\n -98.37570190429688,\n 29.756032197482945\n ],\n [\n -98.51028442382811,\n 29.756032197482945\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a5b8bee4b0ebae89b788d3","contributors":{"authors":[{"text":"Clark, Allan K. 0000-0003-0099-1521 akclark@usgs.gov","orcid":"https://orcid.org/0000-0003-0099-1521","contributorId":1279,"corporation":false,"usgs":true,"family":"Clark","given":"Allan","email":"akclark@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":564202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morris, Robert R.","contributorId":141163,"corporation":false,"usgs":false,"family":"Morris","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":13701,"text":"Volunteer for Science, USGS","active":true,"usgs":false}],"preferred":false,"id":564203,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70171042,"text":"70171042 - 2015 - Etheostoma brevirostrum (Holiday Darter)","interactions":[],"lastModifiedDate":"2018-11-20T15:39:57","indexId":"70171042","displayToPublicDate":"2015-07-08T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"displayTitle":"Etheostoma brevirostrum (Holiday Darter)","title":"Etheostoma brevirostrum (Holiday Darter)","docAbstract":"The life history of the Holiday Darter is incompletely known. Only reproductive behavior (Johnston and Shute 1997; Anderson 2009), habitat use, and spawning seasons (Anderson 2009) have been studied. However, based on similarity of life history attributes among snubnose darters (Carney and Burr 1989; Johnston and Haag 1996; Khudamrongsawat et al. 2005), the Holiday darter probably lives 3+ years and matures in the first year. It is likely a benthic omnivore, feeding primarily on chironomid (midge) larvae and other common orders of aquatic insects and occasional microcrustaceans. Spawning occurs from late March to early June, with most activity occurring in April. Based on four females from the Amicalola Creek system, fecundity ranged from 50 to 150 mature eggs, egg sizes ranged from 1.2mm to 1.6mm diameter. The Holiday Darter is an “egg attacher” (sensu Page and Swofford 1984). A spawning female is courted by multiple males, but a dominant (alpha) male aggressively rebuts encroaching males and defends a “roving territory” of the receptive female. The alpha male is the principal spawning partner although satellite males often rush a spawning pair. The receptive female slowly swims along the stream bottom, frequently stopping, apparently to assess substrate attributes, and selects each spawning site where only one or two eggs are spawned. The process is repeated and often covers several meters of stream bottom until the courted female finishes spawning and is abandoned by the alpha male. Water temperatures during spawning in Amicalola Creek and the upper Etowah River ranged 10 to 17° C (Anderson 2009).
","largerWorkTitle":"Freshwater information network: Tennessee Aquarium Conservation Institute","language":"English","publisher":"ICube","usgsCitation":"Burkhead, N.M., 2015, Etheostoma brevirostrum (Holiday Darter), chap. of Freshwater information network: Tennessee Aquarium Conservation Institute, HTML Document.","productDescription":"HTML Document","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-030831","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":325096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Amicalola Creek, Etowah River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.2544937133789,\n 34.30487507190691\n ],\n [\n -84.2544937133789,\n 34.462126502013184\n ],\n [\n -84.122314453125,\n 34.462126502013184\n ],\n [\n -84.122314453125,\n 34.30487507190691\n ],\n [\n -84.2544937133789,\n 34.30487507190691\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"579dcfade4b0589fa1cbd571","contributors":{"authors":[{"text":"Burkhead, Noel M. nburkhead@usgs.gov","contributorId":3030,"corporation":false,"usgs":true,"family":"Burkhead","given":"Noel","email":"nburkhead@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":629663,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70155521,"text":"70155521 - 2015 - Holocene climate variability in Texas, USA: An integration of existing paleoclimate data and modeling with a new, high-resolution speleothem record","interactions":[],"lastModifiedDate":"2015-10-26T14:00:26","indexId":"70155521","displayToPublicDate":"2015-07-07T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Holocene climate variability in Texas, USA: An integration of existing paleoclimate data and modeling with a new, high-resolution speleothem record","docAbstract":"Delineating the climate processes governing precipitation variability in drought-prone Texas is critical for predicting and mitigating climate change effects, and requires the reconstruction of past climate beyond the instrumental record. We synthesize existing paleoclimate proxy data and climate simulations to provide an overview of climate variability in Texas during the Holocene. Conditions became progressively warmer and drier transitioning from the early to mid Holocene, culminating between 7 and 3 ka (thousand years ago), and were more variable during the late Holocene. The timing and relative magnitude of Holocene climate variability, however, is poorly constrained owing to considerable variability among the different records. To help address this, we present a new speleothem (NBJ) reconstruction from a central Texas cave that comprises the highest resolution proxy record to date, spanning the mid to late Holocene. NBJ trace-element concentrations indicate variable moisture conditions with no clear temporal trend. There is a decoupling between NBJ growth rate, trace-element concentrations, and δ18O values, which indicate that (i) the often direct relation between speleothem growth rate and moisture availability is likely complicated by changes in the overlying ecosystem that affect subsurface CO2 production, and (ii) speleothem δ18O variations likely reflect changes in moisture source (i.e., proportion of Pacific-vs. Gulf of Mexico-derived moisture) that appear not to be linked to moisture amount.
","language":"English","publisher":"Pergamon Press","publisherLocation":"New York, NY","doi":"10.1016/j.quascirev.2015.06.023","usgsCitation":"Wong, C., Banner, J., and Musgrove, M., 2015, Holocene climate variability in Texas, USA: An integration of existing paleoclimate data and modeling with a new, high-resolution speleothem record: Quaternary Science Reviews, v. 127, p. 155-173, https://doi.org/10.1016/j.quascirev.2015.06.023.","productDescription":"19 p.","startPage":"155","endPage":"173","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062965","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":306533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.0517578125,\n 36.491973470593685\n ],\n [\n -99.97558593749999,\n 36.50963615733049\n ],\n [\n -99.99755859375,\n 34.66935854524543\n ],\n [\n -99.7119140625,\n 34.415973384481866\n ],\n [\n -99.404296875,\n 34.52466147177172\n ],\n [\n -99.16259765625,\n 34.27083595165\n ],\n [\n -98.525390625,\n 34.10725639663118\n ],\n [\n -98.23974609375,\n 34.21634468843465\n ],\n [\n -96.3720703125,\n 33.96158628979907\n ],\n [\n -95.55908203125,\n 34.052659421375964\n ],\n [\n -94.8779296875,\n 34.03445260967645\n ],\n [\n -94.39453125,\n 33.669496972795535\n ],\n [\n -93.9990234375,\n 33.65120829920497\n ],\n [\n -93.9990234375,\n 31.970803930433096\n ],\n [\n -93.4716796875,\n 31.2221970321032\n ],\n [\n -93.40576171875,\n 30.90222470517144\n ],\n [\n -93.7353515625,\n 30.543338954230222\n ],\n [\n -93.8232421875,\n 29.954934549656144\n ],\n [\n -93.88916015625,\n 29.66896252599253\n ],\n [\n -95.51513671875,\n 28.806173508854776\n ],\n [\n -96.13037109375,\n 28.497660832963472\n ],\n [\n -96.83349609375,\n 28.14950321154457\n ],\n [\n -97.09716796875,\n 27.488781168937997\n ],\n [\n -97.49267578125,\n 27.059125784374068\n ],\n [\n -97.42675781249999,\n 26.509904531413927\n ],\n [\n -97.119140625,\n 25.997549919572112\n ],\n [\n -97.44873046875,\n 25.799891182088334\n ],\n [\n -98.59130859375,\n 26.15543796871355\n ],\n [\n -99.228515625,\n 26.47057302237511\n ],\n [\n -99.84374999999999,\n 27.527758206861886\n ],\n [\n -100.92041015625,\n 29.0945770775118\n ],\n [\n -101.49169921875,\n 29.630771207229\n ],\n [\n -102.3046875,\n 29.783449456820605\n ],\n [\n -102.76611328125,\n 29.516110386062277\n ],\n [\n -103.1396484375,\n 28.844673680771795\n ],\n [\n -104.8974609375,\n 29.726222319395504\n ],\n [\n -104.78759765625,\n 30.088107753367257\n ],\n [\n -105.1171875,\n 30.58117925738696\n ],\n [\n -105.77636718749999,\n 30.996445897426373\n ],\n [\n -106.787109375,\n 31.87755764334002\n ],\n [\n -106.67724609375,\n 32.045332838858506\n ],\n [\n -103.07373046875,\n 31.989441837922904\n ],\n [\n -103.0517578125,\n 36.491973470593685\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"127","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55c9cb34e4b08400b1fdb70e","contributors":{"authors":[{"text":"Wong, Corinne I.","contributorId":36018,"corporation":false,"usgs":true,"family":"Wong","given":"Corinne I.","affiliations":[],"preferred":false,"id":565675,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Banner, Jay L.","contributorId":58200,"corporation":false,"usgs":true,"family":"Banner","given":"Jay L.","affiliations":[],"preferred":false,"id":565676,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Musgrove, MaryLynn 0000-0003-1607-3864 mmusgrov@usgs.gov","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":1316,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"mmusgrov@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":565674,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70156128,"text":"70156128 - 2015 - Didymosphenia geminata in the Upper Esopus Creek: current status, variability, and controlling factors","interactions":[],"lastModifiedDate":"2015-08-17T11:37:54","indexId":"70156128","displayToPublicDate":"2015-07-06T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Didymosphenia geminata in the Upper Esopus Creek: current status, variability, and controlling factors","docAbstract":"In May of 2009, the bloom-forming diatom Didymosphenia geminata was first identified in the Upper Esopus Creek, a key tributary to the New York City water-supply and a popular recreational stream. The Upper Esopus receives supplemental flows from the Shandaken Portal, an underground aqueduct delivering waters from a nearby basin. The presence of D.geminata is a concern for the local economy, water supply, and aquatic ecosystem because nuisance blooms have been linked to degraded stream condition in other regions. Here we ascertain the extent and severity of the D. geminata invasion, determine the impact of supplemental flows from the Portal on D. geminata, and identify potential factors that may limitD. geminata in the watershed. Stream temperature, discharge, and water quality were characterized at select sites and periphyton samples were collected five times at 6 to 20 study sites between 2009 and 2010 to assess standing crop, diatom community structure, and density of D. geminata and all diatoms. Density of D. geminata ranged from 0–12 cells cm-2 at tributary sites, 0–781 cells cm-2 at sites upstream of the Portal, and 0–2,574 cells cm-2 at sites downstream of the Portal. Survey period and Portal (upstream or downstream) each significantly affected D. geminata cell density. In general, D. geminata was most abundant during the November 2009 and June 2010 surveys and at sites immediately downstream of the Portal. We found that D. geminata did not reach nuisance levels or strongly affect the periphyton community. Similarly, companion studies showed that local macroinvertebrate and fish communities were generally unaffected. A number of abiotic factors including variable flows and moderate levels of phosphorous and suspended sediment may limit blooms of D. geminatain this watershed.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0130558","collaboration":"New York State Dept of Environmental Conservation; USGS","usgsCitation":"George, S.D., and Baldigo, B.P., 2015, Didymosphenia geminata in the Upper Esopus Creek: current status, variability, and controlling factors: PLoS ONE, v. 10, no. 8, p. 1-20, https://doi.org/10.1371/journal.pone.0130558.","productDescription":"20 p.","startPage":"1","endPage":"20","numberOfPages":"20","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-043086","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":471950,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0130558","text":"Publisher Index Page"},{"id":306799,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"8","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-06","publicationStatus":"PW","scienceBaseUri":"55d305a9e4b0518e35468ccc","contributors":{"authors":[{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":567894,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":567893,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70154906,"text":"70154906 - 2015 - Potamochoerus porcus (Artiodactyla: Suidae)","interactions":[],"lastModifiedDate":"2015-08-03T10:36:49","indexId":"70154906","displayToPublicDate":"2015-07-06T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2654,"text":"Mammalian Species","active":true,"publicationSubtype":{"id":10}},"title":"Potamochoerus porcus (Artiodactyla: Suidae)","docAbstract":"Potamochoerus porcus (Linnaeus, 1758) is a monotypic suid commonly known as the red river hog. It is 1 of 2 species in the genus Potamochoerus and among the smallest and most plesiomorphic (ancestral) of the 8 African suids. This is the brightest colored wild pig species and is identified by its rufous coat and white dorsal crest; spectacled black-and-white facemask; and elongated, leaf-shaped ears that end in terminally drooping tufts of hair. P. porcus lives in damp forests throughout the rainforest belt of western and central Africa; it never ranges far from thick vegetative cover, soft soils, and water. Although P. porcus is commonly harvested for subsistence and urban bushmeat markets, it is considered of “Least Concern” by the International Union for Conservation of Nature and Natural Resources.
","language":"English","publisher":"American Society of Mammalogists","doi":"10.1093/mspecies/sev002","usgsCitation":"Leslie, D., and Huffman, B.A., 2015, Potamochoerus porcus (Artiodactyla: Suidae): Mammalian Species, v. 47, no. 919, p. 15-31, https://doi.org/10.1093/mspecies/sev002.","productDescription":"17 p.","startPage":"15","endPage":"31","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056332","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":471951,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/mspecies/sev002","text":"Publisher Index Page"},{"id":305856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"919","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-03","publicationStatus":"PW","scienceBaseUri":"55af6d2de4b09a3b01b51aa9","contributors":{"authors":[{"text":"Leslie, David M. Jr. cleslie@usgs.gov","contributorId":145497,"corporation":false,"usgs":true,"family":"Leslie","given":"David M.","suffix":"Jr.","email":"cleslie@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":564336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huffman, Brent A.","contributorId":145760,"corporation":false,"usgs":false,"family":"Huffman","given":"Brent","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":565191,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70154748,"text":"ofr20151124 - 2015 - An evaluation of fish behavior upstream of the water temperature control tower at Cougar Dam, Oregon, using acoustic cameras, 2013","interactions":[],"lastModifiedDate":"2016-01-08T14:45:29","indexId":"ofr20151124","displayToPublicDate":"2015-07-06T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1124","title":"An evaluation of fish behavior upstream of the water temperature control tower at Cougar Dam, Oregon, using acoustic cameras, 2013","docAbstract":"This report describes the initial year of a 2-year study to determine the feasibility of using acoustic cameras to monitor fish movements to help inform decisions about fish passage at Cougar Dam near Springfield, Oregon. Specifically, we used acoustic cameras to measure fish presence, travel speed, and direction adjacent to the water temperature control tower in the forebay of Cougar Dam during the spring (May, June, and July) and fall (September, October, and November) of 2013. Cougar Dam is a high-head flood-control dam, and the water temperature control tower enables depth-specific water withdrawals to facilitate adjustment of water temperatures released downstream of the dam. The acoustic cameras were positioned at the upstream entrance of the tower to monitor free-ranging subyearling and yearling-size juvenile Chinook salmon (Oncorhynchus tshawytscha). Because of the large size discrepancy, we could distinguish juvenile Chinook salmon from their predators, which enabled us to measure predators and prey in areas adjacent to the entrance of the tower. We used linear models to quantify and assess operational and environmental factors—such as time of day, discharge, and water temperature—that may influence juvenile Chinook salmon movements within the beam of the acoustic cameras. Although extensive milling behavior of fish near the structure may have masked directed movement of fish and added unpredictability to fish movement models, the acoustic-camera technology enabled us to ascertain the general behavior of discrete size classes of fish. Fish travel speed, direction of travel, and counts of fish moving toward the water temperature control tower primarily were influenced by the amount of water being discharged through the dam.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151124","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Adams, N.S., Smith, C.D., Plumb, J.M., Hansen, G.S., and Beeman, J.W., 2015, An evaluation of fish behavior upstream of the water temperature control tower at Cougar Dam, Oregon, using acoustic cameras, 2013: U.S. Geological Survey Open-File Report 2015-1124, 62 p., https://dx.doi.org/10.3133/ofr20151124.","productDescription":"x, 62 p.","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063666","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":305440,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1124/coverthb.jpg"},{"id":305441,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1124/ofr20151124.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Oregon","otherGeospatial":"Cougar Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.25345611572266,\n 44.122345529999656\n ],\n [\n -122.25345611572266,\n 44.132942183139654\n ],\n [\n -122.23114013671875,\n 44.132942183139654\n ],\n [\n -122.23114013671875,\n 44.122345529999656\n ],\n [\n -122.25345611572266,\n 44.122345529999656\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov
The east side of the Uncompahgre River Basin has been a known contributor of dissolved selenium to recipient streams. Discharge of groundwater containing dissolved selenium contributes to surface-water selenium concentrations and loads; however, the groundwater system on the east side of the Uncompahgre River Basin is not well characterized. The U.S. Geological Survey, in cooperation with the Colorado Water Conservation Board and the Bureau of Reclamation, has established a groundwater-monitoring network on the east side of the Uncompahgre River Basin. Ten monitoring wells were installed during October and November 2012. This report presents location data, lithologic logs, well-construction diagrams, and well-development information. Understanding the groundwater system will provide managers with an additional metric for evaluating the effectiveness of salinity and selenium control projects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds923","collaboration":"Prepared in cooperation with Colorado Water Conservation Board and the Bureau of Reclamation","usgsCitation":"Thomas, J.C., and Arnold, L.R., 2015, Installation of a groundwater monitoring-well network on the east side of the Uncompahgre River in the Lower Gunnison River Basin, Colorado, 2012: U.S. Geological Survey Data Series 923, 29 p., https://dx.doi.org/10.3133/ds923.","productDescription":"iv, 29 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059394","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":309728,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/ds955","text":"DS 955"},{"id":305498,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0923/pdf/ds923.pdf","text":"Report","size":"17.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 923"},{"id":305497,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0923/coverthb.jpg"},{"id":305608,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/publication/ds923"}],"country":"United States","state":"Colorado","otherGeospatial":"Uncompahgre River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.6154613494873,\n 37.91705002583544\n ],\n [\n -107.6154613494873,\n 37.928153945306555\n ],\n [\n -107.59949684143065,\n 37.928153945306555\n ],\n [\n -107.59949684143065,\n 37.91705002583544\n ],\n [\n -107.6154613494873,\n 37.91705002583544\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225
http://co.water.usgs.gov
This study identifies areas prone to lahars from hydrothermally altered volcanic edifices on a global scale, using visible and near infrared (VNIR) and short wavelength infrared (SWIR) reflectance data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and digital elevation data from the ASTER Global Digital Elevation Model (GDEM) dataset. This is the first study to create a global database of hydrothermally altered volcanoes showing quantitatively compiled alteration maps and potentially affected drainages, as well as drainage-specific maps illustrating modeled lahars and their potential inundation zones. We (1) identified and prioritized 720 volcanoes based on population density surrounding the volcanoes using the Smithsonian Institution Global Volcanism Program database (GVP) and LandScan™ digital population dataset; (2) validated ASTER hydrothermal alteration mapping techniques using Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) and ASTER data for Mount Shasta, California, and Pico de Orizaba (Citlaltépetl), Mexico; (3) mapped and slope-classified hydrothermal alteration using ASTER VNIR-SWIR reflectance data on 100 of the most densely populated volcanoes; (4) delineated drainages using ASTER GDEM data that show potential flow paths of possible lahars for the 100 mapped volcanoes; (5) produced potential alteration-related lahar inundation maps using the LAHARZ GIS code for Iztaccíhuatl, Mexico, and Mount Hood and Mount Shasta in the United States that illustrate areas likely to be affected based on DEM-derived volume estimates of hydrothermally altered rocks and the ~2x uncertainty factor inherent within a statistically-based lahar model; and (6) saved all image and vector data for 3D and 2D display in Google Earth™, ArcGIS® and other graphics display programs. In addition, these data are available from the ASTER Volcano Archive (AVA) for distribution (available at http://ava.jpl.nasa.gov/recent_alteration_zones.php).
\nUsing the GVP and the LandScan™ digital population dataset, 350 of the most densely populated stratovolcanoes were assessed for study. Of the 350 volcanoes, 250 volcanoes were not mapped due to excessive snow, ice, and (or) vegetation. Results from mapping the remaining 100 stratovolcanoes show that 87 contain slopes with hydrothermal alteration, and 49 have hydrothermally altered rocks on steep slopes situated above areas with populations >100 people per km2. Of these, 17 stratovolcanoes exhibit laterally extensive hydrothermal alteration on slopes >35° and cover an area >0.25 km2, which may pose a significant possibility of generating debris flows.
\nThis study was undertaken during 2012–2013 in cooperation with the National Aeronautics and Space Administration (NASA). Since completion of this study, a new lahar modeling program (LAHAR_pz) has been released, which may produce slightly different modeling results from the LAHARZ model used in this study. The maps and data from this study should not be used in place of existing volcano hazard maps published by local authorities. For volcanoes without hazard maps and (or) published lahar-related hazard studies, this work will provide a starting point from which more accurate hazard maps can be produced. This is the first dataset to provide digital maps of altered volcanoes and adjacent watersheds that can be used for assessing volcanic hazards, hydrothermal alteration, and other volcanic processes in future studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155035","usgsCitation":"Mars, J., Hubbard, B.E., Pieri, D., and Linick, J., 2015, Alteration, slope-classified alteration, and potential lahar inundation maps of volcanoes for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Volcano Archive: U.S. Geological Survey Scientific Investigations Report 2015-5035, https://doi.org/10.3133/sir20155035.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-054579","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":305571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155035.gif"},{"id":305570,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5035/pdf/sir2015-5035.pdf","text":"Report","size":"13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":305557,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5035/"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7eef3e4b0bc0bec09ee12","contributors":{"authors":[{"text":"Mars, John C. jmars@usgs.gov","contributorId":127493,"corporation":false,"usgs":true,"family":"Mars","given":"John C.","email":"jmars@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":564125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":564126,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pieri, David","contributorId":139492,"corporation":false,"usgs":false,"family":"Pieri","given":"David","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":564127,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Linick, Justin","contributorId":139493,"corporation":false,"usgs":false,"family":"Linick","given":"Justin","email":"","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":564128,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70143962,"text":"sir20155032 - 2015 - Groundwater quality in Geauga County, Ohio: status, including detection frequency of methane in water wells, 2009, and changes during 1978-2009","interactions":[],"lastModifiedDate":"2015-07-03T11:05:27","indexId":"sir20155032","displayToPublicDate":"2015-07-03T10:00:00","publicationYear":"2015","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":"2015-5032","title":"Groundwater quality in Geauga County, Ohio: status, including detection frequency of methane in water wells, 2009, and changes during 1978-2009","docAbstract":"Domestic wells that are not safeguarded by regular water-quality testing provide drinking water for 79 percent of the residents of Geauga County, in northeastern Ohio. Since 1978, the U.S. Geological Survey (USGS) has worked cooperatively with the Board of Commissioners and Geauga County Planning Commission to monitor the quality of groundwater in four commonly used aquifers in county—the glacial deposits, the Pottsville Formation, the Cuyahoga Group, and the Berea Sandstone. A 33-percent growth in population from 1980 to 2009 increased the potential for humans to influence groundwater resources by withdrawing more groundwater, disposing of more human waste near the land surface, treating an expanded network of township roads with deicing salt, and likely using more solvents, pesticides, and other chemicals on the land surface than were used in preceding decades.
\nTo describe the status of groundwater quality in 2009 and its suitability for drinking, USGS personnel collected samples of water prior to treatment from 16 wells (mostly domestic) during June 9–19. The samples were analyzed for 92 properties and constituents, 41 of which had human-health benchmarks to which analytical results could be compared to evaluate suitability for drinking. Four of these benchmarks were exceeded at the following frequencies: arsenic (2 of 16 wells, 12.5 percent), total coliform bacteria (2 of 16 wells, 12.5 percent), fecal coliform bacteria (1 of 14 wells, 7 percent), and sodium (6 of 16 wells, 38 percent). No domestic wells sampled in 2009 exceeded the health-based benchmark of 300 micrograms per liter (µg/L) for manganese, although 5 of 65 wells (8 percent) sampled since 1978 have. Analyses from domestic wells were augmented with water-quality data from seven public-supply well fields that were obtained from the Ohio Environmental Protection Agency. These public-supply data were typically collected between 2000 and 2010 and represent water samples that were collected prior to treatment or that were treated by a method that does not effectively remove the constituents of interest. Similar to the domestic-well data, these data indicated that some samples from public-supply wells have also exceeded health-based benchmarks for arsenic and sodium, along with occasional exceedances of health-based benchmarks for cadmium and lead. Concentrations of nitrate, pesticides, and volatile organic compounds in ground-water samples from domestic and (or) public-supply wells were either considerably less than the human-health benchmarks for these constituents or were not detected.
\nWater-quality data collected in 2009 were also compared to aesthetically based benchmarks developed by the U.S. Environmental Protection Agency, called Secondary Maximum Contaminant Levels (SMCLs). Iron and manganese most frequently exceeded SMCLs (in samples from 10 of 16 domestic wells and in untreated water from 3 of 4 public-supply well fields).
\nTo evaluate the frequency of methane detection in water wells in the county, the USGS sampled 16 wells across the county and screened the samples for combustible gas within the headspace (the air above the water in a closed container). Water from three (19 percent) of the wells contained detectable combustible gas (0.10 to 0.40 percent by volume). All three detections were from wells tapping the Cuyahoga Group or the Berea Sandstone, and all detections were less than the lower explosive limit of 5 percent by volume—the concentration at which methane in air can be flammable if an ignition source is present. Analyses of dissolved gas composition in water from these three wells showed methane concentrations ranging from 0.007 to 1.8 milligrams per liter (mg/L).
\nThe primary effect of human activities on groundwater quality found during this study is the input of salinity, or chloride, near land surface. On the basis of ratios of chloride to bromide, the main sources of chloride are road salt and septic leachate rather than oil-field brines (either spilled at land surface or sprayed on roads for dust control). The correlation of chloride concentration to distance of well from road for 31 wells in the county sampled by the U.S. Geological Survey in 1999 suggests that road salt is the dominant source of chloride.
\nThe majority of constituents exceeding health-based and aesthetically based benchmarks in groundwater were those that are naturally present in aquifer rocks and sediments rather than constituents introduced by human activities. Concentrations of such natural contaminants are controlled by geochemical processes in the subsurface, particularly by oxidation-reduction (redox) reactions. The categorization of redox conditions based on the water quality of 116 samples collected from 65 wells in Geauga County during 1978 through 2009 indicates that most groundwater samples were strongly reducing (60 percent) or oxic (18 percent). Oxic waters were found only in the Pottsville Formation and Berea Sandstone and were generally associated with nitrate at concentrations of 0.38 to 6.0 mg/L. Strongly reducing waters occurred in all four commonly used aquifers and were associated with the following naturally occurring contaminants: (1) arsenic and manganese at concentrations exceeding the health-based benchmarks (10 µg/L and 300 µg/L, respectively) in some samples, (2) iron and manganese at concentrations exceeding the aesthetically based standards (300 µg/L and 50 µg/L, respectively) in most samples, and (3) total sulfides (consisting of hydrogen sulfide gas with its characteristic rotten-egg odor and [or] iron sulfide minerals that appear as finely disseminated particulates in water).
\nBecause of the association of redox conditions with specific contaminants, attempts were made to further document spatially where oxic and strongly reducing conditions occur so that contaminant occurrence can be better anticipated by planners and well owners. Within the Pottsville Formation, wells tapping strongly reducing groundwater tended to have a greater thickness of overlying low-permeability (recharge-inhibiting) material such as clay and shale than other wells tapping oxic or nitrate-reducing groundwater. In the Berea Sandstone, oxic conditions were found at well locations where either depth to groundwater was shallow (less than 45 feet [ft] below land surface) or the measured water level was within the open interval (uncased portion) of the well, whereas strongly reducing groundwater was found at well locations where depths to water were greater than 60 ft below land surface and measured water levels were 15 ft or more above the open interval of the well.
\nTo evaluate whether constituent concentrations consistently increased or decreased over time, the strength of the association between sampling year (time) and constituent concentration was statistically evaluated for 116 water-quality samples collected by the USGS in 1978, 1980, 1986, 1999, and 2009 from a total of 65 wells across the county (generally domestic wells or wells serving small businesses or churches). Results indicate that many of the constituents that have been analyzed for decades exhibited no consistent temporal trends at a statistically significant level (p-value less than 0.05); fluctuations in concentrations of these constituents represent natural variation in groundwater quality. Dissolved oxygen, calcium, and sulfate concentrations and chloride:bromide ratios increased over time in one or more aquifers, while pH and concentrations of bromide and dissolved organic carbon decreased over time. Detections of total coliform bacteria and nitrate did not become more frequent from 1986 to 2009, even though potential sources of these constituents, such as number of septic systems (linked to population) and percent developed land in the county, increased during this period.
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We tested these predictions using acoustic telemetry of 2 to 4 kg striped bass (Morone saxatilis Walbaum) and high-resolution spatial water quality sampling in the Patuxent River, a sub-estuary of the Chesapeake Bay, during 2008 and 2009. Striped bass avoided hypoxic (dissolved oxygen ≤2 mg·l−1) subpycnocline waters, but frequently occupied habitats with high temperatures (>25 °C) in the summer months, as cooler habitats were typically not available. Using traditional concepts of the seasonal thermal-niche oxygen-squeeze, most of the Patuxent estuary would beconsidered unsuitable habitat for adult striped bass during summer. Application of a bioenergetics model revealed that habitats selected by striped bass during summer would support positive growth rates assuming fish could feed at one-half ofmaximum consumption. 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