The purpose of this document is to describe a strategy by which monitoring and research data in the natural and social sciences will be collected, analyzed, and provided to the U.S. Department of the Interior (DOI), its bureaus, and to the Glen Canyon Dam Adaptive Management Program (GCDAMP) in support of implementation of the Glen Canyon Dam Long-Term Experimental and Management Plan (LTEMP) (U.S. Department of the Interior, 2016a). The selected alternative identified in the LTEMP Record of Decision (ROD) (U.S. Department of the Interior, 2016b) describes various data collection, analysis, modeling, and interpretation efforts to be conducted by the U.S. Geological Survey’s (USGS) Grand Canyon Monitoring and Research Center (GCMRC), partner agencies, and cooperators that will inform decisions about operations of Glen Canyon Dam and management of downstream resources between 2017 and 2037, the performance period of the LTEMP. General data collection, analysis, modeling, and interpretation activities are described in this science plan, whereas specific monitoring and research activities and detailed study plans are to be described in the GCDAMP’s triennial work plans (TWPs) to be developed by the Bureau of Reclamation and GCMRC with input from partner agencies and cooperators during the LTEMP period, which are to be reviewed and recommended by the GCDAMP and approved by the Secretary of the Interior.
The GCDAMP consists of several components, the primary committee being the Adaptive Management Work Group (AMWG). This Federal advisory committee is composed of 25 agencies and stakeholder groups and is chaired by the Secretary of the Interior’s designee. The AMWG makes recommendations to the Secretary of the Interior concerning operations of Glen Canyon Dam and other experimental management actions that are intended to fulfill some obligations of the Grand Canyon Protection Act of 1992. The Technical Work Group (TWG) is a subcommittee of the AMWG and provides technical advice to the AMWG. It is composed of technical and science representatives from the same agencies and stakeholder groups who serve on the AMWG. GCMRC is the primary science provider to the GCDAMP and also coordinates many aspects of the science performed by cooperators and partner agencies. The Science Advisors Program provides independent science reviews and advice at the request of the GCDAMP.
The plan proposed here necessarily depends on (1) the protocol for decision-making and the requirements for scientific data reporting described in the LTEMP ROD, (2) the priorities of the GCDAMP as directed by the LTEMP ROD (see Department of the Interior, 2016b, section 6.1), (3) the priorities for monitoring and research in the conservation measures section of the Biological Opinion for the LTEMP (U.S. Department of the Interior, 2016b, LTEMP ROD attachment E), (4) the priorities for resource management and information needs established by Federal and State resource-management agencies within the GCDAMP, (5) scientific understanding about the linkage between the status of those resources and operations of Glen Canyon Dam, and (6) the need to resolve existing scientific uncertainties about the linkage between dam operations and the condition of resources. We note that resource-management prioritization is fundamentally a policy decision charged specifically to DOI for the Colorado River in Glen and Grand Canyons, as outlined most recently in the LTEMP ROD, and is not the responsibility of the GCMRC. However, it is the responsibility of the GCMRC to describe the nature of scientific understanding, the nature of scientific uncertainty, and the risk of making resourcemanagement decisions in the face of existing scientific uncertainty. The goals of science activities in the next 20 years are to inform operational decisions regarding Glen Canyon Dam operations described in the LTEMP ROD, resolve remaining scientific uncertainties, and to monitor resource trends that are affected entirely, or in part, by dam operations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171006","usgsCitation":"VanderKooi, S.P., Kennedy, T.A., Topping, D.J., Grams, P.E., Ward, D.L., Fairley, H.C., Bair, L.S., Sankey, J.B., Yackulic, C.B., and Schmidt, J.C., 2017, Scientific monitoring plan in support of the selected alternative of the Glen Canyon Dam Long-Term Experimental and Management Plan: U.S. Geological Survey Open-File Report 2017-1006, 18 p., https://doi.org/10.3133/ofr20171006.","productDescription":"v, 18 p.","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-082810","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":333410,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1006/ofr20171006.pdf","text":"Report","size":"165 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1006 report PDF"},{"id":333409,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1006/coverthb.gif"}],"contact":"GCMRC Staff, Southwest Biological Science Center
U.S. Geological Survey
Grand Canyon Monitoring and Research Center
2255 N. Gemini Drive
Flagstaff, AZ 86001
https://www.gcmrc.gov/
The 3D Elevation Program (3DEP) is a cooperative activity to collect light detection and ranging (lidar) data for the conterminous United States, Hawaii, and U.S. territories; and interferometric synthetic aperture radar (IfSAR) elevation data for Alaska during an 8-year period. The U.S. Geological Survey (USGS) and partner organizations acquire high-quality three-dimensional elevation data for the United States and its territories that support requirements beyond what could be realized if agencies independently pursued lidar and IfSAR data collection activities. Data collection rates have been increasing as a growing number of State and Federal agencies participate in cooperative data acquisition projects. USGS and partner agencies expanded data collection, completed the initial product delivery systems and implemented changes to the program governance to include a restructuring of the 3DEP working group and formalizing the relationship to the Federal Geographic Data Committee during the final year (2015) of program preparation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20161196","usgsCitation":"Sugarbaker, L.J., Eldridge, D.F., Jason, A.L., Lukas, Vicki, Saghy, D.L., Stoker, J.M., and Thunen, D.R., 2017, Status of the 3D Elevation Program, 2015: U.S. Geological Survey Open-File Report 2016–1196, 13 p., https://dx.doi.org/10.3133/ofr20161196.","productDescription":"v, 13 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077494","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":333332,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20151161 ","text":"Open-File Report 2015–1161 - ","linkHelpText":"Status Report for the 3D Elevation Program, 2013–2014"},{"id":333264,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1196/coverthb.jpg"},{"id":333265,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1196/ofr20161196.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1196"}],"contact":"Director, National Geospatial Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 511
Reston, VA 20192
Email: 3DEP@usgs.gov
https://www.usgs.gov/ngpo/
https://nationalmap.gov/3DEP/
The re-colonization of the Santa Barbara channel by sea otters brings these ESA-listed marine mammals closer to active oil and gas production facilities, shipping lanes and naturally occurring oil and gas seeps. However, the degree to which sea otters may actually be affected by human-caused oil spills or exposure to natural oil seeps is currently unknown. Between 2012 and 2014, the U.S. Geological Survey and collaborating agencies conducted a telemetry-based study of sea otters in Santa Barbara channel, in order to provide critical information for resource managers (specifically the Bureau of Ocean Energy Management, henceforth BOEM, and the U.S. Fish and Wildlife Service, henceforth USFWS) about the spatial ecology, population status, and potential population threats to sea otters in Santa Barbara Channel, with particular reference to exposure to manmade structures and sources of oil and natural gas. Analysis of spatial monitoring data using a Bayesian-based synoptic model allowed for description of sea otter home ranges, identification of hot-spots of use, and insights into habitat selection behavior by male and female sea otters. Important findings included the deeper modal depth preferred by males versus females, strong preferences by both sexes for areas with persistent kelp canopy, and greater use of soft-sediment areas by males. The synoptic model also provided the ability to predict population-level density distribution for each sex in new habitats: by calculating the value of these probability density distributions at the known locations of natural seeps, we were able to identify those seeps with higher potential for sea otter encounters. The relative probability of occurrence at locations near to some seeps was sufficiently high (about 1% likelihood of occurrence for some of our study animals) that one would anticipate occasional encounters. Data on male and female survival, reproductive success, activity budgets, and body condition all indicated that sea otters in Santa Barbara Channel are not resource limited, and thus we would expect to see continued strong population growth in this area. However, the principal cause of death for study animals was lethal bites by white sharks, suggesting that shark bite mortality represents the single biggest threat to continued population growth in the Santa Barbara Channel.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171001","collaboration":"Prepared in cooperation with Bureau of Ocean Energy Management (OCS Study BOEM 2017-002)","usgsCitation":"Tinker, M.T., Tomoleoni, Joseph, LaRoche, Nicole, Bowen, Lizabeth, Miles, A. Keith, Murray, Mike, Staedler,\nMichelle, and Randell, Zach, 2017, Southern sea otter range expansion and habitat use in the Santa Barbara\nChannel, California: U.S. Geological Survey Open-File Report 2017–1001 (OCS Study BOEM 2017-002), 76 p.,\nhttps://doi.org/10.3133/ofr20171001.","productDescription":"vi, 76 p.","numberOfPages":"86","onlineOnly":"Y","ipdsId":"IP-081226","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":333276,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1001/coverthb.jpg"},{"id":333277,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1001/ofr20171001.pdf","text":"Report","size":"7.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1001 Report PDF"}],"country":"United States","state":"California","otherGeospatial":"Santa Barbara Channel","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.465087890625,\n 34.35704160076073\n ],\n [\n -120.465087890625,\n 34.65354458279873\n ],\n [\n -120.13000488281249,\n 34.65354458279873\n ],\n [\n -120.13000488281249,\n 34.35704160076073\n ],\n [\n -120.465087890625,\n 34.35704160076073\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
http://www.werc.usgs.gov/
Endangered whooping cranes (Grus americana) of the Aransas-Wood Buffalo population migrate through the Great Plains twice each year. Although there is much interest in conservation and management for this species, information regarding characteristics of nocturnal roost sites used during migration has been limited and based largely on incidental observations. Using high-quality location data collected concurrently, we directed a companion field study designed to characterize sites used as roost or day-use sites to augment knowledge and assist the Platte River Recovery Implementation Program in identifying migration habitat for restoration, conservation, and management actions along the Platte River in central Nebraska. We collected data at 504 roost sites and 83 day-use sites used by marked whooping cranes in Texas, Oklahoma, Kansas, Nebraska, South Dakota, North Dakota, Minnesota, and Montana. Roost sites were located in emergent wetlands (50 percent), lacustrine wetlands (25 percent), rivers (20 percent), and dryland sites (5 percent). Most day-use sites were characterized as dryland sites (54 percent), with the balance in wetlands (45 percent) and rivers (1 percent). Habitat criteria thresholds initially derived by the Platte River Recovery Implementation Program to represent where 90 percent of whooping cranes used along the Platte River were different from those we measured over a larger section of the migration corridor. For most of the metrics, the Platte River Recovery Implementation Program’s initial habitat criteria thresholds would be considered more conservative than critical values estimated from our data; thus, whooping cranes were seemingly able to tolerate a wider range of these metrics than initially suspected. One exception was the metric distance to nearest disturbance feature, where our results suggest that whooping cranes may be less tolerant to nearby disturbances in a larger part of the migration corridor compared to the Platte River. We also determined correlations among some metrics and that using the criteria collectively lead to less than 50 percent of sites we measured being considered whooping crane habitat by the Platte River Recovery Implementation Program. A better understanding of how metrics function collectively may be useful for future efforts in defining habitat for migrating whooping cranes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161209","collaboration":"Prepared in cooperation with the Platte River Recovery Implementation Program and Crane Trust","usgsCitation":"Pearse, A.T., Harner, M.J., Baasch, D.M., Wright, G.D., Caven, A.J., and Metzger, K.L., 2017, Evaluation of nocturnal roost and diurnal sites used by whooping cranes in the Great Plains, United States: U.S. Geological Survey Open-File Report 2016–1209, 29 p., https://doi.org/10.3133/ofr20161209.","productDescription":"v, 29 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-078087","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":332999,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1209/ofr20161209.pdf","text":"Report","size":"6.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1209"},{"id":332998,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1209/coverthb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.67773437499999,\n 28.9600886880068\n ],\n [\n -104.67773437499999,\n 49.03786794532644\n ],\n [\n -94.7021484375,\n 49.03786794532644\n ],\n [\n -94.7021484375,\n 28.9600886880068\n ],\n [\n -104.67773437499999,\n 28.9600886880068\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
This paper describes the tectonic summaries for all magnitude 7 and larger earthquakes in the period 2000–2015, as produced by the U.S. Geological Survey National Earthquake Information Center during their routine response operations to global earthquakes. The goal of such summaries is to provide important event-specific information to the public rapidly and concisely, such that recent earthquakes can be understood within a global and regional seismotectonic framework. We compile these summaries here to provide a long-term archive for this information, and so that the variability in tectonic setting and earthquake history from region to region, and sometimes within a given region, can be more clearly understood.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161192","usgsCitation":"Hayes, G.P., Myers, E.K., Dewey, J.W., Briggs, R.W., Earle, P.S., Benz, H.M., Smoczyk, G.M., Flamme, H.E., Barnhart, W.D., Gold, R.D., and Furlong, K.P., 2017, Tectonic summaries of magnitude 7 and greater earthquakes from 2000 to 2015: U.S. Geological Survey Open-File Report 2016–1192, 148 p., https://doi.org/10.3133/ofr20161192.","productDescription":"Report: v, 148 p.; KMZ file","onlineOnly":"Y","ipdsId":"IP-077362","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":333007,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2016/1192/ofr20161192.kmz","text":"KMZ file","size":"112 kB","description":"OFR 2016-1192 KMZ file"},{"id":333005,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1192/coverthb.jpg"},{"id":333006,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1192/ofr20161192.pdf","text":"Report","size":"5.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1192"}],"otherGeospatial":"Earth","contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS 966
Denver, CO 80225-0046
Heavy rainfall during December 2015 resulted in flooding across parts of Arkansas; rainfall amounts were as high as 12 inches over a period from December 27, 2015, to December 29, 2015. Although precipitation accumulations were highest in northwestern Arkansas, significant flooding occurred in other parts of the State. Flood damage occurred in several counties as water levels rose in streams, and disaster declarations were declared in 32 of the 75 counties in Arkansas.
Given the severity of the December 2015 flooding, the U.S. Geological Survey (USGS), in cooperation with the Federal Emergency Management Agency (FEMA), conducted a study to document the meteorological and hydrological conditions prior to and during the flood; compiled flood-peak gage heights, streamflows, and flood probabilities at USGS streamflow-gaging stations; and estimated streamflows and flood probabilities at selected ungaged locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161198","usgsCitation":"Breaker, B.K., 2017, Peak streamflow on selected streams in Arkansas, December 2015: U.S. Geological Survey Open-File Report 2016–1198, 7 p., https://doi.org/10.3133/ofr20161198.","productDescription":"7 p.","onlineOnly":"Y","ipdsId":"IP-079418","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":332997,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1198/coverthb2.jpg"},{"id":332995,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1198/ofr20161198.pdf","text":"Report","size":"622 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1198"}],"country":"United 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This Surface-Water Quality-Assurance Plan documents the standards, policies, and procedures used by the U.S. Geological Survey Washington Water Science Center (WAWSC) for activities related to the collection, processing, storage, analysis, and publication of surface-water data. This plan serves as a guide to all WAWSC personnel involved in surface-water data activities, and changes as the needs and requirements of the WAWSC change. Regular updates to this plan represent an integral part of the quality-assurance process. In the WAWSC, direct oversight and responsibility by the hydrographer(s) assigned to a surface-water station, combined with team approaches in all work efforts, assure highquality data, analyses, reviews, and reports for cooperating agencies and the public.
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U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
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In a study conducted by the U.S. Geological Survey in cooperation with the New York State Department of Environmental Conservation, groundwater samples were collected from 6 production wells and 7 domestic wells in the Lake Champlain Basin and from 11 production wells and 9 domestic wells in the Susquehanna River Basin in New York. All samples were collected from June through December 2014 to characterize groundwater quality in these basins. The samples were collected and processed using standard procedures of the U.S. Geological Survey and were analyzed for 148 physiochemical properties and constituents, including dissolved gases, major ions, nutrients, trace elements, pesticides, volatile organic compounds, radionuclides, and indicator bacteria.
The Lake Champlain Basin study area covers the 3,050 square miles of the basin in northeastern New York; the remaining part of the basin is in Vermont and Canada. Of the 13 wells sampled in the Lake Champlain Basin, 6 are completed in sand and gravel, and 7 are completed in bedrock. Groundwater in the Lake Champlain Basin was generally of good quality, although properties and concentrations of some constituents— fluoride, iron, manganese, dissolved solids, sodium, radon-222, total coliform bacteria, fecal coliform bacteria, and Escherichia coli bacteria—sometimes equaled or exceeded primary, secondary, or proposed drinking-water standards. The constituent most frequently detected in concentrations exceeding drinking-water standards (5 of 13 samples) was radon-222.
The Susquehanna River Basin study area covers the entire 4,522 square miles of the basin in south-central New York; the remaining part of the basin is in Pennsylvania. Of the 20 wells sampled in the Susquehanna River Basin, 11 are completed in sand and gravel, and 9 are completed in bedrock. Groundwater in the Susquehanna River Basin was generally of good quality, although properties and concentrations of some constituents—pH, chloride, sodium, dissolved solids, iron, manganese, aluminum, arsenic, barium, gross-alpha radioactivity, radon-222, methane, total coliform bacteria, and fecal coliform bacteria—sometimes equaled or exceeded primary, secondary, or proposed drinking-water standards. As in the Lake Champlain Basin, the constituent most frequently detected in concentrations exceeding drinking-water standards (13 of 20 samples) was radon-222.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161153","collaboration":"Prepared in cooperation with the New York State Dept of Environmental Conservation","usgsCitation":"Scott, T.-M., Nystrom, E.A., and Reddy, J.E., 2016, Groundwater quality in the Lake Champlain and Susquehanna River basins, New York, 2014: U.S. Geological Survey Open-File Report 2016–1153, 33 p., appendixes, https://dx.doi.org/10.3133/ofr20161153.","productDescription":"viii, 33p.","startPage":"1","endPage":"33","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-073986","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":329702,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1153/ofr20161153_app1.xlsx","text":"Apprendix 1 (MS Excel)","size":"79.1 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1153 appendix 1","linkHelpText":"- Water sampling results, 2014"},{"id":329700,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1153/coverthb.jpg"},{"id":329703,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1153/ofr20161153_app2.xlsx","text":"Apprendix 2 (MS Excel)","size":"67.6 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1153 appendix 2","linkHelpText":"- Water sampling results, 2004-05, 2009, and 2014"},{"id":329712,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1153/ofr20161153_app2.zip","text":"Appendix 2 (CSV)","size":"13.4 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1153 appendix 2","linkHelpText":"- Water sampling results, 2004-05, 2009, and 2014"},{"id":329711,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1153/ofr20161153_app1.zip","text":"Appendix 1 (CSV)","size":"15.7 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1153 appendix 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York\",\"nation\":\"USA \"}}]}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
http://ny.water.usgs.gov
The North Carolina Turnpike Authority, a division of the North Carolina Department of Transportation, is planning to make transportation improvements in the Currituck Sound area by constructing a two-lane bridge from U.S. Highway 158 just south of Coinjock, North Carolina, to State Highway 12 on the Outer Banks just south of Corolla, North Carolina. The results of the Final Environmental Impact Study associated with the bridge and existing roadway improvements indicated potential water-quality and habitat impacts to Currituck Sound related to stormwater runoff, altered light levels, introduction of piles as hard substrate, and localized turbidity and siltation during construction.
\nThe primary objective of this initial study phase was to establish baseline water-quality conditions and bed-sediment chemistry of Currituck Sound in the vicinity of the planned alignment of the Mid-Currituck Bridge. These data will be used to evaluate the impacts associated with the bridge construction and bridge deck stormwater runoff. Between 2011 and 2015, discrete water-quality samples were collected monthly and after selected storm events from five locations in Currituck Sound. The sampling locations were distributed along the proposed alignment of the Mid-Currituck Bridge. Water samples were analyzed for physical parameters and water-quality constituents associated with bridge deck stormwater runoff and important in identifying impaired waters designated as “SC” (saltwater-aquatic life propagation/ protection and secondary recreation) under North Carolina’s water-quality classifications. Bed-sediment chemistry was also measured three times during the study at the five sampling locations. Continuous water-level and wind speed and direction data in Currituck Sound were also collected by the U.S. Geological Survey during the study period.
\nFor the water samples, measured concentrations were greater than water-quality thresholds on 52 occasions. In addition, there were 190 occurrences of censored results having a reporting level higher than specific thresholds. All 52 occurrences of concentrations greater than water-quality thresholds were confined to seven different physical properties or constituents, namely pH (25), turbidity (8), total recoverable chromium (6), total recoverable copper (6), dissolved copper (3), total recoverable mercury (2), and total recoverable nickel (2). Concentrations of 17 other constituents were never measured to be greater than their established water-quality thresholds during the study.
\nThe focus of the water-quality characterization was on concentrations of constituents identified as parameters of concern in a 2011 collaborative U.S. Geological Survey/North Carolina Department of Transportation study that characterized bridge deck stormwater runoff across North Carolina. The occurrence and distribution of parameters of concern identified in the 2011 study, including pH, nutrients, total recoverable and dissolved metals, and polycyclic aromatic hydrocarbons, and some additional pertinent physical properties (dissolved oxygen, specific conductance, and turbidity), were analyzed in water and bed-sediment samples. Statistical differences were identified between monthly and storm samples for the following physical properties and constituents: pH, dissolved oxygen, specific conductance, turbidity, Escherichia coli bacteria, total recoverable aluminum, and total recoverable iron. Seasonality was observed in pH, specific conductance, dissolved oxygen, turbidity, total phosphorus, and total nitrogen, and total recoverable aluminum, arsenic, iron, lead, and manganese during the study period. The volume and residence time of the water in Currituck Sound are such that the water chemistry is relatively uniform spatially, but variable temporally.
\nOne of the most variable constituents in bed sediments was the fraction of fines, those sediments less than 63 micrometers in diameter. Because most, if not all, of the measured constituents were presumably associated with this fraction, bulk-sediment concentrations are determined largely by the amount of fines present. Only four constituents were greater than bed-sediment thresholds: tin (5 samples), barium (4 samples), aluminum (2 samples), and diethyl phthalate (1 sample). The occurrences of concentrations being greater than referenced thresholds could be underestimated for diethyl phthalate, because the reporting level exceeded the threshold in nine samples. Thirty-five constituents had sampled concentrations that were never greater than quality thresholds, although 21 of these constituents (154 instances) had at least one sample with a reporting level that was greater than the corresponding threshold. Finally, 33 constituents had no quality thresholds.
\nThis study and previous studies of bed-sediment quality in Currituck Sound, although few, indicate that sedimentation in Currituck Sound near the proposed alignment of the MidCurrituck Bridge is characterized overall by low and transient input, frequent wind-driven resuspension, and little long-term deposition of fines. To the extent that it might alter water depths along the alignment, bridge construction might also alter the deposition and resuspension rates of fine sediments in Currituck Sound in the vicinity of the bridge.
\nThe characterization of water-quality and bed-sediment chemistry in Currituck Sound along the proposed alignment of the Mid-Currituck Bridge summarized herein provides a baseline for determining the effect of bridge construction and bridge deck runoff on environmental conditions in Currituck Sound.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151208","collaboration":"Prepared in cooperation with the North Carolina Turnpike Authority","usgsCitation":"Wagner, Chad, Fitzgerald, Sharon, and Antolino, Dominick, 2016, Characterization of water-quality and bed-sediment conditions in Currituck Sound, North Carolina, prior to the Mid-Currituck Bridge construction, 2011–15 (ver. 1.1, July 2016): U.S. Geological Survey Open-File Report 2015–1208, 84 p., https://dx.doi.org/10.3133/ofr20151208.","productDescription":"Report: viii, 84 p.; 2 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066575","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":324820,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2015/1208//versionHist.txt","size":"1.11 KB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2015-1208"},{"id":312524,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1208/ofr20151208_appendix2.xlsx","text":"Appendix 2","size":"38.3 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2015-1208"},{"id":312523,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1208/ofr20151208_appendix1.xlsx","text":"Appendix 1","size":"285 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2015-1208"},{"id":312522,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1208/ofr20151208.pdf","text":"Report","size":"2.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1208"},{"id":312521,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1208/coverthb1.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Currituck Sound, Mid-Currituck Bridge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.4,\n 35.7\n ],\n [\n -76.4,\n 36.75\n ],\n [\n -75.4,\n 36.75\n ],\n [\n -75.4,\n 35.7\n ],\n [\n -76.4,\n 35.7\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1:Originally posted December 24, 2015; Version 1.1: July 8, 2016;","publicComments":"Open-File Report 2015-1208 is superseded by Open-File Report 2020-1031","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
Exploratory sampling of groundwater in coastal Los Angeles County and Kern and Kings Counties of the southern San Joaquin Valley was done by the U.S. Geological Survey from September 2014 through January 2015 as part of the California State Water Resources Control Board’s Water Quality in Areas of Oil and Gas Production Regional Groundwater Monitoring Program. The Regional Groundwater Monitoring Program was established in response to the California Senate Bill 4 of 2013 mandating that the California State Water Resources Control Board design and implement a groundwater-monitoring program to assess potential effects of well-stimulation treatments on groundwater resources in California. The U.S. Geological Survey is in cooperation with the California State Water Resources Control Board to collaboratively implement the Regional Groundwater Monitoring Program through the California Oil, Gas, and Groundwater Project. Many researchers have documented the utility of different suites of chemical tracers for evaluating the effects of oil and gas development on groundwater quality. The purpose of this exploratory sampling effort was to determine whether tracers reported in the literature could be used effectively in California. This reconnaissance effort was not designed to assess the effects of oil and gas on groundwater quality in the sampled areas. A suite of water-quality indicators and geochemical tracers were sampled at groundwater sites in selected areas that have extensive oil and gas development. Groundwater samples were collected from a total of 51 wells, including 37 monitoring wells at 17 multiple-well monitoring sites in coastal Los Angeles County and 5 monitoring wells and 9 water-production wells in southern San Joaquin Valley, primarily in Kern and Kings Counties. Groundwater samples were analyzed for field waterquality indicators; organic constituents, including volatile and semi-volatile organic compounds and dissolved organic carbon indicators; naturally present inorganic constituents, including trace elements, nutrients, major and minor ions, and iron species; naturally present stable and radioactive isotopes; dissolved noble gases; dissolved standard and hydrocarbon gases, δ13C of methane, ethane, and δ2 H of methane. In total, 249 constituents and water-quality indicators were measured. Four types of quality-control samples (blanks, replicates, matrix spikes, and surrogates spiked in environmental and blank samples) were collected at approximately 10 percent of the wells. The quality-control data were used to determine whether the groundwater-sample data were of sufficient quality for the measured analytes to be used as potential indicators of oil and gas effects. The data from the 51 groundwater samples and from the quality-control samples are presented in this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161181","collaboration":"A product of the California Oil and Gas Regional Groundwater Monitoring ProgramDirector, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Data for static water-levels measured in about 610 wells during March-April 2014 by the U.S. Geological Survey (USGS), the Mojave Water Agency (MWA), and other local water districts were compiled to construct a regional water-table map. This map shows the elevation of the water table and general direction of groundwater movement in and around the Mojave River and Morongo groundwater basins. Water-level measurements recorded by the USGS and MWA staff were measured and compiled according to the procedures described in the Groundwater Technical Procedures of the U.S. Geological Survey (Cunningham and Schalk, 2011). Water-level data submitted by cooperating local water districts were collected by using procedures established by the corresponding agency, and compiled according to the procedures described in the Groundwater Technical Procedures of the U.S. Geological Survey (Cunningham and Schalk, 2011). All data were compared to historical data for quality-assurance purposes. Water-level contours from the 2012 water-level map (Teague and others, 2014) were used as a guide to interpret and shape the 2014 water-level contours in areas where 2014 water-level data were not available; these contours are shown as dashed (approximate) on the water-table map. In addition to being available on the interactive map, 2014 water-level data and contours are shown for the entire area of the Mojave River and Morongo groundwater basins on Plate 1. Water-level data for 2014 are accessible through the website by clicking the 2014 Sites button on the Data Downloads page.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161105","collaboration":"Prepared in cooperation with the Mojave Water Agency","usgsCitation":"Teague, N.F., Dick, M.C., House, S.F., and Clark, D.A., 2016, Regional water table (2014) in the Mojave River and Morongo groundwater basins, southwestern Mojave Desert, California, 2016: U.S. Geological Survey Open-File Report 2016–1105 (ver. 3, July 2020), 1 sheet, scale 1:170,000, https://doi.org/10.3133/ofr20161105.","productDescription":"1 Sheet: 42.00 x 37.00 inches; Project Site; Version History","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074861","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":438469,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P848ZZ","text":"USGS data release","linkHelpText":"Regional Water Table (2014) in the Mojave River and Morongo Groundwater Basins, Southwestern Mojave Desert, California (ver. 1.2, September 2020)"},{"id":337647,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1105/cover/coverthb.jpg"},{"id":340194,"rank":2,"type":{"id":18,"text":"Project Site"},"url":"https://ca.water.usgs.gov/mojave/mojave-2014-water-levels.html","text":"Project Site"},{"id":376391,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2016/1105/versionHist.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"}},{"id":376390,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1105/ofr20161105.pdf","text":"Sheet","size":"17 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.5,\n 34.05\n ],\n [\n -117.5,\n 35.25\n ],\n [\n -116.0,\n 35.25\n ],\n [\n -116.0,\n 34.05\n ],\n [\n -117.5,\n 34.05\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted June 28, 2016; Version 2.0: March 30, 2017; Version 3.0: July 15, 2020","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
This report provides an overview of current (2016) U.S. Geological Survey policies and practices related to publishing data on ScienceBase, and an example interactive mapping application to display those data. ScienceBase is an integrated data sharing platform managed by the U.S. Geological Survey. This report describes resources that U.S. Geological Survey Scientists can use for writing data management plans, formatting data, and creating metadata, as well as for data and metadata review, uploading data and metadata to ScienceBase, and sharing metadata through the U.S. Geological Survey Science Data Catalog. Because data publishing policies and practices are evolving, scientists should consult the resources cited in this paper for definitive policy information.
An example is provided where, using the content of a published ScienceBase data release that is associated with an interpretive product, a simple user interface is constructed to demonstrate how the open source capabilities of the R programming language and environment can interact with the properties and objects of the ScienceBase item and be used to generate interactive maps.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161202","collaboration":"Prepared in cooperation with the Community for Data Integration","usgsCitation":"Chase, K.J., Bock, A.R., and Sando, Roy, 2017, Sharing our data—An overview of current (2016) USGS policies and practices for publishing data on ScienceBase and an example interactive mapping application: U.S. Geological Survey Open-File Report 2016–1202, 10 p., https://doi.org/10.3133/ofr20161202.","productDescription":"Report: v, 10 p. ","startPage":"1","endPage":"10","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-076724","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":332690,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1202/coverthb.jpg"},{"id":332691,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1202/ofr20161202.pdf","text":"Report","size":"2.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1202 Report PDF"}],"contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Ave
Helena, MT 59601
http://wy-mt.water.usgs.gov/
Survival estimates for juvenile salmon and steelhead fry in reservoirs impounded by high head dams are coveted data by resource managers. However, this information is difficult to obtain because these fish are too small for tagging using conventional methods such as passive-integrated transponders or radio or acoustic transmitters. We developed a study design and implementation plan to conduct a pilot evaluation that would assess the performance of two models for estimating fry survival in a field setting. The first model is a staggered-release recovery model that was described by Skalski and others (2009) and Skalski (2016). The second model is a parentage-based tagging N-mixture model that was developed and described in this document. Both models are conceptually and statistically sound, but neither has been evaluated in the field. In this document we provide an overview of a proposed study for 2017 in Lookout Point Reservoir, Oregon, that will evaluate survival of Chinook salmon fry using both models. This approach will allow us to test each model and compare survival estimates, to determine model performance and better understand these study designs using field-collected data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161211","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers and the Oregon Department of Fish and Wildlife","usgsCitation":"Kock, T.J., Perry, R.W., Monzyk, F.R., Pope, A.C., and Plumb, J.M., 2016, Development of a study design and implementation plan to estimate juvenile salmon survival in Lookout Point Reservoir and other reservoirs of the Willamette Project, western Oregon: U.S. Geological Survey Open-File Report 2016–1211, 25 p., https://doi.org/10.3133/ofr20161211.","productDescription":"iv, 25 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-079919","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":332514,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1211/coverthb.jpg"},{"id":332515,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1211/ofr20161211.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1211 Report PDF"}],"country":"United States","state":"Oregon","otherGeospatial":"Dexter Dam, Dexter Reservoir, Lookout Point Reservoir, Lookout Point Dam, Middle Fork Willamette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.89718627929688,\n 43.91768033000405\n ],\n [\n -122.81410217285155,\n 43.98589821991874\n ],\n [\n -122.64244079589842,\n 43.929055415997134\n ],\n [\n -122.5140380859375,\n 43.82808744469062\n ],\n [\n -122.63626098632812,\n 43.77059798257491\n ],\n [\n -122.75711059570312,\n 43.854830911225235\n ],\n [\n -122.89718627929688,\n 43.91768033000405\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/
Estimates of juvenile salmon survival are important data for fishery managers in the Yakima River Basin. Radiotelemetry studies during 2012–14 showed that tagged juvenile Chinook salmon (Oncorhynchus tshawytscha) that passed through the fish bypass at Roza Dam had lower survival than fish that passed through other routes at the dam. That study also identified flow-survival relationships in the reaches between the Roza Dam tailrace and Sunnyside Dam. During 2012–14, survival also was estimated through reaches downstream of Sunnyside Dam, but generally, sample sizes were low and the estimates were imprecise. In 2016, we conducted an evaluation using acoustic cameras and acoustic telemetry to build on information collected during the previous study. The goal of the 2016 research was to identify areas where mortality occurs in the fish bypass at Roza Dam, and to estimate reach-specific survival in reaches downstream of the dam. The 2016 study included juvenile Chinook salmon and coho salmon (O. kisutch).
Three acoustic cameras were used to observe fish behavior (1) near the entrances to the fish bypass, (2) at a midway point in the fish bypass (convergence vault), and (3) at the bypass outfall. In total, 504 hours of acoustic camera footage was collected at these locations. We determined that smolt-sized fish (95–170 millimeters [mm]) were present in the highest proportions at each location, but predator-sized fish (greater than 250 mm) also were present at each site. Fish presence generally peaked during nighttime hours and crepuscular periods, and was low during daytime hours. In the convergence vault, smolt-sized fish exhibited holding behavior patterns, which may explain why some fish delayed while passing through the bypass.
Some of the acoustic-tagged fish were delayed in the fish bypass following release, but there was no evidence to suggest that they experienced higher mortality than fish that were released at the bypass outfall or downstream of the dam. Most of the tagged fish that were released in the fish bypass moved downstream and re-entered the river within 12 hours, but 9.8 percent of the Chinook salmon and 15.7 percent of the coho salmon remained in the bypass for 2.5–17.4 days. We developed a set of models for Chinook salmon and coho salmon and used model selection to determine if release site was an important predictor of survival of tagged fish. The models that provided the best fit to the Chinook salmon and coho salmon datasets did not include release site as a covariate. Furthermore, survival estimates for groups of fish from the various release sites were nearly identical for both species. Based on these observations, it appears that passage through the fish bypass did not result in increased mortality relative to groups of fish released downstream of the bypass.
Juvenile Chinook salmon migrated downstream faster than juvenile coho salmon and survival for each species varied with release timing. Median travel time from release at Roza Dam to arrival at a detection gate located at river kilometer (rkm) 527.8 on the Columbia River was 15.4 days for Chinook salmon and 37.4 days for coho salmon. Cumulative survival from Roza Dam to the Columbia River detection gate ranged from 0.299 to 0.678 for Chinook salmon, and from 0.321 to 0.627 for coho salmon. Survival was highest for both species when tagged fish were released in mid-April and lowest when tagged fish were released in early-May. Reach-specific survival estimates were standardized to create estimates that described survival per 100 rkm, which showed that survival was very low (less than 0.500) for some release groups, particularly in the Roza, Sunnyside, and Chandler diversion reaches. A more extensive analysis of reach-specific survival is planned for this dataset, which should provide insights into covariates that affected survival during 2016.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161210","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Kock, T.J., Perry, R.W., and Hansen, A.C., 2016, Survival of juvenile Chinook salmon and coho salmon in the Roza Dam fish bypass and in downstream reaches of the Yakima River, Washington, (ver. 1.1, April 2017): U.S. Geological Survey Open-File Report 2016–1210, 32 p., https://doi.org/10.3133/ofr20161210.","productDescription":"vi, 32 p.","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-079554","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":332490,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1210/ofr20161210.pdf","text":"Report","size":"9.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1210 Report PDF"},{"id":339521,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2016/1210/versionHist.txt","text":"Version 1.1","size":"3 KB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2016-1210 Version History"},{"id":339519,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1210/coverthb3.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Roza Dam, Yakima River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.53076171875,\n 46.14178273759234\n ],\n [\n -121.53076171875,\n 47.46523622438362\n ],\n [\n -119.04235839843749,\n 47.46523622438362\n ],\n [\n -119.04235839843749,\n 46.14178273759234\n ],\n [\n -121.53076171875,\n 46.14178273759234\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted December 22, 2016; Version 1.1: April 10, 2017","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
https://wfrc.usgs.gov/
Discharge from springs in Florida is sourced from aquifers, such as the Upper Floridan aquifer, which is overlain by an upper confining unit that locally can have properties of an aquifer. Water levels in aquifers are affected by several factors, such as precipitation, recharge, and groundwater withdrawals, which in turn can affect discharge from springs. Therefore, identifying groundwater sources and recharge characteristics can be important in assessing how these factors might affect flows and water levels in springs and can be informative in broader applications such as groundwater modeling. Recharge characteristics include the residence time of water at the surface, apparent age of recharge, and recharge water temperature.
The groundwater sources and recharge characteristics of three springs that discharge from the banks of the Suwannee River in northern Florida were assessed for this study: Bell Springs, White Springs, and Suwannee Springs. Sources of groundwater were also assessed for a 150-foot-deep well finished within the Upper Floridan aquifer, hereafter referred to as the UFA well. Water samples were collected for geochemical analyses in November 2012 and October 2013 from the three springs and the UFA well. Samples were analyzed for a suite of major ions, dissolved gases, and isotopes of sulfur, strontium, oxygen, and hydrogen. Daily means of water level and specific conductance at White Springs were continuously recorded from October 2012 through December 2013 by the Suwannee River Water Management District. Suwannee River stage at White Springs was computed on the basis of stage at a U.S. Geological Survey streamgage about 2.4 miles upstream. Water levels in two wells, located about 2.5 miles northwest and 13 miles southeast of White Springs, were also used in the analyses.
Major ion concentrations were used to differentiate water from the springs and Upper Floridan aquifer into three groups: Bell Springs, UFA well, and White and Suwannee Springs. When considered together, evidence from water-level, specific conductance, major-ion concentration, and isotope data indicated that groundwater at Bell Springs and the UFA well was a mixture of surface water and groundwater from the upper confining unit, and that groundwater at White and Suwannee Springs was a mixture of surface water, groundwater from the upper confining unit, and groundwater from the Upper Floridan aquifer. Higher concentrations of magnesium in groundwater samples at the UFA well than in samples at Bell Springs might indicate less mixing with surface water at the UFA well than at Bell Springs. Characteristics of surface-water recharge, such as residence time at the surface, apparent age, and recharge water temperature, were estimated on the basis of isotopic ratios, and dissolved concentrations of gases such as argon, tritium, and sulfur hexafluoride. Oxygen and deuterium isotopic ratios were consistent with rapid recharge by rainwater for samples collected in 2012, and longer residence time at the surface (ponding) for samples collected in 2013. Apparent ages of groundwater samples, computed on the basis of tritium activity and sulfur hexafluoride concentration, indicated groundwater recharge occurred after the late 1980s; however, the estimated apparent ages likely represent the average of ages of multiple sources. Recharge since the 1980s is consistent with groundwater from shallow sources, such as the upper confining unit and Upper Floridan aquifer. Recharge water temperature computed for the three springs and UFA well averaged 20.1 degrees Celsius, which is similar to the mean annual air temperature of 20.6 degrees Celsius at a nearby weather station for 1960–2014.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161190","collaboration":"Prepared in cooperation with the Suwannee River Water Management District","usgsCitation":"Stamm, J.F., and McBride, W.S., 2016, Sources of groundwater and characteristics of surface-water recharge at Bell, White, and Suwannee Springs, Florida: 2012–13: U.S. Geological Survey Open-File Report 2016–1190, 27 p., https://doi.org/10.3133/ofr20161190.","productDescription":"vii, 27 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-066218","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":332418,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1190/coverthb.jpg"},{"id":332419,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1190/ofr20161190.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1190"}],"country":"United States","state":"Florida","otherGeospatial":"Bell Spring, Suwannee Spring, White Spring","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.033333,\n 30.583333\n ],\n [\n -83.033333,\n 30.166667\n ],\n [\n -82.616667,\n 30.166667\n ],\n [\n -82.616667,\n 30.583333\n ],\n [\n -83.033333,\n 30.583333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
The U.S. Geological Survey, in cooperation with the New England Interstate Water Pollution Control Commission and the Vermont Department of Environmental Conservation, estimated daily and 9-month concentrations and fluxes of total and dissolved phosphorus, total nitrogen, chloride, and total suspended solids from 1990 (or first available date) through 2014 for 18 tributaries of Lake Champlain. Estimates of concentration and flux, provided separately in Medalie (2016), were made by using the Weighted Regressions on Time, Discharge, and Season (WRTDS) regression model and update previously published WRTDS model results with recent data. Assessment of progress towards meeting phosphorus-reduction goals outlined in the Lake Champlain management plan relies on annual estimates of phosphorus flux. The percent change in annual concentration and flux is provided for two time periods. The R package EGRETci was used to estimate the uncertainty of the trend estimate. Differences in model specification and function between this study and previous studies that used WRTDS to estimate concentration and flux using data from Lake Champlain tributaries are described.
Winter data were too sparse and nonrepresentative to use for estimates of concentration and flux but were sufficient for estimating the percentage of total annual flux over the period of record. Median winter-to-annual fractions ranged between 21 percent for total suspended solids and 27 percent for dissolved phosphorus. The winter contribution was largest for all constituents from the Mettawee River and smallest from the Ausable River.
For the full record (1991 through 2014 for total and dissolved phosphorus and chloride and 1993 through 2014 for nitrogen and total suspended solids), 6 tributaries had decreasing trends in concentrations of total phosphorus, and 12 had increasing trends; concentrations of dissolved phosphorus decreased in 6 and increased in 8 tributaries; fluxes of total phosphorus decreased in 5 and increased in 10 tributaries; and fluxes of dissolved phosphorus decreased in 4 and increased in 10 tributaries (where the number of increasing and decreasing trends does not add up to 18, the remainder of tributaries had no trends). Concentrations and fluxes of nitrogen decreased in 10 and increased in 4 tributaries and of chloride decreased in 2 and increased in 15 tributaries. Concentrations of total suspended solids decreased in 4 and increased in 8 tributaries, and fluxes of total suspended solids decreased in 3 and increased in 11 tributaries.
Although time intervals for the percent changes from this report are not completely synchronous with those from previous studies, the numbers of and specific tributaries with overall negative percent changes in concentration and flux are similar. Concentration estimates of total phosphorus in the Winooski River were used to trace whether changes in trends between a previous study and the current study were due generally to differences in model specifications or differences from 4 years of additional data. The Winooski River analysis illustrates several things: that keeping all model specifications equal, concentration estimates increased from 2010 to 2014; the effects of a smoothing algorithm used in the current study that was not available previously; that narrowing model half-window widths increased year-to-year variations; and that the change from an annual to a 9-month basis by omitting winter estimates changed a few individual points but not the overall shape of the flow-normalized curve. Similar tests for other tributaries showed that the primary effect of differences in model specifications between the previous and current studies was perhaps to increase scatter over time but that changes in trends generally were the result of 4 years of additional data rather than artifacts of model differences.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161200","collaboration":"Prepared in cooperation with the New England Interstate Water Pollution Control Commission and the Vermont Department of Environmental Conservation","usgsCitation":"Medalie, Laura, 2016, Concentration, flux, and trend estimates with uncertainty for nutrients, chloride, and total suspended solids in tributaries of Lake Champlain, 1990–2014: U.S. Geological Survey Open-File Report 2016–1200, 22 p., https://doi.org/10.3133/ofr20161200.","productDescription":"Report: iv, 22 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076110","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":438482,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RN360M","text":"USGS data release","linkHelpText":"Estimates of annual and daily concentration and flux of nutrients, chloride, and suspended sediment in tributaries of Lake Champlain, 1990 through 2014"},{"id":332328,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7RN360M","text":"USGS data release - Estimates of annual and daily concentration and flux of nutrients, chloride, and total suspended solids in tributaries of Lake Champlain, 1990 through 2014","description":"Usgs Data Release"},{"id":332327,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1200/ofr20161200.pdf","text":"Report","size":"858 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1200"},{"id":332326,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1200/coverthb.jpg"}],"country":"United States","state":"New York, Vermont","otherGeospatial":"Lake Champlain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.597412109375,\n 44.01454613545038\n ],\n [\n -73.00140380859375,\n 44.01454613545038\n ],\n [\n -73.00140380859375,\n 45.00365115687186\n ],\n [\n -73.597412109375,\n 45.00365115687186\n ],\n [\n -73.597412109375,\n 44.01454613545038\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way
Pembroke, NH 03275
http://newengland.water.usgs.gov
","tableOfContents":"The passage of Hurricane Matthew across the central and eastern regions of North Carolina and South Carolina during October 7–9, 2016, resulted in heavy rainfall that caused major flooding in parts of the eastern Piedmont in North Carolina and coastal regions of both States. Rainfall totals of 3 to 8 inches and 8 to more than 15 inches were widespread throughout the central and eastern regions, respectively. U.S. Geological Survey streamgages recorded peaks of record at 26 locations, including 11 sites with long-term periods of 30 or more years of record. A total of 44 additional locations had peak streamflows that ranked in the top 5 for the period of record. Additionally, among 23 U.S. Geological Survey streamgages within the affected basins in North Carolina where stage-only data are collected, new peak stages were recorded at 5 locations during the flooding. U.S. Geological Survey personnel made 102 streamflow measurements at 60 locations in both States to verify, update, or extend existing rating curves (which are used to determine stage-discharge relations) during the October 2016 flood event.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161205","usgsCitation":"Weaver, J.C., Feaster, T.D., and Robbins, J.C., 2016, Preliminary peak stage and streamflow data at selected streamgaging stations in North Carolina and South Carolina for flooding following Hurricane Matthew, October 2016: U.S. Geological Survey Open-File Report 2016–1205, 38 p., https://doi.org/10.3133/ofr20161205.","productDescription":"v, 38 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-081734","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":332170,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1205/coverthb.jpg"},{"id":332171,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1205/ofr20161205.pdf","text":"Report","size":"4.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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Carolina\",\"nation\":\"USA \"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
An effort to build a unified collection of geospatial data for use in land-change modeling (LCM) led to new insights into the requirements and challenges of building an LCM data infrastructure. A case study of data compilation and unification for the Richmond, Va., Metropolitan Statistical Area (MSA) delineated the problems of combining and unifying heterogeneous data from many independent localities such as counties and cities. The study also produced conclusions and recommendations for use by the national LCM community, emphasizing the critical need for simple, practical data standards and conventions for use by localities. This report contributes an uncopyrighted core glossary and a much needed operational definition of data unification.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161176","usgsCitation":"Donato, D.I., and Shapiro, J.L., 2016, Building unified geospatial data for land-change modeling—A case study in the area of Richmond, Virginia: U.S. Geological Survey Open-File Report 2016‒1176, 84 p., https://doi.org/10.3133/ofr20161176.","productDescription":"v, 84 p.","numberOfPages":"92","onlineOnly":"Y","ipdsId":"IP-069929","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":331929,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1176/ofr20161176.pdf","text":"Report","size":"2.48 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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Eastern Geographic Science Center
U.S. Geological Survey
521 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Telephone: 703–648–4230
http://egsc.usgs.gov/
Time-series electromagnetic-induction log (TSEMIL) datasets are collected from polyvinyl-chloride cased or uncased monitoring wells to evaluate changes in water conductivity over time. TSEMIL datasets consist of a series of individual electromagnetic-induction logs, generally collected at a frequency of once per month or once per year that have been compiled into a dataset by eliminating small uniform offsets in bulk conductivity between logs probably caused by minor variations in calibration. These offsets are removed by selecting a depth at which no changes are apparent from year to year, and by adjusting individual logs to the median of all logs at the selected depth. Generally, the selected depths are within the freshwater saturated part of the aquifer, well below the water table. TSEMIL datasets can be used to monitor changes in water conductivity throughout the full thickness of an aquifer, without the need for long open-interval wells which have, in some instances, allowed vertical water flow within the well bore that has biased water conductivity profiles. The TSEMIL dataset compilation process enhances the ability to identify small differences between logs that were otherwise obscured by the offsets. As a result of TSEMIL dataset compilation, the root mean squared error of the linear regression between bulk conductivity of the electromagnetic-induction log measurements and the chloride concentration of water samples decreased from 17.4 to 1.7 millisiemens per meter in well G–3611 and from 3.7 to 2.2 millisiemens per meter in well G–3609. The primary use of the TSEMIL datasets in south Florida is to detect temporal changes in bulk conductivity associated with saltwater intrusion in the aquifer; however, other commonly observed changes include (1) variations in bulk conductivity near the water table where water saturation of pore spaces might vary and water temperature might be more variable, and (2) dissipation of conductive water in high-porosity rock layers, which might have entered these layers during drilling. Although TSEMIL dataset processing of even a few logs improves evaluations of the differences between the logs that are related to changes in the salinity, about 16 logs are needed to estimate the bulk conductivity within ±2 millisiemens per meter. Unlike many other types of data published by the U.S. Geological Survey, the median of TSEMIL datasets should not be considered final until 16 logs are collected and the median of the dataset is stable.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161194","usgsCitation":"Prinos, S.T., and Valderrama, Robert, 2016, Collection, processing, and quality assurance of time-series electromagnetic-induction log datasets, 1995–2016, south Florida: U.S. Geological Survey Open-File Report 2016–1194, 24 p., https://doi.org/10.3133/ofr20161194.","productDescription":"Report: vii, 24 p.; Data Release","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-069121","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":438492,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92Y62KV","text":"USGS data release","linkHelpText":"Time Series Electromagnetic Induction-Log Datasets, Including Logs Collected through the 2018 Water Year in South Florida"},{"id":438491,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70R9NPF","text":"USGS data release","linkHelpText":"Time Series Electromagnetic Induction-Log Datasets, Including Logs Collected through the 2017 Water Year in South Florida"},{"id":438490,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BG2MWD","text":"USGS data release","linkHelpText":"Time Series Electromagnetic Induction-Log Datasets, Including LogsCollected through the 2016 Water Year in South Florida"},{"id":332010,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F78W3BF5","text":"USGS data release - Time Series Electromagnetic Induction Log datasets","description":"USGS Data Release"},{"id":331983,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1194/coverthb.jpg"},{"id":331984,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1194/ofr20161194.pdf","text":"Report","size":"7.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1194"}],"country":"United States","state":"Florida","county":"Broward County, Glades County, Hendry County, Martin County, Miami-Dade County, Palm Beach County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.584716796875,\n 28.19792655722615\n ],\n [\n -80.2001953125,\n 27.430289738862594\n ],\n [\n -79.95849609375,\n 26.362342068998764\n ],\n [\n -80.04638671875,\n 25.97779895546436\n ],\n [\n -80.167236328125,\n 25.53252846853444\n ],\n [\n -80.474853515625,\n 25.11544539706194\n ],\n [\n -80.6396484375,\n 25.60190226111573\n ],\n [\n -80.96923828125,\n 26.49024045886963\n ],\n [\n -81.4306640625,\n 26.37218544169559\n ],\n [\n -81.661376953125,\n 27.059125784374068\n ],\n [\n -81.84814453125,\n 27.49852672279832\n ],\n [\n -80.584716796875,\n 28.19792655722615\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
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4446 Pet Lane, Suite 108
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Because natural patterns of streamflow are a fundamental property of the health of streams, there is a critical need to quantify the degree to which human activities have modified natural streamflows. A requirement for assessing streamflow modification in a given stream is a reliable estimate of flows expected in the absence of human influences. Although there are many techniques to predict streamflows in specific river basins, there is a lack of approaches for making predictions of natural conditions across large regions and over many decades. In this study conducted by the U.S. Geological Survey, in cooperation with The Nature Conservancy and Trout Unlimited, the primary objective was to develop empirical models that predict natural (that is, unaffected by land use or water management) monthly streamflows from 1950 to 2012 for all stream segments in California. Models were developed using measured streamflow data from the existing network of streams where daily flow monitoring occurs, but where the drainage basins have minimal human influences. Widely available data on monthly weather conditions and the physical attributes of river basins were used as predictor variables. Performance of regional-scale models was comparable to that of published mechanistic models for specific river basins, indicating the models can be reliably used to estimate natural monthly flows in most California streams. A second objective was to develop a model that predicts the likelihood that streams experience modified hydrology. New models were developed to predict modified streamflows at 558 streamflow monitoring sites in California where human activities affect the hydrology, using basin-scale geospatial indicators of land use and water management. Performance of these models was less reliable than that for the natural-flow models, but results indicate the models could be used to provide a simple screening tool for identifying, across the State of California, which streams may be experiencing anthropogenic flow modification.
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\"}}]}","contact":"Chief, National Water-Quality Assessment Program
U.S. Geological Survey
413 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The purpose of this project was to map the estimated distribution of grassland communities of the Southern Great Plains prior to Euro-American settlement. The Southern Great Plains Rapid Ecoregional Assessment (REA), under the direction of the Bureau of Land Management and the Great Plains Landscape Conservation Cooperative, includes four ecoregions: the High Plains, Central Great Plains, Southwestern Tablelands, and the Nebraska Sand Hills. The REA advisors and stakeholders determined that the mapping accuracy of available national land-cover maps was insufficient in many areas to adequately address management questions for the REA. Based on the recommendation of the REA stakeholders, we estimated the potential historical distribution of 10 grassland communities within the Southern Great Plains project area using data on soils, climate, and vegetation from the Natural Resources Conservation Service (NRCS) including the Soil Survey Geographic Database (SSURGO) and Ecological Site Information System (ESIS). The dominant grassland communities of the Southern Great Plains addressed as conservation elements for the REA area are shortgrass, mixed-grass, and sand prairies. We also mapped tall-grass, mid-grass, northwest mixed-grass, and cool season bunchgrass prairies, saline and foothill grasslands, and semi-desert grassland and steppe. Grassland communities were primarily defined using the annual productivity of dominant species in the ESIS data. The historical grassland community classification was linked to the SSURGO data using vegetation types associated with the predominant component of mapped soil units as defined in the ESIS data. We augmented NRCS data with Landscape Fire and Resource Management Planning Tools (LANDFIRE) Biophysical Settings classifications 1) where NRCS data were unavailable and 2) where fifth-level watersheds intersected the boundary of the High Plains ecoregion in Wyoming. Spatial data representing the estimated historical distribution of grassland communities of the Southern Great Plains are provided as a 30 x 30-meter gridded surface (raster dataset). This information will help to address the priority management questions for grassland communities for the Southern Great Plains REA and can be used to inform other regional-level land management decisions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161184","collaboration":"Prepared in cooperation with the Bureau of Land Management and the Great Plains Landscape Conservation Cooperative","usgsCitation":"Reese, G.C., Manier, D.J., Carr, N.B., Callan, Ramana, Leinwand, I.I.F., Assal, T.J., Burris, Lucy, and Ignizio, D.A., 2016, Estimated historical distribution of grassland communities of the Southern Great Plains: U.S. Geological Survey Open-File Report 2016–1184, 13 p., https://doi.org/10.3133/ofr20161184. ","productDescription":"Report: v, 13 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-077037","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":438494,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71Z42J3","text":"USGS data release","linkHelpText":"Estimated distribution of historical grassland communities of the Southern Great Plains"},{"id":331479,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F71Z42J3","text":"Estimated historical distribution of grassland communities of the Southern Great Plains","size":"228.75 MB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1184 Data Release"},{"id":331184,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1184/coverthb.jpg"},{"id":331185,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1184/ofr20161184.pdf","text":"Report","size":"3.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1184"}],"country":"United States","otherGeospatial":"Southern Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109,\n 30\n ],\n [\n -109,\n 43.5\n ],\n [\n -94,\n 43.5\n ],\n [\n -94,\n 30\n ],\n [\n -109,\n 30\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, USGS Fort Collins Science Center
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
The U.S. Geological Survey collected high-resolution seismic-reflection data in September 2009, on survey S-8-09-NC, offshore of northern California between Bolinas and Sea Ranch.
The survey area spans about 125 km of California’s coast and extends around Point Reyes. Data were collected aboard the U.S. Geological Survey R/V Parke Snavely. Cumulatively, ~1,150 km of seismic-reflection data were acquired using a SIG 2mille minisparker. Subbottom acoustic depth of penetration spanned tens to several hundred meters and varied by location and underlying sediments and rock types.
This report includes maps and a navigation file of the surveyed transects, utilizing Google Earth™ software, as well as digital data files showing images of each transect in SEG-Y and JPEG formats. The images of bedrock, sediment deposits, and tectonic structure provide geologic information that is essential to hazard assessment, regional sediment management, and coastal and marine spatial planning at Federal, State and local levels. This information is also valuable for future research on the geomorphic, sedimentary, tectonic, and climatic record of central California.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161058","usgsCitation":"Sliter, R.W., Johnson, S.Y., Chin, J.L., Allwardt, P., Beeson, J., and Triezenberg, P.J., 2016, High-resolution seismic-reflection data from offshore of northern California—Bolinas to Sea Ranch: U.S. Geological Survey Open-File Report 2016–1058, https://dx.doi.org/10.3133/ofr20161058.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079352","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":330668,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1058","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"OFR 2016-1058 HTML"},{"id":330667,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1058/images/coverthb.jpg"}],"country":"United States","state":"California","city":"Bolinas, Sea Ranch","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.75299072265624,\n 37.83798775896512\n ],\n [\n -123.0853271484375,\n 37.95502661288625\n ],\n [\n -123.10729980468749,\n 38.04160203158016\n ],\n [\n -123.101806640625,\n 38.23386541556985\n ],\n [\n -123.4808349609375,\n 38.528830289587674\n ],\n [\n -123.662109375,\n 38.74337300148123\n ],\n [\n -123.51104736328125,\n 38.83328935686689\n ],\n [\n -123.035888671875,\n 38.43207668538207\n ],\n [\n -122.63763427734375,\n 37.90736658145496\n ],\n [\n -122.75299072265624,\n 37.83798775896512\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
We estimated abundance and trends of non-native mountain goats (Oreamnos americanus) in the Olympic Mountains of northwestern Washington, based on aerial surveys conducted during July 13–24, 2016. The surveys produced the seventh population estimate since the first formal aerial surveys were conducted in 1983. This was the second population estimate since we adjusted survey area boundaries and adopted new estimation procedures in 2011. Before 2011, surveys encompassed all areas free of glacial ice at elevations above 1,520 meters (m), but in 2011 we expanded survey unit boundaries to include suitable mountain goat habitats at elevations between 1,425 and 1,520 m. In 2011, we also began applying a sightability correction model allowing us to estimate undercounting bias associated with aerial surveys and to adjust survey results accordingly. The 2016 surveys were carried out by National Park Service (NPS) personnel in Olympic National Park and by Washington Department of Fish and Wildlife (WDFW) biologists in Olympic National Forest and in the southeastern part of Olympic National Park. We surveyed a total of 59 survey units, comprising 55 percent of the 60,218-hectare survey area. We estimated a mountain goat population of 623 ±43 (standard error, SE). Based on this level of estimation uncertainty, the 95-percent confidence interval ranged from 561 to 741 mountain goats at the time of the survey.
We examined the rate of increase of the mountain goat population by comparing the current population estimate to previous estimates from 2004 and 2011. Because aerial survey boundaries changed between 2004 and 2016, we recomputed population estimates for 2011 and 2016 surveys based on the revised survey boundaries as well as the previously defined boundaries so that estimates were directly comparable across years. Additionally, because the Mount Washington survey unit was not surveyed in 2011, we used results from an independent survey of the Mount Washington unit conducted by WDFW biologists in 2012 and combined it with the 2011 survey results to produce a complete survey conducted over 2 years. The revised estimates of mountain goat abundance occurring at elevations above 1,520 m were 230 ±19 (SE) in 2004, 350 ±41 (SE) in 2011, and 584 ±39 (SE) in 2016. The difference between the overall 2016 population estimate (623 ±43 [SE]) and the smaller estimate (584 ±39 [SE]) reflected the number of mountain goats counted in the expanded survey areas added in 2011. Based on comparisons within the standardized survey boundary, the mountain goat population in the Olympic Mountains increased at an average finite rate of 6 percent annually from 2004 to 2011, 11 percent annually from 2011 to 2016, and 8 percent annually over the combined period. We caution that the population may have been underestimated in 2011 because of record heavy snows persisting into the survey season. Therefore, the rate of population increase from 2011 and 2016 may be overestimated. The rate of increase measured over the combined period (2004–16) may be more representative of the recent population growth. We conclude that the abundance of mountain goats has increased for more than a decade, and if the recent average rate of population growth were sustained, the population would increase by 45 percent over the next 5 years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161185","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Jenkins, K.J., Happe, P.J., Beime, K.F., and Baccus, W.T., 2016, Mountain goat abundance and population trends in the Olympic Mountains, northwestern Washington, 2016: U.S. Geological Survey Open-File Report 2016–1185, 21 p., https://doi.org/10.3133/ofr20161185.","productDescription":"iv, 21 p.","onlineOnly":"Y","ipdsId":"IP-080401","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":331287,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1185/coverthb.jpg"},{"id":331288,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1185/ofr20161185.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1185 Report PDF"}],"country":"United States","state":"Washington","otherGeospatial":"Olympic Mountains, Olympic National Forest, Olympic National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123,\n 48\n ],\n [\n -123,\n 47.5\n ],\n [\n -124,\n 47.5\n ],\n [\n -124,\n 48\n ],\n [\n -123,\n 48\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
This report provides supporting details and evidence for the rationale, validity and efficacy of a new mark-recapture model, the Barker Robust Design, to estimate regional manatee survival rates used to parameterize several components of the 2012 version of the Manatee Core Biological Model (CBM) and Threats Analysis (TA). The CBM and TA provide scientific analyses on population viability of the Florida manatee subspecies (Trichechus manatus latirostris) for U.S. Fish and Wildlife Service’s 5-year reviews of the status of the species as listed under the Endangered Species Act. The model evaluation is presented in a standardized reporting framework, modified from the TRACE (TRAnsparent and Comprehensive model Evaluation) protocol first introduced for environmental threat analyses. We identify this new protocol as TRACE-MANATEE SURVIVAL and this model evaluation specifically as TRACE-MANATEE SURVIVAL, Barker RD version 1. The longer-term objectives of the manatee standard reporting format are to (1) communicate to resource managers consistent evaluation information over sequential modeling efforts; (2) build understanding and expertise on the structure and function of the models; (3) document changes in model structures and applications in response to evolving management objectives, new biological and ecological knowledge, and new statistical advances; and (4) provide greater transparency for management and research review.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161163","usgsCitation":"Langtimm, C.A., Kendall, W.L., Beck, C.A., Kochman, H.I., Teague, A.L., Meigs-Friend, Gaia, and Peñaloza, C.L., 2016, Model description and evaluation of the mark-recapture survival model used to parameterize the 2012 status and threats analysis for the Florida manatee (Trichechus manatus latirostris): U.S. Geological Survey Open-File Report 2016–1163, 20 p.,\nhttps://doi.org/10.3133/ofr20161163.","productDescription":"v, 20 p.","onlineOnly":"Y","ipdsId":"IP-065130","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":331034,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1163/coverthb.jpg"},{"id":331035,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1163/ofr20161163.pdf","text":"Report","size":"215 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1163"}],"contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71st Street
Gainesville, FL 32653
https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc
","tableOfContents":"