Discharge, suspended sediment, and salinity data collected between 1997 and 2008 indicate that the Gulf Intracoastal Waterway (GIWW) is an important distributary of river water and suspended sediments to coastal wetlands in south-central coastal Louisiana. Following natural hydraulic gradients, the GIWW passively distributes freshwater and suspended sediments from the Atchafalaya River to areas at least 30 to 50 miles west and east, respectively, of Morgan City. The magnitude and reach of the discharge in the GIWW increase as stage of the Wax Lake Outlet at Calumet and Lower Atchafalaya River (LAR) at Morgan City increase. The magnitude and duration of discharge vary from year to year depending on the flow regime of the Atchafalaya River. Annual discharge of water in the GIWW was greater during years when stage of the LAR remained anomalously high throughout the year, compared with average and peak flood years. During years when Atchafalaya River flow is low, Bayou Boeuf, a waterway draining the Verret subbasin, becomes a major source of water maintaining the eastward flow in the GIWW. The GIWW is the only means of getting river water to some parts of coastal Louisiana.
\nThe length of time stage of the LAR at Morgan City exceeds a given height has increased from the 1940s to 2008. This shift has increased the length of time the GIWW functions as a predictable distributary of river water each year. Similar shifts in the future could be expected to increase the duration and amounts of river water reaching coastal Louisiana wetlands through the GIWW.
\nMedian suspended-sediment concentrations in the GIWW to the west of Morgan City were around 160 milligrams per liter (mg/L). In the GIWW east of Morgan City, median concentrations were 120–160 mg/L, except in Bayou Boeuf at Railroad Bridge in Amelia and the parts of the GIWW between Bayou Boeuf and the Houma Navigation Canal; median concentrations here were around 100 mg/L.
\nRiver water penetrates much of the Louisiana coast, as demonstrated by the large year-to-year fluctuations in salinity regimes of intradistributary basins in response to differences in flow regimes of the Mississippi and the Atchafalaya Rivers. This occurs directly through inflow along the GIWW and through controlled diversions and indirectly by transport into basin interiors after mixing with the Gulf of Mexico. The GIWW plays an important role in moderating salinity in intradistributary basins; for example, salinity in surface waters just south of the GIWW between Bayou Boeuf and the Houma Navigation Canal remained low even during a year with prolonged low water (2000).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155132","usgsCitation":"Swarzenski, C.M., and Perrien, S.M., 2015, Discharge, suspended sediment, and salinity in the Gulf Intracoastal Waterway and adjacent surface waters in south-central Louisiana, 1997–2008: U.S. Geological Survey Scientific Investigations Report 2015–5132, 21 p., https://dx.doi.org/10.3133/sir20155132.","productDescription":"v, 21 p.","numberOfPages":"30","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":309802,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5132/sir20155132.pdf","text":"Report","size":"1.09 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5132"},{"id":309801,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5132/coverthb.jpg"}],"country":"United States","state":"Louisiana","city":"Houma City, Morgan City","otherGeospatial":"Atchafalaya River, Cypremort Point, Bayou Lafourche, Verret subbasin, Barataria Basin, Terrebonne Basin, Vermilion-Teche Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.26318359375,\n 28.998531814051795\n ],\n [\n -92.26318359375,\n 30.65681556429287\n ],\n [\n -89.80224609374999,\n 30.65681556429287\n ],\n [\n -89.80224609374999,\n 28.998531814051795\n ],\n [\n -92.26318359375,\n 28.998531814051795\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
3535 S. Sherwood Forest Blvd., Suite 120
Baton Rouge, LA 70816
http://la.water.usgs.gov/
The extent, hydrogeologic framework, and potential well yields of valley-fill aquifers within a 151-square-mile area of eastern Chemung County, New York, were investigated, and the upland distribution of till thickness over bedrock was characterized. The hydrogeologic framework of these valleyfill aquifers was interpreted from multiple sources of surficial and subsurface data and an interpretation of the origin of the glacial deposits, particularly during retreat of glacial ice from the region. Potential yields of screened wells are based on the hydrogeologic framework interpretation and existing well-yield data, most of which are from wells finished with open-ended well casing.
\nWater-resource potential is greatest within saturated sand and gravel in the Chemung River valley (nearly 1 mile wide), especially where induced infiltration of additional water from the Chemung River is possible. The second most favorable area is the Newtown Creek valley at the confluence of Newtown Creek with North Branch Newtown Creek east of Horseheads, N.Y. Extensive sand and gravel deposits within the Breesport, N.Y., area are largely unsaturated but may have greater saturation along the east side of Jackson Creek immediately north of Breesport. Till deposits confine sand and gravel along Newtown Creek at Erin, N.Y., and along much of the upper reach of North Branch Newtown Creek; this confining unit may limit recharge and potential well yield. The north-south oriented valleys of Baldwin and Wynkoop Creeks end at notched divides that imply input of glacial meltwater and limited sediment from outside of the present watersheds. These two valleys are relatively narrow but contain variably sorted sand and gravel, which, in places, may be capable of supplying modest-size community water systems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155092","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Heisig, P.M., 2015, Hydrogeology of valley-fill aquifers and adjacent areas in eastern Chemung County, New York: U.S. Geological Survey Scientific Investigations Report 2015–5092, 19 p. plus appendix and 1 pl., https://dx.doi.org/10.3133/sir20155092.","productDescription":"Report: vi, 18 p.; Plate: 36 x 48 inches; HTML Document; Appendix","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-056841","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":310038,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5092/images/coverthb.jpg"},{"id":310043,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5092/pdf/sir20155092.pdf","text":"Report","size":"7.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5092"},{"id":310039,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2015/5092/plate.html","text":"SIR 2015-5092 - Plate Instructions","linkFileType":{"id":5,"text":"html"},"description":"SIR 2015-5092"},{"id":310048,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2015/5092/pdf/sir20155092_plate1.pdf","text":"SIR 2015-5092 - Plate 1 - 36” x 48”","size":"63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5092"},{"id":310040,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5092/attachments/sir20155092_appendix1.xlsx","text":"SIR 2015-5092 - Appendix 1","size":"86 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5092"}],"country":"United States","state":"New York","county":"Chemung County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.53051757812499,\n 42.00032514831621\n ],\n [\n -77.53051757812499,\n 42.706659563510385\n ],\n [\n -76.22863769531249,\n 42.706659563510385\n ],\n [\n -76.22863769531249,\n 42.00032514831621\n ],\n [\n -77.53051757812499,\n 42.00032514831621\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
(518) 285-5602
Visit our Web site at:
http://ny.water.usgs.gov
This study provides viable estimates of historical storm-induced water levels in the coastal communities of Gambell and Savoonga situated on St. Lawrence Island in the Bering Sea, as well as Unalakleet located at the head of Norton Sound on the western coast of Alaska. Gambell, Savoonga, and Unalakleet are small Native Villages that are regularly impacted by coastal storms but where little quantitative information about these storms exists. The closest continuous water-level gauge is at Nome, located more than 200 kilometers from both St. Lawrence Island and Unalakleet. In this study, storms are identified and quantified using historical atmospheric and sea-ice data and then used as boundary conditions for a suite of numerical models. The work includes storm-surge (temporary rise in water levels due to persistent strong winds and low atmospheric pressures) modeling in the Bering Strait region, as well as modeling of wave runup along specified sections of the coast in Gambell and Unalakleet. Modeled historical water levels are used to develop return periods of storm surge and storm surge plus wave runup at key locations in each community. It is anticipated that the results will fill some of the data void regarding coastal flood data in western Alaska and be used for production of coastal vulnerability maps and community planning efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151193","usgsCitation":"Erikson, L., McCall, R.T., van Rooijen, A., and Norris, B., 2015, Hindcast storm events in the Bering Sea for the St. Lawrence Island and Unalakleet Regions, Alaska: U.S. Geological Survey Open-File Report 2015-1193, vii, 47 p., https://doi.org/10.3133/ofr20151193.","productDescription":"vii, 47 p.","numberOfPages":"57","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059633","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":309820,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1193/coverthb.jpg"},{"id":309821,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1193/ofr20151193.pdf","text":"Report","size":"3.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1192"}],"country":"United States","state":"Alaska","otherGeospatial":"Bering Sea, St. Lawrence Island, Unalakleet Regions","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -171.87011718749997,\n 63.84066844285508\n ],\n [\n -171.36474609375,\n 63.75334975181205\n ],\n [\n -171.01318359374997,\n 63.6949869286095\n ],\n [\n -170.595703125,\n 63.80189351770543\n ],\n [\n -169.892578125,\n 63.66576033778838\n ],\n [\n -169.56298828124997,\n 63.470144746565445\n ],\n [\n -168.64013671875,\n 63.37183226679281\n ],\n [\n -168.55224609375,\n 63.05495931065107\n ],\n [\n -169.21142578125,\n 63.06491420208559\n ],\n [\n -169.56298828124997,\n 62.865168668923125\n ],\n [\n -170.22216796875,\n 62.94523066452288\n ],\n [\n -170.52978515624997,\n 63.22373025329546\n ],\n [\n -171.2109375,\n 63.28306240110864\n ],\n [\n -171.54052734375,\n 63.22373025329546\n ],\n [\n -172.06787109375,\n 63.361982464431236\n ],\n [\n -171.87011718749997,\n 63.84066844285508\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -161.69677734375,\n 64.74601725111455\n ],\n [\n -161.38916015625,\n 64.830253743883\n ],\n [\n -160.7080078125,\n 64.830253743883\n ],\n [\n -160.55419921875,\n 64.67091929440798\n ],\n [\n -160.59814453125,\n 64.37794095121995\n ],\n [\n -160.75195312499997,\n 64.20637724320852\n ],\n [\n -161.25732421875,\n 64.07219957867284\n ],\n [\n -162.09228515625,\n 64.19681461100495\n ],\n [\n -161.982421875,\n 64.58618480339979\n ],\n [\n -161.806640625,\n 64.74601725111455\n ],\n [\n -161.69677734375,\n 64.74601725111455\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/
In 2009, the U.S. Geological Survey, in cooperation with the city of Needles, began a study of the hydrogeology along the All-American Canal, which conveys water from the Colorado River to the Imperial Valley. The focus of this study was to gain a better understanding of the effect of lining the All-American Canal, and other management actions, on future total dissolved solids concentrations in groundwater pumped by Lower Colorado Water Supply Project wells that is delivered to the All-American Canal. The study included the compilation and evaluation of previously published hydrogeologic and geochemical information, establishment of a groundwater-elevation and groundwater-quality monitoring network, results of monitoring groundwater elevations and groundwater quality from 2009 to 2011, site-specific hydrologic investigations of the Lower Colorado Water Supply Project area, examination of groundwater salinity by depth by using time-domain electromagnetic surveys, and monitoring of groundwater-storage change by using microgravity methods.
\nPrior to the completion of the All-American Canal in 1940, groundwater in the study area flowed from east to west, and groundwater was recharged primarily by underflow from the Colorado River Valley. After construction of the All-American Canal, groundwater elevations were altered in the study area as seepage of Colorado River water from the All-American Canal and other canals became the dominant recharge source. By 2005, groundwater elevations had increased by as much as 50–70 feet along the All-American Canal. Superimposed on the east-to-west groundwater gradient was groundwater movement away from the All-American Canal to the north and, most likely, to the south into Mexico. After lining the All-American Canal, from 2007 to 2010, groundwater elevations declined as seepage from the All-American Canal decreased. Between 2005 (the last complete groundwater-elevation survey prior to lining the All-American Canal) and 2011, groundwater elevations declined 20–40 feet along the All-American Canal and as much as 40–45 feet in the vicinity of Lower Colorado Water Supply Project pumping wells.
\nWater-quality and isotope data were used to differentiate historically recharged groundwater from groundwater more recently recharged by seepage of Colorado River surface water from the All-American Canal. Prior to the completion of the All-American Canal in 1940, groundwater in the southern part of the study area was primarily sodium-chloride/sulfate type water that had relatively low total dissolved solids concentrations (500–820 milligrams per liter). During 2007–11, groundwater in the southern part of the study area, near the All-American Canal, ranged from sodium-chloride type water to mixed-cation-sulfate type water that had total dissolved solids concentrations generally less than 879 milligrams per liter. The stable-isotopic signature of groundwater near the All-American Canal sampled in 2009–11 indicated inputs of Colorado River water that had been affected by evaporation, and radioactive isotopes indicated that a substantial fraction of water had been recharged recently, within the past 60 years. This contrasted with historically recharged groundwater near the All-American Canal, which had higher sodium and chloride concentrations, and lower calcium and sulfate concentrations, than recent recharge from the All-American Canal.
\nGroundwater at a distance from the All-American Canal, in the East Mesa, Algodones Dunes, Pilot Knob Mesa, and Cargo Muchacho Mountains piedmont, was found to have higher total dissolved solids concentrations (generally greater than 1,000 milligrams per liter) than recently recharged groundwater near the All-American Canal. Time-domain electromagnetic data indicated that low-salinity groundwater was present down to about 377 feet below land surface near the All-American Canal; groundwater salinity at depth increased with distance north from the All-American Canal. Groundwater several miles or more from the canal also did not contain tritium and had a residence time on the order of thousands to tens of thousands of years. The groundwater in the piedmont of the Cargo Muchacho Mountains had a distinctly light stable-isotopic signature indicative of recharge by runoff from local precipitation, whereas the stable isotopic signature of groundwater in the East Mesa and the Algodones Dunes indicated a mixture of local precipitation and historic Colorado River recharge sources.
\nDuring and after lining the All-American Canal (2007–11), groundwater elevations in the Lower Colorado Water Supply Project area declined, while total dissolved solids concentrations remained relatively constant. The total dissolved solids concentrations in well LCWSP-2 ranged from 650 to 800 milligrams per liter during this study. Depth-specific water-quality and isotope sampling at well LCWSP-2 indicated the groundwater pumped from the deeper part of the screened interval (240–280 feet below land surface) contained a greater proportion of historical groundwater than the groundwater pumped from the shallower part of the screened interval (350–385 feet below land surface). Age-tracer data at well LCWSP-2 indicated that all depths of the screened interval had received recent recharge from seepage of Colorado River water from the All-American Canal.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155102","collaboration":"Prepared in cooperation with the city of Needles, California","usgsCitation":"Coes, A.L., Land, M., Densmore, J.N., Landrum, M.T., Beisner, K.R., Kennedy, J.R., Macy, J.P., and Tillman, F., 2015, Initial characterization of the groundwater system near the Lower Colorado Water Supply Project, Imperial Valley, California: U.S. Geological Survey Scientific Investigations Report 2015-5102, Report: viii, 59 p.; Appendix: 1, https://doi.org/10.3133/sir20155102.","productDescription":"Report: viii, 59 p.; Appendix: 1","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-019073","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":309788,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5102/sir20155102_appendix1.xlsx","text":"Appendix 1","size":"56 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5102 Appendix 1"},{"id":309894,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5102/coverthb2.jpg"},{"id":309787,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5102/sir20155102.pdf","text":"Report","size":"17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5102"}],"country":"United States","state":"California","otherGeospatial":"Imperial Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.87829589843751,\n 32.72721987021932\n ],\n [\n -115.87829589843751,\n 33.06852769197118\n ],\n [\n -114.71923828124999,\n 33.06852769197118\n ],\n [\n -114.71923828124999,\n 32.72721987021932\n ],\n [\n -115.87829589843751,\n 32.72721987021932\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
http://ca.water.usgs.gov
The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, constructed Precipitation-Runoff Modeling System models to estimate daily streamflow for nine river basins in eastern Iowa that drain into the Mississippi River. The models are part of a suite of methods for estimating daily streamflow at ungaged sites. The Precipitation-Runoff Modeling System is a deterministic, distributed- parameter, physical-process-based modeling system developed to evaluate the response of streamflow and general drainage basin hydrology to various combinations of climate and land use. Calibration and validation periods used in each basin mostly were October 1, 2002, through September 30, 2012, but differed depending on the period of record available for daily mean streamflow measurements at U.S. Geological Survey streamflow-gaging stations.
\nA geographic information system tool was used to delineate each basin and estimate values for model parameters based on basin physical and geographical features. A U.S. Geological Survey auto-calibration tool that uses a shuffled complex evolution algorithm was used for initial calibration, and then manual modifications were made to parameter values to complete the calibration of each basin model. The main objective of the calibration was to match daily discharge values of simulated streamflow to measured daily discharge values.
\nThe accuracy of Precipitation-Runoff Modeling System model streamflow estimates of nine river basins in eastern Iowa as compared to measured values at U.S. Geological Survey streamflow-gaging stations varied. The Precipitation-Runoff Modeling System models of nine river basins in eastern Iowa were satisfactory at estimating daily streamflow at 57 of the 79 calibration sites and 13 of the 14 validation sites based on statistical results. Unsatisfactory performance can be contributed to several factors: (1) low flow, no flow, and flashy flow conditions in headwater subbasins having a small drainage area; (2) poor representation of the groundwater and storage components of flow within a basin; (3) lack of accounting for basin withdrawals and water use; and (4) the availability and accuracy of meteorological input data. The Precipitation- Runoff Modeling System models of nine river basins in eastern Iowa will provide water-resource managers with a consistent and documented method for estimating streamflow at ungaged sites and aid in environmental studies, hydraulic design, water management, and water-quality projects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155129","collaboration":"Prepared in cooperation with the Iowa Department of Natural Resources","usgsCitation":"Haj, A.E., Christiansen, D.E., and Hutchinson, K.J., 2015, Simulation of daily streamflow for nine river basins in eastern\nIowa using the Precipitation-Runoff Modeling System: U.S. Geological Survey Scientific Investigations Report\n2015–5129, 29 p., https://dx.doi.org/10.3133/sir20155129.","productDescription":"iv, 29 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-067401","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":309818,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5129/coverthb.jpg"},{"id":309819,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5129/sir20155129.pdf","text":"Report","size":"20.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5129"}],"country":"United States","state":"Iowa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.263427734375,\n 43.810747313446996\n ],\n [\n -96.04248046875,\n 43.96909818325174\n ],\n [\n -94.50439453125,\n 41.07935114946899\n ],\n [\n -92.64770507812499,\n 40.59727063442027\n ],\n [\n -91.40625,\n 40.245991504199026\n ],\n [\n -90.94482421875,\n 40.98819156349393\n ],\n [\n -91.12060546875,\n 41.3025710943056\n ],\n [\n -91.01074218749999,\n 41.45919537950706\n ],\n [\n -90.3515625,\n 41.566141964768384\n ],\n [\n -90.120849609375,\n 42.02481360781777\n ],\n [\n -90.439453125,\n 42.35042512243457\n ],\n [\n -90.72509765625,\n 42.62587560259137\n ],\n [\n -91.03271484375,\n 42.71473218539458\n ],\n [\n -91.175537109375,\n 43.14909399920127\n ],\n [\n -91.0546875,\n 43.31718491566708\n ],\n [\n -91.25244140624999,\n 43.46089378008257\n ],\n [\n -91.263427734375,\n 43.810747313446996\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Iowa Water Science Center
U.S. Geological Survey
P.O. Box 1230
Iowa City, IA 52244
http://ia.water.usgs.gov/
The use of acoustic and other parameters as surrogates for suspended-sediment concentrations (SSC) in rivers has been successful in multiple applications across the Nation. Tools to process and evaluate the data are critical to advancing the operational use of surrogates along with the subsequent development of regression models from which real-time sediment concentrations can be made available to the public. Recent developments in both areas are having an immediate impact on surrogate research and on surrogate monitoring sites currently (2015) in operation.
\nThe Surrogate Analysis and Index Developer (SAID) standalone tool, under development by the U.S. Geological Survey (USGS), assists in the creation of linear regression models that relate constituent and surrogate parameters by providing visual and quantitative diagnostics to the user. SAID also processes acoustic parameters to be used as explanatory variables for SSC. The sediment acoustic method utilizes acoustic parameters from fixed-mount stationary equipment. The theory and method used by the SAID tool have been described in recent publications. The tool also serves to support sediment-acoustic-index methods and other surrogate guidelines such as turbidity and SSC (Rasmussen and others, 2009).
\nThe regression models created in SAID can be used in utilities that have been developed to work with the USGS National Water Information System (NWIS) and for the USGS National Real-Time Water Quality (NRTWQ) Web site. The real-time dissemination of predicted SSC and prediction intervals for each time step has substantial potential to improve understanding of sediment-related water quality and associated engineering and ecological management decisions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151177","collaboration":"Federal Interagency Sedimentation Project and Midwest Region River Sediments and Nutrients Investigations Initiative","usgsCitation":"Domanski, M.M., Straub, T.D., and Landers, M.N., 2015, Surrogate Analysis and Index Developer (SAID) tool (version 1.0, September 2015): U.S. Geological Survey Open-File Report 2015–1177, 38 p., https://doi.org/10.3133/ofr20151177.","productDescription":"Report: vi, 36 p.; HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066947","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":309366,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1177/coverthb.jpg"},{"id":309367,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1177/ofr20151177.pdf","text":"Report","size":"1.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1177"},{"id":309845,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://water.usgs.gov/osw/SALT/SAID/","text":"The Surrogate Analysis and Index Developer (SAID) Tool","linkFileType":{"id":5,"text":"html"},"description":"OFR 2015-1177"}],"contact":"Director, llinois Water Science Center
405 N Goodwin
Urbana, IL 61801
http://il.water.usgs.gov/
Digital flood-inundation maps for a 5.3-mile reach of South Fork Peachtree Creek that extends from about 500 feet above the Brockett Road bridge to the Willivee Drive bridge were developed by the U.S. Geological Survey (USGS) in cooperation with DeKalb County, Georgia. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at South Fork Peachtree at Casa Drive, near Clarkston, Georgia (02336152). Real-time stage information from this USGS streamgage may be obtained at http://waterdata.usgs.gov/ and can be used in conjunction with these maps to estimate near real-time areas of inundation. The National Weather Service (NWS) is incorporating results from this study into the Advanced Hydrologic Prediction Service (AHPS) flood-warning system (http://water.weather.gov/ahps/).
\nA one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers HEC–RAS software for South Fork Peachtree Creek and was used to compute flood profiles for a 5.3-mile reach of South Fork Peachtree Creek. The model was calibrated using the most current (2015) stage-discharge relation at the USGS streamgage South Fork Peachtree at Casa Drive, near Clarkston, Georgia (02336152). The hydraulic model was then used to simulate 13 water-surface profiles at 0.5-foot intervals at the South Fork Peachtree Creek near Clarkston streamgage. The profiles ranged from just above bankfull stage (6.0 feet) to approximately 3.21 feet above the highest recorded water level (12.0 feet). The simulated water-surface profiles were then combined with a geographic information system digital elevation model—derived from light detection and ranging data having a 5.0-foot horizontal resolution—to delineate the area flooded at each 0.5-foot interval of stream stage.
\nThe availability of these flood-inundation maps, when combined with real-time stage information from USGS streamgages, provides emergency management personnel and residents with critical information during flood-response activities, such as evacuations and road closures, in addition to post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3347","collaboration":"Prepared in cooperation with DeKalb County, Georgia","usgsCitation":"Musser, J.W., 2015, Flood-inundation maps for South Fork Peachtree Creek from the Brockett Road bridge to the Willivee Drive bridge, DeKalb County, Georgia: U.S. Geological Survey Scientific Investigations Map 3347, 13 sheets, 10-p. pamphlet, https://dx.doi.org/10.3133/sim3347.","productDescription":"Report: vi, 10 p.; 13 Sheets: 30.50 x 21.00 inches; Metadata; Raw Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-068577","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":309770,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3347/pdf/sim3347_sheet5.pdf","text":"Sheet05 - Gage height of 8.0 feet and an elevation of 940.2 feet at streamgage 02336152","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3347"},{"id":309771,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3347/pdf/sim3347_sheet6.pdf","text":"Sheet06 - 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Inundatation Layer Metadata","size":"60.7 KB","linkFileType":{"id":5,"text":"html"},"description":"SIM 3347"},{"id":309768,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3347/pdf/sim3347_sheet3.pdf","text":"Sheet03 - Gage height of 7.0 feet and an elevation of 939.2 feet at streamgage 02336152","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3347"},{"id":309769,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3347/pdf/sim3347_sheet4.pdf","text":"Sheet04 - Gage height of 7.5 feet and an elevation of 939.7 feet at streamgage 02336152","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3347"},{"id":309778,"rank":15,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3347/pdf/sim3347_sheet13.pdf","text":"Sheet13 - Gage height of 12.0 feet and an elevation of 944.2 feet at streamgage 02336152","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3347"},{"id":309765,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3347/pdf/sim3347_pamphlet.pdf","text":"Report - SIM 3347 Pamphlet","size":"1.61 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3347"},{"id":309766,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3347/pdf/sim3347_sheet1.pdf","text":"Sheet01 - Gage height of 6.0 feet and an elevation of 938.2 feet at streamgage 02336152","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3347"},{"id":309767,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3347/pdf/sim3347_sheet2.pdf","text":"Sheet02 - Gage height of 6.5 feet and an elevation of 938.7 feet at streamgage 02336152","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3347"},{"id":309795,"rank":16,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3347/downloads/sim3347_depth-grid-metadata.html","text":"SIM 3347 - Depth-grid Metadata","size":"61.7 KB","linkFileType":{"id":5,"text":"html"},"description":"SIM 3347"},{"id":309764,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3347/coverthb.jpg"}],"country":"United States","state":"Georgia","county":"DeKalb County","otherGeospatial":"South Fork Peachtree Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.45671081542969,\n 33.777720492564896\n ],\n [\n -84.45671081542969,\n 33.83933825431594\n ],\n [\n -84.24694061279297,\n 33.83933825431594\n ],\n [\n -84.24694061279297,\n 33.777720492564896\n ],\n [\n -84.45671081542969,\n 33.777720492564896\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
Changes to barrier islands occur at time scales that vary from the few hours it takes an individual storm to pass (Morton, 2008) to the millennia it takes for coastal systems to undergo geologic evolution. Developing an understanding of how barrier islands will respond to climate change, sea level rise, and major storms over a range of time scales is relevant to studies of physical, geological, ecological, and societal processes and will help to guide and improve management of our coastal resources (Sallenger and others, 1987). Observations of coastal processes made over a range of spatial and temporal scales and from a variety of instrument platforms (for example, in situ and remote remote sensing) are required to understand and eventually predict the evolution of coastal systems.
\nThe deployment of Landsat and other earth-observing satellites within the last few decades has provided an opportunity to observe barrier islands at frequent intervals, often many times a year. This sample frequency is much higher and the spatial coverage much greater than most routine high-resolution topographic surveys (Guy and others, 2014). In addition, the historical record of these datasets have become long enough to document shorter- (that is, annual) and longer-term (that is, decadal) changes from a single data source. Certain aspects of barrier island morphology, such as island size, shape, and position, can be determined from these images and can indicate erosion, land loss, and island breakup (McBride and others, 1989; Plant and Guy, 2013).
\nThe shoreline is a common variable used as a metric for coastal erosion or change (Himmelstoss and others, 2010). Although shorelines are often extracted from topographic data (for example, ground-based surveys and light detection and ranging [lidar]), image-based shorelines, corrected for their inherent uncertainties (Moore and others, 2006), have provided much of our understanding of long-term shoreline change because they pre-date routine lidar elevation survey methods. Image-based shorelines continue to be valuable because of their higher temporal resolution compared to costly airborne lidar surveys. A method for extracting sandy shorelines from 30-meter (m) resolution Landsat imagery is presented here.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151179","usgsCitation":"Guy, K.K., 2015, Barrier island shorelines extracted from Landsat imagery: U.S. Geological Survey Open-File Report 2015–1179, 3 p., https://dx.doi.org/10.3133/ofr20151179.","productDescription":"Report: iv, 3 p.; Spatial Data","numberOfPages":"8","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-067042","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438679,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7028PMP","text":"USGS data release","linkHelpText":"Shorelines Extracted from Landsat Imagery: Dauphin Island, Alabama"},{"id":312288,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://dx.doi.org/10.5066/F7DZ06CD","text":"Shorelines Extracted from Landsat Imagery: Ship Island, Mississippi","description":"OFR 2015-1179"},{"id":312289,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://dx.doi.org/10.5066/F7JQ0Z3R","text":"Shorelines Extracted from Landsat Imagery: Cat Island, Mississippi","description":"OFR 2015-1179"},{"id":312290,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://dx.doi.org/10.5066/F7XW4GVG","text":"Shorelines Extracted from Landsat Imagery: Horn Island, Mississippi","description":"OFR 2015-1179"},{"id":312291,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://dx.doi.org/10.5066/F72N509Q","text":"Shorelines Extracted from Landsat Imagery: Petit Bois Island, Mississippi","description":"OFR 2015-1179"},{"id":309457,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1179/coverthb.jpg"},{"id":309459,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://dx.doi.org/10.5066/F7028PMP","text":"Shorelines Extracted from Landsat Imagery: Dauphin Island, Alabama","description":"OFR 2015-1179"},{"id":309458,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1179/ofr20151179.pdf","text":"Report","size":"242 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1179"}],"country":"United States","contact":"St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
http://coastal.er.usgs.gov/
Crude oil at a spill site near Bemidji, Minnesota has been undergoing aerobic and anaerobic biodegradation for over 30 years, creating a 150–200 m plume of primary and secondary contaminants. Microbial degradation generates heat that should be measurable under the right conditions. To measure this heat, thermistors were installed in wells in the saturated zone and in water-filled monitoring tubes in the unsaturated zone. In the saturated zone, a thermal groundwater plume originates near the residual oil body with temperatures ranging from 2.9 °C above background near the oil to 1.2 °C down gradient. Temperatures in the unsaturated zone above the oil body were up to 2.7 °C more than background temperatures. Previous work at this site has shown that methane produced from biodegradation of the oil migrates upward and is oxidized in a methanotrophic zone midway between the water table and the surface. Enthalpy calculations and observations demonstrate that the temperature increases primarily result from aerobic methane oxidation in the unsaturated zone above the oil. Methane oxidation rates at the site independently estimated from surface CO2 efflux data are comparable to rates estimated from the observed temperature increases. The results indicate that temperature may be useful as a low-cost measure of activity but care is required to account for the correct heat-generating reactions, other heat sources and the effects of focused recharge.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jconhyd.2015.09.007","usgsCitation":"Warren, E., and Bekins, B.A., 2015, Relating subsurface temperature changes to microbial activity at a crude oil-contaminated site: Journal of Contaminant Hydrology, v. 182, p. 183-193, https://doi.org/10.1016/j.jconhyd.2015.09.007.","productDescription":"11 p.","startPage":"183","endPage":"193","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064342","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":309841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","city":"Bemidji","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.96101379394531,\n 47.41624051540972\n ],\n [\n -94.96101379394531,\n 47.52577916760752\n ],\n [\n -94.77149963378906,\n 47.52577916760752\n ],\n [\n -94.77149963378906,\n 47.41624051540972\n ],\n [\n -94.96101379394531,\n 47.41624051540972\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"182","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"561e1d29e4b0cdb063e59ca7","contributors":{"authors":[{"text":"Warren, Ean ewarren@usgs.gov","contributorId":1351,"corporation":false,"usgs":true,"family":"Warren","given":"Ean","email":"ewarren@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":577259,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bekins, Barbara A. 0000-0002-1411-6018 babekins@usgs.gov","orcid":"https://orcid.org/0000-0002-1411-6018","contributorId":1348,"corporation":false,"usgs":true,"family":"Bekins","given":"Barbara","email":"babekins@usgs.gov","middleInitial":"A.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":577260,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70142817,"text":"70142817 - 2015 - Basement and regional structure along strike of the Queen Charlotte Fault in the context of modern and historical earthquake ruptures","interactions":[],"lastModifiedDate":"2015-10-13T14:00:38","indexId":"70142817","displayToPublicDate":"2015-10-13T13:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Basement and regional structure along strike of the Queen Charlotte Fault in the context of modern and historical earthquake ruptures","docAbstract":"The Queen Charlotte fault (QCF) is a dextral transform system located offshore of southeastern Alaska and western Canada, accommodating ∼4.4 cm/yr of relative motion between the Pacific and North American plates. Oblique convergence along the fault increases southward, and how this convergence is accommodated is still debated. Using seismic reflection data, we interpret offshore basement structure, faulting, and stratigraphy to provide a geological context for two recent earthquakes, an Mw 7.5 strike‐slip event near Craig, Alaska, and an Mw 7.8 thrust event near Haida Gwaii, Canada. We map downwarped Pacific oceanic crust near 54° N, between the two rupture zones. Observed downwarping decreases north and south of 54° N, parallel to the strike of the QCF. Bending of the Pacific plate here may have initiated with increased convergence rates due to a plate motion change at ∼6 Ma. Tectonic reconstruction implies convergence‐driven Pacific plate flexure, beginning at 6 Ma south of a 10° bend the QCF (which is currently at 53.2° N) and lasting until the plate translated past the bend by ∼2 Ma. Normal‐faulted approximately late Miocene sediment above the deep flexural depression at 54° N, topped by relatively undeformed Pleistocene and younger sediment, supports this model. Aftershocks of the Haida Gwaii event indicate a normal‐faulting stress regime, suggesting present‐day plate flexure and underthrusting, which is also consistent with reconstruction of past conditions. We thus favor a Pacific plate underthrusting model to initiate flexure and accommodation space for sediment loading. In addition, mapped structures indicate two possible fault segment boundaries along the QCF at 53.2° N and at 56° N.
","language":"English","publisher":"Seismological Society of Amercia","doi":"10.1785/0120140174","usgsCitation":"Walton, M.A., Gulick, S., Haeussler, P.J., Roland, E.C., and Trehu, A.M., 2015, Basement and regional structure along strike of the Queen Charlotte Fault in the context of modern and historical earthquake ruptures: Bulletin of the Seismological Society of America, v. 105, no. 28, p. 1090-1105, https://doi.org/10.1785/0120140174.","productDescription":"16 p.","startPage":"1090","endPage":"1105","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061089","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":471724,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2152/43271","text":"External Repository"},{"id":309842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Queen Charlotte Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -182.63671875,\n 51.23440735163459\n ],\n [\n -182.02148437499997,\n 52.53627304145948\n ],\n [\n -173.32031249999997,\n 53.22576843579022\n ],\n [\n -166.640625,\n 55.178867663281984\n ],\n [\n -160.400390625,\n 57.32652122521709\n ],\n [\n -156.708984375,\n 59.88893689676585\n ],\n [\n -153.80859375,\n 60.88770004207789\n ],\n [\n -148.974609375,\n 61.897577621605016\n ],\n [\n -141.943359375,\n 61.438767493682825\n ],\n [\n -134.296875,\n 59.40036514079251\n ],\n [\n -129.814453125,\n 55.57834467218206\n ],\n [\n -130.869140625,\n 54.7246201949245\n ],\n [\n -130.341796875,\n 52.53627304145948\n ],\n [\n -131.748046875,\n 51.67255514839676\n ],\n [\n -134.12109375,\n 54.00776876193478\n ],\n [\n -136.669921875,\n 56.992882804633986\n ],\n [\n -139.482421875,\n 58.90464570302001\n ],\n [\n -143.525390625,\n 59.80063426102869\n ],\n [\n -150.732421875,\n 58.99531118795094\n ],\n [\n -151.875,\n 57.040729838360875\n ],\n [\n -155.390625,\n 55.57834467218206\n ],\n [\n -162.509765625,\n 53.9560855309879\n ],\n [\n -173.671875,\n 51.83577752045248\n ],\n [\n -182.28515624999997,\n 50.84757295365389\n ],\n [\n -182.63671875,\n 51.23440735163459\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"105","issue":"28","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-14","publicationStatus":"PW","scienceBaseUri":"561e1d25e4b0cdb063e59ca1","contributors":{"authors":[{"text":"Walton, Maureen A. L.","contributorId":147200,"corporation":false,"usgs":false,"family":"Walton","given":"Maureen","email":"","middleInitial":"A. L.","affiliations":[{"id":13603,"text":"University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":542177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gulick, Sean P. S.","contributorId":147201,"corporation":false,"usgs":false,"family":"Gulick","given":"Sean P. S.","affiliations":[{"id":13603,"text":"University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":542178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haeussler, Peter J. 0000-0002-1503-6247 pheuslr@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":503,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter","email":"pheuslr@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":542176,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roland, Emily C. eroland@usgs.gov","contributorId":5075,"corporation":false,"usgs":true,"family":"Roland","given":"Emily","email":"eroland@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":false,"id":542179,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trehu, Anne M.","contributorId":49884,"corporation":false,"usgs":false,"family":"Trehu","given":"Anne","email":"","middleInitial":"M.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":542180,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155964,"text":"ofr20151078 - 2015 - Identifying trout refuges in the Indian and Hudson Rivers in northern New York through airborne thermal infrared remote sensing","interactions":[],"lastModifiedDate":"2015-10-14T15:28:33","indexId":"ofr20151078","displayToPublicDate":"2015-10-09T07:00:00","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":"2015-1078","title":"Identifying trout refuges in the Indian and Hudson Rivers in northern New York through airborne thermal infrared remote sensing","docAbstract":"The locations and sizes of potential cold-water refuges for trout were examined in 2005 along a 27-kilometer segment of the Indian and Hudson Rivers in northern New York to evaluate the extent of refuges, the effects of routine flow releases from an impoundment, and how these refuges and releases might influence trout survival in reaches that otherwise would be thermally stressed. This river segment supports small populations of brook trout (Salvelinus fontinalis), brown trout (Salmo trutta), and rainbow trout (Oncorhynchus mykiss) and also receives regular releases of reservoir-surface waters to support rafting during the summer, when water temperatures in both the reservoir and the river frequently exceed thermal thresholds for trout survival. Airborne thermal infrared imaging was supplemented with continuous, in-stream temperature loggers to identify potential refuges that may be associated with tributary inflows or groundwater seeps and to define the extent to which the release flows decrease the size of existing refuges. In general, the release flows overwhelmed the refuge areas and greatly decreased the size and number of the areas. Mean water temperatures were unaffected by the releases, but small-scale heterogeneity was diminished. At a larger scale, water temperatures in the upper and lower segments of the reach were consistently warmer than in the middle segment, even during passage of release waters. The inability of remote thermal infrared images to consistently distinguish land from water (in shaded areas) and to detect groundwater seeps (away from the shallow edges of the stream) limited data analysis and the ability to identify potential thermal refuge areas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151078","collaboration":"Prepared in cooperation with New York State Department of Environmental Conservation and Rochester Institute of Technology","usgsCitation":"Ernst, A.G., Baldigo, B.P., Calef, F.J., Freehafer, D.A., and Kremens, R.L., 2015, Identifying trout refuges in the Indian and Hudson Rivers in northern New York through airborne thermal infrared remote sensing: U.S. Geological Survey Open-File Report 2015–1078, 17 p., https://dx.doi.org/10.3133/ofr20151078.","productDescription":"vii, 17 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-054790","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":308601,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1078/coverthb.jpg"},{"id":308602,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1078/ofr20151078.pdf","text":"Report","size":"3.78 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1078"}],"country":"United States","state":"New York","otherGeospatial":"Hudson River and Indian River, Adirondack Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.5751953125,\n 43.60326743161359\n ],\n [\n -74.5751953125,\n 43.98886243884903\n ],\n [\n -73.90777587890625,\n 43.98886243884903\n ],\n [\n -73.90777587890625,\n 43.60326743161359\n ],\n [\n -74.5751953125,\n 43.60326743161359\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
http://ny.water.usgs.gov
Remotely sensed, geographically referenced elevation measurements of the sea floor, acquired by boat- and aircraft-based survey systems, were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida, for the area at Cape Canaveral.
\nThe work was conducted as part of a study to describe an updated bathymetric dataset collected in 2014 and compare it to previous data sets. The updated data focus on the bathymetric features and sediment transport pathways that connect the offshore regions to the shoreline and, therefore, are related to the protection of other portions of the coastal environment, such as dunes, that support infrastructure and ecosystems.
\nCape Canaveral Coastal System (CCCS) is a prominent feature along the Southeast U.S. coastline and is the only large cape south of Cape Fear, North Carolina. Most of the CCCS lies within the Merritt Island National Wildlife Refuge and included within its boundaries are the Cape Canaveral Air Force Station (CCAFS), NASA’s Kennedy Space Center (KSC), and a large portion of Canaveral National Seashore. The actual promontory of the modern cape falls within the jurisdictional boundaries of the CCAFS.
\nHydrographic survey data were collected August 18-20, 2014 (USGS Field Activity Number 2014-324-FA). The study covered a 20 kilometer (km) section of shoreline extending from Port Canaveral, Fla., to the northern end of the KSC property, and from the shoreline to about 2.5 km offshore. Data were acquired using both sound navigation and ranging (sonar) and light detection and ranging (lidar) systems. Two jet skis and a 17-foot (ft) outboard motor boat equipped with the USGS SANDS (System for Accurate Nearshore Depth Surveying) hydrographic system collected precision sonar data. The USGS airborne EAARL-B mapping system flown in a twin engine airplane was used to collect lidar data. The missions were synchronized so that there was temporal and spatial overlap between the sonar and lidar operations. Additional data were collected to evaluate water clarity to verify the ability of lidar to receive bathymetric returns. Both systems used differential Global Positioning System GPS and utilized the National Oceanic and Atmospheric Administration/National Geodetic Survey (NOAA/NGS) Continuously Operating Reference Station (CORS) station located at CCAFS was used as the reference station.
\nThis data series serves as an archive of processed single-beam sonar and lidar bathymetry data. Graphical Information System (GIS) data products include XYZ point bathymetry data files, a color coded bathymetry map, and interpolated bathymetry grid surface.
\nAdditional information includes an error analysis and formal Federal Geographic Data Committee (FGDC) metadata.
\nFor more information about similar projects, please visit the Barrier Island Evolution Web site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds957","usgsCitation":"Hansen, Mark, Plant, N.G., Thompson, D.M., Troche, R.J., Kranenburg, C.J., and Klipp, E.S., 2015, Archive of bathymetry data collected at Cape Canaveral, Florida, 2014: U.S. Geological Survey Data Series 957, https://dx.doi.org/10.3133/ds957.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2014-08-18","temporalEnd":"2014-08-20","ipdsId":"IP-064065","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":309529,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0957","text":"Report HTML","description":"DS 956"},{"id":309528,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0957/images/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Cape Canaveral","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.57132720947264,\n 28.57909501280518\n ],\n [\n -80.56068420410156,\n 28.529337159530115\n ],\n [\n -80.52635192871094,\n 28.461447671879817\n ],\n [\n -80.52532196044922,\n 28.44877013274692\n ],\n [\n -80.5514144897461,\n 28.441525142203908\n ],\n [\n -80.56514739990234,\n 28.434279655423556\n ],\n [\n -80.57716369628906,\n 28.423410494987063\n ],\n [\n -80.5843734741211,\n 28.411030369596805\n ],\n [\n -80.5569076538086,\n 28.397440761221713\n ],\n [\n -80.50712585449219,\n 28.437600565124914\n ],\n [\n -80.49613952636719,\n 28.4656731804089\n ],\n [\n -80.55038452148438,\n 28.585426143239545\n ],\n [\n -80.57132720947264,\n 28.57909501280518\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
600 4th Street South
St. Petersburg, FL 33701
http://coastal.er.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. Thirty wells total were installed for this project: 10 in 2012 (DS 923, http://dx.doi.org/10.3133/ds923), and 20 monitoring wells were installed during April and June 2014 which are presented in this report. This report presents location data, lithologic logs, well-construction diagrams, and well-development information. Understanding the groundwater system can 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/ds955","collaboration":"Prepared in cooperation with Colorado Water Conservation Board and the Bureau of Reclamation","usgsCitation":"Thomas, J.C., 2015, Installation of a groundwater monitoring-well network on the east side of the Uncompahgre River in the Lower Gunnison River Basin, Colorado, 2014: U.S. Geological Survey Data Series 955, 44 p., https://dx.doi.org/10.3133/ds955.","productDescription":"iv, 43 p.","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2014-04-01","temporalEnd":"2014-06-30","ipdsId":"IP-065498","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":309538,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/ds923","text":"DS 923","description":"DS 923"},{"id":309537,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0955/ds955.pdf","text":"Report","size":"8.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 955"},{"id":309536,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0955/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Gunnison River Basin, Uncompahgre River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.08349609375,\n 38.75140585784823\n ],\n [\n -107.91458129882812,\n 38.777372574181335\n ],\n [\n -107.9183578491211,\n 38.63618191259742\n ],\n [\n -107.84385681152344,\n 38.525070076783955\n ],\n [\n -107.64472961425781,\n 38.451168926369206\n ],\n [\n -107.7978515625,\n 38.36346433068098\n ],\n [\n -107.91698455810547,\n 38.49954915714596\n ],\n [\n -107.9794692993164,\n 38.55058194928367\n ],\n [\n -107.99835205078124,\n 38.65039396101565\n ],\n [\n -108.0893325805664,\n 38.74444410121545\n ],\n [\n -108.08349609375,\n 38.75140585784823\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
","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2015-10-07","noUsgsAuthors":false,"publicationDate":"2015-10-07","publicationStatus":"PW","scienceBaseUri":"56163426e4b0ba4884c61465","contributors":{"authors":[{"text":"Thomas, Judith C. 0000-0001-7883-1419 juthomas@usgs.gov","orcid":"https://orcid.org/0000-0001-7883-1419","contributorId":1468,"corporation":false,"usgs":true,"family":"Thomas","given":"Judith","email":"juthomas@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":572894,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70157766,"text":"ofr20151180 - 2015 - Analysis of bathymetric surveys to identify coastal vulnerabilities at Cape Canaveral, Florida","interactions":[],"lastModifiedDate":"2015-10-09T07:58:25","indexId":"ofr20151180","displayToPublicDate":"2015-10-07T10:00:00","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":"2015-1180","title":"Analysis of bathymetric surveys to identify coastal vulnerabilities at Cape Canaveral, Florida","docAbstract":"
Cape Canaveral, Florida, is a prominent feature along the Southeast U.S. coastline. The region includes Merritt Island National Wildlife Refuge, Cape Canaveral Air Force Station, NASA’s Kennedy Space Center, and a large portion of Canaveral National Seashore. The actual promontory of the modern Cape falls within the jurisdictional boundaries of Cape Canaveral Air Force Station. Erosion hazards result from winter and tropical storms, changes in sand resources, sediment budgets, and sea-level rise. Previous work by the USGS has focused on the vulnerability of the dunes to storms, where updated bathymetry and topography have been used for modeling efforts. Existing research indicates that submerged shoals, ridges, and sandbars affect patterns of wave refraction and height, coastal currents, and control sediment transport. These seabed anomalies indicate the availability and movement of sand within the nearshore environment, which may be directly related to the stability of the Cape Canaveral shoreline. Understanding the complex dynamics of the offshore bathymetry and associated sediment pathways can help identify current and future erosion vulnerabilities due to short-term (for example, hurricane and other extreme storms) and long-term (for example, sea-level rise) hazards.
\nThe purpose of this work is to describe an updated bathymetric dataset collected in 2014 and compare it to previous datasets. The updated data focus on the bathymetric features and sediment transport pathways that connect the offshore regions to the shoreline and, therefore, are related to the protection of other portions of the coastal environment, such as dunes, that support infrastructure and ecosystems. Previous survey data include National Oceanic and Atmospheric Administration’s (NOAA) National Ocean Service (NOS) hydrographic survey from 1956 and a USGS survey from 2010 that is augmented with NOS surveys from 2006 and 2007. The primary result of this analysis is documentation and quantification of the nature and rates of bathymetric changes that are near (within about 2.5 km) the current Cape Canaveral shoreline and interpretation of the impact of these changes on future erosion vulnerability.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151180","usgsCitation":"Thompson, D.M., Plant, N.G., and Hansen, M.E., 2015, Analysis of bathymetric surveys to identify coastal vulnerabilities at Cape Canaveral, Florida: U.S. Geological Survey Open–File Report 2015–1180, 24 p., https://dx.doi.org/10.3133/ofr20151180.","productDescription":"vi, 24 p.","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064347","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":309576,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1180/coverthb.jpg"},{"id":309577,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1180/ofr20151180.pdf","size":"6.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1180"},{"id":309798,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://dx.doi.org/10.5066/F75Q4T4N","text":"Single-Beam Bathymetry Data, Cape Canaveral, Florida, 2010","linkFileType":{"id":5,"text":"html"},"description":"OFR 2015-1180"}],"country":"United States","state":"Florida","city":"Cape Canaveral","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.63003540039062,\n 28.655645954019544\n ],\n [\n -80.57098388671874,\n 28.585727616133926\n ],\n [\n -80.56549072265625,\n 28.54954469910389\n ],\n [\n -80.55450439453125,\n 28.50369515241441\n ],\n [\n -80.53390502929688,\n 28.481969987679054\n ],\n [\n -80.52429199218749,\n 28.452996148032607\n ],\n [\n -80.53939819335938,\n 28.4433364363651\n ],\n [\n -80.5572509765625,\n 28.43971381702788\n ],\n [\n -80.57235717773438,\n 28.425222099239033\n ],\n [\n -80.58059692382812,\n 28.409520499193246\n ],\n [\n -80.4913330078125,\n 28.382943257980948\n ],\n [\n -80.44876098632812,\n 28.44454394857482\n ],\n [\n -80.45150756835938,\n 28.509729126769052\n ],\n [\n -80.48171997070312,\n 28.555576049185973\n ],\n [\n -80.48858642578125,\n 28.611048252984677\n ],\n [\n -80.52703857421875,\n 28.662876227341822\n ],\n [\n -80.54351806640625,\n 28.689382962051912\n ],\n [\n -80.63003540039062,\n 28.655645954019544\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
http://coastal.er.usgs.gov/
Biological samples from various locations on Lake Powell and in the Colorado River in the tail water downstream of Glen Canyon Dam were collected by the Bureau of Reclamation and U.S. Geological Survey from December 1990 through December 2009 as part of a long-term water-quality monitoring program that began in 1964. These samples consisted of discrete (1-m deep) chlorophyll samples, discrete (1-m deep) wholewater phytoplankton samples, and 30-m vertically composited zooplankton samples filtered through an 80-µm plankton net. Chlorophyll concentration was determined by acetone extraction followed by trichromatic spectroscopy on 2,051 samples. Phytoplankton analysis consisted of identification to the genus or species level, enumeration, and estimation of biovolume on 1,397 samples. Phytoplankton analysis identified 646 different phytoplankton taxa. Zooplankton analysis consisted of identification to the genus or species level, enumeration, and estimation of biomass from 1,898 samples. Zooplankton analysis identified 114 different zooplankton taxa.
\nThe results of these analyses are presented in this report. From this record, further interpretation may be made concerning primary and secondary production in Lake Powell. These data provide a linkage between physical and chemical water-quality data and fisheries investigations in Lake Powell. They also provide information regarding the export of biological material from Glen Canyon Dam.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds959","collaboration":"Prepared in cooperation with Bureau of Reclamation","usgsCitation":"Vernieu, W.S., 2015, Biological data for water in Lake Powell and from Glen Canyon Dam releases, Utah and Arizona, 1990–2009: U.S. Geological Survey Data Series 959, 12 p., https://dx.doi.org/10.3133/ds959.","productDescription":"v, 12 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1990-12-01","temporalEnd":"2009-12-31","ipdsId":"IP-041385","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":309706,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0959/coverthb.jpg"},{"id":309707,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0959/ds959.pdf","text":"Report","size":"500 KB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 959 PDF"}],"country":"United States","state":"Utah, Arizona","otherGeospatial":"Lake Powell, Colorado River, Glen Canyon Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.1,\n 36.5\n ],\n [\n -112.1,\n 38.1\n ],\n [\n -109.8,\n 38.1\n ],\n [\n -109.8,\n 36.5\n ],\n [\n -112.1,\n 36.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"SBSC Staff, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
http://sbsc.wr.usgs.gov/
Diet estimation is an important field within quantitative ecology, providing critical insights into many aspects of ecology and community dynamics. Quantitative fatty acid signature analysis (QFASA) is a prominent method of diet estimation, particularly for marine mammal and bird species. Investigators using QFASA commonly use computer simulation to evaluate statistical characteristics of diet estimators for the populations they study. Similar computer simulations have been used to explore and compare the performance of different variations of the original QFASA diet estimator. In both cases, computer simulations involve bootstrap sampling prey signature data to construct pseudo-predator signatures with known properties. However, bootstrap sample sizes have been selected arbitrarily and pseudo-predator signatures therefore may not have realistic properties. I develop an algorithm to objectively establish bootstrap sample sizes that generates pseudo-predator signatures with realistic properties, thereby enhancing the utility of computer simulation for assessing QFASA estimator performance. The algorithm also appears to be computationally efficient, resulting in bootstrap sample sizes that are smaller than those commonly used. I illustrate the algorithm with an example using data from Chukchi Sea polar bears (Ursus maritimus) and their marine mammal prey. The concepts underlying the approach may have value in other areas of quantitative ecology in which bootstrap samples are post-processed prior to their use.
","language":"English","publisher":"Science Direct","doi":"10.1016/j.ecoinf.2015.09.011","usgsCitation":"Bromaghin, J.F., 2015, Simulating realistic predator signatures in quantitative fatty acid signature analysis: Ecological Informatics, v. 30, p. 68-71, https://doi.org/10.1016/j.ecoinf.2015.09.011.","productDescription":"4 p.","startPage":"68","endPage":"71","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067252","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":309683,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5614e2ade4b0ba4884c611a6","contributors":{"authors":[{"text":"Bromaghin, Jeffrey F. 0000-0002-7209-9500 jbromaghin@usgs.gov","orcid":"https://orcid.org/0000-0002-7209-9500","contributorId":139899,"corporation":false,"usgs":true,"family":"Bromaghin","given":"Jeffrey","email":"jbromaghin@usgs.gov","middleInitial":"F.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":576564,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70159172,"text":"70159172 - 2015 - Statistical models for the analysis and design of digital polymerase chain (dPCR) experiments","interactions":[],"lastModifiedDate":"2016-07-11T15:43:19","indexId":"70159172","displayToPublicDate":"2015-10-05T13:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":761,"text":"Analytical Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Statistical models for the analysis and design of digital polymerase chain (dPCR) experiments","docAbstract":"Statistical methods for the analysis and design of experiments using digital PCR (dPCR) have received only limited attention and have been misused in many instances. To address this issue and to provide a more general approach to the analysis of dPCR data, we describe a class of statistical models for the analysis and design of experiments that require quantification of nucleic acids. These models are mathematically equivalent to generalized linear models of binomial responses that include a complementary, log–log link function and an offset that is dependent on the dPCR partition volume. These models are both versatile and easy to fit using conventional statistical software. Covariates can be used to specify different sources of variation in nucleic acid concentration, and a model’s parameters can be used to quantify the effects of these covariates. For purposes of illustration, we analyzed dPCR data from different types of experiments, including serial dilution, evaluation of copy number variation, and quantification of gene expression. We also showed how these models can be used to help design dPCR experiments, as in selection of sample sizes needed to achieve desired levels of precision in estimates of nucleic acid concentration or to detect differences in concentration among treatments with prescribed levels of statistical power.
","language":"English","publisher":"American Chemical Society","publisherLocation":"Washington, DC","doi":"10.1021/acs.analchem.5b02429","usgsCitation":"Dorazio, R., and Hunter, M., 2015, Statistical models for the analysis and design of digital polymerase chain (dPCR) experiments: Analytical Chemistry, v. 87, no. 21, p. 10886-10893, https://doi.org/10.1021/acs.analchem.5b02429.","productDescription":"8 p.","startPage":"10886","endPage":"10893","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066660","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":310034,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"87","issue":"21","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-13","publicationStatus":"PW","scienceBaseUri":"56261492e4b0fb9a11dd7651","contributors":{"authors":[{"text":"Dorazio, Robert 0000-0003-2663-0468 bob_dorazio@usgs.gov","orcid":"https://orcid.org/0000-0003-2663-0468","contributorId":149286,"corporation":false,"usgs":true,"family":"Dorazio","given":"Robert","email":"bob_dorazio@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":577747,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunter, Margaret 0000-0002-4760-9302 mhunter@usgs.gov","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":140627,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","email":"mhunter@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":577748,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70158673,"text":"70158673 - 2015 - Classification of rocky headlands in California with relevance to littoral cell boundary delineation","interactions":[],"lastModifiedDate":"2016-10-04T09:21:26","indexId":"70158673","displayToPublicDate":"2015-10-05T13:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Classification of rocky headlands in California with relevance to littoral cell boundary delineation","docAbstract":"Despite extensive studies of hydrodynamics and sediment flux along beaches, there is little information on the processes, pathways and timing of water and sediment transport around rocky headlands. In this study, headlands along the California coast are classified to advance understanding of headland dynamics and littoral cell boundaries in support of improved coastal management decisions. Geomorphological parameters for 78 headlands were quantified from geological maps, remote-sensing imagery, navigational charts, and shoreline geospatial databases. K-means cluster analysis grouped the headlands into eight distinct classes based on headland perimeter, bathymetric slope ratio, and the headland apex angle. Wave data were used to investigate the potential for sediment transport around the headland types and determine the efficacy of the headland as a littoral cell boundary. Four classes of headland appear to function well as littoral cell boundaries, with headland size (e.g., perimeter or area) and a marked change in nearshore bathymetry across the headland being relevant attributes. About half of the traditional California littoral cell boundaries align with headland classes that are expected to perform poorly in blocking alongshore sediment transport, calling into question these boundaries. Better definition of these littoral cell boundaries is important for regional sediment management decisions.
","language":"English","publisher":"Elsevier Science Direct","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.margeo.2015.08.010","collaboration":"University of California at Davis","usgsCitation":"George, D.A., Largier, J.L., Storlazzi, C., and Barnard, P.L., 2015, Classification of rocky headlands in California with relevance to littoral cell boundary delineation: Marine Geology, v. 369, p. 137-152, https://doi.org/10.1016/j.margeo.2015.08.010.","productDescription":"16 p.","startPage":"137","endPage":"152","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062540","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":309565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.18945312500001,\n 41.0130657870063\n ],\n [\n -123.79394531249999,\n 40.16208338164619\n ],\n [\n -122.71728515624999,\n 38.16911413556086\n ],\n [\n -121.59667968749999,\n 38.151837403006766\n ],\n [\n -121.61865234375,\n 36.43896124085945\n ],\n [\n -120.78369140624999,\n 35.496456056584165\n ],\n [\n -120.1904296875,\n 34.813803317113155\n ],\n [\n -119.17968749999999,\n 34.470335121217495\n ],\n [\n -118.10302734374999,\n 34.10725639663118\n ],\n [\n -117.09228515624999,\n 32.91648534731439\n ],\n [\n -116.98242187499999,\n 32.491230287947594\n ],\n [\n -117.44384765625,\n 32.194208672875355\n ],\n [\n -119.28955078124999,\n 32.713355353177555\n ],\n [\n -122.82714843749999,\n 37.055177106660814\n ],\n [\n -124.07958984375001,\n 38.94232097947902\n ],\n [\n -124.91455078125,\n 40.59727063442027\n ],\n [\n -124.18945312500001,\n 41.0130657870063\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"369","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56139122e4b0ba4884c60f60","contributors":{"authors":[{"text":"George, Douglas A.","contributorId":60328,"corporation":false,"usgs":true,"family":"George","given":"Douglas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":576438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Largier, John L.","contributorId":175121,"corporation":false,"usgs":false,"family":"Largier","given":"John","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":576439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":2333,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt D.","email":"cstorlazzi@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":576437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":576440,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70158676,"text":"70158676 - 2015 - Projected wave conditions in the Eastern North Pacific under the influence of two CMIP5 climate scenarios","interactions":[],"lastModifiedDate":"2015-12-07T11:17:03","indexId":"70158676","displayToPublicDate":"2015-10-05T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2925,"text":"Ocean Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Projected wave conditions in the Eastern North Pacific under the influence of two CMIP5 climate scenarios","docAbstract":"Hindcast and 21st century winds, simulated by General Circulation Models (GCMs), were used to drive global- and regional-scale spectral wind-wave generation models in the Pacific Ocean Basin to assess future wave conditions along the margins of the North American west coast and Hawaiian Islands. Three-hourly winds simulated by four separate GCMs were used to generate an ensemble of wave conditions for a recent historical time-period (1976–2005) and projections for the mid and latter parts of the 21st century under two radiative forcing scenarios (RCP 4.5 and RCP 8.5), as defined by the fifth phase of the Coupled Model Inter-comparison Project (CMIP5) experiments. Comparisons of results from historical simulations with wave buoy and ERA-Interim wave reanalysis data indicate acceptable model performance of wave heights, periods, and directions, giving credence to generating projections. Mean and extreme wave heights are projected to decrease along much of the North American west coast. Extreme wave heights are projected to decrease south of ∼50°N and increase to the north, whereas extreme wave periods are projected to mostly increase. Incident wave directions associated with extreme wave heights are projected to rotate clockwise at the eastern end of the Aleutian Islands and counterclockwise offshore of Southern California. Local spatial patterns of the changing wave climate are similar under the RCP 4.5 and RCP 8.5 scenarios, but stronger magnitudes of change are projected under RCP 8.5. Findings of this study are similar to previous work using CMIP3 GCMs that indicates decreasing mean and extreme wave conditions in the Eastern North Pacific, but differ from other studies with respect to magnitude and local patterns of change. This study contributes toward a larger ensemble of global and regional climate projections needed to better assess uncertainty of potential future wave climate change, and provides model boundary conditions for assessing the impacts of climate change on coastal systems.
","language":"English","publisher":"Elsevier Science Ltd","publisherLocation":"Oxford, United Kingdom","doi":"10.1016/j.ocemod.2015.07.004","collaboration":"Christie Hegermiller, UCSC; Peter Ruggiero, Oregon State University; Maarten van Ormondt, Deltares,","usgsCitation":"Erikson, L., Hegermiller, C., Barnard, P., Ruggiero, P., and van Ormondt, M., 2015, Projected wave conditions in the Eastern North Pacific under the influence of two CMIP5 climate scenarios: Ocean Modelling, v. 96, no. 1, p. 171-185, https://doi.org/10.1016/j.ocemod.2015.07.004.","productDescription":"15 p.","startPage":"171","endPage":"185","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051162","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":309542,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -180,\n -3.513421045640032\n ],\n [\n -180,\n 65.2198939361321\n ],\n [\n -78.046875,\n 65.2198939361321\n ],\n [\n -78.046875,\n -3.513421045640032\n ],\n [\n -180,\n -3.513421045640032\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"96","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56139126e4b0ba4884c60f6a","contributors":{"authors":[{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":147149,"corporation":false,"usgs":true,"family":"Erikson","given":"Li H.","email":"lerikson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":576458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hegermiller, Christie 0000-0002-6383-7508 chegermiller@usgs.gov","orcid":"https://orcid.org/0000-0002-6383-7508","contributorId":149010,"corporation":false,"usgs":true,"family":"Hegermiller","given":"Christie","email":"chegermiller@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":576459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":576460,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruggiero, Peter","contributorId":15709,"corporation":false,"usgs":false,"family":"Ruggiero","given":"Peter","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":576461,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van Ormondt, Martin","contributorId":149011,"corporation":false,"usgs":false,"family":"van Ormondt","given":"Martin","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":576462,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70157362,"text":"ofr20151176 - 2015 - Preliminary estimates of annual agricultural pesticide use for counties of the conterminous United States, 2013","interactions":[],"lastModifiedDate":"2016-06-29T13:17:10","indexId":"ofr20151176","displayToPublicDate":"2015-10-05T09:45:00","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":"2015-1176","title":"Preliminary estimates of annual agricultural pesticide use for counties of the conterminous United States, 2013","docAbstract":"This report provides preliminary estimates of annual agricultural use of 387 pesticide compounds in counties of the conterminous United States in 2013, compiled by means of methods described in Thelin and Stone (2013) and Baker and Stone (2015). U.S. Department of Agriculture county-level data for harvested-crop acreage were used in conjunction with proprietary Crop Reporting District-level pesticide-use data to estimate county-level pesticide use. Where Crop Reporting District data were not available or were incomplete, estimated pesticide use values were calculated with two different methods, resulting in a low and a high estimate based on different assumptions about missing survey data (Thelin and Stone, 2013). Preliminary estimates in this report are expected to be revised upon availability of updated crop acreages in the 2017 Agricultural Census, to be published by the U.S. Department of Agriculture in 2019. Estimates of annual agricultural pesticide use are provided as downloadable, tab-delimited files, which are organized by compound, year, state Federal Information Processing Standard (FIPS) code, county Federal Information Processing Standard code, and amount in kilograms (kg). The files, listed below, are a continuation of the 1992–2009 and 2008–2012 pesticide-use estimates reported by Stone (2013) and Baker and Stone (2015), respectively:
\nHigh estimates of county pesticide use, arranged by pesticide name:
\nTable 1. 1-Methyl Cyclopropene through Chlorantraniliprole
Table 2. Chlorethoxyfos through Diflufenzopyr
Table 3. Dimethenamid through Gibberellic Acid
Table 4. Glufosinate through Metiram
Table 5. Metolachlor through Propazine
Table 6. Propiconazole through Triasulfuron
Table 7. Tribenuron Methyl through Zoxamide
Low estimates of county pesticide use, arranged by pesticide name:
\nTable 8. 1-Methyl Cyclopropene through Chlorantraniliprole
Table 9. Chlorethoxyfos through Diflufenzopyr
Table 10. Dimethenamid through Gibberellic Acid
Table 11. Glufosinate through Metiram
Table 12. Metolachlor through Propazine
Table 13. Propiconazole through Triasulfuron
Table 14. Tribenuron Methyl through Zoxamide
Baker, N.T., and Stone, W.W., 2015, Estimated annual agricultural pesticide use for counties of the conterminous United States, 2008–12: U.S. Geological Survey Data Series 907, 9 p., accessed July, 12, 2015, at http://dx.doi.org/10.3133/ds907.
\nStone, W.W., 2013, Estimated annual agricultural pesticide use for counties of the conterminous United States, 1992–2009: U.S. Geological Survey Data Series 752, 1 p., 14 tables
\nThelin, G.P., and Stone, W.W., 2013, Estimation of annual agricultural pesticide use for counties of the conterminous United States,
1992–2009: U.S. Geological Survey Scientific Investigations Report 2013–5009, 54 p.
Director, Indiana Water Science Center
5957 Lakeside Blvd.
Indianapolis, IN 46278
http://in.water.usgs.gov/
Introduction
\nPesticide-Use Estimates
\nAcknowledgments
\nA numerical model, XBeach, calibrated and validated on field data collected at Roi-Namur Island on Kwajalein Atoll in the Republic of Marshall Islands, was used to examine the effects of different coral reef characteristics on potential coastal hazards caused by wave-driven flooding and how these effects may be altered by projected climate change. The results presented herein suggest that coasts fronted by relatively narrow reefs with steep fore reef slopes (~1:10 and steeper) and deeper, smoother reef flats are expected to experience the highest wave runup. Wave runup increases for higher water levels (sea level rise), higher waves, and lower bed roughness (coral degradation), which are all expected effects of climate change. Rising sea levels and climate change will therefore have a significant negative impact on the ability of coral reefs to mitigate the effects of coastal hazards in the future.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2015GL064861","usgsCitation":"Quataert, E., Storlazzi, C.D., van Rooijen, A., van Dongeren, A., and Cheriton, O., 2015, The influence of coral reefs and climate change on wave-driven flooding of tropical coastlines: Geophysical Research Letters, v. 42, no. 15, p. 6407-6415, https://doi.org/10.1002/2015GL064861.","productDescription":"9 p.","startPage":"6407","endPage":"6415","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064753","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471733,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl064861","text":"Publisher Index Page"},{"id":309544,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Republic of the Marshall Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 167.8271484375,\n 7.798078531355303\n ],\n [\n 169.63989257812497,\n 7.798078531355303\n ],\n [\n 169.63989257812497,\n 10.077037154404719\n ],\n [\n 167.8271484375,\n 10.077037154404719\n ],\n [\n 167.8271484375,\n 7.798078531355303\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"15","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-04","publicationStatus":"PW","scienceBaseUri":"56139126e4b0ba4884c60f70","chorus":{"doi":"10.1002/2015gl064861","url":"http://dx.doi.org/10.1002/2015gl064861","publisher":"Wiley-Blackwell","authors":"Quataert Ellen, Storlazzi Curt, van Rooijen Arnold, Cheriton Olivia, van Dongeren Ap","journalName":"Geophysical Research Letters","publicationDate":"8/4/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Quataert, Ellen","contributorId":149000,"corporation":false,"usgs":false,"family":"Quataert","given":"Ellen","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":576425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":576424,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Rooijen, Arnold","contributorId":149001,"corporation":false,"usgs":false,"family":"van Rooijen","given":"Arnold","email":"","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":576426,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Dongeren, Ap","contributorId":149002,"corporation":false,"usgs":false,"family":"van Dongeren","given":"Ap","email":"","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":576427,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cheriton, Olivia 0000-0003-3011-9136 ocheriton@usgs.gov","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":149003,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","email":"ocheriton@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":576428,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70158030,"text":"ofr20151189 - 2015 - Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2014","interactions":[],"lastModifiedDate":"2015-10-05T11:04:29","indexId":"ofr20151189","displayToPublicDate":"2015-10-02T17:00:00","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":"2015-1189","title":"Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2014","docAbstract":"Data from a long-term capture-recapture program were used to assess the status and dynamics of populations of two long-lived, federally endangered catostomids in Upper Klamath Lake, Oregon. Lost River suckers (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) have been captured and tagged with passive integrated transponder (PIT) tags during their spawning migrations in each year since 1995. In addition, beginning in 2005, individuals that had been previously PIT-tagged were re-encountered on remote underwater antennas deployed throughout sucker spawning areas. Captures and remote encounters during the spawning season in spring 2014 were incorporated into capture-recapture analyses of population dynamics.
\nCormack-Jolly-Seber (CJS) open population capture-recapture models were used to estimate annual survival probabilities, and a reverse-time analog of the CJS model was used to estimate recruitment of new individuals into the spawning populations. In addition, data on the size composition of captured fish were examined to provide corroborating evidence of recruitment. Model estimates of survival and recruitment were used to derive estimates of changes in population size over time and to determine the status of the populations through 2013. Separate analyses were conducted for each species and also for each subpopulation of Lost River suckers (LRS). Shortnose suckers (SNS) and one subpopulation of LRS migrate into tributary rivers to spawn, whereas the other LRS subpopulation spawns at groundwater upwelling areas along the eastern shoreline of the lake.
\nIn 2014, we captured, tagged, and released 496 LRS at four lakeshore spawning areas and recaptured an additional 970 individuals that had been tagged in previous years. Across all four areas, the remote antennas detected 6,370 individual LRS during the spawning season. Spawning activity peaked in April and most individuals were encountered at Cinder Flats and Sucker Springs. In the Williamson River, we captured, tagged, and released 3,038 LRS and 267 SNS, and recaptured 762 LRS and 156 SNS that had been tagged in previous years. Remote PIT tag antennas in the traps at the weir on the Williamson River and remote antenna systems that spanned the river at three different locations on the Williamson and Sprague Rivers detected a total of 23,446 LRS and 6,259 SNS. Most LRS passed upstream in the first and second weeks of April when water temperatures were increasing and greater than 10 °C. In contrast, upstream passage for SNS occurred in two pulses, one in early April and one in late April to early May, when water temperatures were increasing and near or greater than 12 °C. Finally, an additional 375 LRS and 884 SNS were captured in trammel net sampling at pre-spawn staging areas in the northeastern part of the lake. Of these, 111 of the LRS and 390 of the SNS had been PIT-tagged in previous years. For LRS captured at the staging areas that had encounter histories that were informative about their spawning location, 79 percent of the fish were members of the subpopulation that spawns in the rivers.
\nCapture-recapture analyses for the LRS subpopulation that spawns at the shoreline areas included encounter histories for more than 13,200 individuals, and analyses for the subpopulation that spawns in the rivers included more than 36,400 encounter histories. With a few exceptions, the survival of males and females in both subpopulations was high (greater than 0.88) between 1999 and 2012. Notably lower survival occurred for both sexes from the rivers in 2000, for males from the shoreline areas in 2002, and for males from the rivers in 2006 and 2012. Between 2001 and 2013, the abundance of males in the lakeshore spawning subpopulation decreased by at least 55 percent and the abundance of females decreased by at least 42 percent. Capture-recapture models suggested that the abundance of both sexes in the river spawning subpopulation of LRS had increased substantially since 2006; increases were mostly due to large estimated recruitment events in 2006 and 2008. We know that the estimates in 2006 are substantially biased in favor of recruitment because of a sampling issue. We are skeptical of the magnitude of recruitment indicated by the 2008 estimates as well because (1) few small individuals that would indicate the presence of new recruits were captured in that year, and (2) recapture probabilities in recruitment models based on just physical recaptures of fish were lower than desired for robust inferences from capture-recapture models. If we assume instead that little or no recruitment occurred for this subpopulation, the abundance of both sexes in the river spawning subpopulation likely has decreased at rates similar to the rates for the lakeshore spawning subpopulation between 2002 and 2013.
\nCapture-recapture analyses for SNS included encounter histories for more than 19,200 individuals. Most annual survival estimates between 2001 and 2012 were high (greater than 0.80), but SNS experienced more years of low survival than either LRS subpopulation. Annual survival of both sexes was relatively low in 2004, 2010, and 2012. In addition, male survival was low in 2002. Capture-recapture models and size composition data indicate that recruitment of new individuals into the SNS spawning population was trivial between 2001 and 2005. Models indicate that more than 10 percent of the population was new recruits in a number of more recent years. As a result, capture-recapture modeling suggests that the abundance of adult spawning SNS was relatively stable between 2006 and 2010. We are skeptical of the estimated recruitment in 2006 because of the known sampling issue. We also are skeptical of the estimated recruitment in other recent years because few small individuals that would indicate the presence of new recruits were captured in any of those years, and recapture probabilities in recruitment models were low. The best-case scenario for SNS, based on capture-recapture recruitment modeling, indicates that the abundance of males in the spawning population decreased by 77 percent and the abundance of females decreased by 73 percent between 2001 and 2013. Decreases in abundance for both sexes likely are greater than these estimates indicate.
\nDespite relatively high survival in most years, we conclude that both species have experienced substantial decreases in the abundance of spawning adults because losses from mortality have not been balanced by recruitment of new individuals. Although capture-recapture data indicate substantial recruitment of new individuals into the spawning populations for SNS and river spawning LRS in some years, size data do not corroborate these estimates. As a result, the status of the endangered sucker populations in Upper Klamath Lake remains worrisome, especially for shortnose suckers. Our monitoring program provides a robust platform for estimating vital population parameters, evaluating the status of the populations, and assessing the effectiveness of conservation and recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151189","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hewitt, D.A., Janney, E.C., Hayes, B.S., and Harris, A.C., 2015, Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2014: U.S. Geological Survey Open-File Report 2015-1189, 36 p., https://dx.doi.org/10.3133/ofr20151189.","productDescription":"iv, 36 p.","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065787","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":309534,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1189/ofr20151189.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1189 PDF"},{"id":309533,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1189/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.80610656738281,\n 42.23512673690766\n ],\n [\n -121.81297302246092,\n 42.26511445833756\n ],\n [\n -121.82876586914061,\n 42.279848959767385\n ],\n [\n -121.82258605957031,\n 42.29711950573175\n ],\n [\n -121.81365966796874,\n 42.30879983710443\n ],\n [\n -121.82052612304688,\n 42.34382782918463\n ],\n [\n -121.82327270507812,\n 42.35296235855687\n ],\n [\n -121.80679321289062,\n 42.383401202818526\n ],\n [\n -121.83563232421875,\n 42.42142901536395\n ],\n [\n -121.86447143554686,\n 42.44372793752476\n ],\n [\n -121.87339782714844,\n 42.453354564875475\n ],\n [\n -121.88987731933594,\n 42.449301428414955\n ],\n [\n -121.90086364746094,\n 42.461460050936715\n ],\n [\n -121.91665649414062,\n 42.47361631282951\n ],\n [\n -121.93244934082031,\n 42.47007098029904\n ],\n [\n -121.95716857910155,\n 42.46855149059522\n ],\n [\n -121.97776794433594,\n 42.48323834594139\n ],\n [\n -122.00592041015626,\n 42.49792175437361\n ],\n [\n -122.04711914062499,\n 42.50197174319114\n ],\n [\n -122.05810546875,\n 42.488808320425846\n ],\n [\n -122.06565856933592,\n 42.46753847696729\n ],\n [\n -122.07252502441406,\n 42.46652544694582\n ],\n [\n -122.07870483398436,\n 42.48627657532141\n ],\n [\n -122.08831787109375,\n 42.482731960032936\n ],\n [\n -122.09449768066405,\n 42.46804498583046\n ],\n [\n -122.08145141601561,\n 42.455381034748896\n ],\n [\n -122.04299926757812,\n 42.42548395494743\n ],\n [\n -122.04505920410156,\n 42.416359972082866\n ],\n [\n -122.03201293945311,\n 42.39810802339276\n ],\n [\n -122.00523376464842,\n 42.39151573685182\n ],\n [\n -121.99356079101562,\n 42.40368557113506\n ],\n [\n -122.00042724609374,\n 42.41179748277328\n ],\n [\n -121.98257446289062,\n 42.40622065620649\n ],\n [\n -121.981201171875,\n 42.39405131362432\n ],\n [\n -121.97708129882812,\n 42.37934354245872\n ],\n [\n -121.95854187011717,\n 42.381879610913195\n ],\n [\n -121.95167541503906,\n 42.39455841668649\n ],\n [\n -121.95716857910155,\n 42.42092212947584\n ],\n [\n -121.94618225097656,\n 42.39912215986002\n ],\n [\n -121.94000244140624,\n 42.38035798213233\n ],\n [\n -121.91940307617188,\n 42.370720143531955\n ],\n [\n -121.90086364746094,\n 42.354992073710456\n ],\n [\n -121.92008972167969,\n 42.34941019930749\n ],\n [\n -121.94549560546875,\n 42.34433533786168\n ],\n [\n -121.94961547851562,\n 42.33519955487233\n ],\n [\n -121.94686889648438,\n 42.31590854308647\n ],\n [\n -121.93588256835938,\n 42.28950073090457\n ],\n [\n -121.92283630371092,\n 42.28035698458569\n ],\n [\n -121.92558288574217,\n 42.29711950573175\n ],\n [\n -121.9207763671875,\n 42.30676863078423\n ],\n [\n -121.904296875,\n 42.31083097788356\n ],\n [\n -121.89193725585936,\n 42.31540080499991\n ],\n [\n -121.88987731933594,\n 42.30321386201705\n ],\n [\n -121.87889099121092,\n 42.293056273848215\n ],\n [\n -121.86927795410156,\n 42.277816819534955\n ],\n [\n -121.8548583984375,\n 42.266638876842244\n ],\n [\n -121.84730529785155,\n 42.25495072629938\n ],\n [\n -121.84730529785155,\n 42.245801966774025\n ],\n [\n -121.83769226074219,\n 42.23766862211923\n ],\n [\n -121.8109130859375,\n 42.23105950761338\n ],\n [\n -121.80610656738281,\n 42.23512673690766\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/
Three aeromagnetic surveys were flown to improve understanding of the geology and structure in the Sacramento Valley. The resulting data serve as a basis for geophysical interpretations, and support geological mapping, water and mineral resource investigations, and other topical studies. Local spatial variations in the Earth's magnetic field (evident as anomalies on aeromagnetic maps) reflect the distribution of magnetic minerals, primarily magnetite, in the underlying rocks. In many cases the volume content of magnetic minerals can be related to rock type, and abrupt spatial changes in the amount of magnetic minerals commonly mark lithologic or structural boundaries. Bodies of serpentinite and other mafic and ultramafic rocks tend to produce the most intense positive magnetic anomalies (for example, in the northwest part of the map). These rock types are the inferred sources, concealed beneath weakly magnetic, valley-fill deposits, of the most prominent magnetic features in the map area, the magnetic highs that extend along the valley axis. Cenozoic volcanic rocks are also an important source of magnetic anomalies and coincide with short-wavelength anomalies that can be either positive (strong central positive anomaly flanked by lower-amplitude negative anomalies) or negative (strong central negative anomaly flanked by lower-amplitude positive anomalies), reflecting the contribution of remanent magnetization. Rocks with more felsic compositions or even some sedimentary units also can cause measurable magnetic anomalies. For example, the long, linear, narrow north-trending anomalies (with amplitudes of <50 nanoteslas [nT]) along the western margin of the valley coincide with exposures of the Mesozoic Great Valley sequence. Note that isolated, short-wavelength anomalies, such as those in the city of Sacramento and along some of the major roads, are caused by manmade features.
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zulanger@usgs.gov","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":148146,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria","email":"zulanger@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":574063,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70146877,"text":"tm6D3 - 2015 - Documentation of a restart option for the U.S. Geological Survey coupled Groundwater and Surface-Water Flow (GSFLOW) model","interactions":[],"lastModifiedDate":"2017-08-01T12:43:52","indexId":"tm6D3","displayToPublicDate":"2015-10-02T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and 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GSFLOW is an integration of the USGS Precipitation-Runoff Modeling System (PRMS) and USGS Modular Groundwater-Flow Model (MODFLOW), and provides three simulation modes: MODFLOW-only, PRMS-only, and GSFLOW (or coupled). The new capability, referred to as the restart option, can be used for all three simulation modes, such that the results from a pair (or set) of spin-up and restart simulations are nearly identical to results produced from a continuous simulation for the same time period. The restart option writes all results to files at the end of a spin-up simulation that are required to initialize a subsequent restart simulation. Previous versions of GSFLOW have had some capability to save model results for use as antecedent condiitions in subsequent simulations; however, the existing capabilities were not comprehensive or easy to use. The new restart option supersedes the previous methods. The restart option was developed in collaboration with the National Oceanic and Atmospheric Administration, National Weather Service as part of the Integrated Water Resources Science and Services Partnership. The primary focus for the development of the restart option was to support medium-range (7- to 14-day) forecasts of low streamflow conditions made by the National Weather Service for critical water-supply basins in which groundwater plays an important role.
\nThe spin-up simulation should be run for a sufficient length of time necessary to establish antecedent conditions throughout a model domain. Each GSFLOW application can require different lengths of time to account for the hydrologic stresses to propagate through a coupled groundwater and surface-water system. Typically, groundwater hydrologic processes require many years to come into equilibrium with dynamic climate and other forcing (or stress) data, such as precipitation and well pumping, whereas runoff-dominated surface-water processes respond relatively quickly. Use of a spin-up simulation can substantially reduce execution-time requirements for applications where the time period of interest is small compared to the time for hydrologic memory; thus, use of the restart option can be an efficient strategy for forecast and calibration simulations that require multiple simulations starting from the same day.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section D: Ground-water/Surface-water in Book 6U.S. Geological Survey
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