Selected micrometeorological and soil-moisture data were collected at the Amargosa Desert Research Site adjacent to a low-level radio-active waste and hazardous chemical waste facility near Beatty, Nevada, 2001-05. Evapotranspiration data were collected from February 2002 through the end of December 2005. Data were col-lected in support of ongoing research to improve the understanding of hydrologic and contaminant-transport processes in arid environments. Micrometeorological data include solar radiation, net radiation, air temperature, relative humidity, saturated and ambient vapor pressure, wind speed and direction, barometric pressure, precipitation, near-surface soil temperature, soil-heat flux and soil-water content. All micrometeorological data were collected using a 10-second sampling interval by data loggers that output daily and hourly mean values. Daily maximum and minimum values are based on hourly mean values. Precipitation data output includes daily and hourly totals. Selected soil-moisture profiles at depth include periodic measurements of soil volumetric water-content measurements at nine neutron-probe access tubes to depths ranging from 5.25 to 29.25 meters. Evapotranspiration data include measurement of daily evapotranspiration and 15-minute fluxes of the four principal energy budget components of latent-heat flux, sensible-heat flux, soil-heat flux, and net radiation. Other data collected and used in equations to determine evapotranspiration include temperature and water content of soil, temperature and vapor pressure of air, and covariance values. Evapotranspiration and flux estimates during 15-minute intervals were calculated at a 0.1-second execution interval using the eddy covariance method. Data files included in this report contain the complete micrometeorological, soil-moisture, and evapotranspiration field data sets. These data files are presented in tabular Excel spreadsheet format. This report highlights selected data contained in the computer generated data files using figures, tables, and brief discussions. Instrumentation used for data collection also is described. Water-content profiles are shown to demonstrate variability of water content with depth. Time-series data are plotted to illustrate temporal variations in micrometeorological, soil-water content, and evapotranspiration data.
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These agricultural basins are one of five areas in the United States selected for study as part of the National Water-Quality Assessment Program Agricultural Chemicals: Source, Transport, and Fate Study. The Program is designed to describe water-quality conditions and trends based on representative surface- and ground-water resources across the Nation. The objective of the Agricultural Chemicals topical study is to investigate the sources, transport, and fate of selected agricultural chemicals in a variety of agriculturally diverse environmental settings. The Granger Drain and DR2 basins were selected for the Agricultural Chemicals topical study because they represent the irrigated agricultural setting that characterizes eastern Washington. These basins are located in one of the most productive agricultural areas in the United States. This report describes the environmental setting of the Granger Drain and DR2 basins in the context of how agricultural practices, including agricultural chemical applications and irrigation methods, interface with natural settings and hydrologic processes.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/sir20075102","usgsCitation":"Payne, K.L., Johnson, H.M., and Black, R.W., 2007, Environmental Setting of the Granger Drain and DR2 Basins, Washington, 2003-04: U.S. Geological Survey Scientific Investigations Report 2007-5102, vi, 27 p., https://doi.org/10.3133/sir20075102.","productDescription":"vi, 27 p.","additionalOnlineFiles":"Y","temporalStart":"2003-01-01","temporalEnd":"2004-12-31","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":194804,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":10070,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2007/5102/","linkFileType":{"id":5,"text":"html"}}],"scale":"1","projection":"Albers","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.21666666666667,46.3 ], [ -120.21666666666667,46.5 ], [ -119.95,46.5 ], [ -119.95,46.3 ], [ -120.21666666666667,46.3 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4aa8e4b07f02db6673af","contributors":{"authors":[{"text":"Payne, Karen L. klpayne@usgs.gov","contributorId":3839,"corporation":false,"usgs":true,"family":"Payne","given":"Karen","email":"klpayne@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":292092,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Henry M. 0000-0002-7571-4994","orcid":"https://orcid.org/0000-0002-7571-4994","contributorId":105291,"corporation":false,"usgs":true,"family":"Johnson","given":"Henry","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":292093,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Black, Robert W. 0000-0002-4748-8213 rwblack@usgs.gov","orcid":"https://orcid.org/0000-0002-4748-8213","contributorId":1820,"corporation":false,"usgs":true,"family":"Black","given":"Robert","email":"rwblack@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":292091,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":80249,"text":"tm10C16 - 2007 - Determination of the δ15N of nitrate in water; RSIL lab code 2899","interactions":[],"lastModifiedDate":"2012-09-18T17:16:41","indexId":"tm10C16","displayToPublicDate":"2007-08-22T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"10-C16","title":"Determination of the δ15N of nitrate in water; RSIL lab code 2899","docAbstract":"The purpose of the Reston Stable Isotope Laboratory (RSIL) lab code 2899 is to determine the δ15N of nitrate (NO3-) in water. The δ15N of the dissolved NO3- is analyzed by conversion of the NO3- to nitrous oxide (N2O), which serves as the analyte for mass spectrometry. A culture of denitrifying bacteria is used in the enzymatic conversion of the NO3- to N2O, which follows the pathway shown in equation 1:NO3- → NO2- → NO → 1/2 N2O (1)
Because the bacteria Pseudomonas aureofaciens lack N2O reductive activity, the reaction stops at N2O, unlike the typical denitrification reaction that goes to N2. After several hours, the conversion is complete, and the N2O is extracted from the vial, separated from volatile organic vapor and water vapor by an automated -65 °C isopropanol-slush trap, a Nafion drier, a CO2 and water removal unit (Costech #021020 carbon dioxide absorbent with Mg(ClO4)2), and trapped in a small-volume trap immersed in liquid nitrogen with a modified Finnigan MAT (now Thermo Scientific) GasBench 2 introduction system. After the N2O is released, it is further purified by gas chromatography before introduction to the isotope-ratio mass spectrometer (IRMS). The IRMS is a Thermo Scientific Delta V Plus continuous flow IRMS (CF-IRMS). It has a universal triple collector, consisting of two wide cups with a narrow cup in the middle; it is capable of simultaneously measuring mass/charge (m/z) of the N2O molecule 44, 45, and 46. The ion beams from these m/z values are as follows: m/z = 44 = N2O = 14N14N16O; m/z = 45 = N2O = 14N15N16O or 14N14N17O; m/z = 46 = N2O = 14N14N18O. The 17O contributions to the m/z 44 and m/z 45 ion beams are accounted for before δ15N values are reported.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Chapter 16 of Section C, Stable Isotope-Ratio Methods, Book 10, Methods of the Reston Stable Isotope Laboratory ","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm10C16","usgsCitation":"Coplen, T.B., Qi, H., Revesz, K., Casciotti, K., and Hannon, J.E., 2007, Determination of the δ15N of nitrate in water; RSIL lab code 2899 (Version 1.0 - 2007, Version 1.1 - September 2012): U.S. Geological Survey Techniques and Methods 10-C16, viii, 35 p., https://doi.org/10.3133/tm10C16.","productDescription":"viii, 35 p.","numberOfPages":"45","onlineOnly":"Y","costCenters":[{"id":543,"text":"Reston Stable Isotope Laboratory","active":false,"usgs":true}],"links":[{"id":192128,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_10_C16.gif"},{"id":10069,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/2006/tm10c16/","linkFileType":{"id":5,"text":"html"}},{"id":261914,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/2006/tm10c16/pdf/tm10c16.pdf","linkFileType":{"id":1,"text":"pdf"}}],"edition":"Version 1.0 - 2007, Version 1.1 - September 2012","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4aa8e4b07f02db667577","contributors":{"authors":[{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":292087,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qi, Haiping 0000-0002-8339-744X haipingq@usgs.gov","orcid":"https://orcid.org/0000-0002-8339-744X","contributorId":507,"corporation":false,"usgs":true,"family":"Qi","given":"Haiping","email":"haipingq@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":292086,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Revesz, Kinga","contributorId":64285,"corporation":false,"usgs":true,"family":"Revesz","given":"Kinga","affiliations":[],"preferred":false,"id":292089,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casciotti, Karen","contributorId":102153,"corporation":false,"usgs":true,"family":"Casciotti","given":"Karen","affiliations":[],"preferred":false,"id":292090,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hannon, Janet E. jehannon@usgs.gov","contributorId":3177,"corporation":false,"usgs":true,"family":"Hannon","given":"Janet","email":"jehannon@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":292088,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":80241,"text":"tm6A21 - 2007 - MODFLOW-2005, The U.S. Geological Survey Modular Ground-Water Model - Documentation of the Multiple-Refined-Areas Capability of Local Grid Refinement (LGR) and the Boundary Flow and Head (BFH) Package","interactions":[],"lastModifiedDate":"2012-02-02T00:14:07","indexId":"tm6A21","displayToPublicDate":"2007-08-21T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-A21","title":"MODFLOW-2005, The U.S. Geological Survey Modular Ground-Water Model - Documentation of the Multiple-Refined-Areas Capability of Local Grid Refinement (LGR) and the Boundary Flow and Head (BFH) Package","docAbstract":"This report documents the addition of the multiple-refined-areas capability to shared node Local Grid Refinement (LGR) and Boundary Flow and Head (BFH) Package of MODFLOW-2005, the U.S. Geological Survey modular, three-dimensional, finite-difference ground-water flow model. LGR now provides the capability to simulate ground-water flow by using one or more block-shaped, higher resolution local grids (child model) within a coarser grid (parent model). LGR accomplishes this by iteratively coupling separate MODFLOW-2005 models such that heads and fluxes are balanced across the shared interfacing boundaries. The ability to have multiple, nonoverlapping areas of refinement is important in situations where there is more than one area of concern within a regional model. In this circumstance, LGR can be used to simulate these distinct areas with higher resolution grids. LGR can be used in two-and three-dimensional, steady-state and transient simulations and for simulations of confined and unconfined ground-water systems. The BFH Package can be used to simulate these situations by using either the parent or child models independently.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Chapter 21 of Book 6, Modeling Techniques, Section A, Ground Water","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/tm6A21","collaboration":"A Product of the Ground-Water Resources Program, Prepared in Cooperation with the U.S. Department of Energy","usgsCitation":"Mehl, S.W., and Hill, M.C., 2007, MODFLOW-2005, The U.S. Geological Survey Modular Ground-Water Model - Documentation of the Multiple-Refined-Areas Capability of Local Grid Refinement (LGR) and the Boundary Flow and Head (BFH) Package (Version 1.0): U.S. Geological Survey Techniques and Methods 6-A21, v, 13 p., https://doi.org/10.3133/tm6A21.","productDescription":"v, 13 p.","onlineOnly":"Y","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":123125,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_6_a21.gif"},{"id":10061,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/2007/06A21/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a7fe4b07f02db648d05","contributors":{"authors":[{"text":"Mehl, Steffen W. swmehl@usgs.gov","contributorId":975,"corporation":false,"usgs":true,"family":"Mehl","given":"Steffen","email":"swmehl@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":true,"id":292069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hill, Mary C. mchill@usgs.gov","contributorId":974,"corporation":false,"usgs":true,"family":"Hill","given":"Mary","email":"mchill@usgs.gov","middleInitial":"C.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":292068,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":80237,"text":"ofr20071212 - 2007 - Interim Summary: Nesting Counts of Ospreys and Brown Pelicans in Northwestern Mexico, 2006","interactions":[],"lastModifiedDate":"2012-02-10T00:11:41","indexId":"ofr20071212","displayToPublicDate":"2007-08-21T00:00:00","publicationYear":"2007","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":"2007-1212","title":"Interim Summary: Nesting Counts of Ospreys and Brown Pelicans in Northwestern Mexico, 2006","docAbstract":"The distribution and abundance of nesting populations of California brown pelicans (Pelecanus occidentalis californicus) and ospreys (Pandion haliaetus) were documented in 2006 in northwestern Mexico. For ospreys only, the 2006 data were compared to population estimates from two previous surveys (one conducted in 1977 and another conducted in the period 1992-1993). Overall, the total osprey nesting population increased from 1977 to 1992-1993 and then only changed slightly by 2006, but included regions with localized declines, increases, and stable populations. Preliminary population estimates for California brown pelicans suggest a large and apparently healthy breeding population.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/ofr20071212","usgsCitation":"Henny, C.J., and Anderson, D.W., 2007, Interim Summary: Nesting Counts of Ospreys and Brown Pelicans in Northwestern Mexico, 2006: U.S. Geological Survey Open-File Report 2007-1212, iii, 15 p., https://doi.org/10.3133/ofr20071212.","productDescription":"iii, 15 p.","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":190525,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":10056,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2007/1212/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -118,22 ], [ -118,34 ], [ -106,34 ], [ -106,22 ], [ -118,22 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49dbe4b07f02db5e0a9e","contributors":{"authors":[{"text":"Henny, Charles J. 0000-0001-7474-350X hennyc@usgs.gov","orcid":"https://orcid.org/0000-0001-7474-350X","contributorId":3461,"corporation":false,"usgs":true,"family":"Henny","given":"Charles","email":"hennyc@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":292054,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Daniel W.","contributorId":74345,"corporation":false,"usgs":false,"family":"Anderson","given":"Daniel","email":"","middleInitial":"W.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":292055,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":80238,"text":"ofr20071240 - 2007 - Legacy mercury in Alviso Slough, south San Francisco Bay, California: Concentration, speciation and mobility","interactions":[],"lastModifiedDate":"2021-09-01T19:41:05.962082","indexId":"ofr20071240","displayToPublicDate":"2007-08-21T00:00:00","publicationYear":"2007","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":"2007-1240","title":"Legacy mercury in Alviso Slough, south San Francisco Bay, California: Concentration, speciation and mobility","docAbstract":"Mercury (Hg) is a significant contaminant in the waters, sediment and biota of San Francisco Bay, largely resulting from extensive historic regional mining activities. Alviso Slough represents one of the most mercury contaminated waterways entering south San Francisco Bay, as it is associated with the drainage of the New Almaden mercury mining district. Wetland habitat restoration of former salt manufacturing ponds adjacent to Alviso Slough is currently being planned. One management scenario being considered is a levee breach between Alviso Slough and Pond A8, which will allow reconnection of the salt pond with the tidal slough. This action is projected to increase the tidal prism within Alviso Slough and result in some degree of sediment remobilization as the main channel deepens and widens. The focus of the current study is to assess: a) the current mercury species composition and concentration in sediments within the Alviso Slough main channel and its associated fringing marsh plain, b) how much of each mercury species will be mobilized as a result of projected channel deepening and widening, and c) potential changes in inorganic reactive mercury bioavailability (for conversion to toxic methylmercury) associated with the mobilized sediment fraction. The current report details the field sampling approach and all laboratory analyses conducted, as well as provides the complete dataset associated with this project including a) a quantitative assessment of mercury speciation (total mercury, reactive mercury and methylmercury), b) estimates of the quantity of sediment and mercury mobilized based on 20-foot and 40-foot levee wall notch scenarios, and c) results from a sediment scour experiment examining the changes in the reactive mercury pool under four treatment conditions (high / low salinity and oxic / anoxic water). Ancillary sediment data also collected and reported herein include bulk density, organic content, magnetic susceptibility, percent dry weight, grain size, pH, oxidation-reduction potential, core photography, and detailed lithographic descriptions.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20071240","usgsCitation":"Marvin-DiPasquale, M., and Cox, M.H., 2007, Legacy mercury in Alviso Slough, south San Francisco Bay, California: Concentration, speciation and mobility: U.S. Geological Survey Open-File Report 2007-1240, vi, 99 p., https://doi.org/10.3133/ofr20071240.","productDescription":"vi, 99 p.","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":192114,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":10057,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2007/1240/","linkFileType":{"id":5,"text":"html"}},{"id":388750,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_81621.htm"}],"country":"United States","state":"California","otherGeospatial":"South San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.728271484375,\n 37.87485339352928\n ],\n [\n -122.22290039062499,\n 37.33522435930639\n ],\n [\n -121.871337890625,\n 37.37015718405753\n ],\n [\n -121.981201171875,\n 37.68382032669382\n ],\n [\n -122.15698242187499,\n 38.004819966413194\n ],\n [\n -122.728271484375,\n 37.87485339352928\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b17e4b07f02db6a61d0","contributors":{"authors":[{"text":"Marvin-DiPasquale, Mark","contributorId":57423,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","affiliations":[],"preferred":false,"id":292057,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cox, Marisa H.","contributorId":52146,"corporation":false,"usgs":true,"family":"Cox","given":"Marisa","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":292056,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":80242,"text":"tm6E3 - 2007 - MMA, A Computer Code for Multi-Model Analysis","interactions":[],"lastModifiedDate":"2012-02-02T00:14:19","indexId":"tm6E3","displayToPublicDate":"2007-08-21T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-E3","title":"MMA, A Computer Code for Multi-Model Analysis","docAbstract":"This report documents the Multi-Model Analysis (MMA) computer code. MMA can be used to evaluate results from alternative models of a single system using the same set of observations for all models. As long as the observations, the observation weighting, and system being represented are the same, the models can differ in nearly any way imaginable. For example, they may include different processes, different simulation software, different temporal definitions (for example, steady-state and transient models could be considered), and so on. The multiple models need to be calibrated by nonlinear regression. Calibration of the individual models needs to be completed before application of MMA.\r\n\r\nMMA can be used to rank models and calculate posterior model probabilities. These can be used to\r\n(1) determine the relative importance of the characteristics embodied in the alternative models,\r\n(2) calculate model-averaged parameter estimates and predictions, and\r\n(3) quantify the uncertainty of parameter estimates and predictions in a way that integrates the variations represented by the alternative models.\r\n\r\nThere is a lack of consensus on what model analysis methods are best, so MMA provides four default methods. Two are based on Kullback-Leibler information, and use the AIC (Akaike Information Criterion) or AICc (second-order-bias-corrected AIC) model discrimination criteria. The other two default methods are the BIC (Bayesian Information Criterion) and the KIC (Kashyap Information Criterion) model discrimination criteria. Use of the KIC criterion is equivalent to using the maximum-likelihood Bayesian model averaging (MLBMA) method. AIC, AICc, and BIC can be derived from Frequentist or Bayesian arguments. The default methods based on Kullback-Leibler information have a number of theoretical advantages, including that they tend to favor more complicated models as more data become available than do the other methods, which makes sense in many situations.\r\n\r\nMany applications of MMA will be well served by the default methods provided. To use the default methods, the only required input for MMA is a list of directories where the files for the alternate models are located.\r\n\r\nEvaluation and development of model-analysis methods are active areas of research. To facilitate exploration and innovation, MMA allows the user broad discretion to define alternatives to the default procedures. For example, MMA allows the user to (a) rank models based on model criteria defined using a wide range of provided and user-defined statistics in addition to the default AIC, AICc, BIC, and KIC criteria, (b) create their own criteria using model measures available from the code, and (c) define how each model criterion is used to calculate related posterior model probabilities.\r\n\r\nThe default model criteria rate models are based on model fit to observations, the number of observations and estimated parameters, and, for KIC, the Fisher information matrix. In addition, MMA allows the analysis to include an evaluation of estimated parameter values. This is accomplished by allowing the user to define unreasonable estimated parameter values or relative estimated parameter values. An example of the latter is that it may be expected that one parameter value will be less than another, as might be the case if two parameters represented the hydraulic conductivity of distinct materials such as fine and coarse sand. Models with parameter values that violate the user-defined conditions are excluded from further consideration by MMA.\r\n\r\nGround-water models are used as examples in this report, but MMA can be used to evaluate any set of models for which the required files have been produced.\r\n\r\nMMA needs to read files from a separate directory for each alternative model considered. The needed files are produced when using the Sensitivity-Analysis or Parameter-Estimation mode of UCODE_2005, or, possibly, the equivalent capability of another program.\r\n\r\nMMA is constructed using ","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Chapter 3 of Book 6. Modeling Techniques, Section E. Model Analysis","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/tm6E3","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, U.S. Department of Energy, and International Ground Water Modeling Center, Colorado School of Mines","usgsCitation":"Poeter, E.P., and Hill, M.C., 2007, MMA, A Computer Code for Multi-Model Analysis (Version 1.0): U.S. Geological Survey Techniques and Methods 6-E3, x, 113 p., https://doi.org/10.3133/tm6E3.","productDescription":"x, 113 p.","onlineOnly":"Y","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":120724,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_6_e3.gif"},{"id":10062,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/2007/06E03/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a7fe4b07f02db648c2b","contributors":{"authors":[{"text":"Poeter, Eileen P.","contributorId":78805,"corporation":false,"usgs":true,"family":"Poeter","given":"Eileen","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":292071,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hill, Mary C. mchill@usgs.gov","contributorId":974,"corporation":false,"usgs":true,"family":"Hill","given":"Mary","email":"mchill@usgs.gov","middleInitial":"C.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":292070,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":80243,"text":"sir20075153 - 2007 - Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Sheyenne River, North Dakota, 1980-2006","interactions":[],"lastModifiedDate":"2017-10-14T14:08:48","indexId":"sir20075153","displayToPublicDate":"2007-08-21T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2007-5153","title":"Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Sheyenne River, North Dakota, 1980-2006","docAbstract":"This report presents the results of a study by the U.S. Geological Survey, done in cooperation with the North Dakota State Water Commission, to estimate water-quality constituent concentrations at seven sites on the Sheyenne River, N. Dak. Regression analysis of water-quality data collected in 1980-2006 was used to estimate concentrations for hardness, dissolved solids, calcium, magnesium, sodium, and sulfate. The explanatory variables examined for the regression relations were continuously monitored streamflow, specific conductance, and water temperature. For the conditions observed in 1980-2006, streamflow was a significant explanatory variable for some constituents. Specific conductance was a significant explanatory variable for all of the constituents, and water temperature was not a statistically significant explanatory variable for any of the constituents in this study.\r\n\r\nThe regression relations were evaluated using common measures of variability, including R2, the proportion of variability in the estimated constituent concentration explained by the explanatory variables and regression equation. R2 values ranged from 0.784 for calcium to 0.997 for dissolved solids. The regression relations also were evaluated by calculating the median relative percentage difference (RPD) between measured constituent concentration and the constituent concentration estimated by the regression equations. Median RPDs ranged from 1.7 for dissolved solids to 11.5 for sulfate. The regression relations also may be used to estimate daily constituent loads.\r\n\r\nThe relations should be monitored for change over time, especially at sites 2 and 3 which have a short period of record. In addition, caution should be used when the Sheyenne River is affected by ice or when upstream sites are affected by isolated storm runoff. Almost all of the outliers and highly influential samples removed from the analysis were made during periods when the Sheyenne River might be affected by ice.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20075153","collaboration":"Prepared in cooperation with the North Dakota State Water Commission","usgsCitation":"Ryberg, K.R., 2007, Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Sheyenne River, North Dakota, 1980-2006: U.S. Geological Survey Scientific Investigations Report 2007-5153, v, 22 p., https://doi.org/10.3133/sir20075153.","productDescription":"v, 22 p.","onlineOnly":"Y","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":125707,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2007_5153.jpg"},{"id":10063,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2007/5153/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"North Dakota","otherGeospatial":"Sheyenne River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -101,46 ], [ -101,48.5 ], [ -96.5,48.5 ], [ -96.5,46 ], [ -101,46 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4af3e4b07f02db6919d4","contributors":{"authors":[{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":292072,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":80240,"text":"tm6E2 - 2007 - OPR-PPR, a computer program for assessing data importance to model predictions using linear statistics","interactions":[],"lastModifiedDate":"2020-01-26T10:37:27","indexId":"tm6E2","displayToPublicDate":"2007-08-21T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-E2","title":"OPR-PPR, a computer program for assessing data importance to model predictions using linear statistics","docAbstract":"The OPR-PPR program calculates the Observation-Prediction (OPR) and Parameter-Prediction (PPR) statistics that can be used to evaluate the relative importance of various kinds of data to simulated predictions. The data considered fall into three categories: (1) existing observations, (2) potential observations, and (3) potential information about parameters. The first two are addressed by the OPR statistic; the third is addressed by the PPR statistic. The statistics are based on linear theory and measure the leverage of the data, which depends on the location, the type, and possibly the time of the data being considered. For example, in a ground-water system the type of data might be a head measurement at a particular location and time. As a measure of leverage, the statistics do not take into account the value of the measurement. As linear measures, the OPR and PPR statistics require minimal computational effort once sensitivities have been calculated. Sensitivities need to be calculated for only one set of parameter values; commonly these are the values estimated through model calibration. OPR-PPR can calculate the OPR and PPR statistics for any mathematical model that produces the necessary OPR-PPR input files. In this report, OPR-PPR capabilities are presented in the context of using the ground-water model MODFLOW-2000 and the universal inverse program UCODE_2005.\r\n\r\nThe method used to calculate the OPR and PPR statistics is based on the linear equation for prediction standard deviation. Using sensitivities and other information, OPR-PPR calculates (a) the percent increase in the prediction standard deviation that results when one or more existing observations are omitted from the calibration data set; (b) the percent decrease in the prediction standard deviation that results when one or more potential observations are added to the calibration data set; or (c) the percent decrease in the prediction standard deviation that results when potential information on one or more parameters is added.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Chapter 2 of Book 6. Modeling Techniques, Section E. Model Analysis","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey ","doi":"10.3133/tm6E2","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Tonkin, M.J., Tiedeman, C.R., Ely, D.M., and Hill, M.C., 2007, OPR-PPR, a computer program for assessing data importance to model predictions using linear statistics: U.S. Geological Survey Techniques and Methods 6-E2, viii, 115 p., https://doi.org/10.3133/tm6E2.","productDescription":"viii, 115 p.","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":190836,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":10059,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/2007/tm6e2/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b23e4b07f02db6adf20","contributors":{"authors":[{"text":"Tonkin, Matthew J.","contributorId":26376,"corporation":false,"usgs":true,"family":"Tonkin","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":292065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tiedeman, Claire R. 0000-0002-0128-3685 tiedeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0128-3685","contributorId":196777,"corporation":false,"usgs":true,"family":"Tiedeman","given":"Claire","email":"tiedeman@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":292066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ely, D. Matthew","contributorId":100052,"corporation":false,"usgs":true,"family":"Ely","given":"D.","email":"","middleInitial":"Matthew","affiliations":[],"preferred":false,"id":292067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hill, Mary C. mchill@usgs.gov","contributorId":974,"corporation":false,"usgs":true,"family":"Hill","given":"Mary","email":"mchill@usgs.gov","middleInitial":"C.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":292064,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":80244,"text":"fs20073058 - 2007 - Assessment of Undiscovered Oil and Gas Resources of the Illinois Basin, 2007","interactions":[],"lastModifiedDate":"2016-09-06T15:16:08","indexId":"fs20073058","displayToPublicDate":"2007-08-21T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2007-3058","title":"Assessment of Undiscovered Oil and Gas Resources of the Illinois Basin, 2007","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated the following quantities of undiscovered, technically recoverable\r\noil and gas resources in the Illinois Basin, USA: (1) a mean of 214 million barrels of oil; (2) a mean of 4.65 trillion cubic feet of natural gas; and (3) a mean of 24 million barrels of natural gas liquids.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20073058","usgsCitation":"Swezey, C., 2007, Assessment of Undiscovered Oil and Gas Resources of the Illinois Basin, 2007: U.S. Geological Survey Fact Sheet 2007-3058, 2 p., https://doi.org/10.3133/fs20073058.","productDescription":"2 p.","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":122358,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2007_3058.jpg"},{"id":10064,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2007/3058/","linkFileType":{"id":5,"text":"html"}},{"id":328285,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2007/3058/fs2007-3058.pdf"}],"country":"United States","otherGeospatial":"Illinois Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92,35 ], [ -92,42 ], [ -84,42 ], [ -84,35 ], [ -92,35 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4af3e4b07f02db691c17","contributors":{"authors":[{"text":"Swezey, Christopher S.","contributorId":52640,"corporation":false,"usgs":true,"family":"Swezey","given":"Christopher S.","affiliations":[],"preferred":false,"id":292073,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":80239,"text":"ofr20071180 - 2007 - Organic geochemistry of sediments in nearshore areas of the Mississippi and Atchafalaya Rivers: I. General organic characterization","interactions":[],"lastModifiedDate":"2022-06-27T21:49:49.594137","indexId":"ofr20071180","displayToPublicDate":"2007-08-21T00:00:00","publicationYear":"2007","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":"2007-1180","title":"Organic geochemistry of sediments in nearshore areas of the Mississippi and Atchafalaya Rivers: I. General organic characterization","docAbstract":"This report presents results on the general organic characteristics of sediment cores collected from the coastal zone of the Mississippi River system, including distributions of the important nutrient elements (C, N, P, and S). This was part of a larger study conducted from 2001-2005 to examine the delivery of sediment-associated contaminants to the Gulf of Mexico by the Mississippi River system, funded by the USGS Coastal and Marine Geology Program. Companion reports emphasize organic contaminants (Rosenbauer and others, 2006), and metals (Swarzenski and others, 2006). The level of contamination within the deltaic system of the Mississippi River system was determined through the collection of sediment cores from interdistributary bays, and offshore in the Gulf of Mexico, including the zone of hypoxia. Results provide the basis for reconstructing contaminant inventories from which to develop historic perspectives on nutrient loading and hypoxia, and to better understand how sediment-hosted contaminants either directly or indirectly move through biota and ultimately affect ecosystem health.\r\n\r\nConcentrations of C, N, P, and S in sediments varied by a factor of 10 between sites, and in down core profiles. Nearshore cores collected in 2001 proved to have erratic downcore C, N, P, and S profiles and sediment deposition rates, suggesting a high energy regime controlled more by variability in river flow rather than by geochemical processes and reactions within the system. These results focused further coring activities further offshore. Atomic C/N ratios suggest that organic matter deposited at all sites is a mix of microbial (algal) and terrestrial (vascular plant) remains, but with algal material dominant. Concentrations of total sulfur in sediments from cores in the zone of hypoxia were often higher than those in nearby zones with oxic water columns. Corresponding atomic C/S ratios were typically lower in sediments from sites in the zone of hypoxia compared to nearby sites with oxic water columns, and thus atomic C/S values may be useful as a proxy for identifying sites impacted by hypoxic conditions in the water column and for examining historical trends in hypoxia. At one site examined in this study, maximum hypoxic conditions were observed in the mid 1960's. The organic elemental composition (C, N, P, and S) of sediments was also used to guide sample selection for contaminant analysis, and to normalize the contaminant data to organic C content of the sediments.\r\n\r\nDissolved hydrocarbon gases in sediments showed a dominance of methane, but identifiable concentrations of ethane and hexane, and trace concentrations of propane, butane, and pentane were also detected. All dissolved gases except hexane were dominated by 'bound' gas, gas released only after agitation of the sediment in a blender. Hexane, in contrast was observed mostly as free gas, determined by headspace analysis.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20071180","usgsCitation":"Orem, W.H., Rosenbauer, R.J., Swarzenski, P.W., Lerch, H.E., Corum, M., and Bates, A.L., 2007, Organic geochemistry of sediments in nearshore areas of the Mississippi and Atchafalaya Rivers: I. General organic characterization: U.S. Geological Survey Open-File Report 2007-1180, 67 p., https://doi.org/10.3133/ofr20071180.","productDescription":"67 p.","onlineOnly":"Y","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":192210,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":402570,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_81622.htm","linkFileType":{"id":5,"text":"html"}},{"id":10058,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2007/1180/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Atchafalaya River, Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.669921875,\n 28.8927788645183\n ],\n [\n -88.802490234375,\n 28.8927788645183\n ],\n [\n -88.802490234375,\n 29.92637417863576\n ],\n [\n -91.669921875,\n 29.92637417863576\n ],\n [\n -91.669921875,\n 28.8927788645183\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b12e4b07f02db6a2f69","contributors":{"authors":[{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":292059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenbauer, Robert J. brosenbauer@usgs.gov","contributorId":204,"corporation":false,"usgs":true,"family":"Rosenbauer","given":"Robert","email":"brosenbauer@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":292058,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":292061,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lerch, Harry E. tlerch@usgs.gov","contributorId":600,"corporation":false,"usgs":true,"family":"Lerch","given":"Harry","email":"tlerch@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":292060,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Corum, M.D. 0000-0002-9038-3935 mcorum@usgs.gov","orcid":"https://orcid.org/0000-0002-9038-3935","contributorId":2249,"corporation":false,"usgs":true,"family":"Corum","given":"M.D.","email":"mcorum@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":292062,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bates, Anne L. 0000-0002-4875-4675 abates@usgs.gov","orcid":"https://orcid.org/0000-0002-4875-4675","contributorId":2789,"corporation":false,"usgs":true,"family":"Bates","given":"Anne","email":"abates@usgs.gov","middleInitial":"L.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":292063,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":80234,"text":"ofr20071149 - 2007 - Monitoring Ground-Water Quality in Coastal Ecosystems","interactions":[],"lastModifiedDate":"2018-05-17T13:49:13","indexId":"ofr20071149","displayToPublicDate":"2007-08-17T00:00:00","publicationYear":"2007","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":"2007-1149","title":"Monitoring Ground-Water Quality in Coastal Ecosystems","docAbstract":"INTRODUCTION\r\n\r\nThe Cape Cod National Seashore (CACO) extends along more than 70 km of Atlantic Ocean open-beach coastline and includes three large saltwater bays - Wellfleet Harbor, Nauset Marsh, and Pleasant Bay (fig. 1). CACO encompasses about 18,000 ha of uplands, lakes, wetlands, and tidal lands (Godfrey and others, 1999) including most habitats typical of the sandy coast in National seashores and parks extending southward from Massachusetts to Florida. In 1995, CACO was selected by the National Park Service (NPS) as a prototype park typifying the Atlantic and Gulf Coast biogeographic region for long-term coastal ecosystem monitoring. The U.S. Geological Survey (USGS) is currently (2007) assisting the NPS in the development of protocols for a Long-Term Coastal Ecosystem Monitoring Program at the CACO in Massachusetts. The overall purpose of the monitoring program is to characterize both natural and human-induced change in the biological resources of the CACO, over a time scale of decades, in the context of a changing global ecosystem.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/ofr20071149","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Colman, J.A., and Masterson, J., 2007, Monitoring Ground-Water Quality in Coastal Ecosystems: U.S. Geological Survey Open-File Report 2007-1149, x, 95 p., https://doi.org/10.3133/ofr20071149.","productDescription":"x, 95 p.","onlineOnly":"Y","costCenters":[{"id":377,"text":"Massachusetts-Rhode Island Water Science Center","active":false,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":192246,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":10053,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2007/1149/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -70.25,41.583333333333336 ], [ -70.25,42.083333333333336 ], [ -69.83333333333333,42.083333333333336 ], [ -69.83333333333333,41.583333333333336 ], [ -70.25,41.583333333333336 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a4de4b07f02db62757c","contributors":{"authors":[{"text":"Colman, John A. 0000-0001-9327-0779 jacolman@usgs.gov","orcid":"https://orcid.org/0000-0001-9327-0779","contributorId":2098,"corporation":false,"usgs":true,"family":"Colman","given":"John","email":"jacolman@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":292045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Masterson, John P. 0000-0003-3202-4413 jpmaster@usgs.gov","orcid":"https://orcid.org/0000-0003-3202-4413","contributorId":1865,"corporation":false,"usgs":true,"family":"Masterson","given":"John P.","email":"jpmaster@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":292044,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":80236,"text":"ofr20071116 - 2007 - Coal quality and major, minor, and trace elements in the Powder River, Green River, and Williston basins, Wyoming and North Dakota","interactions":[],"lastModifiedDate":"2018-08-28T16:17:27","indexId":"ofr20071116","displayToPublicDate":"2007-08-17T00:00:00","publicationYear":"2007","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":"2007-1116","title":"Coal quality and major, minor, and trace elements in the Powder River, Green River, and Williston basins, Wyoming and North Dakota","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the Wyoming Reservoir Management Group (RMG) of the Bureau of Land Management (BLM) and nineteen independent coalbed methane (CBM) gas operators in the Powder River and Green River Basins in Wyoming and the Williston Basin in North Dakota, collected 963 coal samples from 37 core holes (fig. 1; table 1) between 1999 and 2005. The drilling and coring program was in response to the rapid development of CBM, particularly in the Powder River Basin (PRB), and the needs of the RMG BLM for new and more reliable data for CBM resource estimates and reservoir characterization. The USGS and BLM entered into agreements with the gas operators to drill and core Fort Union coal beds, thus supplying core samples for the USGS to analyze and provide the RMG with rapid, real-time results of total gas desorbed, coal quality, and high pressure methane adsorption isotherm data (Stricker and others, 2006).\r\n\r\nThe USGS determined the ultimate composition of all coal core samples; for selected samples analyses also included proximate analysis, calorific value, equilibrium moisture, apparent specific gravity, and forms of sulfur. Analytical procedures followed those of the American Society of Testing Materials (ASTM; 1998). In addition, samples from three wells (129 samples) were analyzed for major, minor, and trace element contents. Ultimate and proximate compositions, calorific value, and forms of sulfur are fundamental parameters in evaluating the economic value of a coal. Determining trace element concentrations, along with total sulfur and ash yield, is also essential to assess the environmental effects of coal use, as is the suitability of the coal for cleaning, gasification, liquefaction, and other treatments. Determination of coal quality in the deeper part (depths greater than 1,000 to 1,200 ft) of the PRB (Rohrbacher and others, 2006; Luppens and others, 2006) is especially important, because these coals are targeted for future mining and development.\r\n\r\nThis report contains summary tables, histograms, and isopleth maps of coal analyses. Details of the compositional internal variability of the coal beds are based on the continuous vertical sampling of coal sequences, including beds in the deeper part of the PRB. Such sampling allows for close comparisons of the compositions of different parts of coal beds as well as within the same coal beds at different core hole locations within short distances of each other.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20071116","usgsCitation":"Stricker, G.D., Flores, R.M., Trippi, M.H., Ellis, M.S., Olson, C.M., Sullivan, J.E., and Takahashi, K., 2007, Coal quality and major, minor, and trace elements in the Powder River, Green River, and Williston basins, Wyoming and North Dakota (Version 1.0): U.S. Geological Survey Open-File Report 2007-1116, Report: iv, 31 p.; 4 Appendices, https://doi.org/10.3133/ofr20071116.","productDescription":"Report: iv, 31 p.; 4 Appendices","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":194733,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":10055,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2007/1116/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -115,40 ], [ -115,49 ], [ -95,49 ], [ -95,40 ], [ -115,40 ] ] ] } } ] }","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49d6e4b07f02db5de033","contributors":{"authors":[{"text":"Stricker, Gary D. gstricker@usgs.gov","contributorId":87163,"corporation":false,"usgs":true,"family":"Stricker","given":"Gary","email":"gstricker@usgs.gov","middleInitial":"D.","affiliations":[{"id":165,"text":"Central Energy Resources Team","active":false,"usgs":true}],"preferred":false,"id":292052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flores, Romeo M. rflores@usgs.gov","contributorId":71984,"corporation":false,"usgs":true,"family":"Flores","given":"Romeo","email":"rflores@usgs.gov","middleInitial":"M.","affiliations":[{"id":165,"text":"Central Energy Resources Team","active":false,"usgs":true}],"preferred":false,"id":292050,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Trippi, Michael H. 0000-0002-1398-3427 mtrippi@usgs.gov","orcid":"https://orcid.org/0000-0002-1398-3427","contributorId":941,"corporation":false,"usgs":true,"family":"Trippi","given":"Michael","email":"mtrippi@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":292048,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ellis, Margaret S. mellis@usgs.gov","contributorId":198,"corporation":false,"usgs":true,"family":"Ellis","given":"Margaret","email":"mellis@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":292047,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olson, Carol M.","contributorId":103758,"corporation":false,"usgs":true,"family":"Olson","given":"Carol","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":292053,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sullivan, Jonah E.","contributorId":48658,"corporation":false,"usgs":true,"family":"Sullivan","given":"Jonah","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":292049,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Takahashi, Kenneth I.","contributorId":85954,"corporation":false,"usgs":true,"family":"Takahashi","given":"Kenneth I.","affiliations":[],"preferred":false,"id":292051,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":80233,"text":"tm10C17 - 2007 - Determination of the δ15N and δ18O of nitrate in water; RSIL lab code 2900","interactions":[],"lastModifiedDate":"2012-09-18T17:16:41","indexId":"tm10C17","displayToPublicDate":"2007-08-16T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"10-C17","title":"Determination of the δ15N and δ18O of nitrate in water; RSIL lab code 2900","docAbstract":"The purpose of the Reston Stable Isotope Laboratory (RSIL) lab code 2900 is to determine the δ15N and δ18O of nitrate (NO3-) in water. The δ15N and δ18O of the dissolved NO3- are analyzed by converting the NO3- to nitrous oxide (N2O), which serves as the analyte for mass spectrometry. A culture of denitrifying bacteria is used in the enzymatic conversion of the NO3- to N2O, which follows the pathway shown in equation 1:NO3- → NO2- → NO → 1/2 N2O (1)
Because the bacteria Pseudomonas aureofaciens lack N2O reductive activity, the reaction stops at N2O, unlike the typical denitrification reaction that goes to N2. After several hours, the conversion is complete, and the N2O is extracted from the vial, separated from volatile organic vapor and water vapor by an automated -65 °C isopropanol-slush trap, a Nafion drier, a CO2 and water removal unit (Costech #021020 carbon dioxide absorbent with Mg(ClO4)2), and trapped in a small-volume trap immersed in liquid nitrogen with a modified Finnigan MAT (now Thermo Scientific) GasBench 2 introduction system. After the N2O is released, it is further purified by gas chromatography before introduction to the isotope-ratio mass spectrometer (IRMS). The IRMS is a Thermo Scientific Delta V Plus continuous flow IRMS (CF-IRMS). It has a universal triple collector, consisting of two wide cups with a narrow cup in the middle; it is capable of simultaneously measuring mass/charge (m/z) of the N2O molecule 44, 45, and 46. The ion beams from these m/z values are as follows: m/z = 44 = N2O = 14N14N16O; m/z = 45 = N2O = 14N15N16O or 14N14N17O; m/z = 46 = N2O = 14N14N18O. The 17O contributions to the m/z 44 and m/z 45 ion beams are accounted for before δ15N values are reported.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Chapter 17 of Section C: Stable Isotope-Ratio Methods, Book 10: Methods of the Reston Stable Isotope Laboratory","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm10C17","usgsCitation":"Coplen, T.B., Qi, H., Revesz, K., Casciotti, K., and Hannon, J.E., 2007, Determination of the δ15N and δ18O of nitrate in water; RSIL lab code 2900 (Version 1.0 - 2007, Version 1.1 - September 2012): U.S. Geological Survey Techniques and Methods 10-C17, viii, 35 p., https://doi.org/10.3133/tm10C17.","productDescription":"viii, 35 p.","numberOfPages":"45","onlineOnly":"Y","costCenters":[{"id":543,"text":"Reston Stable Isotope Laboratory","active":false,"usgs":true}],"links":[{"id":190624,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_10_C17.gif"},{"id":10052,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/2006/tm10c17/","linkFileType":{"id":5,"text":"html"}},{"id":261915,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/2006/tm10c17/pdf/tm10c17.pdf","linkFileType":{"id":1,"text":"pdf"}}],"edition":"Version 1.0 - 2007, Version 1.1 - September 2012","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4aa8e4b07f02db667646","contributors":{"authors":[{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":292040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qi, Haiping 0000-0002-8339-744X haipingq@usgs.gov","orcid":"https://orcid.org/0000-0002-8339-744X","contributorId":507,"corporation":false,"usgs":true,"family":"Qi","given":"Haiping","email":"haipingq@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":292039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Revesz, Kinga","contributorId":64285,"corporation":false,"usgs":true,"family":"Revesz","given":"Kinga","affiliations":[],"preferred":false,"id":292042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casciotti, Karen","contributorId":102153,"corporation":false,"usgs":true,"family":"Casciotti","given":"Karen","affiliations":[],"preferred":false,"id":292043,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hannon, Janet E. jehannon@usgs.gov","contributorId":3177,"corporation":false,"usgs":true,"family":"Hannon","given":"Janet","email":"jehannon@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":292041,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":80231,"text":"tm10C14 - 2007 - Determination of the δ15N and δ18O of nitrate in solids; RSIL lab code 2897","interactions":[],"lastModifiedDate":"2012-09-18T17:16:41","indexId":"tm10C14","displayToPublicDate":"2007-08-16T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"10-C14","title":"Determination of the δ15N and δ18O of nitrate in solids; RSIL lab code 2897","docAbstract":"The purpose of the Reston Stable Isotope Laboratory (RSIL) lab code 2897 is to determine the δ15N and δ18O of nitrate (NO3-) in solids. The NO3- fraction of the nitrogen species is dissolved by water (called leaching) and can be analyzed by the bacterial method covered in RSIL lab code 2900. After leaching, the δ15N and δ18O of the dissolved NO3- is analyzed by conversion of the NO3- to nitrous oxide (N2O), which serves as the analyte for mass spectrometry. A culture of denitrifying bacteria is used in the enzymatic conversion of NO3- to N2O, which follows the pathway shown in equation 1:NO3- → NO2- → NO → 1/2 N2O (1)
Because the bacteria Pseudomonas aureofaciens lack N2O reductive activity, the reaction stops at N2O, unlike the typical denitrification reaction that goes to N2. After several hours, the conversion is complete, and the N2O is extracted from the vial, separated from volatile organic vapor and water vapor by an automated -65 °C isopropanol-slush trap, a Nafion drier, a CO2 and water removal unit (Costech #021020 carbon dioxide absorbent with Mg(ClO4)2), and trapped in a small-volume trap immersed in liquid nitrogen with a modified Finnigan MAT (now Thermo Scientific) GasBench 2 introduction system. After the N2O is released, it is further purified by gas chromatography before introduction to the isotope-ratio mass spectrometer (IRMS). The IRMS is a Thermo Scientific Delta V Plus continuous flow IRMS (CF-IRMS). It has a universal triple collector, consisting of two wide cups with a narrow cup in the middle; it is capable of simultaneously measuring mass/charge (m/z) of the N2O molecule 44, 45, and 46. The ion beams from these m/z values are as follows: m/z = 44 = N2O = 14N14N16O; m/z = 45 = N2O = 14N15N16O or 14N14N17O; m/z = 46 = N2O = 14N14N18O. The 17O contributions to the m/z 44 and m/z 45 ion beams are accounted for before δ15N values are reported.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Chapter 14 of Section C: Stable Isotope-Ratio Methods, Book 10: Methods of the Reston Stable Isotope Laboratory","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm10C14","usgsCitation":"Coplen, T.B., Qi, H., Revesz, K., Casciotti, K., and Hannon, J.E., 2007, Determination of the δ15N and δ18O of nitrate in solids; RSIL lab code 2897 (Version 1.0 - 2007, Version 1.1 - September 2012): U.S. Geological Survey Techniques and Methods 10-C14, viii, 36 p., https://doi.org/10.3133/tm10C14.","productDescription":"viii, 36 p.","numberOfPages":"46","onlineOnly":"Y","costCenters":[{"id":543,"text":"Reston Stable Isotope Laboratory","active":false,"usgs":true}],"links":[{"id":194705,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_10_C14.gif"},{"id":10050,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/2006/tm10c14/","linkFileType":{"id":5,"text":"html"}},{"id":261913,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/2006/tm10c14/pdf/tm10c14.pdf","linkFileType":{"id":1,"text":"pdf"}}],"edition":"Version 1.0 - 2007, Version 1.1 - September 2012","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4aa8e4b07f02db66761a","contributors":{"authors":[{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":292030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qi, Haiping 0000-0002-8339-744X haipingq@usgs.gov","orcid":"https://orcid.org/0000-0002-8339-744X","contributorId":507,"corporation":false,"usgs":true,"family":"Qi","given":"Haiping","email":"haipingq@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":292029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Revesz, Kinga","contributorId":64285,"corporation":false,"usgs":true,"family":"Revesz","given":"Kinga","affiliations":[],"preferred":false,"id":292032,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casciotti, Karen","contributorId":102153,"corporation":false,"usgs":true,"family":"Casciotti","given":"Karen","affiliations":[],"preferred":false,"id":292033,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hannon, Janet E. jehannon@usgs.gov","contributorId":3177,"corporation":false,"usgs":true,"family":"Hannon","given":"Janet","email":"jehannon@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":292031,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":80232,"text":"tm10C12 - 2007 - Determination of the δ15N of nitrate in solids; RSIL lab code 2894","interactions":[],"lastModifiedDate":"2012-09-18T17:16:41","indexId":"tm10C12","displayToPublicDate":"2007-08-16T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"10-C12","title":"Determination of the δ15N of nitrate in solids; RSIL lab code 2894","docAbstract":"The purpose of the Reston Stable Isotope Laboratory (RSIL) lab code 2894 is to determine the δ15N of nitrate (NO3-) in solids. The nitrate fraction of the nitrogen species is dissolved by water (called leaching) and can be analyzed by the bacterial method covered in RSIL lab code 2899. After leaching, the δ15N of the dissolved NO3- is analyzed by conversion of the NO3- to nitrous oxide (N2O), which serves as the analyte for mass spectrometry. A culture of denitrifying bacteria is used in the enzymatic conversion of NO3- to N2O, which follows the pathway shown in equation 1:NO3- → NO2- → NO → 1/2 N2O (1)
Because the bacteria Pseudomonas aureofaciens lack N2O reductive activity, the reaction stops at N2O, unlike the typical denitrification reaction that goes to N2. After several hours, the conversion is complete, and the N2O is extracted from the vial, separated from volatile organic vapor and water vapor by an automated -65 °C isopropanol-slush trap, a Nafion drier, a CO2 and water removal unit (Costech #021020 carbon dioxide absorbent with Mg(ClO4)2), and trapped in a small-volume trap immersed in liquid nitrogen with a modified Finnigan MAT (now Thermo Scientific) GasBench 2 introduction system. After the N2O is released, it is further purified by gas chromatography before introduction to the isotope-ratio mass spectrometer (IRMS). The IRMS is a Thermo Scientific Delta V Plus continuous flow IRMS (CF-IRMS). It has a universal triple collector, consisting of two wide cups with a narrow cup in the middle; it is capable of simultaneously measuring mass/charge (m/z) of the N2O molecule 44, 45, and 46. The ion beams from these m/z values are as follows: m/z = 44 = N2O = 14N14N16O; m/z = 45 = N2O = 14N15N16O or 14N14N17O; m/z = 46 = N2O = 14N14N18O. The 17O contributions to the m/z 44 and m/z 45 ion beams are accounted for before δ15N values are reported.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Chapter 12 of Section C: Stable Isotope-Ratio Methods, Book 10: Methods of the Reston Stable Isotope Laboratory","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm10C12","usgsCitation":"Coplen, T.B., Qi, H., Revesz, K., Casciotti, K., and Hannon, J.E., 2007, Determination of the δ15N of nitrate in solids; RSIL lab code 2894 (Version 1.0 - 2007, Version 1.1 - September 2012): U.S. Geological Survey Techniques and Methods 10-C12, viii, 35 p., https://doi.org/10.3133/tm10C12.","productDescription":"viii, 35 p.","numberOfPages":"45","onlineOnly":"Y","costCenters":[{"id":543,"text":"Reston Stable Isotope Laboratory","active":false,"usgs":true}],"links":[{"id":192403,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_10_C12.gif"},{"id":10051,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/2006/tm10c12/","linkFileType":{"id":5,"text":"html"}},{"id":261912,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/2006/tm10c12/pdf/tm10c12.pdf","linkFileType":{"id":1,"text":"pdf"}}],"edition":"Version 1.0 - 2007, Version 1.1 - September 2012","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4aa8e4b07f02db667571","contributors":{"authors":[{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":292035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qi, Haiping 0000-0002-8339-744X haipingq@usgs.gov","orcid":"https://orcid.org/0000-0002-8339-744X","contributorId":507,"corporation":false,"usgs":true,"family":"Qi","given":"Haiping","email":"haipingq@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":292034,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Revesz, Kinga","contributorId":64285,"corporation":false,"usgs":true,"family":"Revesz","given":"Kinga","affiliations":[],"preferred":false,"id":292037,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casciotti, Karen","contributorId":102153,"corporation":false,"usgs":true,"family":"Casciotti","given":"Karen","affiliations":[],"preferred":false,"id":292038,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hannon, Janet E. jehannon@usgs.gov","contributorId":3177,"corporation":false,"usgs":true,"family":"Hannon","given":"Janet","email":"jehannon@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":292036,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":80230,"text":"ofr20071135 - 2007 - Aquatic Community, Hydrologic, and Water-Quality Data for Apopka, Bugg, Rock, and Wekiva Springs, Central Florida, 1931-2006","interactions":[],"lastModifiedDate":"2012-02-02T00:14:08","indexId":"ofr20071135","displayToPublicDate":"2007-08-16T00:00:00","publicationYear":"2007","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":"2007-1135","title":"Aquatic Community, Hydrologic, and Water-Quality Data for Apopka, Bugg, Rock, and Wekiva Springs, Central Florida, 1931-2006","docAbstract":"This report summarizes aquatic community, hydrologic, and water-quality data collected or compiled by the U.S. Geological Survey (USGS) for Apopka, Bugg, Rock, and Wekiva springs from October 1, 2005 to September 30, 2006. Aquatic community data are summarized for quarterly collections of benthic macroinvertebrates, and fishes collected during one sampling event per spring. Hydrologic data for each spring were compiled from the USGS, St. Johns River Water Management District, and a private landowner. Water-quality data collected by the USGS consisted of quarterly psysicochemical, chlorophyll-a, and pheophytin-a measurements; water-quality data were collected on the same days that the benthic macroinvertebrates were sampled.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/ofr20071135","collaboration":"Prepared in cooperation with the St. Johns River Water Management District","usgsCitation":"Walsh, S.J., and Kroening, S.E., 2007, Aquatic Community, Hydrologic, and Water-Quality Data for Apopka, Bugg, Rock, and Wekiva Springs, Central Florida, 1931-2006: U.S. Geological Survey Open-File Report 2007-1135, vi, 50 p., https://doi.org/10.3133/ofr20071135.","productDescription":"vi, 50 p.","temporalStart":"2005-10-01","temporalEnd":"2006-09-30","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":192213,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2007/1135/report-thumb.jpg"},{"id":91232,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2007/1135/report.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac5e4b07f02db67a0e4","contributors":{"authors":[{"text":"Walsh, Stephen J. 0000-0002-1009-8537 swalsh@usgs.gov","orcid":"https://orcid.org/0000-0002-1009-8537","contributorId":1456,"corporation":false,"usgs":true,"family":"Walsh","given":"Stephen","email":"swalsh@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":292027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kroening, Sharon E.","contributorId":67868,"corporation":false,"usgs":true,"family":"Kroening","given":"Sharon","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":292028,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":80223,"text":"sir20075107 - 2007 - Two-Dimensional Flood-Inundation Model of the Flint River at Albany, Georgia","interactions":[],"lastModifiedDate":"2017-01-17T09:48:16","indexId":"sir20075107","displayToPublicDate":"2007-08-14T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2007-5107","title":"Two-Dimensional Flood-Inundation Model of the Flint River at Albany, Georgia","docAbstract":"Potential flow characteristics of future flooding along a 4.8-mile reach of the Flint River in Albany, Georgia, were simulated using recent digital-elevation-model data and the U.S. Geological Survey finite-element surface-water modeling system for two-dimensional flow in the horizontal plane (FESWMS-2DH). Simulated inundated areas, in 1-foot (ft) increments, were created for water-surface altitudes at the Flint River at Albany streamgage (02352500) from 192.5-ft altitude with a flow of 123,000 cubic feet per second (ft3/s) to 179.5-ft altitude with a flow of 52,500 ft3/s. The model was calibrated to match actual floods during July 1994 and March 2005 and Federal Emergency Management Administration floodplain maps. Continuity checks of selected stream profiles indicate the area near the Oakridge Drive bridge had lower velocities than other areas of the Flint River, which contributed to a rise in the flood-surface profile. The modeled inundated areas were mapped onto monochrome orthophoto imagery for use in planning for future floods. As part of a cooperative effort, the U.S. Geological Survey, the City of Albany, and Dougherty County, Georgia, conducted this study.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/sir20075107","collaboration":"Prepared in cooperation with Albany, Georgia, and Dougherty County, Georgia","usgsCitation":"Musser, J.W., and Dyar, T.R., 2007, Two-Dimensional Flood-Inundation Model of the Flint River at Albany, Georgia: U.S. Geological Survey Scientific Investigations Report 2007-5107, vi, 44 p., https://doi.org/10.3133/sir20075107.","productDescription":"vi, 44 p.","onlineOnly":"Y","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":125735,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2007_5107.jpg"},{"id":10043,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2007/5107/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Georgia","city":"Albany","otherGeospatial":"Flint River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.18333333333334,31.533333333333335 ], [ -84.18333333333334,31.616666666666667 ], [ -84.11666666666666,31.616666666666667 ], [ -84.11666666666666,31.533333333333335 ], [ -84.18333333333334,31.533333333333335 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a2fe4b07f02db6165b3","contributors":{"authors":[{"text":"Musser, Jonathan W. 0000-0002-3543-0807 jwmusser@usgs.gov","orcid":"https://orcid.org/0000-0002-3543-0807","contributorId":2266,"corporation":false,"usgs":true,"family":"Musser","given":"Jonathan","email":"jwmusser@usgs.gov","middleInitial":"W.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":292011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dyar, Thomas R.","contributorId":61911,"corporation":false,"usgs":true,"family":"Dyar","given":"Thomas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":292012,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":80229,"text":"fs20073064 - 2007 - New Jersey Tide Telemetry System","interactions":[],"lastModifiedDate":"2012-03-08T17:16:20","indexId":"fs20073064","displayToPublicDate":"2007-08-14T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2007-3064","title":"New Jersey Tide Telemetry System","docAbstract":"Each summer the population of the barrier-island communities of New Jersey increases by tens of thousands. When a coastal storm threatens these communities, the limited number of bridges and causeways that connect the islands with the mainland become overcrowded, making evacuations from the barrier islands to the mainland difficult. Timely evacuation depends on well-defined emergency evacuation plans used in conjunction with accurate flood forecasting and up to the minute (real-time) tide-level information.\r\n\r\nThe 'Great Nor'easter' storm that struck the coastal areas of New Jersey on December 11, 1992, caused about $270 million in insured damages to public and private property (Dorr and others, 1995). Most of the damage was due to tidal flooding and storm surge, which were especially severe along the back bay areas. Comprehensive and reliable tide-level and meteorological data for the back bays was needed to make accurate flood forecasts.\r\n\r\nCollection of tidal data for the ocean and large bays was adequately covered by the National Oceanic and Atmospheric Administration's National Ocean Service (NOAA's NOS), but in New Jersey little to no data are available for the back-bay areas. The back bays behave quite differently than the ocean as a result of the complex interaction between the winds and the geometry of the inlets and bays. A slow moving Nor'easter can keep tide levels in back bays several feet higher than the ocean tide by not allowing tides to recede, resulting in flooding of bridges and causeways that link the barrier islands to the mainland.\r\n\r\nThe U.S. Geological Survey (USGS), in cooperation with the New Jersey Department of Transportation (NJDOT), designed and installed the New Jersey Tide Telemetry System (NJTTS) with assistance from NOAA's NOS in 1997. This system is part of a statewide network of tide gages, weather stations, and stream gages that collect data in real time. The NJTTS supplies comprehensive, reliable real-time tide-level and meteorological data for flood-prone areas along the New Jersey shore and back bays. These data are transmitted to computer base stations located at offices of the National Weather Service, New Jersey State Police (NJSP), NJDOT, county emergency management agencies, other critical decision-making centers, and the World Wide Web (WWW). This fact sheet describes the NJTTS and identifies its benefits.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/fs20073064","usgsCitation":"Hoppe, H.L., 2007, New Jersey Tide Telemetry System: U.S. Geological Survey Fact Sheet 2007-3064, 4 p., https://doi.org/10.3133/fs20073064.","productDescription":"4 p.","onlineOnly":"Y","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":124523,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2007_3064.jpg"},{"id":10049,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2007/3064/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -75.75,38.75 ], [ -75.75,41.5 ], [ -73.75,41.5 ], [ -73.75,38.75 ], [ -75.75,38.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afee4b07f02db697984","contributors":{"authors":[{"text":"Hoppe, Heidi L. hhoppe@usgs.gov","contributorId":1513,"corporation":false,"usgs":true,"family":"Hoppe","given":"Heidi","email":"hhoppe@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":292026,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":80226,"text":"ofr20071123 - 2007 - Magnetotelluric Data, Mid Valley, Nevada Test Site, Nevada","interactions":[],"lastModifiedDate":"2012-02-02T00:14:08","indexId":"ofr20071123","displayToPublicDate":"2007-08-14T00:00:00","publicationYear":"2007","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":"2007-1123","title":"Magnetotelluric Data, Mid Valley, Nevada Test Site, Nevada","docAbstract":"Introduction\r\n\r\nThe United States Department of Energy (DOE) and the National Nuclear Security Administration (NNSA) at their Nevada Site Office (NSO) are addressing ground-water contamination resulting from historical underground nuclear testing through the Environmental Management (EM) program and, in particular, the Underground Test Area (UGTA) project.\r\n\r\nOne issue of concern is the nature of the somewhat poorly constrained pre-Tertiary geology and its effects on ground-water flow. Ground-water modelers would like to know more about the hydrostratigraphy and geologic structure to support a hydrostratigraphic framework model that is under development for the Rainier Mesa/Shoshone Mountain Corrective Action Unit (CAU).\r\n\r\nDuring 2003, the U.S. Geological Survey (USGS), in cooperation with the DOE and NNSA-NSO, collected and processed data at the Nevada Test Site in and near Yucca Flat (YF) to help define the character, thickness, and lateral extent of the pre-Tertiary confining units. We collected 51 magnetotelluric (MT) and audio-magnetotelluric (AMT), stations for that research. In early 2005 we extended that research with 26 additional MT data stations, located on and near Rainier Mesa and Shoshone Mountain (RM-SM). The new stations extended the area of the hydrogeologic study previously conducted in Yucca Flat. This work was done to help refine what is known about the character, thickness, and lateral extent of pre-Tertiary confining units. In particular, a major goal was to define the upper clastic confining unit (UCCU). The UCCU is comprised of late Devonian to Mississippian siliciclastic rocks assigned to the Eleana Formation and Chainman Shale. The UCCU underlies the Yucca Flat area and extends westward towards Shoshone Mountain, southward to Buckboard Mesa, and northward to Rainier Mesa. Late in 2005 we collected another 14 MT stations in Mid Valley and in northern Yucca Flat basin. That work was done to better determine the extent and thickness of the UCCU near the southeastern RM-SM CAU boundary with the southwestern YF CAU, and also in the northern YF CAU. The purpose of this report is to release the MT data at those 14 stations. No interpretation of the data is included here.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/ofr20071123","collaboration":"Prepared in cooperation with the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office, Office of Environmental Management","usgsCitation":"Williams, J.M., Wallin, E.L., Rodriguez, B.D., Lindsey, C.R., and Sampson, J.A., 2007, Magnetotelluric Data, Mid Valley, Nevada Test Site, Nevada (Version 1.0): U.S. Geological Survey Open-File Report 2007-1123, 137 p., https://doi.org/10.3133/ofr20071123.","productDescription":"137 p.","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":192484,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":10046,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2007/1123/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a80e4b07f02db6493cf","contributors":{"authors":[{"text":"Williams, Jackie M.","contributorId":11217,"corporation":false,"usgs":true,"family":"Williams","given":"Jackie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":292019,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wallin, Erin L.","contributorId":70066,"corporation":false,"usgs":true,"family":"Wallin","given":"Erin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":292021,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodriguez, Brian D. 0000-0002-2263-611X brod@usgs.gov","orcid":"https://orcid.org/0000-0002-2263-611X","contributorId":836,"corporation":false,"usgs":true,"family":"Rodriguez","given":"Brian","email":"brod@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":292018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindsey, Charles R.","contributorId":102963,"corporation":false,"usgs":true,"family":"Lindsey","given":"Charles","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":292022,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sampson, Jay A.","contributorId":13939,"corporation":false,"usgs":true,"family":"Sampson","given":"Jay","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":292020,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":80225,"text":"ofr20071237 - 2007 - Field Reconnaissance of Debris Flows Triggered by a July 21, 2007, Thunderstorm in Alpine, Colorado, and Vicinity","interactions":[],"lastModifiedDate":"2012-02-02T00:14:11","indexId":"ofr20071237","displayToPublicDate":"2007-08-14T00:00:00","publicationYear":"2007","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":"2007-1237","title":"Field Reconnaissance of Debris Flows Triggered by a July 21, 2007, Thunderstorm in Alpine, Colorado, and Vicinity","docAbstract":"On the evening of July 21, 2007, a slow-moving thunderstorm triggered about 45 debris flows on steep mountainsides near the community of Alpine, Colorado. Most of the debris flows were initiated by surface-water runoff that eroded and entrained loose sediment in previously existing channels. About 12 of the debris-flow channels were located in the lower half of Weldon Gulch upslope from Alpine, which is on a debris fan at the mouth of the Gulch. Most of these channels were deeply incised by the flows, and many of the resulting oversteepened channel banks are now failing and beginning to refill the channels with sediment. Debris flows that emerged from the mouth of Weldon Gulch primarily flowed onto the eastern half of the debris fan and closed roads and damaged vehicles and structures. Debris-flow deposits on the fan generally become finer grained and thinner with distance from the head of the fan. Given the existing conditions in Weldon Gulch, it is estimated that the debris-flow hazard on the fan has neither decreased nor increased as a result of the July 21 debris flows. Preventive measures that need to be considered by Alpine residents and government officials concerned with safety on the fan include: (1) establishing a channel and(or) catchment/diversion structure on the fan that routes future water and debris flows in a manner that protects existing roads and structures, and (2) maintaining vigilance during rainstorms by watching and listening for unusual flows of water or debris that may indicate debris-flow activity upstream, particularly during the summer months when thunderstorms are common in the area.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/ofr20071237","usgsCitation":"Coe, J.A., Godt, J.W., Wait, T., and Kean, J.W., 2007, Field Reconnaissance of Debris Flows Triggered by a July 21, 2007, Thunderstorm in Alpine, Colorado, and Vicinity (Version 1.0): U.S. Geological Survey Open-File Report 2007-1237, iii, 25 p., https://doi.org/10.3133/ofr20071237.","productDescription":"iii, 25 p.","onlineOnly":"Y","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":191984,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":10045,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2007/1237/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49fce4b07f02db5f5b67","contributors":{"authors":[{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":292015,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Godt, Jonathan W. 0000-0002-8737-2493 jgodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8737-2493","contributorId":1166,"corporation":false,"usgs":true,"family":"Godt","given":"Jonathan","email":"jgodt@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":292014,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wait, T.C.","contributorId":10883,"corporation":false,"usgs":true,"family":"Wait","given":"T.C.","email":"","affiliations":[],"preferred":false,"id":292017,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":292016,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":80222,"text":"sir20075105 - 2007 - Water Resources of the Duck River Watershed, Tennessee","interactions":[],"lastModifiedDate":"2012-02-10T00:11:41","indexId":"sir20075105","displayToPublicDate":"2007-08-14T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2007-5105","title":"Water Resources of the Duck River Watershed, Tennessee","docAbstract":"The U.S. Geological Survey began a study in 2003 in cooperation with the Tennessee Duck River Development Agency to assess the hydrology of the Duck River watershed from Normandy Dam downstream to Columbia, Tennessee. Ground-water-level data, spring-flow, bacteria samples, and streamflow were collected during this study to characterize the hydrology of the study area. The emphasis of this study was to characterize the temporal and spatial variability of the various components that make up streamflow in the Duck River in this study area.\r\n\r\nWater-level data from wells in the study area indicate a good hydraulic connection between the aquifer and the river, with little long-term storage of water following recharge events. Variations in spring flow and ground-water temperature at springs indicate that a large component of water issuing from springs has a short residence time in the aquifer for most of the springs monitored in the study area. Escherichia coli densities in samples collected from springs are similar to concentrations in samples from tributaries and the Duck River.\r\n\r\nBase-flow synoptic discharge measurements, flow-duration analysis of tributary streams, and streamflow accounting analysis indicate the portion of the watershed between Pottsville and Columbia yields more water than the portion between Shelbyville and Pottsville. Base-flow synoptic measurements show that Fountain Creek yields more water than other tributary basins in the study area, whereas base-flow synoptic measurements on the mainstem indicate that streamflow in the Duck River between Pottsville and Columbia could vary by 10 percent as the result of gaining and losing reaches. These results are applicable for average flow conditions that occurred during the study. Flow-duration analysis indicates that tributaries in this part of the watershed have a large component of ground-water contributing base flow. Streamflow accounting analysis for two periods of extended recession was used to determine the contributions of flow releases from Normandy Dam, tributaries, wastewater discharges, and ground-water discharge. The analysis indicated this same section of the mainstem of the Duck River between Pottsville and Columbia had as much as four times more ground-water discharge as sections upstream from Pottsville.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/sir20075105","collaboration":"Prepared in cooperation with the Tennessee Duck River Development Agency","usgsCitation":"Knight, R., and Kingsbury, J., 2007, Water Resources of the Duck River Watershed, Tennessee: U.S. Geological Survey Scientific Investigations Report 2007-5105, vi, 46 p., https://doi.org/10.3133/sir20075105.","productDescription":"vi, 46 p.","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":121046,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2007_5105.jpg"},{"id":10042,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2007/5105/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.83333333333333,35.333333333333336 ], [ -87.83333333333333,36.166666666666664 ], [ -85.91666666666667,36.166666666666664 ], [ -85.91666666666667,35.333333333333336 ], [ -87.83333333333333,35.333333333333336 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ae1e4b07f02db68884e","contributors":{"authors":[{"text":"Knight, R.R.","contributorId":59063,"corporation":false,"usgs":true,"family":"Knight","given":"R.R.","email":"","affiliations":[],"preferred":false,"id":292010,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kingsbury, J.A.","contributorId":21583,"corporation":false,"usgs":true,"family":"Kingsbury","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":292009,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":80220,"text":"sir20075086 - 2007 - Evaluation of Ground Water Near Sidney, Western Nebraska, 2004-05","interactions":[],"lastModifiedDate":"2024-09-19T17:28:39.161808","indexId":"sir20075086","displayToPublicDate":"2007-08-14T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2007-5086","title":"Evaluation of Ground Water Near Sidney, Western Nebraska, 2004-05","docAbstract":"During times of drought, ground water in the Lodgepole Creek area around Sidney, western Nebraska, may be insufficient to yield adequate supplies to private and municipal wells. Alternate sources of water exist in the Cheyenne Tablelands north of the city, but these sources are limited in extent. In 2003, the U.S. Geological Survey and the South Platte Natural Resources District began a cooperative study to evaluate the ground water near Sidney.
The 122-square-mile study area lies in the south-central part of Cheyenne County. with Lodgepole Creek and Sidney Draw occupying the southern and western parts of the study area and the Cheyenne Tablelands occupying most of the northern part of the study area. Twenty-nine monitoring wells were installed and then sampled in 2004 and 2005 for physical characteristics, nutrients, major ions, and stable isotopes. Some of the 29 sites also were sampled for ground-water age dating.
Ground water is limited in extent in the tableland areas. Spring 2005 depths to ground water in the tableland areas ranged from 95 to 188 feet. Ground-water flow in the tableland areas primarily is northeasterly. South of a ground-water divide, ground-water flows southeasterly toward Lodgepole Creek Valley.
Water samples from monitoring wells in the Ogallala Group were predominantly a calcium bicarbonate type, and those from monitoring wells in the Brule Formation were a sodium bicarbonate type. Water samples from monitoring wells open to the Brule sand were primarily a calcium bicarbonate type at shallow depths and a sodium bicarbonate type at deeper depths. Ground water in Lodgepole Creek Valley had a strong sodium signature, which likely results from most of the wells being open to the Brule. Concentrations of sodium and nitrate in ground-water samples from the Ogallala were significantly different than in water samples from the Brule and Brule sand. In addition, significant differences were seen in concentrations of calcium between water samples from the Ogallala and the Brule sand. Median concentrations of nitrate varied by aquifer-2.6 milligrams per liter (Ogallala). 2.1 milligrams per liter (Brute), and 1.3 milligrams per liter (Brule sand).
The chemistry of the ground water in the study area indicates that ground water flows from recharge areas in both the tableland areas and Lodgepole Creek Valley to discharge areas beyond the study area. Recharging water that percolates into the Ogallala in the tableland areas either enters the Ogallala aquifer. flows along the Ogallala-Brule contact, or enters Brule fractures or sand. Although limited in amount, ground water flowing along the Ogallala-Brule contact or in the Brule fractures or sand appears to be the predominant means by which water moves from the tableland areas to Lodgepole Creek Valley.
Apparent ground-water ages from chlorofluorocarbon and sulfur hexafluoride data generally were similar. Age of ground water for most monitoring wells located in Lodgepole Creek Valley ranged from the mid- to late 1960s to the early 1990s. Ages of ground water in samples from monitoring wells located in tableland draw areas ranged from the mid-1980s to the early 1990s. Water in the Brule (areas without known secondary permeability structures) or deeper Brule sand aquifer was substantially older than water in the Ogallala aquifer and probably was recharged between 10,000 to 30,000 years before present.
The stable isotopic data indicate that the ground water in the study area probably originated from precipitation. Ground water in Lodgepole Creek and the tableland areas are similar in chemistry. However, there appears to be limited interaction between ground water within the Ogallala to the north of Sidney and Lodgepole Creek Valley. Available data indicate that although some of the ground water in the Ogallala likely flows across the Ogallala-Brule contact, most of it does not move toward Lodgepole Creek.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20075086","collaboration":"Prepared in cooperation with the South Platte Natural Resources District","usgsCitation":"Steele, G.V., Sibray, S., and Quandt, K., 2007, Evaluation of Ground Water Near Sidney, Western Nebraska, 2004-05: U.S. Geological Survey Scientific Investigations Report 2007-5086, vi, 54 p., https://doi.org/10.3133/sir20075086.","productDescription":"vi, 54 p.","temporalStart":"2004-01-01","temporalEnd":"2005-12-31","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":422042,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2007/5086/sir20075086.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2007-5086"},{"id":10040,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2007/5086/","linkFileType":{"id":5,"text":"html"}},{"id":190681,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2007/5086/coverthb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -105,40 ], [ -105,42.5 ], [ -102,42.5 ], [ -102,40 ], [ -105,40 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a09e4b07f02db5fafe1","contributors":{"authors":[{"text":"Steele, G. V.","contributorId":62543,"corporation":false,"usgs":true,"family":"Steele","given":"G.","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":292004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sibray, S. S.","contributorId":63048,"corporation":false,"usgs":true,"family":"Sibray","given":"S. S.","affiliations":[],"preferred":false,"id":292005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quandt, K.A.","contributorId":7781,"corporation":false,"usgs":true,"family":"Quandt","given":"K.A.","email":"","affiliations":[],"preferred":false,"id":292003,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":80224,"text":"sir20075111 - 2007 - A graphical method for estimation of barometric efficiency from continuous data: Concepts and application to a site in the Piedmont, Air Force Plant 6, Marietta, Georgia","interactions":[],"lastModifiedDate":"2024-06-13T21:07:49.656235","indexId":"sir20075111","displayToPublicDate":"2007-08-14T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2007-5111","title":"A graphical method for estimation of barometric efficiency from continuous data: Concepts and application to a site in the Piedmont, Air Force Plant 6, Marietta, Georgia","docAbstract":"A graphical method that uses continuous water-level and barometric-pressure data was developed to estimate barometric efficiency. A plot of nearly continuous water level (on the y-axis), as a function of nearly continuous barometric pressure (on the x-axis), will plot as a line curved into a series of connected elliptical loops. Each loop represents a barometric-pressure fluctuation. The negative of the slope of the major axis of an elliptical loop will be the ratio of water-level change to barometric-pressure change, which is the sum of the barometric efficiency plus the error.\r\n\r\nThe negative of the slope of the preferred orientation of many elliptical loops is an estimate of the barometric efficiency. The slope of the preferred orientation of many elliptical loops is approximately the median of the slopes of the major axes of the elliptical loops. If water-level change that is not caused by barometric-pressure change does not correlate with barometric-pressure change, the probability that the error will be greater than zero will be the same as the probability that it will be less than zero. As a result, the negative of the median of the slopes for many loops will be close to the barometric efficiency.\r\n\r\nThe graphical method provided a rapid assessment of whether a well was affected by barometric-pressure change and also provided a rapid estimate of barometric efficiency. The graphical method was used to assess which wells at Air Force Plant 6, Marietta, Georgia, had water levels affected by barometric-pressure changes during a 2003 constant-discharge aquifer test. The graphical method was also used to estimate barometric efficiency. Barometric-efficiency estimates from the graphical method were compared to those of four other methods: average of ratios, median of ratios, Clark, and slope. The two methods (the graphical and median-of-ratios methods) that used the median values of water-level change divided by barometric-pressure change appeared to be most resistant to error caused by barometric-pressure-independent water-level change. The graphical method was particularly resistant to large amounts of barometric-pressure-independent water-level change, having an average and standard deviation of error for control wells that was less than one-quarter that of the other four methods.\r\n\r\nWhen using the graphical method, it is advisable that more than one person select the slope or that the same person fits the same data several times to minimize the effect of subjectivity. Also, a long study period should be used (at least 60 days) to ensure that loops affected by large amounts of barometric-pressure-independent water-level change do not significantly contribute to error in the barometric-efficiency estimate.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20075111","collaboration":"Prepared in cooperation with the U.S. Air Force Aeronautical Systems Center, Marietta, Georgia","usgsCitation":"Gonthier, G., 2007, A graphical method for estimation of barometric efficiency from continuous data: Concepts and application to a site in the Piedmont, Air Force Plant 6, Marietta, Georgia: U.S. Geological Survey Scientific Investigations Report 2007-5111, vi, 30 p., https://doi.org/10.3133/sir20075111.","productDescription":"vi, 30 p.","onlineOnly":"Y","costCenters":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"links":[{"id":10044,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2007/5111/","linkFileType":{"id":5,"text":"html"}},{"id":192956,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":430165,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_81596.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Georgia","city":"Marietta","otherGeospatial":"Air Force Plant 6","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.52712478082185,\n 33.93500578580522\n ],\n [\n -84.52712478082185,\n 33.93080834768527\n ],\n [\n -84.52177388072325,\n 33.93080834768527\n ],\n [\n -84.52177388072325,\n 33.93500578580522\n ],\n [\n -84.52712478082185,\n 33.93500578580522\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4957e4b0b290850ef12f","contributors":{"authors":[{"text":"Gonthier, Gerard 0000-0003-4078-8579 gonthier@usgs.gov","orcid":"https://orcid.org/0000-0003-4078-8579","contributorId":3141,"corporation":false,"usgs":true,"family":"Gonthier","given":"Gerard ","email":"gonthier@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":292013,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}