Groundwater quality in the 633-square-mile (1,639-square-kilometer) Northern Coast Ranges (NOCO) study unit was investigated as part of the Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) Program and the U.S. Geological Survey (USGS) National Water-Quality Assessment Program. The study unit is composed of two study areas (Interior Basins and Coastal Basins) and is located in northern California in Napa, Sonoma, Lake, Colusa, Mendocino, Glenn, Humboldt, and Del Norte Counties. The GAMA-PBP is being conducted by the California State Water Resources Control Board in collaboration with the USGS and the Lawrence Livermore National Laboratory.
\nThe GAMA NOCO study was designed to provide a spatially unbiased assessment of the quality of untreated (ambient) groundwater in the primary aquifer system within the study unit. The assessment is based on water-quality and ancillary data collected in 2009 by the USGS from 58 sites and on water-quality data from the California Department of Public Health (CDPH) database. The primary aquifer system is defined by the perforation intervals of sites listed in the CDPH water-quality database for the NOCO study unit. Groundwater quality in the primary aquifer system may differ from the quality in the shallow or deep water-bearing zones.
\nThe first component of this study, the status assessment of the current quality of the groundwater resource, was performed by using data from samples analyzed for inorganic constituents (such as trace elements and major and minor ions), organic constituents (volatile organic compounds and pesticides and pesticide degradates), the special-interest constituent perchlorate, and microbial indicators. This status assessment is intended to characterize the quality of groundwater resources in the primary aquifer system of the NOCO study unit, not the quality of treated drinking water delivered to consumers by water purveyors.
\nRelative-concentrations (sample concentration divided by the health- or aesthetic-based benchmark concentration) were used for evaluating groundwater quality for those constituents that have Federal or California regulatory or nonregulatory benchmarks for drinking-water quality. A relative-concentration greater than (>) 1.0 indicates a concentration greater than a benchmark, and a relative-concentration less than or equal to (≤) 1.0 indicates a concentration less than or equal to a benchmark. Relative-concentrations of organic constituents and perchlorate were classified as “high” (relative-concentration >1.0), “moderate” (0.1 < relative-concentration ≤1.0), or “low” (relative-concentration ≤0.1). Relative-concentrations of inorganic constituents were classified as “high” (relative-concentration >1.0), “moderate” (0.5 < relative-concentration ≤1.0), or “low” (relative-concentration ≤0.5).
\nAquifer-scale proportion was used as the primary metric in the status assessment for evaluating regional-scale groundwater quality. High aquifer-scale proportion was defined as the percentage of the area of the primary aquifer system with a relative-concentration >1.0 for a particular constituent or class of constituents; the percentage is based on an aerial rather than a volumetric basis. Moderate and low aquifer-scale proportions were defined as the percentage of the primary aquifer system with moderate and low relative-concentrations, respectively. Two statistical approaches—grid-based and spatially weighted—were used to evaluate aquifer-scale proportions for individual constituents and classes of constituents. Grid-based and spatially weighted estimates were comparable in the NOCO study unit (within 90 percent confidence intervals).
\nInorganic constituents (one or more) with health-based benchmarks were detected at high relative-concentrations in 10.3 percent and at moderate relative-concentrations in 13.8 percent of the primary aquifer system. The high aquifer-scale proportion of inorganic constituents primarily reflected high aquifer-scale proportions of boron (in 8.6 percent of the primary aquifer system), arsenic (in 3.4 percent), and barium (in 1.7 percent). Inorganic constituents with aesthetic-based benchmarks were detected at high relative-concentrations in 39.7 percent and at moderate relative-concentrations in 10.3 percent of the primary aquifer system. The constituents present at high relative-concentrations were iron (25.9 percent) and manganese (39.7 percent).
\nRelative-concentrations of organic constituents with health-based benchmarks (one or more) were high in 0.2 percent, moderate in 1.7 percent, and low in 39.7 percent of the primary aquifer system. Organic constituents were not detected in 58.4 percent of the primary aquifer system. Of the 168 organic constituents analyzed, 11 constituents were detected. Two organic constituents had detection frequencies >10 percent: the trihalomethane chloroform and the herbicide simazine. For the 10 detected organic constituents that had health-based benchmarks, nearly all detections had low relative-concentrations. The special-interest constituent perchlorate was detected at moderate relative-concentrations in 1.7 percent and at low relative-concentrations in 22.4 percent of the primary aquifer system. Perchlorate was not detected in 75.9 percent of the primary aquifer system.
\nThe second component of this study, the understanding assessment, evaluated relations between constituent concentrations and values of selected potential explanatory factors to identify the factors potentially affecting the concentrations and occurrences of constituents found at high relative-concentrations or, for organic constituents, with detection frequencies >10 percent. The potential explanatory factors evaluated were land use (including density of septic tanks and leaking or formerly leaking underground fuel tanks), well construction (well depth and depth to the top of the perforated interval in the well), hydrologic conditions (aridity index, field water temperature, and distance to nearest hot spring and geothermal well), pH, dissolved oxygen concentration, study area, groundwater age distribution, and geochemical conditions.
\nHigh and moderate relative-concentrations of boron primarily occurred in the Interior Basins study area and may be attributed to groundwater interacting with hydrothermal systems. High and moderate relative-concentrations of boron were associated with elevated groundwater temperatures, groundwater chemistry characteristics similar to those of geothermal waters, and distance to known geothermal areas. Boron concentrations generally were higher where low dissolved oxygen concentrations or anoxic conditions exist. High and moderate relative-concentrations of arsenic predominantly occur in the Interior Basins study area under reducing conditions. Arsenic concentrations also may be influenced by hydrothermal systems (when present).
\nChloroform, simazine, and perchlorate were observed in the Interior Basins and Coastal Basins study areas, predominantly at shallow sites with top-of-perforation depths ≤70 feet below land surface, with modern water (post-1950s), and with oxic groundwater conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145215","collaboration":"Prepared in cooperation with the California State Water Resources Control Board and the U.S. Geological Survey National Water-Quality Assessment Program","usgsCitation":"Mathany, T.M., and Belitz, K., 2015, Status and understanding of groundwater quality in the Northern Coast Ranges study unit, 2009: California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2014-5215, x, 86 p., https://doi.org/10.3133/sir20145215.","productDescription":"x, 86 p.","numberOfPages":"100","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2009-01-01","temporalEnd":"2009-12-31","ipdsId":"IP-030141","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":298170,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145215.jpg"},{"id":298169,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5215/pdf/sir2014-5215.pdf","text":"Report","size":"13.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298148,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5215/"}],"country":"United States","state":"California","county":"Colusa County, Del Norte County, Glenn County, Humboldt County, Lake County, Mendocino County, Napa County, Sonoma County","otherGeospatial":"Northern Coast Ranges","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.541015625,\n 38.66835610151509\n ],\n [\n -124.541015625,\n 41.96765920367816\n ],\n [\n -121.79443359375,\n 41.96765920367816\n ],\n [\n -121.79443359375,\n 38.66835610151509\n ],\n [\n -124.541015625,\n 38.66835610151509\n ]\n ]\n ]\n }\n }\n ]\n}","publicComments":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f043afe4b02419550ce86c","contributors":{"authors":[{"text":"Mathany, Timothy M. 0000-0002-4747-5113 tmathany@usgs.gov","orcid":"https://orcid.org/0000-0002-4747-5113","contributorId":1713,"corporation":false,"usgs":true,"family":"Mathany","given":"Timothy","email":"tmathany@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":false,"id":541550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":541551,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70116921,"text":"ofr20141109 - 2015 - GRIDGEN Version 1.0: a computer program for generating unstructured finite-volume grids","interactions":[],"lastModifiedDate":"2015-02-26T10:52:37","indexId":"ofr20141109","displayToPublicDate":"2015-02-26T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1109","title":"GRIDGEN Version 1.0: a computer program for generating unstructured finite-volume grids","docAbstract":"GRIDGEN is a computer program for creating layered quadtree grids for use with numerical models, such as the MODFLOW–USG program for simulation of groundwater flow. The program begins by reading a three-dimensional base grid, which can have variable row and column widths and spatially variable cell top and bottom elevations. From this base grid, GRIDGEN will continuously divide into four any cell intersecting user-provided refinement features (points, lines, and polygons) until the desired level of refinement is reached. GRIDGEN will then smooth, or balance, the grid so that no two adjacent cells, including overlying and underlying cells, differ by more than a user-specified level tolerance. Once these gridding processes are completed, GRIDGEN saves a tree structure file so that the layered quadtree grid can be quickly reconstructed as needed. Once a tree structure file has been created, GRIDGEN can then be used to (1) export the layered quadtree grid as a shapefile, (2) export grid connectivity and cell information as ASCII text files for use with MODFLOW–USG or other numerical models, and (3) intersect the grid with shapefiles of points, lines, or polygons, and save intersection output as ASCII text files and shapefiles. The GRIDGEN program is demonstrated by creating a layered quadtree grid for the Biscayne aquifer in Miami-Dade County, Florida, using hydrologic features to control where refinement is added.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141109","collaboration":"Prepared in cooperation with George Mason University","usgsCitation":"Lien, J., Liu, G., and Langevin, C.D., 2015, GRIDGEN Version 1.0: a computer program for generating unstructured finite-volume grids: U.S. Geological Survey Open-File Report 2014-1109, vi, 26 p., https://doi.org/10.3133/ofr20141109.","productDescription":"vi, 26 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055584","costCenters":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"links":[{"id":298168,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141109.jpg"},{"id":298166,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1109/"},{"id":298167,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1109/pdf/ofr2014-1109.pdf","text":"Report","size":"1.93 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f043aae4b02419550ce862","contributors":{"authors":[{"text":"Lien, Jyh-Ming","contributorId":139494,"corporation":false,"usgs":true,"family":"Lien","given":"Jyh-Ming","email":"","affiliations":[],"preferred":false,"id":541557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Gaisheng","contributorId":15158,"corporation":false,"usgs":true,"family":"Liu","given":"Gaisheng","email":"","affiliations":[],"preferred":false,"id":541558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langevin, Christian D. 0000-0001-5610-9759 langevin@usgs.gov","orcid":"https://orcid.org/0000-0001-5610-9759","contributorId":1030,"corporation":false,"usgs":true,"family":"Langevin","given":"Christian","email":"langevin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":519055,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70155505,"text":"70155505 - 2015 - A comparison of hydrologic models for ecological flows and water availability","interactions":[],"lastModifiedDate":"2015-12-07T10:24:59","indexId":"70155505","displayToPublicDate":"2015-02-23T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of hydrologic models for ecological flows and water availability","docAbstract":"Robust hydrologic models are needed to help manage water resources for healthy aquatic ecosystems and reliable water supplies for people, but there is a lack of comprehensive model comparison studies that quantify differences in streamflow predictions among model applications developed to answer management questions. We assessed differences in daily streamflow predictions by four fine-scale models and two regional-scale monthly time step models by comparing model fit statistics and bias in ecologically relevant flow statistics (ERFSs) at five sites in the Southeastern USA. Models were calibrated to different extents, including uncalibrated (level A), calibrated to a downstream site (level B), calibrated specifically for the site (level C) and calibrated for the site with adjusted precipitation and temperature inputs (level D). All models generally captured the magnitude and variability of observed streamflows at the five study sites, and increasing level of model calibration generally improved performance. All models had at least 1 of 14 ERFSs falling outside a +/−30% range of hydrologic uncertainty at every site, and ERFSs related to low flows were frequently over-predicted. Our results do not indicate that any specific hydrologic model is superior to the others evaluated at all sites and for all measures of model performance. Instead, we provide evidence that (1) model performance is as likely to be related to calibration strategy as it is to model structure and (2) simple, regional-scale models have comparable performance to the more complex, fine-scale models at a monthly time step.
","language":"English","publisher":"John Wiley & Sons","publisherLocation":"Chichester, West Sussex, UK","doi":"10.1002/eco.1602","usgsCitation":"Caldwell, P.V., Kennen, J., Sun, G., Kiang, J.E., Butcher, J.B., Eddy, M.C., Hay, L.E., LaFontaine, J.H., Hain, E.F., Nelson, S.C., and McNulty, S., 2015, A comparison of hydrologic models for ecological flows and water availability: Ecohydrology, v. 8, no. 8, p. 1525-1546, https://doi.org/10.1002/eco.1602.","productDescription":"22 p.","startPage":"1525","endPage":"1546","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062207","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":306514,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"8","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-23","publicationStatus":"PW","scienceBaseUri":"55c9cb2ee4b08400b1fdb6e1","contributors":{"authors":[{"text":"Caldwell, Peter V","contributorId":145892,"corporation":false,"usgs":false,"family":"Caldwell","given":"Peter","email":"","middleInitial":"V","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":565591,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":565590,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sun, Ge","contributorId":145893,"corporation":false,"usgs":false,"family":"Sun","given":"Ge","email":"","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":565592,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kiang, Julie E. 0000-0003-0653-4225 jkiang@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-4225","contributorId":2179,"corporation":false,"usgs":true,"family":"Kiang","given":"Julie","email":"jkiang@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":565593,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Butcher, John B","contributorId":145894,"corporation":false,"usgs":false,"family":"Butcher","given":"John","email":"","middleInitial":"B","affiliations":[{"id":16286,"text":"Tetra Tech","active":true,"usgs":false}],"preferred":false,"id":565594,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eddy, Michelle C","contributorId":145895,"corporation":false,"usgs":false,"family":"Eddy","given":"Michelle","email":"","middleInitial":"C","affiliations":[{"id":7151,"text":"RTI International","active":true,"usgs":false}],"preferred":false,"id":565595,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":565596,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"LaFontaine, Jacob H. 0000-0003-4923-2630 jlafonta@usgs.gov","orcid":"https://orcid.org/0000-0003-4923-2630","contributorId":2258,"corporation":false,"usgs":true,"family":"LaFontaine","given":"Jacob","email":"jlafonta@usgs.gov","middleInitial":"H.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":565597,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hain, Ernie F.","contributorId":141247,"corporation":false,"usgs":false,"family":"Hain","given":"Ernie","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":565598,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nelson, Stacy C","contributorId":145896,"corporation":false,"usgs":false,"family":"Nelson","given":"Stacy","email":"","middleInitial":"C","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":565599,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McNulty, Steve G","contributorId":145897,"corporation":false,"usgs":false,"family":"McNulty","given":"Steve G","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":567588,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70177028,"text":"70177028 - 2015 - Metal Mixture Modeling Evaluation project: 2. Comparison of four modeling approaches","interactions":[],"lastModifiedDate":"2016-10-19T15:22:25","indexId":"70177028","displayToPublicDate":"2015-02-20T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Metal Mixture Modeling Evaluation project: 2. Comparison of four modeling approaches","docAbstract":"As part of the Metal Mixture Modeling Evaluation (MMME) project, models were developed by the National Institute of Advanced Industrial Science and Technology (Japan), the U.S. Geological Survey (USA), HDR⎪HydroQual, Inc. (USA), and the Centre for Ecology and Hydrology (UK) to address the effects of metal mixtures on biological responses of aquatic organisms. A comparison of the 4 models, as they were presented at the MMME Workshop in Brussels, Belgium (May 2012), is provided herein. Overall, the models were found to be similar in structure (free ion activities computed by WHAM; specific or non-specific binding of metals/cations in or on the organism; specification of metal potency factors and/or toxicity response functions to relate metal accumulation to biological response). Major differences in modeling approaches are attributed to various modeling assumptions (e.g., single versus multiple types of binding site on the organism) and specific calibration strategies that affected the selection of model parameters. The models provided a reasonable description of additive (or nearly additive) toxicity for a number of individual toxicity test results. Less-than-additive toxicity was more difficult to describe with the available models. 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With these comprehensive environmental inputs and experienced scientific analysis, the BCM provides resource managers with important hydrologic and ecologic understanding of a landscape or basin at hillslope to regional scales. The model is calibrated using historical climate and streamflow data over the range of geologic materials specific to an area. Once calibrated, the model is used to translate climate-change data into hydrologic responses for a defined landscape, to provide managers an understanding of potential ecological risks and threats to water supplies and managed hydrologic systems. Although limited to estimates of unimpaired hydrologic conditions, estimates of impaired conditions, such as agricultural demand, diversions, or reservoir outflows can be incorporated into the calibration of the model to expand its utility. Additionally, the model can be linked to other models, such as groundwater-flow models (that is, MODFLOW) or the integrated hydrologic model (MF-FMP), to provide information about subsurface hydrologic processes. The model can be applied at a relatively small scale, but also can be applied to large-scale national and international river basins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143098","usgsCitation":"Flint, L.E., Flint, A.L., and Thorne, J.H., 2015, Climate change: evaluating your local and regional water resources: U.S. Geological Survey Fact Sheet 2014-3098, 6 p., https://doi.org/10.3133/fs20143098.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-045835","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":297878,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143098.JPG"},{"id":297877,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3098/pdf/fs2014-3098.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297875,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3098/"}],"publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a5ee4b08de9379b301c","contributors":{"authors":[{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540209,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thorne, James H.","contributorId":139144,"corporation":false,"usgs":false,"family":"Thorne","given":"James","email":"","middleInitial":"H.","affiliations":[{"id":12659,"text":"U C Davis","active":true,"usgs":false}],"preferred":false,"id":540210,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70134473,"text":"sir20145220 - 2015 - Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961-2010","interactions":[],"lastModifiedDate":"2015-02-06T12:59:44","indexId":"sir20145220","displayToPublicDate":"2015-02-06T13:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5220","title":"Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961-2010","docAbstract":"The lakes, rivers, and streams of New York State provide an essential water resource for the State. The information provided by time series hydrologic data is essential to understanding ways to promote healthy instream ecology and to strengthen the scientific basis for sound water management decision making in New York. The U.S. Geological Survey, in cooperation with The Nature Conservancy and the New York State Energy Research and Development Authority, has developed the New York Streamflow Estimation Tool to estimate a daily mean hydrograph for the period from October 1, 1960, to September 30, 2010, at ungaged locations across the State. The New York Streamflow Estimation Tool produces a complete estimated daily mean time series from which daily flow statistics can be estimated. In addition, the New York Streamflow Estimation Tool provides a means for quantitative flow assessments at ungaged locations that can be used to address the objectives of the Clean Water Act—to restore and maintain the chemical, physical, and biological integrity of the Nation’s waters.
\nThe New York Streamflow Estimation Tool uses data from the U.S. Geological Survey streamflow network for selected streamgages in New York (excluding Long Island) and surrounding States with shared hydrologic boundaries, and physical and climate basin characteristics to estimate the natural unaltered streamflow at ungaged stream locations. The unaltered streamflow is representative of flows that are minimally altered by regulation, diversion, or mining, and other anthropogenic activities. With the streamflow network data, flow-duration exceedance probability equations were developed to estimate unaltered streamflow exceedance probabilities at an ungaged location using a methodology that equates streamflow as a percentile from a flow-duration curve for a particular day at a hydrologically similar reference streamgage with streamflow as a percentile from the flow-duration curve for the same day at an ungaged location. The reference streamgage is selected using map correlation, a geostatistical method in which variogram models are developed that correlate streamflow at one streamgage with streamflows at all other locations in the study area. Regression equations used to predict 17 flow-duration exceedance probabilities were developed to estimate the flow-duration curves at ungaged locations for New York using geographic information system-derived basin characteristics.
\nA graphical user interface, with an integrated spreadsheet summary report, has been developed to estimate and display the daily mean streamflows and statistics and to evaluate different water management or water withdrawal scenarios with the estimated monthly data. This package of regression equations, U.S. Geological Survey streamgage data, and spreadsheet application produces an interactive tool to estimate an unaltered daily streamflow hydrograph and streamflow statistics at ungaged sites in New York. Among other uses, the New York Streamflow Estimation Tool can assist water managers with permitting water withdrawals, implementing habitat protection, estimating contaminant loads, or determining the potential affect from chemical spills.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145220","collaboration":"Prepared in cooperation with The Nature Conservancy and the New York State Energy Research and Development Authority","usgsCitation":"Gazoorian, C.L., 2015, Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961-2010: U.S. Geological Survey Scientific Investigations Report 2014-5220, Report: viii, 29 p.; Readme; 5 Appendixes; NYSET application, https://doi.org/10.3133/sir20145220.","productDescription":"Report: viii, 29 p.; Readme; 5 Appendixes; NYSET application","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1960-10-01","temporalEnd":"2010-09-30","ipdsId":"IP-055442","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":297799,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145220.jpg"},{"id":297792,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5220/"},{"id":297793,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5220/pdf/sir2014-5220.pdf"},{"id":297794,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/sir2014-5220_readme.pdf","text":"Readme Appendix 1-5","size":"58 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":297795,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/sir2014-5220_app1-4.pdf","text":"Appendix 1-4 PDF","size":"308 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":297796,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/sir2014-5220_app1-4.xlsx","text":"Appendix 1-4 XLS","size":"75 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297797,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/SIR2014-5220_app5.pdf","text":"Appendix 5","size":"696 kB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"User’s Guide for the New York Streamflow Estimation Tool (NYSET) version 1.0"},{"id":297798,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://ny.water.usgs.gov/projects/nyset/","text":"NYSET application","linkFileType":{"id":5,"text":"html"}}],"scale":"200000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"New York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.771728515625,\n 42.27730877423709\n ],\n [\n -79.7607421875,\n 42.00032514831621\n ],\n [\n -75.35522460937499,\n 42.00032514831621\n ],\n [\n -75.003662109375,\n 41.46742831254425\n ],\n [\n -73.773193359375,\n 40.863679665481676\n ],\n [\n -73.487548828125,\n 41.054501963290505\n ],\n [\n -73.2568359375,\n 42.779275360241904\n ],\n [\n -73.223876953125,\n 45.01141864227728\n ],\n [\n -75.003662109375,\n 45.034714778688624\n ],\n [\n -76.5966796875,\n 44.166444664458595\n ],\n [\n -76.201171875,\n 43.58834891179792\n ],\n [\n -79.068603515625,\n 43.29320031385282\n ],\n [\n -79.771728515625,\n 42.27730877423709\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a74e4b08de9379b3070","contributors":{"authors":[{"text":"Gazoorian, Christopher L. 0000-0002-5408-6212 cgazoori@usgs.gov","orcid":"https://orcid.org/0000-0002-5408-6212","contributorId":2929,"corporation":false,"usgs":true,"family":"Gazoorian","given":"Christopher","email":"cgazoori@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":525962,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70137743,"text":"sir20155004 - 2015 - Climate change and prairie pothole wetlands: mitigating water-level and hydroperiod effects through upland management","interactions":[],"lastModifiedDate":"2018-01-05T10:15:53","indexId":"sir20155004","displayToPublicDate":"2015-02-06T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5004","title":"Climate change and prairie pothole wetlands: mitigating water-level and hydroperiod effects through upland management","docAbstract":"Prairie pothole wetlands offer crucial habitat for North America’s waterfowl populations. The wetlands also support an abundance of other species and provide ecological services valued by society. The hydrology of prairie pothole wetlands is dependent on atmospheric interactions. Therefore, changes to the region’s climate can have profound effects on wetland hydrology. The relevant literature related to climate change and upland management effects on prairie pothole wetland water levels and hydroperiods was reviewed. Climate change is widely expected to affect water levels and hydroperiods of prairie pothole wetlands, as well as the biota and ecological services that the wetlands support. In general, hydrologic model projections that incorporate future climate change scenarios forecast lower water levels in prairie pothole wetlands and longer periods spent in a dry condition, despite potential increases in precipitation. However, the extreme natural variability in climate and hydrology of prairie pothole wetlands necessitates caution when interpreting model results. Recent changes in weather patterns throughout much of the Prairie Pothole Region have been in increased precipitation that results in increased water inputs to wetlands above losses associated with warmer temperatures. However, observed precipitation increases are within the range of natural climate variability and therefore, may not persist. Identifying management techniques with the potential to affect water inputs to prairie pothole wetlands would provide increased options for managers when dealing with the uncertainties associated with a changing climate. Several grassland management techniques (for example, grazing and burning) have the potential to affect water levels and hydroperiods of prairie pothole by affecting infiltration, evapotranspiration, and snow deposition.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155004","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and North Dakota State University","usgsCitation":"Renton, D., Mushet, D.M., and DeKeyser, E., 2015, Climate change and prairie pothole wetlands: mitigating water-level and hydroperiod effects through upland management: U.S. Geological Survey Scientific Investigations Report 2015-5004, 32 p., https://doi.org/10.3133/sir20155004.","productDescription":"32 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059680","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":297781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155004.jpg"},{"id":297779,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5004/"},{"id":297780,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5004/pdf/sir2015-5004.pdf","text":"Report","size":"3.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"Canada, United States","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.9169921875,\n 54.03358633521085\n ],\n [\n -114.82910156249999,\n 48.1367666796927\n ],\n [\n -102.4365234375,\n 46.619261036171515\n ],\n [\n -98.8330078125,\n 43.32517767999296\n ],\n [\n -95.00976562499999,\n 41.541477666790286\n ],\n [\n -91.8896484375,\n 41.50857729743935\n ],\n [\n -92.021484375,\n 45.644768217751924\n ],\n [\n -96.3720703125,\n 50.65294336725709\n ],\n [\n -101.77734374999999,\n 52.802761415419674\n ],\n [\n -114.9169921875,\n 54.03358633521085\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a5ee4b08de9379b301a","contributors":{"authors":[{"text":"Renton, David A. drenton@usgs.gov","contributorId":138600,"corporation":false,"usgs":true,"family":"Renton","given":"David A.","email":"drenton@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":539966,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":539965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeKeyser, Edward S.","contributorId":138601,"corporation":false,"usgs":false,"family":"DeKeyser","given":"Edward S.","affiliations":[{"id":12459,"text":"NDSU","active":true,"usgs":false}],"preferred":false,"id":539967,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70140168,"text":"70140168 - 2015 - Mercury concentrations and distribution in soil, water, mine waste leachates, and air in and around mercury mines in the Big Bend region, Texas, USA","interactions":[],"lastModifiedDate":"2018-09-04T15:32:43","indexId":"70140168","displayToPublicDate":"2015-02-04T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1538,"text":"Environmental Geochemistry and Health","active":true,"publicationSubtype":{"id":10}},"title":"Mercury concentrations and distribution in soil, water, mine waste leachates, and air in and around mercury mines in the Big Bend region, Texas, USA","docAbstract":"Samples of soil, water, mine waste leachates, soil gas, and air were collected from areas mined for mercury (Hg) and baseline sites in the Big Bend area, Texas, to evaluate potential Hg contamination in the region. Soil samples collected within 300 m of an inactive Hg mine contained elevated Hg concentrations (3.8–11 µg/g), which were considerably higher than Hg in soil collected from baseline sites (0.03–0.05 µg/g) distal (as much as 24 km) from mines. Only three soil samples collected within 300 m of the mine exceeded the probable effect concentration for Hg of 1.06 µg/g, above which harmful effects are likely to be observed in sediment-dwelling organisms. Concentrations of Hg in mine water runoff (7.9–14 ng/L) were generally higher than those found in springs and wells (0.05–3.1 ng/L), baseline streams (1.1–9.7 ng/L), and sources of drinking water (0.63–9.1 ng/L) collected in the Big Bend region. Concentrations of Hg in all water samples collected in this study were considerably below the 2,000 ng/L drinking water Hg guideline and the 770 ng/L guideline recommended by the U.S. Environmental Protection Agency (USEPA) to protect aquatic wildlife from chronic effects of Hg. Concentrations of Hg in water leachates obtained from leaching of mine wastes varied widely from <0.001 to 760 µg of Hg in leachate/g of sample leached, but only one leachate exceeded the USEPA Hg industrial soil screening level of 31 µg/g. Concentrations of Hg in soil gas collected at mined sites (690–82,000 ng/m3) were highly elevated compared to soil gas collected from baseline sites (1.2–77 ng/m3). However, air collected from mined areas at a height of 2 m above the ground surface contained concentrations of Hg (4.9–64 ng/m3) that were considerably lower than Hg in soil gas from the mined areas. Although concentrations of Hg emitted from mine-contaminated soils and mine wastes were elevated, persistent wind in southwest Texas disperses Hg in the air within a few meters of the ground surface.
","language":"English","publisher":"Springer Netherlands","doi":"10.1007/s10653-014-9628-1","usgsCitation":"Gray, J.E., Theodorakos, P.M., Fey, D.L., and Krabbenhoft, D.P., 2015, Mercury concentrations and distribution in soil, water, mine waste leachates, and air in and around mercury mines in the Big Bend region, Texas, USA: Environmental Geochemistry and Health, v. 37, no. 1, p. 35-48, https://doi.org/10.1007/s10653-014-9628-1.","productDescription":"14 p.","startPage":"35","endPage":"48","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055323","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":472288,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10653-014-9628-1","text":"Publisher Index Page"},{"id":297743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Big Bend region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.78372192382812,\n 28.96609636803482\n ],\n [\n -103.78372192382812,\n 29.627190028270117\n ],\n [\n -102.78396606445312,\n 29.627190028270117\n ],\n [\n -102.78396606445312,\n 28.96609636803482\n ],\n [\n -103.78372192382812,\n 28.96609636803482\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-06-29","publicationStatus":"PW","scienceBaseUri":"54dd2a96e4b08de9379b311a","contributors":{"authors":[{"text":"Gray, John E. jgray@usgs.gov","contributorId":1275,"corporation":false,"usgs":true,"family":"Gray","given":"John","email":"jgray@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":539852,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Theodorakos, Peter M. ptheodor@usgs.gov","contributorId":1566,"corporation":false,"usgs":true,"family":"Theodorakos","given":"Peter","email":"ptheodor@usgs.gov","middleInitial":"M.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":539853,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fey, David L. dfey@usgs.gov","contributorId":713,"corporation":false,"usgs":true,"family":"Fey","given":"David","email":"dfey@usgs.gov","middleInitial":"L.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":539855,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":539854,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70140152,"text":"ofr20141258 - 2015 - Lake Michigan Diversion Accounting land cover change estimation by use of the National Land Cover Dataset and raingage network partitioning analysis","interactions":[],"lastModifiedDate":"2015-02-04T10:58:40","indexId":"ofr20141258","displayToPublicDate":"2015-02-04T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1258","title":"Lake Michigan Diversion Accounting land cover change estimation by use of the National Land Cover Dataset and raingage network partitioning analysis","docAbstract":"The U.S. Army Corps of Engineers (USACE), Chicago District, is responsible for monitoring and computation of the quantity of Lake Michigan water diverted by the State of Illinois. As part of this effort, the USACE uses the Hydrological Simulation Program–FORTRAN (HSPF) with measured meteorological data inputs to estimate runoff from the Lake Michigan diversion special contributing areas (SCAs), the North Branch Chicago River above Niles and the Little Calumet River above South Holland gaged basins, and the Lower Des Plaines and the Calumet ungaged that historically drained to Lake Michigan. These simulated runoffs are used for estimating the total runoff component from the diverted Lake Michigan watershed, which is accountable to the total diversion by the State of Illinois. The runoff is simulated from three interpreted land cover types in the HSPF models: impervious, grass, and forest. The three land cover data types currently in use were derived from aerial photographs acquired in the early 1990s.
\nThis study used the National Land Cover Dataset (NLCD) and developed an automated process for determining the area of the three land cover types, thereby allowing faster updating of future models, and for evaluating land cover changes by use of historical NLCD datasets. The study also carried out a raingage partitioning analysis so that the segmentation of land cover and rainfall in each modeled unit is directly applicable to the HSPF modeling. Historical and existing impervious, grass, and forest land acreages partitioned by percentages covered by two sets of raingages for the Lake Michigan diversion SCAs, gaged basins, and ungaged basins are presented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141258","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Chicago District","usgsCitation":"Sharpe, J.B., and Soong, D.T., 2015, Lake Michigan Diversion Accounting land cover change estimation by use of the National Land Cover Dataset and raingage network partitioning analysis: U.S. Geological Survey Open-File Report 2014-1258, Report: iv, 12 p.; Downloads Directory, https://doi.org/10.3133/ofr20141258.","productDescription":"Report: iv, 12 p.; Downloads Directory","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060110","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":297727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141258.jpg"},{"id":297724,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1258/"},{"id":297725,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1258/pdf/ofr2014-1258.pdf","text":"Report","size":"2.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297726,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1258/downloads/ofr2014-1258_tables5-20.xlsx","text":"Downloads Directory","description":"Downloads Directory","linkHelpText":"Contains: Excel spreadsheets of tables 5 through 20."}],"projection":"Albers Equal-Area Conic Projection","country":"United States","state":"Illinois","otherGeospatial":"Calumet River, Lake Michigan, Little Calumet River, Lower Des Plaines River, North Branch Chicago River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.989501953125,\n 41.3500103516271\n ],\n [\n -87.989501953125,\n 42.370720143531955\n ],\n [\n -87.286376953125,\n 42.370720143531955\n ],\n [\n -87.286376953125,\n 41.3500103516271\n ],\n [\n -87.989501953125,\n 41.3500103516271\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a8de4b08de9379b30ee","contributors":{"authors":[{"text":"Sharpe, Jennifer B. 0000-0002-5192-7848 jbsharpe@usgs.gov","orcid":"https://orcid.org/0000-0002-5192-7848","contributorId":2825,"corporation":false,"usgs":true,"family":"Sharpe","given":"Jennifer","email":"jbsharpe@usgs.gov","middleInitial":"B.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soong, David T. dsoong@usgs.gov","contributorId":2230,"corporation":false,"usgs":true,"family":"Soong","given":"David","email":"dsoong@usgs.gov","middleInitial":"T.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539830,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70157523,"text":"70157523 - 2015 - An integrated Riverine Environmental Flow Decision Support System (REFDSS) to evaluate the ecological effects of alternative flow scenarios on river ecosystems","interactions":[],"lastModifiedDate":"2017-07-21T14:50:38","indexId":"70157523","displayToPublicDate":"2015-02-01T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5004,"text":"Fundamental and Applied Limnology","active":true,"publicationSubtype":{"id":10}},"title":"An integrated Riverine Environmental Flow Decision Support System (REFDSS) to evaluate the ecological effects of alternative flow scenarios on river ecosystems","docAbstract":"In regulated rivers, managers must evaluate competing flow release scenarios that attempt to balance both human and natural needs. Meeting these natural flow needs is complex due to the myriad of interacting physical and hydrological factors that affect ecosystems. Tools that synthesize the voluminous scientific data and models on these factors will facilitate management of these systems. Here, we present the Riverine Environmental Flow Decision Support System (REFDSS), a tool that enables evaluation of competing flow scenarios and other variables on instream habitat. We developed a REFDSS for the Upper Delaware River, USA, a system that is regulated by three headwater reservoirs. This version of the REFDSS has the ability to integrate any set of spatially explicit data and synthesizes modeled discharge for three competing management scenarios, flow-specific 2-D hydrodynamic modeled estimates of local hydrologic conditions (e.g., depth, velocity, shear stress, etc.) at a fine pixel-scale (1 m2), and habitat suitability criteria (HSC) for a variety of taxa. It contains all individual model outputs, computationally integrates these data, and outputs the amount of potentially available habitat for a suite of species of interest under each flow release scenario. Users have the flexibility to change the time period of interest and vary the HSC. The REFDSS was developed to enable side-by-side evaluation of different flow management scenarios and their effects on potential habitat availability, allowing managers to make informed decisions on the best flow scenarios. An exercise comparing two alternative flow scenarios to a baseline scenario for several key species is presented. The Upper Delaware REFDSS was robust to minor changes in HSC (± 10 %). The general REFDSS platform was developed as a user-friendly Windows desktop application that was designed to include other potential parameters of interest (e.g., temperature) and for transferability to other riverine systems.
","language":"English","publisher":"International Association of Theoretical and Applied Limnology","publisherLocation":"Stuttgart, Germany","doi":"10.1127/fal/2015/0611","usgsCitation":"Maloney, K.O., Talbert, C., Cole, J.C., Galbraith, H.S., Blakeslee, C.J., Hanson, L., and Holmquist-Johnson, C.L., 2015, An integrated Riverine Environmental Flow Decision Support System (REFDSS) to evaluate the ecological effects of alternative flow scenarios on river ecosystems: Fundamental and Applied Limnology, v. 186, no. 1-2, p. 171-192, https://doi.org/10.1127/fal/2015/0611.","productDescription":"22 p.","startPage":"171","endPage":"192","numberOfPages":"22","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054083","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":309723,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey, 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B.","email":"talbertc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":573433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cole, Jeffrey C. 0000-0002-2477-7231 jccole@usgs.gov","orcid":"https://orcid.org/0000-0002-2477-7231","contributorId":5585,"corporation":false,"usgs":true,"family":"Cole","given":"Jeffrey","email":"jccole@usgs.gov","middleInitial":"C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":573434,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Galbraith, Heather S. 0000-0003-3704-3517 hgalbraith@usgs.gov","orcid":"https://orcid.org/0000-0003-3704-3517","contributorId":4519,"corporation":false,"usgs":true,"family":"Galbraith","given":"Heather","email":"hgalbraith@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":573435,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blakeslee, Carrie J. 0000-0002-0801-5325 cblakeslee@usgs.gov","orcid":"https://orcid.org/0000-0002-0801-5325","contributorId":5462,"corporation":false,"usgs":true,"family":"Blakeslee","given":"Carrie","email":"cblakeslee@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":573436,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hanson, Leanne hansonl@usgs.gov","contributorId":3231,"corporation":false,"usgs":true,"family":"Hanson","given":"Leanne","email":"hansonl@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":573437,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Holmquist-Johnson, Christopher L. h-johnsonc@usgs.gov","contributorId":922,"corporation":false,"usgs":true,"family":"Holmquist-Johnson","given":"Christopher","email":"h-johnsonc@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":573438,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70155262,"text":"70155262 - 2015 - The forcing of southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter","interactions":[],"lastModifiedDate":"2017-01-18T10:06:49","indexId":"70155262","displayToPublicDate":"2015-02-01T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2216,"text":"Journal of Climate","active":true,"publicationSubtype":{"id":10}},"title":"The forcing of southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter","docAbstract":"Southwestern Asia, defined here as the domain bounded by 20°–40°N and 40°–70°E, which includes the nations of Iraq, Iran, Afghanistan, and Pakistan, is a water-stressed and semiarid region that receives roughly 75% of its annual rainfall during November–April. The November–April climate of southwestern Asia is strongly influenced by tropical Indo-Pacific variability on intraseasonal and interannual time scales, much of which can be attributed to sea surface temperature (SST) variations. The influences of lower-frequency SST variability on southwestern Asia climate during November–April Pacific decadal SST (PDSST) variability and the long-term trend in SST (LTSST) is examined. The U.S. Climate Variability and Predictability Program (CLIVAR) Drought Working Group forced global atmospheric climate models with PDSST and LTSST patterns, identified using empirical orthogonal functions, to show the steady atmospheric response to these modes of decadal to multidecadal SST variability. During November–April, LTSST forces an anticyclone over southwestern Asia, which results in reduced precipitation and increases in surface temperature. The precipitation and tropospheric circulation influences of LTSST are corroborated by independent observed precipitation and circulation datasets during 1901–2004. The decadal variations of southwestern Asia precipitation may be forced by PDSST variability, with two of the three models indicating that the cold phase of PDSST forces an anticyclone and precipitation reductions. However, there are intermodel circulation variations to PDSST that influence subregional precipitation patterns over the Middle East, southwestern Asia, and subtropical Asia. Changes in wintertime temperature and precipitation over southwestern Asia forced by LTSST and PDSST imply important changes to the land surface hydrology during the spring and summer.
","language":"English","publisher":"American Meteorological Society","publisherLocation":"Boston, MA","doi":"10.1175/JCLI-D-14-00344.1","usgsCitation":"Hoell, A., Funk, C.C., and Barlow, M., 2015, The forcing of southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter: Journal of Climate, v. 28, no. 4, p. 1511-1526, https://doi.org/10.1175/JCLI-D-14-00344.1.","productDescription":"16 p.","startPage":"1511","endPage":"1526","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058649","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472296,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jcli-d-14-00344.1","text":"Publisher Index Page"},{"id":306490,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-11","publicationStatus":"PW","scienceBaseUri":"57f7ef86e4b0bc0bec09f1a6","contributors":{"authors":[{"text":"Hoell, Andrew","contributorId":145805,"corporation":false,"usgs":false,"family":"Hoell","given":"Andrew","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565418,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barlow, Mathew","contributorId":145832,"corporation":false,"usgs":false,"family":"Barlow","given":"Mathew","email":"","affiliations":[{"id":16249,"text":"UMASS Lowel","active":true,"usgs":false}],"preferred":false,"id":565419,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70141757,"text":"70141757 - 2015 - Influence of hardness on the bioavailability of silver to a freshwater snail after waterborne exposure to silver nitrate and silver nanoparticles","interactions":[],"lastModifiedDate":"2018-09-04T16:26:28","indexId":"70141757","displayToPublicDate":"2015-02-01T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2809,"text":"Nanotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Influence of hardness on the bioavailability of silver to a freshwater snail after waterborne exposure to silver nitrate and silver nanoparticles","docAbstract":"The release of Ag nanoparticles (AgNPs) into the aquatic environment is likely, but the influence of water chemistry on their impacts and fate remains unclear. Here, we characterize the bioavailability of Ag from AgNO3 and from AgNPs capped with polyvinylpyrrolidone (PVP AgNP) and thiolated polyethylene glycol (PEG AgNP) in the freshwater snail, Lymnaea stagnalis, after short waterborne exposures. Results showed that water hardness, AgNP capping agents, and metal speciation affected the uptake rate of Ag from AgNPs. Comparison of the results from organisms of similar weight showed that water hardness affected the uptake of Ag from AgNPs, but not that from AgNO3. Transformation (dissolution and aggregation) of the AgNPs was also influenced by water hardness and the capping agent. Bioavailability of Ag from AgNPs was, in turn, correlated to these physical changes. Water hardness increased the aggregation of AgNPs, especially for PEG AgNPs, reducing the bioavailability of Ag from PEG AgNPs to a greater degree than from PVP AgNPs. Higher dissolved Ag concentrations were measured for the PVP AgNPs (15%) compared to PEG AgNPs (3%) in moderately hard water, enhancing Ag bioavailability of the former. Multiple drivers of bioavailability yielded differences in Ag influx between very hard and deionized water where the uptake rate constants (kuw, l g-1 d-1 ± SE) varied from 3.1 ± 0.7 to 0.2 ± 0.01 for PEG AgNPs and from 2.3 ± 0.02 to 1.3 ± 0.01 for PVP AgNPs. Modeling bioavailability of Ag from NPs revealed that Ag influx into L. stagnalis comprised uptake from the NPs themselves and from newly dissolved Ag.
Irrigation experiments on 12 instrumented field plots were used to assess the impact of dynamic soil crack networks on infiltration and run-off. During applications of intensity similar to a heavy rainstorm, water was seen being preferentially delivered within the soil profile. However, run-off was not observed until soil water content of the profile reached field capacity, and the apertures of surface-connected cracks had closed >60%. Electrical resistivity measurements suggested that subsurface cracks persisted and enhanced lateral transport, even in wet conditions. Likewise, single-ring infiltration measurements taken before and after irrigation indicated that infiltration remained an important component of the water budget at high soil water content values, despite apparent surface sealing. Overall, although the wetting and sealing of the soil profile showed considerable complexity, an emergent property at the hillslope scale was observed: all of the plots demonstrated a strikingly similar threshold run-off response to the cumulative precipitation amount.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10165","usgsCitation":"Stewart, R.D., Abou Najm, M.R., Rupp, D.E., Lane, J.W., Uribe, H.C., Arumi, J.L., and Selker, J.S., 2015, Hillslope run-off thresholds with shrink–swell clay soils: Hydrological Processes, v. 29, no. 4, p. 557-571, https://doi.org/10.1002/hyp.10165.","productDescription":"15 p.","startPage":"557","endPage":"571","ipdsId":"IP-053604","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"links":[{"id":349125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile","city":"Ninhue, San Agustín de Puñual","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.50538346762502,\n -36.40583448067851\n ],\n [\n -72.52799302875732,\n -36.40583448067851\n ],\n [\n -72.52799302875732,\n -36.4240329414952\n ],\n [\n -72.50538346762502,\n -36.4240329414952\n ],\n [\n -72.50538346762502,\n -36.40583448067851\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-03-11","publicationStatus":"PW","scienceBaseUri":"5a60febde4b06e28e9c2533d","contributors":{"authors":[{"text":"Stewart, Ryan D.","contributorId":199852,"corporation":false,"usgs":false,"family":"Stewart","given":"Ryan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":720204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abou Najm, Majdi R.","contributorId":199853,"corporation":false,"usgs":false,"family":"Abou Najm","given":"Majdi","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":720205,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rupp, David E.","contributorId":199854,"corporation":false,"usgs":false,"family":"Rupp","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":720206,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lane, John W. Jr. 0000-0002-3558-243X jwlane@usgs.gov","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":189168,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":false,"id":720203,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Uribe, Hamil C.","contributorId":199855,"corporation":false,"usgs":false,"family":"Uribe","given":"Hamil","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":720207,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Arumi, Jose Luis","contributorId":199856,"corporation":false,"usgs":false,"family":"Arumi","given":"Jose","email":"","middleInitial":"Luis","affiliations":[],"preferred":false,"id":720208,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Selker, John S.","contributorId":199857,"corporation":false,"usgs":false,"family":"Selker","given":"John","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":720209,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70189346,"text":"70189346 - 2015 - Inter-annual and spatial variability of Hamon potential evapotranspiration model coefficients","interactions":[],"lastModifiedDate":"2017-07-11T16:16:33","indexId":"70189346","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Inter-annual and spatial variability of Hamon potential evapotranspiration model coefficients","docAbstract":"Monthly calibrated values of the Hamon PET coefficient (C) are determined for 109,951 hydrologic response units (HRUs) across the conterminous United States (U.S.). The calibrated coefficient values are determined by matching calculated mean monthly Hamon PET to mean monthly free-water surface evaporation. For most locations and months the calibrated coefficients are larger than the standard value reported by Hamon. The largest changes in the coefficients were for the late winter/early spring and fall months, whereas the smallest changes were for the summer months. Comparisons of PET computed using the standard value of C and computed using calibrated values of C indicate that for most of the conterminous U.S. PET is underestimated using the standard Hamon PET coefficient, except for the southeastern U.S.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2014.12.006","usgsCitation":"McCabe, G., Hay, L.E., Bock, A., Markstrom, S., and Atkinson, R., 2015, Inter-annual and spatial variability of Hamon potential evapotranspiration model coefficients: Journal of Hydrology, v. 521, p. 389-394, https://doi.org/10.1016/j.jhydrol.2014.12.006.","productDescription":"6 p.","startPage":"389","endPage":"394","ipdsId":"IP-058189","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343611,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"521","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5965b4b0e4b0d1f9f05b382f","contributors":{"authors":[{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":1453,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":704307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":704308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bock, Andy 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":174776,"corporation":false,"usgs":true,"family":"Bock","given":"Andy","email":"abock@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":704309,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":1986,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven L.","email":"markstro@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":704310,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atkinson, R. Dwight","contributorId":174777,"corporation":false,"usgs":false,"family":"Atkinson","given":"R. Dwight","affiliations":[{"id":27513,"text":"U.S. Environmental Protection Agency, Office of Water","active":true,"usgs":false}],"preferred":false,"id":704311,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193748,"text":"70193748 - 2015 - Development of a new semi-analytical model for cross-borehole flow experiments in fractured media","interactions":[],"lastModifiedDate":"2018-08-09T12:48:52","indexId":"70193748","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"Development of a new semi-analytical model for cross-borehole flow experiments in fractured media","docAbstract":"Analysis of borehole flow logs is a valuable technique for identifying the presence of fractures in the subsurface and estimating properties such as fracture connectivity, transmissivity and storativity. However, such estimation requires the development of analytical and/or numerical modeling tools that are well adapted to the complexity of the problem. In this paper, we present a new semi-analytical formulation for cross-borehole flow in fractured media that links transient vertical-flow velocities measured in one or a series of observation wells during hydraulic forcing to the transmissivity and storativity of the fractures intersected by these wells. In comparison with existing models, our approach presents major improvements in terms of computational expense and potential adaptation to a variety of fracture and experimental configurations. After derivation of the formulation, we demonstrate its application in the context of sensitivity analysis for a relatively simple two-fracture synthetic problem, as well as for field-data analysis to investigate fracture connectivity and estimate fracture hydraulic properties. These applications provide important insights regarding (i) the strong sensitivity of fracture property estimates to the overall connectivity of the system; and (ii) the non-uniqueness of the corresponding inverse problem for realistic fracture configurations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.advwatres.2014.12.002","usgsCitation":"Roubinet, D., Irving, J., and Day-Lewis, F.D., 2015, Development of a new semi-analytical model for cross-borehole flow experiments in fractured media: Advances in Water Resources, v. 76, p. 97-108, https://doi.org/10.1016/j.advwatres.2014.12.002.","productDescription":"12 p.","startPage":"97","endPage":"108","ipdsId":"IP-061584","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":472304,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://serval.unil.ch/notice/serval:BIB_547C366CAA45","text":"External Repository"},{"id":349128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60febde4b06e28e9c25341","contributors":{"authors":[{"text":"Roubinet, Delphine","contributorId":199840,"corporation":false,"usgs":false,"family":"Roubinet","given":"Delphine","email":"","affiliations":[],"preferred":false,"id":720181,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irving, James","contributorId":199841,"corporation":false,"usgs":false,"family":"Irving","given":"James","email":"","affiliations":[],"preferred":false,"id":720182,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":720180,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70193751,"text":"70193751 - 2015 - Anomalous solute transport in saturated porous media: Relating transport model parameters to electrical and nuclear magnetic resonance properties","interactions":[],"lastModifiedDate":"2018-09-04T15:50:44","indexId":"70193751","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Anomalous solute transport in saturated porous media: Relating transport model parameters to electrical and nuclear magnetic resonance properties","docAbstract":"The advection-dispersion equation (ADE) fails to describe commonly observed non-Fickian solute transport in saturated porous media, necessitating the use of other models such as the dual-domain mass-transfer (DDMT) model. DDMT model parameters are commonly calibrated via curve fitting, providing little insight into the relation between effective parameters and physical properties of the medium. There is a clear need for material characterization techniques that can provide insight into the geometry and connectedness of pore spaces related to transport model parameters. Here, we consider proton nuclear magnetic resonance (NMR), direct-current (DC) resistivity, and complex conductivity (CC) measurements for this purpose, and assess these methods using glass beads as a control and two different samples of the zeolite clinoptilolite, a material that demonstrates non-Fickian transport due to intragranular porosity. We estimate DDMT parameters via calibration of a transport model to column-scale solute tracer tests, and compare NMR, DC resistivity, CC results, which reveal that grain size alone does not control transport properties and measured geophysical parameters; rather, volume and arrangement of the pore space play important roles. NMR cannot provide estimates of more-mobile and less-mobile pore volumes in the absence of tracer tests because these estimates depend critically on the selection of a material-dependent and flow-dependent cutoff time. Increased electrical connectedness from DC resistivity measurements are associated with greater mobile pore space determined from transport model calibration. CC was hypothesized to be related to length scales of mass transfer, but the CC response is unrelated to DDMT.
","language":"English","publisher":"AGU","doi":"10.1002/2014WR015284","usgsCitation":"Swanson, R., Binley, A., Keating, K., France, S., Osterman, G., Day-Lewis, F.D., and Singha, K., 2015, Anomalous solute transport in saturated porous media: Relating transport model parameters to electrical and nuclear magnetic resonance properties: Water Resources Research, v. 51, no. 2, p. 1264-1283, https://doi.org/10.1002/2014WR015284.","productDescription":"20 p.","startPage":"1264","endPage":"1283","ipdsId":"IP-057728","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":472303,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014wr015284","text":"Publisher Index Page"},{"id":349126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-27","publicationStatus":"PW","scienceBaseUri":"5a60febde4b06e28e9c2533f","contributors":{"authors":[{"text":"Swanson, Ryan D","contributorId":199846,"corporation":false,"usgs":false,"family":"Swanson","given":"Ryan D","affiliations":[],"preferred":false,"id":720193,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Binley, Andrew 0000-0002-0938-9070","orcid":"https://orcid.org/0000-0002-0938-9070","contributorId":192556,"corporation":false,"usgs":false,"family":"Binley","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":720194,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keating, Kristina","contributorId":199847,"corporation":false,"usgs":false,"family":"Keating","given":"Kristina","email":"","affiliations":[],"preferred":false,"id":720195,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"France, Samantha","contributorId":199848,"corporation":false,"usgs":false,"family":"France","given":"Samantha","email":"","affiliations":[],"preferred":false,"id":720196,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Osterman, Gordon","contributorId":199849,"corporation":false,"usgs":false,"family":"Osterman","given":"Gordon","email":"","affiliations":[],"preferred":false,"id":720197,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":720192,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Singha, Kamini 0000-0002-0605-3774","orcid":"https://orcid.org/0000-0002-0605-3774","contributorId":191366,"corporation":false,"usgs":false,"family":"Singha","given":"Kamini","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":720198,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70139713,"text":"70139713 - 2015 - Geographically isolated wetlands: Rethinking a misnomer","interactions":[],"lastModifiedDate":"2018-01-04T12:07:02","indexId":"70139713","displayToPublicDate":"2015-01-30T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Geographically isolated wetlands: Rethinking a misnomer","docAbstract":"We explore the category “geographically isolated wetlands” (GIWs; i.e., wetlands completely surrounded by uplands at the local scale) as used in the wetland sciences. As currently used, the GIW category (1) hampers scientific efforts by obscuring important hydrological and ecological differences among multiple wetland functional types, (2) aggregates wetlands in a manner not reflective of regulatory and management information needs, (3) implies wetlands so described are in some way “isolated,” an often incorrect implication, (4) is inconsistent with more broadly used and accepted concepts of “geographic isolation,” and (5) has injected unnecessary confusion into scientific investigations and discussions. Instead, we suggest other wetland classification systems offer more informative alternatives. For example, hydrogeomorphic (HGM) classes based on well-established scientific definitions account for wetland functional diversity thereby facilitating explorations into questions of connectivity without an a priori designation of “isolation.” Additionally, an HGM-type approach could be used in combination with terms reflective of current regulatory or policymaking needs. For those rare cases in which the condition of being surrounded by uplands is the relevant distinguishing characteristic, use of terminology that does not unnecessarily imply isolation (e.g., “upland embedded wetlands”) would help alleviate much confusion caused by the “geographically isolated wetlands” misnomer.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-015-0631-9","usgsCitation":"Mushet, D.M., Calhoun, A.J., Alexander, L., Cohen, M.J., DeKeyser, E., Fowler, L.G., Lane, C., Lang, M.W., Rains, M.C., and Walls, S.C., 2015, Geographically isolated wetlands: Rethinking a misnomer: Wetlands, v. 35, no. 3, p. 423-431, https://doi.org/10.1007/s13157-015-0631-9.","productDescription":"9 p.","startPage":"423","endPage":"431","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056247","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472316,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13157-015-0631-9","text":"Publisher Index Page"},{"id":297639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-27","publicationStatus":"PW","scienceBaseUri":"54dd2a7ee4b08de9379b30a6","contributors":{"authors":[{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":539573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Calhoun, Aram J.K.","contributorId":93829,"corporation":false,"usgs":false,"family":"Calhoun","given":"Aram","email":"","middleInitial":"J.K.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":539574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alexander, Laurie C.","contributorId":138989,"corporation":false,"usgs":false,"family":"Alexander","given":"Laurie C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":539608,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cohen, Matthew J.","contributorId":138990,"corporation":false,"usgs":false,"family":"Cohen","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":539609,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeKeyser, Edward S.","contributorId":138601,"corporation":false,"usgs":false,"family":"DeKeyser","given":"Edward S.","affiliations":[{"id":12459,"text":"NDSU","active":true,"usgs":false}],"preferred":false,"id":539575,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fowler, Laurie G.","contributorId":21199,"corporation":false,"usgs":false,"family":"Fowler","given":"Laurie","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":539576,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lane, Charles R.","contributorId":138991,"corporation":false,"usgs":false,"family":"Lane","given":"Charles R.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":539610,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lang, Megan W.","contributorId":131150,"corporation":false,"usgs":false,"family":"Lang","given":"Megan","email":"","middleInitial":"W.","affiliations":[{"id":7264,"text":"USDA Forest Service, Northern Research Station, Beltsville, MD 20705","active":true,"usgs":false}],"preferred":false,"id":539577,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rains, Mark C.","contributorId":138983,"corporation":false,"usgs":false,"family":"Rains","given":"Mark","email":"","middleInitial":"C.","affiliations":[{"id":12607,"text":"Univ of South florida, School of Geosciences, Tampa FL","active":true,"usgs":false}],"preferred":false,"id":539578,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Walls, Susan C. 0000-0001-7391-9155 swalls@usgs.gov","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":138952,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","email":"swalls@usgs.gov","middleInitial":"C.","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":539579,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70139682,"text":"70139682 - 2015 - The influence of disturbed habitat on the spatial ecology of Argentine black and white tegu (Tupinambis merianae), a recent invader in the Everglades ecosystem (Florida, USA)","interactions":[],"lastModifiedDate":"2015-11-30T10:25:38","indexId":"70139682","displayToPublicDate":"2015-01-30T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"The influence of disturbed habitat on the spatial ecology of Argentine black and white tegu (Tupinambis merianae), a recent invader in the Everglades ecosystem (Florida, USA)","docAbstract":"The threat of invasive species is often intensified in disturbed habitat. To optimize control programs, it is necessary to understand how degraded habitat influences the behavior of invasive species. We conducted a radio telemetry study to characterize movement and habitat use of introduced male Argentine black and white tegus (Tupinambis merianae) in the Everglades of southern Florida from May to August 2012 at the core and periphery of the introduced range. Tegus at the periphery moved farther per day (mean 131.7 ± 11.6 m, n = 6) compared to tegus at the core (mean 50.3 ± 12.4 m, n = 6). However, activity ranges were not significantly smaller in the core (mean 19.4 ± 8.4 ha, n = 6) compared to periphery (mean 29.1 ± 5.2 ha, n = 6). Peripheral activity ranges were more linear due to activity being largely restricted to levee habitat surrounded by open water or marsh. Tegus were located in shrub or tree habitat (mean 96%) more often than expected based on random locations (mean 58%), and the percent cover of trees and shrubs was higher in activity ranges (mean 61%) than the general study area (17%). Our study highlighted the ability of tegus to spread across the Florida landscape, especially in linear disturbed habitats where increased movement occurred and in areas of altered hydrology where movement is not restricted by water.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-014-0834-7","usgsCitation":"Klug, P.E., Reed, R., Mazzotti, F., McEachern, M., Vinci, J.J., Craven, K.K., and Yackel Adams, A.A., 2015, The influence of disturbed habitat on the spatial ecology of Argentine black and white tegu (Tupinambis merianae), a recent invader in the Everglades ecosystem (Florida, USA): Biological Invasions, v. 17, no. 6, p. 1785-1797, https://doi.org/10.1007/s10530-014-0834-7.","productDescription":"13 p.","startPage":"1785","endPage":"1797","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054967","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":297638,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","county":"Miami-Dade County","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.947021484375,\n 25.055745117015316\n ],\n [\n -81.947021484375,\n 26.828972753817787\n ],\n [\n -79.7442626953125,\n 26.828972753817787\n ],\n [\n -79.7442626953125,\n 25.055745117015316\n ],\n [\n -81.947021484375,\n 25.055745117015316\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-04","publicationStatus":"PW","scienceBaseUri":"54dd2abfe4b08de9379b31d0","contributors":{"authors":[{"text":"Klug, Page E. pklug@usgs.gov","contributorId":5545,"corporation":false,"usgs":true,"family":"Klug","given":"Page","email":"pklug@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":539556,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Robert N. reedr@usgs.gov","contributorId":1686,"corporation":false,"usgs":true,"family":"Reed","given":"Robert N.","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":539557,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mazzotti, Frank J.","contributorId":100018,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":539561,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McEachern, Michelle A. mmceachern@usgs.gov","contributorId":5539,"corporation":false,"usgs":true,"family":"McEachern","given":"Michelle A.","email":"mmceachern@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":539560,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vinci, Joy J.","contributorId":138977,"corporation":false,"usgs":false,"family":"Vinci","given":"Joy","email":"","middleInitial":"J.","affiliations":[{"id":12604,"text":"Department of Wildlife Ecology and Conservation, Fort Lauderdale Research and Education Center, 3205 College Avenue, University of Florida, Davie, FL 33314, USA","active":true,"usgs":false}],"preferred":false,"id":539562,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Craven, Katelin K. kcraven@usgs.gov","contributorId":5286,"corporation":false,"usgs":true,"family":"Craven","given":"Katelin","email":"kcraven@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":539559,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":539558,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70138827,"text":"sir20145226 - 2015 - Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99","interactions":[],"lastModifiedDate":"2017-01-18T13:16:53","indexId":"sir20145226","displayToPublicDate":"2015-01-27T09:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5226","title":"Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99","docAbstract":"The real-time Everglades Depth Estimation Network (EDEN) has been established to support a variety of scientific and water management purposes. The expansiveness of the Everglades, limited number of gaging stations, and extreme sensitivity of the ecosystem to small changes in water depth have created a need for accurate water-level and water-depth maps. The EDEN water-surface elevation model uses data from approximately 240 gages in the Everglades to create daily continuous interpolations of the water-surface elevation and water depth for the freshwater portion of the Everglades from 2000 to the present (2014). These maps provide hydrologic data previously unavailable for assessing biological and ecological studies.
\nEcologists working in the Everglades expressed a need to the EDEN project team for daily EDEN water-level surfaces from 1990 to 1999. The additional 10 years of surfaces will provide ecologists and resource managers with two decades (1991–2011) of surfaces to analyze hydrologic dynamics. Before 2000, many of the EDEN gages used to generate water surfaces were not in operation. These datasets were extended to provide estimations of hydrologic time-series histories. The general approach to the record extension (hindcasts) was to (1) create a database of available data from 1990 to the present; (2) use dynamic cluster analysis to group stations with similar hydrologic behaviors for subareas of the Everglades with a large number of stations; (3) use results from the cluster analysis to select candidate explanatory variables; (4) develop linear regression or artificial neural network models to extend water-level records; and (5) evaluate record extensions by using model performance statistics and comparison of water-surface maps for similar hydrologic conditions for the hindcasted period (1991–99) and measured period (2000–11).
\nTo hindcast and fill data records, 214 empirical models were developed—189 are linear regression models and 25 are artificial neural network models. The coefficient of determination (R2) for 163 of the models is greater than 0.80 and the median percent model error (root mean square error divided by the range of the measured data) is 5 percent. To evaluate the performance of the hindcast models as a group, contour maps of modeled water-level surfaces at 2-centimeter (cm) intervals were generated using the hindcasted data. The 2-cm contour maps were examined for selected days to verify that water surfaces from the EDEN model are consistent with the input data. The biweekly 2-cm contour maps did show a higher number of issues during days in 1990 as compared to days after 1990. May 1990 had the lowest water levels in the Everglades of the 21-year dataset used for the hindcasting study. To hindcast these record low conditions in 1990, many of the hindcast models would require large extrapolations beyond the range of the predictive quality of the models. For these reasons, it was decided to limit the hindcasted data to the period January 1, 1991, to December 31, 1999. Overall, the hindcasted and gap-filled data are assumed to provide reasonable estimates of station-specific water-level data for an extended historical period to inform research and natural resource management in the Everglades.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145226","usgsCitation":"Conrads, P., Petkewich, M.D., O’Reilly, A.M., and Telis, P.A., 2015, Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99: U.S. Geological Survey Scientific Investigations Report 2014-5226, Report: vi, 27 p.; 2 Tables; 2 Appendixes, https://doi.org/10.3133/sir20145226.","productDescription":"Report: vi, 27 p.; 2 Tables; 2 Appendixes","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1991-01-01","temporalEnd":"1999-12-31","ipdsId":"IP-059254","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":297562,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145226.jpg"},{"id":297559,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5226/"},{"id":297560,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5226/pdf/sir2014-5226.pdf","size":"2.93 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297561,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5226/downloads/sir2014-5226.xlsx","text":"Table 1 and 3, Appendixes 1-2","size":"149 kB","linkFileType":{"id":3,"text":"xlsx"}}],"projection":"Universal Transverse Mercator projection","country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.93328857421875,\n 25.063209244186485\n ],\n [\n -81.93328857421875,\n 26.649913524725044\n ],\n [\n -79.98596191406249,\n 26.649913524725044\n ],\n [\n -79.98596191406249,\n 25.063209244186485\n ],\n [\n -81.93328857421875,\n 25.063209244186485\n ]\n ]\n ]\n }\n }\n ]\n}","publicComments":"Prepared as part of the U.S. Geological Survey Greater Everglades Priority Ecosystem Science","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a87e4b08de9379b30d1","contributors":{"authors":[{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Petkewich, Matthew D. 0000-0002-5749-6356 mdpetkew@usgs.gov","orcid":"https://orcid.org/0000-0002-5749-6356","contributorId":982,"corporation":false,"usgs":true,"family":"Petkewich","given":"Matthew","email":"mdpetkew@usgs.gov","middleInitial":"D.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Reilly, Andrew M. 0000-0003-3220-1248 aoreilly@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-1248","contributorId":2184,"corporation":false,"usgs":true,"family":"O’Reilly","given":"Andrew","email":"aoreilly@usgs.gov","middleInitial":"M.","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":539312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Telis, Pamela A. patelis@usgs.gov","contributorId":1461,"corporation":false,"usgs":true,"family":"Telis","given":"Pamela","email":"patelis@usgs.gov","middleInitial":"A.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":false,"id":539313,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70134733,"text":"sir20145202 - 2015 - Flood-inundation maps for Indian Creek and Tomahawk Creek, Johnson County, Kansas, 2014","interactions":[],"lastModifiedDate":"2016-06-14T11:12:39","indexId":"sir20145202","displayToPublicDate":"2015-01-26T16:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5202","title":"Flood-inundation maps for Indian Creek and Tomahawk Creek, Johnson County, Kansas, 2014","docAbstract":"Digital flood-inundation maps for a 6.4-mile upper reach of Indian Creek from College Boulevard to the confluence with Tomahawk Creek, a 3.9-mile reach of Tomahawk Creek from 127th Street to the confluence with Indian Creek, and a 1.9-mile lower reach of Indian Creek from the confluence with Tomahawk Creek to just beyond the Kansas/Missouri border at State Line Road in Johnson County, Kansas, were created by the U.S. Geological Survey in cooperation with the city of Overland Park, Kansas. The flood-inundation maps, which can be accessed through the U.S. Geological Survey Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the U.S. Geological Survey streamgages on Indian Creek at Overland Park, Kansas; Indian Creek at State Line Road, Leawood, Kansas; and Tomahawk Creek near Overland Park, Kansas. Near real time stages at these streamgages may be obtained on the Web from the U.S. Geological Survey National Water Information System at http://waterdata.usgs.gov/nwis or the National Weather Service Advanced Hydrologic Prediction Service at http://water.weather.gov/ahps/, which also forecasts flood hydrographs at these sites.
Flood profiles were computed for the stream reaches by means of a one-dimensional step-backwater model. The model was calibrated for each reach by using the most current stage-discharge relations at the streamgages. The hydraulic models were then used to determine 15 water-surface profiles for Indian Creek at Overland Park, Kansas; 17 water-surface profiles for Indian Creek at State Line Road, Leawood, Kansas; and 14 water-surface profiles for Tomahawk Creek near Overland Park, Kansas, for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the next interval above the 0.2-percent annual exceedance probability flood level (500-year recurrence interval). The simulated water-surface profiles were then combined in a geographic information system with a digital elevation model derived from light detection and ranging data (having a 0.429-foot vertical and 0.228-foot horizontal accuracy) to delineate the area flooded at each water level.
The availability of these maps, along with Web information regarding current stage from the U.S. Geological Survey streamgages and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations, road closures, and postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145202","collaboration":"Prepared in cooperation with the City of Overland Park, Kansas","usgsCitation":"Peters, A.J., and Studley, S.E., 2014, Flood-inundation maps for Indian Creek and Tomahawk Creek, Johnson County, Kansas, 2014 (ver. 1.1, January 2016): U.S. Geological Survey Scientific Investigations Report 2014–5202, 11 p., https://dx.doi.org/10.3133/sir20145202.","productDescription":"vi, 11 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056342","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":323570,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5202/downloads/","text":"Downloads Directory","linkHelpText":"Contains: geospatial database. Refer to the Metadata file for more information."},{"id":323571,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2014/5202/downloads/metadata.docx"},{"id":297546,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2014/5202/pdf/coverthb.jpg"},{"id":297545,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5202/pdf/sir20145202.pdf","text":"Report","size":"10.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297536,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5202/"},{"id":314701,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2014/5202/versionhist.txt","size":"1 kb","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2014-5202 version history"}],"country":"United States","state":"Kansas","county":"Johnson County","otherGeospatial":"Indian Creek, Tomahawk Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.1728515625,\n 40.01078714046552\n ],\n [\n -94.833984375,\n 39.9434364619742\n ],\n [\n -94.833984375,\n 37.020098201368114\n ],\n [\n -102.0849609375,\n 37.020098201368114\n ],\n [\n -102.1728515625,\n 40.01078714046552\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted January 26, 2015; Version 1.1: January 25, 2016","contact":"Director, USGS Kansas Water Science Center
4821 Quail Crest Place
Lawrence, KS 66049
Hydrologic exports of dissolved inorganic and organic carbon (DIC, DOC) reflect permafrost conditions in arctic and subarctic river basins. DIC yields in particular, increase with decreased permafrost extent. We investigated the influence of permafrost extent on DIC and DOC yield in a tributary of the Yukon River, where the upper watershed has continuous permafrost and the lower watershed has discontinuous permafrost. Our results indicate that DIC versus DOC predominance switches with interannual changes in water availability and flow routing in intermediate-size watersheds having mixed permafrost coverage. Large water yield and small concentrations from mountainous headwaters and small water yield and high concentrations from lowlands produced similar upstream and downstream carbon yields. However, DOC export exceeded DIC export during high-flow 2011 while DIC predominated during low-flow 2010. The majority of exported carbon derived from near-surface organic sources when landscapes were wet or frozen and from mineralized subsurface sources when infiltration increased.
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