The U.S. Geological Survey (USGS) developed the Stochastic Empirical Loading and Dilution Model (SELDM) in cooperation with the Federal Highway Administration (FHWA) to indicate the risk for stormwater concentrations, flows, and loads to be above user-selected water-quality goals and the potential effectiveness of mitigation measures to reduce such risks. SELDM models the potential effect of mitigation measures by using Monte Carlo methods with statistics that approximate the net effects of structural and nonstructural best management practices (BMPs). In this report, structural BMPs are defined as the components of the drainage pathway between the source of runoff and a stormwater discharge location that affect the volume, timing, or quality of runoff. SELDM uses a simple stochastic statistical model of BMP performance to develop planning-level estimates of runoff-event characteristics. This statistical approach can be used to represent a single BMP or an assemblage of BMPs. The SELDM BMP-treatment module has provisions for stochastic modeling of three stormwater treatments: volume reduction, hydrograph extension, and water-quality treatment. In SELDM, these three treatment variables are modeled by using the trapezoidal distribution and the rank correlation with the associated highway-runoff variables. This report describes methods for calculating the trapezoidal-distribution statistics and rank correlation coefficients for stochastic modeling of volume reduction, hydrograph extension, and water-quality treatment by structural stormwater BMPs and provides the calculated values for these variables. This report also provides robust methods for estimating the minimum irreducible concentration (MIC), which is the lowest expected effluent concentration from a particular BMP site or a class of BMPs. These statistics are different from the statistics commonly used to characterize or compare BMPs. They are designed to provide a stochastic transfer function to approximate the quantity, duration, and quality of BMP effluent given the associated inflow values for a population of storm events. A database application and several spreadsheet tools are included in the digital media accompanying this report for further documentation of methods and for future use.
\nIn this study, analyses were done with data extracted from a modified copy of the January 2012 version of International Stormwater Best Management Practices Database, designated herein as the January 2012a version. Statistics for volume reduction, hydrograph extension, and water-quality treatment were developed with selected data. Sufficient data were available to estimate statistics for 5 to 10 BMP categories by using data from 40 to more than 165 monitoring sites. Water-quality treatment statistics were developed for 13 runoff-quality constituents commonly measured in highway and urban runoff studies including turbidity, sediment and solids; nutrients; total metals; organic carbon; and fecal coliforms. The medians of the best-fit statistics for each category were selected to construct generalized cumulative distribution functions for the three treatment variables. For volume reduction and hydrograph extension, interpretation of available data indicates that selection of a Spearman’s rho value that is the average of the median and maximum values for the BMP category may help generate realistic simulation results in SELDM. The median rho value may be selected to help generate realistic simulation results for water-quality treatment variables.
\nMIC statistics were developed for 12 runoff-quality constituents commonly measured in highway and urban runoff studies by using data from 11 BMP categories and more than 167 monitoring sites. Four statistical techniques were applied for estimating MIC values with monitoring data from each site. These techniques produce a range of lower-bound estimates for each site. Four MIC estimators are proposed as alternatives for selecting a value from among the estimates from multiple sites. Correlation analysis indicates that the MIC estimates from multiple sites were weakly correlated with the geometric mean of inflow values, which indicates that there may be a qualitative or semiquantitative link between the inflow quality and the MIC. Correlations probably are weak because the MIC is influenced by the inflow water quality and the capability of each individual BMP site to reduce inflow concentrations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145037","issn":"2328-0328","collaboration":"Prepared in cooperation with the U.S. Department of Transportation Federal Highway Administration Office of Project Development and Environmental Review","usgsCitation":"Granato, G., 2014, Statistics for stochastic modeling of volume reduction, hydrograph extension, and water-quality treatment by structural stormwater runoff best management practices (BMPs): U.S. Geological Survey Scientific Investigations Report 2014-5037, Report: vii, 37 p.; Digital media, https://doi.org/10.3133/sir20145037.","productDescription":"Report: vii, 37 p.; Digital media","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-053232","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":285854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145037.jpg"},{"id":285853,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5037/sir2014-5037.zip"},{"id":285851,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5037/pdf/sir2014-5037.pdf"},{"id":284444,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5037/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517065e4b05569d805a3cf","contributors":{"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913 ggranato@usgs.gov","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":1692,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory E.","email":"ggranato@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":491974,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70100749,"text":"70100749 - 2014 - Fathead minnow and bluegill sunfish life-stage responses to 17β-estradiol exposure in outdoor mesocosms","interactions":[],"lastModifiedDate":"2018-10-11T16:40:57","indexId":"70100749","displayToPublicDate":"2014-04-07T11:03:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Fathead minnow and bluegill sunfish life-stage responses to 17β-estradiol exposure in outdoor mesocosms","docAbstract":"Developmental and reproductive effects of 17β-estradiol (E2) exposure on two generations of fathead minnows and one generation of bluegill sunfish were assessed. Fish were exposed to E2 for six continuous weeks in outdoor mesocosms simulating natural lake environments. First generation fish were exposed while sexually mature. Second generation fathead minnows were exposed either during early development, sexual maturity, or both stages. Multiple endpoints were measured to assess effects of E2 exposure on fecundity and fish health and development. Plasma vitellogenin concentrations were highly variable in all fish. Differences in egg production timing for both species indicate differences in fecundity between females exposed to E2 and controls. First generation fathead minnows exposed to E2 had lower body condition factors and reduced secondary sexual characteristic expression by males. Only a difference in relative liver weight was observed in second generation fathead minnows. First generation bluegill males exposed to E2 had significantly smaller testes compared to controls. Although fish response was highly variable, results indicate that exposure to E2 at environmentally relevant concentrations affect fathead minnow and bluegill sunfish health and development, which may have implications for the health and sustainability of fish populations. Furthermore, exposure timing and environmental factors affect fish response to E2 exposure.","language":"English","publisher":"American Water Resources Association","doi":"10.1111/jawr.12169","usgsCitation":"Elliott, S.M., Kiesling, R.L., Jorgenson, Z.G., Rearick, D.C., Schoenfuss, H.L., Fredricks, K., and Gaikowski, M.P., 2014, Fathead minnow and bluegill sunfish life-stage responses to 17β-estradiol exposure in outdoor mesocosms: Journal of the American Water Resources Association, v. 50, no. 2, p. 376-387, https://doi.org/10.1111/jawr.12169.","productDescription":"12 p.","startPage":"376","endPage":"387","numberOfPages":"12","ipdsId":"IP-015888","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":285772,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":285749,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/jawr.12169"}],"volume":"50","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5351703ae4b05569d805a200","contributors":{"authors":[{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492423,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kiesling, Richard L. 0000-0002-3017-1826 kiesling@usgs.gov","orcid":"https://orcid.org/0000-0002-3017-1826","contributorId":1837,"corporation":false,"usgs":true,"family":"Kiesling","given":"Richard","email":"kiesling@usgs.gov","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492424,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jorgenson, Zachary G.","contributorId":69476,"corporation":false,"usgs":false,"family":"Jorgenson","given":"Zachary","email":"","middleInitial":"G.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":492427,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rearick, Daniel C.","contributorId":38897,"corporation":false,"usgs":true,"family":"Rearick","given":"Daniel","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":492426,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schoenfuss, Heiko L.","contributorId":76409,"corporation":false,"usgs":false,"family":"Schoenfuss","given":"Heiko","email":"","middleInitial":"L.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":492428,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fredricks, Kim T. 0000-0003-2363-7891 kfredricks@usgs.gov","orcid":"https://orcid.org/0000-0003-2363-7891","contributorId":5163,"corporation":false,"usgs":true,"family":"Fredricks","given":"Kim T.","email":"kfredricks@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":492425,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gaikowski, Mark P. 0000-0002-6507-9341 mgaikowski@usgs.gov","orcid":"https://orcid.org/0000-0002-6507-9341","contributorId":796,"corporation":false,"usgs":true,"family":"Gaikowski","given":"Mark","email":"mgaikowski@usgs.gov","middleInitial":"P.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":492422,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70101024,"text":"70101024 - 2014 - Blood lead concentrations in Alaskan tundra swans: linking breeding and wintering areas with satellite telemetry","interactions":[],"lastModifiedDate":"2018-09-14T15:53:03","indexId":"70101024","displayToPublicDate":"2014-04-07T10:55:47","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Blood lead concentrations in Alaskan tundra swans: linking breeding and wintering areas with satellite telemetry","docAbstract":"Tundra swans (Cygnus columbianus) like many waterfowl species are susceptible to lead (Pb) poisoning, and Pb-induced mortality has been reported from many areas of their wintering range. Little is known however about Pb levels throughout the annual cycle of tundra swans, especially during summer when birds are on remote northern breeding areas where they are less likely to be exposed to anthropogenic sources of Pb. Our objective was to document summer Pb levels in tundra swans throughout their breeding range in Alaska to determine if there were population-specific differences in blood Pb concentrations that might pose a threat to swans and to humans that may consume them. We measured blood Pb concentrations in tundra swans at five locations in Alaska, representing birds that winter in both the Pacific Flyway and Atlantic Flyway. We also marked swans at each location with satellite transmitters and coded neck bands, to identify staging and wintering sites and determine if winter site use correlated with summer Pb concentrations. Blood Pb levels were generally low ( < 0.2 μg/ml) in swans across all breeding areas. Pb levels were lower in cygnets than adults, suggesting that swans were likely exposed to Pb on wintering areas or on return migration to Alaska, rather than on the summer breeding grounds. Blood Pb levels varied significantly across the five breeding areas, with highest concentrations in birds on the North Slope of Alaska (wintering in the Atlantic Flyway), and lowest in birds from the lower Alaska Peninsula that rarely migrate south for winter.","language":"English","publisher":"Springer","doi":"10.1007/s10646-014-1192-z","usgsCitation":"Ely, C.R., and Franson, C., 2014, Blood lead concentrations in Alaskan tundra swans: linking breeding and wintering areas with satellite telemetry: Ecotoxicology, v. 23, no. 3, p. 349-356, https://doi.org/10.1007/s10646-014-1192-z.","productDescription":"8 p.","startPage":"349","endPage":"356","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053240","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":285950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":285949,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10646-014-1192-z"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -141.240234375,\n 69.7181066990676\n ],\n [\n -156.09375,\n 71.41317683396566\n ],\n [\n -166.55273437499997,\n 68.75231494434473\n ],\n [\n -168.57421875,\n 65.47650756256367\n ],\n [\n -165.41015625,\n 59.62332522313024\n ],\n [\n -159.345703125,\n 57.562995459387146\n ],\n [\n -167.16796875,\n 54.36775852406841\n ],\n [\n -177.890625,\n 52.482780222078205\n ],\n [\n -187.3828125,\n 53.54030739150022\n ],\n [\n -187.998046875,\n 52.429222277955134\n ],\n [\n -177.275390625,\n 51.01375465718821\n ],\n [\n -166.904296875,\n 52.802761415419674\n ],\n [\n -161.279296875,\n 54.77534585936447\n ],\n [\n -151.611328125,\n 56.84897198026975\n ],\n [\n -150.99609375,\n 58.768200159239576\n ],\n [\n -146.42578125,\n 59.84481485969105\n ],\n [\n -140.9765625,\n 59.57885104663186\n ],\n [\n -141.240234375,\n 69.7181066990676\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-01-28","publicationStatus":"PW","scienceBaseUri":"53517029e4b05569d805a17b","contributors":{"authors":[{"text":"Ely, Craig R. 0000-0003-4262-0892 cely@usgs.gov","orcid":"https://orcid.org/0000-0003-4262-0892","contributorId":3214,"corporation":false,"usgs":true,"family":"Ely","given":"Craig","email":"cely@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":492546,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Franson, Christian 0000-0002-0251-4238","orcid":"https://orcid.org/0000-0002-0251-4238","contributorId":58941,"corporation":false,"usgs":true,"family":"Franson","given":"Christian","affiliations":[],"preferred":false,"id":492547,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70110902,"text":"70110902 - 2014 - Viruses as groundwater tracers: using ecohydrology to characterize short travel times in aquifers","interactions":[],"lastModifiedDate":"2014-06-02T08:41:02","indexId":"70110902","displayToPublicDate":"2014-04-05T08:28:23","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Viruses as groundwater tracers: using ecohydrology to characterize short travel times in aquifers","docAbstract":"Viruses are attractive tracers of short (<3 year) travel times in aquifers because they have unique genetic signatures, are detectable in trace quantities, and are mobile in groundwater. Virus “snaphots” result from infection and disappearance in a population over time; therefore, the virus snapshot shed in the fecal wastes of an infected population at a specific point in time can serve as a marker for tracking virus and groundwater movement. The virus tracing approach and an example application are described to illustrate their ability to characterize travel times in high-groundwater velocity settings, and provide insight unavailable from standard hydrogeologic approaches. Although characterization of preferential flowpaths does not usually characterize the majority of other travel times occurring in the groundwater system (e.g., center of plume mass; tail of the breakthrough curve), virus approaches can trace very short times of transport, and thus can fill an important gap in our current hydrogeology toolbox.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ground Water","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley Online Library","doi":"10.1111/gwat.12158","usgsCitation":"Hunt, R.J., Borchardt, M., and Bradbury, K.R., 2014, Viruses as groundwater tracers: using ecohydrology to characterize short travel times in aquifers: Ground Water, v. 52, no. 2, p. 187-193, https://doi.org/10.1111/gwat.12158.","productDescription":"7 p.","startPage":"187","endPage":"193","ipdsId":"IP-050901","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":287936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287935,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/gwat.12158"}],"volume":"52","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-01-16","publicationStatus":"PW","scienceBaseUri":"53ae789fe4b0abf75cf2db23","contributors":{"authors":[{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494188,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Borchardt, Mark A.","contributorId":106255,"corporation":false,"usgs":true,"family":"Borchardt","given":"Mark A.","affiliations":[],"preferred":false,"id":494190,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradbury, Kenneth R.","contributorId":49419,"corporation":false,"usgs":true,"family":"Bradbury","given":"Kenneth","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":494189,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70100765,"text":"70100765 - 2014 - Identifying marine Important Bird Areas using at-sea survey data","interactions":[],"lastModifiedDate":"2014-04-04T15:51:07","indexId":"70100765","displayToPublicDate":"2014-04-04T15:47:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Identifying marine Important Bird Areas using at-sea survey data","docAbstract":"Effective marine bird conservation requires identification of at-sea locations used by populations for foraging, staging, and migration. Using an extensive database of at-sea survey data spanning over 30 years, we developed a standardized and data-driven spatial method for identifying globally significant marine Important Bird Areas in Alaska. To delineate these areas we developed a six-step process: binning data and accounting for unequal survey effort, filtering input data for persistence of species use, using a moving window analysis to produce maps representing a gradient from low to high abundance, drawing core area boundaries around major concentrations based on abundance thresholds, validating the results, and combining overlapping boundaries into important areas for multiple species. We identified 126 bird core areas which were merged into 59 pelagic sites important to 45 out of 57 species assessed. The final areas included approximately 34–38% of all marine birds in Alaska waters, within just 6% of the total area. We identified globally significant Important Bird Areas spanning 20 degrees of latitude and 56 degrees of longitude, in two different oceans, with climates ranging from temperate to polar. Although our maps did suffer from some data gaps, these gaps did not preclude us from identifying sites that incorporated 13% of the assessed continental waterbird population and 9% of the assessed global seabird population. The application of this technique over a large and productive region worked well for a wide range of birds, exhibiting a variety of foraging strategies and occupying a variety of ecosystem types.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biological Conservation","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2014.02.039","usgsCitation":"Smith, M.A., Walker, N.J., Free, C.M., Kirchhoff, M.J., Drew, G.S., Warnock, N., and Stenhouse, I.J., 2014, Identifying marine Important Bird Areas using at-sea survey data: Biological Conservation, v. 172, p. 180-189, https://doi.org/10.1016/j.biocon.2014.02.039.","productDescription":"10 p.","startPage":"180","endPage":"189","numberOfPages":"10","ipdsId":"IP-051043","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":285755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":285754,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.biocon.2014.02.039"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea;Chukchi Sea;East Bering Sea;Gulf Of Alaska;West Bering Sea","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 130.5,47.9 ], [ 130.5,74.7 ], [ -167.6,74.7 ], [ -167.6,47.9 ], [ 130.5,47.9 ] ] ] } } ] }","volume":"172","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5351704ee4b05569d805a2db","contributors":{"authors":[{"text":"Smith, Melanie A.","contributorId":31305,"corporation":false,"usgs":true,"family":"Smith","given":"Melanie","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":492431,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, Nathan J.","contributorId":90210,"corporation":false,"usgs":true,"family":"Walker","given":"Nathan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":492435,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Free, Christopher M.","contributorId":40895,"corporation":false,"usgs":true,"family":"Free","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":492433,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kirchhoff, Matthew J.","contributorId":31306,"corporation":false,"usgs":true,"family":"Kirchhoff","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":492432,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Drew, Gary S. 0000-0002-6789-0891 gdrew@usgs.gov","orcid":"https://orcid.org/0000-0002-6789-0891","contributorId":3311,"corporation":false,"usgs":true,"family":"Drew","given":"Gary","email":"gdrew@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":492429,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Warnock, Nils","contributorId":64534,"corporation":false,"usgs":false,"family":"Warnock","given":"Nils","email":"","affiliations":[],"preferred":false,"id":492434,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stenhouse, Iain J.","contributorId":23434,"corporation":false,"usgs":true,"family":"Stenhouse","given":"Iain","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":492430,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70100725,"text":"sir20145020 - 2014 - Simulation of groundwater flow and interaction of groundwater and surface water on the Lac du Flambeau Reservation, Wisconsin","interactions":[],"lastModifiedDate":"2014-04-04T12:51:24","indexId":"sir20145020","displayToPublicDate":"2014-04-04T12:46:00","publicationYear":"2014","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":"2014-5020","title":"Simulation of groundwater flow and interaction of groundwater and surface water on the Lac du Flambeau Reservation, Wisconsin","docAbstract":"The Lac du Flambeau Band of Lake Superior Chippewa and Indian Health Service are interested in improving the understanding of groundwater flow and groundwater/surface-water interaction on the Lac du Flambeau Reservation (Reservation) in southwest Vilas County and southeast Iron County, Wisconsin, with particular interest in an understanding of the potential for contamination of groundwater supply wells and the fate of wastewater that is infiltrated from treatment lagoons on the Reservation. This report describes the construction, calibration, and application of a regional groundwater flow model used to simulate the shallow groundwater flow system of the Reservation and water-quality results for groundwater and surface-water samples collected near a system of waste-water-treatment lagoons.
\nGroundwater flows through a permeable glacial aquifer that ranges in thickness from 60 to more than 200 feet (ft). Seepage and drainage lakes are common in the area and influence groundwater flow patterns on the Reservation. A two-dimensional, steady-state analytic element groundwater flow model was constructed using the program GFLOW. The model was calibrated by matching target water levels and stream base flows through the use of the parameter-estimation program, PEST. Simulated results illustrate that groundwater flow within most of the Reservation is toward the Bear River and the chain of lakes that feed the Bear River. Results of analyses of groundwater and surface-water samples collected downgradient from the wastewater infiltration lagoons show elevated levels of ammonia and dissolved phosphorus. In addition, wastewater indicator chemicals detected in three downgradient wells and a small downgradient stream indicate that infiltrated wastewater is moving southwest of the lagoons toward Moss Lake.
\nPotential effects of extended wet and dry periods (within historical ranges) were evaluated by adjusting precipitation and groundwater recharge in the model and comparing the resulting simulated lake stage and water budgets to stages and water budgets from the calibrated model. Simulated lake water budgets and water level changes illustrate the importance of understanding the position of a lake within the hydrologic system (headwater or downstream), the type of lake (surface-water drainage or seepage lake), and the role of groundwater in dampening the effects of large-scale changes in weather patterns on lake levels.
\nAreas contributing recharge to drinking-water supply wells on the Reservation were delineated using forward particle tracking from the water table to the well. Monte Carlo uncertainty analyses were used to produce maps showing the probability of groundwater capture for areas around each well nest. At the Main Pumphouse site near the Village of Lac du Flambeau, most of the area contributing recharge to the wells occurs downgradient from a large wetland between the wells and the wastewater infiltration lagoons. Nonetheless, a small potential for the wells to capture infiltrated wastewater is apparent when considering uncertainty in the model parameter values. At the West Pumphouse wells south of Flambeau Lake, most of the area contributing recharge is between the wells and Tippecanoe Lake.
\nThe extent of infiltrated wastewater from two infiltration lagoons was tracked using the groundwater flow model and Monte Carlo uncertainty analyses. Wastewater infiltrated from the lagoons flows predominantly south toward Moss Lake as it integrates with the regional groundwater flow system. The wastewater-plume-extent simulations support the area-contributing-recharge simulations, indicating that there is a possibility, albeit at low probability, that some wastewater could be captured by water-supply wells. Comparison of simulated water-table contours indicate that the lagoons may mound the water table approximately 4 ft, with diminishing levels of mounding outward from the lagoons.
\nFour scenarios, representing potential alternatives for wastewater management, were simulated (at current discharge rates) to evaluate the potential extent of wastewater in the aquifer and discharge to surface-water bodies associated with each management scenario. Wastewater simulated to infiltrate through a hypothetical diffuser below a wetland south of the current lagoons appears to discharge to the overlying wetland and would likely discharge to Moss Lake as overland flow. Wastewater simulated to discharge to a small lake (Mindy Lake) between Moss and Fence Lakes appears to spread radically over a large area between the lakes. Wastewater simulated to discharge to lagoons south and northeast of the current lagoons also appears to spread radially, but the areas of the aquifer with the highest probability of encountering waste-water contamination would likely be between the lagoons and the nearest lake, where the wastewater would eventually discharge. Probability results for the wastewater-plume-extent scenarios are sensitive to the number of mathematical water particles used to represent infiltrating wastewater and the level of detail in the synthetic grid used for the probability analysis. Thus, probability results from wastewater-plume-extent simulations are qualitative only; however, it is expected that illustrations of relatively high or low probability will be useful as a general guide for decision making. Management problems requiring quantitative estimates of probability are best re-cast into problems evaluating the area that contributes recharge to the location of interest, which is not dependent upon the number of simulated particles or the resolution of a synthetic grid.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145020","issn":"2328-0328","collaboration":"Prepared in cooperation with the Lac du Flambeau Band of Lake Superior Chippewa and Indian Health Service","usgsCitation":"Juckem, P.F., Fienen, M., and Hunt, R.J., 2014, Simulation of groundwater flow and interaction of groundwater and surface water on the Lac du Flambeau Reservation, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2014-5020, Report: vi, 43 p.; Appendix, https://doi.org/10.3133/sir20145020.","productDescription":"Report: vi, 43 p.; Appendix","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-046060","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":285713,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5020/pdf/sir2014-5020.pdf"},{"id":285714,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5020/appendix/sir2014-5020_appendix_layout.xlsx"},{"id":285715,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145020.jpg"},{"id":285701,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5020/"}],"country":"United States","state":"Wisconsin","county":"Iron County;Vilas County","otherGeospatial":"Lac Du Flambeau Reservation","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -90.0,45.916667 ], [ -90.0,46.083333 ], [ -89.75,46.083333 ], [ -89.75,45.916667 ], [ -90.0,45.916667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517062e4b05569d805a3ab","contributors":{"authors":[{"text":"Juckem, Paul F. 0000-0002-3613-1761 pfjuckem@usgs.gov","orcid":"https://orcid.org/0000-0002-3613-1761","contributorId":1905,"corporation":false,"usgs":true,"family":"Juckem","given":"Paul","email":"pfjuckem@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":893,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","email":"mnfienen@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":492392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492393,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70099604,"text":"sir20145050 - 2014 - Groundwater availability in the Crouch Branch and McQueen Branch aquifers, Chesterfield County, South Carolina, 1900-2012","interactions":[],"lastModifiedDate":"2024-04-10T10:56:07.508306","indexId":"sir20145050","displayToPublicDate":"2014-04-04T12:36:00","publicationYear":"2014","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":"2014-5050","title":"Groundwater availability in the Crouch Branch and McQueen Branch aquifers, Chesterfield County, South Carolina, 1900-2012","docAbstract":"Chesterfield County is located in the northeastern part of South Carolina along the southern border of North Carolina and is primarily underlain by unconsolidated sediments of Late Cretaceous age and younger of the Atlantic Coastal Plain. Approximately 20 percent of Chesterfield County is in the Piedmont Physiographic Province, and this area of the county is not included in this study. These Atlantic Coastal Plain sediments compose two productive aquifers: the Crouch Branch aquifer that is present at land surface across most of the county and the deeper, semi-confined McQueen Branch aquifer. Most of the potable water supplied to residents of Chesterfield County is produced from the Crouch Branch and McQueen Branch aquifers by a well field located near McBee, South Carolina, in the southwestern part of the county. Overall, groundwater availability is good to very good in most of Chesterfield County, especially the area around and to the south of McBee, South Carolina. The eastern part of Chesterfield County does not have as abundant groundwater resources but resources are generally adequate for domestic purposes.
\nThe primary purpose of this study was to determine groundwater-flow rates, flow directions, and changes in water budgets over time for the Crouch Branch and McQueen Branch aquifers in the Chesterfield County area. This goal was accomplished by using the U.S. Geological Survey finite-difference MODFLOW groundwater-flow code to construct and calibrate a groundwater-flow model of the Atlantic Coastal Plain of Chesterfield County. The model was created with a uniform grid size of 300 by 300 feet to facilitate a more accurate simulation of groundwater-surface-water interactions. The model consists of 617 rows from north to south extending about 35 miles and 884 columns from west to east extending about 50 miles, yielding a total area of about 1,750 square miles. However, the active part of the modeled area, or the part where groundwater flow is simulated, totaled about 1,117 square miles.
\nMajor types of data used as input to the model included groundwater levels, groundwater-use data, and hydrostratigraphic data, along with estimates and measurements of stream base flows made specifically for this study. The groundwater-flow model was calibrated to groundwater-level and stream base-flow conditions from 1900 to 2012 using 39 stress periods. The model was calibrated with an automated parameter-estimation approach using the computer program PEST, and the model used regularized inversion and pilot points. The groundwater-flow model was calibrated using field data that included groundwater levels that had been collected between 1940 and 2012 from 239 wells and base-flow measurements from 44 locations distributed within the study area. To better understand recharge and inter-aquifer interactions, seven wells were equipped with continuous groundwater-level recording equipment during the course of the study, between 2008 and 2012. These water levels were included in the model calibration process. The observed groundwater levels were compared to the simulated ones, and acceptable calibration fits were achieved. Root mean square error for the simulated groundwater levels compared to all observed groundwater levels was 9.3 feet for the Crouch Branch aquifer and 8.6 feet for the McQueen Branch aquifer.
\nThe calibrated groundwater-flow model was then used to calculate groundwater budgets for the entire study area and for two sub-areas. The sub-areas are the Alligator Rural Water and Sewer Company well field near McBee, South Carolina, and the Carolina Sandhills National Wildlife Refuge acquisition boundary area. For the overall model area, recharge rates vary from 56 to 1,679 million gallons per day (Mgal/d) with a mean of 737 Mgal/d over the simulation period (1900–2012). The simulated water budget for the streams and rivers varies from 653 to 1,127 Mgal/d with a mean of 944 Mgal/d. The simulated “storage-in term” ranges from 0 to 565 Mgal/d with a mean of 276 Mgal/d. The simulated “storage-out term” has a range of 0 to 552 Mgal/d with a mean of 77 Mgal/d. Groundwater budgets for the McBee, South Carolina, area and the Carolina Sandhills National Wildlife Refuge acquisition area had similar results.
\nAn analysis of the effects of past and current groundwater withdrawals on base flows in the McBee area indicated a negligible effect of pumping from the Alligator Rural Water and Sewer well field on local stream base flows. Simulate base flows for 2012 for selected streams in and around the McBee area were similar with and without simulated groundwater withdrawals from the well field. Removing all pumping from the model for the entire simulation period (1900–2012) produces a negligible difference in increased base flow for the selected streams. The 2012 flow for Lower Alligator Creek was 5.04 Mgal/d with the wells pumping and 5.08 Mgal/d without the wells pumping; this represents the largest difference in simulated flows for the six streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145050","issn":"2328-0328","collaboration":"Prepared in cooperation with the South Carolina Department of Natural Resources","usgsCitation":"Campbell, B.G., and Landmeyer, J., 2014, Groundwater availability in the Crouch Branch and McQueen Branch aquifers, Chesterfield County, South Carolina, 1900-2012: U.S. Geological Survey Scientific Investigations Report 2014-5050, Report: viii, 68 p.; 2 Tables, https://doi.org/10.3133/sir20145050.","productDescription":"Report: viii, 68 p.; 2 Tables","numberOfPages":"80","onlineOnly":"Y","temporalStart":"1900-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-052468","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":285712,"rank":5,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145050.jpg"},{"id":285708,"rank":4,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5050/"},{"id":285709,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5050/pdf/sir2014-5050.pdf"},{"id":285710,"rank":2,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5050/tables/sir2014-5050_table2-1-crouchbranch.xlsx"},{"id":285711,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5050/tables/sir2014-5050_table2-2-mcqueenbranch.xlsx"}],"scale":"100000","projection":"North American Datum of 1983","country":"United States","state":"South Carolina","county":"Chesterfield County","otherGeospatial":"Crouch Branch Aquifer, Mcqueen Branch 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Bruce G. 0000-0003-4800-6674 bcampbel@usgs.gov","orcid":"https://orcid.org/0000-0003-4800-6674","contributorId":995,"corporation":false,"usgs":true,"family":"Campbell","given":"Bruce","email":"bcampbel@usgs.gov","middleInitial":"G.","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":491975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landmeyer, James 0000-0002-5640-3816 jlandmey@usgs.gov","orcid":"https://orcid.org/0000-0002-5640-3816","contributorId":3257,"corporation":false,"usgs":true,"family":"Landmeyer","given":"James","email":"jlandmey@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":491976,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70099787,"text":"ofr20141064 - 2014 - Noble gas isotopes in mineral springs within the Cascadia Forearc, Washington and Oregon","interactions":[],"lastModifiedDate":"2024-01-29T22:47:49.297952","indexId":"ofr20141064","displayToPublicDate":"2014-04-04T08:03:00","publicationYear":"2014","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":"2014-1064","title":"Noble gas isotopes in mineral springs within the Cascadia Forearc, Washington and Oregon","docAbstract":"This U.S. Geological Survey report presents laboratory analyses along with field notes for a pilot study to document the relative abundance of noble gases in mineral springs within the Cascadia forearc of Washington and Oregon. Estimates of the depth to the underlying Juan de Fuca oceanic plate beneath the sample sites are derived from the McCrory and others (2012) slab model. Some of these springs have been previously sampled for chemical analyses (Mariner and others, 2006), but none currently have publicly available noble gas data. Helium isotope values as well as the noble gas values and ratios presented below will be used to determine the sources and mixing history of these mineral waters.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141064","usgsCitation":"McCrory, P.A., Constantz, J., and Hunt, A.G., 2014, Noble gas isotopes in mineral springs within the Cascadia Forearc, Washington and Oregon: U.S. Geological Survey Open-File Report 2014-1064, Report: iv, 20 p.; Tables 1-8, https://doi.org/10.3133/ofr20141064.","productDescription":"Report: iv, 20 p.; Tables 1-8","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052802","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":285666,"rank":10,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1064/"},{"id":285676,"rank":11,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141064.GIF"},{"id":285675,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1064/downloads/ofr2014-1064_Table8_Wilhoit.xlsx"},{"id":285674,"rank":2,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1064/downloads/ofr2014-1064_Table7_Sodaville.xlsx"},{"id":285673,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1064/downloads/ofr2014-1064_Table6_Cascadia.xlsx"},{"id":285669,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1064/downloads/ofr2014-1064_Table2_Olympic.xlsx"},{"id":285672,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1064/downloads/ofr2014-1064_Table5_Boswell.xlsx"},{"id":285671,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1064/downloads/ofr2014-1064_Table4_Pigeon.xlsx"},{"id":285670,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1064/downloads/ofr2014-1064_Table3_JacksonPrairie.xlsx"},{"id":285668,"rank":8,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1064/downloads/ofr2014-1064_Table1_SolDuc.xlsx"},{"id":285667,"rank":9,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1064/pdf/ofr2014-1064.pdf"}],"projection":"Transverse Mercator projection","datum":"World Geodetic System 1984","country":"United States","state":"Oregon;Washington","otherGeospatial":"Cascadia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -132.0,39.0 ], [ -132.0,52.0 ], [ -120.0,52.0 ], [ -120.0,39.0 ], [ -132.0,39.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517057e4b05569d805a345","contributors":{"authors":[{"text":"McCrory, Patricia A. 0000-0003-2471-0018 pmccrory@usgs.gov","orcid":"https://orcid.org/0000-0003-2471-0018","contributorId":2728,"corporation":false,"usgs":true,"family":"McCrory","given":"Patricia","email":"pmccrory@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":492027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Constantz, James E. 0000-0002-4062-2096 jconstan@usgs.gov","orcid":"https://orcid.org/0000-0002-4062-2096","contributorId":1962,"corporation":false,"usgs":true,"family":"Constantz","given":"James E.","email":"jconstan@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":492026,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":492025,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70048943,"text":"ds795 - 2014 - Groundwater-quality data in seven GAMA study units: results from initial sampling, 2004-2005, and resampling, 2007-2008, of wells: California GAMA Program Priority Basin Project","interactions":[],"lastModifiedDate":"2026-05-20T19:18:54.504554","indexId":"ds795","displayToPublicDate":"2014-04-03T16:06:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"795","title":"Groundwater-quality data in seven GAMA study units: results from initial sampling, 2004-2005, and resampling, 2007-2008, of wells: California GAMA Program Priority Basin Project","docAbstract":"The Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) Program was developed in response to the Groundwater Quality Monitoring Act of 2001 and is being conducted by the U.S. Geological Survey (USGS) in cooperation with the California State Water Resources Control Board (SWRCB). The GAMA-PBP began sampling, primarily public supply wells in May 2004. By the end of February 2006, seven (of what would eventually be 35) study units had been sampled over a wide area of the State. Selected wells in these first seven study units were resampled for water quality from August 2007 to November 2008 as part of an assessment of temporal trends in water quality by the GAMA-PBP.
\nThe initial sampling was designed to provide a spatially unbiased assessment of the quality of raw groundwater used for public water supplies within the seven study units. In the 7 study units, 462 wells were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the study area. Wells selected this way are referred to as grid wells or status wells. Approximately 3 years after the initial sampling, 55 of these previously sampled status wells (approximately 10 percent in each study unit) were randomly selected for resampling. The seven resampled study units, the total number of status wells sampled for each study unit, and the number of these wells resampled for trends are as follows, in chronological order of sampling: San Diego Drainages (53 status wells, 7 trend wells), North San Francisco Bay (84, 10), Northern San Joaquin Basin (51, 5), Southern Sacramento Valley (67, 7), San Fernando–San Gabriel (35, 6), Monterey Bay and Salinas Valley Basins (91, 11), and Southeast San Joaquin Valley (83, 9).
\nThe groundwater samples were analyzed for a large number of synthetic organic constituents (volatile organic compounds [VOCs], pesticides, and pesticide degradates), constituents of special interest (perchlorate, N-nitrosodimethylamine [NDMA], and 1,2,3-trichloropropane [1,2,3-TCP]), and naturally-occurring inorganic constituents (nutrients, major and minor ions, and trace elements). Naturally-occurring isotopes (tritium, carbon-14, and stable isotopes of hydrogen and oxygen in water) also were measured to help identify processes affecting groundwater quality and the sources and ages of the sampled groundwater. Nearly 300 constituents and water-quality indicators were investigated.
\nQuality-control samples (blanks, replicates, and samples for matrix spikes) were collected at 24 percent of the 55 status wells resampled for trends, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. Field blanks rarely contained detectable concentrations of any constituent, suggesting that contamination was not a noticeable source of bias in the data for the groundwater samples. Differences between replicate samples were mostly within acceptable ranges, indicating acceptably low variability in analytical results. Matrix-spike recoveries were within the acceptable range (70 to 130 percent) for 75 percent of the compounds for which matrix spikes were collected.
\nThis study did not attempt to evaluate the quality of water delivered to consumers. After withdrawal, groundwater typically is treated, disinfected, and blended with other waters to maintain acceptable water quality. The benchmarks used in this report apply to treated water that is served to the consumer, not to untreated groundwater. To provide some context for the results, however, concentrations of constituents measured in these groundwater samples were compared with benchmarks established by the U.S. Environmental Protection Agency (USEPA) and California Department of Public Health (CDPH). Comparisons between data collected for this study and benchmarks for drinking water are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks.
\nMost constituents that were detected in groundwater samples from the trend wells were found at concentrations less than drinking-water benchmarks. Four VOCs—trichloroethene, tetrachloroethene, 1,2-dibromo-3-chloropropane, and methyl tert-butyl ether—were detected in one or more wells at concentrations greater than their health-based benchmarks, and six VOCs were detected in at least 10 percent of the samples during initial sampling or resampling of the trend wells. No pesticides were detected at concentrations near or greater than their health-based benchmarks. Three pesticide constituents—atrazine, deethylatrazine, and simazine—were detected in more than 10 percent of the trend-well samples during both sampling periods. Perchlorate, a constituent of special interest, was detected more frequently, and at greater concentrations during resampling than during initial sampling, but this may be due to a change in analytical method between the sampling periods, rather than to a change in groundwater quality. Another constituent of special interest, 1,2,3-TCP, was also detected more frequently during resampling than during initial sampling, but this pattern also may not reflect a change in groundwater quality. Samples from several of the wells where 1,2,3-TCP was detected by low-concentration-level analysis during resampling were not analyzed for 1,2,3-TCP using a low-level method during initial sampling. Most detections of nutrients and trace elements in samples from trend wells were less than health-based benchmarks during both sampling periods. Exceptions include nitrate, arsenic, boron, and vanadium, all detected at concentrations greater than their health-based benchmarks in at least one well during both sampling periods, and molybdenum, detected at concentrations greater than its health-based benchmark during resampling only. The isotopic ratios of oxygen and hydrogen in water and tritium and carbon-14 activities generally changed little between sampling periods, suggesting that the predominant sources and ages of groundwater in most trend wells were consistent between the sampling periods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds795","collaboration":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program. Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Kent, R.H., Belitz, K., and Fram, M.S., 2014, Groundwater-quality data in seven GAMA study units: results from initial sampling, 2004-2005, and resampling, 2007-2008, of wells: California GAMA Program Priority Basin Project: U.S. Geological Survey Data Series 795, x, 170 p., https://doi.org/10.3133/ds795.","productDescription":"x, 170 p.","numberOfPages":"184","onlineOnly":"Y","ipdsId":"IP-032958","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":504584,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_99880.htm","linkFileType":{"id":5,"text":"html"}},{"id":285664,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/795/pdf/ds795.pdf"},{"id":285663,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/795/"},{"id":285665,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds795.jpg"}],"projection":"Albers Equal Area Conic Projection","country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125.0,32.0 ], [ -125.0,42.2 ], [ -114.0,42.2 ], [ -114.0,32.0 ], [ -125.0,32.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517044e4b05569d805a243","contributors":{"authors":[{"text":"Kent, Robert H. 0000-0003-4174-9467 rhkent@usgs.gov","orcid":"https://orcid.org/0000-0003-4174-9467","contributorId":175257,"corporation":false,"usgs":true,"family":"Kent","given":"Robert","email":"rhkent@usgs.gov","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485827,"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":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485826,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70100588,"text":"ofr20141072 - 2014 - Distribution and extent of heavy metal accumulation in Song Sparrows (Melospiza melodia), upper Santa Cruz River watershed, southern Arizona, 2011-12","interactions":[],"lastModifiedDate":"2017-11-25T13:44:29","indexId":"ofr20141072","displayToPublicDate":"2014-04-03T15:13:00","publicationYear":"2014","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":"2014-1072","title":"Distribution and extent of heavy metal accumulation in Song Sparrows (Melospiza melodia), upper Santa Cruz River watershed, southern Arizona, 2011-12","docAbstract":"Riparian ecosystems in arid environments provide critical habitat for breeding, migratory, and wintering birds, yet are often at risk of contamination by heavy metals. Birds and other animals living in contaminated areas are susceptible to adverse health effects as a result of long-term exposure and bioaccumulation of heavy metals. We investigated the distribution and cascading extent of heavy metal accumulation in Song Sparrows (Melospiza melodia) in Arizona’s upper Santa Cruz River watershed. This study had three goals: (1) quantify the degree of heavy metal accumulation in sparrows and determine the distributional patterns among study sites, (2) compare concentrations of metals found in this study to those found in studies performed prior to the 2009 international wastewater treatment plant upgrade, and (3) assess sparrow condition among sites with differing potential sources of contamination exposure.
\nWe examined six study sites that reflected different potential sources of contamination. Hematocrit values, body mass residuals, and leukocyte counts were used to assess sparrow condition. Cadmium, copper, mercury, nickel, and selenium exceeded background concentrations at some sites, but generally were lower than or similar to concentrations found in earlier studies performed prior to the 2009 international wastewater treatment plant upgrade. Concentrations were higher in recaptured birds in 2012 than in 2011 for 7 metals in feathers and 14 metals in blood, suggesting possible bioaccumulation. We found no cascading effects as a result of heavy metal exposure, but did find that heavy metal concentrations were reduced following the 2009 international wastewater treatment plant upgrade.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141072","usgsCitation":"Lester, M.B., and van Riper, C., 2014, Distribution and extent of heavy metal accumulation in Song Sparrows (Melospiza melodia), upper Santa Cruz River watershed, southern Arizona, 2011-12: U.S. Geological Survey Open-File Report 2014-1072, vi, 32 p., https://doi.org/10.3133/ofr20141072.","productDescription":"vi, 32 p.","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-044428","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":285659,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141072.GIF"},{"id":285658,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1072/pdf/ofr2014-1072.pdf"},{"id":285656,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1072/"}],"country":"United States","state":"Arizona","otherGeospatial":"Upper Santa Cruz River Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.1487,31.2486 ], [ -111.1487,31.7001 ], [ -110.3996,31.7001 ], [ -110.3996,31.2486 ], [ -111.1487,31.2486 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517034e4b05569d805a1c9","contributors":{"authors":[{"text":"Lester, Michael B.","contributorId":92170,"corporation":false,"usgs":true,"family":"Lester","given":"Michael","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":492342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":492341,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70100635,"text":"70100635 - 2014 - Mercury in the soil of two contrasting watersheds in the eastern United States","interactions":[],"lastModifiedDate":"2018-11-26T09:37:18","indexId":"70100635","displayToPublicDate":"2014-04-03T15:02:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Mercury in the soil of two contrasting watersheds in the eastern United States","docAbstract":"Soil represents the largest store of mercury (Hg) in terrestrial ecosystems, and further study of the factors associated with soil Hg storage is needed to address concerns about the magnitude and persistence of global environmental Hg bioaccumulation. To address this need, we compared total Hg and methyl Hg concentrations and stores in the soil of different landscapes in two watersheds in different geographic settings with similar and relatively high methyl Hg concentrations in surface waters and biota, Fishing Brook, Adirondack Mountains, New York, and McTier Creek, Coastal Plain, South Carolina. Median total Hg concentrations and stores in organic and mineral soil samples were three-fold greater at Fishing Brook than at McTier Creek. Similarly, median methyl Hg concentrations were about two-fold greater in Fishing Brook soil than in McTier Creek soil, but this difference was significant only for mineral soil samples, and methyl Hg stores were not significantly different among these watersheds. In contrast, the methyl Hg/total Hg ratio was significantly greater at McTier Creek suggesting greater climate-driven methylation efficiency in the Coastal Plain soil than that of the Adirondack Mountains. The Adirondack soil had eight-fold greater soil organic matter than that of the Coastal Plain, consistent with greater total Hg stores in the northern soil, but soil organic matter – total Hg relations differed among the sites. A strong linear relation was evident at McTier Creek (r2 = 0.68; p<0.001), but a linear relation at Fishing Brook was weak (r2 = 0.13; p<0.001) and highly variable across the soil organic matter content range, suggesting excess Hg binding capacity in the Adirondack soil. These results suggest greater total Hg turnover time in Adirondack soil than that of the Coastal Plain, and that future declines in stream water Hg concentrations driven by declines in atmospheric Hg deposition will be more gradual and prolonged in the Adirondacks.","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0086855","usgsCitation":"Burns, D.A., Woodruff, L.G., Bradley, P.M., and Cannon, W.F., 2014, Mercury in the soil of two contrasting watersheds in the eastern United States: PLoS ONE, v. 9, no. 2, 15 p., https://doi.org/10.1371/journal.pone.0086855.","productDescription":"15 p.","numberOfPages":"15","onlineOnly":"Y","ipdsId":"IP-040278","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":473066,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0086855","text":"Publisher Index Page"},{"id":285648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":285555,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0086855"}],"country":"United States","state":"New York;South Carolina","otherGeospatial":"Adirondack Mountains;Fishing Brook;Mctier Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -83.63,31.05 ], [ -83.63,47.04 ], [ -71.24,47.04 ], [ -71.24,31.05 ], [ -83.63,31.05 ] ] ] } } ] }","volume":"9","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-02-14","publicationStatus":"PW","scienceBaseUri":"53517054e4b05569d805a328","contributors":{"authors":[{"text":"Burns, Douglas A. 0000-0001-6516-2869 daburns@usgs.gov","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":1237,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas","email":"daburns@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woodruff, Laurel G. 0000-0002-2514-9923 woodruff@usgs.gov","orcid":"https://orcid.org/0000-0002-2514-9923","contributorId":2224,"corporation":false,"usgs":true,"family":"Woodruff","given":"Laurel","email":"woodruff@usgs.gov","middleInitial":"G.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":492360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492357,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cannon, William F. 0000-0002-2699-8118 wcannon@usgs.gov","orcid":"https://orcid.org/0000-0002-2699-8118","contributorId":1883,"corporation":false,"usgs":true,"family":"Cannon","given":"William","email":"wcannon@usgs.gov","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":492359,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70095679,"text":"ofr20141049 - 2014 - Soils, vegetation, and woody debris data from the 2001 Survey Line fire and a comparable unburned site, Tanana Flats region, Alaska","interactions":[],"lastModifiedDate":"2014-04-02T15:03:24","indexId":"ofr20141049","displayToPublicDate":"2014-04-02T14:56:00","publicationYear":"2014","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":"2014-1049","title":"Soils, vegetation, and woody debris data from the 2001 Survey Line fire and a comparable unburned site, Tanana Flats region, Alaska","docAbstract":"This report describes the collection and processing methodologies for samples obtained at two sites within Interior Alaska: (1) a location within the 2001 Survey Line burn, and (2) an unburned location, selected as a control. In 2002 and 2004 U.S. Geological Survey investigators measured soil properties including, but not limited to, bulk density, volumetric water content, carbon content, and nitrogen content from samples obtained from these sites. Stand properties, such as tree density, the amount of woody debris, and understory vegetation, were also measured and are presented in this report.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141049","issn":"2331-1258","usgsCitation":"Manies, K.L., Harden, J.W., and Holingsworth, T.N., 2014, Soils, vegetation, and woody debris data from the 2001 Survey Line fire and a comparable unburned site, Tanana Flats region, Alaska: U.S. Geological Survey Open-File Report 2014-1049, Report: iii, 20 p.; Tanana soil data, https://doi.org/10.3133/ofr20141049.","productDescription":"Report: iii, 20 p.; Tanana soil data","numberOfPages":"25","temporalStart":"2003-01-01","temporalEnd":"2004-12-31","ipdsId":"IP-044961","costCenters":[{"id":556,"text":"Soil Carbon Research","active":false,"usgs":true}],"links":[{"id":285313,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141049.PNG"},{"id":285311,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1049/pdf/ofr2014-1049.pdf"},{"id":283481,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1049/"},{"id":285312,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1049/downloads/ofr2014-1049_data.zip"}],"country":"United States","state":"Alaska","otherGeospatial":"Tanana Flats;Tanana River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -148.422256,64.63788 ], [ -148.422256,64.710289 ], [ -148.188102,64.710289 ], [ -148.188102,64.63788 ], [ -148.422256,64.63788 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517064e4b05569d805a3c3","contributors":{"authors":[{"text":"Manies, Kristen L. 0000-0003-4941-9657 kmanies@usgs.gov","orcid":"https://orcid.org/0000-0003-4941-9657","contributorId":2136,"corporation":false,"usgs":true,"family":"Manies","given":"Kristen","email":"kmanies@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":491341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harden, Jennifer W. 0000-0002-6570-8259 jharden@usgs.gov","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":1971,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","email":"jharden@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":491340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holingsworth, Teresa N.","contributorId":47290,"corporation":false,"usgs":true,"family":"Holingsworth","given":"Teresa","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":491342,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70100468,"text":"70100468 - 2014 - Decadal surface water quality trends under variable climate, land use, and hydrogeochemical setting in Iowa, USA","interactions":[],"lastModifiedDate":"2018-09-14T15:54:17","indexId":"70100468","displayToPublicDate":"2014-04-02T10:53:00","publicationYear":"2014","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":"Decadal surface water quality trends under variable climate, land use, and hydrogeochemical setting in Iowa, USA","docAbstract":"Understanding how nitrogen fluxes respond to changes in agriculture and climate is important for improving water quality. In the midwestern United States, expansion of corn cropping for ethanol production led to increasing N application rates in the 2000s during a period of extreme variability of annual precipitation. To examine the effects of these changes, surface water quality was analyzed in 10 major Iowa Rivers. Several decades of concentration and flow data were analyzed with a statistical method that provides internally consistent estimates of the concentration history and reveals flow-normalized trends that are independent of year-to-year streamflow variations. Flow-normalized concentrations of nitrate+nitrite-N decreased from 2000 to 2012 in all basins. To evaluate effects of annual discharge and N loading on these trends, multiple conceptual models were developed and calibrated to flow-weighted annual concentrations. The recent declining concentration trends can be attributed to both very high and very low discharge in the 2000s and to the long (e.g., 8 year) subsurface residence times in some basins. Dilution of N and depletion of stored N occurs in years with high discharge. Reduced N transport and increased N storage occurs in low-discharge years. Central Iowa basins showed the greatest reduction in flow-normalized concentrations, likely because of smaller storage volumes and shorter residence times. Effects of land-use changes on the water quality of major Iowa Rivers may not be noticeable for years or decades in peripheral basins of Iowa, and may be obscured in the central basins where extreme flows strongly affect annual concentration trends.","language":"English","publisher":"Wiley","doi":"10.1002/2013WR014829","usgsCitation":"Green, C.T., Bekins, B.A., Kalkhoff, S.J., Hirsch, R.M., Liao, L., and Barnes, K., 2014, Decadal surface water quality trends under variable climate, land use, and hydrogeochemical setting in Iowa, USA: Water Resources Research, v. 50, no. 3, p. 2425-2443, https://doi.org/10.1002/2013WR014829.","productDescription":"19 p.","startPage":"2425","endPage":"2443","numberOfPages":"19","onlineOnly":"Y","ipdsId":"IP-052067","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":285296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":285264,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/2013WR014829"}],"country":"United States","state":"Iowa","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96.6395,40.3754 ], [ -96.6395,43.5012 ], [ -90.1426,43.5012 ], [ -90.1426,40.3754 ], [ -96.6395,40.3754 ] ] ] } } ] }","volume":"50","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-03-19","publicationStatus":"PW","scienceBaseUri":"53517032e4b05569d805a1af","contributors":{"authors":[{"text":"Green, Christopher T. 0000-0002-6480-8194 ctgreen@usgs.gov","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":1343,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"ctgreen@usgs.gov","middleInitial":"T.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":492236,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bekins, Barbara A. 0000-0002-1411-6018 babekins@usgs.gov","orcid":"https://orcid.org/0000-0002-1411-6018","contributorId":1348,"corporation":false,"usgs":true,"family":"Bekins","given":"Barbara","email":"babekins@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":492237,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kalkhoff, Stephen J. 0000-0003-4110-1716 sjkalkho@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-1716","contributorId":1731,"corporation":false,"usgs":true,"family":"Kalkhoff","given":"Stephen","email":"sjkalkho@usgs.gov","middleInitial":"J.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492238,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37316,"text":"WMA - 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The brine contamination affects 15–37 billion gallons of groundwater. Brine contamination in the shallow aquifers east of the Poplar River generally moves to the southwest toward the river and then southward in the Poplar River valley. The likely source of brine contamination in the shallow aquifers is brine that is produced with crude oil in the East Poplar oil field study area. Brine contamination has not only affected the water quality from privately owned wells in and near the East Poplar oil field, but also the city of Poplar’s public water-supply wells.
\nThree water-quality types characterize water in the shallow aquifers; a fourth water-quality type in the study area characterizes the brine. Type 1 is uncontaminated water that is suitable for most domestic purposes and typically contains sodium bicarbonate and sodium/magnesium sulfate as the dominant ions. Type 2 is moderately contaminated water that is suitable for some domestic purposes, but not used for drinking water, and typically contains sodium and chloride as the dominant ions. Type 3 is considerably contaminated water that is unsuitable for any domestic purpose and always contains sodium and chloride as the dominant ions. Type 3 quality of water in the shallow aquifers is similar to Type 4, which is the brine that is produced with crude oil.
\n
\n
Electromagnetic apparent conductivity data were collected in the 106 square-mile area and used to determine extent of brine contamination. These data were collected and interpreted in conjunction with water-quality data collected through 2009 to delineate brine plumes in the shallow aquifers. Monitoring wells subsequently were drilled in some areas without existing water wells to confirm most of the delineated brine plumes; however, several possible plumes do not contain either existing water wells or monitoring wells. Analysis of groundwater samples from wells confirms the presence of 12.1 square miles of contamination, as much as 1.7 square miles of which is considerably contaminated (Type 3). Electromagnetic apparent conductivity data in areas with no wells delineate an additional 5.8 square miles of possible contamination, 2.1 square miles of which might be considerably contaminated (Type 3). Storage-tank facilities, oil wells, brine-injection wells, pipelines, and pits are likely sources of brine in the study area. It is not possible to identify discrete oil-related features as likely sources of brine plumes because several features commonly are co-located. During the latter half of the twentieth century, many brine plumes migrated beyond the immediate source area and likely mix together in modern and ancestral Poplar River valley subareas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145024","collaboration":"Prepared in cooperation with the Fort Peck Tribes Office of Environmental Protection","usgsCitation":"Thamke, J., and Smith, B.D., 2014, Delineation of brine contamination in and near the East Poplar oil field, Fort Peck Indian Reservation, northeastern Montana, 2004-09: U.S. Geological Survey Scientific Investigations Report 2014-5024, Report: viii, 40 p.; Appendix, https://doi.org/10.3133/sir20145024.","productDescription":"Report: viii, 40 p.; Appendix","onlineOnly":"Y","ipdsId":"IP-009092","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":285271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145024.jpg"},{"id":285268,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5024/pdf/sir2014-5024.pdf"},{"id":285269,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5024/"},{"id":285270,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5024/appendix"}],"datum":"NAD 27","country":"United States","state":"Montana","city":"Fort Peck","otherGeospatial":"Fort Peck Indian Reservation","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -107.0,48.0 ], [ -107.0,49.0 ], [ -105.0,49.0 ], [ -105.0,48.0 ], [ -107.0,48.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517032e4b05569d805a1b3","contributors":{"authors":[{"text":"Thamke, Joanna N. 0000-0002-6917-1946 jothamke@usgs.gov","orcid":"https://orcid.org/0000-0002-6917-1946","contributorId":1012,"corporation":false,"usgs":true,"family":"Thamke","given":"Joanna N.","email":"jothamke@usgs.gov","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490807,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Bruce D. 0000-0002-1643-2997 bsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-1643-2997","contributorId":845,"corporation":false,"usgs":true,"family":"Smith","given":"Bruce","email":"bsmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":490806,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70168565,"text":"70168565 - 2014 - Understanding thermodynamic relationships and geochemical mass balances from catchment to coast: A tribute to the life and career of Owen P. Bricker III","interactions":[],"lastModifiedDate":"2018-02-21T17:53:58","indexId":"70168565","displayToPublicDate":"2014-04-01T16:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":866,"text":"Aquatic Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Understanding thermodynamic relationships and geochemical mass balances from catchment to coast: A tribute to the life and career of Owen P. Bricker III","docAbstract":"This special volume of aquatic geochemistry is dedicated to the memory of Owen Peterson Bricker III (1936–2011) and serves as a tribute to his life and career. Owen had a distinguished and productive research career in both academics at Johns Hopkins University (Fig. 1) and as a public servant with the Maryland Geological Survey, the US Environmental Protection Agency, and the US Geological Survey. He was a pioneer and leader in aqueous geochemistry, who applied a study approach that quantified mineral weathering reactions and equilibrium thermodynamic relations to better understand the chemical evolution of stream water in small watersheds. He will be especially remembered for his efforts to establish rigorous field studies in small catchments around the United States as a means of quantifying the sources of acid-neutralizing capacity that affect the chemical status and biological health of natural waters.
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The articles were solicited from researchers who participated in the second summer specialty conference on this topic, organized by the American Water Resources Association. The title of the conference was “CECs in Water Resources II: Research, Engineering and Community Action,” and the conference, as well as the articles in this featured collection, focus on a better and more comprehensive understanding of these contaminants. The conference was held in Denver, Colorado, on June 25-27, 2012, and approximately 125 conference attendees participated in an interdisciplinary forum of more than 75 presentations including keynote or plenary presentations by Dana Kolpin, Jorg Drewes, Heiko Schoenfuss, Chris Metcalfe, Vicki Blazer, and Tyrone Hayes. The first conference was held in 2007 and also produced a featured collection of articles (Battaglin and Kolpin, 2009).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of the American Water Resources Association","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Water Resources Association","publisherLocation":"Herndon, VA","doi":"10.1111/jawr.12176","usgsCitation":"Battaglin, W.A., and Kolok, A., 2014, Featured collection introduction: contaminants of emerging concern II: Journal of the American Water Resources Association, v. 50, no. 2, p. 261-265, https://doi.org/10.1111/jawr.12176.","productDescription":"5 p.","startPage":"261","endPage":"265","numberOfPages":"5","ipdsId":"IP-053166","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":290736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":290735,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/jawr.12176"}],"volume":"50","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f124e4b0bc0bec09fbb9","contributors":{"editors":[{"text":"Battaglin, William","contributorId":112783,"corporation":false,"usgs":true,"family":"Battaglin","given":"William","affiliations":[],"preferred":false,"id":509916,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Kolok, Alan","contributorId":76660,"corporation":false,"usgs":true,"family":"Kolok","given":"Alan","email":"","affiliations":[],"preferred":false,"id":509915,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Battaglin, William A. 0000-0001-7287-7096 wbattagl@usgs.gov","orcid":"https://orcid.org/0000-0001-7287-7096","contributorId":1527,"corporation":false,"usgs":true,"family":"Battaglin","given":"William","email":"wbattagl@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":496035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolok, Alan","contributorId":76660,"corporation":false,"usgs":true,"family":"Kolok","given":"Alan","email":"","affiliations":[],"preferred":false,"id":496036,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70100456,"text":"fs20143020 - 2014 - The 3D Elevation Program: summary for Missouri","interactions":[],"lastModifiedDate":"2016-08-17T15:45:20","indexId":"fs20143020","displayToPublicDate":"2014-04-01T15:22:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3020","title":"The 3D Elevation Program: summary for Missouri","docAbstract":"Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. 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\nThe National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.
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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517067e4b05569d805a3e8","contributors":{"authors":[{"text":"Carswell, William J. Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":492228,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70103042,"text":"70103042 - 2014 - Conservation and management of fisheries and aquatic communities in Great Lakes connecting channels","interactions":[],"lastModifiedDate":"2014-06-19T09:21:11","indexId":"70103042","displayToPublicDate":"2014-04-01T15:21:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Conservation and management of fisheries and aquatic communities in Great Lakes connecting channels","docAbstract":"The North American Laurentian Great Lakes are linked by a unique series of riverine and lacustrine waters known as the Great Lakes connecting channels that are as integral to the basin's ecology and economies as the lakes themselves. The St. Marys River (SMR) is the northernmost channel and flows from Lake Superior to Lake Huron. Waters from the upper Great Lakes (Lakes Superior, Michigan, and Huron) empty from Lake Huron via the St. Clair–Detroit River system (SCDRS, also known as the Huron–Erie Corridor) into Lake Erie. The SCDRS is composed of the St. Clair River, Lake St. Clair, and the Detroit River. The Niagara River (NR) serves as the outflow from Lake Erie into Lake Ontario. The NR above Niagara Falls is bisected by Grand Island and contains several other islands and man-made embayments whereas the NR below the falls is more linear. The outflow from Lake Ontario, representing the natural outlet of all the Great Lakes, is the St. Lawrence River (SLR) which empties into the Gulf of St. Lawrence in the northwest Atlantic Ocean.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Great Lakes Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2014.03.003","usgsCitation":"Roseman, E., Thompson, P., Farrell, J.M., Mandrak, N.E., and Stepien, C.A., 2014, Conservation and management of fisheries and aquatic communities in Great Lakes connecting channels: Journal of Great Lakes Research, v. 40, p. 1-6, https://doi.org/10.1016/j.jglr.2014.03.003.","productDescription":"6 p.","startPage":"1","endPage":"6","numberOfPages":"6","ipdsId":"IP-054283","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":286741,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286740,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jglr.2014.03.003"}],"country":"Canada;United States","otherGeospatial":"Great Lakes","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.11,41.4 ], [ -92.11,48.85 ], [ -76.3,48.85 ], [ -76.3,41.4 ], [ -92.11,41.4 ] ] ] } } ] }","volume":"40","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"535f786ae4b078dca33ae34e","contributors":{"authors":[{"text":"Roseman, Edward F.","contributorId":100334,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[],"preferred":false,"id":493125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Patricia A. pathompson@usgs.gov","contributorId":5249,"corporation":false,"usgs":true,"family":"Thompson","given":"Patricia A.","email":"pathompson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":493121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Farrell, John M.","contributorId":12368,"corporation":false,"usgs":true,"family":"Farrell","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":493122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mandrak, Nicholas E.","contributorId":65386,"corporation":false,"usgs":true,"family":"Mandrak","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":493124,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stepien, Carol A.","contributorId":52875,"corporation":false,"usgs":true,"family":"Stepien","given":"Carol","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":493123,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70127912,"text":"70127912 - 2014 - Risk of predation and weather events affect nest site selection by sympatric Pacific (Gavia pacifica) and Yellow-billed (Gavia adamsii) loons in Arctic habitats","interactions":[],"lastModifiedDate":"2014-10-02T14:59:36","indexId":"70127912","displayToPublicDate":"2014-04-01T14:48:55","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Risk of predation and weather events affect nest site selection by sympatric Pacific (Gavia pacifica) and Yellow-billed (Gavia adamsii) loons in Arctic habitats","docAbstract":"Pacific (Gavia pacifica) and Yellow-billed (G. adamsii) loons nest sympatrically in Arctic regions. These related species likely face similar constraints and requirements for nesting success; therefore, use of similar habitats and direct competition for nesting habitat is likely. Both of these loon species must select a breeding lake that provides suitable habitat for nesting and raising chicks; however, characteristics of nest site selection by either species on interior Arctic lakes remains poorly understood. Here, logistic regression was used to compare structural and habitat characteristics of all loon nest locations with random points from lakes on the interior Arctic Coastal Plain, Alaska. Results suggest that both loon species select nest sites to avoid predation and exposure to waves and shifting ice. Loon nest sites were more likely to be on islands and peninsulas (odds ratio = 16.13, 95% CI = 4.64–56.16) than mainland shoreline, which may help loons avoid terrestrial predators. Further, nest sites had a higher degree of visibility (mean degrees of visibility to 100 and 200 m) of approaching predators than random points (odds ratio = 2.57, 95% CI = 1.22–5.39). Nests were sheltered from exposure, having lower odds of being exposed to prevailing winds (odds ratio = 0.34, 95% CI = 0.13–0.92) and lower odds of having high fetch values (odds ratio = 0.46, 95% CI = 0.22–0.96). Differences between Pacific and Yellow-billed loon nesting sites were subtle, suggesting that both species have similar general nest site requirements. However, Yellow-billed Loons nested at slightly higher elevations and were more likely to nest on peninsulas than Pacific Loons. Pacific Loons constructed built up nests from mud and vegetation, potentially in response to limited access to suitable shoreline due to other territorial loons. Results suggest that land managers wishing to protect habitats for these species should focus on lakes with islands as well as shorelines sheltered from exposure to prevailing wind and ice patterns.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Waterbirds","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.037.sp104","usgsCitation":"Haynes, T.B., Schmutz, J.A., Lindberg, M., and Rosenberger, A.E., 2014, Risk of predation and weather events affect nest site selection by sympatric Pacific (Gavia pacifica) and Yellow-billed (Gavia adamsii) loons in Arctic habitats: Waterbirds, v. 37, p. 16-25, https://doi.org/10.1675/063.037.sp104.","productDescription":"10 p.","startPage":"16","endPage":"25","numberOfPages":"10","ipdsId":"IP-045098","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":294875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294845,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1675/063.037.sp104"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic Coastal Plain","volume":"37","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542e697ee4b092f17df5aa1e","contributors":{"authors":[{"text":"Haynes, Trevor B.","contributorId":100302,"corporation":false,"usgs":false,"family":"Haynes","given":"Trevor","email":"","middleInitial":"B.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":502668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":502665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lindberg, Mark S.","contributorId":89466,"corporation":false,"usgs":false,"family":"Lindberg","given":"Mark S.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":502667,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":502666,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70101339,"text":"70101339 - 2014 - A survey of benthic sediment contaminants in reaches of the Columbia River Estuary based on channel sedimentation characteristics","interactions":[],"lastModifiedDate":"2017-01-12T11:30:56","indexId":"70101339","displayToPublicDate":"2014-04-01T13:43:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"A survey of benthic sediment contaminants in reaches of the Columbia River Estuary based on channel sedimentation characteristics","docAbstract":"While previous studies have documented contaminants in fish, sediments, water, and wildlife, few specifics are known about the spatial distribution of contaminants in the Columbia River Estuary (CRE). Our study goal was to characterize sediment contaminant detections and concentrations in reaches of the CRE that were concurrently being sampled to assess contaminants in water, invertebrates, fish, and osprey (Pandion haliaetus) eggs. Our objectives were to develop a survey design based on sedimentation characteristics and then assess whether sediment grain size, total organic carbon (TOC), and contaminant concentrations and detections varied between areas with different sedimentation characteristics. We used a sediment transport model to predict sedimentation characteristics of three 16 km river reaches in the CRE. We then compartmentalized the modeled change in bed mass after a two week simulation to define sampling strata with depositional, stable, or erosional conditions. We collected and analyzed bottom sediments to assess whether substrate composition, organic matter composition, and contaminant concentrations and detections varied among strata within and between the reaches. We observed differences in grain size fractions between strata within and between reaches. We found that the fine sediment fraction was positively correlated with TOC. Contaminant concentrations were statistically different between depositional vs. erosional strata for the industrial compounds, personal care products and polycyclic aromatic hydrocarbons class (Indus–PCP–PAH). We also observed significant differences between strata in the number of detections of Indus–PCP–PAH (depositional vs. erosional; stable vs. erosional) and for the flame retardants, polychlorinated biphenyls, and pesticides class (depositional vs. erosional, depositional vs. stable). When we estimated mean contaminant concentrations by reach, we observed higher contaminant concentrations in the furthest downstream reach with a decreasing trend in the two upstream reaches. Contaminant survey designs that account for sedimentation characteristics could increase the probability that sampling is allocated to areas likely to be contaminated.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2014.03.013","usgsCitation":"Counihan, T.D., Waite, I.R., Nilsen, E.B., Hardiman, J.M., Elias, E., Gelfenbaum, G., and Zaugg, S.D., 2014, A survey of benthic sediment contaminants in reaches of the Columbia River Estuary based on channel sedimentation characteristics: Science of the Total Environment, v. 484, p. 331-343, https://doi.org/10.1016/j.scitotenv.2014.03.013.","productDescription":"13 p.","startPage":"331","endPage":"343","ipdsId":"IP-046003","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":473069,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.escholarship.org/uc/item/1np8s2bf","text":"External Repository"},{"id":286211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"state":"Oregon;Washington","otherGeospatial":"Columbia River Estuary","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.79,41.99 ], [ -124.79,49.0 ], [ -116.46,49.0 ], [ -116.46,41.99 ], [ -124.79,41.99 ] ] ] } } ] }","volume":"484","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53516ef9e4b05569d8059f37","chorus":{"doi":"10.1016/j.scitotenv.2014.03.013","url":"http://dx.doi.org/10.1016/j.scitotenv.2014.03.013","publisher":"Elsevier BV","authors":"Counihan Timothy D., Waite Ian R., Nilsen Elena B., Hardiman Jill M., Elias Edwin, Gelfenbaum Guy, Zaugg Steven D.","journalName":"Science of The Total Environment","publicationDate":"6/2014","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Counihan, Timothy D. 0000-0003-4967-6514 tcounihan@usgs.gov","orcid":"https://orcid.org/0000-0003-4967-6514","contributorId":4211,"corporation":false,"usgs":true,"family":"Counihan","given":"Timothy","email":"tcounihan@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":492665,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waite, Ian R. 0000-0003-1681-6955 iwaite@usgs.gov","orcid":"https://orcid.org/0000-0003-1681-6955","contributorId":616,"corporation":false,"usgs":true,"family":"Waite","given":"Ian","email":"iwaite@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nilsen, Elena B. 0000-0002-0104-6321 enilsen@usgs.gov","orcid":"https://orcid.org/0000-0002-0104-6321","contributorId":923,"corporation":false,"usgs":true,"family":"Nilsen","given":"Elena","email":"enilsen@usgs.gov","middleInitial":"B.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492663,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hardiman, Jill M. 0000-0002-3661-9695 jhardiman@usgs.gov","orcid":"https://orcid.org/0000-0002-3661-9695","contributorId":2672,"corporation":false,"usgs":true,"family":"Hardiman","given":"Jill","email":"jhardiman@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":492664,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Elias, Edwin","contributorId":50615,"corporation":false,"usgs":true,"family":"Elias","given":"Edwin","affiliations":[],"preferred":false,"id":492666,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gelfenbaum, Guy","contributorId":79844,"corporation":false,"usgs":true,"family":"Gelfenbaum","given":"Guy","affiliations":[],"preferred":false,"id":492667,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zaugg, Steven D. sdzaugg@usgs.gov","contributorId":768,"corporation":false,"usgs":true,"family":"Zaugg","given":"Steven","email":"sdzaugg@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":492662,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70048664,"text":"70048664 - 2014 - Stream macroinvertebrate response models for bioassessment metrics: addressing the issue of spatial scale","interactions":[],"lastModifiedDate":"2018-09-27T10:51:00","indexId":"70048664","displayToPublicDate":"2014-04-01T13:36:17","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Stream macroinvertebrate response models for bioassessment metrics: addressing the issue of spatial scale","docAbstract":"We developed independent predictive disturbance models for a full regional data set and four individual ecoregions (Full Region vs. Individual Ecoregion models) to evaluate effects of spatial scale on the assessment of human landscape modification, on predicted response of stream biota, and the effect of other possible confounding factors, such as watershed size and elevation, on model performance. We selected macroinvertebrate sampling sites for model development (n = 591) and validation (n = 467) that met strict screening criteria from four proximal ecoregions in the northeastern U.S.: North Central Appalachians, Ridge and Valley, Northeastern Highlands, and Northern Piedmont. Models were developed using boosted regression tree (BRT) techniques for four macroinvertebrate metrics; results were compared among ecoregions and metrics. Comparing within a region but across the four macroinvertebrate metrics, the average richness of tolerant taxa (RichTOL) had the highest R2 for BRT models. Across the four metrics, final BRT models had between four and seven explanatory variables and always included a variable related to urbanization (e.g., population density, percent urban, or percent manmade channels), and either a measure of hydrologic runoff (e.g., minimum April, average December, or maximum monthly runoff) and(or) a natural landscape factor (e.g., riparian slope, precipitation, and elevation), or a measure of riparian disturbance. Contrary to our expectations, Full Region models explained nearly as much variance in the macroinvertebrate data as Individual Ecoregion models, and taking into account watershed size or elevation did not appear to improve model performance. As a result, it may be advantageous for bioassessment programs to develop large regional models as a preliminary assessment of overall disturbance conditions as long as the range in natural landscape variability is not excessive.","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0090944","usgsCitation":"White, I.R., Kennen, J., May, J., Brown, L.R., Cuffney, T.F., Jones, K.A., and Orlando, J., 2014, Stream macroinvertebrate response models for bioassessment metrics: addressing the issue of spatial scale: PLoS ONE, v. 9, no. 3, p. 1-21, https://doi.org/10.1371/journal.pone.0090944.","productDescription":"e90944; 21 p.","startPage":"1","endPage":"21","ipdsId":"IP-045602","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":473070,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0090944","text":"Publisher Index Page"},{"id":287148,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0090944"},{"id":287150,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"North Central Appalachians;Northeastern Highlands;Northern Piedmont;Ridge And Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80,3.1352777777777776 ], [ -80,0.0011111111111111111 ], [ -72,0.0011111111111111111 ], [ -72,3.1352777777777776 ], [ -80,3.1352777777777776 ] ] ] } } ] }","volume":"9","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-03-27","publicationStatus":"PW","scienceBaseUri":"53749079e4b0870f4d23cfff","contributors":{"authors":[{"text":"White, Ian R.","contributorId":21862,"corporation":false,"usgs":true,"family":"White","given":"Ian","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":485345,"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":485341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"May, Jason T. 0000-0002-5699-2112","orcid":"https://orcid.org/0000-0002-5699-2112","contributorId":14791,"corporation":false,"usgs":true,"family":"May","given":"Jason T.","affiliations":[],"preferred":false,"id":485344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485343,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cuffney, Thomas F. 0000-0003-1164-5560 tcuffney@usgs.gov","orcid":"https://orcid.org/0000-0003-1164-5560","contributorId":517,"corporation":false,"usgs":true,"family":"Cuffney","given":"Thomas","email":"tcuffney@usgs.gov","middleInitial":"F.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485340,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jones, Kimberly A. kjones@usgs.gov","contributorId":937,"corporation":false,"usgs":true,"family":"Jones","given":"Kimberly","email":"kjones@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":485342,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Orlando, James L. 0000-0002-0099-7221","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":95954,"corporation":false,"usgs":true,"family":"Orlando","given":"James L.","affiliations":[],"preferred":false,"id":485346,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70074259,"text":"sir20145010 - 2014 - Equations for estimating selected streamflow statistics in Rhode Island","interactions":[],"lastModifiedDate":"2016-08-19T16:45:20","indexId":"sir20145010","displayToPublicDate":"2014-04-01T13:28:00","publicationYear":"2014","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":"2014-5010","title":"Equations for estimating selected streamflow statistics in Rhode Island","docAbstract":"Regional regression equations were developed for estimating selected natural—unaffected by alteration—streamflows of specific flow durations and low-flow frequency statistics for ungaged stream sites in Rhode Island. Selected at-site streamflow statistics are provided for 41 long-term streamgages, 21 short-term streamgages, and 135 partial-record stations in Rhode Island, eastern Connecticut, and southeastern and south-central Massachusetts. The regression equations for estimating selected streamflow statistics and the at-site statistics estimated for each of the 197 sites may be used by Federal, State, and local water managers in addressing water issues in and near Rhode Island.
\nMultiple and simple linear regression equations were developed to estimate the 99-, 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, 50-, 40-, 30-, 25-, 20-, 15-, 10-, 5-, 2-, and 1-percent flow durations and the 7Q2 (7-day, 2-year) and 7Q10 (7-day, 10-year) low-flow-frequency statistics. An additional 49 selected statistics, for which regression equations were not developed, also were estimated for the long- and short-term streamgages and partial-record stations for flow durations between the 99.99 and 0.01 percent and for the mean annual, mean monthly, and median monthly streamflows. A total of 70 selected streamflow statistics were estimated for 41 long-term streamgages, 21 short-term streamgages, and 135 partial-record stations in and near Rhode Island. Estimates of the long-term streamflow statistics for the 21 short-term streamgages and 135 partial-record stations were developed by the Maintenance of Variance Extension, type 1 (MOVE.1), record-extension technique.
\nThe equations used to estimate selected streamflow statistics were developed by relating the 19 flow-duration and 2 low-flow-frequency statistics to 31 different basin characteristics (physical, land-cover, and climatic) at the 41 long-term and 19 of 21 short-term streamgages (a total of 60 streamgages) in and near Rhode Island. The 135 partial-record stations were not used in the regression analyses. The regression analyses were done by using a user-weighted least-squares technique in the weighted-multiple-linear regression program for the 90- to 1-percent flow-duration statistics. For the 99-, 98-, and 95-percent flow durations and the 7Q2 and 7Q10 statistics, left-censored regression analyses were used to account for zero flows at a few streamgages. The regression analyses determined that two basin characteristics—drainage area and stream density—were the only significant explanatory variables for 16 of the 19 flow-duration and the 2 low-flow regression equations. For the 10-, 15-, and 20-percent flow-duration regression equations, drainage area was the only significant explanatory variable. The standard error of the estimate for the 21 regression equations ranged from 17.58 to 141.83 percent. The 99- to 85-percent flow durations and the low-flow statistics 7Q2 and 7Q10 had the highest standard errors of the estimate, ranging from 48.68 to 141.83 percent. The standard error of the estimate for the medium- to high-flow statistics—the 80- to 1-percent flow durations—ranged from 17.58 to 37.65 percent, with the standard errors for the 60- to 1-percent flow durations all being less than about 21 percent. Data also are provided to allow the user to calculate the 90-percent prediction intervals for the 21 streamflow statistics.
\nThe equations, which are based on data from streams with little to no flow alterations, will provide an estimate of the natural flows for a selected site. They will not estimate flows for altered sites with dams, surface-water withdrawals, groundwater withdrawals (pumping wells), diversions, and wastewater discharges. If the equations are used to estimate streamflow statistics for altered sites, the user should adjust the flow estimates for the alterations. The regression equations should be used only for ungaged sites with drainage areas between 0.52 and 294 square miles and stream densities between 0.94 and 3.49 miles per square mile; these are the ranges of the explanatory variables in the equations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145010","collaboration":"Prepared in cooperation with the Rhode Island Water Resources Board","usgsCitation":"Bent, G.C., Steeves, P.A., and Waite, A.M., 2014, Equations for estimating selected streamflow statistics in Rhode Island: U.S. Geological Survey Scientific Investigations Report 2014-5010, Report: viii, 65 p.; Tables: 5 Excel files, https://doi.org/10.3133/sir20145010.","productDescription":"Report: viii, 65 p.; Tables: 5 Excel files","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-046041","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":285231,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145010.jpg"},{"id":285224,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5010/pdf/sir2014-5010.pdf","text":"Report","size":"13 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eruptions in Yellowstone National Park by earthquakes, earth tides, and weather","docAbstract":"We analyze intervals between eruptions (IBEs) data acquired between 2001 and 2011 at Daisy and Old Faithful geysers in Yellowstone National Park. We focus our statistical analysis on the response of these geysers to stress perturbations from within the solid earth (earthquakes and earth tides) and from weather (air pressure and temperature, precipitation, and wind). We conclude that (1) the IBEs of these geysers are insensitive to periodic stresses induced by solid earth tides and barometric pressure variations; (2) Daisy (pool geyser) IBEs lengthen by evaporation and heat loss in response to large wind storms and cold air; and (3) Old Faithful (cone geyser) IBEs are not modulated by air temperature and pressure variations, wind, and precipitation, suggesting that the subsurface water column is decoupled from the atmosphere. Dynamic stress changes of 0.1−0.2 MPa resulting from the 2002 M-7.9 Denali, Alaska, earthquake surface waves caused a statistically significant shortening of Daisy geyser's IBEs. Stresses induced by other large global earthquakes during the study period were at least an order of magnitude smaller. In contrast, dynamic stresses of >0.5 MPa from three large regional earthquakes in 1959, 1975, and 1983 caused lengthening of Old Faithful's IBEs. We infer that most subannual geyser IBE variability is dominated by internal processes and interaction with other geysers. The results of this study provide quantitative bounds on the sensitivity of hydrothermal systems to external stress perturbations and have implications for studying the triggering and modulation of volcanic eruptions by external forces.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research B: Solid Earth","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/2013JB010803","usgsCitation":"Hurwitz, S., Sohn, R.A., Luttrell, K.M., and Manga, M., 2014, Triggering and modulation of geyser eruptions in Yellowstone National Park by earthquakes, earth tides, and weather: Journal of Geophysical Research B: Solid Earth, v. 119, no. 3, p. 1718-1737, https://doi.org/10.1002/2013JB010803.","productDescription":"20 p.","startPage":"1718","endPage":"1737","ipdsId":"IP-052228","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":473071,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2013jb010803","text":"Publisher Index Page"},{"id":287961,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111,43.5 ], [ -111,45.5 ], [ -110,45.5 ], [ -110,43.5 ], [ -111,43.5 ] ] ] } } ] }","volume":"119","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-03-05","publicationStatus":"PW","scienceBaseUri":"53ae787ce4b0abf75cf2d705","contributors":{"authors":[{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":494214,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sohn, Robert A.","contributorId":37258,"corporation":false,"usgs":true,"family":"Sohn","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":494215,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luttrell, Karen M. kluttrell@usgs.gov","contributorId":3850,"corporation":false,"usgs":true,"family":"Luttrell","given":"Karen","email":"kluttrell@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":494217,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manga, Michael","contributorId":66559,"corporation":false,"usgs":true,"family":"Manga","given":"Michael","affiliations":[],"preferred":false,"id":494216,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159714,"text":"70159714 - 2014 - Climate change impacts on the temperature and magnitude of groundwater discharge from shallow, unconfined aquifers","interactions":[],"lastModifiedDate":"2015-11-18T10:51:03","indexId":"70159714","displayToPublicDate":"2014-04-01T12:00:00","publicationYear":"2014","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":"Climate change impacts on the temperature and magnitude of groundwater discharge from shallow, unconfined aquifers","docAbstract":"Cold groundwater discharge to streams and rivers can provide critical thermal refuge for threatened salmonids and other aquatic species during warm summer periods. Climate change may influence groundwater temperature and flow rates, which may in turn impact riverine ecosystems. This study evaluates the potential impact of climate change on the timing, magnitude, and temperature of groundwater discharge from small, unconfined aquifers that undergo seasonal freezing and thawing. Seven downscaled climate scenarios for 2046–2065 were utilized to drive surficial water and energy balance models (HELP3 and ForHyM2) to obtain future projections for daily ground surface temperature and groundwater recharge. These future surface conditions were then applied as boundary conditions to drive subsurface simulations of variably saturated groundwater flow and energy transport. The subsurface simulations were performed with the U.S. Geological Survey finite element model SUTRA that was recently modified to include the dynamic freeze-thaw process. The SUTRA simulations indicate a potential rise in the magnitude (up to 34%) and temperature (up to 3.6°C) of groundwater discharge to the adjacent river during the summer months due to projected increases in air temperature and precipitation. The thermal response of groundwater to climate change is shown to be strongly dependent on the aquifer dimensions. Thus, the simulations demonstrate that the thermal sensitivity of aquifers and baseflow-dominated streams to decadal climate change may be more complex than previously thought. Furthermore, the results indicate that the probability of exceeding critical temperature thresholds within groundwater-sourced thermal refugia may significantly increase under the most extreme climate scenarios.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2013WR014588","usgsCitation":"Kurylyk, B.L., MacQuarrie, K.T., and Voss, C.I., 2014, Climate change impacts on the temperature and magnitude of groundwater discharge from shallow, unconfined aquifers: Water Resources Research, v. 50, no. 4, p. 3253-3274, https://doi.org/10.1002/2013WR014588.","productDescription":"22 p.","startPage":"3253","endPage":"3274","numberOfPages":"22","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053810","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":311487,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-04-15","publicationStatus":"PW","scienceBaseUri":"564daf45e4b0112df6c62df2","contributors":{"authors":[{"text":"Kurylyk, Barret L.","contributorId":78262,"corporation":false,"usgs":true,"family":"Kurylyk","given":"Barret","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":580168,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"MacQuarrie, Kerry T.B","contributorId":149960,"corporation":false,"usgs":false,"family":"MacQuarrie","given":"Kerry","email":"","middleInitial":"T.B","affiliations":[{"id":17865,"text":"Dept of Civil Engineering & Canadian Rivers Inst. Univ of New Brunswick","active":true,"usgs":false}],"preferred":false,"id":580169,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":580167,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}