{"pageNumber":"361","pageRowStart":"9000","pageSize":"25","recordCount":16506,"records":[{"id":70023103,"text":"70023103 - 2000 - Metal exposure in a benthic macroinvertebrate, Hydropsyche californica, related to mine drainage in the Sacramento River","interactions":[],"lastModifiedDate":"2018-12-07T05:51:27","indexId":"70023103","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Metal exposure in a benthic macroinvertebrate, <i>Hydropsyche californica</i>, related to mine drainage in the Sacramento River","title":"Metal exposure in a benthic macroinvertebrate, Hydropsyche californica, related to mine drainage in the Sacramento River","docAbstract":"<p><span>A biomonitoring technique was employed to complement studies of metal transport in the upper Sacramento River affected by acid mine drainage. Metals (Al, Cd, Cu, Fe, Hg, Pb, and Zn) were determined in a resident invertebrate,&nbsp;</span><i>Hydropsyche californica</i><span><span>&nbsp;</span>(Insecta: Trichoptera), and streambed sediments (&lt;62 µm) to assess metal contamination within a 111-km section of the river downstream of the mining area. Metals in<span>&nbsp;</span></span><i>H. californica</i><span><span>&nbsp;</span>also were interpreted to be broadly indicative of metal exposure in fish. Total Hg was determined in the whole body of the insect, whereas Al, Cd, Cu, Fe, Pb, and Zn were additionally separated into operationally defined cytosolic (used as an indicator of exposure to bioavailable metal) and particulate fractions. Total concentrations of Cd, Cu, Hg, Pb, and Zn in sediments were consistent with documented upstream sources of acid mine drainage. Metal distribution patterns in<span>&nbsp;</span></span><i>H. californica</i><span><span>&nbsp;</span>and sediments were generally consistent for Cd, Cu, and Pb but inconsistent for Hg and Zn. Concentrations in<span>&nbsp;</span></span><i>H. californica</i><span><span>&nbsp;</span>indicated that bioavailable Cd, Cu, Pb, and Zn was transported at least 120 km downstream of the mine sources. Zinc in<span>&nbsp;</span></span><i>H. californica</i><span><span>&nbsp;</span>was elevated, but unlike sediments, did not decrease downstream. Mercury in<span>&nbsp;</span></span><i>H. californica</i><span><span>&nbsp;</span>was not elevated.</span></p>","language":"English","publisher":"NRC Research Press","doi":"10.1139/f99-260","usgsCitation":"Cain, D.J., Carter, J.L., Fend, S.V., Luoma, S.N., Alpers, C.N., and Taylor, H.E., 2000, Metal exposure in a benthic macroinvertebrate, Hydropsyche californica, related to mine drainage in the Sacramento River: Canadian Journal of Fisheries and Aquatic Sciences, v. 57, no. 2, p. 380-390, https://doi.org/10.1139/f99-260.","productDescription":"11 p.","startPage":"380","endPage":"390","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":233625,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River","volume":"57","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a547de4b0c8380cd6cfbf","contributors":{"authors":[{"text":"Cain, Daniel J. 0000-0002-3443-0493 djcain@usgs.gov","orcid":"https://orcid.org/0000-0002-3443-0493","contributorId":1784,"corporation":false,"usgs":true,"family":"Cain","given":"Daniel","email":"djcain@usgs.gov","middleInitial":"J.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":396177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, James L. 0000-0002-0104-9776 jlcarter@usgs.gov","orcid":"https://orcid.org/0000-0002-0104-9776","contributorId":3278,"corporation":false,"usgs":true,"family":"Carter","given":"James","email":"jlcarter@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":396175,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fend, Steven V. 0000-0002-4638-6602 svfend@usgs.gov","orcid":"https://orcid.org/0000-0002-4638-6602","contributorId":3591,"corporation":false,"usgs":true,"family":"Fend","given":"Steven","email":"svfend@usgs.gov","middleInitial":"V.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":396179,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Luoma, Samuel N. 0000-0001-5443-5091 snluoma@usgs.gov","orcid":"https://orcid.org/0000-0001-5443-5091","contributorId":2287,"corporation":false,"usgs":true,"family":"Luoma","given":"Samuel","email":"snluoma@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":396178,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":396180,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Taylor, Howard E. hetaylor@usgs.gov","contributorId":1551,"corporation":false,"usgs":true,"family":"Taylor","given":"Howard","email":"hetaylor@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":396176,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70022911,"text":"70022911 - 2000 - Nitrogen flux and sources in the Mississippi River Basin","interactions":[],"lastModifiedDate":"2018-12-07T05:38:14","indexId":"70022911","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5331,"text":"Science of Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Nitrogen flux and sources in the Mississippi River Basin","docAbstract":"<div id=\"abstracts\" class=\"Abstracts\"><div id=\"aep-abstract-id10\" class=\"abstract author\"><div id=\"aep-abstract-sec-id11\"><p>Nitrogen from the Mississippi River Basin is believed to be at least partly responsible for the large zone of oxygen-depleted water that develops in the Gulf of Mexico each summer. Historical data show that concentrations of nitrate in the Mississippi River and some of its tributaries have increased by factors of 2 to more than 5 since the early 1900s. We have used the historical streamflow and concentration data in regression models to estimate the annual flux of nitrogen (N) to the Gulf of Mexico and to determine where the nitrogen originates within the Mississippi Basin. Results show that for 1980–1996 the mean annual total N flux to the Gulf of Mexico was 1&nbsp;568&nbsp;000 t/year. The flux was approximately 61% nitrate as N, 37% organic N, and 2% ammonium as N. The flux of nitrate to the Gulf has approximately tripled in the last 30 years with most of the increase occurring between 1970 and 1983. The mean annual N flux has changed little since the early 1980s, but large year-to-year variations in N flux occur because of variations in precipitation. During wet years the N flux can increase by 50% or more due to flushing of nitrate that has accumulated in the soils and unsaturated zones in the basin. The principal source areas of N are basins in southern Minnesota, Iowa, Illinois, Indiana, and Ohio that drain agricultural land. Basins in this region yield 800 to more than 3100 kg total N/km<sup>2</sup><span>&nbsp;</span>per year to streams, several times the N yield of basins outside this region. Assuming conservative transport of N in the Mississippi River, streams draining Iowa and Illinois contribute on average approximately 35% of the total N discharged by the Mississippi River to the Gulf of Mexico. In years with high precipitation they can contribute a larger percentage.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/S0048-9697(99)00532-X","issn":"00489697","usgsCitation":"Goolsby, D.A., Battaglin, W., Aulenbach, B., and Hooper, R.P., 2000, Nitrogen flux and sources in the Mississippi River Basin: Science of Total Environment, v. 248, no. 2-3, p. 75-86, https://doi.org/10.1016/S0048-9697(99)00532-X.","productDescription":"12 p.","startPage":"75","endPage":"86","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":208084,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/S0048-9697(99)00532-X"},{"id":233501,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"248","issue":"2-3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a66d8e4b0c8380cd7300b","contributors":{"authors":[{"text":"Goolsby, D. A.","contributorId":50508,"corporation":false,"usgs":true,"family":"Goolsby","given":"D.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":395377,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Battaglin, W.A.","contributorId":16376,"corporation":false,"usgs":true,"family":"Battaglin","given":"W.A.","email":"","affiliations":[],"preferred":false,"id":395375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aulenbach, Brent T.","contributorId":62766,"corporation":false,"usgs":true,"family":"Aulenbach","given":"Brent T.","affiliations":[],"preferred":false,"id":395378,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hooper, R. P.","contributorId":26321,"corporation":false,"usgs":true,"family":"Hooper","given":"R.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":395376,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70022888,"text":"70022888 - 2000 - Sources and yields of dissolved carbon in northern Wisconsin stream catchments with differing amounts of Peatland","interactions":[],"lastModifiedDate":"2022-06-28T14:51:59.004693","indexId":"70022888","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Sources and yields of dissolved carbon in northern Wisconsin stream catchments with differing amounts of Peatland","docAbstract":"<p>In five tributary streams (four inflowing and one outflowing) of 1600-ha Trout Lake in northern Wisconsin, USA, we examined factors that can affect the magnitude of stream flow and transport of dissolved organic and inorganic carbon (DOC and DIC) through the streams to the lake. One catchment, the Allequash Creek basin, was investigated in more detail to describe the dynamics of carbon flow and to identify potential carbon sources. Stream flows and carbon loads showed little or no relation to surface-water catchment area. They were more closely related to ground-water watershed area because ground-water discharge, from both local and regional sources, is a major contributor to the hydrologic budgets of these catchments. An important factor in determining carbon influx to the stream is the area of peatland in the catchment. Peatland porewaters contain DOC concentrations up to 40 mg 1<sup>−1</sup><span>&nbsp;</span>and are a significant potential carbon source. Ground-water discharge and lateral flow through peat are the suspected mechanisms for transport of that carbon to the streams. Carbon and nitrogen isotopes suggested that the sources of DOC in Allequash Creek above Allequash Lake were wetland vegetation and peat and that the sources below Allequash Lake were filamentous algae and wild rice. Catchments with high proportions of peatland, including the Allequash Creek catchment, tended to have elevated DOC loads in outflowing stream water. Respiration and carbon mineralization in lakes within the system tend to produce low DOC and low DOC/DIC in lake outflows, especially at Trout Lake. In Allequash Lake, however, the shallow peat island and vegetation-filled west end were sources of DOC. Despite the vast carbon reservoir in the peatlands, carbon yields were very low in these catchments. Maximum yields were on the order of 2.5 g m<sup>−2</sup><span>&nbsp;</span>y<sup>−1</sup><span>&nbsp;</span>DOC and 5.5 g m<sup>−2</sup><span>&nbsp;</span>y<sup>−1</sup><span>&nbsp;</span>DIC. The small yields were attributable to low stream flows due to lack of significant overland runoff and very limited stream channel coverage of the total catchment area.</p>","language":"English","publisher":"Springer","doi":"10.1672/0277-5212(2000)020[0113:SAYODC]2.0.CO;2","issn":"02775212","usgsCitation":"Elder, J.F., Rybicki, N.B., Carter, V., and Weintraub, V., 2000, Sources and yields of dissolved carbon in northern Wisconsin stream catchments with differing amounts of Peatland: Wetlands, v. 20, no. 1, p. 113-125, https://doi.org/10.1672/0277-5212(2000)020[0113:SAYODC]2.0.CO;2.","productDescription":"13 p.","startPage":"113","endPage":"125","costCenters":[{"id":629,"text":"Water Resources Division","active":false,"usgs":true}],"links":[{"id":233720,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Allequash Lake, Allequash Stream, Big Muskellunge Lake, Crystal Bog, Mann Stream, North Stream, Sparkling Lake, Stevenson Stream, Trout Bog, Trout Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.73289489746094,\n              45.97358317988732\n            ],\n            [\n              -89.55608367919922,\n              45.97358317988732\n            ],\n            [\n              -89.55608367919922,\n              46.085852519246025\n            ],\n            [\n              -89.73289489746094,\n              46.085852519246025\n            ],\n            [\n              -89.73289489746094,\n              45.97358317988732\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"20","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b9363e4b08c986b31a484","contributors":{"authors":[{"text":"Elder, John F.","contributorId":23919,"corporation":false,"usgs":true,"family":"Elder","given":"John","email":"","middleInitial":"F.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":395291,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rybicki, Nancy B. 0000-0002-2205-7927 nrybicki@usgs.gov","orcid":"https://orcid.org/0000-0002-2205-7927","contributorId":2142,"corporation":false,"usgs":true,"family":"Rybicki","given":"Nancy","email":"nrybicki@usgs.gov","middleInitial":"B.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":395293,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carter, Virginia","contributorId":12018,"corporation":false,"usgs":true,"family":"Carter","given":"Virginia","email":"","affiliations":[],"preferred":false,"id":395292,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weintraub, Victoria","contributorId":99340,"corporation":false,"usgs":true,"family":"Weintraub","given":"Victoria","email":"","affiliations":[],"preferred":false,"id":395294,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70022884,"text":"70022884 - 2000 - The vulnerability of wetlands to climate change: A hydrologic landscape perspective","interactions":[],"lastModifiedDate":"2018-03-13T11:26:50","indexId":"70022884","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","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":"The vulnerability of wetlands to climate change: A hydrologic landscape perspective","docAbstract":"<p><span>The vulnerability of wetlands to changes in climate depends on their position within hydrologic landscapes. Hydrologic landscapes are defined by the flow characteristics of ground water and surface water and by the interaction of atmospheric water, surface water, and ground water for any given locality or region. Six general hydrologic landscapes are defined; mountainous, plateau and high plain, broad basins of interior drainage, riverine, flat coastal, and hummocky glacial and dune. Assessment of these landscapes indicate that the vulnerability of all wetlands to climate change fall between two extremes: those dependent primarily on precipitation for their water supply are highly vulnerable, and those dependent primarily on discharge from regional ground water flow systems are the least vulnerable, because of the great buffering capacity of large ground water flow systems to climate change.</span></p>","language":"English","publisher":"American Water Resources Association","doi":"10.1111/j.1752-1688.2000.tb04269.x","issn":"1093474X","usgsCitation":"Winter, T.C., 2000, The vulnerability of wetlands to climate change: A hydrologic landscape perspective: Journal of the American Water Resources Association, v. 36, no. 2, p. 305-311, https://doi.org/10.1111/j.1752-1688.2000.tb04269.x.","productDescription":"7 p.","startPage":"305","endPage":"311","numberOfPages":"7","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":233648,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"2","noUsgsAuthors":false,"publicationDate":"2007-06-08","publicationStatus":"PW","scienceBaseUri":"505bb1cae4b08c986b3253f4","contributors":{"authors":[{"text":"Winter, Thomas C.","contributorId":84736,"corporation":false,"usgs":true,"family":"Winter","given":"Thomas","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":395277,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70022761,"text":"70022761 - 2000 - Analysis of selected herbicide metabolites in surface and ground water of the United States","interactions":[],"lastModifiedDate":"2018-12-07T06:16:43","indexId":"70022761","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","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":"Analysis of selected herbicide metabolites in surface and ground water of the United States","docAbstract":"<div id=\"abstracts\" class=\"Abstracts\"><div id=\"aep-abstract-id10\" class=\"abstract author\"><div id=\"aep-abstract-sec-id11\"><p>One of the primary goals of the US Geological Survey (USGS) Laboratory in Lawrence, Kansas, is to develop analytical methods for the analysis of herbicide metabolites in surface and ground water that are vital to the study of herbicide fate and degradation pathways in the environment. Methods to measure metabolite concentrations from three major classes of herbicides — triazine, chloroacetanilide and phenyl-urea — have been developed. Methods for triazine metabolite detection cover nine compounds: six compounds are detected by gas chromatography/mass spectrometry; one is detected by high-performance liquid chromatography with diode-array detection; and eight are detected by liquid chromatography/mass spectrometry. Two metabolites of the chloroacetanilide herbicides — ethane sulfonic acid and oxanilic acid — are detected by high-performance liquid chromatography with diode-array detection and liquid chromatography/mass spectrometry. Alachlor ethane sulfonic acid also has been detected by solid-phase extraction and enzyme-linked immunosorbent assay. Six phenylurea metabolites are all detected by liquid chromatography/mass spectrometry; four of the six metabolites also are detected by gas chromatography/mass spectrometry. Additionally, surveys of herbicides and their metabolites in surface water, ground water, lakes, reservoirs, and rainfall have been conducted through the USGS laboratory in Lawrence. These surveys have been useful in determining herbicide and metabolite occurrence and temporal distribution and have shown that metabolites may be useful in evaluation of non-point-source contamination.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/S0048-9697(99)00539-2","issn":"00489697","usgsCitation":"Scribner, E., Thurman, E., and Zimmerman, L., 2000, Analysis of selected herbicide metabolites in surface and ground water of the United States: Science of the Total Environment, v. 248, no. 2-3, p. 157-167, https://doi.org/10.1016/S0048-9697(99)00539-2.","productDescription":"11 p.","startPage":"157","endPage":"167","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":233490,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":208078,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/S0048-9697(99)00539-2"}],"volume":"248","issue":"2-3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059eb2ee4b0c8380cd48c87","contributors":{"authors":[{"text":"Scribner, E.A.","contributorId":50925,"corporation":false,"usgs":true,"family":"Scribner","given":"E.A.","email":"","affiliations":[],"preferred":false,"id":394812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thurman, E.M.","contributorId":102864,"corporation":false,"usgs":true,"family":"Thurman","given":"E.M.","affiliations":[],"preferred":false,"id":394813,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zimmerman, L.R.","contributorId":28624,"corporation":false,"usgs":true,"family":"Zimmerman","given":"L.R.","email":"","affiliations":[],"preferred":false,"id":394811,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70022762,"text":"70022762 - 2000 - Use of radioimmunoassay as a screen for antibiotics in confined animal feeding operations and confirmation by liquid chromatography/mass spectrometry","interactions":[],"lastModifiedDate":"2018-12-12T09:06:48","indexId":"70022762","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5331,"text":"Science of Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Use of radioimmunoassay as a screen for antibiotics in confined animal feeding operations and confirmation by liquid chromatography/mass spectrometry","docAbstract":"<p>Approximately one-half of the 50 000000 lb of antibiotics produced in the USA are used in agriculture. Because of the intensive use of antibiotics in the management of confined livestock operations, the potential exists for the transport of these compounds and their metabolites into our nation's water resources. A commercially available radioimmunoassay method, developed as a screen for tetracycline antibiotics in serum, urine, milk, and tissue, was adapted to analyze water samples at a detection level of approximately 1.0 ppb and a semiquantitative analytical range of 1-20 ppb. Liquid waste samples were obtained from 13 hog lagoons in three states and 52 surface- and ground-water samples were obtained primarily from areas associated with intensive swine and poultry production in seven states. These samples were screened for the tetracycline antibiotics by using the modified radioimmunoassay screening method. The radioimmunoassay tests yielded positive results for tetracycline antibiotics in samples from all 13 of the hog lagoons. Dilutions of 10-100-fold of the hog lagoon samples indicated that tetracycline antibiotic concentrations ranged from approximately 5 to several hundred parts per billion in liquid hog lagoon waste. Of the 52 surface- and ground-water samples collected all but two tested negative and these two samples contained tetracycline antibiotic concentrations less than 1 ppb. A new liquid chromatography/mass spectrometry method was used to confirm the radioimmunoassay results in 9 samples and also to identify the tetracycline antibiotics to which the radioimmunoassay test was responding. The new liquid chromatography/mass spectrometry method with online solid-phase extraction and a detection level of 0.5 ??g/l confirmed the presence of chlorotetracycline in the hog lagoon samples and in one of the surface-water samples. The concentrations calculated from the radioimmunoassay were a factor of 1-5 times less than those calculated by the liquid chromatography/mass spectrometry concentrations for chlorotetracycline.&nbsp;</p>","language":"English","publisher":"Elsevier","doi":"10.1016/S0048-9697(99)00541-0","issn":"00489697","usgsCitation":"Meyer, M.T., Bumgarner, J., Varns, J., Daughtridge, J., Thurman, E., and Hostetler, K., 2000, Use of radioimmunoassay as a screen for antibiotics in confined animal feeding operations and confirmation by liquid chromatography/mass spectrometry: Science of Total Environment, v. 248, no. 2-3, p. 181-187, https://doi.org/10.1016/S0048-9697(99)00541-0.","productDescription":"7 p.","startPage":"181","endPage":"187","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":208079,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/S0048-9697(99)00541-0"},{"id":233491,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"248","issue":"2-3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bbf64e4b08c986b329b25","contributors":{"authors":[{"text":"Meyer, M. T.","contributorId":92279,"corporation":false,"usgs":true,"family":"Meyer","given":"M.","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":394818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bumgarner, J.E.","contributorId":82410,"corporation":false,"usgs":true,"family":"Bumgarner","given":"J.E.","email":"","affiliations":[],"preferred":false,"id":394816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Varns, J.L.","contributorId":85369,"corporation":false,"usgs":true,"family":"Varns","given":"J.L.","affiliations":[],"preferred":false,"id":394817,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daughtridge, J.V.","contributorId":69335,"corporation":false,"usgs":true,"family":"Daughtridge","given":"J.V.","email":"","affiliations":[],"preferred":false,"id":394815,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thurman, E.M.","contributorId":102864,"corporation":false,"usgs":true,"family":"Thurman","given":"E.M.","affiliations":[],"preferred":false,"id":394819,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hostetler, K.A.","contributorId":29855,"corporation":false,"usgs":true,"family":"Hostetler","given":"K.A.","email":"","affiliations":[],"preferred":false,"id":394814,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70022817,"text":"70022817 - 2000 - Determination of chloroacetanilide herbicide metabolites in water using high-performance liquid chromatography-diode array detection and high-performance liquid chromatography/mass spectrometry","interactions":[],"lastModifiedDate":"2018-12-12T07:53:10","indexId":"70022817","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","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":"Determination of chloroacetanilide herbicide metabolites in water using high-performance liquid chromatography-diode array detection and high-performance liquid chromatography/mass spectrometry","docAbstract":"<div id=\"abstracts\" class=\"Abstracts\"><div id=\"aep-abstract-id6\" class=\"abstract author\"><div id=\"aep-abstract-sec-id7\"><p>Analytical methods using high-performance liquid chromatography-diode array detection (HPLC-DAD) and high-performance liquid chromatography/mass spectrometry (HPLC/MS) were developed for the analysis of the following chloroacetanilide herbicide metabolites in water: alachlor ethanesulfonic acid (ESA); alachlor oxanilic acid; acetochlor ESA; acetochlor oxanilic acid; metolachlor ESA; and metolachlor oxanilic acid. Good precision and accuracy were demonstrated for both the HPLC-DAD and HPLC/MS methods in reagent water, surface water, and ground water. The average HPLC-DAD recoveries of the chloroacetanilide herbicide metabolites from water samples spiked at 0.25, 0.5 and 2.0 μg/l ranged from 84 to 112%, with relative standard deviations of 18% or less. The average HPLC/MS recoveries of the metabolites from water samples spiked at 0.05, 0.2 and 2.0 μg/l ranged from 81 to 118%, with relative standard deviations of 20% or less. The limit of quantitation (LOQ) for all metabolites using the HPLC-DAD method was 0.20 μg/l, whereas the LOQ using the HPLC/MS method was at 0.05 μg/l. These metabolite-determination methods are valuable for acquiring information about water quality and the fate and transport of the parent chloroacetanilide herbicides in water.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/S0048-9697(99)00538-0","issn":"00489697","usgsCitation":"Hostetler, K., and Thurman, E., 2000, Determination of chloroacetanilide herbicide metabolites in water using high-performance liquid chromatography-diode array detection and high-performance liquid chromatography/mass spectrometry: Science of the Total Environment, v. 248, no. 2-3, p. 147-155, https://doi.org/10.1016/S0048-9697(99)00538-0.","productDescription":"9 p.","startPage":"147","endPage":"155","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":233828,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":208229,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/S0048-9697(99)00538-0"}],"volume":"248","issue":"2-3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059ff9ee4b0c8380cd4f2b5","contributors":{"authors":[{"text":"Hostetler, K.A.","contributorId":29855,"corporation":false,"usgs":true,"family":"Hostetler","given":"K.A.","email":"","affiliations":[],"preferred":false,"id":395000,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thurman, E.M.","contributorId":102864,"corporation":false,"usgs":true,"family":"Thurman","given":"E.M.","affiliations":[],"preferred":false,"id":395001,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70022815,"text":"70022815 - 2000 - An evaluation of the Wyoming Gauge System for snowfall measurement","interactions":[],"lastModifiedDate":"2018-03-27T17:03:11","indexId":"70022815","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","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":"An evaluation of the Wyoming Gauge System for snowfall measurement","docAbstract":"<p><span>The Wyoming snow fence (shield) has been widely used with precipitation gauges for snowfall measurement at more than 25 locations in Alaska since the late 1970s. This gauge's measurements have been taken as the reference for correcting wind‐induced gauge undercatch of snowfall in Alaska. Recently, this fence (shield) was tested in the World Meteorological Organization Solid Precipitation Measurement Intercomparison Project at four locations in the United States of America and Canada for six winter seasons. At the Intercomparison sites an octagonal vertical Double Fence with a Russian Tretyakov gauge or a Universal Belfort recording gauge was installed and used as the Intercomparison Reference (DFIR) to provide true snowfall amounts for this Intercomparison experiment. The Intercomparison data collected were compiled at the four sites that represent a variety of climate, terrain, and exposure. On the basis of these data sets the performance of the Wyoming gauge system for snowfall observations was carefully evaluated against the DFIR and snow cover data. The results show that (1) the mean snow catch efficiency of the Wyoming gauge compared with the DFIR is about 80–90%, (2) there exists a close linear relation between the measurements of the two gauge systems and this relation may serve as a transfer function to adjust the Wyoming gauge records to obtain an estimate of the true snowfall amount, (3) catch efficiency of the Wyoming gauge does not change with wind speed and temperature, and (4) Wyoming gauge measurements are generally compatible to the snowpack water equivalent at selected locations in northern Alaska. These results are important to our effort of determining true snowfall amounts in the high latitudes, and they are also useful for regional hydrologic and climatic analyses.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2000WR900158","usgsCitation":"Yang, D., Kane, D.L., Hinzman, L.D., Goodison, B.E., Metcalfe, J.R., Louie, P.Y., Leavesley, G.H., Emerson, D.G., and Hanson, C.L., 2000, An evaluation of the Wyoming Gauge System for snowfall measurement: Water Resources Research, v. 36, no. 9, p. 2665-2677, https://doi.org/10.1029/2000WR900158.","productDescription":"13 p.","startPage":"2665","endPage":"2677","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":233790,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"9","noUsgsAuthors":false,"publicationDate":"2010-07-09","publicationStatus":"PW","scienceBaseUri":"5059ea54e4b0c8380cd487b3","contributors":{"authors":[{"text":"Yang, Daqing","contributorId":203286,"corporation":false,"usgs":false,"family":"Yang","given":"Daqing","email":"","affiliations":[],"preferred":false,"id":394995,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kane, Douglas L.","contributorId":112099,"corporation":false,"usgs":true,"family":"Kane","given":"Douglas","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":394990,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hinzman, Larry D.","contributorId":97133,"corporation":false,"usgs":true,"family":"Hinzman","given":"Larry","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":394997,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goodison, Barry E.","contributorId":203293,"corporation":false,"usgs":false,"family":"Goodison","given":"Barry","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":394996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Metcalfe, John R.","contributorId":203294,"corporation":false,"usgs":false,"family":"Metcalfe","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":394991,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Louie, Paul Y.T.","contributorId":60419,"corporation":false,"usgs":false,"family":"Louie","given":"Paul","email":"","middleInitial":"Y.T.","affiliations":[],"preferred":false,"id":394993,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Leavesley, George H. george@usgs.gov","contributorId":1202,"corporation":false,"usgs":true,"family":"Leavesley","given":"George","email":"george@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":394998,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Emerson, Douglas G.","contributorId":40579,"corporation":false,"usgs":true,"family":"Emerson","given":"Douglas","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":394992,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hanson, Clayton L.","contributorId":203290,"corporation":false,"usgs":false,"family":"Hanson","given":"Clayton","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":394994,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70022838,"text":"70022838 - 2000 - Restoring ecological integrity of great rivers: Historical hydrographs aid in defining reference conditions for the Missouri River","interactions":[],"lastModifiedDate":"2012-03-12T17:20:05","indexId":"70022838","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Restoring ecological integrity of great rivers: Historical hydrographs aid in defining reference conditions for the Missouri River","docAbstract":"Restoring the ecological integrity of regulated large rivers necessitates characterizing the natural flow regime. We applied 'Indicators of Hydrologic Alteration' to assess the natural range of variation of the Missouri River's flow regime at 11 locations before (1929-1948) and after (1967-1996) mainstem impoundment. The 3768 km long Missouri River was divided into three sections: upper basin least-altered from flow regulation, including the lower Yellowstone River; middle basin inter-reservoir, and lower basin channelized. Flow regulation was associated with a reduction in magnitude and duration of the annual flood pulse, an increase in magnitude and duration of annual discharge minima, a reduction in frequency of annual low-flow pulses, earlier timing of March-October low-flow pulses, and a general increase in frequency of flow reversals with a reduction in the rate of change in river flows. Hydrologic alterations were smallest at two least-altered upper-basin sites and most frequent and severe in inter-reservoir and upper-channelized river sections. The influence of reservoir operations on depressing the annual flood pulse was partially offset by tributary inflow in the lower 600 km of river. Reservoir operations could be modified to more closely approximate the 1929-1948 flow regime to establish a simulated natural riverine ecosystem. For inter-reservoir and upper channelized-river sections, we recommend periodic controlled flooding through managed reservoir releases during June and July; increased magnitude, frequency and duration of annual high-flow pulses; and increased annual rates of hydrograph rises and falls. All of the regulated Missouri River would benefit from reduced reservoir discharges during August-February, modified timing of reservoir releases and a reduced number of annual hydrograph reversals. Assessment of ecological responses to a reregulation of Missouri River flows that more closely approximates the natural flow regime should then be used in an adaptive fashion to further adjust reservoir operations.","largerWorkTitle":"Hydrobiologia","language":"English","issn":"00188158","usgsCitation":"Galat, D., and Lipkin, R., 2000, Restoring ecological integrity of great rivers: Historical hydrographs aid in defining reference conditions for the Missouri River, <i>in</i> Hydrobiologia, v. 422-423, p. 29-48.","startPage":"29","endPage":"48","numberOfPages":"20","costCenters":[],"links":[{"id":233537,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"422-423","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505aaadde4b0c8380cd8658f","contributors":{"authors":[{"text":"Galat, D.L.","contributorId":54546,"corporation":false,"usgs":true,"family":"Galat","given":"D.L.","email":"","affiliations":[],"preferred":false,"id":395092,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lipkin, R.","contributorId":21732,"corporation":false,"usgs":true,"family":"Lipkin","given":"R.","email":"","affiliations":[],"preferred":false,"id":395091,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70022837,"text":"70022837 - 2000 - Biogeochemical effects of global change on U.S. National Parks","interactions":[],"lastModifiedDate":"2022-08-25T17:08:20.817408","indexId":"70022837","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","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":"Biogeochemical effects of global change on U.S. National Parks","docAbstract":"<p><span>Federal parks and other public lands have unique mandates and rules regulating their use and conservation. Because of variation in their response to local, regional, and global-scale disturbance, development of mitigation strategies requires substantial research in the context of long-term inventory and monitoring. In 1982, the National Park Service began long-term, watershed-level studies in a series of national parks. The objective was to provide a more comprehensive database against which the effects of global change and other issues could be quantified. A subset of five sites in North Carolina, Texas, Washington, Michigan, and Alaska, is examined here. During the last 50 years, temperatures have declined at the southern sites and increased at the northern sites with the greatest increase in Alaska. Only the most southern site has shown an increase in precipitation amount. The net effect of these trends, especially for the most northern and southern sites, would likely be an increase in the growing season and especially the time soil processes could continue without moisture or temperature limitations. During the last 18 years, there were few trends in atmospheric ion inputs. The most evident was the decline in SO</span><sub>4</sub><sup>2</sup><span>&nbsp;deposition. There were no significant relationships between ion input and stream water output. This finding suggests other factors as modification of precipitation or canopy throughfall by soil processes, hydrologic flow path, and snowmelt rates are major processes regulating stream water chemical outputs.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/j.1752-1688.2000.tb04272.x","issn":"1093474X","usgsCitation":"Herrmann, R., Stottlemyer, R., Zak, J., Edmonds, R., and Van Miegroet, H., 2000, Biogeochemical effects of global change on U.S. National Parks: Journal of the American Water Resources Association, v. 36, no. 2, p. 337-346, https://doi.org/10.1111/j.1752-1688.2000.tb04272.x.","productDescription":"10 p.","startPage":"337","endPage":"346","costCenters":[],"links":[{"id":233536,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, Michigan, North Carolina, Texas, Washington","otherGeospatial":"Asik watershed, Big Bend National Park, Great Smoky Mountains National Park, Isle Royale National Park, Noatak National Preserve, Noland Divide, Olympic National Park, Pine Canyon, Wallace Lake, West Twin Creek","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -83.924560546875,\n              35.47297322193219\n            ],\n            [\n              -83.87100219726562,\n              35.44612729642443\n            ],\n            [\n              -83.84902954101562,\n              35.44500852178629\n            ],\n            [\n              -83.78860473632812,\n              35.44277092585766\n            ],\n            [\n              -83.75015258789062,\n              35.44500852178629\n            ],\n            [\n              -83.64990234375,\n              35.42710601280137\n            ],\n            [\n              -83.62930297851562,\n              35.43605776486772\n            ],\n            [\n              -83.60870361328125,\n              35.42262976362149\n            ],\n            [\n              -83.5894775390625,\n              35.431582013221266\n            ],\n            [\n              -83.52493286132812,\n              35.43605776486772\n            ],\n            [\n              -83.50433349609375,\n              35.44277092585766\n            ],\n            [\n              -83.48785400390625,\n              35.42598697382711\n            ],\n            [\n              -83.46450805664062,\n              35.45395828344931\n            ],\n            [\n              -83.38760375976562,\n              35.45395828344931\n            ],\n            [\n              -83.353271484375,\n              35.480801595828616\n            ],\n            [\n              -83.32855224609375,\n              35.46626258047241\n            ],\n            [\n              -83.287353515625,\n              35.50651802802079\n            ],\n            [\n              -83.27636718749999,\n              35.49421989176048\n            ],\n            [\n              -83.25576782226562,\n              35.51993202904746\n            ],\n            [\n              -83.28598022460938,\n              35.561277754384555\n            ],\n            [\n              -83.25302124023436,\n              35.575799570297406\n            ],\n            [\n              -83.17474365234374,\n              35.49421989176048\n            ],\n            [\n              -83.14453125,\n              35.51434313431818\n            ],\n            [\n              -83.15689086914062,\n              35.53781387714839\n            ],\n            [\n              -83.111572265625,\n              35.546753306701\n            ],\n            [\n              -83.08685302734375,\n              35.567980458012094\n            ],\n            [\n              -83.0621337890625,\n              35.556808973844596\n            ],\n            [\n              -83.03878784179688,\n              35.58250105910778\n            ],\n            [\n              -83.056640625,\n              35.598135685537905\n            ],\n            [\n              -83.0291748046875,\n              35.6427892190328\n            ],\n            [\n              -82.98934936523438,\n              35.64725320088259\n            ],\n            [\n              -82.99484252929688,\n              35.66510663398735\n            ],\n            [\n              -83.0401611328125,\n              35.660643649881614\n            ],\n            [\n              -83.04153442382812,\n              35.68630240145625\n            ],\n            [\n              -83.08547973632812,\n              35.706377408871774\n            ],\n            [\n              -83.07449340820312,\n              35.72087288213255\n            ],\n            [\n              -83.08959960937499,\n              35.753199435570316\n            ],\n            [\n              -83.11019897460938,\n              35.77102915686019\n            ],\n            [\n              -83.16925048828125,\n              35.767686388511244\n            ],\n            [\n              -83.19122314453125,\n              35.733136223133926\n            ],\n            [\n              -83.24478149414061,\n              35.73202145196925\n            ],\n            [\n              -83.26126098632811,\n              35.721987809328716\n            ],\n            [\n              -83.26400756835938,\n              35.69745580725804\n            ],\n            [\n              -83.29559326171875,\n              35.67626300279665\n            ],\n            [\n              -83.30520629882812,\n              35.65952786487723\n            ],\n            [\n              -83.32168579101562,\n              35.66733803249021\n            ],\n            [\n              -83.34640502929686,\n              35.66845370835343\n            ],\n            [\n              -83.36288452148438,\n              35.6517169333161\n            ],\n            [\n              -83.39309692382811,\n              35.64055713458091\n            ],\n            [\n              -83.41506958007812,\n              35.62939577711732\n            ],\n            [\n              -83.44940185546875,\n              35.61600009092947\n            ],\n            [\n              -83.48236083984375,\n              35.58808520476323\n            ],\n            [\n              -83.4906005859375,\n              35.575799570297406\n            ],\n            [\n              -83.50433349609375,\n              35.56686337967425\n            ],\n            [\n              -83.51806640624999,\n              35.570214567965984\n            ],\n            [\n              -83.58123779296875,\n              35.569097520776076\n            ],\n            [\n              -83.60870361328125,\n              35.58473476410106\n            ],\n            [\n              -83.64028930664062,\n              35.570214567965984\n            ],\n            [\n              -83.66638183593749,\n              35.574682600980914\n            ],\n            [\n              -83.75152587890625,\n              35.56574628576276\n            ],\n            [\n              -83.77212524414062,\n              35.56574628576276\n            ],\n            [\n              -83.8092041015625,\n              35.543401137387335\n            ],\n            [\n              -83.82156372070312,\n              35.52775582793653\n            ],\n            [\n              -83.83255004882812,\n              35.52552053465406\n            ],\n            [\n              -83.84902954101562,\n              35.51993202904746\n            ],\n            [\n              -83.85452270507812,\n              35.52216747798627\n            ],\n            [\n              -83.88473510742186,\n              35.51993202904746\n            ],\n            [\n              -83.91494750976562,\n              35.47632833265728\n            ],\n            [\n              -83.924560546875,\n              35.47297322193219\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.78097534179686,\n              29.249261450389792\n            ],\n            [\n              -103.78097534179686,\n              29.220500620041914\n            ],\n            [\n              -103.71917724609375,\n              29.180941290001776\n            ],\n            [\n              -103.59146118164062,\n              29.148563215253184\n            ],\n            [\n              -103.55850219726562,\n              29.149762585277653\n            ],\n            [\n              -103.47610473632811,\n              29.066973223731654\n            ],\n            [\n              -103.36074829101562,\n              29.014145252385035\n            ],\n            [\n              -103.28521728515625,\n              28.976909313412413\n            ],\n            [\n              -103.14926147460936,\n              28.968499342421694\n            ],\n            [\n              -103.11080932617186,\n              28.97931203672246\n            ],\n            [\n              -103.084716796875,\n              29.0537687665771\n            ],\n            [\n              -103.03253173828124,\n              29.099376992628493\n            ],\n            [\n              -102.98309326171875,\n              29.178543264303006\n            ],\n            [\n              -102.94326782226562,\n              29.16895060109228\n            ],\n            [\n              -102.90481567382812,\n              29.20252099881366\n            ],\n            [\n              -102.86911010742186,\n              29.209713225868185\n            ],\n            [\n              -102.864990234375,\n              29.243270277106987\n            ],\n            [\n              -102.89794921875,\n              29.263638834879824\n            ],\n            [\n              -102.8704833984375,\n              29.34387539941801\n            ],\n            [\n              -102.83477783203125,\n              29.35345166863502\n            ],\n            [\n              -102.83615112304688,\n              29.37140474730792\n            ],\n            [\n              -102.86087036132811,\n              29.38456832654707\n            ],\n            [\n              -102.85675048828125,\n              29.401319510041485\n            ],\n            [\n              -102.90481567382812,\n              29.39773020297217\n            ],\n            [\n              -102.90481567382812,\n              29.42763722319321\n            ],\n            [\n              -103.40469360351562,\n              29.426441111375265\n            ],\n            [\n              -103.51730346679688,\n              29.342678302488952\n            ],\n            [\n              -103.546142578125,\n              29.305561325527698\n            ],\n            [\n              -103.54339599609375,\n              29.270826769181955\n            ],\n            [\n              -103.58596801757811,\n              29.231286878292476\n            ],\n            [\n              -103.64089965820311,\n              29.2324852813013\n            ],\n            [\n              -103.65875244140625,\n              29.252855985973763\n            ],\n            [\n              -103.78097534179686,\n              29.249261450389792\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.26385498046874,\n              47.48380086737799\n            ],\n            [\n              -123.18145751953125,\n              47.60060732292067\n            ],\n            [\n              -123.09906005859375,\n              47.61727271567975\n            ],\n            [\n              -123.00018310546874,\n              47.70606513569572\n            ],\n            [\n              -123.00018310546874,\n              47.879512933970496\n            ],\n            [\n              -123.09631347656249,\n              47.90345483298757\n            ],\n            [\n              -123.0908203125,\n              47.94946583788702\n            ],\n            [\n              -123.25286865234376,\n              48.0156497866894\n            ],\n            [\n              -123.43414306640625,\n              48.057889555610984\n            ],\n            [\n              -123.77471923828125,\n              48.111099041065366\n            ],\n            [\n              -124.0191650390625,\n              48.09642606004488\n            ],\n            [\n              -124.03289794921876,\n              48.057889555610984\n            ],\n            [\n              -123.94775390625,\n              48.0156497866894\n            ],\n            [\n              -124.024658203125,\n              47.96234158490351\n            ],\n            [\n              -124.14276123046876,\n              47.94394667836214\n            ],\n            [\n              -124.26361083984374,\n              47.97889140226657\n            ],\n            [\n              -124.26635742187501,\n              47.85187391101592\n            ],\n            [\n              -124.07409667968749,\n              47.83159592699297\n            ],\n            [\n              -124.03839111328125,\n              47.81499895328108\n            ],\n            [\n              -123.85711669921874,\n              47.70976154266637\n            ],\n            [\n              -123.93951416015626,\n              47.611718174784926\n            ],\n            [\n              -123.8323974609375,\n              47.593198777144636\n            ],\n            [\n              -123.96972656249999,\n              47.470806305936264\n            ],\n            [\n              -123.73077392578124,\n              47.429945332976125\n            ],\n            [\n              -123.51379394531249,\n              47.50050343862717\n            ],\n            [\n              -123.26385498046874,\n              47.48380086737799\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.63419771194457,\n              48.054648191772074\n            ],\n            [\n              -88.62520694732666,\n              48.054648191772074\n            ],\n            [\n              -88.62520694732666,\n              48.058793085266856\n            ],\n            [\n              -88.63419771194457,\n              48.058793085266856\n            ],\n            [\n              -88.63419771194457,\n              48.054648191772074\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -162.04833984375,\n              67.02887556543278\n            ],\n            [\n              -161.8011474609375,\n              67.17208621852586\n            ],\n            [\n              -162.1636962890625,\n              67.34620894041845\n            ],\n            [\n              -162.09228515625,\n              67.39693323856477\n            ],\n            [\n              -161.7572021484375,\n              67.3905985915074\n            ],\n            [\n              -161.136474609375,\n              67.61549716460256\n            ],\n            [\n              -160.9771728515625,\n              67.60084926188547\n            ],\n            [\n              -160.75195312499997,\n              67.54006818806145\n            ],\n            [\n              -160.521240234375,\n              67.61968061043788\n            ],\n            [\n              -160.4278564453125,\n              67.90035413006105\n            ],\n            [\n              -160.84533691406247,\n              67.92101125483218\n            ],\n            [\n              -161.25183105468747,\n              68.01785424468962\n            ],\n            [\n              -161.62536621093747,\n              68.0096280290576\n            ],\n            [\n              -161.9769287109375,\n              67.97875365614591\n            ],\n            [\n              -162.6580810546875,\n              67.89001868431993\n            ],\n            [\n              -162.806396484375,\n              67.79471694725302\n            ],\n            [\n              -162.77893066406247,\n              67.63849694000439\n            ],\n            [\n              -162.96569824218747,\n              67.4770266555557\n            ],\n            [\n              -162.94921875,\n              67.434905815823\n            ],\n            [\n              -162.7239990234375,\n              67.3905985915074\n            ],\n            [\n              -162.7679443359375,\n              67.32080636883347\n            ],\n            [\n              -162.5262451171875,\n              67.21041648785257\n            ],\n            [\n              -162.59216308593747,\n              67.15503096293045\n            ],\n            [\n              -162.344970703125,\n              67.07385369337244\n            ],\n            [\n              -162.04833984375,\n              67.02887556543278\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","issue":"2","noUsgsAuthors":false,"publicationDate":"2007-06-08","publicationStatus":"PW","scienceBaseUri":"5059f152e4b0c8380cd4abb3","contributors":{"authors":[{"text":"Herrmann, R.","contributorId":12640,"corporation":false,"usgs":true,"family":"Herrmann","given":"R.","affiliations":[],"preferred":false,"id":395086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stottlemyer, R.","contributorId":44493,"corporation":false,"usgs":true,"family":"Stottlemyer","given":"R.","email":"","affiliations":[],"preferred":false,"id":395088,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zak, J.C.","contributorId":82097,"corporation":false,"usgs":true,"family":"Zak","given":"J.C.","email":"","affiliations":[],"preferred":false,"id":395090,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edmonds, R.L.","contributorId":32335,"corporation":false,"usgs":true,"family":"Edmonds","given":"R.L.","email":"","affiliations":[],"preferred":false,"id":395087,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Van Miegroet, H.","contributorId":47723,"corporation":false,"usgs":true,"family":"Van Miegroet","given":"H.","affiliations":[],"preferred":false,"id":395089,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70022787,"text":"70022787 - 2000 - Finding minimal herbicide concentrations in ground water? Try looking for their degradates","interactions":[],"lastModifiedDate":"2018-12-07T06:09:06","indexId":"70022787","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","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":"Finding minimal herbicide concentrations in ground water? Try looking for their degradates","docAbstract":"<p>Extensive research has been conducted regarding the occurrence of herbicides in the hydrologic system, their fate, and their effects on human health and the environment. Few studies, however, have considered herbicide transformation products (degradates). In this study of Iowa ground water, herbicide degradates were frequently detected. In fact, herbicide degradates were eight of the 10 most frequently detected compounds. Furthermore, a majority of a herbicide's measured concentration was in the form of its degradates &mdash; ranging from 55 to over 99%. The herbicide detection frequencies and concentrations varied significantly among the major aquifer types sampled. These differences, however, were much more pronounced when herbicide degradates were included. Aquifer types presumed to have the most rapid recharge rates (alluvial and bedrock/karst region aquifers) were those most likely to contain detectable concentrations of herbicide compounds. Two indirect estimates of ground-water age (depth of well completion and dissolved-oxygen concentration) were used to separate the sampled wells into general vulnerability classes (low, intermediate, and high). The results show that the herbicide detection frequencies and concentrations varied significantly among the vulnerability classes regardless of whether or not herbicide degradates were considered. Nevertheless, when herbicide degradates were included, the frequency of herbicide compound detection within the highest vulnerability class approached 90%, and the median total herbicide residue concentration increased over an order of magnitude, relative to the parent compounds alone, to 2 &mu;g/l. The results from this study demonstrate that obtaining data on herbicide degradates is critical for understanding the fate of herbicides in the hydrologic system. Furthermore, the prevalence of herbicide degradates documented in this study suggests that to accurately determine the overall effect on human health and the environment of a specific herbicide its degradates should also be considered.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/S0048-9697(99)00535-5","issn":"00489697","usgsCitation":"Kolpin, D., Thurman, E., and Linhart, S.M., 2000, Finding minimal herbicide concentrations in ground water? Try looking for their degradates: Science of the Total Environment, v. 248, no. 2-3, p. 115-122, https://doi.org/10.1016/S0048-9697(99)00535-5.","productDescription":"8 p.","startPage":"115","endPage":"122","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":233890,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-91.217706,43.50055],[-91.216035,43.481142],[-91.233367,43.455168],[-91.200359,43.412701],[-91.198953,43.389835],[-91.21477,43.365874],[-91.20662,43.352524],[-91.132813,43.32803],[-91.107237,43.313645],[-91.07371,43.274746],[-91.071698,43.261014],[-91.058644,43.257679],[-91.066398,43.239293],[-91.12217,43.197255],[-91.1462,43.152405],[-91.1562,43.142945],[-91.175253,43.134665],[-91.179457,43.067427],[-91.156562,42.978226],[-91.14543,42.958211],[-91.14988,42.941955],[-91.1438,42.922877],[-91.146177,42.90985],[-91.100565,42.883078],[-91.097656,42.859871],[-91.091837,42.851225],[-91.09406,42.830813],[-91.078665,42.827678],[-91.069549,42.769628],[-91.060261,42.761847],[-91.065783,42.753387],[-91.056297,42.747341],[-91.051275,42.737001],[-91.035418,42.73734],[-91.026786,42.724228],[-91.000128,42.716189],[-90.977735,42.696816],[-90.949213,42.685573],[-90.923634,42.6855],[-90.88743,42.67247],[-90.731132,42.643437],[-90.706303,42.634169],[-90.692031,42.610366],[-90.686975,42.591774],[-90.661527,42.567999],[-90.654127,42.5499],[-90.643927,42.540401],[-90.636927,42.513202],[-90.655927,42.491703],[-90.654027,42.478503],[-90.624328,42.458904],[-90.567968,42.440389],[-90.560439,42.432897],[-90.555018,42.416138],[-90.477279,42.383794],[-90.462619,42.367253],[-90.443874,42.355218],[-90.416535,42.325109],[-90.430884,42.27823],[-90.419326,42.254467],[-90.400653,42.239293],[-90.391108,42.225473],[-90.356964,42.205445],[-90.328273,42.201047],[-90.282173,42.178846],[-90.234919,42.165431],[-90.209479,42.15268],[-90.197342,42.128163],[-90.167533,42.122475],[-90.161159,42.106372],[-90.168358,42.075779],[-90.164485,42.042105],[-90.151579,42.030633],[-90.140061,42.003252],[-90.146225,41.981329],[-90.164135,41.956178],[-90.163847,41.944934],[-90.152659,41.933058],[-90.153584,41.906614],[-90.181401,41.844647],[-90.181973,41.80707],[-90.278633,41.767358],[-90.310708,41.742214],[-90.317668,41.72269],[-90.313435,41.698082],[-90.334525,41.679559],[-90.343452,41.646959],[-90.339528,41.598633],[-90.343228,41.587833],[-90.41283,41.565333],[-90.461432,41.523533],[-90.500633,41.518033],[-90.540935,41.526133],[-90.591037,41.512832],[-90.602137,41.506032],[-90.605937,41.494232],[-90.655839,41.462132],[-90.750142,41.449632],[-90.846558,41.455141],[-90.930016,41.421404],[-90.979815,41.434321],[-91.027787,41.423603],[-91.043988,41.415897],[-91.05101,41.387556],[-91.06652,41.365246],[-91.074841,41.305578],[-91.092034,41.286911],[-91.114186,41.250029],[-91.113648,41.241401],[-91.07298,41.207151],[-91.041536,41.166138],[-91.027214,41.163373],[-91.007586,41.166183],[-90.99496,41.160624],[-90.946627,41.096632],[-90.949383,41.072711],[-90.942253,41.034702],[-90.945949,41.006495],[-90.958142,40.979767],[-90.952233,40.954047],[-90.965344,40.921633],[-91.009536,40.900565],[-91.021562,40.884021],[-91.044653,40.868356],[-91.05643,40.848387],[-91.092993,40.821079],[-91.097649,40.805575],[-91.091703,40.779708],[-91.110424,40.745528],[-91.115735,40.725168],[-91.11194,40.697018],[-91.123928,40.669152],[-91.185428,40.638071],[-91.253074,40.637962],[-91.306524,40.626231],[-91.339719,40.613488],[-91.359873,40.601805],[-91.379752,40.57445],[-91.401482,40.559458],[-91.406373,40.551831],[-91.404125,40.539127],[-91.384531,40.530948],[-91.369059,40.512532],[-91.364211,40.500043],[-91.364915,40.484168],[-91.381769,40.442555],[-91.372554,40.4012],[-91.381958,40.387632],[-91.419422,40.378264],[-91.441243,40.386255],[-91.452458,40.375501],[-91.463895,40.375659],[-91.465116,40.385257],[-91.484507,40.3839],[-91.490977,40.393484],[-91.487829,40.403866],[-91.498093,40.401926],[-91.522333,40.409648],[-91.527057,40.416689],[-91.519012,40.431298],[-91.529132,40.434272],[-91.533548,40.440804],[-91.523271,40.450061],[-91.526155,40.458625],[-91.552691,40.458769],[-91.574746,40.465664],[-91.590817,40.492292],[-91.621353,40.510072],[-91.618028,40.53403],[-91.6219,40.542292],[-91.6887,40.55739],[-91.691557,40.564867],[-91.686357,40.580875],[-91.716769,40.59853],[-91.729115,40.61364],[-92.686693,40.589809],[-94.294813,40.571341],[-94.632032,40.571186],[-95.765645,40.585208],[-95.753148,40.59284],[-95.748626,40.603355],[-95.768926,40.621264],[-95.776251,40.647463],[-95.795489,40.662384],[-95.822913,40.66724],[-95.842801,40.677496],[-95.852615,40.702262],[-95.883178,40.717579],[-95.888907,40.731855],[-95.879027,40.753081],[-95.84662,40.768619],[-95.835232,40.779151],[-95.834523,40.787778],[-95.845342,40.811324],[-95.837186,40.835347],[-95.847084,40.854174],[-95.847785,40.864328],[-95.838735,40.872191],[-95.815933,40.879846],[-95.809474,40.891228],[-95.813458,40.901693],[-95.836438,40.921642],[-95.839743,40.93278],[-95.829074,40.975688],[-95.838908,40.986484],[-95.867286,41.001599],[-95.869486,41.009399],[-95.859918,41.025403],[-95.859654,41.035695],[-95.882415,41.060411],[-95.862587,41.088399],[-95.865888,41.117898],[-95.882088,41.143998],[-95.883489,41.154898],[-95.871912,41.168122],[-95.846188,41.166698],[-95.841288,41.174998],[-95.856788,41.187098],[-95.90969,41.184398],[-95.91829,41.186698],[-95.92599,41.195698],[-95.924891,41.211198],[-95.910891,41.231798],[-95.921891,41.264598],[-95.913991,41.271398],[-95.928691,41.281398],[-95.927491,41.298397],[-95.90589,41.300897],[-95.90429,41.293497],[-95.912491,41.279498],[-95.90249,41.273398],[-95.87689,41.285097],[-95.871489,41.295797],[-95.883089,41.316697],[-95.92569,41.322197],[-95.946891,41.334096],[-95.956691,41.345496],[-95.954891,41.351796],[-95.93549,41.360596],[-95.92879,41.370096],[-95.93689,41.396387],[-95.929721,41.411331],[-95.933169,41.42943],[-95.919865,41.447922],[-95.922529,41.455766],[-95.936801,41.46519],[-95.962329,41.46281],[-96.011757,41.476212],[-96.019542,41.486617],[-95.997903,41.504789],[-95.992599,41.514174],[-95.999529,41.538679],[-96.005079,41.544004],[-96.019686,41.545743],[-96.027289,41.541081],[-96.034305,41.512853],[-96.040701,41.507076],[-96.05369,41.508859],[-96.07307,41.525052],[-96.08822,41.530595],[-96.09409,41.539265],[-96.093613,41.558271],[-96.081152,41.577289],[-96.085771,41.585746],[-96.109387,41.596871],[-96.117558,41.609999],[-96.116233,41.621574],[-96.100701,41.635507],[-96.095046,41.647365],[-96.099837,41.66103],[-96.120983,41.677861],[-96.121401,41.688522],[-96.111968,41.697773],[-96.082429,41.698159],[-96.073063,41.705004],[-96.079682,41.717962],[-96.10261,41.728016],[-96.106425,41.73789],[-96.102772,41.746339],[-96.079915,41.757895],[-96.077543,41.777824],[-96.064537,41.793002],[-96.075548,41.807811],[-96.107592,41.820685],[-96.110246,41.84885],[-96.142045,41.868865],[-96.148826,41.888132],[-96.161756,41.90182],[-96.160767,41.908044],[-96.136743,41.920826],[-96.144583,41.941544],[-96.133318,41.955732],[-96.1289,41.969727],[-96.141228,41.978063],[-96.156538,41.980137],[-96.184243,41.976696],[-96.192141,41.984461],[-96.183568,41.999987],[-96.194556,42.008662],[-96.215225,42.006701],[-96.223896,41.995456],[-96.236487,41.996428],[-96.241932,42.006965],[-96.223611,42.022652],[-96.223822,42.033346],[-96.238392,42.041088],[-96.261132,42.038974],[-96.271427,42.044988],[-96.279342,42.07028],[-96.267636,42.096177],[-96.2689,42.11359],[-96.279203,42.12348],[-96.310085,42.132523],[-96.319528,42.146647],[-96.342395,42.160491],[-96.349688,42.172043],[-96.348066,42.194747],[-96.35987,42.210545],[-96.358141,42.214088],[-96.336323,42.218922],[-96.323723,42.229887],[-96.330004,42.240224],[-96.328905,42.254734],[-96.336003,42.264806],[-96.365792,42.285875],[-96.369212,42.308344],[-96.375307,42.318339],[-96.407998,42.337408],[-96.417786,42.351449],[-96.417093,42.361443],[-96.408436,42.376092],[-96.41498,42.393442],[-96.413609,42.407894],[-96.387608,42.432494],[-96.380707,42.446394],[-96.385407,42.473094],[-96.396107,42.484095],[-96.409408,42.487595],[-96.474409,42.491895],[-96.476909,42.497795],[-96.473339,42.503537],[-96.477454,42.509589],[-96.490089,42.512441],[-96.49297,42.517282],[-96.479909,42.524195],[-96.476952,42.556079],[-96.498041,42.558153],[-96.498709,42.57087],[-96.489328,42.5708],[-96.485796,42.575001],[-96.49545,42.579474],[-96.494777,42.585741],[-96.499885,42.588539],[-96.509468,42.61273],[-96.517048,42.615343],[-96.525671,42.609312],[-96.531604,42.615148],[-96.518542,42.62035],[-96.516338,42.630435],[-96.537881,42.646446],[-96.542366,42.660736],[-96.559281,42.657903],[-96.556461,42.663939],[-96.566684,42.675942],[-96.576381,42.671302],[-96.575299,42.682665],[-96.596405,42.688514],[-96.59908,42.697296],[-96.61017,42.694568],[-96.629625,42.705102],[-96.624446,42.714294],[-96.624704,42.725497],[-96.631931,42.725086],[-96.638621,42.734921],[-96.630485,42.750378],[-96.620548,42.753534],[-96.620272,42.757124],[-96.632212,42.761512],[-96.633168,42.768325],[-96.61949,42.784034],[-96.604559,42.783034],[-96.595283,42.792982],[-96.590757,42.808255],[-96.596008,42.815044],[-96.585699,42.818041],[-96.577937,42.827645],[-96.581604,42.837521],[-96.571353,42.837155],[-96.565605,42.830434],[-96.560572,42.839373],[-96.552092,42.836057],[-96.549513,42.839143],[-96.554709,42.846142],[-96.545502,42.849956],[-96.54146,42.857682],[-96.550439,42.863171],[-96.549659,42.870281],[-96.537851,42.878475],[-96.540396,42.888877],[-96.526563,42.893755],[-96.542847,42.903737],[-96.537354,42.908791],[-96.541689,42.922576],[-96.525536,42.935511],[-96.516203,42.933769],[-96.52012,42.938183],[-96.500308,42.959391],[-96.505028,42.970844],[-96.515922,42.972886],[-96.520773,42.980385],[-96.512237,42.985937],[-96.509986,42.995126],[-96.49782,42.998143],[-96.49167,43.009707],[-96.499187,43.019213],[-96.510995,43.024701],[-96.509146,43.03668],[-96.518431,43.042068],[-96.510256,43.049917],[-96.490365,43.050789],[-96.476905,43.062383],[-96.463094,43.062981],[-96.458201,43.067554],[-96.454188,43.083379],[-96.462636,43.089614],[-96.460516,43.09494],[-96.436589,43.120842],[-96.450361,43.142237],[-96.458854,43.143356],[-96.466537,43.150281],[-96.464896,43.182034],[-96.473834,43.189804],[-96.470781,43.205099],[-96.475571,43.221054],[-96.496454,43.223652],[-96.519273,43.21769],[-96.535741,43.22764],[-96.56044,43.224219],[-96.568505,43.231554],[-96.571194,43.238961],[-96.552963,43.247281],[-96.552591,43.257769],[-96.582904,43.26769],[-96.586317,43.274319],[-96.577588,43.2788],[-96.580346,43.298204],[-96.553087,43.29286],[-96.530392,43.300034],[-96.526004,43.309999],[-96.534913,43.336473],[-96.524289,43.347214],[-96.527345,43.368109],[-96.521323,43.374607],[-96.521572,43.38564],[-96.524044,43.394762],[-96.529152,43.397735],[-96.537116,43.395063],[-96.573579,43.419228],[-96.569628,43.427527],[-96.575181,43.431756],[-96.592905,43.43317],[-96.602608,43.449649],[-96.600039,43.45708],[-96.584603,43.46961],[-96.586364,43.478251],[-96.580997,43.481384],[-96.590452,43.494298],[-96.598396,43.495074],[-96.598929,43.500441],[-91.217706,43.50055]]]},\"properties\":{\"name\":\"Iowa\",\"nation\":\"USA  \"}}]}","volume":"248","issue":"2-3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a101ce4b0c8380cd53b1f","contributors":{"authors":[{"text":"Kolpin, D.W.","contributorId":87565,"corporation":false,"usgs":true,"family":"Kolpin","given":"D.W.","email":"","affiliations":[],"preferred":false,"id":394907,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thurman, E.M.","contributorId":102864,"corporation":false,"usgs":true,"family":"Thurman","given":"E.M.","affiliations":[],"preferred":false,"id":394909,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Linhart, S. M.","contributorId":102517,"corporation":false,"usgs":true,"family":"Linhart","given":"S.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":394908,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70022835,"text":"70022835 - 2000 - Patterns of change in tree islands in Arthur R. Marshall Loxahatchee National Wildlife Refuge from 1950 to 1991","interactions":[],"lastModifiedDate":"2022-06-28T14:33:42.899165","indexId":"70022835","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Patterns of change in tree islands in Arthur R. Marshall Loxahatchee National Wildlife Refuge from 1950 to 1991","docAbstract":"Size, shape, orientation, and distribution of tree islands in a remnant of northern Everglades wetland were examined from 1950 and 1991 aerial photography. The objectives were to quantify the patterns of tree islands in Loxahatchee National Wildlife Refuge, to determine if the patterns of tree islands had changed between the two dates, and to relate the tree island patterns to modeled pre- and post-drainage hydrologic patterns. There was considerable variation in the patterns of tree islands spatially and temporally. Changes in the size and shape of tree islands from 1950 to 1991 are consistent with changes in the modeled pre- and post-drainage hydrologic patterns. Photo plots along the edges of the refuge, where hydroperiods are longer and depths deeper than they were historically, show a decrease in tree island size and in overall area of tree islands in the plots. Photo plots in the interior, where hydroperiods are shorter than they were pre-drainage, show an increase in tree island area. Overall, there is a tendency for more tree islands to be irregularly shaped in the 1991 photo plots than in the 1950 plots, a reflection of the loss of water flow, reduction of pulse magnitude, and the ponding of water along the perimeter dikes. This study illustrates the importance of considering long-term changes in hydroperiod, depths, and water flows in the restoration of this area.","language":"English","publisher":"Springer","doi":"10.1672/0277-5212(2000)020[0001:POCITI]2.0.CO;2","issn":"02775212","usgsCitation":"Brandt, L., Portier, K.M., and Kitchens, W.M., 2000, Patterns of change in tree islands in Arthur R. Marshall Loxahatchee National Wildlife Refuge from 1950 to 1991: Wetlands, v. 20, no. 1, p. 1-14, https://doi.org/10.1672/0277-5212(2000)020[0001:POCITI]2.0.CO;2.","productDescription":"14","startPage":"1","endPage":"14","costCenters":[{"id":274,"text":"Florida Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":233497,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","county":"Palm Beach County","otherGeospatial":"Arthur R. Marshall Loxahatchee National Wildlife Refuge, Everglades, Lake Okeechobee","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.44601440429686,\n              26.4711876806674\n            ],\n            [\n              -80.37460327148438,\n              26.377721970428563\n            ],\n            [\n              -80.24894714355469,\n              26.340806769468358\n            ],\n            [\n              -80.24894714355469,\n              26.362342068998764\n            ],\n            [\n              -80.23590087890624,\n              26.38510359603802\n            ],\n            [\n              -80.23590087890624,\n              26.407860638241498\n            ],\n            [\n              -80.21942138671875,\n              26.46565563783836\n            ],\n            [\n              -80.22079467773438,\n              26.51420559869417\n            ],\n            [\n              -80.233154296875,\n              26.543080020962417\n            ],\n            [\n              -80.27778625488281,\n              26.602034978080944\n            ],\n            [\n              -80.33203125,\n              26.632728662035912\n            ],\n            [\n              -80.34713745117188,\n              26.646844988896188\n            ],\n            [\n              -80.36567687988281,\n              26.684275490019488\n            ],\n            [\n              -80.37666320800781,\n              26.6836619742687\n            ],\n            [\n              -80.44876098632812,\n              26.592825266403615\n            ],\n            [\n              -80.44601440429686,\n              26.4711876806674\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"20","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a75c8e4b0c8380cd77d3c","contributors":{"authors":[{"text":"Brandt, Laura A.","contributorId":18608,"corporation":false,"usgs":false,"family":"Brandt","given":"Laura A.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":395081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Portier, Kenneth M.","contributorId":77263,"corporation":false,"usgs":true,"family":"Portier","given":"Kenneth","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":395082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kitchens, Wiley M. kitchensw@usgs.gov","contributorId":2851,"corporation":false,"usgs":true,"family":"Kitchens","given":"Wiley","email":"kitchensw@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":395083,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70022825,"text":"70022825 - 2000 - Sulfur geochemistry of hydrothermal waters in Yellowstone National Park, Wyoming, USA. II. Formation and decomposition of thiosulfate and polythionate in Cinder Pool","interactions":[],"lastModifiedDate":"2018-12-14T06:57:04","indexId":"70022825","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Sulfur geochemistry of hydrothermal waters in Yellowstone National Park, Wyoming, USA. II. Formation and decomposition of thiosulfate and polythionate in Cinder Pool","docAbstract":"<p>Cinder Pool is an acid-sulfate-chloride boiling spring in Norris Geyser Basin, Yellowstone National Park. The pool is unique in that its surface is partially covered with mm-size, black, hollow sulfur spherules, while a layer of molten sulfur resides at the bottom of the pool (18 m depth). The sulfur speciation in the pool was determined on four different days over a period of two years. Samples were taken to evaluate changes with depth and to evaluate the importance of the sulfur spherules on sulfur redox chemistry. All analyses were conducted on site using a combination of ion chromatography and colorimetric techniques.</p><p>Dissolved sulfide (H<sub>2</sub>S), thiosulfate (S<sub>2</sub>O<sub>3</sub><sup>2−</sup>), polythionates (S<sub>x</sub>O<sub>6</sub><sup>2−</sup>), and sulfate were detected. The polythionate concentration was highly variable in time and space. The highest concentrations were found in surficial samples taken from among the sulfur spherules. With depth, the polythionate concentrations dropped off. The maximum observed polythionate concentration was 8 μM. Thiosulfate was rather uniformly distributed throughout the pool and concentrations ranged from 35 to 45 μM. Total dissolved sulfide concentrations varied with time, concentrations ranged from 16 to 48 μM. Sulfate was relatively constant, with concentrations ranging from 1150 to 1300 μM. The sulfur speciation of Cinder Pool is unique in that the thiosulfate and polythionate concentrations are significantly higher than for any other acid-sulfate spring yet sampled in Yellowstone National Park. Complementary laboratory experiments show that thiosulfate is the intermediate sulfoxyanion formed from sulfur hydrolysis under conditions similar to those found in Cinder Pool and that polythionates are formed via the oxidation of thiosulfate by dissolved oxygen. This last reaction is catalyzed by pyrite that occurs as a minor constituent in the sulfur spherules floating on the pool's surface. Polythionate decomposition proceeds via two pathways: (1) a reaction with H<sub>2</sub>S, yielding thiosulfate and elemental sulfur; and (2) by disproportionation to sulfate and thiosulfate.</p><p>This study demonstrates that the presence of a subaqueous molten sulfur pool and sulfur spherules in Cinder Pool is of importance in controlling the pathways of aqueous sulfur redox reactions. Some of the insights gained at Cinder Pool may be relevant to acid crater lakes where sulfur spherules are observed and variations in polythionate concentrations are used to monitor and predict volcanic activity.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/S0377-0273(99)00173-0","issn":"03770273","usgsCitation":"Xu, Y., Schoonen, M., Nordstrom, D.K., Cunningham, K., and Ball, J., 2000, Sulfur geochemistry of hydrothermal waters in Yellowstone National Park, Wyoming, USA. II. Formation and decomposition of thiosulfate and polythionate in Cinder Pool: Journal of Volcanology and Geothermal Research, v. 97, no. 1-4, p. 407-423, https://doi.org/10.1016/S0377-0273(99)00173-0.","productDescription":"17 p.","startPage":"407","endPage":"423","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":233387,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":208027,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/S0377-0273(99)00173-0"}],"volume":"97","issue":"1-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b9dd5e4b08c986b31daf1","contributors":{"authors":[{"text":"Xu, Y.","contributorId":47816,"corporation":false,"usgs":true,"family":"Xu","given":"Y.","email":"","affiliations":[],"preferred":false,"id":395032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoonen, M.A.A.","contributorId":82479,"corporation":false,"usgs":true,"family":"Schoonen","given":"M.A.A.","email":"","affiliations":[],"preferred":false,"id":395034,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nordstrom, D. Kirk 0000-0003-3283-5136 dkn@usgs.gov","orcid":"https://orcid.org/0000-0003-3283-5136","contributorId":749,"corporation":false,"usgs":true,"family":"Nordstrom","given":"D.","email":"dkn@usgs.gov","middleInitial":"Kirk","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":395035,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cunningham, K.M.","contributorId":100020,"corporation":false,"usgs":true,"family":"Cunningham","given":"K.M.","email":"","affiliations":[],"preferred":false,"id":395036,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ball, J.W.","contributorId":67507,"corporation":false,"usgs":true,"family":"Ball","given":"J.W.","affiliations":[],"preferred":false,"id":395033,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70022793,"text":"70022793 - 2000 - Reactive uptake of trace metals in the hyporheic zone of a mining- contaminated stream, Pinal Creek, Arizona","interactions":[],"lastModifiedDate":"2018-12-03T10:42:26","indexId":"70022793","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Reactive uptake of trace metals in the hyporheic zone of a mining- contaminated stream, Pinal Creek, Arizona","docAbstract":"<div class=\"hlFld-Abstract\"><div id=\"abstractBox\"><p class=\"articleBody_abstractText\">Significant uptake of dissolved metals occurred by interaction of groundwater and surface water with hyporheic-zone sediments during transport in Pinal Creek, AZ. The extent of trace metal uptake was calculated by mass balance measurements made directly within the hyporheic zone. A conservative solute tracer injected into the stream was used to quantify hydrologic exchange with the stream and groundwater. Fractional reactive uptake of dissolved metals entering the hyporheic zone was determined at 29 sites and averaged 52 ± 25, 27 ± 19, and 36 ± 24% for Co, Ni, and Zn, compared with Mn uptake of 22 ± 19%. First-order rate constants (λ<sub>h</sub>) of metal uptake in the hyporheic zone were determined at seven sites using the exchange rate of water derived from tracer arrival in the streambed. Reaction-time constants (1/λ<sub>h</sub>) averaged 0.41, 0.84, and 0.38 h for Co, Ni, and Zn, respectively, and 1.3 h for Mn. In laboratory experiments with streambed sediments, metal uptake increased with preexisting Mn oxide concentration, supporting our interpretation that Mn oxides in the hyporheic zone enhance trace metal uptake. Reach-scale mass-balance calculations that include groundwater metal inputs indicated that decreases in metal loads ranged from 12 to 68% over the 7-km perennial reach depending on the metal. The decreases in metal loads are attributed to uptake of trace metals by Mn oxides in the hyporheic zone that is enhanced because of ongoing Mn oxide formation. Analysis of dissolved-metal streambed profiles and conservative solute tracers provide a valuable tool for quantifying metal uptake or release in the hyporheic zone of contaminated streams.</p></div></div>","language":"English","publisher":"ACS","doi":"10.1021/es990714d","issn":"0013936X","usgsCitation":"Fuller, C.C., and Harvey, J., 2000, Reactive uptake of trace metals in the hyporheic zone of a mining- contaminated stream, Pinal Creek, Arizona: Environmental Science & Technology, v. 34, no. 7, p. 1150-1155, https://doi.org/10.1021/es990714d.","productDescription":"6 p.","startPage":"1150","endPage":"1155","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":233419,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":208042,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es990714d"}],"country":"United States","state":"Arizona","otherGeospatial":"Pinal Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -110.913,33.604 ], [ -110.913,33.615 ], [ -110.906,33.615 ], [ -110.906,33.604 ], [ -110.913,33.604 ] ] ] } } ] }","volume":"34","issue":"7","noUsgsAuthors":false,"publicationDate":"2000-02-25","publicationStatus":"PW","scienceBaseUri":"505a958ce4b0c8380cd81ab7","contributors":{"authors":[{"text":"Fuller, C. C.","contributorId":29858,"corporation":false,"usgs":true,"family":"Fuller","given":"C.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":394932,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harvey, J. W. 0000-0002-2654-9873","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":39725,"corporation":false,"usgs":true,"family":"Harvey","given":"J. W.","affiliations":[],"preferred":false,"id":394933,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70022366,"text":"70022366 - 2000 - Evaluation of ground-penetrating radar to detect free-phase hydrocarbons in fractured rocks: Results of numerical modeling and physical experiments","interactions":[],"lastModifiedDate":"2019-10-15T11:19:43","indexId":"70022366","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","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":"Evaluation of ground-penetrating radar to detect free-phase hydrocarbons in fractured rocks: Results of numerical modeling and physical experiments","docAbstract":"The suitability of common-offset ground-penetrating radar (GPR) to detect free-phase hydrocarbons in bedrock fractures was evaluated using numerical modeling and physical experiments. The results of one- and two-dimensional numerical modeling at 100 megahertz indicate that GPR reflection amplitudes are relatively insensitive to fracture apertures ranging from 1 to 4 mm. The numerical modeling and physical experiments indicate that differences in the fluids that fill fractures significantly affect the amplitude and the polarity of electromagnetic waves reflected by subhorizontal fractures. Air-filled and hydrocarbon-filled fractures generate low-amplitude reflections that are in-phase with the transmitted pulse. Water-filled fractures create reflections with greater amplitude and opposite polarity than those reflections created by air-filled or hydrocarbon-filled fractures. The results from the numerical modeling and physical experiments demonstrate it is possible to distinguish water-filled fracture reflections from air- or hydrocarbon-filled fracture reflections, nevertheless subsurface heterogeneity, antenna coupling changes, and other sources of noise will likely make it difficult to observe these changes in GPR field data. This indicates that the routine application of common-offset GPR reflection methods for detection of hydrocarbon-filled fractures will be problematic. Ideal cases will require appropriately processed, high-quality GPR data, ground-truth information, and detailed knowledge of subsurface physical properties. Conversely, the sensitivity of GPR methods to changes in subsurface physical properties as demonstrated by the numerical and experimental results suggests the potential of using GPR methods as a monitoring tool. GPR methods may be suited for monitoring pumping and tracer tests, changes in site hydrologic conditions, and remediation activities.The suitability of common-offset ground-penetrating radar (GPR) to detect free-phase hydrocarbons in bedrock fractures was evaluated using numerical modeling and physical experiments. The results of one- and two-dimensional numerical modeling at 100 megahertz indicate that GPR reflection amplitudes are relatively insensitive to fracture apertures ranging from 1 to 4 mm. The numerical modeling and physical experiments indicate that differences in the fluids that fill fractures significantly affect the amplitude and the polarity of electromagnetic waves reflected by subhorizontal fractures. Air-filled and hydrocarbon-filled fractures generate low-amplitude reflections that are in-phase with the transmitted pulse. Water-filled fractures create reflections with greater amplitude and opposite polarity than those reflections created by air-filled or hydrocarbon-filled fractures. The results from the numerical modeling and physical experiments demonstrate it is possible to distinguish water-filled fracture reflections from air- or hydrocarbon-filled fracture reflections, nevertheless subsurface heterogeneity, antenna coupling changes, and other sources of noise will likely make it difficult to observe these changes in GPR field data. This indicates that the routine application of common-offset GPR reflection methods for detection of hydrocarbon-filled fractures will be problematic. Ideal cases will require appropriately processed, high-quality GPR data, ground-truth information, and detailed knowledge of subsurface physical properties. Conversely, the sensitivity of GPR methods to changes in subsurface physical properties as demonstrated by the numerical and experimental results suggests the potential of using GPR methods as a monitoring tool. GPR methods may be suited for monitoring pumping and tracer tests, changes in site hydrologic conditions, and remediation activities.","language":"English","publisher":"Wiley","doi":"10.1111/j.1745-6584.2000.tb00693.x","issn":"0017467X","usgsCitation":"Lane, J., Buursink, M., Haeni, F., and Versteeg, R., 2000, Evaluation of ground-penetrating radar to detect free-phase hydrocarbons in fractured rocks: Results of numerical modeling and physical experiments: Ground Water, v. 38, no. 6, p. 929-938, https://doi.org/10.1111/j.1745-6584.2000.tb00693.x.","productDescription":"10 p.","startPage":"929","endPage":"938","costCenters":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":230608,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"6","noUsgsAuthors":false,"publicationDate":"2005-08-04","publicationStatus":"PW","scienceBaseUri":"505a0c80e4b0c8380cd52b94","contributors":{"authors":[{"text":"Lane, J.W. Jr.","contributorId":66723,"corporation":false,"usgs":true,"family":"Lane","given":"J.W.","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":393395,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buursink, M. L. 0000-0001-6491-386X","orcid":"https://orcid.org/0000-0001-6491-386X","contributorId":73658,"corporation":false,"usgs":true,"family":"Buursink","given":"M. L.","affiliations":[],"preferred":false,"id":393396,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haeni, F.P.","contributorId":87105,"corporation":false,"usgs":true,"family":"Haeni","given":"F.P.","affiliations":[],"preferred":false,"id":393398,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Versteeg, R.J.","contributorId":74159,"corporation":false,"usgs":true,"family":"Versteeg","given":"R.J.","email":"","affiliations":[],"preferred":false,"id":393397,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70022823,"text":"70022823 - 2000 - Distribution, hydrologic transport, and cycling of total mercury and methyl mercury in a contaminated river-reservoir-wetland system (Sudbury River, eastern Massachusetts)","interactions":[],"lastModifiedDate":"2012-03-12T17:20:06","indexId":"70022823","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Distribution, hydrologic transport, and cycling of total mercury and methyl mercury in a contaminated river-reservoir-wetland system (Sudbury River, eastern Massachusetts)","docAbstract":"Riparian wetlands contaminated with Hg from an industrial point source were found to be important sites of production and release of methyl mercury (MeHg) in a 40-km reach of the Sudbury River in eastern Massachusetts. Stream discharge and concentration measurements were used to calculate annual mean loads for total Hg (??Hg) and MeHg in contaminated river reaches, a reservoir, and a riparian wetland downstream from the industrial source. Budgets based on these loads indicate that the annual mean ??Hg load increased sixfold in a reach receiving flow from the point source, but the annual mean MeHg load did not increase. About 23% of the ??Hg load was removed by sedimentation during flow through the reservoir. Net production of MeHg in the reservoir was similar to that reported elsewhere for lakes receiving Hg from atmospheric deposition only. ??Hg concentrations and loads increased significantly as the river passed through the riparian wetland reach. On the basis of flooded wetland area, net production of MeHg was 15 times greater in the wetland reach than in wetland-associated drainages described in other studies.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Canadian Journal of Fisheries and Aquatic Sciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","issn":"0706652X","usgsCitation":"Waldron, M., Colman, J., and Breault, R., 2000, Distribution, hydrologic transport, and cycling of total mercury and methyl mercury in a contaminated river-reservoir-wetland system (Sudbury River, eastern Massachusetts): Canadian Journal of Fisheries and Aquatic Sciences, v. 57, no. 5, p. 1080-1091.","startPage":"1080","endPage":"1091","numberOfPages":"12","costCenters":[],"links":[{"id":233353,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0320e4b0c8380cd50358","contributors":{"authors":[{"text":"Waldron, M.C.","contributorId":33342,"corporation":false,"usgs":true,"family":"Waldron","given":"M.C.","email":"","affiliations":[],"preferred":false,"id":395027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Colman, J.A.","contributorId":63032,"corporation":false,"usgs":true,"family":"Colman","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":395028,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breault, R.F.","contributorId":102117,"corporation":false,"usgs":true,"family":"Breault","given":"R.F.","email":"","affiliations":[],"preferred":false,"id":395029,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70022792,"text":"70022792 - 2000 - Changes in herbicide concentrations in Midwestern streams in relation to changes in use, 1989-1998","interactions":[],"lastModifiedDate":"2018-12-07T10:00:50","indexId":"70022792","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5331,"text":"Science of Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Changes in herbicide concentrations in Midwestern streams in relation to changes in use, 1989-1998","docAbstract":"<p><span>Water samples were collected from Midwestern streams in 1994–1995 and 1998 as part of a study to help determine if changes in herbicide use resulted in changes in herbicide concentrations since a previous reconnaissance study in 1989–1990. Sites were sampled during the first significant runoff period after the application of pre-emergent herbicides in 1989–1990, 1994–1995, and 1998. Samples were analyzed for selected herbicides, two atrazine metabolites, three cyanazine metabolites, and one alachlor metabolite. In the Midwestern USA, alachlor use was much greater in 1989 than in 1995, whereas acetochlor was not used in 1989 but was commonly used in 1995. The use of atrazine, cyanazine, and metolachlor was approximately the same in 1989 and 1995. The median concentrations of atrazine, alachlor, cyanazine, and metolachlor were substantially higher in 1989–1990 than in 1994–1995 or 1998. The median acetochlor concentration was higher in 1998 than in 1994 or 1995.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/S0048-9697(99)00547-1","issn":"00489697","usgsCitation":"Scribner, E., Battaglin, W., Goolsby, D.A., and Thurman, E., 2000, Changes in herbicide concentrations in Midwestern streams in relation to changes in use, 1989-1998: Science of Total Environment, v. 248, no. 2-3, p. 255-263, https://doi.org/10.1016/S0048-9697(99)00547-1.","productDescription":"9 p.","startPage":"255","endPage":"263","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":233386,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":208026,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/S0048-9697(99)00547-1"}],"volume":"248","issue":"2-3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f418e4b0c8380cd4bb2c","contributors":{"authors":[{"text":"Scribner, E.A.","contributorId":50925,"corporation":false,"usgs":true,"family":"Scribner","given":"E.A.","email":"","affiliations":[],"preferred":false,"id":394930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Battaglin, W.A.","contributorId":16376,"corporation":false,"usgs":true,"family":"Battaglin","given":"W.A.","email":"","affiliations":[],"preferred":false,"id":394928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goolsby, D. A.","contributorId":50508,"corporation":false,"usgs":true,"family":"Goolsby","given":"D.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":394929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thurman, E.M.","contributorId":102864,"corporation":false,"usgs":true,"family":"Thurman","given":"E.M.","affiliations":[],"preferred":false,"id":394931,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70022818,"text":"70022818 - 2000 - Occurrence of cotton herbicides and insecticides in playa lakes of the High Plains of West Texas","interactions":[],"lastModifiedDate":"2018-12-07T10:01:24","indexId":"70022818","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5331,"text":"Science of Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Occurrence of cotton herbicides and insecticides in playa lakes of the High Plains of West Texas","docAbstract":"<p><span>During the summer of 1997, water samples were collected and analyzed for pesticides from 32 playa lakes of the High Plains that receive drainage from both cotton and corn agriculture in West Texas. The major cotton herbicides detected in the water samples were diuron, fluometuron, metolachlor, norflurazon, and prometryn. Atrazine and propazine, corn and sorghum herbicides, were also routinely detected in samples from the playa lakes. Furthermore, the metabolites of all the herbicides studied were found in the playa lake samples. In some cases, the concentration of metabolites was equal to or exceeded the concentration of the parent compound. The types of metabolites detected suggested that the parent compounds had been transported to and had undergone degradation in the playa lakes. The types of metabolites and the ratio of metabolites to parent compounds may be useful in indicating the time that the herbicides were transported to the playa lakes. The median concentration of total herbicides was 7.2 μg/l, with the largest total concentrations exceeding 30 μg/l. Organophosphate insecticides were detected in only one water sample. Further work will improve the understanding of the fate of these compounds in the playa lake area.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/S0048-9697(99)00542-2","issn":"00489697","usgsCitation":"Thurman, E., Bastian, K., and Mollhagen, T., 2000, Occurrence of cotton herbicides and insecticides in playa lakes of the High Plains of West Texas: Science of Total Environment, v. 248, no. 2-3, p. 189-200, https://doi.org/10.1016/S0048-9697(99)00542-2.","productDescription":"12 p.","startPage":"189","endPage":"200","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":233859,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":208246,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/S0048-9697(99)00542-2"}],"volume":"248","issue":"2-3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a6be2e4b0c8380cd74935","contributors":{"authors":[{"text":"Thurman, E.M.","contributorId":102864,"corporation":false,"usgs":true,"family":"Thurman","given":"E.M.","affiliations":[],"preferred":false,"id":395004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bastian, K.C.","contributorId":83694,"corporation":false,"usgs":true,"family":"Bastian","given":"K.C.","email":"","affiliations":[],"preferred":false,"id":395003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mollhagen, T.","contributorId":34693,"corporation":false,"usgs":true,"family":"Mollhagen","given":"T.","affiliations":[],"preferred":false,"id":395002,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70022951,"text":"70022951 - 2000 - Sorption of selected organic compounds from water to a peat soil and its humic-acid and humin fractions: Potential sources of the sorption nonlinearity","interactions":[],"lastModifiedDate":"2018-12-03T10:58:15","indexId":"70022951","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Sorption of selected organic compounds from water to a peat soil and its humic-acid and humin fractions: Potential sources of the sorption nonlinearity","docAbstract":"The sorption isotherms of ethylene dibromide (EDB), diuron (DUN), and 3,5-dichlorophenol (DCP) from water on the humic acid and humin fractions of a peat soil and on the humic-acid of a muck soil have been measured. The data were compared with those of the solutes with the whole peat from which the humic-acid (HA) and humin (HM) fractions were derived and on which the sorption of the solutes exhibited varying extents of nonlinear capacities at low relative concentrations (C(e)/S(w)). The HA fraction as prepared by the density-fractionated method is relatively pure and presumably free of high- surface-area carbonaceous material (HSACM) that is considered to be responsible for the observed nonlinear sorption for nonpolar solutes (e.g., EDB) on the peat; conversely, the base-insoluble HM fraction as prepared is presumed to be enriched with HSACM, as manifested by the greatly higher BET- (N2) surface area than that of the whole peat. The sorption of EDB on HA exhibits no visible nonlinear effect, whereas the sorption on HM shows an enhanced nonlinearity over that on the whole peat. The sorption of polar DUN and DCP on HA and HM display nonlinear effects comparable with those on the whole peat; the effects are much more significant than those with nonpolar EDB. These results conform to the hypothesis that adsorption onto a small amount of strongly adsorbing HSACM is largely responsible for the nonlinear sorption of nonpolar solutes on soils and that additional specific interactions with the active groups of soil organic matter are responsible for the generally higher nonlinear sorption of the polar solutes.","language":"English","publisher":"ACS","doi":"10.1021/es990261c","issn":"0013936X","usgsCitation":"Chiou, C.T., Kile, D.E., Rutherford, D., Sheng, G., and Boyd, S., 2000, Sorption of selected organic compounds from water to a peat soil and its humic-acid and humin fractions: Potential sources of the sorption nonlinearity: Environmental Science & Technology, v. 34, no. 7, p. 1254-1258, https://doi.org/10.1021/es990261c.","productDescription":"5 p.","startPage":"1254","endPage":"1258","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":233580,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":208119,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es990261c"}],"volume":"34","issue":"7","noUsgsAuthors":false,"publicationDate":"2000-03-03","publicationStatus":"PW","scienceBaseUri":"505b9310e4b08c986b31a277","contributors":{"authors":[{"text":"Chiou, C. T.","contributorId":97080,"corporation":false,"usgs":true,"family":"Chiou","given":"C.","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":395595,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kile, D. E.","contributorId":22758,"corporation":false,"usgs":true,"family":"Kile","given":"D.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":395592,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rutherford, D.W.","contributorId":21244,"corporation":false,"usgs":true,"family":"Rutherford","given":"D.W.","email":"","affiliations":[],"preferred":false,"id":395591,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sheng, G.","contributorId":70961,"corporation":false,"usgs":true,"family":"Sheng","given":"G.","email":"","affiliations":[],"preferred":false,"id":395593,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boyd, S.A.","contributorId":74517,"corporation":false,"usgs":true,"family":"Boyd","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":395594,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70022257,"text":"70022257 - 2000 - Empirical assessment of fish introductions in a subtropical wetland: An evaluation of contrasting views","interactions":[],"lastModifiedDate":"2012-03-12T17:19:46","indexId":"70022257","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Empirical assessment of fish introductions in a subtropical wetland: An evaluation of contrasting views","docAbstract":"We summarized data from eight quantitative fish surveys conducted in southern Florida to evaluate the distribution and relative abundance of introduced fishes across a variety of habitats. These surveys encompassed marsh and canal habitats throughout most of the Everglades region, including the mangrove fringe of Florida Bay. Two studies provided systematically collected density information over a 20-year period, and documented the first local appearance of four introduced fishes based on their repeated absence in prior surveys. Those species displayed a pattern of rapid population growth followed by decline, then persistence at lower densities. Estuarine areas in the southern Everglades, characterized by natural tidal creeks surrounded by mangrove-dominated marshes, and canals held the largest introduced-fish populations. Introduced fishes were also common, at times exceeding 50% of the fish community, in solution holes that serve as dry-season refuges in short-hydroperiod rockland habitats of the eastern Everglades. Wet prairies and alligator ponds distant from canals generally held few individuals of introduced fishes. These patterns suggest that the introduced fishes in southern Florida at present may not be well-adapted to persist in freshwater marshes of the Everglades, possibly because of an interaction of periodic cold-temperature stress and hydrologic fluctuation. Our analyses indicated low densities of these fishes in central or northern Everglades wet-prairie communities, and, in the absence of experimental data, little evidence of biotic effects in this spatially extensive habitat. There is no guarantee that this condition will be maintained, especially under the cumulative effects of future invasions or environmental change.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biological Invasions","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1023/A:1011488118444","issn":"13873547","usgsCitation":"Trexler, J., Loftus, W., Jordan, F., Lorenz, J., Chick, J., and Kobza, R.M., 2000, Empirical assessment of fish introductions in a subtropical wetland: An evaluation of contrasting views: Biological Invasions, v. 2, no. 4, p. 265-277, https://doi.org/10.1023/A:1011488118444.","startPage":"265","endPage":"277","numberOfPages":"13","costCenters":[],"links":[{"id":206736,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1023/A:1011488118444"},{"id":230669,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0904e4b0c8380cd51d74","contributors":{"authors":[{"text":"Trexler, J.C.","contributorId":23108,"corporation":false,"usgs":true,"family":"Trexler","given":"J.C.","email":"","affiliations":[],"preferred":false,"id":392869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loftus, W.F.","contributorId":29363,"corporation":false,"usgs":true,"family":"Loftus","given":"W.F.","email":"","affiliations":[],"preferred":false,"id":392870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jordan, F.","contributorId":80622,"corporation":false,"usgs":true,"family":"Jordan","given":"F.","affiliations":[],"preferred":false,"id":392872,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lorenz, J.J.","contributorId":67058,"corporation":false,"usgs":true,"family":"Lorenz","given":"J.J.","email":"","affiliations":[],"preferred":false,"id":392871,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chick, J.H.","contributorId":93004,"corporation":false,"usgs":true,"family":"Chick","given":"J.H.","affiliations":[],"preferred":false,"id":392873,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kobza, Robert M.","contributorId":103822,"corporation":false,"usgs":false,"family":"Kobza","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":7036,"text":"South Florida Water Management District","active":true,"usgs":false}],"preferred":false,"id":392874,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70022230,"text":"70022230 - 2000 - Modeling regional salinization of the Ogallala aquifer, Southern High Plains, TX, USA","interactions":[],"lastModifiedDate":"2012-03-12T17:19:46","indexId":"70022230","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling regional salinization of the Ogallala aquifer, Southern High Plains, TX, USA","docAbstract":"Two extensive plumes (combined area > 1000 km2) have been delineated within the Ogallala aquifer in the Southern High Plains, TX, USA. Salinity varies within the plumes spatially and increases with depth; Cl ranges from 50 to >500 mg 1-1. Variable-density flow modeling using SUTRA has identified three broad regions of upward cross-formational flow from the underlying evaporite units. The upward discharge within the modeled plume area is in the range of 10-4-10-5 m3 day-1, and the TDS concentrations are typically >3000 mg 1-1. Regions of increased salinity, identified within the Whitehorse Group (evaporite unit) underlying the Ogallala aquifer, are controlled by the structure and thickness variations relative to the recharge areas. Distinct flow paths, on the order of tens of km to >100 km in length, and varying flow velocities indicate that the salinization of the Ogallala aquifer has been a slow, ongoing process and may represent circulation of waters recharged during Pleistocene or earlier times. On-going pumping has had negligible impact on the salinity distribution in the Ogallala aquifer, although simulations indicate that the velocity distribution in the underlying units may have been affected to depths of 150 m after 30 years of pumping. Because the distribution of saline ground water in this region of the Ogallala aquifer is heterogeneous, careful areal and vertical characterization is warranted prior to any well-field development. (C) 2000 Elsevier Science B.V.Two extensive plumes (combined area >1000 km2) have been delineated within the Ogallala aquifer in the Southern High Plains, TX, USA. Salinity varies within the plumes spatially and increases with depth; Cl ranges from 50 to >500 mg l-1. Variable-density flow modeling using SUTRA has identified three broad regions of upward cross-formational flow from the underlying evaporite units. The upward discharge within the modeled plume area is in the range of 10-4-10-5 m3 day-1, and the TDS concentrations are typically >3000 mg l-1. Regions of increased salinity, identified within the Whitehorse Group (evaporite unit) underlying the Ogallala aquifer, are controlled by the structure and thickness variations relative to the recharge areas. Distinct flow paths, on the order of tens of km to >100 km in length, and varying flow velocities indicate that the salinization of the Ogallala aquifer has been a slow, ongoing process and may represent circulation of waters recharged during Pleistocene or earlier times. On-going pumping has had negligible impact on the salinity distribution in the Ogallala aquifer, although simulations indicate that the velocity distribution in the underlying units may have been affected to depths of 150 m after 30 years of pumping. Because the distribution of saline ground water in this region of the Ogallala aquifer is heterogeneous, careful areal and vertical characterization is warranted prior to any well-field development.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier Science B.V.","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/S0022-1694(00)00314-0","issn":"00221694","usgsCitation":"Mehta, S., Fryar, A., Brady, R., and Morin, R.H., 2000, Modeling regional salinization of the Ogallala aquifer, Southern High Plains, TX, USA: Journal of Hydrology, v. 238, no. 1-2, p. 44-64, https://doi.org/10.1016/S0022-1694(00)00314-0.","startPage":"44","endPage":"64","numberOfPages":"21","costCenters":[],"links":[{"id":206802,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/S0022-1694(00)00314-0"},{"id":230822,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"238","issue":"1-2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5c22e4b0c8380cd6fa71","contributors":{"authors":[{"text":"Mehta, S.","contributorId":74902,"corporation":false,"usgs":true,"family":"Mehta","given":"S.","email":"","affiliations":[],"preferred":false,"id":392778,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fryar, A.E.","contributorId":59928,"corporation":false,"usgs":true,"family":"Fryar","given":"A.E.","affiliations":[],"preferred":false,"id":392776,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brady, R.M.","contributorId":70558,"corporation":false,"usgs":true,"family":"Brady","given":"R.M.","email":"","affiliations":[],"preferred":false,"id":392777,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morin, R. H.","contributorId":31794,"corporation":false,"usgs":true,"family":"Morin","given":"R.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":392775,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70022240,"text":"70022240 - 2000 - Geochemical modeling of iron, sulfur, oxygen and carbon in a coastal plain aquifer","interactions":[],"lastModifiedDate":"2012-03-12T17:19:48","indexId":"70022240","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Geochemical modeling of iron, sulfur, oxygen and carbon in a coastal plain aquifer","docAbstract":"Fe(III) reduction in the Magothy aquifer of Long Island, NY, results in high dissolved-iron concentrations that degrade water quality. Geochemical modeling was used to constrain iron-related geochemical processes and redox zonation along a flow path. The observed increase in dissolved inorganic carbon is consistent with the oxidation of sedimentary organic matter coupled to the reduction of O2 and SO4/2- in the aerobic zone, and to the reduction of SO4/2- in the anaerobic zone; estimated rates of CO2 production through reduction of Fe(III) were relatively minor by comparison. The rates of CO2 production calculated from dissolved inorganic carbon mass transfer (2.55 x 10-4 to 48.6 x 10-4 mmol 1-1 yr-1) generally were comparable to the calculated rates of CO2 production by the combined reduction of O2, Fe(III) and SO4/2- (1.31 x 10-4 to 15 x 10-4 mmol 1-1 yr-1). The overall increase in SO4/2- concentrations along the flow path, together with the results of mass-balance calculations, and variations in ??34S values along the flow path indicate that SO4/2- loss through microbial reduction is exceeded by SO4/2- gain through diffusion from sediments and through the oxidation of FeS2. Geochemichal and microbial data on cores indicate that Fe(III) oxyhydroxide coatings on sediment grains in local, organic carbon- and SO4/2- -rich zones have localized SO4/2- -reducing zones in which the formation of iron disulfides been depleted by microbial reduction and resulted in decreases dissolved iron concentrations. These localized zones of SO4/2- reduction, which are important for assessing zones of low dissolved iron for water-supply development, could be overlooked by aquifer studies that rely only on groundwater data from well-water samples for geochemical modeling. (C) 2000 Elsevier Science B.V.Fe(III) reduction in the Magothy aquifer of Long Island, NY, results in high dissolved-iron concentrations that degrade water quality. Geochemical modeling was used to constrain iron-related geochemical processes and redox zonation along a flow path. The observed increase in dissolved inorganic carbon is consistent with the oxidation of sedimentary organic matter coupled to the reduction of O2 and SO42- in the aerobic zone, and to the reduction of SO42- in the anaerobic zone; estimated rates of CO2 production through reduction of Fe(III) were relatively minor by comparison. The rates of CO2 production calculated from dissolved inorganic carbon mass transfer (2.55??10-4 to 48.6??10-4mmol l-1yr-1) generally were comparable to the calculated rates of CO2 production by the combined reduction of O2, Fe(III) and SO42- (1.31??10-4 to 15??10-4mmol l-1yr-1). The overall increase in SO42- concentrations along the flow path, together with the results of mass-balance calculations, and variations in ??34S values along the flow path indicate that SO42- loss through microbial reduction is exceeded by SO42- gain through diffusion from sediments and through the oxidation of FeS2. Geochemical and microbial data on cores indicate that Fe(III) oxyhydroxide coatings on sediment grains in local, organic carbon- and SO42--rich zones have been depleted by microbial reduction and resulted in localized SO42--reducing zones in which the formation of iron disulfides decreases dissolved iron concentrations. These localized zones of SO42- reduction, which are important for assessing zones of low dissolved iron for water-supply development, could be overlooked by aquifer studies that rely only on groundwater data from well-water samples for geochemical modeling.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier Science B.V.","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/S0022-1694(00)00296-1","issn":"00221694","usgsCitation":"Brown, C.J., Schoonen, M., and Candela, J., 2000, Geochemical modeling of iron, sulfur, oxygen and carbon in a coastal plain aquifer: Journal of Hydrology, v. 237, no. 3-4, p. 147-168, https://doi.org/10.1016/S0022-1694(00)00296-1.","startPage":"147","endPage":"168","numberOfPages":"22","costCenters":[],"links":[{"id":206607,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/S0022-1694(00)00296-1"},{"id":230368,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"237","issue":"3-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a1688e4b0c8380cd551a6","contributors":{"authors":[{"text":"Brown, C. J.","contributorId":90342,"corporation":false,"usgs":true,"family":"Brown","given":"C.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":392818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoonen, M.A.A.","contributorId":82479,"corporation":false,"usgs":true,"family":"Schoonen","given":"M.A.A.","email":"","affiliations":[],"preferred":false,"id":392817,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Candela, J.L.","contributorId":6884,"corporation":false,"usgs":true,"family":"Candela","given":"J.L.","email":"","affiliations":[],"preferred":false,"id":392816,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70022948,"text":"70022948 - 2000 - Pesticides in the atmosphere of the Mississippi River Valley, part II: Air","interactions":[],"lastModifiedDate":"2021-05-28T16:34:14.011048","indexId":"70022948","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5331,"text":"Science of Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Pesticides in the atmosphere of the Mississippi River Valley, part II: Air","docAbstract":"<p><span>Weekly composite air samples were collected from early April through to mid-September 1995 at three paired urban and agricultural sites along the Mississippi River region of the Midwestern United States. The paired sampling sites were located in Mississippi, Iowa, and Minnesota. A background site, removed from dense urban and agricultural areas, was located on the shore of Lake Superior in Michigan. Each sample was analyzed for 49 compounds; of these, 21 of 26 herbicides, 13 of 19 insecticides, and 4 of 4 related transformation products were detected during the study, with most pesticides detected in more than one sample. The maximum number of pesticides detected in an air sample was 18. Herbicides were the predominant type of pesticide detected at every site. Detection frequencies of most herbicides were similar at the urban and agricultural sites in Iowa and Minnesota. In Mississippi, herbicides generally were detected more frequently at the agricultural site. The insecticides chlorpyrifos, diazinon, and carbaryl, which are used in agricultural and non-agricultural settings, were detected more frequently in urban sites than agricultural sites in Mississippi and Iowa. Methyl parathion was detected in 70% of the samples from the Mississippi agricultural site and at the highest concentration (62 ng/m</span><sup>3</sup><span>&nbsp;air) of any insecticide measured in the study. At the background site, dacthal (100%), atrazine (35%), cyanazine (22%), and the (primarily atrazine) triazine transformation products CIAT (35%) and CEAT (17%) were detected most frequently, suggesting their potential for long-range atmospheric transport.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/S0048-9697(99)00544-6","usgsCitation":"Foreman, W., Majewski, M., Goolsby, D.A., Wiebe, F., and Coupe, R., 2000, Pesticides in the atmosphere of the Mississippi River Valley, part II: Air: Science of Total Environment, v. 248, no. 2-3, p. 213-226, https://doi.org/10.1016/S0048-9697(99)00544-6.","productDescription":"14 p.","startPage":"213","endPage":"226","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":233505,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mississippi River Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.76953125,\n              30.334953881988564\n            ],\n            [\n              -88.154296875,\n              35.02999636902566\n            ],\n            [\n              -83.6279296875,\n              35.35321610123823\n            ],\n            [\n              -81.650390625,\n              36.27970720524017\n            ],\n            [\n              -83.84765625,\n              36.59788913307022\n            ],\n            [\n              -82.001953125,\n              37.50972584293751\n            ],\n            [\n              -82.9248046875,\n              38.47939467327645\n            ],\n            [\n              -80.6396484375,\n              39.740986355883564\n            ],\n            [\n              -80.6396484375,\n              41.96765920367816\n            ],\n            [\n              -83.3642578125,\n              41.705728515237524\n            ],\n            [\n              -82.5732421875,\n              43.16512263158296\n            ],\n            [\n              -83.0126953125,\n              44.05601169578525\n            ],\n            [\n              -83.5400390625,\n              45.24395342262324\n            ],\n            [\n              -83.8916015625,\n              46.40756396630067\n            ],\n            [\n              -85.1220703125,\n              46.89023157359399\n            ],\n            [\n              -88.2861328125,\n              47.45780853075031\n            ],\n            [\n              -89.912109375,\n              48.07807894349862\n            ],\n            [\n              -95.5810546875,\n              48.922499263758255\n            ],\n            [\n              -96.8994140625,\n              49.03786794532644\n            ],\n            [\n              -96.591796875,\n              43.61221676817573\n            ],\n            [\n              -95.7568359375,\n              40.78054143186033\n            ],\n            [\n              -94.658203125,\n              38.92522904714054\n            ],\n            [\n              -94.52636718749999,\n              35.88905007936091\n            ],\n            [\n              -94.482421875,\n              33.46810795527896\n            ],\n            [\n              -93.955078125,\n              33.358061612778876\n            ],\n            [\n              -94.04296874999999,\n              31.98944183792288\n            ],\n            [\n              -93.55957031249999,\n              30.789036751261136\n            ],\n            [\n              -93.6474609375,\n              29.80251790576445\n            ],\n            [\n              -90.3076171875,\n              29.075375179558346\n            ],\n            [\n              -88.76953125,\n              30.334953881988564\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"248","issue":"2-3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a776de4b0c8380cd784be","contributors":{"authors":[{"text":"Foreman, W.T.","contributorId":94684,"corporation":false,"usgs":true,"family":"Foreman","given":"W.T.","email":"","affiliations":[],"preferred":false,"id":395577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Majewski, M.S.","contributorId":88501,"corporation":false,"usgs":true,"family":"Majewski","given":"M.S.","email":"","affiliations":[],"preferred":false,"id":395576,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goolsby, D. A.","contributorId":50508,"corporation":false,"usgs":true,"family":"Goolsby","given":"D.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":395573,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiebe, F.W.","contributorId":83311,"corporation":false,"usgs":true,"family":"Wiebe","given":"F.W.","email":"","affiliations":[],"preferred":false,"id":395574,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coupe, R.H.","contributorId":84778,"corporation":false,"usgs":true,"family":"Coupe","given":"R.H.","affiliations":[],"preferred":false,"id":395575,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70022945,"text":"70022945 - 2000 - Age of irrigation water in ground water from the Eastern Snake River Plain Aquifer, south-central Idaho","interactions":[],"lastModifiedDate":"2018-12-12T08:24:51","indexId":"70022945","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","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":"Age of irrigation water in ground water from the Eastern Snake River Plain Aquifer, south-central Idaho","docAbstract":"Stable isotope data (<sup>2</sup>H and <sup>18</sup>O) were used in conjunction with chlorofluorocarbon (CFC) and tritium/helium-3 (<sup>3</sup>H/<sup>3</sup>He) data to determine the fraction and age of irrigation water in ground water mixtures from farmed parts of the Eastern Snake River Plain (ESRP) Aquifer in south-central Idaho. Two groups of waters were recognized: (1) regional background water, unaffected by irrigation and fertilizer application, and (2) mixtures of irrigation water from the Snake River with regional background water. New data are presented comparing CFC and <sup>3</sup>H/<sup>3</sup>He dating of water recharged through deep fractured basalt, and dating of young fractions in ground water mixtures. The <sup>3</sup>H/<sup>3</sup>He ages of irrigation water in most mixtures ranged from about zero to eight years. The CFC ages of irrigation water in mixtures ranged from values near those based on <sup>3</sup>H/<sup>3</sup>He dating to values biased older than the <sup>3</sup>H/<sup>3</sup>He ages by as much as eight to 10 years. Unsaturated zone air had CFC-12 and CFC-113 concentrations that were 60% to 95%, and 50% to 90%, respectively, of modern air concentrations and were consistently contaminated with CFC-11. Irrigation water diverted from the Snake River was contaminated with CFC-11 but near solubility equilibrium with CFC-12 and CFC-113. The dating indicates ground water velocities of 5 to 8 m/d for water along the top of the ESRP Aquifer near the southwestern boundary of the Idaho National Engineering and Environmental Laboratory (INEEL). Many of the regional background waters contain excess terrigenic helium with a <sup>3</sup>He/<sup>4</sup>He isotope ratio of 7 x 10-6 to 11 x 10-6 (R/R<sub>a</sub> = 5 to 8) and could not be dated. Ratios of CFC data indicate that some rangeland water may contain as much as 5% to 30% young water (ages of less than or equal to two to 11.5 years) mixed with old regional background water. The relatively low residence times of ground water in irrigated parts of the ESRP Aquifer and the dilution with low-NO<sub>3</sub> irrigation water from the Snake River lower the potential for NO<sub>3</sub> contamination in agricultural areas.","language":"English","publisher":"NGWA","doi":"10.1111/j.1745-6584.2000.tb00338.x","issn":"0017467X","usgsCitation":"Plummer, N., Rupert, M., Busenberg, E., and Schlosser, P., 2000, Age of irrigation water in ground water from the Eastern Snake River Plain Aquifer, south-central Idaho: Ground Water, v. 38, no. 2, p. 264-283, https://doi.org/10.1111/j.1745-6584.2000.tb00338.x.","productDescription":"20 p.","startPage":"264","endPage":"283","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":233466,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278546,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1745-6584.2000.tb00338.x"}],"volume":"38","issue":"2","noUsgsAuthors":false,"publicationDate":"2005-08-04","publicationStatus":"PW","scienceBaseUri":"5059e8efe4b0c8380cd47fb5","contributors":{"authors":[{"text":"Plummer, Niel 0000-0002-4020-1013 nplummer@usgs.gov","orcid":"https://orcid.org/0000-0002-4020-1013","contributorId":190100,"corporation":false,"usgs":true,"family":"Plummer","given":"Niel","email":"nplummer@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":395566,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rupert, M.G.","contributorId":24455,"corporation":false,"usgs":true,"family":"Rupert","given":"M.G.","email":"","affiliations":[],"preferred":false,"id":395564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Busenberg, E.","contributorId":56796,"corporation":false,"usgs":true,"family":"Busenberg","given":"E.","affiliations":[],"preferred":false,"id":395565,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schlosser, P.","contributorId":106656,"corporation":false,"usgs":true,"family":"Schlosser","given":"P.","email":"","affiliations":[],"preferred":false,"id":395567,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70022258,"text":"70022258 - 2000 - Drainage-basis-scale geomorphic analysis to determine refernce conditions for ecologic restoration-Kissimmee River, Florida","interactions":[],"lastModifiedDate":"2022-09-22T15:01:46.5241","indexId":"70022258","displayToPublicDate":"2000-01-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Drainage-basis-scale geomorphic analysis to determine refernce conditions for ecologic restoration-Kissimmee River, Florida","docAbstract":"<p>Major controls on the retention, distribution, and discharge of surface water in the historic (precanal) Kissimmee drainage basin and river were investigated to determine reference conditions for ecosystem restoration. Precanal Kissimmee drainage-basin hydrology was largely controlled by landforms derived from relict, coastal ridge, lagoon, and shallow-shelf features; widespread carbonate solution depressions; and a poorly developed fluvial drainage network. Prior to channelization for flood control, the Kissimmee River was a very low gradient, moderately meandering river that flowed from Lake Kissimmee to Lake Okeechobee through the lower drainage basin.</p><p>We infer that during normal wet seasons, river discharge rapidly exceeded Lake Okeechobee outflow capacity, and excess surface water backed up into the low-gradient Kissimmee River. This backwater effect induced bankfull and peak discharge early in the flood cycle and transformed the flood plain into a shallow aquatic system with both lacustrine and riverine characteristics. The large volumes of surface water retained in the lakes and wetlands of the upper basin maintained overbank flow conditions for several months after peak discharge. Analysis indicates that most of the geomorphic work on the channel and flood plain occurred during the frequently recurring extended periods of overbank discharge and that discharge volume may have been significant in determining channel dimensions.</p><p>Comparison of hydrogeomorphic relationships with other river systems identified links between geomorphology and hydrology of the precanal Kissimmee River. However, drainage-basin and hydraulic geometry models derived solely from general populations of river systems may produce spurious reference conditions for restoration design criteria.</p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/0016-7606(2000)112<884:DGATDR>2.0.CO;2","issn":"00167606","usgsCitation":"Warne, A., Toth, L., and White, W., 2000, Drainage-basis-scale geomorphic analysis to determine refernce conditions for ecologic restoration-Kissimmee River, Florida: Geological Society of America Bulletin, v. 112, no. 6, p. 884-899, https://doi.org/10.1130/0016-7606(2000)112<884:DGATDR>2.0.CO;2.","productDescription":"16 p.","startPage":"884","endPage":"899","costCenters":[],"links":[{"id":230670,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Kissimmee River, Lake Kissimmee, Lake Okeechobee","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.18690490722655,\n              27.800817328100297\n            ],\n            [\n              -81.19102478027344,\n              27.870644599673355\n            ],\n            [\n              -81.20201110839844,\n              27.877321374551116\n            ],\n            [\n              -81.21986389160156,\n              27.93254072134666\n            ],\n            [\n              -81.22055053710938,\n              27.955591004642553\n            ],\n            [\n              -81.29539489746094,\n              28.002283068261377\n            ],\n            [\n              -81.32011413574219,\n              27.99803917062052\n            ],\n            [\n              -81.30569458007812,\n              27.977423576428517\n            ],\n            [\n              -81.34620666503906,\n              27.97499795326776\n            ],\n            [\n              -81.36886596679688,\n              27.97984914504167\n            ],\n            [\n              -81.36817932128906,\n              27.971359416256693\n            ],\n            [\n              -81.34963989257812,\n              27.934967298584915\n            ],\n            [\n              -81.31599426269531,\n              27.921013735392084\n            ],\n            [\n              -81.32148742675781,\n              27.90159708626247\n            ],\n            [\n              -81.31050109863281,\n              27.883390812774888\n            ],\n            [\n              -81.309814453125,\n              27.867609565973098\n            ],\n            [\n              -81.30775451660156,\n              27.859111019382624\n            ],\n            [\n              -81.24938964843749,\n              27.840897604499386\n            ],\n            [\n              -81.24114990234374,\n              27.8421119273228\n            ],\n            [\n              -81.2164306640625,\n              27.81782288866404\n            ],\n            [\n              -81.221923828125,\n              27.79352841586229\n            ],\n            [\n              -81.16561889648438,\n              27.685352198428955\n            ],\n            [\n              -81.17385864257812,\n              27.67379895781762\n            ],\n            [\n              -81.17935180664061,\n              27.581937684694736\n            ],\n            [\n              -81.22673034667969,\n              27.54480631775389\n            ],\n            [\n              -81.21780395507811,\n              27.492435852729894\n            ],\n            [\n              -81.18690490722655,\n              27.421147650741265\n            ],\n            [\n              -81.12648010253906,\n              27.38030375235113\n            ],\n            [\n              -81.05575561523438,\n              27.34554408168226\n            ],\n            [\n              -81.05026245117188,\n              27.31565424126349\n            ],\n            [\n              -81.02210998535156,\n              27.290027966206214\n            ],\n            [\n              -80.98297119140625,\n              27.21433494529935\n            ],\n            [\n              -80.96992492675781,\n              27.178301644674047\n            ],\n            [\n              -80.8978271484375,\n              27.15447663185513\n            ],\n            [\n              -81.02485656738281,\n              27.039556602163195\n            ],\n            [\n              -81.11686706542967,\n              26.974097380304208\n            ],\n            [\n              -81.09832763671875,\n              26.93492599433896\n            ],\n            [\n              -81.03103637695311,\n              26.866343323987433\n            ],\n            [\n              -80.97267150878906,\n              26.882268012500234\n            ],\n            [\n              -80.93971252441406,\n              26.759712731468568\n            ],\n            [\n              -80.82778930664062,\n              26.69163742147271\n            ],\n            [\n              -80.73165893554688,\n              26.676913083105454\n            ],\n            [\n              -80.67741394042969,\n              26.748063090366852\n            ],\n            [\n              -80.6890869140625,\n              26.800170623841804\n            ],\n            [\n              -80.64788818359375,\n              26.83203637945121\n            ],\n            [\n              -80.60531616210938,\n              26.895740996697807\n            ],\n            [\n              -80.60462951660156,\n              26.974097380304208\n            ],\n            [\n              -80.65132141113281,\n              27.088473156555896\n            ],\n            [\n              -80.65475463867188,\n              27.112923428713707\n            ],\n            [\n              -80.73234558105469,\n              27.18685297304107\n            ],\n            [\n              -80.7879638671875,\n              27.216777459372924\n            ],\n            [\n              -80.83946228027344,\n              27.202732272259045\n            ],\n            [\n              -80.96786499023438,\n              27.254629577800063\n            ],\n            [\n              -80.98640441894531,\n              27.37908429955532\n            ],\n            [\n              -81.06124877929688,\n              27.423585614918853\n            ],\n            [\n              -81.10176086425781,\n              27.53993569880378\n            ],\n            [\n              -81.09695434570312,\n              27.647039394312074\n            ],\n            [\n              -81.18690490722655,\n              27.800817328100297\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"112","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a03d3e4b0c8380cd50680","contributors":{"authors":[{"text":"Warne, A.G.","contributorId":97669,"corporation":false,"usgs":true,"family":"Warne","given":"A.G.","email":"","affiliations":[],"preferred":false,"id":392877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Toth, L.A.","contributorId":55174,"corporation":false,"usgs":true,"family":"Toth","given":"L.A.","email":"","affiliations":[],"preferred":false,"id":392876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, W.A.","contributorId":24489,"corporation":false,"usgs":true,"family":"White","given":"W.A.","email":"","affiliations":[],"preferred":false,"id":392875,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
]}