{"pageNumber":"456","pageRowStart":"11375","pageSize":"25","recordCount":69053,"records":[{"id":70170089,"text":"70170089 - 2016 - High rates of detection of Clade 2.3.4.4 Highly Pathogenic Avian Influenza H5 viruses in wild birds in the Pacific Northwest during the winter of 2014-2015","interactions":[],"lastModifiedDate":"2018-01-03T13:03:50","indexId":"70170089","displayToPublicDate":"2016-04-06T12:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":948,"text":"Avian Diseases","active":true,"publicationSubtype":{"id":10}},"title":"High rates of detection of Clade 2.3.4.4 Highly Pathogenic Avian Influenza H5 viruses in wild birds in the Pacific Northwest during the winter of 2014-2015","docAbstract":"<p><span>In 2014, Clade 2.3.4.4 H5N8 highly pathogenic avian influenza (HPAI) viruses spread across the Republic of Korea and ultimately were reported in China, Japan, Russia and Europe. Mortality associated with a reassortant HPAI H5N2 virus was detected in poultry farms in Western Canada at the end of November. The same strain (with identical genetic structure) was then detected in free-living wild birds that had died prior to December 8 of unrelated causes in Whatcom County, Washington, USA in an area contiguous with the index Canadian location. A gyrfalcon (Falco rusticolus) that had hunted and fed on an American wigeon (Anas americana) on December 6 in the same area and died two days later, tested positive for the Eurasian origin HPAI H5N8. Subsequently, an Active Surveillance Program using hunter-harvest waterfowl in Washington and Oregon detected ten HPAI H5 viruses, of three different subtypes (four H5N2, three H5N8 and three H5N1) with 4 segments in common (HA, PB2, NP and MA). In addition, a mortality-based Passive Surveillance Program detected 18 HPAI (14 H5N2 and four H5N8) cases from Idaho, Kansas, Oregon, Minnesota, Montana, Washington and Wisconsin. Comparatively, mortality-based passive surveillance appears to be detecting these HPAI infections at a higher rate than active surveillance during the period following initial introduction into the US.</span></p>","language":"English","publisher":"American Association of Avian Pathologists","publisherLocation":"Ithaca, NY","doi":"10.1637/11137-050815-Reg","usgsCitation":"Ip, S., Dusek, R.J., Bodenstein, B., Kim Torchetti, M., DeBruyn, P., Mansfield, K.G., DeLiberto, T., and Sleeman, J.M., 2016, High rates of detection of Clade 2.3.4.4 Highly Pathogenic Avian Influenza H5 viruses in wild birds in the Pacific Northwest during the winter of 2014-2015: Avian Diseases, v. 60, no. 1s, p. 354-358, https://doi.org/10.1637/11137-050815-Reg.","productDescription":"5 p.","startPage":"354","endPage":"358","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065496","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":319830,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"1s","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5719f9b9e4b071321fe22bd1","contributors":{"authors":[{"text":"Ip, S. 0000-0003-4844-7533 hip@usgs.gov","orcid":"https://orcid.org/0000-0003-4844-7533","contributorId":727,"corporation":false,"usgs":true,"family":"Ip","given":"S.","email":"hip@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":626102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dusek, Robert J. 0000-0001-6177-7479 rdusek@usgs.gov","orcid":"https://orcid.org/0000-0001-6177-7479","contributorId":152316,"corporation":false,"usgs":true,"family":"Dusek","given":"Robert","email":"rdusek@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":626113,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bodenstein, Barbara L. 0000-0001-7946-0103 bbodenstein@usgs.gov","orcid":"https://orcid.org/0000-0001-7946-0103","contributorId":139354,"corporation":false,"usgs":true,"family":"Bodenstein","given":"Barbara L.","email":"bbodenstein@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":626114,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kim Torchetti, Mia","contributorId":139355,"corporation":false,"usgs":false,"family":"Kim Torchetti","given":"Mia","email":"","affiliations":[{"id":12747,"text":"USDA APHIS VS National Veterinary Services Laboratories, Ames, IA","active":true,"usgs":false}],"preferred":false,"id":626103,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeBruyn, Paul","contributorId":139364,"corporation":false,"usgs":false,"family":"DeBruyn","given":"Paul","email":"","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":626111,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mansfield, Kristin G.","contributorId":139359,"corporation":false,"usgs":false,"family":"Mansfield","given":"Kristin","email":"","middleInitial":"G.","affiliations":[{"id":12748,"text":"State of Washington","active":true,"usgs":false}],"preferred":false,"id":626112,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DeLiberto, Thomas J.","contributorId":139362,"corporation":false,"usgs":false,"family":"DeLiberto","given":"Thomas J.","affiliations":[{"id":12749,"text":"USDA APHIS National Wildlife Research Center, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":626117,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sleeman, Jonathan M. 0000-0002-9910-6125 jsleeman@usgs.gov","orcid":"https://orcid.org/0000-0002-9910-6125","contributorId":128,"corporation":false,"usgs":true,"family":"Sleeman","given":"Jonathan","email":"jsleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":626118,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70170072,"text":"70170072 - 2016 - Differentiating sex and species of Western Grebes (<i>Aechmophorus occidentalis</i>) and Clark's Grebes (<i>Aechmophorus clarkii</i>) and their eggs using external morphometrics and discriminant function analysis","interactions":[],"lastModifiedDate":"2018-08-07T11:53:57","indexId":"70170072","displayToPublicDate":"2016-04-06T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Differentiating sex and species of Western Grebes (<i>Aechmophorus occidentalis</i>) and Clark's Grebes (<i>Aechmophorus clarkii</i>) and their eggs using external morphometrics and discriminant function analysis","docAbstract":"<p><span>In birds where males and females are similar in size and plumage, sex determination by alternative means is necessary. Discriminant function analysis based on external morphometrics was used to distinguish males from females in two closely related species: Western Grebe (</span><i>Aechmophorus occidentalis</i><span>) and Clark's Grebe (</span><i>A. clarkii</i><span>). Additionally, discriminant function analysis was used to evaluate morphometric divergence between Western and Clark's grebe adults and eggs.&nbsp;</span><i>Aechmophorus</i><span>&nbsp;grebe adults (</span><i>n</i><span>&nbsp;= 576) and eggs (</span><i>n</i><span>&nbsp;= 130) were sampled across 29 lakes and reservoirs throughout California, USA, and adult sex was determined using molecular analysis. Both Western and Clark's grebes exhibited considerable sexual size dimorphism. Males averaged 6&ndash;26% larger than females among seven morphological measurements, with the greatest sexual size dimorphism occurring for bill morphometrics. Discriminant functions based on bill length, bill depth, and short tarsus length correctly assigned sex to 98% of Western Grebes, and a function based on bill length and bill depth correctly assigned sex to 99% of Clark's Grebes. Further, a simplified discriminant function based only on bill depth correctly assigned sex to 96% of Western Grebes and 98% of Clark's Grebes. In contrast, external morphometrics were not suitable for differentiating between Western and Clark's grebe adults or their eggs, with correct classification rates of discriminant functions of only 60%, 63%, and 61% for adult males, adult females, and eggs, respectively. Our results indicate little divergence in external morphology between species of&nbsp;</span><i>Aechmophorus</i><span>&nbsp;grebes, and instead separation is much greater between males and females.</span></p>","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.039.0103","usgsCitation":"Hartman, C.A., Ackerman, J., Eagles-Smith, C.A., and Herzog, M.P., 2016, Differentiating sex and species of Western Grebes (<i>Aechmophorus occidentalis</i>) and Clark's Grebes (<i>Aechmophorus clarkii</i>) and their eggs using external morphometrics and discriminant function analysis: Waterbirds, v. 39, no. 1, p. 13-26, https://doi.org/10.1675/063.039.0103.","productDescription":"14 p.","startPage":"13","endPage":"26","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068816","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":319822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"572477a4e4b0b13d3914e046","contributors":{"authors":[{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131109,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":626025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":626024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":626027,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70170085,"text":"70170085 - 2016 - Semi-arid vegetation response to antecedent climate and water balance windows","interactions":[],"lastModifiedDate":"2016-06-15T16:24:21","indexId":"70170085","displayToPublicDate":"2016-04-06T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":849,"text":"Applied Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Semi-arid vegetation response to antecedent climate and water balance windows","docAbstract":"<div id=\"avsc12232-sec-0001\" class=\"section\">\n<h4>Questions</h4>\n<div class=\"para\">\n<p>Can we improve understanding of vegetation response to water availability on monthly time scales in semi-arid environments using remote sensing methods? What climatic or water balance variables and antecedent windows of time associated with these variables best relate to the condition of vegetation? Can we develop credible near-term forecasts from climate data that can be used to prepare for future climate change effects on vegetation?</p>\n</div>\n</div>\n<div id=\"avsc12232-sec-0002\" class=\"section\">\n<h4>Location</h4>\n<div class=\"para\">\n<p>Semi-arid grasslands in Capitol Reef National Park, Utah, USA.</p>\n</div>\n</div>\n<div id=\"avsc12232-sec-0003\" class=\"section\">\n<h4>Methods</h4>\n<div class=\"para\">\n<p>We built vegetation response models by relating the normalized difference vegetation index (NDVI) from MODIS imagery in Mar&ndash;Nov 2000&ndash;2013 to antecedent climate and water balance variables preceding the monthly NDVI observations. We compared how climate and water balance variables explained vegetation greenness and then used a multi-model ensemble of climate and water balance models to forecast monthly NDVI for three holdout years.</p>\n</div>\n</div>\n<div id=\"avsc12232-sec-0004\" class=\"section\">\n<h4>Results</h4>\n<div class=\"para\">\n<p>Water balance variables explained vegetation greenness to a greater degree than climate variables for most growing season months. Seasonally important variables included measures of antecedent water input and storage in spring, switching to indicators of drought, input or use in summer, followed by antecedent moisture availability in autumn. In spite of similar climates, there was evidence the grazed grassland showed a response to drying conditions 1&nbsp;mo sooner than the ungrazed grassland. Lead times were generally short early in the growing season and antecedent window durations increased from 3&nbsp;mo early in the growing season to 1&nbsp;yr or more as the growing season progressed. Forecast accuracy for three holdout years using a multi-model ensemble of climate and water balance variables outperformed forecasts made with a na&iuml;ve NDVI climatology.</p>\n</div>\n</div>\n<div id=\"avsc12232-sec-0005\" class=\"section\">\n<h4>Conclusions</h4>\n<div class=\"para\">\n<p>We determined the influence of climate and water balance on vegetation at a fine temporal scale, which presents an opportunity to forecast vegetation response with short lead times. This understanding was obtained through high-frequency vegetation monitoring using remote sensing, which reduces the costs and time necessary for field measurements and can lead to more rapid detection of vegetation changes that could help managers take appropriate actions.</p>\n</div>\n</div>","language":"English","publisher":"Wiley","doi":"10.1111/avsc.12232","usgsCitation":"Thoma, D.P., Munson, S.M., Irvine, K.M., Witwicki, D.L., and Bunting, E., 2016, Semi-arid vegetation response to antecedent climate and water balance windows: Applied Vegetation Science, v. 19, no. 3, p. 413-429, https://doi.org/10.1111/avsc.12232.","productDescription":"17 p.","startPage":"413","endPage":"429","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068856","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":319819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-30","publicationStatus":"PW","scienceBaseUri":"572477b1e4b0b13d3914e14e","contributors":{"authors":[{"text":"Thoma, David P.","contributorId":45975,"corporation":false,"usgs":true,"family":"Thoma","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":626080,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":626079,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":626081,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Witwicki, Dana L.","contributorId":72473,"corporation":false,"usgs":true,"family":"Witwicki","given":"Dana","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":626082,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bunting, Erin 0000-0001-9103-6065 ebunting@usgs.gov","orcid":"https://orcid.org/0000-0001-9103-6065","contributorId":168488,"corporation":false,"usgs":true,"family":"Bunting","given":"Erin","email":"ebunting@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":626083,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70170086,"text":"70170086 - 2016 - Effect of variable annual precipitation and nutrient input on nitrogen and phosphorus transport from two Midwestern agricultural watersheds","interactions":[],"lastModifiedDate":"2016-08-17T11:01:21","indexId":"70170086","displayToPublicDate":"2016-04-06T11:45:00","publicationYear":"2016","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":"Effect of variable annual precipitation and nutrient input on nitrogen and phosphorus transport from two Midwestern agricultural watersheds","docAbstract":"<p><span>Precipitation patterns and nutrient inputs affect transport of nitrate (NO</span><sub>3</sub><span>-N) and phosphorus (TP) from Midwest watersheds. Nutrient concentrations and yields from two subsurface-drained watersheds, the Little Cobb River (LCR) in southern Minnesota and the South Fork Iowa River (SFIR) in northern Iowa, were evaluated during 1996&ndash;2007 to document relative differences in timings and amounts of nutrients transported. Both watersheds are located in the prairie pothole region, but the SFIR exhibits a longer growing season and more livestock production. The SFIR yielded significantly more NO</span><sub>3</sub><span>-N than the LCR watershed (31.2 versus 21.3&nbsp;kg&nbsp;NO</span><sub>3</sub><span>-N&nbsp;ha</span><sup>&minus;&nbsp;1</sup><span>&nbsp;y</span><sup>&minus;&nbsp;1</sup><span>). The SFIR watershed also yielded more TP than the LCR watershed (1.13 versus 0.51&nbsp;kg&nbsp;TP&nbsp;ha</span><sup>&minus;&nbsp;1</sup><span>&nbsp;yr</span><sup>&minus;&nbsp;1</sup><span>), despite greater TP concentrations in the LCR. About 65% of NO</span><sub>3</sub><span>-N and 50% of TP loads were transported during April&ndash;June, and &lt;&nbsp;20% of the annual loads were transported later in the growing season from July&ndash;September. Monthly NO</span><sub>3</sub><span>-N and TP loads peaked in April from the LCR but peaked in June from the SFIR; this difference was attributed to greater snowmelt runoff in the LCR. The annual NO</span><sub>3</sub><span>-N yield increased with increasing annual runoff at a similar rate in both watersheds, but the LCR watershed yielded less annual NO</span><sub>3</sub><span>-N than the SFIR for a similar annual runoff. These two watersheds are within 150 km of one another and have similar dominant agricultural systems, but differences in climate and cropping inputs affected amounts and timing of nutrient transport.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.03.127","usgsCitation":"Kalkhoff, S.J., Hubbard, L.E., Tomer, M.D., and James, D., 2016, Effect of variable annual precipitation and nutrient input on nitrogen and phosphorus transport from two Midwestern agricultural watersheds: Science of the Total Environment, v. 559, p. 53-62, https://doi.org/10.1016/j.scitotenv.2016.03.127.","productDescription":"10 p.","startPage":"53","endPage":"62","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066764","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":471088,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.03.127","text":"Publisher Index Page"},{"id":319818,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"559","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"572477a5e4b0b13d3914e070","chorus":{"doi":"10.1016/j.scitotenv.2016.03.127","url":"http://dx.doi.org/10.1016/j.scitotenv.2016.03.127","publisher":"Elsevier BV","authors":"Kalkhoff S.J., Hubbard L.E., Tomer M.D., James D.E.","journalName":"Science of The Total Environment","publicationDate":"7/2016","publiclyAccessibleDate":"4/5/2017"},"contributors":{"authors":[{"text":"Kalkhoff, Stephen J. 0000-0003-4110-1716 sjkalkho@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-1716","contributorId":1731,"corporation":false,"usgs":true,"family":"Kalkhoff","given":"Stephen","email":"sjkalkho@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hubbard, Laura E. 0000-0003-3813-1500 lhubbard@usgs.gov","orcid":"https://orcid.org/0000-0003-3813-1500","contributorId":4221,"corporation":false,"usgs":true,"family":"Hubbard","given":"Laura","email":"lhubbard@usgs.gov","middleInitial":"E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tomer, Mark D.","contributorId":168489,"corporation":false,"usgs":false,"family":"Tomer","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":25309,"text":"U.S. Department of Agriculture Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":626086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"James, D.E.","contributorId":22927,"corporation":false,"usgs":true,"family":"James","given":"D.E.","email":"","affiliations":[],"preferred":false,"id":626087,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70159959,"text":"ofr20151231 - 2016 - Report of the River Master of the Delaware River for the period December 1, 2008–November 30, 2009","interactions":[],"lastModifiedDate":"2016-04-06T10:42:33","indexId":"ofr20151231","displayToPublicDate":"2016-04-06T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1231","title":"Report of the River Master of the Delaware River for the period December 1, 2008–November 30, 2009","docAbstract":"<p>A Decree of the Supreme Court of the United States, entered June 7, 1954, established the position of Delaware River Master within the U.S. Geological Survey (USGS). In addition, the Decree authorizes diversions of water from the Delaware River Basin and requires compensating releases from certain reservoirs, owned by New York City, to be made under the supervision and direction of the River Master. The Decree stipulates that the River Master will furnish reports to the Court, not less frequently than annually. This report is the 56th Annual Report of the River Master of the Delaware River. It covers the 2009 River Master report year, the period from December 1, 2008, to November 30, 2009.</p><p>During the report year, precipitation in the upper Delaware River Basin was 50.89 inches (in.) or 116 percent of the long-term average. Combined storage in Pepacton, Cannonsville, and Neversink Reservoirs remained high throughout the year and did not decline below 80 percent of combined capacity at any time. Delaware River operations during the year were conducted as stipulated by the Decree and the Flexible Flow Management Program (FFMP).</p><p>Diversions from the Delaware River Basin by New York City and New Jersey were in full compliance with the Decree. Reservoir releases were made as directed by the River Master at rates designed to meet the flow objective for the Delaware River at Montague, New Jersey, on 25 days during the report year. Releases were made at conservation rates—rates designed to relieve thermal stress and protect the fishery and aquatic habitat in the tailwaters of the reservoirs—on all other days.</p><p>During the report year, New York City and New Jersey complied fully with the terms of the Decree, and directives and requests of the River Master.</p><p>As part of a long-term program, the quality of water in the Delaware Estuary between Trenton, New Jersey, and Reedy Island Jetty, Delaware, was monitored at various locations. Data on water temperature, specific conductance, dissolved oxygen, and pH were collected continuously by electronic instruments at four sites. In addition, selected water-quality data were collected at 22 sites on a monthly basis.</p><p>The Delaware River Basin Commission (DRBC) collects monthly samples from March through October at 22 sites between Biles Channel and South Brown Shoal. Samples were collected and analyzed by the State of Delaware for the DRBC. At each site, water samples were collected at a single point near the center of the channel near the surface and analyzed for selected physical properties, and chemical and biological constituents including routine chemical substances, nutrients and bacteria. These consist of analyses of field measurements and laboratory determinations.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151231","usgsCitation":"Krejmas, B.E., Paulachok, G.N., Mason, R.R., Jr., and Owens, Marie, 2016, Report of the River Master of the Delaware River for the period December 1, 2008–November 30, 2009: U.S. Geological Survey Open-File Report 2015–1231, 76 p., https://dx.doi.org/10.3133/ofr20151231.","productDescription":"vi, 76 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2008-12-01","ipdsId":"IP-070813","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":319219,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1231/ofr20151231.pdf","size":"1.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1231"},{"id":319218,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1231/coverthb.jpg"}],"country":"United States","otherGeospatial":"Delaware River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.4815673828125,\n              39.70296052957233\n            ],\n            [\n              -74.498291015625,\n              39.8465036024177\n            ],\n            [\n              -74.4927978515625,\n              40.26695230509781\n            ],\n            [\n              -74.970703125,\n              40.75974059207392\n            ],\n            [\n              -74.6685791015625,\n              40.979898069620155\n            ],\n            [\n              -74.5806884765625,\n              41.335575973123895\n            ],\n            [\n              -74.11376953125,\n              42.13082130188811\n            ],\n            [\n              -74.9432373046875,\n              42.44372793752476\n            ],\n            [\n              -75.574951171875,\n              42.00848901572399\n            ],\n            [\n              -75.8880615234375,\n              41.244772343082104\n            ],\n            [\n              -76.343994140625,\n              40.329795743702064\n            ],\n            [\n              -76.04736328125,\n              39.73253798438173\n            ],\n            [\n              -75.4815673828125,\n              39.70296052957233\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:gs-w_odrm_webmaster@usgs.gov\">Deputy</a> Delaware River Master<br /> U.S. Geological Survey<br /> 10 Buist Road, Bldg. 3, Suite 304<br /> Milford Professional Park<br /> Milford, PA 18337<br /> Fax: 570&ndash;296&ndash;9414<br /> <a href=\"http://water.usgs.gov/osw/odrm\">http://water.usgs.gov/osw/odrm/</a></p>","tableOfContents":"<ul>\n<li>River Master Letter of Transmittal and Special Report</li>\n<li>Delaware River Operations</li>\n<li>Quality of Water in the Delaware Estuary</li>\n<li>Appendix A. &nbsp;Agreement (Temporary IERQ Extraordinary Needs Bank Release Program for Summer 2009)&nbsp;</li>\n<li>Appendix B. &nbsp;Agreement (Revised FFMP Language to Address Storage Zone Bouncing)</li>\n<li>Appendix C. &nbsp;Temporary Supplemental Release Program for Tentative 2009 Rondout West Branch Tunnel Shutdown</li>\n</ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-04-06","noUsgsAuthors":false,"publicationDate":"2016-04-06","publicationStatus":"PW","scienceBaseUri":"572477b0e4b0b13d3914e132","contributors":{"authors":[{"text":"Krejmas, Bruce E.","contributorId":102501,"corporation":false,"usgs":true,"family":"Krejmas","given":"Bruce","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":581195,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paulachok, Gary N. gnpaulac@usgs.gov","contributorId":3500,"corporation":false,"usgs":true,"family":"Paulachok","given":"Gary","email":"gnpaulac@usgs.gov","middleInitial":"N.","affiliations":[],"preferred":true,"id":581194,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mason, Jr. 0000-0002-3998-3468 rrmason@usgs.gov","orcid":"https://orcid.org/0000-0002-3998-3468","contributorId":2090,"corporation":false,"usgs":true,"family":"Mason","suffix":"Jr.","email":"rrmason@usgs.gov","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":581193,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Owens, Marie mowens@usgs.gov","contributorId":150268,"corporation":false,"usgs":true,"family":"Owens","given":"Marie","email":"mowens@usgs.gov","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":false,"id":581192,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70169105,"text":"ofr20161040 - 2016 - Logistic and linear regression model documentation for statistical relations between continuous real-time and discrete water-quality constituents in the Kansas River, Kansas, July 2012 through June 2015","interactions":[],"lastModifiedDate":"2016-04-07T09:02:24","indexId":"ofr20161040","displayToPublicDate":"2016-04-06T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1040","title":"Logistic and linear regression model documentation for statistical relations between continuous real-time and discrete water-quality constituents in the Kansas River, Kansas, July 2012 through June 2015","docAbstract":"<p>The Kansas River is a primary source of drinking water for about 800,000 people in northeastern Kansas. Source-water supplies are treated by a combination of chemical and physical processes to remove contaminants before distribution. Advanced notification of changing water-quality conditions and cyanobacteria and associated toxin and taste-and-odor compounds provides drinking-water treatment facilities time to develop and implement adequate treatment strategies. The U.S. Geological Survey (USGS), in cooperation with the Kansas Water Office (funded in part through the Kansas State Water Plan Fund), and the City of Lawrence, the City of Topeka, the City of Olathe, and Johnson County Water One, began a study in July 2012 to develop statistical models at two Kansas River sites located upstream from drinking-water intakes. Continuous water-quality monitors have been operated and discrete-water quality samples have been collected on the Kansas River at Wamego (USGS site number 06887500) and De Soto (USGS site number 06892350) since July 2012. Continuous and discrete water-quality data collected during July 2012 through June 2015 were used to develop statistical models for constituents of interest at the Wamego and De Soto sites. Logistic models to continuously estimate the probability of occurrence above selected thresholds were developed for cyanobacteria, microcystin, and geosmin. Linear regression models to continuously estimate constituent concentrations were developed for major ions, dissolved solids, alkalinity, nutrients (nitrogen and phosphorus species), suspended sediment, indicator bacteria (<i>Escherichia coli</i>, fecal coliform, and enterococci), and actinomycetes bacteria. These models will be used to provide real-time estimates of the probability that cyanobacteria and associated compounds exceed thresholds and of the concentrations of other water-quality constituents in the Kansas River. The models documented in this report are useful for characterizing changes in water-quality conditions through time, characterizing potentially harmful cyanobacterial events, and indicating changes in water-quality conditions that may affect drinking-water treatment processes.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161040","collaboration":"Prepared in cooperation with the Kansas Water Office, the City of Lawrence, the City of Topeka, the City of Olathe, and Johnson County Water One","usgsCitation":"Foster, G.M., and Graham, J.L., 2016, Logistic and linear regression model documentation for statistical relations between continuous real-time and discrete water-quality constituents in the Kansas River, Kansas, July 2012 through June 2015: U.S. Geological Survey Open-File Report 2016–1040, 27 p., https://dx.doi.org/10.3133/ofr20161040. ","productDescription":"Report: iv, 27 p.; 31 Appendixes","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-071163","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":319781,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1040/coverthb.jpg"},{"id":319791,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1040/downloads/","text":"Appendixes 1 through 31","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1040 Appendixes"},{"id":319782,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1040/ofr20161040.pdf","text":"Report","size":"830 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1040"}],"country":"United States","state":"Kansas","otherGeospatial":"Kansas River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -94.6142578125,\n              38.81403111409755\n            ],\n            [\n              -94.921875,\n              39.14710270770074\n            ],\n            [\n              -95.185546875,\n              39.45316112807394\n            ],\n            [\n              -95.5810546875,\n              39.90130858574735\n            ],\n            [\n              -95.635986328125,\n              39.95185892663005\n            ],\n            [\n              -95.82275390625,\n              39.707186656826565\n            ],\n            [\n              -96.207275390625,\n              39.690280594818034\n            ],\n            [\n              -96.39404296875,\n              39.487084981687495\n            ],\n            [\n              -96.50390625,\n              39.18117526158749\n            ],\n            [\n              -96.866455078125,\n              39.26628442213066\n            ],\n            [\n              -96.88842773437499,\n              38.976492485539424\n            ],\n            [\n              -96.910400390625,\n              38.60828592850559\n            ],\n            [\n              -96.94335937499999,\n              38.42777351132905\n            ],\n            [\n              -96.624755859375,\n              38.53097889440026\n            ],\n            [\n              -96.075439453125,\n              38.61687046392973\n            ],\n            [\n              -95.020751953125,\n              38.65119833229951\n            ],\n            [\n              -94.68017578125,\n              38.659777730712534\n            ],\n            [\n              -94.6142578125,\n              38.81403111409755\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, Kansas Water Science Center<br>U.S. Geological Survey<br> 4821 Quail Crest Place<br> Lawrence, KS 66049<br></p><p><a href=\"http://ks.water.usgs.gov\" data-mce-href=\"http://ks.water.usgs.gov\">http://ks.water.usgs.gov</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Description of Study Area</li><li>Methods</li><li>Results of Logistic Regression Analysis for Cyanobacteria and Associated Compounds</li><li>Results of Linear Regression Analysis for Selected Constituents</li><li>Summary</li><li>References Cited</li><li>Tables</li><li>Appendixes 1–31</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-04-06","noUsgsAuthors":false,"publicationDate":"2016-04-06","publicationStatus":"PW","scienceBaseUri":"572477aae4b0b13d3914e0a1","contributors":{"authors":[{"text":"Foster, Guy M. gfoster@usgs.gov","contributorId":3437,"corporation":false,"usgs":true,"family":"Foster","given":"Guy M.","email":"gfoster@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":622947,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":1769,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":622948,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70168640,"text":"sir20165025 - 2016 - Effect of a levee setback on aquatic resources using two-dimensional flow and bioenergetics models","interactions":[],"lastModifiedDate":"2016-04-06T08:25:40","indexId":"sir20165025","displayToPublicDate":"2016-04-05T18:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5025","title":"Effect of a levee setback on aquatic resources using two-dimensional flow and bioenergetics models","docAbstract":"<p class=\"p1\">Watershed restoration is the focus of many resource managers and can include a multitude of restoration actions each with specific restoration objectives. For the White River flowing through the cities of Pacific and Sumner, Washington, a levee setback has been proposed to reconnect the river with its historical floodplain to help reduce flood risks, as well as provide increased habitat for federally listed species of salmonids. The study presented here documents the use of a modeling framework that integrates two-dimensional hydraulic modeling with process-based bioenergetics modeling for predicting how changes in flow from reconnecting the river with its floodplain affects invertebrate drift density and the net rate of energy intake of juvenile salmonids. Modeling results were calculated for flows of 25.9 and 49.3 cubic meters per second during the spring, summer, and fall. Predicted hypothetical future mean velocities and depths were significantly lower and more variable when compared to current conditions. The abundance of low energetic cost and positive growth locations for salmonids were predicted to increase significantly in the study reach following floodplain reconnection, particularly during the summer. This modeling framework presents a viable approach for evaluating the potential fisheries benefits of reconnecting a river to its historical floodplain that integrates our understanding of hydraulic, geomorphology, and organismal biology.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165025","collaboration":"Prepared in cooperation with the King County Water and Land Resources Division","usgsCitation":"Black, R.W., Czuba, C.R., Magirl, C.S., McCarthy, Sarah, Berge, Hans, and Comanor, Kyle, 2016, Effect of a levee setback on aquatic resources using two-dimensional flow and bioenergetics models: U.S. Geological Survey Scientific Investigations Report 2016–5025, 26 p., https://dx.doi.org/10.3133/sir20165025.","productDescription":"v, 26 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066982","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":319584,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5025/coverthb.jpg"},{"id":319585,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5025/sir20165025.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5025"}],"country":"United States","state":"Washington","city":"Pacific","otherGeospatial":"White River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.25688934326172,\n              47.22866141531796\n            ],\n            [\n              -122.25688934326172,\n              47.28633255817871\n            ],\n            [\n              -122.18358993530273,\n              47.28633255817871\n            ],\n            [\n              -122.18358993530273,\n              47.22866141531796\n            ],\n            [\n              -122.25688934326172,\n              47.22866141531796\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_wa@usgs.gov\">Director</a>, Washington Water Science Center<br /> U.S. Geological Survey<br /> 934 Broadway, Suite 300<br /> Tacoma, Washington 98402<br /> <a href=\"http://wa.water.usgs.gov\" target=\"blank\">http://wa.water.usgs.gov</a></p>","tableOfContents":"<ul>\n<li>Abstract</li>\n<li>Introduction</li>\n<li>Methods</li>\n<li>Results</li>\n<li>Discussion</li>\n<li>Conclusions</li>\n<li>Acknowledgments</li>\n<li>References Cited</li>\n<li>Appendix A. Initial Drift Densities Used in Invertebrate Drift Model</li>\n<li>Appendix B. Invertebrate Attributes Used in Invertebrate Drift Model</li>\n</ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2016-04-05","noUsgsAuthors":false,"publicationDate":"2016-04-05","publicationStatus":"PW","scienceBaseUri":"572477a5e4b0b13d3914e066","contributors":{"authors":[{"text":"Black, Robert W. 0000-0002-4748-8213 rwblack@usgs.gov","orcid":"https://orcid.org/0000-0002-4748-8213","contributorId":1820,"corporation":false,"usgs":true,"family":"Black","given":"Robert","email":"rwblack@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":621096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Czuba, Christiana R. cczuba@usgs.gov","contributorId":4555,"corporation":false,"usgs":true,"family":"Czuba","given":"Christiana","email":"cczuba@usgs.gov","middleInitial":"R.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":621097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Magirl, Christopher S. 0000-0002-9922-6549 magirl@usgs.gov","orcid":"https://orcid.org/0000-0002-9922-6549","contributorId":1822,"corporation":false,"usgs":true,"family":"Magirl","given":"Christopher","email":"magirl@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":621098,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCarthy, Sarah","contributorId":13097,"corporation":false,"usgs":true,"family":"McCarthy","given":"Sarah","affiliations":[],"preferred":false,"id":621099,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Berge, Hans","contributorId":167120,"corporation":false,"usgs":false,"family":"Berge","given":"Hans","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":621100,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Comanor, Kyle","contributorId":168354,"corporation":false,"usgs":true,"family":"Comanor","given":"Kyle","email":"","affiliations":[],"preferred":false,"id":625553,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70169134,"text":"fs20163014 - 2016 - Hydrologic monitoring for Chicago’s Sustainable Streetscapes Program","interactions":[],"lastModifiedDate":"2016-06-24T09:00:51","indexId":"fs20163014","displayToPublicDate":"2016-04-05T13:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3014","title":"Hydrologic monitoring for Chicago’s Sustainable Streetscapes Program","docAbstract":"<p>The Chicago Department of Transportation’s Sustainable Streetscapes Program is an innovative program that strives to convert Chicago’s neighborhood commercial areas, riverwalks, and bicycle facilities into active, attractive places for Chicagoans to live, work, and play. The objective of each project is to create flourishing public places while improving the ability of infrastructure to support dense urban living. The U.S. Geological Survey (USGS), in cooperation with the Metropolitan Water Reclamation District of Greater Chicago (MWRDGC), and the Chicago Department of Transportation (CDOT), is monitoring the pre- and postconstruction hydrologic characteristics of an urban corridor on the south side of Chicago that is being renovated using sustainable streetscapes technology.</p><p>The CDOT Sustainable Streetscapes Program utilizes urban stormwater best-management practices (BMPs) to reduce the storm runoff to the local combined sewer system. The urban stormwater BMPs include permeable pavement, bioswales, infiltration basins, and planters. The urban stormwater BMPs are designed to capture the first flush of storm runoff through features that enhance the infiltration of stormwater runoff to shallow groundwater.</p><p>The hydrology of the Sustainable Streetscapes Program area is being monitored to evaluate the impacts and effectiveness of the urban stormwater BMP’s. Continuous monitoring of rainfall, sewer flows, stormwater runoff, soil moisture, and groundwater levels will give engineers and scientists measured data to define baseline pre- and postconstruction conditions for the evaluation of the BMPs.</p><p>Three tipping-bucket rain gages are located along the project corridor. The data provide information on the intensity and volume of rainfall. Rainfall can be highly variable even over a small area like the project corridor.</p><p>Continuous recording meters are located at specific locations in the combined sewers to record water level and flow during both dry weather (mostly sanitary flow) and wet weather conditions (stormwater runoff in addition to the sanitary flow). Sanitary flow is the largest source of flow in the combined sewers during dry weather, and stormwater runoff and sanitary flow combine during wet weather. The sewer flow data allow engineers and scientists to calculate total runoff volume for selected storm events.</p><p>Wells are located within the project corridor to record water levels and help determine the direction of movement of groundwater in response to rainfall and snowmelt. In urban settings with aging sewer systems, groundwater can seep into the sewers or combined sewage can seep from the sewers into the local groundwater system. The groundwater data are also important in evaluating the overall impacts of increased infiltration resulting from BMPs.</p><p>Data from wells show the relative water levels of shallow groundwater, water levels in the combined sewer system, and nearby surface-water channels within the project corridor. In some aging urban sewer systems, the local combined sewer system lies below the water table and receives substantial amounts of groundwater inflow, which can significantly reduce the amount of additional water the sewer system can accept.</p><p>The bioswale along the south side of West Cermak Road near South Throop Street functions to infiltrate stormwater runoff from the road. Stormwater on the road surface initially drains to the curb and then flows along the curb until it reaches a curb cut-out. Materials within the bioswale allow stormwater to infiltrate and reduce the load to the combined sewer.</p><p>A common feature in urban areas are curbside catch basins that collect stormwater runoff from paved streets. Stormwater drains first to the curb and then flows along the curb to the catch basin. Lateral sewer pipe connects the catch basin to the combined sewer beneath the street. The use of permeable pavers along the curbs in the project study reach let stormwater infiltrate before it reaches the curb, thus reducing the amount of stormwater draining to the combined sewers.</p><p>Water-level data from catch basins in the project study area show the effects of permeable pavers in reducing the stormwater drainage to the combined sewers.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163014","collaboration":"Prepared in cooperation with the Metropolitan Water Reclamation District of Greater Chicago (MWRDGC), and the Chicago Department of Transportation (CDOT)","usgsCitation":"Duncker, J.J., and Morrow, W.S., 2016, Hydrologic monitoring for Chicago’s Sustainable Streetscapes Program. U.S. Geological Survey Fact Sheet 2016–3014, 6 p., https://dx.doi.org/10.3133/fs20163014.","productDescription":"6 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054040","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":319331,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3014/coverthb.jpg"},{"id":319332,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3014/fs20163014.pdf","text":"Report","size":"3.70 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3014"}],"country":"United States","state":"Illinois","city":"Chicago","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -87.68531799316406,\n              41.8384904853889\n            ],\n            [\n              -87.68531799316406,\n              41.86035637336661\n            ],\n            [\n              -87.64274597167967,\n              41.86035637336661\n            ],\n            [\n              -87.64274597167967,\n              41.8384904853889\n            ],\n            [\n              -87.68531799316406,\n              41.8384904853889\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_il@usgs.gov\" data-mce-href=\"mailto:dc_il@usgs.gov\">Director</a>, Illinois Water Science Center<br> U.S. Geological Survey<br> 405 N. Goodwin Ave<br>Urbana, IL 61801<br> <a href=\"http://il.water.usgs.gov/\" data-mce-href=\"http://il.water.usgs.gov/\">http://il.water.usgs.gov/</a></p>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2016-04-05","noUsgsAuthors":false,"publicationDate":"2016-04-05","publicationStatus":"PW","scienceBaseUri":"572477aae4b0b13d3914e09b","contributors":{"authors":[{"text":"Duncker, James J. 0000-0001-5464-7991 jduncker@usgs.gov","orcid":"https://orcid.org/0000-0001-5464-7991","contributorId":4316,"corporation":false,"usgs":true,"family":"Duncker","given":"James","email":"jduncker@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":623170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morrow, William S. 0000-0002-2250-3165 wsmorrow@usgs.gov","orcid":"https://orcid.org/0000-0002-2250-3165","contributorId":1886,"corporation":false,"usgs":true,"family":"Morrow","given":"William","email":"wsmorrow@usgs.gov","middleInitial":"S.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":623171,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70168519,"text":"ofr20161011 - 2016 - Simulation of hypothetical Asian carp egg and larvae development and transport in the Lockport, Brandon Road, Dresden Island, and Marseilles Pools of the Illinois Waterway by use of the Fluvial Egg Drift Simulator (FluEgg) model","interactions":[],"lastModifiedDate":"2016-04-06T08:18:57","indexId":"ofr20161011","displayToPublicDate":"2016-04-05T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1011","title":"Simulation of hypothetical Asian carp egg and larvae development and transport in the Lockport, Brandon Road, Dresden Island, and Marseilles Pools of the Illinois Waterway by use of the Fluvial Egg Drift Simulator (FluEgg) model","docAbstract":"<p>As part of the Great Lakes and Mississippi River Interbasin Study, the U.S. Army Corps of Engineers (USACE) is conducting an assessment of the vulnerability of the Chicago Area Waterway System and Des Plaines River to Asian carp (specifically, <i>Hypophthalmichthys nobilis</i> (bighead carp) and <i>Hypophthalmichthys molitrix</i> (silver carp)) spawning and recruitment. As part of this assessment, the USACE requested the help of the U.S. Geological Survey in predicting the fate and transport of Asian carp eggs hypothetically spawned at the electric dispersal barrier on the Chicago Sanitary and Ship Canal and downstream of the Brandon Road Lock and Dam on the Des Plaines River under dry weather flow and high water temperature conditions. The Fluvial Egg Drift Simulator (FluEgg) model predicted that approximately 80 percent of silver carp eggs spawned near the electric dispersal barrier would hatch within the Lockport and Brandon Road pools (as close as 3.6 miles downstream of the barrier) and approximately 82 percent of the silver carp eggs spawned near the Brandon Road Dam would hatch in the Des Plaines River (as close as 1.6 miles downstream from the gates of Brandon Road Lock). Extension of the FluEgg model to include the fate and transport of larvae until gas bladder inflation&mdash;the point at which the larvae begin to leave the drift&mdash;suggests that eggs spawned at the electric dispersal barrier would reach the gas bladder inflation stage primarily within the Dresden Island Pool, and those spawned at the Brandon Road Dam would reach this stage primarily within the Marseilles and Starved Rock Pools.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161011","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, Great Lakes Restoration Initiative","usgsCitation":"Murphy, E.A., Garcia, Tatiana, Jackson, P.R., and Duncker J.J., 2016, Simulation of hypothetical Asian carp egg and larvae development and transport in the Lockport, Brandon Road, Dresden Island, and Marseilles Pools of the Illinois Waterway by use of the fluvial egg drift simulator (FluEgg) model: U.S. Geological Survey Open File Report 2016–1011, 19 p., https://dx.doi.org/10.3133/ofr20161011.","productDescription":"vii, 19 p.","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070545","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":319192,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1011/ofr20161011.pdf","size":"2.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1011"},{"id":319191,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1011/coverthb.jpg"}],"country":"United States","state":"Illinois","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.96728515624999,\n              40.95501133048621\n            ],\n            [\n              -88.96728515624999,\n              41.85319643776675\n            ],\n            [\n              -87.9345703125,\n              41.85319643776675\n            ],\n            [\n              -87.9345703125,\n              40.95501133048621\n            ],\n            [\n              -88.96728515624999,\n              40.95501133048621\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, Illinois Water Science Center<br> U.S. Geological Survey<br> 405 N Goodwin<br> Urbana, IL 61801<br> <a href=\"http://il.water.usgs.gov/\" data-mce-href=\"http://il.water.usgs.gov/\">http://il.water.usgs.gov/</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>FluEgg Model Overview</li><li>Hydraulic Data</li><li>FluEgg Simulation Scenarios</li><li>Results</li><li>Limitations</li><li>Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2016-04-05","noUsgsAuthors":false,"publicationDate":"2016-04-05","publicationStatus":"PW","scienceBaseUri":"572477b1e4b0b13d3914e151","contributors":{"authors":[{"text":"Murphy, Elizabeth A. emurphy@usgs.gov","contributorId":140328,"corporation":false,"usgs":true,"family":"Murphy","given":"Elizabeth A.","email":"emurphy@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":620771,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, Tatiana 0000-0002-1979-7246 tgarcia@usgs.gov","orcid":"https://orcid.org/0000-0002-1979-7246","contributorId":140327,"corporation":false,"usgs":true,"family":"Garcia","given":"Tatiana","email":"tgarcia@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620772,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, P. Ryan pjackson@usgs.gov","contributorId":2960,"corporation":false,"usgs":true,"family":"Jackson","given":"P. Ryan","email":"pjackson@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":620773,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duncker, James J. 0000-0001-5464-7991 jduncker@usgs.gov","orcid":"https://orcid.org/0000-0001-5464-7991","contributorId":4316,"corporation":false,"usgs":true,"family":"Duncker","given":"James","email":"jduncker@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620774,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70174473,"text":"70174473 - 2016 - Toxicity of waters from the Rochester Embayment Area of Concern to the plankton species <i>Pseudokirchneriella subcapitata</i> and <i>Ceriodaphnia dubia</i>","interactions":[],"lastModifiedDate":"2016-07-12T12:57:46","indexId":"70174473","displayToPublicDate":"2016-04-05T09:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Toxicity of waters from the Rochester Embayment Area of Concern to the plankton species <i>Pseudokirchneriella subcapitata</i> and <i>Ceriodaphnia dubia</i>","docAbstract":"<p class=\"p1\"><span class=\"s1\">The lower Genesee River and Rochester Embayment of Lake Ontario are a designated Area of Concern (AOC) under the binational Great Lakes Water Quality Agreement. The &ldquo;degradation of phytoplankton and zooplankton populations&rdquo; or plankton Beneficial Use Impairment (BUI) was classified as unknown and in need of further assessment in this AOC because water quality data suggested plankton communities could be effected and community data were either unavailable or indicated impacts. The plankton BUI may now be obsolete because local contaminant sources have been largely eliminated. The present study was conducted between July 2013 and August 2014 to assess the BUI-removal criteria: &ldquo;AOC plankton bioassays confirm that toxicity in ambient waters (i.e., no growth inhibition) is not significantly higher than comparable non-AOC controls&rdquo;. Acute and chronic toxicity of waters from 13 sites were quantified seasonally using standardized bioassays with the green alga <i>Pseudokirchneriella subcapitata</i> and water flea <i>Ceriodaphnia dubia</i> to test the hypothesis that toxicity of waters from AOC sites was not higher than that of waters from comparable non-AOC reference sites. Survival and reproduction of <i>C. dubia</i> did not differ significantly between site types, systems, or months. The growth of <i>P. subcapitata</i> did not differ between site types, but differed among systems and months. All results indicate that waters from AOC sites were no more toxic to both plankton species than waters from reference sites. Assuming test species represent natural plankton assemblages, water quality should not negatively affect survival and growth of resident plankton populations in the Rochester Embayment AOC.</span></p>","language":"English","publisher":"International Association for Great Lakes Research","doi":"10.1016/j.jglr.2015.12.007","usgsCitation":"Baldigo, B.P., Duffy, B.T., Smith, A., and George, S.D., 2016, Toxicity of waters from the Rochester Embayment Area of Concern to the plankton species <i>Pseudokirchneriella subcapitata</i> and <i>Ceriodaphnia dubia</i>: Journal of Great Lakes Research, v. 42, no. 2, p. 464-471, https://doi.org/10.1016/j.jglr.2015.12.007.","productDescription":"8 p.","startPage":"464","endPage":"471","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062670","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":471089,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2015.12.007","text":"Publisher Index Page"},{"id":325100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Lake Ontario","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -78.7005615234375,\n              42.944360446966314\n            ],\n            [\n              -78.7005615234375,\n              43.44893105587766\n            ],\n            [\n              -76.80541992187499,\n              43.44893105587766\n            ],\n            [\n              -76.80541992187499,\n              42.944360446966314\n            ],\n            [\n              -78.7005615234375,\n              42.944360446966314\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"42","issue":"2","edition":"2016","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"579dd04ee4b0589fa1cbdf45","chorus":{"doi":"10.1016/j.jglr.2015.12.007","url":"http://dx.doi.org/10.1016/j.jglr.2015.12.007","publisher":"Elsevier BV","authors":"Baldigo Barry P., Duffy Brian T., Smith Alexander J., George Scott D.","journalName":"Journal of Great Lakes Research","publicationDate":"4/2016"},"contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642213,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duffy, Brian T.","contributorId":6352,"corporation":false,"usgs":true,"family":"Duffy","given":"Brian","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":642215,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Alexander J.","contributorId":140345,"corporation":false,"usgs":false,"family":"Smith","given":"Alexander J.","affiliations":[{"id":13464,"text":"Environmental Analyst, NY State Dept of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":642216,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642214,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70162808,"text":"sir20155019D - 2016 - Adjusted peak-flow frequency estimates for selected streamflow-gaging stations in or near Montana based on data through water year 2011: Chapter D in Montana StreamStats","interactions":[{"subject":{"id":70162808,"text":"sir20155019D - 2016 - Adjusted peak-flow frequency estimates for selected streamflow-gaging stations in or near Montana based on data through water year 2011: Chapter D in Montana StreamStats","indexId":"sir20155019D","publicationYear":"2016","noYear":false,"chapter":"D","displayTitle":"Adjusted peak-flow frequency estimates for selected streamflow-gaging stations in or near Montana based on data through water year 2011: Chapter D in <i>Montana StreamStats</i>","title":"Adjusted peak-flow frequency estimates for selected streamflow-gaging stations in or near Montana based on data through water year 2011: Chapter D in Montana StreamStats"},"predicate":"IS_PART_OF","object":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"id":1}],"isPartOf":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"lastModifiedDate":"2024-12-13T19:40:04.515679","indexId":"sir20155019D","displayToPublicDate":"2016-04-05T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5019","chapter":"D","displayTitle":"Adjusted peak-flow frequency estimates for selected streamflow-gaging stations in or near Montana based on data through water year 2011: Chapter D in <i>Montana StreamStats</i>","title":"Adjusted peak-flow frequency estimates for selected streamflow-gaging stations in or near Montana based on data through water year 2011: Chapter D in Montana StreamStats","docAbstract":"<p>The climatic conditions of the specific time period during which peak-flow data were collected at a given streamflow-gaging station (hereinafter referred to as gaging station) can substantially affect how well the peak-flow frequency (hereinafter referred to as frequency) results represent long-term hydrologic conditions. Differences in the timing of the periods of record can result in substantial inconsistencies in frequency estimates for hydrologically similar gaging stations. Potential for inconsistency increases with decreasing peak-flow record length. The representativeness of the frequency estimates for a short-term gaging station can be adjusted by various methods including weighting the at-site results in association with frequency estimates from regional regression equations (RREs) by using the Weighted Independent Estimates (WIE) program. Also, for gaging stations that cannot be adjusted by using the WIE program because of regulation or drainage areas too large for application of RREs, frequency estimates might be improved by using record extension procedures, including a mixed-station analysis using the maintenance of variance type I (MOVE.1) procedure. The U.S. Geological Survey, in cooperation with the Montana Department of Transportation and the Montana Department of Natural Resources and Conservation, completed a study to provide adjusted frequency estimates for selected gaging stations through water year 2011.</p><p>The purpose of Chapter D of this Scientific Investigations Report is to present adjusted frequency estimates for 504 selected streamflow-gaging stations in or near Montana based on data through water year 2011. Estimates of peak-flow magnitudes for the 66.7-, 50-, 42.9-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities are reported. These annual exceedance probabilities correspond to the 1.5-, 2-, 2.33-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively.</p><p>The at-site frequency estimates were adjusted by weighting with frequency estimates from RREs using the WIE program for 438 selected gaging stations in Montana. These 438 selected gaging stations (1) had periods of record less than or equal to 40 years, (2) represented unregulated or minor regulation conditions, and (3) had drainage areas less than about 2,750 square miles.</p><p>The weighted-average frequency estimates obtained by weighting with RREs generally are considered to provide improved frequency estimates. In some cases, there are substantial differences among the at-site frequency estimates, the regression-equation frequency estimates, and the weighted-average frequency estimates. In these cases, thoughtful consideration should be applied when selecting the appropriate frequency estimate. Some factors that might be considered when selecting the appropriate frequency estimate include (1) whether the specific gaging station has peak-flow characteristics that distinguish it from most other gaging stations used in developing the RREs for the hydrologic region; and (2) the length of the peak-flow record and the general climatic characteristics during the period when the peak-flow data were collected. For critical structure-design applications, a conservative approach would be to select the higher of the at-site frequency estimate and the weighted-average frequency estimate.</p><p>The mixed-station MOVE.1 procedure generally was applied in cases where three or more gaging stations were located on the same large river and some of the gaging stations could not be adjusted using the weighted-average method because of regulation or drainage areas too large for application of RREs. The mixed-station MOVE.1 procedure was applied to 66 selected gaging stations on 19 large rivers.</p><p>The general approach for using mixed-station record extension procedures to adjust at-site frequencies involved (1) determining appropriate base periods for the gaging stations on the large rivers, (2) synthesizing peak-flow data for the gaging stations with incomplete peak-flow records during the base periods by using the mixed-station MOVE.1 procedure, and (3) conducting frequency analysis on the combined recorded and synthesized peak-flow data for each gaging station. Frequency estimates for the combined recorded and synthesized datasets for 66 gaging stations with incomplete peak-flow records during the base periods are presented. The uncertainties in the mixed-station record extension results are difficult to directly quantify; thus, it is important to understand the intended use of the estimated frequencies based on analysis of the combined recorded and synthesized datasets. The estimated frequencies are considered general estimates of frequency relations among gaging stations on the same stream channel that might be expected if the gaging stations had been gaged during the same long-term base period. However, because the mixed-station record extension procedures involve secondary statistical analysis with accompanying errors, the uncertainty of the frequency estimates is larger than would be obtained by collecting systematic records for the same number of years in the base period.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Montana StreamStats (Scientific Investigation Report 2015-5019)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155019D","collaboration":"Prepared in cooperation with the Montana Department of Transportation, Montana Department of Environmental Quality, and Montana Department of Natural Resources and Conservation","usgsCitation":"Sando, S.K., Sando, Roy, McCarthy, P.M., and Dutton, D.M., 2016, Adjusted peak-flow frequency estimates for selected streamflow-gaging stations in or near Montana based on data through water 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 \"}}]}","edition":"Version 1.0: April 6, 2016; Version 1.1: February 26, 2018","contact":"<p>Director, Wyoming-Montana Water Science Center<br />U.S. Geological Survey<br />3162 Bozeman Ave<br />Helena, MT 59601</p>\n<p><a href=\"http://wy-mt.water.usgs.gov/\">http://wy-mt.water.usgs.gov/</a></p>","tableOfContents":"<ul>\n<li>Acknowledgments</li>\n<li>Abstract</li>\n<li>Introduction</li>\n<li>Methods of Analysis</li>\n<li>Adjusted Peak-Flow Frequency Estimates for Selected Streamflow-Gaging Stations in or&nbsp;near Montana</li>\n<li>Summary</li>\n<li>References Cited</li>\n<li>Appendix 1. Information on Selected Streamflow-Gaging Stations, Peak-Flow Frequency Adjustment Methods, And Adjusted Peak-Flow Frequency Estimates</li>\n</ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-04-05","revisedDate":"2018-02-26","noUsgsAuthors":false,"publicationDate":"2016-04-05","publicationStatus":"PW","scienceBaseUri":"5724779ee4b0b13d3914dfe0","contributors":{"authors":[{"text":"Sando, Steven K. 0000-0003-1206-1030 sksando@usgs.gov","orcid":"https://orcid.org/0000-0003-1206-1030","contributorId":1016,"corporation":false,"usgs":true,"family":"Sando","given":"Steven","email":"sksando@usgs.gov","middleInitial":"K.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620706,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sando, Roy 0000-0003-0704-6258","orcid":"https://orcid.org/0000-0003-0704-6258","contributorId":26230,"corporation":false,"usgs":true,"family":"Sando","given":"Roy","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":false,"id":620707,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCarthy, Peter 0000-0002-2396-7463 pmccarth@usgs.gov","orcid":"https://orcid.org/0000-0002-2396-7463","contributorId":2504,"corporation":false,"usgs":true,"family":"McCarthy","given":"Peter","email":"pmccarth@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dutton, DeAnn M. ddutton@usgs.gov","contributorId":20762,"corporation":false,"usgs":true,"family":"Dutton","given":"DeAnn M.","email":"ddutton@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":false,"id":620709,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70163219,"text":"sir20155019A - 2016 - Montana StreamStats—A method for retrieving basin and streamflow characteristics in Montana: Chapter A in <i>Montana StreamStats</i>","interactions":[{"subject":{"id":70163219,"text":"sir20155019A - 2016 - Montana StreamStats—A method for retrieving basin and streamflow characteristics in Montana: Chapter A in <i>Montana StreamStats</i>","indexId":"sir20155019A","publicationYear":"2016","noYear":false,"chapter":"A","title":"Montana StreamStats—A method for retrieving basin and streamflow characteristics in Montana: Chapter A in <i>Montana StreamStats</i>"},"predicate":"IS_PART_OF","object":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"id":1}],"isPartOf":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"lastModifiedDate":"2018-02-28T16:37:26","indexId":"sir20155019A","displayToPublicDate":"2016-04-05T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5019","chapter":"A","title":"Montana StreamStats—A method for retrieving basin and streamflow characteristics in Montana: Chapter A in <i>Montana StreamStats</i>","docAbstract":"<p>The U.S. Geological Survey (USGS) provides streamflow characteristics and other related information needed by water-resource managers to protect people and property from floods, plan and manage water-resource activities, and protect water quality. Streamflow characteristics provided by the USGS, such as peak-flow and low-flow frequencies for streamflow-gaging stations, are frequently used by engineers, flood forecasters, land managers, biologists, and others to guide their everyday decisions. In addition to providing streamflow characteristics at streamflow-gaging stations, the USGS also develops regional regression equations and drainage area-adjustment methods for estimating streamflow characteristics at locations on ungaged streams. Regional regression equations can be complex and often require users to determine several basin characteristics, which are physical and climatic characteristics of the stream and its drainage basin. Obtaining these basin characteristics for streamflow-gaging stations and ungaged sites traditionally has been time consuming and subjective, and led to inconsistent results.</p><p>StreamStats is a Web-based geographic information system application that was created by the USGS to provide users with access to an assortment of analytical tools that are useful for water-resource planning and management. StreamStats allows users to easily obtain streamflow and basin characteristics for USGS streamflow-gaging stations and user-selected locations on ungaged streams. The USGS, in cooperation with Montana Department of Transportation, Montana Department of Environmental Quality, and Montana Department of Natural Resources and Conservation, completed a study to develop a StreamStats application for Montana, compute streamflow characteristics at streamflow-gaging stations, and develop regional regression equations to estimate streamflow characteristics at ungaged sites. Chapter A of this Scientific Investigations Report describes the Montana StreamStats application and the datasets, streamflow-gaging stations, streamflow characteristics, and regression equations (as described fully in Chapters B through G of this report) that are used for development of the StreamStats application for Montana.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Montana StreamStats (Scientific Investigations Report 2015-5019)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155019A","collaboration":"Prepared in cooperation with the Montana Department of Transportation, Montana Department of Environmental Quality, and Montana Department of Natural Resources and Conservation","usgsCitation":"McCarthy, P.M., Dutton, D.M., Sando, S.K., and Sando, Roy, 2016, Montana StreamStats—A method for retrieving basin and streamflow characteristics in Montana: U.S. Geological Survey Scientific Investigations Report 2015–\n5019–A, 16 p., https://dx.doi.org/10.3133/sir20155019A.","productDescription":"Report: v, 16 p.; 4 Tables","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069671","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":319587,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5019A/sir20155019A.pdf","text":"Report","size":"1.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015–5019–A"},{"id":319586,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5019A/coverthb.jpg"},{"id":319588,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2015/5019A/sir20155019A_tables.xlsx","text":"Tables 1 and 1–1 through 1–3","size":"296 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015–5019–A Tables"}],"country":"United 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 \"}}]}","contact":"<p>Director, Wyoming-Montana Water Science Center<br />U.S. Geological Survey<br />3162 Bozeman Ave<br />Helena, MT 59601</p>\n<p><a href=\"http://wy-mt.water.usgs.gov/\">http://wy-mt.water.usgs.gov/</a></p>","tableOfContents":"<ul>\n<li>Acknowledgments</li>\n<li>Abstract</li>\n<li>Introduction</li>\n<li>Montana StreamStats</li>\n<li>Summary</li>\n<li>References Cited</li>\n<li>Appendix 1. Streamflow-Gaging Stations, Dams, and Major Regulation Structures Used in&nbsp;this Study</li>\n</ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-04-05","noUsgsAuthors":false,"publicationDate":"2016-04-05","publicationStatus":"PW","scienceBaseUri":"572477ace4b0b13d3914e0b4","contributors":{"authors":[{"text":"McCarthy, Peter 0000-0002-2396-7463 pmccarth@usgs.gov","orcid":"https://orcid.org/0000-0002-2396-7463","contributorId":2504,"corporation":false,"usgs":true,"family":"McCarthy","given":"Peter","email":"pmccarth@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620714,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dutton, DeAnn M. ddutton@usgs.gov","contributorId":20762,"corporation":false,"usgs":true,"family":"Dutton","given":"DeAnn M.","email":"ddutton@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":false,"id":620715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sando, Steven K. 0000-0003-1206-1030 sksando@usgs.gov","orcid":"https://orcid.org/0000-0003-1206-1030","contributorId":1016,"corporation":false,"usgs":true,"family":"Sando","given":"Steven","email":"sksando@usgs.gov","middleInitial":"K.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620716,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sando, Roy 0000-0003-0704-6258","orcid":"https://orcid.org/0000-0003-0704-6258","contributorId":26230,"corporation":false,"usgs":true,"family":"Sando","given":"Roy","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":false,"id":620717,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70164337,"text":"sir20155019C - 2016 - Peak-flow frequency analyses and results based on data through water year 2011 for selected streamflow-gaging stations in or near Montana: Chapter C in <i>Montana StreamStats</i>","interactions":[{"subject":{"id":70164337,"text":"sir20155019C - 2016 - Peak-flow frequency analyses and results based on data through water year 2011 for selected streamflow-gaging stations in or near Montana: Chapter C in <i>Montana StreamStats</i>","indexId":"sir20155019C","publicationYear":"2016","noYear":false,"chapter":"C","title":"Peak-flow frequency analyses and results based on data through water year 2011 for selected streamflow-gaging stations in or near Montana: Chapter C in <i>Montana StreamStats</i>"},"predicate":"IS_PART_OF","object":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"id":1}],"isPartOf":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"lastModifiedDate":"2018-02-28T16:38:25","indexId":"sir20155019C","displayToPublicDate":"2016-04-05T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5019","chapter":"C","title":"Peak-flow frequency analyses and results based on data through water year 2011 for selected streamflow-gaging stations in or near Montana: Chapter C in <i>Montana StreamStats</i>","docAbstract":"<p>Chapter C of this Scientific Investigations Report documents results from a study by the U.S. Geological Survey, in cooperation with the Montana Department of Transportation and the Montana Department of Natural Resources, to provide an update of statewide peak-flow frequency analyses and results for Montana. The purpose of this report chapter is to present peak-flow frequency analyses and results for 725 streamflow-gaging stations in or near Montana based on data through water year 2011. The 725 streamflow-gaging stations included in this study represent nearly all streamflowgaging stations in Montana (plus some from adjacent states or Canadian Provinces) that have at least 10 years of peak-flow records through water year 2011. For 29 of the 725 streamflow-gaging stations, peak-flow frequency analyses and results are reported for both unregulated and regulated conditions. Thus, peak-flow frequency analyses and results are reported for a total of 754 analyses. Estimates of peak-flow magnitudes for 66.7-, 50-, 42.9-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities are reported. These annual exceedance probabilities correspond to 1.5-, 2-, 2.33-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Montana StreamStats (Scientific Investigations Report 2015-5019)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155019C","collaboration":"Prepared in cooperation with the Montana Department of Transportation and Montana Department of Natural Resources and Conservation","usgsCitation":"Sando, S.K., McCarthy, P.M., and Dutton, D.M., 2016, Peak-flow frequency analyses and results based on data through water year 2011 for selected streamflow-gaging stations in or near Montana: U.S. Geological Survey Scientific Investigations Report 2015–5019–C, 27 p., https://dx.doi.org/10.3133/sir20155019C.","productDescription":"Report: v, 27 p.; 6 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 \"}}]}","contact":"<p>Director, Wyoming-Montana Water Science Center<br />U.S. Geological Survey<br />3162 Bozeman Ave<br />Helena, MT 59601</p>\n<p><a href=\"http://wy-mt.water.usgs.gov/\">http://wy-mt.water.usgs.gov/</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Data Compilation and Pre-Analysis Augmentation and Manipulation</li><li>Determination of Regulation Status of Streamflow-Gaging Stations</li><li>Peak-Flow Frequency Analyses and Results</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Information on Streamflow-Gaging Stations, Data Augmentation, Regulation Structures, and Peak-Flow Frequency Analyses and Results</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-04-05","noUsgsAuthors":false,"publicationDate":"2016-04-05","publicationStatus":"PW","scienceBaseUri":"572477aee4b0b13d3914e0d5","contributors":{"authors":[{"text":"Sando, Steven K. 0000-0003-1206-1030 sksando@usgs.gov","orcid":"https://orcid.org/0000-0003-1206-1030","contributorId":1016,"corporation":false,"usgs":true,"family":"Sando","given":"Steven","email":"sksando@usgs.gov","middleInitial":"K.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620701,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCarthy, Peter 0000-0002-2396-7463 pmccarth@usgs.gov","orcid":"https://orcid.org/0000-0002-2396-7463","contributorId":2504,"corporation":false,"usgs":true,"family":"McCarthy","given":"Peter","email":"pmccarth@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":625609,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dutton, DeAnn M. ddutton@usgs.gov","contributorId":20762,"corporation":false,"usgs":true,"family":"Dutton","given":"DeAnn M.","email":"ddutton@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":false,"id":625610,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70163218,"text":"sir20155019E - 2016 - Streamflow characteristics based on data through water year 2009 for selected streamflow-gaging stations in or near Montana: Chapter E in <i>Montana StreamStats</i>","interactions":[{"subject":{"id":70163218,"text":"sir20155019E - 2016 - Streamflow characteristics based on data through water year 2009 for selected streamflow-gaging stations in or near Montana: Chapter E in <i>Montana StreamStats</i>","indexId":"sir20155019E","publicationYear":"2016","noYear":false,"chapter":"E","title":"Streamflow characteristics based on data through water year 2009 for selected streamflow-gaging stations in or near Montana: Chapter E in <i>Montana StreamStats</i>"},"predicate":"IS_PART_OF","object":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"id":1}],"isPartOf":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"lastModifiedDate":"2018-02-28T16:38:48","indexId":"sir20155019E","displayToPublicDate":"2016-04-05T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5019","chapter":"E","title":"Streamflow characteristics based on data through water year 2009 for selected streamflow-gaging stations in or near Montana: Chapter E in <i>Montana StreamStats</i>","docAbstract":"<p>Chapter E of this Scientific Investigations Report documents results from a study by the U.S. Geological Survey, in cooperation with the Montana Department of Environmental Quality and the Montana Department of Natural Resources and Conservation, to provide an update of statewide streamflow characteristics based on data through water year 2009 for streamflow-gaging stations in or near Montana. Streamflow characteristics are presented for 408 streamflow-gaging stations in Montana and adjacent areas having 10 or more years of record. Data include the magnitude and probability of annual low and high streamflow, the magnitude and probability of low streamflow for three seasons (March&ndash;June, July&ndash;October, and November&ndash;February), streamflow duration statistics for monthly and annual periods, and mean streamflows for monthly and annual periods. Streamflow is considered to be regulated at streamflow-gaging stations where dams or other large-scale human modifications affect 20 percent or more of the contributing drainage basin. Separate streamflow characteristics are presented for the unregulated and regulated periods of record for streamflow-gaging stations with sufficient data.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Montana StreamStats (Scientific Investigations Report 2015-5019)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155019E","collaboration":"Prepared in cooperation with the Montana Department of Environmental Quality and Montana Department of Natural Resources and Conservation","usgsCitation":"McCarthy, P.M., 2016, Streamflow characteristics based on data through water year 2009 for selected streamflow-gaging stations in or near Montana: U.S. Geological Survey Scientific Investigations Report 2015–5019–E, 10 p., https://dx.doi.org/10.3133/sir20155019E.","productDescription":"Report: v, 10 p.; 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 \"}}]}","contact":"<p>Director, Wyoming-Montana Water Science Center<br />U.S. Geological Survey<br />3162 Bozeman Ave<br />Helena, MT 59601</p>\n<p><a href=\"http://wy-mt.water.usgs.gov/\">http://wy-mt.water.usgs.gov/</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Streamflow Characteristics Analyses and Results.</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Information and Streamflow Characteristics for Streamflow-Gaging Stations</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-04-05","noUsgsAuthors":false,"publicationDate":"2016-04-05","publicationStatus":"PW","scienceBaseUri":"572477b1e4b0b13d3914e155","contributors":{"authors":[{"text":"McCarthy, Peter 0000-0002-2396-7463 pmccarth@usgs.gov","orcid":"https://orcid.org/0000-0002-2396-7463","contributorId":2504,"corporation":false,"usgs":true,"family":"McCarthy","given":"Peter","email":"pmccarth@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620700,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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Montana StreamStats was developed by the U.S. Geological Survey (USGS) in cooperation with the Montana Departments of Transportation, Environmental Quality, and Natural Resources and Conservation. The USGS Scientific Investigations Report consists of seven independent but complementary chapters dealing with various aspects of this effort.</p><p>Chapter A describes the Montana StreamStats application, the basin and streamflow datasets, and provides a brief overview of the streamflow characteristics and regression equations used in the study. Chapters B through E document the datasets, methods, and results of analyses to determine streamflow characteristics, such as peak-flow frequencies, low-flow frequencies, and monthly and annual characteristics, for USGS streamflow-gaging stations in and near Montana. 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 \"}}]}","contact":"<p>Director, Wyoming-Montana Water Science Center<br />U.S. Geological Survey<br />3162 Bozeman Ave<br />Helena, MT 59601</p>\n<p><a href=\"http://wy-mt.water.usgs.gov/\">http://wy-mt.water.usgs.gov/</a></p>","publishedDate":"2016-04-05","noUsgsAuthors":false,"publicationDate":"2016-04-05","publicationStatus":"PW","scienceBaseUri":"572477ace4b0b13d3914e0b1"}
,{"id":70164333,"text":"sir20155019F - 2016 - Methods for estimating peak-flow frequencies at ungaged sites in Montana based on data through water year 2011: Chapter F in <i>Montana StreamStats</i>","interactions":[{"subject":{"id":70164333,"text":"sir20155019F - 2016 - Methods for estimating peak-flow frequencies at ungaged sites in Montana based on data through water year 2011: Chapter F in <i>Montana StreamStats</i>","indexId":"sir20155019F","publicationYear":"2016","noYear":false,"chapter":"F","title":"Methods for estimating peak-flow frequencies at ungaged sites in Montana based on data through water year 2011: Chapter F in <i>Montana StreamStats</i>"},"predicate":"IS_PART_OF","object":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"id":1}],"isPartOf":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"lastModifiedDate":"2024-12-13T19:49:49.154547","indexId":"sir20155019F","displayToPublicDate":"2016-04-05T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5019","chapter":"F","title":"Methods for estimating peak-flow frequencies at ungaged sites in Montana based on data through water year 2011: Chapter F in <i>Montana StreamStats</i>","docAbstract":"<p>The U.S. Geological Survey (USGS), in cooperation with the Montana Department of Natural Resources and Conservation, completed a study to update methods for estimating peak-flow frequencies at ungaged sites in Montana based on peak-flow data at streamflow-gaging stations through water year 2011. The methods allow estimation of peak-flow frequencies (that is, peak-flow magnitudes, in cubic feet per second, associated with annual exceedance probabilities of 66.7, 50, 42.9, 20, 10, 4, 2, 1, 0.5, and 0.2 percent) at ungaged sites. The annual exceedance probabilities correspond to 1.5-, 2-, 2.33-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively.</p><p>Regional regression analysis is a primary focus of Chapter F of this Scientific Investigations Report, and regression equations for estimating peak-flow frequencies at ungaged sites in eight hydrologic regions in Montana are presented. The regression equations are based on analysis of peak-flow frequencies and basin characteristics at 537 streamflow-gaging stations in or near Montana and were developed using generalized least squares regression or weighted least squares regression.</p><p>All of the data used in calculating basin characteristics that were included as explanatory variables in the regression equations were developed for and are available through the USGS StreamStats application (http://water.usgs.gov/osw/streamstats/) for Montana. StreamStats is a Web-based geographic information system application that was created by the USGS to provide users with access to an assortment of analytical tools that are useful for water-resource planning and management. The primary purpose of the Montana StreamStats application is to provide estimates of basin characteristics and streamflow characteristics for user-selected ungaged sites on Montana streams. The regional regression equations presented in this report chapter can be conveniently solved using the Montana StreamStats application.</p><p>Selected results from this study were compared with results of previous studies. For most hydrologic regions, the regression equations reported for this study had lower mean standard errors of prediction (in percent) than the previously reported regression equations for Montana. The equations presented for this study are considered to be an improvement on the previously reported equations primarily because this study (1) included 13 more years of peak-flow data; (2) included 35 more streamflow-gaging stations than previous studies; (3) used a detailed geographic information system (GIS)-based definition of the regulation status of streamflow-gaging stations, which allowed better determination of the unregulated peak-flow records that are appropriate for use in the regional regression analysis; (4) included advancements in GIS and remote-sensing technologies, which allowed more convenient calculation of basin characteristics and investigation of many more candidate basin characteristics; and (5) included advancements in computational and analytical methods, which allowed more thorough and consistent data analysis.</p><p>This report chapter also presents other methods for estimating peak-flow frequencies at ungaged sites. Two methods for estimating peak-flow frequencies at ungaged sites located on the same streams as streamflow-gaging stations are described. Additionally, envelope curves relating maximum recorded annual peak flows to contributing drainage area for each of the eight hydrologic regions in Montana are presented and compared to a national envelope curve. In addition to providing general information on characteristics of large peak flows, the regional envelope curves can be used to assess the reasonableness of peak-flow frequency estimates determined using the regression equations.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Montana StreamStats (Scientific Investigations Report 2015-5019)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155019F","collaboration":"Prepared in cooperation with the Montana Department of Natural Resources and Conservation","usgsCitation":"Sando, Roy, Sando, S.K., McCarthy, P.M., and Dutton, D.M., 2016, Methods for estimating peak-flow frequencies at ungaged sites in Montana based on data through water year 2011 (ver. 1.1, February 2018) : U.S. Geological Survey Scientific Investigations Report 2015–5019–F, 30 p., https://doi.org/10.3133/sir20155019F.","productDescription":"Report: viii, 30 p.; 5 Tables","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-063766","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":319655,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5019F/coverthb2.jpg"},{"id":351030,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2015/5019F/versionHist.txt","text":"Version History","size":"6.13 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2015–5019–F Version History"},{"id":351028,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5019F/sir20155019F.pdf","text":"Report","size":"7.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015–5019–F"},{"id":351029,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5019F/sir20155019F_tables.xlsx","text":"Tables 1–1 through 1–5","size":"250 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015–5019–F Appendix Tables"}],"country":"United 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 \"}}]}","edition":"Version 1.1: February 2018","contact":"<p>Director, Wyoming-Montana Water Science Center<br />U.S. Geological Survey<br />3162 Bozeman Ave<br />Helena, MT 59601</p>\n<p><a href=\"http://wy-mt.water.usgs.gov/\">http://wy-mt.water.usgs.gov/</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>General Flood Characteristics in Montana</li><li>Peak-Flow Frequencies at Streamflow-Gaging Stations</li><li>Methods for Estimating Peak-Flow Frequencies at Ungaged Sites in Montana</li><li>Examples of Estimating Peak-Flow Frequencies at Ungaged Sites</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Supplemental Information Relating to the Regional Regression Analysis</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-04-05","revisedDate":"2018-02-26","noUsgsAuthors":false,"publicationDate":"2016-04-05","publicationStatus":"PW","scienceBaseUri":"570f6db6e4b0ef3b7ca35696","contributors":{"authors":[{"text":"Sando, Roy 0000-0003-0704-6258","orcid":"https://orcid.org/0000-0003-0704-6258","contributorId":26230,"corporation":false,"usgs":true,"family":"Sando","given":"Roy","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":false,"id":620702,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sando, Steven K. 0000-0003-1206-1030 sksando@usgs.gov","orcid":"https://orcid.org/0000-0003-1206-1030","contributorId":1016,"corporation":false,"usgs":true,"family":"Sando","given":"Steven","email":"sksando@usgs.gov","middleInitial":"K.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620703,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCarthy, Peter 0000-0002-2396-7463 pmccarth@usgs.gov","orcid":"https://orcid.org/0000-0002-2396-7463","contributorId":2504,"corporation":false,"usgs":true,"family":"McCarthy","given":"Peter","email":"pmccarth@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620705,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dutton, DeAnn M. ddutton@usgs.gov","contributorId":20762,"corporation":false,"usgs":true,"family":"Dutton","given":"DeAnn M.","email":"ddutton@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":false,"id":620704,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70163006,"text":"sir20155019B - 2016 - Temporal trends and stationarity in annual peak flow and peak-flow timing for selected long-term streamflow-gaging stations in or near Montana through water year 2011: Chapter B in <i>Montana StreamStats</i>","interactions":[{"subject":{"id":70163006,"text":"sir20155019B - 2016 - Temporal trends and stationarity in annual peak flow and peak-flow timing for selected long-term streamflow-gaging stations in or near Montana through water year 2011: Chapter B in <i>Montana StreamStats</i>","indexId":"sir20155019B","publicationYear":"2016","noYear":false,"chapter":"B","title":"Temporal trends and stationarity in annual peak flow and peak-flow timing for selected long-term streamflow-gaging stations in or near Montana through water year 2011: Chapter B in <i>Montana StreamStats</i>"},"predicate":"IS_PART_OF","object":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"id":1}],"isPartOf":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"lastModifiedDate":"2018-02-28T16:38:07","indexId":"sir20155019B","displayToPublicDate":"2016-04-05T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5019","chapter":"B","title":"Temporal trends and stationarity in annual peak flow and peak-flow timing for selected long-term streamflow-gaging stations in or near Montana through water year 2011: Chapter B in <i>Montana StreamStats</i>","docAbstract":"<p>A large-scale study by the U.S. Geological Survey, in cooperation with the Montana Department of Transportation and the Montana Department of Natural Resources and Conservation, was done to investigate general patterns in peak-flow temporal trends and stationarity through water year 2011 for 24 long-term streamflow-gaging stations (hereinafter referred to as gaging stations) in Montana. Hereinafter, all years refer to water years; a water year is the 12-month period from October 1 through September 30 and is designated by the year in which it ends. The primary focus of the study was to identify general patterns in peak-flow temporal trends and stationarity that are relevant to application of peak-flow frequency analyses within a statewide gaging-station network.</p>\n<p>Temporal trends were analyzed for two hydrologic variables: annual peak flow and peak-flow timing. Annual peak flow is the maximum instantaneous discharge, in cubic feet per second, recorded each year a gaging station was operated. Peak-flow timing is the day of the annual peak flow (hereinafter referred to as day of peak), recorded each year a gaging station was operated.</p>\n<p>Study results provide evidence that annual peak flow for most of the long-term gaging stations can be reasonably considered as stationary for application of peak-flow frequency analyses within a statewide gaging station network. Upward trends in annual peak flow during 1930&ndash;76 generally were stronger than downward trends during 1967&ndash;2011 for most long-term gaging stations. Statistical distributions of annual peak flow generally were similar among three summary time periods (1930&ndash;78, 1979&ndash;2011, and the entire period of record). However, for two low-elevation gaging stations in eastern Montana (Poplar River at international boundary [gaging station 06178000] and Powder River at Moorhead, Montana [gaging station 06324500]), substantial downward trends in annual peak flow during 1967&ndash;2011 were of similar or stronger magnitude than the upward trends during 1930&ndash;76, and the annual-peak-flow medians for 1979&ndash;2011 were substantially lower than the medians for the entire period of record.</p>\n<p>For peak-flow timing for most long-term gaging stations, differences in trends between 1930&ndash;76 and 1967&ndash;2011 are variable and not particularly strong. Statistical distributions generally are similar among the summary time periods. However, for two high-elevation gaging stations on a Missouri River headwater tributary (Gallatin River near Gallatin Gateway, Montana [gaging station 06043500] and Gallatin River at Logan, Montana [gaging station 06052500]) and for five high-elevation gaging stations in the Yellowstone River Basin (Yellowstone River at Corwin Springs, Montana [gaging station 06191500], Yellowstone River near Livingston, Montana [gaging station 06192500], Clarks Fork Yellowstone River near Belfry, Montana [gaging station 06207500], Clarks Fork Yellowstone River at Edgar, Montana [gaging station 06208500], and Yellowstone River at Billings, Montana [gaging station 06214500]) downward trends in peak-flow timing during 1967&ndash;2011 generally were stronger than upward trends during 1930&ndash;1976, and day-of-peak medians for 1979&ndash;2011 were considerably less than medians for 1930&ndash;78. The downward trends in peak-flow timing for 1967&ndash;2011 indicate that the timing of annual peak flows changed from later in the year to earlier in the year. For the seven high-elevation gaging stations, the mean change during 1967&ndash;2011 was about 13 days (range of 8 to 22 days).</p>\n<p>For most of the high-elevation gaging stations in the Missouri River headwaters, Yellowstone River Basin, and Columbia River Basin, there was general correspondence between trend patterns for annual peak flow and trend patterns for peak-flow timing; that is, during periods when there were upward trends in annual peak flow, there generally also were upward trends in peak-flow timing. Conversely, during periods when there were downward trends in annual peak flow, there generally also were downward trends in peak-flow timing.</p>\n<p>The two low-elevation gaging stations in eastern Montana (Poplar River at international boundary [gaging station 06178000] and Powder River at Moorhead, Montana [gaging station 06324500]) had considerable changes in annual-peakflow characteristics after the mid-1970s, which might provide evidence of potential nonstationarity in the peak-flow records. The two low-elevation gaging stations that have potential nonstationarity are located in drainage basins that are strongly affected by agricultural activities that potentially affect the hydrologic regimes. Primary agricultural activities that might&nbsp;alter natural hydrologic conditions include construction of small impoundments (primarily for stock-watering purposes) and irrigation diversions. Temporal variability in these activities might contribute to the potential nonstationarity issues. Changes in climatic characteristics after the mid-1970s also possibly contribute to the potential nonstationarity issues. Lack of considerable indication of potential nonstationarity in annual peak flow for the other long-term gaging stations in this study might indicate that climatic changes have been more pronounced with respect to effects on peak flows in low elevation areas in eastern Montana than in areas represented by the other long-term gaging stations. Another possibility is that climatic changes after the mid-1970s are exacerbated in low-elevation areas where small-impoundment development and potential effects of irrigation diversions might be more extensive.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Montana StreamStats (Scientific Investigations Report 2015-5019)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155019B","collaboration":"Prepared in cooperation with the Montana Department of Transportation and Montana Department of Natural Resources and Conservation","usgsCitation":"Sando, S.K., McCarthy, P.M., Sando, Roy, and Dutton, D.M., 2016, Temporal trends and stationarity in annual peak flow and peak-flow timing for selected long-term streamflow-gaging stations in or near Montana through water year 2011: U.S. Geological Survey Scientific Investigations Report 2015–5019–B, 48 p., 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 \"}}]}","contact":"<p>Director, Wyoming-Montana Water Science Center<br />U.S. Geological Survey<br />3162 Bozeman Ave<br />Helena, MT 59601</p>\n<p><a href=\"http://wy-mt.water.usgs.gov/\">http://wy-mt.water.usgs.gov/</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Selection of Streamflow-Gaging Stations</li><li>Methods of Analysis</li><li>Factors that Affect Interpretation of Results</li><li>Temporal Trends and Stationarity in Annual Peak Flow and Peak-Flow Timing</li><li>Summary and Conclusions</li><li>References</li><li>Appendix 1. Information on Peak-Flow Frequency Analyses for Low-Elevation Streamflow-Gaging Stations in Eastern Montana</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-04-05","noUsgsAuthors":false,"publicationDate":"2016-04-05","publicationStatus":"PW","scienceBaseUri":"572477b3e4b0b13d3914e159","contributors":{"authors":[{"text":"Sando, Steven K. 0000-0003-1206-1030 sksando@usgs.gov","orcid":"https://orcid.org/0000-0003-1206-1030","contributorId":1016,"corporation":false,"usgs":true,"family":"Sando","given":"Steven","email":"sksando@usgs.gov","middleInitial":"K.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":622047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCarthy, Peter 0000-0002-2396-7463 pmccarth@usgs.gov","orcid":"https://orcid.org/0000-0002-2396-7463","contributorId":2504,"corporation":false,"usgs":true,"family":"McCarthy","given":"Peter","email":"pmccarth@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":625587,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sando, Roy 0000-0003-0704-6258","orcid":"https://orcid.org/0000-0003-0704-6258","contributorId":26230,"corporation":false,"usgs":true,"family":"Sando","given":"Roy","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":false,"id":625588,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dutton, DeAnn M. ddutton@usgs.gov","contributorId":20762,"corporation":false,"usgs":true,"family":"Dutton","given":"DeAnn M.","email":"ddutton@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":false,"id":625589,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70164331,"text":"sir20155019G - 2016 - Methods for estimating streamflow characteristics at ungaged sites in western Montana based on data through water year 2009: Chapter G in <i>Montana StreamStats</i>","interactions":[{"subject":{"id":70164331,"text":"sir20155019G - 2016 - Methods for estimating streamflow characteristics at ungaged sites in western Montana based on data through water year 2009: Chapter G in <i>Montana StreamStats</i>","indexId":"sir20155019G","publicationYear":"2016","noYear":false,"chapter":"G","displayTitle":"Methods for estimating streamflow characteristics at ungaged sites in western Montana based on data through water year 2009: Chapter G in <i>Montana StreamStats</i>","title":"Methods for estimating streamflow characteristics at ungaged sites in western Montana based on data through water year 2009: Chapter G in <i>Montana StreamStats</i>"},"predicate":"IS_PART_OF","object":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"id":1}],"isPartOf":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"lastModifiedDate":"2020-10-27T16:48:18.337033","indexId":"sir20155019G","displayToPublicDate":"2016-04-05T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5019","chapter":"G","displayTitle":"Methods for estimating streamflow characteristics at ungaged sites in western Montana based on data through water year 2009: Chapter G in <i>Montana StreamStats</i>","title":"Methods for estimating streamflow characteristics at ungaged sites in western Montana based on data through water year 2009: Chapter G in <i>Montana StreamStats</i>","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the Montana Department of Environmental Quality and the Montana Department of Natural Resources and Conservation, developed regional regression equations based on basin and streamflow characteristics for streamflow-gaging stations through water year 2009 that can be used to estimate streamflow characteristics for ungaged sites in western Montana. The regression equations allow estimation of low-flow frequencies; mean annual and mean monthly streamflows; and the 20-, 50-, and 80-percent durations for annual and monthly duration streamflows for ungaged sites in western Montana that are unaffected by regulation.</p>\n<p>Regression equations were developed for 54 streamflow characteristics in each of the 4 hydrologic regions generally located in western Montana. Exploratory data analyses determined that of the 40 basin characteristics used as explanatory variables, only 3 were significant in the final equations. These three basin characteristics are contributing drainage area, mean annual precipitation of the drainage basin, and percentage of basin with slopes greater than 50 percent. Low-flow frequency data and daily mean streamflow data from 152 streamflow-gaging stations were used to develop the regression equations. These 152 streamflow-gaging stations were considered to be unregulated (or only the unregulated period of record for regulated streamflow-gaging stations were used). For this study, a streamflow-gaging station is considered to be unregulated if cumulative drainage area upstream from all upstream dams is less than 20 percent of the drainage basin for the streamflow-gaging station, and if no large diversion canals are upstream from the streamflow-gaging station.</p>\n<p>In addition to the regional regression equations, two methods for estimating streamflow characteristics based on drainage areas of a nearby streamflow-gaging station are provided. Also, spreadsheet tools are provided for calculating streamflow characteristics based on regression equations or the drainage-area ratio method.</p>\n<p>All of the data used to calculate basin characteristics were derived from publicly available data sources and are available through&nbsp;the U.S. Geological Survey Streamstats program&nbsp;(<a href=\"http://water.usgs.gov/osw/streamstats/\">http://water.usgs.gov/osw/streamstats/</a>) for Montana. The primary purpose of the Montana StreamStats application is to provide estimates of basin characteristics and streamflow characteristics for user-selected ungaged sites on Montana streams. The regional regression equations presented in this report have been loaded to the Montana StreamStats application and can be used to derive streamflow characteristics for ungaged sites.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Montana StreamStats (Scientific Investigations Report 2015-5019)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155019G","collaboration":"Prepared in cooperation with the Montana Department of Environmental Quality and Montana Department of Natural Resources and Conservation","usgsCitation":"McCarthy, P.M., Sando, Roy, Sando, S.K., and Dutton, D.M., 2016, Methods for estimating streamflow characteristics at ungaged sites in western Montana based on data through water year 2009: U.S. Geological Survey Scientific Investigations Report 2015–5019–G, 19 p., https://dx.doi.org/10.3133/sir20155019G.","productDescription":"Report: vii, 19 p.; 10 Tables","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-067085","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":319659,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5019G/coverthb.jpg"},{"id":319661,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2015/5019G/sir20155019G_tables.xlsx","text":"Tables 1 through 4, 1–1 through 1–4, and 2–1 through 2–2","size":"483 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015–5019–G Tables"},{"id":319660,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5019G/sir20155019G.pdf","text":"Report","size":"9.77 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015–5019–G"}],"country":"United States","state":"Montana","geographicExtents":"{\n  \"type\": 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href=\"http://wy-mt.water.usgs.gov/\">http://wy-mt.water.usgs.gov/</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods for Estimating Streamflow Characteristics at Ungaged Sites in Montana</li><li>Tools for Estimating Streamflow Characteristics at Ungaged Sites in Montana</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Supplemental Information Relating to the Regional Regression Analyses</li><li>Appendix 2. Estimates of Streamflow Characteristics at Ungaged Sites</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-04-05","noUsgsAuthors":false,"publicationDate":"2016-04-05","publicationStatus":"PW","scienceBaseUri":"570f6db6e4b0ef3b7ca35698","contributors":{"authors":[{"text":"McCarthy, Peter 0000-0002-2396-7463 pmccarth@usgs.gov","orcid":"https://orcid.org/0000-0002-2396-7463","contributorId":2504,"corporation":false,"usgs":true,"family":"McCarthy","given":"Peter","email":"pmccarth@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620710,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sando, Roy 0000-0003-0704-6258","orcid":"https://orcid.org/0000-0003-0704-6258","contributorId":26230,"corporation":false,"usgs":true,"family":"Sando","given":"Roy","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":false,"id":620711,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sando, Steven K. 0000-0003-1206-1030 sksando@usgs.gov","orcid":"https://orcid.org/0000-0003-1206-1030","contributorId":1016,"corporation":false,"usgs":true,"family":"Sando","given":"Steven","email":"sksando@usgs.gov","middleInitial":"K.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620712,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dutton, DeAnn M. ddutton@usgs.gov","contributorId":20762,"corporation":false,"usgs":true,"family":"Dutton","given":"DeAnn M.","email":"ddutton@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":false,"id":620713,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70160856,"text":"sir20155186 - 2016 - Hydrogeology and groundwater quality at monitoring wells installed for the Tunnel and Reservoir Plan System and nearby water-supply wells, Cook County, Illinois, 1995–2013","interactions":[],"lastModifiedDate":"2016-05-17T08:51:18","indexId":"sir20155186","displayToPublicDate":"2016-04-04T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5186","title":"Hydrogeology and groundwater quality at monitoring wells installed for the Tunnel and Reservoir Plan System and nearby water-supply wells, Cook County, Illinois, 1995–2013","docAbstract":"<p>Groundwater-quality data collected from 1995 through 2013 from 106 monitoring wells open to the base of the Silurian aquifer surrounding the Tunnel and Reservoir Plan (TARP) System in Cook County, Illinois, were analyzed by the U.S. Geological Survey, in cooperation with the Metropolitan Water Reclamation District of Greater Chicago, to assess the efficacy of the monitoring network and the effects of water movement from the tunnel system to the surrounding aquifer. Groundwater from the Silurian aquifer typically drains to the tunnel system so that analyte concentrations in most of the samples from most of the monitoring wells primarily reflect the concentration of the analyte in the nearby Silurian aquifer. Water quality in the Silurian aquifer is spatially variable because of a variety of natural and non-TARP anthropogenic processes. Therefore, the trends in analyte values at a given well from 1995 through 2013 are primarily a reflection of the spatial variation in the value of the analyte in groundwater within that part of the Silurian aquifer draining to the tunnels. Intermittent drainage of combined sewer flow from the tunnel system to the Silurian aquifer when flow in the tunnel systemis greater than 80 million gallons per day may affect water quality in some nearby monitoring wells. Intermittent drainage of combined sewer flow from the tunnel system to the Silurian aquifer appears to affect the values of electrical conductivity, hardness, sulfate, chloride, dissolved organic carbon, ammonia, and fecal coliform in samples from many wells but typically during less than 5 percent of the sampling events. Drainage of combined sewer flow into the aquifer is most prevalent in the downstream parts of the tunnel systems because of the hydraulic pressures elevated above background values and long residence time of combined sewer flow in those areas. Elevated values of the analytes emplaced during intermittent migration of combined sewer flow into the Silurian aquifer decrease through time as water from the aquifer drains back into the tunnels in response to typical hydraulic conditions. Of the analytes sampled, fecal coliform provides the clearest indication of the location and timing of combined sewer flow into the Silurian aquifer surrounding the tunnel system.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155186","collaboration":"Prepared in cooperation with the Metropolitan Water Reclamation District of Greater Chicago","usgsCitation":"Kay, R.T., 2016, Hydrogeology and groundwater quality at monitoring wells installed for the Tunnel and Reservoir Plan System and nearby water-supply wells, Cook County, Illinois, 1995–2013 (ver 1.1, May 2016): U.S. Geological Survey Scientific Investigations Report 2015–5186, 347 p., https://dx.doi.org/10.3133/sir20155186.","productDescription":"vi, 347 p.","numberOfPages":"357","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1995-01-01","ipdsId":"IP-063316","costCenters":[{"id":344,"text":"Illinois Water Science 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1.0: Originally posted April 4, 2016; Version 1.1: May 16, 2016","contact":"<p><a href=\"mailto:dc_il@usgs.gov\">Director</a> Illinois Water Science Center<br /> U.S. Geological Survey<br /> 405 N Goodwin<br /> Urbana, IL 61801<br /> <a href=\"http://il.water.usgs.gov/\">http://il.water.usgs.gov/</a></p>","tableOfContents":"<ul>\n<li>Abstract</li>\n<li>Introduction</li>\n<li>Methods of Study</li>\n<li>Hydrogeology in the Vicinity of the Tunnel and Reservoir Plan System</li>\n<li>Water Quality in Tunnel and Reservoir Plan System Monitoring Wells</li>\n<li>Coliform Bacteria and <em>Escherichia coli</em> Data from Water-Supply Wells in the Vicinity of the Tunnel and Reservoir Plan System</li>\n<li>Implications for Future Monitoring</li>\n<li>Summary and Conclusions&nbsp;</li>\n<li>Acknowledgments</li>\n<li>References Cited</li>\n</ul>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2016-04-04","revisedDate":"2016-05-16","noUsgsAuthors":false,"publicationDate":"2016-04-04","publicationStatus":"PW","scienceBaseUri":"57038220e4b0328dcb81b367","contributors":{"authors":[{"text":"Kay, Robert T. 0000-0002-6281-8997 rtkay@usgs.gov","orcid":"https://orcid.org/0000-0002-6281-8997","contributorId":1122,"corporation":false,"usgs":true,"family":"Kay","given":"Robert","email":"rtkay@usgs.gov","middleInitial":"T.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":584048,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70192436,"text":"70192436 - 2016 - Enriched groundwater seeps in two Vermont headwater catchments are hotspots of nitrate turnover","interactions":[],"lastModifiedDate":"2017-10-30T11:22:28","indexId":"70192436","displayToPublicDate":"2016-04-04T00:00:00","publicationYear":"2016","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":"Enriched groundwater seeps in two Vermont headwater catchments are hotspots of nitrate turnover","docAbstract":"<p>Groundwater seeps in upland catchments are often enriched relative to stream waters, higher in pH, Ca<sup>2+</sup> and sometimes NO<sub>3</sub>¯. These seeps could be a NO<sub>3</sub>¯ sink because of increased denitrification potential but may also be ‘hotspots’ for nitrification because of the relative enrichment. We compared seep soils with nearby well-drained soils in two upland forested watersheds in Vermont that are sites of ongoing biogeochemical studies. Gross N transformation rates were measured over three years along with denitrification rates in the third year. Gross ammonification rates were not different between the seep and upland soils but gross nitrification rates were about 3 × higher in the seep soils. Net nitrification rates trended higher in the upland soils and NO<sub>3</sub>¯ consumption (gross—net) was 8 times higher in the seep soils. The average denitrification rate for seep soils was about equal to the difference in NO<sub>3</sub>¯ consumption between seep and upland soils, suggesting denitrification can make up the difference. Temporal variation in seep water NO<sub>3</sub>¯ concentration was correlated with watershed outlet NO<sub>3</sub>¯ concentration. However, it is not clear that in-seep processes greatly altered seep water NO<sub>3</sub>¯ contribution to the streams. Seep soils appear to be hotspots of both nitrification and denitrification.</p>","language":"English","publisher":"Springer","doi":"10.1007/s13157-016-0733-z","usgsCitation":"Kaur, A.J., Ross, D., Shanley, J.B., and Yatzor, A.R., 2016, Enriched groundwater seeps in two Vermont headwater catchments are hotspots of nitrate turnover: Wetlands, v. 36, no. 2, p. 237-249, https://doi.org/10.1007/s13157-016-0733-z.","productDescription":"13 p.","startPage":"237","endPage":"249","ipdsId":"IP-070374","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":347511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","volume":"36","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-15","publicationStatus":"PW","scienceBaseUri":"59f83a3ce4b063d5d309810a","contributors":{"authors":[{"text":"Kaur, Amninder J.","contributorId":198364,"corporation":false,"usgs":false,"family":"Kaur","given":"Amninder","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":715818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ross, Donald S.","contributorId":178218,"corporation":false,"usgs":false,"family":"Ross","given":"Donald S.","affiliations":[],"preferred":false,"id":715819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":715817,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yatzor, Anna R.","contributorId":198365,"corporation":false,"usgs":false,"family":"Yatzor","given":"Anna","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":715820,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70174881,"text":"70174881 - 2016 - Evaluating potential artefacts of photo-reversal on behavioral studies with nocturnal invasive sea lamprey (<i>Petromyzon marinus<i>)","interactions":[],"lastModifiedDate":"2016-07-20T11:35:47","indexId":"70174881","displayToPublicDate":"2016-04-01T18:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating potential artefacts of photo-reversal on behavioral studies with nocturnal invasive sea lamprey (<i>Petromyzon marinus<i>)","docAbstract":"<p><span>Sea lampreys (</span><i>Petromyzon marinus</i><span>&nbsp;L., 1758) are nocturnal, so experiments evaluating their behaviour to chemosensory cues have typically been conducted at night. However, given the brief timeframe each year that adult&nbsp;</span><i>P. marinus</i><span>&nbsp;are available for experimentation, we investigated whether&nbsp;</span><i>P. marinus</i><span>&nbsp;exposed to a 12 h shifted diurnal cycle (reversed photoperiod) could be tested in a darkened arena during the day and show the same response to chemosensory cues as natural photoperiod&nbsp;</span><i>P. marinus</i><span>&nbsp;that were tested during the night. Ten replicates of 10&nbsp;</span><i>P. marinus</i><span>, from each photoperiod, were exposed to deionized water (negative control), 2-phenylethylamine hydrochloride (PEA HCl, putative predator cue), or&nbsp;</span><i>P. marinus</i><span>&nbsp;whole-body extract (conspecific alarm cue). All&nbsp;</span><i>P. marinus</i><span>&nbsp;demonstrated a significant avoidance response to both cues. No significant differences were found in avoidance to PEA HCl between photoperiods. Avoidance of&nbsp;</span><i>P. marinus</i><span>&nbsp;whole-body extract was significantly stronger in natural compared with reversed photoperiod&nbsp;</span><i>P. marinus</i><span>. The use of reversed photoperiod subjects is suitable for examining the presence or absence of avoidance in response to novel chemosensory alarm cues, or the change in the magnitude of antipredator response. Studies investigating the natural magnitude of antipredator response should use natural photoperiod experimental subjects.</span></p>","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjz-2015-0254","collaboration":"Matthew Barnett; R.T. Di Rocco; Grant E. Brown; C. Michael Wager","usgsCitation":"Barnett, M., Imre, I., Wagner, C., Di Rocco, R.T., Johnson, N., and Brown, G.E., 2016, Evaluating potential artefacts of photo-reversal on behavioral studies with nocturnal invasive sea lamprey (<i>Petromyzon marinus<i>): Canadian Journal of Zoology, v. 94, no. 6, p. 405-410, https://doi.org/10.1139/cjz-2015-0254.","productDescription":"5 p.","startPage":"405","endPage":"410","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073715","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":325474,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5790a17ee4b030378fb47428","contributors":{"authors":[{"text":"Barnett, Matthew","contributorId":173003,"corporation":false,"usgs":false,"family":"Barnett","given":"Matthew","email":"","affiliations":[{"id":6585,"text":"Algoma University","active":true,"usgs":false}],"preferred":false,"id":642966,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Imre, Istvan","contributorId":150985,"corporation":false,"usgs":false,"family":"Imre","given":"Istvan","email":"","affiliations":[{"id":6585,"text":"Algoma University","active":true,"usgs":false}],"preferred":false,"id":642967,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wagner, C. Michael","contributorId":173006,"corporation":false,"usgs":false,"family":"Wagner","given":"C. Michael","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":642970,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Di Rocco, Richard T.","contributorId":173004,"corporation":false,"usgs":false,"family":"Di Rocco","given":"Richard","email":"","middleInitial":"T.","affiliations":[{"id":6585,"text":"Algoma University","active":true,"usgs":false}],"preferred":false,"id":642968,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":150983,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":642965,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brown, Grant E.","contributorId":173005,"corporation":false,"usgs":false,"family":"Brown","given":"Grant","email":"","middleInitial":"E.","affiliations":[{"id":6586,"text":"Concordia University","active":true,"usgs":false}],"preferred":false,"id":642969,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70202369,"text":"70202369 - 2016 - Managing nutrients, water, and energy for producing more food with low pollution (MoFoLoPo); What would success look like?","interactions":[],"lastModifiedDate":"2019-02-26T14:56:18","indexId":"70202369","displayToPublicDate":"2016-04-01T14:56:09","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1532,"text":"Environmental Development","active":true,"publicationSubtype":{"id":10}},"title":"Managing nutrients, water, and energy for producing more food with low pollution (MoFoLoPo); What would success look like?","docAbstract":"Synthetic nitrogen (N) fertilizer has enabled modern agriculture to greatly improve human nutrition during the 20th century, but it has also created unintended human health and environmental pollution challenges for the 21st century. Averaged globally, about half of the fertilizer N applied to farms is removed with the crops, while the other half remains in the soil or is lost from farmers’ fields, resulting in water and air pollution. As human population continues to grow and food security improves in the developing world, the dual development goals of producing more nutritious food with low pollution will require both technological and socio-economic innovations in agriculture.","language":"English","publisher":"Elsevier","doi":"10.1016/j.envdev.2016.03.002","usgsCitation":"Baron, J., 2016, Managing nutrients, water, and energy for producing more food with low pollution (MoFoLoPo); What would success look like?: Environmental Development, v. 18, p. 52-53, https://doi.org/10.1016/j.envdev.2016.03.002.","productDescription":"2 p.","startPage":"52","endPage":"53","ipdsId":"IP-073940","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":361558,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Baron, Jill 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":194124,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":758047,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70199158,"text":"70199158 - 2016 - Multi-laboratory survey of qPCR enterococci analysis method performance in U.S. coastal and inland surface waters","interactions":[],"lastModifiedDate":"2018-09-07T11:06:31","indexId":"70199158","displayToPublicDate":"2016-04-01T11:06:23","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2390,"text":"Journal of Microbiological Methods","active":true,"publicationSubtype":{"id":10}},"title":"Multi-laboratory survey of qPCR enterococci analysis method performance in U.S. coastal and inland surface waters","docAbstract":"<p><span>Quantitative polymerase chain reaction (qPCR) has become a frequently used technique for quantifying enterococci in recreational surface waters, but there are several methodological options. Here we evaluated how three method permutations, type of mastermix, sample extract dilution and use of controls in results calculation, affect method reliability among multiple laboratories with respect to sample interference. Multiple samples from each of 22 sites representing an array of habitat types were analyzed using EPA Method 1611 and 1609 reagents with full strength and five-fold diluted extracts. The presence of interference was assessed three ways: using sample processing and PCR amplifications controls; consistency of results across extract dilutions; and relative recovery of target genes from spiked enterococci in water sample compared to control matrices with acceptable recovery defined as 50 to 200%. Method 1609, which is based on an environmental mastermix, was found to be superior to Method 1611, which is based on a universal mastermix. Method 1611 had over a 40% control assay failure rate with undiluted extracts and a 6% failure rate with diluted extracts. Method 1609 failed in only 11% and 3% of undiluted and diluted extracts analyses. Use of sample processing control assay results in the delta–delta Ct method for calculating relative target gene recoveries increased the number of acceptable recovery results. Delta–delta tended to bias recoveries from apparent partially inhibitory samples on the high side which could help in avoiding potential underestimates of enterococci — an important consideration in a public health context. Control assay and delta–delta recovery results were largely consistent across the range of habitats sampled, and among laboratories. The methodological option that best balanced acceptable estimated target gene recoveries with method sensitivity and avoidance of underestimated enterococci densities was Method 1609 without extract dilution and using the delta–delta calculation method. The applicability of this method can be extended by the analysis of diluted extracts to sites where interference is indicated but, particularly in these instances, should be confirmed by augmenting the control assays with analyses for target gene recoveries from spiked target organisms.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.mimet.2016.01.017","usgsCitation":"Haugland, R.A., Siefring, S., Varma, M., Oshima, K.H., Sivaganesan, M., Cao, Y., Raith, M., Griffith, J., Weisberg, S.B., Noble, R.T., Blackwood, A.D., Kinzelman, J., Anan’eva, T., Bushon, R.N., Stelzer, E.A., Harwood, V.J., Gordon, K.V., and Sinigalliano, C., 2016, Multi-laboratory survey of qPCR enterococci analysis method performance in U.S. coastal and inland surface waters: Journal of Microbiological Methods, v. 123, p. 114-125, https://doi.org/10.1016/j.mimet.2016.01.017.","productDescription":"12 p.","startPage":"114","endPage":"125","ipdsId":"IP-101153","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":471094,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.17615/k7h6-m925","text":"External Repository"},{"id":357113,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a622e4b0702d0e8430c2","contributors":{"authors":[{"text":"Haugland, Richard A.","contributorId":207703,"corporation":false,"usgs":false,"family":"Haugland","given":"Richard","email":"","middleInitial":"A.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":744463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siefring, Shawn","contributorId":207704,"corporation":false,"usgs":false,"family":"Siefring","given":"Shawn","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":744464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Varma, Manju","contributorId":207705,"corporation":false,"usgs":false,"family":"Varma","given":"Manju","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":744465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oshima, Kevin H.","contributorId":178927,"corporation":false,"usgs":false,"family":"Oshima","given":"Kevin","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":744466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sivaganesan, Mano","contributorId":207706,"corporation":false,"usgs":false,"family":"Sivaganesan","given":"Mano","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":744467,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cao, Yiping","contributorId":207707,"corporation":false,"usgs":false,"family":"Cao","given":"Yiping","email":"","affiliations":[{"id":13211,"text":"Southern California Coastal Water Research Project Authority","active":true,"usgs":false}],"preferred":false,"id":744468,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Raith, Meredith","contributorId":207708,"corporation":false,"usgs":false,"family":"Raith","given":"Meredith","email":"","affiliations":[{"id":13211,"text":"Southern California Coastal Water Research Project Authority","active":true,"usgs":false}],"preferred":false,"id":744469,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Griffith, John","contributorId":207709,"corporation":false,"usgs":false,"family":"Griffith","given":"John","affiliations":[{"id":13211,"text":"Southern California Coastal Water Research Project Authority","active":true,"usgs":false}],"preferred":false,"id":744470,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Weisberg, Stephen B.","contributorId":207710,"corporation":false,"usgs":false,"family":"Weisberg","given":"Stephen","email":"","middleInitial":"B.","affiliations":[{"id":13211,"text":"Southern California Coastal Water Research Project Authority","active":true,"usgs":false}],"preferred":false,"id":744471,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Noble, Rachel T.","contributorId":207711,"corporation":false,"usgs":false,"family":"Noble","given":"Rachel","email":"","middleInitial":"T.","affiliations":[{"id":37611,"text":"Institute of Marine Sciences, University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":744472,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Blackwood, A. 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,{"id":70170956,"text":"70170956 - 2016 - Informing Lake Erie agriculture nutrient management via scenario evaluation","interactions":[],"lastModifiedDate":"2016-05-23T15:08:58","indexId":"70170956","displayToPublicDate":"2016-04-01T07:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Informing Lake Erie agriculture nutrient management via scenario evaluation","docAbstract":"<p>Harmful algal blooms (HABs) have been increasing in extent and intensity in the western basin of Lake Erie. The cyanobacteria <i>Microcystis</i> produces toxins that pose serious threats to animal and human health, resulting in beach closures and impaired water supplies, and have even forced a &ldquo;do not drink&rdquo; advisory for the City of Toledo water system for several days in the summer of 2014. The main driver of Lake Erie HABs is elevated phosphorus loading from watersheds draining to the western basin, particularly from the Maumee River watershed (Obenour et al. 2014). Through the 2012 Great Lakes Water Quality Agreement (GLWQA), the U.S. and Canadian governments agreed to revise Lake Erie phosphorus loading targets to decrease HAB severity below levels representing a hazard to ecosystem and human health. New targets limit March-July loadings from the Maumee River to 186 metric tonnes of dissolved reactive phosphorus (DRP) and 860 metric tonnes of total phosphorus (TP) &ndash; a 40% reduction from 2008 loads (GLWQA 2016).</p>\n<p>The Great Lakes region must now determine what policy options are most effective and feasible for meeting those targets. While all sources are important, our focus is on agriculture because it overwhelms other sources. In a conservative ballpark estimate we found that 85% of the Maumee River&rsquo;s load to Lake Erie comes from farm fertilizers and manures, even though this is only 10% of farmland fertilizer applications (Figure 1). Load targets will not be met without reductions from agriculture.</p>\n<p>Therefore, the overall goal of this study was to identify potential options for agricultural management to reduce phosphorus loads and lessen future HABs in Lake Erie. We applied multiple watershed models to test the ability of a series of land management scenarios, developed in consultation with agricultural and environmental stakeholders, to reach the proposed targets.&nbsp;</p>","language":"English","publisher":"University of Michigan Water Center","usgsCitation":"Scavia, D., Kalcic, M., Muenich, R.L., Aloysius, N., Arnold, J., Boles, C., Confesor, R., DePinto, J., Gildow, M., Martin, J., Read, J., Redder, T., Robertson, D.M., Sowa, S.P., Wang, Y., White, M., and Yen, H., 2016, Informing Lake Erie agriculture nutrient management via scenario evaluation, 79 p.","productDescription":"79 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074926","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":321515,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":321514,"rank":1,"type":{"id":15,"text":"Index 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,{"id":70168634,"text":"70168634 - 2016 - Increasing influence of air temperature on upper Colorado River streamflow","interactions":[],"lastModifiedDate":"2018-04-03T11:23:43","indexId":"70168634","displayToPublicDate":"2016-04-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Increasing influence of air temperature on upper Colorado River streamflow","docAbstract":"<p><span>This empirical study examines the influence of precipitation, temperature, and antecedent soil moisture on upper Colorado River basin (UCRB) water year streamflow over the past century. While cool season precipitation explains most of the variability in annual flows, temperature appears to be highly influential under certain conditions, with the role of antecedent fall soil moisture less clear. In both wet and dry years, when flow is substantially different than expected given precipitation, these factors can modulate the dominant precipitation influence on streamflow. Different combinations of temperature, precipitation, and soil moisture can result in flow deficits of similar magnitude, but recent droughts have been amplified by warmer temperatures that exacerbate the effects of relatively modest precipitation deficits. Since 1988, a marked increase in the frequency of warm years with lower flows than expected, given precipitation, suggests continued warming temperatures will be an increasingly important influence in reducing future UCRB water supplies.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015GL067613","usgsCitation":"Woodhouse, C.A., Pederson, G.T., Morino, K., McAfee, S., and McCabe, G., 2016, Increasing influence of air temperature on upper Colorado River streamflow: Geophysical Research Letters, v. 43, no. 5, p. 2174-2181, https://doi.org/10.1002/2015GL067613.","productDescription":"8 p.","startPage":"2174","endPage":"2181","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069464","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471106,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl067613","text":"Publisher Index Page"},{"id":322023,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-09","publicationStatus":"PW","scienceBaseUri":"57500767e4b0ee97d51bb659","contributors":{"authors":[{"text":"Woodhouse, Connie A.","contributorId":187601,"corporation":false,"usgs":false,"family":"Woodhouse","given":"Connie","email":"","middleInitial":"A.","affiliations":[{"id":32413,"text":"University of Arizona, Tucson, AZ, USA, 85721","active":true,"usgs":false}],"preferred":false,"id":621077,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":621076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morino, Kiyomi","contributorId":78210,"corporation":false,"usgs":true,"family":"Morino","given":"Kiyomi","email":"","affiliations":[],"preferred":false,"id":621078,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McAfee, Stephanie A.","contributorId":167115,"corporation":false,"usgs":false,"family":"McAfee","given":"Stephanie A.","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":621079,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":167116,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":621080,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
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