{"pageNumber":"326","pageRowStart":"8125","pageSize":"25","recordCount":41075,"records":[{"id":70215101,"text":"70215101 - 2019 - Interferometric synthetic aperture radar study of recent eruptive activity at Shrub mud volcano, Alaska","interactions":[],"lastModifiedDate":"2020-10-07T20:05:21.607512","indexId":"70215101","displayToPublicDate":"2019-09-06T14:48:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Interferometric synthetic aperture radar study of recent eruptive activity at Shrub mud volcano, Alaska","docAbstract":"Shrub mud volcano is one of three large mud volcanoes that comprise the Klawasi Group in the Copper River Basin of southcentral Alaska. Except for minor discharges in the mid-1950s when the group was first described, Shrub was dormant prior to its reactivation in summer 1996. From 1997 to 1999, Shrub vigorously erupted more than 5 x 105 cubic meters of saline mud and carbon dioxide-rich gas at temperatures as high as 54 degrees C. Thereafter, activity waned but continued at least through 2015. We analyzed 192 interferograms derived from 106 synthetic aperture radar (SAR) images acquired by the JERS-1 (L-band), ERS-1/2 (C-band), RADARSAT-1 (C-band), and ALOS PALSAR (L-band) satellites to characterize ground deformation at Shrub before, during, and after its reactivation. Collectively, the interferograms span 1992–2000 and 2006–2011. We fit the observations with two deformation sources: a deflating, steeply dipping, pipe-like body under the summit area and an inflating, shallow-dipping, sill-like body under the southwest flank. Both sources are shallow, with centroids less than 1 km beneath the summit. Prior to reactivation, the flank source inflated ~0.35 x 105 cubic meters per year from July 1992 to May 1996. During eruptive activity, the summit source deflated at higher rates that peaked at ~8.71 x 105 cubic meters per year during May–November 1997 and continued at ~0.95 x 105 cubic meters per year during the 2006–2011 observation window. Cumulative source-volume loss is comparable to the volume of mud erupted. We interpret the summit source as the volcano’s feeder conduit that pressurized prior to the first SAR observation in 1992. Also before 1992, the conduit ruptured to feed a lateral intrusion of mud under the southwest flank, perhaps along a bedding plane in underlying glaciolacustrine deposits. The growing sill caused the southwest flank to inflate while it accommodated the mud supply from depth, which explains why we observed pre-eruptive inflation of the flank but not the summit. The summit began deflating when the conduit ruptured to the surface at the onset of eruptive activity. The flank source did not deflate concurrently because the weight of the thin overburden was insufficient to collapse the sill. There is a suggestion in the modern topography that lateral intrusions under Shrub’s southwest flank are a common feature of activity there.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2019.106671","usgsCitation":"Niu, Y., Dzurisin, D., and Lu, Z., 2019, Interferometric synthetic aperture radar study of recent eruptive activity at Shrub mud volcano, Alaska: Journal of Volcanology and Geothermal Research, v. 387, 106671 12p., https://doi.org/10.1016/j.jvolgeores.2019.106671.","productDescription":"106671 12p.","ipdsId":"IP-109278","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":379173,"type":{"id":15,"text":"Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2019.106671"},{"id":379196,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Shrub Mud Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -145.2886962890625,\n              61.87169117378061\n            ],\n            [\n              -144.5306396484375,\n              61.87169117378061\n            ],\n            [\n              -144.5306396484375,\n              62.37509086856917\n            ],\n            [\n              -145.2886962890625,\n              62.37509086856917\n            ],\n            [\n              -145.2886962890625,\n              61.87169117378061\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"387","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Niu, Yufen","contributorId":242811,"corporation":false,"usgs":false,"family":"Niu","given":"Yufen","email":"","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":800868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dzurisin, Daniel 0000-0002-0138-5067 dzurisin@usgs.gov","orcid":"https://orcid.org/0000-0002-0138-5067","contributorId":538,"corporation":false,"usgs":true,"family":"Dzurisin","given":"Daniel","email":"dzurisin@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":800869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lu, Zhong","contributorId":199794,"corporation":false,"usgs":false,"family":"Lu","given":"Zhong","affiliations":[],"preferred":false,"id":800870,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70203995,"text":"pp1842H - 2019 - The effects of management practices on grassland birds—Marbled Godwit (<i>Limosa fedoa</i>)","interactions":[{"subject":{"id":70203995,"text":"pp1842H - 2019 - The effects of management practices on grassland birds—Marbled Godwit (<i>Limosa fedoa</i>)","indexId":"pp1842H","publicationYear":"2019","noYear":false,"chapter":"H","displayTitle":"The Effects of Management Practices on Grassland Birds—Marbled Godwit (<i>Limosa fedoa</i>)","title":"The effects of management practices on grassland birds—Marbled Godwit (<i>Limosa fedoa</i>)"},"predicate":"IS_PART_OF","object":{"id":70203022,"text":"pp1842 - 2019 - The effects of management practices on grassland birds","indexId":"pp1842","publicationYear":"2019","noYear":false,"title":"The effects of management practices on grassland birds"},"id":1}],"isPartOf":{"id":70203022,"text":"pp1842 - 2019 - The effects of management practices on grassland birds","indexId":"pp1842","publicationYear":"2019","noYear":false,"title":"The effects of management practices on grassland birds"},"lastModifiedDate":"2023-12-20T21:07:12.547889","indexId":"pp1842H","displayToPublicDate":"2019-09-06T10:15:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1842","chapter":"H","displayTitle":"The Effects of Management Practices on Grassland Birds—Marbled Godwit (<i>Limosa fedoa</i>)","title":"The effects of management practices on grassland birds—Marbled Godwit (<i>Limosa fedoa</i>)","docAbstract":"<p>Keys to Marbled Godwit (<i>Limosa fedoa</i>) management include providing large expanses of short, sparsely to moderately vegetated landscapes that include native grasslands and wetland complexes. Optimal wetland complexes should contain a diversity of wetland classes and sizes, such as ephemeral, temporary, seasonal, semipermanent, permanent, and alkali wetlands, as well as intermittent streams. Marbled Godwits use wetlands of various salinities. The species has been reported to use habitats with less than or equal to 70 centimeters (cm) average vegetation height, 4–23 cm visual obstruction reading, and 1–9 cm litter depth.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1842H","usgsCitation":"Shaffer, J.A., Igl, L.D., Johnson, D.H., Sondreal, M.L., Goldade, C.M., Nenneman, M.P., and Euliss, B.R., 2019, The effects of management practices on grassland birds—Marbled Godwit (<i>Limosa fedoa</i>), chap. H <i>of</i> Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 9 p., https://doi.org/10.3133/pp1842H.","productDescription":"iv, 9 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-095156","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":366525,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/h/coverthb.jpg"},{"id":366526,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/h/pp1842h.pdf","text":"Report","size":"1.10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842–H"}],"contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/npwrc\" data-mce-href=\"https://www.usgs.gov/centers/npwrc\">Northern Prairie Wildlife Research Center</a> <br>U.S. Geological Survey<br>8711 37th Street Southeast <br>Jamestown, ND 58401</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Capsule Statement</li><li>Breeding Range</li><li>Suitable Habitat</li><li>Area Requirements and Landscape Associations</li><li>Brood Parasitism by Cowbirds and Other Species</li><li>Breeding-Season Phenology and Site Fidelity</li><li>Species’ Response to Management</li><li>Management Recommendations from the Literature</li><li>References</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2019-09-06","noUsgsAuthors":false,"publicationDate":"2019-09-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Shaffer, Jill A. 0000-0003-3172-0708 jshaffer@usgs.gov","orcid":"https://orcid.org/0000-0003-3172-0708","contributorId":3184,"corporation":false,"usgs":true,"family":"Shaffer","given":"Jill","email":"jshaffer@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":765272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Igl, Lawrence D. 0000-0003-0530-7266 ligl@usgs.gov","orcid":"https://orcid.org/0000-0003-0530-7266","contributorId":2381,"corporation":false,"usgs":true,"family":"Igl","given":"Lawrence","email":"ligl@usgs.gov","middleInitial":"D.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":765271,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Douglas H. 0000-0002-7778-6641","orcid":"https://orcid.org/0000-0002-7778-6641","contributorId":216665,"corporation":false,"usgs":true,"family":"Johnson","given":"Douglas H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":765273,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sondreal, Marriah L.","contributorId":215631,"corporation":false,"usgs":false,"family":"Sondreal","given":"Marriah","email":"","middleInitial":"L.","affiliations":[{"id":39297,"text":"former U.S. Geological Survey employee","active":true,"usgs":false}],"preferred":false,"id":765274,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goldade, Christopher M.","contributorId":215632,"corporation":false,"usgs":false,"family":"Goldade","given":"Christopher","email":"","middleInitial":"M.","affiliations":[{"id":39297,"text":"former U.S. Geological Survey employee","active":true,"usgs":false}],"preferred":false,"id":765275,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nenneman, Melvin P.","contributorId":190777,"corporation":false,"usgs":false,"family":"Nenneman","given":"Melvin","email":"","middleInitial":"P.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":765276,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Euliss, Betty R.","contributorId":191881,"corporation":false,"usgs":false,"family":"Euliss","given":"Betty","email":"","middleInitial":"R.","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":765277,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70227103,"text":"70227103 - 2019 - Activity patterns of cave-dwelling bat species during pre-hibernation swarming and post-hibernation emergence in the central Appalachians","interactions":[],"lastModifiedDate":"2021-12-29T14:09:04.256479","indexId":"70227103","displayToPublicDate":"2019-09-06T08:03:10","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Activity patterns of cave-dwelling bat species during pre-hibernation swarming and post-hibernation emergence in the central Appalachians","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">In North America, bat research efforts largely have focused on summer maternity colonies and winter hibernacula, leaving the immediate pre- and post-hibernation ecology for many species unstudied. Understanding these patterns and processes is critical for addressing potential additive impacts to White-nose Syndrome (WNS)-affected bats, as autumn is a time of vital weight gain and fat resources are largely depleted in early spring in surviving individuals. Our study sought to examine autumn and spring bat activity patterns in the central Appalachian Mountains around three hibernacula to better understand spatio-temporal patterns during staging for hibernation and post-hibernation migration in the post-WNS environment. From early September through November 2015 and 2016, and from early March through April 2016 and 2017, we assessed the effects of distance to hibernacula and ambient conditions on nightly bat activity for<span>&nbsp;</span><span class=\"html-italic\">Myotis</span><span>&nbsp;</span>spp. and big brown bats (<span class=\"html-italic\">Eptesicus fuscus</span>) using zero-crossing frequency division bat detectors near cave entrances and 1 km, 2 km, and 3 km distant from caves. Following identification of echolocation calls, we used generalized linear mixed effects models to examine patterns of activity across the landscape over time and relative to weather. Overall bat activity was low at all sample sites during autumn and spring periods except at sites closest to hibernacula. Best-supported models describing bat activity varied, but date and ambient temperatures generally appeared to be major drivers of activity in both seasons. Total activity for all species had largely ceased by mid-November. Spring bat activity was variable across the sampling season, however, some activity was observed as early as mid-March, almost a month earlier than the historically accepted emergence time regionally. Current timing of restrictions on forest management activities that potentially remove day-roosts near hibernacula when bats are active on the landscape may be mismatched with actual spring post-hibernation emergence. Adjustments to the timing of these restrictions during the spring may help to avoid potentially additive negative impacts on WNS-impacted bat species.<span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span></span></span></div>","language":"English","publisher":"MDPI","doi":"10.3390/d11090159","usgsCitation":"Muthersbaugh, M.S., Ford, W., Silvis, A., and Powers, K.E., 2019, Activity patterns of cave-dwelling bat species during pre-hibernation swarming and post-hibernation emergence in the central Appalachians: Diversity, v. 11, no. 9, 159, 24 p., https://doi.org/10.3390/d11090159.","productDescription":"159, 24 p.","ipdsId":"IP-099086","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":459904,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d11090159","text":"Publisher Index Page"},{"id":393571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"9","noUsgsAuthors":false,"publicationDate":"2019-09-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Muthersbaugh, Michael S.","contributorId":270636,"corporation":false,"usgs":false,"family":"Muthersbaugh","given":"Michael","email":"","middleInitial":"S.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":829635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":829634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silvis, Alexander","contributorId":270638,"corporation":false,"usgs":false,"family":"Silvis","given":"Alexander","affiliations":[{"id":56191,"text":"Resource Environmental Solutions","active":true,"usgs":false}],"preferred":false,"id":829636,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powers, Karen E.","contributorId":270639,"corporation":false,"usgs":false,"family":"Powers","given":"Karen","email":"","middleInitial":"E.","affiliations":[{"id":34752,"text":"Radford University","active":true,"usgs":false}],"preferred":false,"id":829637,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70204482,"text":"ofr20191083 - 2019 - Numerical model simulations of potential changes in water levels and capture of natural discharge from groundwater withdrawals in Snake Valley and adjacent areas, Utah and Nevada","interactions":[],"lastModifiedDate":"2019-09-06T09:03:16","indexId":"ofr20191083","displayToPublicDate":"2019-09-05T14:12:01","publicationYear":"2019","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":"2019-1083","displayTitle":"Numerical Model Simulations of Potential Changes in Water Levels and Capture of Natural Discharge From Groundwater Withdrawals in Snake Valley and Adjacent Areas, Utah and Nevada","title":"Numerical model simulations of potential changes in water levels and capture of natural discharge from groundwater withdrawals in Snake Valley and adjacent areas, Utah and Nevada","docAbstract":"<p>The National Park Service (NPS) and the Bureau of Land Management (BLM) are concerned about cumulative effects of groundwater development on groundwater-dependent resources managed by, and other groundwater resources of interest to, these agencies in Snake Valley and adjacent areas, Utah and Nevada. Of particular concern to the NPS and BLM are withdrawals from all existing approved, perfected, certified, permitted, and vested groundwater rights in Snake Valley totaling about 55,272 acre-feet per year (acre-ft/yr), and from several senior water-right applications filed by the Southern Nevada Water Authority (SNWA) totaling 50,680 acre-ft/yr.</p><p>An existing groundwater-flow model of the eastern Great Basin was used to investigate where potential drawdown and capture of natural discharge is likely to result from potential groundwater withdrawals from existing groundwater rights in Snake Valley, and from groundwater withdrawals proposed in several applications filed by the SNWA. To evaluate the potential effects of the existing and proposed SNWA groundwater withdrawals, 11 withdrawal scenarios were simulated. All scenarios were run as steady state to estimate the ultimate long-term effects of the simulated withdrawals. This assessment provides a general understanding of the relative susceptibility of the groundwater resources of interest to the NPS and BLM, and the groundwater system in general, to existing and future groundwater development in the study area.</p><p>At the NPS and BLM groundwater resource sites of interest, simulated drawdown resulting from withdrawals based on existing approved, perfected, certified, permitted, and vested groundwater rights within Snake Valley ranged between 0 and 159 feet (ft) without accounting for irrigation return flow, and between 0 and 123 ft with accounting for irrigation return flow. With the addition of proposed SNWA withdrawals of 35,000 acre-ft/yr (equal to the Unallocated Groundwater portion allotted to Nevada in a draft interstate agreement), simulated drawdowns at the NPS and BLM sites of interest increased to range between 0 and 2,074 ft without irrigation return flow, and between 0 and 2,002 ft with irrigation return flow. With the addition of the proposed SNWA withdrawals of an amount equal to the full application amounts (50,680 acre-ft/yr), simulated drawdowns at the NPS and BLM sites of interest increased to range between 1 and 3,119 ft without irrigation return flow, and between 1 and 3,044 ft with irrigation return flow.</p><p>At the NPS and BLM groundwater resource sites of interest, simulated capture of natural discharge resulting from withdrawals based on existing groundwater rights in Snake Valley, both with and without irrigation return flow, ranged between 0 and 100 percent; simulated capture of 100 percent occurred at four sites. With the addition of proposed SNWA withdrawals of an amount equal to the Unallocated Groundwater portion allotted to Nevada in the draft interstate agreement, simulated capture of 100 percent occurred at nine additional sites without irrigation return flow, and at eight additional sites with irrigation return flow. With the addition of the proposed SNWA withdrawals of an amount equal to the full application amounts, simulated capture of 100 percent occurred at 11 additional sites without irrigation return flow, and at 9 additional sites with irrigation return flow.</p><p>The large simulated drawdowns produced in the scenarios that include large portions or all of the proposed SNWA withdrawals indicate that the groundwater system may not be able to support the amount of withdrawals from the proposed points of diversion (PODs) in the current SNWA water-right applications. Therefore, four additional scenarios were simulated where the withdrawal rates at the SNWA PODs were constrained by not allowing drawdowns to be deeper than the assumed depth of the PODs (about 2,000 ft). In the constrained scenarios, total withdrawals at the SNWA PODs were reduced to about 48 percent of the Unallocated Groundwater portion allotted to Nevada (35,000 acre-ft/yr reduced to 16,817 acre-ft/yr or 16,914 acre-ft/yr, without or with irrigation return flow, respectively), and about 44 percent of the full application amounts (50,680 acre-ft/yr reduced to 22,048 acre-ft/yr or 22,165 acre-ft/yr, without or with irrigation return flow, respectively). This indicates that the SNWA may need to add more PODs, or PODs in different locations, in order to withdraw large portions or all of the groundwater that has been applied for.</p><p>At the NPS and BLM groundwater resource sites of interest, simulated drawdown resulting from the addition of the constrained SNWA withdrawals applied to the Unallocated Groundwater amount ranged between 0 and 290 ft without irrigation return flow, and between 0 and 252 ft with irrigation return flow. With the addition of the constrained SNWA withdrawals applied to the full application amounts, simulated drawdowns at the NPS and BLM sites of interest ranged between 0 and 358 ft without irrigation return flow, and between 0 and 313 ft with irrigation return flow.</p><p>At the NPS and BLM groundwater resource sites of interest, with the addition of the constrained SNWA withdrawals applied to the Unallocated Groundwater amount, simulated capture of 100 percent of the natural discharge occurred at five additional sites without irrigation return flow, and at two additional sites with irrigation return flow (in addition to the four captured from existing water rights both with and without irrigation return flow). With the addition of the constrained SNWA withdrawals applied to the full application amounts, simulated capture of 100 percent occurred at six additional sites both with and without irrigation return flow.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191083","collaboration":"Prepared in cooperation with the National Park Service and the Bureau of Land Management","usgsCitation":"Masbruch, M.D., 2019, Numerical model simulations of potential changes in water levels and capture of natural discharge from groundwater withdrawals in Snake Valley and adjacent areas, Utah and Nevada: U.S. Geological Survey Open-File Report 2019–1083, 49 p., https://doi.org/10.3133/ofr20191083.","productDescription":"Report: vi, 49 p.; Data Release","numberOfPages":"49","onlineOnly":"Y","ipdsId":"IP-103457","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":367115,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1083/coverthb_.jpg"},{"id":367116,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1083/ofr20191083.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1083"},{"id":367119,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LQDQGM","text":"Data Release","linkHelpText":"MODFLOW-2005 files for numerical model simulations of potential changes in water levels and capture of natural discharge from groundwater withdrawals in Snake Valley and adjacent areas, Utah and Nevada"}],"country":"United States","state":"Nevada, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.48828125000001,\n              35.53222622770337\n            ],\n            [\n              -110.302734375,\n              39.36827914916014\n            ],\n            [\n              -110.12695312499999,\n              40.97989806962013\n            ],\n            [\n              -111.005859375,\n              42.68243539838623\n            ],\n            [\n              -114.78515624999999,\n              41.244772343082076\n            ],\n            [\n              -117.59765625,\n              37.64903402157866\n            ],\n            [\n              -115.48828125000001,\n              35.53222622770337\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/ut-water/connect\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/ut-water/connect\">Director</a>,&nbsp;<br><a href=\"https://ut.water.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://ut.water.usgs.gov\">Utah Water Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>2329 West Orton Circle<br>Salt Lake City, Utah 84119-2047<br>801-908-5000</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Potential Effects of Groundwater Withdrawals</li><li>Model Limitations</li><li>Appropriate Uses of the Model</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2019-08-30","noUsgsAuthors":false,"publicationDate":"2019-08-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Masbruch, Melissa D. 0000-0001-6568-160X mmasbruch@usgs.gov","orcid":"https://orcid.org/0000-0001-6568-160X","contributorId":1902,"corporation":false,"usgs":true,"family":"Masbruch","given":"Melissa","email":"mmasbruch@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":767190,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70209688,"text":"70209688 - 2019 - Crustal magmatism and anisotropy beneath the Arabian Shield - A cautionary tale","interactions":[],"lastModifiedDate":"2020-04-21T16:39:34.366322","indexId":"70209688","displayToPublicDate":"2019-09-05T11:34:14","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Crustal magmatism and anisotropy beneath the Arabian Shield - A cautionary tale","docAbstract":"<p><span>Volcanism in Saudi Arabia includes a historic eruption close to the holy city of Al Madinah. As part of a volcanic hazard assessment of this area, magnetotelluric (MT) data were collected to investigate the structural setting, the distribution of melt within the crust, and the mantle source of volcanism. Interpretation of a new 3‐D resistivity model includes a shallow graben beneath thin lava fields (Harrats), a melt‐free upper crust, and decompression melting in the asthenosphere below thin lithosphere. Within the lower crust the model images elongate conductivity anomalies, one of which was attributed in a previous MT study to melt. The regional MT data, combined with perspective from geology and geophysical modeling, suggest the lower crust is anisotropic with no interconnected melt zones. These divergent interpretations have distinct hazard implications and highlight the importance of large survey aperture and anisotropic modeling to MT studies of volcanic regions. Lower‐crustal anisotropy extends beyond the Harrat, with the most conductive direction oriented N10°E and a factor of 3–5, determined from 2‐D anisotropic inversion, between the most and least conductive directions. The enhanced conductivity is likely due to interconnected grain boundary graphite, while the anisotropy direction reflects either frozen‐in fabric from Neoproterozoic stabilization of the Arabian Shield or modern ductile deformation driven by channelized asthenospheric flow coupled through a thin rigid mantle lid. Asthenospheric melt is interpreted to transect the crust primarily through diking, with limited melt storage and short residence times in the crust.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JB017903","collaboration":"","usgsCitation":"Bedrosian, P.A., Peacock, J., Al-Dhahry, M.K., Shareef, A., Feucht, D., and Zahran, H.M., 2019, Crustal magmatism and anisotropy beneath the Arabian Shield - A cautionary tale: Journal of Geophysical Research B: Solid Earth, v. 124, no. 10, p. 10153-10179, https://doi.org/10.1029/2019JB017903.","productDescription":"27 p.","startPage":"10153","endPage":"10179","ipdsId":"IP-104561","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":374162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Saudi Arabia","otherGeospatial":"Arabian Shield","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              35.68359375,\n              27.605670826465445\n            ],\n            [\n              37.3095703125,\n              24.5271348225978\n            ],\n            [\n              39.15527343749999,\n              21.3303150734318\n            ],\n            [\n              41.3525390625,\n              18.145851771694467\n            ],\n            [\n              42.7587890625,\n              16.341225619207496\n            ],\n            [\n              42.978515625,\n              16.551961721972525\n            ],\n            [\n              44.1650390625,\n              18.521283325496277\n            ],\n            [\n              45.2197265625,\n              20.756113874762082\n            ],\n            [\n              43.3740234375,\n              23.40276490540795\n            ],\n            [\n              40.5615234375,\n              27.01998400798257\n            ],\n            [\n              35.68359375,\n              27.605670826465445\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"124","issue":"10","noUsgsAuthors":false,"publicationDate":"2019-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":787526,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peacock, Jared R. 0000-0002-0439-0224","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":210082,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":787527,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Al-Dhahry, Maher K.","contributorId":224237,"corporation":false,"usgs":false,"family":"Al-Dhahry","given":"Maher","email":"","middleInitial":"K.","affiliations":[{"id":36695,"text":"Saudi Geological Survey","active":true,"usgs":false}],"preferred":true,"id":787528,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shareef, Adel","contributorId":216214,"corporation":false,"usgs":false,"family":"Shareef","given":"Adel","email":"","affiliations":[{"id":36695,"text":"Saudi Geological Survey","active":true,"usgs":false}],"preferred":false,"id":787529,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Feucht, D. 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,{"id":70204915,"text":"sir20195090 - 2019 - Tritium as an indicator of modern, mixed, and premodern groundwater age","interactions":[],"lastModifiedDate":"2019-09-05T09:14:28","indexId":"sir20195090","displayToPublicDate":"2019-09-05T10:00:00","publicationYear":"2019","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":"2019-5090","title":"Tritium as an indicator of modern, mixed, and premodern groundwater age","docAbstract":"<p>Categorical classification of groundwater age is often used for the assessment and understanding of groundwater resources. This report presents a tritium-based age classification system for the conterminous United States based on tritium (<sup>3</sup>H) thresholds that vary in space and time: modern (recharged in 1953 or later), if the measured value is larger than an upper threshold; premodern (recharged prior to 1953) if the measured value is smaller than a lower threshold; or mixed if the measured value is between the two thresholds. Inclusion of spatially varying thresholds, rather than a single threshold, accounts for the observed systematic variation in <sup>3</sup>H deposition across the United States. Inclusion of time-varying thresholds, rather than a single threshold, accounts for the date of sampling given the radioactive decay of <sup>3</sup>H.</p><p>The efficacy of the tritium-based age classification system was evaluated at national and regional scales. The system was evaluated at a national scale by classifying samples from 1,788 public-supply wells distributed across 19 principal aquifers and comparing those results with expectations based on hydrogeologic principles. The regional-scale data are from five paired networks of shallow and deep wells (287 wells). As expected, modern groundwater is more prevalent in shallow wells than in deeper wells, in fractured-rock and carbonate aquifers as compared to clastic aquifers, in unconfined areas as compared to confined areas, and in humid climates as compared to arid climates. The results from a tritium-based age classification system compared favorably with the results of 14 previous studies of groundwater ages that used different age tracers and analytical methods. The wells and samples from the Cambrian-Ordovician aquifer that had been analyzed using a more complex multi-tracer analysis were also analyzed using the tritium-based age classification system, and there was a close match between the two methods. The results from these various studies suggest that the tritium-based age classification system may be informative as a screening tool prior to selecting more expensive and complex age-dating tracers and methods, or to provide an explanatory variable for other water-quality data where more complex methods or tracers are not available.</p><p>This work improves on previous groundwater age classification using <sup>3</sup>H by developing methods that (1) determine&nbsp;<sup>3</sup>H thresholds for groundwater recharged in 1953 or later that minimize the misclassification of modern samples as mixed; (2) determine a pre-1953 threshold to estimate premodern background concentrations; and (3) add a mixed category to classify samples that are clearly neither entirely modern nor entirely premodern. As with any tritium-based approach, it can fail when the <sup>3</sup>H record in precipitation does not accurately reflect the record of <sup>3</sup>H in recharge</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20195090","usgsCitation":"Lindsey, B.D., Jurgens, B.C., and Belitz, K., 2019, Tritium as an indicator of modern, mixed, and premodern groundwater age: U.S. Geological Survey Scientific Investigations Report 2019–5090, 18 p., https://doi.org/10.3133/sir20195090.","productDescription":"vii, 18 p.","onlineOnly":"Y","ipdsId":"IP-097386","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":437353,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DU94RV","text":"USGS data release","linkHelpText":"Data for Tritium as an Indicator of Modern, Mixed and Premodern Groundwater Age"},{"id":367188,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5090/coverthb.jpg"},{"id":367189,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5090/sir20195090.pdf","text":"Report","size":"6.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5090"}],"country":"United States","otherGeospatial":"Conterminous United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n   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             -102.48,\n                29.76\n              ],\n              [\n                -103.11,\n                28.97\n              ],\n              [\n                -103.94,\n                29.27\n              ],\n              [\n                -104.45697,\n                29.57196\n              ],\n              [\n                -104.70575,\n                30.12173\n              ],\n              [\n                -105.03737,\n                30.64402\n              ],\n              [\n                -105.63159,\n                31.08383\n              ],\n              [\n                -106.1429,\n                31.39995\n              ],\n              [\n                -106.50759,\n                31.75452\n              ],\n              [\n                -108.24,\n                31.75485\n              ],\n              [\n                -108.24194,\n                31.34222\n              ],\n              [\n                -109.035,\n                31.34194\n              ],\n              [\n                -111.02361,\n                31.33472\n              ],\n              [\n                -113.30498,\n                32.03914\n              ],\n              [\n                -114.815,\n                32.52528\n              ],\n              [\n                -114.72139,\n                32.72083\n              ],\n              [\n                -115.99135,\n                32.61239\n              ],\n              [\n                -117.12776,\n                32.53534\n              ],\n              [\n                -117.29594,\n                33.04622\n              ],\n              [\n                -117.944,\n                33.62124\n              ],\n              [\n                -118.4106,\n                33.74091\n              ],\n              [\n                -118.51989,\n                34.02778\n              ],\n              [\n                -119.081,\n                34.078\n              ],\n              [\n                -119.43884,\n                34.34848\n              ],\n              [\n                -120.36778,\n                34.44711\n              ],\n              [\n                -120.62286,\n                34.60855\n              ],\n              [\n                -120.74433,\n                35.15686\n              ],\n              [\n                -121.71457,\n                36.16153\n              ],\n              [\n                -122.54747,\n                37.55176\n              ],\n              [\n                -122.51201,\n                37.78339\n              ],\n              [\n                -122.95319,\n                38.11371\n              ],\n              [\n                -123.7272,\n                38.95166\n              ],\n              [\n                -123.86517,\n                39.76699\n              ],\n              [\n                -124.39807,\n                40.3132\n              ],\n              [\n                -124.17886,\n                41.14202\n              ],\n              [\n                -124.2137,\n                41.99964\n              ],\n              [\n                -124.53284,\n                42.76599\n              ],\n              [\n                -124.14214,\n                43.70838\n              ],\n              [\n                -124.02053,\n                44.6159\n              ],\n              [\n                -123.89893,\n                45.52341\n              ],\n              [\n                -124.07963,\n                46.86475\n              ],\n              [\n                -124.39567,\n                47.72017\n              ],\n              [\n                -124.68721,\n                48.18443\n              ],\n              [\n                -124.5661,\n                48.37971\n              ],\n              [\n                -123.12,\n                48.04\n              ],\n              [\n                -122.58736,\n                47.096\n              ],\n              [\n                -122.34,\n                47.36\n              ],\n              [\n                -122.5,\n                48.18\n              ],\n              [\n                -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                49\n              ],\n              [\n                -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","contact":"<p>Chief Scientist, <a href=\"https://water.usgs.gov/nawqa/\" data-mce-href=\"https://water.usgs.gov/nawqa/\">NAWQA</a><br>U.S. Geological Survey<br>2201 Sunrise Valley Drive, MS 413<br>Reston, VA 20192-0002</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results and Discussion</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2019-09-04","noUsgsAuthors":false,"publicationDate":"2019-09-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":175346,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce","email":"blindsey@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":768999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":127842,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","email":"bjurgens@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770172,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":769001,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70205247,"text":"70205247 - 2019 - Modeling spatially and temporally complex range dynamics when detection is imperfect","interactions":[],"lastModifiedDate":"2023-04-04T13:09:47.297173","indexId":"70205247","displayToPublicDate":"2019-09-05T09:48:15","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Modeling spatially and temporally complex range dynamics when detection is imperfect","docAbstract":"<p><span>Species distributions are determined by the interaction of multiple biotic and abiotic factors, which produces complex spatial and temporal patterns of occurrence. As habitats and climate change due to anthropogenic activities, there is a need to develop species distribution models that can quantify these complex range dynamics. In this paper, we develop a dynamic occupancy model that uses a spatial generalized additive model to estimate non-linear spatial variation in occupancy not accounted for by environmental covariates. The model is flexible and can accommodate data from a range of sampling designs that provide information about both occupancy and detection probability. Output from the model can be used to create distribution maps and to estimate indices of temporal range dynamics. We demonstrate the utility of this approach by modeling long-term range dynamics of 10 eastern North American birds using data from the North American Breeding Bird Survey. We anticipate this framework will be particularly useful for modeling species’ distributions over large spatial scales and for quantifying range dynamics over long temporal scales.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41598-019-48851-5","usgsCitation":"Rushing, C.S., Royle, J.A., Ziolkowski, D., and Pardieck, K.L., 2019, Modeling spatially and temporally complex range dynamics when detection is imperfect: Scientific Reports, v. 9, 12805, 9 p., https://doi.org/10.1038/s41598-019-48851-5.","productDescription":"12805, 9 p.","ipdsId":"IP-098777","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":459911,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-019-48851-5","text":"Publisher Index Page"},{"id":367307,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Rushing, Clark S. 0000-0002-9283-6563","orcid":"https://orcid.org/0000-0002-9283-6563","contributorId":218851,"corporation":false,"usgs":true,"family":"Rushing","given":"Clark","email":"","middleInitial":"S.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":true,"id":770529,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":770530,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ziolkowski, David 0000-0002-2500-4417 dziolkowski@usgs.gov","orcid":"https://orcid.org/0000-0002-2500-4417","contributorId":195409,"corporation":false,"usgs":true,"family":"Ziolkowski","given":"David","email":"dziolkowski@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":770531,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pardieck, Keith L. 0000-0003-2779-4392 kpardieck@usgs.gov","orcid":"https://orcid.org/0000-0003-2779-4392","contributorId":4104,"corporation":false,"usgs":true,"family":"Pardieck","given":"Keith","email":"kpardieck@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":770532,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70204783,"text":"ofr20191091 - 2019 - Evaluation of groundwater-flow models for estimating drawdown from proposed groundwater development in Tule Desert, Nevada","interactions":[],"lastModifiedDate":"2019-09-17T18:18:38","indexId":"ofr20191091","displayToPublicDate":"2019-09-05T09:37:47","publicationYear":"2019","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":"2019-1091","displayTitle":"Evaluation of Groundwater-Flow Models for Estimating Drawdown from Proposed Groundwater Development in Tule Desert, Nevada","title":"Evaluation of groundwater-flow models for estimating drawdown from proposed groundwater development in Tule Desert, Nevada","docAbstract":"<p>At the request of the Bureau of Land Management (BLM), the U.S. Geological Survey (USGS) is releasing with this open-file report (OFR) a previously unpublished review and comparison of two numerical models for Tule Desert, Nevada. The original review was performed in spring 2013, and only minor editorial revisions were made in the current (2019) OFR for clarity and to reformat the original interagency correspondence to the USGS OFR template. No revisions have been made to the technical content of the original review for this OFR release. Report content presented in the purpose and scope statement, and all subsequent sections of the OFR, are original content submitted to BLM in May 2013. Model review and comparisons described in the following paragraphs are based on, in part, results of a long-term (more than 2 years) aquifer test mandated by Nevada State Engineer Order 1169. Additional information on Order 1169 and associated aquifer test results can be found at the State of Nevada Division of Water Resources website (State of Nevada, 2019).<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191091","collaboration":"By request of the Bureau of Land Management, Nevada State Office","usgsCitation":"Halford, K., 2019, Evaluation of groundwater-flow models for estimating drawdown from proposed groundwater development in Tule Desert, Nevada: U.S. Geological Survey Open-File Report 2019–1091, 21 p., https://doi.org/10.3133/ofr20191091.","productDescription":"vi, 21 p.","numberOfPages":"21","onlineOnly":"Y","ipdsId":"IP-108521","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":367140,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1091/coverthb.jpg"},{"id":367141,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1091/ofr20191091.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1091"}],"country":"United States","state":"Nevada","otherGeospatial":"Tule Desert","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.09963989257812,\n              36.43454191900892\n            ],\n            [\n              -114.05181884765625,\n              36.43454191900892\n            ],\n            [\n              -114.05181884765625,\n              37.27186719156333\n            ],\n            [\n              -115.09963989257812,\n              37.27186719156333\n            ],\n            [\n              -115.09963989257812,\n              36.43454191900892\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a data-mce-href=\"https://www.usgs.gov/centers/nv-water\" href=\"https://www.usgs.gov/centers/nv-water\" target=\"_blank\" rel=\"noopener\">Nevada Water Science Center</a><br><a data-mce-href=\"https://www.usgs.gov/\" href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\">U.S. Geological Survey</a><br>2730 N. Deer Run Road<br>Carson City, Nevada 95819</p>","tableOfContents":"<ul><li>Introduction</li><li>Purpose and Scope</li><li>Aquifer-Test Results and Transmissivity Distributions</li><li>Conceptual Model of Muddy River Springs and Responses to Pumping Well MX-5</li><li>Simulated Drawdowns in Tule Desert</li><li>References Cited</li><li>Appendix</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2019-09-05","noUsgsAuthors":false,"publicationDate":"2019-09-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Halford, Keith J. 0000-0002-7322-1846 khalford@usgs.gov","orcid":"https://orcid.org/0000-0002-7322-1846","contributorId":1374,"corporation":false,"usgs":true,"family":"Halford","given":"Keith","email":"khalford@usgs.gov","middleInitial":"J.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":768469,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70205793,"text":"70205793 - 2019 - Comparison of methods for modeling fractional cover using simulated satellite hyperspectral imager spectra","interactions":[],"lastModifiedDate":"2019-12-09T10:57:03","indexId":"70205793","displayToPublicDate":"2019-09-04T13:57:09","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Comparison of Methods for Modeling Fractional Cover using Simulated Satellite Hyperspectral Imager Spectra","title":"Comparison of methods for modeling fractional cover using simulated satellite hyperspectral imager spectra","docAbstract":"Remotely sensed data can be used to model the fractional cover of green vegetation (GV), non-photosynthetic vegetation (NPV), and soil in natural and agricultural ecosystems. NPV and soil cover are difficult to estimate accurately since absorption by lignin, cellulose, and other organic molecules cannot be resolved by broadband multispectral data. A new generation of satellite hyperspectral imagers will provide contiguous narrowband coverage, enabling new, more accurate, and potentially global fractional cover products. We used six field spectroscopy datasets collected in prior experiments from sites with partial crop, grass, shrub, and low-stature resprouting tree cover to simulate satellite hyperspectral data, including sensor noise and atmospheric correction artifacts. The combined dataset was used to compare hyperspectral index-based and spectroscopic methods for estimating GV, NPV, and soil fractional cover. GV fractional cover was estimated most accurately. NPV and soil fractions were more difficult to estimate, with spectroscopic methods like partial least squares (PLS) regression, spectral feature analysis (SFA), and multiple endmember spectral mixture analysis (MESMA) typically outperforming hyperspectral indices. Using an independent validation dataset, the lowest root mean squared error (RMSE) values were 0.115 for GV using either normalized difference vegetation index (NDVI) or SFA, 0.164 for NPV using PLS, and 0.126 for soil using PLS. PLS also had the lowest RMSE averaged across all three cover types. This work highlights the need for more extensive and diverse fine spatial scale measurements of fractional cover, to improve methodologies for estimating cover in preparation for future hyperspectral global monitoring missions.","language":"English","publisher":"MDPI","doi":"10.3390/rs11182072","usgsCitation":"Dennison, P.E., Qi, Y., Meerdink, S.K., Kokaly, R.F., Thompson, D., Daughtry, C.S., Quemada, M., Roberts, D.A., Gader, P., Wetherley, E., Numata, I., and Roth, K.L., 2019, Comparison of methods for modeling fractional cover using simulated satellite hyperspectral imager spectra: Remote Sensing, v. 11, no. 18, 2072, 23 p., https://doi.org/10.3390/rs11182072.","productDescription":"2072, 23 p.","ipdsId":"IP-102364","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459915,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs11182072","text":"Publisher Index Page"},{"id":367977,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"18","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Dennison, Philip E.","contributorId":105132,"corporation":false,"usgs":true,"family":"Dennison","given":"Philip","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":772400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qi, Yi","contributorId":219504,"corporation":false,"usgs":false,"family":"Qi","given":"Yi","email":"","affiliations":[],"preferred":false,"id":772401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meerdink, Susan K.","contributorId":219505,"corporation":false,"usgs":false,"family":"Meerdink","given":"Susan","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":772402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":205165,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"","middleInitial":"F.","affiliations":[{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":772403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, David R.","contributorId":152638,"corporation":false,"usgs":false,"family":"Thompson","given":"David R.","affiliations":[{"id":18954,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA","active":true,"usgs":false}],"preferred":false,"id":772404,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Daughtry, Craig S.T.","contributorId":214079,"corporation":false,"usgs":false,"family":"Daughtry","given":"Craig","email":"","middleInitial":"S.T.","affiliations":[{"id":38179,"text":"USDA Agricultural Research Service, Hydrology and Remote Sensing Laboratory","active":true,"usgs":false}],"preferred":false,"id":772405,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Quemada, Miguel","contributorId":211094,"corporation":false,"usgs":false,"family":"Quemada","given":"Miguel","email":"","affiliations":[{"id":38180,"text":"School of Agricultural Engineering and CEIGRAM, Technical University of Madrid","active":true,"usgs":false}],"preferred":false,"id":772406,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Roberts, Dar A.","contributorId":100503,"corporation":false,"usgs":false,"family":"Roberts","given":"Dar","email":"","middleInitial":"A.","affiliations":[{"id":12804,"text":"Univ. of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":772407,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gader, Paul","contributorId":219506,"corporation":false,"usgs":false,"family":"Gader","given":"Paul","email":"","affiliations":[],"preferred":false,"id":772408,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wetherley, Erin","contributorId":219507,"corporation":false,"usgs":false,"family":"Wetherley","given":"Erin","email":"","affiliations":[],"preferred":false,"id":772409,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Numata, Izaya","contributorId":219508,"corporation":false,"usgs":false,"family":"Numata","given":"Izaya","email":"","affiliations":[],"preferred":false,"id":772410,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Roth, Keely L.","contributorId":187593,"corporation":false,"usgs":false,"family":"Roth","given":"Keely","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":772411,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70205513,"text":"70205513 - 2019 - Adult survival of common eiders in Maine","interactions":[],"lastModifiedDate":"2019-09-20T11:08:51","indexId":"70205513","displayToPublicDate":"2019-09-04T11:05:48","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2898,"text":"Northeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Adult survival of common eiders in Maine","docAbstract":"<p><span>Although most species of sea ducks are poorly studied, much is known about the population dynamics of the American race of&nbsp;</span><i>Somateria mollissma dresseri</i><span>&nbsp;(Common Eider). Although Common Eiders typically have high adult survival and low recruitment rates, their populations in Maine have declined since the early 1990s. Wildlife managers hypothesized this decline was due to reduced adult survival; therefore, they decreased daily bag limits in Maine in 1999 and 2009 to increase local populations. The goals of this project were to assess (a) whether survival rates of adult females captured while nesting varied between historical estimates (1943–1993) and recent estimates (2000–2012), (b) whether survival rates increased from 2000–2009 after the initial harvest restrictions were implemented in 1999, and (c) determine if estimates of survival rates of adult males and females captured while molting differed from estimates of adult females captured while nesting. We used mark–recapture models to estimate survival rates of Common Eiders we banded in Maine (nesting females [</span><i>n</i><span>&nbsp;= 2340] from 2000 to 2012; molting males [&nbsp;</span><i>n</i><span>&nbsp;= 4366] and molting females [</span><i>n</i><span>&nbsp;= 4952] from 2000 to 2009). We found no difference in survival of nesting females based on historical (mean ± SE = 0.9003 ± 0.0841) and recent estimates (0.90 ± 0.015). Although we observed annual fluctuations in survival, survival rates did not increase following the implementation of harvest restrictions. Mean annual survival rates were similarly high for molting females (0.894 ± 0.0205) and nesting females, but lower for molting males (0.855 ± 0.0128). Lower survival rates of adult males may reflect the preference by US hunters to selectively harvest adult males. Overall mean recovery rates of banded birds were low (females: 0.037 ± 0.00043, males: 0.0226 ± 0.0006). We hypothesize that current harvest rates may be influencing decreased survival of adult males to some extent.</span></p>","language":"English","publisher":"BioOne","doi":"10.1656/045.026.0320","usgsCitation":"Allen, R.B., McAuley, D., and Zimmerman, G., 2019, Adult survival of common eiders in Maine: Northeastern Naturalist, v. 26, no. 3, p. 656-671, https://doi.org/10.1656/045.026.0320.","productDescription":"6 p.","startPage":"656","endPage":"671","ipdsId":"IP-090678","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":367601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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 \"}}]}","volume":"26","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, R. B.","contributorId":219165,"corporation":false,"usgs":false,"family":"Allen","given":"R.","email":"","middleInitial":"B.","affiliations":[{"id":39965,"text":"Maine Department of Inland Fisheries and Wildlife","active":true,"usgs":false}],"preferred":false,"id":771466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAuley, Daniel 0000-0003-3674-6392 dmcauley@usgs.gov","orcid":"https://orcid.org/0000-0003-3674-6392","contributorId":215182,"corporation":false,"usgs":true,"family":"McAuley","given":"Daniel","email":"dmcauley@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":771465,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zimmerman, G.","contributorId":219166,"corporation":false,"usgs":false,"family":"Zimmerman","given":"G.","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":771467,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70207459,"text":"70207459 - 2019 - Benthic algal (Periphyton) growth rates in response to nitrogen and phosphorus: Parameter estimation for water quality models","interactions":[],"lastModifiedDate":"2019-12-19T16:50:18","indexId":"70207459","displayToPublicDate":"2019-09-03T16:46:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Benthic algal (Periphyton) growth rates in response to nitrogen and phosphorus: Parameter estimation for water quality models","docAbstract":"Nitrogen (N) and phosphorus (P) are important pollutants that can stimulate nuisance blooms of algae. Water-quality models (e.g., WASP, CE-QUAL-R1, CE-QUAL-ICM, QUAL2k) are valuable and widely used management tools for algal accrual because of excess nutrients in the presence of other limiting factors. These models utilize the Monod and Droop equations to associate algal growth rate with dissolved nutrient concentration and intra-cellular nutrient concentration. Having accurate parameter values is essential to model performance; however, published values for model parameterization are limited, particularly for benthic (periphyton) algae. We conducted a 10-day mesocosm experiment and measured diatom-dominated periphyton biomass accrual through time as chlorophyll a (chl a) and ash-free dry mass (AFDM) in response to additions of N (range 5-12,390 µg NO3-N/L) and P (range 0.89-59.51 µg SRP/L). Resulting half saturation coefficients and growth rates are similar to other published values, but minimum intra-cellular nutrient concentration (quota, Qmin) are higher than those previously reported. Saturation concentration for N ranged from 150 to 2450 µg NO3-N/L based on chl a and from 8.5 to 60 µg NO3-N/L when based on AFDM. Similarly, the saturation concentration for P ranged from 12 to 29 µg-P/L based on chl a, and from 2.5 to 6.1 µg-P/L based on AFDM. These saturation concentrations provide an upper limit for streams where diatom growth can be expected to respond to nutrient levels and a benchmark for reducing nutrient concentrations to a point where benthic algal growth will be limited.","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12797","usgsCitation":"Schmidt, T., Konrad, C., Miller, J.L., Whitlock, S.D., and Stricker, C.A., 2019, Benthic algal (Periphyton) growth rates in response to nitrogen and phosphorus: Parameter estimation for water quality models: Journal of the American Water Resources Association, v. 55, no. 6, p. 1479-1491, https://doi.org/10.1111/1752-1688.12797.","productDescription":"13 p.","startPage":"1479","endPage":"1491","ipdsId":"IP-102549","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":459923,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7029675","text":"External Repository"},{"id":370525,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Schmidt, Travis S. 0000-0003-1400-0637 tschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-1400-0637","contributorId":1300,"corporation":false,"usgs":true,"family":"Schmidt","given":"Travis S.","email":"tschmidt@usgs.gov","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":778127,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Konrad, Christopher 0000-0002-7354-547X","orcid":"https://orcid.org/0000-0002-7354-547X","contributorId":217886,"corporation":false,"usgs":true,"family":"Konrad","given":"Christopher","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":778128,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Janet L.","contributorId":218842,"corporation":false,"usgs":false,"family":"Miller","given":"Janet","email":"","middleInitial":"L.","affiliations":[{"id":39922,"text":"No affilcation","active":true,"usgs":false}],"preferred":false,"id":778129,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitlock, Stephen D.","contributorId":218841,"corporation":false,"usgs":false,"family":"Whitlock","given":"Stephen","email":"","middleInitial":"D.","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":778130,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":778131,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70204416,"text":"sir20195070 - 2019 - Stratigraphic analysis of Corte Madera Creek flood control channel deposits","interactions":[],"lastModifiedDate":"2019-09-03T16:51:36","indexId":"sir20195070","displayToPublicDate":"2019-09-03T14:15:55","publicationYear":"2019","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":"2019-5070","displayTitle":"Stratigraphic Analysis of Corte Madera Creek Flood Control Channel Deposits","title":"Stratigraphic analysis of Corte Madera Creek flood control channel deposits","docAbstract":"<p>Sedimentation in a channel can reduce flood conveyance capability and potentially place nearby property and life at risk from flooding. In 1998, Marin County Public Works dredged the concrete-lined segment of Corte Madera Creek, which drains a hilly and largely urbanized watershed that terminates in San Francisco Bay, California. From then through 2015, approximately 4,100 cubic meters of sand and gravel infilled the concrete-lined segment. Determining when and under what conditions this material was deposited informs dredging operations for the Corte Madera Creek Flood Control Project and increases understanding of sediment delivery timing and mechanisms from this and other San Francisco Bay tributaries.</p><p>Two hypothesized scenarios were investigated: (1) complete flushing during high flows and re-deposition of channel fill afterward and (2) more steady, gradual channel infilling. Stratigraphic analysis of eight sediment cores collected from the flood-control channel deposits in August 2017 was used to identify the most likely scenario. In addition, sediment elevation profiles, grain-size data, and a one-dimensional hydrodynamic model were used to assess the potential for longitudinal-channel scour and deposition following the wet winter of water year 2017 in the intertidal reach of the concrete channel in Corte Madera Creek.</p><p>Results indicated the channel is undergoing gradual infilling. Storm flows of water year 2017 did not completely scour the concrete channel fill. Sediment cores, stratigraphic analysis, and sediment elevation profiles indicated 0.23 meter of scour at the downstream end of the concrete-lined section and that roughly 0.5 meter of channel fill remained in the channel. The hydrodynamic model demonstrated that sediment deposition in the concrete channel is expected to start downstream from the point where the channel bed reaches mean lower low-water level. High flows can carry most of the sediment through this segment of channel, depositing the bed-material load downstream from the transition to a wide channel, where velocity and bed shear stress decrease abruptly.</p><p>Although the storm flows of 2017 did not completely scour the channel fill, subsequent material deposited in the channel could be transported downstream from the concrete channel if the sediment elevation profile is in equilibrium with present (2019) mean sea level. A calibrated, coupled hydrodynamic-sediment transport model could be used to test the present equilibrium between sediment elevation profiles and mean sea level, such that additional sediment build-up in the concrete channel is remobilized during subsequent wet-season flows and deposited downstream from the concrete-lined segment.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195070","collaboration":"Prepared in cooperation with Marin County Flood Control District","usgsCitation":"Livsey, D., Work, P., and Downing-Kunz, M., 2019, Stratigraphic analysis of Corte Madera Creek flood control channel deposits: U.S. Geological Survey Scientific Investigation Report 2019–5070, 28 p., https://doi.org/10.3133/sir20195070.","productDescription":"vi, 28 p.","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-102889","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":367137,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5070/sir20195070.pdf","text":"Report","size":"7.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5070"},{"id":367136,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5070/coverthb.jpg"}],"country":"United States","state":"California","county":"Marin County","otherGeospatial":"Corte Madera Creek","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.55360603332518,\n              37.95983152006781\n            ],\n            [\n              -122.55401372909544,\n              37.95940856550367\n            ],\n            [\n              -122.55317687988281,\n              37.95847805688854\n            ],\n            [\n              -122.55341291427611,\n              37.957395268386534\n            ],\n            [\n              -122.5513744354248,\n              37.95446827582245\n            ],\n            [\n              -122.54940032958984,\n              37.95382533697663\n            ],\n            [\n              -122.54691123962402,\n              37.95343618704664\n            ],\n            [\n              -122.54618167877197,\n              37.95331774970222\n            ],\n            [\n              -122.54616022109984,\n              37.95120276497281\n            ],\n            [\n              -122.54598855972289,\n              37.95069515957716\n            ],\n            [\n              -122.54487276077272,\n              37.95086436176544\n            ],\n            [\n              -122.54515171051024,\n              37.95292859708327\n            ],\n            [\n              -122.5455379486084,\n              37.9540960487555\n            ],\n            [\n              -122.54740476608275,\n              37.95441751769712\n            ],\n            [\n              -122.55006551742552,\n              37.95548343096359\n            ],\n            [\n              -122.55236148834227,\n              37.957632129735394\n            ],\n            [\n              -122.55236148834227,\n              37.9587487515198\n            ],\n            [\n              -122.55360603332518,\n              37.95983152006781\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/ca-water/connect\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/ca-water/connect\">Director</a>,<br><a href=\"https://ca.water.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://ca.water.usgs.gov\">California Water Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>6000 J Street, Placer Hall<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Field Methods</li><li>Interpretation of Sediment Cores</li><li>Sediment Erosion and Deposition</li><li>One-Dimensional Simulation of Channel Flow and Bed Shear Stress</li><li>Conclusions</li><li>References Cited</li><li>Appendix</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2019-09-03","noUsgsAuthors":false,"publicationDate":"2019-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Livsey, Daniel N. 0000-0002-2028-6128 dlivsey@usgs.gov","orcid":"https://orcid.org/0000-0002-2028-6128","contributorId":181870,"corporation":false,"usgs":true,"family":"Livsey","given":"Daniel","email":"dlivsey@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766793,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Work, Paul A. 0000-0002-2815-8040 pwork@usgs.gov","orcid":"https://orcid.org/0000-0002-2815-8040","contributorId":168561,"corporation":false,"usgs":true,"family":"Work","given":"Paul","email":"pwork@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766792,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Downing-Kunz, Maureen A. 0000-0002-4879-0318 mdowning-kunz@usgs.gov","orcid":"https://orcid.org/0000-0002-4879-0318","contributorId":3690,"corporation":false,"usgs":true,"family":"Downing-Kunz","given":"Maureen","email":"mdowning-kunz@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766794,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70207028,"text":"70207028 - 2019 - Phosphorus and nitrogen transport in the binational Great Lakes Basin estimated using SPARROW watershed models","interactions":[],"lastModifiedDate":"2020-01-08T14:10:14","indexId":"70207028","displayToPublicDate":"2019-09-03T13:55:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Phosphorus and nitrogen transport in the binational Great Lakes Basin estimated using SPARROW watershed models","docAbstract":"<p><span>Eutrophication problems in the Great Lakes are caused by excessive nutrient inputs (primarily phosphorus, P, and nitrogen, N) from various sources throughout its basin. In developing protection and restoration plans, it is important to know where and from what sources the nutrients originate. As part of a binational effort, Midcontinent SPARROW (SPAtially Referenced Regression On Watershed attributes) models were developed and used to estimate P and N loading from throughout the entire basin based on nutrient inputs similar to 2002; previous SPARROW models only estimated U.S. contributions. The new models have a higher resolution (~2‐km</span><sup>2</sup><span>&nbsp;catchments) enabling improved descriptions of where nutrients originate and the sources at various spatial scales. The models were developed using harmonized geospatial datasets describing the stream network, nutrient sources, and environmental characteristics affecting P and N delivery. The models were calibrated using loads from sites estimated with ratio estimator and regression techniques and additional statistical approaches to reduce spatial correlation in the residuals and have all monitoring sites equally influence model development. SPARROW results, along with interlake transfers and direct atmospheric inputs, were used to quantify the entire P and N input to each lake and describe the importance of each nutrient source. Model results can be used to compare loading and yields from various tributaries and jurisdictions.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12792","usgsCitation":"Robertson, D.M., Saad, D., Benoy, G.A., Vouk, I., Schwarz, G.E., and Laitta, M.T., 2019, Phosphorus and nitrogen transport in the binational Great Lakes Basin estimated using SPARROW watershed models: Journal of the American Water Resources Association, v. 55, no. 6, p. 1401-1424, https://doi.org/10.1111/1752-1688.12792.","productDescription":"24 p.","startPage":"1401","endPage":"1424","ipdsId":"IP-099596","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":459925,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12792","text":"Publisher Index Page"},{"id":369886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -92.8125,\n              41.27780646738183\n            ],\n            [\n              -75.8056640625,\n              41.27780646738183\n            ],\n            [\n              -75.8056640625,\n              48.980216985374994\n            ],\n            [\n              -92.8125,\n              48.980216985374994\n            ],\n            [\n              -92.8125,\n              41.27780646738183\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"55","issue":"6","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Robertson, Dale M. 0000-0001-6799-0596","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":204668,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"","middleInitial":"M.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":776559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saad, David A. 0000-0001-6559-6181","orcid":"https://orcid.org/0000-0001-6559-6181","contributorId":217251,"corporation":false,"usgs":true,"family":"Saad","given":"David A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":776560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Benoy, Glenn A. 0000-0001-6530-7220","orcid":"https://orcid.org/0000-0001-6530-7220","contributorId":172405,"corporation":false,"usgs":false,"family":"Benoy","given":"Glenn","email":"","middleInitial":"A.","affiliations":[{"id":13361,"text":"International Joint Commission, Washington DC","active":true,"usgs":false}],"preferred":false,"id":776561,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vouk, Ivana 0000-0002-9134-6933","orcid":"https://orcid.org/0000-0002-9134-6933","contributorId":211795,"corporation":false,"usgs":false,"family":"Vouk","given":"Ivana","email":"","affiliations":[{"id":38321,"text":"National Research Council Canada","active":true,"usgs":false}],"preferred":false,"id":776562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":213621,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory","email":"gschwarz@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":776563,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Laitta, Michael T","contributorId":221001,"corporation":false,"usgs":false,"family":"Laitta","given":"Michael","email":"","middleInitial":"T","affiliations":[{"id":40305,"text":"International Joint Commission, U.S. Section","active":true,"usgs":false}],"preferred":false,"id":776564,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70205186,"text":"70205186 - 2019 - Floodplains provide important amphibian habitat despite multiple ecological threats","interactions":[],"lastModifiedDate":"2019-09-06T09:41:14","indexId":"70205186","displayToPublicDate":"2019-09-03T09:35:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Floodplains provide important amphibian habitat despite multiple ecological threats","docAbstract":"<p><span>Floodplain ponds and wetlands are productive and biodiverse ecosystems, yet they face multiple threats including altered hydrology, land use change, and non‐native species. Protecting and restoring important floodplain ecosystems requires understanding how organisms use these habitats and respond to altered environmental conditions. We developed Bayesian models to evaluate occupancy of six amphibian species across 103 off‐channel aquatic habitats in the Chehalis River floodplain, Washington State, USA. The basin has been altered by changes in land use, reduced river–wetland connections, and the establishment of non‐native American bullfrogs (</span><i>Rana catesbeiana</i><span>&nbsp;=&nbsp;</span><i>Lithobates catesbeianus</i><span>) and centrarchid fishes, all of which we hypothesized could influence native amphibian occupancy. Despite potential threats, the floodplain habitats had relatively high rates of native amphibian occupancy, particularly when compared to studies from non‐floodplain habitats within the species’ native ranges. The biggest challenge for native amphibians appears to be non‐native centrarchid fishes, which strongly reduced occupancy of two native amphibians: the northern red‐legged frog (</span><i>Rana aurora</i><span>) and the northwestern salamander (</span><i>Ambystoma gracile</i><span>). Emergent vegetative cover increased occupancy probability for all five native amphibian species, indicating that plant management may offer a strategy to counter the negative effect of centrarchids by providing refuge from predation. We found that temporary and permanent hydroperiod sites supported different species; hence, both should be conserved on the landscape. Lastly, human‐created and natural ponds had similar amphibian occupancy patterns, suggesting that pond construction offers a viable strategy for adding habitats to the floodplain landscape. Overall, floodplain ponds and wetlands provide important amphibian habitat, and we offer management strategies that will bolster amphibian occupancy in an altered floodplain landscape.</span></p>","language":"English","publisher":"ESA","doi":"10.1002/ecs2.2853","usgsCitation":"Holgerson, M., Duarte, A., Hayes, M., Adams, M.J., Tyson, J.A., Douville, K., and Strecker, A., 2019, Floodplains provide important amphibian habitat despite multiple ecological threats: Ecosphere, v. 10, no. 9, e02853, 18 p., https://doi.org/10.1002/ecs2.2853.","productDescription":"e02853, 18 p.","ipdsId":"IP-106837","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":459938,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2853","text":"Publisher Index Page"},{"id":367248,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Chehalis River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.17297363281251,\n              47.09069560264967\n            ],\n            [\n              -124.17297363281251,\n              46.9465122958623\n            ],\n            [\n              -124.07958984375001,\n              46.77184961467733\n            ],\n            [\n              -123.33251953125,\n              46.77749276376827\n            ],\n            [\n              -123.43414306640625,\n              46.60982785835103\n            ],\n            [\n              -122.9754638671875,\n              46.219752144776876\n            ],\n            [\n              -122.25585937500001,\n              46.543749602738565\n            ],\n            [\n              -123.5687255859375,\n              47.344406158662125\n            ],\n            [\n              -124.17297363281251,\n              47.09069560264967\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"9","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Holgerson, Meredith","contributorId":218790,"corporation":false,"usgs":false,"family":"Holgerson","given":"Meredith","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":770278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duarte, Adam","contributorId":28492,"corporation":false,"usgs":false,"family":"Duarte","given":"Adam","affiliations":[{"id":6960,"text":"Department of Biology, Texas State University","active":true,"usgs":false}],"preferred":false,"id":770279,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Marc","contributorId":218791,"corporation":false,"usgs":false,"family":"Hayes","given":"Marc","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":770280,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Michael J. 0000-0001-8844-042X","orcid":"https://orcid.org/0000-0001-8844-042X","contributorId":211916,"corporation":false,"usgs":true,"family":"Adams","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":770282,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tyson, Julie A.","contributorId":218792,"corporation":false,"usgs":false,"family":"Tyson","given":"Julie","email":"","middleInitial":"A.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":770281,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Douville, Keith","contributorId":218793,"corporation":false,"usgs":false,"family":"Douville","given":"Keith","email":"","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":770283,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Strecker, Angela","contributorId":218794,"corporation":false,"usgs":false,"family":"Strecker","given":"Angela","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":770284,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70205841,"text":"70205841 - 2019 - Evaluating the factors responsible for post-fire water quality response in forests of the western USA","interactions":[],"lastModifiedDate":"2019-10-28T10:32:13","indexId":"70205841","displayToPublicDate":"2019-09-03T07:34:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the factors responsible for post-fire water quality response in forests of the western USA","docAbstract":"Wildfires commonly increase nutrient, carbon, sediment, and metal inputs to streams yet the factors responsible for the type, magnitude and duration of water quality effects are poorly understood. Prior work by the current authors found increased nitrogen, phosphorus and cation exports were common the first five post-fire years from a synthesis of 159 wildfires across the western United States. In the current study, an analysis is undertaken to determine factors that best explain post-fire streamwater responses observed in those watersheds. Increased post-fire total nitrogen and phosphorus loading were proportional to the catchment extent of moderate and high burn severity. Post-fire dissolved metal concentrations increased in catchments with < 2% pre-fire soil organic matter. In contrast, in catchments with > 2% soil organic matter, post-fire dissolved metal concentrations decreased compared to pre-fire conditions. Where post-fire normalized difference vegetation index (NDVI), a remote sensing indicator of live green vegetation, was low, total metal concentrations increased by 25% on average and by > 100% in some cases.  When pre-fire soil field capacity exceeded 17%, there was a 750% median increase in total metals export to streams. Overall, the current analysis identified burn severity, post-fire vegetation cover, and several soil properties as the key variables explaining extended post-fire water quality response across a broad range of conditions found in the western US.","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WF18191","usgsCitation":"Rust, A.J., Saxe, S., McCray, J.E., Rhoades, C.C., and Hogue, T.S., 2019, Evaluating the factors responsible for post-fire water quality response in forests of the western USA: International Journal of Wildland Fire, v. 28, no. 10, p. 769-784, https://doi.org/10.1071/WF18191.","productDescription":"16 p.","startPage":"769","endPage":"784","ipdsId":"IP-109789","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":368081,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, Wyoming","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-104.053249,41.001406],[-102.124972,41.002338],[-102.051292,40.749591],[-102.04192,37.035083],[-102.979613,36.998549],[-103.002247,36.911587],[-103.064423,32.000518],[-106.565142,32.000736],[-106.577244,31.810406],[-106.750547,31.783706],[-108.208394,31.783599],[-108.208573,31.333395],[-111.000643,31.332177],[-114.813613,32.494277],[-114.722746,32.713071],[-117.118868,32.534706],[-117.50565,33.334063],[-118.088896,33.729817],[-118.428407,33.774715],[-118.519514,34.027509],[-119.159554,34.119653],[-119.616862,34.420995],[-120.441975,34.451512],[-120.608355,34.556656],[-120.644311,35.139616],[-120.873046,35.225688],[-120.884757,35.430196],[-121.851967,36.277831],[-121.932508,36.559935],[-121.788278,36.803994],[-121.880167,36.950151],[-122.140578,36.97495],[-122.419113,37.24147],[-122.511983,37.77113],[-122.425942,37.810979],[-122.168449,37.504143],[-122.144396,37.581866],[-122.385908,37.908136],[-122.301804,38.105142],[-122.484411,38.11496],[-122.492474,37.82484],[-122.972378,38.020247],[-123.103706,38.415541],[-123.725367,38.917438],[-123.851714,39.832041],[-124.373599,40.392923],[-124.063076,41.439579],[-124.536073,42.814175],[-124.150267,43.91085],[-123.962887,45.280218],[-123.996766,46.20399],[-123.548194,46.248245],[-124.029924,46.308312],[-124.06842,46.601397],[-123.97083,46.47537],[-123.84621,46.716795],[-124.022413,46.708973],[-124.108078,46.836388],[-123.86018,46.948556],[-124.138035,46.970959],[-124.425195,47.738434],[-124.672427,47.964414],[-124.727022,48.371101],[-123.981032,48.164761],[-122.748911,48.117026],[-122.637425,47.889945],[-123.15598,47.355745],[-122.527593,47.905882],[-122.578211,47.254804],[-122.725738,47.33047],[-122.691771,47.141958],[-122.796646,47.341654],[-122.863732,47.270221],[-122.67813,47.103866],[-122.364168,47.335953],[-122.429841,47.658919],[-122.230046,47.970917],[-122.425572,48.232887],[-122.358375,48.056133],[-122.512031,48.133931],[-122.424102,48.334346],[-122.689121,48.476849],[-122.425271,48.599522],[-122.796887,48.975026],[-104.048736,48.999877],[-104.053249,41.001406]]],[[[-119.789798,34.05726],[-119.5667,34.053452],[-119.795938,33.962929],[-119.916216,34.058351],[-119.789798,34.05726]]],[[[-118.524531,32.895488],[-118.573522,32.969183],[-118.369984,32.839273],[-118.524531,32.895488]]],[[[-118.500212,33.449592],[-118.32446,33.348782],[-118.593969,33.467198],[-118.500212,33.449592]]],[[[-122.519535,48.288314],[-122.66921,48.240614],[-122.400628,48.036563],[-122.419274,47.912125],[-122.744612,48.20965],[-122.664928,48.374823],[-122.519535,48.288314]]],[[[-122.800217,48.60169],[-122.883759,48.418793],[-123.173061,48.579086],[-122.949116,48.693398],[-122.743049,48.661991],[-122.800217,48.60169]]]]},\"properties\":{\"name\":\"Arizona\",\"nation\":\"USA  \"}}]}","volume":"28","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rust, Ashley J.","contributorId":219575,"corporation":false,"usgs":false,"family":"Rust","given":"Ashley","email":"","middleInitial":"J.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":772578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saxe, Samuel","contributorId":219574,"corporation":false,"usgs":true,"family":"Saxe","given":"Samuel","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":772577,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCray, John E.","contributorId":169186,"corporation":false,"usgs":false,"family":"McCray","given":"John","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":772579,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rhoades, Charles C.","contributorId":219576,"corporation":false,"usgs":false,"family":"Rhoades","given":"Charles","email":"","middleInitial":"C.","affiliations":[{"id":40027,"text":"United States Forest Service","active":true,"usgs":false}],"preferred":false,"id":772580,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hogue, Terri S.","contributorId":205175,"corporation":false,"usgs":false,"family":"Hogue","given":"Terri","email":"","middleInitial":"S.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":772581,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70206689,"text":"70206689 - 2019 - PaCTS 1.0: A crowdsourced reporting standard for paleoclimate data","interactions":[],"lastModifiedDate":"2019-12-03T10:05:49","indexId":"70206689","displayToPublicDate":"2019-09-03T06:36:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5790,"text":"Paleoceanography and Paleoclimatology","active":true,"publicationSubtype":{"id":10}},"title":"PaCTS 1.0: A crowdsourced reporting standard for paleoclimate data","docAbstract":"The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on that data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the re-use value of paleoclimate datasets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, this standard elicitation process involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new vs. legacy datasets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate datasets. Since such goals are at odds with present practices, we discuss a transparent path towards implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches.","language":"English","publisher":"Wiley","doi":"10.1029/2019PA003632","usgsCitation":"Kehrwald, N.M., Khider, D., Emile-Geay, J., McKay, N., Gili, Y., Garijo, D., Ratnakar, V., Brewer, P., Csank, A., Dassie, E., Delong, K., Felix, T., Gray, W., Jonkers, L., Kahle, M., Kaufman, D.S., Richey, J.N., Schmittner, A., Sutherland, E.K., Alonso-Garcia, M., Sebastian, B., Bothe, O., Bunn, A., Chevalier, M., Francus, P., Frappier, A., Goring, S., Martrat, B., McGregor, H.V., Allen, K.J., Arnaud, F., Axford, Y.L., Barrows, T.T., Bazin, L., Birch, P., Bradley, E., Bregy, J., Capron, E., Cartapanis, O., Chiang, H., Cobb, K., Debret, M., Dommain, R., Du, J., Dyez, K., Emerick, S., Erb, M., Falster, G., Finsinger, W., Fortier, D., Gauthier, N., George, S., Grimm, E., Hertzberg, J., Hibbert, F., Hillman, A., Hobbs, W., Huber, M., Hughes, A.L., Jaccard, S., Jiaoyang, R., Kienast, M., Konecky, B., Le Roux, G., Lyubchich, V., Novello, V., Olaka, L., Partin, J.W., Pearce, C., Phipps, S.J., Pignol, C., Pietrowska, N., Poli, M., Prokopenko, A., Schwanck, F., Stepanek, C., Swann, G.E., Telford, R., Thomas, E.R., Thomas, Z., Truebe, S., von Gunten, L., Waite, A., Weitzel, N., Wilhelm, B., Williams, J.B., Winstrup, M., Zhao, N., and Zhou, Y., 2019, PaCTS 1.0: A crowdsourced reporting standard for paleoclimate data: Paleoceanography and Paleoclimatology, v. 34, no. 10, p. 1570-1596, https://doi.org/10.1029/2019PA003632.","productDescription":"27 p.","startPage":"1570","endPage":"1596","ipdsId":"IP-108314","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":459946,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019pa003632","text":"Publisher Index 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Blac, CNRS, Chambery, France","active":true,"usgs":false}],"preferred":false,"id":775447,"contributorType":{"id":1,"text":"Authors"},"rank":71},{"text":"Pietrowska, Natalia","contributorId":220687,"corporation":false,"usgs":false,"family":"Pietrowska","given":"Natalia","email":"","affiliations":[{"id":40237,"text":"Institute of Physics-CSE, Silesian University of Technology, Gliwice, Poland","active":true,"usgs":false}],"preferred":false,"id":775448,"contributorType":{"id":1,"text":"Authors"},"rank":72},{"text":"Poli, Maria-Serena","contributorId":220688,"corporation":false,"usgs":false,"family":"Poli","given":"Maria-Serena","email":"","affiliations":[{"id":40238,"text":"Department of Geography and Geology, Eastern Michigan University, Ypsilanti, Michigan, USA","active":true,"usgs":false}],"preferred":false,"id":775449,"contributorType":{"id":1,"text":"Authors"},"rank":73},{"text":"Prokopenko, Alexander","contributorId":220689,"corporation":false,"usgs":false,"family":"Prokopenko","given":"Alexander","email":"","affiliations":[{"id":37804,"text":"University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":775450,"contributorType":{"id":1,"text":"Authors"},"rank":74},{"text":"Schwanck, Franciele","contributorId":220690,"corporation":false,"usgs":false,"family":"Schwanck","given":"Franciele","email":"","affiliations":[{"id":40239,"text":"Centro Polar e Climatico, UFRGS, Rio Grande do Sul, Brazil","active":true,"usgs":false}],"preferred":false,"id":775451,"contributorType":{"id":1,"text":"Authors"},"rank":75},{"text":"Stepanek, Christian","contributorId":220691,"corporation":false,"usgs":false,"family":"Stepanek","given":"Christian","email":"","affiliations":[{"id":40240,"text":"Alfred Wegener Institute-Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany","active":true,"usgs":false}],"preferred":false,"id":775452,"contributorType":{"id":1,"text":"Authors"},"rank":76},{"text":"Swann, George E. A.","contributorId":194606,"corporation":false,"usgs":false,"family":"Swann","given":"George","email":"","middleInitial":"E. A.","affiliations":[],"preferred":false,"id":775453,"contributorType":{"id":1,"text":"Authors"},"rank":77},{"text":"Telford, Richard","contributorId":220692,"corporation":false,"usgs":false,"family":"Telford","given":"Richard","email":"","affiliations":[{"id":40241,"text":"Department of Biological Sciences, Bergen University, Bergen, Germany","active":true,"usgs":false}],"preferred":false,"id":775454,"contributorType":{"id":1,"text":"Authors"},"rank":78},{"text":"Thomas, Elizabeth R.","contributorId":202635,"corporation":false,"usgs":false,"family":"Thomas","given":"Elizabeth","email":"","middleInitial":"R.","affiliations":[{"id":36505,"text":"British Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":775455,"contributorType":{"id":1,"text":"Authors"},"rank":79},{"text":"Thomas, Zoe","contributorId":220693,"corporation":false,"usgs":false,"family":"Thomas","given":"Zoe","email":"","affiliations":[{"id":40242,"text":"School of Biological, earth, and Environmental Science, UNSW, Sydney, Australia","active":true,"usgs":false}],"preferred":false,"id":775456,"contributorType":{"id":1,"text":"Authors"},"rank":80},{"text":"Truebe, Sarah","contributorId":220694,"corporation":false,"usgs":false,"family":"Truebe","given":"Sarah","email":"","affiliations":[{"id":40243,"text":"Arizona State Parks and Trails, Benson, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":775457,"contributorType":{"id":1,"text":"Authors"},"rank":81},{"text":"von Gunten, Lucien","contributorId":195003,"corporation":false,"usgs":false,"family":"von Gunten","given":"Lucien","email":"","affiliations":[],"preferred":false,"id":775458,"contributorType":{"id":1,"text":"Authors"},"rank":82},{"text":"Waite, Amanda","contributorId":220695,"corporation":false,"usgs":false,"family":"Waite","given":"Amanda","email":"","affiliations":[{"id":40244,"text":"ANGARI Foundation, West Palm Beach, Florida, USA","active":true,"usgs":false}],"preferred":false,"id":775459,"contributorType":{"id":1,"text":"Authors"},"rank":83},{"text":"Weitzel, Nils","contributorId":220696,"corporation":false,"usgs":false,"family":"Weitzel","given":"Nils","email":"","affiliations":[{"id":40245,"text":"Institute of Environmental Physics, Heidelberg University, Heidelberg, Germany","active":true,"usgs":false}],"preferred":false,"id":775460,"contributorType":{"id":1,"text":"Authors"},"rank":84},{"text":"Wilhelm, Bruno","contributorId":220697,"corporation":false,"usgs":false,"family":"Wilhelm","given":"Bruno","email":"","affiliations":[{"id":40246,"text":"Universite grenoble Alpes, CNRS, IRD, Grenoble, INP, IGE, Grenoble, France","active":true,"usgs":false}],"preferred":false,"id":775461,"contributorType":{"id":1,"text":"Authors"},"rank":85},{"text":"Williams, John B.","contributorId":173055,"corporation":false,"usgs":false,"family":"Williams","given":"John","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":775462,"contributorType":{"id":1,"text":"Authors"},"rank":86},{"text":"Winstrup, Mai","contributorId":140729,"corporation":false,"usgs":false,"family":"Winstrup","given":"Mai","email":"","affiliations":[],"preferred":false,"id":775463,"contributorType":{"id":1,"text":"Authors"},"rank":87},{"text":"Zhao, Ning","contributorId":220698,"corporation":false,"usgs":false,"family":"Zhao","given":"Ning","email":"","affiliations":[{"id":40247,"text":"Max Planck Institute for Chemistry, Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":775464,"contributorType":{"id":1,"text":"Authors"},"rank":88},{"text":"Zhou, Yuxin","contributorId":220699,"corporation":false,"usgs":false,"family":"Zhou","given":"Yuxin","email":"","affiliations":[{"id":40248,"text":"Lamont-Dohery Earth Observatory, Columbia University, Palisades, New York, USA","active":true,"usgs":false}],"preferred":false,"id":775465,"contributorType":{"id":1,"text":"Authors"},"rank":89}]}}
,{"id":70230061,"text":"70230061 - 2019 - Paleo calendar-effect adjustments in time-slice and transient climate-model simulations (PaleoCalAdjust v1.0): Impact and strategies for data analysis","interactions":[],"lastModifiedDate":"2022-03-28T11:25:22.892578","indexId":"70230061","displayToPublicDate":"2019-09-03T06:23:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1818,"text":"Geoscientific Model Development","active":true,"publicationSubtype":{"id":10}},"title":"Paleo calendar-effect adjustments in time-slice and transient climate-model simulations (PaleoCalAdjust v1.0): Impact and strategies for data analysis","docAbstract":"<p>The “paleo calendar effect” is a common expression for the impact that changes in the length of months or seasons over time, related to changes in the eccentricity of Earth's orbit and precession, have on the analysis or summarization of climate-model output. This effect can have significant implications for paleoclimate analyses. In particular, using a “fixed-length” definition of months (i.e., defined by a fixed number of days), as opposed to a “fixed-angular” definition (i.e., defined by a fixed number of degrees of the Earth's orbit), leads to comparisons of data from different positions along the Earth's orbit when comparing paleo with modern simulations. This effect can impart characteristic spatial patterns or signals in comparisons of time-slice simulations that otherwise might be interpreted in terms of specific paleoclimatic mechanisms, and we provide examples for 6, 97, 116, and 127 ka. The calendar effect is exacerbated in transient climate simulations in which, in addition to spatial or map-pattern effects, it can influence the apparent timing of extrema in individual time series and the characterization of phase relationships among series. We outline an approach for adjusting paleo simulations that have been summarized using a modern fixed-length definition of months and that can also be used for summarizing and comparing data archived as daily data. We describe the implementation of this approach in a set of Fortran 90 programs and modules (PaleoCalAdjust v1.0).</p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/gmd-12-3889-2019","usgsCitation":"Bartlein, P.J., and Shafer, S., 2019, Paleo calendar-effect adjustments in time-slice and transient climate-model simulations (PaleoCalAdjust v1.0): Impact and strategies for data analysis: Geoscientific Model Development, v. 12, p. 3889-3913, https://doi.org/10.5194/gmd-12-3889-2019.","productDescription":"25 p.","startPage":"3889","endPage":"3913","ipdsId":"IP-101124","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":459948,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-12-3889-2019","text":"Publisher Index Page"},{"id":397667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","noUsgsAuthors":false,"publicationDate":"2019-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Bartlein, Patrick J. 0000-0001-7657-5685","orcid":"https://orcid.org/0000-0001-7657-5685","contributorId":211587,"corporation":false,"usgs":false,"family":"Bartlein","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":33397,"text":"U of Oregon","active":true,"usgs":false}],"preferred":false,"id":838926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shafer, Sarah 0000-0003-3739-2637 sshafer@usgs.gov","orcid":"https://orcid.org/0000-0003-3739-2637","contributorId":149866,"corporation":false,"usgs":true,"family":"Shafer","given":"Sarah","email":"sshafer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":838927,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70215341,"text":"70215341 - 2019 - Updating estimates of low-streamflow statistics to account for possible trends","interactions":[],"lastModifiedDate":"2020-10-15T18:52:38.595974","indexId":"70215341","displayToPublicDate":"2019-09-02T13:46:08","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7162,"text":"Hydrologic Sciences Journal","active":true,"publicationSubtype":{"id":10}},"title":"Updating estimates of low-streamflow statistics to account for possible trends","docAbstract":"<div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>Accurate estimators of streamflow statistics are critical to the design, planning, and management of water resources. Given increasing evidence of trends in low-streamflow, new approaches to estimating low-streamflow statistics are needed. Here we investigate simple approaches to select a recent subset of the low-flow record to update the commonly used statistic of 7<i>Q</i>10, the annual minimum 7-day streamflow exceeded in 9 out of 10 years on average. Informed by low-streamflow records at 174 US Geological Survey streamgages, Monte Carlo simulation experiments evaluate competing approaches. We find that a strategy which estimates 7<i>Q</i>10 using the most recent 30 years of record when a trend is detected, reduces error and bias in 7<i>Q</i>10 estimators compared to use of the full record. This simple rule-based approach has potential as the basis for a framework for updating frequency-based statistics in the context of possible trends.</p></div></div>","language":"English","publisher":"Taylor and Francis","doi":"10.1080/02626667.2019.1655148","usgsCitation":"Blum, A., Archfield, S.A., Hirsch, R.M., Vogel, R., Kiang, J.E., and Dudley, R., 2019, Updating estimates of low-streamflow statistics to account for possible trends: Hydrologic Sciences Journal, v. 6, no. 12, p. 1404-1414, https://doi.org/10.1080/02626667.2019.1655148.","productDescription":"11 p.","startPage":"1404","endPage":"1414","ipdsId":"IP-102570","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":459950,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02626667.2019.1655148","text":"Publisher Index Page"},{"id":379423,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -78.2666015625,\n              36.527294814546245\n            ],\n            [\n              -71.630859375,\n              36.527294814546245\n            ],\n            [\n              -71.630859375,\n              42.48830197960227\n            ],\n            [\n              -78.2666015625,\n              42.48830197960227\n            ],\n            [\n              -78.2666015625,\n              36.527294814546245\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"6","issue":"12","noUsgsAuthors":false,"publicationDate":"2019-09-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Blum, Annalise G.","contributorId":193846,"corporation":false,"usgs":false,"family":"Blum","given":"Annalise G.","affiliations":[],"preferred":false,"id":801792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":801793,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":801794,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vogel, Richard M","contributorId":241035,"corporation":false,"usgs":false,"family":"Vogel","given":"Richard M","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":801795,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kiang, Julie E. 0000-0003-0653-4225 jkiang@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-4225","contributorId":2179,"corporation":false,"usgs":true,"family":"Kiang","given":"Julie","email":"jkiang@usgs.gov","middleInitial":"E.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":801796,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dudley, Robert W. 0000-0002-0934-0568","orcid":"https://orcid.org/0000-0002-0934-0568","contributorId":220211,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert W.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":801797,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70204920,"text":"70204920 - 2019 - Back to the future: Rebuilding the Everglades","interactions":[],"lastModifiedDate":"2019-09-03T15:08:16","indexId":"70204920","displayToPublicDate":"2019-09-01T10:57:55","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"chapter":"8","title":"Back to the future: Rebuilding the Everglades","docAbstract":"Society values landscapes that are engrained in cultural tradition and have a rich connection with human history. As such, there has been a concerted effort to look at the pristine past and develop plans to move the past into the future. However, bringing the past back is constrained by hysteretic changes, irrevocable damages, and anthropogenic trends that do not reflect past conditions. The scale of the Everglades and its importance to water supply and flood control is such that a full recovery, to past, pre-drainage conditions, is not possible. What is possible?  The answer is the federally authorized Comprehensive Everglades Restoration Plan (CERP) and the first, most significant implementation of the $12 Billion CERP is the $2 Billion Central Everglades Planning Project (CEPP). CEPP is our “flux-capacitor” in the DeLorean sports car that generates the ability to go back and forth in time, in the movie series “Back to the Future.” \n \nThe primary hydrological modeling outputs of CEPP came from a version of the Regional Simulation Model (RSM), developed by the South Florida Water Management District. The RSM is the DeLorean vehicle, designed to carry the bags of ecological restoration. Unfortunately, the capacity of this vehicle (i.e., CEPP) is limited, but is it large enough? Will CEPP make a difference? The 20-year RSM simulations (1965 – 1985) without restoration showed nine dry periods when there was no water in the sloughs of Everglades National Park (ENP). When the model was run with CEPP conditions, all of these extreme dry conditions were eliminated. The impact of this was most apparent for fish, especially the size classes that wading birds eat. With our DeLorean (i.e. the RSM) we saw a 60-90% increase in fish density. As one might expect, the birds in our alternative future responded to the fish. The increased volume, flow, and connectivity in the CEPP simulations significantly improved the foraging response of all wading bird species, especially in Water Conservation Area 3 (WCA-3) and ENP. Foraging conditions for an average CEPP year improved by 25-100%. Further downstream, the CEPP simulations showed increased delivery of low nutrient fresh water to the Coastal Everglades and Florida Bay that displaced the relatively P-rich marine water, increased water transparency, and thus decreased algal blooms. However, in a future with accelerating sea levels and estuarine lakes with legacy phosphorus (P), how much more fresh water will be needed to maintain submerged aquatic vegetated habitats? The quest for Everglades Restoration will reach a resource management milestone with the implementation of CEPP. CEPP successfully used a broad suite of hydrological, ecological and societal models to build an acceptable and feasible adaptive management vision of the future. It has been a long and difficult journey, but what we have learned in the process will guide future travelers back in time.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The Coastal Everglades: The Dynamics of Social-Ecological Transformation in the South Florida Landscape","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Oxford University Press","usgsCitation":"Sklar, F.H., Beerens, J.M., Brandt, L.A., Coronado-Molina, C.A., Davis, S.M., Frankovich, T., Madden, C., McLean, A., Trexler, J.C., and Wilcox, W., 2019, Back to the future: Rebuilding the Everglades, chap. 8 <i>of</i> The Coastal Everglades: The Dynamics of Social-Ecological Transformation in the South Florida Landscape, p. 202-230.","productDescription":"29 p.","startPage":"202","endPage":"230","ipdsId":"IP-069574","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":367151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":367150,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://global.oup.com/academic/product/the-coastal-everglades-9780190869007?cc=us&lang=en&#"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.25900268554688,\n              25.09430487853125\n            ],\n            [\n              -80.53253173828124,\n              25.09430487853125\n            ],\n            [\n              -80.53253173828124,\n              25.667522551344298\n            ],\n            [\n              -81.25900268554688,\n              25.667522551344298\n            ],\n            [\n              -81.25900268554688,\n              25.09430487853125\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sklar, Fred H.","contributorId":195576,"corporation":false,"usgs":false,"family":"Sklar","given":"Fred","email":"","middleInitial":"H.","affiliations":[{"id":27553,"text":"South Florida Water Management District, West Palm Beach, FL","active":true,"usgs":false}],"preferred":false,"id":769022,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beerens, James M. 0000-0001-8143-916X jbeerens@usgs.gov","orcid":"https://orcid.org/0000-0001-8143-916X","contributorId":143722,"corporation":false,"usgs":true,"family":"Beerens","given":"James","email":"jbeerens@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":769021,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brandt, Laura A.","contributorId":146646,"corporation":false,"usgs":false,"family":"Brandt","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":769023,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coronado-Molina, Carlos A.","contributorId":195566,"corporation":false,"usgs":false,"family":"Coronado-Molina","given":"Carlos","email":"","middleInitial":"A.","affiliations":[{"id":27553,"text":"South Florida Water Management District, West Palm Beach, FL","active":true,"usgs":false}],"preferred":false,"id":769024,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davis, Steven M","contributorId":213398,"corporation":false,"usgs":false,"family":"Davis","given":"Steven","email":"","middleInitial":"M","affiliations":[{"id":38747,"text":"Ibis Ecosystems Associates, Inc","active":true,"usgs":false}],"preferred":false,"id":769025,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Frankovich, Tom","contributorId":218331,"corporation":false,"usgs":false,"family":"Frankovich","given":"Tom","email":"","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":769026,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Madden, Christopher","contributorId":195949,"corporation":false,"usgs":false,"family":"Madden","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":769027,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McLean, Agnes","contributorId":218332,"corporation":false,"usgs":false,"family":"McLean","given":"Agnes","email":"","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":769028,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Trexler, Joel C.","contributorId":36267,"corporation":false,"usgs":false,"family":"Trexler","given":"Joel","email":"","middleInitial":"C.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":769029,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wilcox, Walter","contributorId":218333,"corporation":false,"usgs":false,"family":"Wilcox","given":"Walter","affiliations":[{"id":36603,"text":"SFWMD","active":true,"usgs":false}],"preferred":false,"id":769030,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70227951,"text":"70227951 - 2019 - Framework for using downscaled climate model projections in ecological experiments to quantify plant and soil responses","interactions":[],"lastModifiedDate":"2022-02-02T16:33:18.692498","indexId":"70227951","displayToPublicDate":"2019-09-01T10:16:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Framework for using downscaled climate model projections in ecological experiments to quantify plant and soil responses","docAbstract":"<p>Soil and plant responses to climate change can be quantified in controlled settings. However, the complexity of climate projections often leads researchers to evaluate ecosystem response based on general trends, rather than specific climate model outputs. Climate projections capture spatial and temporal climate extremes and variability that are lost when using mean climate trends. In addition, application of climate projections in experimental settings remains limited. Our objective was to develop a framework to incorporate statistically downscaled climate model projections into the design of temperature and precipitation treatments for ecological experiments. To demonstrate the utility of experimental treatments derived from climate projections, we used wetlands in the Great Plains as a model ecosystem for evaluating plant and soil responses. Spatial and temporal projections were selected to capture variability and intensity of projected future conditions for exemplary purposes. To illustrate climate projection application for ecological experiments, we developed temperature and precipitation treatments based on moderate-emissions scenario climate outputs (i.e., RCP4.5–650&nbsp;ppm CO<sub>2</sub><span>&nbsp;</span>equivalent). Our temperature treatments captured weekly trends that represented cool, average, and warm temperature predictions, and our daily precipitation treatments mimicked various seasonal precipitation trends and extreme events projected for the late 21st century. Treatments were applied to two short-term controlled experiments evaluating (1) plant germination (temperature treatment applied in growth chamber) and (2) soil nitrogen cycling (precipitation treatment applied in greenhouse) responses to projected future conditions in the Great Plains. Our approach provides flexibility for selecting appropriate and precise climate model outputs to design experimental treatments. Using these techniques, ecologists can better incorporate variation in climate model projections for experimentally evaluating ecosystem responses to future climate conditions, reduce uncertainty in predictive ecological models, and apply predicted outcomes when making management and policy decisions.</p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2857","usgsCitation":"Owen, R.K., Webb, E.B., Goyne, K.W., Svoma, B.M., and Gautam, S., 2019, Framework for using downscaled climate model projections in ecological experiments to quantify plant and soil responses: Ecosphere, v. 10, no. 9, p. 1-19, https://doi.org/10.1002/ecs2.2857.","productDescription":"e02857, 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-095468","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":459964,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2857","text":"Publisher 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,{"id":70203458,"text":"70203458 - 2019 - Absence of magnetite microlites, geochemistry of magnetite veins and replacements in IOA deposits, SE Missouri, USA: Relations to intermediate intrusions","interactions":[],"lastModifiedDate":"2019-12-03T12:22:43","indexId":"70203458","displayToPublicDate":"2019-08-31T12:19:04","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Absence of magnetite microlites, geochemistry of magnetite veins and replacements in IOA deposits, SE Missouri, USA: Relations to intermediate intrusions","docAbstract":"<p> The paragenesis, textures, and chemical compositions of magnetite in two mafic to intermediate intrusions and four IOA deposits in SE Missouri were studied to discriminate between igneous and hydrothermal sources. In this study, we found that replacement magnetite with mineral inclusion-rich cores yields erroneously high Ti, Al, Si, Mg, and Mn contents as determined by EMP and LA-ICP-MS due to rutile and silicate inclusions. Thus, identification of high-Ti microlites on the basis of inclusion-rich cores with high Ti contents is an analytical artefact. Since the high-Ti magnetite microlite flotation model is critically dependent on this type of analysis, it may be invalid. The presence of coarse-grained high-Ti vein magnetite with ilmenite lamellae enveloped by replacement magnetite with inclusion-rich cores in ore zones suggests that the veins were high-temperature conduits for low-temperature replacement ores. The trace element compositions of vein and replacement magnetite suggest that iron was sourced from mafic to intermediate intrusions. These results support a magmatic-hydrothermal origin for IOA systems in SE Missouri.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Life with Ore Deposits on Earth – 15th SGA Biennial Meeting 2019","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":" 15th SGA Biennial Meeting 2019","conferenceDate":"August 27-30, 2019","conferenceLocation":"Glasgow, Scotland","language":"English","publisher":"Society for Geology Applied to Mineral Deposits (SGA)","usgsCitation":"Meighan, C.J., Hofstra, A.H., Adams, D., Marsh, E.E., Lowers, H.A., and Koenig, A., 2019, Absence of magnetite microlites, geochemistry of magnetite veins and replacements in IOA deposits, SE Missouri, USA: Relations to intermediate intrusions, <i>in</i> Life with Ore Deposits on Earth – 15th SGA Biennial Meeting 2019, v. 1, Glasgow, Scotland, August 27-30, 2019, p. 396-399.","productDescription":"4 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,{"id":70205696,"text":"70205696 - 2019 - The effect of resolution on terrain feature extraction","interactions":[],"lastModifiedDate":"2019-10-08T07:06:17","indexId":"70205696","displayToPublicDate":"2019-08-30T12:48:21","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"The effect of resolution on terrain feature extraction","docAbstract":"Recent increase in the production of high-resolution digital elevation models (DEMs) from lidar data has led to interest in their use for terrain mapping. Although the impact of different resolutions has been studied relative to terrain characteristics like roughness, slope and curvature, its relationship to the extraction of terrain features remains unclear. To address this question, this study tests the impact of four resolutions on the capture of glacial cirques from DEMs. Mean curvature was derived from one arc-second, one-third arc-second, one-ninth arc-second and half meter DEMs representing a cirque-covered mountainous region southwest of Lake Tahoe, California. Using a GEOBIA workflow, ridge objects were identified, and three scales - via the multi-resolution scale parameter (SP) - of objects bordering the ridges were classified as cirque objects. The resulting classifications were compared to reference cirques digitized at a scale of ~1:10,000. Results show that the one-third arc-second DEM produces the set of cirque objects most closely resembling the reference cirques. The one-ninth arc-second DEM afforded the second-best classification. These results emphasize the importance in carefully choosing resolution relative to the features extracted, rather than using the highest resolution data available. In the case of GEOBIA workflows, the choice of scale parameter is equally important.","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Geomorphometry 2018","largerWorkSubtype":{"id":19,"text":"Conference Paper"},"conferenceDate":"August 13-17, 2018","language":"English","publisher":"PeerJ","doi":"10.7287/peerj.preprints.27072v1","usgsCitation":"Arundel, S., Li, W., and Zhou, X., 2019, The effect of resolution on terrain feature extraction, <i>in</i> Geomorphometry 2018, August 13-17, 2018, 4 p., https://doi.org/10.7287/peerj.preprints.27072v1.","productDescription":"4 p.","ipdsId":"IP-094644","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":460303,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.7287/peerj.preprints.27072v1","text":"External Repository"},{"id":368033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sierra Nevada mountain range","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.23574829101562,\n              38.82981255949193\n            ],\n            [\n              -120.02632141113283,\n              38.82981255949193\n            ],\n            [\n              -120.02632141113283,\n              39.0047782882536\n            ],\n            [\n              -120.23574829101562,\n              39.0047782882536\n            ],\n            [\n              -120.23574829101562,\n              38.82981255949193\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Arundel, Samantha T. 0000-0002-4863-0138 sarundel@usgs.gov","orcid":"https://orcid.org/0000-0002-4863-0138","contributorId":192598,"corporation":false,"usgs":true,"family":"Arundel","given":"Samantha","email":"sarundel@usgs.gov","middleInitial":"T.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":772079,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Wenwen 0000-0003-2237-9499","orcid":"https://orcid.org/0000-0003-2237-9499","contributorId":219356,"corporation":false,"usgs":false,"family":"Li","given":"Wenwen","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":772080,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhou, Xiran","contributorId":219357,"corporation":false,"usgs":false,"family":"Zhou","given":"Xiran","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":772081,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70208760,"text":"70208760 - 2019 - Sequestration and transformation in chemically enhanced treatment wetlands: DOC, DBPPs and Nutrients","interactions":[],"lastModifiedDate":"2020-02-28T06:43:57","indexId":"70208760","displayToPublicDate":"2019-08-30T06:42:13","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2255,"text":"Journal of Environmental Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Sequestration and transformation in chemically enhanced treatment wetlands: DOC, DBPPs and Nutrients","docAbstract":"We examined the effectiveness of chemically enhanced treatment wetlands (CETWs), wetlands that received water treated with coagulants, to remove dissolved organic carbon (DOC), disinfection byproduct precursors (DBPPs), nutrients and metals from agricultural drain water. Wetlands consisted of controls with no coagulant addition, ferric sulfate dosed and polyaluminum chloride dosed treatments. CETWs were more effective in removal of DOC, DBPPs, phosphate, dissolved organic nitrogen and metals than control wetlands. Coagulation treated wetlands removed 245 – 349 g/m2yr DOC, whereas control wetlands produced 51 g/m2yr. Wetland passage released DOC in the controls and treatments; this release was directly correlated to temperature and suggested thermally dependent mechanism(s) were partly responsible. A first-order plug flow reactor kinetic model that considered hydraulic retention time (HRT), temperature and concentration was tested for wetland DOC processing. Models indicate that operating CETWs at high coagulant dosing and low temperature can result in lowest DOC release with additional release suppression. Operating at the lowest HRT to meet discharge targets help overcome wetland processes that increase DOC release and provide the smallest footprint needed for treatment.","language":"English","publisher":"ASCE","doi":"10.1061/(ASCE)EE.1943-7870.0001536","usgsCitation":"Bachand, P.A., Bachand, S.M., Kraus, T.E., Stern, D., Ling Liang, Y., and Horwath, W.R., 2019, Sequestration and transformation in chemically enhanced treatment wetlands: DOC, DBPPs and Nutrients: Journal of Environmental Engineering, v. 145, no. 8, 04019044, 16 p., https://doi.org/10.1061/(ASCE)EE.1943-7870.0001536.","productDescription":"04019044, 16 p.","ipdsId":"IP-097091","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":467330,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1061/(asce)ee.1943-7870.0001536","text":"Publisher Index Page"},{"id":372722,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"145","issue":"8","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bachand, Philip A. M. 0000-0002-6757-2404","orcid":"https://orcid.org/0000-0002-6757-2404","contributorId":207558,"corporation":false,"usgs":false,"family":"Bachand","given":"Philip","email":"","middleInitial":"A. M.","affiliations":[{"id":12526,"text":"Bachand & Associates","active":true,"usgs":false}],"preferred":false,"id":783301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bachand, Sandra M. 0000-0001-5235-9726","orcid":"https://orcid.org/0000-0001-5235-9726","contributorId":207557,"corporation":false,"usgs":false,"family":"Bachand","given":"Sandra","email":"","middleInitial":"M.","affiliations":[{"id":12526,"text":"Bachand & Associates","active":true,"usgs":false}],"preferred":false,"id":783302,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kraus, Tamara E. C. 0000-0002-5187-8644 tkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-5187-8644","contributorId":147560,"corporation":false,"usgs":true,"family":"Kraus","given":"Tamara","email":"tkraus@usgs.gov","middleInitial":"E. C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783300,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stern, Dylan 0000-0001-5676-8711","orcid":"https://orcid.org/0000-0001-5676-8711","contributorId":215742,"corporation":false,"usgs":false,"family":"Stern","given":"Dylan","email":"","affiliations":[{"id":39311,"text":"Delta Stewardship Program, Aquatic Science Program","active":true,"usgs":false}],"preferred":false,"id":783303,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ling Liang, Yan 0000-0001-5999-3148","orcid":"https://orcid.org/0000-0001-5999-3148","contributorId":207555,"corporation":false,"usgs":false,"family":"Ling Liang","given":"Yan","email":"","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":783304,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Horwath, William R. 0000-0003-3707-0697","orcid":"https://orcid.org/0000-0003-3707-0697","contributorId":207560,"corporation":false,"usgs":false,"family":"Horwath","given":"William","email":"","middleInitial":"R.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":783305,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70206389,"text":"70206389 - 2019 - Surface rupture and distributed deformation revealed by optical satellite imagery: The intraplate 2016 Mw 6.0 Petermann Ranges earthquake, Australia","interactions":[],"lastModifiedDate":"2019-12-23T08:40:19","indexId":"70206389","displayToPublicDate":"2019-08-29T14:19:21","publicationYear":"2019","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":"Surface rupture and distributed deformation revealed by optical satellite imagery: The intraplate 2016 Mw 6.0 Petermann Ranges earthquake, Australia","docAbstract":"High-resolution optical satellite imagery is used to quantify vertical surface deformation associated with the intraplate 20 May 2016 Mw 6.0 Petermann Ranges earthquake, Northern Territory, Australia. The 21 ╓ 1 km long NW-trending rupture resulted from reverse motion on a northeast-dipping fault. Vertical surface offsets of up to 0.7 ╓ 0.1 m distributed across a 0.5-to-1 km wide deformation zone are measured using the Iterative Closest Point (ICP) algorithm to compare pre- and post-earthquake digital elevation models (DEMs) derived from Worldview imagery. The results are validated by comparison with field-based observations and interferometric synthetic aperture radar (InSAR). The pattern of surface uplift is consistent with distributed shear above the propagating tip of a reverse fault, leading to both an emergent fault and folding proximal to the rupture. This study demonstrates the potential for quantifying modest (<1 m) vertical deformation on a reverse fault using optical satellite imagery.","language":"English","publisher":"AGU","doi":"10.1029/2019GL084926","collaboration":"Geoscience Australia, Symonston, ACT, Australia; University of Iowa, Iowa City, IA, USA; University of Melbourne, Melbourne, Australia","usgsCitation":"Gold, R.D., Clark, D., Barnhart, W., King, T., Quigley, M., and Briggs, R.W., 2019, Surface rupture and distributed deformation revealed by optical satellite imagery: The intraplate 2016 Mw 6.0 Petermann Ranges earthquake, Australia: Geophysical Research Letters, v. 46, no. 17-18, p. 10394-10403, https://doi.org/10.1029/2019GL084926.","productDescription":"10 p.","startPage":"10394","endPage":"10403","ipdsId":"IP-110619","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":467331,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019gl084926","text":"Publisher Index Page"},{"id":368840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              125.33203125,\n              -26.509904531413916\n            ],\n            [\n              129.111328125,\n              -26.509904531413916\n            ],\n            [\n              129.111328125,\n              -21.739091217718574\n            ],\n            [\n              125.33203125,\n              -21.739091217718574\n            ],\n            [\n              125.33203125,\n              -26.509904531413916\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"46","issue":"17-18","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":774360,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Dan","contributorId":175111,"corporation":false,"usgs":false,"family":"Clark","given":"Dan","email":"","affiliations":[],"preferred":false,"id":774361,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnhart, William D. 0000-0003-0498-1697","orcid":"https://orcid.org/0000-0003-0498-1697","contributorId":192730,"corporation":false,"usgs":false,"family":"Barnhart","given":"William D.","affiliations":[],"preferred":false,"id":774362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"King, Tamarah","contributorId":220153,"corporation":false,"usgs":false,"family":"King","given":"Tamarah","email":"","affiliations":[{"id":40134,"text":"University of Melbourne, Melbourne, Australia","active":true,"usgs":false}],"preferred":false,"id":774363,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Quigley, Mark","contributorId":220154,"corporation":false,"usgs":false,"family":"Quigley","given":"Mark","email":"","affiliations":[{"id":40134,"text":"University of Melbourne, Melbourne, Australia","active":true,"usgs":false}],"preferred":false,"id":774364,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":139002,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":774365,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70204522,"text":"sir20195072 - 2019 - Arsenic, antimony, mercury, and water temperature in streams near Stibnite mining area, central Idaho, 2011–17","interactions":[],"lastModifiedDate":"2019-08-28T10:27:00","indexId":"sir20195072","displayToPublicDate":"2019-08-27T13:23:40","publicationYear":"2019","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":"2019-5072","displayTitle":"Arsenic, Antimony, Mercury, and Water Temperature in Streams near Stibnite Mining Area, Central Idaho, 2011–17","title":"Arsenic, antimony, mercury, and water temperature in streams near Stibnite mining area, central Idaho, 2011–17","docAbstract":"Mineralization and historical mining of stibnite (antimony sulfide), tungsten, gold, silver, and mercury in the headwaters of the East Fork of the South Fork Salmon River (EFSFSR) near the former town of Stibnite in central Idaho resulted in water-quality impairments related to mercury, antimony, and arsenic. Additionally, mining-related disturbances and wildfires have resulted in a lack of riparian shade in some areas, likely impacting water temperatures. In 2011, the U.S. Geological Survey, in cooperation with Midas Gold Corporation and the Idaho Department of Lands, began a study to characterize the spatial and temporal occurrence of trace metals to the EFSFSR. Five sites on the EFSFSR and its tributaries (Meadow and Sugar Creeks) were sampled about six times annually during 2011–17, during a range of streamflow conditions, for a total of 36–40 samples per location. Continuous water temperature, specific conductance, and streamflow also were measured at each site. The purpose of this report is to update previously reported information related to arsenic, antimony, mercury, and water temperature.\n\nConcentrations of dissolved arsenic and antimony generally increased from upstream to downstream in the EFSFSR. At the upstream site, upstream of the Meadow Creek confluence, dissolved arsenic and antimony concentrations averaged 8.86 and 0.93 micrograms per liter (μg/L), respectively. Downstream, upstream from the Sugar Creek confluence, average dissolved concentrations increased to 56.5 and 27.9 μg/L, respectively. All samples from the downstream EFSFSR site exceeded the human-health based criterion for both dissolved arsenic (10 µg/L) and dissolved antimony (5.6 µg/L). The chronic aquatic life criterion for dissolved arsenic (150 μg/L) was not exceeded (the maximum sample concentration was 108 μg/L), and aquatic life criteria for antimony have not been established. The highest concentrations of both dissolved arsenic and dissolved antimony occurred during low-flow periods (July–March), suggesting the constituents are present in groundwater. In contrast, total mercury concentrations were highest during high-flow periods (April–June) and were particulate-associated, suggesting that mercury is present in surface materials. At Sugar Creek, where the highest total mercury concentrations were measured, 97 percent of samples exceeded the chronic aquatic life criterion (0.012 μg/L) and 11 percent exceeded the acute criterion (2.1 μg/L). At all sites, summertime water temperatures frequently  exceeded criteria related to salmonid spawning.\n\nSurrogate models previously developed to estimate continuous concentrations of arsenic, antimony, and mercury were reevaluated and updated, and the importance of explanatory variables on constituent concentrations is discussed. Results from this study can help guide future remediation locations and strategies, and provide a baseline against which future changes can be measured.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195072","collaboration":"Prepared in cooperation with the Idaho Department of Lands and Midas Gold Idaho, Inc.","usgsCitation":"Baldwin, A.K., and Etheridge, A.B., 2019, Arsenic, antimony, mercury, and water temperature in streams near Stibnite mining area, central Idaho, 2011–17: U.S. Geological Survey Scientific Investigations Report 2019-5072, 20 p., plus appendix, https://doi.org/10.3133/sir20195072.","productDescription":"Report: vi, 20 p.; Appendix","onlineOnly":"Y","ipdsId":"IP-093353","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":366989,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5072/coverthb.jpg"},{"id":366990,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5072/sir20195072.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5072"},{"id":366991,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5072/sir20195072_appendix.pdf","text":"Appendix","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5072 Appendix","linkHelpText":" — Surrogate Regression Model Archive Summaries."}],"country":"United States","state":"Idaho","otherGeospatial":"Stibnite Mining Area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.67985534667969,\n              44.793530904744074\n            ],\n            [\n              -115.14564514160158,\n              44.793530904744074\n            ],\n            [\n              -115.14564514160158,\n              45.15541134861056\n            ],\n            [\n              -115.67985534667969,\n              45.15541134861056\n            ],\n            [\n              -115.67985534667969,\n              44.793530904744074\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_id@usgs.gov\" data-mce-href=\"mailto:dc_id@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/id-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/id-water\">Idaho Water Science Center</a><br>U.S. Geological Survey<br>230 Collins Rd<br>Boise, Idaho 83702-4520</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Study Methods</li><li>Results</li><li>Summary</li><li>References Cited</li><li>Appendix. Surrogate Regression Model Archive Summaries</li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2019-08-27","noUsgsAuthors":false,"publicationDate":"2019-08-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":767385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Etheridge, Alexandra B. 0000-0003-1282-7315 aetherid@usgs.gov","orcid":"https://orcid.org/0000-0003-1282-7315","contributorId":3542,"corporation":false,"usgs":true,"family":"Etheridge","given":"Alexandra","email":"aetherid@usgs.gov","middleInitial":"B.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":767386,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
]}