{"pageNumber":"265","pageRowStart":"6600","pageSize":"25","recordCount":40778,"records":[{"id":70212762,"text":"70212762 - 2020 - Procedures for developing multi-period response spectra at non-conterminous United States sites","interactions":[],"lastModifiedDate":"2021-01-22T18:10:01.008346","indexId":"70212762","displayToPublicDate":"2020-08-01T11:57:53","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"P-2078","title":"Procedures for developing multi-period response spectra at non-conterminous United States sites","docAbstract":"

This study complements proposals to the Provisions Update Committee of the Building Seismic Safety Council that would incorporate multi-period response spectra (MPRS) in the 2020 edition of the NEHRP Recommended Seismic Provisions for New Buildings and Other Structures (2020 NEHRP Provisions) and related proposals to the ASCE 7-22 Seismic Subcommittee of the American Society of Civil Engineers for incorporation of MPRS in ASCE Standard, ASCE/SEI 7-22, Minimum Design Loads and Associated Criteria for Buildings and Other Structures (ASCE 7-22). Ultimately, the intent is that the proposed MPRS and related design requirements of ASCE 7-22 would be adopted, by reference, as part of the 2024 International Building Code.


The technical basis and associated methods herein enable the U.S. Geological Survey (USGS) to develop MPRS for sites in non-conterminous U.S. regions for which seismic hazard analyses have not yet been updated by the USGS to fully define all 22 periods and eight site classes of interest in the MPRS related proposals for the 2020 NEHRP Provisions and ASCE 7-22. These regions include Alaska, Hawaii, Guam and the Northern Mariana Islands, Puerto Rico and the U.S. Virgin Islands, and American Samoa.


The methods developed can be used to derive MPRS using only the three currently available ground motion parameters SS, S1, and TL for all nonconterminous United States regions of interest. The methods include models that characterize generic shapes of Risk-Targeted Maximum Considered Earthquake (MCER) ground motions as a function of these three parameters. For deriving MPRS that represent probabilistic MCER ground motions, models are based on statistical analyses of large sample sets of probabilistic MCER response spectra for Western United States (WUS) and Cascadia sites in California, Oregon, Washington (including Puget Sound), Idaho, and Nevada. For deriving MPRS that represent deterministic MCER ground motions, models are based on sets of deterministic MCER response spectra calculated using WUS shallow crustal ground motion models for earthquake magnitudes and shaking levels typical of sites governed by deterministic
MCER ground motions.

","language":"English","publisher":"FEMA","usgsCitation":"Tong, M., Hanson, R.D., Kircher, C.A., Rezaeian, S., and Luco, N., 2020, Procedures for developing multi-period response spectra at non-conterminous United States sites, 558 p.","productDescription":"558 p.","ipdsId":"IP-114085","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":382506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":382504,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.fema.gov/sites/default/files/2020-11/fema_p-2078_multi-period-response-spectra_08-01-2020.pdf"}],"country":"United States","state":"Alaska, American Samoa, Hawaii, Guam and the Northern Mariana Islands, Puerto Rico, U.S. Virgin Islands","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tong, Mai","contributorId":222338,"corporation":false,"usgs":false,"family":"Tong","given":"Mai","email":"","affiliations":[{"id":40528,"text":"Federal Emergency Management Agency","active":true,"usgs":false}],"preferred":false,"id":808821,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanson, Robert D.","contributorId":81004,"corporation":false,"usgs":true,"family":"Hanson","given":"Robert","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":808822,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kircher, Charles A","contributorId":221886,"corporation":false,"usgs":false,"family":"Kircher","given":"Charles","email":"","middleInitial":"A","affiliations":[{"id":40454,"text":"Kircher & Associates, Consulting Engineers","active":true,"usgs":false}],"preferred":false,"id":797423,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":797424,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":797425,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228560,"text":"70228560 - 2020 - Spatiotemporal variation in occurrence and co-occurrence of pesticides, hormones, and other organic contaminants in rivers in the Chesapeake Bay Watershed, United States","interactions":[],"lastModifiedDate":"2022-02-15T12:22:36.066283","indexId":"70228560","displayToPublicDate":"2020-08-01T09:59:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal variation in occurrence and co-occurrence of pesticides, hormones, and other organic contaminants in rivers in the Chesapeake Bay Watershed, United States","docAbstract":"Investigating the spatiotemporal dynamics of contaminants in surface water is crucial to better understand how introduced chemicals are interacting with and potentially influencing aquatic organisms and environments. Within the Chesapeake Bay Watershed, USA, there are concerns about the potential role of contaminant exposure on fish health. Evidence suggests that exposure to contaminants in surface water is causing immunosuppression and intersex in freshwater fish species. Despite these concerns, there is a paucity of information regarding the complex dynamics of contaminant occurrence and co-occurrence in surface water across both space and time. To address these concerns, we applied a Bayesian hierarchical joint-contaminant model to describe the occurrence and co-occurrence patterns of 28 contaminants and total estrogenicity across six river sites and over three years. We found that seasonal occurrence patterns varied by contaminant, with the highest occurrence probabilities during the spring and summer months. Additionally, we found that the proportion of agricultural landcover in the immediate catchment, as well as stream discharge, did not have a significant effect on the occurrence probabilities of most compounds. Four pesticides (atrazine, metolachlor, fipronil and simazine) co-occurred across sites after accounting for environmental covariates. These results provide baseline information on the contaminant occurrence patterns of several classes of compounds within the Chesapeake Bay Watershed. Understanding the spatiotemporal dynamics of contaminants in surface water is the first step in investigating the effects of contaminant exposure on fisheries and aquatic environments.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.138765","usgsCitation":"McClure, C.M., Smalling, K., Blazer, V.S., Sperry, A., Schall, M.K., Kolpin, D., Phillips, P.J., Hladik, M.L., and Wagner, T., 2020, Spatiotemporal variation in occurrence and co-occurrence of pesticides, hormones, and other organic contaminants in rivers in the Chesapeake Bay Watershed, United States: Science of the Total Environment, v. 728, p. 1-13, https://doi.org/10.1016/j.scitotenv.2020.138765.","productDescription":"138765, 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-117478","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":455790,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.138765","text":"Publisher Index Page"},{"id":395889,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New York, Pennsylvania, Virginia, West Virginia","otherGeospatial":"Chesapeake Bay Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.1904296875,\n 38.41916639395372\n ],\n [\n -75.223388671875,\n 38.64261790634527\n ],\n [\n -75.35522460937499,\n 38.79690830348427\n ],\n [\n -75.498046875,\n 38.87392853923629\n ],\n [\n -75.5419921875,\n 39.0533181067413\n ],\n [\n -75.662841796875,\n 39.30029918615029\n ],\n [\n -75.750732421875,\n 39.70718665682654\n ],\n [\n -75.6298828125,\n 40.052847601823984\n ],\n [\n -75.69580078125,\n 40.07807142745009\n ],\n [\n -75.95947265625,\n 40.052847601823984\n ],\n [\n -76.0693359375,\n 40.069664523297774\n ],\n [\n -76.058349609375,\n 40.18726672309203\n ],\n [\n -75.9375,\n 40.29628651711716\n ],\n [\n -75.91552734375,\n 40.3549167507906\n ],\n [\n -75.89355468749999,\n 40.47202439692057\n ],\n [\n -76.09130859375,\n 40.56389453066509\n ],\n [\n -76.190185546875,\n 40.64730356252251\n ],\n [\n -76.0693359375,\n 40.75557964275589\n ],\n [\n -75.83862304687499,\n 40.871987756697415\n ],\n [\n -75.76171875,\n 40.91351257612758\n ],\n [\n -75.706787109375,\n 40.95501133048621\n ],\n [\n -75.7177734375,\n 41.071069130806414\n ],\n [\n -75.662841796875,\n 41.1455697310095\n ],\n [\n -75.5419921875,\n 41.13729606112276\n ],\n [\n -75.322265625,\n 41.104190944576466\n ],\n [\n -75.377197265625,\n 41.22824901518529\n ],\n [\n -75.377197265625,\n 41.28606238749825\n ],\n [\n -75.377197265625,\n 41.43449030894922\n ],\n [\n -75.399169921875,\n 41.6154423246811\n ],\n [\n -75.34423828125,\n 41.68111756290652\n ],\n [\n -75.2783203125,\n 41.91045347666418\n ],\n [\n -75.38818359375,\n 42.00848901572399\n ],\n [\n -75.377197265625,\n 42.09007006868398\n ],\n [\n -75.223388671875,\n 42.17968819665961\n ],\n [\n -74.970703125,\n 42.26917949243506\n ],\n [\n -74.8388671875,\n 42.32606244456202\n ],\n [\n -74.520263671875,\n 42.415346114253616\n ],\n [\n -74.278564453125,\n 42.54498667313236\n ],\n [\n -74.322509765625,\n 42.64204079304426\n ],\n [\n -74.410400390625,\n 42.80346172417078\n ],\n [\n -74.68505859374999,\n 42.924251753870685\n ],\n [\n -75.069580078125,\n 42.98053954751642\n ],\n [\n -75.38818359375,\n 42.96446257387128\n ],\n [\n -75.684814453125,\n 42.93229601903058\n ],\n [\n -75.9375,\n 42.87596410238256\n ],\n [\n -76.201171875,\n 42.827638636242284\n ],\n [\n -76.26708984375,\n 42.72280375732727\n ],\n [\n -76.2890625,\n 42.601619944327965\n ],\n [\n -76.2890625,\n 42.52069952914966\n ],\n [\n -76.343994140625,\n 42.415346114253616\n ],\n [\n -76.46484375,\n 42.382894009614034\n ],\n [\n -76.640625,\n 42.431565872579185\n ],\n [\n -76.7724609375,\n 42.39912215986002\n ],\n [\n -76.80541992187499,\n 42.24478535602799\n ],\n [\n -76.88232421875,\n 42.285437007491545\n ],\n [\n -76.9482421875,\n 42.415346114253616\n ],\n [\n -77.04711914062499,\n 42.44778143462245\n ],\n [\n -77.14599609375,\n 42.415346114253616\n ],\n [\n -77.2998046875,\n 42.382894009614034\n ],\n [\n -77.222900390625,\n 42.54498667313236\n ],\n [\n -77.442626953125,\n 42.69858589169842\n ],\n [\n -77.574462890625,\n 42.60970621339408\n ],\n [\n -77.640380859375,\n 42.48830197960227\n ],\n [\n -77.728271484375,\n 42.439674178149424\n ],\n [\n -77.6513671875,\n 42.31793945446847\n ],\n [\n -77.596435546875,\n 42.22851735620852\n ],\n [\n -77.5634765625,\n 42.09007006868398\n ],\n [\n -77.6953125,\n 41.92680320648791\n ],\n [\n -77.9150390625,\n 41.83682786072714\n ],\n [\n -78.0908203125,\n 41.795888098191426\n ],\n [\n -78.453369140625,\n 41.599013054830216\n ],\n [\n -78.453369140625,\n 41.50857729743935\n ],\n [\n -78.42041015625,\n 41.376808565702355\n ],\n [\n -78.3984375,\n 41.21172151054787\n ],\n [\n -78.519287109375,\n 41.054501963290505\n ],\n [\n -78.541259765625,\n 40.9218144123785\n ],\n [\n -78.409423828125,\n 40.713955826286046\n ],\n [\n -78.299560546875,\n 40.55554790286311\n ],\n [\n -78.343505859375,\n 40.48873742102282\n ],\n [\n -78.475341796875,\n 40.30466538259176\n ],\n [\n -78.64013671875,\n 40.06125658140474\n ],\n [\n -78.826904296875,\n 39.9434364619742\n ],\n [\n -78.848876953125,\n 39.80853604144591\n ],\n [\n -78.85986328125,\n 39.715638134796336\n ],\n [\n -78.99169921875,\n 39.69873414348139\n ],\n [\n -79.046630859375,\n 39.64799732373418\n ],\n [\n -79.266357421875,\n 39.436192999314095\n ],\n [\n -79.420166015625,\n 39.2832938689385\n ],\n [\n -79.354248046875,\n 39.26628442213066\n ],\n [\n -79.266357421875,\n 39.232253141714885\n ],\n [\n -79.2333984375,\n 39.155622393423215\n ],\n [\n -79.244384765625,\n 39.01918369029134\n ],\n [\n -79.27734374999999,\n 38.89103282648846\n ],\n [\n -79.398193359375,\n 38.74551518488265\n ],\n [\n -79.661865234375,\n 38.54816542304656\n ],\n [\n -79.683837890625,\n 38.47079371120379\n ],\n [\n -79.727783203125,\n 38.34165619279595\n ],\n [\n -79.815673828125,\n 38.20365531807149\n ],\n [\n -80.04638671875,\n 38.013476231041935\n ],\n [\n -80.17822265625,\n 37.779398571318765\n ],\n [\n -80.2880859375,\n 37.59682400108367\n ],\n [\n -80.4638671875,\n 37.47485808497102\n ],\n [\n -80.694580078125,\n 37.38761749978395\n ],\n [\n -80.771484375,\n 37.23032838760387\n ],\n [\n -80.57373046875,\n 37.26530995561875\n ],\n [\n -80.44189453125,\n 37.309014074275915\n ],\n [\n -80.255126953125,\n 37.31775185163688\n ],\n [\n -80.013427734375,\n 37.3002752813443\n ],\n [\n -79.8486328125,\n 37.23907530202184\n ],\n [\n -79.771728515625,\n 37.18657859524883\n ],\n [\n -79.6728515625,\n 37.07271048132943\n ],\n [\n -79.541015625,\n 37.09900294387622\n ],\n [\n -79.354248046875,\n 37.142803443716836\n ],\n [\n -79.1455078125,\n 37.10776507118514\n ],\n [\n -79.112548828125,\n 37.055177106660814\n ],\n [\n -78.936767578125,\n 36.932330061503144\n ],\n [\n -78.837890625,\n 36.94111143010769\n ],\n [\n -78.662109375,\n 37.055177106660814\n ],\n [\n -78.486328125,\n 37.03763967977139\n ],\n [\n -78.42041015625,\n 36.94111143010769\n ],\n [\n -78.20068359374999,\n 36.96744946416934\n ],\n [\n -77.904052734375,\n 37.03763967977139\n ],\n [\n -77.750244140625,\n 37.081475648860525\n ],\n [\n -77.53051757812499,\n 37.081475648860525\n ],\n [\n -77.354736328125,\n 37.07271048132943\n ],\n [\n -77.069091796875,\n 37.081475648860525\n ],\n [\n -76.959228515625,\n 37.01132594307015\n ],\n [\n -76.893310546875,\n 36.932330061503144\n ],\n [\n -76.871337890625,\n 36.83566824724438\n ],\n [\n -76.849365234375,\n 36.677230602346214\n ],\n [\n -76.7724609375,\n 36.527294814546245\n ],\n [\n -76.629638671875,\n 36.55377524336089\n ],\n [\n -76.46484375,\n 36.589068371399115\n ],\n [\n -76.35498046875,\n 36.48314061639213\n ],\n [\n -76.256103515625,\n 36.57142382346277\n ],\n [\n -76.190185546875,\n 36.66841891894786\n ],\n [\n -76.0693359375,\n 36.65079252503471\n ],\n [\n -75.9375,\n 36.66841891894786\n ],\n [\n -75.948486328125,\n 36.76529191711624\n ],\n [\n -75.904541015625,\n 37.01132594307015\n ],\n [\n -75.926513671875,\n 37.17782559332976\n ],\n [\n -75.882568359375,\n 37.42252593456307\n ],\n [\n -75.618896484375,\n 37.640334898059486\n ],\n [\n -75.509033203125,\n 37.82280243352756\n ],\n [\n -75.38818359375,\n 38.013476231041935\n ],\n [\n -75.16845703124999,\n 38.272688535980976\n ],\n [\n -75.1904296875,\n 38.41916639395372\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"728","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Barcelo, Damia","contributorId":278587,"corporation":false,"usgs":false,"family":"Barcelo","given":"Damia","affiliations":[],"preferred":false,"id":834817,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"McClure, Catherine M.","contributorId":276135,"corporation":false,"usgs":false,"family":"McClure","given":"Catherine","email":"","middleInitial":"M.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":834596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smalling, Kelly","contributorId":276136,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834597,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":276137,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki","email":"vblazer@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":834598,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sperry, Adam 0000-0002-4815-3730","orcid":"https://orcid.org/0000-0002-4815-3730","contributorId":203243,"corporation":false,"usgs":true,"family":"Sperry","given":"Adam","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":834599,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schall, Megan K.","contributorId":274359,"corporation":false,"usgs":false,"family":"Schall","given":"Megan","email":"","middleInitial":"K.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":834816,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kolpin, Dana W.","contributorId":276139,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834600,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Phillips, Patrick J. 0000-0001-5915-2015 pjphilli@usgs.gov","orcid":"https://orcid.org/0000-0001-5915-2015","contributorId":276140,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick","email":"pjphilli@usgs.gov","middleInitial":"J.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834601,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":221229,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834602,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834595,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70216432,"text":"70216432 - 2020 - Three-dimensional shape and structure of the Susitna basin, south-central Alaska, from geophysical data","interactions":[],"lastModifiedDate":"2020-11-18T13:35:24.510584","indexId":"70216432","displayToPublicDate":"2020-08-01T07:30:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Three-dimensional shape and structure of the Susitna basin, south-central Alaska, from geophysical data","docAbstract":"

We use gravity, magnetic, seismic reflection, well, and outcrop data to determine the three-dimensional shape and structural features of south-central Alaska’s Susitna basin. This basin is located within the Aleutian-Alaskan convergent margin region and is expected to show effects of regional subduction zone processes. Aeromagnetic data, when filtered to highlight anomalies associated with sources within the upper few kilometers, show numerous linear northeast-trending highs and some linear north-trending highs. Comparisons to seismic reflection and well data show that these highs correspond to areas where late Paleocene to early Eocene volcanic layers have been locally uplifted due to folding and/or faulting. The combined magnetic and seismic reflection data suggest that the linear highs represent northeast-trending folds and north-striking faults. Several lines of evidence suggest that the northeast-trending folds formed during the middle Eocene to early Miocene and may have continued to be active in the Pliocene. The north-striking faults, which in some areas appear to cut the northeast-trending folds, show evidence of Neogene and probable modern movement. Gravity data facilitate estimates of the shape and depth of the basin. This was accomplished by separating the observed gravity anomaly into two components—one representing low-density sedimentary fill within the basin and one representing density heterogeneities within the underlying crystalline basement. We then used the basin anomaly, seismic reflection data, and well data to estimate the depth of the basin. Together, the magnetic, gravity, and reflection seismic analyses reveal an asymmetric basin comprising sedimentary rock over 4 km thick with steep, fault-bounded sides to the southwest, west, and north and a mostly gentle rise toward the east. Relations to the broader tectonic regime are suggested by fold axis orientations within the Susitna basin and neighboring Cook Inlet basin, which are roughly parallel to the easternmost part of the Alaska-Aleutian trench and associated Wadati-Benioff zone as it trends from northeast to north-northeast to northeast. An alignment between forearc basin folds and the subduction zone trench has been observed at other convergent margins, attributed to strain partitioning generated by regional rheologic variations that are associated with the subducting plate and arc magmatism. The asymmetric shape of the basin, especially its gentle rise to the east, may reflect uplift associated with flat-slab subduction of the Yakutat microplate, consistent with previous work that suggested Yakutat influence on the nearby Talkeetna Mountains and western Alaska Range. Yakutat subduction may also have contributed to Neogene and later reverse slip along north-striking faults within the Susitna basin.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02165.1","usgsCitation":"Shah, A.K., Phillips, J., Lewis, K.A., Stanley, R.G., Haeussler, P., and Potter, C.J., 2020, Three-dimensional shape and structure of the Susitna basin, south-central Alaska, from geophysical data: Geosphere, v. 16, no. 4, p. 969-990, https://doi.org/10.1130/GES02165.1.","productDescription":"22 p.","startPage":"969","endPage":"990","ipdsId":"IP-103718","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":455808,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02165.1","text":"Publisher Index Page"},{"id":380589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"South Central Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.775390625,\n 57.844750992891\n ],\n [\n -145.634765625,\n 57.844750992891\n ],\n [\n -145.634765625,\n 62.71446210149774\n ],\n [\n -154.775390625,\n 62.71446210149774\n ],\n [\n -154.775390625,\n 57.844750992891\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-06-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Shah, Anjana K. 0000-0002-3198-081X ashah@usgs.gov","orcid":"https://orcid.org/0000-0002-3198-081X","contributorId":2297,"corporation":false,"usgs":true,"family":"Shah","given":"Anjana","email":"ashah@usgs.gov","middleInitial":"K.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":805103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Jeffrey 0000-0002-6459-2821 jeff@usgs.gov","orcid":"https://orcid.org/0000-0002-6459-2821","contributorId":127453,"corporation":false,"usgs":true,"family":"Phillips","given":"Jeffrey","email":"jeff@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":805104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lewis, Kristen A. 0000-0003-4991-3399 klewis@usgs.gov","orcid":"https://orcid.org/0000-0003-4991-3399","contributorId":4120,"corporation":false,"usgs":true,"family":"Lewis","given":"Kristen","email":"klewis@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":805105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stanley, Richard G. 0000-0001-6192-8783 rstanley@usgs.gov","orcid":"https://orcid.org/0000-0001-6192-8783","contributorId":1832,"corporation":false,"usgs":true,"family":"Stanley","given":"Richard","email":"rstanley@usgs.gov","middleInitial":"G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":805106,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":805107,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Potter, Christopher J. 0000-0002-2300-6670 cpotter@usgs.gov","orcid":"https://orcid.org/0000-0002-2300-6670","contributorId":1026,"corporation":false,"usgs":true,"family":"Potter","given":"Christopher","email":"cpotter@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":805108,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70211518,"text":"sir20205069 - 2020 - Incipient bed-movement and flood-frequency analysis using hydrophones to estimate flushing flows on the upper Colorado River, Colorado, 2019","interactions":[],"lastModifiedDate":"2020-08-05T18:38:22.157905","indexId":"sir20205069","displayToPublicDate":"2020-07-31T18:00:00","publicationYear":"2020","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":"2020-5069","displayTitle":"Incipient Bed-Movement and Flood-Frequency Analysis using Hydrophones to Estimate Flushing Flows on the Upper Colorado River, Colorado, 2019","title":"Incipient bed-movement and flood-frequency analysis using hydrophones to estimate flushing flows on the upper Colorado River, Colorado, 2019","docAbstract":"

In 2019, the U.S. Geological Survey, in cooperation with the Upper Colorado River Wild and Scenic Stakeholder Group, studied the magnitude and recurrence interval of streamflow (discharge) needed to initiate bed movement of gravel-sized and finer sediment in a segment of the Colorado River in Colorado to better understand sediment movement and its relation to flow regimes of the river. The study area extended from the confluence of the Blue and Colorado Rivers near Kremmling, Colorado, downstream to the confluence of the Eagle and Colorado Rivers near Dotsero, Colo. Bed movement occurred more frequently and at lower streamflows from State Bridge to Catamount Bridge compared to the study area upstream from State Bridge. As a result, the flushing flow was characterized in the study area using two definitions: the “upstream flushing flow” for locations above State Bridge and the “downstream flushing flow” for locations below State Bridge.

Acoustic data from stationary hydrophones continuously deployed in the spring and summer of 2019 and longitudinal hydrophone acoustic profiles manually collected in summer 2019 were used to identify the streamflow needed for incipient gravel-bed movement and establish flushing flows defined for this study. The upstream flushing flow was defined as 3,000 cubic feet per second (ft3/s) at streamgage 09058000 Colorado River near Kremmling, Colo. (the Kremmling streamgage) based on the underwater acoustic data from the downstream location at the Radium stationary site (2,950 ft3/s at the Kremmling streamgage which was rounded to 3,000 ft3/s). The downstream flushing flow was defined as 2,400 ft3/s at the Kremmling streamgage or 3,100 ft3/s at streamgage 09060799 Colorado River at Catamount Bridge, Colo. (the Catamount Bridge streamgage) based on the more conservative streamflow associated with the flushing flow defined using underwater acoustic data from the downstream location at the above Catamount Bridge stationary site (2,310 ft3/s at the Kremmling streamgage which was rounded to 2,400 ft3/s and 3,040 ft3/s at the Catamount Bridge streamgage which was rounded to 3,100 ft3/s).

The annual series of peak-streamflow data at the Kremmling streamgage were used to estimate annual exceedance probability (AEP) streamflows to compare to the flushing flow. Results from the Denver Water Platte and Colorado Simulation Model were used to generate daily peak-streamflows for a future conditions scenario provided for this report. The upstream flushing flow of approximately 3,000 ft3/s at the Kremmling streamgage has an AEP near 0.50 (2-year return period) depending on the period of historical record and an AEP near 0.43 (2.33-year return period) for the future period. The downstream flushing flow of approximately 2,400 ft3/s at the Kremmling streamgage has an AEP near 0.67 (1.5-year return period) depending on the period of historical record and an AEP near 0.67 (1.5-year return period) for the future period.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205069","collaboration":"Prepared in cooperation with the Upper Colorado River Wild and Scenic Stakeholder Group and the Colorado River Water Conservation District","usgsCitation":"Kohn, M.S., Marineau, M.D., Hempel, L.A., and McDonald, R.R., 2020, Incipient bed-movement and flood-frequency analysis using hydrophones to estimate flushing flows on the upper Colorado River, Colorado, 2019: U.S. Geological Survey Scientific Investigations Report 2020–5069, 39 p., https://doi.org/10.3133/sir20205069.","productDescription":"Report: viii, 39 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-114386","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":376916,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J5L78O","text":"USGS data release","linkHelpText":"Acoustic, Spatial, and Sediment Size Data Collected on the Upper Colorado River to Estimate the Flushing Flows, Colorado, 2019"},{"id":376851,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5069/sir20205069.pdf","text":"Report","size":"26.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5069"},{"id":376850,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5069/coverthb.jpg"}],"country":"United States","state":"Colorado","county":"Eagle County, Grand County","otherGeospatial":"Upper Colorado River","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-106.4343,39.9249],[-106.4359,39.9197],[-106.4359,39.9156],[-106.4335,39.9106],[-106.4304,39.907],[-106.4298,39.9034],[-106.4292,39.8947],[-106.4291,39.883],[-106.4297,39.8811],[-106.4315,39.8771],[-106.432,39.8743],[-106.4314,39.8707],[-106.4224,39.8562],[-106.4211,39.8522],[-106.4199,39.8427],[-106.4181,39.8381],[-106.4084,39.82],[-106.3932,39.7892],[-106.3908,39.782],[-106.3896,39.7743],[-106.3859,39.768],[-106.3805,39.7625],[-106.3679,39.753],[-106.3631,39.7512],[-106.3571,39.7513],[-106.3535,39.7526],[-106.3482,39.7563],[-106.3446,39.7576],[-106.3422,39.7567],[-106.3416,39.7536],[-106.341,39.75],[-106.3356,39.745],[-106.3283,39.7355],[-106.3223,39.7291],[-106.3139,39.7242],[-106.3038,39.7219],[-106.2996,39.7192],[-106.2947,39.7115],[-106.2911,39.7043],[-106.2845,39.6993],[-106.2774,39.6975],[-106.2702,39.7007],[-106.2654,39.7007],[-106.263,39.6998],[-106.263,39.6966],[-106.2624,39.6839],[-106.2588,39.6799],[-106.2546,39.6772],[-106.2462,39.6781],[-106.2414,39.6781],[-106.239,39.6777],[-106.239,39.6659],[-106.2372,39.6622],[-106.233,39.6595],[-106.227,39.6595],[-106.2216,39.6604],[-106.2192,39.66],[-106.218,39.6546],[-106.2162,39.6528],[-106.2073,39.6519],[-106.1995,39.6501],[-106.1852,39.6501],[-106.1828,39.6478],[-106.1798,39.6397],[-106.1762,39.6351],[-106.1756,39.6297],[-106.1761,39.6215],[-106.1767,39.6152],[-106.1779,39.6066],[-106.1803,39.603],[-106.1839,39.6007],[-106.1892,39.6007],[-106.1958,39.6025],[-106.2006,39.6025],[-106.2048,39.6011],[-106.2077,39.5975],[-106.2113,39.5911],[-106.2136,39.5848],[-106.213,39.5775],[-106.21,39.5675],[-106.2082,39.563],[-106.2052,39.5607],[-106.1986,39.5571],[-106.1981,39.5562],[-106.1992,39.5544],[-106.2034,39.5512],[-106.2052,39.5499],[-106.2058,39.549],[-106.2093,39.5317],[-106.2105,39.529],[-106.2111,39.5286],[-106.2135,39.529],[-106.2177,39.5313],[-106.2231,39.5331],[-106.226,39.5349],[-106.2302,39.5376],[-106.2332,39.5417],[-106.2368,39.5476],[-106.238,39.5485],[-106.2398,39.5485],[-106.2463,39.5425],[-106.2511,39.5385],[-106.2576,39.5335],[-106.2582,39.5316],[-106.257,39.5289],[-106.2558,39.5267],[-106.254,39.5244],[-106.2546,39.5203],[-106.254,39.5162],[-106.2522,39.5144],[-106.2474,39.5113],[-106.2474,39.5099],[-106.248,39.5049],[-106.2486,39.4981],[-106.2479,39.4895],[-106.2497,39.4804],[-106.2503,39.4732],[-106.2508,39.4682],[-106.249,39.4646],[-106.2472,39.4619],[-106.2401,39.4533],[-106.2383,39.4501],[-106.2353,39.4447],[-106.2323,39.4415],[-106.2257,39.4365],[-106.2239,39.4342],[-106.2239,39.4324],[-106.2257,39.4306],[-106.2293,39.4265],[-106.2299,39.4225],[-106.2274,39.4147],[-106.2262,39.4134],[-106.2245,39.4134],[-106.2149,39.4166],[-106.212,39.4161],[-106.2102,39.4139],[-106.2096,39.4112],[-106.2137,39.4057],[-106.2143,39.3985],[-106.2089,39.3799],[-106.2226,39.3794],[-106.2238,39.3785],[-106.2368,39.3667],[-106.241,39.364],[-106.2463,39.3626],[-106.2546,39.3621],[-106.257,39.3617],[-106.2778,39.3535],[-106.282,39.353],[-106.2873,39.3525],[-106.2909,39.3539],[-106.301,39.3588],[-106.3082,39.3611],[-106.3141,39.3624],[-106.3177,39.362],[-106.329,39.3597],[-106.3373,39.3578],[-106.348,39.3555],[-106.3528,39.3555],[-106.3564,39.356],[-106.3599,39.3573],[-106.3629,39.3605],[-106.3695,39.3686],[-106.3713,39.3704],[-106.3874,39.3763],[-106.3952,39.3794],[-106.3981,39.3794],[-106.4017,39.3799],[-106.4041,39.3776],[-106.4076,39.3735],[-106.4165,39.3658],[-106.7129,39.362],[-107.1137,39.3661],[-107.1132,39.395],[-107.1134,39.5623],[-107.1133,39.5918],[-107.1129,39.6063],[-107.1124,39.6507],[-107.1122,39.6802],[-107.1121,39.7097],[-107.1108,39.7414],[-107.1116,39.7931],[-107.1122,39.8303],[-107.1122,39.8362],[-107.1129,39.9192],[-107.0313,39.919],[-106.6269,39.9192],[-106.6267,39.925],[-106.6242,40.0005],[-106.6356,40.0002],[-106.636,40.1047],[-106.6358,40.1493],[-106.6368,40.1788],[-106.6319,40.179],[-106.6317,40.1936],[-106.6317,40.2364],[-106.6311,40.2799],[-106.6314,40.324],[-106.6311,40.3414],[-106.652,40.3414],[-106.6515,40.3663],[-106.6514,40.4068],[-106.6516,40.4463],[-106.6493,40.4434],[-106.6489,40.4396],[-106.6405,40.4332],[-106.6334,40.4327],[-106.6223,40.4321],[-106.6206,40.43],[-106.6242,40.4279],[-106.6287,40.4192],[-106.6249,40.4157],[-106.6184,40.4053],[-106.6176,40.4032],[-106.6139,40.3928],[-106.6083,40.3792],[-106.6077,40.3774],[-106.6053,40.3751],[-106.6028,40.3747],[-106.5998,40.3747],[-106.5962,40.3761],[-106.592,40.3783],[-106.5872,40.3793],[-106.5781,40.3784],[-106.5715,40.3771],[-106.5606,40.3776],[-106.5564,40.3763],[-106.5546,40.3749],[-106.5533,40.3726],[-106.5509,40.3699],[-106.5479,40.3681],[-106.5412,40.3659],[-106.5388,40.365],[-106.5334,40.3627],[-106.5309,40.3628],[-106.5291,40.3637],[-106.5285,40.3664],[-106.5274,40.3736],[-106.5256,40.3809],[-106.5232,40.3841],[-106.5209,40.3859],[-106.5197,40.3864],[-106.516,40.3882],[-106.513,40.3887],[-106.51,40.39],[-106.5082,40.3941],[-106.5076,40.3946],[-106.5016,40.3987],[-106.5004,40.4001],[-106.4896,40.4092],[-106.4872,40.4101],[-106.4848,40.4101],[-106.4806,40.4088],[-106.4763,40.4056],[-106.4739,40.402],[-106.4738,40.3983],[-106.478,40.3929],[-106.4774,40.3902],[-106.4726,40.387],[-106.4707,40.3848],[-106.4713,40.3811],[-106.4707,40.3793],[-106.4653,40.3762],[-106.4634,40.3735],[-106.4628,40.3698],[-106.4616,40.3676],[-106.4579,40.3653],[-106.4567,40.363],[-106.4573,40.3603],[-106.4561,40.3576],[-106.4531,40.3558],[-106.4476,40.3495],[-106.4446,40.3481],[-106.4403,40.3481],[-106.4355,40.3495],[-106.4283,40.3518],[-106.4229,40.3514],[-106.4156,40.3496],[-106.4072,40.346],[-106.4023,40.3433],[-106.3993,40.3401],[-106.3956,40.3347],[-106.3932,40.3338],[-106.3914,40.3342],[-106.3902,40.3356],[-106.3902,40.3383],[-106.3909,40.3456],[-106.3897,40.3479],[-106.3824,40.352],[-106.3758,40.3542],[-106.3704,40.3556],[-106.3644,40.3552],[-106.3602,40.3561],[-106.3565,40.3566],[-106.3517,40.3548],[-106.3438,40.3471],[-106.3347,40.3385],[-106.3317,40.3376],[-106.3281,40.3371],[-106.3251,40.3362],[-106.3196,40.334],[-106.3148,40.3313],[-106.3082,40.3295],[-106.3045,40.3295],[-106.3003,40.3304],[-106.2973,40.3313],[-106.2955,40.3327],[-106.2949,40.335],[-106.2955,40.3395],[-106.2968,40.344],[-106.2968,40.3476],[-106.2962,40.3495],[-106.2938,40.3531],[-106.2902,40.3563],[-106.2872,40.3572],[-106.2835,40.3577],[-106.2763,40.3554],[-106.2727,40.3554],[-106.2697,40.3568],[-106.2654,40.3591],[-106.2624,40.3591],[-106.26,40.3582],[-106.2576,40.3554],[-106.2491,40.34],[-106.2412,40.3319],[-106.2346,40.3265],[-106.2309,40.3247],[-106.2279,40.3238],[-106.2249,40.3242],[-106.2207,40.326],[-106.2159,40.327],[-106.211,40.327],[-106.2038,40.3261],[-106.1954,40.3261],[-106.1923,40.3261],[-106.1863,40.3279],[-106.1827,40.3297],[-106.1803,40.3325],[-106.1743,40.342],[-106.1713,40.3438],[-106.1689,40.3443],[-106.1653,40.3443],[-106.1622,40.3429],[-106.158,40.3402],[-106.1544,40.3357],[-106.1507,40.3334],[-106.1471,40.3316],[-106.1417,40.3302],[-106.1357,40.3298],[-106.1339,40.3307],[-106.1327,40.3312],[-106.1321,40.3348],[-106.1314,40.3361],[-106.126,40.338],[-106.123,40.3393],[-106.1188,40.3434],[-106.117,40.3443],[-106.108,40.3484],[-106.1049,40.3507],[-106.1019,40.3525],[-106.0995,40.353],[-106.0977,40.3525],[-106.0917,40.3489],[-106.088,40.3471],[-106.0844,40.3466],[-106.0814,40.3471],[-106.0772,40.3484],[-106.0651,40.3552],[-106.0621,40.3561],[-106.0525,40.358],[-106.0506,40.3584],[-106.041,40.3634],[-106.0356,40.3657],[-106.0265,40.3698],[-106.0235,40.3702],[-106.0199,40.3707],[-106.0163,40.3702],[-106.0126,40.368],[-106.0078,40.363],[-106.006,40.3616],[-106.0036,40.3616],[-105.9994,40.3625],[-105.9939,40.363],[-105.9879,40.362],[-105.9789,40.3593],[-105.9746,40.3571],[-105.9716,40.3548],[-105.9662,40.3475],[-105.962,40.3457],[-105.9608,40.3457],[-105.9584,40.3457],[-105.9553,40.348],[-105.9493,40.358],[-105.9469,40.3602],[-105.9414,40.3611],[-105.9378,40.3625],[-105.9366,40.3643],[-105.9366,40.3666],[-105.9384,40.3693],[-105.9414,40.3711],[-105.9438,40.3729],[-105.9438,40.3752],[-105.9432,40.3793],[-105.942,40.3815],[-105.9396,40.3834],[-105.936,40.3843],[-105.9299,40.387],[-105.9257,40.3892],[-105.9191,40.3974],[-105.9185,40.3979],[-105.9167,40.3988],[-105.9137,40.3983],[-105.9046,40.396],[-105.9028,40.3969],[-105.901,40.4046],[-105.8997,40.4092],[-105.8991,40.4164],[-105.8991,40.4305],[-105.8991,40.4341],[-105.8967,40.445],[-105.8961,40.4568],[-105.8954,40.4627],[-105.8936,40.4677],[-105.8924,40.4686],[-105.8894,40.4718],[-105.8864,40.4736],[-105.8839,40.474],[-105.8791,40.4749],[-105.8664,40.4763],[-105.8598,40.4785],[-105.8537,40.4826],[-105.8513,40.4849],[-105.835,40.4808],[-105.8289,40.4789],[-105.8241,40.4767],[-105.8229,40.4758],[-105.8199,40.4735],[-105.8175,40.4708],[-105.8126,40.4694],[-105.8066,40.4671],[-105.8036,40.4653],[-105.8024,40.463],[-105.8018,40.4585],[-105.8024,40.454],[-105.8042,40.4485],[-105.8097,40.439],[-105.8115,40.4358],[-105.8133,40.4295],[-105.8128,40.4263],[-105.811,40.4227],[-105.8037,40.4145],[-105.7953,40.4036],[-105.7911,40.3968],[-105.7869,40.3855],[-105.7845,40.3805],[-105.7797,40.3732],[-105.7689,40.3646],[-105.7641,40.3591],[-105.7556,40.3527],[-105.7496,40.3487],[-105.7442,40.3473],[-105.737,40.3464],[-105.7339,40.345],[-105.7321,40.3427],[-105.7316,40.3391],[-105.7298,40.3359],[-105.7243,40.3336],[-105.7165,40.3309],[-105.7117,40.3295],[-105.7057,40.3259],[-105.7003,40.3218],[-105.6997,40.32],[-105.7003,40.3159],[-105.7003,40.3136],[-105.6979,40.3109],[-105.6949,40.3091],[-105.6925,40.3077],[-105.6907,40.3059],[-105.6907,40.3036],[-105.6895,40.3018],[-105.6883,40.3],[-105.6877,40.2973],[-105.6877,40.2946],[-105.6865,40.2927],[-105.6847,40.2914],[-105.6847,40.2896],[-105.6853,40.2878],[-105.6854,40.2859],[-105.6848,40.2837],[-105.6806,40.2782],[-105.68,40.2759],[-105.6794,40.2719],[-105.6788,40.2696],[-105.6746,40.2669],[-105.6716,40.2664],[-105.6674,40.2659],[-105.6637,40.2655],[-105.6601,40.2641],[-105.6577,40.2614],[-105.6553,40.2587],[-105.6517,40.255],[-105.6518,40.2527],[-105.653,40.2496],[-105.6566,40.2469],[-105.659,40.2428],[-105.6663,40.2365],[-105.6669,40.2351],[-105.67,40.2174],[-105.6694,40.2142],[-105.6694,40.2115],[-105.67,40.2088],[-105.6724,40.2047],[-105.6749,40.2025],[-105.6767,40.1993],[-105.6773,40.1957],[-105.6761,40.1902],[-105.6738,40.1857],[-105.672,40.1821],[-105.6684,40.1757],[-105.6678,40.1721],[-105.669,40.1684],[-105.669,40.1671],[-105.6696,40.1635],[-105.6684,40.1603],[-105.6661,40.1567],[-105.6595,40.1525],[-105.6535,40.1503],[-105.6438,40.1484],[-105.6396,40.1466],[-105.6307,40.1375],[-105.6283,40.1339],[-105.6253,40.1207],[-105.6254,40.118],[-105.6266,40.1162],[-105.6332,40.1103],[-105.6338,40.1076],[-105.6339,40.1031],[-105.6327,40.0976],[-105.6333,40.0953],[-105.6357,40.0908],[-105.6363,40.0886],[-105.6346,40.0804],[-105.6352,40.0777],[-105.643,40.0668],[-105.6485,40.0614],[-105.6491,40.0573],[-105.6467,40.0528],[-105.6449,40.0491],[-105.6438,40.0473],[-105.6371,40.0446],[-105.6371,40.0432],[-105.6426,40.0337],[-105.648,40.0278],[-105.6505,40.0251],[-105.6517,40.0192],[-105.6523,40.0174],[-105.6571,40.0156],[-105.6751,40.0143],[-105.6823,40.013],[-105.686,40.0098],[-105.6878,40.0057],[-105.6878,40.0012],[-105.6866,39.9976],[-105.6824,39.9907],[-105.6813,39.9853],[-105.6831,39.9717],[-105.6855,39.9654],[-105.6862,39.9631],[-105.6844,39.9567],[-105.6856,39.9536],[-105.6904,39.9491],[-105.691,39.9432],[-105.6911,39.9413],[-105.6899,39.9382],[-105.6857,39.9345],[-105.6743,39.93],[-105.6779,39.9241],[-105.6798,39.9182],[-105.6804,39.9141],[-105.684,39.91],[-105.6864,39.9064],[-105.6895,39.8978],[-105.6925,39.8933],[-105.6955,39.8892],[-105.6955,39.8861],[-105.6961,39.8783],[-105.6955,39.8734],[-105.6926,39.8634],[-105.6908,39.8548],[-105.6884,39.8507],[-105.6903,39.847],[-105.6909,39.8434],[-105.6927,39.838],[-105.6963,39.8357],[-105.7005,39.8348],[-105.7053,39.8348],[-105.7095,39.8362],[-105.7125,39.8362],[-105.7143,39.8349],[-105.7161,39.8312],[-105.7167,39.8258],[-105.7203,39.8204],[-105.7257,39.8149],[-105.7311,39.8086],[-105.733,39.8054],[-105.7359,39.8032],[-105.7414,39.8009],[-105.7539,39.7973],[-105.7623,39.7951],[-105.7659,39.7951],[-105.7755,39.7983],[-105.7779,39.7992],[-105.7862,39.8015],[-105.7934,39.8019],[-105.7982,39.8015],[-105.8018,39.7997],[-105.806,39.7961],[-105.8108,39.7906],[-105.8156,39.7879],[-105.8222,39.7861],[-105.8264,39.7861],[-105.8408,39.7884],[-105.8449,39.7884],[-105.8473,39.7884],[-105.8485,39.7898],[-105.8539,39.7948],[-105.8569,39.7961],[-105.8737,39.797],[-105.8814,39.7971],[-105.885,39.7962],[-105.8856,39.7934],[-105.8856,39.7907],[-105.8856,39.788],[-105.8892,39.7835],[-105.8898,39.7812],[-105.8887,39.7785],[-105.8857,39.7748],[-105.8851,39.7712],[-105.8827,39.7653],[-105.8803,39.7621],[-105.8785,39.7603],[-105.8785,39.7585],[-105.8803,39.7553],[-105.8821,39.7517],[-105.8821,39.7495],[-105.8809,39.7463],[-105.8803,39.7422],[-105.8803,39.7381],[-105.8821,39.7349],[-105.8863,39.7318],[-105.8911,39.7295],[-105.8995,39.7291],[-105.9025,39.7277],[-105.9043,39.725],[-105.9055,39.7205],[-105.9103,39.7155],[-105.9157,39.7109],[-105.9193,39.7069],[-105.9211,39.7005],[-105.9211,39.6969],[-105.93,39.6937],[-105.9378,39.6897],[-105.9402,39.6892],[-105.9432,39.6897],[-105.945,39.691],[-105.9468,39.6928],[-105.9492,39.6928],[-105.9569,39.6919],[-105.9623,39.6906],[-105.9701,39.6897],[-105.9784,39.6879],[-105.9886,39.6847],[-105.9946,39.6838],[-106.0065,39.6847],[-106.0149,39.686],[-106.0215,39.6892],[-106.0269,39.6933],[-106.0316,39.6987],[-106.037,39.7069],[-106.0394,39.7123],[-106.0424,39.716],[-106.0496,39.7223],[-106.0538,39.7237],[-106.0556,39.7255],[-106.0574,39.7291],[-106.0604,39.7418],[-106.0646,39.7576],[-106.0736,39.7776],[-106.0772,39.7858],[-106.079,39.7939],[-106.0814,39.8012],[-106.0856,39.8057],[-106.094,39.8138],[-106.103,39.8211],[-106.1126,39.8283],[-106.1192,39.8347],[-106.1246,39.8406],[-106.1282,39.8428],[-106.1336,39.8424],[-106.1395,39.8405],[-106.1425,39.8396],[-106.1461,39.8392],[-106.1539,39.841],[-106.1701,39.845],[-106.1827,39.8514],[-106.1899,39.8563],[-106.1977,39.8631],[-106.2025,39.8708],[-106.2073,39.8776],[-106.2145,39.884],[-106.2229,39.8908],[-106.2284,39.8971],[-106.2338,39.903],[-106.2404,39.9075],[-106.2482,39.912],[-106.2578,39.9152],[-106.2692,39.916],[-106.289,39.916],[-106.2938,39.916],[-106.313,39.9155],[-106.3956,39.9144],[-106.3953,39.9249],[-106.4343,39.9249]]]},\"properties\":{\"name\":\"Eagle\",\"state\":\"CO\"}}]}","contact":"

Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225

","tableOfContents":"","publishedDate":"2020-07-31","noUsgsAuthors":false,"publicationDate":"2020-07-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Kohn, Michael S. 0000-0002-5989-7700 mkohn@usgs.gov","orcid":"https://orcid.org/0000-0002-5989-7700","contributorId":4549,"corporation":false,"usgs":true,"family":"Kohn","given":"Michael","email":"mkohn@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":794469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marineau, Mathieu D. 0000-0002-6568-0743 mmarineau@usgs.gov","orcid":"https://orcid.org/0000-0002-6568-0743","contributorId":4954,"corporation":false,"usgs":true,"family":"Marineau","given":"Mathieu","email":"mmarineau@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":794470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hempel, Laura A. 0000-0001-5020-6056","orcid":"https://orcid.org/0000-0001-5020-6056","contributorId":224286,"corporation":false,"usgs":true,"family":"Hempel","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":794471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McDonald, Richard R. 0000-0002-0703-0638 rmcd@usgs.gov","orcid":"https://orcid.org/0000-0002-0703-0638","contributorId":2428,"corporation":false,"usgs":true,"family":"McDonald","given":"Richard","email":"rmcd@usgs.gov","middleInitial":"R.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":794472,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70211568,"text":"ofr20201052 - 2020 - Calibration of the U.S. Geological Survey National Crustal Model","interactions":[],"lastModifiedDate":"2020-08-05T18:39:28.395394","indexId":"ofr20201052","displayToPublicDate":"2020-07-31T12:40:00","publicationYear":"2020","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":"2020-1052","displayTitle":"Calibration of the U.S. Geological Survey National Crustal Model","title":"Calibration of the U.S. Geological Survey National Crustal Model","docAbstract":"

The U.S. Geological Survey National Crustal Model (NCM) is being developed to include spatially varying estimates of site response in seismic hazard assessments. Primary outputs of the NCM are continuous velocity and density profiles from the Earth’s surface to the mantle transition zone at 410-kilometer (km) depth for each location on a 1-km grid across the conterminous United States. Datasets used to produce the NCM may have a resolution of better than 1 km near the Earth’s surface in some regions, but, with increasing depth, NCM resolution decreases to tens to hundreds of kilometers in the mantle. Basic subsurface information is provided by the NCM geologic framework, thermal model, and petrologic and mineral physics database. In this report, the velocities and densities that can be extracted from the NCM are calibrated through the development of a porosity model based on Biot-Gassmann theory and more than 2,000 compressional- and (or) shear-wave velocity profiles less than 10 km deep from across the conterminous United States and southwestern Canada.

Sediment and rock porosities are derived from shear-wave velocity and are found to depend on effective pressure, rock type, and age (for sedimentary and extrusive volcanic deposits). Porosity-effective pressure functions are then estimated for each rock type (and age for sedimentary and extrusive volcanic deposits). Unconsolidated sediments are found to have higher porosities than consolidated units, which have higher porosities than unweathered igneous units; young sedimentary units (for example, Quaternary age units) tend to have higher porosities than older sedimentary units (for example, pre-Cenozoic age units); porosity decreases with increasing effective pressure; and porosities can decrease quickly through the weathered layer of intrusive rocks.

Comparing two Los Angeles area velocity models and the U.S. Geological Survey Bay Area velocity model with the NCM, the NCM does a better job on average of reproducing observed shear-wave velocities below 1 km per second because it has less bias and uncertainty. Approaching and above 1 km per second, the NCM tends to underpredict observed shear-wave velocity. Whereas several factors could contribute to this, the primary factor is probably bias in the NCM geologic framework. For example, the NCM will predict lower velocities in places where the depth to bedrock and basement appear shallower in the measured velocity profiles than specified in the NCM geologic framework. With regard to observed compressional-wave velocity and density, the NCM has significantly less bias than California models for the former, especially below 2 km per second, and all models tend to overpredict density for densities less than about 2,200 kilograms per cubic meter.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201052","usgsCitation":"Boyd, O.S., 2020, Calibration of the U.S. Geological Survey National Crustal Model: U.S. Geological Survey Open-File Report 2020–1052, 23 p., https://doi.org/10.3133/ofr20201052.","productDescription":"Report: vi, 23 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-115717","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":436847,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NQ5LNU","text":"USGS data release","linkHelpText":"GeoPhys"},{"id":376928,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1052/ofr20201052.pdf","text":"Report","size":"6.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1052"},{"id":376929,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GO3CP8","text":"USGS data release","linkHelpText":"Calibration Coefficients for the U.S. Geological Survey National Crustal Model and Depth to Water Table"},{"id":376927,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1052/coverthb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -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":"

Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS-966
Denver, CO 80225-0046

","tableOfContents":"","publishedDate":"2020-07-31","noUsgsAuthors":false,"publicationDate":"2020-07-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":794641,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70227404,"text":"70227404 - 2020 - Radiocarbon dating of tsunami and storm deposits","interactions":[],"lastModifiedDate":"2022-01-14T14:13:31.416486","indexId":"70227404","displayToPublicDate":"2020-07-31T07:10:09","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"30","title":"Radiocarbon dating of tsunami and storm deposits","docAbstract":"

Radiocarbon age determinations can be an expedient and accurate means to assign age to deposits of tsunami or storm origin. Essential to the process of incorporating radiocarbon age determinations in tsunami or coastal storm investigations is an awareness on the part of the investigator that a sample will always return an age from a laboratory, but only carefully selected samples inform deposit age. Samples that inform deposit age are of two fundamentally different sample types, in-growth-position samples and detrital samples. For both in-growth-position samples and detrital samples, stratigraphic context is the critical information needed to evaluate how well sample age can constrain deposit age. Well constrained deposit ages require bracketing samples collected to provide both maximum and minimum limiting ages for the deposit(s) of interest. Therefore, sampling should be carried out with the intention of multiple sample submissions for age in order to optimize the potential for acquiring closely limiting ages. If there are multiple age determinations within a stratigraphic sequence that contains tsunami or storm deposits, then the calibrated radiocarbon ages can be, and should be, framed within a Bayesian model structure to better constrain deposit ages. Such models can be further improved by the incorporation of independent stratigraphic age information.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geological records of tsunamis and other extreme waves","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-815686-5.00030-4","usgsCitation":"Kelsey, H., and Witter, R., 2020, Radiocarbon dating of tsunami and storm deposits, chap. 30 of Geological records of tsunamis and other extreme waves, p. 663-685, https://doi.org/10.1016/B978-0-12-815686-5.00030-4.","productDescription":"23 p.","startPage":"663","endPage":"685","ipdsId":"IP-108632","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":394307,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kelsey, Harvey M.","contributorId":206893,"corporation":false,"usgs":false,"family":"Kelsey","given":"Harvey M.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":830756,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":830757,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70211444,"text":"ofr20201082 - 2020 - seawaveQ—An R package providing a model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables, version 2.0.0","interactions":[],"lastModifiedDate":"2020-08-04T20:24:39.347599","indexId":"ofr20201082","displayToPublicDate":"2020-07-30T09:24:24","publicationYear":"2020","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":"2020-1082","displayTitle":"seawaveQ—An R Package Providing a Model and Utilities for Analyzing Trends in Chemical Concentrations in Streams with a Seasonal Wave (seawave) and Adjustment for Streamflow (Q) and Other Ancillary Variables, Version 2.0.0","title":"seawaveQ—An R package providing a model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables, version 2.0.0","docAbstract":"

The seawaveQ R package provides functionality and help to fit a parametric regression model, SEAWAVE-Q, to pesticide concentration data from stream-water samples to assess trends. The model incorporates the strong seasonality and high degree of censoring common in pesticide data, and users can incorporate numerous ancillary variables such as streamflow anomalies. The model is fitted to pesticide data using maximum likelihood methods for censored data and is robust in terms of pesticide, stream location, and degree of censoring of the concentration data. This R package standardizes this methodology for trend analysis, documents the code, and provides help and tutorial information.

In previous investigations, the SEAWAVE-Q model assumed a linear trend across the period analyzed. For short trend periods, this assumption of a linear trend is adequate. However, as the period of record analyzed becomes longer, the assumption of linearity is problematic because of changes in pesticide regulation and use, some of which can be abrupt. In this update to the model, a restricted cubic spline option was added for long trend periods. This option allows for more flexibility in the time component of the model. Bootstrap functionality is included to determine statistical significance. Model results with the new restricted cubic spline option are compared to the linear trend option for two pesticide-site combinations.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201082","collaboration":"National Water Quality Program","usgsCitation":"Ryberg, K.R., and York, B.C., 2020, seawaveQ—An R package providing a model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables, version 2.0.0: U.S. Geological Survey Open-File Report 2020–1082, 25 p., https://doi.org/10.3133/ofr20201082.","productDescription":"Report: vi, 25; 3 Appendixes","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-101011","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":376796,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1082/ofr20201082_appendix_1.pdf","text":"Appendix 1.","size":"356 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1082 Appendix 1","linkHelpText":"— Vignette for seawaveQ—An R Package Providing a Model and Utilities for Analyzing Trends in Chemical Concentrations in Streams with a Seasonal Wave (seawave) and Adjustment for Streamflow (Q) and Other Ancillary Variables"},{"id":376797,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1082/ofr20201082_appendix_2.pdf","text":"Appendix 2.","size":"228 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1082 Appendix 2","linkHelpText":"— R Documentation"},{"id":376798,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1082/ofr20201082_appendix_4.pdf","text":"Appendix 4.","size":"1.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1082 Appendix 4","linkHelpText":"— Model Comparisons Using seawaveQ"},{"id":376794,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1082/coverthb.jpg"},{"id":376795,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1082/ofr20201082.pdf","text":"Report","size":"2.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1082"}],"contact":"

Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503

1608 Mountain View Road
Rapid City, SD

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-07-30","noUsgsAuthors":false,"publicationDate":"2020-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":794150,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"York, Benjamin C. 0000-0002-3449-3574 byork@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-3574","contributorId":213613,"corporation":false,"usgs":true,"family":"York","given":"Benjamin","email":"byork@usgs.gov","middleInitial":"C.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":794151,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70211992,"text":"70211992 - 2020 - Implanted satellite transmitters affect sea duck movement patterns at short- and long-term time scales","interactions":[],"lastModifiedDate":"2020-09-23T15:55:41.727144","indexId":"70211992","displayToPublicDate":"2020-07-30T07:59:46","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1318,"text":"Condor","active":true,"publicationSubtype":{"id":10}},"title":"Implanted satellite transmitters affect sea duck movement patterns at short- and long-term time scales","docAbstract":"Studies of the effects of transmitters on wildlife often focus on survival. However, non-lethal behavioral changes resulting from radiomarking have the potential to affect inferences from telemetry data and may vary based on individual and environmental characteristics. We used a long-term, multi-species tracking study of sea ducks to assess behavioral patterns at multiple temporal scales following implantation of intracoelomic satellite transmitters. We applied state-space models to assess short-term behavioral patterns in individuals with implanted satellite transmitters, as well as comparing breeding site attendance and migratory phenology across multiple years after capture. In the short term, our results suggest an increase in dispersive behavior immediately following capture and transmitter implantation; however, behavior returned to seasonally-average patterns within approximately five days after release. Over multiple years, we found that breeding site attendance by both males and females was depressed during the first breeding season after radiomarking relative to subsequent years, with larger relative decreases in breeding site attendance among males than females. We also found that spring migration occurred later in the first year after radiomarking than in subsequent years. Across all behavioral effects, the severity of behavioral change often varied by species, sex, age, and capture season, suggesting heterogeneity in individual sensitivity. We conclude that, although individuals appear to adjust relatively quickly (i.e., within one week) to implanted satellite transmitters, changes in breeding phenology may occur over the longer term and should be considered when analyzing and reporting telemetry data.","language":"English","publisher":"Oxford Academic","doi":"10.1093/condor/duaa029","usgsCitation":"Lamb, J.S., Paton, P.W., Osenkowski, J.E., Badzinski, S.S., Berlin, A., Bowman, T.D., Dwyer, C., Fara, L., Gilliland, S.G., Kenow, K.P., Lepage, C., Mallory, M.L., Olsen, G.H., Perry, M., Petrie, S.A., Savard, J.L., Savoy, L., Schummer, M.L., Spiegel, C.S., and McWilliams, S.R., 2020, Implanted satellite transmitters affect sea duck movement patterns at short- and long-term time scales: Condor, duaa029, 16 p., https://doi.org/10.1093/condor/duaa029.","productDescription":"duaa029, 16 p.","ipdsId":"IP-117761","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":455822,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/condor/duaa029","text":"Publisher Index Page"},{"id":377482,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2020-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Lamb, Juliet S. 0000-0003-0358-3240","orcid":"https://orcid.org/0000-0003-0358-3240","contributorId":198059,"corporation":false,"usgs":false,"family":"Lamb","given":"Juliet","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":796120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paton, Peter WC","contributorId":216933,"corporation":false,"usgs":false,"family":"Paton","given":"Peter","email":"","middleInitial":"WC","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":796121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Osenkowski, Jason E.","contributorId":216934,"corporation":false,"usgs":false,"family":"Osenkowski","given":"Jason","email":"","middleInitial":"E.","affiliations":[{"id":39552,"text":"Rhode Island Department of Environmental Management","active":true,"usgs":false}],"preferred":false,"id":796122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Badzinski, Shannon S.","contributorId":176348,"corporation":false,"usgs":false,"family":"Badzinski","given":"Shannon","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":796123,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Berlin, Alicia 0000-0002-5275-3077 aberlin@usgs.gov","orcid":"https://orcid.org/0000-0002-5275-3077","contributorId":168416,"corporation":false,"usgs":true,"family":"Berlin","given":"Alicia","email":"aberlin@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":796124,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bowman, Timothy D.","contributorId":80779,"corporation":false,"usgs":false,"family":"Bowman","given":"Timothy","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":796125,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dwyer, Chris","contributorId":177908,"corporation":false,"usgs":false,"family":"Dwyer","given":"Chris","affiliations":[],"preferred":false,"id":796126,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fara, Luke J. 0000-0002-1143-4395","orcid":"https://orcid.org/0000-0002-1143-4395","contributorId":202973,"corporation":false,"usgs":true,"family":"Fara","given":"Luke J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":796127,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gilliland, Scott G.","contributorId":216936,"corporation":false,"usgs":false,"family":"Gilliland","given":"Scott","email":"","middleInitial":"G.","affiliations":[{"id":12590,"text":"Canadian Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":796128,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kenow, Kevin P. 0000-0002-3062-5197 kkenow@usgs.gov","orcid":"https://orcid.org/0000-0002-3062-5197","contributorId":3339,"corporation":false,"usgs":true,"family":"Kenow","given":"Kevin","email":"kkenow@usgs.gov","middleInitial":"P.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":796129,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lepage, Christine","contributorId":194564,"corporation":false,"usgs":false,"family":"Lepage","given":"Christine","email":"","affiliations":[],"preferred":false,"id":796130,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mallory, Mark L.","contributorId":127438,"corporation":false,"usgs":false,"family":"Mallory","given":"Mark","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":796131,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Olsen, Glenn H. 0000-0002-7188-6203","orcid":"https://orcid.org/0000-0002-7188-6203","contributorId":238130,"corporation":false,"usgs":true,"family":"Olsen","given":"Glenn","email":"","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":796132,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Perry, Matthew 0000-0001-6452-9534 mperry@usgs.gov","orcid":"https://orcid.org/0000-0001-6452-9534","contributorId":179173,"corporation":false,"usgs":true,"family":"Perry","given":"Matthew","email":"mperry@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":796133,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Petrie, Scott A.","contributorId":141223,"corporation":false,"usgs":false,"family":"Petrie","given":"Scott","email":"","middleInitial":"A.","affiliations":[{"id":13717,"text":"Long Point Waterfowl","active":true,"usgs":false}],"preferred":false,"id":796134,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Savard, Jean-Pierre L.","contributorId":101776,"corporation":false,"usgs":false,"family":"Savard","given":"Jean-Pierre","email":"","middleInitial":"L.","affiliations":[{"id":6962,"text":"Science and Technology Branch, Environment Canada","active":true,"usgs":false}],"preferred":false,"id":796135,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Savoy, Lucas","contributorId":171896,"corporation":false,"usgs":false,"family":"Savoy","given":"Lucas","affiliations":[{"id":6928,"text":"BioDiversity Research Institute, Gorham, ME 04038","active":true,"usgs":false}],"preferred":false,"id":796136,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Schummer, Michael L.","contributorId":176347,"corporation":false,"usgs":false,"family":"Schummer","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":796137,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Spiegel, Caleb S.","contributorId":216938,"corporation":false,"usgs":false,"family":"Spiegel","given":"Caleb","email":"","middleInitial":"S.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":796138,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"McWilliams, Scott R.","contributorId":172328,"corporation":false,"usgs":false,"family":"McWilliams","given":"Scott","email":"","middleInitial":"R.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":796139,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70211224,"text":"sir20205055 - 2020 - Estimating streamflow and base flow within the nontidal Chesapeake Bay riverine system","interactions":[],"lastModifiedDate":"2021-07-02T13:31:15.859682","indexId":"sir20205055","displayToPublicDate":"2020-07-30T05:47:08","publicationYear":"2020","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":"2020-5055","displayTitle":"Estimating Streamflow and Base Flow Within the Nontidal Chesapeake Bay Riverine System","title":"Estimating streamflow and base flow within the nontidal Chesapeake Bay riverine system","docAbstract":"

Daily mean streamflow was estimated for all the nontidal parts of the Chesapeake Bay riverine system with the Unit Flows in Networks of Channels computer application using measured streamflow at the most downstream gage of selected rivers. The streamflows estimated by the Unit Flows in Networks of Channels computer application were aggregated at the 12-digit Hydrologic Unit Code level, after which base flow was estimated by two hydrograph-separation methods. Based on six sites selected for comparison, modeled streamflows are typically within an order of magnitude of measured streamflows, and monthly mean streamflows are in better agreement than daily streamflows. For the six selected sites, the base-flow values calculated by the two hydrograph-separation methods were compared. The monthly base-flow values also were in better agreement than the daily base-flow values. The modeled data were animated to better visualize spatial and temporal variability of streamflow and base-flow index.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205055","usgsCitation":"Buffington, P.C., and Capel, P.D., 2020, Estimating streamflow and base flow within the nontidal Chesapeake Bay riverine system: U.S. Geological Survey Scientific Investigations Report 2020–5055, 26 p., https://doi.org/10.3133/sir20205055.","productDescription":"Report: v, 26 p.; Figure Animations: Figures 15–18; Data Release","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-098068","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":376516,"rank":8,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS water data for the Nation","linkHelpText":"— National Water Information System database"},{"id":376515,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P906K5GZ","text":"USGS data release","description":"USGS data release","linkHelpText":"Datasets and scripts used for estimating streamflow and base flow within the nontidal Chesapeake Bay riverine system, water years 2006–15"},{"id":376514,"rank":6,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2020/5055/sir20205055_fig18_animation.mp4","text":"Figure 18 Animation","size":"56.7 MB","description":"SIR 2020–5055 Figure 18","linkHelpText":"— Monthly base-flow index animation for the nontidal Chesapeake Bay watershed outside of the Susquehanna watershed."},{"id":376513,"rank":5,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2020/5055/sir20205055_fig17_animation.mp4","text":"Figure 17 Animation","size":"45.2 MB","description":"SIR 2020–5055 Figure 17","linkHelpText":"— Monthly mean streamflow animation for the nontidal Chesapeake Bay watershed outside of the Susquehanna watershed."},{"id":376512,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2020/5055/sir20205055_fig16_animation.mp4","text":"Figure 16 Animation","size":"56.6 MB","description":"SIR 2020–5055 Figure 16","linkHelpText":"— Monthly base-flow index (BFI) animation for the watershed of the Susquehanna River, upstream from Harrisburg, Pennsylvania."},{"id":376511,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2020/5055/sir20205055_fig15_animation.mp4","text":"Figure 15 Animation","size":"51.0 MB","description":"SIR 2020–5055 Figure 15","linkHelpText":"— Monthly mean streamflow animation for the watershed of the Susquehanna River, upstream from Harrisburg, Pennsylvania."},{"id":376510,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5055/sir20205055.pdf","text":"Report","size":"3.70 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5055"},{"id":376509,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5055/coverthb2.jpg"}],"country":"United States","state":"Delaware, Maryland, New York, Pennsylvania, Virginia, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.1904296875,\n 38.41916639395372\n ],\n [\n -75.223388671875,\n 38.64261790634527\n ],\n [\n -75.35522460937499,\n 38.79690830348427\n ],\n [\n -75.498046875,\n 38.87392853923629\n ],\n [\n -75.5419921875,\n 39.0533181067413\n ],\n [\n -75.662841796875,\n 39.30029918615029\n ],\n [\n -75.750732421875,\n 39.70718665682654\n ],\n [\n -75.6298828125,\n 40.052847601823984\n ],\n [\n -75.69580078125,\n 40.07807142745009\n ],\n [\n -75.95947265625,\n 40.052847601823984\n ],\n [\n -76.0693359375,\n 40.069664523297774\n ],\n [\n -76.058349609375,\n 40.18726672309203\n ],\n [\n -75.9375,\n 40.29628651711716\n ],\n [\n -75.91552734375,\n 40.3549167507906\n ],\n [\n -75.89355468749999,\n 40.47202439692057\n ],\n [\n -76.09130859375,\n 40.56389453066509\n ],\n [\n -76.190185546875,\n 40.64730356252251\n ],\n [\n -76.0693359375,\n 40.75557964275589\n ],\n [\n -75.83862304687499,\n 40.871987756697415\n ],\n [\n -75.76171875,\n 40.91351257612758\n ],\n [\n -75.706787109375,\n 40.95501133048621\n ],\n [\n -75.7177734375,\n 41.071069130806414\n ],\n [\n -75.662841796875,\n 41.1455697310095\n ],\n [\n -75.5419921875,\n 41.13729606112276\n ],\n [\n -75.322265625,\n 41.104190944576466\n ],\n [\n -75.377197265625,\n 41.22824901518529\n ],\n [\n -75.377197265625,\n 41.28606238749825\n ],\n [\n -75.377197265625,\n 41.43449030894922\n ],\n [\n -75.399169921875,\n 41.6154423246811\n ],\n [\n -75.34423828125,\n 41.68111756290652\n ],\n [\n -75.2783203125,\n 41.91045347666418\n ],\n [\n -75.38818359375,\n 42.00848901572399\n ],\n [\n -75.377197265625,\n 42.09007006868398\n ],\n [\n -75.223388671875,\n 42.17968819665961\n ],\n [\n -74.970703125,\n 42.26917949243506\n ],\n [\n -74.8388671875,\n 42.32606244456202\n ],\n [\n -74.520263671875,\n 42.415346114253616\n ],\n [\n -74.278564453125,\n 42.54498667313236\n ],\n [\n -74.322509765625,\n 42.64204079304426\n ],\n [\n -74.410400390625,\n 42.80346172417078\n ],\n [\n -74.68505859374999,\n 42.924251753870685\n ],\n [\n -75.069580078125,\n 42.98053954751642\n ],\n [\n -75.38818359375,\n 42.96446257387128\n ],\n [\n -75.684814453125,\n 42.93229601903058\n ],\n [\n -75.9375,\n 42.87596410238256\n ],\n [\n -76.201171875,\n 42.827638636242284\n ],\n [\n -76.26708984375,\n 42.72280375732727\n ],\n [\n -76.2890625,\n 42.601619944327965\n ],\n [\n -76.2890625,\n 42.52069952914966\n ],\n [\n -76.343994140625,\n 42.415346114253616\n ],\n [\n -76.46484375,\n 42.382894009614034\n ],\n [\n -76.640625,\n 42.431565872579185\n ],\n [\n -76.7724609375,\n 42.39912215986002\n ],\n [\n -76.80541992187499,\n 42.24478535602799\n ],\n [\n -76.88232421875,\n 42.285437007491545\n ],\n [\n -76.9482421875,\n 42.415346114253616\n ],\n [\n -77.04711914062499,\n 42.44778143462245\n ],\n [\n -77.14599609375,\n 42.415346114253616\n ],\n [\n -77.2998046875,\n 42.382894009614034\n ],\n [\n -77.222900390625,\n 42.54498667313236\n ],\n [\n -77.442626953125,\n 42.69858589169842\n ],\n [\n -77.574462890625,\n 42.60970621339408\n ],\n [\n -77.640380859375,\n 42.48830197960227\n ],\n [\n -77.728271484375,\n 42.439674178149424\n ],\n [\n -77.6513671875,\n 42.31793945446847\n ],\n [\n -77.596435546875,\n 42.22851735620852\n ],\n [\n -77.5634765625,\n 42.09007006868398\n ],\n [\n -77.6953125,\n 41.92680320648791\n ],\n [\n -77.9150390625,\n 41.83682786072714\n ],\n [\n -78.0908203125,\n 41.795888098191426\n ],\n [\n -78.453369140625,\n 41.599013054830216\n ],\n [\n -78.453369140625,\n 41.50857729743935\n ],\n [\n -78.42041015625,\n 41.376808565702355\n ],\n [\n -78.3984375,\n 41.21172151054787\n ],\n [\n -78.519287109375,\n 41.054501963290505\n ],\n [\n -78.541259765625,\n 40.9218144123785\n ],\n [\n -78.409423828125,\n 40.713955826286046\n ],\n [\n -78.299560546875,\n 40.55554790286311\n ],\n [\n -78.343505859375,\n 40.48873742102282\n ],\n [\n -78.475341796875,\n 40.30466538259176\n ],\n [\n -78.64013671875,\n 40.06125658140474\n ],\n [\n -78.826904296875,\n 39.9434364619742\n ],\n [\n -78.848876953125,\n 39.80853604144591\n ],\n [\n -78.85986328125,\n 39.715638134796336\n ],\n [\n -78.99169921875,\n 39.69873414348139\n ],\n [\n -79.046630859375,\n 39.64799732373418\n ],\n [\n -79.266357421875,\n 39.436192999314095\n ],\n [\n -79.420166015625,\n 39.2832938689385\n ],\n [\n -79.354248046875,\n 39.26628442213066\n ],\n [\n -79.266357421875,\n 39.232253141714885\n ],\n [\n -79.2333984375,\n 39.155622393423215\n ],\n [\n -79.244384765625,\n 39.01918369029134\n ],\n [\n -79.27734374999999,\n 38.89103282648846\n ],\n [\n -79.398193359375,\n 38.74551518488265\n ],\n [\n -79.661865234375,\n 38.54816542304656\n ],\n [\n -79.683837890625,\n 38.47079371120379\n ],\n [\n -79.727783203125,\n 38.34165619279595\n ],\n [\n -79.815673828125,\n 38.20365531807149\n ],\n [\n -80.04638671875,\n 38.013476231041935\n ],\n [\n -80.17822265625,\n 37.779398571318765\n ],\n [\n -80.2880859375,\n 37.59682400108367\n ],\n [\n -80.4638671875,\n 37.47485808497102\n ],\n [\n -80.694580078125,\n 37.38761749978395\n ],\n [\n -80.771484375,\n 37.23032838760387\n ],\n [\n -80.57373046875,\n 37.26530995561875\n ],\n [\n -80.44189453125,\n 37.309014074275915\n ],\n [\n -80.255126953125,\n 37.31775185163688\n ],\n [\n -80.013427734375,\n 37.3002752813443\n ],\n [\n -79.8486328125,\n 37.23907530202184\n ],\n [\n -79.771728515625,\n 37.18657859524883\n ],\n [\n -79.6728515625,\n 37.07271048132943\n ],\n [\n -79.541015625,\n 37.09900294387622\n ],\n [\n -79.354248046875,\n 37.142803443716836\n ],\n [\n -79.1455078125,\n 37.10776507118514\n ],\n [\n -79.112548828125,\n 37.055177106660814\n ],\n [\n -78.936767578125,\n 36.932330061503144\n ],\n [\n -78.837890625,\n 36.94111143010769\n ],\n [\n -78.662109375,\n 37.055177106660814\n ],\n [\n -78.486328125,\n 37.03763967977139\n ],\n [\n -78.42041015625,\n 36.94111143010769\n ],\n [\n -78.20068359374999,\n 36.96744946416934\n ],\n [\n -77.904052734375,\n 37.03763967977139\n ],\n [\n -77.750244140625,\n 37.081475648860525\n ],\n [\n -77.53051757812499,\n 37.081475648860525\n ],\n [\n -77.354736328125,\n 37.07271048132943\n ],\n [\n -77.069091796875,\n 37.081475648860525\n ],\n [\n -76.959228515625,\n 37.01132594307015\n ],\n [\n -76.893310546875,\n 36.932330061503144\n ],\n [\n -76.871337890625,\n 36.83566824724438\n ],\n [\n -76.849365234375,\n 36.677230602346214\n ],\n [\n -76.7724609375,\n 36.527294814546245\n ],\n [\n -76.629638671875,\n 36.55377524336089\n ],\n [\n -76.46484375,\n 36.589068371399115\n ],\n [\n -76.35498046875,\n 36.48314061639213\n ],\n [\n -76.256103515625,\n 36.57142382346277\n ],\n [\n -76.190185546875,\n 36.66841891894786\n ],\n [\n -76.0693359375,\n 36.65079252503471\n ],\n [\n -75.9375,\n 36.66841891894786\n ],\n [\n -75.948486328125,\n 36.76529191711624\n ],\n [\n -75.904541015625,\n 37.01132594307015\n ],\n [\n -75.926513671875,\n 37.17782559332976\n ],\n [\n -75.882568359375,\n 37.42252593456307\n ],\n [\n -75.618896484375,\n 37.640334898059486\n ],\n [\n -75.509033203125,\n 37.82280243352756\n ],\n [\n -75.38818359375,\n 38.013476231041935\n ],\n [\n -75.16845703124999,\n 38.272688535980976\n ],\n [\n -75.1904296875,\n 38.41916639395372\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

U.S. Geological Survey
National Water-Quality Assessment (NAWQA) Science Team
12201 Sunrise Valley Drive
Reston, VA 20192

https://water.usgs.gov/nawqa/

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-07-30","noUsgsAuthors":false,"publicationDate":"2020-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Buffington, Patrick C.","contributorId":229470,"corporation":false,"usgs":false,"family":"Buffington","given":"Patrick","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":793268,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Capel, Paul D. 0000-0003-1620-5185 capel@usgs.gov","orcid":"https://orcid.org/0000-0003-1620-5185","contributorId":1002,"corporation":false,"usgs":true,"family":"Capel","given":"Paul","email":"capel@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":793267,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216379,"text":"70216379 - 2020 - Life at the frozen limit: Microbial carbon metabolism across a Late Pleistocene permafrost chronosequence","interactions":[],"lastModifiedDate":"2020-11-13T15:09:56.965257","indexId":"70216379","displayToPublicDate":"2020-07-29T09:00:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1702,"text":"Frontiers in Microbiology","onlineIssn":"1664-302X","active":true,"publicationSubtype":{"id":10}},"title":"Life at the frozen limit: Microbial carbon metabolism across a Late Pleistocene permafrost chronosequence","docAbstract":"

Permafrost is an extreme habitat yet it hosts microbial populations that remain active over millennia. Using permafrost collected from a Pleistocene chronosequence (19 to 33 ka), we hypothesized that the functional genetic potential of microbial communities in permafrost would reflect microbial strategies to metabolize permafrost soluble organic matter (OM) in situ over geologic time. We also hypothesized that changes in the metagenome across the chronosequence would correlate with shifts in carbon chemistry, permafrost age, and paleoclimate at the time of permafrost formation. We combined high-resolution characterization of water-soluble OM by Fourier-transform ion-cyclotron-resonance mass spectrometry (FT-ICR MS), quantification of organic anions in permafrost water extracts, and metagenomic sequencing to better understand the relationships between the molecular-level composition of potentially bioavailable OM, the microbial community, and permafrost age. Both age and paleoclimate had marked effects on both the molecular composition of dissolved OM and the microbial community. The relative abundance of genes associated with hydrogenotrophic methanogenesis, carbohydrate active enzyme families, nominal oxidation state of carbon (NOSC), and number of identifiable molecular formulae significantly decreased with increasing age. In contrast, genes associated with fermentation of short chain fatty acids (SCFAs), the concentration of SCFAs and ammonium all significantly increased with age. We present a conceptual model of microbial metabolism in permafrost based on fermentation of OM and the buildup of organic acids that helps to explain the unique chemistry of ancient permafrost soils. These findings imply long-term in situ microbial turnover of ancient permafrost OM and that this pooled biolabile OM could prime ancient permafrost soils for a larger and more rapid microbial response to thaw compared to younger permafrost soils.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmicb.2020.01753","usgsCitation":"Leewis, M., Berlemont, R., Podgorski, D.C., Srinivas, A., Zito, P., Spencer, R.G., McFarland, J., Douglas, T.A., Conaway, C., Waldrop, M., and Mackelprang, R., 2020, Life at the frozen limit: Microbial carbon metabolism across a Late Pleistocene permafrost chronosequence: Frontiers in Microbiology, v. 11, 1753, 15 p., https://doi.org/10.3389/fmicb.2020.01753.","productDescription":"1753, 15 p.","ipdsId":"IP-114701","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":455834,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmicb.2020.01753","text":"Publisher Index Page"},{"id":436855,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P933APLH","text":"USGS data release","linkHelpText":"Microbial Carbon and Nitrogen Metabolism Across a Late Pleistocene Permafrost Chronosequence"},{"id":436854,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P933APLH","text":"USGS data release","linkHelpText":"Microbial Carbon and Nitrogen Metabolism Across a Late Pleistocene Permafrost Chronosequence"},{"id":380506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Fairbanks","otherGeospatial":"Cold Regions Research and Engineering Laboratory","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -147.8814697265625,\n 64.82616499475317\n ],\n [\n -147.5148010253906,\n 64.82616499475317\n ],\n [\n -147.5148010253906,\n 64.98807019388211\n ],\n [\n -147.8814697265625,\n 64.98807019388211\n ],\n [\n -147.8814697265625,\n 64.82616499475317\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2020-07-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Leewis, Mary-Cathrine 0000-0001-6496-8094","orcid":"https://orcid.org/0000-0001-6496-8094","contributorId":244858,"corporation":false,"usgs":true,"family":"Leewis","given":"Mary-Cathrine","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":804829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berlemont, Renaud 0000-0001-9243-5092","orcid":"https://orcid.org/0000-0001-9243-5092","contributorId":244872,"corporation":false,"usgs":false,"family":"Berlemont","given":"Renaud","email":"","affiliations":[{"id":34411,"text":"California State University Long Beach","active":true,"usgs":false}],"preferred":false,"id":804830,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Podgorski, David C.","contributorId":178153,"corporation":false,"usgs":false,"family":"Podgorski","given":"David","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":804831,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Srinivas, Archana","contributorId":244875,"corporation":false,"usgs":false,"family":"Srinivas","given":"Archana","email":"","affiliations":[{"id":49006,"text":"Department of Biology, California State University Northridge, Northridge, CA, USA","active":true,"usgs":false}],"preferred":false,"id":804832,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zito, Phoebe","contributorId":206101,"corporation":false,"usgs":false,"family":"Zito","given":"Phoebe","email":"","affiliations":[{"id":37245,"text":"University of New Orleans","active":true,"usgs":false}],"preferred":false,"id":804833,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spencer, Robert G. M. 0000-0003-0777-0748","orcid":"https://orcid.org/0000-0003-0777-0748","contributorId":238028,"corporation":false,"usgs":false,"family":"Spencer","given":"Robert","email":"","middleInitial":"G. M.","affiliations":[{"id":47686,"text":"Department of Earth, Ocean and Atmospheric Science, Florida State University","active":true,"usgs":false}],"preferred":false,"id":804834,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McFarland, Jack 0000-0001-9672-8597","orcid":"https://orcid.org/0000-0001-9672-8597","contributorId":214819,"corporation":false,"usgs":true,"family":"McFarland","given":"Jack","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":804835,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Douglas, Thomas A. 0000-0003-1314-1905","orcid":"https://orcid.org/0000-0003-1314-1905","contributorId":64553,"corporation":false,"usgs":false,"family":"Douglas","given":"Thomas","email":"","middleInitial":"A.","affiliations":[{"id":33087,"text":"Cold Regions Research and Engineering Laboratory","active":true,"usgs":false}],"preferred":true,"id":804836,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Conaway, Christopher H. 0000-0002-0991-033X","orcid":"https://orcid.org/0000-0002-0991-033X","contributorId":201932,"corporation":false,"usgs":true,"family":"Conaway","given":"Christopher H.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":804837,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Waldrop, Mark 0000-0003-1829-7140","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":216758,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","affiliations":[],"preferred":true,"id":804838,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mackelprang, Rachel","contributorId":200882,"corporation":false,"usgs":false,"family":"Mackelprang","given":"Rachel","email":"","affiliations":[{"id":7080,"text":"California State University, Northridge","active":true,"usgs":false}],"preferred":false,"id":804839,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70220672,"text":"70220672 - 2020 - Pulsed Mesozoic deformation in the Cordilleran hinterland and evolution of the Nevadaplano: Insights from the Pequop Mountains, NE Nevada","interactions":[],"lastModifiedDate":"2021-05-25T13:00:03.956533","indexId":"70220672","displayToPublicDate":"2020-07-29T07:54:15","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Pulsed Mesozoic deformation in the Cordilleran hinterland and evolution of the Nevadaplano: Insights from the Pequop Mountains, NE Nevada","docAbstract":"

Mesozoic crustal shortening in the North American Cordillera’s hinterland was related to the construction of the Nevadaplano orogenic plateau. Petrologic and geochemical proxies in Cordilleran core complexes suggest substantial Late Cretaceous crustal thickening during plateau construction. In eastern Nevada, geobarometry from the Snake Range and Ruby Mountains-East Humboldt Range-Wood Hills-Pequop Mountains (REWP) core complexes suggests that the ~10–12 km thick Neoproterozoic-Triassic passive-margin sequence was buried to great depths (>30 km) during Mesozoic shortening and was later exhumed to the surface via high-magnitude Cenozoic extension. Deep regional burial is commonly reconciled with structural models involving cryptic thrust sheets, such as the hypothesized Windermere thrust in the REWP. We test the viability of deep thrust burial by examining the least-deformed part of the REWP in the Pequop Mountains. Observations include a compilation of new and published peak temperature estimates (⁠n=60\">n=60n=60⁠) spanning the Neoproterozoic-Triassic strata, documentation of critical field relationships that constrain deformation style and timing, and new 40Ar/39Ar ages. This evidence refutes models of deep regional thrust burial, including (1) recognition that most contractional structures in the Pequop Mountains formed in the Jurassic, not Cretaceous, and (2) peak temperature constraints and field relationships are inconsistent with deep burial. Jurassic deformation recorded here correlates with coeval structures spanning western Nevada to central Utah, which highlights that Middle-Late Jurassic shortening was significant in the Cordilleran hinterland. These observations challenge commonly held views for the Mesozoic-early Cenozoic evolution of the REWP and Cordilleran hinterland, including the timing of contractional strain, temporal evolution of plateau growth, and initial conditions for high-magnitude Cenozoic extension. The long-standing differences between peak-pressure estimates and field relationships in Nevadan core complexes may reflect tectonic overpressure.

","language":"English","publisher":"Geological Society of America","doi":"10.2113/2020/8850336","usgsCitation":"Zuza, A.V., Thorman, C.H., Henry, C., Levy, D.A., Dee, S., Long, S.P., Sandberg, C., and Soignard, E., 2020, Pulsed Mesozoic deformation in the Cordilleran hinterland and evolution of the Nevadaplano: Insights from the Pequop Mountains, NE Nevada: Geosphere, v. 2020, no. 1, 8850336, 24 p., https://doi.org/10.2113/2020/8850336.","productDescription":"8850336, 24 p.","ipdsId":"IP-119785","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":455838,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2113/2020/8850336","text":"Publisher Index Page"},{"id":385917,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Pequop Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.95520019531249,\n 39.86758762451019\n ],\n [\n -114.1094970703125,\n 39.86758762451019\n ],\n [\n -114.1094970703125,\n 41.306697618181865\n ],\n [\n -115.95520019531249,\n 41.306697618181865\n ],\n [\n -115.95520019531249,\n 39.86758762451019\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2020","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-07-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Zuza, Andrew V","contributorId":258288,"corporation":false,"usgs":false,"family":"Zuza","given":"Andrew","email":"","middleInitial":"V","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":816373,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thorman, Charles H. 0000-0002-1269-1393","orcid":"https://orcid.org/0000-0002-1269-1393","contributorId":258289,"corporation":false,"usgs":true,"family":"Thorman","given":"Charles","email":"","middleInitial":"H.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":816376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henry, Christopher D.","contributorId":175501,"corporation":false,"usgs":false,"family":"Henry","given":"Christopher D.","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":816374,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Levy, Drew A.","contributorId":258372,"corporation":false,"usgs":false,"family":"Levy","given":"Drew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":816426,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dee, Seth","contributorId":248823,"corporation":false,"usgs":false,"family":"Dee","given":"Seth","email":"","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":816375,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Long, Sean P.","contributorId":193434,"corporation":false,"usgs":false,"family":"Long","given":"Sean","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":816427,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sandberg, Charles sandberg@usgs.gov","contributorId":199124,"corporation":false,"usgs":true,"family":"Sandberg","given":"Charles","email":"sandberg@usgs.gov","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":816428,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Soignard, Emmanuel","contributorId":258373,"corporation":false,"usgs":false,"family":"Soignard","given":"Emmanuel","email":"","affiliations":[],"preferred":false,"id":816429,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70211634,"text":"70211634 - 2020 - Legacy effects of hydrologic alteration in playa wetland responses to droughts","interactions":[],"lastModifiedDate":"2020-12-29T21:21:31.795804","indexId":"70211634","displayToPublicDate":"2020-07-28T15:46:12","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Legacy effects of hydrologic alteration in playa wetland responses to droughts","docAbstract":"

Wetland conservation increasingly must account for climate change and legacies of previous land-use practices. Playa wetlands provide critical wildlife habitat, but may be impacted by intensifying droughts and previous hydrologic modifications. To inform playa restoration planning, we asked: (1) what are the trends in playa inundation? (2) what are the factors influencing inundation? (3) how is playa inundation affected by increasingly severe drought? (4) do certain playas provide hydrologic refugia during droughts, and (5) if so, how are refugia patterns related to historical modifications? Using remotely sensed surface-water data, we evaluated a 30-year time series (1985–2015) of inundation for 153 playas of the Great Basin, USA. Inundation likelihood and duration increased with wetter weather conditions and were greater in modified playas. Inundation probability was projected to decrease from 22% under average conditions to 11% under extreme drought, with respective annual inundation decreasing from 1.7 to 0.9 months. Only 4% of playas were inundated for at least 2 months in each of the 5 driest years, suggesting their potential as drought refugia. Refugial playas were larger and more likely to have been modified, possibly because previous land managers selected refugial playas for modification. These inundation patterns can inform efforts to restore wetland functions and to conserve playa habitats as climate conditions change.

","language":"English","publisher":"Springer","doi":"10.1007/s13157-020-01334-0","usgsCitation":"Russell, M.T., Cartwright, J.M., Collins, G.H., Long, R.A., and Eitel, J., 2020, Legacy effects of hydrologic alteration in playa wetland responses to droughts: Wetlands, v. 40, p. 2011-2024, https://doi.org/10.1007/s13157-020-01334-0.","productDescription":"14 p.","startPage":"2011","endPage":"2024","ipdsId":"IP-111867","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":455846,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13157-020-01334-0","text":"Publisher Index Page"},{"id":377103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Oregon","otherGeospatial":"Sheldon-Hart Mountain National Wildlife Refuge Complex","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.96246337890624,\n 41.52091689636249\n ],\n [\n -118.69354248046875,\n 41.52091689636249\n ],\n [\n -118.69354248046875,\n 42.84777884235988\n ],\n [\n -119.96246337890624,\n 42.84777884235988\n ],\n [\n -119.96246337890624,\n 41.52091689636249\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","noUsgsAuthors":false,"publicationDate":"2020-07-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Russell, Micah T.","contributorId":236988,"corporation":false,"usgs":false,"family":"Russell","given":"Micah","email":"","middleInitial":"T.","affiliations":[{"id":38118,"text":"Western Colorado University","active":true,"usgs":false}],"preferred":false,"id":794877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cartwright, Jennifer M. 0000-0003-0851-8456 jmcart@usgs.gov","orcid":"https://orcid.org/0000-0003-0851-8456","contributorId":5386,"corporation":false,"usgs":true,"family":"Cartwright","given":"Jennifer","email":"jmcart@usgs.gov","middleInitial":"M.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":794878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collins, Gail H.","contributorId":59170,"corporation":false,"usgs":false,"family":"Collins","given":"Gail","email":"","middleInitial":"H.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":794879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Long, Ryan A.","contributorId":236989,"corporation":false,"usgs":false,"family":"Long","given":"Ryan","email":"","middleInitial":"A.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":794880,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eitel, Jan H.","contributorId":236991,"corporation":false,"usgs":false,"family":"Eitel","given":"Jan H.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":794881,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211358,"text":"70211358 - 2020 - Quantifying development to inform management of Mojave and Sonoran desert tortoise habitat in the American southwest","interactions":[],"lastModifiedDate":"2020-08-27T14:47:07.029758","indexId":"70211358","displayToPublicDate":"2020-07-28T13:40:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying development to inform management of Mojave and Sonoran desert tortoise habitat in the American southwest","docAbstract":"Two tortoise species native to the American southwest have experienced significant habitat loss from development and are vulnerable to ongoing threats associated with continued development. Mojave desert tortoises Gopherus agassizii are listed as threatened under the US Endangered Species Act, and Sonoran desert tortoises G. morafkai are protected in Arizona (USA) and Mexico. Substantial habitat for both species occurs on multiple-use public lands, where development associated with traditional and renewable energy production, recreation, and other activities is likely to continue. Our goal was to quantify development to inform and evaluate actions implemented to protect and manage desert tortoise habitat. We quantified a landscape-level index of development across the Mojave and Sonoran desert tortoise ranges using models of potential habitat for each species (152485 total observations). We used 13 years of Mojave desert tortoise monitoring data (4732 observations) to inform the levels and spatial scales at which tortoises may be affected by development. Most (66–70%) desert tortoise habitat has some development within 1 km. Development levels on desert tortoise habitat are lower inside versus outside areas protected by actions at national, state, and local levels, suggesting that protection efforts may be having the desired effects and providing a needed baseline for future effectiveness evaluations. Of the relatively undeveloped desert tortoise habitat, 43% (74030 km2) occurs outside of existing protections. These lands are managed by multiple federal, state, and local entities and private landowners, and may provide opportunities for future land acquisition or protection, including as mitigation for energy development on public lands.","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr01045","usgsCitation":"Carter, S.K., Nussear, K., Esque, T., Leinwand, I.I., Masters, E.H., Inman, R.D., Carr, N.B., and Allison, L.J., 2020, Quantifying development to inform management of Mojave and Sonoran desert tortoise habitat in the American southwest: Endangered Species Research, v. 42, p. 167-184, https://doi.org/10.3354/esr01045.","productDescription":"18 p.","startPage":"167","endPage":"184","ipdsId":"IP-088248","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":455849,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01045","text":"Publisher Index Page"},{"id":377921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada, Utah","otherGeospatial":"Mojave Desert, Sonoran Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.137451171875,\n 31.868227816180674\n ],\n [\n -110.863037109375,\n 34.134541681937364\n ],\n [\n -112.34619140625,\n 35.69299463209881\n ],\n [\n -113.785400390625,\n 36.85325222344018\n ],\n [\n -113.48876953125,\n 37.69251435532741\n ],\n [\n -115.68603515624999,\n 38.40194908237822\n ],\n [\n -119.10278320312499,\n 38.35027253825765\n ],\n [\n -119.871826171875,\n 38.20365531807149\n ],\n [\n -118.30078125,\n 35.639441068973944\n ],\n [\n -115.29052734375,\n 32.667124733120325\n ],\n [\n -112.181396484375,\n 31.737511125687828\n ],\n [\n -112.137451171875,\n 31.868227816180674\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Carter, Sarah K. 0000-0003-3778-8615","orcid":"https://orcid.org/0000-0003-3778-8615","contributorId":192418,"corporation":false,"usgs":true,"family":"Carter","given":"Sarah","email":"","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":794011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nussear, Kenneth","contributorId":194538,"corporation":false,"usgs":false,"family":"Nussear","given":"Kenneth","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":794012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":794013,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leinwand, Ian IF","contributorId":229704,"corporation":false,"usgs":false,"family":"Leinwand","given":"Ian","email":"","middleInitial":"IF","affiliations":[{"id":41706,"text":"Cherokee Services Group Inc.","active":true,"usgs":false}],"preferred":false,"id":794014,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Masters, Elroy H.","contributorId":229705,"corporation":false,"usgs":false,"family":"Masters","given":"Elroy","email":"","middleInitial":"H.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":794015,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Inman, Richard D. 0000-0002-1982-7791 rdinman@usgs.gov","orcid":"https://orcid.org/0000-0002-1982-7791","contributorId":187754,"corporation":false,"usgs":true,"family":"Inman","given":"Richard","email":"rdinman@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":794016,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carr, Natasha B. 0000-0002-4842-0632 carrn@usgs.gov","orcid":"https://orcid.org/0000-0002-4842-0632","contributorId":1918,"corporation":false,"usgs":true,"family":"Carr","given":"Natasha","email":"carrn@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":794017,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Allison, Linda J. 0000-0003-1983-901X","orcid":"https://orcid.org/0000-0003-1983-901X","contributorId":229706,"corporation":false,"usgs":false,"family":"Allison","given":"Linda","email":"","middleInitial":"J.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":794018,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70227774,"text":"70227774 - 2020 - Vegetation sampling and management","interactions":[],"lastModifiedDate":"2022-01-31T17:47:50.412067","indexId":"70227774","displayToPublicDate":"2020-07-28T11:39:15","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"19","title":"Vegetation sampling and management","docAbstract":"What is the utility of vegetation measurements for wildlife managers? In the prairie, savanna, tundra, forest, steppe, and wetland regions of the world, mixtures of plant species provide wildlife with food, cover and, in some circumstances, water; the 3 essential habitat elements necessary to sustain viable wildlife populations. We define habitat in reference to use of a vegetation type by an animal (e.g., deer habitat) and vegetation type when referring to differences in vegetation stands (e.g., marsh vegetation type versus tall grass prairie vegetation type; Hall et al. 1997). In strict definition, the variety of wildlife using plants ranges from snails and voles (Microtus spp.) to bison (Bison bison) and elephants (Loxodonta spp.) in uplands and from mosquitoes and ducks to muskrats (Ondatra zibethicus) and manatees (Trichechus manatus) in wetlands. Through evolutionary processes, some wildlife species are totally dependent on vegetation for all annual life requirements, whereas other species use vegetation only for cover or food. Regardless of the role of vegetation in the sustenance of wildlife, any management or research project that requires evaluation of wildlife and vegetation type relationships on a unit of land will necessitate some form of vegetation measurement.\nThe term vegetation can refer to a single plant or species on a specific site or a community in the landscape. Vegetation may occur naturally or be introduced, and may be live or dead. Uses of vegetation measurements are many: (1) evaluation of vegetation response to management practices, (2) estimation of carrying capacity and/or forage production, (3) characterization of cover and habitat components for an endangered species, or (4) long-term monitoring of the general trend of plant vigor or vegetation type condition.\nSurveying and measuring quantity and quality of vegetation within habitats are basic to wildlife research and management. Grassland, shrubland, and woodland vegetation types are comprised of populations in which individual plants are usually too numerous to inventory completely. Consequently, wildlife biologists usually use sampling techniques to make inferences about the total plant population within a given vegetation type.\nVegetation sampling methodologies have evolved within several ecological disciplines (e.g., plant ecology, forestry, rangeland science) and for a variety of management or research objectives (e.g., estimating forage for ungulates, describing habitat use by passerine birds). Description of every method that has been used to sample vegetation is beyond the scope of this chapter. We describe how to measure vegetation structure, which Dansereau (1957) defined as the spatial organization (distribution) of individuals that form a stand. We have organized this chapter into a description of basic methods of vegetation sampling with examples of how those methods have been applied or modified in wildlife research and management. We assume the investigator/reader has adequate knowledge of the concepts of wildlife ecology, primary habitat requirements of wildlife species under study, and ability to systematically identify the species of wildlife and vascular plants within the geographical area of investigation.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The wildlife techniques manual. Volume 1: Research. Volume 2: Management.","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Johns Hopkins University Press","collaboration":"The Wildlife Society","usgsCitation":"Higgins, K., Jenkins, K., Uresk, D.W., Perkins, L.B., Jensen, K., Norland, J., Klaver, R.W., and Naugle, D.E., 2020, Vegetation sampling and management, chap. 19 of The wildlife techniques manual. Volume 1: Research. Volume 2: Management., p. 409-438.","productDescription":"30 p.","startPage":"409","endPage":"438","ipdsId":"IP-092410","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"links":[{"id":395165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Higgins, Kenneth F.","contributorId":272584,"corporation":false,"usgs":false,"family":"Higgins","given":"Kenneth F.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":832179,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkins, Kurt 0000-0003-1415-6607","orcid":"https://orcid.org/0000-0003-1415-6607","contributorId":221472,"corporation":false,"usgs":true,"family":"Jenkins","given":"Kurt","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":832183,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Uresk, Daniel W.","contributorId":272585,"corporation":false,"usgs":false,"family":"Uresk","given":"Daniel","email":"","middleInitial":"W.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":832181,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perkins, Lora B.","contributorId":272586,"corporation":false,"usgs":false,"family":"Perkins","given":"Lora","email":"","middleInitial":"B.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":832182,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jensen, Kent C.","contributorId":272587,"corporation":false,"usgs":false,"family":"Jensen","given":"Kent C.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":832184,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Norland, Jack E.","contributorId":272588,"corporation":false,"usgs":false,"family":"Norland","given":"Jack E.","affiliations":[{"id":12471,"text":"North Dakota State University","active":true,"usgs":false}],"preferred":false,"id":832185,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832180,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Naugle, David E.","contributorId":272589,"corporation":false,"usgs":false,"family":"Naugle","given":"David","email":"","middleInitial":"E.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":832186,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70223184,"text":"70223184 - 2020 - Cryptic evolved melts beneath monotonous basaltic shield volcanoes in the Galápagos Archipelago","interactions":[],"lastModifiedDate":"2021-08-17T13:35:37.373175","indexId":"70223184","displayToPublicDate":"2020-07-28T07:49:53","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Cryptic evolved melts beneath monotonous basaltic shield volcanoes in the Galápagos Archipelago","docAbstract":"

Many volcanoes erupt compositionally homogeneous magmas over timescales ranging from decades to millennia. This monotonous activity is thought to reflect a high degree of chemical homogeneity in their magmatic systems, leading to predictable eruptive behaviour. We combine petrological analyses of erupted crystals with new thermodynamic models to characterise the diversity of melts in magmatic systems beneath monotonous shield volcanoes in the Galápagos Archipelago (Wolf and Fernandina). In contrast with the uniform basaltic magmas erupted at the surface over long timescales, we find that the sub-volcanic systems contain extreme heterogeneity, with melts extending to rhyolitic compositions. Evolved melts are in low abundance and large volumes of basalt flushing through the crust from depth overprint their chemical signatures. This process will only maintain monotonous activity while the volume of melt entering the crust is high, raising the possibility of transitions to more silicic activity given a decrease in the crustal melt flux.

","language":"English","publisher":"Nature","doi":"10.1038/s41467-020-17590-x","usgsCitation":"Stock, M., Geist, D., Neave, D., Gleason, M., Bernard, B., Howard, K.A., Buisman, I., and Maclennan, J., 2020, Cryptic evolved melts beneath monotonous basaltic shield volcanoes in the Galápagos Archipelago: Nature Communications, v. 11, 3767, 13 p., https://doi.org/10.1038/s41467-020-17590-x.","productDescription":"3767, 13 p.","ipdsId":"IP-121924","costCenters":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":455855,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-020-17590-x","text":"Publisher Index Page"},{"id":387984,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Galápagos Archipelago","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.92260742187499,\n -1.7136116598836224\n ],\n [\n -88.83544921874999,\n -1.7136116598836224\n ],\n [\n -88.83544921874999,\n 0.7470491450051796\n ],\n [\n -91.92260742187499,\n 0.7470491450051796\n ],\n [\n -91.92260742187499,\n -1.7136116598836224\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2020-07-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Stock, M.J.","contributorId":264294,"corporation":false,"usgs":false,"family":"Stock","given":"M.J.","email":"","affiliations":[{"id":54430,"text":"Trinity College, Dublin","active":true,"usgs":false}],"preferred":false,"id":821300,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Geist, D.","contributorId":264295,"corporation":false,"usgs":false,"family":"Geist","given":"D.","affiliations":[{"id":12642,"text":"National Science Foundation","active":true,"usgs":false}],"preferred":false,"id":821301,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Neave, DA","contributorId":264296,"corporation":false,"usgs":false,"family":"Neave","given":"DA","email":"","affiliations":[{"id":27871,"text":"University of Manchester","active":true,"usgs":false}],"preferred":false,"id":821302,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gleason, M.L.M .","contributorId":264297,"corporation":false,"usgs":false,"family":"Gleason","given":"M.L.M","email":"","middleInitial":".","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":821303,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bernard, B.","contributorId":264298,"corporation":false,"usgs":false,"family":"Bernard","given":"B.","email":"","affiliations":[{"id":54432,"text":"Escuela Politecnica Nacional, Quito","active":true,"usgs":false}],"preferred":false,"id":821304,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Howard, Keith A. 0000-0002-6462-2947 khoward@usgs.gov","orcid":"https://orcid.org/0000-0002-6462-2947","contributorId":3439,"corporation":false,"usgs":true,"family":"Howard","given":"Keith","email":"khoward@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":821305,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Buisman, I.","contributorId":264299,"corporation":false,"usgs":false,"family":"Buisman","given":"I.","email":"","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":821306,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Maclennan, J.","contributorId":264300,"corporation":false,"usgs":false,"family":"Maclennan","given":"J.","affiliations":[{"id":54433,"text":"Uiversity of Cambridge","active":true,"usgs":false}],"preferred":false,"id":821307,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70211334,"text":"sir20205056 - 2020 - Geochemical assessment of the Hueco Bolson, New Mexico and Texas, 2016–17","interactions":[],"lastModifiedDate":"2020-07-28T14:48:03.82138","indexId":"sir20205056","displayToPublicDate":"2020-07-28T06:33:22","publicationYear":"2020","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":"2020-5056","displayTitle":"Geochemical Assessment of the Hueco Bolson, New Mexico and Texas, 2016–17","title":"Geochemical assessment of the Hueco Bolson, New Mexico and Texas, 2016–17","docAbstract":"

Understanding groundwater quality in transboundary aquifers like the Hueco Bolson is important for the 2.7 million people along the United States and Mexico border living in and near the combined metropolitan areas of Ciudad Juárez, Mexico, and El Paso, Texas, who rely on groundwater for water supply. To better understand water-quality conditions in the Mexico–New Mexico–Texas transboundary area, 23 water-supply wells were sampled in the Hueco Bolson within the United States near El Paso, Tex., during August–September 2016 and May–June 2017. Groundwater samples were analyzed for physical properties, major ions, dissolved solids, nutrients, trace elements, organic compounds, and selected isotopes such as strontium, hydrogen, oxygen, tritium, and carbon-14.

Most of the water samples from the Hueco Bolson water-supply wells were classified as a sodium-chloride type water. Only four wells sampled in the study area had dissolved-solids concentrations greater than 1,000 milligrams per liter (mg/L), with three of those wells closest to the Rio Grande/Río Bravo del Norte (hereinafter referred to as the Rio Grande).

Nitrate concentrations in the groundwater samples collected in the study area ranged from below the long-term method detection level of 0.04 to 6.2 mg/L. Arsenic was the only trace element detected in the wells sampled that had concentrations exceeding the designated drinking-water standard of 10 micrograms per liter (μg/L). Four of the 23 wells had arsenic concentrations greater than 10 μg/L, and these wells were all located near the Rio Grande. Three of the wells with the highest uranium concentrations (greater than 10 μg/L) were also located near the Rio Grande, and two of those wells were the same wells that had arsenic concentrations greater than 10 μg/L. Groundwater samples were analyzed for 83 organic compounds, but only 6 were detected—simazine, prometryn, prometon, atrazine, deethylatrazine, and dichloroaniline. All concentrations for the organic compounds detected were less than 0.03 μg/L, and the detections were only in five groundwater wells, three of which were located near the Rio Grande.

Strontium, hydrogen, and oxygen isotopic values indicate that recharge water to the central and northern sections of the study area originates from near the Franklin Mountains, whereas groundwater in the southern section of the study area is likely from the Rio Grande valley. Tritium and carbon-14 values indicate that most of the wells that were sampled contained water that is considered premodern, which means that it is more than several hundred years old. Three wells with modern groundwater (approximately less than 70 years old) are located near the Rio Grande and are the same wells that had elevated arsenic or uranium concentrations and organic compound detections. Most of the results of the geochemical analyses indicate that groundwater near the Rio Grande has higher dissolved-solids concentrations, higher concentrations of several trace elements, and slightly more organic compound detections than the groundwater farther away from the Rio Grande; therefore, the groundwater may be affected by the Rio Grande and surrounding land-use activities.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205056","usgsCitation":"Ging, P.B., Humberson, D.G., and Ikard, S.J., 2020, Geochemical assessment of the Hueco Bolson, New Mexico and Texas, 2016–17: U.S. Geological Survey Scientific Investigations Report 2020–5056, 30 p., https://doi.org/10.3133/sir20205056.","productDescription":"Report: viii, 30 p.; Data Release","numberOfPages":"42","onlineOnly":"N","ipdsId":"IP-112001","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":376690,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5056/sir20205056.pdf","text":"Report","size":"5.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 22020–5056"},{"id":376689,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5056/coverthb.jpg"},{"id":376691,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73T9GHR","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Transboundary Aquifer Assessment Program—Water-quality data from groundwater wells in the Hueco Bolson near El Paso, Texas, August 2016–June 2017"}],"country":"United States","state":"New Mexico, Texas","otherGeospatial":"Hueco Bolson","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.4462890625,\n 31.12819929911196\n ],\n [\n -105.53466796874999,\n 31.12819929911196\n ],\n [\n -105.53466796874999,\n 32.491230287947594\n ],\n [\n -107.4462890625,\n 32.491230287947594\n ],\n [\n -107.4462890625,\n 31.12819929911196\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-07-28","noUsgsAuthors":false,"publicationDate":"2020-07-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Ging, Patricia B. 0000-0001-5491-8448 pbging@usgs.gov","orcid":"https://orcid.org/0000-0001-5491-8448","contributorId":1788,"corporation":false,"usgs":true,"family":"Ging","given":"Patricia","email":"pbging@usgs.gov","middleInitial":"B.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":793823,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Humberson, Delbert G. 0000-0001-6789-9135","orcid":"https://orcid.org/0000-0001-6789-9135","contributorId":97201,"corporation":false,"usgs":true,"family":"Humberson","given":"Delbert G.","affiliations":[],"preferred":false,"id":793824,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ikard, Scott J. 0000-0002-8304-4935","orcid":"https://orcid.org/0000-0002-8304-4935","contributorId":207285,"corporation":false,"usgs":true,"family":"Ikard","given":"Scott","email":"","middleInitial":"J.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":793825,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70274309,"text":"70274309 - 2020 - Linking magma storage and ascent to eruption volume and composition at an arc caldera","interactions":[],"lastModifiedDate":"2026-03-26T15:46:40.758295","indexId":"70274309","displayToPublicDate":"2020-07-28T00:00:00","publicationYear":"2020","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":"Linking magma storage and ascent to eruption volume and composition at an arc caldera","docAbstract":"

Conceptual models of magma storage and transport under calderas favor a connected system of sills and dikes. These features are individually below the resolution of standard seismic tomography, but radial seismic anisotropy can reveal where they exist in aggregate. We model radial anisotropy at Okmok caldera, Alaska, to demonstrate the presence of a caldera-centered stacked sill complex and surrounding dike system. We show that ascending magma, inferred from seismicity, either intersects the sill complex, resulting in a larger volume eruption of evolved magma, or bypasses the overlying sill complex via dikes, resulting in a low-volume mafic eruption. Our results exemplify how the locations of magma storage and paths of transport impact eruption size and composition. As this type of crustal storage is likely common to many calderas, this analysis offers a potential new framework for volcano observatories to forecast the size of impending eruptions.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GL088122","usgsCitation":"Miller, D., Bennington, N., Haney, M.M., Bedrosian, P.A., Key, K., Thurber, C., Hart, L., and Ohlendorf, S., 2020, Linking magma storage and ascent to eruption volume and composition at an arc caldera: Geophysical Research Letters, v. 47, no. 14, e2020GL088122, 9 p., https://doi.org/10.1029/2020GL088122.","productDescription":"e2020GL088122, 9 p.","ipdsId":"IP-109819","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":501607,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/c8e18fc1eae64dc78c6b03f108287254","text":"External Repository"},{"id":501580,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Aleutian Islands, Okmok caldera","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -167.12198767983367,\n 55.318525399141095\n ],\n [\n -167.12198767983367,\n 53.798526218879715\n ],\n [\n -162.2019428127277,\n 53.798526218879715\n ],\n [\n -162.2019428127277,\n 55.318525399141095\n ],\n [\n -167.12198767983367,\n 55.318525399141095\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"47","issue":"14","noUsgsAuthors":false,"publicationDate":"2020-07-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, David","contributorId":367856,"corporation":false,"usgs":false,"family":"Miller","given":"David","affiliations":[{"id":34113,"text":"University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":957822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bennington, Ninfa","contributorId":367857,"corporation":false,"usgs":false,"family":"Bennington","given":"Ninfa","affiliations":[{"id":34113,"text":"University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":957823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":957824,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":957825,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Key, Kerry","contributorId":367858,"corporation":false,"usgs":false,"family":"Key","given":"Kerry","affiliations":[{"id":28041,"text":"Lamont-Doherty Earth Observatory, Columbia University","active":true,"usgs":false}],"preferred":false,"id":957826,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thurber, Cliff","contributorId":367859,"corporation":false,"usgs":false,"family":"Thurber","given":"Cliff","affiliations":[{"id":34113,"text":"University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":957827,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hart, Laney","contributorId":367860,"corporation":false,"usgs":false,"family":"Hart","given":"Laney","affiliations":[{"id":34113,"text":"University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":957828,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ohlendorf, Summer","contributorId":367861,"corporation":false,"usgs":false,"family":"Ohlendorf","given":"Summer","affiliations":[{"id":87631,"text":"National Tsunami Warning Center","active":true,"usgs":false}],"preferred":false,"id":957829,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70211345,"text":"sir20205072 - 2020 - Quality of pesticide data for groundwater analyzed for the National Water-Quality Assessment Project, 2013–18","interactions":[],"lastModifiedDate":"2021-05-27T13:25:01.758364","indexId":"sir20205072","displayToPublicDate":"2020-07-27T15:40:18","publicationYear":"2020","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":"2020-5072","displayTitle":"Quality of Pesticide Data for Groundwater Analyzed for the National Water-Quality Assessment Project, 2013–18","title":"Quality of pesticide data for groundwater analyzed for the National Water-Quality Assessment Project, 2013–18","docAbstract":"

The National Water-Quality Assessment (NAWQA) Project of the U.S. Geological Survey (USGS) submitted nearly 1,900 samples collected from groundwater sites across the United States in 2013–18 for analysis of 225 pesticide compounds (pesticides and pesticide degradates, hereafter referred to as “pesticides”) by USGS National Water Quality Laboratory schedule 2437 (S2437). For the associated NAWQA study of pesticide occurrence and concentration in groundwater, and for other studies using pesticide results determined by S2437, it is necessary to assess the ability of reported results to meet data-quality requirements that will allow study objectives to be achieved. This assessment of the quality of S2437 results reported in 2013–18 examined data from field and laboratory quality-control samples, along with third-party performance assessment samples, to estimate bias and variability and to identify their potential sources, with an emphasis on implications for the interpretation of pesticide data for groundwater. Results indicate that measurements produced by the S2437 method for most pesticides have bias and variability that would be considered acceptable for many interpretative studies, which could therefore use the results without qualification or censoring. However, the reported data for a subset of pesticides have the potential for unacceptable contamination bias, high or low recovery bias, or high variability as a consequence of method performance and (or) nonlaboratory factors that could preclude their use for certain common objectives or could necessitate adjustment or qualification to meet those objectives.

Based on data for laboratory blanks, censoring of some detections for a subset of pesticides reported by the laboratory in environmental samples might be necessary or desirable to avoid an unacceptably high likelihood of a false-positive result caused by laboratory contamination. The 90-percent upper confidence limit for the 95th percentile of laboratory blank concentration equals or exceeds the minimum reported groundwater concentration in at least 1 water year for 28 pesticides. During at least 1 water year, this upper confidence limit exceeds the maximum laboratory detection limit for 17 pesticides and exceeds the maximum laboratory reporting limit for 3 pesticides (ametryn, atrazine, and diazinon). The level of contamination indicated by this upper confidence limit should not substantially affect the suitability of reported environmental concentrations for any compound for comparison with corresponding human-health benchmarks.

Despite being subjected to the same laboratory processes as laboratory blanks, field blanks indicated little evidence of contamination bias. This observation could largely be the consequence of data-reporting practices, which utilize detections in laboratory blanks to censor results in associated field samples (including blanks and environmental samples) when relative concentrations indicate that a result could have a substantial contribution from laboratory contamination. Laboratory censoring appears likely to reduce the risk of false-positive results in environmental samples below the level that laboratory blank results alone would imply.

Whereas data available for third-party blind blank samples analyzed in 2018 indicate that only propoxur had any false-positive results, data for pesticides that were not spiked into blind spike samples analyzed in 2013–18 indicate that the false-positive rates for 31 pesticides exceeded 1 percent when considering only detections reported at concentrations greater than the maximum detection limit. Although about half of these pesticides lack substantial supporting evidence of contamination bias based on laboratory blank or field blank detections, indicating that spiking issues or degradation of parent compounds within the spiked samples might be a contributing factor to some false-positive results, these results indicate the need to closely examine detections reported for some pesticides in environmental samples analyzed during a similar period for possible contributions from contamination bias. Data for blind spike samples that were spiked at concentrations above the maximum reporting limit indicate that false-negative rates for eight pesticides exceed 10 percent; substantial low bias could affect results reported for these pesticides in environmental samples analyzed during a similar period.

Data for laboratory reagent spikes, which measure recovery of pesticides in blank water, show little evidence for unacceptable recovery bias for S2437 pesticides. However, field matrix spikes, which measure recovery of pesticides in environmental matrices, indicate that degradation and (or) matrix effects could result in moderate to substantial low bias for groundwater results for several pesticides. Low bias could cause some reported concentrations to be categorized as being below a benchmark when the actual concentration in groundwater is greater than the benchmark. Occurrence and concentrations in groundwater could be substantially underrepresented for six pesticides with benchmarks (1H-1,2,4-triazole, asulam, bifenthrin, cis-permethrin, fenbutatin oxide, and naled) that have median recoveries between zero and 50 percent in field matrix spikes. Two compounds (didealkylatrazine and 2-hydroxy-6-ethylamino-4-amino-s-triazine) have median recoveries near or greater than 150 percent in field matrix spikes, indicating a substantial high bias. Plots of data for all spike types show clear changes in the typical recovery with time for some pesticides, which would require further examination for evaluation of temporal trends in environmental concentrations.

Data for laboratory reagent spikes indicate that nearly all S2437 pesticides have acceptable variability resulting from random measurement error. Only two compounds (fenbutatin oxide and naled) have F-pseudosigma values greater than 30 percent for recovery, which implies the potential for relatively high variability in reported concentrations and could affect comparison of concentrations to benchmarks and determination of whether concentrations for samples collected at separate locations or times are truly different with a specified level of confidence. Data for third-party blind spike samples show relatively high variability for a greater number of pesticides, although these results likely reflect the influence of degradation and (or) differences in the magnitude and variability of concentrations used for blind spikes relative to laboratory reagent spikes. Detailed analysis of variability using field replicate data is possible for only 12 pesticides on S2437; low variability in analyte detection and concentration is indicated for most of these pesticides in groundwater.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205072","collaboration":"National Water-Quality Assessment Project","usgsCitation":"Bexfield, L.M., Belitz, K., Sandstrom, M.W., Beaty, D., Medalie, L., Lindsey, B.D., and Nowell, L.H., 2020, Quality of pesticide data for groundwater analyzed for the National Water-Quality Assessment Project, 2013–18: U.S. Geological Survey Scientific Investigations Report 2020–5072, 35 p., https://doi.org/10.3133/sir20205072.","productDescription":"Report: vi, 35 p.; 11 Tables; Data Release","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-111029","costCenters":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":376742,"rank":17,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5072/sir20205072_table11.xlsx","text":"Table 11","size":"34.1 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5072 Table 11","linkHelpText":"— Summary of results of data-quality assessment for schedule 2437 pesticide compounds based on all quality-control sample types, May 2013 through September 2018"},{"id":376741,"rank":16,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5072/sir20205072_table08.csv","text":"Table 8","size":"22.8 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5072 Table 8","linkHelpText":"— Summary statistics for the recovery of schedule 2437 pesticide compounds in field matrix spikes, May 2013 through September 2018"},{"id":376740,"rank":15,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5072/sir20205072_table08.xlsx","text":"Table 8","size":"64.7 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5072 Table 8","linkHelpText":"— Summary statistics for the recovery of schedule 2437 pesticide compounds in field matrix spikes, May 2013 through September 2018"},{"id":376739,"rank":14,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5072/sir20205072_table07.csv","text":"Table 7","size":"22.4 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5072 Table 7","linkHelpText":"— Summary statistics for the recovery of schedule 2437 pesticide compounds in third-party blind spike samples, May 2013 through September 2018"},{"id":376738,"rank":13,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5072/sir20205072_table07.xlsx","text":"Table 7","size":"55.3 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5072 Table 7","linkHelpText":"— Summary statistics for the recovery of schedule 2437 pesticide compounds in third-party blind spike samples, May 2013 through September 2018"},{"id":376737,"rank":12,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5072/sir20205072_table06.csv","text":"Table 6","size":"23.4 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5072 Table 6","linkHelpText":"— Summary statistics for the recovery of schedule 2437 pesticide compounds in laboratory reagent spikes, May 2013 through September 2018"},{"id":376736,"rank":11,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5072/sir20205072_table06.xlsx","text":"Table 6","size":"58.7 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5072 Table 6","linkHelpText":"— Summary statistics for the recovery of schedule 2437 pesticide compounds in laboratory reagent spikes, May 2013 through September 2018"},{"id":376735,"rank":10,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5072/sir20205072_table05.csv","text":"Table 5","size":"19.4 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5072 Table 5","linkHelpText":"— Summary of false-positive and false-negative results for schedule 2437 pesticide compounds based on third-party blind spike samples, May 2013 through September 2018"},{"id":376734,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5072/sir20205072_table05.xlsx","text":"Table 5","size":"47.9 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5072 Table 5","linkHelpText":"— Summary of false-positive and false-negative results for schedule 2437 pesticide compounds based on third-party blind spike samples, May 2013 through September 2018"},{"id":376733,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5072/sir20205072_table04.csv","text":"Table 4","size":"54.7 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5072 Table 4","linkHelpText":"— Comparison of the 90-percent upper confidence limit for the 90th, 95th, and 99th percentiles of schedule 2437 pesticide compounds in laboratory blanks by water year, with minimum groundwater concentrations, maximum laboratory limits, and human-health benchmarks"},{"id":376732,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5072/sir20205072_table04.xlsx","text":"Table 4","size":"91.2 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5072 Table 4","linkHelpText":"— Comparison of the 90-percent upper confidence limit for the 90th, 95th, and 99th percentiles of schedule 2437 pesticide compounds in laboratory blanks by water year, with minimum groundwater concentrations, maximum laboratory limits, and human-health benchmarks"},{"id":376731,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5072/sir20205072_table03.csv","text":"Table 3","size":"23.3 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5072 Table 3","linkHelpText":"— Summary of detections of schedule 2437 pesticide compounds in groundwater, field blanks, and laboratory blanks, May 2013 through September 2018"},{"id":376730,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5072/sir20205072_table03.xlsx","text":"Table 3","size":"53.9 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5072 Table 3","linkHelpText":"— Summary of detections of schedule 2437 pesticide compounds in groundwater, field blanks, and laboratory blanks, May 2013 through September 2018"},{"id":376729,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5072/sir20205072_table01.csv","text":"Table 1","size":"39.1 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5072 Table 1","linkHelpText":"— Information about pesticide compounds included on the National Water Quality Laboratory schedule 2437, with human-health benchmarks and ranges of detection and laboratory reporting limits"},{"id":376728,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5072/sir20205072_table01.xlsx","text":"Table 1","size":"55.2 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5072 Table 1","linkHelpText":"— Information about pesticide compounds included on the National Water Quality Laboratory schedule 2437, with human-health benchmarks and ranges of detection and laboratory reporting limits"},{"id":376727,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5072/sir20205072.pdf","text":"Report","size":"3.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5072"},{"id":376744,"rank":19,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90BFKA4","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Field, laboratory, and third-party data for assessment of the quality of pesticide results reported by the National Water Quality Laboratory for groundwater samples collected by the National Water-Quality Assessment Project, 2013–18"},{"id":376743,"rank":18,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5072/sir20205072_table11.csv","text":"Table 11","size":"18.6 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5072 Table 11","linkHelpText":"— Summary of results of data-quality assessment for schedule 2437 pesticide compounds based on all quality-control sample types, May 2013 through September 2018"},{"id":376726,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5072/coverthb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -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":"

Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-07-27","noUsgsAuthors":false,"publicationDate":"2020-07-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Bexfield, Laura M. 0000-0002-1789-654X bexfield@usgs.gov","orcid":"https://orcid.org/0000-0002-1789-654X","contributorId":1273,"corporation":false,"usgs":true,"family":"Bexfield","given":"Laura","email":"bexfield@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":793945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":793946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sandstrom, Mark W. 0000-0003-0006-5675 sandstro@usgs.gov","orcid":"https://orcid.org/0000-0003-0006-5675","contributorId":706,"corporation":false,"usgs":true,"family":"Sandstrom","given":"Mark","email":"sandstro@usgs.gov","middleInitial":"W.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":793947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beaty, Delicia 0000-0003-2044-2319 dbeaty@usgs.gov","orcid":"https://orcid.org/0000-0003-2044-2319","contributorId":3469,"corporation":false,"usgs":true,"family":"Beaty","given":"Delicia","email":"dbeaty@usgs.gov","affiliations":[],"preferred":true,"id":793948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Medalie, Laura 0000-0002-2440-2149 lmedalie@usgs.gov","orcid":"https://orcid.org/0000-0002-2440-2149","contributorId":3657,"corporation":false,"usgs":true,"family":"Medalie","given":"Laura","email":"lmedalie@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":793949,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":793950,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nowell, Lisa H. 0000-0001-5417-7264 lhnowell@usgs.gov","orcid":"https://orcid.org/0000-0001-5417-7264","contributorId":490,"corporation":false,"usgs":true,"family":"Nowell","given":"Lisa","email":"lhnowell@usgs.gov","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":793951,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70211353,"text":"fs20203039 - 2020 - A not so sudden impact—Historical relations between conifers and insects can help predict damage by nonnative insects","interactions":[],"lastModifiedDate":"2020-09-01T13:51:45.951306","indexId":"fs20203039","displayToPublicDate":"2020-07-27T12:00:14","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3039","displayTitle":"A Not So Sudden Impact—Historical Relations Between Conifers and Insects Can Help Predict Damage by Nonnative Insects","title":"A not so sudden impact—Historical relations between conifers and insects can help predict damage by nonnative insects","docAbstract":"

The arrival and establishment of nonnative insects in North America is increasingly problematic. International trade has created opportunities to move wood products and nursery stock worldwide, which has increased the risk of insect introduction to regions or countries where they are not native. One group of researchers, the High-impact Insect Invasions Working Group (HIIWG), has developed a predictive model that can be used to estimate the likelihood that a newly arriving nonnative insect may significantly impact North American conifers. The HIIWG examined several traits and factors associated with nonnative insects feeding on conifers (a conifer specialist) already established in North America. Using these data, the HIIWG identified which combination of factors best predicted the risk that a conifer specialist would have a high impact. The researchers then developed a statistical model to predict the probability that a conifer specialist yet to arrive in North America would cause significant damage to conifers if the insect became established. Using three factors, the model calculates the odds of any particular conifer specialist having a high impact on a North American conifer in a range between 1 in 6.5 to 1 in 2,858. This model is a valuable tool to help identify invading insects with the potential to be the most damaging if the insect becomes established in North America. In addition, application of tools like this model can increase positive environmental outcomes for land managers by focusing their efforts on conifer populations that are deemed most vulnerable to extensive mortality

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203039","usgsCitation":"Durden, L.A., Schulz, A.N., Mech, A., and Thomas, K.A., 2020, A not so sudden impact—Historical relations between conifers and insects can help predict damage by nonnative insects: U.S. Geological Survey Fact Sheet 2020-3039, 4 p., https://doi.org/10.3133/fs20203039.","productDescription":"4 p.","numberOfPages":"4","ipdsId":"IP-117878","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":376753,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3039/fs20203039.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":376752,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3039/covrthb.jpg"}],"contact":"
Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2020-07-27","noUsgsAuthors":false,"publicationDate":"2020-07-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Durden, Lekeah A. 0000-0002-8145-6354","orcid":"https://orcid.org/0000-0002-8145-6354","contributorId":229702,"corporation":false,"usgs":true,"family":"Durden","given":"Lekeah","email":"","middleInitial":"A.","affiliations":[],"preferred":true,"id":793995,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schulz, Ashley N.","contributorId":219894,"corporation":false,"usgs":false,"family":"Schulz","given":"Ashley","email":"","middleInitial":"N.","affiliations":[{"id":40088,"text":"Department of Biological Sciences, Arkansas State University, Jonesboro, AR","active":true,"usgs":false}],"preferred":false,"id":793996,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mech, Angela M.","contributorId":219892,"corporation":false,"usgs":false,"family":"Mech","given":"Angela","email":"","middleInitial":"M.","affiliations":[{"id":40087,"text":"School of Environmental and Forest Sciences, University of Washington, Seattle, WA. Corresponding email: ammech@wcu.edu. Present address: Department of Geosciences and Natural Resources, Western Carolina University, Cullowhee, NC","active":true,"usgs":false}],"preferred":false,"id":793997,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thomas, Kathryn A. 0000-0002-7131-8564 kathryn_a_thomas@usgs.gov","orcid":"https://orcid.org/0000-0002-7131-8564","contributorId":167,"corporation":false,"usgs":true,"family":"Thomas","given":"Kathryn","email":"kathryn_a_thomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":793998,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70213307,"text":"70213307 - 2020 - Geological and thermal control of the hydrothermal system in northern Yellowstone Lake: Inferences from high resolution magnetic surveys","interactions":[],"lastModifiedDate":"2020-09-17T16:30:39.105748","indexId":"70213307","displayToPublicDate":"2020-07-27T11:10:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6453,"text":"Journal of Geophysical Research Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Geological and thermal control of the hydrothermal system in northern Yellowstone Lake: Inferences from high resolution magnetic surveys","docAbstract":"

A multiscale magnetic survey of the northern basin of Yellowstone Lake was undertaken in 2016 as part of the Hydrothermal Dynamics of Yellowstone Lake Project (HD‐YLAKE)—a broad research effort to characterize the cause‐and‐effect relationships between geologic and environmental processes and hydrothermal activity on the lake floor. The magnetic survey includes lake surface, regional aeromagnetic, and near‐bottom autonomous underwater vehicle (AUV) data. The study reveals a strong contrast between the northeastern lake basin, characterized by a regional magnetic low punctuated by stronger local magnetic lows, many of which host hydrothermal vent activity, and the northwestern lake basin with higher‐amplitude magnetic anomalies and no obvious hydrothermal activity or punctuated magnetic lows. The boundary between these two regions is marked by a steep gradient in heat flow and magnetic values, likely reflecting a significant structure within the currently active ~20‐km‐long Eagle Bay‐Lake Hotel fault zone that may be related to the ~2.08‐Ma Huckleberry Ridge caldera rim. Modeling suggests that the broad northeastern magnetic low reflects both a shallower Curie isotherm and widespread hydrothermal activity that has demagnetized the rock. Along the western lake shoreline are sinuous‐shaped, high‐amplitude magnetic anomaly highs, interpreted as lava flow fronts of upper units of the West Thumb rhyolite. The AUV magnetic survey shows decreased magnetization at the periphery of the active Deep Hole hydrothermal vent. We postulate that lower magnetization in the outer zone results from enhanced hydrothermal alteration of rhyolite by hydrothermal condensates while the vapor‐dominated center of the vent is less altered.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB019743","usgsCitation":"Bouligand, C., Tivey, M.A., Finn, C., Morgan, L.A., Shanks, W.C., and Sohn, R., 2020, Geological and thermal control of the hydrothermal system in northern Yellowstone Lake: Inferences from high resolution magnetic surveys: Journal of Geophysical Research Solid Earth, v. 125, no. 9, e2020JB019743, 20 p., https://doi.org/10.1029/2020JB019743.","productDescription":"e2020JB019743, 20 p.","ipdsId":"IP-117428","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":455857,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2020jb019743","text":"External Repository"},{"id":378514,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.55816650390625,\n 44.44162421758805\n ],\n [\n -110.21759033203125,\n 44.44162421758805\n ],\n [\n -110.21759033203125,\n 44.574817404670306\n ],\n [\n -110.55816650390625,\n 44.574817404670306\n ],\n [\n -110.55816650390625,\n 44.44162421758805\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-08-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Bouligand, Claire","contributorId":240831,"corporation":false,"usgs":false,"family":"Bouligand","given":"Claire","affiliations":[{"id":34188,"text":"University of Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":798998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tivey, Maurice A.","contributorId":240832,"corporation":false,"usgs":false,"family":"Tivey","given":"Maurice","email":"","middleInitial":"A.","affiliations":[{"id":13294,"text":"Woods Hole Oceanographic Institute","active":true,"usgs":false}],"preferred":false,"id":798999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finn, Carol A. 0000-0002-6178-0405","orcid":"https://orcid.org/0000-0002-6178-0405","contributorId":205010,"corporation":false,"usgs":true,"family":"Finn","given":"Carol A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":799000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morgan, Lisa A","contributorId":240835,"corporation":false,"usgs":false,"family":"Morgan","given":"Lisa","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":799001,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shanks, W. C. Pat III 0000-0001-5336-3954","orcid":"https://orcid.org/0000-0001-5336-3954","contributorId":240915,"corporation":false,"usgs":true,"family":"Shanks","given":"W.","suffix":"III","email":"","middleInitial":"C. Pat","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":799002,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sohn, Robert A.","contributorId":240840,"corporation":false,"usgs":false,"family":"Sohn","given":"Robert A.","affiliations":[{"id":13294,"text":"Woods Hole Oceanographic Institute","active":true,"usgs":false}],"preferred":false,"id":799003,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70211354,"text":"ofr20201083 - 2020 - A standard operating procedure for the preparation of purposely killed juvenile salmon used to test survival model assumptions","interactions":[],"lastModifiedDate":"2020-07-28T14:21:01.694632","indexId":"ofr20201083","displayToPublicDate":"2020-07-27T09:59:25","publicationYear":"2020","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":"2020-1083","displayTitle":"A Standard Operating Procedure for the Preparation of Purposely Killed Juvenile Salmon Used to Test Survival Model Assumptions","title":"A standard operating procedure for the preparation of purposely killed juvenile salmon used to test survival model assumptions","docAbstract":"

This document describes a standard operating procedure (SOP) for the preparation of purposely killed juvenile salmon, implanted with telemetry transmitters, to be released into rivers, lakes, or streams to test one of the survival model assumptions. Procedures for releases of purposely killed fish (hereinafter dead fish releases) were developed by staff from the U.S. Geological Survey’s Columbia River Research Laboratory, on the basis of laboratory experiments and practical experience with telemetry studies in the Columbia River Basin. Initially, we used extended exposure to high dose anesthetic baths to euthanize fish for dead fish releases. This approach was selected on the basis of euthanization procedures described in the literature for studies that required an effective and rapid procedure, such as stress physiology assessments. Ultimately, this technique was deemed insufficient because detection records suggested that some fish seemed to revive and continue their migration with limited effect. That is, the detection histories of dead fish were very similar to those of live fish. To overcome this challenge, we adapted our procedures to require a combination of euthanization procedures on individual fish to ensure that there was no opportunity for revival. A combination of euthanization procedures for dead fish releases was used in one study in Germany. This SOP has been used by the U.S. Geological Survey to test survival model assumptions in several field studies and has consistently performed well. In addition, limited laboratory tests were completed to ensure that no live juvenile salmon were found in holding tanks for 24 hours following the procedures described in this SOP.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201083","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Tomka, R.G., Liedtke, T.L., Frost, C., and Smith, C.D., 2020, A standard operating procedure for the preparation of purposely killed juvenile salmon used to test survival model assumptions: U.S. Geological Survey Open-File Report 2020–1083, 11 p., https://doi.org/10.3133/ofr20201083.","productDescription":"iv, 11 p.","onlineOnly":"Y","ipdsId":"IP-116988","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":376754,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1083/coverthb.jpg"},{"id":376755,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1083/ofr20201083.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1083"}],"contact":"

Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016

","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2020-07-27","noUsgsAuthors":false,"publicationDate":"2020-07-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Tomka, Ryan G. 0000-0003-1078-6089 rtomka@usgs.gov","orcid":"https://orcid.org/0000-0003-1078-6089","contributorId":3706,"corporation":false,"usgs":true,"family":"Tomka","given":"Ryan","email":"rtomka@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":793999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liedtke, Theresa L. 0000-0001-6063-9867 tliedtke@usgs.gov","orcid":"https://orcid.org/0000-0001-6063-9867","contributorId":2999,"corporation":false,"usgs":true,"family":"Liedtke","given":"Theresa","email":"tliedtke@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":794000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frost, Conrad","contributorId":229703,"corporation":false,"usgs":false,"family":"Frost","given":"Conrad","email":"","affiliations":[],"preferred":false,"id":794001,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Collin D. 0000-0003-4184-5686 cdsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-4184-5686","contributorId":7915,"corporation":false,"usgs":true,"family":"Smith","given":"Collin D.","email":"cdsmith@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":794002,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228654,"text":"70228654 - 2020 - The role of phosphorus and nitrogen on chlorophyll a: Evidence from hundreds of lakes","interactions":[],"lastModifiedDate":"2022-02-16T15:29:53.80312","indexId":"70228654","displayToPublicDate":"2020-07-27T09:26:58","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The role of phosphorus and nitrogen on chlorophyll a: Evidence from hundreds of lakes","title":"The role of phosphorus and nitrogen on chlorophyll a: Evidence from hundreds of lakes","docAbstract":"

The effect of nutrients on phytoplankton biomass in lakes continues to be a subject of debate by aquatic scientists. However, determining whether or not chlorophyll a (CHL) is limited by phosphorus (P) and/or nitrogen (N) is rarely considered using a probabilistic method in studies of hundreds of lakes across broad spatial extents. Several studies have applied a unified CHL-nutrient relationship to determine nutrient limitation, but pose a risk of ecological fallacy because they neglect spatial heterogeneity in ecological contexts. To examine whether or not CHL is limited by P, N, or both nutrients in hundreds of lakes and across diverse ecological settings, a probabilistic machine learning method, Bayesian Network, was applied. Spatial heterogeneity in ecological context was accommodated by the probabilistic nature of the results. We analyzed data from 1382 lakes in 17 US states to evaluate the cause-effect relationships between CHL and nutrients. Observations of CHL, total phosphorus (TP), and total nitrogen (TN) were discretized into three trophic states (oligo-mesotrophic, eutrophic, and hypereutrophic) to train the model. We found that although both nutrients were related to CHL trophic state, TP was more related to CHL than TN, especially under oligo-mesotrophic and eutrophic CHL conditions. However, when the CHL trophic state was hypereutrophic, both TP and TN were important. These results provide additional evidence that P-limitation is more likely under oligo-mesotrophic or eutrophic CHL conditions and that co-limitation of P and N occurs under hypereutrophic CHL conditions. We also found a decreasing pattern of the TN/TP ratio with increasing CHL concentrations, which might be a key driver for the role change of nutrients. Previous work performed at smaller scales support our findings, indicating potential for extension of our findings to other regions. Our findings enhance the understanding of nutrient limitation at macroscales and revealed that the current debate on the limiting nutrient might be caused by failure to consider CHL trophic state. Our findings also provide prior information for the site-specific eutrophication management of unsampled or data-limited lakes.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2020.116236","usgsCitation":"Liang, Z., Soranno, P., and Wagner, T., 2020, The role of phosphorus and nitrogen on chlorophyll a: Evidence from hundreds of lakes: Water Research, v. 185, 116236, 9 p., https://doi.org/10.1016/j.watres.2020.116236.","productDescription":"116236, 9 p.","ipdsId":"IP-113421","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":455860,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2020.116236","text":"Publisher Index Page"},{"id":396014,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"185","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Liang, Zhongyao","contributorId":279427,"corporation":false,"usgs":false,"family":"Liang","given":"Zhongyao","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":834941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soranno, Patricia A.","contributorId":279428,"corporation":false,"usgs":false,"family":"Soranno","given":"Patricia A.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":834942,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834940,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70215736,"text":"70215736 - 2020 - Integrating perspectives to understand lake ice dynamics in a changing world","interactions":[],"lastModifiedDate":"2020-10-28T13:02:25.289795","indexId":"70215736","displayToPublicDate":"2020-07-27T07:58:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Integrating perspectives to understand lake ice dynamics in a changing world","docAbstract":"

Ice cover plays a critical role in physical, biogeochemical, and ecological processes in lakes. Despite its importance, winter limnology remains relatively understudied. Here, we provide a primer on the predominant drivers of freshwater lake ice cover and the current methodologies used to study lake ice, including in situ and remote sensing observations, physical based models, and experiments. We highlight opportunities for future research by integrating these four disciplines to address key knowledge gaps in our understanding of lake ice dynamics in changing winters. Advances in technology, data integration, and interdisciplinary collaboration will allow the field to move toward developing global forecasts of lake ice cover for small to large lakes across broad spatial and temporal scales, quantifying ice quality and ice thickness, moving from binary to continuous ice records, and determining how winter ice conditions and quality impact ecosystem processes in lakes over winter. Ultimately, integrating disciplines will improve our ability to understand the impacts of changing winters on lake ice.

","language":"English","publisher":"Wiley","doi":"10.1029/2020JG005799","usgsCitation":"Sharma, S., Meyer, M.F., Culpepper, J., Yang, X., Hampton, S., Berger, S.A., Brousil, M.R., Fradkin, S.C., Higgins, S.N., Jankowski, K.J., Kirillin, G., Smits, A.P., Whitaker, E.C., Yousef, F., and Zhang, S., 2020, Integrating perspectives to understand lake ice dynamics in a changing world: Journal of Geophysical Research: Biogeosciences, v. 125, no. 8, e2020JG005799, 18 p., https://doi.org/10.1029/2020JG005799.","productDescription":"e2020JG005799, 18 p.","ipdsId":"IP-118500","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":379863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","issue":"8","noUsgsAuthors":false,"publicationDate":"2020-08-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Sharma, Sapna","contributorId":150332,"corporation":false,"usgs":false,"family":"Sharma","given":"Sapna","email":"","affiliations":[{"id":16184,"text":"York University","active":true,"usgs":false}],"preferred":false,"id":803226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meyer, Michael F. 0000-0002-8034-9434","orcid":"https://orcid.org/0000-0002-8034-9434","contributorId":244065,"corporation":false,"usgs":false,"family":"Meyer","given":"Michael","email":"","middleInitial":"F.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":803227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Culpepper, Joshua","contributorId":244067,"corporation":false,"usgs":false,"family":"Culpepper","given":"Joshua","email":"","affiliations":[{"id":37455,"text":"University of Nevada","active":true,"usgs":false}],"preferred":false,"id":803228,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yang, Xiao","contributorId":149701,"corporation":false,"usgs":false,"family":"Yang","given":"Xiao","affiliations":[],"preferred":false,"id":803229,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hampton, Stephanie","contributorId":150338,"corporation":false,"usgs":false,"family":"Hampton","given":"Stephanie","affiliations":[{"id":5127,"text":"Washington State University, P.O. Box 644236, Pullman, WA 99164","active":true,"usgs":false}],"preferred":false,"id":803230,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Berger, Stella A. 0000-0002-8835-545X","orcid":"https://orcid.org/0000-0002-8835-545X","contributorId":244069,"corporation":false,"usgs":false,"family":"Berger","given":"Stella","email":"","middleInitial":"A.","affiliations":[{"id":38332,"text":"Leibniz-Institute of Freshwater Ecology and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":803231,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brousil, Matthew R.","contributorId":244071,"corporation":false,"usgs":false,"family":"Brousil","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":803232,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fradkin, Steven C.","contributorId":168638,"corporation":false,"usgs":false,"family":"Fradkin","given":"Steven","email":"","middleInitial":"C.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":803233,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Higgins, Scott N.","contributorId":166843,"corporation":false,"usgs":false,"family":"Higgins","given":"Scott","email":"","middleInitial":"N.","affiliations":[{"id":24553,"text":"International Institute for Sustainable Development - Experimental Lakes Area, Winnipeg, Manitoba, R3B 2L6, Canada","active":true,"usgs":false}],"preferred":false,"id":803234,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jankowski, Kathi Jo 0000-0002-3292-4182","orcid":"https://orcid.org/0000-0002-3292-4182","contributorId":207429,"corporation":false,"usgs":true,"family":"Jankowski","given":"Kathi","email":"","middleInitial":"Jo","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":803235,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kirillin, Georgiy 0000-0001-7337-3586","orcid":"https://orcid.org/0000-0001-7337-3586","contributorId":244076,"corporation":false,"usgs":false,"family":"Kirillin","given":"Georgiy","email":"","affiliations":[{"id":38332,"text":"Leibniz-Institute of Freshwater Ecology and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":803236,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Smits, Adrianne P 0000-0001-9967-5419","orcid":"https://orcid.org/0000-0001-9967-5419","contributorId":217759,"corporation":false,"usgs":false,"family":"Smits","given":"Adrianne","email":"","middleInitial":"P","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":803237,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Whitaker, Emily C.","contributorId":244079,"corporation":false,"usgs":false,"family":"Whitaker","given":"Emily","email":"","middleInitial":"C.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":803238,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Yousef, Foad 0000-0003-0718-9267","orcid":"https://orcid.org/0000-0003-0718-9267","contributorId":244082,"corporation":false,"usgs":false,"family":"Yousef","given":"Foad","email":"","affiliations":[{"id":16946,"text":"Westminster College","active":true,"usgs":false}],"preferred":false,"id":803239,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Zhang, Shuai","contributorId":244084,"corporation":false,"usgs":false,"family":"Zhang","given":"Shuai","email":"","affiliations":[{"id":27051,"text":"University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":803240,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70218687,"text":"70218687 - 2020 - Importance of accurately quantifying internal loading in developing phosphorus reduction strategies for a chain of shallow lakes","interactions":[],"lastModifiedDate":"2021-03-05T13:34:17.984695","indexId":"70218687","displayToPublicDate":"2020-07-27T07:31:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2592,"text":"Lake and Reservoir Management","active":true,"publicationSubtype":{"id":10}},"title":"Importance of accurately quantifying internal loading in developing phosphorus reduction strategies for a chain of shallow lakes","docAbstract":"

The Winnebago Pool is a chain of 4 shallow lakes in Wisconsin. Because of high external phosphorus (P) inputs to the lakes, the lakes became highly eutrophic, with much P contained in their sediments. In developing a total maximum daily load (TMDL) for these lakes, it is important to determine how their phosphorus concentrations should respond to changes in external P loading. In many TMDLs, internal P loading is assumed to be negligible or it is estimated based on sediment release rates and dissolved oxygen conditions in the lake, and each lake is considered independently. To evaluate these assumptions, internal P loading and external P loading were quantified by developing detailed P budgets for the Winnebago Pool chain of lakes. This information was then inputted into 2 eutrophication models (BATHTUB and Jensen models), which were used to simulate the steady-state and transient effects of various P reduction strategies. The importance of internal P loading varied among lakes, from being a minor source to representing almost 60% of the summer P input. Model results indicate that each lake responds to external P reductions, but internal loading can delay the lake responses, especially in the most downstream lake, Lake Winnebago, where internal P loading was most important to its summer P budget. Accurately quantifying net internal P loading and using this information in lake models are important in evaluating how large shallow lakes should respond to P reduction strategies, setting realistic expectations from watershed P reductions, and guiding TMDL efforts.

","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10402381.2020.1783727","usgsCitation":"Robertson, D., and Diebel, M.W., 2020, Importance of accurately quantifying internal loading in developing phosphorus reduction strategies for a chain of shallow lakes: Lake and Reservoir Management, v. 36, no. 4, p. 391-411, https://doi.org/10.1080/10402381.2020.1783727.","productDescription":"21 p.","startPage":"391","endPage":"411","ipdsId":"IP-109187","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":455873,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/10402381.2020.1783727","text":"Publisher Index Page"},{"id":384062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Lake Winnebago","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.65142822265625,\n 43.733398628766096\n ],\n [\n -88.17901611328125,\n 43.733398628766096\n ],\n [\n -88.17901611328125,\n 44.270771508583536\n ],\n [\n -88.65142822265625,\n 44.270771508583536\n ],\n [\n -88.65142822265625,\n 43.733398628766096\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-07-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Robertson, Dale M. 0000-0001-6799-0596","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":217258,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":811373,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diebel, Matthew W. 0000-0002-5164-598X","orcid":"https://orcid.org/0000-0002-5164-598X","contributorId":206517,"corporation":false,"usgs":false,"family":"Diebel","given":"Matthew","email":"","middleInitial":"W.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":811374,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70211260,"text":"sir20205058 - 2020 - Comparison of storm runoff models for a small watershed in an urban metropolitan area, Albuquerque, New Mexico","interactions":[],"lastModifiedDate":"2020-07-28T14:49:34.126291","indexId":"sir20205058","displayToPublicDate":"2020-07-26T14:54:58","publicationYear":"2020","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":"2020-5058","displayTitle":"Comparison of Storm Runoff Models for a Small Watershed in an Urban Metropolitan Area, Albuquerque, New Mexico","title":"Comparison of storm runoff models for a small watershed in an urban metropolitan area, Albuquerque, New Mexico","docAbstract":"

In order to comply with a current U.S. Environmental Protection Agency watershed-based National Pollutant Discharge Elimination System permit, the City of Albuquerque required a better understanding of the rainfall-runoff processes in its small urban watersheds. That requirement prompted the initiation of the assessment of three existing watershed models that were developed to simulate those processes. Three existing rainfall-runoff modeling software packages—Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) (using two sets of methods), Program for Predicting Polluting Particle Passage Through Pits, Puddles, and Ponds (P8), and Arid-Lands Hydrologic Model (AHYMO)—were compared to determine which provided the best balance of accuracy and usability for simulating storm runoff in small watersheds in the urbanized area of Albuquerque, New Mexico. Additionally, results of this study could help inform model users who have interest in simulating storm runoff in similar urban areas throughout the United States. Each model was used to simulate storm runoff in the Hahn Arroyo watershed, an urbanized watershed with concrete-lined arroyo channels in the northeastern quadrant of Albuquerque that exhibits flashy, monsoonal-driven storm runoff. Model results were compared to observed discharge data, according to literature-recommended performance measures and performance evaluation criteria. The HEC-HMS model using the Soil Conservation Service (SCS) curve number (CN) and SCS unit hydrograph methods ranked the highest when averaging the individual performance measures (Nash-Sutcliffe Efficiency, percent bias, and coefficient of determination) rankings together across the hourly calibration and validation periods, followed by P8, which was tied with the HEC-HMS initial and constant approach. For daily rankings using the same rank-averaging approach, the HEC-HMS CN-based model and P8 were tied for the highest ranking, followed by the HEC-HMS initial and constant approach. Alternatively, rating performance using validation period results as an indication of the expected confidence in forecasted results for future conditions, the P8 model performed best for both hourly and daily time-steps, followed by the HEC-HMS CN-based model and the HEC-HMS initial and constant-based model. However, based on the literature performance evaluation criteria, the HEC-HMS and P8 models overall had marginally satisfactory performance only for operation at the daily time-step. Direct comparison of the HEC-HMS and P8 models to the AHYMO is difficult, given the different performance assessment criteria used to assess these models separately in this study, as recommended by the literature. The AHYMO results generally lacked precision, given the wide range in the performance assessment values across events in percent error in peak discharge, difference in timing of peak discharge, percent error in total runoff volume, and difference in duration of event relative to observed data. For some events, however, the AHYMO results were fairly accurate, and AHYMO was likely a good predictor of the timing of storm runoff and the shape of the hydrograph. This study did not assess the results for all potential applications of the models in the Albuquerque urbanized area. Further study may be required to assess the model performance capabilities in other modeling applications.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205058","collaboration":"Prepared in cooperation with the City of Albuquerque","usgsCitation":"Shephard, Z.M., and Douglas-Mankin, K.R., 2020, Comparison of storm runoff models for a small watershed in an urban metropolitan area, Albuquerque, New Mexico: U.S. Geological Survey Scientific Investigations Report 2020–5058, 30 p., https://doi.org/10.3133/sir20205058.","productDescription":"Report: viii, 30 p.; Data Release","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-113457","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":376561,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5058/coverthb.jpg"},{"id":376562,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5058/sir20205058.pdf","text":"Report","size":"1.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5058"},{"id":376563,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P930WKCH","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Input and output data used to compare storm runoff models for a small watershed in an urban metropolitan area, Albuquerque, New Mexico"}],"country":"United States","state":"New Mexico","city":"Albuquerque","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.71844482421874,\n 35.08395557927643\n ],\n [\n -106.44996643066406,\n 35.08395557927643\n ],\n [\n -106.45545959472653,\n 35.19345038573419\n ],\n [\n -106.66694641113278,\n 35.19232810975203\n ],\n [\n -106.71844482421874,\n 35.08395557927643\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd NE
Albuquerque, New Mexico 87113

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-07-26","noUsgsAuthors":false,"publicationDate":"2020-07-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Shephard, Zachary M. 0000-0003-2994-3355","orcid":"https://orcid.org/0000-0003-2994-3355","contributorId":218999,"corporation":false,"usgs":true,"family":"Shephard","given":"Zachary M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":793451,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas-Mankin, Kyle R. 0000-0002-3155-3666","orcid":"https://orcid.org/0000-0002-3155-3666","contributorId":203927,"corporation":false,"usgs":true,"family":"Douglas-Mankin","given":"Kyle","email":"","middleInitial":"R.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":793452,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}