The spatial footprint of unconventional (hydraulic fracturing) and conventional oil and gas development in the Marcellus Shale region of the State of Pennsylvania was digitized from high-resolution, ortho-rectified, digital aerial photography, from 2004 to 2010. We used these data to measure the spatial extent of oil and gas development and to assess the exposure of the extant natural resources across the landscape of the watersheds in the study area. We found that either form of development: (1) occurred in ~50% of the 930 watersheds that defined the study area; (2) was closer to streams than the recommended safe distance in ~50% of the watersheds; (3) was in some places closer to impaired streams and state-defined wildland trout streams than the recommended safe distance; (4) was within 10 upstream kilometers of surface drinking water intakes in ~45% of the watersheds that had surface drinking water intakes; (5) occurred in ~10% of state-defined exceptional value watersheds; (6) occurred in ~30% of the watersheds with resident populations defined as disproportionately exposed to pollutants; (7) tended to occur at interior forest locations; and (8) had >100 residents within 3 km for ~30% of the unconventional oil and gas development sites. Further, we found that exposure to the potential effects of landscape disturbance attributable to conventional oil and gas development was more prevalent than its unconventional counterpart.
","language":"English","publisher":"MDPI","publisherLocation":"Basel, Switzerland","doi":"10.3390/environments2020200","usgsCitation":"Slonecker, T.E., and Milheim, L., 2015, Landscape disturbance from unconventional and conventional oil and gas development in the Marcellus Shale region of Pennsylvania, USA: Environments, v. 2, no. 2, p. 200-220, https://doi.org/10.3390/environments2020200.","productDescription":"21 p.","startPage":"200","endPage":"220","numberOfPages":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060471","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":472026,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/environments2020200","text":"Publisher Index Page"},{"id":306663,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Marcellus Shale region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.53700943985835,\n 39.858770491692525\n ],\n [\n -75.94119467051401,\n 40.343724405280796\n ],\n [\n -74.31416203114968,\n 41.136613984593424\n ],\n [\n -75.42940506094872,\n 41.98252460542756\n ],\n [\n -79.77579741680867,\n 42.02225947674938\n ],\n [\n -79.89037718014443,\n 42.20358852900213\n ],\n [\n -80.53202385482297,\n 41.97684616967814\n ],\n [\n -80.54730115660134,\n 39.73552379388724\n ],\n [\n -78.82096605567959,\n 39.70614679531755\n ],\n [\n -78.69874764145489,\n 40.425182945651585\n ],\n [\n -78.04946231588691,\n 41.021453137217605\n ],\n [\n -76.71269841030623,\n 41.2573156562668\n ],\n [\n -76.84255547541991,\n 40.894543228560565\n ],\n [\n -76.52937078896939,\n 40.923407813957596\n ],\n [\n -78.25570588989113,\n 39.89980363356864\n ],\n [\n -78.28626049344695,\n 39.676757283700994\n ],\n [\n -77.69044572410263,\n 39.73552379388724\n ],\n [\n -77.04116039853469,\n 40.16883881318182\n ],\n [\n -76.51409348719147,\n 40.81943634649028\n ],\n [\n -76.04049713207142,\n 40.73845679874668\n ],\n [\n -76.84255547541991,\n 40.11044319933444\n ],\n [\n -76.53700943985835,\n 39.858770491692525\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-08","publicationStatus":"PW","scienceBaseUri":"55cdbfb6e4b08400b1fe140c","contributors":{"authors":[{"text":"Slonecker, Terry E. tslonecker@usgs.gov","contributorId":446,"corporation":false,"usgs":true,"family":"Slonecker","given":"Terry","email":"tslonecker@usgs.gov","middleInitial":"E.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":548237,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milheim, Lesley E. lmilheim@usgs.gov","contributorId":2560,"corporation":false,"usgs":true,"family":"Milheim","given":"Lesley E.","email":"lmilheim@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":548239,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70150458,"text":"70150458 - 2015 - Control of nitrogen and phosphorus transport by reservoirs in agricultural landscapes","interactions":[],"lastModifiedDate":"2018-07-16T15:20:21","indexId":"70150458","displayToPublicDate":"2015-06-07T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Control of nitrogen and phosphorus transport by reservoirs in agricultural landscapes","docAbstract":"Reservoirs often receive excess nitrogen (N) and phosphorus (P) lost from agricultural land, and may subsequently influence N and P delivery to inland and coastal waters through internal processes such as nutrient burial, denitrification, and nutrient turnover. Currently there is a need to better understand how reservoirs affect nutrient transport in agricultural landscapes, where few prior studies have provided joint views on the variation in net retention/loss among reservoirs, the role of reservoirs apart from natural lakes, and differences in effects on N versus P, especially over time frames >1 year. To address these needs, we compiled water quality data from many rivers in intermediate-to-large drainages of the Midwestern US, including tributaries to the Upper Mississippi River, Great Lakes, and Ohio River Basins, where cropland often covers >50 % of the contributing area. Incorporating 18 years of data (1990–2007), effects of reservoirs on river nutrient transport were examined using comparisons between reservoir out- flow sites and unimpeded river sites (N = 869, including 100 reservoir outflow sites) supported by mass balance analysis of individual reservoirs (n = 17). Reservoir outflows sites commonly had 20 % lower annual yields (mass per catchment area per year) of total N and total P (TP) than unimpeded rivers after accounting for cropland coverage. Reservoir outflow sites also had lower interannual variability in TP yields. The mass balance approach confirmed net N losses in reservoirs, suggesting denitrification of agricultural N, or N burial in sediments. Net retention of P ranged more widely, and multiple systems showed net P export, providing new evidence that legacy P within reservoir systems may mobilize over the long-term. Our results indicate that reservoirs broadly influence the downstream transport of N and P through agricultural river networks, including networks where natural lakes and wetlands are relatively scarce. This calls for a more complete understanding of agricultural reservoirs as open, connected features of river networks where biogeochemical processes are often influential to downstream water quality, but potentially sensitive to changes associated with sedimentation, eutrophication, infrastructure aging, and reservoir management.
","language":"English","publisher":"Springer","doi":"10.1007/s10533-015-0106-3","usgsCitation":"Powers, S.M., Tank, J., and Robertson, D.M., 2015, Control of nitrogen and phosphorus transport by reservoirs in agricultural landscapes: Biogeochemistry, v. 124, p. 417-439, https://doi.org/10.1007/s10533-015-0106-3.","productDescription":"23 p.","startPage":"417","endPage":"439","ipdsId":"IP-056109","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":355702,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Midwest, Upper Mississippi River, Great Lakes, Ohio River Basin","volume":"124","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-22","publicationStatus":"PW","scienceBaseUri":"5b6fcbf3e4b0f5d57878ecc3","contributors":{"authors":[{"text":"Powers, Stephen M.","contributorId":35238,"corporation":false,"usgs":false,"family":"Powers","given":"Stephen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":556910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tank, Jennifer L.","contributorId":103870,"corporation":false,"usgs":true,"family":"Tank","given":"Jennifer L.","affiliations":[],"preferred":false,"id":556911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robertson, Dale M. 0000-0001-6799-0596 dzrobert@usgs.gov","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":150760,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"dzrobert@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":556909,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70143609,"text":"70143609 - 2015 - Geomorphic consequences of volcanic eruptions in Alaska: A review","interactions":[],"lastModifiedDate":"2021-04-26T17:54:39.089956","indexId":"70143609","displayToPublicDate":"2015-06-06T13:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphic consequences of volcanic eruptions in Alaska: A review","docAbstract":"Eruptions of Alaska volcanoes have significant and sometimes profound geomorphic consequences on surrounding landscapes and ecosystems. The effects of eruptions on the landscape can range from complete burial of surface vegetation and preexisting topography to subtle, short-term perturbations of geomorphic and ecological systems. In some cases, an eruption will allow for new landscapes to form in response to the accumulation and erosion of recently deposited volcaniclastic material. In other cases, the geomorphic response to a major eruptive event may set in motion a series of landscape changes that could take centuries to millennia to be realized. The effects of volcanic eruptions on the landscape and how these effects influence surface processes has not been a specific focus of most studies concerned with the physical volcanology of Alaska volcanoes. Thus, what is needed is a review of eruptive activity in Alaska in the context of how this activity influences the geomorphology of affected areas. To illustrate the relationship between geomorphology and volcanic activity in Alaska, several eruptions and their geomorphic impacts will be reviewed. These eruptions include the 1912 Novarupta–Katmai eruption, the 1989–1990 and 2009 eruptions of Redoubt volcano, the 2008 eruption of Kasatochi volcano, and the recent historical eruptions of Pavlof volcano. The geomorphic consequences of eruptive activity associated with these eruptions are described, and where possible, information about surface processes, rates of landscape change, and the temporal and spatial scale of impacts are discussed.
A common feature of volcanoes in Alaska is their extensive cover of glacier ice, seasonal snow, or both. As a result, the generation of meltwater and a variety of sediment–water mass flows, including debris-flow lahars, hyperconcentrated-flow lahars, and sediment-laden water floods, are typical outcomes of most types of eruptive activity. Occasionally, such flows can be quite large, with flow volumes in the range of 107–109 m3. A review of the lahars generated during the 2009 eruption of Redoubt volcano will illustrate the geomorphic impacts of lahars on stream channels and riparian habitat. Although much work is needed to develop a comprehensive understanding of the geomorphic consequences of volcanic activity in Alaska, this review provides a synthesis of some of the best-studied eruptions and perhaps will serve as a starting point for future work on this topic.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.geomorph.2015.06.004","usgsCitation":"Waythomas, C.F., 2015, Geomorphic consequences of volcanic eruptions in Alaska: A review: Geomorphology, v. 246, p. 123-145, https://doi.org/10.1016/j.geomorph.2015.06.004.","productDescription":"23 p.","startPage":"123","endPage":"145","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064492","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":310296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.94140625,\n 63.74363097533544\n ],\n [\n -144.05273437499997,\n 59.95501026206206\n ],\n [\n -149.0185546875,\n 57.302789656350086\n ],\n [\n -154.8193359375,\n 54.29088164657006\n ],\n [\n -158.9501953125,\n 53.82659674299413\n ],\n [\n -163.828125,\n 52.26815737376817\n ],\n [\n -172.96875,\n 50.233151832472245\n ],\n [\n -179.7802734375,\n 49.809631563563094\n ],\n [\n -187.55859375,\n 50.45750402042058\n ],\n [\n -193.4912109375,\n 52.855864177853995\n ],\n [\n -191.0302734375,\n 54.826007999094955\n ],\n [\n -181.494140625,\n 53.930219863940025\n ],\n [\n -170.595703125,\n 55.47885346331034\n ],\n [\n -162.9052734375,\n 57.7041472343419\n ],\n [\n -149.94140625,\n 63.74363097533544\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"246","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5628b733e4b0d158f5926c20","contributors":{"authors":[{"text":"Waythomas, Christopher F. 0000-0002-3898-272X cwaythomas@usgs.gov","orcid":"https://orcid.org/0000-0002-3898-272X","contributorId":640,"corporation":false,"usgs":true,"family":"Waythomas","given":"Christopher","email":"cwaythomas@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":542804,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70147788,"text":"ds933 - 2015 - Hydrologic data from wells at or in the vicinity of the San Juan coal mine, San Juan County, New Mexico","interactions":[],"lastModifiedDate":"2015-06-05T12:48:35","indexId":"ds933","displayToPublicDate":"2015-06-05T13:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"933","title":"Hydrologic data from wells at or in the vicinity of the San Juan coal mine, San Juan County, New Mexico","docAbstract":"In 2010, in cooperation with the Mining and Minerals Division (MMD) of the State of New Mexico Energy, Minerals and Natural Resources Department, the U.S. Geological Survey (USGS) initiated a 4-year assessment of hydrologic conditions at the San Juan coal mine (SJCM), located about 14 miles west-northwest of the city of Farmington, San Juan County, New Mexico. The mine produces coal for power generation at the adjacent San Juan Generating Station (SJGS) and stores coal-combustion byproducts from the SJGS in mined-out surface-mining pits. The purpose of the hydrologic assessment is to identify groundwater flow paths away from SJCM coal-combustion-byproduct storage sites that might allow metals that may be leached from coal-combustion byproducts to eventually reach wells or streams after regional dewatering ceases and groundwater recovers to predevelopment levels. The hydrologic assessment, undertaken between 2010 and 2013, included compilation of existing data. The purpose of this report is to present data that were acquired and compiled by the USGS for the SJCM hydrologic assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds933","collaboration":"Prepared in cooperation with the Mining and Minerals Division of the State of New Mexico Energy, Minerals and Natural Resources Department","usgsCitation":"Stewart, A.M., and Thomas, N., 2015, Hydrologic data from wells at or in the vicinity of the San Juan coal mine, San Juan County, New Mexico: U.S. Geological Survey Data Series 933, HTML Document, https://doi.org/10.3133/ds933.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059091","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":301053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds933.jpg"},{"id":301051,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0933/"},{"id":301052,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0933/ds933.html","text":"Report","size":"19 KB","linkFileType":{"id":5,"text":"html"},"description":"Report"}],"country":"United States","state":"New Mexico","county":"San Juan County","otherGeospatial":"San Juan coal mine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.24623107910156,\n 36.72402574695313\n ],\n [\n -108.19747924804688,\n 36.76584198280488\n ],\n [\n -108.18168640136719,\n 36.791140738852704\n ],\n [\n -108.18168640136719,\n 36.8037869853087\n ],\n [\n -108.15284729003906,\n 36.86039455866718\n ],\n [\n -108.1391143798828,\n 36.88401445049676\n ],\n [\n -108.13156127929686,\n 36.90762703795211\n ],\n [\n -108.13499450683594,\n 36.929036787414525\n ],\n [\n -108.16932678222656,\n 36.93836736111466\n ],\n [\n -108.20091247558592,\n 36.94001381436853\n ],\n [\n -108.22288513183594,\n 36.92848789456677\n ],\n [\n -108.24829101562499,\n 36.89499795802219\n ],\n [\n -108.26133728027344,\n 36.8631414329529\n ],\n [\n -108.28125,\n 36.83346996591306\n ],\n [\n -108.3306884765625,\n 36.82797398619907\n ],\n [\n -108.39317321777344,\n 36.832370801556834\n ],\n [\n -108.48518371582031,\n 36.79718920417815\n ],\n [\n -108.49067687988281,\n 36.74328605437939\n ],\n [\n -108.29498291015624,\n 36.72017310567465\n ],\n [\n -108.24623107910156,\n 36.72402574695313\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5572ba25e4b077dba76c1b90","contributors":{"authors":[{"text":"Stewart, Anne M. astewart@usgs.gov","contributorId":3938,"corporation":false,"usgs":true,"family":"Stewart","given":"Anne","email":"astewart@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Nicole nithomas@usgs.gov","contributorId":5649,"corporation":false,"usgs":true,"family":"Thomas","given":"Nicole","email":"nithomas@usgs.gov","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548226,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70139689,"text":"ofr20151010 - 2015 - Multi-elemental analysis of aqueous geochemical samples by quadrupole inductively coupled plasma-mass spectrometry (ICP-MS)","interactions":[],"lastModifiedDate":"2015-06-05T11:58:22","indexId":"ofr20151010","displayToPublicDate":"2015-06-05T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1010","title":"Multi-elemental analysis of aqueous geochemical samples by quadrupole inductively coupled plasma-mass spectrometry (ICP-MS)","docAbstract":"Typically, quadrupole inductively coupled plasma-mass spectrometry (ICP-MS) is used to determine as many as 57 major, minor, and trace elements in aqueous geochemical samples, including natural surface water and groundwater, acid mine drainage water, and extracts or leachates from geological samples. The sample solution is aspirated into the inductively coupled plasma (ICP) which is an electrodeless discharge of ionized argon gas at a temperature of approximately 6,000 degrees Celsius. The elements in the sample solution are subsequently volatilized, atomized, and ionized by the ICP. The ions generated are then focused and introduced into a quadrupole mass filter which only allows one mass to reach the detector at a given moment in time. As the settings of the mass analyzer change, subsequent masses are allowed to impact the detector. Although the typical quadrupole ICP-MS system is a sequential scanning instrument (determining each mass separately), the scan speed of modern instruments is on the order of several thousand masses per second. Consequently, typical total sample analysis times of 2–3 minutes are readily achievable for up to 57 elements.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151010","usgsCitation":"Wolf, R.E., and Adams, M., 2015, Multi-elemental analysis of aqueous geochemical samples by quadrupole inductively coupled plasma-mass spectrometry (ICP-MS): U.S. Geological Survey Open-File Report 2015-1010, Report: iv, 34 p.; Downloads Directory, https://doi.org/10.3133/ofr20151010.","productDescription":"Report: iv, 34 p.; Downloads Directory","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-056063","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":301050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151010.jpg"},{"id":301047,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1010/"},{"id":301048,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1010/pdf/ofr2015-1010.pdf","text":"Report","size":"700 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":301049,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1010/downloads/ofr2015-1010_table1-2.xlsx","text":"Download","linkHelpText":"Contains table 1–2, a correction equations calculation worksheet with formulas used for calculations in the report"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5572ba27e4b077dba76c1b92","contributors":{"authors":[{"text":"Wolf, Ruth E. rwolf@usgs.gov","contributorId":903,"corporation":false,"usgs":true,"family":"Wolf","given":"Ruth","email":"rwolf@usgs.gov","middleInitial":"E.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":539563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Monique madams@usgs.gov","contributorId":1231,"corporation":false,"usgs":true,"family":"Adams","given":"Monique","email":"madams@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":539564,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148345,"text":"fs20153041 - 2015 - Real-time, continuous water-quality monitoring in Indiana and Kentucky","interactions":[],"lastModifiedDate":"2026-06-29T18:23:08.762687","indexId":"fs20153041","displayToPublicDate":"2015-06-05T09:15:00","publicationYear":"2015","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":"2015-3041","title":"Real-time, continuous water-quality monitoring in Indiana and Kentucky","docAbstract":"Water-quality “super” gages (also known as “sentry” gages) provide real-time, continuous measurements of the physical and chemical characteristics of stream water at or near selected U.S. Geological Survey (USGS) streamgages in Indiana and Kentucky. A super gage includes streamflow and water-quality instrumentation and representative stream sample collection for laboratory analysis. USGS scientists can use statistical surrogate models to relate instrument values to analyzed chemical concentrations at a super gage. Real-time, continuous and laboratory-analyzed concentration and load data are publicly accessible on USGS Web pages.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153041","usgsCitation":"Shoda, M.E., Lathrop, T., and Risch, M.R., 2015, Real-time, continuous water-quality monitoring in Indiana and Kentucky: U.S. Geological Survey Fact Sheet 2015-3041, 4 p., https://doi.org/10.3133/fs20153041.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061469","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":506264,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_101990.htm","text":"Yellow River Watershed, Indiana","linkFileType":{"id":5,"text":"html"}},{"id":506262,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_101989.htm","text":"Eagle Creek, Boone County, Indiana","linkFileType":{"id":5,"text":"html"}},{"id":301044,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153041.jpg"},{"id":301042,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3041/"},{"id":301043,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3041/pdf/fs2015-3041.pdf","text":"Report","size":"3.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Indiana, Kentucky","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.8089599609375,\n 41.759019938155404\n ],\n [\n -86.82769775390625,\n 41.76106872528616\n ],\n [\n -87.07489013671875,\n 41.66060124302088\n ],\n [\n -87.24517822265624,\n 41.623655390686395\n ],\n [\n -87.41546630859375,\n 41.638025739250786\n ],\n [\n -87.52532958984374,\n 41.724180549563606\n ],\n [\n -87.53356933593749,\n 39.35553794109382\n ],\n [\n -87.637939453125,\n 39.15988184949157\n ],\n [\n -87.5006103515625,\n 38.74551518488265\n ],\n [\n -87.967529296875,\n 38.26406296833961\n ],\n [\n -88.14880371093749,\n 37.67947293019486\n ],\n [\n -88.0718994140625,\n 37.505368263398104\n ],\n [\n -88.4619140625,\n 37.40943717748788\n ],\n [\n -88.43994140625,\n 37.10776507118514\n ],\n [\n -88.505859375,\n 37.08585785263673\n ],\n [\n -88.98376464843749,\n 37.24782120155428\n ],\n [\n -89.1815185546875,\n 37.06394430056685\n ],\n [\n -89.20898437499999,\n 36.60670888641815\n ],\n [\n -89.56054687499999,\n 36.575835338491764\n ],\n [\n -89.527587890625,\n 36.491973470593685\n ],\n [\n -88.04443359375,\n 36.50522086338427\n ],\n [\n -88.0718994140625,\n 36.69485094156225\n ],\n [\n -87.8302001953125,\n 36.64638529597495\n ],\n [\n -86.5283203125,\n 36.64638529597495\n ],\n [\n -85.242919921875,\n 36.62434536776987\n ],\n [\n -83.6773681640625,\n 36.59788913307022\n ],\n [\n -83.49334716796875,\n 36.66841891894786\n ],\n [\n -83.111572265625,\n 36.74768773190056\n ],\n [\n -82.69958496093749,\n 37.13404537126446\n ],\n [\n -82.2930908203125,\n 37.29153547292737\n ],\n [\n -81.990966796875,\n 37.54893261064111\n ],\n [\n -82.27111816406249,\n 37.67947293019486\n ],\n [\n -82.5018310546875,\n 38.00049145082287\n ],\n [\n -82.64465332031249,\n 38.156156969924915\n ],\n [\n -82.6007080078125,\n 38.44068226417387\n ],\n [\n -82.694091796875,\n 38.56105262446978\n ],\n [\n -82.8533935546875,\n 38.603993275591684\n ],\n [\n -82.891845703125,\n 38.77549900381297\n ],\n [\n -83.25439453125,\n 38.62116234642254\n ],\n [\n -83.51806640624999,\n 38.70694605159386\n ],\n [\n -83.682861328125,\n 38.638327308061875\n ],\n [\n -83.78173828125,\n 38.676933444637925\n ],\n [\n -83.9410400390625,\n 38.79690830348427\n ],\n [\n -84.2156982421875,\n 38.8225909761771\n ],\n [\n -84.30908203125,\n 39.01918369029134\n ],\n [\n -84.473876953125,\n 39.06184913429154\n ],\n [\n -84.7100830078125,\n 39.15136267949032\n ],\n [\n -84.825439453125,\n 39.11727568585595\n ],\n [\n -84.8089599609375,\n 41.759019938155404\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5572ba28e4b077dba76c1b94","contributors":{"authors":[{"text":"Shoda, Megan E. 0000-0002-5343-9717 meshoda@usgs.gov","orcid":"https://orcid.org/0000-0002-5343-9717","contributorId":4352,"corporation":false,"usgs":true,"family":"Shoda","given":"Megan","email":"meshoda@usgs.gov","middleInitial":"E.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547779,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lathrop, Timothy R. trlathro@usgs.gov","contributorId":4065,"corporation":false,"usgs":true,"family":"Lathrop","given":"Timothy R.","email":"trlathro@usgs.gov","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547780,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Risch, Martin R. 0000-0002-7908-7887 mrrisch@usgs.gov","orcid":"https://orcid.org/0000-0002-7908-7887","contributorId":2118,"corporation":false,"usgs":true,"family":"Risch","given":"Martin","email":"mrrisch@usgs.gov","middleInitial":"R.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547781,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70136054,"text":"70136054 - 2015 - Accounting for groundwater in stream fish thermal habitat responses to climate change","interactions":[],"lastModifiedDate":"2015-07-01T16:18:39","indexId":"70136054","displayToPublicDate":"2015-06-04T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Accounting for groundwater in stream fish thermal habitat responses to climate change","docAbstract":"Forecasting climate change effects on aquatic fauna and their habitat requires an understanding of how water temperature responds to changing air temperature (i.e., thermal sensitivity). Previous efforts to forecast climate effects on brook trout habitat have generally assumed uniform air-water temperature relationships over large areas that cannot account for groundwater inputs and other processes that operate at finer spatial scales. We developed regression models that accounted for groundwater influences on thermal sensitivity from measured air-water temperature relationships within forested watersheds in eastern North America (Shenandoah National Park, USA, 78 sites in 9 watersheds). We used these reach-scale models to forecast climate change effects on stream temperature and brook trout thermal habitat, and compared our results to previous forecasts based upon large-scale models. Observed stream temperatures were generally less sensitive to air temperature than previously assumed, and we attribute this to the moderating effect of shallow groundwater inputs. Predicted groundwater temperatures from air-water regression models corresponded well to observed groundwater temperatures elsewhere in the study area. Predictions of brook trout future habitat loss derived from our fine-grained models were far less pessimistic than those from prior models developed at coarser spatial resolutions. However, our models also revealed spatial variation in thermal sensitivity within and among catchments resulting in a patchy distribution of thermally suitable habitat. Habitat fragmentation due to thermal barriers therefore may have an increasingly important role for trout population viability in headwater streams. Our results demonstrate that simple adjustments to air-water temperature regression models can provide a powerful and cost-effective approach for predicting future stream temperatures while accounting for effects of groundwater.
From August 28 to 29, 2011, Tropical Storm Irene delivered rainfall ranging from about 4 inches to more than 7 inches in the White River Basin. The rainfall resulted in severe flooding throughout the basin and significant damage along the White River and Tweed River. In response to the flooding, the U.S. Geological Survey, in cooperation with the Federal Emergency Management Agency, conducted a new flood study to aid in the flood recovery and restoration. This flood study includes a 20.7-mile reach of the White River from the downstream end at about 2,000 feet downstream from the State Route 107 bridge in the Village of Bethel, Vermont, to the upstream end at about 1,000 feet upstream from the River Brook Drive bridge in the Village of Rochester, Vt., and a 7.9-mile reach of the Tweed River from its mouth in Stockbridge, Vt., to the confluence of the West and South Branches of the Tweed River and continuing upstream on the South Branch Tweed River to the Pittsfield, Vt., town line.
\nThis report presents water-surface elevations determined for the study reaches using the U.S. Army Corps of Engineers one-dimensional step-backwater Hydrologic Engineering Center River Analysis System model, also known as HEC– RAS. The water-surface elevations were determined for floods having a 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probability (AEP) and for the floodway.
\nEighteen high-water marks from Tropical Storm Irene were available along the studied reaches. The discharges in the Tropical Storm Irene HEC–RAS model were adjusted so that the resulting water-surface elevations matched the high-water mark elevations along the study reaches. This allowed for an estimation of the water-surface profile throughout the study area resulting from Tropical Storm Irene. From a comparison of the estimated water-surface profile of Tropical Storm Irene to the water-surface profiles of the 1- and 0.2-percent AEP floods, it was determined that the high-water elevations resulting from Tropical Storm Irene exceeded the estimated 1-percent AEP flood throughout the White River and Tweed River study reaches and exceeded the estimated 0.2-percent AEP flood in 16.7 of the 28.6 study reach miles. The simulated water-surface profiles were then combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data having a 18.2-centimeter vertical accuracy at the 95-percent confidence level and 1-meter horizontal resolution to delineate the area flooded for each water-surface profile.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155056","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Olson, S.A., 2015, Flood recovery maps for the White River in Bethel, Stockbridge, and Rochester, Vermont, and the Tweed River in Stockbridge and Pittsfield, Vermont, 2014: U.S. Geological Survey Scientific Investigations Report 2015-5056, Report: vi, 32 p.; Readme; Map file and datasets; Metadata, https://doi.org/10.3133/sir20155056.","productDescription":"Report: vi, 32 p.; Readme; Map file and datasets; Metadata","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2014-01-01","temporalEnd":"2014-12-31","ipdsId":"IP-057993","costCenters":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"links":[{"id":301023,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155056.jpg"},{"id":301018,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5056/"},{"id":301019,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5056/pdf/sir2015-5056.pdf","text":"Report","size":"2.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":301020,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2015/5056/attachments/sir2015-5056_readme.txt","text":"Readme","size":"1.09 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Readme"},{"id":301021,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5056/attachments/sir2015-5056_map.zip","text":"Map file and datasets","size":"2.11 GB","linkFileType":{"id":6,"text":"zip"},"description":"Map file and datasets","linkHelpText":"Contains the published map file and the map dataset. 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2015 - Turbidity alters pre-mating social interactions between native and invasive stream fishes","interactions":[],"lastModifiedDate":"2015-08-17T15:17:46","indexId":"70148369","displayToPublicDate":"2015-06-03T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Turbidity alters pre-mating social interactions between native and invasive stream fishes","docAbstract":"In 1963, the U.S. Department of the Interior’s Bureau of Reclamation finished building Glen Canyon Dam on the Colorado River in northern Arizona, 25 kilometers upstream from Grand Canyon National Park. The dam impounded 300 kilometers of the Colorado River, creating Lake Powell, the nation’s second largest reservoir.
\nBy 1974, scientists found that the downstream river’s alluvial sandbars were eroding because the reservoir trapped the fine sediment that replenished the deposits during annual floods. These sandbars are important structures for many kinds of life in and along the river.
\nNow, by implementing a new strategy that calls for repeated releases of large volumes of water from the dam, the U.S. Department of the Interior (DOI) seeks to increase the size and number of these sandbars. Three years into the \"high-flow experiment\" (HFE) protocol, the releases appear to be achieving the desired effect. Many sandbars have increased in size following each controlled flood, and the cumulative results of the first three releases suggest that sandbar declines may be reversed if controlled floods can be implemented frequently enough.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2015EO030349","usgsCitation":"Grams, P.E., Schmidt, J.C., Wright, S., Topping, D.J., Melis, T., and Rubin, D.M., 2015, Building sandbars in the Grand Canyon: Eos, Earth and Space Science News, v. 96, p. 1-11, https://doi.org/10.1029/2015EO030349.","productDescription":"11 p.","startPage":"1","endPage":"11","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059907","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":472033,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2015eo030349","text":"Publisher Index Page"},{"id":309718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"96","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56164232e4b0ba4884c6147c","contributors":{"authors":[{"text":"Grams, Paul E. 0000-0002-0873-0708 pgrams@usgs.gov","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":1830,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","email":"pgrams@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":576832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidt, John C. 0000-0002-2988-3869 jcschmidt@usgs.gov","orcid":"https://orcid.org/0000-0002-2988-3869","contributorId":1983,"corporation":false,"usgs":true,"family":"Schmidt","given":"John","email":"jcschmidt@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":576833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":576834,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Topping, David J. 0000-0002-2104-4577 dtopping@usgs.gov","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":140985,"corporation":false,"usgs":true,"family":"Topping","given":"David","email":"dtopping@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":576835,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Melis, Theodore S. 0000-0003-0473-3968 tmelis@usgs.gov","orcid":"https://orcid.org/0000-0003-0473-3968","contributorId":1829,"corporation":false,"usgs":true,"family":"Melis","given":"Theodore S.","email":"tmelis@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":576836,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rubin, David M. 0000-0003-1169-1452 drubin@usgs.gov","orcid":"https://orcid.org/0000-0003-1169-1452","contributorId":3159,"corporation":false,"usgs":true,"family":"Rubin","given":"David","email":"drubin@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":576837,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70147067,"text":"ofr20151082 - 2015 - Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2013","interactions":[],"lastModifiedDate":"2015-06-03T10:47:23","indexId":"ofr20151082","displayToPublicDate":"2015-06-03T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1082","title":"Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2013","docAbstract":"Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2013 (October 1, 2012, through September 30, 2013) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow and water-quality data used in the study were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board (PWSB) in the cooperative study. Streamflow was measured or estimated by the USGS following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected at 37 sampling stations by the PWSB and at 14 continuous-record streamgages by the USGS during WY 2013 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the PWSB are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2013.
\nThe largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed a mean streamflow of 30 cubic feet per second (ft3/s) to the reservoir during WY 2013. For the same time period, annual mean1 streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.45 to about 19 ft3/s. Together, tributaries (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,300,000 kilograms (kg) of sodium and 2,100,000 kg of chloride to the Scituate Reservoir during WY 2013; sodium and chloride yields for the tributaries ranged from 8,600 to 58,000 kilograms per square mile (kg/mi2) and from 14,000 to 97,000 kg/mi2, respectively.
\nAt the stations where water-quality samples were collected by the PWSB, the median of the median chloride concentrations was 18 milligrams per liter (mg/L), median nitrite concentration was 0.002 mg/L as nitrogen (N), median nitrate concentration was less than 0.01 mg/L as N, median orthophosphate concentration was 0.128 mg/L as phosphate, and median concentrations of total coliform bacteria and Escherichia coli (E. coli) were 330 and 15 colony-forming units per 100 milliliters (CFU/100mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 100 kilograms per day (kg/d; 50 kilograms per day per square mile [kg/d/mi2]), 10 grams per day (g/d; 5.1 grams per day per square mile [g/d/mi2]), 73 g/d (28 g/d/mi2), 720 g/d (320 g/d/mi2), 21,000 colony-forming units per day (CFU×106/d; 8,700 CFU×106/d/mi2), and 1,000 CFU×106/d (510 CFU×106/d/mi2), respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151082","collaboration":"Prepared in cooperation with the Providence Water Supply Board","usgsCitation":"Smith, K.P., 2015, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2013: U.S. Geological Survey Open-File Report 2015-1082, Report: v, 31 p.; Appendix, https://doi.org/10.3133/ofr20151082.","productDescription":"Report: v, 31 p.; Appendix","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2012-10-01","temporalEnd":"2013-09-30","ipdsId":"IP-056176","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":301013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151082.jpg"},{"id":301012,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1082/attachments/ofr2015-1082_appendix1.xlsx","text":"Appendix 1","size":"32 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix 1","linkHelpText":"Water-quality data collected by the Providence Water Supply Board at 37 monitoring stations in the Scituate Reservoir drainage area, Rhode Island, water year 2013."},{"id":301011,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1082/pdf/ofr2015-1082.pdf","text":"Report","size":"873 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":301010,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1082/"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.78947448730469,\n 41.74160260664948\n ],\n [\n -71.78947448730469,\n 41.92782492551717\n ],\n [\n -71.5484619140625,\n 41.92782492551717\n ],\n [\n -71.5484619140625,\n 41.74160260664948\n ],\n [\n -71.78947448730469,\n 41.74160260664948\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5570171de4b0d9246a9fd151","contributors":{"authors":[{"text":"Smith, Kirk P. 0000-0003-0269-474X kpsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-474X","contributorId":1516,"corporation":false,"usgs":true,"family":"Smith","given":"Kirk","email":"kpsmith@usgs.gov","middleInitial":"P.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545615,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70146944,"text":"ofr20151073 - 2015 - Southern Salish Sea Habitat Map Series: Admiralty Inlet","interactions":[],"lastModifiedDate":"2015-06-05T08:29:44","indexId":"ofr20151073","displayToPublicDate":"2015-06-03T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1073","subseriesTitle":"Southern Salish Sea Habitat Map Series","title":"Southern Salish Sea Habitat Map Series: Admiralty Inlet","docAbstract":"In 2010 the Environmental Protection Agency, Region 10 initiated the Puget Sound Scientific Studies and Technical Investigations Assistance Program, designed to support research in support of implementing the Puget Sound Action Agenda. The Action Agenda was created in response to Puget Sound having been designated as one of 28 estuaries of national significance under section 320 of the U.S. Clean Water Act, and its overall goal is to restore the Puget Sound Estuary's environment by 2020. The Southern Salish Sea Mapping Project was funded by the Assistance Program request for proposals process, which also supports a large number of coastal-zone- and ocean-management issues. The issues include the recommendations of the Marine Protected Areas Work Group to the Washington State Legislature (Van Cleve and others, 2009), which endorses a Puget Sound and coast-wide marine conservation needs assessment, gap analysis of existing Marine Protected Areas (MPA) and recommendations for action. This publication is the first of four U.S. Geological Survey Scientific Investigation Maps that make up the Southern Salish Sea Mapping Project. The remaining three map blocks to be published in the future, located south of Admiralty Inlet, are shown in figure 1.
\nPuget Sound is a deep, fjord-type estuary covering an area of 2,330 km2 in the Pacific Northwest region of the United States (fig. 1). It is connected to the ocean by the Strait of Juan de Fuca, a turbulent passage approximately 160 km in length and 22 km wide at its west end, expanding to over 40 km wide at its east end (Thomson, 1994). During the Pleistocene, the area was occupied several times by lobes of continental ice, resulting in a complex basin-fill of glacial and interglacial deposits that are locally as thick as 1100 m (Johnson and others, 2001). The last glaciation, called the Fraser glaciation, began after 28,800±740 14C yr B.P. when ice started a slow expansion (Clague, 1981). At peak advance the westward Juan de Fuca lobe reached the edge of the continental shelf through the Juan de Fuca Strait shortly before 14,460±200 14C yr B.P. (Herzer and Bornhold, 1982). The southward Puget lobe advanced to its terminal position in Puget Sound by around 14,150 14C yr B.P. (Porter and Swanson, 1998). Ice retreated from its maximum to northern Whidbey Island by 13,650±350 14C yr B.P. (Dethier and others, 1995). Retreating glaciers resulted in a thick sequence of ice-contact, glacial-marine sediment, and early post-glacial sediments (Linden and Schurrer, 1988). These deposits have experienced the effects of a marine transgression followed by regression, resulting in a sea-level several tens of meters lower than the present day (Linden and Schurrer, 1988). A second transgression brought sea level to about the present level by around 5,470±120 14C yr B.P. (Clague and others, 1982) establishing the present oceanographic and geologic environment
\nPuget Sound is separated into four interconnected basins; Whidbey, Central (Main), Hood Canal, and South (Thomson, 1994). The Whidbey, Central, and Hood Canal basins are the three main branches of the Puget Sound estuary and are separated from the Strait of Juan de Fuca by a double sill at Admiralty Inlet. The Admiralty Inlet map area includes the Inlet and a portion of the Whidbey Basin (fig. 1). The shallower South Basin is separated by a sill at Tacoma Narrows and is highly branched with numerous finger inlets. Flow within Puget Sound is dominated by tidal currents of as much as 1 m/s at Admiralty Inlet, reducing to approximately 0.5 m/s in the Central Basin (Lavelle and others, 1988). The lack of silt and clay-sized sediments in the Admiralty Inlet map area is likely a result of the strong currents (see Ground-Truth Studies for the Admiralty Inlet Map Area, sheet 3). The subtidal component of flow reaches approximately 0.1 m/s and is driven by density gradients arising from the contrast in salty ocean water at the entrance and freshwater inputs from stream flow (Lavelle and others, 1988). The total freshwater input to Puget Sound is approximately 3.4 x 106 m3/day, primarily from the Skagit River (Cannon, 1983). The subtidal circulation mostly consists of a two-layered flow in the basins with fresher water exiting at the surface and saltier water entering at depth (Ebbesmeyer and Cannon, 2001). In general, surface waters flow north and deeper waters flow south; variations arise from wind effects that can drive a surface current in the same direction as the wind, and a baroclinic response in the lower layer to about 100-m depth (Matsuura and Cannon, 1997). Oceanographic properties are influenced by temporal forcing parameters such as reduced stream flow during the 2000-01 drought that increased surface salinity and decreased differences between surface and bottom waters (Newton and others, 2003).
\nOn offshore seismic-reflection profiles, Pleistocene strata (excluding latest Pleistocene glacial and post-glacial deposits) form a distinct seismic unit, bounded below by pre-Tertiary or Tertiary basement and above by typically flat-lying latest Pleistocene to Holocene deposits that fill in erosional or depositional relief (Johnson and others, 2001). Cores from central Puget Sound have accumulation rates that range from 85 to 1200 mg/cm2/yr, or 0.12 to 2.4 cm/yr; the highest accumulation rates are near the southern end of central Puget Sound (Carpenter and others, 1985). Carpenter and others (1985) un-weighted arithmetic mean of accumulation rates for central Puget Sound deeper stations is 480±340 (± one standard deviation) mg/cm2/yr. Lavelle and others (1985) also found rates as high as 1200 mg/cm2/yr over the past approximately 70 years in cores in the Central Basin off of and north and south of Elliott Bay. Puget Sound basin rates are comparable to rates in midshelf silt deposits on the Washington coast north of the Columbia River (Nittrouer and others, 1979).
\nThe deep subtidal (in other words, below SCUBA depths) habitats of Puget Sound are relatively poorly known. A few subtidal surveys exist for several habitat types from the 1960s and 1970s (reviewed in Dethier, 1990), using grab and box core data. The Dethier (1990) review divides habitat up into Coast and Marine Ecological Classification Standard (CMECS) substrate, water column energy, and depth zones but does not attempt to map these habitats, rather it is an inventory of habitats found in the area and the flora and fauna associated with each habitat.
\nThe approach of the Southern Salish Sea Mapping project is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, and bottom-sediment sampling data. This approach is based in part on methods presented and data collection and product needs identified at the Washington State Seafloor Mapping Workshop (Washington State Seafloor Mapping Workshop Steering Committee, 2008), attended by coastal and marine managers and scientists. The map products display seafloor geomorphology and substrate, and identify potential marine benthic habitats. It is emphasized that the more interpretive habitat and geology maps rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. Oceanographic current and wave data is not included in this analysis, however, the accompanying geographic information system (GIS) data set is designed and intended to be combined with oceanographic and biologic data sets assembled by others in the future and some of the GIS data has already been incorporated in the unpublished Nature Conservancy Benthic Habitats of Puget Sound database.
\nThis publication includes four map sheets, explanatory text, and a descriptive pamphlet. Each map sheet is published as a portable document format (PDF) file. ESRI ArcGIS compatible geotiffs (for example, bathymetry) and shapefiles (for example video observation points) will be available for download in the data catalog associated with this publication (Cochrane, 2015). An ArcGIS Project File with the symbology used to generate the map sheets is also provided. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151073","usgsCitation":"Cochrane, G.R., Dethier, M.N., Hodson, T.O., Kull, K.K., Golden, N., Ritchie, A.C., Moegling, C., and Pacunski, R.E., 2015, Southern Salish Sea Habitat Map Series: Admiralty Inlet: U.S. Geological Survey Open-File Report 2015-1073, Report: iv, 34 p.; 4 Plates: 40 x 36 inches, https://doi.org/10.3133/ofr20151073.","productDescription":"Report: iv, 34 p.; 4 Plates: 40 x 36 inches","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-054193","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":300998,"rank":6,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151073.jpg"},{"id":300985,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1073/"},{"id":300995,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/935/downloads/AdmiraltyInlet/ds935_AdmiraltyInlet.html","text":"Data Catalog—Admiralty Inlet, Washington","linkHelpText":"Each GIS data file is listed with a brief description, a small image, and links to the metadata files and the downloadable data files."},{"id":300989,"rank":9,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1073/pdf/ofr20151073_pamphlet.pdf","text":"Pamphlet","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2015-1073 Pamphlet"},{"id":300990,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1073/pdf/ofr20151073_sheet1.pdf","text":"Sheet 1","size":"159 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2015-1073 Sheet 1","linkHelpText":"Bathymetry Map of the of Admiralty Inlet Map Area, Washington By Andrew C. Ritchie, Guy R. Cochrane, and Crescent Moegling"},{"id":300991,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1073/pdf/ofr20151073_sheet2.pdf","text":"Sheet 2","size":"121 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2015-1073 Sheet 2","linkHelpText":"CMECS Geoform Component Map of the Admiralty Inlet Map Area, Washington By Timothy O. Hodson, Guy R. Cochrane, Andrew C. Ritchie, and Crescent Moegling"},{"id":300994,"rank":8,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1073/ofr2015-1073_metadata.html","text":"Metadata"},{"id":300992,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1073/pdf/ofr20151073_sheet3.pdf","text":"Sheet 3","size":"121 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2015-1073 Sheet 3","linkHelpText":"CMECS Substrate Component Map of the Admiralty Inlet Map Area, Washington By Timothy O. Hodson, Guy R. Cochrane, Andrew C. 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2015 - Southern Salish Sea Habitat Map Series data catalog","interactions":[],"lastModifiedDate":"2015-06-03T09:22:22","indexId":"ds935","displayToPublicDate":"2015-06-03T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"935","title":"Southern Salish Sea Habitat Map Series data catalog","docAbstract":"In 2010, the U.S. Environmental Protection Agency, Region 10 initiated the Puget Sound Scientific Studies and Technical Investigations Assistance Program, which was designed to support research for implementing the Puget Sound Action Agenda. The Action Agenda was created because Puget Sound was designated as one of 28 estuaries of National Significance under section 320 of the Clean Water Act, and its overall goal is to restore the environment of the Puget Sound Estuary by 2020. The Southern Salish Sea Mapping Project was funded through the Assistance Program request for proposal process which also supports a large number of coastal-zone- and ocean-management issues, and includes the recommendations of the Marine Protected Areas Work Group to the Washington State Legislature. These recommendations include a Puget Sound and coast-wide marine conservation needs assessment, gap analysis of existing Marine Protected Areas and recommendations for action.
\nFour areas with recently acquired National Ocean Service hydrographic data are included in the Southern Salish Sea Habitat Map Series (fig. 1), each to be published individually as USGS Open File Reports at a scale of 1:40,000. The map products display seafloor geoforms, substrate, and biotopes using the Coastal and Marine Ecological Classification Standard.
\nThis data catalog contains much of the data used to prepare the SIMs in the Southern Salish Sea Habitat Map Series. Other data that were used to prepare the maps were compiled from previously published sources (for example, sediment samples and seismic reflection profiles) and are not included in this data series.
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We conducted laboratory microcosm experiments and computer simulations with larvae of the burrowing benthic midge Chironomus plumosus to quantify burrow oxygen uptake rates and subsequent contribution to sediment oxygen demand in central Lake Erie. Burrow oxygen uptake and water flow velocities through burrows were measured using oxygen microelectrodes and hot film anemometry, respectively. Burrow oxygen consumption averaged 2.66 × 10− 10 (SE = ± 7.82 × 10− 11) mol O2/burrow/s at 24 °C and 9.64 × 10− 10 (SE = ± 4.86 × 10− 10) mol O2/burrow/s at 15 °C. In sealed microcosm experiments, larvae increased SOD 500% at 24 °C (density = 1508/m2) and 375% at 15 °C (density = 864/m2). To further evaluate effects of densities of C. plumosus burrows on SOD we developed a 3-D transport reaction model of the process. Using experimental data and chironomid abundance data in faunal surveys in 2009 and 2010, we estimated that bioirrigation by a population of 140 larvae/m2 could account for between 2.54 × 10− 11 mol/L/s (model results) and 5.58 × 10− 11 mol/L/s (experimental results) of the average 4.22 × 10− 11 mol/L/s oxygen depletion rate between 1970 and 2003, which could have accounted for 60–132% of the oxygen decline. At present, it appears that the population density of this species may be an important factor in development of hypoxic or anoxic conditions in central Lake Erie.
","language":"English","publisher":"International Association for Great Lakes Research","publisherLocation":"Toronto","doi":"10.1016/j.jglr.2015.02.008","collaboration":"Soster (senior author; DePauw Univ), Matisoff (Case Western Univ), Edwards (Univ Niagara)","usgsCitation":"Soster, F.M., Matisoff, G., Schloesser, D.W., and Edwards, W.J., 2015, Potential impact of Chironomus plumosus larvae on hypolimnetic oxygen in the central basin of Lake Erie: Journal of Great Lakes Research, v. 41, no. 2, p. 348-357, https://doi.org/10.1016/j.jglr.2015.02.008.","productDescription":"10 p.","startPage":"348","endPage":"357","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061609","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":313069,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.31986999511719,\n 41.43088670022892\n ],\n [\n -82.35557556152344,\n 41.426768045309\n ],\n [\n -82.38922119140625,\n 41.415440397070654\n ],\n [\n -82.43110656738281,\n 41.39741506646461\n ],\n [\n -82.47367858886717,\n 41.38299120166604\n ],\n [\n -82.51075744628906,\n 41.38196080315539\n ],\n [\n -82.55538940429688,\n 41.396384896536276\n ],\n [\n -82.58834838867188,\n 41.41235069554362\n ],\n [\n -82.60688781738281,\n 41.41852995163519\n ],\n [\n -82.65151977539062,\n 41.57025176609894\n ],\n [\n -82.63984680175781,\n 41.645722822493845\n ],\n [\n -82.54989624023438,\n 41.67342470920953\n ],\n [\n -82.48260498046875,\n 41.668808555620586\n ],\n [\n -82.35626220703124,\n 41.64623592868676\n ],\n [\n -82.29515075683594,\n 41.58925619641459\n ],\n [\n -82.3040771484375,\n 41.48389104267175\n ],\n [\n -82.31986999511719,\n 41.43088670022892\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56850ee1e4b0a04ef4933a9e","contributors":{"authors":[{"text":"Soster, Frederick M.","contributorId":9092,"corporation":false,"usgs":true,"family":"Soster","given":"Frederick","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":583873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matisoff, Gerald","contributorId":15046,"corporation":false,"usgs":true,"family":"Matisoff","given":"Gerald","email":"","affiliations":[],"preferred":false,"id":583874,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schloesser, Donald W. dschloesser@usgs.gov","contributorId":3579,"corporation":false,"usgs":true,"family":"Schloesser","given":"Donald","email":"dschloesser@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583872,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edwards, William J.","contributorId":47206,"corporation":false,"usgs":true,"family":"Edwards","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":583875,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70144300,"text":"70144300 - 2015 - Coupling geophysical investigation with hydrothermal modeling to constrain the enthalpy classification of a potential geothermal resource.","interactions":[],"lastModifiedDate":"2015-10-23T12:34:52","indexId":"70144300","displayToPublicDate":"2015-06-01T13:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Coupling geophysical investigation with hydrothermal modeling to constrain the enthalpy classification of a potential geothermal resource.","docAbstract":"An appreciable challenge in volcanology and geothermal resource development is to understand the relationships between volcanic systems and low-enthalpy geothermal resources. The enthalpy of an undeveloped geothermal resource in the Karckar region of Armenia is investigated by coupling geophysical and hydrothermal modeling. The results of 3-dimensional inversion of gravity data provide key inputs into a hydrothermal circulation model of the system and associated hot springs, which is used to evaluate possible geothermal system configurations. Hydraulic and thermal properties are specified using maximum a priori estimates. Limited constraints provided by temperature data collected from an existing down-gradient borehole indicate that the geothermal system can most likely be classified as low-enthalpy and liquid dominated. We find the heat source for the system is likely cooling quartz monzonite intrusions in the shallow subsurface and that meteoric recharge in the pull-apart basin circulates to depth, rises along basin-bounding faults and discharges at the hot springs. While other combinations of subsurface properties and geothermal system configurations may fit the temperature distribution equally well, we demonstrate that the low-enthalpy system is reasonably explained based largely on interpretation of surface geophysical data and relatively simple models.
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This study reviews two published pit lake modeling studies and one pit lake monitoring program in order to increase the transparency of approaches used in pit lake prediction and management. The first model is a two-year limnological simulation of the existing Dexter pit lake, Nevada, USA that accurately modeled temperature profiles, salinity profiles, and turnover events observed between 1999 and 2000. The second model is a 55-year prediction of a future pit lake in the Martha Mine, New Zealand that identified the need for additional mitigation and evaluated potential effects of cost-effective mitigation options. The final study reviews eight years of monitoring data collected from the Berkeley pit lake, Montana, USA, from 2004 to 2012. This study identifies changes in the physical limnology and water quality of the pit lake that resulted from metal recovery operations, and highlights the value of monitoring programs in general. Whereas these pit lakes are different in many ways, the management tools discussed herein maximized the value and understanding of the post-mining resources.
Pit lakes are permanent hydrologic/landscape features that can result from open pit mining for metals, coal, uranium, diamonds, oil sands, and aggregates. Risks associated with pit lakes include local and regional impacts to water quality and related impacts to aquatic and terrestrial ecosystems. Stakeholders rely on predictive models of water chemistry to prepare for and manage these risks. This paper is the first of a two part series on the modeling and management of pit lakes. Herein, we review approaches that have been used to quantify wall-rock runoff geochemistry, wall-rock leachate geochemistry, pit lake water balance, pit lake limnology (i.e. extent of vertical mixing), and pit lake water quality, and conclude with guidance on the application of models within the mine life cycle. The purpose of this paper is to better prepare stakeholders, including future modelers, mine managers, consultants, permitting agencies, land management agencies, regulators, research scientists, academics, and other interested parties, for the challenges of predicting and managing future pit lakes in un-mined areas.
Regional stream and pond sediment, panned concentrate, and water sampling at and around known mineral occurrences in the Tyonek quadrangle, Alaska Range, Alaska were undertaken to determine geochemical signatures in the different media. For sediment samples, two different size fractions (− 80 mesh and − 230 mesh) were analyzed. Elevated concentrations (mostly ~ 2 × median) of elements such as As, Au, Cd, Cu, Mo, Pb, and/or Zn were measured in both size fractions in streams draining known occurrences as well as from several other locations. Gold, molybdenite, arsenopyrite, and/or Cu minerals identified in panned concentrates explain some of these elevated values. Water samples from most stream, pond and seep sediment sample sites were analyzed by high-resolution ICP-MS methodology. Relative high concentrations of constituents (including Mo, Re, As, Tl, and/or Cu and/or SO4) were commonly measured in waters where high metal concentrations were also measured in corresponding sediments and/or heavy mineral concentrates. However, water chemistry yielded higher contrast of upper quartile and anomalous groups relative to median values than observed in sediments. Elevated As, Mo and/or Re probably relate both to deposit mineralogy and the higher solubility of these metals (compared to that of Cu, Pb, Zn) under the predominantly oxidized and near-neutral pH conditions. Our pilot study indicates that, despite large input of snowmelt and very low absolute concentrations (μg/L), water chemistry can be useful for delineating sulfide-bearing mineral occurrences in this region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gexplo.2015.05.014","usgsCitation":"Graham, G.E., Taylor, R.D., Lee, G.K., and Tripp, D., 2015, Targeting Cu–Au and Mo resources using multi-media exploration geochemistry: An example from Tyonek Quadrangle, Alaska Range, Alaska: Journal of Geochemical Exploration, v. 157, p. 52-65, https://doi.org/10.1016/j.gexplo.2015.05.014.","productDescription":"14 p.","startPage":"52","endPage":"65","ipdsId":"IP-056638","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":366531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Tyonek Quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -152.9901123046875,\n 61.902752284767615\n ],\n [\n -151.28173828125,\n 61.902752284767615\n ],\n [\n -151.28173828125,\n 62.80246795273706\n ],\n [\n -152.9901123046875,\n 62.80246795273706\n ],\n [\n -152.9901123046875,\n 61.902752284767615\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"157","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Graham, Garth E. 0000-0003-0657-0365 ggraham@usgs.gov","orcid":"https://orcid.org/0000-0003-0657-0365","contributorId":1031,"corporation":false,"usgs":true,"family":"Graham","given":"Garth","email":"ggraham@usgs.gov","middleInitial":"E.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":548142,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Ryan D. 0000-0002-8845-5290 rtaylor@usgs.gov","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":3412,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan","email":"rtaylor@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":548143,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Gregory K. glee@usgs.gov","contributorId":1220,"corporation":false,"usgs":true,"family":"Lee","given":"Gregory","email":"glee@usgs.gov","middleInitial":"K.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":548144,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tripp, Dick","contributorId":141057,"corporation":false,"usgs":false,"family":"Tripp","given":"Dick","email":"","affiliations":[{"id":13665,"text":"USGS contractor (deceased)","active":true,"usgs":false}],"preferred":false,"id":548145,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70155261,"text":"70155261 - 2015 - The leading mode of observed and CMIP5 ENSO-residual sea surface temperatures and associated changes in Indo-Pacific climate","interactions":[],"lastModifiedDate":"2018-03-27T13:00:12","indexId":"70155261","displayToPublicDate":"2015-06-01T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2216,"text":"Journal of Climate","active":true,"publicationSubtype":{"id":10}},"title":"The leading mode of observed and CMIP5 ENSO-residual sea surface temperatures and associated changes in Indo-Pacific climate","docAbstract":"SSTs in the western Pacific Ocean have tracked closely with CMIP5 simulations despite recent hiatus cooling in the eastern Pacific. This paper quantifies these similarities and associated circulation and precipitation variations using the first global 1900–2012 ENSO-residual empirical orthogonal functions (EOFs) of 35 variables: observed SSTs; 28 CMIP5 SST simulations; Simple Ocean Data Assimilation (SODA) 25-, 70-, and 171-m ocean temperatures and sea surface heights (SSHs); and Twentieth Century Reanalysis, version 2 (20CRv2), surface winds and precipitation.
\nWhile estimated independently, these leading EOFs across all variables fit together in a meaningful way, and the authors refer to them jointly as the west Pacific warming mode (WPWM). WPWM SST EOFs correspond closely in space and time. Their spatial patterns form a “western V” extending from the Maritime Continent into the extratropical Pacific. Their temporal principal components (PCs) have increased rapidly since 1990; this increase has been primarily due to radiative forcing and not natural decadal variability.
\nWPWM circulation changes appear consistent with a Matsuno–Gill-like atmospheric response associated with an ocean–atmosphere dipole structure contrasting increased (decreased) western (eastern) Pacific precipitation, SSHs, and ocean temperatures. These changes have enhanced the Walker circulation and modulated weather on a global scale. An AGCM experiment and the WPWM of global boreal spring precipitation indicate significant drying across parts of East Africa, the Middle East, the southwestern United States, southern South America, and Asia. Changes in the WPWM have tracked closely with precipitation and the increase in drought frequency over the semiarid and water-insecure areas of East Africa, the Middle East, and southwest Asia.
","language":"English","publisher":"American Meteorological Society","publisherLocation":"Boston, MA","doi":"10.1175/JCLI-D-14-00334.1","usgsCitation":"Funk, C.C., and Hoell. Andrew, 2015, The leading mode of observed and CMIP5 ENSO-residual sea surface temperatures and associated changes in Indo-Pacific climate: Journal of Climate, v. 28, no. 11, p. 4309-4329, https://doi.org/10.1175/JCLI-D-14-00334.1.","productDescription":"21 p.","startPage":"4309","endPage":"4329","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056779","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":306492,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"11","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-27","publicationStatus":"PW","scienceBaseUri":"57f7ef1ae4b0bc0bec09eee2","contributors":{"authors":[{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565415,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoell. Andrew","contributorId":145831,"corporation":false,"usgs":false,"family":"Hoell. Andrew","affiliations":[{"id":13549,"text":"UC Santa Barbara Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565416,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148616,"text":"70148616 - 2015 - Movement ecology of five Afrotropical waterfowl species from Malawi, Mali and Nigeria","interactions":[],"lastModifiedDate":"2018-02-06T12:41:28","indexId":"70148616","displayToPublicDate":"2015-06-01T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2970,"text":"Ostrich","active":true,"publicationSubtype":{"id":10}},"title":"Movement ecology of five Afrotropical waterfowl species from Malawi, Mali and Nigeria","docAbstract":"Habitat availability for Afrotropical waterbirds is highly dynamic with unpredictable rainfall patterns and ephemeral wetlands resulting in diverse movement strategies among different species. Movement strategies among waterfowl encompass resident, regional and intercontinental migrants, but little quantitative information exists on their specific movement patterns. We studied the movement ecology of five Afrotropical waterfowl species marked with satellite transmitters in Malawi, Mali and Nigeria. Resident species, including White-faced Whistling Ducks Dendrocygna viduata, Fulvous Whistling Ducks Dendrocygna bicolor and Spur-winged Geese Plectropterus gambensis, remained sedentary during the rainy season and only flew limited distances during other months. In contrast, Knob-billed Ducks Sarkidiornis melanotos made short regional movements >50 km in all months and showed little site fidelity to previously used habitats in subsequent years. Garganey Anas quequedula followed an intercontinental strategy and made long-distance jumps across the Sahara and Mediterranean to their Eurasian breeding grounds. Most species flew farthest during the dry season, as mean daily movements varied from 1.5 to 14.2 km and was greatest in the winter months (January-March). Total distance moved varied from 9.5 km for White-faced Whistling Ducks (October-December) to 45.6 km for Knob-billed Ducks (April-June). Nomadic behaviour by Knob-billed Ducks was evidenced by long exploratory flights, but small mean daily movements suggested that they were relying on previous experience. Improving our understanding of these movement strategies increases our ability to assess connectivity of wetland resources that support waterfowl throughout their annual cycle and focuses conservation efforts on their most important habitats.
","language":"English","publisher":"Taylor & Francis","publisherLocation":"London","doi":"10.2989/00306525.2015.1033773","usgsCitation":"Takekawa, J.Y., Heath, S., Iverson, S.R., Gaidet, N., Cappelle, J., Dodman, T., Hagemeijer, W., Eldridge, W., Petrie, S.A., Yarris, G., Manu, S., Olsen, G.H., Prosser, D.J., Spragens, K.A., Douglas, D.C., and Newman, S.H., 2015, Movement ecology of five Afrotropical waterfowl species from Malawi, Mali and Nigeria: Ostrich, v. 86, no. 1-2, p. 155-168, https://doi.org/10.2989/00306525.2015.1033773.","productDescription":"14 p.","startPage":"155","endPage":"168","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063584","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":305717,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Malawi, Mali, Nigeria","otherGeospatial":"Hadejia-Nguru Wetlands, Inner Niger Delta, Lake Chad Basin, Lake Chilwa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 33.782958984375,\n -14.519780046326073\n ],\n [\n 33.782958984375,\n -9.308148692484803\n ],\n [\n 35.39794921875,\n -9.308148692484803\n ],\n [\n 35.39794921875,\n -14.519780046326073\n ],\n [\n 33.782958984375,\n -14.519780046326073\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -4.74609375,\n 14.668625907385902\n ],\n [\n -4.74609375,\n 16.804541076383455\n ],\n [\n -2.48291015625,\n 16.804541076383455\n ],\n [\n -2.48291015625,\n 14.668625907385902\n ],\n [\n -4.74609375,\n 14.668625907385902\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 13.38134765625,\n 12.618897304044024\n ],\n [\n 13.38134765625,\n 13.27202630119995\n ],\n [\n 14.765625,\n 13.27202630119995\n ],\n [\n 14.765625,\n 12.618897304044024\n ],\n [\n 13.38134765625,\n 12.618897304044024\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"86","issue":"1-2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-15","publicationStatus":"PW","scienceBaseUri":"55a632abe4b0183d66e45cc9","contributors":{"authors":[{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":548893,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heath, Shane R.","contributorId":72263,"corporation":false,"usgs":true,"family":"Heath","given":"Shane R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":548894,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iverson, S. 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2015 - Potential effects of climate change on the growth of fishes from different thermal guilds in Lakes Michigan and Huron","interactions":[],"lastModifiedDate":"2015-07-10T13:24:36","indexId":"70148566","displayToPublicDate":"2015-06-01T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Potential effects of climate change on the growth of fishes from different thermal guilds in Lakes Michigan and Huron","docAbstract":"We used a bioenergetics modeling approach to investigate potential effects of climate change on the growth of two economically important native fishes: yellow perch (Perca flavescens), a cool-water fish, and lake whitefish (Coregonus clupeaformis), a cold-water fish, in deep and oligotrophic Lakes Michigan and Huron. For assessing potential changes in fish growth, we contrasted simulated fish growth in the projected future climate regime during the period 2043-2070 under different prey availability scenarios with the simulated growth during the baseline (historical reference) period 1964-1993. Results showed that effects of climate change on the growth of these two fishes are jointly controlled by behavioral thermoregulation and prey availability. With the ability of behavioral thermoregulation, temperatures experienced by yellow perch in the projected future climate regime increased more than those experienced by lake whitefish. Thus simulated future growth decreased more for yellow perch than for lake whitefish under scenarios where prey availability remains constant into the future. Under high prey availability scenarios, simulated future growth of these two fishes both increased but yellow perch could not maintain the baseline efficiency of converting prey consumption into body weight. We contended that thermal guild should not be the only factor used to predict effects of climate change on the growth of a fish, and that ecosystem responses to climate change should be also taken into account.
","language":"English","publisher":"International Association for Great Lakes Research","publisherLocation":"Toronto","doi":"10.1016/j.jglr.2015.03.012","usgsCitation":"Kao, Y., Madenjian, C.P., Bunnell, D., Lofgren, B.M., and Perroud, M., 2015, Potential effects of climate change on the growth of fishes from different thermal guilds in Lakes Michigan and Huron: Journal of Great Lakes Research, v. 41, no. 2, p. 423-435, https://doi.org/10.1016/j.jglr.2015.03.012.","productDescription":"13 p.","startPage":"423","endPage":"435","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052585","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":301220,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Huron, Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":548645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bunnell, David B. dbunnell@usgs.gov","contributorId":141167,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":548647,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lofgren, Brent M.","contributorId":139534,"corporation":false,"usgs":false,"family":"Lofgren","given":"Brent","email":"","middleInitial":"M.","affiliations":[{"id":12789,"text":"NOAA Great Lakes Environmental Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":548648,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Perroud, Marjorie","contributorId":139535,"corporation":false,"usgs":false,"family":"Perroud","given":"Marjorie","email":"","affiliations":[{"id":12790,"text":"Cooperative Institute for Limnology and Ecosystems Research, University of Michigan","active":true,"usgs":false}],"preferred":false,"id":548649,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70148564,"text":"70148564 - 2015 - Predicting alpine headwater stream intermittency: a case study in the northern Rocky Mountains","interactions":[],"lastModifiedDate":"2015-09-16T09:26:57","indexId":"70148564","displayToPublicDate":"2015-06-01T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3892,"text":"Ecohydrology & Hydrobiology","active":true,"publicationSubtype":{"id":10}},"title":"Predicting alpine headwater stream intermittency: a case study in the northern Rocky Mountains","docAbstract":"This investigation used climatic, geological, and environmental data coupled with observational stream intermittency data to predict alpine headwater stream intermittency. Prediction was made using a random forest classification model. Results showed that the most important variables in the prediction model were snowpack persistence, represented by average snow extent from March through July, mean annual mean monthly minimum temperature, and surface geology types. For stream catchments with intermittent headwater streams, snowpack, on average, persisted until early June, whereas for stream catchments with perennial headwater streams, snowpack, on average, persisted until early July. Additionally, on average, stream catchments with intermittent headwater streams were about 0.7 °C warmer than stream catchments with perennial headwater streams. Finally, headwater stream catchments primarily underlain by coarse, permeable sediment are significantly more likely to have intermittent headwater streams than those primarily underlain by impermeable bedrock. Comparison of the predicted streamflow classification with observed stream status indicated a four percent classification error for first-order streams and a 21 percent classification error for all stream orders in the study area.
","language":"English","publisher":"International Centre for Ecology","publisherLocation":"Warsaw","doi":"10.1016/j.ecohyd.2015.04.002","usgsCitation":"Sando, R., and Blasch, K.W., 2015, Predicting alpine headwater stream intermittency: a case study in the northern Rocky Mountains: Ecohydrology & Hydrobiology, v. 15, no. 2, p. 68-80, https://doi.org/10.1016/j.ecohyd.2015.04.002.","productDescription":"13 p.","startPage":"68","endPage":"80","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052878","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":301221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557ff73ae4b023124e8ef98a","contributors":{"authors":[{"text":"Sando, Roy 0000-0003-0704-6258","orcid":"https://orcid.org/0000-0003-0704-6258","contributorId":3874,"corporation":false,"usgs":true,"family":"Sando","given":"Roy","email":"","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":548640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blasch, Kyle W. 0000-0002-0590-0724 kblasch@usgs.gov","orcid":"https://orcid.org/0000-0002-0590-0724","contributorId":1631,"corporation":false,"usgs":true,"family":"Blasch","given":"Kyle","email":"kblasch@usgs.gov","middleInitial":"W.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548641,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148400,"text":"70148400 - 2015 - Biodynamics of copper oxide nanoparticles and copper ions in an oligochaete: Part I: relative importance of water and sediment as exposure routes","interactions":[],"lastModifiedDate":"2018-09-04T16:24:31","indexId":"70148400","displayToPublicDate":"2015-06-01T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":874,"text":"Aquatic Toxicology","active":true,"publicationSubtype":{"id":10}},"title":"Biodynamics of copper oxide nanoparticles and copper ions in an oligochaete: Part I: relative importance of water and sediment as exposure routes","docAbstract":"Copper oxide (CuO) nanoparticles (NPs) are widely used, and likely released into the aquatic environment. Both aqueous (i.e., dissolved Cu) and particulate Cu can be taken up by organisms. However, how exposure routes influence the bioavailability and subsequent toxicity of Cu remains largely unknown. Here, we assess the importance of exposure routes (water and sediment) and Cu forms (aqueous and nanoparticulate) on Cu bioavailability and toxicity to the freshwater oligochaete, Lumbriculus variegatus, a head-down deposit-feeder. We characterize the bioaccumulation dynamics of Cu in L. variegatus across a range of exposure concentrations, covering both realistic and worst-case levels of Cu contamination in the environment. Both aqueous Cu (Cu-Aq; administered as Cu(NO3)2) and nanoparticulate Cu (CuO NPs), whether dispersed in artificial moderately hard freshwater or mixed into sediment, were weakly accumulated by L. variegatus. Once incorporated into tissues, Cu elimination was negligible, i.e., elimination rate constants were in general not different from zero for either exposure route or either Cu form. Toxicity was only observed after waterborne exposure to Cu-Aq at very high concentration (305 µgL-1), where all worms died. There was no relationship between exposure route, Cu form or Cu exposure concentration on either worm survival or growth. Slow feeding rates and low Cu assimilation efficiency (approximately 30%) characterized the uptake of Cu from the sediment for both Cu forms. In nature, L. variegatus is potentially exposed to Cu via both water and sediment. However, sediment progressively becomes the predominant exposure route for Cu in L. variegatus as Cu partitioning to sediment increases.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.aquatox.2015.04.022","usgsCitation":"Ramskov, T., Thit, A., Croteau, M.N., and Selck, H., 2015, Biodynamics of copper oxide nanoparticles and copper ions in an oligochaete: Part I: relative importance of water and sediment as exposure routes: Aquatic Toxicology, v. 164, p. 81-91, https://doi.org/10.1016/j.aquatox.2015.04.022.","productDescription":"11 p.","startPage":"81","endPage":"91","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061794","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":300967,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"164","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"556ed3b7e4b0d9246a9fa7c7","contributors":{"authors":[{"text":"Ramskov, Tina","contributorId":140202,"corporation":false,"usgs":false,"family":"Ramskov","given":"Tina","email":"","affiliations":[{"id":13410,"text":"Department of Environmental, Social and Spatial Change, Roskilde University, PO Box 260, Universitetsvej 1, DK-4000 Roskilde, Denmark","active":true,"usgs":false}],"preferred":false,"id":547998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thit, Amalie","contributorId":141022,"corporation":false,"usgs":false,"family":"Thit","given":"Amalie","email":"","affiliations":[{"id":13657,"text":"Department of Environmental, Social and Spatial Change, Roskilde University, Denmark","active":true,"usgs":false}],"preferred":false,"id":547999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Croteau, Marie Noele 0000-0003-0346-3580 mcroteau@usgs.gov","orcid":"https://orcid.org/0000-0003-0346-3580","contributorId":895,"corporation":false,"usgs":true,"family":"Croteau","given":"Marie","email":"mcroteau@usgs.gov","middleInitial":"Noele","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":547997,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Selck, Henriette","contributorId":28475,"corporation":false,"usgs":false,"family":"Selck","given":"Henriette","affiliations":[{"id":13410,"text":"Department of Environmental, Social and Spatial Change, Roskilde University, PO Box 260, Universitetsvej 1, DK-4000 Roskilde, Denmark","active":true,"usgs":false}],"preferred":false,"id":548000,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70148545,"text":"70148545 - 2015 - Nearshore dynamics of artificial sand and oil agglomerates","interactions":[],"lastModifiedDate":"2015-06-12T09:41:14","indexId":"70148545","displayToPublicDate":"2015-06-01T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Nearshore dynamics of artificial sand and oil agglomerates","docAbstract":"Weathered oil can mix with sediment to form heavier-than-water sand and oil agglomerates (SOAs) that can cause beach re-oiling for years after a spill. Few studies have focused on the physical dynamics of SOAs. In this study, artificial SOAs (aSOAs) were created and deployed in the nearshore, and shear stress-based mobility formulations were assessed to predict SOA response. Prediction sensitivity to uncertainty in hydrodynamic conditions and shear stress parameterizations were explored. Critical stress estimates accounting for large particle exposure in a mixed bed gave the best predictions of mobility under shoaling and breaking waves. In the surf zone, the 10-cm aSOA was immobile and began to bury in the seafloor while smaller size classes dispersed alongshore. aSOAs up to 5 cm in diameter were frequently mobilized in the swash zone. The uncertainty in predicting aSOA dynamics reflects a broader uncertainty in applying mobility and transport formulations to cm-sized particles.
","language":"English","publisher":"International Conference on the Environmental Management of Enclosed Coastal Seas","publisherLocation":"London, England","doi":"10.1016/j.marpolbul.2015.04.049","usgsCitation":"Dalyander, P.S., Plant, N.G., Long, J.W., and McLaughlin, M.R., 2015, Nearshore dynamics of artificial sand and oil agglomerates: Marine Pollution Bulletin, v. 96, no. 1-2, p. 344-355, https://doi.org/10.1016/j.marpolbul.2015.04.049.","productDescription":"12 p.","startPage":"344","endPage":"355","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065022","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438692,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z2XFRJ","text":"USGS data release","linkHelpText":"Laboratory Observations of Variable Size and Shape Particles: Artificial Sand and Oil Agglomerates"},{"id":301185,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"96","issue":"1-2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557c02d9e4b023124e8edf2c","contributors":{"authors":[{"text":"Dalyander, P. Soupy 0000-0001-9583-0872 sdalyander@usgs.gov","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":141015,"corporation":false,"usgs":true,"family":"Dalyander","given":"P.","email":"sdalyander@usgs.gov","middleInitial":"Soupy","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":548559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":548560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, Joseph W. 0000-0003-2912-1992 jwlong@usgs.gov","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":3303,"corporation":false,"usgs":true,"family":"Long","given":"Joseph","email":"jwlong@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":548561,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McLaughlin, Molly R. 0000-0001-6962-6392 mmclaughlin@usgs.gov","orcid":"https://orcid.org/0000-0001-6962-6392","contributorId":4089,"corporation":false,"usgs":true,"family":"McLaughlin","given":"Molly","email":"mmclaughlin@usgs.gov","middleInitial":"R.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":548562,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70148412,"text":"70148412 - 2015 - Characteristics of storms driving wave-induced seafloor mobility on the U.S. East Coast continental shelf","interactions":[],"lastModifiedDate":"2015-06-02T09:48:13","indexId":"70148412","displayToPublicDate":"2015-06-01T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Characteristics of storms driving wave-induced seafloor mobility on the U.S. East Coast continental shelf","docAbstract":"This study investigates the relationship between spatial and temporal patterns of wave-driven sediment mobility events on the U.S. East Coast continental shelf and the characteristics of the storms responsible for them. Mobility events, defined as seafloor wave stress exceedance of the critical stress of 0.35 mm diameter sand (0.2160 Pa) for 12 or more hours, were identified from surface wave observations at National Data Buoy Center buoys in the Middle Atlantic Bight (MAB) and South Atlantic Bight (SAB) over the period of 1997-2007. In water depths ranging from 36-48 m, there were 4-9 mobility events/year of 1-2 days duration. Integrated wave stress during events (IWAVES) was used as a combined metric of wave-driven mobility intensity and duration. In the MAB, over 67% of IWAVES was caused by extratropical storms, while in the SAB, greater than 66% of IWAVES was caused by tropical storms. On average, mobility events were caused by waves generated by storms located 800+ km away. Far-field hurricanes generated swell 2-4 days before the waves caused mobility on the shelf. Throughout most of the SAB, mobility events were driven by storms to the south, east, and west. In the MAB and near Cape Hatteras, winds from more northerly storms and low-pressure extratropical systems in the mid-western U.S. also drove mobility events. Waves generated by storms off the SAB generated mobility events along the entire U.S. East Coast shelf north to Cape Cod, while Cape Hatteras shielded the SAB area from swell originating to the north offshore of the MAB.
","language":"English","publisher":"North Pacific Marine Science Organization","publisherLocation":"New York, NY","doi":"10.1016/j.csr.2015.05.003","usgsCitation":"Dalyander, P.S., and Butman, B., 2015, Characteristics of storms driving wave-induced seafloor mobility on the U.S. East Coast continental shelf: Continental Shelf Research, v. 104, p. 1-14, https://doi.org/10.1016/j.csr.2015.05.003.","productDescription":"14 p.","startPage":"1","endPage":"14","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062841","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":472042,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2015.05.003","text":"Publisher Index Page"},{"id":300965,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"104","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"556ed3b8e4b0d9246a9fa7cc","chorus":{"doi":"10.1016/j.csr.2015.05.003","url":"http://dx.doi.org/10.1016/j.csr.2015.05.003","publisher":"Elsevier BV","authors":"Dalyander P. Soupy, Butman Bradford","journalName":"Continental Shelf Research","publicationDate":"8/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Dalyander, P. Soupy 0000-0001-9583-0872 sdalyander@usgs.gov","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":141015,"corporation":false,"usgs":true,"family":"Dalyander","given":"P.","email":"sdalyander@usgs.gov","middleInitial":"Soupy","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":548062,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Butman, Bradford 0000-0002-4174-2073 bbutman@usgs.gov","orcid":"https://orcid.org/0000-0002-4174-2073","contributorId":943,"corporation":false,"usgs":true,"family":"Butman","given":"Bradford","email":"bbutman@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":548063,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}