{"pageNumber":"311","pageRowStart":"7750","pageSize":"25","recordCount":40783,"records":[{"id":70205666,"text":"70205666 - 2019 - Regionalization of groundwater residence time using metamodeling","interactions":[],"lastModifiedDate":"2019-10-02T11:09:04","indexId":"70205666","displayToPublicDate":"2019-10-02T11:00:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Regionalization of groundwater residence time using metamodeling","docAbstract":"Groundwater residence-time distributions (RTDs) are critical for assessing susceptibility of water resources to degradation. A novel combination of numerical modeling and statistical methods allows estimation of regional RTDs with unprecedented speed.  In this method, particle RTDs are generated in 30 type locales in the northeastern glaciated U.S using automated generalized finite-difference groundwater flow and advective transport models. Targets for statistical learning were created from particle RTDs by fitting Weibull, gamma, and inverse Gaussian distributions. Whole-basin flux-weighted RTDs were well fit by one-component Weibull distributions. Flux-weighted RTDs at stressed receptors such as wells often produced more complicated RTDs that required a two-component mixture to fit. A Multitask Lasso regression was trained on the parametric RTDs using hydrogeographic features of the modeled areas as explanatory features. In this way, RTDs are regionalized using mappable physical features such as recharge and aquifer volume. The shape, location, and scale parameters of the parametric RTDs are strongly related to the mean exponential age. The shape parameter of the distribution, which controls deviation from exponential, is additionally a function of aquifer heterogeneity and hydrologic features. Regionalized RTDs provide useful metrics with respect to groundwater lag times and solute loading to streams. The lag time between input and output contained in the RTD is critical to understanding the relation between the land surface and human and ecological receptors.","language":"English","publisher":"Wiley","doi":"10.1029/2017WR021531","usgsCitation":"Starn, J., and Belitz, K., 2019, Regionalization of groundwater residence time using metamodeling: Water Resources Research, v. 54, no. 9, p. 6357-6373, https://doi.org/10.1029/2017WR021531.","productDescription":"17 p.","startPage":"6357","endPage":"6373","ipdsId":"IP-086784","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":459636,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017wr021531","text":"Publisher Index Page"},{"id":367916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"9","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Starn, J. Jeffrey 0000-0001-5909-0010 jjstarn@usgs.gov","orcid":"https://orcid.org/0000-0001-5909-0010","contributorId":1916,"corporation":false,"usgs":true,"family":"Starn","given":"J. Jeffrey","email":"jjstarn@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":false,"id":772025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":772026,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70215329,"text":"70215329 - 2019 - Genomic pedigree reconstruction identifies predictors of mating and reproductive success in an invasive vertebrate","interactions":[],"lastModifiedDate":"2020-10-16T14:03:28.428405","indexId":"70215329","displayToPublicDate":"2019-10-02T08:59:08","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Genomic pedigree reconstruction identifies predictors of mating and reproductive success in an invasive vertebrate","docAbstract":"<p><span>The persistence of an invasive species is influenced by its reproductive ecology, and a successful control program must operate on this premise. However, the reproductive ecology of invasive species may be enigmatic due to factors that also limit their management, such as cryptic coloration and behavior. We explored the mating and reproductive ecology of the invasive Brown Treesnake (BTS</span><i>: Boiga irregularis</i><span>) by reconstructing a multigenerational genomic pedigree based on 654 single nucleotide polymorphisms for a geographically closed population established in 2004 on Guam (</span><i>N</i><span>&nbsp;=&nbsp;426). The pedigree allowed annual estimates of individual mating and reproductive success to be inferred for snakes in the study population over a 14‐year period. We then employed generalized linear mixed models to gauge how well phenotypic and genomic data could predict sex‐specific annual mating and reproductive success. Average snout–vent length (SVL), average body condition index (BCI), and trappability were significantly related to annual mating success for males, with average SVL also related to annual mating success for females. Male and female annual reproductive success was positively affected by SVL, BCI, and trappability. Surprisingly, the degree to which individuals were inbred had no effect on annual mating or reproductive success. When juxtaposed with current control methods, these results indicate that baited traps, a common interdiction tool, may target fecund BTS in some regards but not others. Our study emphasizes the importance of reproductive ecology as a focus for improving BTS control and promotes genomic pedigree reconstruction for such an endeavor in this invasive species and others.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.5694","usgsCitation":"Levine, B., Douglas, M.R., Yackel Adams, A.A., Lardner, B., Reed, R., Savidge, J.A., and Douglas, M.E., 2019, Genomic pedigree reconstruction identifies predictors of mating and reproductive success in an invasive vertebrate: Ecology and Evolution, v. 9, no. 20, p. 11863-11877, https://doi.org/10.1002/ece3.5694.","productDescription":"15 p.","startPage":"11863","endPage":"11877","ipdsId":"IP-110981","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":459638,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5694","text":"Publisher Index Page"},{"id":437315,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X1AKVJ","text":"USGS data release","linkHelpText":"Brown Treesnake mating and reproductive success on Guam, 2004-2018"},{"id":379463,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Guam","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              144.86709594726562,\n              13.548212606976776\n            ],\n            [\n              144.9594497680664,\n              13.548212606976776\n            ],\n            [\n              144.9594497680664,\n              13.630138790321915\n            ],\n            [\n              144.86709594726562,\n              13.630138790321915\n            ],\n            [\n              144.86709594726562,\n              13.548212606976776\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"20","noUsgsAuthors":false,"publicationDate":"2019-10-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Levine, Brenna A","contributorId":243207,"corporation":false,"usgs":false,"family":"Levine","given":"Brenna A","affiliations":[{"id":38022,"text":"University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":801737,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas, Marlis R","contributorId":243208,"corporation":false,"usgs":false,"family":"Douglas","given":"Marlis","email":"","middleInitial":"R","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":801739,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":801738,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lardner, Bjorn","contributorId":225066,"corporation":false,"usgs":false,"family":"Lardner","given":"Bjorn","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":801740,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Robert 0000-0001-8349-6168 reedr@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":152301,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":801741,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Savidge, Julie A.","contributorId":175196,"corporation":false,"usgs":false,"family":"Savidge","given":"Julie","email":"","middleInitial":"A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":801742,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Douglas, Michael E","contributorId":243209,"corporation":false,"usgs":false,"family":"Douglas","given":"Michael","email":"","middleInitial":"E","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":801743,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70205764,"text":"70205764 - 2019 - In vitro immune function in laboratory-reared age-0 smallmouth bass (Micropterus dolomieu) relative to diet","interactions":[],"lastModifiedDate":"2020-01-03T10:15:03","indexId":"70205764","displayToPublicDate":"2019-10-01T16:55:06","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1644,"text":"Fish & Shellfish Immunology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"<i>In vitro</i> immune function in laboratory-reared age-0 smallmouth bass (<i>Micropterus dolomieu</i>) relative to diet","title":"In vitro immune function in laboratory-reared age-0 smallmouth bass (Micropterus dolomieu) relative to diet","docAbstract":"<p><span>Smallmouth bass (</span><i>Micropterus dolomieu</i><span>) are used as an indicator species in environmental monitoring and assessment studies. However, laboratory-based studies for methods development and effector assessment are limited for this species. Nutrition, a known modulator of teleost physiological responses including immune function, is a critical knowledge-gap sometimes overlooked in the design of laboratory studies. We report the results from a study evaluating a commercially available artificial pelleted diet for bass and live feed (fathead minnows). Following a six-month diet-acclimation period, age-0 smallmouth bass were assessed using morphometric measures, histologic and immune-function end points using conventional methods, miniaturized cell isolation and assay methods as well as imaging flow cytometry. Fish on the two diets did not significantly differ in length, weight, or condition factor, indicating that growth was similar in the two groups. Histologic examination revealed relatively higher levels of macrophage aggregates and accumulation of ceroid/lipofuscin in the spleen as well as hepatocyte changes in the pellet-fed group. Leukocytes from the pellet-fed group exhibited significantly elevated bactericidal activity and significantly depressed mitogen response compared to fish fed live feed. Following exposure to a known inducer of inflammatory responses, bacterial lipopolysaccharide, responses including the transition of leukocytes to an apoptotic/necrotic condition differed significantly based on diet. Histologic findings were consistent with the occurrence of diet-related oxidative stress in the pellet-fed fish. Oxidative stress can be induced by multiple factors including environmental pollutants. For a diet to be useful in laboratory-based studies, it cannot elicit response that could also be induced by experimental treatments. To do so greatly complicates the detection of experimental effects. Until an artificial diet is developed for smallmouth bass that does not produce potentially confounding conditions for laboratory-based studies, use of a live feed appears to be the best option.</span></p>","language":"English","publisher":"Elseiver","doi":"10.1016/j.fsi.2019.10.005","usgsCitation":"Ottinger, C., Smith, C.R., and Blazer, V., 2019, In vitro immune function in laboratory-reared age-0 smallmouth bass (Micropterus dolomieu) relative to diet: Fish & Shellfish Immunology, v. 95, p. 1-10, https://doi.org/10.1016/j.fsi.2019.10.005.","productDescription":"10 p.","startPage":"1","endPage":"10","ipdsId":"IP-109860","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":459644,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fsi.2019.10.005","text":"Publisher Index Page"},{"id":368726,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"95","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ottinger, Christopher 0000-0003-2551-1985","orcid":"https://orcid.org/0000-0003-2551-1985","contributorId":205874,"corporation":false,"usgs":true,"family":"Ottinger","given":"Christopher","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":772251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Cheyenne R. 0000-0002-7226-1774","orcid":"https://orcid.org/0000-0002-7226-1774","contributorId":219236,"corporation":false,"usgs":true,"family":"Smith","given":"Cheyenne","email":"","middleInitial":"R.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":772252,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":772253,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70227809,"text":"70227809 - 2019 - Landscape genetics reveals unique and shared effects of urbanization for two sympatric pool-breeding amphibians","interactions":[],"lastModifiedDate":"2022-02-01T20:31:57.099474","indexId":"70227809","displayToPublicDate":"2019-10-01T15:31:35","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Landscape genetics reveals unique and shared effects of urbanization for two sympatric pool-breeding amphibians","docAbstract":"<p>Metapopulation-structured species can be negatively affected when landscape fragmentation impairs connectivity. We investigated the effects of urbanization on genetic diversity and gene flow for two sympatric amphibian species, spotted salamanders (<i>Ambystoma maculatum</i>) and wood frogs (<i>Lithobates sylvaticus</i>), across a large (&gt;35,000 km<sup>2</sup>) landscape in Maine, USA, containing numerous natural and anthropogenic gradients. Isolation-by-distance (IBD) patterns differed between the species. Spotted salamanders showed a linear and relatively high variance relationship between genetic and geographic distances (<i>r</i> = .057, <i>p</i> &lt; .001), whereas wood frogs exhibited a strongly nonlinear and lower variance relationship (<i>r</i> = 0.429, <i>p</i> &lt; .001). Scale dependence analysis of IBD found gene flow has its most predictable influence (strongest IBD correlations) at distances up to 9 km for spotted salamanders and up to 6 km for wood frogs. Estimated effective migration surfaces revealed contrasting patterns of high and low genetic diversity and gene flow between the two species. Population isolation, quantified as the mean IBD residuals for each population, was associated with local urbanization and less genetic diversity in both species. The influence of geographic proximity and urbanization on population connectivity was further supported by distance-based redundancy analysis and multiple matrix regression with randomization. Resistance surface modeling found interpopulation connectivity to be influenced by developed land cover, light roads, interstates, and topography for both species, plus secondary roads and rivers for wood frogs. Our results highlight the influence of anthropogenic landscape features within the context of natural features and broad spatial genetic patterns, in turn supporting the premise that while urbanization significantly restricts interpopulation connectivity for wood frogs and spotted salamanders, specific landscape elements have unique effects on these two sympatric species.</p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.5685","usgsCitation":"Homola, J.J., Loftin, C., and Kinnison, M., 2019, Landscape genetics reveals unique and shared effects of urbanization for two sympatric pool-breeding amphibians: Ecology and Evolution, v. 9, no. 20, p. 11799-11823, https://doi.org/10.1002/ece3.5685.","productDescription":"25 p.","startPage":"11799","endPage":"11823","ipdsId":"IP-098892","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":459647,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5685","text":"Publisher Index Page"},{"id":395242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","city":"Bangor, Portland","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -70.57891845703125,\n              43.530629170442424\n            ],\n            [\n              -70.11474609375,\n              43.530629170442424\n            ],\n            [\n              -70.11474609375,\n              43.83650797709095\n            ],\n            [\n              -70.57891845703125,\n              43.83650797709095\n            ],\n            [\n              -70.57891845703125,\n              43.530629170442424\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -68.994140625,\n              44.67646564865964\n            ],\n            [\n              -68.57666015625,\n              44.67646564865964\n            ],\n            [\n              -68.57666015625,\n              44.953136827528816\n            ],\n            [\n              -68.994140625,\n              44.953136827528816\n            ],\n            [\n              -68.994140625,\n              44.67646564865964\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"20","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Homola, Jared J.","contributorId":264547,"corporation":false,"usgs":false,"family":"Homola","given":"Jared","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":832349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loftin, Cynthia S. 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":2167,"corporation":false,"usgs":true,"family":"Loftin","given":"Cynthia S.","email":"cyndy_loftin@usgs.gov","affiliations":[],"preferred":true,"id":832348,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kinnison, Michael T.","contributorId":264555,"corporation":false,"usgs":false,"family":"Kinnison","given":"Michael T.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":832350,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70217792,"text":"70217792 - 2019 - Burial history reconstruction of the Appalachian Basin in Kentucky, West Virginia, Ohio, Pennsylvania, and New York, using 1D petroleum system models","interactions":[],"lastModifiedDate":"2021-02-02T19:47:44.189506","indexId":"70217792","displayToPublicDate":"2019-10-01T14:47:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2789,"text":"Mountain Geologist","active":true,"publicationSubtype":{"id":10}},"title":"Burial history reconstruction of the Appalachian Basin in Kentucky, West Virginia, Ohio, Pennsylvania, and New York, using 1D petroleum system models","docAbstract":"<p class=\"indent\">Nine 1D burial history models were built across the Appalachian Basin to reconstruct the burial, erosional, and thermal maturation histories of contained petroleum source rocks. Models were calibrated to measured downhole temperature and to vitrinite reflectance (% R<sub>o</sub>) data from Devonian through Pennsylvanian petroleum source rocks. The highest levels of thermal maturity in Devonian and Mississippian source rocks are within and proximal to the Rome trough in the deep basin, which is also within the confluence of increased structural complexity and associated faulting, overpressured Devonian shales, and thick intervals of salt in the underlying Silurian Salina Group.</p><p class=\"indent\">Models incorporate minor erosion from 260 to 140 million years ago (Ma) that allows for extended burial and heating of underlying strata and generally results in less eroded thickness, compared to previously published models. Two modeled times of increased erosion, from 140 to 90 Ma and 23 to 5.3 Ma, are followed by less erosion from 5.3 Ma to Present. Absent strata are mainly Permian shales and sandstone; thickness of these removed layers increased from about 6,200 ft (1,890 m) west of the Rome trough to as much as 9,650 ft (2,940 m) within the trough. The onset of oil generation is based on 0.6% R<sub>o</sub><span>&nbsp;</span>for Pennsylvanian coal samples; time of onset for the Ordovician Utica Shale ranges from 387 to 306 Ma, and 359 to 282 Ma for Middle Devonian to basal Mississippian shales. The ∼1.2% R<sub>o</sub><span>&nbsp;</span>onset of wet gas generation ranges from 360 to 281 Ma in the Utica Shale, and 298 to 150 Ma for Middle Devonian to lowermost Mississippian shales.</p>","language":"English","publisher":"The Rocky Mountain Association of Geologists","doi":"10.31582/rmag.mg.56.4.365","usgsCitation":"Higley, D.K., and Enomoto, C.B., 2019, Burial history reconstruction of the Appalachian Basin in Kentucky, West Virginia, Ohio, Pennsylvania, and New York, using 1D petroleum system models: Mountain Geologist, v. 56, no. 4, p. 365-396, https://doi.org/10.31582/rmag.mg.56.4.365.","productDescription":"32 p.","startPage":"365","endPage":"396","ipdsId":"IP-098203","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":382896,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kentucky, New York, Ohio, Pennsylvania, West 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 \"}}]}","volume":"56","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-10-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Higley, Debra K. 0000-0001-8024-9954 higley@usgs.gov","orcid":"https://orcid.org/0000-0001-8024-9954","contributorId":152663,"corporation":false,"usgs":true,"family":"Higley","given":"Debra","email":"higley@usgs.gov","middleInitial":"K.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":809726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Enomoto, Catherine B. 0000-0002-4119-1953 cenomoto@usgs.gov","orcid":"https://orcid.org/0000-0002-4119-1953","contributorId":2126,"corporation":false,"usgs":true,"family":"Enomoto","given":"Catherine","email":"cenomoto@usgs.gov","middleInitial":"B.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science 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,{"id":70209090,"text":"70209090 - 2019 - Spatial fingerprinting of biogenic and anthropogenic volatile organic compounds in an arid unsaturated zone","interactions":[],"lastModifiedDate":"2020-03-16T06:20:18","indexId":"70209090","displayToPublicDate":"2019-10-01T13:42:44","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3674,"text":"Vadose Zone Journal","active":true,"publicationSubtype":{"id":10}},"title":"Spatial fingerprinting of biogenic and anthropogenic volatile organic compounds in an arid unsaturated zone","docAbstract":"Subsurface volatile organic compounds (VOCs) can pose risks to human and environmental health and mediate biological processes. VOCs have both anthropogenic and biogenic origins, but the relative importance of these sources has not been explored in subsurface environments. This study synthesizes 17 years of VOC data from the Amargosa Desert Research Site (ADRS) with the goal of improving understanding of spatial and temporal variations that distinguish sources of VOCs from a landfill and surrounding ambient sources including biogenic VOCs (bVOCs). Gas samples were collected from 1999 to 2016 from an array of shallow sample points (0.5 m and 1.5 m depth) and from vertical profiles at three deep boreholes, two (109 m deep) near the border of a waste facility (33 and 100 m distant), and one (29 m deep) in a remote area 3 km to the south. Samples were analyzed for target VOCs and a subset was analyzed for non-target VOCs to enumerate a greater variety of potential bVOCs. Principal components analysis of the target and non-target VOCs provided an assessment of spatial variability of VOCs originating from the landfill site and from ambient sources. Ambient VOCs occurred at all sample sites over a range of depths and most were consistent with biogenic origins, indicating, for the first time, presence of bVOCs in the deep unsaturated zone. Because some VOCs have both anthropogenic and biogenic sources, discrimination of sources can be important for estimating the extent and migration of anthropogenic plumes in arid unsaturated zones.","language":"English","publisher":"Wiley","doi":"10.2136/vzj2019.05.0047","usgsCitation":"Green, C., Luo, W., Conaway, C., Haase, K., Baker, R., and Andraski, B.J., 2019, Spatial fingerprinting of biogenic and anthropogenic volatile organic compounds in an arid unsaturated zone: Vadose Zone Journal, v. 18, no. 1, 190047, https://doi.org/10.2136/vzj2019.05.0047.","productDescription":"190047","ipdsId":"IP-106246","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":459654,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2136/vzj2019.05.0047","text":"Publisher Index Page"},{"id":373272,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","county":"Nye County","otherGeospatial":"Amargosa Desert Research Site","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-115.9082,39.1615],[-115.5191,38.9578],[-115.4725,38.9325],[-115.4433,38.9162],[-115.3694,38.8769],[-115.363,38.874],[-115.242,38.8093],[-115.0969,38.7309],[-115.0777,38.721],[-115.0604,38.7107],[-115.0291,38.6937],[-114.999,38.6777],[-114.9996,38.592],[-114.9997,38.4315],[-114.9994,38.3894],[-115.0004,38.0507],[-115.1185,38.0508],[-115.1436,38.0508],[-115.326,38.0515],[-115.3453,38.0514],[-115.4003,38.051],[-115.4587,38.0506],[-115.6394,38.0512],[-115.6581,38.051],[-115.8404,38.0504],[-115.8931,38.0507],[-115.8938,37.723],[-115.8969,37.5498],[-115.8975,37.2796],[-115.8982,37.1926],[-115.8942,36.8425],[-115.8941,36.686],[-115.8945,36.6702],[-115.8949,36.598],[-115.8949,36.5962],[-115.8946,36.5858],[-115.8947,36.5005],[-115.8945,36.4806],[-115.8949,36.462],[-115.8944,36.457],[-115.8948,36.3087],[-115.8945,36.2923],[-115.8943,36.1957],[-115.8945,36.1608],[-115.8948,36.1163],[-115.8948,36.0927],[-115.895,36.0015],[-115.9178,36.0192],[-115.9518,36.0457],[-115.9925,36.0773],[-116.049,36.1211],[-116.0624,36.1314],[-116.1039,36.1636],[-116.1287,36.1829],[-116.1702,36.2152],[-116.173,36.2174],[-116.2311,36.2626],[-116.2834,36.3028],[-116.2954,36.3122],[-116.3752,36.373],[-116.5107,36.4764],[-116.5247,36.4871],[-116.5589,36.5131],[-116.574,36.5245],[-116.5946,36.54],[-116.6556,36.5867],[-116.6583,36.5888],[-116.6764,36.6024],[-116.706,36.6248],[-116.7895,36.6877],[-116.8424,36.7276],[-116.8453,36.7298],[-116.8806,36.7568],[-116.8912,36.7648],[-116.9237,36.7891],[-116.9641,36.8193],[-116.9783,36.8299],[-116.981,36.8319],[-117.0046,36.8495],[-117.164,36.9688],[-117.1639,36.9698],[-117.1637,37.0182],[-117.164,37.0894],[-117.1642,37.171],[-117.1641,37.1909],[-117.1641,37.1936],[-117.1665,37.6995],[-117.1664,37.714],[-117.1663,37.7285],[-117.1663,37.7435],[-117.1662,37.7585],[-117.1657,38.0019],[-117.2198,38.0482],[-117.2397,38.0483],[-117.239,38.0641],[-117.2408,38.0705],[-117.2653,38.0932],[-117.6896,38.4731],[-118.0197,38.7599],[-118.197,38.9154],[-118.1972,38.9993],[-117.8559,39.0746],[-117.7748,39.092],[-117.7008,39.1058],[-117.6409,39.1149],[-117.5946,39.1231],[-117.4742,39.1431],[-117.3823,39.1562],[-117.3609,39.1585],[-117.3318,39.1629],[-117.3063,39.1634],[-117.2849,39.1633],[-117.1995,39.1632],[-117.0856,39.1628],[-117.0322,39.1626],[-117.0144,39.1626],[-116.9871,39.1625],[-116.9158,39.1631],[-116.7562,39.1622],[-116.7301,39.1625],[-116.5996,39.1616],[-116.5859,39.162],[-116.4815,39.1616],[-116.3497,39.1618],[-116.2358,39.1616],[-116.0548,39.1624],[-115.9082,39.1615]]]},\"properties\":{\"name\":\"Nye\",\"state\":\"NV\"}}]}","volume":"18","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Green, Christopher 0000-0002-6480-8194","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":201642,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":784891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luo, Wentai 0000-0003-3421-4958","orcid":"https://orcid.org/0000-0003-3421-4958","contributorId":222128,"corporation":false,"usgs":false,"family":"Luo","given":"Wentai","email":"","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":784892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conaway, Christopher H. 0000-0002-0991-033X","orcid":"https://orcid.org/0000-0002-0991-033X","contributorId":201932,"corporation":false,"usgs":true,"family":"Conaway","given":"Christopher H.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":784893,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haase, Karl B. 0000-0002-6897-6494","orcid":"https://orcid.org/0000-0002-6897-6494","contributorId":216317,"corporation":false,"usgs":true,"family":"Haase","given":"Karl B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":784894,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baker, Ronald J. 0000-0001-5966-554X","orcid":"https://orcid.org/0000-0001-5966-554X","contributorId":223375,"corporation":false,"usgs":false,"family":"Baker","given":"Ronald J.","affiliations":[{"id":36625,"text":"Emeritus","active":true,"usgs":false}],"preferred":false,"id":784895,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Andraski, Brian J. 0000-0002-2086-0417 andraski@usgs.gov","orcid":"https://orcid.org/0000-0002-2086-0417","contributorId":168800,"corporation":false,"usgs":true,"family":"Andraski","given":"Brian","email":"andraski@usgs.gov","middleInitial":"J.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":784896,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70205890,"text":"70205890 - 2019 - Wetland biomass and productivity in Coastal Louisiana: Base line data (1976-2015) and knowledge gaps for the development of spatially explicit models for ecosystem restoration and rehabilitation initiatives","interactions":[],"lastModifiedDate":"2019-10-10T08:13:33","indexId":"70205890","displayToPublicDate":"2019-10-01T13:21:54","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Wetland biomass and productivity in Coastal Louisiana: Base line data (1976-2015) and knowledge gaps for the development of spatially explicit models for ecosystem restoration and rehabilitation initiatives","docAbstract":"Coastal Louisiana host 37% of the coastal wetland area in the conterminous US, including one of the deltaic coastal regions more susceptible to the synergy of human and natural impacts causing wetland loss. As a result of the construction of flood protection infrastructure, dredging of channels across wetlands for oil/gas exploration and maritime transport activities, coastal Coastal Louisiana hosts 37% of the coastal wetland area in the conterminous US, including one of the deltaic coastal regions more susceptible to the synergy of human and natural impacts causing wetland loss. As a result of the construction of flood protection infrastructure, dredging of channels across wetlands for oil/gas exploration and maritime transport activities, coastal Louisiana has lost approximately 4900 km2 of wetland area since the early 1930s. Despite the economic relevance of both wetland biomass and net primary productivity (NPP) as ecosystem services, there is a lack of vegetation simulation models to forecast the trends of those functional attributes at the landscape level as hydrological restoration projects are implemented. Here, we review the availability of peer-reviewed biomass and NPP wetland data (below and aboveground) published during the period 1976–2015 for use in the development, calibration and validation of high spatial resolution (<200 m × 200 m) vegetation process-based ecological models. We discuss and list the knowledge gaps for those species that represent vegetation community associations of ecological importance, including the long-term research issues associated to limited number of paired belowground biomass and productivity studies across hydrological basins currently undergoing different freshwater diversions management regimes and hydrological restoration priorities.","language":"English","publisher":"MDPI","doi":"10.3390/w11102054","usgsCitation":"Rivera-Monroy, V.H., Elliton, C., Narra, S., Meselhe, E., Zhao, X., White, E., Sasser, C.E., Visser, J.M., Meng, X., Wang, H., Xue, Z., and Jaramillo, F., 2019, Wetland biomass and productivity in Coastal Louisiana: Base line data (1976-2015) and knowledge gaps for the development of spatially explicit models for ecosystem restoration and rehabilitation initiatives: Water, v. 11, no. 10, 2054, https://doi.org/10.3390/w11102054.","productDescription":"2054","ipdsId":"IP-108198","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":459655,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w11102054","text":"Publisher Index Page"},{"id":368202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.8671875,\n              30.278044377800153\n            ],\n            [\n              -94.02099609375,\n              29.57345707301757\n            ],\n            [\n              -88.61572265625,\n              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University","active":true,"usgs":false}],"preferred":false,"id":772886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meselhe, Ehab","contributorId":95333,"corporation":false,"usgs":true,"family":"Meselhe","given":"Ehab","email":"","affiliations":[],"preferred":false,"id":772887,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhao, Xiaochen","contributorId":219696,"corporation":false,"usgs":false,"family":"Zhao","given":"Xiaochen","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":772888,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"White, Eric","contributorId":194507,"corporation":false,"usgs":false,"family":"White","given":"Eric","affiliations":[],"preferred":false,"id":772889,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sasser, Charles E.","contributorId":86858,"corporation":false,"usgs":true,"family":"Sasser","given":"Charles","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":772890,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Visser, Jenneke M.","contributorId":90397,"corporation":false,"usgs":true,"family":"Visser","given":"Jenneke","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":772891,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Meng, X.","contributorId":56962,"corporation":false,"usgs":true,"family":"Meng","given":"X.","email":"","affiliations":[],"preferred":false,"id":772892,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":140432,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":772893,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Xue, Zuo","contributorId":47216,"corporation":false,"usgs":true,"family":"Xue","given":"Zuo","affiliations":[],"preferred":false,"id":772894,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jaramillo, Fernando","contributorId":219697,"corporation":false,"usgs":false,"family":"Jaramillo","given":"Fernando","email":"","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":772895,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70206767,"text":"70206767 - 2019 - Seasonal, spring-neap, and tidal variation in cohesive sediment transport parameters in estuarine shallows","interactions":[],"lastModifiedDate":"2020-01-03T10:44:49","indexId":"70206767","displayToPublicDate":"2019-10-01T10:55:52","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2321,"text":"Journal of Geophysical Research: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal, spring-neap, and tidal variation in cohesive sediment transport parameters in estuarine shallows","docAbstract":"<p><span>Numerical models for predicting sediment concentrations and transport rely on parameters such as settling velocity and bed erodibility that describe sediment characteristics, yet these parameters are rarely probed directly. We investigated temporal and spatial variation in sediment parameters in the shallows of San Pablo Bay, CA. Flow, turbulence, and suspended sediment data were measured at sites located at 1 and 2&nbsp;m below mean lower low water (MLLW) from November 2013 through April 2015, supplemented by monthlong periods in 2011, 2012, and 2016. Maximum current velocities were 0.40–0.47&nbsp;m s</span><sup>-1</sup><span>&nbsp;at these depths; the strongest currents decreased to 0.27–0.34&nbsp;m s</span><sup>-1</sup><span>&nbsp;during neap periods. Winters 2013–2014 and 2014–2015 experienced strong drought conditions, limiting the potential for seasonal impact on sediment conditions during this experiment. Despite this, the more storm‐influenced site showed clear changes during the winter: the roughness parameter decreased from 10</span><sup>−4</sup><span>&nbsp;to 10</span><sup>−5</sup><span>&nbsp;m, from hydrodynamically rough to smooth conditions, and bed erodibility increased by an order of magnitude. Median settling velocity was 2.05·10</span><sup>−4</sup><span>&nbsp;m s</span><sup>-1</sup><span>; it varied twofold within a tidal cycle, decreasing as current velocity grew during flood and ebb. This tidal control on floc size affected settling velocity on the spring‐neap timescale, possibly driving a spring‐neap oscillation in erodibility. Our findings highlight variation in sediment dynamics that is commonly ignored in numerical models and the need for field observations to ground truth ongoing modeling efforts.</span></p>","language":"English","publisher":"Wiley","doi":"10.1029/2018JC014825","usgsCitation":"Allen, R., Lacy, J.R., Stacey, M.T., and Variano, E.A., 2019, Seasonal, spring-neap, and tidal variation in cohesive sediment transport parameters in estuarine shallows: Journal of Geophysical Research: Oceans, v. 124, no. 11, p. 7265-7284, https://doi.org/10.1029/2018JC014825.","productDescription":"20 p.","startPage":"7265","endPage":"7284","ipdsId":"IP-103807","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":369464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Pablo Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.57858276367186,\n              37.95827503526034\n            ],\n            [\n              -122.23251342773438,\n              37.95827503526034\n            ],\n            [\n              -122.23251342773438,\n              38.16479533621134\n            ],\n            [\n              -122.57858276367186,\n              38.16479533621134\n            ],\n            [\n              -122.57858276367186,\n              37.95827503526034\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"124","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, Rachel 0000-0002-0287-6466","orcid":"https://orcid.org/0000-0002-0287-6466","contributorId":216002,"corporation":false,"usgs":true,"family":"Allen","given":"Rachel","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":775714,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lacy, Jessica R. 0000-0002-2797-6172","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":201703,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":775715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stacey, Mark T. 0000-0002-0952-2812","orcid":"https://orcid.org/0000-0002-0952-2812","contributorId":220770,"corporation":false,"usgs":false,"family":"Stacey","given":"Mark","email":"","middleInitial":"T.","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":775716,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Variano, Evan A 0000-0001-5102-238X","orcid":"https://orcid.org/0000-0001-5102-238X","contributorId":216003,"corporation":false,"usgs":false,"family":"Variano","given":"Evan","email":"","middleInitial":"A","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":775717,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70259333,"text":"70259333 - 2019 - Monitoring, forecasting collapse events, and mapping pyroclastic deposits at Sinabung volcano with satellite imagery","interactions":[],"lastModifiedDate":"2024-10-04T13:56:02.834055","indexId":"70259333","displayToPublicDate":"2019-10-01T08:47:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring, forecasting collapse events, and mapping pyroclastic deposits at Sinabung volcano with satellite imagery","docAbstract":"<p><span>During the ongoing (2013–present) eruption of Sinabung volcano, north Sumatra, we have routinely used a variety of&nbsp;satellite remote sensing&nbsp;data to observe and forecast&nbsp;lava dome&nbsp;and&nbsp;lava flow&nbsp;collapse events, to map the resulting&nbsp;pyroclastic deposits, and to estimate effusion rates. In this paper, we focus on the first two years of the current eruption (September 2013–December 2015), and we summarize major events in 2016. We divide the eruption into 5 major phases: 1) phreatomagmatic (July 2013–18 December 2013), 2) first dome growth and collapse (18 December 2013–10 January 2014), 3) lava-flow (10 January 2014–mid-September 2014), 4) second lava dome and collapse (mid-September 2014–July 2015), 5) lava dome collapse and ash explosion phase (August 2015–present). Throughout the eruption, remotely sensed information has been instrumental in assessing the stability of the lava dome and flow and to forecast collapse events that produce pyroclastic density currents (PDCs: block-and-ash flows, co-ignimbrite surges, and blasts). Forecasts based on&nbsp;remote sensing&nbsp;data in combination with seismic, geodetic and gas-monitoring data have also helped inform decisions related to alert levels and evacuations. Relatively unusual aspects of the Sinabung eruption include the transition from dome to flow morphology (phase 2 to phase 3 transition) and the frequent occurrence during phase 3 of collapses from the lava flow-front and flow-margins—collapses that produced extensive pyroclastic density currents. By analogy to the well-known “Merapi type” collapses and pyroclastic deposits, we propose that lava flow-front and flow-margin collapses with associated PDCs be known as “Sinabung type.” Although detailed study of deposits has not been possible due to continuing hazards, our observations suggest that the transition from lava dome to lava flow and the occurrence of flow-front and flow-margin collapses reflect a particular combination of lava viscosity and steepness of slope. Our observations also show clear evidence of at least one slope-parallel high-velocity and dilute PDC (a “blast”) that emanated from a lava-margin collapse site 500 m downslope from the vent. This 1 February 2014 blast downed and singed a forest out to at least 3.9 km from the collapse site and killed 16 people. We also use a combination of field and remotely sensed data to map the distribution of Sinabung deposits. We estimate eruptive volumes and extrusion rates by combining sequential measurements of lava surface and&nbsp;pyroclastic flow&nbsp;areas with thickness estimates derived from simple geometric assumptions, oblique photographs and&nbsp;Digital Elevation Models&nbsp;(DEMs) derived from remotely sensed data. Our estimates of short-term effusion rates vary widely on a daily to weekly basis, from &lt;1 to &gt;20 m</span><sup>3</sup><span> s</span><sup>−1</sup><span>. In a few cases, periods of increased extrusion precede lava flow-front collapses by a few days to a week, suggesting delays in&nbsp;transmittance&nbsp;of effusion pulses as lava moves from vent to flow front. We find that, as of 1 January 2016, the total area of deposits is 10</span><sup>7</sup><span> m</span><sup>2</sup><span>, and their approximate deposit volume is about 0.3 km</span><sup>3</sup><span>, equivalent to 0.2 km</span><sup>3</sup><span>&nbsp;Dense Rock Equivalent (DRE). We anticipate that our deposit maps will be valuable in the future as a framework for the study of the magmatic and textural evolution of eruptive products through time.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2018.05.012","usgsCitation":"Pallister, J.S., Wessels, R., Griswold, J.P., McCausland, W.A., Kartadinata, N., Gunawan, H., Budianto, A., and Primulyana, S., 2019, Monitoring, forecasting collapse events, and mapping pyroclastic deposits at Sinabung volcano with satellite imagery: Journal of Volcanology and Geothermal Research, v. 382, p. 149-163, https://doi.org/10.1016/j.jvolgeores.2018.05.012.","productDescription":"15 p.","startPage":"149","endPage":"163","ipdsId":"IP-077545","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467319,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2018.05.012","text":"Publisher Index Page"},{"id":462593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia","otherGeospatial":"Sinabung volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              97.99743834932508,\n              3.449644799978927\n            ],\n            [\n              97.99743834932508,\n              2.1401582830417425\n            ],\n            [\n              99.24416582769311,\n              2.1401582830417425\n            ],\n            [\n              99.24416582769311,\n              3.449644799978927\n            ],\n            [\n              97.99743834932508,\n              3.449644799978927\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"382","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pallister, John S. 0000-0002-2041-2147 jpallist@usgs.gov","orcid":"https://orcid.org/0000-0002-2041-2147","contributorId":2024,"corporation":false,"usgs":true,"family":"Pallister","given":"John","email":"jpallist@usgs.gov","middleInitial":"S.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":914964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wessels, Rick 0000-0001-9711-6402 rwessels@usgs.gov","orcid":"https://orcid.org/0000-0001-9711-6402","contributorId":198602,"corporation":false,"usgs":true,"family":"Wessels","given":"Rick","email":"rwessels@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":914965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Griswold, Julia P. 0000-0001-5597-5030 griswold@usgs.gov","orcid":"https://orcid.org/0000-0001-5597-5030","contributorId":202823,"corporation":false,"usgs":true,"family":"Griswold","given":"Julia","email":"griswold@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":914966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCausland, Wendy A. 0000-0002-8683-1440","orcid":"https://orcid.org/0000-0002-8683-1440","contributorId":204380,"corporation":false,"usgs":true,"family":"McCausland","given":"Wendy","email":"","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":914967,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kartadinata, Nugraha","contributorId":344903,"corporation":false,"usgs":false,"family":"Kartadinata","given":"Nugraha","email":"","affiliations":[{"id":37068,"text":"CVGHM","active":true,"usgs":false}],"preferred":false,"id":914968,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gunawan, Hendra","contributorId":344904,"corporation":false,"usgs":false,"family":"Gunawan","given":"Hendra","affiliations":[{"id":37068,"text":"CVGHM","active":true,"usgs":false}],"preferred":false,"id":914969,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Budianto, Agus","contributorId":344905,"corporation":false,"usgs":false,"family":"Budianto","given":"Agus","affiliations":[{"id":37068,"text":"CVGHM","active":true,"usgs":false}],"preferred":false,"id":914970,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Primulyana, Sofyan","contributorId":344906,"corporation":false,"usgs":false,"family":"Primulyana","given":"Sofyan","affiliations":[{"id":37068,"text":"CVGHM","active":true,"usgs":false}],"preferred":false,"id":914971,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70206800,"text":"70206800 - 2019 - Formation pressure and fluid flow measurements in marine gas hydrate reservoirs, NGHP-02 expedition, offshore India","interactions":[],"lastModifiedDate":"2019-11-22T08:28:35","indexId":"70206800","displayToPublicDate":"2019-10-01T08:26:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2382,"text":"Journal of Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Formation pressure and fluid flow measurements in marine gas hydrate reservoirs, NGHP-02 expedition, offshore India","docAbstract":"Open Hole Modular Dynamic Testing (MDT) measurements were conducted in a gas hydrate-bearing sand-rich reservoir offshore India during the National Gas Hydrate Program 02 (NGHP-02) Expedition. The primary goal of this test was to obtain effective reservoir petrophysical properties in the presence of gas hydrates. The test plan included a series of pre-hydrate dissociation flow and build-up (shut-in) tests, and an attempt to dissociate gas hydrate in a sand-rich reservoir by depressurization to collect formation fluid samples and to further characterize in situ gas hydrate stability conditions. Schlumberger’s wireline MDT tool was used in a dual-packer configuration to isolate the formation being tested.\n\nThis paper presents the results of the open hole MDT measurements that were conducted in Hole NGHP-02-23-C in Krishna-Godavari Basin at a water depth of 2553.5 m. The MDT dual packer test was conducted in 27 cm (10.63 in) diameter open hole section of the borehole within a 1-m interval isolated between two inflatable packers with the midpoint of the test interval at 2853.0 meter below rig floor (mbrf) (271.0 meter below sea floor (mbsf)). This was the first gas hydrate MDT test ever conducted in ultradeep water to characterize a gas hydrate reservoir system. Pre-hydrate dissociation testing was performed with a drawdown period (depressurization) of 20 minutes followed by a build-up (shut-in) of 20 minutes. The measured formation pressure was 4090.7 psia and the formation fluid (i.e., water) mobility was calculated at 1.98 mD/cP. During the second dissociation phase of the same test a maximum pressure drawdown of 840 psia was achieved; however, falling short of the 1120 psia drawdown required for dissociation. During the dissociation test the flow line pressure stabilized at a flowing pressure of 3250 psia which can be attributed to the relatively high mobility of the free water phase in the hydrate-bearing reservoir. Good quality formation pressure and near well bore mobility data was acquired that yielded a “high confidence” reservoir effective radial permeability-thickness product of 0.2 mD.m  (or a horizontal effective permeability of 0.1 mD assuming a reservoir thicknees of 1.8 m) using pressure transient analysis (radial flow regime was achieved) despite unstable borehole conditions and complex operations in these shallow unconsolidated sedimentary sections.","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2018.11.035","usgsCitation":"Kumar, P., Collett, T.S., Yadav, U., and Singh, J., 2019, Formation pressure and fluid flow measurements in marine gas hydrate reservoirs, NGHP-02 expedition, offshore India: Journal of Marine and Petroleum Geology, v. 108, p. 609-618, https://doi.org/10.1016/j.marpetgeo.2018.11.035.","productDescription":"10 p.","startPage":"609","endPage":"618","ipdsId":"IP-103515","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":459669,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1636237","text":"Publisher Index Page"},{"id":369450,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[77.83745,35.49401],[78.91227,34.32194],[78.81109,33.5062],[79.20889,32.99439],[79.17613,32.48378],[78.45845,32.61816],[78.73889,31.51591],[79.72137,30.88271],[81.11126,30.18348],[80.47672,29.72987],[80.08842,28.79447],[81.0572,28.4161],[81.99999,27.92548],[83.30425,27.36451],[84.67502,27.2349],[85.25178,26.7262],[86.02439,26.63098],[87.22747,26.3979],[88.06024,26.41462],[88.1748,26.81041],[88.04313,27.44582],[88.12044,27.87654],[88.73033,28.08686],[88.81425,27.29932],[88.83564,27.09897],[89.74453,26.7194],[90.37327,26.87572],[91.21751,26.80865],[92.03348,26.83831],[92.10371,27.45261],[91.69666,27.77174],[92.50312,27.89688],[93.41335,28.64063],[94.56599,29.27744],[95.4048,29.03172],[96.11768,29.4528],[96.58659,28.83098],[96.24883,28.41103],[97.32711,28.26158],[97.40256,27.88254],[97.05199,27.69906],[97.134,27.08377],[96.41937,27.26459],[95.12477,26.57357],[95.15515,26.00131],[94.60325,25.1625],[94.55266,24.67524],[94.10674,23.85074],[93.32519,24.07856],[93.28633,23.04366],[93.06029,22.70311],[93.16613,22.27846],[92.67272,22.04124],[92.14603,23.6275],[91.86993,23.62435],[91.70648,22.98526],[91.15896,23.50353],[91.46773,24.07264],[91.91509,24.13041],[92.3762,24.97669],[91.7996,25.14743],[90.87221,25.1326],[89.92069,25.26975],[89.83248,25.96508],[89.35509,26.01441],[88.56305,26.44653],[88.20979,25.76807],[88.93155,25.23869],[88.30637,24.86608],[88.08442,24.50166],[88.69994,24.23371],[88.52977,23.63114],[88.87631,22.87915],[89.03196,22.05571],[88.88877,21.69059],[88.2085,21.70317],[86.9757,21.49556],[87.03317,20.74331],[86.49935,20.15164],[85.06027,19.47858],[83.94101,18.30201],[83.18922,17.67122],[82.19279,17.01664],[82.19124,16.55666],[81.69272,16.31022],[80.792,15.95197],[80.3249,15.89918],[80.02507,15.13641],[80.23327,13.83577],[80.28629,13.00626],[79.86255,12.05622],[79.858,10.35728],[79.34051,10.30885],[78.88535,9.54614],[79.18972,9.21654],[78.27794,8.93305],[77.94117,8.25296],[77.5399,7.96553],[76.59298,8.89928],[76.13006,10.29963],[75.74647,11.30825],[75.3961,11.78125],[74.86482,12.74194],[74.61672,13.99258],[74.44386,14.61722],[73.5342,15.99065],[73.11991,17.92857],[72.82091,19.20823],[72.82448,20.4195],[72.63053,21.35601],[71.17527,20.75744],[70.47046,20.87733],[69.16413,22.0893],[69.64493,22.45077],[69.3496,22.84318],[68.17665,23.69197],[68.8426,24.35913],[71.04324,24.35652],[70.8447,25.2151],[70.28287,25.72223],[70.16893,26.49187],[69.51439,26.94097],[70.6165,27.9892],[71.77767,27.91318],[72.82375,28.96159],[73.45064,29.97641],[74.42138,30.97981],[74.40593,31.69264],[75.25864,32.27111],[74.45156,32.7649],[74.10429,33.44147],[73.74995,34.3177],[74.2402,34.74889],[75.75706,34.50492],[76.87172,34.65354],[77.83745,35.49401]]]},\"properties\":{\"name\":\"India\"}}]}","volume":"108","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kumar, Pushpendra","contributorId":212239,"corporation":false,"usgs":false,"family":"Kumar","given":"Pushpendra","affiliations":[{"id":38465,"text":"Oil and Natural Gas Corp. Panvel, Navi Mumbai, India","active":true,"usgs":false}],"preferred":false,"id":775823,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":775824,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yadav, U.S.","contributorId":127763,"corporation":false,"usgs":false,"family":"Yadav","given":"U.S.","email":"","affiliations":[{"id":7141,"text":"Oil and Natural Gas Corporation Ltd, KDM Institute of Petroleum Exploration, India","active":true,"usgs":false}],"preferred":false,"id":775825,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Singh, Juli","contributorId":220817,"corporation":false,"usgs":false,"family":"Singh","given":"Juli","email":"","affiliations":[],"preferred":false,"id":775826,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70206802,"text":"70206802 - 2019 - India National Gas Hydrate Program Expedition-02: Operational and technical summary","interactions":[],"lastModifiedDate":"2019-11-22T08:25:02","indexId":"70206802","displayToPublicDate":"2019-10-01T08:23:28","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2382,"text":"Journal of Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"India National Gas Hydrate Program Expedition-02: Operational and technical summary","docAbstract":"The India National Gas Hydrate Program is being steered by the government of India's Ministry of Petroleum and Natural Gas (MoPNG) with participation of Directorate General of Hydrocarbons (DGH), Oil and Natural Gas Corporation Limited (ONGC), and the National Oil Companies and Research Institutes of India. The India National Gas Hydrate Program Expedition 01 (NGHP-01) established the presence of gas hydrate in the Krishna Godavari (KG) and Mahanadi Basins and in the offshore area of the Andaman Sea Basin. However, the gas hydrates discovered during NGHP-01 were mainly distributed as fracture-filling material in fine-grained clay-rich sediments. The India National Gas Hydrate Program Expedition 02 (NGHP-02) was carried out with an objective to discover gas hydrate in sand-rich sediment along the eastern offshore margin of India. ONGC planned and executed NGHP-02 on the behalf of the MoPNG.\n\nNGHP-02 started on March 3, 2015 and was completed on July 28, 2015 (total 147 days) using the Japanese scientific Drilling Vessel Chikyu (D/V Chikyu). During NGHP-02, 42 holes at 25 sites were drilled, cored, and/or surveyed with downhole logging tools. These sites were located in four areas along the eastern margin of India and formally named Area A (Mahanadi Basin, three sites), Area B (northern part of the KG-Basin, twelve sites), Area C (central part of the KG-Basin, six sites), and Area E (southern part to the KG-Basin, four sites). All 25 sites established during NGHP-02 were first drilled and logged with logging-while-drilling (LWD) tools and an additional 17 holes were then drilled and/or cored with conventional coring tools (HPCS/ESCS) or pressure coring tools (PCTB). Wireline logging was conducted in 10 holes and formation tests using a dual packer Modular Formation Dynamics Tester (MDT) tool were carried out in two holes.\n\nThe onboard science team used the laboratory facilities on the D/V Chikyu to examine and analyse the physical properties, geochemistry, and sedimentology of all the cores collected during the expedition. Core samples were also analysed in additional post-expedition shore-based studies conducted in numerous domestic and international gas hydrate research laboratories. The NGHP-02 sediment cores were archived at the National Gas Hydrate Core Repository in Mumbai (India), which is associated with the ONGC Gas Hydrate Research and Technology Centre (GHRTC). The necessary data for characterizing the occurrence of gas hydrate, such as interstitial water chlorinities, core-derived gas chemistry, physical and sedimentological properties, thermal images of the recovered cores, pressure core and downhole measured logging data (LWD and/or conventional wireline log data), were obtained from most of the drill sites established during NGHP-02. Almost all the drill sites yielded evidence for the occurrence of gas hydrate; however, the inferred in situ concentration of gas hydrate varied substantially from site to site. For the most part, the interpretation of downhole logging data, core thermal images, interstitial water analyses, and pressure core images from the sites established during NGHP-02 indicate that the occurrence of concentrated gas hydrate is mostly associated with coarser grained (sand-rich) sediments. This paper presents the operational and technical summary of NGHP-02.\n\nNGHP-02 started on March 3, 2015 and was completed on July 28, 2015 (total 147 days) using the Japanese scientific Drilling Vessel Chikyu (D/V Chikyu). During NGHP-02, 42 holes at 25 sites were drilled, cored, and/or surveyed with downhole logging tools. These sites were located in four areas along the eastern margin of India and formally named Area A (Mahanadi Basin, three sites), Area B (northern part of the KG-Basin, twelve sites), Area C (central part of the KG-Basin, six sites), and Area E (southern part to the KG-Basin, four sites). All 25 sites established during NGHP-02 were first drilled and logged with logging-while-drilling (LWD) to","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2018.11.021","usgsCitation":"Kumar, P., Collett, T.S., K. M. Shukla, Yadav, U.S., Lall, M.V., and Krishna Vishwanath, 2019, India National Gas Hydrate Program Expedition-02: Operational and technical summary: Journal of Marine and Petroleum Geology, v. 108, p. 3-38, https://doi.org/10.1016/j.marpetgeo.2018.11.021.","productDescription":"36 p.","startPage":"3","endPage":"38","ipdsId":"IP-103513","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":459672,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1636323","text":"Publisher Index Page"},{"id":369449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[77.83745,35.49401],[78.91227,34.32194],[78.81109,33.5062],[79.20889,32.99439],[79.17613,32.48378],[78.45845,32.61816],[78.73889,31.51591],[79.72137,30.88271],[81.11126,30.18348],[80.47672,29.72987],[80.08842,28.79447],[81.0572,28.4161],[81.99999,27.92548],[83.30425,27.36451],[84.67502,27.2349],[85.25178,26.7262],[86.02439,26.63098],[87.22747,26.3979],[88.06024,26.41462],[88.1748,26.81041],[88.04313,27.44582],[88.12044,27.87654],[88.73033,28.08686],[88.81425,27.29932],[88.83564,27.09897],[89.74453,26.7194],[90.37327,26.87572],[91.21751,26.80865],[92.03348,26.83831],[92.10371,27.45261],[91.69666,27.77174],[92.50312,27.89688],[93.41335,28.64063],[94.56599,29.27744],[95.4048,29.03172],[96.11768,29.4528],[96.58659,28.83098],[96.24883,28.41103],[97.32711,28.26158],[97.40256,27.88254],[97.05199,27.69906],[97.134,27.08377],[96.41937,27.26459],[95.12477,26.57357],[95.15515,26.00131],[94.60325,25.1625],[94.55266,24.67524],[94.10674,23.85074],[93.32519,24.07856],[93.28633,23.04366],[93.06029,22.70311],[93.16613,22.27846],[92.67272,22.04124],[92.14603,23.6275],[91.86993,23.62435],[91.70648,22.98526],[91.15896,23.50353],[91.46773,24.07264],[91.91509,24.13041],[92.3762,24.97669],[91.7996,25.14743],[90.87221,25.1326],[89.92069,25.26975],[89.83248,25.96508],[89.35509,26.01441],[88.56305,26.44653],[88.20979,25.76807],[88.93155,25.23869],[88.30637,24.86608],[88.08442,24.50166],[88.69994,24.23371],[88.52977,23.63114],[88.87631,22.87915],[89.03196,22.05571],[88.88877,21.69059],[88.2085,21.70317],[86.9757,21.49556],[87.03317,20.74331],[86.49935,20.15164],[85.06027,19.47858],[83.94101,18.30201],[83.18922,17.67122],[82.19279,17.01664],[82.19124,16.55666],[81.69272,16.31022],[80.792,15.95197],[80.3249,15.89918],[80.02507,15.13641],[80.23327,13.83577],[80.28629,13.00626],[79.86255,12.05622],[79.858,10.35728],[79.34051,10.30885],[78.88535,9.54614],[79.18972,9.21654],[78.27794,8.93305],[77.94117,8.25296],[77.5399,7.96553],[76.59298,8.89928],[76.13006,10.29963],[75.74647,11.30825],[75.3961,11.78125],[74.86482,12.74194],[74.61672,13.99258],[74.44386,14.61722],[73.5342,15.99065],[73.11991,17.92857],[72.82091,19.20823],[72.82448,20.4195],[72.63053,21.35601],[71.17527,20.75744],[70.47046,20.87733],[69.16413,22.0893],[69.64493,22.45077],[69.3496,22.84318],[68.17665,23.69197],[68.8426,24.35913],[71.04324,24.35652],[70.8447,25.2151],[70.28287,25.72223],[70.16893,26.49187],[69.51439,26.94097],[70.6165,27.9892],[71.77767,27.91318],[72.82375,28.96159],[73.45064,29.97641],[74.42138,30.97981],[74.40593,31.69264],[75.25864,32.27111],[74.45156,32.7649],[74.10429,33.44147],[73.74995,34.3177],[74.2402,34.74889],[75.75706,34.50492],[76.87172,34.65354],[77.83745,35.49401]]]},\"properties\":{\"name\":\"India\"}}]}","volume":"108","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kumar, Pushpendra","contributorId":220793,"corporation":false,"usgs":false,"family":"Kumar","given":"Pushpendra","email":"","affiliations":[{"id":40268,"text":"Oil and Natural Gas Corporation, Panvel, Navi Mumbai, India","active":true,"usgs":false}],"preferred":false,"id":775784,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":775783,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"K. M. Shukla","contributorId":220795,"corporation":false,"usgs":false,"family":"K. M. Shukla","affiliations":[{"id":40269,"text":"Oil and Natural Gas Corporation Ltd","active":true,"usgs":false}],"preferred":false,"id":775785,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yadav, U. S.","contributorId":220796,"corporation":false,"usgs":false,"family":"Yadav","given":"U.","email":"","middleInitial":"S.","affiliations":[{"id":40270,"text":"Oil and Natural Gas Corporation Ltd.","active":true,"usgs":false}],"preferred":false,"id":775786,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lall, M. V.","contributorId":220797,"corporation":false,"usgs":false,"family":"Lall","given":"M.","email":"","middleInitial":"V.","affiliations":[{"id":40270,"text":"Oil and Natural Gas Corporation Ltd.","active":true,"usgs":false}],"preferred":false,"id":775787,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Krishna Vishwanath","contributorId":220798,"corporation":false,"usgs":false,"family":"Krishna Vishwanath","affiliations":[{"id":40271,"text":"Directorate General of Hydrocarbons","active":true,"usgs":false}],"preferred":false,"id":775788,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70206804,"text":"70206804 - 2019 - National Gas Hydrate Program expedition 02: Identification of gas hydrate prospects in the Krishna-Godavari Basin, offshore India","interactions":[],"lastModifiedDate":"2019-11-22T08:16:58","indexId":"70206804","displayToPublicDate":"2019-10-01T08:15:05","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2382,"text":"Journal of Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"National Gas Hydrate Program expedition 02: Identification of gas hydrate prospects in the Krishna-Godavari Basin, offshore India","docAbstract":"After completing the first expedition of India's National Gas Hydrate Program (NGHP-01) in 2006, it was concluded that for the next expedition (National Gas Hydrate Program 02; NGHP-02), a new drill site review effort should focus on identifying potential deep-water offshore gas hydrate accumulations in sand dominated depositional environments. Therefore, geological and geophysical data analysis and 3D seismic data interpretation along with associated seismic modeling were carried out in three areas of the Krishna-Godavari Basin: Areas B, C, and E. Conventional petroleum exploration approaches of seismic amplitude evaluation were adapted to prospect for potential sand-rich depositional systems within the gas hydrate stability zone. Subsequently, these prospective areas were further assessed through the  geological and geophysical evaluation of depositional setting, gas sources, and gas migration pathways.  In Area B, prospecting focused on a large anticlinal structure with a prominent bottom-simulating reflector and several key horizons that indicated evidence for potential sand-hosted hydrate occurrences.  In Area C, the prospects were distributed throughout various settings within a very large deep-water channel-levee-fan system with complex indications of potential gas hydrate occurrence in sand-prone seismic facies.  In Area E, prospects were associated with high amplitude events within inferred channel-levee sequences.  Based on the pre-expedition/onboard drill-site evaluation, the 22 most promising sites in the Krishna-Godavari Basin were identified and prioritized to investigate and delineate a total of 17 identified gas hydrate prospects.  This paper describes the geo-scientific studies carried out prior to NGHP-02 for site identification, evaluation and prioritization. An important outcome of this study is the identification of two potentially producible gas hydrate systems inferred to host significant quantity of gas hydrate in stratigraphic-structural traps.","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2018.11.013","usgsCitation":"Shukla, K., U.S. Yadav, Kumar, P., Collett, T., Boswell, R., Frye, M., M. Riedel, Kaurf, I., and Vishwanathf, K., 2019, National Gas Hydrate Program expedition 02: Identification of gas hydrate prospects in the Krishna-Godavari Basin, offshore India: Journal of Marine and Petroleum Geology, v. 108, p. 167-184, https://doi.org/10.1016/j.marpetgeo.2018.11.013.","productDescription":"18 p.","startPage":"167","endPage":"184","ipdsId":"IP-102093","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":459677,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"text":"Publisher Index 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,{"id":70206805,"text":"70206805 - 2019 - Numerical simulations of depressurization-induced gas production from an interbedded turbidite gas hydrate-bearing sedimentary section in the offshore India: Site NGHP-02-16 (Area-B)","interactions":[],"lastModifiedDate":"2019-11-22T08:11:09","indexId":"70206805","displayToPublicDate":"2019-10-01T08:06:17","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2382,"text":"Journal of Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Numerical simulations of depressurization-induced gas production from an interbedded turbidite gas hydrate-bearing sedimentary section in the offshore India: Site NGHP-02-16 (Area-B)","docAbstract":"The recent National Gas Hydrate Program Expedition 02 (NGHP-02) identified the existence of gas hydrate-bearing sand reservoirs at a number of sites in the offshore of India including Site NGHP-02-16 in Area-B of the Krishna-Godavari Basin. The architecture of that gas hydrate accumulation is characterized by thin, gas hydrate-bearing, high quality sand layers interbedded with mud layers within a turbidite interval. The lowest gas hydrate-bearing layer contacting a thinly-interbedded saline aquifer designates the base of the gas hydrate stability zone (BGHSZ). The proximity of the BGHSZ and the average temperature around 20oC make the reservoir a favorable target for hydrate destabilization by means of the depressurization method. The results of the reservoir simulations indicate high gas production potential from this marine gas hydrate deposit with manageable concomitant water production using a well completion design that hydraulically isolates layers with water-saturated sands. Using a detailed geological input model, the predicted cumulative gas rates reach 3.1 x 104 m3/day (1.1 mmscf/day) after 90 days of continuous depressurization and demonstrate sustained production rates of 3.0 x 104 m3/day (1.0 mmscf/day) after 5 years of production. The interbedded nature of this gas hydrate occurrence promotes the development of horizontal dissociation interfaces between gas hydrate-bearing sand and mud layers. As a result, non-uniform gas production along the horizontal interfaces becomes a primary determinant of reservoir performance. Simulation cases have been executed to determine the impact of the uncertainty in in situ reservoir permeability and the manner in which intrinsic permeability dynamically changes during dissociation in response to the imposed effective stress increase.  The cases where effective permeability is initially low and compaction is highly sensitive to stress result in the least favorable production predictions.","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2018.10.047","usgsCitation":"Myshakin, E.M., Seol, Y., Lin, J., Uchida, S., Collett, T., and Boswell, R., 2019, Numerical simulations of depressurization-induced gas production from an interbedded turbidite gas hydrate-bearing sedimentary section in the offshore India: Site NGHP-02-16 (Area-B): Journal of Marine and Petroleum Geology, v. 108, p. 619-638, https://doi.org/10.1016/j.marpetgeo.2018.10.047.","productDescription":"20 p.","startPage":"619","endPage":"638","ipdsId":"IP-100825","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":459680,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1607771","text":"Publisher Index 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,{"id":70206806,"text":"70206806 - 2019 - India National Gas Hydrate Program Expedition 02 summary of scientific results: Numerical simulation of reservoir response to depressurization","interactions":[],"lastModifiedDate":"2019-11-22T08:04:12","indexId":"70206806","displayToPublicDate":"2019-10-01T08:02:05","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2382,"text":"Journal of Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"India National Gas Hydrate Program Expedition 02 summary of scientific results: Numerical simulation of reservoir response to depressurization","docAbstract":"The India National Gas Hydrate Program Expedition 02 (NGHP-02) discovered gas hydrate at high saturation in sand reservoirs at several sites in the deepwater Bay of Bengal.  To assess the potential response of those deposits to scientific depressurization experiments, comprehensive geologic models were constructed to enable numerical simulation for two sites.  Both sites (NGHP-02-09 and NGHP-02-16) feature thick sequences of thinly-interbedded reservoir and non-reservoir facies at sub-seafloor depths of less than 300 m and sub-sea depths of 2,400 m or more.  These settings pose significant challenges to current modeling capabilities.  First, the thinly-bedded reservoir architecture complicates the determination of basic reservoir parameters from both log and core data due to measurement resolution issues.  Secondly, the fine-scale variation in sediment properties imparts great contrasts in key parameters over very short distances, creating high gradients at multiple scales and varying orientations that necessitate careful design of high-definition simulation grids.  Thirdly, the deposits include internal sources of water, as well as a range of complex boundary conditions, including variable permeability within the overlying mud-rich “seals”, that complicate reservoir depressurization.  Lastly, because of the unique combination of great water depth and relatively shallow sub-seafloor depth, models designed to maximize the dissociation rate impose large pressure drawdowns on relatively low-strength sediments.  This condition renders the proper evaluation and integration of the geomechanical response to hydrate dissociation critical.  In this report, we review the history of gas hydrate reservoir simulation, discuss methods for creating geologic input models, and summarize the key findings and implications of the collaborative NGHP-02 numerical simulation effort.  Together, the studies confirm the viability of the modeled accumulations for scientific testing and identify key challenges related to the selection of specific test sites and the design of test wells.","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2018.09.026","usgsCitation":"Boswell, R., Myshakin, E., Moridis, G., Konno, Y., Collett, T.S., Reagan, M., Ajayi, T., and Seol, Y., 2019, India National Gas Hydrate Program Expedition 02 summary of scientific results: Numerical simulation of reservoir response to depressurization: Journal of Marine and Petroleum Geology, v. 108, p. 154-166, https://doi.org/10.1016/j.marpetgeo.2018.09.026.","productDescription":"13 p.","startPage":"154","endPage":"166","ipdsId":"IP-099199","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":459683,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Boswell, Ray","contributorId":195143,"corporation":false,"usgs":false,"family":"Boswell","given":"Ray","affiliations":[],"preferred":false,"id":775816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Myshakin, Evgeniy","contributorId":195140,"corporation":false,"usgs":false,"family":"Myshakin","given":"Evgeniy","affiliations":[],"preferred":false,"id":775818,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moridis, George","contributorId":220814,"corporation":false,"usgs":false,"family":"Moridis","given":"George","email":"","affiliations":[{"id":40278,"text":"Lawrence Berkeley National Laboratory, Berkeley, CA, USA","active":true,"usgs":false}],"preferred":false,"id":775817,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Konno, Yoshihiro","contributorId":220815,"corporation":false,"usgs":false,"family":"Konno","given":"Yoshihiro","email":"","affiliations":[{"id":40279,"text":"The University of Tokyo, Chiba, Japan","active":true,"usgs":false}],"preferred":false,"id":775821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":775815,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reagan, Matthew","contributorId":220816,"corporation":false,"usgs":false,"family":"Reagan","given":"Matthew","email":"","affiliations":[{"id":40278,"text":"Lawrence Berkeley National Laboratory, Berkeley, CA, USA","active":true,"usgs":false}],"preferred":false,"id":775822,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ajayi, Taiwo","contributorId":178324,"corporation":false,"usgs":false,"family":"Ajayi","given":"Taiwo","email":"","affiliations":[],"preferred":false,"id":775819,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Seol, Yongkoo","contributorId":195139,"corporation":false,"usgs":false,"family":"Seol","given":"Yongkoo","email":"","affiliations":[],"preferred":false,"id":775820,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70205831,"text":"70205831 - 2019 - Discrete Zr and REE mineralization of the Baerzhe rare-metal deposit, China","interactions":[],"lastModifiedDate":"2019-10-08T07:50:17","indexId":"70205831","displayToPublicDate":"2019-10-01T07:49:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":738,"text":"American Mineralogist","active":true,"publicationSubtype":{"id":10}},"title":"Discrete Zr and REE mineralization of the Baerzhe rare-metal deposit, China","docAbstract":"Although REE (lanthanides + Y) mineralization in alkaline silicate systems is commonly accompanied with Zr mineralization worldwide, our understanding of the relationship between Zr and REE mineralization is still incomplete (e.g. Škoda and Novák, 2007; Linnen et al., 2014; Petrella et al., 2014; Möller and Williams-Jones, 2016; Wu et al., 2018). The Baerzhe deposit in NE China is a source of Zr, REE, and Nb linked to the formation of an early Cretaceous, silica-saturated, alkaline intrusive complex. In-situ laser ablation–inductively coupled plasma mass spectrometry (LA-ICP-MS) analyses of zircon and monazite crystals constrain the relationship between Zr and REE mineralization at Baerzhe.\nThree populations of zircon are identified and are differentiated based upon textural observations and compositional characteristics. Type I zircon display well-developed oscillatory zoning are are typically found as inclusions within sodic amphibole. Type II zircons are darker than Type I zircons in CL images, can overgrow Type I zircon, and have more irregular zoning and resorption features. Type III zircons contain irregular but translucent cores and rims with oscillatory zoning that are murky brown in color and grow in aggregates.  Textural features and compositional data suggest that Types I and II zircon crystallized at the magmatic stage, with Type 1 being least altered and Type II being strongly altered, and Type III precipitated during the magmatic to magmatic-hydrothermal transition.\nWhereas the magnitude of the Eu anomaly is moderate in the barren alkaline granite, all three populations of zircon exhibit pronounced negative anomalies. Such features are difficult to explain exclusively by feldspar fractionation and could indicate the presence of fluid modification of the rocks. Monazite crystals occur mostly through replacement of zircon and sodic amphibole; monazite clusters are also present. Textural and compositional evidence suggests that monazite at Baerzhe is hydrothermal.\nLeast and strongly altered magmatic zircon yield 207Pb-corrected 206Pb/238U ages of 127.3±1.2 Ma and 125.67±0.76 Ma, respectively. Deuteric zircon precipitated at 125.11±0.69 Ma. The chronological data suggest that the magmatic stage of the highly-evolved Baerzhe alkaline granite lasted less than two million years. Hydrothermal monazite records REE mineralization at 123.41±0.63 Ma, approximately 1 or 2 million years later than Zr mineralization. We therefore propose a model in which parental magmas underwent extensive magmatic differentiation while residual melts interacted with aqueous hydrothermal fluids. Deuteric zircon precipitated from a hydrosilicate liquid, and subsequent REE mineralization, exemplified by hydrothermal monazite, correlates with the metasomatic alteration from external fluid sources. Such interplay between magmatic and hydrothermal processes resulted in the formation of discrete Zr and REE mineralization at Baerzhe.","language":"English","publisher":"GeoScienceWorld","doi":"10.2138/am-2019-6890","usgsCitation":"Qiu, K., Yu, H., Wu, M., Geng, J., Ge, X., Gou, Z., and Taylor, R., 2019, Discrete Zr and REE mineralization of the Baerzhe rare-metal deposit, China: American Mineralogist, v. 104, no. 10, p. 1487-1502, https://doi.org/10.2138/am-2019-6890.","productDescription":"16 p.","startPage":"1487","endPage":"1502","ipdsId":"IP-103418","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science 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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Qiu, Kunfeng","contributorId":219546,"corporation":false,"usgs":false,"family":"Qiu","given":"Kunfeng","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":772528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yu, Haocheng","contributorId":219547,"corporation":false,"usgs":false,"family":"Yu","given":"Haocheng","email":"","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":772529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wu, Mingqian","contributorId":219548,"corporation":false,"usgs":false,"family":"Wu","given":"Mingqian","email":"","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":772530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Geng, Jianzhen","contributorId":219549,"corporation":false,"usgs":false,"family":"Geng","given":"Jianzhen","email":"","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":772531,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ge, Xiangkun","contributorId":219550,"corporation":false,"usgs":false,"family":"Ge","given":"Xiangkun","email":"","affiliations":[{"id":40023,"text":"Beijing Research Institute of Uranium Geology, Beijing","active":true,"usgs":false}],"preferred":false,"id":772532,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gou, Zongyang","contributorId":219551,"corporation":false,"usgs":false,"family":"Gou","given":"Zongyang","email":"","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":772533,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Taylor, Ryan D. 0000-0002-8845-5290","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":201948,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":772527,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70206403,"text":"70206403 - 2019 - Ensembles of ETAS models provide optimal operational earthquake forecasting during swarms: Insights from the 2015 San Ramon, California swarm","interactions":[],"lastModifiedDate":"2019-12-03T10:01:11","indexId":"70206403","displayToPublicDate":"2019-10-01T06:48:33","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Ensembles of ETAS models provide optimal operational earthquake forecasting during swarms: Insights from the 2015 San Ramon, California swarm","docAbstract":"Earthquake swarms, typically modeled as time-varying changes in background seismicity that are driven by external processes such as fluid flow or aseismic creep, present challenges for operational earthquake forecasting.  While the time decay of aftershock sequences can be estimated with the modified Omori law, it is difficult to forecast the temporal behavior of seismicity rates during a swarm.  To explore these issues, we apply the Epidemic-Type Aftershock Sequence (ETAS) model (Ogata, JASA, 1988) to the 2015 San Ramon, California swarm, which lasted several weeks and had almost 100 2≤M≤3.6 earthquakes.  We develop 3-day forecasts during the swarm based on an ETAS model fit to all prior seismicity in the region as well as an ETAS model fit only to previous swarms in the region, which is better at capturing the higher background rate during the swarm.  We also explore forecasts where the background rate is updated periodically during the swarm using data over different lookback windows and find that generally these models perform better than the models where the background rate is fixed.  Finally, we construct ensemble forecasts by combining the different models weighted according to their performance.  The ensemble forecasts outperform all of the individual models and allow us to avoid making arbitrary choices at the outset of a swarm as to which single model will perform the best.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120190020","usgsCitation":"Llenos, A.L., and Michael, A.J., 2019, Ensembles of ETAS models provide optimal operational earthquake forecasting during swarms: Insights from the 2015 San Ramon, California swarm: Bulletin of the Seismological Society of America, v. 109, no. 6, p. 2145-2158, https://doi.org/10.1785/0120190020.","productDescription":"14 p.","startPage":"2145","endPage":"2158","ipdsId":"IP-101090","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":368858,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Contra Costa County","city":"San 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,{"id":70205386,"text":"sir20195100 - 2019 - Analytical framework to estimate water use associated with continuous oil and gas development","interactions":[],"lastModifiedDate":"2019-10-01T11:39:08","indexId":"sir20195100","displayToPublicDate":"2019-09-30T20:57:45","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5100","displayTitle":"Analytical Framework to Estimate Water Use Associated with Continuous Oil and Gas Development","title":"Analytical framework to estimate water use associated with continuous oil and gas development","docAbstract":"<p>An analytical framework was designed to estimate water use associated with continuous oil and gas (COG) development in support of the U.S. Geological Survey Water Availability and Use Science Program. This framework was developed to better understand the relation between the production of COG resources for energy and the amount of water needed to sustain this type of energy development in the United States. The total mean undiscovered, technically recoverable volume of COG has increased, highlighting the continued need to develop approaches to better characterize water use associated with COG development.</p><p>The analytical framework can be used to estimate water use associated with COG development for three water-use components—direct, indirect, and ancillary water use—that are related to the life cycle of COG development. Direct water use is defined as water used in a wellbore to complete a well, including the water used for drilling, cementing, stimulating, and maintaining the well during production. Indirect water use is the water used at or near the well site, including water used for dust abatement, for cleaning equipment, and for crew and staff use. Ancillary water use is all other water used during the life cycle of COG development that is not categorized as direct or indirect, such as additional local or regional water use resulting from a change (for example, population) related to COG development. The analytical framework includes the data inputs, the processes involved in estimating the water-use coefficients and analyzing their uncertainties, and the outputs. The analytical framework was developed as an R script, which contains the statistical models used to estimate water-use components.</p><p>The availability of data across COG reservoirs in the United States is variable and presents challenges for estimating water use for extracting COG from their reservoirs; thus, the R script can be modified for the types of data available within a COG reservoir, the extent and resolution of data available for each water-use component, and the desired output of the water-use assessment. The script was written so that the units of the data in the script were standardized. Water-use estimates were simulated for the mean and 10th, 50th, and 90th percentiles of the data distributions. Uncertainties were quantified with confidence intervals for the estimated coefficients. Uncertainty for estimated or simulated data can be calculated with the R script by providing a range of representative values that are within the appropriate confidence intervals of the mean of the data.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20195100","collaboration":"Water Availability and Use Science Program","usgsCitation":"Valder, J.F., McShane, R.R., Barnhart, T.B., Wheeling, S.L., Carter, J.M., Macek-Rowland, K.M., Delzer, G.C., and Thamke, J.N., 2019, Analytical framework to estimate water use associated with continuous oil and gas development: U.S. Geological Survey Scientific Investigations Report 2019–5100, 19 p., https://doi.org/10.3133/sir20195100.","productDescription":"Report: vi, 19 p.; Appendix; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-106622","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":367751,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5100/coverthb.jpg"},{"id":367753,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5100/COGWaterUseTool.zip","text":"COG Water Use Tool","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2019–5100 Appendix"},{"id":367754,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CPKRLW","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data to estimate water use associated with continuous oil and gas development, Williston Basin, United States, 1980–2017"},{"id":367752,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5100/sir20195100.pdf","text":"Report ","size":"2.13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5100"}],"country":"United States ","otherGeospatial":"Lower 48 states ","geographicExtents":"{\n  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R Script</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2019-09-30","noUsgsAuthors":false,"publicationDate":"2019-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Valder, Joshua F. 0000-0003-3733-8868 jvalder@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-8868","contributorId":139256,"corporation":false,"usgs":true,"family":"Valder","given":"Joshua","email":"jvalder@usgs.gov","middleInitial":"F.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":770984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McShane, Ryan R. 0000-0002-3128-0039","orcid":"https://orcid.org/0000-0002-3128-0039","contributorId":219009,"corporation":false,"usgs":true,"family":"McShane","given":"Ryan R.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770985,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnhart, Theodore B. 0000-0002-9682-3217","orcid":"https://orcid.org/0000-0002-9682-3217","contributorId":219010,"corporation":false,"usgs":true,"family":"Barnhart","given":"Theodore","email":"","middleInitial":"B.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770986,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wheeling, Spencer L. 0000-0003-4411-6526","orcid":"https://orcid.org/0000-0003-4411-6526","contributorId":219011,"corporation":false,"usgs":true,"family":"Wheeling","given":"Spencer L.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770987,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carter, Janet M. 0000-0002-6376-3473","orcid":"https://orcid.org/0000-0002-6376-3473","contributorId":40660,"corporation":false,"usgs":true,"family":"Carter","given":"Janet M.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":770988,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Macek-Rowland, Kathleen M.  0000-0003-2526-6860","orcid":"https://orcid.org/0000-0003-2526-6860","contributorId":219012,"corporation":false,"usgs":true,"family":"Macek-Rowland","given":"Kathleen M. ","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770989,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Delzer, Gregory C. 0000-0002-7077-4963","orcid":"https://orcid.org/0000-0002-7077-4963","contributorId":203448,"corporation":false,"usgs":true,"family":"Delzer","given":"Gregory","email":"","middleInitial":"C.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770990,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thamke, Joanna N. 0000-0002-6917-1946 jothamke@usgs.gov","orcid":"https://orcid.org/0000-0002-6917-1946","contributorId":1012,"corporation":false,"usgs":true,"family":"Thamke","given":"Joanna N.","email":"jothamke@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":770991,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70203179,"text":"70203179 - 2019 - Linking sedimentation and erosion patterns with reservoir morphology and dam operations during streambed drawdowns in a flood-control reservoir in the Oregon Cascades","interactions":[],"lastModifiedDate":"2022-01-12T15:24:06.587116","indexId":"70203179","displayToPublicDate":"2019-09-30T17:11:38","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Linking sedimentation and erosion patterns with reservoir morphology and dam operations during streambed drawdowns in a flood-control reservoir in the Oregon Cascades","docAbstract":"<p>Since water-year (WY) 2011, pool levels at Fall Creek Lake, Oregon, are temporarily lowered to an elevation near historical streambed each fall, creating free-flowing channel conditions that facilitate downstream passage of juvenile spring Chinook salmon. These drawdown operations have also mobilized substantial quantities of predominantly fine (&lt;2 mm) reservoir sediment as well as some coarser gravels. To assess the potential impact of reservoir sediment erosion and transport on downstream reach morphology and habitats, linkages between reservoir sedimentation in Fall Creek Lake and drawdown-related reservoir erosion are inferred from geomorphic mapping and volumetric change analyses developed from high resolution aerial photographs and digital elevation models of the empty reservoir. Recent and historical drawdown operations have helped maintain a thalweg in much of Fall Creek Lake, constraining most coarse-grained sediment transport and re-deposition, whereas fine-grained deposition has mainly occurred on the former floodplain and lowermost reservoir reaches. Fine-grained sediment deposits are thickest and bury pre-dam morphology immediately upstream of the dam where they are accessible to fluvial erosion during streambed drawdown operations. Farther from the dam, where pre-dam morphology has not been buried, erosion is limited to sediment accumulation in the reservoir thalweg and minor tributary and ‘drawdown’ channels. In former floodplain regions of the reservoir not adjacent to the thalweg, thicker sediment deposits are inaccessible to fluvial erosion at full streambed drawdown. Altogether, these findings highlight controls on patterns and processes of reservoir erosion during drawdowns. This understanding of long-term sedimentation and streambed-drawdown erosion at Fall Creek Lake allows better evaluation and anticipation of the timing, magnitude, and sediment characteristics delivered to downstream reaches.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SEDHYD 2019","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD 2019 Conference","conferenceDate":"June 24-28, 2019","conferenceLocation":"Reno, NV","language":"English","publisher":"Federal Interagency Sedimentation Conference (FISC) and Federal Interagency Hydrologic Modeling Conference (FIHMC)","usgsCitation":"Keith, M.K., and Stratton, L., 2019, Linking sedimentation and erosion patterns with reservoir morphology and dam operations during streambed drawdowns in a flood-control reservoir in the Oregon Cascades, <i>in</i> Proceedings of SEDHYD 2019, v. 3, Reno, NV, June 24-28, 2019, 11 p.","productDescription":"11 p.","ipdsId":"IP-104720","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":369932,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":369931,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2019/#sedhyd-2019-proceedings"}],"country":"United States","state":"Oregon","otherGeospatial":"Fall Creek Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.76088714599608,\n              43.92336814487696\n            ],\n            [\n              -122.65205383300781,\n              43.92336814487696\n            ],\n            [\n              -122.65205383300781,\n              43.97922818610027\n            ],\n            [\n              -122.76088714599608,\n              43.97922818610027\n            ],\n            [\n              -122.76088714599608,\n              43.92336814487696\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Keith, Mackenzie K. 0000-0002-7239-0576 mkeith@usgs.gov","orcid":"https://orcid.org/0000-0002-7239-0576","contributorId":196963,"corporation":false,"usgs":true,"family":"Keith","given":"Mackenzie","email":"mkeith@usgs.gov","middleInitial":"K.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":761525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stratton, Laurel E. 0000-0001-8567-8619","orcid":"https://orcid.org/0000-0001-8567-8619","contributorId":215056,"corporation":false,"usgs":true,"family":"Stratton","given":"Laurel E.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":761526,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70205422,"text":"ofr20191100 - 2019 - Anderson Ranch wetlands hydrologic characterization in Taos County, New Mexico","interactions":[],"lastModifiedDate":"2019-10-03T14:08:15","indexId":"ofr20191100","displayToPublicDate":"2019-09-30T15:57:27","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1100","displayTitle":"Anderson Ranch Wetlands Hydrologic Characterization in Taos County, New Mexico","title":"Anderson Ranch wetlands hydrologic characterization in Taos County, New Mexico","docAbstract":"<p>The Anderson Ranch property (study area), located in Taos County, north-central New Mexico, was transferred from Chevron Mining, Inc. (CMI) to the Bureau of Land Management (BLM) as part of a Natural Resource Damage Assessment and Restoration (NRDAR) court-ordered settlement. The study area supports freshwater emergent wetlands and freshwater ponds. The settlement states that CMI will provide the land and a monetary settlement to support the restoration of the wetlands on the property. To best manage the study area, the BLM requires an understanding of potential effects of climate variability and groundwater withdrawals on the wetland function. This study, completed by the U.S. Geological Survey in cooperation with the BLM, provides an initial hydrologic characterization of the study area, which included literature review, collection of groundwater-level and aqueous-chemistry data, completion of a vegetation survey, and preliminary data analysis. The data compiled, collected, and analyzed as part of this study indicate that the wetlands within the study area are groundwater fed and that the water maintaining the wetlands is modern. Surface-water levels in the pond and groundwater levels in the surrounding wetland fluctuate seasonally. The hydraulic gradient in the study area is from northeast to southwest. Evapotranspiration is a main driver of water demand within the study area.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191100","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Galanter, A.E., Shephard, Z.M., and Herrera-Olivas, P., 2019, Anderson Ranch wetlands hydrologic characterization in Taos County, New Mexico: U.S. Geological Survey Open-File Report 2019–1100, 42 p., https://doi.org/10.3133/ofr20191100. ","productDescription":"iii, 42 p. ","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-109765","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":367755,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1100/coverthb.jpg"},{"id":367756,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1100/ofr20191100.pdf","text":"Slide Presentation","size":"9.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1100"}],"country":"United States ","state":"New Mexico ","county":"Taos 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<a data-mce-href=\"https://www.usgs.gov/centers/nm-water\" href=\"https://www.usgs.gov/centers/nm-water\">New Mexico Water Science Center</a><br>U.S. Geological Survey<br>6700 Edith Blvd. NE, Suite B<br>Albuquerque, NM 87113<br></p>","tableOfContents":"<ul><li>Abstract</li><li>Purpose and Scope</li><li>Study Area</li><li>Study Approach</li><li>Hydrogeology</li><li>Groundwater Levels</li><li>Aqueous Chemistry</li><li>Vegetation Survey</li><li>Water Budget</li><li>Conclusions</li><li>Future Work</li><li>References Cited</li><li>Appendix</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2019-09-30","noUsgsAuthors":false,"publicationDate":"2019-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Galanter, Amy E. 0000-0002-2960-0136","orcid":"https://orcid.org/0000-0002-2960-0136","contributorId":219038,"corporation":false,"usgs":true,"family":"Galanter","given":"Amy","email":"","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":771114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shephard, Zachary M. 0000-0003-2994-3355","orcid":"https://orcid.org/0000-0003-2994-3355","contributorId":219039,"corporation":false,"usgs":true,"family":"Shephard","given":"Zachary","email":"","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":771115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herrera-Olivas, Pamela","contributorId":219040,"corporation":false,"usgs":false,"family":"Herrera-Olivas","given":"Pamela","email":"","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":771116,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70205607,"text":"70205607 - 2019 - Can geologic factors be predictive for distinguishing between productive and non-productive geothermal wells?","interactions":[],"lastModifiedDate":"2019-12-02T15:07:45","indexId":"70205607","displayToPublicDate":"2019-09-30T15:06:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1827,"text":"Geothermal Resources Council Transactions","active":true,"publicationSubtype":{"id":10}},"title":"Can geologic factors be predictive for distinguishing between productive and non-productive geothermal wells?","docAbstract":"Geologic data are examined to evaluate whether certain geologic characteristics occur in higher abundance or higher magnitude along production geothermal wells relative to non-productive wells. We perform 3D geologic mapping, 3D stress modeling, and fault-slip modeling to estimate fourteen different geologic factors that are hypothesized to control or correlate with well productivity. The geologic factors are; heat, fault-damage zone thickness, distance from active faults, fault intersection/termination density, fault curvature, slip tendency of faults, dilation tendency of faults, dilation resulting from modeled fault slip, normal stress reduction resulting from modeled fault slip, Coulomb shear stress increase resulting from modeled fault slip, the summed thickness of ‘favorable’ lithologies within a borehole, the summed  thickness of fault damage zones in favorable lithologies within a borehole, the distance along the borehole to the nearest geologic contact, and the thickness of individual stratigraphic units. These geologic factors are quantified along fifty wells at Brady geothermal system, including twelve production wells and thirty-one non-productive wells. Results indicate that geologic factors such as stress changes associated with faulting, nearness to and thickness of fault zones, distance from geologic contacts, and heat occur in higher magnitude or higher abundance along production wells relative to non-productive wells.  These geologic factors may play an important role in controlling the locations and distribution of fluid circulation in geothermal fields.","language":"English","publisher":"Geothermal Resources Council","usgsCitation":"Siler, D.L., Burns, E.R., and Faulds, J.E., 2019, Can geologic factors be predictive for distinguishing between productive and non-productive geothermal wells?: Geothermal Resources Council Transactions, v. 43, p. 884-901.","productDescription":"8 p.","startPage":"884","endPage":"901","ipdsId":"IP-108708","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":369828,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":369827,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1034178"}],"volume":"43","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Siler, Drew L. 0000-0001-7540-8244","orcid":"https://orcid.org/0000-0001-7540-8244","contributorId":203341,"corporation":false,"usgs":true,"family":"Siler","given":"Drew","email":"","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":771830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":771831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Faulds, James E","contributorId":218147,"corporation":false,"usgs":false,"family":"Faulds","given":"James","email":"","middleInitial":"E","affiliations":[{"id":39739,"text":"Nevada Bureau of Mines and Geology, University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":771832,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70205774,"text":"70205774 - 2019 - Integration of eDNA-based biological monitoring within the US Geological Survey’s national streamgage network","interactions":[],"lastModifiedDate":"2020-01-03T10:02:21","indexId":"70205774","displayToPublicDate":"2019-09-30T14:14:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Integration of eDNA-based biological monitoring within the US Geological Survey’s national streamgage network","docAbstract":"<p><span>This study explores the feasibility and utility of integrating environmental DNA (eDNA) assessments of species occurrences into the United States (U.S.) Geological Survey’s national streamgage network. We used an existing network of five gages in southwest Idaho to explore the type of information that could be gained as well as the associated costs and limitations. Hydrologic technicians were trained in eDNA sampling protocols and they collected samples during routine monthly visits to streamgages over an entire water year (2016). We analyzed the eDNA in the filtered water samples to determine the presence of two fish species: bull trout and rainbow trout. We then modeled the spatiotemporal distribution of each species using discharge and temperature data. To assess the influence of the spatial distribution of the gages on the biological information obtained, we also collected eDNA samples from locations between the gages three times during the water year. We found eDNA monitoring at the five gages provided meaningful information about the distribution of both species, especially when detection probabilities accounted for variations in temperature and discharge. Sampling between the gages provided additional information about bull trout distribution — the rarer of the two species. Our study suggests the integration of eDNA sampling into a streamgage network is feasible and could provide a novel and powerful source of biological information for riverine ecosystems in the U.S.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12800","usgsCitation":"Pilliod, D.S., Laramie, M., McCoy, D., and Maclean, S., 2019, Integration of eDNA-based biological monitoring within the US Geological Survey’s national streamgage network: Journal of the American Water Resources Association, v. 55, no. 6, p. 1505-1518, https://doi.org/10.1111/1752-1688.12800.","productDescription":"14 p.","startPage":"1505","endPage":"1518","numberOfPages":"14","ipdsId":"IP-104039","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":459688,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12800","text":"Publisher Index Page"},{"id":367934,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Nebraska ","otherGeospatial":"Bruneau–Jarbidge Rivers watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.26281738281249,\n              41.32732632036622\n            ],\n            [\n              -114.87854003906249,\n              41.32732632036622\n            ],\n            [\n              -114.87854003906249,\n              42.46399280017058\n            ],\n            [\n              -116.26281738281249,\n              42.46399280017058\n            ],\n            [\n              -116.26281738281249,\n              41.32732632036622\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"55","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":216342,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":772287,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Laramie, Matthew 0000-0001-7820-2583 mlaramie@usgs.gov","orcid":"https://orcid.org/0000-0001-7820-2583","contributorId":152532,"corporation":false,"usgs":true,"family":"Laramie","given":"Matthew","email":"mlaramie@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":772288,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCoy, Dorene","contributorId":219452,"corporation":false,"usgs":false,"family":"McCoy","given":"Dorene","email":"","affiliations":[{"id":39997,"text":"Idaho Water Science Center (retired)","active":true,"usgs":false}],"preferred":false,"id":772289,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maclean, Scott","contributorId":219453,"corporation":false,"usgs":false,"family":"Maclean","given":"Scott","email":"","affiliations":[{"id":6696,"text":"BLM","active":true,"usgs":false}],"preferred":false,"id":772290,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70205084,"text":"sir20195095 - 2019 - Water resources on Guam—Potential impacts of and adaptive response to climate change","interactions":[],"lastModifiedDate":"2019-12-30T11:39:08","indexId":"sir20195095","displayToPublicDate":"2019-09-30T12:48:06","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5095","displayTitle":"Water resources on Guam—Potential impacts of and adaptive response to climate change","title":"Water resources on Guam—Potential impacts of and adaptive response to climate change","docAbstract":"<p>The goals of this joint U.S. Geological Survey, University of Hawaiʻi, University of Guam, University of Texas, and East-West Center study were to (1) provide basic understanding about water resources for U.S. Department of Defense installations on Guam and (2) assess the resulting effect of sea-level rise and a changing climate on freshwater availability, on the basis of historic information, sea-level rise projections, and global-climate model temperature and rainfall projections. Downscaled regional climate models, informed by a multimodel ensemble of global climate models provided projections of future climate conditions for Guam. These projected climate conditions provided input to surface-water and groundwater models developed for Guam’s hydrology. Guam’s water resources in a future climate condition (2080–99) are projected to diminish relative to the recent climate condition. Projected average temperature increases, and average rainfall decreases will lead to reduced streamflow in southern Guam and reduced groundwater recharge to the Northern Guam Lens Aquifer (NGLA). Projected average temperatures in southern Guam will increase about 5.8 °F (3.22 °C), overall rainfall will decrease about 7 percent, and streamflow will consequently decrease 18 percent in important areas of southern Guam. Similarly, across the NGLA, future groundwater recharge will be 19 percent less than estimated recharge from 2012. Reduced future streamflow will decrease water availability from the Fena Valley Reservoir; however, the reservoir is expected to be able to supply water at recent demand rates without lowering the reservoir level to the elevation of the water-supply intakes throughout the simulated period of a future climate. A twelve-year simulation indicates that the reservoir can supply about twice the 2018 demand without lowering the reservoir level to the water-supply intakes. By following mitigation strategies to increase reservoir water availability, the withdrawal rate can be increased by 1.7 percent if the water-supply intakes are lowered 5 ft, by 3.5 percent if the spillway height is raised 5 ft, and by 5.3 percent if both strategies are combined. Higher sea level and reduced future recharge will decrease water availability from the NGLA. An index of composite chloride concentration from&nbsp;production wells increases to 300 milligrams per liter (mg/L) for future climate conditions and at 2010 withdrawal rates, compared with 130 mg/L under historic climate conditions. Most of this increase is due to reduced recharge as higher (+3.2 ft) sea level only has a small role in increasing withdrawn water salinity. A redistributed withdrawal scenario in which the composite chloride concentration is 290 mg/L offers only slight improvement. Should future droughts reduce recharge proportionally to the decreases observed during historic droughts, the composite concentration would be about 900 mg/L, and more than 70 percent of Guam’s production wells would produce water with a composite concentration greater than 500 mg/L. Potential mitigation strategies for increasing the potable yield of the NGLA in a future climate include reducing depths of deep production wells and reducing the withdrawal rates in selected wells projected to have higher chloride concentrations. Simulations show both strategies are effective in lowering the composite concentration of the withdrawn water.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195095","collaboration":"Prepared in cooperation with the Strategic Environmental Research and Development Program, U.S. Department of Defense","usgsCitation":"Gingerich, S.B., Johnson, A.G., Rosa, S.N., Marineau, M.D., Wright, S.A., Hay, L.E., Widlansky, M.J., Jenson, J.W., Wong, C.I., Banner, J.L., Keener, V.W., and Finucane, M.L., 2019, Water resources on Guam—Potential impacts of and adaptive response to climate change: U.S. Geological Survey Scientific Investigations Report 2019–5095, 55 p., https://doi.org/10.3133/sir20195095.","productDescription":"Report: viii, 55 p.: 3 Data Releases ","numberOfPages":"55","onlineOnly":"Y","ipdsId":"IP-099440","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":367769,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A64801","linkHelpText":"Mean annual water-budget components for Guam for historic (1990–2009) and future (2080–2099) climate conditions"},{"id":367768,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5095/sir20195095.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5095"},{"id":367770,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U34ACT","linkHelpText":"SUTRA model used to evaluate the freshwater flow system for a future (2080–2099) climate on Guam"},{"id":367771,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90S1CSX","linkHelpText":"Southern Guam watershed model and Fena Valley Reservoir water-balance model input files for historic (1990–2099) climate conditions"},{"id":367767,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5095/coverthb.jpg"}],"country":"Guam ","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              144.53613281249997,\n              13.090179355733738\n            ],\n            [\n              145.01953124999997,\n              13.090179355733738\n            ],\n            [\n              145.01953124999997,\n              13.870080100685891\n            ],\n            [\n              144.53613281249997,\n              13.870080100685891\n            ],\n            [\n              144.53613281249997,\n              13.090179355733738\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p style=\"font-weight: 400;\" data-mce-style=\"font-weight: 400;\"><a data-mce-href=\"mailto:dc_hi@usgs.gov\" href=\"mailto:dc_hi@usgs.gov\" target=\"_blank\" rel=\"noopener\">Director</a>,<br><a data-mce-href=\"https://www.usgs.gov/centers/piwsc\" href=\"https://www.usgs.gov/centers/piwsc\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\" data-mce-style=\"font-weight: 400;\">Pacific Islands Water Science Center</span></a><br><a data-mce-href=\"https://www.usgs.gov/\" href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\">U.S. Geological Survey</a><br>Inouye Regional Center<br>1845 Wasp Blvd., B176<br>Honolulu, HI 96818</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Water Resources on Guam</li><li>Methods</li><li>Results and Discussion</li><li>Study Limitations</li><li>Conclusions</li><li>References Cited</li><li>Appendix 1. Guam Water-Budget Models Used to Estimate Recharge</li><li>Appendix 2. Storage Capacity 5 Feet Above Spillway, Fena Valley Reservoir, Guam</li><li>Appendix 3. Stakeholder Outreach and Response</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2019-09-30","noUsgsAuthors":false,"publicationDate":"2019-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Gingerich, Stephen B. 0000-0002-4381-0746 sbginger@usgs.gov","orcid":"https://orcid.org/0000-0002-4381-0746","contributorId":1426,"corporation":false,"usgs":true,"family":"Gingerich","given":"Stephen","email":"sbginger@usgs.gov","middleInitial":"B.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":769914,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Adam G. 0000-0003-2448-5746 ajohnson@usgs.gov","orcid":"https://orcid.org/0000-0003-2448-5746","contributorId":4752,"corporation":false,"usgs":true,"family":"Johnson","given":"Adam","email":"ajohnson@usgs.gov","middleInitial":"G.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":769915,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosa, Sarah N. 0000-0002-3653-0826 snrosa@usgs.gov","orcid":"https://orcid.org/0000-0002-3653-0826","contributorId":2968,"corporation":false,"usgs":true,"family":"Rosa","given":"Sarah","email":"snrosa@usgs.gov","middleInitial":"N.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":769916,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marineau, Mathieu D. 0000-0002-6568-0743 mmarineau@usgs.gov","orcid":"https://orcid.org/0000-0002-6568-0743","contributorId":4954,"corporation":false,"usgs":true,"family":"Marineau","given":"Mathieu","email":"mmarineau@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":769917,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":769918,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hay, Lauren E. 0000-0003-3763-4595","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":211478,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":769919,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Widlansky, Matthew J.","contributorId":215334,"corporation":false,"usgs":false,"family":"Widlansky","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":39222,"text":"Joint Institute for Marine and Atmospheric Research, School of Ocean and Earth Science and Technology, University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":769920,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jenson, John W.","contributorId":218688,"corporation":false,"usgs":false,"family":"Jenson","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":39888,"text":"University of Guam, Water and Environmental Research Institute of the Western Pacific","active":true,"usgs":false}],"preferred":false,"id":769921,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wong, Corinne I.","contributorId":218689,"corporation":false,"usgs":false,"family":"Wong","given":"Corinne","email":"","middleInitial":"I.","affiliations":[{"id":39889,"text":"Environmental Science Institute, University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":769922,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Banner, Jay L.","contributorId":218690,"corporation":false,"usgs":false,"family":"Banner","given":"Jay","email":"","middleInitial":"L.","affiliations":[{"id":39890,"text":"University of Texas at Austin, Jackson School of Geosciences","active":true,"usgs":false}],"preferred":false,"id":769923,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Finucane, Melissa L.","contributorId":140152,"corporation":false,"usgs":false,"family":"Finucane","given":"Melissa","email":"","middleInitial":"L.","affiliations":[{"id":13398,"text":"East-West Center","active":true,"usgs":false}],"preferred":false,"id":769925,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Keener, Victoria W.","contributorId":218691,"corporation":false,"usgs":false,"family":"Keener","given":"Victoria","email":"","middleInitial":"W.","affiliations":[{"id":13398,"text":"East-West Center","active":true,"usgs":false}],"preferred":false,"id":769924,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70205851,"text":"70205851 - 2019 - A fuzzy logic approach for estimating recovery factors of miscible CO2-EOR projects in the United States","interactions":[],"lastModifiedDate":"2019-10-08T12:35:44","indexId":"70205851","displayToPublicDate":"2019-09-30T12:34:24","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2419,"text":"Journal of Petroleum Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"A fuzzy logic approach for estimating recovery factors of miscible CO2-EOR projects in the United States","docAbstract":"\"Recovery factor (RF) is one of the most fundamental parameters that define engineering and economical success of any operational phase in oil and gas production. The effectiveness of the operation, e.g. CO2-EOR (enhanced oil recovery with carbon dioxide injection), is usually defined by multiplying the resultant recovery factor by the original oil in place. Moreover, investment decisions for such engineering projects are also performed based on predicted recovery factors. Despite its importance, though, it is not easy to predict recovery factors as they are affected by many factors including the type of the recovery process, reservoir type, fluid properties, reservoir heterogeneity, depth, thickness, to name a few. The usual method of estimating recovery factors is laboratory experiments or numerical modeling, each of which has their own limitations due to data requirements, boundary conditions and scale effects.\nIn this work, a fuzzy inference system approach has been adopted to predict miscible CO2-EOR recovery factors of the major field applications in the United States with the premise that it can be used as a guidance tool for making decisions based on different inputs. The fuzzy system was build using a Mamdani-type fuzzy logic inference engine, and by using reservoir data compiled from different sources as inputs and recovery factors gathered from a literature survey. Due to the limited number of field cases that could be used for this purpose, 24 sets of applications were included in the study. Selected input variables were water saturation after waterflood (Sorw), well spacing, porosity, permeability, depth, net pay thickness, initial pressure, API gravity of oil, hydrocarbon pore volume CO2 injected, and reservoir lithology. The type of membership functions were decided based on the system’s predictive performance. The model showed reasonable predictive capability for the field observations of recovery factor despite the complexity of this parameter. In addition, since the fuzzy solution was multi-dimensional due to multiple inputs, system behavior was used to demonstrate response of miscible CO2-EOR recovery factor to different inputs.\n\"","language":"English","publisher":"Elsevier","doi":"10.1016/j.petrol.2019.106533","usgsCitation":"Karacan, C.O., 2019, A fuzzy logic approach for estimating recovery factors of miscible CO2-EOR projects in the United States: Journal of Petroleum Science and Engineering, v. 184, 106533, https://doi.org/10.1016/j.petrol.2019.106533.","productDescription":"106533","ipdsId":"IP-103343","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":368100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368097,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S0920410519309544"}],"volume":"184","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Karacan, C. Ozgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":201991,"corporation":false,"usgs":true,"family":"Karacan","given":"C.","email":"","middleInitial":"Ozgen","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":772619,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70211355,"text":"70211355 - 2019 - Finding the sweet spot: Shifting climate optima for maple syrup production in North America","interactions":[],"lastModifiedDate":"2020-07-29T13:43:01.131868","indexId":"70211355","displayToPublicDate":"2019-09-30T11:28:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Finding the sweet spot: Shifting climate optima for maple syrup production in North America","docAbstract":"Climate change is affecting the benefits society derives from forests. One such forest ecosystem service is maple syrup, which is primarily derived from Acer saccharum (sugar maple), currently an abundant and widespread tree species in eastern North America.  Two climate sensitive components of sap affect syrup production: sugar content and sap flow.  The sugar in maple sap derives from carbohydrate stores influenced by prior year growing season conditions.  Sap flow is tied to freeze/thaw cycles during early spring.  Predicting climate effects on syrup production thus requires integrating observations across scales and biological processes. We observed sap at 6 sugar maple stands spanning sugar maple’s latitudinal range over 2¬–6 years to predict the role of climate variation on sugar content and sap flow.  We found that the timing of sap collection advanced by 4.3 days for every 1 °C increase in March mean temperature, sap volume peaked at a January-May mean temperature of 1 °C, and sap sugar content declined by 0.1 °Brix for every 1 °C increase in previous May-October mean temperature. Using these empirical relationships, we projected that the sap collection season midpoint will be 1 month earlier and sap sugar content will decline by 0.7 °Brix across sugar maple’s range by the year 2100 in an RCP 8.5 climate change scenario. The region of maximum sap flow is expected to shift northward by 400km, from near the 43rd parallel to the 48th parallel by 2100. Our findings suggest climate change will have profound effects on syrup yield across most of sugar maple’s range; drastic shifts in the timing of the tapping season accompanied by flat to moderate increases in syrup yield per tap in Canada contrast with declines in syrup yield and higher frequencies of poor syrup production years across most of the U.S. range.","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2019.05.045","usgsCitation":"Rapp, J.M., Lutz, D.A., Huish, R.H., Dufour, B., Ahmed, S., Morelli, T.L., and Stinson, K.A., 2019, Finding the sweet spot: Shifting climate optima for maple syrup production in North America: Forest Ecology and Management, v. 448, p. 187-197, https://doi.org/10.1016/j.foreco.2019.05.045.","productDescription":"11 p.","startPage":"187","endPage":"197","ipdsId":"IP-104958","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":459695,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2019.05.045","text":"Publisher Index Page"},{"id":376779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"448","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rapp, Joshua M.","contributorId":200307,"corporation":false,"usgs":false,"family":"Rapp","given":"Joshua","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":794107,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lutz, David A.","contributorId":232418,"corporation":false,"usgs":false,"family":"Lutz","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":794108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huish, Ryan H.","contributorId":232414,"corporation":false,"usgs":false,"family":"Huish","given":"Ryan","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":794109,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dufour, Boris","contributorId":232415,"corporation":false,"usgs":false,"family":"Dufour","given":"Boris","email":"","affiliations":[],"preferred":false,"id":794110,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ahmed, Selena","contributorId":232416,"corporation":false,"usgs":false,"family":"Ahmed","given":"Selena","email":"","affiliations":[],"preferred":false,"id":794111,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":794003,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stinson, Kristina A.","contributorId":232417,"corporation":false,"usgs":false,"family":"Stinson","given":"Kristina","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":794112,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70205101,"text":"ofr20191099 - 2019 - Using the stream salmonid simulator (S3) to assess juvenile Chinook salmon (Oncorhynchus tshawytscha) production under historical and proposed action flows in the Klamath River, California","interactions":[],"lastModifiedDate":"2019-10-02T15:01:10","indexId":"ofr20191099","displayToPublicDate":"2019-09-30T11:00:32","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1099","displayTitle":"Using the Stream Salmonid Simulator (S3) to Assess Juvenile Chinook Salmon (<em>Oncorhynchus tshawytscha</em>) Production Under Historical and Proposed Action Flows in the Klamath River, California","title":"Using the stream salmonid simulator (S3) to assess juvenile Chinook salmon (Oncorhynchus tshawytscha) production under historical and proposed action flows in the Klamath River, California","docAbstract":"<h1>Executive Summary</h1><p class=\"p1\">The production of Klamath River fall Chinook salmon (<i>Oncorhynchus tshawytscha</i>) in northern California and southern Oregon is thought to be limited by poor survival during freshwater juvenile life stages, in part a result of <i>Ceratonova shasta</i>—a highly infectious disease that can lead to high fish mortality. Higher flushing river flows are thought to affect the concentration of <i>C. shasta</i> spores, and in turn, juvenile salmon infection and mortality. The Stream Salmonid Simulator (S3) model was built to simulate the spatiotemporal dynamics of the growth, movement, and survival of juvenile salmon from spawning through migration to the Pacific Ocean in response to river flow, habitat availability, water temperature, and <i>C. shasta</i> spore concentrations. The S3 model has been calibrated to juvenile fall Chinook salmon abundances at a trap site within the Klamath River, and was specifically designed to provide objective predictions of juvenile salmon abundance and survival in relation to proposed flow management alternatives and resulting fish infection and mortality by <i>C. shasta</i>. Infection by <i>C. shasta</i> in the Klamath River is location specific, occurring in a “disease zone” with high spore concentrations. The spatial extent of this disease zone (from river kilometer 289.6 to 212.9) has been incorporated in the S3 model for the Klamath River, enabling the assessment of disease effects on fish at specific spatial locations such as the trap sampling sites, and for fish that were or were not exposed to the disease zone as they emigrate the Klamath River to the Pacific Ocean.</p><p class=\"p1\">Given the information gained from field observations on spore concentrations in relation to river flow, deliberations by resource managers resulted in the incorporation of springtime flushing flows in a Proposed Action (PA) scenario developed in part to lower spore concentrations within the disease zone. A Historical (HI) scenario based on the observed flows, temperatures, and spore concentrations from 2004 to 2016 was used to compare and contrast the potential benefits to juvenile salmon from PA flows in relation to the HI conditions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191099","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration, National Marine Fisheries Service","usgsCitation":"Plumb, J.M., Perry, R.W., Som, N.A., Alexander, J., and Hetrick, N.J., 2019, Using the stream salmonid simulator (S3) to assess juvenile Chinook salmon (Oncorhynchus tshawytscha) production under historical and proposed action flows in the Klamath River, California: U.S. Geological Survey Open-File\nReport 2019-1099, 43 p., https://doi.org/10.3133/ofr20191099.","productDescription":"vi, 43 p.","onlineOnly":"Y","ipdsId":"IP-107092","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":367843,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1099/coverthb.jpg"},{"id":367844,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1099/ofr20191099.pdf","text":"Report","size":"3.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1099"}],"country":"United States","state":"California","otherGeospatial":"Klamath River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.5247802734375,\n              41.38917324986403\n            ],\n            [\n              -122.23114013671875,\n              41.38917324986403\n            ],\n            [\n              -122.23114013671875,\n              41.92475971933975\n            ],\n            [\n              -123.5247802734375,\n              41.92475971933975\n            ],\n            [\n              -123.5247802734375,\n              41.38917324986403\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/wfrc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/wfrc\">Western Fisheries Research Center</a><br>U.S. Geological Survey<br>6505 NE 65th Street<br>Seattle, Washington 98115-5016</p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2019-09-30","noUsgsAuthors":false,"publicationDate":"2019-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Plumb, John M. 0000-0003-4255-1612 jplumb@usgs.gov","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":3569,"corporation":false,"usgs":true,"family":"Plumb","given":"John","email":"jplumb@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":770028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":770029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Som, Nicholas A.","contributorId":203773,"corporation":false,"usgs":false,"family":"Som","given":"Nicholas","email":"","middleInitial":"A.","affiliations":[{"id":36713,"text":"Statistician, USFWS - Arcata Fisheries Program, Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":770030,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alexander, Julie","contributorId":218725,"corporation":false,"usgs":false,"family":"Alexander","given":"Julie","affiliations":[{"id":39896,"text":"Oregon State University, College of Agricultural Sciences and College of Science, Department of Microbiology, Nash Hall 522, Corvallis, OR 97331","active":true,"usgs":false}],"preferred":false,"id":770031,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hetrick, Nicholas J.","contributorId":168367,"corporation":false,"usgs":false,"family":"Hetrick","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":5128,"text":"U.S. Fish and Wildlife Service, University of Montana, Missoula, MT 59812","active":true,"usgs":false}],"preferred":false,"id":770032,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
]}