The cycling and sequestration of carbon are important ecosystem functions of estuarine wetlands that may be affected by climate change. We conducted experiments across a latitudinal and climate gradient of tidal marshes in the northeast Pacific to evaluate the effects of climate- and vegetation-related factors on litter decomposition. We manipulated tidal exposure and litter type in experimental mesocosms at two sites and used variation across marsh landscapes at seven sites to test for relationships between decomposition and marsh elevation, soil temperature, vegetation composition, litter quality, and sediment organic content. A greater than tenfold increase in manipulated tidal inundation resulted in small increases in decomposition of roots and rhizomes of two species, but no significant change in decay rates of shoots of three other species. In contrast, across the latitudinal gradient, decomposition rates of Salicornia pacifica litter were greater in high marsh than in low marsh. Rates were not correlated with sediment temperature or organic content, but were associated with plant assemblage structure including above-ground cover, species composition, and species richness. Decomposition rates also varied by litter type; at two sites in the Pacific Northwest, the grasses Deschampsia cespitosa and Distichlis spicata decomposed more slowly than the forb S. pacifica. Our data suggest that elevation gradients and vegetation structure in tidal marshes both affect rates of litter decay, potentially leading to complex spatial patterns in sediment carbon dynamics. Climate change may thus have direct effects on rates of decomposition through increased inundation from sea-level rise and indirect effects through changing plant community composition.
","language":"English","publisher":"Springer","doi":"10.1007/s10021-017-0111-6","usgsCitation":"Janousek, C., Buffington, K., Guntenspergen, G.R., Thorne, K.M., Dugger, B., and Takekawa, J.Y., 2017, Inundation, vegetation, and sediment effects on litter decomposition in Pacific Coast tidal marshes: Ecosystems, v. 20, no. 7, p. 1296-1310, https://doi.org/10.1007/s10021-017-0111-6.","productDescription":"15 p.","startPage":"1296","endPage":"1310","ipdsId":"IP-082125","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":438262,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70P0X6C","text":"USGS data release","linkHelpText":"Decomposition of plant litter in Pacific coast tidal marshes, 2014-2015"},{"id":344068,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126,\n 33\n ],\n [\n -115,\n 33\n ],\n [\n -115,\n 48\n ],\n [\n -126,\n 48\n ],\n [\n -126,\n 33\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"7","noUsgsAuthors":false,"publicationDate":"2017-02-03","publicationStatus":"PW","scienceBaseUri":"59706faee4b0d1f9f065a857","contributors":{"authors":[{"text":"Janousek, Christopher 0000-0003-2124-6715 cjanousek@usgs.gov","orcid":"https://orcid.org/0000-0003-2124-6715","contributorId":150053,"corporation":false,"usgs":true,"family":"Janousek","given":"Christopher","email":"cjanousek@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":705682,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buffington, Kevin J. 0000-0001-9741-1241 kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":705683,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":705684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorne, Karen M. 0000-0002-1381-0657 kthorne@usgs.gov","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":4191,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen","email":"kthorne@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":705685,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dugger, Bruce D.","contributorId":81236,"corporation":false,"usgs":true,"family":"Dugger","given":"Bruce D.","affiliations":[],"preferred":false,"id":705686,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":705687,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70189642,"text":"70189642 - 2017 - Observations of indirect filial cannibalism in response to nest failure of Black-crowned Night-Herons (Nycticorax nycticorax)","interactions":[],"lastModifiedDate":"2017-07-20T10:56:38","indexId":"70189642","displayToPublicDate":"2017-07-19T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3784,"text":"Wilson Journal of Ornithology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Observations of indirect filial cannibalism in response to nest failure of Black-crowned Night-Herons (Nycticorax nycticorax)","title":"Observations of indirect filial cannibalism in response to nest failure of Black-crowned Night-Herons (Nycticorax nycticorax)","docAbstract":"During 2011, four separate instances of indirect filial cannibalism, whereby adults consumed their young that died from unknown causes, were observed using video-monitoring techniques in a nesting colony of Black-crowned Night-Herons (Nycticorax nycticorax) on Alcatraz Island. Though they were not observed actively killing their young, in all four observations adult Black-crowned Night-Herons consumed their young following death (i.e., indirect filial cannibalism). We could not determine cause of chick mortality, but parental neglect was likely a contributing factor in at least two instances. Indirect filial cannibalism is not commonly documented among birds, and understanding how cannibalism contributes to nest failure can help researchers better understand factors that limit nesting populations.
","language":"English","publisher":"Wilson Ornithological Society","doi":"10.1676/16-013.1","usgsCitation":"Brussee, B.E., Coates, P.S., Dwight, I., and Young, L.G., 2017, Observations of indirect filial cannibalism in response to nest failure of Black-crowned Night-Herons (Nycticorax nycticorax): Wilson Journal of Ornithology, v. 129, no. 2, p. 390-394, https://doi.org/10.1676/16-013.1.","productDescription":"5 p.","startPage":"390","endPage":"394","ipdsId":"IP-075281","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":344035,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Alcatraz Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.42381393909456,\n 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bbrussee@usgs.gov","orcid":"https://orcid.org/0000-0002-2452-7101","contributorId":4249,"corporation":false,"usgs":true,"family":"Brussee","given":"Brianne","email":"bbrussee@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":705549,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":705548,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dwight, Ian 0000-0002-8393-5391 idwight@usgs.gov","orcid":"https://orcid.org/0000-0002-8393-5391","contributorId":192077,"corporation":false,"usgs":true,"family":"Dwight","given":"Ian","email":"idwight@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":705550,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, Laura G.","contributorId":194873,"corporation":false,"usgs":false,"family":"Young","given":"Laura","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":705551,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189619,"text":"70189619 - 2017 - Adjusting central and eastern North America ground-motion intensity measures between sites with different reference-rock site conditions","interactions":[],"lastModifiedDate":"2021-04-27T19:14:28.758048","indexId":"70189619","displayToPublicDate":"2017-07-19T00:00:00","publicationYear":"2017","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":"Adjusting central and eastern North America ground-motion intensity measures between sites with different reference-rock site conditions","docAbstract":"Adjustment factors are provided for converting ground‐motion intensity measures between central and eastern North America (CENA) sites with different reference‐rock site conditions (VS30=760, 2000, and 3000 m/s) for moment magnitudes ranging from 2 to 8, rupture distances ranging from 2 to 1200 km, Fourier amplitude spectra (FAS) for frequencies ranging from 0.01 to 100 Hz, response spectra for periods ranging from 0.01 to 10.0 s, peak ground acceleration, and peak ground velocity. The adjustment factors are given for a wide range of the site diminution parameters (κ0) for sites with VS30=760 m/s and for a κ0 of 0.006 s for two harder rock sites. Fourteen CENA velocity profiles with VS30 values within a factor of 1.1 of 760 m/s were used to derive average FAS amplification factors as a function of frequency, which were then used in simulations of peak ground‐motion parameters and response spectra to derive the adjustment factors. The amplification function differs from that used in western North America (e.g., Campbell and Boore, 2016) in having a peak near 9 Hz, due to the resonance of motions in the relatively thin low‐velocity material over hard rock that characterizes many CENA sites with VS30 near 760 m/s. We call these B/C sites, because this velocity marks the boundary between National Earthquake Hazards Reduction Program site classes B and C (Building Seismic Safety Council, 2004). The adjustments for short‐period motions are sensitive to the value of κ0, but there are very few if any determinations of κ0 for CENA B/C sites. For this reason, we determined κ0from multiple recordings at Pinyon Flat Observatory (PFO), California, which has a velocity‐depth profile similar to those of CENA B/C sites. The PFO and other results from the literature suggest that appropriate values of κ0 for CENA B/C sites are expected to lie between 0.01 and 0.03 s.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120160208","usgsCitation":"Boore, D., and Campbell, K.W., 2017, Adjusting central and eastern North America ground-motion intensity measures between sites with different reference-rock site conditions: Bulletin of the Seismological Society of America, v. 107, no. 1, p. 132-148, https://doi.org/10.1785/0120160208.","productDescription":"17 p.","startPage":"132","endPage":"148","ipdsId":"IP-063723","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":344017,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-20","publicationStatus":"PW","scienceBaseUri":"59706fb0e4b0d1f9f065a86d","contributors":{"authors":[{"text":"Boore, David 0000-0002-8605-9673 boore@usgs.gov","orcid":"https://orcid.org/0000-0002-8605-9673","contributorId":140502,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705461,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell, Kenneth W.","contributorId":74391,"corporation":false,"usgs":false,"family":"Campbell","given":"Kenneth","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":705542,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70189644,"text":"70189644 - 2017 - Trends and drivers of fire activity vary across California aridland ecosystems","interactions":[],"lastModifiedDate":"2017-07-19T13:25:55","indexId":"70189644","displayToPublicDate":"2017-07-19T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Trends and drivers of fire activity vary across California aridland ecosystems","docAbstract":"Fire activity has increased in western US aridland ecosystems due to increased human-caused ignitions and the expansion of flammable exotic grasses. Because many desert plants are not adapted to fire, increased fire activity may have long-lasting ecological impacts on native vegetation and the wildlife that depend on it. Given the heterogeneity across aridland ecosystems, it is important to understand how trends and drivers of fire vary, so management can be customized accordingly. We examined historical trends and quantified the relative importance of and interactions among multiple drivers of fire patterns across five aridland ecoregions in southeastern California from 1970 to 2010. Fire frequency increased across all ecoregions for the first couple decades, and declined or plateaued since the 1990s; but area burned continued to increase in some regions. The relative importance of anthropogenic and biophysical drivers varied across ecoregions, with both direct and indirect influences on fire. Anthropogenic variables were equally important as biophysical variables, but some contributed indirectly, presumably via their influence on annual grass distribution and abundance. Grass burned disproportionately more than other cover types, suggesting that addressing exotics may be the key to fire management and conservation in much of the area.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2017.03.017","usgsCitation":"Syphard, A.D., Keeley, J.E., and Abatzoglou, J.T., 2017, Trends and drivers of fire activity vary across California aridland ecosystems: Journal of Arid Environments, v. 144, p. 110-122, https://doi.org/10.1016/j.jaridenv.2017.03.017.","productDescription":"13 p.","startPage":"110","endPage":"122","ipdsId":"IP-076808","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":344047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.970947265625,\n 32.667124733120325\n ],\n [\n -114.136962890625,\n 32.667124733120325\n ],\n [\n -114.136962890625,\n 37.90953361677018\n ],\n [\n -118.970947265625,\n 37.90953361677018\n ],\n [\n -118.970947265625,\n 32.667124733120325\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"144","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59706fafe4b0d1f9f065a860","contributors":{"authors":[{"text":"Syphard, Alexandra D.","contributorId":8977,"corporation":false,"usgs":false,"family":"Syphard","given":"Alexandra","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":705557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":705556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Abatzoglou, John T.","contributorId":191729,"corporation":false,"usgs":false,"family":"Abatzoglou","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":33345,"text":" University of Idaho","active":true,"usgs":false}],"preferred":false,"id":705558,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189687,"text":"70189687 - 2017 - Evidence of Asian carp spawning upstream of a key choke point in the Mississippi River","interactions":[],"lastModifiedDate":"2017-07-21T10:39:56","indexId":"70189687","displayToPublicDate":"2017-07-19T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Evidence of Asian carp spawning upstream of a key choke point in the Mississippi River","docAbstract":"Bighead Carp Hypophthalmichthys nobilis, Silver Carp H. molitrix, and Grass Carp Ctenopharyngodon idella(collectively termed “Asian carp”) were introduced into North America during the 1960s and 1970s and have become established in the lower Mississippi River basin. Previously published evidence for spawning of these species in the upper Mississippi River has been limited to an area just downstream of Dam 22 (near Saverton, Missouri). In 2013 and 2014, we sampled ichthyoplankton at 18 locations in the upper Mississippi River main stem from Dam 9 through Dam 19 and in four tributaries of the Mississippi River (Des Moines, Skunk, Iowa, and Wisconsin rivers). We identified eggs and larvae by using morphological techniques and then used genetic tools to confirm species identity. The spawning events we observed often included more than one species of Asian carp and in a few cases included eggs that must have been derived from more than one upstream spawning event. The upstream extent of genetically confirmed Grass Carp ichthyoplankton was the Wisconsin River, while Bighead Carp and Silver Carp ichthyoplankton were observed in Pool 16. In all these cases, ichthyoplankton likely drifted downstream for several hours prior to collection. Higher water velocities (and, to a lesser extent, higher temperatures) were associated with an increased likelihood of observing eggs or larvae, although the temperature range we encountered was mostly above 17°C. Several major spawning events were detected in 2013, but no major spawning events were observed in 2014. The area between Dam 15 and Dam 19 appears to be the upstream edge of spawning activity for both Silver Carp and Bighead Carp, suggesting that this area could be a focal point for management efforts designed to limit further upstream movement of these species..
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/02755947.2017.1327901","usgsCitation":"Larson, J.H., Knights, B.C., McCalla, S.G., Monroe, E., Tuttle-Lau, M.T., Chapman, D., George, A.E., Vallazza, J.M., and Amberg, J., 2017, Evidence of Asian carp spawning upstream of a key choke point in the Mississippi River: North American Journal of Fisheries Management, v. 37, no. 4, p. 903-919, https://doi.org/10.1080/02755947.2017.1327901.","productDescription":"18 p. ","startPage":"903","endPage":"919","ipdsId":"IP-077083","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":469673,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Evidence_of_Asian_Carp_Spawning_Upstream_of_a_Key_Choke_Point_in_the_Mississippi_River/5222098","text":"External Repository"},{"id":344114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.26318359375,\n 44.35527821160296\n ],\n [\n -91.56005859375,\n 43.068887774169625\n ],\n [\n -91.34033203125,\n 42.601619944327965\n ],\n [\n -91.2744140625,\n 41.541477666790286\n ],\n [\n -91.69189453125,\n 40.79717741518766\n ],\n [\n -91.69189453125,\n 40.212440718286466\n ],\n [\n -91.7138671875,\n 39.605688178320804\n ],\n [\n -91.49414062499999,\n 38.87392853923629\n ],\n [\n -90.966796875,\n 37.52715361723378\n ],\n [\n -89.20898437499999,\n 37.59682400108367\n ],\n [\n -89.736328125,\n 38.839707613545144\n ],\n [\n -91.0546875,\n 40.06125658140474\n ],\n [\n -90.85693359375,\n 40.59727063442024\n ],\n [\n -89.69238281249999,\n 41.623655390686395\n ],\n [\n -89.9560546875,\n 42.22851735620852\n ],\n [\n -90.791015625,\n 43.24520272203356\n ],\n [\n -91.03271484375,\n 44.35527821160296\n ],\n [\n -92.26318359375,\n 44.35527821160296\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-19","publicationStatus":"PW","scienceBaseUri":"5971c1c0e4b0ec1a4885dab8","contributors":{"authors":[{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":705810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":705811,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCalla, S. Grace 0000-0003-4292-8694 smccalla@usgs.gov","orcid":"https://orcid.org/0000-0003-4292-8694","contributorId":168436,"corporation":false,"usgs":true,"family":"McCalla","given":"S.","email":"smccalla@usgs.gov","middleInitial":"Grace","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":705812,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Monroe, Emy","contributorId":140978,"corporation":false,"usgs":false,"family":"Monroe","given":"Emy","affiliations":[{"id":13635,"text":"Whitney Genetics Lab, U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":705813,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tuttle-Lau, Maren T.","contributorId":146196,"corporation":false,"usgs":false,"family":"Tuttle-Lau","given":"Maren","email":"","middleInitial":"T.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":705814,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":705815,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"George, Amy E. 0000-0003-1150-8646 ageorge@usgs.gov","orcid":"https://orcid.org/0000-0003-1150-8646","contributorId":3950,"corporation":false,"usgs":true,"family":"George","given":"Amy","email":"ageorge@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":705816,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Vallazza, Jonathan M. 0000-0003-2367-4887 jvallazza@usgs.gov","orcid":"https://orcid.org/0000-0003-2367-4887","contributorId":149362,"corporation":false,"usgs":true,"family":"Vallazza","given":"Jonathan","email":"jvallazza@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":705817,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":705818,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70189636,"text":"70189636 - 2017 - Alternative rupture-scaling relationships for subduction interface and other offshore environments","interactions":[],"lastModifiedDate":"2017-07-19T08:19:16","indexId":"70189636","displayToPublicDate":"2017-07-19T00:00:00","publicationYear":"2017","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":"Alternative rupture-scaling relationships for subduction interface and other offshore environments","docAbstract":"Alternative fault-rupture-scaling relationships are developed for Mw 7.1–\n9.5 subduction interface earthquakes using a new database of consistently derived finitefault\nrupture models from teleseismic inversion. Scaling relationships are derived for\nrupture area, rupture length, rupture width, maximum slip, and average slip. These relationships\napply width saturation for large-magnitude interface earthquakes (approximately\nMw >8:6) for which the physical characteristics of subduction zones limit the\ndepth extent of seismogenic rupture, and consequently, the down-dip limit of strong\nground motion generation. On average, the down-dip rupture width for interface earthquakes\nsaturates near 200 km (196 km on average). Accordingly, the reinterpretation of\nrupture-area scaling for subduction interface earthquakes through the use of a bilinear\nscaling model suggests that rupture asperity area is less well correlated with magnitude\nfor earthquakes Mw >8:6. Consequently, the size of great-magnitude earthquakes appears\nto be more strongly controlled by the average slip across asperities.\nThe sensitivity of the interface scaling relationships is evaluated against geographic\nregion (or subduction zone) and average dip along the rupture interface to\nassess the need for correction factors. Although regional perturbations in fault-rupture\nscaling could be identified, statistical significance analyses suggest there is little\nrationale for implementing regional correction factors based on the limited number\nof interface rupture models available for each region.\nFault-rupture-scaling relationships are also developed for intraslab (within the\nsubducting slab), extensional outer-rise and offshore strike-slip environments. For\nthese environments, the rupture width and area scaling properties yield smaller dimensions\nthan interface ruptures for the corresponding magnitude. However, average and\nmaximum slip metrics yield larger values than interface events. These observations\nreflect both the narrower fault widths and higher stress drops in these faulting environments.\nAlthough expressing significantly different rupture-scaling properties from\nearthquakes in subduction environments, the characteristics of offshore strike-slip\nearthquake ruptures compare similarly to commonly used rupture-scaling relationships\nfor onshore strike-slip earthquakes.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120160255","usgsCitation":"Allen, T., and Hayes, G.P., 2017, Alternative rupture-scaling relationships for subduction interface and other offshore environments: Bulletin of the Seismological Society of America, v. 107, no. 3, p. 1240-1253, https://doi.org/10.1785/0120160255.","productDescription":"14 p.","startPage":"1240","endPage":"1253","ipdsId":"IP-083339","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":344007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-21","publicationStatus":"PW","scienceBaseUri":"59706fb0e4b0d1f9f065a869","contributors":{"authors":[{"text":"Allen, Trevor I.","contributorId":138667,"corporation":false,"usgs":false,"family":"Allen","given":"Trevor","middleInitial":"I.","affiliations":[{"id":6672,"text":"former: USGS Southwest Biological Science Center, Colorado Plateau Research Station, Flagstaff, AZ. Current address: TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":false,"id":705525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayes, Gavin P. 0000-0003-3323-0112 ghayes@usgs.gov","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":147556,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin","email":"ghayes@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705526,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70188308,"text":"fs20173043 - 2017 - Assessment of continuous oil and gas resources in the San Jorge Basin Province, Argentina, 2017","interactions":[],"lastModifiedDate":"2017-07-19T12:48:44","indexId":"fs20173043","displayToPublicDate":"2017-07-18T15:50:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-3043","title":"Assessment of continuous oil and gas resources in the San Jorge Basin Province, Argentina, 2017","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated mean undiscovered, technically recoverable resources of 78 million barrels of oil and 8.9 trillion cubic feet of gas in the San Jorge Basin Province, Argentina.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173043","usgsCitation":"Schenk, C.J., Mercier, T.J., Hawkins, S.J., Tennyson, M.E., Marra, K.R., Finn, T.M., Le, P.A., Brownfield, M.E., Leathers-Miller, H.M., and Woodall, C.A., 2017, Assessment of continuous oil and gas resources in the San Jorge Basin Province, Argentina, 2017: U.S. Geological Survey Fact Sheet 2017–3043, 2 p., https://doi.org/10.3133/fs20173043.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-085502","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":343850,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3043/fs20173043.pdf","text":"Report","size":"356 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3043"},{"id":343851,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20173042","text":"Fact Sheet 2017–3042:","linkHelpText":"Assessment of Undiscovered Oil and Gas Resources in the Cuyo Basin Province, Argentina, 2017"},{"id":343849,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3043/coverthb.jpg"},{"id":343865,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20173025","text":"Fact Sheet 2017–3025:","linkHelpText":"Assessment of Continuous Oil and Gas Resources in the Neuquén Basin Province, Argentina, 2016"}],"country":"Argentina","state":"San Jorge Basin Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72,\n -48.25\n ],\n [\n -63,\n -48.25\n ],\n [\n -63,\n -42\n ],\n [\n -72,\n -42\n ],\n [\n -72,\n -48.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Using a geology-based assessment methodology, the U.S. Geological Survey estimated mean undiscovered, technically recoverable resources of 236 million barrels of oil and 112 billion cubic feet of associated gas in the Cuyo Basin Province, Argentina.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173042","usgsCitation":"Schenk, C.J., Brownfield, M.E., Tennyson, M.E., Le, P.A., Mercier, T.J., Finn, T.M., Hawkins, S.J., Gaswirth, S.B., Marra, K.R., Klett, T.R., Leathers-Miller, H.M., and Woodall, C.A., 2017, Assessment of undiscovered oil and gas resources in the Cuyo Basin Province, Argentina, 2017: U.S. Geological Survey Fact Sheet 2017–3042, 2 p., https://doi.org/10.3133/fs20173042.","productDescription":"Report: 2 p. ","startPage":"1","endPage":"2","onlineOnly":"N","ipdsId":"IP-086211","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":343843,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3042/fs20173042.pdf","text":"Report","size":"364 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3042"},{"id":343846,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20173043","text":"Fact Sheet 2017–3043:","linkHelpText":"Assessment of Continuous Oil and Gas Resources in the San Jorge Basin Province, Argentina, 2017"},{"id":343862,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20173025","text":"Fact Sheet 2017–3025:","linkHelpText":"Assessment of Continuous Oil and Gas Resources in the Neuquén Basin Province, Argentina, 2016"},{"id":343842,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3042/coverthb.jpg"}],"country":"Argentina","otherGeospatial":"Cuyo Basin Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -69.697265625,\n -33.87041555094182\n ],\n [\n -70.4443359375,\n -34.70549341022545\n ],\n [\n -70.5322265625,\n -35.281500657891186\n ],\n [\n -70.400390625,\n -35.81781315869662\n ],\n [\n -70.6640625,\n -36.3151251474805\n ],\n [\n -71.103515625,\n -36.63316209558656\n ],\n [\n -71.1474609375,\n -37.020098201368114\n ],\n [\n -71.279296875,\n -37.64903402157864\n ],\n [\n -71.19140625,\n -38.272688535980954\n ],\n [\n -70.5322265625,\n -37.54457732085582\n ],\n [\n -70.0048828125,\n -37.020098201368114\n ],\n [\n -69.43359375,\n -37.020098201368114\n ],\n [\n -68.6865234375,\n -37.19533058280063\n ],\n [\n -68.203125,\n -38.03078569382294\n ],\n [\n -67.4560546875,\n -38.8225909761771\n ],\n [\n -65.7421875,\n -35.71083783530008\n ],\n [\n -66.09375,\n -34.74161249883172\n ],\n [\n -66.97265625,\n -34.415973384481866\n ],\n [\n -68.203125,\n -34.161818161230386\n ],\n [\n -69.697265625,\n -33.87041555094182\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Long-term rates of shoreline change for the Gulf of Mexico and Southeast Atlantic regions of the United States have been updated as part of the U.S. Geological Survey’s National Assessment of Shoreline Change project. Additional shoreline position data were used to compute rates where the previous rate-of-change assessment only included four shoreline positions at a given location. The long-term shoreline change rates also incorporate the proxy-datum bias correction to account for the unidirectional onshore bias of the proxy-based high water line shorelines relative to the datum-based mean high water shorelines. The calculation of uncertainty associated with the long-term average rates has also been updated to match refined methods used in other study regions of the National Assessment project. The average rates reported here have a reduced amount of uncertainty relative to those presented in the previous assessments for these two regions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171015","usgsCitation":"Himmelstoss, E.A., Kratzmann, M.G., and Thieler, E.R., 2017, National assessment of shoreline change—Summary statistics for updated vector shorelines and associated shoreline change data for the Gulf of Mexico and Southeast Atlantic coasts: U.S. Geological Survey Open-File Report 2017–1015, 8 p., https://doi.org/10.3133/ofr20171015.","productDescription":"Report: vi, 8 p.; 2 Data Releases","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-080390","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":343570,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1015/coverthb.jpg"},{"id":343571,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1015/ofr20171015.pdf","text":"Report","size":"567 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\"}}]}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center routinely produces and distributes a remote sensing phenology (RSP) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR) 1-km data compiled from a series of National Oceanic and Atmospheric Administration (NOAA) satellites (NOAA-11, −14, −16, −17, −18, and −19). Each NOAA satellite experienced orbital drift during its duty period, which influenced the AVHRR reflectance measurements. To understand the effect of the orbital drift on the AVHRR-derived RSP dataset, we analyzed the impact of solar zenith angle (SZA) on the RSP metrics in the conterminous United States (CONUS). The AVHRR weekly composites were used to calculate the growing-season median SZA at the pixel level for each year from 1989 to 2014. The results showed that the SZA increased towards the end of each NOAA satellite mission with the highest increasing rate occurring during NOAA-11 (1989–1994) and NOAA-14 (1995–2000) missions. The growing-season median SZA values (44°–60°) in 1992, 1993, 1994, 1999, and 2000 were substantially higher than those in other years (28°–40°). The high SZA in those years caused negative trends in the SZA time series, that were statistically significant (at α = 0.05 level) in 76.9% of the CONUS area. A pixel-based temporal correlation analysis showed that the phenological metrics and SZA were significantly correlated (at α = 0.05 level) in 4.1–20.4% of the CONUS area. After excluding the 5 years with high SZA (>40°) from the analysis, the temporal SZA trend was largely reduced, significantly affecting less than 2% of the study area. Additionally, significant correlation between the phenological metrics and SZA was observed in less than 7% of the study area. Our study concluded that the NOAA satellite orbital drift increased SZA, and in turn, influenced the phenological metrics. Elimination of the years with high median SZA reduced the influence of orbital drift on the RSP time series.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jag.2017.06.013","usgsCitation":"Ji, L., and Brown, J.F., 2017, Effect of NOAA satellite orbital drift on AVHRR-derived phenological metrics: International Journal of Applied Earth Observation and Geoinformation, v. 62, p. 215-223, https://doi.org/10.1016/j.jag.2017.06.013.","productDescription":"9 p.","startPage":"215","endPage":"223","ipdsId":"IP-081678","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":469675,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jag.2017.06.013","text":"Publisher Index Page"},{"id":343965,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"596f1e1fe4b0d1f9f064073c","contributors":{"authors":[{"text":"Ji, Lei 0000-0002-6133-1036 lji@usgs.gov","orcid":"https://orcid.org/0000-0002-6133-1036","contributorId":139587,"corporation":false,"usgs":true,"family":"Ji","given":"Lei","email":"lji@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":705288,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":176609,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":705289,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70189586,"text":"fs20173054 - 2017 - Brackish groundwater and its potential to augment freshwater supplies","interactions":[],"lastModifiedDate":"2017-07-19T08:49:00","indexId":"fs20173054","displayToPublicDate":"2017-07-18T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-3054","title":"Brackish groundwater and its potential to augment freshwater supplies","docAbstract":"Secure, reliable, and sustainable water resources are fundamental to the Nation’s food production, energy independence, and ecological and human health and well-being. Indications are that at any given time, water resources are under stress in selected parts of the country. The large-scale development of groundwater resources has caused declines in the amount of groundwater in storage and declines in discharges to surface water bodies (Reilly and others, 2008). Water supply in some regions, particularly in arid and semiarid regions, is not adequate to meet demand, and severe drought intensifies the stresses affecting water resources (National Drought Mitigation Center, the U.S. Department of Agriculture, and the National Oceanic and Atmospheric Association, 2015). If these drought conditions continue, water shortages could adversely affect the human condition and threaten environmental flows necessary to maintain ecosystem health.
In support of the national census of water resources, the U.S. Geological Survey (USGS) completed the national brackish groundwater assessment to provide updated information about brackish groundwater as a potential resource to augment or replace freshwater supplies (Stanton and others, 2017). Study objectives were to consolidate available data into a comprehensive database of brackish groundwater resources in the United States and to produce a summary report highlighting the distribution, physical and chemical characteristics, and use of brackish groundwater resources. This assessment was authorized by section 9507 of the Omnibus Public Land Management Act of 2009 (42 U.S.C. 10367), passed by Congress in March 2009. Before this assessment, the last national brackish groundwater compilation was completed in the mid-1960s (Feth, 1965). Since that time, substantially more hydrologic and geochemical data have been collected and now can be used to improve the understanding of the Nation’s brackish groundwater resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173054","usgsCitation":"Stanton, J.S., and Dennehy, K.F., 2017, Brackish groundwater and its potential to augment freshwater supplies: U.S. Geological Survey Fact Sheet 2017–3054, 4 p., https://doi.org/10.3133/fs20173054.","productDescription":"Document: 4 p.; Companion File; Data Release","onlineOnly":"N","ipdsId":"IP-078564","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":343973,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3054/coverthb.jpg"},{"id":343974,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3054/fs20173054.pdf","text":"Fact Sheet","size":"2.38 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017–3054"},{"id":343975,"rank":3,"type":{"id":7,"text":"Companion 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U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Oil shales are fine-grained sedimentary rocks formed in many different depositional environments (terrestrial, lacustrine, marine) containing large quantities of thermally immature organic matter in the forms of kerogen and bitumen. If defined from an economic standpoint, a rock containing a sufficient concentration of oil-prone kerogen to generate economic quantities of synthetic crude oil upon heating to high temperatures (350–600 °C) in the absence of oxygen (pyrolysis) can be considered an oil shale.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of Geochemistry","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer International Publishing","doi":"10.1007/978-3-319-39193-9_181-1","isbn":"978-3-319-39193-9","usgsCitation":"Birdwell, J.E., 2017, Oil Shale, chap. of Encyclopedia of Geochemistry, 3 p., https://doi.org/10.1007/978-3-319-39193-9_181-1.","productDescription":"3 p.","ipdsId":"IP-085028","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":343971,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-14","publicationStatus":"PW","scienceBaseUri":"596f1e1fe4b0d1f9f0640740","contributors":{"authors":[{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":705264,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70189379,"text":"ofr20171091 - 2017 - Case studies of riparian and watershed restoration in the southwestern United States—Principles, challenges, and successes","interactions":[],"lastModifiedDate":"2017-07-19T08:53:12","indexId":"ofr20171091","displayToPublicDate":"2017-07-18T00:00:00","publicationYear":"2017","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":"2017-1091","title":"Case studies of riparian and watershed restoration in the southwestern United States—Principles, challenges, and successes","docAbstract":"Globally, rivers and streams are highly altered by impoundments, diversions, and stream channelization associated with agricultural and water delivery needs. Climate change imposes additional challenges by further reducing discharge, introducing variability in seasonal precipitation patterns, and increasing temperatures. Collectively, these changes in a river or stream’s annual hydrology affects surface and groundwater dynamics, fluvial processes, and the linked aquatic and riparian responses, particularly in arid regions. Recognizing the inherent ecosystem services that riparian and aquatic habitats provide, society increasingly supports restoring the functionality of riparian and aquatic ecosystems.
Given the wide range in types and scales of riparian impacts, approaches to riparian restoration can range from tactical, short-term, and site-specific efforts to strategic projects and long-term collaborations best pursued at the watershed scale. In the spirit of sharing information, the U.S. Geological Survey’s Grand Canyon Monitoring and Research Center convened a workshop June 23-25, 2015, in Flagstaff, Ariz. for practitioners in restoration science to share general principles, successful restoration practices, and discuss the challenges that face those practicing riparian restoration in the southwestern United States. Presenters from the Colorado River and the Rio Grande basins, offered their perspectives and experiences in restoration at the local, reach and watershed scale. Outcomes of the workshop include this Proceedings volume, which is composed of extended abstracts of most of the presentations given at the workshop, and recommendations or information needs identified by participants. The organization of the Proceedings follows a general progression from local scale restoration to river and watershed scale approaches, and finishes with restoration assessments and monitoring.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171091","usgsCitation":"Ralston, B.E., and Sarr, D.A., 2017, Case studies of riparian and watershed restoration in the southwestern United States—Principles, challenges, and successes: U.S. Geological Survey Open-File Report 2017-1091, 116 p., https://doi.org/10.3133/ofr20171091.","productDescription":"ix, 116 p.","onlineOnly":"Y","ipdsId":"IP-087333","costCenters":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"links":[{"id":343991,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1091/ofr20171091.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1091"},{"id":343990,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1091/coverthb.jpg"}],"country":"United States","contact":"Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
Ground-based gravitational wave interferometers such as the Laser Interferometer Gravitational-wave Observatory (LIGO) are susceptible to ground shaking from high-magnitude teleseismic events, which can interrupt their operation in science mode and significantly reduce their duty cycle. It can take several hours for a detector to stabilize enough to return to its nominal state for scientific observations. The down time can be reduced if advance warning of impending shaking is received and the impact is suppressed in the isolation system with the goal of maintaining stable operation even at the expense of increased instrumental noise. Here, we describe an early warning system for modern gravitational-wave observatories. The system relies on near real-time earthquake alerts provided by the U.S. Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA). Preliminary low latency hypocenter and magnitude information is generally available in 5 to 20 min of a significant earthquake depending on its magnitude and location. The alerts are used to estimate arrival times and ground velocities at the gravitational-wave detectors. In general, 90% of the predictions for ground-motion amplitude are within a factor of 5 of measured values. The error in both arrival time and ground-motion prediction introduced by using preliminary, rather than final, hypocenter and magnitude information is minimal. By using a machine learning algorithm, we develop a prediction model that calculates the probability that a given earthquake will prevent a detector from taking data. Our initial results indicate that by using detector control configuration changes, we could prevent interruption of operation from 40 to 100 earthquake events in a 6-month time-period.
","language":"English","publisher":"Institute of Physics","doi":"10.1088/1361-6382/aa5a60","usgsCitation":"Coughlin, M., Earle, P.S., Harms, J., Biscans, S., Buchanan, C., Coughlin, E., Donovan, F., Fee, J., Gabbard, H., Guy, M.M., Mukund, N., and Perry, M., 2017, Limiting the effects of earthquakes on gravitational-wave interferometers: Classical and Quantum Gravity, v. 34, no. 4, Article 044004: 14 p., https://doi.org/10.1088/1361-6382/aa5a60.","productDescription":"Article 044004: 14 p.","ipdsId":"IP-083270","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":469676,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://arxiv.org/abs/1611.09812","text":"External Repository"},{"id":343966,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-02","publicationStatus":"PW","scienceBaseUri":"596f1e20e4b0d1f9f0640744","contributors":{"authors":[{"text":"Coughlin, Michael","contributorId":194752,"corporation":false,"usgs":false,"family":"Coughlin","given":"Michael","email":"","affiliations":[],"preferred":false,"id":705250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Earle, Paul S. 0000-0002-3500-017X pearle@usgs.gov","orcid":"https://orcid.org/0000-0002-3500-017X","contributorId":173551,"corporation":false,"usgs":true,"family":"Earle","given":"Paul","email":"pearle@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harms, Jan","contributorId":194753,"corporation":false,"usgs":false,"family":"Harms","given":"Jan","email":"","affiliations":[],"preferred":false,"id":705252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Biscans, Sebastien","contributorId":194754,"corporation":false,"usgs":false,"family":"Biscans","given":"Sebastien","email":"","affiliations":[],"preferred":false,"id":705253,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buchanan, Christopher","contributorId":194755,"corporation":false,"usgs":false,"family":"Buchanan","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":705254,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coughlin, Eric","contributorId":194756,"corporation":false,"usgs":false,"family":"Coughlin","given":"Eric","email":"","affiliations":[],"preferred":false,"id":705255,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Donovan, Fred","contributorId":194757,"corporation":false,"usgs":false,"family":"Donovan","given":"Fred","email":"","affiliations":[],"preferred":false,"id":705256,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fee, Jeremy 0000-0002-6851-2796 jmfee@usgs.gov","orcid":"https://orcid.org/0000-0002-6851-2796","contributorId":194758,"corporation":false,"usgs":true,"family":"Fee","given":"Jeremy","email":"jmfee@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705257,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gabbard, Hunter","contributorId":194759,"corporation":false,"usgs":false,"family":"Gabbard","given":"Hunter","email":"","affiliations":[],"preferred":false,"id":705258,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Guy, Michelle M. 0000-0003-3450-4656 mguy@usgs.gov","orcid":"https://orcid.org/0000-0003-3450-4656","contributorId":173432,"corporation":false,"usgs":true,"family":"Guy","given":"Michelle","email":"mguy@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705259,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mukund, Nikhil","contributorId":194760,"corporation":false,"usgs":false,"family":"Mukund","given":"Nikhil","email":"","affiliations":[],"preferred":false,"id":705260,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Perry, Matthew","contributorId":194761,"corporation":false,"usgs":false,"family":"Perry","given":"Matthew","affiliations":[],"preferred":false,"id":705261,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70188612,"text":"ofr20171074 - 2017 - Lithofacies and sequence stratigraphic description of the upper part of the Avon Park Formation and the Arcadia Formation in U.S. Geological Survey G–2984 test corehole, Broward County, Florida","interactions":[],"lastModifiedDate":"2017-10-17T10:03:46","indexId":"ofr20171074","displayToPublicDate":"2017-07-18T00:00:00","publicationYear":"2017","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":"2017-1074","title":"Lithofacies and sequence stratigraphic description of the upper part of the Avon Park Formation and the Arcadia Formation in U.S. Geological Survey G–2984 test corehole, Broward County, Florida","docAbstract":"Rock core and sediment from U.S. Geological Survey test corehole G–2984 completed in 2011 in Broward County, Florida, provide an opportunity to improve the understanding of the lithostratigraphic, sequence stratigraphic, and hydrogeologic framework of the intermediate confining unit and Floridan aquifer system in southeastern Florida. A multidisciplinary approach including characterization of sequence stratigraphy, lithofacies, ichnology, foraminiferal paleontology, depositional environments, porosity, and permeability was used to describe the geologic samples from this test corehole. This information has produced a detailed characterization of the lithofacies and sequence stratigraphy of the upper part of the middle Eocene Avon Park Formation and Oligocene to middle Miocene Arcadia Formation. This enhancement of the knowledge of the sequence stratigraphic framework is especially important, because subaerial karst unconformities at the upper boundary of depositional cycles at various hierarchical scales are commonly associated with secondary porosity and enhanced permeability in the Floridan aquifer system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171074","collaboration":"Prepared in cooperation with Broward County, Florida","usgsCitation":"Cunningham, K.J., and Robinson, Edward, 2017, Lithofacies and sequence stratigraphic description of the upper part of the Avon Park Formation and the Arcadia Formation in U.S. Geological Survey G–2984 test corehole, Broward County, Florida: U.S. Geological Survey Open File-Report 2017–1074, 139 p., https://doi.org/10.3133/ofr20171074.","productDescription":"v, 139 p.","onlineOnly":"Y","ipdsId":"IP-083814","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":343757,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1074/coverthb2.jpg"},{"id":343758,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1074/ofr20171074.pdf","text":"Report","size":"23.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1074"}],"country":"United States","state":"Florida","county":"Broward County","otherGeospatial":"Test corehole G-2984","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.15,\n 26.35\n ],\n [\n -80.1,\n 26.35\n ],\n [\n -80.1,\n 26.3\n ],\n [\n -80.15,\n 26.3\n ],\n [\n -80.15,\n 26.35\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Climate change, tectonics, and humans create long- and short-term temporal variations in the supply of suspended sediment to rivers. These signals, generated in upland erosional areas, are filtered by alluvial storage before reaching the basin outlet. We quantified this filter using a random walk model driven by sediment budget data, a power-law distributed probability density function (PDF) to determine how long sediment remains stored, and a constant downstream drift velocity during transport of 157 km/yr. For 25 km of transport, few particles are stored, and the median travel time is 0.2 yr. For 1000 km of transport, nearly all particles are stored, and the median travel time is 2.5 m.y. Both travel-time distributions are power laws. The 1000 km travel-time distribution was then used to filter sinusoidal input signals with periods of 10 yr and 104 yr. The 10 yr signal is delayed by 12.5 times its input period, damped by a factor of 380, and is output as a power law. The 104 yr signal is delayed by 0.15 times its input period, damped by a factor of 3, and the output signal retains its sinusoidal input form (but with a power-law “tail”). Delivery time scales for these two signals are controlled by storage; in-channel transport time is insignificant, and low-frequency signals are transmitted with greater fidelity than high-frequency signals. These signal modifications are essential to consider when evaluating watershed restoration schemes designed to control sediment loading, and where source-area geomorphic processes are inferred from the geologic record.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G38170.1","usgsCitation":"Pizzuto, J.E., Keeler, J., Skalak, K., and Karwan, D., 2017, Storage filters upland suspended sediment signals delivered from watersheds: Geology, v. 45, no. 2, p. 151-154, https://doi.org/10.1130/G38170.1.","productDescription":"4 p.","startPage":"151","endPage":"154","ipdsId":"IP-081208","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":343977,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-01","publicationStatus":"PW","scienceBaseUri":"596f1e1ee4b0d1f9f0640734","contributors":{"authors":[{"text":"Pizzuto, James E.","contributorId":49424,"corporation":false,"usgs":false,"family":"Pizzuto","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":13220,"text":"The Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":705310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keeler, Jeremy","contributorId":194778,"corporation":false,"usgs":false,"family":"Keeler","given":"Jeremy","email":"","affiliations":[],"preferred":false,"id":705311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skalak, Katherine 0000-0003-4122-1240 kskalak@usgs.gov","orcid":"https://orcid.org/0000-0003-4122-1240","contributorId":3990,"corporation":false,"usgs":true,"family":"Skalak","given":"Katherine","email":"kskalak@usgs.gov","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":705309,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Karwan, Diana","contributorId":194779,"corporation":false,"usgs":false,"family":"Karwan","given":"Diana","affiliations":[],"preferred":false,"id":705312,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187723,"text":"fs20173039 - 2017 - Assessment of continuous oil and gas resources in the Perth Basin Province, Australia, 2017","interactions":[],"lastModifiedDate":"2019-12-23T09:37:30","indexId":"fs20173039","displayToPublicDate":"2017-07-17T15:25:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-3039","title":"Assessment of continuous oil and gas resources in the Perth Basin Province, Australia, 2017","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey assessed undiscovered, technically recoverable mean resources of 223 million barrels of oil and 14.5 trillion cubic feet of gas in the Perth Basin Province, Australia.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173039","usgsCitation":"Schenk, C.J., Tennyson, M.E., Finn, T.M., Mercier, T.J., Hawkins, S.J., Gaswirth, S.B., Marra, K.R., Klett, T.R., Le, P.A., Leathers-Miller, H.M., and Woodall, C.A., 2017, Assessment of continuous oil and gas resources in the Perth Basin Province, Australia, 2017: U.S. Geological Survey Fact Sheet 2017–3039, 2 p., https://doi.org/10.3133/fs20173039.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-084736","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":343834,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3039/fs20173039.pdf ","text":"Report","size":"344 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3039"},{"id":343833,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3039/coverthb.jpg"}],"country":"Australia","otherGeospatial":"Perth Basin Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 114.08203125,\n -35.42486791930557\n ],\n [\n 119.2236328125,\n -35.42486791930557\n ],\n [\n 119.2236328125,\n -27.955591004642528\n ],\n [\n 114.08203125,\n -27.955591004642528\n ],\n [\n 114.08203125,\n -35.42486791930557\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
In order to determine the hydrocarbon potential of oil reservoirs within the U.S. sedimentary basins for which the carbon dioxide enhanced oil recovery (CO2-EOR) process has been considered suitable, the CO2 Prophet model was chosen by the U.S. Geological Survey (USGS) to be the primary source for estimating recovery-factor values for individual reservoirs. The choice was made because of the model’s reliability and the ease with which it can be used to assess a large number of reservoirs. The other two approaches—the empirical decline curve analysis (DCA) method and a review of published literature on CO2-EOR projects—were deployed to verify the results of the CO2 Prophet model. This chapter discusses the results from CO2 Prophet (chapter B, by Emil D. Attanasi, this report) and compares them with results from decline curve analysis (chapter C, by Hossein Jahediesfanjani) and those reported in the literature for selected reservoirs with adequate data for analyses (chapter D, by Ricardo A. Olea).
To estimate the technically recoverable hydrocarbon potential for oil reservoirs where CO2-EOR has been applied, two of the three approaches—CO2 Prophet modeling and DCA—do not include analysis of economic factors, while the third approach—review of published literature—implicitly includes economics. For selected reservoirs, DCA has provided estimates of the technically recoverable hydrocarbon volumes, which, in combination with calculated amounts of original oil in place (OOIP), helped establish incremental CO2-EOR recovery factors for individual reservoirs.
The review of published technical papers and reports has provided substantial information on recovery factors for 70 CO2-EOR projects that are either commercially profitable or classified as pilot tests. When comparing the results, it is important to bear in mind the differences and limitations of these three approaches.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Three approaches for estimating recovery factors in carbon dioxide enhanced oil recovery (Scientific Investigations Report 2017–5062)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175062E","usgsCitation":"Verma, M.K., 2017, Summary of the analyses for recovery factors, chap. E of Verma, M.K., ed., Three approaches for estimating recovery factors in carbon dioxide enhanced oil recovery: U.S. Geological Survey Scientific Investigations Report 2017–5062, p. E1–E2, https://doi.org/10.3133/sir20175062E.","productDescription":"iii, 2 p.","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":343123,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5062/e/coverthb.jpg"},{"id":343124,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5062/e/sir20175062_chape.pdf","text":"Report","size":"198 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5062E"}],"contact":" Eastern Energy Resources Science Center
U.S. Geological Survey
Mail Stop 956 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The Oil and Gas Journal’s enhanced oil recovery (EOR) survey for 2014 (Koottungal, 2014) showed that gas injection is the most frequently applied method of EOR in the United States and that carbon dioxide (CO2 ) is the most commonly used injection fluid for miscible operations. The CO2-EOR process typically follows primary and secondary (waterflood) phases of oil reservoir development. The common objective of implementing a CO2-EOR program is to produce oil that remains after the economic limit of waterflood recovery is reached. Under conditions of miscibility or multicontact miscibility, the injected CO2 partitions between the gas and liquid CO2 phases, swells the oil, and reduces the viscosity of the residual oil so that the lighter fractions of the oil vaporize and mix with the CO2 gas phase (Teletzke and others, 2005). Miscibility occurs when the reservoir pressure is at least at the minimum miscibility pressure (MMP). The MMP depends, in turn, on oil composition, impurities of the CO2 injection stream, and reservoir temperature. At pressures below the MMP, component partitioning, oil swelling, and viscosity reduction occur, but the efficiency is increasingly reduced as the pressure falls farther below the MMP.
CO2-EOR processes are applied at the reservoir level, where a reservoir is defined as an underground formation containing an individual and separate pool of producible hydrocarbons that is confined by impermeable rock or water barriers and is characterized by a single natural pressure system. A field may consist of a single reservoir or multiple reservoirs that are not in communication but which may be associated with or related to a single structural or stratigraphic feature (U.S. Energy Information Administration [EIA], 2000).
The purpose of modeling the CO2-EOR process is discussed along with the potential CO2-EOR predictive models. The data demands of models and the scope of the assessments require tradeoffs between reservoir-specific data that can be assembled and simplifying assumptions that allow assignment of default values for some reservoir parameters. These issues are discussed in the context of the CO2 Prophet EOR model, and their resolution is demonstrated with the computation of recovery-factor estimates for CO2-EOR of 143 reservoirs in the Powder River Basin Province in southeastern Montana and northeastern Wyoming.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Three approaches for estimating recovery factors in carbon dioxide enhanced oil recovery (Scientific Investigations Report 2017–5062)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175062B","usgsCitation":"Attanasi, E.D., 2017, Using CO2 Prophet to estimate recovery factors for carbon dioxide enhanced oil recovery, chap. B of Verma, M.K., ed., Three approaches for estimating recovery factors in carbon dioxide enhanced oil recovery: U.S. Geological Survey Scientific Investigations Report 2017–5062, p. B1–B10, https://doi.org/10.3133/sir20175062B.","productDescription":"iii, 10 p.","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":343112,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5062/b/sir20175062_chapb.pdf","text":"Report","size":"377 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5062B"},{"id":343111,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5062/b/coverthb.jpg"}],"contact":" Eastern Energy Resources Science Center
U.S. Geological Survey
Mail Stop 956 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
In the decline curve analysis (DCA) method of estimating recoverable hydrocarbon volumes, the analyst uses historical production data from a well, lease, group of wells (or pattern), or reservoir and plots production rates against time or cumulative production for the analysis. The DCA of an individual well is founded on the same basis as the fluid-flow principles that are used for pressure-transient analysis of a single well in a reservoir domain and therefore can provide scientifically reasonable and accurate results. However, when used for a group of wells, a lease, or a reservoir, the DCA becomes more of an empirical method. Plots from the DCA reflect the reservoir response to the oil withdrawal (or production) under the prevailing operating and reservoir conditions, and they continue to be good tools for estimating recoverable hydrocarbon volumes and future production rates. For predicting the total recoverable hydrocarbon volume, the DCA results can help the analyst to evaluate the reservoir performance under any of the three phases of reservoir productive life—primary, secondary (waterflood), or tertiary (enhanced oil recovery) phases—so long as the historical production data are sufficient to establish decline trends at the end of the three phases.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Three approaches for estimating recovery factors in carbon dioxide enhanced oil recovery (Scientific Investigations Report 2017–5062)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175062C","usgsCitation":"Jahediesfanjani, Hossein, 2017, Application of decline curve analysis to estimate recovery factors for carbon dioxide enhanced oil recovery, chap. C of Verma, M.K., ed., Three approaches for estimating recovery factors in carbon dioxide enhanced oil recovery: U.S. Geological Survey Scientific Investigations Report 2017–5062, \np. C1–C20, https://doi.org/10.3133/sir20175062C.","productDescription":"iv, 20 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":343119,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5062/c/sir20175062_chapc.pdf","text":"Report","size":"1.10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017=5062C"},{"id":343118,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5062/c/coverthb.jpg"}],"contact":" Eastern Energy Resources Science Center
U.S. Geological Survey
Mail Stop 956 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The U.S. Geological Survey (USGS) compared methods for estimating an incremental recovery factor (RF) for the carbon dioxide enhanced oil recovery (CO2-EOR) process involving the injection of CO2 into oil reservoirs. This chapter first provides some basic information on the RF, including its dependence on various reservoir and operational parameters, and then discusses the three development phases of oil recovery—primary, secondary, and tertiary (EOR). It ends with a brief discussion of the three approaches for estimating recovery factors, which are detailed in subsequent chapters.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Three approaches for estimating recovery factors in carbon dioxide enhanced oil recovery (Scientific Investigations Report 2017–5062)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175062A","usgsCitation":"Verma, M.K., 2017, General introduction and recovery factors, chap. A of Verma, M.K., ed., Three approaches for estimating recovery factors in carbon dioxide enhanced oil recovery: U.S. Geological Survey Scientific Investigations Report 2017–5062, p. A1–A3, https://doi.org/10.3133/sir20175062A.","productDescription":"iii, 3 p.","numberOfPages":"7","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":343114,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5062/a/sir20175062_chapa.pdf","text":"Report","size":"239 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5062A"},{"id":343113,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5062/a/coverthb.jpg"}],"contact":" Eastern Energy Resources Science Center
U.S. Geological Survey
Mail Stop 956 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The need to increase the efficiency of oil recovery and environmental concerns are bringing to prominence the use of carbon dioxide (CO2) as a tertiary recovery agent. Assessment of the impact of flooding with CO2 all eligible reservoirs in the United States not yet undergoing enhanced oil recovery (EOR) requires making the best possible use of the experience gained in 40 years of applications. Review of the publicly available literature has located relevant CO2-EOR information for 53 units (fields, reservoirs, pilot areas) in the United States and 17 abroad.
As the world simultaneously faces an increasing concentration of CO2 in the atmosphere and a higher demand for fossil fuels, the CO2-EOR process continues to gain popularity for its efficiency as a tertiary recovery agent and for the potential for having some CO2 trapped in the subsurface as an unintended consequence of the enhanced production (Advanced Resources International and Melzer Consulting, 2009). More extensive application of CO2-EOR worldwide, however, is not making it significantly easier to predict the exact outcome of the CO2 flooding in new reservoirs. The standard approach to examine and manage risks is to analyze the intended target by conducting laboratory work, running simulation models, and, finally, gaining field experience with a pilot test. This approach, though, is not always possible. For example, assessment of the potential of CO2-EOR at the national level in a vast country such as the United States requires making forecasts based on information already available.
Although many studies are proprietary, the published literature has provided reviews of CO2-EOR projects. Yet, there is always interest in updating reports and analyzing the information under new perspectives. Brock and Bryan (1989) described results obtained during the earlier days of CO2-EOR from 1972 to 1987. Most of the recovery predictions, however, were based on intended injections of 30 percent the size of the reservoir’s hydrocarbon pore volume (HCPV), and the predictions in most cases badly missed the actual recoveries because of the embryonic state of tertiary recovery in general and CO2 flooding in particular at the time. Brock and Bryan (1989), for example, reported for the Weber Sandstone in the Rangely oil field in Colorado, an expected recovery of 7.5 percent of the original oil in place (OOIP) after injecting a volume of CO2 equivalent to 30 percent of the HCPV, but Clark (2012) reported that after injecting a volume of CO2 equivalent to 46 percent of the HCPV, the actual recovery was 4.8 percent of the OOIP. Decades later, the numbers by Brock and Bryan (1989) continue to be cited as part of expanded reviews, such as the one by Kuuskraa and Koperna (2006). Other comprehensive reviews including recovery factors are those of Christensen and others (2001) and Lake and Walsh (2008). The Oil and Gas Journal (O&GJ) periodically reports on active CO2-EOR operations worldwide, but those releases do not include recovery factors. The monograph by Jarrell and others (2002) remains the most technically comprehensive publication on CO2 flooding, but it does not cover recovery factors either.
This chapter is a review of the literature found in a search for information about CO2-EOR. It has been prepared as part of a project by the U.S. Geological Survey (USGS) to assess the incremental oil production that would be technically feasible by CO2 flooding of all suitable oil reservoirs in the country not yet undergoing tertiary recovery.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Three approaches for estimating recovery factors in carbon dioxide enhanced oil recovery (Scientific Investigations Report 2017–5062)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, Virginia","doi":"10.3133/sir20175062D","usgsCitation":"Olea, R.A., 2017, Carbon dioxide enhanced oil recovery performance according to the literature, chap. D of Verma, M.K., ed., Three approaches for estimating recovery factors in carbon dioxide enhanced oil recovery: U.S. Geological Survey Scientific Investigations Report 2017–5062, p. D1–D21, https://doi.org/10.3133/sir20175062D.","productDescription":"iii, 21 p.","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":343121,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5062/d/coverthb.jpg"},{"id":343122,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5062/d/sir20175062_chapd.pdf","text":"Report","size":"570 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5062D"}],"contact":" Eastern Energy Resources Science Center
U.S. Geological Survey
Mail Stop 956 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The Energy Independence and Security Act of 2007 authorized the U.S. Geological Survey (USGS) to conduct a national assessment of geologic storage resources for carbon dioxide (CO2) and requested the USGS to estimate the “potential volumes of oil and gas recoverable by injection and sequestration of industrial carbon dioxide in potential sequestration formations” (42 U.S.C. 17271(b)(4)). Geologic CO2 sequestration associated with enhanced oil recovery (EOR) using CO2 in existing hydrocarbon reservoirs has the potential to increase the U.S. hydrocarbon recoverable resource. The objective of this report is to provide detailed information on three approaches that can be used to calculate the incremental recovery factors for CO2-EOR. Therefore, the contents of this report could form an integral part of an assessment methodology that can be used to assess the sedimentary basins of the United States for the hydrocarbon recovery potential using CO2-EOR methods in conventional oil reservoirs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175062","usgsCitation":"Verma, M.K., ed., 2017, Three approaches for estimating recovery factors in carbon dioxide enhanced oil recovery: U.S. Geological Survey Scientific Investigations Report 2017–5062–A–E, variously paged, https://doi.org/10.3133/sir20175062.","productDescription":"88 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068432","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":342892,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5062/sir20175062.pdf","text":"Report","size":"1.77 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5062"},{"id":342891,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5062/coverthb.jpg"}],"contact":" Eastern Energy Resources Science Center
U.S. Geological Survey
Mail Stop 956 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The U.S. Geological Survey has developed a new global high-resolution hydrologic derivative database. Loosely modeled on the HYDRO1k database, this new database, entitled Hydrologic Derivatives for Modeling and Analysis, provides comprehensive and consistent global coverage of topographically derived raster layers (digital elevation model data, flow direction, flow accumulation, slope, and compound topographic index) and vector layers (streams and catchment boundaries). The coverage of the data is global, and the underlying digital elevation model is a hybrid of three datasets: HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales), GMTED2010 (Global Multi-resolution Terrain Elevation Data 2010), and the SRTM (Shuttle Radar Topography Mission). For most of the globe south of 60°N., the raster resolution of the data is 3 arc-seconds, corresponding to the resolution of the SRTM. For the areas north of 60°N., the resolution is 7.5 arc-seconds (the highest resolution of the GMTED2010 dataset) except for Greenland, where the resolution is 30 arc-seconds. The streams and catchments are attributed with Pfafstetter codes, based on a hierarchical numbering system, that carry important topological information. This database is appropriate for use in continental-scale modeling efforts. The work described in this report was conducted by the U.S. Geological Survey in cooperation with the National Aeronautics and Space Administration Goddard Space Flight Center.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1053","collaboration":"Prepared in cooperation with the National Aeronautics and Space Administration Goddard Space Flight Center","usgsCitation":"Verdin, K.L., 2017, Hydrologic Derivatives for Modeling and Analysis—A new global high-resolution database: U.S. Geological Survey Data Series 1053, 16 p., https://doi.org/10.3133/ds1053.","productDescription":"Report: iv, 16 p.; Data Release","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-079740","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":343796,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1053/ds1053.pdf","text":"Report","size":"7.92 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1053"},{"id":343795,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1053/coverthb.jpg"},{"id":343823,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7S180ZP","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Hydrologic Derivatives for Modeling and Applications (HDMA) database"}],"contact":"Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225-0046