Annual reservoir drawdowns at Fall Creek Lake, Oregon, have occurred for eight consecutive years from December 2012 to November 2019. The annual drawdowns are the result of the 2008 Biological Opinion of the US Army Corps of Engineers (USACE) Willamette Valley Project operations, which directed the USACE to carry out interim operational measures that would provide volitional downstream passage for endangered species act (ESA)-listed Chinook salmon. At Fall Creek Lake, the USACE modifies its operations by lowering the reservoir elevation to 690-ft, approximately 40 feet below the normal winter low-pool elevation. This action results in a runof-river scenario through the dam allowing juvenile Chinook salmon to safely pass through the regulating outlets. Monitoring of juvenile Chinook salmon in screw traps at the outlet of the dam has shown variable timing in out-migration associated with reservoir elevation, and that most of the juvenile fish exited the reservoir when the pool elevation passed 700-ft (Taylor and others, 2015). The annual drawdown has therefore been effective in providing safe downstream fish passage and has also had the collateral effect of transporting large quantities of suspended sediment to the downstream reaches of Fall Creek and the Middle Fork Willamette River. The US Geological Survey (USGS) has calculated time-series of suspended sediment concentrations (SSC) and suspended sediment loads (SSL) before, during, and after the drawdowns for six of the last nine drawdown years (water years [WY] 2013-2018), which have lasted between 5-14 days. The transport and deposition of sediment from the drawdowns has affected side-channel habitat below the dam by depositing large quantities of sand-size material resulting in streambed aggradation in several locations. The results from the USGS monitoring effort have provided important information to USACE on how the modification of their operations has affected sediment transport in the river reaches below the dam.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceeding 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 and Hydrologic Modeling Conference","usgsCitation":"Schenk, L.N., and Bragg, H.M., 2019, Monitoring the effect of deep drawdowns of a flood control reservoir on sediment transport and dissolved oxygen, Fall Creek Lake, Oregon, in Proceeding of SEDHYD 2019, v. 5, Reno, NV, June 24-28, 2019, 8 p.","productDescription":"8 p.","ipdsId":"IP-105587","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":382592,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2019/openconf/modules/request.php?module=oc_program&action=program.php&p=program"},{"id":382593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"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 -123.13339233398438,\n 43.74431283565998\n ],\n [\n -122.45498657226561,\n 43.74431283565998\n ],\n [\n -122.45498657226561,\n 44.104351509943406\n ],\n [\n -123.13339233398438,\n 44.104351509943406\n ],\n [\n -123.13339233398438,\n 43.74431283565998\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schenk, Liam N. 0000-0002-2491-0813 lschenk@usgs.gov","orcid":"https://orcid.org/0000-0002-2491-0813","contributorId":4273,"corporation":false,"usgs":true,"family":"Schenk","given":"Liam","email":"lschenk@usgs.gov","middleInitial":"N.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bragg, Heather M. 0000-0002-0013-4573 hmbragg@usgs.gov","orcid":"https://orcid.org/0000-0002-0013-4573","contributorId":239645,"corporation":false,"usgs":true,"family":"Bragg","given":"Heather","email":"hmbragg@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797467,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218758,"text":"70218758 - 2019 - Conservation status of the world’s swan populations, Cygnus sp. and Coscoroba sp.: a review of current trends and gaps in knowledge","interactions":[],"lastModifiedDate":"2021-03-12T14:41:49.419103","indexId":"70218758","displayToPublicDate":"2019-12-31T08:39:56","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3764,"text":"Wildfowl","onlineIssn":"2052-6458","printIssn":"0954-6324","active":true,"publicationSubtype":{"id":10}},"title":"Conservation status of the world’s swan populations, Cygnus sp. and Coscoroba sp.: a review of current trends and gaps in knowledge","docAbstract":"Recent estimates of the world’s swan Cygnus sp. populations indicate that there are currently between 1.5–1.6 million birds in 8 species, including the Coscoroba Swan Coscoroba coscoroba as an honorary swan. Monitoring programmes in Europe and North America indicate that most populations increased following the introduction of national and international legislation to protect the species during the early- to mid-20th century. A switch from feeding primarily on aquatic vegetation to foraging on farmland (especially high-energy arable crops) in winter during the second half of the 20th century, is also considered a contributing factor. Trumpeter Swans Cygnus buccinator famously increased from just 69 individuals known to exist in 1935 (although small numbers were missed) to c. 76,000 at the present time, and most of the northern hemisphere swan populations have continued to show increasing/stable trends over the last 20 years. The exception to this pattern is a decline since 1995 in the Northwest European Bewick’s Swan population, following an increase in its population size during the 1970s–1980s, which is now being addressed through implementation of an International Single Species Action Plan. A proposal to change enforcement regulations of the Migratory Bird Treaty Act in the United States is also of concern, as potentially undermining protection for Trumpeter Swans in North America, illustrating the importance of politics and legislation as well as on-the-ground measures for species conservation. Elsewhere, less is known about the trends and conservation status for swans in central and eastern Asia, though count and research programmes introduced in China, added to those underway in Japan and Korea, have recently greatly enhanced our knowledge of swan populations on the East Asian flyway. Trends for the Black Swan Cygnus atratus in Australia and for the Black-necked Swan Cygnus melancoryphus in South America are also poorly known, because of the large numbers involved for the former and a lack of coordinated counts across difficult terrain for the latter. These southern hemisphere species are considered vulnerable to water resource developments (i.e. where diversion of water is shrinking wetlands), and to droughts associated with El Nino events and climate change. More extensive monitoring is therefore required to determine whether swan populations and species are stable, fluctuating or in decline.
The Spatially Explicit Asian carp Population (SEAcarP) model was developed to inform management and research decisions with the goal of minimizing the abundance of Bighead Carp and Silver Carp (collectively referred to as “Asian carp” in this document) in the upper Illinois River waterway, thereby reducing risk of population expansion toward the Great Lakes and reducing potential impacts on native species. This model provides an objective, data-driven approach to maximize return on investment of management actions and facilitates defining research and monitoring priorities.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2019 Asian carp interim summary report","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Asian Carp Regional Coordinating Committee","usgsCitation":"Erickson, R.A., 2019, Asian carp population modeling to support an Adaptive Management framework, USGS Contribution, chap. of 2019 Asian carp interim summary report, p. 175-176.","productDescription":"2 p.","startPage":"175","endPage":"176","ipdsId":"IP-120441","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":391318,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":391078,"type":{"id":11,"text":"Document"},"url":"https://invasivecarp.us/Documents/Interim-Summary-Report-2019.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":826005,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70223489,"text":"70223489 - 2019 - Diel feeding and movement activity of Northern Snakehead Channa argus","interactions":[],"lastModifiedDate":"2021-08-30T13:31:06.021598","indexId":"70223489","displayToPublicDate":"2019-12-31T08:30:48","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Diel feeding and movement activity of Northern Snakehead Channa argus","docAbstract":"Understanding the diel activity of a species can shed light on potential interactions with other species and inform management practices. To understand the diel activity of Northern Snakehead Channa argus, feeding habits and movement patterns were observed. Two hundred seventy-three Northern Snakehead were captured by boat electrofishing during May and June of 2007 and 2008. Their gut contents were extracted and preserved. The level of digestion of each prey item was estimated from fresh (1) to >50% digested (4) or empty (5). Random forest models were used to predict feeding activity based on time of day, tide level, date, water temperature, fish total length, and sex. Diel movement patterns were assessed by implanting Northern Snakehead with radio transmitters and monitoring them every 1.5 h for 24 h in both March and July 2007. Movement rates were compared between March and July and among four daily time periods. Independent variables accounted for only 6% of the variation in feeding activity; however, temporal feeding patterns were apparent. No fresh items were observed in guts between 12:30 and 7:30 am, and the proportion of empty stomachs increased at the end of May coinciding with the onset of spawning. Overall, fish moved greater distances during the July tracking period compared to March. Fish showed a greater propensity to move during daylight hours than at night during the March tracking period. A similar but nonsignificant (P > 0.05) pattern was observed in July. Movement and feeding data both indicated greater activity during daylight hours than at night, suggesting that Northern Snakehead is a diurnal species. Based on our preliminary findings, we hypothesize that a) diurnal species are more susceptible than nocturnal species to predation by Northern Snakehead and b) Northern Snakehead are more likely to compete for food with diurnal than nocturnal predators.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"American Fisheries Society symposium 89","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"The First International Snakehead Symposium","conferenceDate":"Jul 17-19, 2019","conferenceLocation":"Alexandria, VA","language":"English","publisher":"American Fisheries Society","doi":"10.47886/9781934874585.ch6","usgsCitation":"Lapointe, N., Saylor, R., and Angermeier, P.L., 2019, Diel feeding and movement activity of Northern Snakehead Channa argus, in American Fisheries Society symposium 89, Alexandria, VA, Jul 17-19, 2019, 13 p., https://doi.org/10.47886/9781934874585.ch6.","productDescription":"13 p.","ipdsId":"IP-103396","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":388658,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"lower Potomac River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.33551025390624,\n 38.46864331036051\n ],\n [\n -76.87408447265625,\n 38.46864331036051\n ],\n [\n -76.87408447265625,\n 38.9914373369788\n ],\n [\n -77.33551025390624,\n 38.9914373369788\n ],\n [\n -77.33551025390624,\n 38.46864331036051\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lapointe, Nicolas W. R.","contributorId":264893,"corporation":false,"usgs":false,"family":"Lapointe","given":"Nicolas W. R.","affiliations":[{"id":54575,"text":"Canadian Wildlife Federation","active":true,"usgs":false}],"preferred":false,"id":822151,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saylor, Ryan K.","contributorId":264894,"corporation":false,"usgs":false,"family":"Saylor","given":"Ryan K.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":822152,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":822150,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70223690,"text":"70223690 - 2019 - Heavy mineral sands resources in China","interactions":[],"lastModifiedDate":"2021-09-02T13:27:48.977348","indexId":"70223690","displayToPublicDate":"2019-12-31T08:25:07","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Heavy mineral sands resources in China","docAbstract":"About 200 known coastal deposits of heavy mineral sands (HMS) occur in China, in which considerable mineral resources of titanium, zircon, rare earth elements, and thorium exist in the forms of ilmenite, rutile, zircon, and monazite. More than 20 of these HMS deposits are reported as having been or are actively being mined in China during the past three decades, of which 12 have been reported to have industrial resources. Commercially important deposits occur almost entirely in Cenozoic beach and sand dune deposits, principally along China’s eastern coast (e.g., Shandong Province) and southern coast (e.g., Guangxi, Guangdong, Hainan, and Fujian provinces), and particularly on Hainan island. There are also important deposits of HMS along coastal areas of Taiwan. China has the largest share of the world’s economic ilmenite resources in HMS deposits (31%). \n\nA variety of igneous and associated metamorphic rocks along the coastal areas of China provided an abundant source of heavy minerals for the formation of the HMS occurrences. Studies of titanium-rich HMS deposits have shown that ilmenite is mostly sourced from igneous rocks. For example, 40% of the bedrock of Hainan island consists of Triassic and Cretaceous granites emplaced into rocks of the Cathyasia Block, and all of the HMS districts on the island lie no more than 15 km downstream from a Middle Triassic suite of syenite to granite intrusions. The southern coastal regions of Guangdong and Guangxi provinces are dominated by Jurassic granodiorite, biotite granite, two-mica granite, and A-type granite, with minor gabbro and syenite. Identified accessory minerals in the Jurassic alkaline granitoids include zircon, apatite, allanite, titanite, magnetite, ilmenite, monazite, and niobite. Thus, multiple plutons are in proximity to the Cenozoic coastal plain and are available as bedrock sources for the detrital titanium minerals, zircon, and monazite. \n\nMore than 100 HMS deposits and prospects have been identified in Shandong Province, consisting of more than 20 varieties of heavy minerals in quartz sand, which include zircon, ilmenite, rutile, monazite, magnetite, xenotime, and gold (in general order of abundance) derived from Precambrian metamorphic basement and Mesozoic intrusions. Of these minerals, zircon, magnetite, gold, and quartz sand have economic significance. The quartz sands are used by the glass and construction industries. The placers mainly occur in and adjacent to the littoral zones of the northern and southern coasts of the Jiaodong Peninsula in Shandong province. Seven beach placer, HMS prospective areas have been delineated in coastal areas of the peninsula. \n\nDue to nearly exhausted placer reserves in the Chinese coastal zones, as well as increased environmental restrictions, future prospecting for heavy minerals will likely focus on ancient beach systems in China’s inland sedimentary basins. Also, offshore deposits of HMS in shallow coastal waters are other potential sources of heavy minerals, such as the Baoding Sea zircon-titanium, minerals-rich placer under development near Wanning on Hainan. Similarly, there is potential for offshore HMS deposits in shallow waters of the entire coastal area of southern Taiwan that remains to be fully evaluated. Reconnaissance sampling along Taiwan island’s coasts has revealed the potential for extensive, high-grade HMS accumulations nearshore.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Mineral deposits of China","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Society of Economic Geologists","usgsCitation":"Van Gosen, B.S., Hou, B., and Song, T., 2019, Heavy mineral sands resources in China, chap. of Mineral deposits of China, v. 22, p. 581-593.","productDescription":"13 p.","startPage":"581","endPage":"593","ipdsId":"IP-068729","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science 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Gosen, Bradley S. 0000-0003-4214-3811 bvangose@usgs.gov","orcid":"https://orcid.org/0000-0003-4214-3811","contributorId":1174,"corporation":false,"usgs":true,"family":"Van Gosen","given":"Bradley","email":"bvangose@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":822336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hou, Baohong","contributorId":265156,"corporation":false,"usgs":false,"family":"Hou","given":"Baohong","email":"","affiliations":[{"id":54613,"text":"Geological Survey of Australia","active":true,"usgs":false}],"preferred":false,"id":822337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Song, Tianrui","contributorId":265157,"corporation":false,"usgs":false,"family":"Song","given":"Tianrui","email":"","affiliations":[{"id":54614,"text":"China","active":true,"usgs":false}],"preferred":false,"id":822338,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70214977,"text":"70214977 - 2019 - Holocene sedimentary architecture and paleoclimate variability at Mono Lake, California","interactions":[{"subject":{"id":70214977,"text":"70214977 - 2019 - Holocene sedimentary architecture and paleoclimate variability at Mono Lake, California","indexId":"70214977","publicationYear":"2019","noYear":false,"chapter":"19","title":"Holocene sedimentary architecture and paleoclimate variability at Mono Lake, California"},"predicate":"IS_PART_OF","object":{"id":70225733,"text":"70225733 - 2021 - From saline to freshwater: The diversity of western lakes in space and time","indexId":"70225733","publicationYear":"2021","noYear":false,"title":"From saline to freshwater: The diversity of western lakes in space and time"},"id":1}],"isPartOf":{"id":70225733,"text":"70225733 - 2021 - From saline to freshwater: The diversity of western lakes in space and time","indexId":"70225733","publicationYear":"2021","noYear":false,"title":"From saline to freshwater: The diversity of western lakes in space and time"},"lastModifiedDate":"2021-11-08T18:11:30.877032","indexId":"70214977","displayToPublicDate":"2019-12-31T08:11:48","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"19","title":"Holocene sedimentary architecture and paleoclimate variability at Mono Lake, California","docAbstract":"Soil chronosequences on alpine moraine complexes have been used to help unravel the glacial histories of the eastern Sierra Nevada. The moraine sequence along Bishop Creek includes well-preserved moraines that have been previously dated using cosmogenic 36Cl surface exposure ages. The goal of this study was to interpret pedogenesis within a soil geomorphic context on these quantitatively dated moraines. Soil development, surface clast cover, and moraine morphology were studied on seven of the moraines, ranging in age from 15 to 170 ka. Older moraines had gentler slopes, broader crests, and decreased surface rock cover. Soils showed weak development across the chronosequence of moraines. Pedogenesis involved slight increases in clay, the formation of clay lamellae, development of a vesicular horizon in a surface layer of aeolian dust, and weathering of surface and subsurface granitic clasts. Soil reddening and structure development were minimal. Soil formation was likely inhibited by the arid to semi-arid climate and intermittent wind and water erosion during the time span of the chronosequence.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.catena.2019.104222","usgsCitation":"Rossi, A., Graham, R., and Kendrick, K.J., 2019, Pedogenic evolution on the arid Bishop Creek moraines, eastern Sierra Nevada, California: Catena, v. 183, 104222, 14 p., https://doi.org/10.1016/j.catena.2019.104222.","productDescription":"104222, 14 p.","ipdsId":"IP-102151","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":378160,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Eastern Sierra Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.87207031250001,\n 37.69251435532741\n ],\n [\n -118.49304199218749,\n 37.69251435532741\n ],\n [\n -118.49304199218749,\n 37.84015683604136\n ],\n [\n -118.87207031250001,\n 37.84015683604136\n ],\n [\n -118.87207031250001,\n 37.69251435532741\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"183","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rossi, Annie 0000-0001-8955-0065","orcid":"https://orcid.org/0000-0001-8955-0065","contributorId":239863,"corporation":false,"usgs":false,"family":"Rossi","given":"Annie","email":"","affiliations":[{"id":48012,"text":"U.S.D.A. - NRCS","active":true,"usgs":false}],"preferred":false,"id":797908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graham, Robert","contributorId":239864,"corporation":false,"usgs":false,"family":"Graham","given":"Robert","affiliations":[{"id":12655,"text":"University of California, Riverside","active":true,"usgs":false}],"preferred":false,"id":797909,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendrick, Katherine J. 0000-0002-9839-6861","orcid":"https://orcid.org/0000-0002-9839-6861","contributorId":207907,"corporation":false,"usgs":true,"family":"Kendrick","given":"Katherine","email":"","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":797910,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70206051,"text":"sir20195115 - 2019 - A probabilistic assessment methodology for carbon dioxide enhanced oil recovery and associated carbon dioxide retention","interactions":[],"lastModifiedDate":"2022-04-25T18:38:51.233329","indexId":"sir20195115","displayToPublicDate":"2019-12-31T07:20:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5115","displayTitle":"A Probabilistic Assessment Methodology for Carbon Dioxide Enhanced Oil Recovery and Associated Carbon Dioxide Retention","title":"A probabilistic assessment methodology for carbon dioxide enhanced oil recovery and associated carbon dioxide retention","docAbstract":"The U.S. Energy Independence and Security Act of 2007 authorized the U.S. Geological Survey (USGS) to conduct a national assessment of the potential volume of hydrocarbons recoverable by injection of carbon dioxide (CO2) into known oil reservoirs with historical production. The implementation of CO2 enhanced oil recovery (CO2-EOR) techniques could increase the U.S. recoverable hydrocarbon resource base. Use of anthropogenic CO2 in the CO2-EOR process could reduce the amount of CO2 released to the atmosphere by allowing a percentage of the injected CO2 to remain in reservoir pore space once occupied by produced oil and water or by CO2 dissolution in oil and water in the reservoir.
The USGS has developed a new methodology for the national assessment of technically recoverable oil resources that may be produced by using current CO2-EOR technologies. The methodology relies on a proprietary reservoir-level database, the comprehensive resource database (CRD). The CRD incorporates commercially available geologic and engineering data, and USGS-defined play averages or province averages of reservoir data were used to populate incomplete records. Values from the CRD are used to estimate the original oil in place (OOIP) for each reservoir. The inputs are reviewed by USGS geologists, particularly when play or province averages have been used. Monte Carlo simulation is used to produce a numerical probability distribution for the OOIP for each reservoir, with the mean defined as the value of the OOIP in the CRD. A reservoir model (CO2 Prophet, developed for the U.S. Department of Energy by Texaco, Inc.) is used to determine the incremental recovery factors for oil during the CO2-EOR process, on an individual reservoir basis. The model is also used to estimate the volume of CO2 remaining in the reservoir after the CO2-EOR process is complete. Empirical decline curve analysis and comparison with data from published papers and reports on CO2-EOR projects are utilized to substantiate the simulation results. Numerical distributions of recovery factors are prepared for variations in the reservoir lithology (clastic or carbonate). The distribution of incremental oil is computed by multiplying the appropriate probability distribution of recovery factors by the individual reservoir distribution of the OOIP. A way to estimate the CO2 remaining in the reservoir after the completion of the CO2-EOR process is also included in the methodology.
Assessment results will be aggregated to play, petroleum province, regional, and national scales. This assessment methodology has been tested on the Horseshoe Atoll, Upper Pennsylvanian-Wolfcampian play in the Permian Basin Province in Texas; the play consists of 27 reservoirs having at least 2 billion barrels of OOIP that are amenable to the CO2-EOR process. The play was selected as a test case because CO2-EOR production data and published reports are available for several reservoirs within the play. Preliminary estimates of oil recoverable by implementation of miscible CO2-EOR are comparable to those reported in the literature and obtained by reservoir decline curve analysis.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195115","usgsCitation":"Warwick, P.D., Attanasi, E.D., Olea, R.A., Blondes, M.S., Freeman, P.A., Brennan, S.T., Merrill, M.D., Verma, M.K., Karacan, C.Ö., Shelton, J.L., Lohr, C.D., Jahediesfanjani, H., and Roueché, J.N., 2019, A probabilistic assessment methodology for carbon dioxide enhanced oil recovery and associated carbon dioxide retention: U.S. Geological Survey Scientific Investigations Report 2019–5115, 51 p., https://doi.org/10.3133/sir20195115.","productDescription":"x, 51 p.","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069832","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":399600,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109570.htm"},{"id":370863,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5115/sir20195115.pdf","text":"Report","size":"8.81 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5115"},{"id":370862,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5115/coverthb.jpg"}],"contact":"Eastern Energy Resources Science Center
12201 Sunrise Valley Drive
956 National Center
Reston, VA 20192
In keeping with our national mission, the USGS in Alaska provides timely and objective scientific information to help the Nation address issues and solve problems in five major topical areas (listed alphabetically):
The USGS in Alaska engages about 400 scientists and support staff working in three major science centers, Cooperative Research Units, and USGS centers outside Alaska, with a combined annual science budget of about $60 million. In just the last 5 years, the USGS in Alaska has produced scientific benefits resulting from more than 1,000 publications and about 250 technical reports. Publications relevant to Alaska can be conveniently searched by keyword through the USGS Publications Warehouse at https://pubs.er.usgs.gov/search?q=Alaska.
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Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Beach erosion is a persistent problem along most open-ocean shores of the United States. Along the Arctic coast of Alaska, coastal erosion is widespread and threatens communities, defense and energy-related infrastructure, and coastal habitat. As coastal populations continue to expand and infrastructure and habitat are increasingly threatened by erosion, there is increased demand for accurate information regarding past and present trends and rates of shoreline movement.
Shoreline change was evaluated by comparing three to four historical shoreline positions derived from 1950s-era topographic surveys and black and white aerial photography, 1980s-era color-infrared Alaska High-Altitude Aerial Photography, 2003 natural color aerial photography, and 2010s-era natural color aerial photography. Long-term (1950s–2010s) and short-term (1980s–2010s) shoreline change rates were calculated using linear-regression and end-point methods, respectively, at transects spaced approximately every 50 meters along both the mainland and barrier island coasts.
Shoreline change rates calculated on more than 24,000 individual transects indicate that between 1948 and 2016 the northern coast of Alaska between Icy Cape and Cape Prince of Wales was slightly erosional, with 68 percent of the total transects showing shoreline retreat over the long term and 63 percent over the short term. However, only 9 percent of the total transects showed shoreline retreat greater than 1 meter per year (m/yr) over the long and short term, respectively. Mean rates of shoreline change of −0.2±0.1 and −0.2±0.3 m/yr, were calculated for the long and short term, respectively. Many rates measured were near the limit of our shoreline change uncertainty estimates. Erosion and accretion rates on individual transects ranged from −8.3 to +9.6 m/yr over the long term and −16.0 to +20.0 m/yr over the short-term analysis periods. The highest rates of erosion and accretion were associated with the formation and migration of inlets along barrier island coasts. The highest erosional rates of change were measured in the southern part of the study area between Sullivan Lake and Cape Prince of Wales. The highest accretional rates of change were measured in the northern part of the study area on the open-ocean coast of barrier islands fronting Kasegaluk Lagoon.
Open-ocean exposed shorelines compose 85 percent of all transects and 70 percent were erosional over the long term. Sheltered mainland-lagoon shorelines compose 15 percent of all transects in the study area and 58 percent were erosional over the long term. Although mean shoreline change rates were quite low along all coasts, exposed shorelines retreated at twice the rate (−0.2±0.1 m/yr) of sheltered shorelines (−0.1±0.1 m/yr). Barrier shoreline transects (includes barrier islands, spits, and beaches) compose 49 percent of the total transects and 56 percent of all exposed shoreline transects. Mean shoreline change rates on exposed barrier shorelines were only slightly greater than exposed mainland shorelines (−0.3±0.1 and −0.2±0.1 m/yr, respectively). Mean shoreline change rates on sheltered barrier shorelines were similar to sheltered mainland shorelines (−0.1±0.3 m/yr).
In contrast to the majority of the Nation’s shorelines, for all but three months of the year (July–September), the north coast of Alaska has historically been protected by landfast sea ice from processes such as waves, winds, and currents that typically drive coastal change on beaches in more temperate regions of the world. Projected and observed increases in periods of sea-ice-free conditions, as sea ice melts earlier and forms later in the year, particularly in the autumn, when large storms are more common in the Arctic, suggest that Arctic coasts will be more vulnerable to storm surge and wave energy, potentially resulting in accelerated shoreline erosion and terrestrial habitat loss in the future. Increases in air and sea water temperatures may also increase erosion of the ice-rich, coastal permafrost bluffs present along much of Alaska’s Arctic coast. More frequent shoreline change data collection and analysis in this rapidly changing environment should be considered in order to evaluate shoreline change trends in the future.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191146","usgsCitation":"Gibbs, A.E., Snyder, A.G., and Richmond, B.M., 2019, National assessment of shoreline change — Historical shoreline change along the north coast of Alaska, Icy Cape to Cape Prince of Wales: U.S. Geological Survey Open-File Report 2019–1146, 52 p., https://doi.org/10.3133/ofr20191146.","productDescription":"Report: vi, 52 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-111408","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":399433,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109572.htm"},{"id":370888,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1146/coverthb.jpg"},{"id":370889,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1146/ofr20191146.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1146"},{"id":370890,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H1S1PV","linkHelpText":"National assessment of shoreline change—A GIS compilation of updated vector shorelines and associated shoreline change data for the north coast of Alaska, Icy Cape to Cape Prince of Wales"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -168.1194,\n 65.5739\n ],\n [\n -160.9839,\n 65.5739\n ],\n [\n -160.9839,\n 70.3322\n ],\n [\n -168.1194,\n 70.3322\n ],\n [\n -168.1194,\n 65.5739\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
Stream stability, flood frequency, and streambed scour potential were evaluated at 20 Alaskan river- and stream-spanning bridges lacking a quantitative scour analysis or having unknown foundation details. Three of the bridges had been assessed shortly before the study described in this report but were re-assessed using different methods or data. Channel instability related to mining may affect scour at one site, while channel instability related to flow distribution changes can be seen at one site. One bridge was closed because of abutment scour prior to the study. Otherwise, channels generally showed stable bed elevations.
Contraction and abutment scour were calculated for all 20 bridges, and pier scour was calculated for the 2 bridges that had piers. Vertical contraction (pressure flow) scour was calculated for one site at which the modeled water surface was higher than the superstructure of the bridge. Hydraulic variables for the scour calculations were derived from one-dimensional and two-dimensional hydraulic models of the 1- and 0.2-percent annual exceedance probability floods (also known as the 100- and 500-year floods, respectively). Scour also was calculated for large recorded floods at two sites.
At many sites, overflow of road approaches relieves the bridge during floods and lessens the potential for scour. Two-dimensional hydraulic models are superior to one-dimensional hydraulic models at distributing flow between bridges, road approaches, and floodplains, and therefore likely produce more reasonable scour values at sites with substantial floodplain flow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195110","collaboration":"Prepared in cooperation with the Alaska Department of Transportation and Public Facilities","usgsCitation":"Beebee, R.A., Dworsky, K.L., and Knopp, S.J., 2019, Streambed scour evaluations and conditions at selected bridge Sites in Alaska, 2016–17 (version 1.1, April 2023): U.S. Geological Survey Scientific Investigations Report 2019-5110, 32 p., https://doi.org/10.3133/sir20195110.","productDescription":"Report: vi, 32 p.; Data Release","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-099321","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":399597,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109571.htm"},{"id":370872,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5110/coverthb2.jpg"},{"id":370873,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5110/sir20195110.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5110"},{"id":415671,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2019/5110/sir20195110_RevisionHistory.txt","description":"SIR 2019-5110 Version History"},{"id":370874,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LUTFHZ","linkHelpText":"Tabular input/output data and model files for 19 hydraulic models for streambed scour evaluations at selected bridge sites, Alaska, 2016–17"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.41259765625,\n 59.01794033995248\n ],\n [\n -144.77783203125,\n 59.01794033995248\n ],\n [\n -144.77783203125,\n 64.97006438589436\n ],\n [\n -155.41259765625,\n 64.97006438589436\n ],\n [\n -155.41259765625,\n 59.01794033995248\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: April 2023; Version 1.0: December 2019","contact":"Director,
Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Investments in landscape-scale restoration and fuels management projects can protect publicly managed trusts, enhance public health and safety, and help to preserve the many environmental goods and services enjoyed by the public. These investments can also support jobs and generate business sales activities within nearby local economies. This report investigates how investments made by the Rio Grande Water Fund (RGWF) on wildfire risk reduction and source water protection projects in northern New Mexico and southern Colorado affect local economic activity. To implement these projects, the RGWF spent a total of $855,000 in 2018 on contractors located in the Western States regional economy. Including direct and secondary effects, these expenditures supported an estimated 22 jobs, $1,089,000 in labor income, $1,324,000 in value added, and $1,907,000 in economic output in the 17 Western States economy. The majority (73 percent or $623,000) of these expenditures were made by hiring local businesses operating within a 13-county region in northern New Mexico and southern Colorado that comprises the RGWF project area. Including direct and secondary effects, local expenditures support an estimate 15 jobs, $676,000 in labor income, $791,000 in value added, and $1,120,000 in economic output within the 13-county RGWF project area. These results demonstrate how investments in wildfire risk reduction and source water protection projects can support jobs and livelihoods, small businesses, and rural economies in the Mountain West.
","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191108","collaboration":"Prepared in cooperation with The Nature Conservancy","usgsCitation":"Huber, C., Cullinane Thomas, C., Meldrum, J.R., Meier, R., and Bassett, S., 2019, Economic effects of wildfire risk reduction and source water protection projects in the Rio Grande River Basin in northern New Mexico and southern Colorado: U.S. Geological Survey Open-File Report 2019–1108, 8 p., https://doi.org/10.3133/ofr20191108.","productDescription":"iv, 8 p.","onlineOnly":"Y","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":399416,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109581.htm"},{"id":370215,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1108/ofr20191108.pdf","text":"Report","size":"7.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1108"},{"id":370214,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1108/coverthb.jpg"}],"country":"United States","state":"Colorado, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.6408,\n 34.2403\n ],\n [\n -103.6667,\n 34.2403\n ],\n [\n -103.6667,\n 37.3417\n ],\n [\n -107.6408,\n 37.3417\n ],\n [\n -107.6408,\n 34.2403\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
Chief, Analysis and Prediction Branch
Integrated Modeling and Prediction Division
Water Resources Mission Area
U.S. Geological Survey, Mail Stop 415
12201 Sunrise Valley Drive
Reston, VA 20192
Otolith microanalysis is often used to assess population age structure and growth of fishes during their early stages. Shoal Bass Micropterus cataractae is a recently described species of conservation concern and little is known regarding factors affecting their recruitment. In 2004, Georgia Department of Natural Resources (GADNR) and the US National Park Service (NPS) stocked Shoal Bass marked with oxytetracycline (OTC) in the Chattahoochee River near Atlanta, Georgia in an effort to restore this population, creating known-age fish to examine the effect of environment on daily age accuracy. We obtained samples of stocked juvenile (<150 mm) Shoal Bass from standard monitoring that occurred approximately 30–60 days after stocking in the Chattahoochee River to 1) validate daily rings for estimating age, hatch dates, and growth rates for stocked age-0 Shoal Bass, and 2) evaluate the effect of habitat (location) on age bias. Shoal Bass otoliths were examined for OTC marks and daily rings were counted in reference to OTC marks to assess age estimation accuracy. Age estimation accuracy ranged from -2 to -25 days and was influenced by the environment where Shoal Bass were captured, with greater inaccuracy in colder water temperatures. Fish collected from locations with colder temperatures displayed closer spacing of daily rings, potentially leading to greater underestimation of age. Growth rates of stocked Shoal Bass, corrected for age estimation error, ranged from 0.5 mm/day to 0.8 mm/day. This study demonstrates the effect of environmental variability on age inaccuracy and subsequent interpretation of results. Incorporating methods to assess age estimation accuracy is needed to understand interspecific differences in recruitment among black bass species in the variety of natural and human-modified environments they inhabit.
This report summarizes a national assessment of flowing waters conducted by the U.S. Geological Survey’s (USGS) National Water-Quality Assessment (NAWQA) Project and addresses several pressing questions about the modification of natural flows in streams and rivers. The assessment is based on the integration, modeling, and synthesis of monitoring data collected by the USGS and the U.S. Environmental Protection Agency at more than 7,000 streams and rivers across the conterminous United States from 1980 to 2014. Key findings include the following. First, flow in many of the Nation’s streams and rivers is different from what it would be under natural conditions. In particular, low flows are more frequent, are of shorter duration, and vary less from one year to the next than they would naturally. In addition, high flows have been reduced in magnitude, are of shorter duration, are less frequent, and vary less from one year to the next than they would naturally. Other characteristics of natural flows also have been modified. Second, over the last 60 years (1955–2014), climatic trends have caused a change of 50 percent or more in one or more streamflow attributes at two-thirds of climate-sensitive streamgaging sites. However, these climate-induced changes have been less influential on streamflow modification than have land and water-management practices. Third, in every region assessed, streamflow modification was associated with reduced ecological health, as indicated by two biological communities—invertebrates and fish. Biological communities were increasingly likely to be impaired (defined as having lost a statistically significant number of species) in streams with flows most different from natural conditions. Finally, several case studies are presented that illustrate viable management strategies for balancing the water needs of people and ecosystems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1461","collaboration":"National Water-Quality ProgramNational Water-Quality Program
U.S. Geological Survey
413 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Digital flood-inundation maps for an 8.8-mile reach of the North Platte River, from 1.5 miles upstream from the Highway 92 bridge to 3 miles downstream from the Highway 71 bridge in Scottsbluff County, were created by the U.S. Geological Survey (USGS) in cooperation with the Cities of Scottsbluff and Gering, Nebraska. The flood-inundation maps, which can be accessed through the Flood Inundation Mapping (FIM) Program website at https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program?qt-science_center_objects=0#qt-science_center_objects, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the North Platte River at Scottsbluff, Nebr. (station number 06680500). Near-real-time stages at this streamgage may be obtained on the internet from the USGS National Water Information System at https://doi.org/10.5066/F7P55KJN or from the National Weather Service Advanced Hydrologic Prediction Service (site SBRN1) at https://water.weather.gov/ahps2/hydrograph.php?wfo=cys&gage=sbrn1.
Flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated by using the current (2018) stage-discharge relation at the North Platte River at Scottsbluff, Nebr., streamgage.
The hydraulic model was then used to compute 10 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from 9 ft, or near bankfull, to 18 ft, which exceeds the stage that corresponds to the estimated 1-percent annual exceedance probability flood (100-year recurrence interval flood). The simulated water-surface profiles were then combined with a geographic information system digital elevation model derived from light detection and ranging data having a 0.6-ft root mean square error and 2-ft horizontal resolution resampled to a 6-ft grid to delineate the area flooded at each water level. The availability of these maps, along with internet information regarding current stage from the USGS streamgage, may provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195099","collaboration":"Prepared in cooperation with the City of Scottsbluff and the City of Gering","usgsCitation":"Strauch, K.R., 2019, Flood-inundation maps for the North Platte River at Scottsbluff and Gering, Nebraska, 2018: U.S. Geological Survey Scientific Investigations Report 2019–5099, 9 p., https://doi.org/10.3133/sir20195099.","productDescription":"Report: vi, 9 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-102434","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":399544,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109564.htm"},{"id":370451,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5099/sir20195099.pdf","text":"Report","size":"25.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5099"},{"id":370452,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NCAIKN","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Flood-inundation geospatial datasets for the North Platte River at Scottsbluff and Gering, Nebraska"},{"id":370450,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5099/coverthb.jpg"}],"country":"United States","state":"Nebraska","city":"Scottsbluff, Gering","otherGeospatial":"North Platte River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.05426025390625,\n 41.74467659677642\n ],\n [\n -103.33740234375,\n 41.74467659677642\n ],\n [\n -103.33740234375,\n 42.05948945192712\n ],\n [\n -104.05426025390625,\n 42.05948945192712\n ],\n [\n -104.05426025390625,\n 41.74467659677642\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Beaver Lake was constructed in 1966 on the White River in the northwest corner of Arkansas for flood control, hydroelectric power, public water supply, and recreation. The surface area of Beaver Lake is about 27,900 acres and approximately 449 miles of shoreline are at the conservation pool level (1,120 feet above the North American Vertical Datum of 1988). Sedimentation in reservoirs can result in reduced water storage capacity and a reduction in usable aquatic habitat. Therefore, accurate and up-to-date estimates of reservoir water capacity are important for managing pool levels, power generation, recreation, and downstream aquatic habitat. Many of the lakes operated by the U.S. Army Corps of Engineers are periodically surveyed to monitor bathymetric changes that affect water capacity. In October 2018, the U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, completed one such survey of Beaver Lake using a multibeam echosounder. The echosounder data were combined with light detection and ranging (lidar) data to prepare a bathymetric map and a surface area and capacity table.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3445","collaboration":"Prepared in cooperation with the U.S. Army Corp of Engineers, Southwestern Division, Little Rock District","usgsCitation":"Huizinga, R.J., Ellis, J.T., Sharpe, J.B., LeRoy, J.Z., and Richards, J.M., 2019, Bathymetric map and surface area and capacity table for Beaver Lake near Rogers, Arkansas, 2018: U.S. Geological Survey Scientific Investigations Map 3445,\n2 sheets, https://doi.org/10.3133/sim3445.","productDescription":"2 Sheets: 44 x 36 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-113370","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":370609,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3445/coverthb.jpg"},{"id":399518,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109565.htm"},{"id":370612,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91PLLGV","text":"USGS data release","linkHelpText":"Bathymetric and supporting data for Beaver Lake near Rogers, Arkansas, 2018"},{"id":370610,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3445/sim3445_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3445 Sheet 1"},{"id":370611,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3445/sim3445_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3445 Sheet 2"}],"scale":"24000","country":"United States","state":"Arkansas","city":"Rogers","otherGeospatial":"Beaver Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.11575317382812,\n 36.17446549576358\n ],\n [\n -93.79440307617188,\n 36.17446549576358\n ],\n [\n -93.79440307617188,\n 36.45829281489\n ],\n [\n -94.11575317382812,\n 36.45829281489\n ],\n [\n -94.11575317382812,\n 36.17446549576358\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
The U.S. Geological Survey (USGS), in cooperation with the Oklahoma Department of Transportation, updated peak-streamflow regression equations for estimating flows with annual exceedance probabilities from 50 to 0.2 percent for the State of Oklahoma. These regression equations incorporate basin characteristics to estimate peak-streamflow magnitude and frequency throughout the State by use of a generalized least-squares regression analysis. The most statistically significant independent variables required to estimate peak-streamflow magnitude and frequency for unregulated streams in Oklahoma are contributing drainage area, mean-annual precipitation, and main-channel slope. The regression equations are applicable for stream basins with drainage areas less than 2,510 square miles that are not affected by regulation. The standard model error ranged from 31.28 to 49.32 percent for the different annual exceedance probabilities that were computed.
Annual-maximum peak flows observed at 212 USGS streamgages through water year 2017 were used for the regression analysis, excluding the Oklahoma Panhandle region. The USGS StreamStats web application was used to obtain the independent variables required for the peak-streamflow regression equations. Limitations on the use of the regression equations and the reliability of regression estimates for natural unregulated streams are described. Log-Pearson Type III analysis information, basin and climate characteristics, and the peak-streamflow frequency estimates for the 212 streamgages in and near Oklahoma are provided in this report.
This report contains descriptions of the methods that can be used to estimate peak streamflows at ungaged sites by using estimates from streamgages on unregulated streams. For ungaged sites on urban streams and streams regulated by small floodwater-retarding structures, an adjustment of the statewide regression equations for natural unregulated streams can be used to estimate peak-streamflow magnitude and frequency.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195143","collaboration":"Prepared in cooperation with the Oklahoma Department of Transportation","usgsCitation":"Lewis, J.M., Hunter, S.L., and Labriola, L.G., 2019, Methods for estimating the magnitude and frequency of peak streamflows for unregulated streams in Oklahoma developed by using streamflow data through 2017 (ver. 1.1, March 2020): U.S. Geological Survey Scientific Investigations Report 2019–5143, 39 p., https://doi.org/10.3133/sir20195143.","productDescription":"Report: v, 39 p.; Data Release","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-111975","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":373219,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5143/sir20195143_v1.1.pdf","text":"Report","size":"5.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5143"},{"id":370619,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B99TQZ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data release of basin characteristics, generalized skew map and peak-streamflow frequency estimates in Oklahoma, 2017"},{"id":373218,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5143/coverthb2.jpg"},{"id":373266,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2019/5143/versionHist.txt","text":"Version History","description":"Version History"},{"id":399618,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109563.htm"}],"country":"United States","state":"Arkansas, Kansas, Missouri, Oklahoma, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.919921875,\n 36.87962060502676\n ],\n [\n -102.83203125,\n 34.415973384481866\n ],\n [\n -97.91015624999999,\n 33.97980872872457\n ],\n [\n -94.5703125,\n 33.17434155100208\n ],\n [\n -93.515625,\n 33.97980872872457\n ],\n [\n -93.251953125,\n 37.125286284966805\n ],\n [\n -93.7353515625,\n 38.09998264736481\n ],\n [\n -99.8876953125,\n 38.09998264736481\n ],\n [\n -101.953125,\n 37.71859032558816\n ],\n [\n -102.919921875,\n 36.87962060502676\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: March 2020; Version 1.0: December 2019","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501
River connectivity is defined as the water-mediated exchange of matter, energy, and biota between different elements of the riverine landscape. Connectivity is an especially important concept in large-river corridors (channel plus floodplain ) because large rivers integrate fluxes of water, sediment, nutrients, contaminants, and other transported constituents emanating from large contributing drainage basins, and thereby contribute to the complexity of large-river ecosystems. Large rivers are also highly valued for socioeconomic goods and services, which has led to historical fragmentation, lack of connectivity, and contentiousness about best policies for managing large-river corridors. The classification is intended to serve as a template for understanding geographic variation in large rivers within the Midwest, to aid in designing scientific studies of large river ecological processes, and to match specific river-management and restoration objectives to specific river reaches. The focus of the classification is on measuring river connectivity from available hydrological and geomorphic data.
We provide a multiscale assessment and classification for segments of 15 rivers that meet various criteria for largeness. All rivers are tributaries to the Mississippi River system. The 11,600 kilometers (km) that qualified as large were classified by major alterations (unimpounded, navigation pools, storage reservoir) and additionally assessed for their network continuity as a function of numbers and heights of dams. Among the 15 rivers, 55 percent of segment length was unimpounded, 30 percent was in navigation pools, and 15 percent was under storage reservoirs. Assessment of network longitudinal connectivity among river segments documented the contrast between river segments with low-head navigation dams (Upper Mississippi, Illinois, Ohio, Green, and Cumberland Rivers) and those segments with high-head dams (mostly in the Upper Missouri River). The longest unimpounded river pathways exist in the Lower Missouri River and connected tributaries where nearly 1,300 km of the Missouri River connect to an additional 1,800 km of the Middle and Lower Mississippi Rivers.
At our finest scale, we present a statistically based, component classification based on 10-km segments. Cluster analysis of hydrologic variables from 66 streamflow-gaging stations yielded 5 clusters calculated from 5 ecohydrological metrics related to lateral connectivity with the floodplain. A separate cluster analysis of 5 geomorphologic variables associated with each of the 1,172 river segments also yielded 5 clusters. When the hydrologic variables were associated with corresponding segments, the cluster analysis yielded 8 hydrogeomorphic clusters that could be explained in terms of their contribution to floodplain connectivity. Although the clusters overlap considerably in principal component space, the resulting hydrogeomorphic classification leads to a physically reasonable distribution of classes. The resulting classification is intended to increase geographic awareness of the range of variation of connectivity potential among large rivers of the Upper Midwest, to increase understanding of the extent of alteration of these rivers, and potentially to serve as a template for stratifying study designs of large-river corridor ecological processes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195132","usgsCitation":"Jacobson, R.B., Rohweder, J.J., and DeJager, N.R., 2019, A hydrogeomorphic classification of connectivity of large rivers of the Upper Midwest, United States: U.S. Geological Survey Scientific Investigations Report 2019–5132, 55 p., https://doi.org/10.3133/sir20195132.","productDescription":"Report: vi, 55 p.; 2 Data Releases","numberOfPages":"66","onlineOnly":"Y","ipdsId":"IP-104678","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":399611,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109562.htm"},{"id":370623,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5132/sir20195132.pdf","text":"Report","size":"9.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5132"},{"id":370625,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HFYOLO","text":"USGS data release","linkHelpText":"River valley boundaries and transects generated for select large rivers of the Upper Midwest, United States"},{"id":370624,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YGOKWZ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Segment-scale classification, large rivers of the Upper Midwest United States"},{"id":370622,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5132/coverthb.jpg"}],"country":"United States","state":"Colorado, Illinois, Indiana, Iowa, Kansas, Kentucky, Minnesota, Missouri, Montana, Nebraska, New York, North Carolilna,North Dakota, Ohio, Pennsylvania, South Dakota, Tennessee, Virginia, West Virginia, Wisconsin, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.8251953125,\n 35.460669951495305\n ],\n [\n -80.5078125,\n 37.020098201368114\n ],\n [\n -80.15625,\n 35.60371874069731\n ],\n [\n -79.541015625,\n 37.43997405227057\n ],\n [\n -79.365234375,\n 39.87601941962116\n ],\n [\n -77.7392578125,\n 42.74701217318067\n ],\n [\n -82.265625,\n 40.91351257612758\n ],\n [\n -86.8359375,\n 41.73852846935917\n ],\n [\n -87.5830078125,\n 41.60722821271717\n ],\n [\n -88.9453125,\n 43.61221676817573\n ],\n [\n -89.4287109375,\n 43.45291889355465\n ],\n [\n -89.7802734375,\n 46.10370875598026\n ],\n [\n -90.439453125,\n 46.37725420510028\n ],\n [\n -93.42773437499999,\n 46.86019101567027\n ],\n [\n -94.9658203125,\n 47.57652571374621\n ],\n [\n -96.85546875,\n 45.55252525134013\n ],\n [\n -100.94238281249999,\n 48.42920055556841\n ],\n [\n -104.150390625,\n 49.210420445650286\n ],\n [\n -112.0166015625,\n 49.03786794532644\n ],\n [\n -113.99414062499999,\n 45.79816953017265\n ],\n [\n -112.9833984375,\n 44.5278427984555\n ],\n [\n -111.09374999999999,\n 44.77793589631623\n ],\n [\n -106.3916015625,\n 41.47566020027821\n ],\n [\n -105.6884765625,\n 39.67337039176558\n ],\n [\n -104.150390625,\n 38.75408327579141\n ],\n [\n -94.921875,\n 38.16911413556086\n ],\n [\n -91.93359375,\n 36.98500309285596\n ],\n [\n -89.736328125,\n 36.80928470205937\n ],\n [\n -85.8251953125,\n 35.460669951495305\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201
Masting, or the synchronous and irregular production of seed crops, is controlled by environmental conditions and resource budgets. Increasing temperatures and shifting precipitation regimes may alter the frequency and magnitude of masting, especially in species that experience chronic resource stress. Yet the effects of a changing climate on seed production are unlikely to be uniform across populations, particularly those that span broad abiotic gradients. In this study, we assessed the spatiotemporal patterns of masting across the latitudinal distribution of a widely distributed dryland conifer species, piñon pine Pinus edulis . We quantified seed cone production from 2004 to 2017 using cone abscission scars in 187 trees from 28 sites along an 1100 km latitudinal gradient to investigate the spatiotemporal drivers of seed cone production and synchrony across populations. Populations from chronically hot and dry areas (greater climatic water deficits and less monsoonal precipitation) tended to have greater interannual variability in seed cone production and smaller crop sizes. Mast years generally followed years with low vapor pressure deficits and high precipitation during key periods of the reproductive process, but the strength of these relationships varied across the region. Populations that received greater monsoonal precipitation were less sensitive to late summer vapor pressure deficits during seed cone initiation yet more sensitive to spring vapor pressure deficits during pollination. Spatially correlated patterns of vapor pressure deficit better predicted synchrony in seed cone production than geographic distance, and these patterns were conserved at distances up to 500 km. These results demonstrate that aridity drives spatiotemporal variability in seed cone production. As a result, projected increases in aridity are likely to decrease the frequency and magnitude of masting in these dry forests and woodlands. Declines in seed production may compound climatic limitations to recruitment and impede tree regeneration, with cascading effects for numerous wildlife species.
Widespread use of neonicotinoid insecticides in North America has led to frequent detection of neonicotinoids in surface waters. Despite frequent surface water detection, few studies have evaluated underlying sediments for the presence of neonicotinoids. Thus, we sampled water and sediments for neonicotinoids during a one-year period at 40 floodplain wetlands throughout Missouri. Analyzed for six common neonicotinoids, sediment samples consistently (63% of samples) contained neonicotinoids (e.g., imidacloprid and clothianidin) in all sampling periods. Mean sediment and aqueous neonicotinoid concentrations were 1.19 μg kg–1 (range: 0–17.99 μg kg–1) and 0.03 μg L–1 (0–0.97 μg L–1), respectively. We used boosted regression tree analysis to explain sediment neonicotinoid concentrations and ultimately identified six variables that accounted for 31.6% of concentration variability. Efforts to limit sediment neonicotinoid contamination could include reducing agriculture within a wetland below a threshold of 25% area planted. Also, prolonging periods of overlying water >25 cm deep when water temperatures reach/exceed 18 °C could promote conditions favorable for neonicotinoid degradation. Results of this study can be useful in determining potential routes and levels of neonicotinoid exposure experienced by nontarget benthic aquatic invertebrates as well as potential means to mitigate neonicotinoid concentrations in floodplain wetlands.
Zebra mussels (Dreissena polymorpha) are invasive bivalves that have perturbed aquatic ecosystems within North America since their introduction in the mid-1980s. Control of zebra mussels has largely been restricted to raw water conveyance systems and associated infrastructures because few control products are registered for application in surface waters. The biopesticide Zequanox was registered in 2014 by the U.S. Environmental Protection Agency for controlling dreissenid mussels (zebra and quagga mussels (Dreissena rostriformis bugensis) in surface waters. Previous Zequanox applications in surface waters have used vertical impermeable-membrane barriers to contain treated water. Studies have indicated that uncontained applications may be successful if Zequanox suspensions of the correct viscosity are applied to facilitate the creation of stratified benthic treatment layer. In this study, Zequanox was applied to replicate 0.30-hectare plots within a small inland lake using a custom-engineered, boat-mounted application system to determine if uncontained Zequanox applications could be used to manage zebra mussel populations and to protect native unionid mussels within zebra mussel infested waters. To determine success, the following specific objectives were investigated during, 30 days after, and/or 1 year after Zequanox exposure: (1) evaluate Zequanox concentrations during exposure; (2) monitor water quality during and after exposure; (3) evaluate the mortality of zebra mussels that were caged within treatment zones during the exposures; (4) evaluate the densities of naturally occurring zebra mussels with treatment zones before and after Zequanox exposure; and (5) evaluate the survival, condition, and dreissenid infestation of native mussels in the treatment zones before and after Zequanox exposure. Zequanox rapidly dissipated from the treated plots, resulting in no appreciable treatment-related mortality of zebra mussels and insignificant impacts to water quality. Zequanox exposure-related impacts to native mussels were not observed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191126","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Luoma, J.A., Waller, D.L., Severson, T.J., Barbour, M.T., Wise, J.K., Lord, E.G., Bartsch, L.A., and Bartsch, M.R., Assessment of uncontained Zequanox applications for zebra mussel control in a Midwestern lake: U.S. Geological Survey Open-File Report 2019–1126, 21 p., https://doi.org/10.3133/ofr20191126.","productDescription":"viii, 21 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-108267","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":437255,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90JY18D","text":"USGS data release","linkHelpText":"Assessment of uncontained Zequanox applications in a Midwestern lake 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Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Rd.
La Crosse, WI 54603