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
Laboratory experiments that simulate lava flows have been in use by volcanologists for many years. The behavior of flows in the lab, where “eruption” parameters, material properties, and environmental settings are tightly controlled, provides insight into the influence of various factors on flow evolution. A second benefit of laboratory lava flows is to provide a set of observations with which numerical models of flow emplacement can be tested. Models of lava flow emplacement vary in mathematical approach, physical assumptions, and computational cost. Nonetheless, all models require thorough testing and evaluation, and laboratory experiments produce an excellent test for models.
This paper provides a primer on modern analog laboratory lava flow experiments. It reviews scaling con- siderations and provides quantitative information meant to guide future experimentalists in designing their experiments to be relevant to natural processes. Traditional and novel laboratory techniques are described, including a discussion of current limitations. New insights from recent experiments highlight the impact of topographic conditions and highlight the importance of considering bed roughness, major obstacles, and slope breaks. The influence of episodic or non-uniform effusion rate is demonstrated through recent experi- mental works. Lastly, the paper discusses several open questions about lava flow emplacement and the ways in which future improvements in experimental methods, such as the ability to utilize three-phase suspensions and materials with complex rheologies and to image the interior of flows could help answer these.
","language":"English","publisher":"National Institute of Geophysics and Volcanology (INGV)","doi":"10.4401/ag-7843","usgsCitation":"Lev, E., Rumpf, M.E., and Dietterich, H., 2019, Analog experiments of lava flow emplacement: Annals of Geophysics, v. 62, no. 2, VO225, 21 p., https://doi.org/10.4401/ag-7843.","productDescription":"VO225, 21 p.","ipdsId":"IP-103534","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":458876,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4401/ag-7843","text":"Publisher Index Page"},{"id":377875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lev, Einat 0000-0002-8174-0558","orcid":"https://orcid.org/0000-0002-8174-0558","contributorId":194355,"corporation":false,"usgs":false,"family":"Lev","given":"Einat","email":"","affiliations":[{"id":27369,"text":"Lamont-Doherty Earth Observatory at Columbia University","active":true,"usgs":false}],"preferred":false,"id":797292,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rumpf, M. Elise 0000-0001-7906-2623","orcid":"https://orcid.org/0000-0001-7906-2623","contributorId":217992,"corporation":false,"usgs":true,"family":"Rumpf","given":"M.","email":"","middleInitial":"Elise","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":797294,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dietterich, Hannah R. 0000-0001-7898-4343","orcid":"https://orcid.org/0000-0001-7898-4343","contributorId":212771,"corporation":false,"usgs":true,"family":"Dietterich","given":"Hannah R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":797293,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208580,"text":"70208580 - 2019 - Genetically-informed seed transfer zones for Pleuraphis jamesii, Sphaeralcea parvifolia, and Sporobolus cryptandrus across the Colorado Plateau and adjacent regions","interactions":[],"lastModifiedDate":"2020-02-20T06:51:01","indexId":"70208580","displayToPublicDate":"2019-12-31T06:48:01","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Genetically-informed seed transfer zones for Pleuraphis jamesii, Sphaeralcea parvifolia, and Sporobolus cryptandrus across the Colorado Plateau and adjacent regions","docAbstract":"(Massatti) Introduction: The majority of native plant materials (NPMs) utilized for restoration purposes are developed for widely distributed species that provide a variety of ecosystem services (Wood et al. 2015; Butterfield et al. 2017). Disturbed ecosystems benefit from the use of appropriate NPMs, which are those that display ecological fitness at the restoration site, are compatible with conspecifics and other members of the plant community, and that do not demonstrate invasive tendencies (Jones 2013). Furthermore, the use of appropriate NPMs can help address specific environmental challenges, rejuvenate ecosystem function, and improve the delivery of ecosystem services (Hughes 2008). While many NPMs have been developed for restoration (e.g., Aubry et al. 2005), there is interest in broadening the diversity of species available and the geographic representation of sources to provide appropriate choices in relation to the characteristics of any restoration site. In addition, researchers are providing guidance to managers and practitioners regarding how best to transfer NPMs across the landscape. For example, guidance on seed transfer has been derived from genecological studies, which utilize common gardens to correlate phenotypic variation to environmental gradients (summarized in Kilkenny 2015), molecular studies, which identify putative adaptive genetic loci and infer environmental drivers of variation (Shryock et al. 2017), and climate modeling studies, which can provide guidance when species-specific data are unavailable (Bower et al. 2014; Doherty et al. 2017). All of these approaches intend to improve the long-term viability of NPMs at restoration sites, thereby improving outcomes and stretching limiting restoration resources (e.g., time and money).","language":"English","publisher":"Bureau of Land Management","usgsCitation":"Massatti, R., 2019, Genetically-informed seed transfer zones for Pleuraphis jamesii, Sphaeralcea parvifolia, and Sporobolus cryptandrus across the Colorado Plateau and adjacent regions, 11 p.","productDescription":"11 p.","ipdsId":"IP-113144","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":372440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":372412,"type":{"id":15,"text":"Index Page"},"url":"https://www.blm.gov/sites/blm.gov/files/GWRC_STZ_report1.pdf"}],"country":"United States","otherGeospatial":"Colorado Plateau ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.42138671875,\n 39.57182223734374\n ],\n [\n -118.23486328125,\n 36.65079252503471\n ],\n [\n -111.7529296875,\n 33.76088200086917\n ],\n [\n -107.1826171875,\n 33.137551192346145\n ],\n [\n -104.0185546875,\n 33.284619968887675\n ],\n [\n -104.7216796875,\n 39.027718840211605\n ],\n [\n -107.70996093749999,\n 40.111688665595956\n ],\n [\n -111.4013671875,\n 41.77131167976407\n ],\n [\n -114.5654296875,\n 42.52069952914966\n ],\n [\n -117.2900390625,\n 42.06560675405716\n ],\n [\n -118.87207031250001,\n 40.84706035607122\n ],\n [\n -119.42138671875,\n 39.57182223734374\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Massatti, Robert 0000-0001-5854-5597","orcid":"https://orcid.org/0000-0001-5854-5597","contributorId":207294,"corporation":false,"usgs":true,"family":"Massatti","given":"Robert","email":"","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":782587,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70206261,"text":"sir20195110 - 2019 - Streambed scour evaluations and conditions at selected bridge sites in Alaska, 2016–17","interactions":[],"lastModifiedDate":"2023-04-13T10:56:36.045601","indexId":"sir20195110","displayToPublicDate":"2019-12-30T15:47:16","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":"2019-5110","displayTitle":"Streambed Scour Evaluations and Conditions at Selected Bridge Sites in Alaska, 2016–17","title":"Streambed scour evaluations and conditions at selected bridge sites in Alaska, 2016–17","docAbstract":"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
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.
Reliable estimates of life history parameters and their functional role in animal population trajectories are critical, yet often missing, components in conservation and management. We developed seasonal matrix population models of the Red-tailed Hawk Buteo jamaicensis jamaicensis in the upper and lower forests of the Luquillo Mountains, Puerto Rico, to describe the influence of early life stages (nestling and clutch survival) on population growth. Modelled populations exhibited positive discrete rates of growth in forests above 400 m (λ highlands = 1.05) and in forests below 400 m (λ lowlands = 1.27) of the Luquillo Mountains. Further, adult survival was the parameter with the highest proportional effect and direct contribution to growth of the population. Besides survival of adults, our results identified that nestling survival had the second greatest influence on λ, stressing the importance of this life stage for the population growth rate of Red-tailed Hawks in our study area. Seasonal matrices are not commonly used to describe population dynamics of birds. However, these may be a useful tool to analyse the influence of life stages in the annual cycle to better address conservation and management needs, especially for species inhabiting oceanic islands.
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
Autumn ungulate hunting in the Greater Yellowstone Ecosystem carries the risk of hunter–grizzly bear (Ursus arctos) conflict and creates a substantial challenge for managers. For Grand Teton National Park, Wyoming, USA, a key information need is whether increased availability of elk (Cervus canadensis) carcasses during a late autumn (Nov–Dec) harvest within the national park attracts grizzly bears and increases the potential for conflict with hunters. Using a robust design analysis with 6 primary sampling periods during 2014–2015, we tested the hypothesis that the elk harvest resulted in temporary movements of grizzly bears into the hunt areas, thus increasing bear numbers. We detected 31 unique individuals (6 F, 25 M) through genetic sampling and retained 26 encounter histories for analysis. Markovian movement models had more support than a null model of no temporary movement. Contrary to our research hypothesis, temporary movements into the study area occurred between the July–August (no hunt; N̄2014–2015 = 5) and September–October (no hunt; N̄2014–2015 = 24) primary periods each year, rather than during the transition from September–October (no hunt) to November–December (hunt; N̄2014–2015 = 15). A post hoc analysis indicated that September–October population estimates were biased high by detections of transient bears. Grizzly bear presence during the elk hunt was limited to approximately 15 resident bears that specialized in accessing elk carcasses. The late timing of the elk hunt likely moderated the effect of carcasses as a food attractant because it coincides with the onset of hibernation. From a population response perspective, the current timing of the elk harvest likely represents a scenario of low relative risk of hunter–bear conflicts. The risk of hunter–grizzly bear encounters remains, but may be more a function of factors that operate at the level of individual bears and hunters, such as hunter movements and bear responses to olfactory cues.
","language":"English","publisher":"International Association for Bear Research and Management","doi":"10.2192/URSUS-D-18-00018R2","usgsCitation":"van Manen, F.T., Ebinger, M.R., Gustine, D.D., Haroldson, M.A., Wilmot, K.R., and Whitman, C., 2019, Primarily resident grizzly bears respond to late-season elk harvest: Ursus, v. 30, no. e1, 15 p., https://doi.org/10.2192/URSUS-D-18-00018R2.","productDescription":"15 p.","ipdsId":"IP-099097","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":458896,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2192/ursus-d-18-00018r2","text":"Publisher Index Page"},{"id":437249,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IWSJUX","text":"USGS data release","linkHelpText":"Detection histories of grizzly bears in Grand Teton National Park, 2014-2015"},{"id":380007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Grand Teton National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.85205078124999,\n 43.6599240747891\n ],\n [\n -110.49224853515625,\n 43.6599240747891\n ],\n [\n -110.49224853515625,\n 43.91372326852401\n ],\n [\n -110.85205078124999,\n 43.91372326852401\n ],\n [\n -110.85205078124999,\n 43.6599240747891\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"e1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":803625,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ebinger, Michael R. 0000-0002-2586-7829 mebinger@usgs.gov","orcid":"https://orcid.org/0000-0002-2586-7829","contributorId":244264,"corporation":false,"usgs":true,"family":"Ebinger","given":"Michael","email":"mebinger@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":803626,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gustine, David D. 0000-0003-1087-1937","orcid":"https://orcid.org/0000-0003-1087-1937","contributorId":201734,"corporation":false,"usgs":false,"family":"Gustine","given":"David","email":"","middleInitial":"D.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":803627,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":803628,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilmot, Katharine R.","contributorId":244265,"corporation":false,"usgs":false,"family":"Wilmot","given":"Katharine","email":"","middleInitial":"R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":803629,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whitman, Craig 0000-0002-1187-4649 cwhitman@usgs.gov","orcid":"https://orcid.org/0000-0002-1187-4649","contributorId":206044,"corporation":false,"usgs":true,"family":"Whitman","given":"Craig","email":"cwhitman@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":803630,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70205417,"text":"sir20195099 - 2019 - Flood-inundation maps for the North Platte River at Scottsbluff and Gering, Nebraska, 2018","interactions":[],"lastModifiedDate":"2022-04-22T21:43:56.878264","indexId":"sir20195099","displayToPublicDate":"2019-12-23T20:34:51","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":"2019-5099","displayTitle":"Flood-Inundation Maps for the North Platte River at Scottsbluff and Gering, Nebraska, 2018","title":"Flood-inundation maps for the North Platte River at Scottsbluff and Gering, Nebraska, 2018","docAbstract":"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
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
In East Africa, accurate grain yield predictions can help save lives and protect livelihoods. Regional grain yield forecasts can inform decisions regarding the availability and prices of key staples, food aid, and large humanitarian responses. Here, we use earth observation (EO) products to develop and evaluate subnational grain yield forecasts for 56 regions located in two severely food insecure countries: Kenya and Somalia. We identify, for a given region and time of year, which, if any, product is the best indicator for end-of-season maize yields. Our analysis seeks to inform a real-world situation in which analysts have access to multiple regularly updated EO data products, but predictive skill corresponding to each may vary across these regions and throughout the season. We find that the most accurate predictions can be made for high-producing areas, but that the relationship between production and forecast accuracy diminishes in areas with yields averaging greater than one metric ton per hectare. However, while forecast accuracy is highest in high production areas, in many of these regions, the forecast accuracy of models using EO products is not better than a set of baseline models that do not use EO products. Overall, we find that rainfall is the best indicator in low-producing regions and that other EO products work best in areas where yields are relatively consistent, but production is still limited by environmental factors.
","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/ab5ccd","usgsCitation":"Davenport, F., Harrison, L., Shukla, S., Husak, G., Funk, C., and McNally, A., 2019, Using out-of-sample yield forecast experiments to evaluate which earth observation products best indicate end of season maize yields: Environmental Research Letters, v. 14, no. 2, 124095, 13 p., https://doi.org/10.1088/1748-9326/ab5ccd.","productDescription":"124095, 13 p.","ipdsId":"IP-101895","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":458900,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ab5ccd","text":"Publisher Index Page"},{"id":372947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Kenya, Somalia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 31.728515624999996,\n -5.615985819155327\n ],\n [\n 51.50390625,\n -5.615985819155327\n ],\n [\n 51.50390625,\n 10.833305983642491\n ],\n [\n 31.728515624999996,\n 10.833305983642491\n ],\n [\n 31.728515624999996,\n -5.615985819155327\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Davenport, Frank","contributorId":145816,"corporation":false,"usgs":false,"family":"Davenport","given":"Frank","email":"","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":783964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harrison, Laura","contributorId":192382,"corporation":false,"usgs":false,"family":"Harrison","given":"Laura","email":"","affiliations":[],"preferred":false,"id":784025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shukla, Shraddhanand","contributorId":145841,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","affiliations":[{"id":16255,"text":"Climate Hazards Group University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":783965,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Husak, Gregory","contributorId":145811,"corporation":false,"usgs":false,"family":"Husak","given":"Gregory","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":783966,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","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":783963,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McNally, Amy","contributorId":53225,"corporation":false,"usgs":true,"family":"McNally","given":"Amy","affiliations":[],"preferred":false,"id":784026,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70211054,"text":"70211054 - 2019 - Functional characterization and osmoregulatory role of the Na+/K+/2Cl--cotransporter (NKCC1) in the gill of sea lamprey (Petromyzon marinus), a basal vertebrate","interactions":[],"lastModifiedDate":"2020-07-13T13:51:22.896616","indexId":"70211054","displayToPublicDate":"2019-12-23T08:50:01","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":730,"text":"American Journal of Physiology - Regulatory, Integrative and Comparative Physiology","onlineIssn":"1522-1490","printIssn":"0363-6119","active":true,"publicationSubtype":{"id":10}},"title":"Functional characterization and osmoregulatory role of the Na+/K+/2Cl--cotransporter (NKCC1) in the gill of sea lamprey (Petromyzon marinus), a basal vertebrate","docAbstract":"The present study provides molecular and functional characterization of Na+/K+/2Cl- cotransporter (nkcc1/NKCC1) in the gills of sea lamprey, the most basal extant vertebrate with an osmoregulatory strategy. We report the full-length peptide sequence for the lamprey NKCC1, which we show to group strongly with and occupy a basal position among other vertebrate NKCC1 sequences. Lamprey nkcc1 mRNA were present in many tissues but was 5-fold higher in the gill than any other tissue. NKCC1 protein was only detected in the gill. Gill mRNA and protein abundances of NKCC1 and Na+/K+-ATPase (NKA) were significantly upregulated (20- to 200-fold) in late metamorphosis in freshwater, coinciding with the development of salinity tolerance, and were upregulated an additional 2-fold after acclimation to seawater. Immunohistochemistry revealed that NKCC1 in the gill is found in filamental ionocytes that develop during metamorphosis. Lamprey treated with bumetanide, a widely used pharmacological inhibitor of NKCC1, exhibited higher plasma Cl- and osmolality and reduced muscle water content after 24 h in seawater, but had no effect in FW. This work provides the first functional characterization of NKCC1 as having a functional role mechanism for branchial salt secretion in lampreys, providing evidence that this mode of Cl- secretion has been present among vertebrates for ~550 million years.","language":"English","publisher":"American Physiological Society","doi":"10.1152/ajpregu.00125.2019","usgsCitation":"Shaughnessy, C.A., and McCormick, S.D., 2019, Functional characterization and osmoregulatory role of the Na+/K+/2Cl--cotransporter (NKCC1) in the gill of sea lamprey (Petromyzon marinus), a basal vertebrate: American Journal of Physiology - Regulatory, Integrative and Comparative Physiology, v. 318, no. 1, p. R17-R29, https://doi.org/10.1152/ajpregu.00125.2019.","productDescription":"13 p.","startPage":"R17","endPage":"R29","ipdsId":"IP-107838","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":458904,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1152/ajpregu.00125.2019","text":"Publisher Index Page"},{"id":376301,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"318","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shaughnessy, Ciaran Alvar Seeland 0000-0003-2146-9126","orcid":"https://orcid.org/0000-0003-2146-9126","contributorId":228962,"corporation":false,"usgs":true,"family":"Shaughnessy","given":"Ciaran","email":"","middleInitial":"Alvar Seeland","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":792612,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":792613,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70205439,"text":"sir20195102 - 2019 - Simulation of groundwater flow and chloride transport in the “1,500-foot” sand, “2,400-foot” sand, and “2,800-foot” sand of the Baton Rouge area, Louisiana","interactions":[],"lastModifiedDate":"2022-04-22T21:50:43.452534","indexId":"sir20195102","displayToPublicDate":"2019-12-22T16:38:39","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":"2019-5102","displayTitle":"Simulation of Groundwater Flow and Chloride Transport in the “1,500-Foot” Sand, “2,400-Foot” Sand, and “2,800-Foot” Sand of the Baton Rouge Area, Louisiana","title":"Simulation of groundwater flow and chloride transport in the “1,500-foot” sand, “2,400-foot” sand, and “2,800-foot” sand of the Baton Rouge area, Louisiana","docAbstract":"Groundwater withdrawals since the 1940s have lowered water levels, altered groundwater-flow directions, and caused saltwater to intrude within some freshwater-containing sands of the fluvial-deltaic Southern Hills regional aquifer system beneath Baton Rouge, Louisiana. New interpretations of stratigraphic correlations amongst geophysical well logs were utilized to revise a hydrogeologic framework that delineates the depth and thickness variations of aquifers and confining units in the Southern Hills regional aquifer system. A groundwater-flow and chloride-transport model incorporating the revised framework was constructed to assess the effects of groundwater withdrawals on the rate and pathways of saltwater migration in the “1,500-foot” sand, “2,400-foot” sand, and the “2,800-foot” sand. Groundwater withdrawals reported since 1940 were compiled to specify annual average withdrawal rates through 2016 for 722 wells. Regional groundwater flow throughout the Southern Hills regional aquifer system was first simulated with MODFLOW, and flow-model parameters were calibrated to 8,810 water levels observed through 2016 by using the parameter-estimation code PEST++. Saltwater transport was subsequently simulated for the “1,500-foot” sand, “2,400-foot” sand, and the “2,800-foot” sand by using the variable-density code, SEAWAT. Chloride-concentration measurements were used as a proxy for saltwater to formulate the concentration initial conditions and calibrate the transport-model parameters.
Three groundwater-management scenarios were simulated to evaluate the effects of different groundwater withdrawals on future groundwater levels and saltwater concentrations in the “1,500-foot” sand, “2,400-foot” sand, and “2,800-foot” sand. All three scenarios simulated the period from 2017 through 2112 (96 years), and the water levels and concentrations simulated for 2047 and 2112 were compared among the scenarios. The first scenario simulated a continuation of groundwater withdrawals at 2016 rates and represents the “status quo” of groundwater withdrawals. The second scenario simulated the effects of discontinuing 10,620 gallons per minute (gal/min) of withdrawals from the “2,800-foot” sand, and the third scenario simulated reallocating 2,000 gal/min of withdrawals from the “1,500-foot” sand to the “2,800-foot” sand. Continuation of the “status quo” withdrawals results in lower water levels by 2047 around groundwater-withdrawal locations in the “1,500-foot” sand, “2,400-foot” sand, and “2,800-foot” sand. By 2112, water levels recover to higher levels as flow in the aquifer approaches equilibrium. Saltwater within the “1,500-foot” sand would continue migrating toward public-supply wells located 2.4 miles (mi) north of the Baton Rouge Fault, but a “scavenger well” that removes relatively concentrated water from the base of the “1,500-foot” sand attenuates chloride concentrations at the public-supply wells. Saltwater within the “2,400-foot” sand would continue to encroach on a well with large withdrawals and farther east within an area about 1 mi north of the Baton Rouge Fault. Saltwater within the “2,800-foot” sand would migrate northward toward withdrawal wells located about 3 mi north of the industrial district. Cessation of 10,620 gal/min of industrial withdrawals from the “2,800-foot” sand about 12 mi northwest of the industrial district (scenario 2) would cause a substantial water-level recovery in the “2,800-foot” sand in the area of discontinued withdrawals. Groundwater levels 3 mi north of the industrial district would be 25–30 feet higher in 2047 than predicted for the “status quo” withdrawals. Saltwater encroachment toward wells north of the industrial district would be slowed because of the decreased hydraulic gradient. Reallocating 2,000 gal/min of withdrawals from the “1,500-foot” sand to the “2,800-foot” sand 12 mi northwest of the industrial district (scenario 3) would have a negligible effect on water levels and chloride concentrations in the “1,500-foot” sand 15 mi to the south-southeast where saltwater is encroaching toward wells in the “1,500-foot” sand. Within the “2,800-foot” sand, the area of saltwater encroachment is only 3 mi from increased withdrawals in the “2,800-foot” sand, and water levels would be about 5 feet lower in 2047 than for the “status quo” scenario. A larger hydraulic gradient would cause slightly faster saltwater transport and higher chloride concentrations within this area of the “2,800-foot” sand.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195102","collaboration":"Prepared in cooperation with the Capital Area Groundwater Conservation Commission; the Louisiana Department of Transportation and Development, Public Works and Water Resources Division; and the City of Baton Rouge and Parish of East Baton Rouge","usgsCitation":"Heywood, C.E., Lindaman, M., and Lovelace, J.K., 2019, Simulation of groundwater flow and chloride transport in the “1,500-foot” sand, “2,400-foot” sand, and “2,800-foot” sand of the Baton Rouge area, Louisiana: U.S. Geological Survey Scientific Investigations Report 2019–5102, 49 p., https://doi.org/10.3133/sir20195102.","productDescription":"Report: ix, 49 p.; Data Release","numberOfPages":"63","onlineOnly":"N","ipdsId":"IP-099059","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":399545,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109561.htm"},{"id":370615,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5102/sir20195102.pdf","text":"Report","size":"22.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5102"},{"id":370616,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9URJ38Q","text":"USGS data release","description":"USGS Data Release","linkHelpText":"SEAWAT model archive of chloride transport in the “1,500-foot”, “2,400-foot”, and “2,800-foot” sands of the Baton Rouge Area, Louisiana"},{"id":370614,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5102/coverthb.jpg"}],"country":"United States","state":"Louisiana","city":"Baton Rouge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.75,\n 31.25\n ],\n [\n -90.5,\n 31.25\n ],\n [\n -90.5,\n 30.25\n ],\n [\n -91.75,\n 30.25\n ],\n [\n -91.75,\n 31.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park Drive, Suite 100
Nashville, TN 37211
The rate of groundwater flow past underground nuclear testing areas in Yucca Flat at the Nevada National Security Site, southern Nevada, was estimated using results from the ER-6-1-2 main multiple-well aquifer test (MWAT), done during February 5–July 23, 2004. Drawdowns in 13 observation wells were evaluated from pumping in well ER-6-1-2 main and used as observations in a regional groundwater-flow model to estimate the groundwater-flow rate. Flow from southern Yucca Flat regionally was constrained by detecting drawdown in Tracer Well 3, which is 33 miles south-southwest of pumping well ER-6-1-2 main. Predevelopment flow, the ER-6-1-2 main MWAT, and regional groundwater pumping were simulated in separate models that jointly informed estimates of transmissivity and specific-yield distributions. Predevelopment flow constrained groundwater-flow estimates from southern Yucca Flat because the steady-state model correctly simulated regional groundwater discharges in the Ash Meadows groundwater basin and the surrounding basins. Less than 600 acre-feet per year of groundwater moves from underground nuclear testing areas and flows south of well ER-6-1-2 main in southern Yucca Flat.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195038","collaboration":"Prepared in cooperation with the U.S. Department of Energy Office of Environmental Management, National Nuclear Security Administration, Nevada Site Office, under Interagency Agreement DE-EM0004969","usgsCitation":"Jackson, T.R., and Halford, K.J., 2019, Estimation of groundwater flow through Yucca Flat based on a multiple-well aquifer test at well ER-6–1–2 main, Nevada National Security Site, southern Nevada: U.S. Geological Survey Scientific Investigations Report 2019–5038, 27 p., https://doi.org/10.3133/sir20195038.\n","productDescription":"Report: vi, 27 p.; Data Release","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-098808","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":370390,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5038/coverthb.jpg"},{"id":370391,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5038/sir20195038.pdf","text":"Report","size":"3.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5038"},{"id":370392,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U2WG04","text":"USGS data release","linkHelpText":"Supplemental data for estimation of groundwater flow through Yucca Flat based on a multiple-well aquifer test at well ER-6–1–2 main, Nevada National Security Site, southern Nevada"}],"country":"United States","state":"Nevada","otherGeospatial":"Nevada National Security Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.633333,\n 37.283333\n ],\n [\n -116.633333,\n 36.966667\n ],\n [\n -116.45,\n 36.966667\n ],\n [\n -116.45,\n 37.283333\n ],\n [\n -116.633333,\n 37.283333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 95819
The clade comprising the soricid tribes Blarinellini (Blarinella) and Blarinini (Blarina and Cryptotis) is notable within the Soricidae (Eulipotyphla) for the large proportion of reportedly semifossorial species. To better define locomotor modes among species in these two tribes, we quantified purported locomotor adaptations by calculating 23 functional indices from postcranial measurements obtained from museum specimens of Blarina and Blarinella and published measurements for 16 species of Cryptotis. We then analyzed relative ambulatory–fossorial function of each species using principal component analyses and mean percentile rank (MPR) analysis of the indices. Species within the Blarinellini–Blarinini clade exhibit a graded series of morphologies with four primary functional groupings that we classified as “ambulatory,” “intermediate,” “semifossorial,” and “fossorial.” To obtain a preliminary overview of evolution of locomotor modes in this group, we mapped MPRs on a composite phylogeny and examined the resulting patterns. That analysis revealed that the most recent common ancestor of the Blarinellini–Blarinini clade most likely had an intermediate or semifossorial locomotor morphology. Individual subclades subsequently evolved either more ambulatory or more fossorial morphologies. Hence, evolution of locomotor traits within this clade is complex. Multiple shifts in locomotor mode likely occurred, and no single directional tendency is apparent either among the major modes or in levels of complexity.
","language":"English","publisher":"Oxford Academic Press","doi":"10.1093/jmammal/gyz098","usgsCitation":"Woodman, N., and Wilken, A.T., 2019, Comparative functional skeletal morphology among three genera of shrews: Implications for the evolution of locomotor behavior in the Soricinae (Eulipotyphla: Soricidae): Journal of Mammalogy, v. 100, no. 6, p. 1750-1764, https://doi.org/10.1093/jmammal/gyz098.","productDescription":"15 p.","startPage":"1750","endPage":"1764","ipdsId":"IP-108146","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":458923,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyz098","text":"Publisher Index Page"},{"id":370666,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","issue":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Woodman, Neal 0000-0003-2689-7373 nwoodman@usgs.gov","orcid":"https://orcid.org/0000-0003-2689-7373","contributorId":3547,"corporation":false,"usgs":true,"family":"Woodman","given":"Neal","email":"nwoodman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":778388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilken, Alec T.","contributorId":217703,"corporation":false,"usgs":false,"family":"Wilken","given":"Alec","email":"","middleInitial":"T.","affiliations":[{"id":39687,"text":"University of Missouri, Columbia","active":true,"usgs":false}],"preferred":false,"id":778389,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70205733,"text":"fs20193053 - 2019 - Assessment of coal resources and reserves in the Little Snake River coal field and Red Desert assessment area, Greater Green River Basin, Wyoming","interactions":[],"lastModifiedDate":"2022-04-19T21:19:35.302655","indexId":"fs20193053","displayToPublicDate":"2019-12-19T11:00:00","publicationYear":"2019","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":"2019-3053","displayTitle":"Assessment of Coal Resources and Reserves in the Little Snake River Coal Field and Red Desert Assessment Area, Greater Green River Basin, Wyoming","title":"Assessment of coal resources and reserves in the Little Snake River coal field and Red Desert assessment area, Greater Green River Basin, Wyoming","docAbstract":"The assessment of the Little Snake River coal field and Red Desert area covers approximately 2,300 square miles in the eastern portion of the Greater Green River Basin in south-central Wyoming. Coal-bearing formations are present throughout the Eocene, Paleocene, and Cretaceous strata in the assessment area. Paleogene-age coal beds are present in the Eocene Wasatch Formation and Paleocene Fort Union Formation. Cretaceous-age coal beds are present in the Lance, Almond, and Allen Ridge Formations. Utilizing over 4,000 data points, 55 individual coal beds were identified in the assessment area. Coal resources were calculated using geologic models generated from these data points, using criteria for minimum thickness and areal extent. The geologic modeling criteria indicated that 33 of the 55 individual coal beds had sufficient thickness and areal extent to be economically significant. Calculated original coal resources within the assessment area were approximately 73.2 billion short tons (BST). After excluding coal resources lost due to land use and technical restrictions, recoverable coal resources were approximately 19.37 BST, including 2.14 BST of coal resources that could be extracted using surface mining methods and 17.23 BST of coal resources that could be extracted using underground mining methods. Due to mining costs and projected low potential sales value of the coal resources, only approximately 167 million short tons (MST) can be classified as reserves, which is less than 1 percent of the recoverable coal resources
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193053","usgsCitation":"Shaffer, B.N., Pierce, P.E., Kinney, S.A., Olea, R., and Luppens, J.A., 2019, Assessment of coal resources and reserves in the Little Snake River coal field and Red Desert assessment area, Greater Green River Basin, Wyoming: U.S. Geological Survey Fact Sheet 2019–3053, 6 p., https://doi.org/10.3133/fs20193053.","productDescription":"6 p.","onlineOnly":"N","ipdsId":"IP-109360","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":370380,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3053/coverthb.jpg"},{"id":370382,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1836","text":"Coal Geology and Assessment of Resources and Reserves in the Little Snake River Coal Field and Red Desert Assessment Area, Greater Green River Basin, Wyoming"},{"id":370381,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3053/fs20193053.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3053"},{"id":399136,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109583.htm"}],"country":"United States","state":"Wyoming","otherGeospatial":"Little Snake River coal field, Red Desert assessment area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.35,\n 41\n ],\n [\n -107.3333,\n 41\n ],\n [\n -107.3333,\n 42.1078\n ],\n [\n -108.35,\n 42.1078\n ],\n [\n -108.35,\n 41\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046