In collaboration with the Bureau of Reclamation, the U.S. Geological Survey began a consistent monitoring program for endangered Lost River suckers (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Clear Lake Reservoir, California, in the fall of 2004. The program was intended to develop a more complete understanding of the Clear Lake Reservoir populations because they are important to the recovery efforts for these species. We report results from this ongoing program and include sampling efforts from fall 2008 to spring 2010. We summarize catches and passive integrated transponder (PIT) tagging efforts from trammel net sampling in fall 2008 and fall 2009, as well as detections of PIT-tagged suckers on remote antennas in the spawning tributary, Willow Creek, in spring 2009 and spring 2010.
\nTrammel net sampling resulted in a relatively low catch of suckers in fall 2008 and a high catch of suckers in fall 2009. We attribute the high catch of suckers to low lake levels in 2009, which concentrated fish. As in previous years, shortnose suckers made up the vast majority of the sucker catch and recaptures of previously PIT-tagged suckers were relatively uncommon. Across the 2 years, we captured and tagged 389 new Lost River suckers and 2,874 new shortnose suckers. Since the program began, we have tagged a total of about 1,200 Lost River suckers and 5,900 shortnose suckers that can be detected on the remote antennas in Willow Creek. Detections of tagged suckers were low in both spring 2009 and spring 2010. The magnitude of the spawning migration was presumably small in both years because of low flows in Willow Creek; detections were similar to a previous low-flow year (spring 2007) and much lower than previous years with higher flows (spring 2006 and spring 2008).
\nThe size composition of fish captured in fall trammel net sampling over time suggests that the Lost River sucker population probably has decreased in abundance from what it was in the early 2000s. Shortnose suckers are smaller than Lost River suckers, and we are unable to infer any trend in abundance for shortnose suckers because it is impossible to separate recruitment of small fish from size selectivity of the trammel nets. Nonetheless, the substantial catch of small shortnose suckers in 2009, especially females, indicates that some new individuals recruited to the population.
\nProblems with inferring status and population dynamics from size composition data can be overcome by a robust capture-recapture program that follows the histories of PIT-tagged individuals. Inferences from such a program are currently hindered by poor detection rates during spawning seasons with low flows in Willow Creek, which indicate that a key assumption of capture-recapture models is violated. We suggest that the most straightforward solution to this issue would be to collect detection data during the spawning season using remote PIT tag antennas in the strait between the west and east lobes of the lake.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131301","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hewitt, D.A., and Hayes, B., 2013, Monitoring of adult Lost River and shortnose suckers in Clear Lake Reservoir, California, 2008–2010: U.S. Geological Survey Open-File Report 2013-1301, iv, 18 p., https://doi.org/10.3133/ofr20131301.","productDescription":"iv, 18 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051993","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":280526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131301.JPG"},{"id":280524,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1301/pdf/ofr2013-1301.pdf","text":"Report","size":"900 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":280525,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1301/"}],"country":"United States","state":"California, Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.3831,41.78000 ], [ -122.3831,42.7534 ], [ -120.9161,42.7534 ], [ -120.9161,41.78000 ], [ -122.3831,41.78000 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b95be1e4b0a747b3e7e7a1","contributors":{"authors":[{"text":"Hewitt, David A. 0000-0002-5387-0275 dhewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-5387-0275","contributorId":3767,"corporation":false,"usgs":false,"family":"Hewitt","given":"David","email":"dhewitt@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":487664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayes, Brian S. 0000-0001-8229-4070","orcid":"https://orcid.org/0000-0001-8229-4070","contributorId":37022,"corporation":false,"usgs":true,"family":"Hayes","given":"Brian S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":487665,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70058790,"text":"pp1803 - 2013 - Selenium in ecosystems within the mountaintop coal mining and valley-fill region of southern West Virginia-assessment and ecosystem-scale modeling","interactions":[],"lastModifiedDate":"2013-12-23T14:47:58","indexId":"pp1803","displayToPublicDate":"2013-12-23T14:28:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1803","title":"Selenium in ecosystems within the mountaintop coal mining and valley-fill region of southern West Virginia-assessment and ecosystem-scale modeling","docAbstract":"Coal and associated waste rock are among environmental selenium (Se) sources that have the potential to affect reproduction in fish and aquatic birds. Ecosystems of southern West Virginia that are affected by drainage from mountaintop coal mines and valleys filled with waste rock in the Coal, Gauley, and Lower Guyandotte watersheds were assessed during 2010 and 2011. Sampling data from earlier studies in these watersheds (for example, Upper Mud River Reservoir) and other mining-affected watersheds also are included to assess additional hydrologic settings and food webs for comparison. Basin schematics give a comprehensive view of sampled species and Se concentration data specific to location and date. Food-web diagrams document the progression of Se trophic transfer across suspended particulate material, invertebrates, and fish for each site to serve as the basis for developing an ecosystem-scale model to predict Se exposure within the hydrologic conditions and food webs of southern West Virginia. This approach integrates a site-specific predator’s dietary exposure pathway into modeling to ensure an adequate link to Se toxicity and, thus, to species vulnerability.\n\nSite-specific fish abundance and richness data in streams documented various species of chub, shiner, dace, darters, bass, minnow, sunfish, sucker, catfish, and central stoneroller (Campostoma anomalum), mottled sculpin (Cottus bairdii), and least brook lamprey (Lampetra aepyptera). However, Se assessment species for streams, and hence, model species for streams, were limited to creek chub (Semotilus atromaculatus) and central stoneroller. Both of these species of fish are generally considered to have a high tolerance for environmental stress based on traditional comparative fish community assessment, with creek chub being present at all sites. Aquatic insects (mayfly, caddisfly, stonefly, dobsonfly, chironomid) were the main invertebrates sampled in streams. Collection of suspended particulate material acted as an integrator of organic-rich, fine-grained biomass present in streams.\n\nThe base-case food web modeled for streams was suspended particulate material to aquatic insect to creek chub, with comparative modeling of a direct particulate-to-stoneroller food web. Model species for a reservoir setting were based on an earlier study of bluegill sunfish (Lepomis macrochirus), green sunfish (Lepomis cyanellus), and largemouth bass (Micropterus salmoides). Several reservoir food webs were considered based on a variety of invertebrates (insect, snail, clam). For stream and reservoir settings, predicted Se concentrations in exposure scenarios showed a high degree of correlation (r2 = 0.91 for invertebrates and 0.75 for fish) with field observations of Se concentrations when modeling was initiated from suspended-particulate-material Se concentrations and model transfer parameters defined previously in the literature were used. These strong correlations validate the derived site-specific model and establish sufficient confidence that the predictions from the developed model can be quantitatively applied to the ecosystems in southern West Virginia.\n\nAn application of modeling used a metric describing the partitioning of Se between particulate material and dissolved phases (Kd) to allow determination of a dissolved Se concentration that would be necessary to attain a site-specific Se fish body burden. The operationally defined Kd quantifies the complex process of transformation at the base of a food web on a site-specific basis. The magnitude of this metric is known to vary with such factors as Se speciation, particulate-material type, and hydrology. This application (1) ties dissolved Se concentrations to fish tissue concentrations; (2) allows consideration of different choices for intervening site-specific exposure steps that set Se bioaccumulation, partitioning, and bioavailability; and (3) generates implications for management decisions that define protection through different regulatory pathways and guidelines. The range of model outcomes accounts for critical sources of variability and establishes whether site and food-web characterization were adequate to represent the dynamics of the system with certainty. This is especially true in terms of particulate-material phases at the base of the food web and utilization of Kd in different hydrologic settings. For streams, a range of field-derived Kdds were applied to food-web exposure scenarios within a framework of locational and hydrologic variables (area of stream basin; stream gradient and discharge) that may affect the magnitude of Kd. Overlaying even a coarse temporal scale that acknowledges variability in stream dissolved Se and Se speciation, such as through seasonal derivation of Kd, can substantially narrow model uncertainty.\n\nModeling that constrains the place and time of greatest ecosystem Se sensitivity within a specified food web gives insight into Se risk and identifies controlling management alternatives within a watershed or stream basin. If there is a range of hydrologic settings, specificity is needed to establish a hierarchy of in-stream and off-stream habitats for a watershed approach that takes into account Se-enriched water moving through different Kd and food web environments. If there is a range of predator vulnerabilities (measured as a combination of food-web Se biodynamics and response in Se toxicity tests) within the site-specific community of fish species to be protected, then choice of fish species is critical to protection because it determines the food web and, hence, the magnitude of biotransfer through which Se is modeled. Whether creek chub is representative of the vulnerability to Se of all fish species encountered within the study-site ecosystems will require additional species-specific data and analysis. A range of site-specific scenarios illustrated here set model outcomes, but the final quantitative evaluation of alternatives and their implications will be those generated through choices and guidance formulated by state and other agencies in their decisionmaking processes.\n\nProposed additions and refinements to the ecosystem-scale site-specific approach developed here include consideration of:\n\nmeasurement of temporally matched pairs of dissolved and suspended-particulate-material Se concentrations across a broader range of stream sites to expand the stream Kd database and to test the representativeness of a suspended-particulate-material sample within a stream;\ncharacterization of different phases of particulate material across seasons to better define the base of the food web and connect to invertebrate feeding;\nrefinement of model assumptions concerning dietary preferences and composition for fish to develop additional trophic transfer factors (TTFs) (for example, calculation of TTFinvertebrate composite for mixed diets);\nexpansion of modeling of fish species and their food webs to include Se-vulnerable species;\ntemporal characterization of a predator’s life cycle and habitat use as additional model layers to integrate with Se biodynamics in streams;\ninvestigation of the effect of stream gradient on Kd based on a finer scale than presented here in terms of such variables as residence time, watershed dilution, and physical habitat attributes (for example, amount of ponding versus run or riffle within a stream); and\nlinkage to discharge through use of stream gaging to record variability and enable model organization within water-year types and discharge seasons.\nInvestigating the presence and variability of prey and predator species in demographically open systems such as streams also is key to model outcomes given the overall environmental stressors (for example, general landscape change, food-web disruption, recolonization potential) imposed on the composition of biological communities in coal mining and valley-fill affected watersheds","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1803","usgsCitation":"Presser, T.S., 2013, Selenium in ecosystems within the mountaintop coal mining and valley-fill region of southern West Virginia-assessment and ecosystem-scale modeling: U.S. Geological Survey Professional Paper 1803, vi, 86 p., https://doi.org/10.3133/pp1803.","productDescription":"vi, 86 p.","numberOfPages":"96","additionalOnlineFiles":"N","ipdsId":"IP-051155","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":280523,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp1803.jpg"},{"id":280521,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1803/"},{"id":280522,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1803/pdf/pp1803.pdf"}],"country":"United States","state":"West Virginia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.8207,37.4749 ], [ -81.8207,38.6340 ], [ -80.1453,38.6340 ], [ -80.1453,37.4749 ], [ -81.8207,37.4749 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b95be2e4b0a747b3e7e7aa","contributors":{"authors":[{"text":"Presser, Theresa S. 0000-0001-5643-0147 tpresser@usgs.gov","orcid":"https://orcid.org/0000-0001-5643-0147","contributorId":2467,"corporation":false,"usgs":true,"family":"Presser","given":"Theresa","email":"tpresser@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":487377,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70059593,"text":"ofr20121024F - 2013 - Geologic framework for the national assessment of carbon dioxide storage resources: Arkoma Basin, Kansas Basins, and Midcontinent Rift Basin study areas","interactions":[{"subject":{"id":70059593,"text":"ofr20121024F - 2013 - Geologic framework for the national assessment of carbon dioxide storage resources: Arkoma Basin, Kansas Basins, and Midcontinent Rift Basin study areas","indexId":"ofr20121024F","publicationYear":"2013","noYear":false,"chapter":"F","title":"Geologic framework for the national assessment of carbon dioxide storage resources: Arkoma Basin, Kansas Basins, and Midcontinent Rift Basin study areas"},"predicate":"IS_PART_OF","object":{"id":70093199,"text":"ofr20121024 - 2012 - Geologic framework for the national assessment of carbon dioxide storage resources","indexId":"ofr20121024","publicationYear":"2012","noYear":false,"title":"Geologic framework for the national assessment of carbon dioxide storage resources"},"id":1}],"isPartOf":{"id":70093199,"text":"ofr20121024 - 2012 - Geologic framework for the national assessment of carbon dioxide storage resources","indexId":"ofr20121024","publicationYear":"2012","noYear":false,"title":"Geologic framework for the national assessment of carbon dioxide storage resources"},"lastModifiedDate":"2019-02-21T11:38:30","indexId":"ofr20121024F","displayToPublicDate":"2013-12-23T12:40:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1024","chapter":"F","title":"Geologic framework for the national assessment of carbon dioxide storage resources: Arkoma Basin, Kansas Basins, and Midcontinent Rift Basin study areas","docAbstract":"2007 Energy Independence and Security Act (Public Law 110–140) directs the U.S. Geological Survey (USGS) to conduct a national assessment of potential geologic storage resources for carbon dioxide (CO2). The methodology used by the USGS for the national CO2 assessment follows that of previous USGS work. This methodology is non-economic and intended to be used at regional to subbasinal scales. This report identifies and contains geologic descriptions of three storage assessment units (SAUs) in Upper Cambrian to Mississippian sedimentary rocks within the Arkoma Basin study area, and two SAUs in Upper Cambrian to Mississippian sedimentary rocks within the Kansas Basins study area. The Arkoma Basin and Kansas Basins are adjacent with very similar geologic units; although the Kansas Basins area is larger, the Arkoma Basin is more structurally complex. The report focuses on the characteristics, specified in the methodology, that influence the potential CO2 storage resource in the SAUs. Specific descriptions of the SAU boundaries as well as their sealing and reservoir units are included. Properties for each SAU, such as depth to top, gross thickness, porosity, permeability, groundwater quality, and structural reservoir traps, are usually provided to illustrate geologic factors critical to the assessment. Although assessment results are not contained in this report, the geologic information herein was employed, as specified in the USGS methodology, to calculate a probabilistic distribution of potential storage resources in each SAU. The Midcontinent Rift Basin study area was not assessed, because no suitable storage formations meeting our size, depth, reservoir quality, and regional seal guidelines were found. Figures in this report show study area boundaries along with the SAU boundaries and cell maps of well penetrations through sealing units into the top of the storage formations. The cell maps show the number of penetrating wells within one-square mile and are derived from interpretations of incompletely attributed well data and from a digital compilation that is known not to include all drilling. The USGS does not expect to know the location of all wells and cannot guarantee the amount of drilling through specific formations in any given cell shown on the cell maps.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Geologic framework for the national assessment of carbon dioxide storage resources (Open-File Report 2012-1024)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121024F","usgsCitation":"Buursink, M.L., Craddock, W.H., Blondes, M., Freeman, P.A., Cahan, S.M., DeVera, C.A., and Lohr, C., 2013, Geologic framework for the national assessment of carbon dioxide storage resources: Arkoma Basin, Kansas Basins, and Midcontinent Rift Basin study areas: U.S. Geological Survey Open-File Report 2012-1024, Report: x, 35 p.; 2 compressed ZIP files, https://doi.org/10.3133/ofr20121024F.","productDescription":"Report: x, 35 p.; 2 compressed ZIP files","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":280512,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2012/1024/f/downloads/Cell_C5056_C5062.zip"},{"id":280510,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1024/f/pdf/of2012-1024-F.pdf"},{"id":280513,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2012/1024/f/downloads/SAU_C5056_C5062.zip"},{"id":280511,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1024/f/","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":280514,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121024F.jpg"}],"projection":"Albers equal area","country":"United States","state":"Arkansas;Louisiana;Oklahoma;Texas","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.7129,31.3724 ], [ -95.7129,37.6664 ], [ -88.7476,37.6664 ], [ -88.7476,31.3724 ], [ -95.7129,31.3724 ] ] ] } } ] }","publicComments":"This report is Chapter F in Geologic framework for the national assessment of carbon dioxide storage resources. For more information, see Open File Report 2012-1024.","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b95bc0e4b0a747b3e7e724","contributors":{"authors":[{"text":"Buursink, Marc L. 0000-0001-6491-386X mbuursink@usgs.gov","orcid":"https://orcid.org/0000-0001-6491-386X","contributorId":3362,"corporation":false,"usgs":true,"family":"Buursink","given":"Marc","email":"mbuursink@usgs.gov","middleInitial":"L.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":487705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Craddock, William H. 0000-0002-4181-4735 wcraddock@usgs.gov","orcid":"https://orcid.org/0000-0002-4181-4735","contributorId":3411,"corporation":false,"usgs":true,"family":"Craddock","given":"William","email":"wcraddock@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":487706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blondes, Madalyn S. 0000-0003-0320-0107 mblondes@usgs.gov","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":3598,"corporation":false,"usgs":true,"family":"Blondes","given":"Madalyn S.","email":"mblondes@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":487707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Freeman, Phillip A. 0000-0002-0863-7431","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":84661,"corporation":false,"usgs":true,"family":"Freeman","given":"Phillip","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":487711,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cahan, Steven M. 0000-0002-4776-3668 scahan@usgs.gov","orcid":"https://orcid.org/0000-0002-4776-3668","contributorId":4529,"corporation":false,"usgs":true,"family":"Cahan","given":"Steven","email":"scahan@usgs.gov","middleInitial":"M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":487710,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeVera, Christina A. 0000-0002-4691-6108 cdevera@usgs.gov","orcid":"https://orcid.org/0000-0002-4691-6108","contributorId":3845,"corporation":false,"usgs":true,"family":"DeVera","given":"Christina","email":"cdevera@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":487708,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lohr, Celeste D. 0000-0001-6287-9047 clohr@usgs.gov","orcid":"https://orcid.org/0000-0001-6287-9047","contributorId":3866,"corporation":false,"usgs":true,"family":"Lohr","given":"Celeste D.","email":"clohr@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":487709,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70055710,"text":"sim3259 - 2013 - Base of the upper layer of the phase-three Elkhorn-Loup groundwater-flow model, north-central Nebraska","interactions":[],"lastModifiedDate":"2013-12-23T11:24:50","indexId":"sim3259","displayToPublicDate":"2013-12-23T11:01:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3259","title":"Base of the upper layer of the phase-three Elkhorn-Loup groundwater-flow model, north-central Nebraska","docAbstract":"The Elkhorn and Loup Rivers in Nebraska provide water for irrigation, recreation, hydropower production, aquatic life, and municipal water systems for the Omaha and Lincoln metropolitan areas. Groundwater is another important resource in the region and is extracted primarily for agricultural irrigation. Water managers of the area are interested in balancing and sustaining the long-term uses of these essential surface-water and groundwater resources. Thus, a cooperative study was established in 2006 to compile reliable data describing hydrogeologic properties and water-budget components and to improve the understanding of stream-aquifer interactions in the Elkhorn and Loup River Basins. A groundwater-flow model was constructed as part of the first two phases of that study as a tool for understanding the effect of groundwater pumpage on stream base flow and the effects of management strategies on hydrologically connected groundwater and surface-water supplies. The third phase of the study was implemented to gain additional geologic knowledge and update the ELM with enhanced water-budget information and refined discretization of the model grid and stress periods. As part of that effort, the ELM is being reconstructed to include two vertical model layers, whereas phase-one and phase-two simulations represented the aquifer system using one vertical model layer. This report presents a map of and methods for developing the elevation of the base of the upper model layer for the phase-three ELM. Digital geospatial data of elevation contours and geologic log sites used to estimate elevation contours are available as part of this report.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3259","collaboration":"Prepared in cooperation with the Lower Elkhorn, Lower Loup, Lower Platte North, Middle Niobrara, and Upper Elkhorn Natural Resources Districts","usgsCitation":"Stanton, J.S., 2013, Base of the upper layer of the phase-three Elkhorn-Loup groundwater-flow model, north-central Nebraska: U.S. Geological Survey Scientific Investigations Map 3259, Map: 49 inches x 39 inches; Associated Metadata and GIS files, https://doi.org/10.3133/sim3259.","productDescription":"Map: 49 inches x 39 inches; Associated Metadata and GIS files","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-043054","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":280507,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3259.gif"},{"id":280504,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/sim2013-3259_sites.xml"},{"id":280503,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3259/pdf/sim3259.pdf"},{"id":280505,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/sim2013-3259_contours.xml"},{"id":280506,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3259/"}],"country":"United States","state":"Nebraska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -102.4640,40.5000 ], [ -102.4640,43.0000 ], [ -97.2839,43.0000 ], [ -97.2839,40.5000 ], [ -102.4640,40.5000 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b95b5fe4b0a747b3e7e599","contributors":{"authors":[{"text":"Stanton, Jennifer S. 0000-0002-2520-753X jstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-2520-753X","contributorId":830,"corporation":false,"usgs":true,"family":"Stanton","given":"Jennifer","email":"jstanton@usgs.gov","middleInitial":"S.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486231,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70059317,"text":"ofr20121024D - 2013 - Geologic framework for the national assessment of carbon dioxide storage resources: Columbia Basin of Oregon, Washington, and Idaho, and the Western Oregon-Washington basins","interactions":[{"subject":{"id":70059317,"text":"ofr20121024D - 2013 - Geologic framework for the national assessment of carbon dioxide storage resources: Columbia Basin of Oregon, Washington, and Idaho, and the Western Oregon-Washington basins","indexId":"ofr20121024D","publicationYear":"2013","noYear":false,"chapter":"D","title":"Geologic framework for the national assessment of carbon dioxide storage resources: Columbia Basin of Oregon, Washington, and Idaho, and the Western Oregon-Washington basins"},"predicate":"IS_PART_OF","object":{"id":70093199,"text":"ofr20121024 - 2012 - Geologic framework for the national assessment of carbon dioxide storage resources","indexId":"ofr20121024","publicationYear":"2012","noYear":false,"title":"Geologic framework for the national assessment of carbon dioxide storage resources"},"id":1}],"isPartOf":{"id":70093199,"text":"ofr20121024 - 2012 - Geologic framework for the national assessment of carbon dioxide storage resources","indexId":"ofr20121024","publicationYear":"2012","noYear":false,"title":"Geologic framework for the national assessment of carbon dioxide storage resources"},"lastModifiedDate":"2022-12-12T23:22:33.273379","indexId":"ofr20121024D","displayToPublicDate":"2013-12-20T13:16:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1024","chapter":"D","title":"Geologic framework for the national assessment of carbon dioxide storage resources: Columbia Basin of Oregon, Washington, and Idaho, and the Western Oregon-Washington basins","docAbstract":"The 2007 Energy Independence and Security Act (Public Law 110–140) directs the U.S. Geological Survey (USGS) to conduct a national assessment of potential geologic storage resources for carbon dioxide (CO2). The methodology used by the USGS for the national CO2 assessment follows that of previous USGS work. The methodology is non-economic and intended to be used at regional to subbasinal scales. This report identifies and contains geologic descriptions of three storage assessment units (SAUs) in Eocene and Oligocene sedimentary rocks within the Columbia, Puget, Willapa, Astoria, Nehalem, and Willamette Basins of Oregon, Washington, and Idaho, and focuses on the characteristics, specified in the methodology, that influence the potential CO2 storage resource in those SAUs. Specific descriptions of the SAU boundaries as well as their sealing and reservoir units are included. Properties for each SAU, such as depth to top, gross thickness, porosity, permeability, groundwater quality, and structural reservoir traps, are provided to illustrate geologic factors critical to the assessment. The designated sealing unit in the Columbia Basin is tentatively chosen to be the ubiquitous and thick Miocene Columbia River Basalt Group. As a result of uncertainties regarding the seal integrity of the Columbia River Basalt Group, the SAUs were not quantitatively assessed. Figures in this report show SAU boundaries and cell maps of well penetrations through sealing units into the top of the storage formations. The cell maps show the number of penetrating wells within one square mile and are derived from interpretations of incompletely attributed well data, a digital compilation that is known not to include all drilling. The USGS does not expect to know the location of all wells and cannot guarantee the amount of drilling through specific formations in any given cell shown on the cell maps.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Geologic framework for the national assessment of carbon dioxide storage resources (Open-File Report 2012-1024)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121024D","usgsCitation":"Covault, J.A., Blondes, M., Cahan, S.M., DeVera, C.A., Freeman, P., and Lohr, C., 2013, Geologic framework for the national assessment of carbon dioxide storage resources: Columbia Basin of Oregon, Washington, and Idaho, and the Western Oregon-Washington basins: U.S. Geological Survey Open-File Report 2012-1024, Report: vi, 19 p.; Data Downloads, https://doi.org/10.3133/ofr20121024D.","productDescription":"Report: vi, 19 p.; Data Downloads","numberOfPages":"25","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":164,"text":"Central Energy Resources Science 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anomala","interactions":[],"lastModifiedDate":"2013-12-20T09:52:04","indexId":"70059275","displayToPublicDate":"2013-12-20T09:47:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Laboratory-derived temperature preference and effect on the feeding rate and survival of juvenile Hemimysis anomala","docAbstract":"Hemimysis anomala is a warm-water mysid that invaded the Great Lakes region in 2006 and has since rapidly spread throughout the basin. We conducted three laboratory experiments to better define the temperature preference, tolerance limits, and temperature effects on feeding rates of juvenile Hemimysis, using individuals acclimated to mid (16 °C) and upper (22 °C) preferred temperature values previously reported for the species. For temperature preference, we fit a two-parameter Gaussian (μ, σ) function to the experimental data, and found that the peak values (μ, interpreted as the preference temperature) were 22.0 °C (SE 0.25) when acclimated to 16 and 21.9 °C (SE 0.38) when acclimated to 22 °C, with the σ-values of the curves at 2.6 and 2.5 °C, respectively. No mysids were observed in temperatures below 10 or above 28 °C in these preference experiments. In short-term tolerance experiments for temperatures between 4 and 32 °C, all mysids died within 8 h at 30.2 °C for 16 °C acclimated mysids, and at 31.8 °C for 22 °C acclimated mysids. No lower lethal limit was found. Feeding rates increased with temperature from an average of 4 Bosmina eaten per hour at 5 °C to 19 Bosmina eaten per hour at 27 °C. The results of our experiments indicate an optimal temperature for Hemimysis between 21 and 27 °C, which corresponds with temperatures during periods of high population growth in the field. These results contribute a better understanding of this species' biological response to temperature that will help guide field studies and inform bioenergetics modeling.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Great Lakes Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2013.09.006","usgsCitation":"Sun, J., Rudstam, L.S., Boscarino, B.T., Walsh, M.G., and Lantry, B.F., 2013, Laboratory-derived temperature preference and effect on the feeding rate and survival of juvenile Hemimysis anomala: Journal of Great Lakes Research, v. 39, no. 4, p. 630-636, https://doi.org/10.1016/j.jglr.2013.09.006.","productDescription":"7 p.","startPage":"630","endPage":"636","numberOfPages":"7","ipdsId":"IP-043550","costCenters":[{"id":357,"text":"Lake Ontario Biological Station","active":false,"usgs":true}],"links":[{"id":280453,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280452,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jglr.2013.09.006"}],"country":"United States","state":"New York","otherGeospatial":"Seneca Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76.972683,42.387703 ], [ -76.972683,42.869365 ], [ -76.859287,42.869365 ], [ -76.859287,42.387703 ], [ -76.972683,42.387703 ] ] ] } } ] }","volume":"39","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd638ce4b0b290850fedd9","contributors":{"authors":[{"text":"Sun, Jennifer","contributorId":106005,"corporation":false,"usgs":true,"family":"Sun","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":487559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rudstam, Lars S.","contributorId":67402,"corporation":false,"usgs":true,"family":"Rudstam","given":"Lars","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":487556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boscarino, Brent T.","contributorId":104361,"corporation":false,"usgs":true,"family":"Boscarino","given":"Brent","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":487558,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walsh, Maureen G.","contributorId":92506,"corporation":false,"usgs":true,"family":"Walsh","given":"Maureen","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":487557,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lantry, Brian F. 0000-0001-8797-3910 bflantry@usgs.gov","orcid":"https://orcid.org/0000-0001-8797-3910","contributorId":3435,"corporation":false,"usgs":true,"family":"Lantry","given":"Brian","email":"bflantry@usgs.gov","middleInitial":"F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":487555,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70048980,"text":"sir20135202 - 2013 - Land-cover effects on the fate and transport of surface-applied antibiotics and 17-beta-estradiol on a sandy outwash plain, Anoka County, Minnesota, 2008–09","interactions":[],"lastModifiedDate":"2013-12-20T07:37:19","indexId":"sir20135202","displayToPublicDate":"2013-12-20T07:20:39","publicationYear":"2013","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":"2013-5202","title":"Land-cover effects on the fate and transport of surface-applied antibiotics and 17-beta-estradiol on a sandy outwash plain, Anoka County, Minnesota, 2008–09","docAbstract":"A plot-scale field experiment on a sandy outwash plain in Anoka County in east-central Minnesota was used to investigate the fate and transport of two antibiotics, sulfamethazine (SMZ) and sulfamethoxazole (SMX), and a hormone, 17-beta-estradiol (17BE), in four land-cover types: bare soil, corn, hay, and prairie. The SMZ, SMX, and 17BE were applied to the surface of five plots of each land-cover type in May 2008 and again in April 2009. The cumulative application rate was 16.8 milligrams per square meter (mg/m2) for each antibiotic and 0.6 mg/m2 for 17BE. Concentrations of each chemical in plant-tissue, soil, soil-water, and groundwater samples were determined by using enzyme-linked immunosorbent assay (ELISA) kits. Soil-water and groundwater sampling events were scheduled to capture the transport of SMZ, SMX, and 17BE during two growing seasons. Soil and plant-tissue sampling events were scheduled to identify the fate of the parent chemicals of SMZ, SMX, and 17BE in these matrices after two chemical applications. Areal concentrations (mg/m2) of SMZ and SMX in soil tended to decrease in prairie plots in the 8 weeks after the second chemical application, from April 2009 to June 2009, but not in other land-cover types. During these same 8 weeks, prairie plots produced more aboveground biomass and had extracted more water from the upper 125 centimeters of the soil profile compared to all other land-cover types. Areal concentrations of SMZ and SMX in prairie plant tissue did not explain the temporal changes in areal concentrations of these chemicals in soil. The areal concentrations of SMZ and SMX in the aboveground plant tissues in June 2009 and August 2009 were much lower, generally two to three orders of magnitude, than the areal concentrations of these chemicals in soil. Pooling all treatment plot data, the median areal concentration of SMZ and SMX in plant tissues was 0.01 and 0.10 percent of the applied chemical mass compared to 22 and 12 percent in soil, respectively. Furthermore, areal concentrations of SMZ and SMX in plant-tissue samples were variable, and did not differ significantly between control and treatment plots within each land-cover type. SMZ was detected in 23 percent of soil-water samples and in 16 percent of groundwater samples collected between October 2008 and October 2009 in treatment plots, indicating that surface-applied SMZ leached below the rooting zone and reached groundwater. SMX was detected in only 1 percent of soil-water and groundwater samples during this same time period. In contrast to the antibiotics, 17BE was not reliably detected in soil samples. Additionally, ELISA-determined 17BE concentrations in plant-tissue, soil-water, and groundwater samples indicated the presence of chemicals that were not applied as part of this experiment [17BE from an external source or other chemical(s) that interfered with the 17BE ELISA kits].","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135202","collaboration":"Prepared in cooperation with the College of Biological Sciences of the University of Minnesota and the Legislative-Citizen Commission on Minnesota Resources","usgsCitation":"Trost, J.J., Kiesling, R.L., Erickson, M., Rose, P.J., and Elliott, S.M., 2013, Land-cover effects on the fate and transport of surface-applied antibiotics and 17-beta-estradiol on a sandy outwash plain, Anoka County, Minnesota, 2008–09: U.S. Geological Survey Scientific Investigations Report 2013-5202, Report: x, 51 p.; Downloads Directory, https://doi.org/10.3133/sir20135202.","productDescription":"Report: x, 51 p.; 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Sequencing efforts showed that some pigeon feces from California contained sequences similar to C. marimammalium found in gull feces. These data suggest that the prevalence, geographic scope, and ecology of C. marimammalium in host birds other than gulls require further investigation. This study represents an important first step in the multi-laboratory assessment of these methods and highlights the need to broaden and standardize additional evaluations, including environmentally relevant target concentrations in ambient waters from diverse geographic regions.
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Resource managers must balance the benefits of energy development with the potential consequences for ecological resources and ecosystem services. To facilitate access to geospatial data related to energy resources, energy infrastructure, and natural resources that may be affected by energy development, the U.S. Geological Survey has developed an online Interactive Energy Atlas (Energy Atlas) for Colorado and New Mexico. The Energy Atlas is designed to meet the needs of varied users who seek information about energy in the western United States. The Energy Atlas has two primary capabilities: a geographic information system (GIS) data viewer and an interactive map gallery. The GIS data viewer allows users to preview and download GIS data related to energy potential and development in Colorado and New Mexico. The interactive map gallery contains a collection of maps that compile and summarize thematically related data layers in a user-friendly format. The maps are dynamic, allowing users to explore data at different resolutions and obtain information about the features being displayed. The Energy Atlas also includes an interactive decision-support tool, which allows users to explore the potential consequences of energy development for species that vary in their sensitivity to disturbance.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133112","usgsCitation":"Carr, N.B., Ignizio, D., Diffendorfer, J., Latysh, N., Matherne, A.M., Linard, J.I., Leib, K.J., and Hawkins, S.J., 2013, Interactive energy atlas for Colorado and New Mexico: an online resource for decisionmakers: U.S. Geological Survey Fact Sheet 2013-3112, 2 p., https://doi.org/10.3133/fs20133112.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-045619","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":280402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133112.jpg"},{"id":280400,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3112/"},{"id":280401,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3112/pdf/fs2013-3112.pdf"}],"country":"United States","state":"Colorado;New Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.06,31.33 ], [ -109.06,41.0 ], [ -102.04,41.0 ], [ -102.04,31.33 ], [ -109.06,31.33 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b2c405e4b08e3289f15709","contributors":{"authors":[{"text":"Carr, Natasha B. 0000-0002-4842-0632 carrn@usgs.gov","orcid":"https://orcid.org/0000-0002-4842-0632","contributorId":1918,"corporation":false,"usgs":true,"family":"Carr","given":"Natasha","email":"carrn@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":486345,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ignizio, Drew A. 0000-0001-8054-5139 dignizio@usgs.gov","orcid":"https://orcid.org/0000-0001-8054-5139","contributorId":4822,"corporation":false,"usgs":true,"family":"Ignizio","given":"Drew A.","email":"dignizio@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":486348,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":486346,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Latysh, Natalie 0000-0003-0149-3962 nlatysh@usgs.gov","orcid":"https://orcid.org/0000-0003-0149-3962","contributorId":1356,"corporation":false,"usgs":true,"family":"Latysh","given":"Natalie","email":"nlatysh@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":5060,"text":"Data Preservation Program","active":true,"usgs":true}],"preferred":true,"id":486343,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Matherne, Ann Marie","contributorId":73909,"corporation":false,"usgs":true,"family":"Matherne","given":"Ann","email":"","middleInitial":"Marie","affiliations":[],"preferred":false,"id":486349,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Linard, Joshua I. jilinard@usgs.gov","contributorId":1465,"corporation":false,"usgs":true,"family":"Linard","given":"Joshua","email":"jilinard@usgs.gov","middleInitial":"I.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486344,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Leib, Kenneth J. 0000-0002-0373-0768 kjleib@usgs.gov","orcid":"https://orcid.org/0000-0002-0373-0768","contributorId":701,"corporation":false,"usgs":true,"family":"Leib","given":"Kenneth","email":"kjleib@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":486342,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hawkins, Sarah J. 0000-0002-1878-9121 shawkins@usgs.gov","orcid":"https://orcid.org/0000-0002-1878-9121","contributorId":4818,"corporation":false,"usgs":true,"family":"Hawkins","given":"Sarah","email":"shawkins@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":486347,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70049023,"text":"fs20133058 - 2013 - The 3D Elevation Program: summary for Florida","interactions":[],"lastModifiedDate":"2016-08-17T16:00:47","indexId":"fs20133058","displayToPublicDate":"2013-12-18T11:04:00","publicationYear":"2013","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":"2013-3058","title":"The 3D Elevation Program: summary for Florida","docAbstract":"Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Florida, elevation data are critical for natural resources conservation; flood risk management; infrastructure and construction management; coastal zone management; sea level rise and subsidence; wildfire management, planning, and response; and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.
\nThe National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios.The new 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the OMB Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133058","usgsCitation":"Carswell, W., 2013, The 3D Elevation Program: summary for Florida: U.S. Geological Survey Fact Sheet 2013-3058, 2 p., https://doi.org/10.3133/fs20133058.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-046393","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":280399,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133058.jpg"},{"id":280397,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3058/"},{"id":280398,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3058/pdf/fs2013-3058.pdf","text":"Report","size":"407 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United 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During summer, groundwater discharge is a source of cold water to streams and typically cools the surface water into which it discharges and buffers diurnal temperature fluctuations. Near-streambed temperatures were averaged over 1-m-long sections of cable during 1-minute periods every 30 minutes for 1-week periods using a fiber-optic distributed temperature sensor positioned on top of the streambed. The position of the fiber-optic cable was surveyed with a Global Positioning System. Stream temperatures and survey data are presented as Microsoft Excel® files consisting of date and time, water temperature, and geographical coordinates.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds807","collaboration":"Prepared in cooperation with the Swinomish Indian Tribal Community","usgsCitation":"Gendaszek, A.S., and Opatz, C.C., 2013, Thermal profiles for reaches of Snee-Oosh and Fornsby Creeks, Swinomish Indian Reservation, northwestern Washington, July 2013: U.S. Geological Survey Data Series 807, Report: iv, 5 p.; Tables 1-4, https://doi.org/10.3133/ds807.","productDescription":"Report: iv, 5 p.; Tables 1-4","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052762","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":280391,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds807.GIF"},{"id":280389,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/807/pdf/ds807.pdf"},{"id":280390,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/807/downloads/ds807_tables.xlsx"},{"id":280388,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/807/"}],"scale":"100000","projection":"Washington State Plane North FIPS","datum":"North American Datum of 1983","country":"United States","state":"Washington","otherGeospatial":"Fornsby Creek;Snee-oosh Creek;Swinomish Indian Reservation","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.591005,48.369938 ], [ -122.591005,48.466653 ], [ -122.48269,48.466653 ], [ -122.48269,48.369938 ], [ -122.591005,48.369938 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b2c406e4b08e3289f15718","contributors":{"authors":[{"text":"Gendaszek, Andrew S. 0000-0002-2373-8986 agendasz@usgs.gov","orcid":"https://orcid.org/0000-0002-2373-8986","contributorId":3509,"corporation":false,"usgs":true,"family":"Gendaszek","given":"Andrew","email":"agendasz@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Opatz, Chad C. 0000-0002-5272-0195 copatz@usgs.gov","orcid":"https://orcid.org/0000-0002-5272-0195","contributorId":48857,"corporation":false,"usgs":true,"family":"Opatz","given":"Chad","email":"copatz@usgs.gov","middleInitial":"C.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":486892,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70193776,"text":"70193776 - 2013 - Catchment-scale stormwater management via economic incentives – An overview and lessons-learned","interactions":[],"lastModifiedDate":"2017-12-19T10:47:30","indexId":"70193776","displayToPublicDate":"2013-12-18T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Catchment-scale stormwater management via economic incentives – An overview and lessons-learned","docAbstract":"Long-term field studies of the effectiveness and sustainability of decentralized stormwater management are rare. 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Under the guidelines and regulations that have been developed to protect and restore water-quality in the Chesapeake Bay, the six State jurisdictions that fall within the Chesapeake Bay watershed are required to report their progress in promoting agricultural conservation practices to the CBP Partnership on an annual basis. The installation and adoption of agricultural best management practices is supported by technical and financial assistance from both Federal and State conservation programs. The farm enrollment data for USDA conservation programs are confidential, but agencies can obtain access to the privacy-protected data if they are established as USDA Conservation Cooperators. The datasets can also be released to the public if they are first aggregated to protect farmer privacy. In 2012, the USGS used its Conservation Cooperator status to obtain implementation data for conservation programs sponsored by the USDA Natural Resources Conservation Service (NRCS) and the USDA Farm Service Agency (FSA) for farms within the Chesapeake Bay watershed. Three jurisdictions (Delaware, Pennsylvania, and West Virginia) used the USGS-provided aggregated dataset to report conservation progress in 2012, whereas the remaining three jurisdictions (Maryland, New York, and Virginia) used jurisdictional Conservation Cooperator Agreements to obtain privacy-protected data directly from the USDA. 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}\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b172bfe4b0d9b3252245ec","contributors":{"authors":[{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":9391,"corporation":false,"usgs":true,"family":"Hively","given":"W. Dean","affiliations":[],"preferred":false,"id":487265,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Devereux, Olivia H.","contributorId":97238,"corporation":false,"usgs":true,"family":"Devereux","given":"Olivia","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":487267,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Claggett, Peter R. 0000-0002-5335-2857 pclaggett@usgs.gov","orcid":"https://orcid.org/0000-0002-5335-2857","contributorId":176287,"corporation":false,"usgs":true,"family":"Claggett","given":"Peter","email":"pclaggett@usgs.gov","middleInitial":"R.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":487266,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70056038,"text":"sir20135209 - 2013 - A preliminary assessment of streamflow gains and losses for selected stream reaches in the lower Guadalupe River Basin, Texas, 2010-12","interactions":[],"lastModifiedDate":"2016-08-05T13:18:32","indexId":"sir20135209","displayToPublicDate":"2013-12-17T12:40:00","publicationYear":"2013","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":"2013-5209","title":"A preliminary assessment of streamflow gains and losses for selected stream reaches in the lower Guadalupe River Basin, Texas, 2010-12","docAbstract":"The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers–Fort Worth District, the Texas Water Development Board, the Guadalupe-Blanco River Authority, and the Edwards Aquifer Authority, investigated streamflow gains and losses in the lower Guadalupe River Basin during four selected base-flow periods in March 2010, April 2011, August 2011, and, for a stream reach between Seguin, Tex., and Gonzales, Tex., in September 2012. Major sources of streamflow in this basin include releases from Canyon Lake, inflow from major springs (Comal Springs, San Marcos Springs, and Hueco Springs), and base flow (groundwater seeping to streams). Streamflow and spring-flow data were collected at 35 streamflow-gaging stations (including 6 deployed for this study) during the base-flow periods. This report describes streamflow in the lower Guadalupe River Basin, which consists of the Guadalupe River drainage basin downstream from Canyon Lake to the Guadalupe River near Tivoli, Tex.
\nStreamflow conditions in the lower Guadalupe River Basin were analyzed by computing surface-water budgets for reaches of the lower Guadalupe River and tributary streams. Streamflow gains and losses were mapped for reaches where the computed gain or loss was greater than the uncertainty in the computed streamflow at the upstream and downstream ends of the reach.
\nDuring the March 15–21, 2010, base-flow period, five reaches had gains greater than the uncertainty in the computed streamflow, including reach 1 on the Guadalupe River, which gained 130 cubic feet per second (ft3/s), and reach 3 on the Comal River, which gained 359 ft3/s. Streamflow gains during March 2010 primarily were derived from (1) inflow from the Edwards aquifer outcrop, including Hueco Springs and Comal Springs; (2) flow conveyed through the alluvium of the streambed; (3) inflows from the Carrizo-Wilcox aquifer and the Yegua Jackson aquifer; and (4) groundwater inflows from the Gulf Coast aquifer, which are enhanced by seepage losses from Coleto Creek Reservoir. During this base-flow period, none of the reaches had a loss greater in magnitude than the uncertainty in the computed streamflow.
\nDuring the April 10–16, 2011, base-flow period, three reaches had gains greater than the uncertainty in the computed streamflow. Among these three reaches were reach 1 on the Guadalupe River, which gained 40.7 ft3/s, and reach 3 on the Comal River, which gained 271 ft3/s—reaches where streamflow gains were also measured in March 2010. Streamflow gains during April 2011 primarily were derived from (1) inflow from the Edwards aquifer outcrop, including Hueco Springs and Comal Springs; and (2) inflows from the Carrizo-Wilcox aquifer. During this base-flow period, three reaches had losses greater in magnitude than the uncertainty in the computed streamflow. A reach of the Blanco River near Kyle, Tex. (reach 10), lost 18.7 cubic feet per second (ft3/s). Much of this loss likely entered the groundwater system through the numerous faults that intersect the stream channel northwest of Kyle. The reach that included the confluence of the Guadalupe and San Marcos Rivers (reach 17) lost 155 ft3/s, likely as recharge to the Sparta and Queen City aquifers.
\nDuring the August 19–25, 2011, base-flow period, three reaches had gains greater than the uncertainty in the computed streamflow, including reach 3 on the Comal River (168 ft3/s gain), which was one of the reaches where gains in streamflow also were measured in March 2010 and April 2011. Streamflow gains in August 2011 were primarily from (1) inflows from Comal Springs, (2) inflows from the Yegua Jackson aquifer, and (3) groundwater inflows from the Gulf Coast aquifer, which are enhanced by seepage losses from Coleto Creek Reservoir. During this base-flow period, five reaches had losses greater in magnitude than the uncertainty in the computed streamflow. The reach including the confluence of the Guadalupe and Comal Rivers lost 82.8 ft3/s. Much of that loss likely seeped into the local groundwater system. The reach of the Guadalupe River south of New Braunfels, Tex., to Seguin, Tex., lost 53.5 ft3/s. Part of that loss may have been from seepage through streambed alluvium. Reaches 9 and 10 of the Blanco River near Kyle lost 2.20 and 6.60 ft3/s, respectively, likely as infiltration through numerous faults intersecting the stream channel northwest of Kyle. Plum Creek between Lockhart, Tex., and Luling, Tex., lost 2.11 ft3/s, likely as recharge to the Carrizo-Wilcox aquifer. A base-flow period during September 22–28, 2012, was studied for the reach of the Guadalupe River between Seguin and Gonzalez, including flows from San Marcos River and Plum Creek. During this period, for the Guadalupe River reach between Seguin and Oak Forest, no computed gains or losses were greater in magnitude than the uncertainty in the computed streamflow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135209","issn":"2328-0328","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers–Fort Worth District, the Texas Water Development Board, the Guadalupe-Blanco River Authority, and the Edwards Aquifer Authority","usgsCitation":"Wehmeyer, L.L., Winters, K.E., and Ockerman, D.J., 2013, A preliminary assessment of streamflow gains and losses for selected stream reaches in the lower Guadalupe River Basin, Texas, 2010-12: U.S. Geological Survey Scientific Investigations Report 2013-5209, v, 30 p., https://doi.org/10.3133/sir20135209.","productDescription":"v, 30 p.","numberOfPages":"39","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2010-01-01","temporalEnd":"2012-12-01","ipdsId":"IP-050892","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":280374,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135209.jpg"},{"id":280372,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5209/"},{"id":280373,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5209/pdf/sir2013-5209.pdf"}],"scale":"100000","datum":"North American Datum of 1983","country":"United States","state":"Texas","otherGeospatial":"Guadalupe River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -100.0,28.0 ], [ -100.0,30.2 ], [ -96.0,30.2 ], [ -96.0,28.0 ], [ -100.0,28.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b17262e4b0d9b325224481","contributors":{"authors":[{"text":"Wehmeyer, Loren L.","contributorId":90412,"corporation":false,"usgs":true,"family":"Wehmeyer","given":"Loren","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":486301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winters, Karl E. kwinters@usgs.gov","contributorId":3554,"corporation":false,"usgs":true,"family":"Winters","given":"Karl","email":"kwinters@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":486300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ockerman, Darwin J. 0000-0003-1958-1688 ockerman@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-1688","contributorId":1579,"corporation":false,"usgs":true,"family":"Ockerman","given":"Darwin","email":"ockerman@usgs.gov","middleInitial":"J.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486299,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70059027,"text":"fs20133118 - 2013 - Methane occurrence in groundwater of south-central New York State, 2012: summary of findings","interactions":[],"lastModifiedDate":"2013-12-17T11:33:28","indexId":"fs20133118","displayToPublicDate":"2013-12-17T11:27:00","publicationYear":"2013","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":"2013-3118","title":"Methane occurrence in groundwater of south-central New York State, 2012: summary of findings","docAbstract":"A survey of methane in groundwater was undertaken to document methane occurrence on the basis of hydrogeologic setting within a glaciated 1,810-square-mile area of south-central New York that has not seen shale-gas resource development. The adjacent region in northeastern Pennsylvania has undergone shale-gas resource development from the Marcellus Shale.\n\nWell construction and subsurface data were required for each well sampled so that the local hydrogeologic setting could be classified. All wells were also at least 1 mile from any known gas well (active, exploratory, or abandoned). Sixty-six domestic wells and similar purposed supply wells were sampled during summer 2012. Field water-quality characteristics (pH, specific conductance, dissolved oxygen, and temperature) were measured at each well, and samples were collected and analyzed for dissolved gases, including methane and short-chain hydrocarbons. Carbon and hydrogen isotopic ratios of methane were measured in 21 samples that had at least 0.3 milligram per liter (mg/L) methane.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133118","issn":"2327-6932","usgsCitation":"Heisig, P.M., and Scott, T., 2013, Methane occurrence in groundwater of south-central New York State, 2012: summary of findings: U.S. Geological Survey Fact Sheet 2013-3118, 2 p., https://doi.org/10.3133/fs20133118.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-053308","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":280366,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133118.jpg"},{"id":280365,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3118/pdf/fs2013-3118.pdf"},{"id":280364,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3118"}],"country":"United States","state":"New York","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -78.0,41.0 ], [ -78.0,43.0 ], [ -75.0,43.0 ], [ -75.0,41.0 ], [ -78.0,41.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b172c0e4b0d9b3252245f6","contributors":{"authors":[{"text":"Heisig, Paul M. 0000-0003-0338-4970 pmheisig@usgs.gov","orcid":"https://orcid.org/0000-0003-0338-4970","contributorId":793,"corporation":false,"usgs":true,"family":"Heisig","given":"Paul","email":"pmheisig@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scott, Tia-Marie 0000-0002-5677-0544 tia-mariescott@usgs.gov","orcid":"https://orcid.org/0000-0002-5677-0544","contributorId":5122,"corporation":false,"usgs":true,"family":"Scott","given":"Tia-Marie","email":"tia-mariescott@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487439,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70058836,"text":"70058836 - 2013 - Characterizing response of total suspended solids and total phosphorus loading to weather and watershed characteristics for rainfall and snowmelt events in agricultural watersheds","interactions":[],"lastModifiedDate":"2013-12-17T09:32:07","indexId":"70058836","displayToPublicDate":"2013-12-17T09:20:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing response of total suspended solids and total phosphorus loading to weather and watershed characteristics for rainfall and snowmelt events in agricultural watersheds","docAbstract":"Understanding the response of total suspended solids (TSS) and total phosphorus (TP) to influential weather and watershed variables is critical in the development of sediment and nutrient reduction plans. In this study, rainfall and snowmelt event loadings of TSS and TP were analyzed for eight agricultural watersheds in Wisconsin, with areas ranging from 14 to 110 km2 and having four to twelve years of data available. The data showed that a small number of rainfall and snowmelt runoff events accounted for the majority of total event loading. The largest 10% of the loading events for each watershed accounted for 73–97% of the total TSS load and 64–88% of the total TP load. More than half of the total annual TSS load was transported during a single event for each watershed at least one of the monitored years. Rainfall and snowmelt events were both influential contributors of TSS and TP loading. TSS loading contributions were greater from rainfall events at five watersheds, from snowmelt events at two watersheds, and nearly equal at one watershed. The TP loading contributions were greater from rainfall events at three watersheds, from snowmelt events at two watersheds and nearly equal at three watersheds. Stepwise multivariate regression models for TSS and TP event loadings were developed separately for rainfall and snowmelt runoff events for each individual watershed and for all watersheds combined by using a suite of precipitation, melt, temperature, seasonality, and watershed characteristics as predictors. All individual models and the combined model for rainfall events resulted in two common predictors as most influential for TSS and TP. These included rainfall depth and the antecedent baseflow. Using these two predictors alone resulted in an R2 greater than 0.7 in all but three individual models and 0.61 or greater for all individual models. The combined model yielded an R2 of 0.66 for TSS and 0.59 for TP. Neither the individual nor the combined models were substantially improved by using additional predictors. Snowmelt event models were statistically significant for individual and combined watershed models, but the model fits were not all as good as those for rainfall events (R2 between 0.19 and 0.87). Predictor selection varied from watershed to watershed, and the common variables that were selected were not always selected in the same order. Influential variables were commonly direct measures of moisture in the watershed such as snowmelt, rainfall + snowmelt, and antecedent baseflow, or measures of potential snowmelt volume in the watershed such as air temperature.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"doi":"10.1016/j.jhydrol.2013.09.038","usgsCitation":"Danz, M., Corsi, S., Brooks, W.R., and Bannerman, R.T., 2013, Characterizing response of total suspended solids and total phosphorus loading to weather and watershed characteristics for rainfall and snowmelt events in agricultural watersheds: Journal of Hydrology, v. 507, p. 249-261, https://doi.org/10.1016/j.jhydrol.2013.09.038.","productDescription":"13 p.","startPage":"249","endPage":"261","numberOfPages":"13","ipdsId":"IP-045989","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":280353,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280312,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jhydrol.2013.09.038"}],"country":"United States","state":"Wisconsin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.8894,42.4919 ], [ -92.8894,47.0807 ], [ -86.764,47.0807 ], [ -86.764,42.4919 ], [ -92.8894,42.4919 ] ] ] } } ] }","volume":"507","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b172bae4b0d9b3252245c6","contributors":{"authors":[{"text":"Danz, Mari E. medanz@usgs.gov","contributorId":3349,"corporation":false,"usgs":true,"family":"Danz","given":"Mari E.","email":"medanz@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corsi, Steven","contributorId":106002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":487381,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brooks, Wesley R. wrbrooks@usgs.gov","contributorId":4217,"corporation":false,"usgs":true,"family":"Brooks","given":"Wesley","email":"wrbrooks@usgs.gov","middleInitial":"R.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487379,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bannerman, Roger T. 0000-0001-9221-2905 rbannerman@usgs.gov","orcid":"https://orcid.org/0000-0001-9221-2905","contributorId":5560,"corporation":false,"usgs":true,"family":"Bannerman","given":"Roger","email":"rbannerman@usgs.gov","middleInitial":"T.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487380,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70058711,"text":"ofr20131290 - 2013 - Evaluation of the behavior and movement patterns of adult coho salmon and steelhead in the North Fork Toutle River, Washington, 2005-2009","interactions":[],"lastModifiedDate":"2013-12-19T08:47:32","indexId":"ofr20131290","displayToPublicDate":"2013-12-16T11:29:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1290","title":"Evaluation of the behavior and movement patterns of adult coho salmon and steelhead in the North Fork Toutle River, Washington, 2005-2009","docAbstract":"The 1980 eruption of Mount St. Helens severely affected the North Fork Toutle River (hereafter Toutle River), Washington, and threatened anadromous salmon (Oncorhynchus spp.) populations in the basin. The Toutle River was further affected in 1989 when a sediment retention structure (SRS) was constructed to trap sediments in the upper basin. The SRS completely blocked upstream volitional passage, so a fish collection facility (FCF) was constructed to trap adult coho salmon (O. kisutch) and steelhead (O. mykiss) so they could be transported upstream of the SRS. The Washington Department of Fish and Wildlife (WDFW) has operated a trap-and-haul program since 1989 to transport coho salmon and steelhead into tributaries of the Toutle River, upstream of the SRS. Although this program has allowed wild coho salmon and steelhead populations to persist in the Toutle River basin, the trap-andhaul program has faced many challenges that may be limiting the effectiveness of the program. We conducted a multi-year evaluation during 2005–2009 to monitor tagged fish in the upper Toutle River to provide information on the movements and behavior of adult coho salmon and steelhead, and to evaluate the efficacy of the FCF. Radio-tagged coho salmon and steelhead were released: (1) in Toutle River tributaries to evaluate the behavior and movements of fish released as part of the trap-and-haul program; (2) between the FCF and SRS to determine if volitional upstream passage through the SRS spillway was possible; (3) in the sediment plain upstream of the SRS to determine if volitional passage through the sediment plain was possible; and (4) downstream of the FCF to evaluate the efficacy of the structure. We also deployed an acoustic camera in the FCF to monitor fish movements near the entrance to the FCF, and in the fish holding vault where coho salmon and steelhead are trapped.
\nA total of 20 radio-tagged coho salmon and 10 radio-tagged steelhead were released into Alder and Hoffstadt Creeks, the locations where trap-and-haul fish were released during 2005–2006. None of the tagged fish left the tributaries where they were released, but four radio tags were detected near the release sites, and it was not possible to determine if this was because the transmitters were regurgitated, or if some of the tagged fish had died. The results from this portion of the study indicated that trap-and-haul fish remain in the tributaries where they can spawn, but the trap-and-haul process is labor-intensive, and handling stress and mortality could occur.
\nTagged-fish releases upstream of the FCF showed that the SRS spillway was a complete migration barrier for all coho salmon and most steelhead. We released a total of 20 radio-tagged coho salmon and 23 radio-tagged steelhead during 2005–2007. No tagged coho salmon passed upstream through the SRS spillway, whereas 13 percent of the radio-tagged steelhead did migrate upstream through the structure. Radio-tagged coho salmon and steelhead that did not pass upstream remained in the FCF–SRS reach for an average of 7.5 and 16.1 d, respectively, before moving downstream. These data show that trap-and-haul releases of fish immediately upstream of the FCF would not be beneficial to coho salmon and steelhead populations in the system.
\nReleasing tagged fish into the sediment plain was only moderately successful for coho salmon,\nbut a large percentage of tagged steelhead moved upstream through the sediment plain to areas where\nspawning could presumably occur. During 2005–2009, we released 47 tagged coho salmon and 65\ntagged steelhead into the sediment plain. Only 28 percent of the coho salmon were later detected\nupstream of the sediment plain, and the highest percentage of the release group (62 percent) never left\nthe sediment plain. However, 69 percent of the steelhead moved upstream through the sediment plain\nand entered Toutle River tributaries or remained in the mainstem Toutle River where spawning could\npresumably occur. Adult steelhead can survive freshwater spawning, outmigrate to the ocean, and then\nreturn to spawn in successive years; 12 percent of the tagged steelhead successfully moved downstream\nof the FCF after the spawning period, and 5 percent of the tagged steelhead returned to the FCF a year\nafter they were originally tagged.
\nEvaluations at the FCF showed that the structure was not efficient at collecting adult salmon.\nDuring 2008–2009, 9 radio-tagged coho salmon and 11 radio-tagged steelhead were released to observe\nbehavior near the facility and to estimate the recapture rate in the FCF. None of the tagged coho salmon\nwere recaptured and only 27 percent of the tagged steelhead were recaptured. Additionally, we observed\nfish behavior at the FCF with an acoustic camera and found that relatively large numbers (>100\nfish/sampling period) of adult salmon entered the FCF but similar numbers of fish exited during these\nperiods as well. This suggested that the efficacy of the FCF was low.
\nOur study was limited by the number of fish that could be handled each year and the number of\ntransmitters that could be purchased annually, but our evaluations provided the first empirical data on\nadult salmon behavior and movement patterns in the Toutle River since the 1980 eruption of Mount St.\nHelens. Since the completion of this work, the U.S. Army Corps of Engineers has altered the SRS\nspillway and sediment plain; however, our results do provide information to assist fishery managers\ntasked with the complex management of wild salmon populations in the Toutle River. Future\nevaluations of juvenile and adult salmon behavior and movement likely will be required to effectively\nmanage these populations in this complex system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131290","usgsCitation":"Liedtke, T.L., Kock, T.J., and Rondorf, D.W., 2013, Evaluation of the behavior and movement patterns of adult coho salmon and steelhead in the North Fork Toutle River, Washington, 2005-2009: U.S. Geological Survey Open-File Report 2013-1290, iv, 26 p., https://doi.org/10.3133/ofr20131290.","productDescription":"iv, 26 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-050770","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":280326,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131290.JPG"},{"id":280325,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1290/pdf/ofr2013-1290.pdf"},{"id":280324,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1290/"}],"country":"United States","state":"Washington","otherGeospatial":"North Fork Toutle River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.385782,46.240798 ], [ -122.385782,46.28767 ], [ -122.182554,46.28767 ], [ -122.182554,46.240798 ], [ -122.385782,46.240798 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b0211ee4b0242fceec857d","contributors":{"authors":[{"text":"Liedtke, Theresa L. 0000-0001-6063-9867 tliedtke@usgs.gov","orcid":"https://orcid.org/0000-0001-6063-9867","contributorId":2999,"corporation":false,"usgs":true,"family":"Liedtke","given":"Theresa","email":"tliedtke@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":487292,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kock, Tobias J. 0000-0001-8976-0230 tkock@usgs.gov","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":3038,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","email":"tkock@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":487293,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rondorf, Dennis W. drondorf@usgs.gov","contributorId":2970,"corporation":false,"usgs":true,"family":"Rondorf","given":"Dennis","email":"drondorf@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":487291,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70049017,"text":"sir20135181 - 2013 - Hydrology and water quality of Shell Lake, Washburn County, Wisconsin, with special emphasis on the effects of diversion and changes in water level on the water quality of a shallow terminal lake","interactions":[],"lastModifiedDate":"2018-02-06T12:17:35","indexId":"sir20135181","displayToPublicDate":"2013-12-16T11:00:00","publicationYear":"2013","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":"2013-5181","title":"Hydrology and water quality of Shell Lake, Washburn County, Wisconsin, with special emphasis on the effects of diversion and changes in water level on the water quality of a shallow terminal lake","docAbstract":"Shell Lake is a relatively shallow terminal lake (tributaries but no outlets) in northwestern Wisconsin that has experienced approximately 10 feet (ft) of water-level fluctuation over more than 70 years of record and extensive flooding of nearshore areas starting in the early 2000s. The City of Shell Lake (City) received a permit from the Wisconsin Department of Natural Resources in 2002 to divert water from the lake to a nearby river in order to lower water levels and reduce flooding. Previous studies suggested that water-level fluctuations were driven by long-term cycles in precipitation, evaporation, and runoff, although questions about the lake’s connection with the groundwater system remained. The permit required that the City evaluate assumptions about lake/groundwater interactions made in previous studies and evaluate the effects of the water diversion on water levels in Shell Lake and other nearby lakes. Therefore, a cooperative study between the City and U.S. Geological Survey (USGS) was initiated to improve the understanding of the hydrogeology of the area and evaluate potential effects of the diversion on water levels in Shell Lake, the surrounding groundwater system, and nearby lakes. Concerns over deteriorating water quality in the lake, possibly associated with changes in water level, prompted an additional cooperative project between the City and the USGS to evaluate efeffects of changes in nutrient loading associated with changes in water levels on the water quality of Shell Lake. Numerical models were used to evaluate how the hydrology and water quality responded to diversion of water from the lake and historical changes in the watershed. The groundwater-flow model MODFLOW was used to simulate groundwater movement in the area around Shell Lake, including groundwater/surface-water interactions. Simulated results from the MODFLOW model indicate that groundwater flows generally northward in the area around Shell Lake, with flow locally converging toward the lake. Total groundwater inflow to Shell Lake is small (approximately 5 percent of the water budget) compared with water entering the lake from precipitation (83 percent) and surface-water runoff (13 percent). The MODFLOW model also was used to simulate average annual hydrologic conditions from 1949 to 2009, including effects of the removal of 3 billion gallons of water during 2003–5. The maximum decline in simulated average annual water levels for Shell Lake due to the diversion alone was 3.3 ft at the end of the diversion process in 2005. Model simulations also indicate that although water level continued to decline through 2009 in response to local weather patterns (local drought), the effects of the diversion decreased after the diversion ceased; that is, after 4 years of recovery (2006–9), drawdown attributable to the diversion alone decreased by about 0.6 ft because of increased groundwater inflow and decreased lake-water outflow to groundwater caused by the artificially lower lake level. A delayed response in drawdown of less than 0.5 ft was transmitted through the groundwater-flow system to upgradient lakes. This relatively small effect on upgradient lakes is attributed in part to extensive layers of shallow clay that limit lake/groundwater interaction in the area. Data collected in the lake indicated that Shell Lake is polymictic (characterized by frequent deep mixing) and that its productivity is limited by the amount of phosphorus in the lake. The lake was typically classified as oligotrophic-mesotrophic in June, mesotrophic in July, and mesotrophic-eutrophic in August. In polymictic lakes like Shell Lake, phosphorus released from the sediments is not trapped near the bottom of the lake but is intermittently released to the shallow water, resulting in deteriorating water quality as summer progresses. Because the productivity of Shell Lake is limited by phosphorus, the sources of phosphorus to the lake were quantified, and the response in water quality to changes in phosphorus inputs were evaluated by means of eutrophication models. During 2009, the total input of phosphorus to Shell Lake was 1,730 pounds (lb), of which 1,320 lb came from external sources (76 percent) and 414 lb came from internal loading from sediments in the lake (24 percent). The largest external source was from surface-water runoff, which delivered about 52 percent of the total phosphorus load compared with about 13 percent of the water input. The second largest source was from precipitation (wetfall and dryfall), which delivered 19 percent of the load compared to about 83 percent of the water input. Contributions from septic systems and groundwater accounted for about 3 and 2 percent, respectively. Increased runoff raises water levels in the lake but does not necessarily increase phosphorus loading because phosphorus concentrations in the tributaries decline during increased flow, possibly because of shorter retention times in upstream wetlands. Phosphorus loading to the lake in 2009 represented what occurred after a series of dry years; therefore, this information was combined with data from 2011, a wet year, to estimate phosphorus loading during a range of hydrologic conditions by estimating loading from each component of the phosphorus budget for each year from 1949 to 2011. Comparisons of historical water-quality records with historical water levels and applications of a hydrodynamic model (Dynamic Lake Model, DLM) and empirical eutrophication models were used to understand how changes in water level and the coinciding changes in phosphorus loading affect the water quality of Shell Lake. DLM simulations indicate that large changes in water level (approximately 10 ft) affect the persistence of stratification in the lake. During periods with low water levels, the lake is a well-mixed, polymictic system, with water quality degrading slightly as summer progresses. During periods with high water levels, the lake is more stratified, and phosphorus from internal loading is trapped in the hypolimnion and released later in summer, which results in more extreme seasonality in water quality and better clarity in early summer. Results of eutrophication model simulations using a range in external phosphorus inputs illustrate how water quality in Shell Lake (phosphorus and chlorophyll a concentrations and Secchi depths) responds to changes in external phosphorus loading. Results indicate that a 50-percent reduction in external loading from that measured in 2009 would be required to change phosphorus concentrations from 0.018 milligram per liter (mg/L) (measured in 2009) to 0.012 mg/L (estimated for the mid-1800s from analysis of diatoms in sediment cores). Such reductions in phosphorus loading cannot be accomplished by targeting septic systems or internal loading alone because septic systems contribute only about 3 percent of the phosphorus input to the lake, and internal loading from the sediments of Shell Lake contributes only about 25 percent of phosphorus input. Complete elimination of phosphorus from septic systems and internal loading would decrease the phosphorus concentrations in the lake by 0.003–0.004 mg/L. Therefore, reducing phosphorus concentration in the lake more than by 0.004 mg/L requires decreasing phosphorus loading from surface-water contributions, primarily runoff to the lake. Reconstructed changes in water quality from 1860 to 2010, based on changes in the diatom communities archived in the sediments and eutrophication model simulations, suggest that anthropogenic changes in the watershed (sawmill construction in 1881; the establishment of the village of Shell Lake; and land-use changes in the 1920s, including increased agriculture) had a much larger effect on water quality than the natural changes associated with fluctuations in water level. Although the effects of natural changes in water level on water quality appear to be small, changes in water level do have a modest effect on water quality, primarily manifested as small improvements during higher water levels. Fluctuations in water level, however, have a larger effect on the seasonality of water-quality patterns, with better water quality, especially increased Secchi depths, in early summer during years with high water levels.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135181","collaboration":"In cooperation with the City of Shell Lake, Wisconsin","usgsCitation":"Juckem, P.F., and Robertson, D.M., 2013, Hydrology and water quality of Shell Lake, Washburn County, Wisconsin, with special emphasis on the effects of diversion and changes in water level on the water quality of a shallow terminal lake: U.S. Geological Survey Scientific Investigations Report 2013-5181, Report: x, 77 p.; Appendix 1: PDF file; Appendix 2: PDF file, https://doi.org/10.3133/sir20135181.","productDescription":"Report: x, 77 p.; Appendix 1: PDF file; Appendix 2: PDF file","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-045912","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":280323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135181.jpg"},{"id":280321,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5181/pdf/sir2013-5181_appendix1.pdf"},{"id":280322,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5181/pdf/sir2013-5181_appendix2.pdf"},{"id":280320,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5181/pdf/sir2013-5181.pdf"},{"id":280319,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5181/"}],"country":"United States","state":"Wisconsin","county":"Washburn County","otherGeospatial":"Shell Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.94286346435547,\n 45.75506798173109\n ],\n [\n -91.86355590820312,\n 45.75530752680575\n ],\n [\n -91.86424255371094,\n 45.70881653205482\n ],\n [\n -91.89960479736327,\n 45.7066587939899\n ],\n [\n -91.9068145751953,\n 45.70929601809127\n ],\n [\n -91.94252014160156,\n 45.70953575956707\n ],\n [\n -91.94286346435547,\n 45.75506798173109\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b0211fe4b0242fceec8584","contributors":{"authors":[{"text":"Juckem, Paul F. 0000-0002-3613-1761 pfjuckem@usgs.gov","orcid":"https://orcid.org/0000-0002-3613-1761","contributorId":1905,"corporation":false,"usgs":true,"family":"Juckem","given":"Paul","email":"pfjuckem@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robertson, Dale M. 0000-0001-6799-0596 dzrobert@usgs.gov","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":150760,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"dzrobert@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486030,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70049012,"text":"sir20135183 - 2013 - Assessment of water-quality data from Long Lake National Wildlife Refuge, North Dakota--2008 through 2012","interactions":[],"lastModifiedDate":"2013-12-16T11:05:29","indexId":"sir20135183","displayToPublicDate":"2013-12-16T10:30:00","publicationYear":"2013","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":"2013-5183","title":"Assessment of water-quality data from Long Lake National Wildlife Refuge, North Dakota--2008 through 2012","docAbstract":"ong Lake National Wildlife Refuge, located in south-central North Dakota, is an important habitat for numerous migratory birds and waterfowl, including several threatened or endangered species. The refuge is distinguished by Long Lake, which is approximately 65 square kilometers and consists of four primary water management units. Water levels in the Long Lake units are maintained by low-level dikes and water-control structures, which after construction during the 1930s increased the water-storage capacity of Long Lake and reduced the frequency and volume of flushing flows downstream. The altered water regime, along with the negative precipitation:evaporation ratio of the region, may be contributing to the accumulation of water-borne chemical constituents such as salts, trace metals, and other constituents, which at certain threshold concentrations may impair aquatic plant, invertebrate, and bird communities of the refuge. The refuge’s comprehensive conservation planning process identified the need for water-quality monitoring to assess current (2013) conditions, establish comparative baselines, evaluate changes over time (trends), and support adaptive management of the wetland units. In 2008, the U.S. Geological Survey, U.S. Fish and Wildlife Service, and North Dakota Department of Health began a water-quality monitoring program at Long Lake National Wildlife Refuge to address these needs. Biweekly water-quality samples were collected for ions, trace metals, and nutrients; and in situ sensors and data loggers were installed for the continuous measurement of specific conductance and water depth.\n\nLong Lake was characterized primarily by sodium, bicarbonate, and sulfate ions. Overall results for total alkalinity and hardness were 580 and 329 milligrams per liter, respectively; thus, Long Lake is considered alkaline and classified as very hard. The mean pH and sodium adsorption ratio for Long Lake were 8.8 and 10, respectively. Total dissolved solids concentrations averaged approximately 1,750 milligrams per liter, and ranged from 117 to 39,700 milligrams per liter. Twelve of the 14 trace metals detected in the water samples had established North Dakota water-quality standards for aquatic life, and only aluminum and copper consistently exceeded these criteria. Aluminum is considered harmful to aquatic biota in acidic (pH less than 5.5) systems and most of the copper standard exceedances were collected from highly concentrated waters because of evaporation and seasonally low water levels. Concentrations for various forms of nitrogen and phosphorus generally were similar to reported regional values.\n\nSpecific conductance of Long Lake varied seasonally and annually both within and among management units, with values ranging from less than 500 to nearly 40,000 microsiemens per centimeter at 25 degrees Celsius. Long Lake was characterized by consistent seasonal patterns of increasing specific conductance from spring (March and April) to fall (September and October), with levels stabilizing through the end of the sampling season (November). These seasonal patterns in specific conductance were associated with decreasing water levels throughout the summer due primarily to evaporation and continuous water releases through the Unit 1 outlet structure, which resulted in the concentration of salts. Specific conductance of each unit, along with water levels, also varied among years. Overall, specific conductance levels were greatest during the drier year of 2008 when water levels were low. Specific conductance levels were lowest during the spring of 2009 following above-average volumes of fresh water from snowmelt runoff. Comparisons of specific conductance among sample sites that were spatially distributed within each management unit suggested that spatial variability within units was low except for areas associated with local inflows.\n\nData collected during this study revealed consistent seasonal patterns and low within-unit spatial variability of specific conductance. Based on these data results, future sample collection efforts may be reduced, as well as the number of sample locations, to limit sampling costs. Water-quality samples collected monthly or seasonally during the growing season (spring, summer, and fall) from a single representative location within each water-management unit should provide sufficient data to assess seasonal changes in water-quality over time and provide information for Long Lake management decisions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135183","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and North Dakota Department of Health","usgsCitation":"Tangen, B., Finocchiaro, R.G., Gleason, R.A., Rabenberg, M.J., Dahl, C.F., and Ell, M., 2013, Assessment of water-quality data from Long Lake National Wildlife Refuge, North Dakota--2008 through 2012: U.S. Geological Survey Scientific Investigations Report 2013-5183, Report: vi, 27 p.; Appendix 1: XLSX file; Appendix 2: XLSX file, https://doi.org/10.3133/sir20135183.","productDescription":"Report: vi, 27 p.; Appendix 1: XLSX file; Appendix 2: XLSX file","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-045659","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":280315,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135183.jpg"},{"id":280316,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5183/"},{"id":280317,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5183/pdf/sir2013-5183.pdf"},{"id":280318,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5183/downloads/"}],"projection":"Universal Transverse Mercator, zone 13N","datum":"North American Datum of 1983","country":"United States","state":"North Dakota","otherGeospatial":"Long Lake National Wildlife Refuge","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -100.327148,46.658156 ], [ -100.327148,46.773731 ], [ -99.983482,46.773731 ], [ -99.983482,46.658156 ], [ -100.327148,46.658156 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b0211ee4b0242fceec8576","contributors":{"authors":[{"text":"Tangen, Brian A. 0000-0001-5157-9882 btangen@usgs.gov","orcid":"https://orcid.org/0000-0001-5157-9882","contributorId":467,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian A.","email":"btangen@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":486015,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finocchiaro, Raymond G. rfinocchiaro@usgs.gov","contributorId":3673,"corporation":false,"usgs":true,"family":"Finocchiaro","given":"Raymond","email":"rfinocchiaro@usgs.gov","middleInitial":"G.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":486017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gleason, Robert A. 0000-0001-5308-8657 rgleason@usgs.gov","orcid":"https://orcid.org/0000-0001-5308-8657","contributorId":2402,"corporation":false,"usgs":true,"family":"Gleason","given":"Robert","email":"rgleason@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":486016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rabenberg, Michael J.","contributorId":47278,"corporation":false,"usgs":true,"family":"Rabenberg","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":486019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dahl, Charles F. cdahl@usgs.gov","contributorId":4052,"corporation":false,"usgs":true,"family":"Dahl","given":"Charles","email":"cdahl@usgs.gov","middleInitial":"F.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":486018,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ell, Mike J.","contributorId":101175,"corporation":false,"usgs":true,"family":"Ell","given":"Mike J.","affiliations":[],"preferred":false,"id":486020,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70118277,"text":"70118277 - 2013 - Discerning crystal growth from diffusion profiles in zoned olivine by in situ Mg–Fe isotopic analyses","interactions":[],"lastModifiedDate":"2014-07-28T11:13:27","indexId":"70118277","displayToPublicDate":"2013-12-15T11:06:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Discerning crystal growth from diffusion profiles in zoned olivine by in situ Mg–Fe isotopic analyses","docAbstract":"Mineral zoning is used in diffusion-based geospeedometry to determine magmatic timescales. Progress in this field has been hampered by the challenge to discern mineral zoning produced by diffusion from concentration gradients inherited from crystal growth. A zoned olivine phenocryst from Kilauea Iki lava lake (Hawaii) was selected for this study to evaluate the potential of Mg and Fe isotopes for distinguishing these two processes. Microdrilling of the phenocryst (∼300 μm drill holes) followed by MC-ICPMS analysis of the powders revealed negatively coupled Mg and Fe isotopic fractionations (δ26Mg from +0.1‰ to −0.2‰ and δ56Fe from −1.2‰ to −0.2‰ from core to rim), which can only be explained by Mg–Fe exchange between melt and olivine. The data can be explained with ratios of diffusivities of Mg and Fe isotopes in olivine scaling as D2/D1 = (m1/m2)β with βMg ∼0.16 and βFe ∼0.27. LA-MC-ICPMS and MC-SIMS Fe isotopic measurements are developed and are demonstrated to yield accurate δ56Fe measurements within precisions of ∼0.2‰ (1 SD) at spatial resolutions of ∼50 μm. δ56Fe and δ26Mg stay constant with Fo# in the rim (late-stage overgrowth), whereas in the core (original phenocryst) δ56Fe steeply trends toward lighter compositions and δ26Mg trends toward heavier compositions with higher Fo#. A plot of δ56Fe vs. Fo# immediately distinguishes growth-controlled from diffusion-controlled zoning in these two regions. The results are consistent with the idea that large isotopic fractionation accompanies chemical diffusion in crystals, whereas fractional crystallization induces little or no isotopic fractionation. The cooling timescale inferred from the chemical-isotope zoning profiles is consistent with the documented cooling history of the lava lake. In the absence of geologic context, in situ stable isotopic measurements may now be used to interpret the nature of mineral zoning. Stable isotope measurements by LA-MC-ICPMS and MC-SIMS can be used as standard petrologic tools to identify samples for diffusion-based geospeedometry.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geochimica et Cosmochimica Acta","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Geochemical Society","publisherLocation":"New York, NY","doi":"10.1016/j.gca.2013.06.008","usgsCitation":"Sio, C.K., Dauphas, N., Teng, F., Chaussidon, M., Helz, R., and Roskosz, M., 2013, Discerning crystal growth from diffusion profiles in zoned olivine by in situ Mg–Fe isotopic analyses: Geochimica et Cosmochimica Acta, v. 123, p. 302-321, https://doi.org/10.1016/j.gca.2013.06.008.","productDescription":"20 p.","startPage":"302","endPage":"321","numberOfPages":"20","costCenters":[],"links":[{"id":291139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291138,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.gca.2013.06.008"}],"volume":"123","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f1e7e4b0bc0bec0a008a","contributors":{"authors":[{"text":"Sio, Corliss Kin I.","contributorId":26634,"corporation":false,"usgs":true,"family":"Sio","given":"Corliss","email":"","middleInitial":"Kin I.","affiliations":[],"preferred":false,"id":496684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dauphas, Nicolas","contributorId":67430,"corporation":false,"usgs":true,"family":"Dauphas","given":"Nicolas","email":"","affiliations":[],"preferred":false,"id":496686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teng, Fang-Zhen","contributorId":87075,"corporation":false,"usgs":true,"family":"Teng","given":"Fang-Zhen","email":"","affiliations":[],"preferred":false,"id":496688,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chaussidon, Marc","contributorId":99486,"corporation":false,"usgs":true,"family":"Chaussidon","given":"Marc","email":"","affiliations":[],"preferred":false,"id":496689,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Helz, Rosalind T. 0000-0003-1550-0684","orcid":"https://orcid.org/0000-0003-1550-0684","contributorId":66181,"corporation":false,"usgs":true,"family":"Helz","given":"Rosalind T.","affiliations":[],"preferred":false,"id":496685,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roskosz, Mathieu","contributorId":72317,"corporation":false,"usgs":true,"family":"Roskosz","given":"Mathieu","email":"","affiliations":[],"preferred":false,"id":496687,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}