The State of California conducted an extensive and systematic survey of mercury (Hg) in fish from the California coast in 2009 and 2010. The California survey sampled 3483 fish representing 46 species at 68 locations, and demonstrated that methylHg in fish presents a widespread exposure risk to fish consumers. Most of the locations sampled (37 of 68) had a species with an average concentration above 0.3 μg/g wet weight (ww), and 10 locations an average above 1.0 μg/g ww. The recent and robust dataset from California provided a basis for a broader examination of spatial and temporal patterns in fish Hg in coastal waters of Western North America. There is a striking lack of data in publicly accessible databases on Hg and other contaminants in coastal fish. An assessment of the raw data from these databases suggested the presence of relatively high concentrations along the California coast and in Puget Sound, and relatively low concentrations along the coasts of Alaska and Oregon, and the outer coast of Washington. The dataset suggests that Hg concentrations of public health concern can be observed at any location on the coast of Western North America where long-lived predator species are sampled. Output from a linear mixed-effects model resembled the spatial pattern observed for the raw data and suggested, based on the limited dataset, a lack of trend in fish Hg over the nearly 30-year period covered by the dataset. Expanded and continued monitoring, accompanied by rigorous data management procedures, would be of great value in characterizing methylHg exposure, and tracking changes in contamination of coastal fish in response to possible increases in atmospheric Hg emissions in Asia, climate change, and terrestrial Hg control efforts in coastal watersheds.
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Dendrochronology, field mapping, and aerial photographic analysis are used to evaluate whether a 19th century earthen, water-conveyance ditch has altered the regime of debris flow occurrence in the Colorado River headwaters. Identifying any shifts in disturbance processes or changes in magnitudes and frequencies of occurrence is fundamental to establishing the historical range of variability (HRV) at the site. We found no substantial difference in frequency of debris flows cataloged at eleven sites of deposition between the east (8) and west (11) sides of the Colorado River valley over the last century, but four of the five largest debris flows originated on the west side of the valley in association with the earthen ditch, while the fifth is on a steep hillslope of hydrothermally altered rock on the east side. These results suggest that the ditch has altered the regime of debris flow activity in the Colorado River headwaters as compared to HRV by increasing the frequency of debris flows large enough to reach the Colorado River valley. Valley confinement is a dominant control on response to debris flows, influencing volumes of aggradation and persistence of debris flow deposits. Large, frequent debris flows, exceeding HRV, create persistent effects due to valley geometry and geomorphic setting conducive to sediment storage that are easily delineated by valley confinement ratios which are useful to land managers.
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\nA series of digital flood-inundation maps were developed on the basis of the water-surface profiles produced by the model. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program Web site at http://water.usgs.gov/osw/flood_inundation, depict estimates of the areal extent and depth of flooding corresponding to selected water levels at the USGS streamgage Pee Dee River at Pee Dee Refuge near Ansonville, N.C. These maps, when combined with real-time water-level information from USGS streamgages, provide managers with critical information to help plan flood-response activities and resource protection efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155137","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Smith, D.G., and Wagner, C.R., 2016, Hydraulic model and flood-inundation maps developed for the Pee Dee National Wildlife Refuge, North Carolina: U.S. Geological Survey Scientific Investigations Report 2015–5137, 14 p., https://dx.doi.org/10.3133/sir20155137.","productDescription":"Document: vi, 14 p.; Metadata: 3 downloadable files","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069288","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":319758,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5137/sir20155137.pdf","size":"1.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5137"},{"id":319789,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5137/sir20155137_peedee.xml","size":"15.6 KB xml","description":"SIR 2015-5137"},{"id":319787,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5137/sir20155137_peedee-grids.zip","size":"302 MB grids","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5137"},{"id":319788,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5137/sir20155137_peedee-shapefiles.zip","size":"18.8 MB","linkFileType":{"id":4,"text":"shapefile"},"description":"SIR 2015-5137"},{"id":319757,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5137/coverthb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Pee Dee National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.266667,\n 35.233333\n ],\n [\n -80.266667,\n 35\n ],\n [\n -79.85,\n 35\n ],\n [\n -79.85,\n 35.233333\n ],\n [\n -80.266667,\n 35.233333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
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Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
Improving access to data and fostering open exchange of water information is foundational to solving water resources issues. In this vein, the Department of the Interior's Assistant Secretary for Water and Science put forward the charge to undertake an Open Water Data Initiative (OWDI) that would prioritize and accelerate work toward better water data infrastructure. The goal of the OWDI is to build out the Open Water Web (OWW). We therefore considered the OWW in terms of four conceptual functions: water data cataloging, water data as a service, enriching water data, and community for water data. To describe the current state of the OWW and identify areas needing improvement, we conducted an analysis of existing systems using a standard model for describing distributed systems and their business requirements. Our analysis considered three OWDI-focused use cases—flooding, drought, and contaminant transport—and then examined the landscape of other existing applications that support the Open Water Web. The analysis, which includes a discussion of observed successful practices of cataloging, serving, enriching, and building community around water resources data, demonstrates that we have made significant progress toward the needed infrastructure, although challenges remain. The further development of the OWW can be greatly informed by the interpretation and findings of our analysis.
","language":"English","publisher":"American Water Resources Associaton","publisherLocation":"Herndon, VA","doi":"10.1111/1752-1688.12417","usgsCitation":"Blodgett, D.L., Read, E.K., Lucido, J., Slawecki, T., and Young, D., 2016, An analysis of water data systems to inform the Open Water Data Initiative: Journal of the American Water Resources Association, v. 52, no. 4, p. 845-858, https://doi.org/10.1111/1752-1688.12417.","productDescription":"14 p.","startPage":"845","endPage":"858","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071340","costCenters":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"links":[{"id":471083,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12417","text":"Publisher Index Page"},{"id":319943,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-08","publicationStatus":"PW","scienceBaseUri":"570ccaace4b0ef3b7ca14703","contributors":{"authors":[{"text":"Blodgett, David L. 0000-0001-9489-1710 dblodgett@usgs.gov","orcid":"https://orcid.org/0000-0001-9489-1710","contributorId":3868,"corporation":false,"usgs":true,"family":"Blodgett","given":"David","email":"dblodgett@usgs.gov","middleInitial":"L.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626327,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Read, Emily K. 0000-0002-9617-9433 eread@usgs.gov","orcid":"https://orcid.org/0000-0002-9617-9433","contributorId":5815,"corporation":false,"usgs":true,"family":"Read","given":"Emily","email":"eread@usgs.gov","middleInitial":"K.","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":false,"id":626328,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lucido, Jessica M. jlucido@usgs.gov","contributorId":4695,"corporation":false,"usgs":true,"family":"Lucido","given":"Jessica M.","email":"jlucido@usgs.gov","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":626329,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Slawecki, Tad","contributorId":168540,"corporation":false,"usgs":false,"family":"Slawecki","given":"Tad","email":"","affiliations":[{"id":25325,"text":"LimnoTech, 501 Avis Drive, Ann Arbor, Michigan, USA 48108","active":true,"usgs":false}],"preferred":false,"id":626330,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Young, Dwane","contributorId":168541,"corporation":false,"usgs":false,"family":"Young","given":"Dwane","affiliations":[{"id":25326,"text":"U.S. Environmental Protection Agency, 1200 Pennsylvania Ave., NW, Washington, DC, USA 20460","active":true,"usgs":false}],"preferred":false,"id":626331,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188535,"text":"70188535 - 2016 - Tomographic Rayleigh-wave group velocities in the Central Valley, California centered on the Sacramento/San Joaquin Delta","interactions":[],"lastModifiedDate":"2017-06-14T15:14:42","indexId":"70188535","displayToPublicDate":"2016-04-08T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Tomographic Rayleigh-wave group velocities in the Central Valley, California centered on the Sacramento/San Joaquin Delta","docAbstract":"If shaking from a local or regional earthquake in the San Francisco Bay region were to rupture levees in the Sacramento/San Joaquin Delta then brackish water from San Francisco Bay would contaminate the water in the Delta: the source of fresh water for about half of California. As a prelude to a full shear-wave velocity model that can be used in computer simulations and further seismic hazard analysis, we report on the use of ambient noise tomography to build a fundamental-mode, Rayleigh-wave group velocity model for the region around the Sacramento/San Joaquin Delta in the western Central Valley, California. Recordings from the vertical component of about 31 stations were processed to compute the spatial distribution of Rayleigh wave group velocities. Complex coherency between pairs of stations were stacked over 8 months to more than a year. Dispersion curves were determined from 4 to about 18 seconds. We calculated average group velocities for each period and inverted for deviations from the average for a matrix of cells that covered the study area. Smoothing using the first difference is applied. Cells of the model were about 5.6 km in either dimension. Checkerboard tests of resolution, which is dependent on station density, suggest that the resolving ability of the array is reasonably good within the middle of the array with resolution between 0.2 and 0.4 degrees. Overall, low velocities in the middle of each image reflect the deeper sedimentary syncline in the Central Valley. In detail, the model shows several centers of low velocity that may be associated with gross geologic features such as faulting along the western margin of the Central Valley, oil and gas reservoirs, and large cross cutting features like the Stockton arch. At shorter periods around 5.5s, the model’s western boundary between low and high velocities closely follows regional fault geometry and the edge of a residual isostatic gravity low. In the eastern part of the valley, the boundaries of the low velocity zone and gravity anomaly are better aligned at longer periods (around 10.5s) suggesting that the eastern edge of the gravity low is associated with deeper structure. There is a strong correspondence between a low in gravity near the Kirby Hills fault and low velocities from the ambient noise tomography. At longer periods, higher velocities creep in from the east and narrow the overall dimension defined by the lower velocities. Overall, there is a strong correspondence between the shape and location of low velocities in the Rayleigh wave velocity images, and geological and geophysical features.","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JB012376","usgsCitation":"Fletcher, J.P., Erdem, J., Seats, K., and Lawrence, J., 2016, Tomographic Rayleigh-wave group velocities in the Central Valley, California centered on the Sacramento/San Joaquin Delta: Journal of Geophysical Research B: Solid Earth, v. 121, no. 4, p. 2429-2446, https://doi.org/10.1002/2015JB012376.","productDescription":"18 p. ","startPage":"2429","endPage":"2446","ipdsId":"IP-062590","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":471084,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb012376","text":"Publisher Index Page"},{"id":342506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley, Sacramento/San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.7117919921875,\n 39.89709437260048\n ],\n [\n -122.01416015625,\n 38.225235239076824\n ],\n [\n -121.4813232421875,\n 37.63163475580643\n ],\n [\n -121.00341796874999,\n 37.08585785263673\n ],\n [\n -120.67932128906249,\n 36.730079507078415\n ],\n [\n -118.55895996093749,\n 37.53150992479082\n ],\n [\n -118.7017822265625,\n 38.043765107439675\n ],\n [\n -119.08630371093749,\n 38.543869175876154\n ],\n [\n -119.80590820312499,\n 39.317300373271024\n ],\n [\n -120.2838134765625,\n 39.774769485295465\n ],\n [\n -120.948486328125,\n 40.29628651711716\n ],\n [\n -121.31103515625,\n 40.53050177574321\n ],\n [\n -121.97021484374999,\n 40.53050177574321\n ],\n [\n -122.398681640625,\n 40.40094763151963\n ],\n [\n -122.72277832031251,\n 40.225024210604964\n ],\n [\n -122.7117919921875,\n 39.89709437260048\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-08","publicationStatus":"PW","scienceBaseUri":"59424b39e4b0764e6c65dc30","contributors":{"authors":[{"text":"Fletcher, Jon Peter B. 0000-0001-8885-6177 jfletcher@usgs.gov","orcid":"https://orcid.org/0000-0001-8885-6177","contributorId":1216,"corporation":false,"usgs":true,"family":"Fletcher","given":"Jon","email":"jfletcher@usgs.gov","middleInitial":"Peter B.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":698169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erdem, Jemile 0000-0003-2353-9431 jerdem@usgs.gov","orcid":"https://orcid.org/0000-0003-2353-9431","contributorId":127700,"corporation":false,"usgs":true,"family":"Erdem","given":"Jemile","email":"jerdem@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":698172,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seats, Kevin","contributorId":192927,"corporation":false,"usgs":false,"family":"Seats","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":698170,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawrence, Jesse","contributorId":192928,"corporation":false,"usgs":false,"family":"Lawrence","given":"Jesse","affiliations":[],"preferred":false,"id":698171,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170099,"text":"70170099 - 2016 - Influence of manatees' diving on their risk of collision with watercraft","interactions":[],"lastModifiedDate":"2016-07-11T15:44:59","indexId":"70170099","displayToPublicDate":"2016-04-07T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Influence of manatees' diving on their risk of collision with watercraft","docAbstract":"Watercraft pose a threat to endangered Florida manatees (Trichechus manatus latirostris). Mortality from watercraft collisions has adversely impacted the manatee population’s growth rate, therefore reducing this threat is an important management goal. To assess factors that contribute to the risk of watercraft strikes to manatees, we studied the diving behavior of nine manatees carrying GPS tags and time–depth recorders in Tampa Bay, Florida, during winters 2002–2006. We applied a Bayesian formulation of generalized linear mixed models to depth data to model the probability (Pt) that manatees would be no deeper than 1.25 m from the water’s surface as a function of behavioral and habitat covariates. Manatees above this threshold were considered to be within striking depth of a watercraft. Seventy-eight percent of depth records (individual range 62–86%) were within striking depth (mean = 1.09 m, max = 16.20 m), illustrating how vulnerable manatees are to strikes. In some circumstances manatees made consecutive dives to the bottom while traveling, even in areas >14 m, possibly to conserve energy. This is the first documentation of potential cost-efficient diving behavior in manatees. Manatees were at higher risk of being within striking depth in shallow water (<0.91 m), over seagrass, at night, and while stationary or moving slowly; they were less likely to be within striking depth when ≤50 m from a charted waterway. In shallow water the probability of a manatee being within striking depth was 0.96 (CI = 0.93–0.98) and decreased as water depth increased. The probability was greater over seagrass (Pt = 0.96, CI = 0.93–0.98) than over other substrates (Pt = 0.73, CI = 0.58–0.84). Quantitative approaches to assessing risk can improve the effectiveness of manatee conservation measures by helping identify areas for protection.
","language":"English","publisher":"PLos One","doi":"10.1371/journal.pone.0151450","usgsCitation":"Edwards, H.H., Martin, J., Deutsch, C., Muller, R.G., Koslovsky, S.M., Smith, A., and Barlas, M., 2016, Influence of manatees' diving on their risk of collision with watercraft: PLoS ONE, v. 11, no. 4, 15 p., https://doi.org/10.1371/journal.pone.0151450.","productDescription":"15 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060636","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471085,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0151450","text":"Publisher Index Page"},{"id":319882,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.76275634765625,\n 28.13133880763851\n ],\n [\n -82.4139404296875,\n 28.06228599981216\n ],\n [\n -82.3260498046875,\n 27.81357174811185\n ],\n [\n -82.47299194335936,\n 27.410785702577023\n ],\n [\n -82.72018432617188,\n 27.42297612892041\n ],\n [\n -82.84790039062499,\n 27.847576211806295\n ],\n [\n -82.85888671875,\n 28.02592458049937\n ],\n [\n -82.84515380859375,\n 28.13133880763851\n ],\n [\n -82.77374267578125,\n 28.13739395116007\n ],\n [\n -82.76275634765625,\n 28.13133880763851\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-06","publicationStatus":"PW","scienceBaseUri":"5710bf30e4b0ef3b7ca55149","contributors":{"authors":[{"text":"Edwards, Holly H.","contributorId":66419,"corporation":false,"usgs":true,"family":"Edwards","given":"Holly","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":626165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Julien 0000-0002-7375-129X julienmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":5785,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","email":"julienmartin@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":626164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deutsch, Charles J.","contributorId":64135,"corporation":false,"usgs":true,"family":"Deutsch","given":"Charles J.","affiliations":[],"preferred":false,"id":626166,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muller, Robert G","contributorId":168507,"corporation":false,"usgs":false,"family":"Muller","given":"Robert","email":"","middleInitial":"G","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":626167,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koslovsky, Stacie M.","contributorId":168508,"corporation":false,"usgs":false,"family":"Koslovsky","given":"Stacie","email":"","middleInitial":"M.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":626168,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Alexander J.","contributorId":140345,"corporation":false,"usgs":false,"family":"Smith","given":"Alexander J.","affiliations":[{"id":13464,"text":"Environmental Analyst, NY State Dept of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":626169,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barlas, Margie E.","contributorId":168510,"corporation":false,"usgs":false,"family":"Barlas","given":"Margie E.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":626170,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70170157,"text":"70170157 - 2016 - From \"Duck Factory\" to \"Fish Factory\": Climate induced changes in vertebrate communities of prairie pothole wetlands and small lakes","interactions":[],"lastModifiedDate":"2017-01-03T16:18:55","indexId":"70170157","displayToPublicDate":"2016-04-07T09:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"From \"Duck Factory\" to \"Fish Factory\": Climate induced changes in vertebrate communities of prairie pothole wetlands and small lakes","docAbstract":"The Prairie Pothole Region’s myriad wetlands and small lakes contribute to its stature as the “duck factory” of North America. The fishless nature of the region’s aquatic habitats, a result of frequent drying, freezing, and high salinity, influences its importance to waterfowl. Recent precipitation increases have resulted in higher water levels and wetland/lake freshening. In 2012–13, we sampled chemical characteristics and vertebrates (fish and salamanders) of 162 Prairie Pothole wetlands and small lakes. We used non-metric multidimensional scaling, principal component analysis, and bootstrapping techniques to reveal relationships. We found fish present in a majority of sites (84 %). Fish responses to water chemistry varied by species. Fathead minnows (Pimephales promelas) and brook sticklebacks (Culaea inconstans) occurred across the broadest range of conditions. Yellow perch (Perca flavescens) occurred in a smaller, chemically defined, subset. Iowa darters (Etheostoma exile) were restricted to the narrowest range of conditions. Tiger salamanders (Ambystoma mavortium) rarely occurred in lakes with fish. We also compared our chemical data to similar data collected in 1966–1976 to explore factors contributing to the expansion of fish into previously fishless sites. Our work contributes to a better understanding of relationships between aquatic biota and climate-induced changes in this ecologically important area.
","language":"English","publisher":"Society of Wetland Scientists","publisherLocation":"McClean, VA","doi":"10.1007/s13157-016-0766-3","usgsCitation":"McLean, K.I., Mushet, D.M., and Stockwell, C., 2016, From \"Duck Factory\" to \"Fish Factory\": Climate induced changes in vertebrate communities of prairie pothole wetlands and small lakes: Wetlands, v. 36, no. s2, p. 407-421, https://doi.org/10.1007/s13157-016-0766-3.","productDescription":"15 p.","startPage":"407","endPage":"421","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068956","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":319944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","county":"Kidder County, Stutsman County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-100.1129,47.3272],[-100.0347,47.327],[-99.6498,47.3274],[-99.6077,47.3267],[-99.5248,47.3275],[-99.4801,47.3267],[-99.2669,47.3268],[-98.8466,47.327],[-98.8392,47.327],[-98.8232,47.3272],[-98.8152,47.3271],[-98.4991,47.327],[-98.467,47.3266],[-98.4677,47.2402],[-98.4685,46.9788],[-98.4412,46.9789],[-98.4396,46.6296],[-98.7894,46.6294],[-99.0379,46.6309],[-99.1616,46.6317],[-99.4122,46.6316],[-99.4498,46.6319],[-99.912,46.6319],[-100.0799,46.6316],[-100.0794,46.705],[-100.0794,46.7123],[-100.0792,46.7454],[-100.0791,46.7513],[-100.0777,46.9794],[-100.1162,46.98],[-100.1139,47.1567],[-100.1129,47.3272]]]},\"properties\":{\"name\":\"Kidder\",\"state\":\"ND\"}}]}","volume":"36","issue":"s2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-07","publicationStatus":"PW","scienceBaseUri":"570ccab2e4b0ef3b7ca14718","contributors":{"authors":[{"text":"McLean, Kyle I. kmclean@usgs.gov","contributorId":147397,"corporation":false,"usgs":true,"family":"McLean","given":"Kyle","email":"kmclean@usgs.gov","middleInitial":"I.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":626292,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":626291,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stockwell, Craig A.","contributorId":55257,"corporation":false,"usgs":true,"family":"Stockwell","given":"Craig A.","affiliations":[],"preferred":false,"id":626293,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70170463,"text":"70170463 - 2016 - Integrated assessment of wastewater treatment plant effluent estrogenicity in the Upper Murray River, Australia, using the native Murray rainbowfish (Melanotaenia fluviatilis)","interactions":[],"lastModifiedDate":"2018-08-09T12:33:24","indexId":"70170463","displayToPublicDate":"2016-04-07T06:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Integrated assessment of wastewater treatment plant effluent estrogenicity in the Upper Murray River, Australia, using the native Murray rainbowfish (Melanotaenia fluviatilis)","docAbstract":"The contamination of major continental river systems by endocrine-active chemicals (EACs) derived from the discharge of wastewater treatment plant (WWTP) effluents can affect human and ecosystem health. As part of a long-term effort to develop a native fish model organism for assessment of endocrine disruption in Australia's largest watershed, the Murray-Darling River Basin, the present study evaluated endocrine disruption in adult males of the native Australian Murray rainbowfish (Melanotaenia fluviatilis) exposed to effluent from an activated sludge WWTP and water from the Murray River during a 28-d, continuous-flow, on-site experiment. Analysis of the WWTP effluent and river water detected estrone and 17β-estradiol at concentrations up to approximately 25 ng L−1. Anti-estrogenicity of effluent samples was detected in vitro using yeast-based bioassays (yeast estrogen screen) throughout the experiment, but estrogenicity was limited to the first week of the experiment. Histological evaluation of the testes indicated significant suppression of spermatogenesis by WWTP effluent after 28 d of exposure. Plasma vitellogenin concentrations and expression of vitellogenin messenger RNA in liver were not significantly affected by exposure to WWTP effluent. The combination of low contaminant concentrations in the WWTP effluent, limited endocrine disrupting effects in the Murray rainbowfish, and high in-stream dilution factors (>99%) suggest minimal endocrine disruption impacts on native Australian fish in the Murray River downstream from the WWTP outfall.
","language":"English","publisher":"Elsevier Science","doi":"10.1002/etc.2895","usgsCitation":"Vajda, A.M., Kumar, A., Woods, M., Williams, M., Doan, H., Tolsher, P., Kookana, R.S., and Barber, L.B., 2016, Integrated assessment of wastewater treatment plant effluent estrogenicity in the Upper Murray River, Australia, using the native Murray rainbowfish (Melanotaenia fluviatilis): Environmental Toxicology and Chemistry, v. 34, no. 5, p. 1078-1087, https://doi.org/10.1002/etc.2895.","productDescription":"10 p.","startPage":"1078","endPage":"1087","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062599","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":320526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","otherGeospatial":"Upper Murray 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lbbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":921,"corporation":false,"usgs":true,"family":"Barber","given":"Larry","email":"lbbarber@usgs.gov","middleInitial":"B.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":627311,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70170081,"text":"sim3352 - 2016 - Potentiometric surfaces, summer 2013 and winter 2015, and select hydrographs for the Southern High Plains aquifer, Cannon Air Force Base, Curry County, New Mexico","interactions":[],"lastModifiedDate":"2016-04-11T08:44:03","indexId":"sim3352","displayToPublicDate":"2016-04-07T00:00:00","publicationYear":"2016","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":"3352","title":"Potentiometric surfaces, summer 2013 and winter 2015, and select hydrographs for the Southern High Plains aquifer, Cannon Air Force Base, Curry County, New Mexico","docAbstract":"Cannon Air Force Base (Cannon AFB) is located in the High Plains physiographic region of east-central New Mexico, about 5 miles west of Clovis, New Mexico. The area surrounding Cannon AFB is primarily used for agriculture, including irrigated cropland and dairies. The Southern High Plains aquifer is the principal source of water for Cannon AFB, for the nearby town of Clovis, and for local agriculture and dairies. The Southern High Plains aquifer in the vicinity of Cannon AFB consists of three subsurface geological formations: the Chinle Formation of Triassic age, the Ogallala Formation of Tertiary age, and the Blackwater Draw Formation of Quaternary age. The Ogallala Formation is the main water-yielding formation of the Southern High Plains aquifer. Groundwater-supplied, center-pivot irrigation dominates pumping from the Southern High Plains aquifer in the area surrounding Cannon AFB, where the irrigation season typically extends from early March through October. The U.S. Geological Survey has been monitoring groundwater levels in the vicinity of Cannon AFB since 1954 and has developed general potentiometric-surface maps that show groundwater flow from northwest to southeast in the study area. While previous potentiometric-surface maps show the general direction of groundwater flow, a denser well network is needed to show details of groundwater flow at a local scale. Groundwater levels were measured in 93 wells during summer 2013 and 100 wells during winter 2015.
The summer and winter potentiometric-surface maps display the presence of what is interpreted to be a groundwater trough trending from the northwest to the southeast through the study area. This groundwater trough may be the hydraulic expression of a Tertiary-age paleochannel. Groundwater north of the trough flows in a southerly direction into the trough, and groundwater south of the trough flows in an easterly direction into the trough.
During the 18-month period between summer 2013 and winter 2015, changes in groundwater levels ranged from a rise of 10.0 to a decline of 3.8 feet. The regions to the north and south of the groundwater trough contained the majority of the rises in groundwater levels, whereas the regions within the trough contained the majority of the declines in groundwater levels. In contrast, the long-term groundwater-level trend in wells with 20 to 60 years of record is a steady decline in average annual water levels, with declines ranging from 0.41 to 2.81 feet per year. Overall, the northwestern part of the study area exhibits the smallest average annual declines, while the southeastern part of the study area exhibits the largest average annual declines.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3352","collaboration":"Prepared in cooperation with the Air Force Civil Engineer Center, San Antonio, Texas","usgsCitation":"Collison, Jake, 2016, Potentiometric surfaces, summer 2013 and winter 2015, and select hydrographs for the Southern High Plains aquifer, Cannon Air Force Base, Curry County, New Mexico: U.S. Geological Survey Scientific Investigations Map 3352, https://dx.doi.org/10.3133/sim3352.","productDescription":"2 Sheets: 22 x 30 inches","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069490","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":319842,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3352/sim3352.pdf","text":"Map","size":"3.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3352"},{"id":319796,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3352/coverthb.jpg"}],"country":"United States","state":"New Mexico","county":"Curry County","otherGeospatial":"Southern High Plains Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.1997299194336,\n 34.30799463462751\n ],\n [\n -103.20213317871094,\n 34.32472485669068\n ],\n [\n -103.20144653320312,\n 34.349105308603086\n ],\n [\n -103.20144653320312,\n 34.36922801491184\n ],\n [\n -103.20144653320312,\n 34.387079327815805\n ],\n [\n -103.20247650146484,\n 34.415406930259294\n ],\n [\n -103.20281982421875,\n 34.43239888779366\n ],\n [\n -103.20625305175781,\n 34.453350878522286\n ],\n [\n -103.2117462158203,\n 34.45844651413059\n ],\n [\n -103.22410583496094,\n 34.46552326993406\n ],\n [\n -103.23715209960938,\n 34.468353804284924\n ],\n [\n -103.25809478759764,\n 34.469769035464836\n ],\n [\n -103.27869415283203,\n 34.47203335543746\n ],\n [\n -103.29689025878905,\n 34.472599425831355\n ],\n [\n -103.32572937011719,\n 34.47458064197167\n ],\n [\n -103.34152221679688,\n 34.47797690306098\n ],\n [\n -103.36658477783203,\n 34.47882594673332\n ],\n [\n -103.38512420654297,\n 34.477693886583516\n ],\n [\n -103.4036636352539,\n 34.474014585017066\n ],\n [\n -103.40572357177734,\n 34.46920294587255\n ],\n [\n -103.41053009033203,\n 34.45788034775209\n ],\n [\n -103.41053009033203,\n 34.44259240448441\n ],\n [\n -103.41190338134766,\n 34.43466422118617\n ],\n [\n -103.41293334960938,\n 34.41795594404557\n ],\n [\n -103.41361999511719,\n 34.41059191445944\n ],\n [\n -103.41293334960938,\n 34.40237742424137\n ],\n [\n -103.41121673583984,\n 34.39387882699731\n ],\n [\n -103.40744018554688,\n 34.38311269824024\n ],\n [\n -103.4084701538086,\n 34.37206181069581\n ],\n [\n -103.40572357177734,\n 34.361292876752564\n ],\n [\n -103.39508056640625,\n 34.35193978491414\n ],\n [\n -103.3868408203125,\n 34.34627073645813\n ],\n [\n -103.38306427001952,\n 34.336348979311985\n ],\n [\n -103.38272094726561,\n 34.326426048404265\n ],\n [\n -103.37448120117188,\n 34.3207552752374\n ],\n [\n -103.3480453491211,\n 34.31678550602219\n ],\n [\n -103.31817626953125,\n 34.313382697259456\n ],\n [\n -103.2879638671875,\n 34.311397661782244\n ],\n [\n -103.26221466064453,\n 34.30969616544571\n ],\n [\n -103.23646545410156,\n 34.30997975056304\n ],\n [\n -103.21792602539062,\n 34.30714385628804\n ],\n [\n -103.1997299194336,\n 34.30799463462751\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
5338 Montgomery Blvd. NE, Suite 400
Albuquerque, NM 87109–1311
In 2014, Clade 2.3.4.4 H5N8 highly pathogenic avian influenza (HPAI) viruses spread across the Republic of Korea and ultimately were reported in China, Japan, Russia and Europe. Mortality associated with a reassortant HPAI H5N2 virus was detected in poultry farms in Western Canada at the end of November. The same strain (with identical genetic structure) was then detected in free-living wild birds that had died prior to December 8 of unrelated causes in Whatcom County, Washington, USA in an area contiguous with the index Canadian location. A gyrfalcon (Falco rusticolus) that had hunted and fed on an American wigeon (Anas americana) on December 6 in the same area and died two days later, tested positive for the Eurasian origin HPAI H5N8. Subsequently, an Active Surveillance Program using hunter-harvest waterfowl in Washington and Oregon detected ten HPAI H5 viruses, of three different subtypes (four H5N2, three H5N8 and three H5N1) with 4 segments in common (HA, PB2, NP and MA). In addition, a mortality-based Passive Surveillance Program detected 18 HPAI (14 H5N2 and four H5N8) cases from Idaho, Kansas, Oregon, Minnesota, Montana, Washington and Wisconsin. Comparatively, mortality-based passive surveillance appears to be detecting these HPAI infections at a higher rate than active surveillance during the period following initial introduction into the US.
","language":"English","publisher":"American Association of Avian Pathologists","publisherLocation":"Ithaca, NY","doi":"10.1637/11137-050815-Reg","usgsCitation":"Ip, S., Dusek, R.J., Bodenstein, B., Kim Torchetti, M., DeBruyn, P., Mansfield, K.G., DeLiberto, T., and Sleeman, J.M., 2016, High rates of detection of Clade 2.3.4.4 Highly Pathogenic Avian Influenza H5 viruses in wild birds in the Pacific Northwest during the winter of 2014-2015: Avian Diseases, v. 60, no. 1s, p. 354-358, https://doi.org/10.1637/11137-050815-Reg.","productDescription":"5 p.","startPage":"354","endPage":"358","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065496","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":319830,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"1s","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5719f9b9e4b071321fe22bd1","contributors":{"authors":[{"text":"Ip, S. 0000-0003-4844-7533 hip@usgs.gov","orcid":"https://orcid.org/0000-0003-4844-7533","contributorId":727,"corporation":false,"usgs":true,"family":"Ip","given":"S.","email":"hip@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":626102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dusek, Robert J. 0000-0001-6177-7479 rdusek@usgs.gov","orcid":"https://orcid.org/0000-0001-6177-7479","contributorId":152316,"corporation":false,"usgs":true,"family":"Dusek","given":"Robert","email":"rdusek@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":626113,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bodenstein, Barbara L. 0000-0001-7946-0103 bbodenstein@usgs.gov","orcid":"https://orcid.org/0000-0001-7946-0103","contributorId":139354,"corporation":false,"usgs":true,"family":"Bodenstein","given":"Barbara L.","email":"bbodenstein@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":626114,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kim Torchetti, Mia","contributorId":139355,"corporation":false,"usgs":false,"family":"Kim Torchetti","given":"Mia","email":"","affiliations":[{"id":12747,"text":"USDA APHIS VS National Veterinary Services Laboratories, Ames, IA","active":true,"usgs":false}],"preferred":false,"id":626103,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeBruyn, Paul","contributorId":139364,"corporation":false,"usgs":false,"family":"DeBruyn","given":"Paul","email":"","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":626111,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mansfield, Kristin G.","contributorId":139359,"corporation":false,"usgs":false,"family":"Mansfield","given":"Kristin","email":"","middleInitial":"G.","affiliations":[{"id":12748,"text":"State of Washington","active":true,"usgs":false}],"preferred":false,"id":626112,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DeLiberto, Thomas J.","contributorId":139362,"corporation":false,"usgs":false,"family":"DeLiberto","given":"Thomas J.","affiliations":[{"id":12749,"text":"USDA APHIS National Wildlife Research Center, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":626117,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sleeman, Jonathan M. 0000-0002-9910-6125 jsleeman@usgs.gov","orcid":"https://orcid.org/0000-0002-9910-6125","contributorId":128,"corporation":false,"usgs":true,"family":"Sleeman","given":"Jonathan","email":"jsleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":626118,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70170072,"text":"70170072 - 2016 - Differentiating sex and species of Western Grebes (Aechmophorus occidentalis) and Clark's Grebes (Aechmophorus clarkii) and their eggs using external morphometrics and discriminant function analysis","interactions":[],"lastModifiedDate":"2018-08-07T11:53:57","indexId":"70170072","displayToPublicDate":"2016-04-06T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Differentiating sex and species of Western Grebes (Aechmophorus occidentalis) and Clark's Grebes (Aechmophorus clarkii) and their eggs using external morphometrics and discriminant function analysis","docAbstract":"In birds where males and females are similar in size and plumage, sex determination by alternative means is necessary. Discriminant function analysis based on external morphometrics was used to distinguish males from females in two closely related species: Western Grebe (Aechmophorus occidentalis) and Clark's Grebe (A. clarkii). Additionally, discriminant function analysis was used to evaluate morphometric divergence between Western and Clark's grebe adults and eggs. Aechmophorus grebe adults (n = 576) and eggs (n = 130) were sampled across 29 lakes and reservoirs throughout California, USA, and adult sex was determined using molecular analysis. Both Western and Clark's grebes exhibited considerable sexual size dimorphism. Males averaged 6–26% larger than females among seven morphological measurements, with the greatest sexual size dimorphism occurring for bill morphometrics. Discriminant functions based on bill length, bill depth, and short tarsus length correctly assigned sex to 98% of Western Grebes, and a function based on bill length and bill depth correctly assigned sex to 99% of Clark's Grebes. Further, a simplified discriminant function based only on bill depth correctly assigned sex to 96% of Western Grebes and 98% of Clark's Grebes. In contrast, external morphometrics were not suitable for differentiating between Western and Clark's grebe adults or their eggs, with correct classification rates of discriminant functions of only 60%, 63%, and 61% for adult males, adult females, and eggs, respectively. Our results indicate little divergence in external morphology between species of Aechmophorus grebes, and instead separation is much greater between males and females.
","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.039.0103","usgsCitation":"Hartman, C.A., Ackerman, J., Eagles-Smith, C.A., and Herzog, M.P., 2016, Differentiating sex and species of Western Grebes (Aechmophorus occidentalis) and Clark's Grebes (Aechmophorus clarkii) and their eggs using external morphometrics and discriminant function analysis: Waterbirds, v. 39, no. 1, p. 13-26, https://doi.org/10.1675/063.039.0103.","productDescription":"14 p.","startPage":"13","endPage":"26","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068816","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":319822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"572477a4e4b0b13d3914e046","contributors":{"authors":[{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131109,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":626025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":626024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":626026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":626027,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170085,"text":"70170085 - 2016 - Semi-arid vegetation response to antecedent climate and water balance windows","interactions":[],"lastModifiedDate":"2016-06-15T16:24:21","indexId":"70170085","displayToPublicDate":"2016-04-06T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":849,"text":"Applied Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Semi-arid vegetation response to antecedent climate and water balance windows","docAbstract":"Can we improve understanding of vegetation response to water availability on monthly time scales in semi-arid environments using remote sensing methods? What climatic or water balance variables and antecedent windows of time associated with these variables best relate to the condition of vegetation? Can we develop credible near-term forecasts from climate data that can be used to prepare for future climate change effects on vegetation?
\nSemi-arid grasslands in Capitol Reef National Park, Utah, USA.
\nWe built vegetation response models by relating the normalized difference vegetation index (NDVI) from MODIS imagery in Mar–Nov 2000–2013 to antecedent climate and water balance variables preceding the monthly NDVI observations. We compared how climate and water balance variables explained vegetation greenness and then used a multi-model ensemble of climate and water balance models to forecast monthly NDVI for three holdout years.
\nWater balance variables explained vegetation greenness to a greater degree than climate variables for most growing season months. Seasonally important variables included measures of antecedent water input and storage in spring, switching to indicators of drought, input or use in summer, followed by antecedent moisture availability in autumn. In spite of similar climates, there was evidence the grazed grassland showed a response to drying conditions 1 mo sooner than the ungrazed grassland. Lead times were generally short early in the growing season and antecedent window durations increased from 3 mo early in the growing season to 1 yr or more as the growing season progressed. Forecast accuracy for three holdout years using a multi-model ensemble of climate and water balance variables outperformed forecasts made with a naïve NDVI climatology.
\nWe determined the influence of climate and water balance on vegetation at a fine temporal scale, which presents an opportunity to forecast vegetation response with short lead times. This understanding was obtained through high-frequency vegetation monitoring using remote sensing, which reduces the costs and time necessary for field measurements and can lead to more rapid detection of vegetation changes that could help managers take appropriate actions.
\nPrecipitation patterns and nutrient inputs affect transport of nitrate (NO3-N) and phosphorus (TP) from Midwest watersheds. Nutrient concentrations and yields from two subsurface-drained watersheds, the Little Cobb River (LCR) in southern Minnesota and the South Fork Iowa River (SFIR) in northern Iowa, were evaluated during 1996–2007 to document relative differences in timings and amounts of nutrients transported. Both watersheds are located in the prairie pothole region, but the SFIR exhibits a longer growing season and more livestock production. The SFIR yielded significantly more NO3-N than the LCR watershed (31.2 versus 21.3 kg NO3-N ha− 1 y− 1). The SFIR watershed also yielded more TP than the LCR watershed (1.13 versus 0.51 kg TP ha− 1 yr− 1), despite greater TP concentrations in the LCR. About 65% of NO3-N and 50% of TP loads were transported during April–June, and < 20% of the annual loads were transported later in the growing season from July–September. Monthly NO3-N and TP loads peaked in April from the LCR but peaked in June from the SFIR; this difference was attributed to greater snowmelt runoff in the LCR. The annual NO3-N yield increased with increasing annual runoff at a similar rate in both watersheds, but the LCR watershed yielded less annual NO3-N than the SFIR for a similar annual runoff. These two watersheds are within 150 km of one another and have similar dominant agricultural systems, but differences in climate and cropping inputs affected amounts and timing of nutrient transport.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.03.127","usgsCitation":"Kalkhoff, S.J., Hubbard, L.E., Tomer, M.D., and James, D., 2016, Effect of variable annual precipitation and nutrient input on nitrogen and phosphorus transport from two Midwestern agricultural watersheds: Science of the Total Environment, v. 559, p. 53-62, https://doi.org/10.1016/j.scitotenv.2016.03.127.","productDescription":"10 p.","startPage":"53","endPage":"62","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066764","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":471088,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.03.127","text":"Publisher Index Page"},{"id":319818,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"559","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"572477a5e4b0b13d3914e070","chorus":{"doi":"10.1016/j.scitotenv.2016.03.127","url":"http://dx.doi.org/10.1016/j.scitotenv.2016.03.127","publisher":"Elsevier BV","authors":"Kalkhoff S.J., Hubbard L.E., Tomer M.D., James D.E.","journalName":"Science of The Total Environment","publicationDate":"7/2016","publiclyAccessibleDate":"4/5/2017"},"contributors":{"authors":[{"text":"Kalkhoff, Stephen J. 0000-0003-4110-1716 sjkalkho@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-1716","contributorId":1731,"corporation":false,"usgs":true,"family":"Kalkhoff","given":"Stephen","email":"sjkalkho@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hubbard, Laura E. 0000-0003-3813-1500 lhubbard@usgs.gov","orcid":"https://orcid.org/0000-0003-3813-1500","contributorId":4221,"corporation":false,"usgs":true,"family":"Hubbard","given":"Laura","email":"lhubbard@usgs.gov","middleInitial":"E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tomer, Mark D.","contributorId":168489,"corporation":false,"usgs":false,"family":"Tomer","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":25309,"text":"U.S. Department of Agriculture Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":626086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"James, D.E.","contributorId":22927,"corporation":false,"usgs":true,"family":"James","given":"D.E.","email":"","affiliations":[],"preferred":false,"id":626087,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159959,"text":"ofr20151231 - 2016 - Report of the River Master of the Delaware River for the period December 1, 2008–November 30, 2009","interactions":[],"lastModifiedDate":"2016-04-06T10:42:33","indexId":"ofr20151231","displayToPublicDate":"2016-04-06T10:30:00","publicationYear":"2016","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":"2015-1231","title":"Report of the River Master of the Delaware River for the period December 1, 2008–November 30, 2009","docAbstract":"A Decree of the Supreme Court of the United States, entered June 7, 1954, established the position of Delaware River Master within the U.S. Geological Survey (USGS). In addition, the Decree authorizes diversions of water from the Delaware River Basin and requires compensating releases from certain reservoirs, owned by New York City, to be made under the supervision and direction of the River Master. The Decree stipulates that the River Master will furnish reports to the Court, not less frequently than annually. This report is the 56th Annual Report of the River Master of the Delaware River. It covers the 2009 River Master report year, the period from December 1, 2008, to November 30, 2009.
During the report year, precipitation in the upper Delaware River Basin was 50.89 inches (in.) or 116 percent of the long-term average. Combined storage in Pepacton, Cannonsville, and Neversink Reservoirs remained high throughout the year and did not decline below 80 percent of combined capacity at any time. Delaware River operations during the year were conducted as stipulated by the Decree and the Flexible Flow Management Program (FFMP).
Diversions from the Delaware River Basin by New York City and New Jersey were in full compliance with the Decree. Reservoir releases were made as directed by the River Master at rates designed to meet the flow objective for the Delaware River at Montague, New Jersey, on 25 days during the report year. Releases were made at conservation rates—rates designed to relieve thermal stress and protect the fishery and aquatic habitat in the tailwaters of the reservoirs—on all other days.
During the report year, New York City and New Jersey complied fully with the terms of the Decree, and directives and requests of the River Master.
As part of a long-term program, the quality of water in the Delaware Estuary between Trenton, New Jersey, and Reedy Island Jetty, Delaware, was monitored at various locations. Data on water temperature, specific conductance, dissolved oxygen, and pH were collected continuously by electronic instruments at four sites. In addition, selected water-quality data were collected at 22 sites on a monthly basis.
The Delaware River Basin Commission (DRBC) collects monthly samples from March through October at 22 sites between Biles Channel and South Brown Shoal. Samples were collected and analyzed by the State of Delaware for the DRBC. At each site, water samples were collected at a single point near the center of the channel near the surface and analyzed for selected physical properties, and chemical and biological constituents including routine chemical substances, nutrients and bacteria. These consist of analyses of field measurements and laboratory determinations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151231","usgsCitation":"Krejmas, B.E., Paulachok, G.N., Mason, R.R., Jr., and Owens, Marie, 2016, Report of the River Master of the Delaware River for the period December 1, 2008–November 30, 2009: U.S. Geological Survey Open-File Report 2015–1231, 76 p., https://dx.doi.org/10.3133/ofr20151231.","productDescription":"vi, 76 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2008-12-01","ipdsId":"IP-070813","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":319219,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1231/ofr20151231.pdf","size":"1.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1231"},{"id":319218,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1231/coverthb.jpg"}],"country":"United States","otherGeospatial":"Delaware River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.4815673828125,\n 39.70296052957233\n ],\n [\n -74.498291015625,\n 39.8465036024177\n ],\n [\n -74.4927978515625,\n 40.26695230509781\n ],\n [\n -74.970703125,\n 40.75974059207392\n ],\n [\n -74.6685791015625,\n 40.979898069620155\n ],\n [\n -74.5806884765625,\n 41.335575973123895\n ],\n [\n -74.11376953125,\n 42.13082130188811\n ],\n [\n -74.9432373046875,\n 42.44372793752476\n ],\n [\n -75.574951171875,\n 42.00848901572399\n ],\n [\n -75.8880615234375,\n 41.244772343082104\n ],\n [\n -76.343994140625,\n 40.329795743702064\n ],\n [\n -76.04736328125,\n 39.73253798438173\n ],\n [\n -75.4815673828125,\n 39.70296052957233\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Deputy Delaware River Master
U.S. Geological Survey
10 Buist Road, Bldg. 3, Suite 304
Milford Professional Park
Milford, PA 18337
Fax: 570–296–9414
http://water.usgs.gov/osw/odrm/
The Kansas River is a primary source of drinking water for about 800,000 people in northeastern Kansas. Source-water supplies are treated by a combination of chemical and physical processes to remove contaminants before distribution. Advanced notification of changing water-quality conditions and cyanobacteria and associated toxin and taste-and-odor compounds provides drinking-water treatment facilities time to develop and implement adequate treatment strategies. The U.S. Geological Survey (USGS), in cooperation with the Kansas Water Office (funded in part through the Kansas State Water Plan Fund), and the City of Lawrence, the City of Topeka, the City of Olathe, and Johnson County Water One, began a study in July 2012 to develop statistical models at two Kansas River sites located upstream from drinking-water intakes. Continuous water-quality monitors have been operated and discrete-water quality samples have been collected on the Kansas River at Wamego (USGS site number 06887500) and De Soto (USGS site number 06892350) since July 2012. Continuous and discrete water-quality data collected during July 2012 through June 2015 were used to develop statistical models for constituents of interest at the Wamego and De Soto sites. Logistic models to continuously estimate the probability of occurrence above selected thresholds were developed for cyanobacteria, microcystin, and geosmin. Linear regression models to continuously estimate constituent concentrations were developed for major ions, dissolved solids, alkalinity, nutrients (nitrogen and phosphorus species), suspended sediment, indicator bacteria (Escherichia coli, fecal coliform, and enterococci), and actinomycetes bacteria. These models will be used to provide real-time estimates of the probability that cyanobacteria and associated compounds exceed thresholds and of the concentrations of other water-quality constituents in the Kansas River. The models documented in this report are useful for characterizing changes in water-quality conditions through time, characterizing potentially harmful cyanobacterial events, and indicating changes in water-quality conditions that may affect drinking-water treatment processes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161040","collaboration":"Prepared in cooperation with the Kansas Water Office, the City of Lawrence, the City of Topeka, the City of Olathe, and Johnson County Water One","usgsCitation":"Foster, G.M., and Graham, J.L., 2016, Logistic and linear regression model documentation for statistical relations between continuous real-time and discrete water-quality constituents in the Kansas River, Kansas, July 2012 through June 2015: U.S. Geological Survey Open-File Report 2016–1040, 27 p., https://dx.doi.org/10.3133/ofr20161040. ","productDescription":"Report: iv, 27 p.; 31 Appendixes","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-071163","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":319781,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1040/coverthb.jpg"},{"id":319791,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1040/downloads/","text":"Appendixes 1 through 31","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1040 Appendixes"},{"id":319782,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1040/ofr20161040.pdf","text":"Report","size":"830 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1040"}],"country":"United States","state":"Kansas","otherGeospatial":"Kansas River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.6142578125,\n 38.81403111409755\n ],\n [\n -94.921875,\n 39.14710270770074\n ],\n [\n -95.185546875,\n 39.45316112807394\n ],\n [\n -95.5810546875,\n 39.90130858574735\n ],\n [\n -95.635986328125,\n 39.95185892663005\n ],\n [\n -95.82275390625,\n 39.707186656826565\n ],\n [\n -96.207275390625,\n 39.690280594818034\n ],\n [\n -96.39404296875,\n 39.487084981687495\n ],\n [\n -96.50390625,\n 39.18117526158749\n ],\n [\n -96.866455078125,\n 39.26628442213066\n ],\n [\n -96.88842773437499,\n 38.976492485539424\n ],\n [\n -96.910400390625,\n 38.60828592850559\n ],\n [\n -96.94335937499999,\n 38.42777351132905\n ],\n [\n -96.624755859375,\n 38.53097889440026\n ],\n [\n -96.075439453125,\n 38.61687046392973\n ],\n [\n -95.020751953125,\n 38.65119833229951\n ],\n [\n -94.68017578125,\n 38.659777730712534\n ],\n [\n -94.6142578125,\n 38.81403111409755\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place
Lawrence, KS 66049
Watershed restoration is the focus of many resource managers and can include a multitude of restoration actions each with specific restoration objectives. For the White River flowing through the cities of Pacific and Sumner, Washington, a levee setback has been proposed to reconnect the river with its historical floodplain to help reduce flood risks, as well as provide increased habitat for federally listed species of salmonids. The study presented here documents the use of a modeling framework that integrates two-dimensional hydraulic modeling with process-based bioenergetics modeling for predicting how changes in flow from reconnecting the river with its floodplain affects invertebrate drift density and the net rate of energy intake of juvenile salmonids. Modeling results were calculated for flows of 25.9 and 49.3 cubic meters per second during the spring, summer, and fall. Predicted hypothetical future mean velocities and depths were significantly lower and more variable when compared to current conditions. The abundance of low energetic cost and positive growth locations for salmonids were predicted to increase significantly in the study reach following floodplain reconnection, particularly during the summer. This modeling framework presents a viable approach for evaluating the potential fisheries benefits of reconnecting a river to its historical floodplain that integrates our understanding of hydraulic, geomorphology, and organismal biology.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165025","collaboration":"Prepared in cooperation with the King County Water and Land Resources Division","usgsCitation":"Black, R.W., Czuba, C.R., Magirl, C.S., McCarthy, Sarah, Berge, Hans, and Comanor, Kyle, 2016, Effect of a levee setback on aquatic resources using two-dimensional flow and bioenergetics models: U.S. Geological Survey Scientific Investigations Report 2016–5025, 26 p., https://dx.doi.org/10.3133/sir20165025.","productDescription":"v, 26 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066982","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":319584,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5025/coverthb.jpg"},{"id":319585,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5025/sir20165025.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5025"}],"country":"United States","state":"Washington","city":"Pacific","otherGeospatial":"White River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.25688934326172,\n 47.22866141531796\n ],\n [\n -122.25688934326172,\n 47.28633255817871\n ],\n [\n -122.18358993530273,\n 47.28633255817871\n ],\n [\n -122.18358993530273,\n 47.22866141531796\n ],\n [\n -122.25688934326172,\n 47.22866141531796\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
The Chicago Department of Transportation’s Sustainable Streetscapes Program is an innovative program that strives to convert Chicago’s neighborhood commercial areas, riverwalks, and bicycle facilities into active, attractive places for Chicagoans to live, work, and play. The objective of each project is to create flourishing public places while improving the ability of infrastructure to support dense urban living. The U.S. Geological Survey (USGS), in cooperation with the Metropolitan Water Reclamation District of Greater Chicago (MWRDGC), and the Chicago Department of Transportation (CDOT), is monitoring the pre- and postconstruction hydrologic characteristics of an urban corridor on the south side of Chicago that is being renovated using sustainable streetscapes technology.
The CDOT Sustainable Streetscapes Program utilizes urban stormwater best-management practices (BMPs) to reduce the storm runoff to the local combined sewer system. The urban stormwater BMPs include permeable pavement, bioswales, infiltration basins, and planters. The urban stormwater BMPs are designed to capture the first flush of storm runoff through features that enhance the infiltration of stormwater runoff to shallow groundwater.
The hydrology of the Sustainable Streetscapes Program area is being monitored to evaluate the impacts and effectiveness of the urban stormwater BMP’s. Continuous monitoring of rainfall, sewer flows, stormwater runoff, soil moisture, and groundwater levels will give engineers and scientists measured data to define baseline pre- and postconstruction conditions for the evaluation of the BMPs.
Three tipping-bucket rain gages are located along the project corridor. The data provide information on the intensity and volume of rainfall. Rainfall can be highly variable even over a small area like the project corridor.
Continuous recording meters are located at specific locations in the combined sewers to record water level and flow during both dry weather (mostly sanitary flow) and wet weather conditions (stormwater runoff in addition to the sanitary flow). Sanitary flow is the largest source of flow in the combined sewers during dry weather, and stormwater runoff and sanitary flow combine during wet weather. The sewer flow data allow engineers and scientists to calculate total runoff volume for selected storm events.
Wells are located within the project corridor to record water levels and help determine the direction of movement of groundwater in response to rainfall and snowmelt. In urban settings with aging sewer systems, groundwater can seep into the sewers or combined sewage can seep from the sewers into the local groundwater system. The groundwater data are also important in evaluating the overall impacts of increased infiltration resulting from BMPs.
Data from wells show the relative water levels of shallow groundwater, water levels in the combined sewer system, and nearby surface-water channels within the project corridor. In some aging urban sewer systems, the local combined sewer system lies below the water table and receives substantial amounts of groundwater inflow, which can significantly reduce the amount of additional water the sewer system can accept.
The bioswale along the south side of West Cermak Road near South Throop Street functions to infiltrate stormwater runoff from the road. Stormwater on the road surface initially drains to the curb and then flows along the curb until it reaches a curb cut-out. Materials within the bioswale allow stormwater to infiltrate and reduce the load to the combined sewer.
A common feature in urban areas are curbside catch basins that collect stormwater runoff from paved streets. Stormwater drains first to the curb and then flows along the curb to the catch basin. Lateral sewer pipe connects the catch basin to the combined sewer beneath the street. The use of permeable pavers along the curbs in the project study reach let stormwater infiltrate before it reaches the curb, thus reducing the amount of stormwater draining to the combined sewers.
Water-level data from catch basins in the project study area show the effects of permeable pavers in reducing the stormwater drainage to the combined sewers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163014","collaboration":"Prepared in cooperation with the Metropolitan Water Reclamation District of Greater Chicago (MWRDGC), and the Chicago Department of Transportation (CDOT)","usgsCitation":"Duncker, J.J., and Morrow, W.S., 2016, Hydrologic monitoring for Chicago’s Sustainable Streetscapes Program. U.S. Geological Survey Fact Sheet 2016–3014, 6 p., https://dx.doi.org/10.3133/fs20163014.","productDescription":"6 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054040","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":319331,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3014/coverthb.jpg"},{"id":319332,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3014/fs20163014.pdf","text":"Report","size":"3.70 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3014"}],"country":"United States","state":"Illinois","city":"Chicago","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.68531799316406,\n 41.8384904853889\n ],\n [\n -87.68531799316406,\n 41.86035637336661\n ],\n [\n -87.64274597167967,\n 41.86035637336661\n ],\n [\n -87.64274597167967,\n 41.8384904853889\n ],\n [\n -87.68531799316406,\n 41.8384904853889\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
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As part of the Great Lakes and Mississippi River Interbasin Study, the U.S. Army Corps of Engineers (USACE) is conducting an assessment of the vulnerability of the Chicago Area Waterway System and Des Plaines River to Asian carp (specifically, Hypophthalmichthys nobilis (bighead carp) and Hypophthalmichthys molitrix (silver carp)) spawning and recruitment. As part of this assessment, the USACE requested the help of the U.S. Geological Survey in predicting the fate and transport of Asian carp eggs hypothetically spawned at the electric dispersal barrier on the Chicago Sanitary and Ship Canal and downstream of the Brandon Road Lock and Dam on the Des Plaines River under dry weather flow and high water temperature conditions. The Fluvial Egg Drift Simulator (FluEgg) model predicted that approximately 80 percent of silver carp eggs spawned near the electric dispersal barrier would hatch within the Lockport and Brandon Road pools (as close as 3.6 miles downstream of the barrier) and approximately 82 percent of the silver carp eggs spawned near the Brandon Road Dam would hatch in the Des Plaines River (as close as 1.6 miles downstream from the gates of Brandon Road Lock). Extension of the FluEgg model to include the fate and transport of larvae until gas bladder inflation—the point at which the larvae begin to leave the drift—suggests that eggs spawned at the electric dispersal barrier would reach the gas bladder inflation stage primarily within the Dresden Island Pool, and those spawned at the Brandon Road Dam would reach this stage primarily within the Marseilles and Starved Rock Pools.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161011","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, Great Lakes Restoration Initiative","usgsCitation":"Murphy, E.A., Garcia, Tatiana, Jackson, P.R., and Duncker J.J., 2016, Simulation of hypothetical Asian carp egg and larvae development and transport in the Lockport, Brandon Road, Dresden Island, and Marseilles Pools of the Illinois Waterway by use of the fluvial egg drift simulator (FluEgg) model: U.S. Geological Survey Open File Report 2016–1011, 19 p., https://dx.doi.org/10.3133/ofr20161011.","productDescription":"vii, 19 p.","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070545","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":319192,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1011/ofr20161011.pdf","size":"2.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1011"},{"id":319191,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1011/coverthb.jpg"}],"country":"United States","state":"Illinois","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.96728515624999,\n 40.95501133048621\n ],\n [\n -88.96728515624999,\n 41.85319643776675\n ],\n [\n -87.9345703125,\n 41.85319643776675\n ],\n [\n -87.9345703125,\n 40.95501133048621\n ],\n [\n -88.96728515624999,\n 40.95501133048621\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 N Goodwin
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http://il.water.usgs.gov/
The lower Genesee River and Rochester Embayment of Lake Ontario are a designated Area of Concern (AOC) under the binational Great Lakes Water Quality Agreement. The “degradation of phytoplankton and zooplankton populations” or plankton Beneficial Use Impairment (BUI) was classified as unknown and in need of further assessment in this AOC because water quality data suggested plankton communities could be effected and community data were either unavailable or indicated impacts. The plankton BUI may now be obsolete because local contaminant sources have been largely eliminated. The present study was conducted between July 2013 and August 2014 to assess the BUI-removal criteria: “AOC plankton bioassays confirm that toxicity in ambient waters (i.e., no growth inhibition) is not significantly higher than comparable non-AOC controls”. Acute and chronic toxicity of waters from 13 sites were quantified seasonally using standardized bioassays with the green alga Pseudokirchneriella subcapitata and water flea Ceriodaphnia dubia to test the hypothesis that toxicity of waters from AOC sites was not higher than that of waters from comparable non-AOC reference sites. Survival and reproduction of C. dubia did not differ significantly between site types, systems, or months. The growth of P. subcapitata did not differ between site types, but differed among systems and months. All results indicate that waters from AOC sites were no more toxic to both plankton species than waters from reference sites. Assuming test species represent natural plankton assemblages, water quality should not negatively affect survival and growth of resident plankton populations in the Rochester Embayment AOC.
","language":"English","publisher":"International Association for Great Lakes Research","doi":"10.1016/j.jglr.2015.12.007","usgsCitation":"Baldigo, B.P., Duffy, B.T., Smith, A., and George, S.D., 2016, Toxicity of waters from the Rochester Embayment Area of Concern to the plankton species Pseudokirchneriella subcapitata and Ceriodaphnia dubia: Journal of Great Lakes Research, v. 42, no. 2, p. 464-471, https://doi.org/10.1016/j.jglr.2015.12.007.","productDescription":"8 p.","startPage":"464","endPage":"471","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062670","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":471089,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2015.12.007","text":"Publisher Index Page"},{"id":325100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.7005615234375,\n 42.944360446966314\n ],\n [\n -78.7005615234375,\n 43.44893105587766\n ],\n [\n -76.80541992187499,\n 43.44893105587766\n ],\n [\n -76.80541992187499,\n 42.944360446966314\n ],\n [\n -78.7005615234375,\n 42.944360446966314\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"2","edition":"2016","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"579dd04ee4b0589fa1cbdf45","chorus":{"doi":"10.1016/j.jglr.2015.12.007","url":"http://dx.doi.org/10.1016/j.jglr.2015.12.007","publisher":"Elsevier BV","authors":"Baldigo Barry P., Duffy Brian T., Smith Alexander J., George Scott D.","journalName":"Journal of Great Lakes Research","publicationDate":"4/2016"},"contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642213,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duffy, Brian T.","contributorId":6352,"corporation":false,"usgs":true,"family":"Duffy","given":"Brian","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":642215,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Alexander J.","contributorId":140345,"corporation":false,"usgs":false,"family":"Smith","given":"Alexander J.","affiliations":[{"id":13464,"text":"Environmental Analyst, NY State Dept of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":642216,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642214,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70162808,"text":"sir20155019D - 2016 - Adjusted peak-flow frequency estimates for selected streamflow-gaging stations in or near Montana based on data through water year 2011: Chapter D in Montana StreamStats","interactions":[{"subject":{"id":70162808,"text":"sir20155019D - 2016 - Adjusted peak-flow frequency estimates for selected streamflow-gaging stations in or near Montana based on data through water year 2011: Chapter D in Montana StreamStats","indexId":"sir20155019D","publicationYear":"2016","noYear":false,"chapter":"D","displayTitle":"Adjusted peak-flow frequency estimates for selected streamflow-gaging stations in or near Montana based on data through water year 2011: Chapter D in Montana StreamStats","title":"Adjusted peak-flow frequency estimates for selected streamflow-gaging stations in or near Montana based on data through water year 2011: Chapter D in Montana StreamStats"},"predicate":"IS_PART_OF","object":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"id":1}],"isPartOf":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"lastModifiedDate":"2024-12-13T19:40:04.515679","indexId":"sir20155019D","displayToPublicDate":"2016-04-05T00:00:00","publicationYear":"2016","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":"2015-5019","chapter":"D","displayTitle":"Adjusted peak-flow frequency estimates for selected streamflow-gaging stations in or near Montana based on data through water year 2011: Chapter D in Montana StreamStats","title":"Adjusted peak-flow frequency estimates for selected streamflow-gaging stations in or near Montana based on data through water year 2011: Chapter D in Montana StreamStats","docAbstract":"The climatic conditions of the specific time period during which peak-flow data were collected at a given streamflow-gaging station (hereinafter referred to as gaging station) can substantially affect how well the peak-flow frequency (hereinafter referred to as frequency) results represent long-term hydrologic conditions. Differences in the timing of the periods of record can result in substantial inconsistencies in frequency estimates for hydrologically similar gaging stations. Potential for inconsistency increases with decreasing peak-flow record length. The representativeness of the frequency estimates for a short-term gaging station can be adjusted by various methods including weighting the at-site results in association with frequency estimates from regional regression equations (RREs) by using the Weighted Independent Estimates (WIE) program. Also, for gaging stations that cannot be adjusted by using the WIE program because of regulation or drainage areas too large for application of RREs, frequency estimates might be improved by using record extension procedures, including a mixed-station analysis using the maintenance of variance type I (MOVE.1) procedure. The U.S. Geological Survey, in cooperation with the Montana Department of Transportation and the Montana Department of Natural Resources and Conservation, completed a study to provide adjusted frequency estimates for selected gaging stations through water year 2011.
The purpose of Chapter D of this Scientific Investigations Report is to present adjusted frequency estimates for 504 selected streamflow-gaging stations in or near Montana based on data through water year 2011. Estimates of peak-flow magnitudes for the 66.7-, 50-, 42.9-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities are reported. These annual exceedance probabilities correspond to the 1.5-, 2-, 2.33-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively.
The at-site frequency estimates were adjusted by weighting with frequency estimates from RREs using the WIE program for 438 selected gaging stations in Montana. These 438 selected gaging stations (1) had periods of record less than or equal to 40 years, (2) represented unregulated or minor regulation conditions, and (3) had drainage areas less than about 2,750 square miles.
The weighted-average frequency estimates obtained by weighting with RREs generally are considered to provide improved frequency estimates. In some cases, there are substantial differences among the at-site frequency estimates, the regression-equation frequency estimates, and the weighted-average frequency estimates. In these cases, thoughtful consideration should be applied when selecting the appropriate frequency estimate. Some factors that might be considered when selecting the appropriate frequency estimate include (1) whether the specific gaging station has peak-flow characteristics that distinguish it from most other gaging stations used in developing the RREs for the hydrologic region; and (2) the length of the peak-flow record and the general climatic characteristics during the period when the peak-flow data were collected. For critical structure-design applications, a conservative approach would be to select the higher of the at-site frequency estimate and the weighted-average frequency estimate.
The mixed-station MOVE.1 procedure generally was applied in cases where three or more gaging stations were located on the same large river and some of the gaging stations could not be adjusted using the weighted-average method because of regulation or drainage areas too large for application of RREs. The mixed-station MOVE.1 procedure was applied to 66 selected gaging stations on 19 large rivers.
The general approach for using mixed-station record extension procedures to adjust at-site frequencies involved (1) determining appropriate base periods for the gaging stations on the large rivers, (2) synthesizing peak-flow data for the gaging stations with incomplete peak-flow records during the base periods by using the mixed-station MOVE.1 procedure, and (3) conducting frequency analysis on the combined recorded and synthesized peak-flow data for each gaging station. Frequency estimates for the combined recorded and synthesized datasets for 66 gaging stations with incomplete peak-flow records during the base periods are presented. The uncertainties in the mixed-station record extension results are difficult to directly quantify; thus, it is important to understand the intended use of the estimated frequencies based on analysis of the combined recorded and synthesized datasets. The estimated frequencies are considered general estimates of frequency relations among gaging stations on the same stream channel that might be expected if the gaging stations had been gaged during the same long-term base period. However, because the mixed-station record extension procedures involve secondary statistical analysis with accompanying errors, the uncertainty of the frequency estimates is larger than would be obtained by collecting systematic records for the same number of years in the base period.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Montana StreamStats (Scientific Investigation Report 2015-5019)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155019D","collaboration":"Prepared in cooperation with the Montana Department of Transportation, Montana Department of Environmental Quality, and Montana Department of Natural Resources and Conservation","usgsCitation":"Sando, S.K., Sando, Roy, McCarthy, P.M., and Dutton, D.M., 2016, Adjusted peak-flow frequency estimates for selected streamflow-gaging stations in or near Montana based on data through water year 2011 (ver. 1.1, February 2018): U.S. Geological Survey Scientific Investigations Report 2015–5019–D, 12 p., https://doi.org/10.3133/sir20155019D.","productDescription":"Report: v, 12 p.; 5 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\"}}]}","edition":"Version 1.0: April 6, 2016; Version 1.1: February 26, 2018","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Ave
Helena, MT 59601
Chapter E of this Scientific Investigations Report documents results from a study by the U.S. Geological Survey, in cooperation with the Montana Department of Environmental Quality and the Montana Department of Natural Resources and Conservation, to provide an update of statewide streamflow characteristics based on data through water year 2009 for streamflow-gaging stations in or near Montana. Streamflow characteristics are presented for 408 streamflow-gaging stations in Montana and adjacent areas having 10 or more years of record. Data include the magnitude and probability of annual low and high streamflow, the magnitude and probability of low streamflow for three seasons (March–June, July–October, and November–February), streamflow duration statistics for monthly and annual periods, and mean streamflows for monthly and annual periods. Streamflow is considered to be regulated at streamflow-gaging stations where dams or other large-scale human modifications affect 20 percent or more of the contributing drainage basin. Separate streamflow characteristics are presented for the unregulated and regulated periods of record for streamflow-gaging stations with sufficient data.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Montana StreamStats (Scientific Investigations Report 2015-5019)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155019E","collaboration":"Prepared in cooperation with the Montana Department of Environmental Quality and Montana Department of Natural Resources and Conservation","usgsCitation":"McCarthy, P.M., 2016, Streamflow characteristics based on data through water year 2009 for selected streamflow-gaging stations in or near Montana: U.S. Geological Survey Scientific Investigations Report 2015–5019–E, 10 p., https://dx.doi.org/10.3133/sir20155019E.","productDescription":"Report: v, 10 p.; Table","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-061125","costCenters":[{"id":5050,"text":"WY-MT Water Science 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\"}}]}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Ave
Helena, MT 59601
A large-scale study by the U.S. Geological Survey, in cooperation with the Montana Department of Transportation and the Montana Department of Natural Resources and Conservation, was done to investigate general patterns in peak-flow temporal trends and stationarity through water year 2011 for 24 long-term streamflow-gaging stations (hereinafter referred to as gaging stations) in Montana. Hereinafter, all years refer to water years; a water year is the 12-month period from October 1 through September 30 and is designated by the year in which it ends. The primary focus of the study was to identify general patterns in peak-flow temporal trends and stationarity that are relevant to application of peak-flow frequency analyses within a statewide gaging-station network.
\nTemporal trends were analyzed for two hydrologic variables: annual peak flow and peak-flow timing. Annual peak flow is the maximum instantaneous discharge, in cubic feet per second, recorded each year a gaging station was operated. Peak-flow timing is the day of the annual peak flow (hereinafter referred to as day of peak), recorded each year a gaging station was operated.
\nStudy results provide evidence that annual peak flow for most of the long-term gaging stations can be reasonably considered as stationary for application of peak-flow frequency analyses within a statewide gaging station network. Upward trends in annual peak flow during 1930–76 generally were stronger than downward trends during 1967–2011 for most long-term gaging stations. Statistical distributions of annual peak flow generally were similar among three summary time periods (1930–78, 1979–2011, and the entire period of record). However, for two low-elevation gaging stations in eastern Montana (Poplar River at international boundary [gaging station 06178000] and Powder River at Moorhead, Montana [gaging station 06324500]), substantial downward trends in annual peak flow during 1967–2011 were of similar or stronger magnitude than the upward trends during 1930–76, and the annual-peak-flow medians for 1979–2011 were substantially lower than the medians for the entire period of record.
\nFor peak-flow timing for most long-term gaging stations, differences in trends between 1930–76 and 1967–2011 are variable and not particularly strong. Statistical distributions generally are similar among the summary time periods. However, for two high-elevation gaging stations on a Missouri River headwater tributary (Gallatin River near Gallatin Gateway, Montana [gaging station 06043500] and Gallatin River at Logan, Montana [gaging station 06052500]) and for five high-elevation gaging stations in the Yellowstone River Basin (Yellowstone River at Corwin Springs, Montana [gaging station 06191500], Yellowstone River near Livingston, Montana [gaging station 06192500], Clarks Fork Yellowstone River near Belfry, Montana [gaging station 06207500], Clarks Fork Yellowstone River at Edgar, Montana [gaging station 06208500], and Yellowstone River at Billings, Montana [gaging station 06214500]) downward trends in peak-flow timing during 1967–2011 generally were stronger than upward trends during 1930–1976, and day-of-peak medians for 1979–2011 were considerably less than medians for 1930–78. The downward trends in peak-flow timing for 1967–2011 indicate that the timing of annual peak flows changed from later in the year to earlier in the year. For the seven high-elevation gaging stations, the mean change during 1967–2011 was about 13 days (range of 8 to 22 days).
\nFor most of the high-elevation gaging stations in the Missouri River headwaters, Yellowstone River Basin, and Columbia River Basin, there was general correspondence between trend patterns for annual peak flow and trend patterns for peak-flow timing; that is, during periods when there were upward trends in annual peak flow, there generally also were upward trends in peak-flow timing. Conversely, during periods when there were downward trends in annual peak flow, there generally also were downward trends in peak-flow timing.
\nThe two low-elevation gaging stations in eastern Montana (Poplar River at international boundary [gaging station 06178000] and Powder River at Moorhead, Montana [gaging station 06324500]) had considerable changes in annual-peakflow characteristics after the mid-1970s, which might provide evidence of potential nonstationarity in the peak-flow records. The two low-elevation gaging stations that have potential nonstationarity are located in drainage basins that are strongly affected by agricultural activities that potentially affect the hydrologic regimes. Primary agricultural activities that might alter natural hydrologic conditions include construction of small impoundments (primarily for stock-watering purposes) and irrigation diversions. Temporal variability in these activities might contribute to the potential nonstationarity issues. Changes in climatic characteristics after the mid-1970s also possibly contribute to the potential nonstationarity issues. Lack of considerable indication of potential nonstationarity in annual peak flow for the other long-term gaging stations in this study might indicate that climatic changes have been more pronounced with respect to effects on peak flows in low elevation areas in eastern Montana than in areas represented by the other long-term gaging stations. Another possibility is that climatic changes after the mid-1970s are exacerbated in low-elevation areas where small-impoundment development and potential effects of irrigation diversions might be more extensive.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Montana StreamStats (Scientific Investigations Report 2015-5019)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155019B","collaboration":"Prepared in cooperation with the Montana Department of Transportation and Montana Department of Natural Resources and Conservation","usgsCitation":"Sando, S.K., McCarthy, P.M., Sando, Roy, and Dutton, D.M., 2016, Temporal trends and stationarity in annual peak flow and peak-flow timing for selected long-term streamflow-gaging stations in or near Montana through water year 2011: U.S. Geological Survey Scientific Investigations Report 2015–5019–B, 48 p., https://dx.doi.org/10.3133/sir20155019B.","productDescription":"vi, 48 p.","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-060698","costCenters":[{"id":5050,"text":"WY-MT Water Science 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\"}}]}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Ave
Helena, MT 59601
Montana StreamStats is a Web-based geographic information system (http://water.usgs.gov/osw/streamstats/) application that provides users with access to basin and streamflow characteristics for gaged and ungaged streams in Montana. Montana StreamStats was developed by the U.S. Geological Survey (USGS) in cooperation with the Montana Departments of Transportation, Environmental Quality, and Natural Resources and Conservation. The USGS Scientific Investigations Report consists of seven independent but complementary chapters dealing with various aspects of this effort.
Chapter A describes the Montana StreamStats application, the basin and streamflow datasets, and provides a brief overview of the streamflow characteristics and regression equations used in the study. Chapters B through E document the datasets, methods, and results of analyses to determine streamflow characteristics, such as peak-flow frequencies, low-flow frequencies, and monthly and annual characteristics, for USGS streamflow-gaging stations in and near Montana. The StreamStats analytical toolsets that allow users to delineate drainage basins and solve regression equations to estimate streamflow characteristics at ungaged sites in Montana are described in Chapters F and G.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155019","collaboration":"Prepared in cooperation with the Montana Department of Environmental Quality, Montana Department of Natural Resources and Conservation, and the Montana Department of Transportation","productDescription":"Chapters A-G","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":319890,"rank":2,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5019/sir20155019_2.zip","text":"Complete Volume","size":"60.7 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015"},{"id":319889,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5019/coverthb.jpg"}],"country":"United 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\"}}]}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Ave
Helena, MT 59601
The U.S. Geological Survey (USGS), in cooperation with the Montana Department of Natural Resources and Conservation, completed a study to update methods for estimating peak-flow frequencies at ungaged sites in Montana based on peak-flow data at streamflow-gaging stations through water year 2011. The methods allow estimation of peak-flow frequencies (that is, peak-flow magnitudes, in cubic feet per second, associated with annual exceedance probabilities of 66.7, 50, 42.9, 20, 10, 4, 2, 1, 0.5, and 0.2 percent) at ungaged sites. The annual exceedance probabilities correspond to 1.5-, 2-, 2.33-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively.
Regional regression analysis is a primary focus of Chapter F of this Scientific Investigations Report, and regression equations for estimating peak-flow frequencies at ungaged sites in eight hydrologic regions in Montana are presented. The regression equations are based on analysis of peak-flow frequencies and basin characteristics at 537 streamflow-gaging stations in or near Montana and were developed using generalized least squares regression or weighted least squares regression.
All of the data used in calculating basin characteristics that were included as explanatory variables in the regression equations were developed for and are available through the USGS StreamStats application (http://water.usgs.gov/osw/streamstats/) for Montana. StreamStats is a Web-based geographic information system application that was created by the USGS to provide users with access to an assortment of analytical tools that are useful for water-resource planning and management. The primary purpose of the Montana StreamStats application is to provide estimates of basin characteristics and streamflow characteristics for user-selected ungaged sites on Montana streams. The regional regression equations presented in this report chapter can be conveniently solved using the Montana StreamStats application.
Selected results from this study were compared with results of previous studies. For most hydrologic regions, the regression equations reported for this study had lower mean standard errors of prediction (in percent) than the previously reported regression equations for Montana. The equations presented for this study are considered to be an improvement on the previously reported equations primarily because this study (1) included 13 more years of peak-flow data; (2) included 35 more streamflow-gaging stations than previous studies; (3) used a detailed geographic information system (GIS)-based definition of the regulation status of streamflow-gaging stations, which allowed better determination of the unregulated peak-flow records that are appropriate for use in the regional regression analysis; (4) included advancements in GIS and remote-sensing technologies, which allowed more convenient calculation of basin characteristics and investigation of many more candidate basin characteristics; and (5) included advancements in computational and analytical methods, which allowed more thorough and consistent data analysis.
This report chapter also presents other methods for estimating peak-flow frequencies at ungaged sites. Two methods for estimating peak-flow frequencies at ungaged sites located on the same streams as streamflow-gaging stations are described. Additionally, envelope curves relating maximum recorded annual peak flows to contributing drainage area for each of the eight hydrologic regions in Montana are presented and compared to a national envelope curve. In addition to providing general information on characteristics of large peak flows, the regional envelope curves can be used to assess the reasonableness of peak-flow frequency estimates determined using the regression equations.
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\"}}]}","edition":"Version 1.1: February 2018","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Ave
Helena, MT 59601
Chapter C of this Scientific Investigations Report documents results from a study by the U.S. Geological Survey, in cooperation with the Montana Department of Transportation and the Montana Department of Natural Resources, to provide an update of statewide peak-flow frequency analyses and results for Montana. The purpose of this report chapter is to present peak-flow frequency analyses and results for 725 streamflow-gaging stations in or near Montana based on data through water year 2011. The 725 streamflow-gaging stations included in this study represent nearly all streamflowgaging stations in Montana (plus some from adjacent states or Canadian Provinces) that have at least 10 years of peak-flow records through water year 2011. For 29 of the 725 streamflow-gaging stations, peak-flow frequency analyses and results are reported for both unregulated and regulated conditions. Thus, peak-flow frequency analyses and results are reported for a total of 754 analyses. Estimates of peak-flow magnitudes for 66.7-, 50-, 42.9-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities are reported. These annual exceedance probabilities correspond to 1.5-, 2-, 2.33-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Montana StreamStats (Scientific Investigations Report 2015-5019)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155019C","collaboration":"Prepared in cooperation with the Montana Department of Transportation and Montana Department of Natural Resources and Conservation","usgsCitation":"Sando, S.K., McCarthy, P.M., and Dutton, D.M., 2016, Peak-flow frequency analyses and results based on data through water year 2011 for selected streamflow-gaging stations in or near Montana: U.S. Geological Survey Scientific Investigations Report 2015–5019–C, 27 p., https://dx.doi.org/10.3133/sir20155019C.","productDescription":"Report: v, 27 p.; 6 Tables","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-061583","costCenters":[{"id":5050,"text":"WY-MT Water Science 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\"}}]}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Ave
Helena, MT 59601