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The Illinois River is the largest river in Illinois and is the primary contributing watershed for nitrogen, phosphorus, and suspended-sediment loading to the upper Mississippi River from Illinois. In addition to streamflow, the following water-quality constituents were monitored at the Illinois River at Florence, Illinois (U.S. Geological Survey station number 05586300), during May 2012–October 2013: phosphate, nitrate, turbidity, temperature, specific conductance, pH, and dissolved oxygen. The objectives of this monitoring were to (1) determine performance capabilities of the in-situ instruments; (2) collect continuous data that would provide an improved understanding of constituent characteristics during normal, low-, and high-flow periods and during different climatic and land-use seasons; (3) evaluate the ability to use continuous turbidity as a surrogate constituent to determine suspended-sediment concentrations; and (4) evaluate the ability to develop a regression model for total phosphorus using phosphate, turbidity, and other measured parameters. Reliable data collection was achieved, following some initial periods of instrument and data-communication difficulties. The resulting regression models for suspended sediment had coefficient of determination (R2) values of about 0.9. Nitrate plus nitrite loads computed using continuous data were found to be approximately 8 percent larger than loads computed using traditional discrete-sampling based models. A regression model for total phosphorus was developed by using historic orthophosphate data (important during periods of low flow and low concentrations) and historic suspended-sediment data (important during periods of high flow and higher concentrations). The R2of the total phosphorus regression model using orthophosphorus and suspended sediment was 0.8. Data collection and refinement of the regression models is ongoing.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155040","collaboration":"Prepared in cooperation with the Illinois Environmental Protection Agency","usgsCitation":"Terrio, P.J., Straub, T., Domanski, M.M., and Siudyla, N.A., 2015, Continuous monitoring of sediment and nutrients in the Illinois River at Florence, Illinois, 2012-13: U.S. Geological Survey Scientific Investigations Report 2015-5040, vii, 61 p., https://doi.org/10.3133/sir20155040.","productDescription":"vii, 61 p.","numberOfPages":"74","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2012-05-01","temporalEnd":"2013-10-31","ipdsId":"IP-051216","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":300901,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5040/"},{"id":300902,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5040/pdf/sir2015-5040.pdf","text":"Report","size":"4.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":300903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155040.jpg"}],"projection":"Albers Equal-Area Conic projection","country":"United States","state":"Illinois","city":"Florence","otherGeospatial":"Illinois River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.60956954956055,\n 39.636563184336524\n ],\n [\n -90.6097412109375,\n 39.62783759836399\n ],\n [\n -90.60416221618652,\n 39.627903705425176\n ],\n [\n -90.60502052307129,\n 39.63662928306019\n ],\n [\n -90.60956954956055,\n 39.636563184336524\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55682e1ae4b0d9246a9f60de","contributors":{"authors":[{"text":"Terrio, Paul J. 0000-0002-1515-9570 pjterrio@usgs.gov","orcid":"https://orcid.org/0000-0002-1515-9570","contributorId":3313,"corporation":false,"usgs":true,"family":"Terrio","given":"Paul","email":"pjterrio@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":543037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Straub, Timothy D. 0000-0002-5896-0851 tdstraub@usgs.gov","orcid":"https://orcid.org/0000-0002-5896-0851","contributorId":2273,"corporation":false,"usgs":true,"family":"Straub","given":"Timothy D.","email":"tdstraub@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":543038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Domanski, Marian M. 0000-0002-0468-314X mdomanski@usgs.gov","orcid":"https://orcid.org/0000-0002-0468-314X","contributorId":5035,"corporation":false,"usgs":true,"family":"Domanski","given":"Marian","email":"mdomanski@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547816,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Siudyla, Nicholas A. nsiudyla@usgs.gov","contributorId":5420,"corporation":false,"usgs":true,"family":"Siudyla","given":"Nicholas","email":"nsiudyla@usgs.gov","middleInitial":"A.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":543039,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70148266,"text":"70148266 - 2015 - Integrated Environmental Modelling: Human decisions, human challenges","interactions":[],"lastModifiedDate":"2018-03-27T14:00:42","indexId":"70148266","displayToPublicDate":"2015-05-28T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5011,"text":"Geological Society of London Special Publications","active":true,"publicationSubtype":{"id":10}},"title":"Integrated Environmental Modelling: Human decisions, human challenges","docAbstract":"

Integrated Environmental Modelling (IEM) is an invaluable tool for understanding the complex, dynamic ecosystems that house our natural resources and control our environments. Human behaviour affects the ways in which the science of IEM is assembled and used for meaningful societal applications. In particular, human biases and heuristics reflect adaptation and experiential learning to issues with frequent, sharply distinguished, feedbacks. Unfortunately, human behaviour is not adapted to the more diffusely experienced problems that IEM typically seeks to address. Twelve biases are identified that affect IEM (and science in general). These biases are supported by personal observations and by the findings of behavioural scientists. A process for critical analysis is proposed that addresses some human challenges of IEM and solicits explicit description of (1) represented processes and information, (2) unrepresented processes and information, and (3) accounting for, and cognizance of, potential human biases. Several other suggestions are also made that generally complement maintaining attitudes of watchful humility, open-mindedness, honesty and transparent accountability. These suggestions include (1) creating a new area of study in the behavioural biogeosciences, (2) using structured processes for engaging the modelling and stakeholder communities in IEM, and (3) using ‘red teams’ to increase resilience of IEM constructs and use.

","language":"English","publisher":"The Geological Society of London","doi":"10.1144/SP408.9","usgsCitation":"Glynn, P.D., 2015, Integrated Environmental Modelling: Human decisions, human challenges: Geological Society of London Special Publications, v. 408, 22 p., https://doi.org/10.1144/SP408.9.","productDescription":"22 p.","numberOfPages":"22","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061573","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":472072,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1144/sp408.9","text":"Publisher Index Page"},{"id":300887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"408","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-21","publicationStatus":"PW","scienceBaseUri":"55682e22e4b0d9246a9f60e6","contributors":{"authors":[{"text":"Glynn, Pierre D. 0000-0001-8804-7003 pglynn@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7003","contributorId":2141,"corporation":false,"usgs":true,"family":"Glynn","given":"Pierre","email":"pglynn@usgs.gov","middleInitial":"D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":547631,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70144009,"text":"fs20153031 - 2015 - The 3D Elevation Program: summary for Delaware","interactions":[],"lastModifiedDate":"2016-08-17T14:59:36","indexId":"fs20153031","displayToPublicDate":"2015-05-28T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3031","title":"The 3D Elevation Program: summary for Delaware","docAbstract":"

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Delaware, elevation data are critical for agriculture and precision farming, river and stream resource management, natural resources conservation, flood risk management, coastal zone management, geologic resource assessment and hazard mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide publicly available coverage to support existing and emerging applications enabled by lidar data.

\n

The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153031","usgsCitation":"Carswell, W., 2015, The 3D Elevation Program: summary for Delaware: U.S. Geological Survey Fact Sheet 2015-3031, 2 p., https://doi.org/10.3133/fs20153031.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061951","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":300886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153031.jpg"},{"id":300884,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3031/"},{"id":300885,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3031/pdf/fs2015-3031.pdf","text":"Report","size":"287 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United 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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":543267,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70148348,"text":"ofr20151038 - 2015 - Development of conceptual ecological models linking management of the Missouri River to pallid sturgeon population dynamics","interactions":[],"lastModifiedDate":"2015-05-28T10:23:39","indexId":"ofr20151038","displayToPublicDate":"2015-05-28T09:30:00","publicationYear":"2015","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":"2015-1038","title":"Development of conceptual ecological models linking management of the Missouri River to pallid sturgeon population dynamics","docAbstract":"

This report documents the process of developing and refining conceptual ecological models (CEMs) for linking river management to pallid sturgeon (Scaphirhynchus albus) population dynamics in the Missouri River. The refined CEMs are being used in the Missouri River Pallid Sturgeon Effects Analysis to organize, document, and formalize an understanding of pallid sturgeon population responses to past and future management alternatives. The general form of the CEMs, represented by a population-level model and component life-stage models, was determined in workshops held in the summer of 2013. Subsequently, the Missouri River Pallid Sturgeon Effects Analysis team designed a general hierarchical structure for the component models, refined the graphical structure, and reconciled variation among the components and between models developed for the upper river (Upper Missouri & Yellowstone Rivers) and the lower river (Missouri River downstream from Gavins Point Dam). Importance scores attributed to the relations between primary biotic characteristics and survival were used to define a candidate set of working dominant hypotheses about pallid sturgeon population dynamics. These CEMs are intended to guide research and adaptive-management actions to benefit pallid sturgeon populations in the Missouri River.

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mannis@usgs.gov","contributorId":3498,"corporation":false,"usgs":true,"family":"Annis","given":"Mandy","email":"mannis@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":false,"id":547789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Colvin, Michael E.","contributorId":140975,"corporation":false,"usgs":false,"family":"Colvin","given":"Michael E.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":547790,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Welker, Timothy L.","contributorId":140976,"corporation":false,"usgs":false,"family":"Welker","given":"Timothy","email":"","middleInitial":"L.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":547791,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"James, Daniel 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In managing fish populations, especially at-risk species, realistic mathematical models are needed to help predict population response to potential management actions in the context of environmental conditions and changing climate while effectively incorporating the stochastic nature of real world conditions. We provide a key component of such a model for the endangered pallid sturgeon (Scaphirhynchus albus) in the form of an individual-based bioenergetics model influenced not only by temperature but also by flow. This component is based on modification of a known individual-based bioenergetics model through incorporation of: the observed ontogenetic shift in pallid sturgeon diet from marcroinvertebrates to fish; the energetic costs of swimming under flowing-water conditions; and stochasticity. We provide an assessment of how differences in environmental conditions could potentially alter pallid sturgeon growth estimates, using observed temperature and velocity from channelized portions of the Lower Missouri River mainstem. We do this using separate relationships between the proportion of maximum consumption and fork length and swimming cost standard error estimates for fish captured above and below the Kansas River in the Lower Missouri River. Critical to our matching observed growth in the field with predicted growth based on observed environmental conditions was a two-step shift in diet from macroinvertebrates to fish.

","language":"English","publisher":"The Geological Society of London","doi":"10.1144/SP408.10","usgsCitation":"Wildhaber, M.L., Dey, R., Wikle, C.K., Moran, E.H., Anderson, C.J., and Franz, K.J., 2015, A stochastic bioenergetics model based approach to translating large river flow and temperature in to fish population responses: The pallid sturgeon example: Geological Society of London Special Publications, v. 408, p. 1-17, https://doi.org/10.1144/SP408.10.","productDescription":"18 p. 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Sea-level rise during the late Pleistocene and early Holocene inundated nearshore areas in many parts of the world, producing drastic changes in local ecosystems and obscuring significant portions of the archeological record. Although global forces are at play, the effects of sea-level rise are highly localized due to variability in glacial isostatic adjustment (GIA) effects. Interpretations of coastal paleoecology and archeology require reliable estimates of ancient shorelines that account for GIA effects. Here we build on previous models for California's Northern Channel Islands, producing more accurate late Pleistocene and Holocene paleogeographic reconstructions adjusted for regional GIA variability. This region has contributed significantly to our understanding of early New World coastal foragers. Sea level that was about 80–85 m lower than present at the time of the first known human occupation brought about a landscape and ecology substantially different than today. During the late Pleistocene, large tracts of coastal lowlands were exposed, while a colder, wetter climate and fluctuating marine conditions interacted with rapidly evolving littoral environments. At the close of the Pleistocene and start of the Holocene, people in coastal California faced shrinking land, intertidal, and subtidal zones, with important implications for resource availability and distribution.

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2015 - Intersexual allometry differences and ontogenetic shifts of coloration patterns in two aquatic turtles, Graptemys oculifera and Graptemys flavimaculata","interactions":[],"lastModifiedDate":"2015-06-04T10:27:28","indexId":"70148304","displayToPublicDate":"2015-05-27T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Intersexual allometry differences and ontogenetic shifts of coloration patterns in two aquatic turtles, Graptemys oculifera and Graptemys flavimaculata","docAbstract":"

Coloration can play critical roles in a species' biology. The allometry of color patterns may be useful for elucidating the evolutionary mechanisms responsible for shaping the traits. We measured characteristics relating to eight aspects of color patterns from Graptemys oculifera and G. flavimaculata to investigate the allometric differences among male, female, and unsexed juvenile specimens. Additionally, we investigated ontogenetic shifts by incorporating the unsexed juveniles into the male and female datasets. In general, male color traits were isometric (i.e., color scaled with body size), while females and juvenile color traits were hypoallometric, growing in size more slowly than the increase in body size. When we included unsexed juveniles in our male and female datasets, our linear regression analyses found all relationships to be hypoallometric and our model selection analysis found support for nonlinear models describing the relationship between body size and color patterns, suggestive of an ontogenetic shift in coloration traits for both sexes at maturity. Although color is critical for many species' biology and therefore under strong selective pressure in many other species, our results are likely explained by an epiphenomenon related to the different selection pressures on body size and growth rates between juveniles and adults and less attributable to the evolution of color patterns themselves.

","language":"English","publisher":"Blackwell Pub. Ltd.","publisherLocation":"Oxford","doi":"10.1002/ece3.1517","usgsCitation":"Ennen, J., Lindeman, P.V., and Lovich, J.E., 2015, Intersexual allometry differences and ontogenetic shifts of coloration patterns in two aquatic turtles, Graptemys oculifera and Graptemys flavimaculata: Ecology and Evolution, v. 5, no. 11, p. 2296-2305, https://doi.org/10.1002/ece3.1517.","productDescription":"10 p.","startPage":"2296","endPage":"2305","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063446","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":472074,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1517","text":"Publisher Index Page"},{"id":300836,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-20","publicationStatus":"PW","scienceBaseUri":"5566dcade4b0d9246a9ec28f","contributors":{"authors":[{"text":"Ennen, Joshua R.","contributorId":60368,"corporation":false,"usgs":false,"family":"Ennen","given":"Joshua R.","affiliations":[{"id":13216,"text":"Tennessee Aquarium Conservation Institute","active":true,"usgs":false}],"preferred":false,"id":547682,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lindeman, Peter V.","contributorId":140947,"corporation":false,"usgs":false,"family":"Lindeman","given":"Peter","email":"","middleInitial":"V.","affiliations":[{"id":13624,"text":"Edinboro University, Department of Biology and Health Services, 230 Scotland Rd., Edinboro, Pennsylvania 16444, USA","active":true,"usgs":false}],"preferred":false,"id":547683,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":547681,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70148334,"text":"70148334 - 2015 - Performance of species occurrence estimators when basic assumptions are not met: a test using field data where true occupancy status is known","interactions":[],"lastModifiedDate":"2015-05-27T09:21:26","indexId":"70148334","displayToPublicDate":"2015-05-27T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Performance of species occurrence estimators when basic assumptions are not met: a test using field data where true occupancy status is known","docAbstract":"
    \n
  1. Populations are rarely censused. Instead, observations are subject to incomplete detection, misclassification and detection heterogeneity that result from human and environmental constraints. Though numerous methods have been developed to deal with observational uncertainty, validation under field conditions is rare because truth is rarely known in these cases.
    2. \n
  2. We present the most comprehensive test of occupancy estimation methods to date, using more than 33 000 auditory call observations collected under standard field conditions and where the true occupancy status of sites was known. Basic occupancy estimation approaches were biased when two key assumptions were not met: that no false positives occur and that no unexplained heterogeneity in detection parameters occurs. The greatest bias occurred for dynamic parameters (i.e. local colonization and extinction), and in many cases, the degree of inaccuracy would render results largely useless.
    3. \n
  3. We examined three approaches to increase adherence or relax these assumptions: modifying the sampling design, employing estimators that account for false-positive detections and using covariates to account for site-level heterogeneity in both false-negative and false-positive detection probabilities. We demonstrate that bias can be substantially reduced by modifications to sampling methods and by using estimators that simultaneously account for false-positive detections and site-level covariates to explain heterogeneity.
    4. \n
  4. Our results demonstrate that even small probabilities of misidentification and among-site detection heterogeneity can have severe effects on estimator reliability if ignored. We challenge researchers to place greater attention on both heterogeneity and false positives when designing and analysing occupancy studies. We provide 9 specific recommendations for the design, implementation and analysis of occupancy studies to better meet this challenge.
    5. \n
","language":"English","publisher":"Wiley","doi":"10.1111/2041-210X.12342","usgsCitation":"Miller, D.A., Bailey, L., Grant, E., McClintock, B.T., Weir, L.A., and Simons, T.R., 2015, Performance of species occurrence estimators when basic assumptions are not met: a test using field data where true occupancy status is known: Methods in Ecology and Evolution, v. 6, no. 5, p. 557-565, https://doi.org/10.1111/2041-210X.12342.","productDescription":"9 p.","startPage":"557","endPage":"565","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058867","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472075,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.12342","text":"Publisher Index Page"},{"id":300833,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"5","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-27","publicationStatus":"PW","scienceBaseUri":"5566dcb1e4b0d9246a9ec297","chorus":{"doi":"10.1111/2041-210x.12342","url":"http://dx.doi.org/10.1111/2041-210x.12342","publisher":"Wiley-Blackwell","authors":"Miller David A. W., Bailey Larissa L., Grant Evan H. Campbell, McClintock Brett T., Weir Linda A., Simons Theodore R.","journalName":"Methods in Ecology and Evolution","publicationDate":"3/27/2015","auditedOn":"2/24/2015"},"contributors":{"authors":[{"text":"Miller, David A. W.","contributorId":126732,"corporation":false,"usgs":false,"family":"Miller","given":"David","email":"","middleInitial":"A. W.","affiliations":[{"id":5039,"text":"Department of Environment, Land, and Infrastructure Engineering, Politecnico di Torino, Torino, Italy","active":true,"usgs":false}],"preferred":false,"id":547695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bailey, Larissa L.","contributorId":93183,"corporation":false,"usgs":true,"family":"Bailey","given":"Larissa L.","affiliations":[],"preferred":false,"id":547696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grant, Evan H. Campbell","contributorId":14686,"corporation":false,"usgs":true,"family":"Grant","given":"Evan H. Campbell","affiliations":[],"preferred":false,"id":547697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McClintock, Brett T. 0000-0001-6154-4376","orcid":"https://orcid.org/0000-0001-6154-4376","contributorId":83785,"corporation":false,"usgs":true,"family":"McClintock","given":"Brett","email":"","middleInitial":"T.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":547698,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weir, Linda A. lweir@usgs.gov","contributorId":140505,"corporation":false,"usgs":true,"family":"Weir","given":"Linda","email":"lweir@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":547694,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Simons, Theodore R. 0000-0002-1884-6229 tsimons@usgs.gov","orcid":"https://orcid.org/0000-0002-1884-6229","contributorId":2623,"corporation":false,"usgs":true,"family":"Simons","given":"Theodore","email":"tsimons@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":547699,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70148338,"text":"70148338 - 2015 - Slipstream: an early Holocene slump and turbidite record from the frontal ridge of the Cascadia accretionary wedge off western Canada and paleoseismic implications","interactions":[],"lastModifiedDate":"2015-05-28T09:26:18","indexId":"70148338","displayToPublicDate":"2015-05-27T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1168,"text":"Canadian Journal of Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Slipstream: an early Holocene slump and turbidite record from the frontal ridge of the Cascadia accretionary wedge off western Canada and paleoseismic implications","docAbstract":"

Slipstream Slump, a well-preserved 3 km wide sedimentary failure from the frontal ridge of the Cascadia accretionary wedge 85 km off Vancouver Island, Canada, was sampled during Canadian Coast Guard Ship (CCGS) John P. Tully cruise 2008007PGC along a transect of five piston cores. Shipboard sediment analysis and physical property logging revealed 12 turbidites interbedded with thick hemipelagic sediments overlying the slumped glacial diamict. Despite the different sedimentary setting, atop the abyssal plain fan, this record is similar in number and age to the sequence of turbidites sampled farther to the south from channel systems along the Cascadia Subduction Zone, with no extra turbidites present in this local record. Given the regional physiographic and tectonic setting, megathrust earthquake shaking is the most likely trigger for both the initial slumping and subsequent turbidity currents, with sediments sourced exclusively from the exposed slump face of the frontal ridge. Planktonic foraminifera picked from the resedimented diamict of the underlying main slump have a disordered cluster of 14C ages between 12.8 and 14.5 ka BP. For the post-slump stratigraphy, an event-free depth scale is defined by removing the turbidite sediment intervals and using the hemipelagic sediments. Nine14C dates from the most foraminifera-rich intervals define a nearly constant hemipelagic sedimentation rate of 0.021 cm/year. The combined age model is defined using only planktonic foraminiferal dates and Bayesian analysis with a Poisson-process sedimentation model. The age model of ongoing hemipelagic sedimentation is strengthened by physical property correlations from Slipstream events to the turbidites for the Barkley Canyon site 40 km south. Additional modelling addressed the possibilities of seabed erosion or loss and basal erosion beneath turbidites. Neither of these approaches achieves a modern seabed age when applying the commonly used regional marine 14C reservoir age of 800 years (marine reservoir correction ΔR= 400 years). Rather, the top of the core appears to be 400 years in the future. A younger marine reservoir age of 400 years (ΔR = 0 years) brings the top to the present and produces better correlations with the nearby Effingham Inlet paleo-earthquake chronology based only on terrestrial carbon requiring no reservoir correction. The high-resolution dating and facies analysis of Slipstream Slump in this isolated slope basin setting demonstrates that this is also a useful type of sedimentary target for sampling the paleoseismic record in addition to the more studied turbidites from submarine canyon and channel systems. The first 10 turbidites at Slipstream Slump were deposited between 10.8 and 6.6 ka BP, after which the system became sediment starved and only two more turbidites were deposited. The recurrence interval for the inferred frequent early Holocene megathrust earthquakes is 460 ± 140 years, compatible with other estimates of paleoseismic megathrust earthquake occurrence rates along the subduction zone.

","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjes-2014-0131","usgsCitation":"Hamilton, T., Enkin, R.J., Riedel, M., Rogers, G., Pohlman, J.W., and Benway, H.M., 2015, Slipstream: an early Holocene slump and turbidite record from the frontal ridge of the Cascadia accretionary wedge off western Canada and paleoseismic implications: Canadian Journal of Earth Sciences, v. 52, p. 1-26, https://doi.org/10.1139/cjes-2014-0131.","productDescription":"26 p.","startPage":"1","endPage":"26","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065348","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":472078,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://archimer.ifremer.fr/doc/00496/60803/","text":"External Repository"},{"id":300831,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"Slipstream Slump","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -128.836669921875,\n 45.4524242413431\n ],\n [\n -128.836669921875,\n 45.4524242413431\n ],\n [\n -128.836669921875,\n 45.4524242413431\n ],\n [\n -128.836669921875,\n 45.4524242413431\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.035400390625,\n 49.10983779052439\n ],\n [\n -124.815673828125,\n 48.922499263758255\n ],\n [\n -126.02416992187499,\n 48.268569112964336\n ],\n [\n -126.529541015625,\n 48.61838518688487\n ],\n [\n -125.035400390625,\n 49.10983779052439\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5566dcb2e4b0d9246a9ec29b","contributors":{"authors":[{"text":"Hamilton, T.S.","contributorId":140949,"corporation":false,"usgs":false,"family":"Hamilton","given":"T.S.","email":"","affiliations":[{"id":13625,"text":"Dept. of Chemistry and Geoscience Camosun College, Victoria, B.C.","active":true,"usgs":false}],"preferred":false,"id":547708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Enkin, Randolph J.","contributorId":75373,"corporation":false,"usgs":true,"family":"Enkin","given":"Randolph","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":547709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Riedel, Michael","contributorId":7518,"corporation":false,"usgs":true,"family":"Riedel","given":"Michael","email":"","affiliations":[],"preferred":false,"id":547710,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rogers, Gary C.","contributorId":41980,"corporation":false,"usgs":false,"family":"Rogers","given":"Gary C.","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":547711,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pohlman, John W. jpohlman@usgs.gov","contributorId":139874,"corporation":false,"usgs":true,"family":"Pohlman","given":"John","email":"jpohlman@usgs.gov","middleInitial":"W.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":547707,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Benway, Heather M.","contributorId":140951,"corporation":false,"usgs":false,"family":"Benway","given":"Heather","email":"","middleInitial":"M.","affiliations":[{"id":13627,"text":"Woods Hole Oceanographic Institution, Woods Hole, MA","active":true,"usgs":false}],"preferred":false,"id":547712,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70136357,"text":"sir20145236 - 2015 - Flood-inundation maps for the Hoosic River, North Adams and Williamstown, Massachusetts, from the confluence with the North Branch Hoosic River to the Vermont State line","interactions":[],"lastModifiedDate":"2015-11-04T12:07:21","indexId":"sir20145236","displayToPublicDate":"2015-05-27T09:30:00","publicationYear":"2015","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":"2014-5236","title":"Flood-inundation maps for the Hoosic River, North Adams and Williamstown, Massachusetts, from the confluence with the North Branch Hoosic River to the Vermont State line","docAbstract":"

A series of nine digital flood-inundation maps were developed for an 8-mile reach of the Hoosic River in North Adams and Williamstown, Massachusetts, by the U.S. Geological Survey (USGS) in cooperation with the Federal Emergency Management Agency. The coverage of the maps extends from the confluence with the North Branch Hoosic River to the Vermont State line. Peak flows with 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities were computed for the reach from updated flood-frequency analyses. These peak flows were routed through a one-dimensional step-backwater hydraulic model to obtain the corresponding peak water-surface elevations, and to place the tropical storm Irene flood of August 28, 2011 into historical context. The hydraulic model was calibrated by using the current (2014) stage-discharge relation at the USGS streamgage Hoosic River near Williamstown, Massachusetts (01332500), and from documented high-water marks from the tropical storm Irene flood, which had approximately a 1-percent annual exceedance probability.

\n

The hydraulic model was used to compute water-surface profiles for flood stages referenced to the streamgage and ranging from 9 feet (ft; 624.45 ft North American Vertical Datum of 1988 [NAVD 1988]), which is near bankfull, to 16.1 ft (631.59 ft NAVD 1988), which exceeds the maximum recorded water level at the streamgage and the National Weather Service major flood stage of 13.0 ft. The mapped stages, 10.9 to 16.1 ft, were selected to match the stages of flows with annual exceedance probabilities between 20 and 0.2 percent, and thus do not fall at exact 1-ft increments. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data having a 0.5-ft vertical accuracy to create a set of flood-inundation maps.

\n

The availability of the flood-inundation maps, combined with information regarding current (near real-time) stage from USGS streamgage Hoosic River near Williamstown, and forecasted flood stages from the National Weather Service Advanced Hydrologic Prediction Service will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, and post-flood recovery efforts. The flood-inundation maps are nonregulatory, but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during selected peak-flow events.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145236","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Lombard, P., and Bent, G.C., 2015, Flood-inundation maps for the Hoosic River, North Adams and Williamstown, Massachusetts, from the confluence with the North Branch Hoosic River to the Vermont State line: U.S. Geological Survey Scientific Investigations Report 2014-5236, Report: vi, 15 p.; Downloads Directory, https://doi.org/10.3133/sir20145236.","productDescription":"Report: vi, 15 p.; Downloads Directory","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059673","costCenters":[{"id":371,"text":"Maine Water Science 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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5566dca7e4b0d9246a9ec28b","contributors":{"authors":[{"text":"Lombard, Pamela J. plombard@usgs.gov","contributorId":140923,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela J.","email":"plombard@usgs.gov","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":false,"id":547600,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bent, Gardner C. 0000-0002-5085-3146 gbent@usgs.gov","orcid":"https://orcid.org/0000-0002-5085-3146","contributorId":1864,"corporation":false,"usgs":true,"family":"Bent","given":"Gardner","email":"gbent@usgs.gov","middleInitial":"C.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547601,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70142283,"text":"70142283 - 2015 - Evaluating turbidity and suspended-sediment concentration relations from the North Fork Toutle River basin near Mount St. Helens, Washington; annual, seasonal, event, and particle size variations - a preliminary analysis.","interactions":[],"lastModifiedDate":"2015-11-09T16:39:17","indexId":"70142283","displayToPublicDate":"2015-05-26T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Evaluating turbidity and suspended-sediment concentration relations from the North Fork Toutle River basin near Mount St. Helens, Washington; annual, seasonal, event, and particle size variations - a preliminary analysis.","docAbstract":"

Regression of in-stream turbidity with concurrent sample-based suspended-sediment concentration (SSC) has become an accepted method for producing unit-value time series of inferred SSC (Rasmussen et al., 2009). Turbidity-SSC regression models are increasingly used to generate suspended-sediment records for Pacific Northwest rivers (e.g., Curran et al., 2014; Schenk and Bragg, 2014; Uhrich and Bragg, 2003). Recent work developing turbidity-SSC models for the North Fork Toutle River in Southwest Washington (Uhrich et al., 2014), as well as other studies (Landers and Sturm, 2013, Merten et al., 2014), suggests that models derived from annual or greater datasets may not adequately reflect shorter term changes in turbidity-SSC relations, warranting closer inspection of such relations. In-stream turbidity measurements and suspended-sediment samples have been collected from the North Fork Toutle River since 2010. The study site, U.S. Geological Survey (USGS) streamgage 14240525 near Kid Valley, Washington, is 13 river km downstream of the debris avalanche emplaced by the 1980 eruption of Mount St. Helens (Lipman and Mullineaux, 1981), and 2 river km downstream of the large sediment retention structure (SRS) built from 1987–1989 to mitigate the associated sediment hazard. The debris avalanche extends roughly 25 km down valley from the edifice of the volcano and is the primary source of suspended sediment moving past the streamgage (NF Toutle-SRS). Other significant sources are debris flow events and sand deposits upstream of the SRS, which are periodically remobilized and transported downstream. Also, finer material often is derived from the clay-rich original debris avalanche deposit, while coarser material can derive from areas such as fluvially reworked terraces.

","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Proceedings of the joint federal interagency conference 2015","conferenceTitle":"5th Federal Interagency Hydrologic Modeling Conference and the 10th Federal Interagency Sedimentation Conference","conferenceDate":"April 19-23, 2015","conferenceLocation":"Reno, Nevada","language":"English","collaboration":"US Army Corps of Engineers","usgsCitation":"Uhrich, M.A., Spicer, K.R., Mosbrucker, A.R., and Christianson, T.S., 2015, Evaluating turbidity and suspended-sediment concentration relations from the North Fork Toutle River basin near Mount St. Helens, Washington; annual, seasonal, event, and particle size variations - a preliminary analysis., in Proceedings of the joint federal interagency conference 2015, Reno, Nevada, April 19-23, 2015, 11 p.","productDescription":"11 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061916","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":311139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"North Fork Toutle River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.50408172607422,\n 46.30140615437332\n ],\n [\n -122.53498077392578,\n 46.210962348068314\n ],\n [\n -122.46322631835938,\n 46.18244521829928\n ],\n [\n -122.37361907958984,\n 46.17959269136383\n ],\n [\n -122.27611541748045,\n 46.18006812279714\n ],\n [\n -122.24006652832033,\n 46.17079646832833\n ],\n [\n -122.19680786132812,\n 46.216188883247405\n ],\n [\n -122.19715118408202,\n 46.258458011742235\n ],\n [\n -122.32864379882811,\n 46.27103747280261\n ],\n [\n -122.3650360107422,\n 46.27578368908797\n ],\n [\n -122.4367904663086,\n 46.30662407603325\n ],\n [\n -122.47936248779295,\n 46.31089291474789\n ],\n [\n -122.49927520751953,\n 46.30875853700599\n ],\n [\n -122.50545501708984,\n 46.302829273239325\n ],\n [\n -122.50408172607422,\n 46.30140615437332\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5641d1bee4b0831b7d62e73c","contributors":{"authors":[{"text":"Uhrich, Mark A. 0000-0002-5202-8086 mauhrich@usgs.gov","orcid":"https://orcid.org/0000-0002-5202-8086","contributorId":1149,"corporation":false,"usgs":true,"family":"Uhrich","given":"Mark","email":"mauhrich@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":541809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spicer, Kurt R. 0000-0001-5030-3198 krspicer@usgs.gov","orcid":"https://orcid.org/0000-0001-5030-3198","contributorId":2684,"corporation":false,"usgs":true,"family":"Spicer","given":"Kurt","email":"krspicer@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":541810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mosbrucker, Adam R. 0000-0003-0298-0324 amosbrucker@usgs.gov","orcid":"https://orcid.org/0000-0003-0298-0324","contributorId":4968,"corporation":false,"usgs":true,"family":"Mosbrucker","given":"Adam","email":"amosbrucker@usgs.gov","middleInitial":"R.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":541812,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christianson, Tami S. 0000-0002-6873-9229 tchristianson@usgs.gov","orcid":"https://orcid.org/0000-0002-6873-9229","contributorId":5986,"corporation":false,"usgs":true,"family":"Christianson","given":"Tami","email":"tchristianson@usgs.gov","middleInitial":"S.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":541811,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171170,"text":"70171170 - 2015 - Initiation of migration and movement rates of Atlantic salmon smolts in fresh water","interactions":[],"lastModifiedDate":"2016-05-25T16:18:28","indexId":"70171170","displayToPublicDate":"2015-05-25T13:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Initiation of migration and movement rates of Atlantic salmon smolts in fresh water","docAbstract":"

Timing of ocean entry is critical for marine survival of both hatchery and wild Atlantic salmon (Salmo salar) smolts. Management practices and barriers to migration such as dams may constrain timing of smolt migrations resulting in suboptimal performance at saltwater entry. We modeled influences of stocking location, smolt development, and environmental conditions on (i) initiation of migration by hatchery-reared smolts and (ii) movement rate of hatchery- and wild-reared Atlantic salmon smolts in the Penobscot River, Maine, USA, from 2005 through 2014 using acoustic telemetry data. We also compared movement rates in free-flowing reaches with rates in reaches with hydropower dams and head ponds. We compared movement rates before and after (1) removal of two mainstem dams and (2) construction of new powerhouses. Initiation of movement by hatchery fish was influenced by smolt development, stocking location, and environmental conditions. Smolts with the greatest gill Na+, K+-ATPase (NKA) activity initiated migration 24 h sooner than fish with the lowest gill NKA activity. Fish with the greatest cumulative thermal experience initiated migration 5 days earlier than those with lowest cumulative thermal experience. Smolts released furthest from the ocean initiated migration earlier than those released downstream, but movement rate increased by fivefold closer to the ocean, indicating behavioral trade-offs between initiation and movement rate. Dams had a strong effect on movement rate. Movement rate increased from 2.8 to 5.4 km·h−1 in reaches where dams were removed, but decreased from 2.1 to 0.1 km·h−1 in reaches where new powerhouses were constructed. Movement rate varied throughout the migratory period and was inversely related to temperature. Fish moved slower at extreme high or low discharge. Responses in fish movement rates to dam removal indicate the potential scope of recovery for these activities.

","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2014-0570","usgsCitation":"Stich, D.S., Kinnison, M.T., Kocik, J.F., and Zydlewski, J.D., 2015, Initiation of migration and movement rates of Atlantic salmon smolts in fresh water: Canadian Journal of Fisheries and Aquatic Sciences, v. 72, no. 9, p. 1339-1351, https://doi.org/10.1139/cjfas-2014-0570.","productDescription":"13 p.","startPage":"1339","endPage":"1351","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060916","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":321685,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Penobscot River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.5,\n 44.7\n ],\n [\n -68.5,\n 45.1\n ],\n [\n -68.8,\n 45.1\n ],\n [\n -68.8,\n 44.7\n ],\n [\n -68.5,\n 44.7\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"72","issue":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5746ccbde4b07e28b662dce6","contributors":{"authors":[{"text":"Stich, Daniel S.","contributorId":139212,"corporation":false,"usgs":false,"family":"Stich","given":"Daniel","email":"","middleInitial":"S.","affiliations":[{"id":12606,"text":"University of Maine, Dept of Plant, Soil, & Envir Sciences","active":true,"usgs":false}],"preferred":false,"id":630301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kinnison, Michael T.","contributorId":169617,"corporation":false,"usgs":false,"family":"Kinnison","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":630302,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kocik, John F.","contributorId":103162,"corporation":false,"usgs":true,"family":"Kocik","given":"John","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":630303,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":630304,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70243861,"text":"70243861 - 2015 - End-of-winter snow depth variability on glaciers in Alaska","interactions":[],"lastModifiedDate":"2023-05-24T15:05:42.814122","indexId":"70243861","displayToPublicDate":"2015-05-23T15:56:20","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5739,"text":"Journal of Geophysical Research: Earth Surface","onlineIssn":"2169-9011","active":true,"publicationSubtype":{"id":10}},"title":"End-of-winter snow depth variability on glaciers in Alaska","docAbstract":"

A quantitative understanding of snow thickness and snow water equivalent (SWE) on glaciers is essential to a wide range of scientific and resource management topics. However, robust SWE estimates are observationally challenging, in part because SWE can vary abruptly over short distances in complex terrain due to interactions between topography and meteorological processes. In spring 2013, we measured snow accumulation on several glaciers around the Gulf of Alaska using both ground- and helicopter-based ground-penetrating radar surveys, complemented by extensive ground truth observations. We found that SWE can be highly variable (40% difference) over short spatial scales (tens to hundreds of meters), especially in the ablation zone where the underlying ice surfaces are typically rough. Elevation provides the dominant basin-scale influence on SWE, with gradients ranging from 115 to 400 mm/100 m. Regionally, total accumulation and the accumulation gradient are strongly controlled by a glacier's distance from the coastal moisture source. Multiple linear regressions, used to calculate distributed SWE fields, show that robust results require adequate sampling of the true distribution of multiple terrain parameters. Final SWE estimates (comparable to winter balances) show reasonable agreement with both the Parameter-elevation Relationships on Independent Slopes Model climate data set (9–36% difference) and the U.S. Geological Survey Alaska Benchmark Glaciers (6–36% difference). All the glaciers in our study exhibit substantial sensitivity to changing snow-rain fractions, regardless of their location in a coastal or continental climate. While process-based SWE projections remain elusive, the collection of ground-penetrating radar (GPR)-derived data sets provides a greatly enhanced perspective on the spatial distribution of SWE and will pave the way for future work that may eventually allow such projections.

","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JF003539","usgsCitation":"Mcgrath, D., Sass, L., O’Neel, S., Arendt, A., Wolken, G., Gusmeroli, A., Kienholz, C., and McNeil, C., 2015, End-of-winter snow depth variability on glaciers in Alaska: Journal of Geophysical Research: Earth Surface, v. 120, no. 8, p. 1530-1550, https://doi.org/10.1002/2015JF003539.","productDescription":"21 p.","startPage":"1530","endPage":"1550","ipdsId":"IP-064450","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":472080,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jf003539","text":"Publisher Index Page"},{"id":438700,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7K072BV","text":"USGS data release","linkHelpText":"Raw Ground Penetrating Radar Data, Valdez Glacier, Alaska; 2013"},{"id":438699,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7F769M4","text":"USGS data release","linkHelpText":"Raw Ground Penetrating Radar Data, Eklutna Glacier, Alaska; 2013"},{"id":438698,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Z60M35","text":"USGS data release","linkHelpText":"Raw Ground Penetrating Radar Data, Eureka Glacier, Alaska; 2013"},{"id":438697,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TH8JRR","text":"USGS data release","linkHelpText":"Raw Ground Penetrating Radar Data, Gulkana Glacier, Alaska; 2013"},{"id":438696,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BG2M16","text":"USGS data release","linkHelpText":"Raw Ground Penetrating Radar Data,Taku Glacier, Alaska; 2013"},{"id":438695,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7G73BRH","text":"USGS data release","linkHelpText":"Raw Ground Penetrating Radar Data, Wolverine Glacier, Alaska; 2013"},{"id":438694,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76Q1V81","text":"USGS data release","linkHelpText":"Raw Ground Penetrating Radar Data, Scott Glacier, Alaska; 2013"},{"id":417368,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -151.14517565646327,\n 62.938908091713984\n ],\n [\n -151.14517565646327,\n 57.55690540490215\n ],\n [\n -137.04945194161488,\n 57.55690540490215\n ],\n [\n -137.04945194161488,\n 62.938908091713984\n ],\n [\n -151.14517565646327,\n 62.938908091713984\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"120","issue":"8","noUsgsAuthors":false,"publicationDate":"2015-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Mcgrath, Daniel 0000-0002-9462-6842","orcid":"https://orcid.org/0000-0002-9462-6842","contributorId":220417,"corporation":false,"usgs":true,"family":"Mcgrath","given":"Daniel","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":873543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sass, Louis C. 0000-0003-4677-029X lsass@usgs.gov","orcid":"https://orcid.org/0000-0003-4677-029X","contributorId":3555,"corporation":false,"usgs":true,"family":"Sass","given":"Louis C.","email":"lsass@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":873544,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Neel, Shad 0000-0002-9185-0144 soneel@usgs.gov","orcid":"https://orcid.org/0000-0002-9185-0144","contributorId":166740,"corporation":false,"usgs":true,"family":"O’Neel","given":"Shad","email":"soneel@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":873545,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arendt, Anthony 0000-0003-0429-6905","orcid":"https://orcid.org/0000-0003-0429-6905","contributorId":220394,"corporation":false,"usgs":false,"family":"Arendt","given":"Anthony","email":"","affiliations":[{"id":40162,"text":"U. of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":873546,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolken, Gabriel","contributorId":305685,"corporation":false,"usgs":false,"family":"Wolken","given":"Gabriel","affiliations":[{"id":16126,"text":"Alaska Division of Geological and Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":873547,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gusmeroli, Alessio 0000-0002-8355-5591","orcid":"https://orcid.org/0000-0002-8355-5591","contributorId":220395,"corporation":false,"usgs":false,"family":"Gusmeroli","given":"Alessio","email":"","affiliations":[{"id":40163,"text":"U of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":873548,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kienholz, Christian 0000-0001-7962-4446","orcid":"https://orcid.org/0000-0001-7962-4446","contributorId":220396,"corporation":false,"usgs":false,"family":"Kienholz","given":"Christian","email":"","affiliations":[{"id":40162,"text":"U. of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":873549,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McNeil, Christopher J. 0000-0003-4170-0428 cmcneil@usgs.gov","orcid":"https://orcid.org/0000-0003-4170-0428","contributorId":5803,"corporation":false,"usgs":true,"family":"McNeil","given":"Christopher J.","email":"cmcneil@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":873550,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70147415,"text":"sir20155061 - 2015 - Groundwater flow in the Brunswick/Glynn County area, Georgia, 2000-04","interactions":[],"lastModifiedDate":"2017-01-18T13:19:32","indexId":"sir20155061","displayToPublicDate":"2015-05-22T15:00:00","publicationYear":"2015","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":"2015-5061","title":"Groundwater flow in the Brunswick/Glynn County area, Georgia, 2000-04","docAbstract":"

An existing regional steady-state model for coastal Georgia, and parts of South Carolina and Florida, was revised to evaluate the local effects of pumping on the migration of high chloride (saline) water in the Upper Floridan aquifer located in the Brunswick/Glynn County, Georgia (Ga.) area. Revisions were focused on enhancing the horizontal and vertical resolution of the regional model grid in the vicinity of saline water. Modifications to the regional model consisted of (1) limiting grid size to a maximum of 500 feet (ft) per side in the vicinity of chloride contamination; (2) representing the upper and lower Brunswick aquifers with distinct model layers; (3) similarly, representing upper and lower water-bearing zones of the Upper Floridan aquifer with distinct model layers in Glynn and Camden Counties, Ga.; and (4) establishing new hydraulic-property zones in the Upper Floridan aquifer. The revised model simulated steady-state conditions that were assumed to exist during 2000 and 2004.

\n

Calibration of the revised steady-state model using pumping rates from 2000 indicates a \"good\" match (±10 ft) based on 181 observations, with median residuals (simulated minus observed water levels) in each of the active model layers ranging from -8.62 to 4.67 ft, and root mean square error (RMSE) ranging from 10.9 to 11.4 ft. In the Brunswick/Glynn County area, groundwater-level residuals in the upper water-bearing zone of the Upper Floridan aquifer (layer 7) indicate an \"excellent\" match (±5 ft) based on 41 observations with a median residual of -0.35 ft and RMSE of 4.32 ft.

\n

Calibration of the revised steady-state model using 2004 pumping rates and adjusted specified-head input values in the Floridan aquifer system indicates a \"good\" match (-10 ft) based on 88 observations, with median residuals in each of the active model layers ranging from -6.31 to -2.05 ft, and RMSE ranging from -6.95 to 14.5 ft. In the Brunswick/Glynn County area, groundwater-level residuals in the upper water-bearing zone of the Upper Floridan aquifer (layer 7) indicate an \"excellent\" match (±5 ft) based on 32 observations with a median residual of -1.50 ft and RMSE of 5.34 ft.

\n

Simulated potentiometric surfaces for 2000 and 2004 indicate coastward groundwater flow in the Upper and Lower Floridan aquifers influenced by pumping centers at Savannah, Jesup, and Brunswick, Ga., and indicate steep potentiometric gradients to the west and north of the Gulf Trough. In the Brunswick/Glynn County area, simulated industrial production wells located north of downtown Brunswick intercept local groundwater flow in the upper and lower water-bearing zones of the Upper Floridan aquifer and have created a cone of depression that locally alters the regional coastward flow direction.

\n

Maps of simulated water-level change during the 2000-04 period show differences in groundwater levels in the Upper Floridan aquifer that range from -2.5 ft to more than 5 ft in areas of coastal Georgia, and more than 20 ft near the Georgia-Florida State Line. Positive values indicate higher simulated water levels during 2004 than during 2000, which were caused by reduced pumping in the Upper Floridan aquifer prompted by the shutdown of a paper mill near the southern model boundary in 2002 and increased recharge following a prolonged drought during 1998-2002.

\n

Simulated potentiometric profiles for 2000 and 2004 were used to evaluate the potentiometric gradients in the upper water-bearing zone of the Upper Floridan aquifer (layer 7) near the chloride plume in the downtown Brunswick area. Four potentiometric profiles were constructed for 2000 to compare the simulated and observed water levels in 13 wells and were oriented outward from a primary well field. The simulated potentiometric gradients from the four profiles for 2000 ranged from 3.6 to 5.2 feet per mile (ft/mi) compared to observed values ranging from 4.1 to 5.6 ft/mi. The five potentiometric profiles constructed for 2004 allowed for a similar comparison using simulated and observed water levels in 18 wells. The simulated potentiometric gradients from the five profiles for 2000 ranged from 3.6 to 11.1 ft/mi compared to observed values ranging from 3.8 to 10.2 ft/mi. Simulated potentiometric gradients were higher for 2004 than for 2000 because of the inclusion of a well located within the cone of depression near downtown Brunswick.

\n

Composite-scaled sensitivities of the model parameters indicate the revised model is most sensitive to pumping rates, followed by the horizontal hydraulic conductivity in the Upper Floridan aquifer for zones along coastal Georgia. The revised model is least sensitive to the horizontal hydraulic conductivity of the confining units and vertical hydraulic conductivity of the aquifers. For parameters defined by hydraulic-property zones in the upper and lower water-bearing zones of the Upper Floridan aquifer, such as horizontal hydraulic conductivity, model sensitivity was not as great in the Brunswick/Glynn County area as other areas along coastal Georgia. The model exhibited more sensitivity to these parameters however, than to parameters representing the majority of zones defining the vertical hydraulic conductivity of the confining units, which originally were assumed to govern upward migration of chloride contamination into this aquifer.

\n

Analysis of simulated water-budget components for 2000 and 2004 indicate that specified-head boundaries in the Floridan aquifer system to the south and southwest of the regional model area control about 70 percent of inflows and nearly 50 percent of outflows to the model region. Other water-budget components indicate an 80-million-gallon-per-day decrease in pumping from the Floridan aquifer system during this period.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155061","usgsCitation":"Cherry, G.S., 2015, Groundwater flow in the Brunswick/Glynn County area, Georgia, 2000-04: U.S. Geological Survey Scientific Investigations Report 2015-5061, viii, 88 p., https://doi.org/10.3133/sir20155061.","productDescription":"viii, 88 p.","numberOfPages":"100","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2000-01-01","temporalEnd":"2004-12-31","ipdsId":"IP-015105","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":300754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155061.jpg"},{"id":300753,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5061/pdf/sir2015-5061.pdf","text":"Report","size":"10.4 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"SIR 2015-5061 Report"},{"id":300752,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5061/"}],"country":"United States","state":"Georgia","county":"Brunswick County, Glynn County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.52284622192383,\n 31.121439619206097\n ],\n [\n -81.52284622192383,\n 31.178147212117395\n ],\n [\n -81.4577865600586,\n 31.178147212117395\n ],\n [\n -81.4577865600586,\n 31.121439619206097\n ],\n [\n -81.52284622192383,\n 31.121439619206097\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5560452be4b0afeb70724149","contributors":{"authors":[{"text":"Cherry, Gregory S. 0000-0002-5567-1587 gccherry@usgs.gov","orcid":"https://orcid.org/0000-0002-5567-1587","contributorId":1567,"corporation":false,"usgs":true,"family":"Cherry","given":"Gregory","email":"gccherry@usgs.gov","middleInitial":"S.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545930,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70146512,"text":"sir20155055 - 2015 - Comparisons of estimates of annual exceedance-probability discharges for small drainage basins in Iowa, based on data through water year 2013","interactions":[],"lastModifiedDate":"2015-05-22T13:13:31","indexId":"sir20155055","displayToPublicDate":"2015-05-22T14:15:00","publicationYear":"2015","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":"2015-5055","title":"Comparisons of estimates of annual exceedance-probability discharges for small drainage basins in Iowa, based on data through water year 2013","docAbstract":"

Traditionally, the Iowa Department of Transportation has used the Iowa Runoff Chart and single-variable regional-regression equations (RREs) from a U.S. Geological Survey report (published in 1987) as the primary methods to estimate annual exceedance-probability discharge (AEPD) for small (20 square miles or less) drainage basins in Iowa. With the publication of new multi- and single-variable RREs by the U.S. Geological Survey (published in 2013), the Iowa Department of Transportation needs to determine which methods of AEPD estimation provide the best accuracy and the least bias for small drainage basins in Iowa.

\n

Twenty five streamgages with drainage areas less than 2 square miles (mi2) and 55 streamgages with drainage areas between 2 and 20 mi2 were selected for the comparisons that used two evaluation metrics. Estimates of AEPDs calculated for the streamgages using the expected moments algorithm/multiple Grubbs-Beck test analysis method were compared to estimates of AEPDs calculated from the 2013 multivariable RREs; the 2013 single-variable RREs; the 1987 single-variable RREs; the TR-55 rainfall-runoff model; and the Iowa Runoff Chart.

\n

For the 25 streamgages with drainage areas less than 2 mi2, results of the comparisons seem to indicate the best overall accuracy and the least bias may be achieved by using the TR-55 method for flood regions 1 and 3 (published in 2013) and by using the 1987 single-variable RREs for flood region 2 (published in 2013).

\n

For drainage basins with areas between 2 and 20 mi2, results of the comparisons seem to indicate the best overall accuracy and the least bias may be achieved by using the 1987 single-variable RREs for the Southern Iowa Drift Plain landform region and for flood region 3 (published in 2013), by using the 2013 multivariable RREs for the Iowan Surface landform region, and by using the 2013 or 1987 single-variable RREs for flood region 2 (published in 2013). For all other landform or flood regions in Iowa, use of the 2013 single-variable RREs may provide the best overall accuracy and the least bias.

\n

An examination was conducted to understand why the 1987 single-variable RREs seem to provide better accuracy and less bias than either of the 2013 multi- or single-variable RREs. A comparison of 1-percent annual exceedance-probability regression lines for hydrologic regions 1-4 from the 1987 single-variable RREs and for flood regions 1-3 from the 2013 single-variable RREs indicates that the 1987 single-variable regional-regression lines generally have steeper slopes and lower discharges when compared to 2013 single-variable regional-regression lines for corresponding areas of Iowa. The combination of the definition of hydrologic regions, the lower discharges, and the steeper slopes of regression lines associated with the 1987 single-variable RREs seem to provide better accuracy and less bias when compared to the 2013 multi- or single-variable RREs; better accuracy and less bias was determined particularly for drainage areas less than 2 mi2, and also for some drainage areas between 2 and 20 mi2. The 2013 multi- and single-variable RREs are considered to provide better accuracy and less bias for larger drainage areas. Results of this study indicate that additional research is needed to address the curvilinear relation between drainage area and AEPDs for areas of Iowa.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155055","collaboration":"Prepared in cooperation with the Iowa Department of Transportation and the Iowa Highway Research Board (Project TR-678)","usgsCitation":"Eash, D.A., 2015, Comparisons of estimates of annual exceedance-probability discharges for small drainage basins in Iowa, based on data through water year 2013: U.S. Geological Survey Scientific Investigations Report 2015-5055, viii, 37 p., https://doi.org/10.3133/sir20155055.","productDescription":"viii, 37 p.","numberOfPages":"50","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2013-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-058580","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":300734,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155055.jpg"},{"id":300732,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5055/pdf/sir2015-5055.pdf","text":"Report","size":"2.06 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"SIR 2015-5055"},{"id":300731,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5055/"},{"id":300733,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5055/downloads/","text":"Downloads Directory","linkFileType":{"id":3,"text":"xlsx"},"description":"Contains: Table 3, 4, 8, 9, and 10 in XLSX format","linkHelpText":"SIR 2015-5055 Downloads Directory"}],"country":"United States","state":"Iowa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.7236328125,\n 43.51668853502906\n ],\n [\n -91.2744140625,\n 43.51668853502906\n ],\n [\n -91.01074218749999,\n 43.29320031385282\n ],\n [\n -91.20849609375,\n 43.11702412135048\n ],\n [\n -91.01074218749999,\n 42.79540065303723\n ],\n [\n -90.703125,\n 42.65012181368022\n ],\n [\n -90.06591796875,\n 42.08191667830631\n ],\n [\n -90.32958984375,\n 41.508577297439324\n ],\n [\n -91.01074218749999,\n 41.37680856570233\n ],\n [\n -90.85693359375,\n 40.896905775860006\n ],\n [\n -91.47216796875,\n 40.29628651711716\n ],\n [\n -91.8017578125,\n 40.58058466412761\n ],\n [\n -95.73486328124999,\n 40.54720023441049\n ],\n [\n -95.97656249999999,\n 40.713955826286046\n ],\n [\n -96.70166015624999,\n 42.73087427928485\n ],\n [\n -96.70166015624999,\n 43.14909399920127\n ],\n [\n -96.7236328125,\n 43.51668853502906\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5560451be4b0afeb70724141","contributors":{"authors":[{"text":"Eash, David A. 0000-0002-2749-8959 daeash@usgs.gov","orcid":"https://orcid.org/0000-0002-2749-8959","contributorId":1887,"corporation":false,"usgs":true,"family":"Eash","given":"David","email":"daeash@usgs.gov","middleInitial":"A.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544976,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70141461,"text":"sir20155015 - 2015 - Evaluation of groundwater levels in the South Platte River alluvial aquifer, Colorado, 1953-2012, and design of initial well networks for monitoring groundwater levels","interactions":[],"lastModifiedDate":"2015-05-28T09:27:59","indexId":"sir20155015","displayToPublicDate":"2015-05-22T12:30:00","publicationYear":"2015","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":"2015-5015","title":"Evaluation of groundwater levels in the South Platte River alluvial aquifer, Colorado, 1953-2012, and design of initial well networks for monitoring groundwater levels","docAbstract":"

The South Platte River and underlying alluvial aquifer form an important hydrologic resource in northeastern Colorado that provides water to population centers along the Front Range and to agricultural communities across the rural plains. Water is regulated based on seniority of water rights and delivered using a network of administration structures that includes ditches, reservoirs, wells, impacted river sections, and engineered recharge areas. A recent addendum to Colorado water law enacted during 2002-2003 curtailed pumping from thousands of wells that lacked authorized augmentation plans. The restrictions in pumping were hypothesized to increase water storage in the aquifer, causing groundwater to rise near the land surface at some locations. The U.S. Geological Survey (USGS), in cooperation with the Colorado Water Conservation Board and the Colorado Water Institute, completed an assessment of 60 years (yr) of historical groundwater-level records collected from 1953 to 2012 from 1,669 wells. Relations of \"high\" groundwater levels, defined as depth to water from 0 to 10 feet (ft) below land surface, were compared to precipitation, river discharge, and 36 geographic and administrative attributes to identify natural and human controls in areas with shallow groundwater.

\n

Averaged per decade and over the entire aquifer, depths to groundwater varied between 24 and 32 ft over the 60-yr record. The shallowest average depth to water was identified during 1983-1992, which also recorded the highest levels of decadal precipitation. Average depth to water was greatest (32 ft) during 1953-1962 and intermediate (30 ft) in the recent decade (2003-2012) following curtailment of pumping. Between the decades 1993-2002 and 2003-2012, groundwater levels declined about 2 ft across the aquifer. In comparison, in areas where groundwater levels were within 20 ft of the land surface, observed groundwater levels rose about 0.6 ft, on average, during the same period, which demonstrated preferential rise in areas with shallow groundwater.

\n

Approximately 29 percent of water-level observations were identified as high groundwater in the South Platte River alluvial aquifer over the 60-yr record. High groundwater levels were found in 17 to 33 percent of wells examined by decade, with the largest percentages occurring over three decades from 1963 to 1992. The recent decade (2003-2012) exhibited an intermediate percentage (25 percent) of wells with high groundwater levels but also had the highest percentage (30 percent) of high groundwater observations, although results by observations were similar (26-29 percent) over three decades prior, from 1963 to 1992. Major sections of the aquifer from north of Sterling to Julesburg and areas near Greeley, La Salle, and Gilcrest were identified with the highest frequencies of high groundwater levels.

\n

Changes in groundwater levels were evaluated using Kendal line and least trimmed squares regression methods using a significance level of 0.01 and statistical power of 0.8. During 2003-2012, following curtailment of pumping, 88 percent of wells and 81 percent of subwatershed areas with significant trends in groundwater levels exhibited rising water levels. Over the complete 60-yr record, however, 66 percent of wells and 57 percent of subwatersheds with significant groundwater-level trends still showed declining water levels; rates of groundwater-level change were typically less than 0.125 ft/yr in areas near the South Platte River, with greater declines along the southern tributaries. In agreement, 58 percent of subwatersheds evaluated between 1963-1972 and 2003-2012 showed net declines in average decadal groundwater levels. More areas had groundwater decline in upgradient sections to the west and rise in downgradient sections to the east, implying a redistribution of water has occurred in some areas of the aquifer.

\n

Precipitation was identified as having the strongest statistically significant correlations to river discharge over annual and decadal periods (Pearson correlation coefficients of 0.5 and 0.8, respectively, and statistical significance defined by p-values less than 0.05). Correlation coefficients between river discharge and frequency of high groundwater levels were statistically significant at 0.4 annually and 0.6 over decadal periods, indicating that periods of high river flow were often coincident with high groundwater conditions. Over seasonal periods in five of the six decades examined, peak high groundwater levels occurred after spring runoff from July to September when administrative structures were most active. Between 1993-2002 and 2003-2012, groundwater levels rose while river discharge decreased, in part from greater reliance on surface water and curtailed pumping from wells without augmentation plans.

\n

Geographic attributes of elevation and proximity to streams and rivers showed moderate correlations to high groundwater levels in wells used for observing groundwater levels (correlation coefficients of 0.3 to 0.4). Local depressions and regional lows within the aquifer were identified as areas of potential shallow groundwater. Wells close to the river regularly indicated high groundwater levels, while those within depleted tributaries tended to have low frequencies of high groundwater levels. Some attributes of administrative structures were spatially correlated to high groundwater levels at moderate to high magnitudes (correlation coefficients of 0.3 to 0.7). The number of affected river reaches or recharge areas that surround a well where groundwater levels were observed and its distance from the nearest well field showed the strongest controls on high groundwater levels. Influences of administrative structures on groundwater levels were in some cases local over a mile or less but could extend to several miles, often manifesting as diffuse effects from multiple surrounding structures.

\n

A network of candidate monitoring wells was proposed to initiate a regional monitoring program. Consistent monitoring and analysis of groundwater levels will be needed for informed decisions to optimize beneficial use of water and to limit high groundwater levels in susceptible areas. Finalization of the network will require future field reconnaissance to assess local site conditions and discussions with State authorities.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155015","collaboration":"Prepared in cooperation with the Colorado Water Institute and Colorado Water Conservation Board","usgsCitation":"Wellman, T., 2015, Evaluation of groundwater levels in the South Platte River alluvial aquifer, Colorado, 1953-2012, and design of initial well networks for monitoring groundwater levels: U.S. Geological Survey Scientific Investigations Report 2015-5015, viii, 68 p., https://doi.org/10.3133/sir20155015.","productDescription":"viii, 68 p.","numberOfPages":"79","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1953-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-057966","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":300710,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155015.jpg"},{"id":300708,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5015/pdf/sir2015-5015.pdf","text":"Report","size":"17.7 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"SIR 2015-5015 Report"},{"id":300709,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5015/"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.13818359375,\n 36.98500309285596\n ],\n [\n -109.13818359375,\n 41.04621681452063\n ],\n [\n -101.9970703125,\n 41.04621681452063\n ],\n [\n -101.9970703125,\n 36.98500309285596\n ],\n [\n -109.13818359375,\n 36.98500309285596\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55604523e4b0afeb70724143","contributors":{"authors":[{"text":"Wellman, Tristan 0000-0003-3049-6214 twellman@usgs.gov","orcid":"https://orcid.org/0000-0003-3049-6214","contributorId":2166,"corporation":false,"usgs":true,"family":"Wellman","given":"Tristan","email":"twellman@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547513,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70148004,"text":"sir20155072 - 2015 - Simulated effects of Lower Floridan aquifer pumping on the Upper Floridan aquifer at Rincon, Effingham County, Georgia","interactions":[],"lastModifiedDate":"2017-01-18T13:21:04","indexId":"sir20155072","displayToPublicDate":"2015-05-22T10:00:00","publicationYear":"2015","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":"2015-5072","title":"Simulated effects of Lower Floridan aquifer pumping on the Upper Floridan aquifer at Rincon, Effingham County, Georgia","docAbstract":"

Steady-state simulations using a revised regional groundwater-flow model based on MODFLOW were run to assess the potential long-term effects on the Upper Floridan aquifer (UFA) of pumping the Lower Floridan aquifer (LFA) at well (36S048) near the City of Rincon in coastal Georgia near Savannah. Simulated pumping of well 36S048 at a rate of 1,000 gallons per minute (gal/min; or 1.44 million gallons per day [Mgal/d]) indicated a maximum drawdown of about 6.8 feet (ft) in the UFA directly above the pumped well and at least 1 ft of drawdown within a nearly 400-square-mile area (scenario A). Induced vertical leakage from the UFA provided about 99 percent of the water to the pumped well. Simulated pumping of well 36S048 indicated increased downward leakage in all layers above the LFA, decreased upward leakage in all layers above the LFA, increased inflow to and decreased outflow from lateral specified-head boundaries in the UFA and LFA, and an increase in the volume of induced inflow from the general-head boundary representing outcrop units. Water budgets for scenario A indicated that changes in inflows and outflows through general-head boundaries would compose about 72 percent of the simulated pumpage from well 36S048, with the remaining 28 percent of the pumped water derived from flow across lateral specified-head boundaries.

\n

Additional steady-state simulations were run to evaluate a pumping rate in the UFA of 292 gal/min (0.42 Mgal/d), which would produce the equivalent maximum drawdown in the UFA as pumping from well 36S048 in the LFA at a rate of 1,000 gal/min (called the drawdown offset; scenario B). Simulated pumping in the UFA for the drawdown offset produced about 6.7 ft of drawdown, comparable to 6.8 ft of drawdown in the UFA simulated in scenario A. Water budgets for scenario B also provided favorable comparisons with scenario A, indicating that 69 percent of the drawdown-offset pumpage (0.42 Mgal/d) in the UFA originates as increased inflow and decreased outflow across general-head boundaries from overlying units in the surficial and Brunswick aquifer systems and that the remaining simulated pumpage originates as flow across general- and specified-head boundaries within the UFA.

\n

A steady-state simulation representing implementation of drawdown-offset-pumping reductions totaling 292 gal/min at Rincon UFA production wells 36S034 and 36S035 and pumping from the new LFA well 36S048 at 1,000 gal/min (scenario C) resulted in decreased magnitude and areal extent of drawdown in the UFA compared with scenario A. In the latter scenario, the LFA well was pumped without UFA drawdown-offset-pumping reductions. Water budgets for scenario C yielded percentage contributions from flow components that were consistent with those from scenario B. Specifically, 69 percent of the increased pumping in scenario C originated from general-head boundaries from overlying units of the surficial and Brunswick aquifer systems and the balance of flow was derived from general- and specified-head boundaries in the UFA. In all scenarios, the placement of model boundaries and type of boundary exerted the greatest control on overall groundwater flow and interaquifer leakage in the system.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155072","collaboration":"Prepared in cooperation with the City of Rincon, Georgia","usgsCitation":"Cherry, G.S., and Clarke, J.S., 2015, Simulated effects of Lower Floridan aquifer pumping on the Upper Floridan aquifer at Rincon, Effingham County, Georgia: U.S. Geological Survey Scientific Investigations Report 2015-5072, viii, 36 p., https://doi.org/10.3133/sir20155072.","productDescription":"viii, 36 p.","numberOfPages":"47","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-054209","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":300691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155072.jpg"},{"id":300690,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5072/pdf/sir2015-5072.pdf","text":"Report","size":"5.16 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"SIR 2015-5072 Report"},{"id":300689,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5072/"}],"country":"United States","state":"Georgia","county":"Effingham County","otherGeospatial":"Rincon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.4251708984375,\n 31.785384226419566\n ],\n [\n -81.4251708984375,\n 32.21396296653795\n ],\n [\n -80.80307006835938,\n 32.21396296653795\n ],\n [\n -80.80307006835938,\n 31.785384226419566\n ],\n [\n -81.4251708984375,\n 31.785384226419566\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5560452ce4b0afeb7072414b","contributors":{"authors":[{"text":"Cherry, Gregory S. 0000-0002-5567-1587 gccherry@usgs.gov","orcid":"https://orcid.org/0000-0002-5567-1587","contributorId":1567,"corporation":false,"usgs":true,"family":"Cherry","given":"Gregory","email":"gccherry@usgs.gov","middleInitial":"S.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clarke, John S. jsclarke@usgs.gov","contributorId":400,"corporation":false,"usgs":true,"family":"Clarke","given":"John","email":"jsclarke@usgs.gov","middleInitial":"S.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546736,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70156183,"text":"70156183 - 2015 - Modeling apple snail population dynamics on the Everglades landscape","interactions":[],"lastModifiedDate":"2019-07-25T15:01:35","indexId":"70156183","displayToPublicDate":"2015-05-22T01:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling apple snail population dynamics on the Everglades landscape","docAbstract":"

Context

\n

The Florida Everglades has diminished in size and its existing wetland hydrology has been altered. The endangered snail kite (Rostrhamus sociabilis) has nearly abandoned the Everglades, and its prey, the apple snail (Pomacea paludosa), has declined.

\n

Objective

\n

We developed a population model (EverSnail) to understand apple snail response to inter- and intra-annual fluctuations in water depths over the Everglades landscape. EverSnail was developed as a tool to understand how apple snails respond to different hydrologic scenarios.

\n

Methods

\n

EverSnail is an age- and size-structured, spatially-explicit landscape model of P. paludosa in the Everglades. Landscape-level inputs are water depth and air temperature. We conducted sensitivity analyses by running EverSnail with ± 20 % the baseline value of eight parameters.

\n

Results

\n

EverSnail was sensitive to changes in survival and water depth associated with reproduction. The EverSnail population varied with changes and/or differences in depth generally consistent with empirical data; site-specific comparisons to field data proved less reliable. A simulated 3-year wet period resulted in a shift in apple snail distribution, but little change in total abundance over the landscape. In contrast, a simulated 3-year succession of relatively dry years resulted in overall lower snail abundances.

\n

Conclusions

\n

Comparisons of model output to empirical data indicate the need for more data to better understand, and eventually parameterize, several aspects of snail ecology in support of EverSnail. A primary value of EverSnail is its capacity to describe the relative response of snail abundance to alternative hydrologic scenarios considered for Everglades water management and restoration.

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Lake Heat Flux Analyzer is a program used for calculating the surface energy fluxes in lakes according to established literature methodologies. The program was developed in MATLAB for the rapid analysis of high-frequency data from instrumented lake buoys in support of the emerging field of aquatic sensor network science. To calculate the surface energy fluxes, the program requires a number of input variables, such as air and water temperature, relative humidity, wind speed, and short-wave radiation. Available outputs for Lake Heat Flux Analyzer include the surface fluxes of momentum, sensible heat and latent heat and their corresponding transfer coefficients, incoming and outgoing long-wave radiation. Lake Heat Flux Analyzer is open source and can be used to process data from multiple lakes rapidly. It provides a means of calculating the surface fluxes using a consistent method, thereby facilitating global comparisons of high-frequency data from lake buoys.

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Mercury (Hg) is an element that occurs naturally, but evidence suggests that human activities have resulted in increased amounts being released to the atmosphere and land surface. When Hg is converted to methylmercury (MeHg) in aquatic ecosystems, MeHg accumulates and increases in the food web so that some fish contain levels which pose a health risk to humans and wildlife that consume these fish. Reservoirs unlike natural lakes, are a part of river systems that are managed for flood control. Data compiled and interpreted for six flood-control reservoirs in Indiana showed a relation between Hg transport, MeHg formation in water, and MeHg in fish that was influenced by physical, chemical, and biological differences among the reservoirs. Existing information precludes a uniform comparison of Hg and MeHg in all reservoirs in the State, but factors and conditions were identified that can indicate where and when Hg and MeHg levels in reservoirs could be highest.

\n

As part of a statewide monitoring network for Hg and MeHg in Indiana streams, 66 water samples were collected from four reservoir tailwater sites (downstream near the dams) on a quarterly schedule for 5 years. The reservoirs were Brookville Lake, Cagles Mill Lake, J. Edward Roush Lake, and Mississinewa Lake. Particulate-bound Hg concentrations were significantly lower in tailwater samples than in samples from free-flowing streams in the statewide network. (Free-flowing streams were not affected by dams and were not upstream from these reservoirs.) These data indicated the reduced flow velocity of water upstream from dams was allowing particulate-bound Hg to settle out of the water in the reservoir pools. The concentration ratios of MeHg to Hg were significantly higher in the tailwater samples than in samples from free-flowing streams, and the MeHg to Hg ratios were significantly higher in summer than in other seasons.

\n

To evaluate the conditions related to MeHg formation, pools of three reservoirs (Brookville Lake, Monroe Lake, and Patoka Lake) were investigated during summer hydrologic conditions. Water temperature and dissolved oxygen were measured from the water surface to the lake bottom at 10 to 17 transects across each reservoir to identify three thermal strata, defined by water temperature, dissolved oxygen concentration, and depth. Depth-specific water samples were collected from these thermal strata throughout each reservoir, from the headwaters to the dam and from the tailwater. Mercury concentrations higher than 0.04 nanogram per liter (ng/L) were detected in all 53 samples, and MeHg concentrations higher than 0.04 ng/L were detected in 53 percent of the samples.

\n

The investigation found a zone of water below 8 or 9 meters, with temperatures less than 18 degrees Celsius and dissolved oxygen less than 3.5 milligrams per liter, extending through nearly half the reservoir area in Monroe Lake and Patoka Lake. This zone had abundant dissolved MeHg and concentration ratios of dissolved MeHg to Hg that ranged from 25 to 82 percent. This zone also had water with pH less than 7 and decreased dissolved sulfate, conditions indicating sulfate reduction by microorganisms that promoted a high potential for the conversion of Hg to MeHg. Reservoir outflow came from this zone at Monroe Lake and contributed to a tailwater concentration ratio for dissolved MeHg to Hg of 56 percent. Reservoir outflow at Patoka Lake was not from this zone, and dissolved MeHg was not detected in the tailwater. In contrast, samples from the summer pool at Brookville Lake had no MeHg detections even though Hg was detected, probably because the water pH higher than 7 inhibited sulfate reduction and did not promote the conversion of Hg to MeHg.

\n

Mercury and MeHg concentrations and the concentration ratios of MeHg to Hg in water varied among the six reservoirs in Indiana, and the differences were related to a combination of factors that could apply to other reservoirs. In areas with moderate to high rates of atmospheric Hg wet and dry deposition, Hg runoff and transport to streams and reservoirs was potentially highest for reservoirs with heavily forested watersheds in steep terrains of near-surface bedrock. Methylmercury concentrations and concentration ratios of MeHg to Hg were highest for reservoirs with the longest summer pools and highest inflow-to-outflow retention times, where water-chemistry conditions favoring sulfate reduction promoted conversion of Hg to MeHg.

\n

Methylmercury (reported as Hg) in fish-tissue samples collected for the State fish consumption advisory program was used to describe MeHg food-web accumulation and magnification in the reservoirs. The highest percentages of fish-tissue samples with Hg concentrations that exceeded the criterion of 0.30 milligram per kilogram for protection of human health were from Monroe Lake (38 percent) and Patoka Lake (33 percent). A review of the number and size of fish species caught from these two reservoirs resulted in two implications for fish consumption by humans. First, the highest numbers of fish harvested for potential human consumption were species more likely to have MeHg concentrations lower than the human-health criterion (crappie, bluegill, and catfish). Second, although largemouth bass were likely to have MeHg concentrations higher than the human-health criterion, they were caught and released more often than they were harvested. However, the average size largemouth bass (in both reservoirs) and above-average size walleye (in Monroe Lake) that were harvested for potential human consumption were likely to have MeHg concentrations higher than the human-health criterion.

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Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":543842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fredericksen, Amanda L. afredericksen@usgs.gov","contributorId":2440,"corporation":false,"usgs":true,"family":"Fredericksen","given":"Amanda","email":"afredericksen@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":false,"id":543841,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155021,"text":"70155021 - 2015 - Self-noise models of five commercial strong-motion accelerometers","interactions":[],"lastModifiedDate":"2016-08-29T15:19:49","indexId":"70155021","displayToPublicDate":"2015-05-20T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research 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Strong‐motion accelerometers provide onscale seismic recordings during moderate‐to‐large ground motions (e.g., up to tens of m/s2 peak). Such instruments have played a fundamental role in improving our understanding of earthquake source physics (Bocketal., 2011), earthquake engineering (Youdet al., 2004), and regional seismology (Zollo et al., 2010). Although strong‐motion accelerometers tend to have higher noise levels than high‐quality broadband velocity seismometers, their higher clip‐levels provide linear recordings at near‐field sites even for the largest of events where a collocated broadband sensor would no longer be able to provide onscale recordings (Clinton and Heaton, 2002).

\n

Recently, the seismological community has begun to make use of strong‐motion accelerometer data even in the absence of large ground motions (e.g., Tibuleac et al., 2011). The noise floor of the instruments often limits the usefulness of strong‐motion accelerometer data in such studies, because it obscures first arrivals or can make the traces dominated by noise. When a strong‐motion accelerometer is deployed in a quiet setting, the noise floors of the digitizer and the accelerometer tend to dominate the other noise sources (Cauzzi and Clinton, 2013). This situation is unlike that using broadband sensors, in which site conditions are typically the largest contributing source of noise in seismic data, especially at long periods (Wilson et al., 2002). With the widespread deployment of strong‐motion accelerometers recorded on high resolution digitizers, it is now possible to get continuous high‐rate acceleration data in which the digitizer noise is not the dominant noise source (Cauzzi and Clinton, 2013).

\n

To better characterize the noise of a number of commonly deployed accelerometers in a standardized way, we conducted noise measurements on five different models of strong‐motion accelerometers. Our study was limited to traditional accelerometers (Fig. 1) and is in no way exhaustive.

","language":"English","publisher":"Seismological Society of America","publisherLocation":"El Cerrito, CA","doi":"10.1785/0220150027","usgsCitation":"Ringler, A.T., Evans, J.R., and Hutt, C.R., 2015, Self-noise models of five commercial strong-motion accelerometers: Seismological Research Letters, v. 86, no. 4, p. 1143-1147, https://doi.org/10.1785/0220150027.","productDescription":"5 p.","startPage":"1143","endPage":"1147","numberOfPages":"5","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065493","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":305951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-20","publicationStatus":"PW","scienceBaseUri":"55b361b6e4b09a3b01b5dab5","contributors":{"authors":[{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":564680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, John R. jrevans@usgs.gov","contributorId":529,"corporation":false,"usgs":true,"family":"Evans","given":"John","email":"jrevans@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":564681,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hutt, Charles R. 0000-0001-9033-9195 bhutt@usgs.gov","orcid":"https://orcid.org/0000-0001-9033-9195","contributorId":1622,"corporation":false,"usgs":true,"family":"Hutt","given":"Charles","email":"bhutt@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":564682,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70147159,"text":"ofr20151083 - 2015 - Status and threats analysis for the Florida manatee (Trichechus manatus latirostris), 2012","interactions":[],"lastModifiedDate":"2024-03-04T19:05:07.028529","indexId":"ofr20151083","displayToPublicDate":"2015-05-20T11:45:00","publicationYear":"2015","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":"2015-1083","title":"Status and threats analysis for the Florida manatee (Trichechus manatus latirostris), 2012","docAbstract":"

The endangered West Indian manatee (Trichechus manatus), especially the Florida subspecies (T. m. latirostris), has been the focus of conservation efforts and extensive research since its listing under the Endangered Species Act. On the basis of the best information available as of December 2012, the threats facing the Florida manatee were determined to be less severe than previously thought, either because the conservation efforts have been successful, or because our knowledge of the demographic effects of those threats is increased, or both. Using the manatee Core Biological Model, we estimated the probability of the Florida manatee population on either the Atlantic or Gulf coast falling below 500 adults in the next 150 years to be 0.92 percent. The primary threats remain watercraft-related mortality and long-term loss of warm-water habitat. Since 2009, however, there have been a number of unusual events that have not yet been incorporated into this analysis, including several severely cold winters, a severe red-tide die off, and substantial loss of seagrass habitat in Brevard County, Fla. Further, the version of the Core Biological Model used in 2012 makes a number of assumptions that are under investigation. A revision of the Core Biological Model and an update of this quantitative threats analysis are underway as of 2015.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151083","usgsCitation":"Runge, M.C., Langtimm, C.A., Martin, J., and Fonnesbeck, C.J., 2015, Status and threats analysis for the Florida manatee (Trichechus manatus latirostris), 2012: U.S. Geological Survey Open-File Report 2015-1083, v, 23 p., https://doi.org/10.3133/ofr20151083.","productDescription":"v, 23 p.","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2012-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-064691","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":300427,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1083/"},{"id":300430,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151083.jpg"},{"id":300428,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1083/pdf/ofr2015-1083.pdf","size":"2.03 MB","linkFileType":{"id":1,"text":"pdf"}}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"555da21ce4b0a92fa7eb82bd","contributors":{"authors":[{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":545700,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Langtimm, Catherine A. 0000-0001-8499-5743 clangtimm@usgs.gov","orcid":"https://orcid.org/0000-0001-8499-5743","contributorId":3045,"corporation":false,"usgs":true,"family":"Langtimm","given":"Catherine","email":"clangtimm@usgs.gov","middleInitial":"A.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":545701,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":545702,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fonnesbeck, Christopher J.","contributorId":83047,"corporation":false,"usgs":true,"family":"Fonnesbeck","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":545703,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70146514,"text":"sim3327 - 2015 - Offshore geology and geomorphology from Point Piedras Blancas to Pismo Beach, San Luis Obispo County, California","interactions":[],"lastModifiedDate":"2022-01-21T17:39:30.321003","indexId":"sim3327","displayToPublicDate":"2015-05-19T15:30:00","publicationYear":"2015","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":"3327","title":"Offshore geology and geomorphology from Point Piedras Blancas to Pismo Beach, San Luis Obispo County, California","docAbstract":"

Marine geology and geomorphology were mapped along the continental shelf and upper slope between Point Piedras Blancas and Pismo Beach, California. The map area is divided into the following three (smaller) map areas, listed from north to south: San Simeon, Morro Bay, and Point San Luis. Each smaller map area consists of a geologic map and the corresponding geophysical data that support the geologic mapping. Each geophysical data sheet includes shaded-relief multibeam bathymetry, seismic-reflection-survey tracklines, and residual magnetic anomalies, as well as a smaller version of the geologic map for reference. Offshore geologic units were delineated on the basis of integrated analysis of adjacent onshore geology, seafloor-sediment and rock samples, multibeam bathymetry and backscatter imagery, magnetic data, and high-resolution seismic-reflection profiles. Although the geologic maps are presented here at 1:35,000 scale, map interpretation was conducted at scales of between 1:6,000 and 1:12,000.

\n

Sea level was approximately 120 to 130 m lower during the Last Glacial Maximum (about 21 ka). This approximate depth corresponds to the modern shelf break, a lateral change from the gently dipping (0.8° to 1.0°) outer shelf to the slightly more steeply dipping (about 1.5° to 2.5°) upper slope in the central and northern parts of the map area. South of Point San Luis in San Luis Bay, deltaic deposits offshore of the mouth of the Santa Maria River (11 km south of the map area) have prograded across the shelf break and now form a continuous low-angle (about 0.8°) ramp that extends to water depths of more than 160 m. The shelf break defines the landward boundary of slope deposits. North of Estero Bay, the shelf break is characterized by a distinctly sharp slope break that is mapped as a landslide headscarp above landslide deposits. Multibeam imagery and seismic-reflection profiles across this part of the shelf break show evidence of slope failure, such as slumping, sliding, and soft-sediment deformation, along the entire length of the scarp. Notably, this shelf-break scarp corresponds to a west splay of the Hosgri Fault that dies out just north of the scarp, suggesting that faulting is controlling the location (and instability) of the shelf break in this area.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3327","usgsCitation":"Watt, J., Johnson, S.Y., Hartwell, S., and Roberts, M., 2015, Offshore geology and geomorphology from Point Piedras Blancas to Pismo Beach, San Luis Obispo County, California: U.S. Geological Survey Scientific Investigations Map 3327, Pamphlet: iii, 6 p.; 6 Sheets: 49.0 x 36.26 inches or smaller; Metadata; Data catalog, https://doi.org/10.3133/sim3327.","productDescription":"Pamphlet: iii, 6 p.; 6 Sheets: 49.0 x 36.26 inches or smaller; Metadata; Data catalog","numberOfPages":"9","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-044298","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science 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Multiple factors, including limitation in food resources, have been proposed as possible causes for the lack of recovery of the endangered western segment of the Steller sea lion population in the United States. Because maternal body condition has important consequences on fetal development and neonatal survival, the diets of pregnant females may be particularly important in regulating population sizes. We used the stable carbon and nitrogen isotope values of vibrissae from Steller sea lion pups as an indirect indicator of maternal diets during gestation. Combining these data with isotope data from potential prey species in a Bayesian mixing model, we generated proportional estimates of dietary consumption for key prey. Our analysis indicated that females in the most westerly metapopulations relied heavily on Atka mackerel and squid, whereas females inhabiting the Gulf of Alaska region had a fairly mixed diet, and the metapopulation of Southeast Alaska showed a strong reliance on forage fish. These results are similar to previous data from scat collections; however, they indicate a possible under-representation of soft-bodied prey (squid) or prey with fragile skeletons (forage fish) from analyses of data from scats. This study supports the utility of stable isotope modeling in predicting diet composition in gestating adult female Steller sea lions during winter, using pup vibrissae.

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,{"id":70146632,"text":"sim3326 - 2015 - Water-table and potentiometric-surface altitudes in the Upper Glacial, Magothy, and Lloyd aquifers of Long Island, New York, April-May 2013","interactions":[],"lastModifiedDate":"2016-06-23T16:08:43","indexId":"sim3326","displayToPublicDate":"2015-05-18T23:45:00","publicationYear":"2015","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":"3326","title":"Water-table and potentiometric-surface altitudes in the Upper Glacial, Magothy, and Lloyd aquifers of Long Island, New York, April-May 2013","docAbstract":"

The U.S. Geological Survey (USGS), in cooperation with State and local agencies, systematically collects groundwater data at varying measurement frequencies to monitor the hydrologic conditions on Long Island, New York. Each year during April and May, the USGS conducts a synoptic survey of water levels to define the spatial distribution of the water table and potentiometric surfaces within the three main water-bearing units underlying Long Island—the upper glacial, Magothy, and Lloyd aquifers (Smolensky and others, 1989)—and the hydraulically connected Jameco (Soren, 1971) and North Shore aquifers (Stumm, 2001). These data and the maps constructed from them are commonly used in studies of Long Island's hydrology and are utilized by water managers and suppliers for aquifer management and planning purposes.

\n

Water-level measurements made in 502 monitoring wells (observation and supply wells) and 16 streamgage locations across Long Island during April–May 2013 were used to prepare the maps in this report. Groundwater measurements were made by the wetted-tape method to the nearest hundredth of a foot. Contours of water-table and potentiometric-surface altitudes were created by using the groundwater measurements. The water-table contours were interpreted by using water-level data collected from 16 streamgages, 334 observation wells, and 1 supply well screened in the upper glacial aquifer or the shallow Magothy aquifer; the Magothy aquifer's potentiometric-surface contours were interpreted from measurements at 70 observation wells and 31 supply wells screened in the middle to deep Magothy aquifer and the contiguous and hydraulically connected Jameco aquifer. The Lloyd aquifer's potentiometric-surface contours were interpreted from measurements at 58 observation wells and 8 supply wells screened in the Lloyd aquifer and the contiguous and hydraulically connected North Shore aquifer. Many of the supply wells are in continuous operation and therefore, were turned off for a minimum of 24 hours before measurements were made to allow the water levels in the wells to recover to ambient (non-pumping) conditions. Full recovery time at some of these supply wells can exceed 24 hours; therefore, water levels measured at these wells are assumed to be less accurate than those measured at observation wells, which are not pumped (Busciolano, 2002). In addition to pumping stresses, elevated chloride concentrations (saline water) also lower the water levels measured in certain wells. This reduction in water level is the result of saline water being denser than freshwater (Lusczynski, 1961). In this report, all water-level altitudes are referenced to the National Geodetic Vertical Datum of 1929 (NGVD 29).

\n

The land surface or topography was downloaded from the National Map portal (http://nationalmap.gov), which represents the most currently available terrain representation as a 10-meter digital elevation model (DEM). The National Map terrain representation was combined with additional land surface terrain models of Suffolk County and New York City, which were collected using lidar to produce a high accuracy three-dimensional land surface altitude model based on the geospatial product for coastal flood mapping. The datum for land surface altitude is North American Vertical Datum of 1988 (NAVD 88). On Long Island NAVD 88 is approximately 1-foot lower than NGVD 29.

\n

Hydrographs are included on these maps for selected wells that have digital recording equipment. These hydrographs are representative of the 2013 water year to show the changes that have occurred throughout that period. The synoptic survey water level measured at the well is included on each hydrograph.

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Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180
(518) 285-5600
http://ny.water.usgs.gov

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