{"pageNumber":"703","pageRowStart":"17550","pageSize":"25","recordCount":40789,"records":[{"id":70043805,"text":"70043805 - 2012 - Radar analysis of fall bird migration stopover sites in the Northeastern U.S.","interactions":[],"lastModifiedDate":"2022-03-25T15:46:40.474276","indexId":"70043805","displayToPublicDate":"2012-06-30T08:05:55","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Radar analysis of fall bird migration stopover sites in the Northeastern U.S.","docAbstract":"The national network of weather surveillance radars (WSR-88D/NEXRAD) detects birds in flight, and has proven to be a useful remote-sensing tool for ornithological study. We used data collected during Fall 2008 and 2009 by 16 WSR-88D and 3 terminal Doppler weather radars in the northeastern U.S. (U.S. Fish and Wildlife Service Region 5) to study the spatial distribution of landbirds shortly after they leave daytime stopover sites to embark on nocturnal migratory flights. The aerial density of birds, as estimated by radar reflectivity, was georeferenced to the approximate locations on the ground from which birds emerged. We classified bird stopover use by the magnitude and variation of radar reflectivity across nights; areas were considered ‘important’ stopover sites from a conservation perspective if relative bird density was consistently or occasionally high. These results were used to develop models to predict potentially important stopover sites in portions of the region not sampled by the radars, based on land cover, ground elevation, and geographic location. Locally important stopover sites generally were associated with deciduous forests embedded within landscapes dominated by developed or agricultural lands, or near the shores of major water bodies. Large areas of regionally important stopover sites were located along the coastlines of Long Island Sound, throughout the Delmarva Peninsula, in areas surrounding Baltimore and Washington, along the western edge of the Adirondack Mountains, and within the Appalachian Mountains of southwestern Virginia and West Virginia. Important stopover sites, both within and outside radar-sampled areas and on 34 national wildlife refuges sampled by the radars, were mapped in a Geographic Information System, providing base maps for conservation uses and a sampling frame for field surveys to ‘ground truth’ the radar and analytical results. Our analysis indicates that preserving patches of natural habitat, particularly deciduous forests, in developed or agricultural landscapes and along major coastlines should be a priority for conservation plans addressing the stopover requirements of migratory landbirds.","publisher":"University of Delaware","publisherLocation":"Newark, Deleware","usgsCitation":"Butler, J.J., and Dawson, D.K., 2012, Radar analysis of fall bird migration stopover sites in the Northeastern U.S., 96 p.","productDescription":"96 p.","numberOfPages":"96","ipdsId":"IP-038462","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":397607,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":397521,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://acjv.org/radar_study/Buler_Dawson_2012.pdf"}],"country":"United States","state":"Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New 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,{"id":70038890,"text":"70038890 - 2012 - Prion protein degradation by lichens of the genus Cladonia","interactions":[],"lastModifiedDate":"2021-01-04T13:45:42.451036","indexId":"70038890","displayToPublicDate":"2012-06-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2616,"text":"Lichenologist","active":true,"publicationSubtype":{"id":10}},"title":"Prion protein degradation by lichens of the genus Cladonia","docAbstract":"<p><span>It has recently been discovered that lichens contain a serine protease capable of degrading the pathogenic prion protein, the etiological agent of prion diseases such as sheep scrapie and cervid chronic wasting disease. Limited methods are available to degrade or inactivate prion disease agents, especially in the environment, and lichens or their serine protease could prove important for management of these diseases. Scant information is available regarding the presence or absence of the protease responsible for degrading prion protein (PrP) in lichen species and, in this study, we tested the hypothesis that PrP degradation activity in lichens is phylogenetically-based by testing 44 species of&nbsp;</span><span class=\"italic\">Cladonia</span><span>&nbsp;lichens, a genus for which a significant portion of the phylogeny is well established. We categorized PrP degradation activity among the 44 species (high, moderate, low or none) and found that activity in&nbsp;</span><span class=\"italic\">Cladonia</span><span>&nbsp;species did not correspond with phylogenetic position of the species. Degradation of PrP did correspond, however, with three classical taxonomic characters within the genus: species with brown apothecia, no usnic acid, and the presence of a cortex. Of the 44 species studied, 18 (41%) had either high or moderate PrP degradation activity, suggesting the protease may be frequent in this genus of lichens.</span></p>","language":"English","publisher":"Cambridge University Press","doi":"10.1017/S0024282912000102","usgsCitation":"Bennett, J.P., Rodriguez, C.M., and Johnson, C.J., 2012, Prion protein degradation by lichens of the genus Cladonia: Lichenologist, v. 44, no. 4, p. 523-531, https://doi.org/10.1017/S0024282912000102.","productDescription":"9 p.","startPage":"523","endPage":"531","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":381843,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"North America","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": 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M.","contributorId":27753,"corporation":false,"usgs":true,"family":"Rodriguez","given":"Cynthia","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":465176,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Christopher J. cjjohnson@usgs.gov","contributorId":3491,"corporation":false,"usgs":true,"family":"Johnson","given":"Christopher","email":"cjjohnson@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":465175,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70118289,"text":"70118289 - 2012 - Disequilibrium dihedral angles in dolerite sills","interactions":[],"lastModifiedDate":"2014-07-28T11:27:09","indexId":"70118289","displayToPublicDate":"2012-06-29T11:26:15","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Disequilibrium dihedral angles in dolerite sills","docAbstract":"The geometry of clinopyroxene-plagioclase-plagioclase junctions in mafic rocks, measured by the median dihedral angle Θ<sub>cpp</sub>, is created during solidification. In the solidifying Kilauea Iki (Hawaii) lava lake, the wider junctions between plagioclase grains are the first to be filled by pyroxene, followed by the narrower junctions. The final Θ<sub>cpp</sub>, attained when all clinopyroxene-plagioclase-plagioclase junctions are formed, is 78° in the upper crust of the lake, and 85° in the lower solidification front. Θ<sub>cpp</sub> in the 3.5-m-thick Traigh Bhàn na Sgùrra sill (Inner Hebrides) is everywhere 78°. In the Whin Sill (northern England, 38 m thick) and the Portal Peak sill (Antarctica, 129 m thick), Θ<sub>cpp</sub> varies symmetrically, with the lowest values at the margins. The 266-m-thick Basement Sill (Antarctica) has asymmetric variation of Θ<sub>cpp</sub>, attributed to a complex filling history. The chilled margins of the Basement Sill are partially texturally equilibrated, with high Θ<sub>cpp</sub>. The plagioclase grain size in the two widest sills varies asymmetrically, with the coarsest rocks found in the upper third. Both Θ<sub>cpp</sub> and average grain size are functions of model crystallization times. Θ<sub>cpp</sub> increases from 78° to a maximum of ∼100° as the crystallization time increases from 1 to 500 yr. Because the use of grain size as a measure of crystallization time is dependent on an estimate of crystal growth rates, dihedral angles provide a more direct proxy for cooling rates in dolerites.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","doi":"10.1130/G33119.1","usgsCitation":"Holness, M.B., Richardson, C., and Helz, R., 2012, Disequilibrium dihedral angles in dolerite sills: Geology, v. 40, no. 9, p. 795-798, https://doi.org/10.1130/G33119.1.","productDescription":"4 p.","startPage":"795","endPage":"798","numberOfPages":"4","costCenters":[],"links":[{"id":291148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291147,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1130/G33119.1"}],"volume":"40","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f4d1e4b0bc0bec0a11fe","contributors":{"authors":[{"text":"Holness, Marian B.","contributorId":17541,"corporation":false,"usgs":true,"family":"Holness","given":"Marian","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":496705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richardson, Chris","contributorId":11960,"corporation":false,"usgs":true,"family":"Richardson","given":"Chris","email":"","affiliations":[],"preferred":false,"id":496704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Helz, Rosalind T. 0000-0003-1550-0684","orcid":"https://orcid.org/0000-0003-1550-0684","contributorId":66181,"corporation":false,"usgs":true,"family":"Helz","given":"Rosalind T.","affiliations":[],"preferred":false,"id":496706,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70038872,"text":"sir20125124 - 2012 - A conceptual model of the hydrogeologic framework, geochemistry, and groundwater-flow system of the Edwards-Trinity and related aquifers in the Pecos County region, Texas","interactions":[],"lastModifiedDate":"2016-08-08T08:57:40","indexId":"sir20125124","displayToPublicDate":"2012-06-29T00:00:00","publicationYear":"2012","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":"2012-5124","title":"A conceptual model of the hydrogeologic framework, geochemistry, and groundwater-flow system of the Edwards-Trinity and related aquifers in the Pecos County region, Texas","docAbstract":"<p>A conceptual model of the hydrogeologic framework, geochemistry, and groundwater-flow system of the Edwards-Trinity and related aquifers, which include the Pecos Valley, Igneous, Dockum, Rustler, and Capitan Reef aquifers, was developed as the second phase of a groundwater availability study in the Pecos County region in west Texas. The first phase of the study was to collect and compile groundwater, surface-water, water-quality, geophysical, and geologic data in the area. The third phase of the study involves a numerical groundwater-flow model of the Edwards-Trinity aquifer in order to simulate groundwater conditions based on various groundwater-withdrawal scenarios. Resource managers plan to use the results of the study to establish management strategies for the groundwater system. The hydrogeologic framework is composed of the hydrostratigraphy, structural features, and hydraulic properties of the groundwater system. Well and geophysical logs were interpreted to define the top and base surfaces of the Edwards-Trinity aquifer units. Elevations of the top and base of the Edwards-Trinity aquifer generally decrease from the southwestern part of the study area to the northeast. The thicknesses of the Edwards-Trinity aquifer units were calculated using the interpolated top and base surfaces of the hydrostratigraphic units. Some of the thinnest sections of the aquifer were in the eastern part of the study area and some of the thickest sections were in the Pecos, Monument Draw, and Belding-Coyanosa trough areas. Normal-fault zones, which formed as growth and collapse features as sediments were deposited along the margins of more resistant rocks and as overlying sediments collapsed into the voids created by the dissolution of Permian-age evaporite deposits, were delineated based on the interpretation of hydrostratigraphic cross sections. The lowest aquifer transmissivity values were measured in the eastern part of the study area; the highest transmissivity values were measured in a faulted area of the Monument Draw trough. Hydraulic conductivity values generally exhibited the same trends as the transmissivity values. Groundwater-quality data and groundwater-level data were used in context with the hydrogeologic framework to assess the chemical characteristics of water from different sources, regional groundwater-flow paths, recharge sources, the mixing of water from different sources, and discharge in the study area. Groundwater-level altitudes generally decrease from southwest to northeast and regional groundwater flow is from areas of recharge south and west to the north and northeast. Four principal sources of recharge to the Edwards-Trinity aquifer were identified: (1) regional flow that originated as recharge northwest of the study area, (2) runoff from the Barilla, Davis, and Glass Mountains, (3) return flow from irrigation, and (4) upwelling from deeper aquifers. Results indicated Edwards-Trinity aquifer water in the study area was dominated by mineralized, regional groundwater flow that most likely recharged during the cooler, wetter climates of the Pleistocene with variable contributions of recent, local recharge. Groundwater generally flows into the down-dip extent of the Edwards-Trinity aquifer where it discharges into overlying or underlying aquifer units, discharges from springs, discharges to the Pecos River, follows a regional flow path east out of the study area, or is withdrawn by groundwater wells. Structural features such as mountains, troughs, and faults play a substantial role in the distribution of recharge, local and regional groundwater flow, spring discharge, and aquifer interaction.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125124","collaboration":"Prepared in cooperation with the Middle Pecos Groundwater Conservation District, Pecos County, City of Fort Stockton, Brewster County, and Pecos County Water Control and Improvement District No. 1","usgsCitation":"Bumgarner, J.R., Stanton, G.P., Teeple, A., Thomas, J.V., Houston, N.A., Payne, J., and Musgrove, M., 2012, A conceptual model of the hydrogeologic framework, geochemistry, and groundwater-flow system of the Edwards-Trinity and related aquifers in the Pecos County region, Texas: U.S. Geological Survey Scientific Investigations Report 2012-5124, vii, 74 p., https://doi.org/10.3133/sir20125124.","productDescription":"vii, 74 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":258081,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5124.bmp"},{"id":258079,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5124/pdf/SIR12-5124.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":258080,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5124/","linkFileType":{"id":5,"text":"html"}}],"scale":"2000000","projection":"Albers Equal Area Projection","datum":"North American Datum of 1983","country":"United States","state":"Texas","county":"Pecos County, Reeves County","city":"Balmorhea, Belding, Fort Stockton","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104,30.25 ], [ -104,31.5 ], [ -102,31.5 ], [ -102,30.25 ], [ -104,30.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e394e4b0c8380cd460ea","contributors":{"authors":[{"text":"Bumgarner, Johnathan R. jbumgarner@usgs.gov","contributorId":5378,"corporation":false,"usgs":true,"family":"Bumgarner","given":"Johnathan","email":"jbumgarner@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":465131,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanton, Gregory P. 0000-0001-8622-0933 gstanton@usgs.gov","orcid":"https://orcid.org/0000-0001-8622-0933","contributorId":1583,"corporation":false,"usgs":true,"family":"Stanton","given":"Gregory","email":"gstanton@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":465128,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teeple, Andrew   0000-0003-1781-8354 apteeple@usgs.gov","orcid":"https://orcid.org/0000-0003-1781-8354","contributorId":1399,"corporation":false,"usgs":true,"family":"Teeple","given":"Andrew  ","email":"apteeple@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":465127,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thomas, Jonathan V. 0000-0003-0903-9713 jvthomas@usgs.gov","orcid":"https://orcid.org/0000-0003-0903-9713","contributorId":2194,"corporation":false,"usgs":true,"family":"Thomas","given":"Jonathan","email":"jvthomas@usgs.gov","middleInitial":"V.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465130,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Houston, Natalie A. 0000-0002-6071-4545 nhouston@usgs.gov","orcid":"https://orcid.org/0000-0002-6071-4545","contributorId":1682,"corporation":false,"usgs":true,"family":"Houston","given":"Natalie","email":"nhouston@usgs.gov","middleInitial":"A.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465129,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Payne, Jason  0000-0003-4294-7924 jdpayne@usgs.gov","orcid":"https://orcid.org/0000-0003-4294-7924","contributorId":1062,"corporation":false,"usgs":true,"family":"Payne","given":"Jason ","email":"jdpayne@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":465126,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Musgrove, MaryLynn","contributorId":34878,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","affiliations":[],"preferred":false,"id":465132,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70038873,"text":"ofr20121137 - 2012 - Documentation of the U.S. Geological Survey sea floor stress and sediment mobility database","interactions":[],"lastModifiedDate":"2021-07-21T15:28:29.946526","indexId":"ofr20121137","displayToPublicDate":"2012-06-29T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1137","displayTitle":"Documentation of the U.S. Geological Survey Sea Floor Stress and Sediment Mobility Database","title":"Documentation of the U.S. Geological Survey sea floor stress and sediment mobility database","docAbstract":"The U.S. Geological Survey Sea Floor Stress and Sediment Mobility Database contains estimates of bottom stress and sediment mobility for the U.S. continental shelf. This U.S. Geological Survey database provides information that is needed to characterize sea floor ecosystems and evaluate areas for human use. The estimates contained in the database are designed to spatially and seasonally resolve the general characteristics of bottom stress over the U.S. continental shelf and to estimate sea floor mobility by comparing critical stress thresholds based on observed sediment texture data to the modeled stress. This report describes the methods used to make the bottom stress and mobility estimates, statistics used to characterize stress and mobility, data validation procedures, and the metadata for each dataset and provides information on how to access the database online.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121137","usgsCitation":"Dalyander, P., Butman, B., Sherwood, C.R., and Signell, R.P., 2012, Documentation of the U.S. Geological Survey sea floor stress and sediment mobility database: U.S. Geological Survey Open-File Report 2012-1137, iv, 9 p., https://doi.org/10.3133/ofr20121137.","productDescription":"iv, 9 p.","onlineOnly":"Y","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438811,"rank":301,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P999PY84","text":"USGS data release","linkHelpText":"U.S. Geological Survey Sea Floor Stress and Sediment Mobility Database"},{"id":258076,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1137.gif"},{"id":258070,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1137/","linkFileType":{"id":5,"text":"html"}},{"id":258071,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1137/pdf/ofr2012-1137.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0385e4b0c8380cd504ff","contributors":{"authors":[{"text":"Dalyander, P. Soupy 0000-0001-9583-0872","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":65177,"corporation":false,"usgs":true,"family":"Dalyander","given":"P. Soupy","affiliations":[],"preferred":false,"id":465136,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Butman, Bradford 0000-0002-4174-2073 bbutman@usgs.gov","orcid":"https://orcid.org/0000-0002-4174-2073","contributorId":943,"corporation":false,"usgs":true,"family":"Butman","given":"Bradford","email":"bbutman@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":465133,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":465135,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Signell, Richard P. rsignell@usgs.gov","contributorId":1435,"corporation":false,"usgs":true,"family":"Signell","given":"Richard","email":"rsignell@usgs.gov","middleInitial":"P.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":465134,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70038875,"text":"70038875 - 2012 - The effect of changes in habitat conditions on the movement of juvenile Snail Kites Rostrhamus sociabilis","interactions":[],"lastModifiedDate":"2018-03-06T15:57:40","indexId":"70038875","displayToPublicDate":"2012-06-29T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1961,"text":"Ibis","active":true,"publicationSubtype":{"id":10}},"title":"The effect of changes in habitat conditions on the movement of juvenile Snail Kites Rostrhamus sociabilis","docAbstract":"The degradation of habitats due to human activities is a major topic of interest for the conservation and management of wild populations. There is growing evidence that the Florida Everglades ecosystem continues to suffer from habitat degradation. After a period of recovery in the 1990s, the Snail Kite Rostrhamus sociabilis population suffered a substantial decline in 2001 and has not recovered since. Habitat degradation has been suggested as one of the primary reasons for this lack of recovery. As a consequence of the continued degradation of the Everglades, we hypothesized that this would have led to increased movement of juvenile Kites over time, as a consequence of the need to find more favourable habitat. We used multistate mark-recapture models to compare between-site movement probabilities of juvenile Snail Kites in the 1990s (1992&ndash;95; which corresponds to the period before the decline) and 2000s (2003&ndash;06; after the decline). Our analyses were based on an extensive radiotelemetry study (266 birds tracked monthly over the entire state of Florida for a total period of 6 years) and considered factors such as sex and age of marked individuals. There was evidence of increased movement of juvenile Snail Kites during the post-decline period from most of the wetland regions used historically by Kites. Higher movement rates may contribute to an increase in the probability of mortality of young individuals and could contribute to the observed declines.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ibis: International Journal of Avain Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1474-919X.2012.01231.x","usgsCitation":"Bowling, A.C., Martin, J., and Kitchens, W.M., 2012, The effect of changes in habitat conditions on the movement of juvenile Snail Kites Rostrhamus sociabilis: Ibis, v. 154, no. 3, p. 554-565, https://doi.org/10.1111/j.1474-919X.2012.01231.x.","productDescription":"12 p.","startPage":"554","endPage":"565","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":258115,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258094,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1474-919X.2012.01231.x","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","volume":"154","issue":"3","noUsgsAuthors":false,"publicationDate":"2012-04-26","publicationStatus":"PW","scienceBaseUri":"505bab19e4b08c986b322c04","contributors":{"authors":[{"text":"Bowling, Andrea C.","contributorId":43615,"corporation":false,"usgs":true,"family":"Bowling","given":"Andrea","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":465143,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Julien 0000-0002-7375-129X julienmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":5785,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","email":"julienmartin@usgs.gov","affiliations":[{"id":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":465142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kitchens, Wiley M. kitchensw@usgs.gov","contributorId":2851,"corporation":false,"usgs":true,"family":"Kitchens","given":"Wiley","email":"kitchensw@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":465141,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70038878,"text":"70038878 - 2012 - A proxy for high-resolution regional reanalysis for the Southeast United States: assessment of precipitation variability in dynamically downscaled reanalyses","interactions":[],"lastModifiedDate":"2012-06-30T01:01:56","indexId":"70038878","displayToPublicDate":"2012-06-29T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1248,"text":"Climate Dynamics","active":true,"publicationSubtype":{"id":10}},"title":"A proxy for high-resolution regional reanalysis for the Southeast United States: assessment of precipitation variability in dynamically downscaled reanalyses","docAbstract":"We present an analysis of the seasonal, subseasonal, and diurnal variability of rainfall from COAPS Land- Atmosphere Regional Reanalysis for the Southeast at 10-km resolution (CLARReS10). Most of our assessment focuses on the representation of summertime subseasonal and diurnal variability.Summer precipitation in the Southeast United States is a particularly challenging modeling problem because of the variety of regional-scale phenomena, such as sea breeze, thunderstorms and squall lines, which are not adequately resolved in coarse atmospheric reanalyses but contribute significantly to the hydrological budget over the region. We find that the dynamically downscaled reanalyses are in good agreement with station and gridded observations in terms of both the relative seasonal distribution and the diurnal structure of precipitation, although total precipitation amounts tend to be systematically overestimated. The diurnal cycle of summer precipitation in the downscaled reanalyses is in very good agreement with station observations and a clear improvement both over their \"parent\" reanalyses and over newer-generation reanalyses. The seasonal cycle of precipitation is particularly well simulated in the Florida; this we attribute to the ability of the regional model to provide a more accurate representation of the spatial and temporal structure of finer-scale phenomena such as fronts and sea breezes. Over the northern portion of the domain summer precipitation in the downscaled reanalyses remains, as in the \"parent\" reanalyses, overestimated. Given the degree of success that dynamical downscaling of reanalyses demonstrates in the simulation of the characteristics of regional precipitation, its favorable comparison to conventional newer-generation reanalyses and its cost-effectiveness, we conclude that for the Southeast United states such downscaling is a viable proxy for high-resolution conventional reanalysis.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Climate Dynamics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s00382-011-1230-y","usgsCitation":"Stefanova, L., Misra, V., Chan, S., Griffin, M., O’Brien, J.J., and Smith, T.J., 2012, A proxy for high-resolution regional reanalysis for the Southeast United States: assessment of precipitation variability in dynamically downscaled reanalyses: Climate Dynamics, v. 38, no. 11-12, p. 2449-2466, https://doi.org/10.1007/s00382-011-1230-y.","productDescription":"18 p.","startPage":"2449","endPage":"2466","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":258091,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258084,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00382-011-1230-y","linkFileType":{"id":5,"text":"html"}}],"country":"United States","volume":"38","issue":"11-12","noUsgsAuthors":false,"publicationDate":"2011-11-10","publicationStatus":"PW","scienceBaseUri":"5059e522e4b0c8380cd46b44","contributors":{"authors":[{"text":"Stefanova, Lydia","contributorId":48300,"corporation":false,"usgs":true,"family":"Stefanova","given":"Lydia","email":"","affiliations":[],"preferred":false,"id":465156,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Misra, Vasubandhu","contributorId":63520,"corporation":false,"usgs":true,"family":"Misra","given":"Vasubandhu","email":"","affiliations":[],"preferred":false,"id":465158,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chan, Steven","contributorId":16971,"corporation":false,"usgs":true,"family":"Chan","given":"Steven","affiliations":[],"preferred":false,"id":465155,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Griffin, Melissa","contributorId":59667,"corporation":false,"usgs":true,"family":"Griffin","given":"Melissa","email":"","affiliations":[],"preferred":false,"id":465157,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Brien, James J.","contributorId":100997,"corporation":false,"usgs":true,"family":"O’Brien","given":"James","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":465159,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Thomas J. III tom_j_smith@usgs.gov","contributorId":1615,"corporation":false,"usgs":true,"family":"Smith","given":"Thomas","suffix":"III","email":"tom_j_smith@usgs.gov","middleInitial":"J.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":465154,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70003782,"text":"70003782 - 2012 - Wetland selection by breeding and foraging black terns in the Prairie Pothole Region of the United States","interactions":[],"lastModifiedDate":"2012-07-03T17:03:08","indexId":"70003782","displayToPublicDate":"2012-06-29T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Wetland selection by breeding and foraging black terns in the Prairie Pothole Region of the United States","docAbstract":"We examined wetland selection by the Black Tern (Chlidonias niger), a species that breeds primarily in the prairie pothole region, has experienced population declines, and is difficult to manage because of low site fidelity. To characterize its selection of wetlands in this region, we surveyed 589 wetlands throughout North and South Dakota. We documented breeding at 5% and foraging at 17% of wetlands. We created predictive habitat models with a machine-learning algorithm, Random Forests, to explore the relative role of local wetland characteristics and those of the surrounding landscape and to evaluate which characteristics were important to predicting breeding versus foraging. We also examined area-dependent wetland selection while addressing the passive sampling bias by replacing occurrence of terns in the models with an index of density. Local wetland variables were more important than landscape variables in predictions of occurrence of breeding and foraging. Wetland size was more important to prediction of foraging than of breeding locations, while floating matted vegetation was more important to prediction of breeding than of foraging locations. The amount of seasonal wetland in the landscape was the only landscape variable important to prediction of both foraging and breeding. Models based on a density index indicated that wetland selection by foraging terns may be more area dependent than that by breeding terns. Our study provides some of the first evidence for differential breeding and foraging wetland selection by Black Terns and for a more limited role of landscape effects and area sensitivity than has been previously shown.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"The Condor","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"University of California Press","publisherLocation":"Berkeley, CA","doi":"10.1525/cond.2012.110097","usgsCitation":"Steen, V., and Powell, A., 2012, Wetland selection by breeding and foraging black terns in the Prairie Pothole Region of the United States: The Condor, v. 114, no. 1, p. 155-165, https://doi.org/10.1525/cond.2012.110097.","productDescription":"11 p.","startPage":"155","endPage":"165","costCenters":[{"id":108,"text":"Alaska Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":474438,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1525/cond.2012.110097","text":"Publisher Index Page"},{"id":258111,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258103,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1525/cond.2012.110097","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Prairie Pothole Region","volume":"114","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bd01fe4b08c986b32ecb0","contributors":{"authors":[{"text":"Steen, Valerie A.","contributorId":59663,"corporation":false,"usgs":true,"family":"Steen","given":"Valerie A.","affiliations":[],"preferred":false,"id":348823,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powell, Abby N. abby_powell@usgs.gov","contributorId":2534,"corporation":false,"usgs":false,"family":"Powell","given":"Abby N.","email":"abby_powell@usgs.gov","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":348822,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70038879,"text":"ofr20091057 - 2012 - Quick-start guide for version 3.0 of EMINERS - Economic Mineral Resource Simulator","interactions":[],"lastModifiedDate":"2012-07-03T17:03:08","indexId":"ofr20091057","displayToPublicDate":"2012-06-29T00:00:00","publicationYear":"2012","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":"2009-1057","title":"Quick-start guide for version 3.0 of EMINERS - Economic Mineral Resource Simulator","docAbstract":"Quantitative mineral resource assessment, as developed by the U.S. Geological Survey (USGS), consists of three parts: (1) development of grade and tonnage mineral deposit models; (2) delineation of tracts permissive for each deposit type; and (3) probabilistic estimation of the numbers of undiscovered deposits for each deposit type (Singer and Menzie, 2010). The estimate of the number of undiscovered deposits at different levels of probability is the input to the EMINERS (Economic Mineral Resource Simulator) program. EMINERS uses a Monte Carlo statistical process to combine probabilistic estimates of undiscovered mineral deposits with models of mineral deposit grade and tonnage to estimate mineral resources. It is based upon a simulation program developed by Root and others (1992), who discussed many of the methods and algorithms of the program. Various versions of the original program (called \"MARK3\" and developed by David H. Root, William A. Scott, and Lawrence J. Drew of the USGS) have been published (Root, Scott, and Selner, 1996; Duval, 2000, 2012). The current version (3.0) of the EMINERS program is available as USGS Open-File Report 2004-1344 (Duval, 2012). Changes from version 2.0 include updating 87 grade and tonnage models, designing new templates to produce graphs showing cumulative distribution and summary tables, and disabling economic filters. The economic filters were disabled because embedded data for costs of labor and materials, mining techniques, and beneficiation methods are out of date. However, the cost algorithms used in the disabled economic filters are still in the program and available for reference for mining methods and milling techniques included in Camm (1991). EMINERS is written in C++ and depends upon the Microsoft Visual C++ 6.0 programming environment. The code depends heavily on the use of Microsoft Foundation Classes (MFC) for implementation of the Windows interface. The program works only on Microsoft Windows XP or newer personal computers. It does not work on Macintosh computers. This report demonstrates how to execute EMINERS software using default settings and existing deposit models. Many options are available when setting up the simulation. Information and explanations addressing these optional parameters can be found in the EMINERS Help files. Help files are available during execution of EMINERS by selecting EMINERS Help from the pull-down menu under Help on the EMINERS menu bar. There are four sections in this report. Part I describes the installation, setup, and application of the EMINERS program, and Part II illustrates how to interpret the text file that is produced. Part III describes the creation of tables and graphs by use of the provided Excel templates. Part IV summarizes grade and tonnage models used in version 3.0 of EMINERS.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20091057","collaboration":"A supplement to USGS Open-File Report 2004-1344, Version 3.0 of EMINERS - Economic Mineral Resource Simulator, by J.S. Duval","usgsCitation":"Bawiec, W.J., and Spanski, G.T., 2012, Quick-start guide for version 3.0 of EMINERS - Economic Mineral Resource Simulator: U.S. Geological Survey Open-File Report 2009-1057, iii, 26 p., https://doi.org/10.3133/ofr20091057.","productDescription":"iii, 26 p.","onlineOnly":"Y","costCenters":[{"id":410,"text":"National Center","active":false,"usgs":true}],"links":[{"id":258092,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1057.bmp"},{"id":258085,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2009/1057/OFR2009-1057.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":258086,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1057/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a9302e4b0c8380cd80b70","contributors":{"authors":[{"text":"Bawiec, Walter J.","contributorId":83909,"corporation":false,"usgs":true,"family":"Bawiec","given":"Walter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":465161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spanski, Gregory T.","contributorId":43806,"corporation":false,"usgs":true,"family":"Spanski","given":"Gregory","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":465160,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70038860,"text":"tm6A41 - 2012 - User guide for MODPATH version 6—A particle-tracking model for MODFLOW","interactions":[],"lastModifiedDate":"2025-09-10T18:48:21.353885","indexId":"tm6A41","displayToPublicDate":"2012-06-28T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-A41","title":"User guide for MODPATH version 6—A particle-tracking model for MODFLOW","docAbstract":"MODPATH is a particle-tracking post-processing model that computes three-dimensional flow paths using output from groundwater flow simulations based on MODFLOW, the U.S. Geological Survey (USGS) finite-difference groundwater flow model. This report documents MODPATH version 6. Previous versions were documented in USGS Open-File Reports 89-381 and 94-464. The program uses a semianalytical particle-tracking scheme that allows an analytical expression of a particle's flow path to be obtained within each finite-difference grid cell. A particle's path is computed by tracking the particle from one cell to the next until it reaches a boundary, an internal sink/source, or satisfies another termination criterion. Data input to MODPATH consists of a combination of MODFLOW input data files, MODFLOW head and flow output files, and other input files specific to MODPATH. Output from MODPATH consists of several output files, including a number of particle coordinate output files intended to serve as input data for other programs that process, analyze, and display the results in various ways. MODPATH is written in FORTRAN and can be compiled by any FORTRAN compiler that fully supports FORTRAN-2003 or by most commercially available FORTRAN-95 compilers that support the major FORTRAN-2003 language extensions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A41","usgsCitation":"Pollock, D.W., 2012, User guide for MODPATH version 6—A particle-tracking model for MODFLOW: U.S. Geological Survey Techniques and Methods 6-A41, viii, 58 p., https://doi.org/10.3133/tm6A41.","productDescription":"viii, 58 p.","onlineOnly":"Y","costCenters":[{"id":494,"text":"Office of Groundwater","active":false,"usgs":true}],"links":[{"id":258048,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_6-a41.jpg"},{"id":258067,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/6a41/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bbfbfe4b08c986b329d47","contributors":{"authors":[{"text":"Pollock, David W. dwpolloc@usgs.gov","contributorId":4248,"corporation":false,"usgs":true,"family":"Pollock","given":"David","email":"dwpolloc@usgs.gov","middleInitial":"W.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":465090,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70038861,"text":"ofr20121132 - 2012 - Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida","interactions":[{"subject":{"id":70038861,"text":"ofr20121132 - 2012 - Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida","indexId":"ofr20121132","publicationYear":"2012","noYear":false,"title":"Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida"},"predicate":"SUPERSEDED_BY","object":{"id":70039814,"text":"sir20125161 - 2012 - Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida","indexId":"sir20125161","publicationYear":"2012","noYear":false,"title":"Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida"},"id":1}],"supersededBy":{"id":70039814,"text":"sir20125161 - 2012 - Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida","indexId":"sir20125161","publicationYear":"2012","noYear":false,"title":"Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida"},"lastModifiedDate":"2018-04-02T15:33:45","indexId":"ofr20121132","displayToPublicDate":"2012-06-28T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1132","title":"Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida","docAbstract":"A numerical transient model of the surficial and Floridan aquifer systems in east-central Florida was developed to (1) increase the understanding of water exchanges between the surficial and the Floridan aquifer systems, (2) assess the recharge rates to the surficial aquifer system from infiltration through the unsaturated zone and (3) obtain a simulation tool that could be used by water-resource managers to assess the impact of changes in groundwater withdrawals on spring flows and on the potentiometric surfaces of the hydrogeologic units composing the Floridan aquifer system. The hydrogeology of east-central Florida was evaluated and used to develop and calibrate the groundwater flow model, which simulates the regional fresh groundwater flow system. The U.S. Geological Survey three-dimensional groundwater flow model, MODFLOW-2005, was used to simulate transient groundwater flow in the surficial, intermediate, and Floridan aquifer systems from 1995 to 2006. The east-central Florida transient model encompasses an actively simulated area of about 9,000 square miles. Although the model includes surficial processes-rainfall, irrigation, evapotranspiration, runoff, infiltration, lake water levels, and stream water levels and flows-its primary purpose is to characterize and refine the understanding of groundwater flow in the Floridan aquifer system. Model-independent estimates of the partitioning of rainfall into evapotranspiration, streamflow, and aquifer recharge are provided from a water-budget analysis of the surficial aquifer system. The interaction of the groundwater flow system with the surface environment was simulated using the Green-Ampt infiltration method and the MODFLOW-2005 Unsaturated-Zone Flow, Lake, and Streamflow-Routing Packages. The model is intended to simulate the part of the groundwater system that contains freshwater. The bottom and lateral boundaries of the model were established at the estimated depths where the chloride concentration is 5,000 milligrams per liter in the Floridan aquifer system. Potential flow across the interface represented by this chloride concentration is simulated by the General Head Boundary Package. During 1995 through 2006, there were no major groundwater withdrawals near the freshwater and saline-water interface, making the general head boundary a suitable feature to estimate flow through the interface. The east-central Florida transient model was calibrated using the inverse parameter estimation code, PEST. Steady-state models for 1999 and 2003 were developed to estimate hydraulic conductivity (K) using average annual heads and spring flows as observations. The spatial variation of K was represented using zones of constant values in some layers, and pilot points in other layers. Estimated K values were within one order of magnitude of aquifer performance test data. A simulation of the final two years (2005-2006) of the 12-year model, with the K estimates from the steady-state calibration, was used to guide the estimation of specific yield and specific storage values. The final model yielded head and spring-flow residuals that met the calibration criteria for the 12-year transient simulation. The overall mean residual for heads, defining residual as simulated minus measured value, was -0.04 foot. The overall root-mean square residual for heads was less than 3.6 feet for each year in the 1995 to 2006 simulation period. The overall mean residual for spring flows was -0.3 cubic foot per second. The spatial distribution of head residuals was generally random, with some minor indications of bias. Simulated average evapotranspiration (ET) over the 1995 to 2006 period was 34.5 inches per year, compared to the calculated average ET rate of 36.6 inches per year from the model-independent water-budget analysis. Simulated average net recharge to the surficial aquifer system was 3.6 inches per year, compared with the calculated average of 3.2 inches per year from the model-independent waterbudget analysis. Groundwater withdrawals from the Floridan aquifer system averaged about 800 million gallons per day, which is equivalent to about 2 inches per year over the model area and slightly more than half of the simulated average net recharge to the surficial aquifer system over the same period. Annual net simulated recharge rates to the surficial aquifer system were less than the total groundwater withdrawals from the Floridan aquifer system only during the below-average rainfall years of 2000 and 2006.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121132","collaboration":"Prepared in cooperation with the St. Johns River Water Management District, South Florida Water Management District, and Southwest Florida Water Management District","usgsCitation":"Sepulveda, N., Tiedeman, C.R., O’Reilly, A.M., Davis, J., and Burger, P., 2012, Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida: U.S. Geological Survey Open-File Report 2012-1132, xiv, 226 p., https://doi.org/10.3133/ofr20121132.","productDescription":"xiv, 226 p.","onlineOnly":"Y","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"links":[{"id":258061,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1132.jpg"},{"id":258054,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1132/","linkFileType":{"id":5,"text":"html"}}],"projection":"Universal Transverse Mercator Projector, Zone 17","country":"United States","state":"Florida","county":"Brevard;Hardee;Highlands;Indian River;Lake;Marion;Okeechobee;Orange;Osceola;Polk;Seminole;Volusia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -82,27.5 ], [ -82,29.166666666666668 ], [ -80.5,29.166666666666668 ], [ -80.5,27.5 ], [ -82,27.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a2da0e4b0c8380cd5bf64","contributors":{"authors":[{"text":"Sepulveda, Nicasio 0000-0002-6333-1865 nsepul@usgs.gov","orcid":"https://orcid.org/0000-0002-6333-1865","contributorId":1454,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Nicasio","email":"nsepul@usgs.gov","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":465091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tiedeman, Claire R. 0000-0002-0128-3685 tiedeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0128-3685","contributorId":196777,"corporation":false,"usgs":true,"family":"Tiedeman","given":"Claire","email":"tiedeman@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":465094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Reilly, Andrew M. 0000-0003-3220-1248 aoreilly@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-1248","contributorId":2184,"corporation":false,"usgs":true,"family":"O’Reilly","given":"Andrew","email":"aoreilly@usgs.gov","middleInitial":"M.","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":465092,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Jeffery B.","contributorId":44032,"corporation":false,"usgs":true,"family":"Davis","given":"Jeffery B.","affiliations":[],"preferred":false,"id":465093,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burger, Patrick","contributorId":90976,"corporation":false,"usgs":true,"family":"Burger","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":465095,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70038852,"text":"fs20123088 - 2012 - National Enhanced Elevation Assessment at a glance","interactions":[],"lastModifiedDate":"2012-06-28T01:01:38","indexId":"fs20123088","displayToPublicDate":"2012-06-27T00:00:00","publicationYear":"2012","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":"2012-3088","title":"National Enhanced Elevation Assessment at a glance","docAbstract":"Elevation data are essential for hazards mitigation, conservation, infrastructure development, national security, and many other applications. Under the leadership of the U.S. Geological Survey and the member States of the National Digital Elevation Program (NDEP), Federal agencies, State agencies, and others work together to acquire high-quality elevation data for the United States and its territories. New elevation data are acquired using modern technology to replace elevation data that are, on average, more than 30 years old. Through the efforts of the NDEP, a project-by-project data acquisition approach resulted in improved, publicly available data for 28 percent of the conterminous United States and 15 percent of Alaska over the past 15 years. Although the program operates efficiently, the rate of data collection and the typical project specifications are currently insufficient to address the needs of government, the private sector, and other organizations. The National Enhanced Elevation Assessment was conducted to (1) document national-level requirements for improved elevation data, (2) estimate the benefits and costs of meeting those requirements, and (3) evaluate multiple national-level program-implementation scenarios. The assessment was sponsored by the NDEP's member agencies. The study participants came from 34 Federal agencies, agencies from all 50 States, selected local government and Tribal offices, and private and not-for-profit organizations. A total of 602 mission-critical activities were identified that need significantly more accurate data than are currently available. The results of the assessment indicate that a national-level enhanced-elevation-data program has the potential to generate from $1.2 billion to $13 billion in new benefits annually.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123088","usgsCitation":"Snyder, G., 2012, National Enhanced Elevation Assessment at a glance: U.S. Geological Survey Fact Sheet 2012-3088, 2 p., https://doi.org/10.3133/fs20123088.","productDescription":"2 p.","onlineOnly":"Y","costCenters":[{"id":410,"text":"National Center","active":false,"usgs":true}],"links":[{"id":258037,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3088.gif"},{"id":258012,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3088/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a61d0e4b0c8380cd71b9c","contributors":{"authors":[{"text":"Snyder, Gregory I. gsnyder@usgs.gov","contributorId":4069,"corporation":false,"usgs":true,"family":"Snyder","given":"Gregory I.","email":"gsnyder@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":465080,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70038846,"text":"sir20115114 - 2012 - Nutrient concentrations and loads in the northeastern United States - Status and trends, 1975-2003","interactions":[],"lastModifiedDate":"2017-11-10T18:53:32","indexId":"sir20115114","displayToPublicDate":"2012-06-27T00:00:00","publicationYear":"2012","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":"2011-5114","title":"Nutrient concentrations and loads in the northeastern United States - Status and trends, 1975-2003","docAbstract":"The U.S. Geological Survey (USGS) National Water-Quality Assessment Program (NAWQA) began regional studies in 2003 to synthesize information on nutrient concentrations, trends, stream loads, and sources. In the northeastern United States, a study area that extends from Maine to central Virginia, nutrient data were evaluated for 130 USGS water-quality monitoring stations. Nutrient data were analyzed for trends in flow-adjusted concentrations, modeled instream (non-flow-adjusted) concentrations, and stream loads for 32 stations with 22 to 29 years of water-quality and daily mean streamflow record during 1975-2003 (termed the long-term period), and for 46 stations during 1993-2003 (termed the recent period), by using a coupled statistical model of streamflow and water quality developed by the USGS. Recent trends in flow-adjusted concentrations of one or more nutrients also were analyzed for 90 stations by using Tobit regression. Annual stream nutrient loads were estimated, and annual nutrient yields were calculated, for 47 stations for the long-term and recent periods, and for 37 additional stations that did not have a complete streamflow and water-quality record for 1993-2003. Nutrient yield information was incorporated for 9 drainage basins evaluated in a national NAWQA study, for a total of 93 stations evaluated for nutrient yields. Long-term downward trends in flow-adjusted concentrations of total nitrogen and total phosphorus (18 and 19 of 32 stations, respectively) indicate regional improvements in nutrient-related water-quality conditions. Most of the recent trends detected for total phosphorus were upward (17 of 83 stations), indicating possible reversals to the long-term improvements. Concentrations of nutrients in many streams persist at levels that are likely to affect aquatic habitat adversely and promote freshwater or coastal eutrophication. Recent trends for modeled instream concentrations, and modeled reference concentrations, were evaluated relative to ecoregion-based nutrient criteria proposed by the U.S. Environmental Protection Agency. Instream concentrations of total nitrogen and total phosphorus persist at levels higher than proposed criteria at more than one-third and about one-half, respectively, of the 46 stations analyzed. Long-term trends in nutrient loads were primarily downward, with downward trends in total nitrogen and total phosphorus loads detected at 12 and 17 of 32 stations, respectively. Upward trends were rare, with one upward trend for total nitrogen loads and none for total phosphorus. Trends in loads of nitrite-plus-nitrate nitrogen included 7 upward and 8 downward trends among 32 stations. Downward trends in loads of ammonia nitrogen and total Kjeldahl nitrogen were detected at all six stations evaluated. Long-term downward trends detected in four of the five largest drainage basins evaluated include: total nitrogen loads for the Connecticut, Delaware, and James Rivers; total Kjeldahl nitrogen and ammonia nitrogen loads for the Susquehanna River; ammonia nitrogen and nitrite-plus-nitrate nitrogen loads for the James River; and total phosphorus loads for the Connecticut and Delaware Rivers. No trends in load were detected for the Potomac River. Nutrient yields were evaluated relative to the extent of land development in 93 drainage basins. The undeveloped land-use category included forested drainage basins with undeveloped land ranging from 75 to 100 percent of basin area. Median total nitrogen yields for the 27 undeveloped drainage basins evaluated, including 9 basins evaluated in a national NAWQA study, ranged from 290 to 4,800 pounds per square mile per year (lb/mi<sup>2</sup>/yr). Total nitrogen yields even in the most pristine drainage basins may be elevated relative to natural conditions, because of high rates of atmospheric deposition of nitrogen in parts of the northeastern United States. Median total phosphorus yields ranged from 12 to 330 lb/mi<sup>2</sup>/yr for the 26 undeveloped basins evaluated. The undeveloped category includes some large drainage basins with point-source discharges and small percentages of developed land; in these basins, streamflow from undeveloped headwater areas dilutes streamflow in more urbanized reaches, and dampens but does not eliminate the point-source \"signal\" of higher nutrient loads. Median total nitrogen yields generally do not exceed 1,700 lb/mi<sup>2</sup>/yr, and median total phosphorus yields generally do not exceed 100 lb/mi<sup>2</sup>/yr, in the drainage basins that are least affected by human land-use and waste-disposal practices. Agricultural and urban land use has increased nutrient yields substantially relative to undeveloped drainage basins. Median total nitrogen yields for 24 agricultural basins ranged from 1,700 to 26,000 lb/mi<sup>2</sup>/yr, and median total phosphorus yields ranged from 94 to 1,000 lb/mi<sup>2</sup>/yr. The maximum estimated total nitrogen and total phosphorus yields, 32,000 and 16,000 lb/mi<sup>2</sup>/yr, respectively, for all stations in the region were in small (less than 50 square miles (mi<sup>2</sup>)) agricultural drainage basins. Median total nitrogen yields ranged from 1,400 to 17,000 lb/mi<sup>2</sup>/yr in 26 urbanized drainage basins, and median total phosphorus yields ranged from 43 to 1,900 lb/mi<sup>2</sup>/yr. Urbanized drainage basins with the highest nutrient yields are generally small (less than 300 mi2) and are drained by streams that receive major point-source discharges. Instream nutrient loads were evaluated relative to loads from point-source discharges in four drainage basins: the Quinebaug River Basin in Connecticut, Massachusetts, and Rhode Island; the Raritan River Basin in New Jersey; the Patuxent River Basin in Maryland; and the James River Basin in Virginia. Long-term downward trends in nutrient loads, coupled with similar trends in flow-adjusted nutrient concentrations, indicate long-term reductions in the delivery of most nutrients to these streams. However, the absence of recent downward trends in load for most nutrients, coupled with instream concentrations that exceed proposed nutrient criteria in several of these waste-receiving streams, indicates that challenges remain in reducing delivery of nutrients to streams from point sources. During dry years, the total nutrient load from point sources in some of the drainage basins approached or equaled the nutrient load transported by the stream.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115114","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Trench, E.C., Moore, R.B., Ahearn, E.A., Mullaney, J.R., Hickman, R.E., and Schwarz, G., 2012, Nutrient concentrations and loads in the northeastern United States - Status and trends, 1975-2003: U.S. Geological Survey Scientific Investigations Report 2011-5114, xi, 134 p.; Tables: pgs. 135-148; Appendices: pgs. 149-169; Excel Tables 1-10; Excel Tables 11-27; Appendix index page with contents and file downloads, https://doi.org/10.3133/sir20115114.","productDescription":"xi, 134 p.; Tables: pgs. 135-148; Appendices: pgs. 149-169; Excel Tables 1-10; Excel Tables 11-27; Appendix index page with contents and file downloads","temporalStart":"1975-01-01","temporalEnd":"2003-12-31","costCenters":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"links":[{"id":258027,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5114.jpg"},{"id":258009,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5114/","linkFileType":{"id":5,"text":"html"}}],"scale":"2000000","projection":"1990 Albers Equal-Area Projection","datum":"North American Datum of 1983","country":"United States","state":"Connecticut;Delaware;Maine;Maryl;Massachusetts;New Hampshire;New Jersey;New York;Pennsylvania;Rhode Island;Vermont;Virginia;Washington D.C.;West Virginia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -82,36 ], [ -82,48 ], [ -66,48 ], [ -66,36 ], [ -82,36 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a697be4b0c8380cd73d48","contributors":{"authors":[{"text":"Trench, Elaine C. Todd etrench@usgs.gov","contributorId":4557,"corporation":false,"usgs":true,"family":"Trench","given":"Elaine","email":"etrench@usgs.gov","middleInitial":"C. Todd","affiliations":[],"preferred":true,"id":465075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Richard B. rmoore@usgs.gov","contributorId":1464,"corporation":false,"usgs":true,"family":"Moore","given":"Richard","email":"rmoore@usgs.gov","middleInitial":"B.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465071,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ahearn, Elizabeth A. 0000-0002-5633-2640 eaahearn@usgs.gov","orcid":"https://orcid.org/0000-0002-5633-2640","contributorId":194658,"corporation":false,"usgs":true,"family":"Ahearn","given":"Elizabeth","email":"eaahearn@usgs.gov","middleInitial":"A.","affiliations":[{"id":377,"text":"Massachusetts-Rhode Island Water Science Center","active":false,"usgs":true},{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"preferred":false,"id":465072,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mullaney, John R. 0000-0003-4936-5046 jmullane@usgs.gov","orcid":"https://orcid.org/0000-0003-4936-5046","contributorId":1957,"corporation":false,"usgs":true,"family":"Mullaney","given":"John","email":"jmullane@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465073,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hickman, R. Edward 0000-0001-5160-3723 whickman@usgs.gov","orcid":"https://orcid.org/0000-0001-5160-3723","contributorId":3153,"corporation":false,"usgs":true,"family":"Hickman","given":"R.","email":"whickman@usgs.gov","middleInitial":"Edward","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465074,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":543,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory E.","email":"gschwarz@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":false,"id":465070,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70003555,"text":"70003555 - 2012 - Field evaluation of distance-estimation error during wetland-dependent bird surveys","interactions":[],"lastModifiedDate":"2017-05-10T13:54:51","indexId":"70003555","displayToPublicDate":"2012-06-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"title":"Field evaluation of distance-estimation error during wetland-dependent bird surveys","docAbstract":"<p><strong>Context:</strong> The most common methods to estimate detection probability during avian point-count surveys involve recording a distance between the survey point and individual birds detected during the survey period. Accurately measuring or estimating distance is an important assumption of these methods; however, this assumption is rarely tested in the context of aural avian point-count surveys. <strong>Aims:</strong> We expand on recent bird-simulation studies to document the error associated with estimating distance to calling birds in a wetland ecosystem. <strong>Methods:</strong> We used two approaches to estimate the error associated with five surveyor's distance estimates between the survey point and calling birds, and to determine the factors that affect a surveyor's ability to estimate distance. <strong>Key results:</strong> We observed biased and imprecise distance estimates when estimating distance to simulated birds in a point-count scenario (<i>x̄</i><sub>error</sub> = -9 m, s.d.<sub>error</sub> = 47 m) and when estimating distances to real birds during field trials (<i>x̄</i><sub>error</sub> = 39 m, s.d.<sub>error</sub> = 79 m). The amount of bias and precision in distance estimates differed among surveyors; surveyors with more training and experience were less biased and more precise when estimating distance to both real and simulated birds. Three environmental factors were important in explaining the error associated with distance estimates, including the measured distance from the bird to the surveyor, the volume of the call and the species of bird. Surveyors tended to make large overestimations to birds close to the survey point, which is an especially serious error in distance sampling. <strong>Conclusions:</strong> Our results suggest that distance-estimation error is prevalent, but surveyor training may be the easiest way to reduce distance-estimation error. <strong>Implications:</strong> The present study has demonstrated how relatively simple field trials can be used to estimate the error associated with distance estimates used to estimate detection probability during avian point-count surveys. Evaluating distance-estimation errors will allow investigators to better evaluate the accuracy of avian density and trend estimates. Moreover, investigators who evaluate distance-estimation errors could employ recently developed models to incorporate distance-estimation error into analyses. We encourage further development of such models, including the inclusion of such models into distance-analysis software.</p>","publisher":"CSIRO Publishing","publisherLocation":"Collingwood, Victoria, Australia","doi":"10.1071/WR11161","usgsCitation":"Nadeau, C.P., and Conway, C.J., 2012, Field evaluation of distance-estimation error during wetland-dependent bird surveys: Wildlife Research, v. 39, no. 4, p. 311-320, https://doi.org/10.1071/WR11161.","productDescription":"10 p.","startPage":"311","endPage":"320","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-025947","costCenters":[],"links":[{"id":257970,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0fb4e4b0c8380cd539b1","contributors":{"authors":[{"text":"Nadeau, Christopher P.","contributorId":105956,"corporation":false,"usgs":true,"family":"Nadeau","given":"Christopher","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":347716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":347715,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70038856,"text":"fs20123086 - 2012 - Science implementation of Forecast Mekong for food and environmental security","interactions":[],"lastModifiedDate":"2012-06-28T01:01:38","indexId":"fs20123086","displayToPublicDate":"2012-06-27T00:00:00","publicationYear":"2012","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":"2012-3086","title":"Science implementation of Forecast Mekong for food and environmental security","docAbstract":"Forecast Mekong is a significant international thrust under the Delta Research and Global Observation Network (DRAGON) of the U.S. Geological Survey (USGS) and was launched in 2009 by the U.S. Department of State and the Foreign Ministers of Cambodia, Laos, Thailand, and Vietnam under U.S. Department of State Secretary Hillary R. Clinton's Lower Mekong Initiative to enhance U.S. engagement with countries of the Lower Mekong River Basin in the areas of environment, health, education, and infrastructure. Since 2009, the USGS has worked closely with the U.S. Department of State; personnel from Cambodia, Laos, Thailand, and Vietnam; nongovernmental organizations; and academia to collect and use research and data from the Lower Mekong River Basin to provide hands-on results that will help decisionmakers in future planning and design for restoration, conservation, and management efforts in the Lower Mekong River Basin. In 2012 Forecast Mekong is highlighting the increasing cooperation between the United States and Lower Mekong River Basin countries in the areas of food and environmental security. Under the DRAGON, Forecast Mekong continues work in interactive data integration, modeling, and visualization system by initiating three-dimensional bathymetry and river flow data along with a pilot study of fish distribution, population, and migratory patterns in the Lower Mekong River Basin. When fully developed by the USGS, in partnership with local governments and universities throughout the Mekong River region, Forecast Mekong will provide valuable planning tools to visualize the consequences of climate change and river management.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123086","usgsCitation":"Turnipseed, D.P., 2012, Science implementation of Forecast Mekong for food and environmental security: U.S. Geological Survey Fact Sheet 2012-3086, 4 p., https://doi.org/10.3133/fs20123086.","productDescription":"4 p.","onlineOnly":"Y","temporalStart":"2009-01-01","temporalEnd":"2012-12-31","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":258017,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3086/","linkFileType":{"id":5,"text":"html"}},{"id":258038,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3086.bmp"}],"country":"Cambodia;Laos;Thailand;Vietnam","city":"Phnom Penh","otherGeospatial":"Mekong River;TonléSap River","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b8773e4b08c986b3164b4","contributors":{"authors":[{"text":"Turnipseed, D. Phil 0000-0002-9737-3203 pturnip@usgs.gov","orcid":"https://orcid.org/0000-0002-9737-3203","contributorId":298,"corporation":false,"usgs":true,"family":"Turnipseed","given":"D.","email":"pturnip@usgs.gov","middleInitial":"Phil","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":465082,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70038853,"text":"gip144 - 2012 - Forecast Mekong 2012: Building scientific capacity","interactions":[],"lastModifiedDate":"2012-06-28T01:01:38","indexId":"gip144","displayToPublicDate":"2012-06-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"144","title":"Forecast Mekong 2012: Building scientific capacity","docAbstract":"In 2009, U.S. Secretary of State Hillary R. Clinton joined the Foreign Ministers of Cambodia, Laos, Thailand, and Vietnam in launching the Lower Mekong Initiative to enhance U.S. engagement with the countries of the Lower Mekong River Basin in the areas of environment, health, education, and infrastructure. The U.S. Geological Survey Forecast Mekong supports the Lower Mekong Initiative through a variety of activities. The principal objectives of Forecast Mekong include the following: * Build scientific capacity in the Lower Mekong Basin and promote cooperation and collaboration among scientists working in the region. * Provide data, information, and scientific models to help resource managers there make informed decisions. * Produce forecasting and visualization tools to support basin planning, including climate change adaptation. The focus of this product is Forecast Mekong accomplishments and current activities related to the development of scientific capacity at organizations and institutions in the region. Building on accomplishments in 2010 and 2011, Forecast Mekong continues to enhance scientific capacity in the Lower Mekong Basin with a suite of activities in 2012.","language":"English","publisher":"U.S. Geological Suvey","publisherLocation":"Reston, VA","doi":"10.3133/gip144","usgsCitation":"Stefanov, J.E., 2012, Forecast Mekong 2012: Building scientific capacity: U.S. Geological Survey General Information Product 144, 8 p., https://doi.org/10.3133/gip144.","productDescription":"8 p.","onlineOnly":"Y","temporalStart":"2009-01-01","temporalEnd":"2012-12-31","costCenters":[],"links":[{"id":258036,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/gip_144.gif"},{"id":258014,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/gip/144/","linkFileType":{"id":5,"text":"html"}}],"country":"Cambodia;Laos;Thailand;Vietnam","otherGeospatial":"Lower Mekong Basin","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a130fe4b0c8380cd544e2","contributors":{"authors":[{"text":"Stefanov, James E. jestefan@usgs.gov","contributorId":1575,"corporation":false,"usgs":true,"family":"Stefanov","given":"James","email":"jestefan@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":465081,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70006199,"text":"70006199 - 2012 - Spatial ecology of refuge selection by an herbivore under risk of predation","interactions":[],"lastModifiedDate":"2017-05-10T09:47:42","indexId":"70006199","displayToPublicDate":"2012-06-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Spatial ecology of refuge selection by an herbivore under risk of predation","docAbstract":"Prey species use structures such as burrows to minimize predation risk. The spatial arrangement of these resources can have important implications for individual and population fitness. For example, there is evidence that clustered resources can benefit individuals by reducing predation risk and increasing foraging opportunity concurrently, which leads to higher population density. However, the scale of clustering that is important in these processes has been ignored during theoretical and empirical development of resource models. Ecological understanding of refuge exploitation by prey can be improved by spatial analysis of refuge use and availability that incorporates the effect of scale. We measured the spatial distribution of pygmy rabbit (Brachylagus idahoensis) refugia (burrows) through censuses in four 6-ha sites. Point pattern analyses were used to evaluate burrow selection by comparing the spatial distribution of used and available burrows. The presence of food resources and additional overstory cover resources was further examined using logistic regression. Burrows were spatially clustered at scales up to approximately 25 m, and then regularly spaced at distances beyond ~40 m. Pygmy rabbit exploitation of burrows did not match availability. Burrows used by pygmy rabbits were likely to be located in areas with high overall burrow density (resource clusters) and high overstory cover, which together minimized predation risk. However, in some cases we observed an interaction between either overstory cover (safety) or understory cover (forage) and burrow density. The interactions show that pygmy rabbits will use burrows in areas with low relative burrow density (high relative predation risk) if understory food resources are high. This points to a potential trade-off whereby rabbits must sacrifice some safety afforded by additional nearby burrows to obtain ample forage resources. Observed patterns of clustered burrows and non-random burrow use improve understanding of the importance of spatial distribution of refugia for burrowing herbivores. The analyses used allowed for the estimation of the spatial scale where subtle trade-offs between predation avoidance and foraging opportunity are likely to occur in a natural system.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecosphere","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","publisherLocation":"Ithaca, NY","doi":"10.1890/ES11-00247.1","usgsCitation":"Wilson, T.L., Rayburn, A.P., and Edwards, T.C., 2012, Spatial ecology of refuge selection by an herbivore under risk of predation: Ecosphere, v. 3, no. 1, 18 p.; Article 6, https://doi.org/10.1890/ES11-00247.1.","productDescription":"18 p.; Article 6","ipdsId":"IP-034244","costCenters":[{"id":609,"text":"Utah Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":488011,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/es11-00247.1","text":"Publisher Index Page"},{"id":257955,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257939,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/ES11-00247.1","linkFileType":{"id":5,"text":"html"}}],"country":"United States","volume":"3","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-01-24","publicationStatus":"PW","scienceBaseUri":"505b9477e4b08c986b31aadd","contributors":{"authors":[{"text":"Wilson, Tammy L.","contributorId":81741,"corporation":false,"usgs":true,"family":"Wilson","given":"Tammy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":354054,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rayburn, Andrew P.","contributorId":8710,"corporation":false,"usgs":true,"family":"Rayburn","given":"Andrew","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":354053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, Thomas C. Jr. 0000-0002-0773-0909 tce@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-0909","contributorId":2061,"corporation":false,"usgs":true,"family":"Edwards","given":"Thomas","suffix":"Jr.","email":"tce@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":false,"id":354052,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70004058,"text":"70004058 - 2012 - Rotenone persistence model for montane streams","interactions":[],"lastModifiedDate":"2012-06-26T01:01:35","indexId":"70004058","displayToPublicDate":"2012-06-25T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Rotenone persistence model for montane streams","docAbstract":"The efficient and effective use of rotenone is hindered by its unknown persistence in streams. Environmental conditions degrade rotenone, but current label instructions suggest fortifying the chemical along a stream based on linear distance or travel time rather than environmental conditions. Our objective was to develop models that use measurements of environmental conditions to predict rotenone persistence in streams. Detailed measurements of ultraviolet radiation, water temperature, dissolved oxygen, total dissolved solids (TDS), conductivity, pH, oxidation&ndash;reduction potential (ORP), substrate composition, amount of organic matter, channel slope, and travel time were made along stream segments located between rotenone treatment stations and cages containing bioassay fish in six streams. The amount of fine organic matter, biofilm, sand, gravel, cobble, rubble, small boulders, slope, pH, TDS, ORP, light reaching the stream, energy dissipated, discharge, and cumulative travel time were each significantly correlated with fish death. By using logistic regression, measurements of environmental conditions were paired with the responses of bioassay fish to develop a model that predicted the persistence of rotenone toxicity in streams. This model was validated with data from two additional stream treatment reaches. Rotenone persistence was predicted by a model that used travel time, rubble, and ORP. When this model predicts a probability of less than 0.95, those who apply rotenone can expect incomplete eradication and should plan on fortifying rotenone concentrations. The significance of travel time has been previously identified and is currently used to predict rotenone persistence. However, rubble substrate, which may be associated with the degradation of rotenone by adsorption and volatilization in turbulent environments, was not previously considered.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Transactions of the American Fisheries Society","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","publisherLocation":"Philadephia, PA","doi":"10.1080/00028487.2012.670186","usgsCitation":"Brown, P., and Zale, A.V., 2012, Rotenone persistence model for montane streams: Transactions of the American Fisheries Society, v. 141, no. 2, p. 560-569, https://doi.org/10.1080/00028487.2012.670186.","productDescription":"10 p.","startPage":"560","endPage":"569","costCenters":[{"id":398,"text":"Montana Cooperative Fishery Research Unit","active":false,"usgs":true}],"links":[{"id":257885,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257872,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/00028487.2012.670186","linkFileType":{"id":5,"text":"html"}}],"volume":"141","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-03-27","publicationStatus":"PW","scienceBaseUri":"505aae9fe4b0c8380cd87135","contributors":{"authors":[{"text":"Brown, Peter J.","contributorId":63661,"corporation":false,"usgs":true,"family":"Brown","given":"Peter J.","affiliations":[],"preferred":false,"id":350382,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zale, Alexander V. 0000-0003-1703-885X zale@usgs.gov","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":3010,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"zale@usgs.gov","middleInitial":"V.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":350381,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70038829,"text":"sir20125109 - 2012 - Magnitude of flood flows for selected annual exceedance probabilities in Rhode Island through 2010","interactions":[],"lastModifiedDate":"2017-11-10T18:52:29","indexId":"sir20125109","displayToPublicDate":"2012-06-25T00:00:00","publicationYear":"2012","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":"2012-5109","title":"Magnitude of flood flows for selected annual exceedance probabilities in Rhode Island through 2010","docAbstract":"<p>Heavy persistent rains from late February through March 2010 caused severe widespread flooding in Rhode Island that set or nearly set record flows and water levels at many long-term streamgages in the State. In response, the U.S. Geological Survey, in partnership with the Federal Emergency Management Agency, conducted a study to update estimates of flood magnitudes at streamgages and regional equations for estimating flood flows at ungaged locations. This report provides information needed for flood plain management, transportation infrastructure design, flood insurance studies, and other purposes that can help minimize future flood damages and risks. The magnitudes of floods were determined from the annual peak flows at 43 streamgages in Rhode Island (20 sites), Connecticut (14 sites), and Massachusetts (9 sites) using the standard Bulletin 17B log-Pearson type III method and a modification of this method called the expected moments algorithm (EMA) for 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probability (AEP) floods. Annual-peak flows were analyzed for the period of record through the 2010 water year; however, records were extended at 23 streamgages using the maintenance of variance extension (MOVE) procedure to best represent the longest period possible for determining the generalized skew and flood magnitudes. Generalized least square regression equations were developed from the flood quantiles computed at 41 streamgages (2 streamgages in Rhode Island with reported flood quantiles were not used in the regional regression because of regulation or redundancy) and their respective basin characteristics to estimate magnitude of floods at ungaged sites. Of 55 basin characteristics evaluated as potential explanatory variables, 3 were statistically significant&mdash;drainage area, stream density, and basin storage. The pseudo-coefficient of determination (pseudo-<i>R2</i>) indicates these three explanatory variables explain 95 to 96 percent of the variance in the flood magnitudes from 20- to 0.2-percent AEPs. Estimates of uncertainty of the at-site and regression flood magnitudes are provided and were combined with their respective estimated flood quantiles to improve estimates of flood flows at streamgages. This region has a long history of urban development, which is considered to have an important effect on flood flows. This study includes basins that have an impervious area ranging from 0.5 to 37 percent. Although imperviousness provided some explanatory power in the regression, it was not statistically significant at the 95-percent confidence level for any of the AEPs examined. Influence of urbanization on flood flows indicates a complex interaction with other characteristics that confounds a statistical explanation of its effects. Standard methods for calculating magnitude of floods for given AEP are based on the assumption of stationarity, that is, the annual peak flows exhibit no significant trend over time. A subset of 16 streamgages with 70 or more years of unregulated systematic record indicates all but 4 streamgages have a statistically significant positive trend at the 95-percent confidence level; three of these are statistically significant at about the 90-percent confidence level or above. If the trend continues linearly in time, the estimated magnitude of floods for any AEP, on average, will increase by 6, 13, and 21 percent in 10, 20, and 30 years' time, respectively. In 2010, new peaks of record were set at 18 of the 21 active streamgages in Rhode Island. The updated flood frequency analysis indicates the peaks at these streamgages ranged from 2- to 0.2-percent AEP. Many streamgages in the State peaked at a 0.5- and 0.2-percent AEP, except for streamgages in the Blackstone River Basin, which peaked from a 4- to 2-percent AEP.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125109","collaboration":"Prepared in cooperation with the Department of Homeland Security Federal Emergency Management Agency","usgsCitation":"Zarriello, P.J., Ahearn, E.A., and Levin, S.B., 2012, Magnitude of flood flows for selected annual exceedance probabilities in Rhode Island through 2010: U.S. Geological Survey Scientific Investigations Report 2012-5109, vii [vii], 48 p.; Glossary: pgs. 49-50; Tables 7, 13, and 15: pgs. 51-76; Appendices: pgs. 77-81; XLS Download of Appendix 3, https://doi.org/10.3133/sir20125109.","productDescription":"vii [vii], 48 p.; Glossary: pgs. 49-50; Tables 7, 13, and 15: pgs. 51-76; Appendices: pgs. 77-81; XLS Download of Appendix 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Science Center","active":true,"usgs":true}],"preferred":false,"id":465034,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Levin, Sara B. 0000-0002-2448-3129 slevin@usgs.gov","orcid":"https://orcid.org/0000-0002-2448-3129","contributorId":1870,"corporation":false,"usgs":true,"family":"Levin","given":"Sara","email":"slevin@usgs.gov","middleInitial":"B.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465036,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70038825,"text":"sim3189 - 2012 - Flood-inundation maps for Peachtree Creek from the Norfolk Southern Railway bridge to the Moores Mill Road NW bridge, Atlanta, Georgia","interactions":[],"lastModifiedDate":"2017-01-11T12:38:52","indexId":"sim3189","displayToPublicDate":"2012-06-25T00:00:00","publicationYear":"2012","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":"3189","title":"Flood-inundation maps for Peachtree Creek from the Norfolk Southern Railway bridge to the Moores Mill Road NW bridge, Atlanta, Georgia","docAbstract":"Digital flood-inundation maps for a 5.5-mile reach of the Peachtree Creek from the Norfolk Southern Railway bridge to the Moores Mill Road NW bridge, were developed by the U.S. Geological Survey (USGS) in cooperation with the City of Atlanta, Georgia. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Peachtree Creek at Atlanta, Georgia (02336300) and the USGS streamgage at Chattahoochee River at Georgia 280, near Atlanta, Georgia (02336490). Current water level (stage) at these USGS streamgages may be obtained at http://waterdata.usgs.gov/ and can be used in conjunction with these maps to estimate near real-time areas of inundation. The National Weather Service (NWS) is incorporating results from this study into the Advanced Hydrologic Prediction Service (AHPS) flood warning system (http:/water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that commonly are collocated at USGS streamgages. The forecasted peak-stage information for the USGS streamgage at Peachtree Creek, which is available through the AHPS Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers HEC&ndash;RAS software for a 6.5-mile reach of Peachtree Creek and was used to compute flood profiles for a 5.5-mile reach of the creek. The model was calibrated using the most current stage-discharge relations at the Peachtree Creek at Atlanta, Georgia, streamgage (02336300), and the Chattahoochee River at Georgia 280, near Atlanta, Georgia, streamgage (02336490) as well as high water marks collected during the 2010 annual peak flow event. The hydraulic model was then used to determine 50 water-surface profiles. The profiles are for 10 flood stages at the Peachtree Creek streamgage at 1-foot intervals referenced to the streamgage datum and ranging from just above bankfull stage (15.0 feet) to approximately the highest recorded water level at the streamgage (24.0 feet). At each stage on Peachtree Creek, five stages at the Chattahoochee River streamgage, from 26.4 feet to 38.4 feet in 3-foot intervals, were used to determine backwater effects. The simulated water-surface profiles were then combined with a geographic information system digital elevation model&mdash;derived from Light Detection and Ranging (LiDAR) data having a 0.3-foot vertical and 16.4-foot horizontal resolution&mdash;to delineate the area flooded for each 1-foot increment of stream stage. The availability of these maps, when combined with real-time information regarding current stage from USGS streamgages and forecasted stream stages from the NWS, provide emergency management personnel and residents with critical information during flood response activities, such as evacuations and road closures as well as for postflood-recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3189","collaboration":"Prepared in cooperation with the City of Atlanta, Georgia","usgsCitation":"Musser, J.W., 2012, Flood-inundation maps for Peachtree Creek from the Norfolk Southern Railway bridge to the Moores Mill Road NW bridge, Atlanta, Georgia: U.S. Geological Survey Scientific Investigations Map 3189, v [vi], 9 p.; PDF and JPG Downloads of Sheets 1-50: 35.00 x 24.00 inches; Downloads Directory, https://doi.org/10.3133/sim3189.","productDescription":"v [vi], 9 p.; PDF and JPG Downloads of Sheets 1-50: 35.00 x 24.00 inches; Downloads Directory","startPage":"i","endPage":"9","numberOfPages":"15","additionalOnlineFiles":"Y","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":257880,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3189.png"},{"id":257877,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3189/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Georgia","city":"Atlanta","otherGeospatial":"Peachtree Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.45,33.800555555555555 ], [ -84.45,33.81777777777778 ], [ -84.36694444444444,33.81777777777778 ], [ -84.36694444444444,33.800555555555555 ], [ -84.45,33.800555555555555 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a1165e4b0c8380cd53f9d","contributors":{"authors":[{"text":"Musser, Jonathan W. 0000-0002-3543-0807 jwmusser@usgs.gov","orcid":"https://orcid.org/0000-0002-3543-0807","contributorId":2266,"corporation":false,"usgs":true,"family":"Musser","given":"Jonathan","email":"jwmusser@usgs.gov","middleInitial":"W.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465024,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70003674,"text":"70003674 - 2012 - Explaining differences between bioaccumulation measurements in laboratory and field data through use of a probabilistic modeling approach","interactions":[],"lastModifiedDate":"2020-01-11T12:00:43","indexId":"70003674","displayToPublicDate":"2012-06-23T19:24:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Explaining differences between bioaccumulation measurements in laboratory and field data through use of a probabilistic modeling approach","docAbstract":"In the regulatory context, bioaccumulation assessment is often hampered by substantial data uncertainty as well as by the poorly understood differences often observed between results from laboratory and field bioaccumulation studies. Bioaccumulation is a complex, multifaceted process, which calls for accurate error analysis. Yet, attempts to quantify and compare propagation of error in bioaccumulation metrics across species and chemicals are rare. Here, we quantitatively assessed the combined influence of physicochemical, physiological, ecological, and environmental parameters known to affect bioaccumulation for 4 species and 2 chemicals, to assess whether uncertainty in these factors can explain the observed differences among laboratory and field studies. The organisms evaluated in simulations including mayfly larvae, deposit-feeding polychaetes, yellow perch, and little owl represented a range of ecological conditions and biotransformation capacity. The chemicals, pyrene and the polychlorinated biphenyl congener PCB-153, represented medium and highly hydrophobic chemicals with different susceptibilities to biotransformation. An existing state of the art probabilistic bioaccumulation model was improved by accounting for bioavailability and absorption efficiency limitations, due to the presence of black carbon in sediment, and was used for probabilistic modeling of variability and propagation of error. Results showed that at lower trophic levels (mayfly and polychaete), variability in bioaccumulation was mainly driven by sediment exposure, sediment composition and chemical partitioning to sediment components, which was in turn dominated by the influence of black carbon. At higher trophic levels (yellow perch and the little owl), food web structure (i.e., diet composition and abundance) and chemical concentration in the diet became more important particularly for the most persistent compound, PCB-153. These results suggest that variation in bioaccumulation assessment is reduced most by improved identification of food sources as well as by accounting for the chemical bioavailability in food components. Improvements in the accuracy of aqueous exposure appear to be less relevant when applied to moderate to highly hydrophobic compounds, because this route contributes only marginally to total uptake. The determination of chemical bioavailability and the increase in understanding and qualifying the role of sediment components (black carbon, labile organic matter, and the like) on chemical absorption efficiencies has been identified as a key next steps.","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/ieam.217","usgsCitation":"Selck, H., Drouillard, K., Eisenreich, K., Koelmans, A.A., Palmqvist, A., Ruus, A., Salvito, D., Schultz, I., Stewart, A.R., Weisbrod, A., van den Brink, N.W., and van den Heuvel-Greve, M., 2012, Explaining differences between bioaccumulation measurements in laboratory and field data through use of a probabilistic modeling approach: Integrated Environmental Assessment and Management, v. 8, no. 1, p. 42-63, https://doi.org/10.1002/ieam.217.","productDescription":"22 p.","startPage":"42","endPage":"63","costCenters":[{"id":148,"text":"Branch of Regional Research-Western Region","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":499906,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research.wur.nl/en/publications/explaining-differences-between-bioaccumulation-measurements-in-la","text":"External Repository"},{"id":257848,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-01-01","publicationStatus":"PW","scienceBaseUri":"505a0e03e4b0c8380cd53280","contributors":{"authors":[{"text":"Selck, Henriette","contributorId":28475,"corporation":false,"usgs":false,"family":"Selck","given":"Henriette","affiliations":[{"id":13410,"text":"Department of Environmental, Social and Spatial Change, Roskilde University, PO Box 260, Universitetsvej 1, DK-4000 Roskilde, Denmark","active":true,"usgs":false}],"preferred":false,"id":348278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drouillard, Ken","contributorId":38001,"corporation":false,"usgs":true,"family":"Drouillard","given":"Ken","affiliations":[],"preferred":false,"id":348280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eisenreich, Karen","contributorId":18221,"corporation":false,"usgs":true,"family":"Eisenreich","given":"Karen","affiliations":[],"preferred":false,"id":348277,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koelmans, Albert A.","contributorId":51594,"corporation":false,"usgs":true,"family":"Koelmans","given":"Albert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":348282,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Palmqvist, Annemette","contributorId":53224,"corporation":false,"usgs":true,"family":"Palmqvist","given":"Annemette","email":"","affiliations":[],"preferred":false,"id":348283,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ruus, Anders","contributorId":36413,"corporation":false,"usgs":true,"family":"Ruus","given":"Anders","email":"","affiliations":[],"preferred":false,"id":348279,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Salvito, Daniel","contributorId":14687,"corporation":false,"usgs":true,"family":"Salvito","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":348276,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schultz, Irv","contributorId":81745,"corporation":false,"usgs":true,"family":"Schultz","given":"Irv","email":"","affiliations":[],"preferred":false,"id":348285,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stewart, A. Robin 0000-0003-2918-546X arstewar@usgs.gov","orcid":"https://orcid.org/0000-0003-2918-546X","contributorId":1482,"corporation":false,"usgs":true,"family":"Stewart","given":"A.","email":"arstewar@usgs.gov","middleInitial":"Robin","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":40553,"text":"WMA - Office of the Chief Operating Officer","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":348275,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Weisbrod, Annie","contributorId":107976,"corporation":false,"usgs":true,"family":"Weisbrod","given":"Annie","email":"","affiliations":[],"preferred":false,"id":348286,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"van den Brink, Nico W.","contributorId":39229,"corporation":false,"usgs":true,"family":"van den Brink","given":"Nico","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":348281,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"van den Heuvel-Greve, Martine","contributorId":80136,"corporation":false,"usgs":true,"family":"van den Heuvel-Greve","given":"Martine","affiliations":[],"preferred":false,"id":348284,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70038287,"text":"70038287 - 2012 - Vulnerability of recently recharged groundwater in principal aquifers of the United States to nitrate contamination","interactions":[],"lastModifiedDate":"2012-06-23T01:01:40","indexId":"70038287","displayToPublicDate":"2012-06-22T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Vulnerability of recently recharged groundwater in principal aquifers of the United States to nitrate contamination","docAbstract":"Recently recharged water (defined here as <60 years old) is generally the most vulnerable part of a groundwater resource to nonpoint-source nitrate contamination. Understanding at the appropriate scale the interactions of natural and anthropogenic controlling factors that influence nitrate occurrence in recently recharged groundwater is critical to support best management and policy decisions that are often made at the aquifer to subaquifer scale. New logistic regression models were developed using data from the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) program and National Water Information System for 17 principal aquifers of the U.S. to identify important source, transport, and attenuation factors that control nonpoint source nitrate concentrations greater than relative background levels in recently recharged groundwater and were used to predict the probability of detecting elevated nitrate in areas beyond the sampling network. Results indicate that dissolved oxygen, crops and irrigated cropland, fertilizer application, seasonally high water table, and soil properties that affect infiltration and denitrification are among the most important factors in predicting elevated nitrate concentrations. Important differences in controlling factors and spatial predictions were identified in the principal aquifer and national-scale models and support the conclusion that similar spatial scales are needed between informed groundwater management and model development.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Science and Technology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Chemical Society","publisherLocation":"Washington, D.C.","doi":"10.1021/es300688b","usgsCitation":"Gurdak, J., and Qi, S.L., 2012, Vulnerability of recently recharged groundwater in principal aquifers of the United States to nitrate contamination: Environmental Science & Technology, v. 46, no. 11, p. 6004-6012, https://doi.org/10.1021/es300688b.","productDescription":"9 p.","startPage":"6004","endPage":"6012","costCenters":[{"id":157,"text":"Cascades Volcano Observatory","active":false,"usgs":true}],"links":[{"id":257829,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es300688b"},{"id":257830,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"46","issue":"11","noUsgsAuthors":false,"publicationDate":"2012-05-24","publicationStatus":"PW","scienceBaseUri":"505bc381e4b08c986b32b202","contributors":{"authors":[{"text":"Gurdak, Jason J.","contributorId":65125,"corporation":false,"usgs":true,"family":"Gurdak","given":"Jason J.","affiliations":[],"preferred":false,"id":463803,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qi, Sharon L. 0000-0001-7278-4498 slqi@usgs.gov","orcid":"https://orcid.org/0000-0001-7278-4498","contributorId":1130,"corporation":false,"usgs":true,"family":"Qi","given":"Sharon","email":"slqi@usgs.gov","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":463802,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70038295,"text":"70038295 - 2012 - Use of vertical temperature gradients for prediction of tidal flat sediment characteristics","interactions":[],"lastModifiedDate":"2013-02-23T22:25:16","indexId":"70038295","displayToPublicDate":"2012-06-22T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Use of vertical temperature gradients for prediction of tidal flat sediment characteristics","docAbstract":"Sediment characteristics largely govern tidal flat morphologic evolution; however, conventional methods of investigating spatial variability in lithology on tidal flats are difficult to employ in these highly dynamic regions. In response, a series of laboratory experiments was designed to investigate the use of temperature diffusion toward sediment characterization. A vertical thermistor array was used to quantify temperature gradients in simulated tidal flat sediments of varying compositions. Thermal conductivity estimates derived from these arrays were similar to measurements from a standard heated needle probe, which substantiates the thermistor methodology. While the thermal diffusivities of dry homogeneous sediments were similar, diffusivities for saturated homogeneous sediments ranged approximately one order of magnitude. The thermal diffusivity of saturated sand was five times the thermal diffusivity of saturated kaolin and more than eight times the thermal diffusivity of saturated bentonite. This suggests that vertical temperature gradients can be used for distinguishing homogeneous saturated sands from homogeneous saturated clays and perhaps even between homogeneous saturated clay types. However, experiments with more realistic tidal flat mixtures were less discriminating. Relationships between thermal diffusivity and percent fines for saturated mixtures varied depending upon clay composition, indicating that clay hydration and/or water content controls thermal gradients. Furthermore, existing models for the bulk conductivity of sediment mixtures were improved only through the use of calibrated estimates of homogeneous end-member conductivity and water content values. Our findings suggest that remotely sensed observations of water content and thermal diffusivity could only be used to qualitatively estimate tidal flat sediment characteristics.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research C: Oceans","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, DC","doi":"10.1029/2011JC007566","usgsCitation":"Miselis, J.L., Holland, K.T., Reed, A.H., and Abelev, A., 2012, Use of vertical temperature gradients for prediction of tidal flat sediment characteristics: Journal of Geophysical Research C: Oceans, v. 117, no. C3, p. C03012-C03023, https://doi.org/10.1029/2011JC007566.","productDescription":"10 p.","startPage":"C03012","endPage":"C03023","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":474444,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011jc007566","text":"Publisher Index Page"},{"id":257826,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2011JC007566"},{"id":257831,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"117","issue":"C3","noUsgsAuthors":false,"publicationDate":"2012-03-09","publicationStatus":"PW","scienceBaseUri":"505bbface4b08c986b329cdb","contributors":{"authors":[{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":463809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holland, K. Todd","contributorId":68748,"corporation":false,"usgs":true,"family":"Holland","given":"K.","email":"","middleInitial":"Todd","affiliations":[],"preferred":false,"id":463812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Allen H.","contributorId":60898,"corporation":false,"usgs":true,"family":"Reed","given":"Allen","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":463810,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abelev, Andrei","contributorId":65709,"corporation":false,"usgs":true,"family":"Abelev","given":"Andrei","email":"","affiliations":[],"preferred":false,"id":463811,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70147686,"text":"70147686 - 2012 - Progress report for project modeling Arctic barrier island-lagoon system response to projected Arctic warming","interactions":[],"lastModifiedDate":"2018-06-18T11:10:03","indexId":"70147686","displayToPublicDate":"2012-06-22T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Progress report for project modeling Arctic barrier island-lagoon system response to projected Arctic warming","docAbstract":"<p>Changes in Arctic coastal ecosystems in response to global warming may be some of the most severe on the planet. A better understanding and analysis of the rates at which these changes are expected to occur over the coming decades is crucial in order to delineate high-priority areas that are likely to be affected by climate changes. In this study we investigate the likelihood of changes to habitat-supporting barrier island – lagoon systems in response to projected changes in atmospheric and oceanographic forcing associated with Arctic warming. To better understand the relative importance of processes responsible for the current and future coastal landscape, key parameters related to increasing arctic temperatures are investigated and used to establish boundary conditions for models that simulate barrier island migration and inundation of deltaic deposits and low-lying tundra. The modeling effort investigates the dominance and relative importance of physical processes shaping the modern Arctic coastline as well as decadal responses due to projected conditions out to the year 2100.</p>","language":"English","publisher":"Arctic Landscape Conservation Cooperative (ALCC)","usgsCitation":"Erikson, L., Gibbs, A.E., Richmond, B.M., Storlazzi, C.D., and Jones, B.M., 2012, Progress report for project modeling Arctic barrier island-lagoon system response to projected Arctic warming, 23 p.","productDescription":"23 p.","ipdsId":"IP-038998","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":332300,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":355097,"rank":2,"type":{"id":22,"text":"Related Work"},"url":"https://www.sciencebase.gov/catalog/item/5a0ae47be4b09af898cb5d2f","linkHelpText":"Project Website"},{"id":355098,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://arcticlcc.org/assets/products/ARCT2011-02/progress_reports/ALCC-Progress-Report-AreyLagoonfinal.pdf"}],"country":"United States","state":"Alaska","otherGeospatial":"North Slope of Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -144.21615600585938,\n              70.03512833760948\n            ],\n            [\n              -144.16259765624997,\n              70.09552886456429\n            ],\n            [\n              -143.91815185546875,\n              70.11842572544462\n            ],\n            [\n              -143.778076171875,\n              70.14083079717587\n            ],\n            [\n              -143.57070922851562,\n              70.15761869835048\n          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H.","email":"lerikson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":546232,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":546229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richmond, Bruce M. 0000-0002-0056-5832 brichmond@usgs.gov","orcid":"https://orcid.org/0000-0002-0056-5832","contributorId":2459,"corporation":false,"usgs":true,"family":"Richmond","given":"Bruce","email":"brichmond@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":546230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":546231,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":546233,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70038817,"text":"sim3205 - 2012 - Flood-inundation maps for the St. Marys River at Fort Wayne, Indiana","interactions":[],"lastModifiedDate":"2014-02-07T13:40:51","indexId":"sim3205","displayToPublicDate":"2012-06-22T00:00:00","publicationYear":"2012","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":"3205","title":"Flood-inundation maps for the St. Marys River at Fort Wayne, Indiana","docAbstract":"Digital flood-inundation maps for a 9-mile reach of the St. Marys River that extends from South Anthony Boulevard to Main Street at Fort Wayne, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the City of Fort Wayne. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site, depict estimates of the areal extent of flooding corresponding to selected water levels (stages) at the USGS streamgage 04182000 St. Marys River near Fort Wayne, Ind. Current conditions at the USGS streamgages in Indiana may be obtained from the National Water Information System: Web Interface. In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system. The NWS forecasts flood hydrographs at many places that are often collocated at USGS streamgages. That forecasted peak-stage information, also available on the Internet, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, water-surface profiles were simulated for the stream reach by means of a hydraulic one-dimensional step-backwater model. The model was calibrated using the most current stage-discharge relation at the USGS streamgage 04182000 St. Marys River near Fort Wayne, Ind. The hydraulic model was then used to simulate 11 water-surface profiles for flood stages at 1-ft intervals referenced to the streamgage datum and ranging from bankfull to approximately the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. A flood inundation map was generated for each water-surface profile stage (11 maps in all) so that for any given flood stage users will be able to view the estimated area of inundation. The availability of these maps along with current stage from USGS streamgages and forecasted stream stages from the NWS provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post flood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3205","collaboration":"Prepared in Cooperation with the City of Fort Wayne, Indiana","usgsCitation":"Menke, C.D., Kim, M.H., and Fowler, K.K., 2012, Flood-inundation maps for the St. Marys River at Fort Wayne, Indiana: U.S. Geological Survey Scientific Investigations Map 3205, iv, 7 p.; Data Files; Dataset Directory, README, Vector Metadata, Raster Metadata; 11 Sheets; Sheet 1: 17.03 inches x 22.00 inches, Sheet 2: 17.03 inches x 22.00 inches, Sheet 3: 17.03 inches x 22.00 inches, Sheet 4: 17.03 inches x 22.00 inches, Sheet 5: 17.00 inches x 22.00 inches, Sheet 6: 17.03 inches x 22.00 inches, Sheet 7: 17.03 inches x 22.00 inches, Sheet 8: 17.03 inches x 22.00 inches, Sheet 9: 17.03 inches x 22.00 inches, Sheet 10: 17.03 inches x 22.00 inches, Sheet 10: 17.03 inches x 22.00 inches; 11 low resolution sheets; Sheet 1: 17.03 inches x 22.00 inches, Sheet 2: 17.03 inches x 22.00 inches, Sheet 3: 17.03 inches x 22.00 inches, Sheet 4: 17.03 inches x 22.00 inches, Sheet 5: 17.00 inches x 22.00 inches, Sheet 6: 17.03 inches x 22.00 inches, Sheet 7: 17.03 inches x 22.00 inches, Sheet 8: 17.03 inches x 22.00 inches, Sheet 9: 17.03 inches x 22.00 inches, Sheet 10: 17.03 inches x 22.00 inches, Sheet 11: 17.03 inches x 22.00 inches, https://doi.org/10.3133/sim3205.","productDescription":"iv, 7 p.; Data Files; Dataset Directory, README, Vector Metadata, Raster Metadata; 11 Sheets; Sheet 1: 17.03 inches x 22.00 inches, Sheet 2: 17.03 inches x 22.00 inches, Sheet 3: 17.03 inches x 22.00 inches, Sheet 4: 17.03 inches x 22.00 inches, Sheet 5: 17.00 inches x 22.00 inches, Sheet 6: 17.03 inches x 22.00 inches, Sheet 7: 17.03 inches x 22.00 inches, Sheet 8: 17.03 inches x 22.00 inches, Sheet 9: 17.03 inches x 22.00 inches, Sheet 10: 17.03 inches x 22.00 inches, Sheet 10: 17.03 inches x 22.00 inches; 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