Predation of endangered Lost River suckers (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) during larval egress to Upper Klamath Lake from the Williamson River is poorly understood but may be an important factor limiting recruitment into adult spawning populations. Native and non-native piscivores are abundant in nursery wetland habitat, but larval predation has not been directly studied for all species. Larvae lack hard body structures and digest rapidly in predator digestive systems. Therefore, traditional visual methods for diet analysis may fail to identify the extent of predation on larvae. The goals of this study were to (1) use quantitative polymerase chain reaction (qPCR) and single nucleotide polymorphism (SNP) assays developed for Lost River and shortnose suckers to assay predator stomach contents for sucker DNA, and (2) to assess our ability to use this technique to study predation. Predators were captured opportunistically during larval sucker egress. Concurrent feeding trials indicate that most predators—yellow perch (Perca flaverscens), fathead minnow (Pimephales promelas), blue chub (Gila coerulea), Klamath tui chub (Siphatales bicolor bicolor), Klamath Lake sculpin (Cottus princeps), slender sculpin (Cottus tenuis)—preyed on sucker larvae in the laboratory. However, sucker DNA was not detected in fathead minnow stomachs. Of the stomachs screened from fish captured in the Williamson River Delta, 15.6 percent of yellow perch contained sucker DNA. This study has demonstrated that the application of qPCR and SNP assays is effective for studying predation on larval suckers. We suggest that techniques associated with dissection or detection of sucker DNA from fathead minnow stomachs need improvement.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161094","usgsCitation":"Hereford, D.M., Ostberg, C.O., and Burdick, S.M., 2016, Predation on larval suckers in the Williamson River Delta revealed by molecular genetic assays—A pilot study: U.S. Geological Survey Open-File Report 2016-1094, 16 p., https://dx.doi.org/10.3133/ofr20161094.","productDescription":"iv, 16 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074834","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":323556,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1094/coverthb.jpg"},{"id":323557,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1094/ofr20161094.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1094"}],"country":"United States","state":"Oregon","otherGeospatial":"Williamson River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.95922851562501,\n 42.484504292781125\n ],\n [\n -121.95922851562501,\n 42.5171568649003\n ],\n [\n -121.91493988037108,\n 42.5171568649003\n ],\n [\n -121.91493988037108,\n 42.484504292781125\n ],\n [\n -121.95922851562501,\n 42.484504292781125\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/
In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath bathymetry data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow subsurface geology.
The Monterey Canyon and Vicinity map area lies within Monterey Bay in central California. Monterey Bay is one of the largest embayments along the west coast of the United States, spanning 36 km from its northern to southern tips (in Santa Cruz and Monterey, respectively) and 20 km along its central axis. Not only does it contain one of the broadest sections of continental shelf along California’s coast, it also contains Monterey Canyon, one of the largest and deepest submarine canyons in the world. Note that the California’s State Waters limit extends farther offshore between Santa Cruz and Monterey so that it encompasses all of Monterey Bay.
The coastal area within the map area is lightly populated. The community of Moss Landing (population, 204) hosts the largest commercial fishing fleet in Monterey Bay in its harbor. The map area also includes parts of the cities of Marina (population, about 20,000) and Castroville (population, about 6,500). Fertile lowlands of the Salinas River and Pajaro River valleys largely occupy the inland part of the map area, and land use is primarily agricultural.
The offshore part of the map area lies completely within the Monterey Bay National Marine Sanctuary. The map area also includes Portuguese Ledge and Soquel Canyon State Marine Conservation Areas. Designated conservation and (or) recreation areas in the onshore part of the map area include Salinas River National Wildlife Refuge, Elkhorn Slough State Marine Conservation Area, Elkhorn Slough State Marine Reserve, Moss Landing Wildlife Area, Zmudowski and Salinas River State Beaches, and Marina Dunes Preserve.
Monterey Bay, a geologically complex area within a tectonically active continental margin, lies between two major, converging strike-slip faults. The northwest-striking San Andreas Fault lies about 34 km east of Monterey Bay; this section of the fault ruptured in both the 1989 M6.9 Loma Prieta earthquake and the 1906 M7.8 great California earthquake. The northwest-striking San Gregorio Fault crosses Monterey Canyon west of Monterey Bay. Between these two regional faults, strain is accommodated by the northwest-striking Monterey Bay Fault Zone. Deformation associated with these major regional faults and related structures has resulted in uplift of the Santa Cruz Mountains, as well as the granitic highlands of the Monterey peninsula.
Monterey Canyon begins in the nearshore area directly offshore of Moss Landing and Elkhorn Slough, and it can be traced for more than 400 km seaward, out to water depths of more than 4,000 m. Within the map area, the canyon can be traced for about 42 km to a water depth of about 1,520 m. The head of the canyon consists of three branches that begin about 150 m offshore of Moss Landing Harbor. At 500 m offshore, the canyon is already 70 m deep and 750 m wide. Large sand waves, which have heights from 1 to 3 m and wavelengths of about 50 m, are present along the channel axis in the upper 4 km of the canyon.
Soquel Canyon is the most prominent tributary of Monterey Canyon within the map area. The head of Soquel Canyon is isolated from coastal watersheds and, thus, is considered inactive as a conduit for coarse sediment transport.
North and south of Monterey and Soquel Canyons, the relatively flat continental shelf contains only a few rocky outcrop exposures. Bedrock is covered largely by sediment derived from the Salinas and Pajaro Rivers. North of Monterey Canyon, the broad and flat continental shelf dips gently seaward, to water depths of about 95 m. To the south, the shelf also dips slightly, to water depths of as much as 150 m along the canyon edge.
In the map area, Monterey Canyon splits the Santa Cruz littoral cell (north of the canyon) and the southern Monterey littoral cell (south of the canyon). It is estimated that about 400,000 m3/yr of sand on average enters Monterey Canyon from both of these littoral cells.
In the Santa Cruz littoral cell, sand generally travels east and south. Sand is supplied through sea cliff erosion, as well as from the San Lorenzo River, the Pajaro River, and several other smaller coastal watersheds. About 152,911 m3/yr of sand is dredged from the entrance channel of the Santa Cruz Small Craft Harbor north of the map area and then placed on beaches to the east (downdrift) of it. This sand feeds the beaches in the southeastern reach of the Santa Cruz littoral cell and (or) is eventually trapped and lost by Monterey Canyon.
The southern Monterey Bay littoral cell in the map area consists of two subcells. From the head of Monterey Canyon to the Salinas River, littoral drift is dominantly to the north; sand entering the ocean from the Salinas River either is deposited offshore or travels north in the littoral zone, nourishing the beaches until it is transported down Monterey Canyon. From south of the Salinas River to the southern extent of the map area, coastal sediment is moved mainly to the south; dune erosion is the only significant source of sand in this subcell.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161072","usgsCitation":"Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., Endris, C.A., and Krigsman, L.M. (P. Dartnell and S.A. Cochran, eds.), 2016, California State Waters Map Series — Monterey Canyon and Vicinity, California: U.S. Geological Survey Open-File Report 2016–1072, 48 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20161072.","productDescription":"Pamphlet: iv, 48 p.; 10 Sheets: 72.75 x 36.00 inches or smaller; Data Catalog; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059488","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438614,"rank":22,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7XD0ZQ4","text":"USGS data release","linkHelpText":"California State Waters Map Series Data Catalog--Monterey Canyon and Vicinity, California"},{"id":321805,"rank":20,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20161025","text":"Open-File Report 2016–1025","linkHelpText":"California State Waters Map Series—Offshore of Aptos, California, by Guy R. 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Cochrane and others."},{"id":321801,"rank":16,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/sim/3306/","text":"Scientific Investigations Map 3306","linkHelpText":"California State Waters Map Series—Offshore of San Gregorio, California, by Guy R. Cochrane and others."},{"id":321798,"rank":13,"type":{"id":28,"text":"Dataset"},"url":"https://dx.doi.org/10.5066/F7XD0ZQ4","text":"Data Catalog","linkFileType":{"id":5,"text":"html"},"linkHelpText":"The GIS data layers for this map are accessible from “Data Catalog—Monterey Canyon and Vicinity, California” which is part of California State Waters Map Series Data Catalog. Each GIS data file is listed with a brief description, a small image, and links to the metadata files and the downloadable data files."},{"id":321796,"rank":11,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_sheet9.pdf","text":"Sheet 9","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1072 Sheet 9 PDF","linkHelpText":"Local (Monterey Canyon and Vicinity Map Area) and Regional (Offshore from Pigeon Point to Southern Monterey Bay) Shallow-Subsurface Geology and Structure, California By Katherine L. Maier, Samuel Y. Johnson, Stephen R. Hartwell, Janet T. Watt, and Ray W. Sliter"},{"id":321794,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_sheet7.pdf","text":"Sheet 7","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1072 Sheet 7 PDF","linkHelpText":"Potential Marine Benthic Habitats, Monterey Canyon and Vicinity Map Area, California By Bryan E. Dieter, Charles A. Endris, H. 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Cochrane"},{"id":321791,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_sheet4.pdf","text":"Sheet 4","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1072 Sheet 4 PDF","linkHelpText":"Data Integration and Visualization, Monterey Canyon and Vicinity Map Area, California By Peter Dartnell"},{"id":321790,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_sheet3.pdf","text":"Sheet 3","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1072 Sheet 3 PDF","linkHelpText":"Acoustic Backscatter, Monterey Canyon and Vicinity Map Area, California By Peter Dartnell, Andrew C. Ritchie, David P. Finlayson, and Rikk G. Kvitek"},{"id":321789,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1072 Sheet 2 PDF","linkHelpText":"Shaded-Relief Bathymetry, Monterey Canyon and Vicinity Map Area, California By Peter Dartnell, Andrew C. Ritchie, David P. Finlayson, and Rikk G. Kvitek"},{"id":321788,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1072 Sheet 1 PDF","linkHelpText":"Colored Shaded-Relief Bathymetry, Monterey Canyon and Vicinity Map Area, California By Peter Dartnell, Andrew C. Ritchie, David P. Finlayson, and Rikk G. Kvitek"},{"id":399103,"rank":21,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_104300.htm"},{"id":321799,"rank":14,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_metadata.html"},{"id":321797,"rank":12,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_sheet10.pdf","text":"Sheet 10","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1072 Sheet 10 PDF","linkHelpText":"Offshore and Onshore Geology and Geomorphology, Monterey Canyon and Vicinity Map Area, California By Katherine L. Maier, Stephen R. Hartwell, Samuel Y. Johnson, Clifton W. Davenport, and H. Gary Greene"},{"id":321793,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_sheet6.pdf","text":"Sheet 6","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1072 Sheet 6 PDF","linkHelpText":"Ground-Truth Studies, Monterey Canyon and Vicinity Map Area, California By Mercedes D. Erdey, Guy R. Cochrane, Lisa M. Krigsman, and Nadine E. Golden"},{"id":321787,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1072 Pamphlet"},{"id":321795,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_sheet8.pdf","text":"Sheet 8","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1072 Sheet 8 PDF","linkHelpText":"Seismic-Reflection Profiles, Monterey Canyon and Vicinity Map Area, California by Katherine L. Maier, Samuel Y. Johnson, Stephen R. Hartwell, and Ray W. Sliter"},{"id":321800,"rank":15,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/781/","text":"Data Series 781","linkHelpText":"California State Waters Map Series Data Catalog"},{"id":321786,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1072/coverthb.jpg"}],"scale":"24000","country":"United States","state":"California","otherGeospatial":"Monterey Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.0628,\n 36.6850\n ],\n [\n -122.0628,\n 36.8469\n ],\n [\n -121.7358,\n 36.8469\n ],\n [\n -121.7358,\n 36.6850\n ],\n [\n -122.0628,\n 36.6850\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2016-06-10","noUsgsAuthors":false,"publicationDate":"2016-06-10","publicationStatus":"PW","scienceBaseUri":"575bd6a0e4b04f417c275edb","contributors":{"editors":[{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":630600,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cochran, Susan A. 0000-0002-2442-8787 scochran@usgs.gov","orcid":"https://orcid.org/0000-0002-2442-8787","contributorId":2062,"corporation":false,"usgs":true,"family":"Cochran","given":"Susan A.","email":"scochran@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science 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Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":630573,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dieter, Bryan E.","contributorId":21859,"corporation":false,"usgs":true,"family":"Dieter","given":"Bryan E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":630574,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Golden, Nadine E. 0000-0001-6007-6486 ngolden@usgs.gov","orcid":"https://orcid.org/0000-0001-6007-6486","contributorId":138974,"corporation":false,"usgs":true,"family":"Golden","given":"Nadine","email":"ngolden@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":630575,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Samuel Y. 0000-0001-7972-9977 sjohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-7972-9977","contributorId":2607,"corporation":false,"usgs":true,"family":"Johnson","given":"Samuel","email":"sjohnson@usgs.gov","middleInitial":"Y.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":630576,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hartwell, Stephen R. 0000-0002-3522-7526 shartwell@usgs.gov","orcid":"https://orcid.org/0000-0002-3522-7526","contributorId":4995,"corporation":false,"usgs":true,"family":"Hartwell","given":"Stephen","email":"shartwell@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":630577,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cochrane, Guy R. 0000-0002-8094-4583 gcochrane@usgs.gov","orcid":"https://orcid.org/0000-0002-8094-4583","contributorId":2870,"corporation":false,"usgs":true,"family":"Cochrane","given":"Guy","email":"gcochrane@usgs.gov","middleInitial":"R.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":630578,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ritchie, Andrew C.","contributorId":139060,"corporation":false,"usgs":false,"family":"Ritchie","given":"Andrew C.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":630579,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Finlayson, David P. dfinlayson@usgs.gov","contributorId":1381,"corporation":false,"usgs":true,"family":"Finlayson","given":"David","email":"dfinlayson@usgs.gov","middleInitial":"P.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":630580,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kvitek, Rikk G.","contributorId":44099,"corporation":false,"usgs":true,"family":"Kvitek","given":"Rikk","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":630581,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sliter, Ray W. 0000-0003-0337-3454 rsliter@usgs.gov","orcid":"https://orcid.org/0000-0003-0337-3454","contributorId":1992,"corporation":false,"usgs":true,"family":"Sliter","given":"Ray","email":"rsliter@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":630582,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Greene, H. Gary","contributorId":38958,"corporation":false,"usgs":true,"family":"Greene","given":"H. Gary","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":630583,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Davenport, Clifton W.","contributorId":140374,"corporation":false,"usgs":false,"family":"Davenport","given":"Clifton W.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":630584,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Endris, Charles A.","contributorId":87875,"corporation":false,"usgs":true,"family":"Endris","given":"Charles","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":630585,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Krigsman, Lisa M.","contributorId":43642,"corporation":false,"usgs":true,"family":"Krigsman","given":"Lisa M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":630586,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70173766,"text":"ofr20161095 - 2016 - Jaguar surveying and monitoring in the United States","interactions":[],"lastModifiedDate":"2016-11-08T16:41:35","indexId":"ofr20161095","displayToPublicDate":"2016-06-10T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1095","title":"Jaguar surveying and monitoring in the United States","docAbstract":"
Because of the jaguar’s (Panthera onca) endangered status under the Endangered Species Act (ESA) of 1973 throughout its range (from Arizona in the north to Argentina in the south), jaguar individuals and populations are monitored to varying degrees throughout their range. Knowledge gained from monitoring jaguars is helpful for wildlife managers who are responsible for conserving this species. The University of Arizona (UA) has conducted a multiyear surveying and monitoring effort for jaguars and ocelots in southern Arizona and New Mexico. The purpose of this work was to establish an effective surveying and monitoring system for jaguars along the United States-Mexico border. Surveying and monitoring in this study focused on the United States side of the border, but the methods could also be used in Mexico. The intent was to develop and implement a surveying and monitoring system that would provide the greatest probability of recording jaguar presence in, and passage through, the border area.
\nThis project established and implemented a noninvasive system for detecting and monitoring jaguars. The study area incorporates most of the mountainous areas north of the United States-Mexico international border and south of Interstate 10, from the Baboquivari Mountains in Arizona to the Animas Mountains in New Mexico. We used two primary methods to detect exact jaguar locations: paired motion-sensor trail cameras, and genetic testing of large carnivore scat collected in the field. We emphasize that this project used entirely noninvasive methods and no jaguars were captured, radiocollared, baited, or harassed in any way. Scat sample collection occurred during the entire field part of the study, but was intensified with the use of a trained scat detection dog following the first jaguar photo detection event (photo detection event was October 2012, scat detection dog began working January 2013). We also collected weather, vegetation, and geographic information system (GIS) data to analyze in conjunction with photo and video data. The results of this study are intended to aid and inform future management and conservation practices for jaguars and ocelots in this region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161095","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Culver, Melanie, 2016, Jaguar surveying and monitoring in the United States (ver. 1.1, November 2016): U.S. Geological Survey Open-File Report 2016–1095, 228 p., https://dx.doi.org/10.3133/ofr20161095.","productDescription":"228 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-075400","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323458,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1095/ofr20161095.pdf","text":"Report","size":"18.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1095"},{"id":323457,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1095/coverthb.jpg"},{"id":330879,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2016/1095/versionHist.txt","size":"708 bytes","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2016-1095 Version History"}],"country":"United States","state":"Arizona, California, New Mexico, Texas","otherGeospatial":"United States - Mexico Border","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.3779296875,\n 33.50475906922606\n ],\n [\n -104.9853515625,\n 32.32427558887655\n ],\n [\n -97.3388671875,\n 27.644606381943326\n ],\n [\n -97.3828125,\n 24.806681353851964\n ],\n [\n -102.26074218749999,\n 27.955591004642553\n ],\n [\n -106.74316406249999,\n 30.29701788337205\n ],\n [\n -117.158203125,\n 31.203404950917395\n ],\n [\n -117.3779296875,\n 33.50475906922606\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Leader, Arizona Cooperative Fish and Wildlife Research Unit
U.S. Geological Survey
325 Biosciences East
Tucson, Arizona 85721
http://www.coopunits.org/Arizona/
The U.S. Geological Survey conducted a bathymetric survey in Little Holland Tract, a flooded agricultural tract, in the northern Sacramento-San Joaquin Delta (the “Delta”) during the summer of 2015. The new bathymetric data were combined with existing data to generate a digital elevation model (DEM) at 1-meter resolution. Little Holland Tract (LHT) was historically diked off for agricultural uses and has been tidally inundated since an accidental levee breach in 1983. Shallow tidal regions such as LHT have the potential to improve habitat quality in the Delta. The DEM of LHT was developed to support ongoing studies of habitat quality in the area and to provide a baseline for evaluating future geomorphic change. The new data comprise 138,407 linear meters of real-time-kinematic (RTK) Global Positioning System (GPS) elevation data, including both bathymetric data collected from personal watercraft and topographic elevations collected on foot at low tide. A benchmark (LHT15_b1) was established for geodetic control of the survey. Data quality was evaluated both by comparing results among surveying platforms, which showed systematic offsets of 1.6 centimeters (cm) or less, and by error propagation, which yielded a mean vertical uncertainty of 6.7 cm. Based on the DEM and time-series measurements of water depth, the mean tidal prism of LHT was determined to be 2,826,000 cubic meters. The bathymetric data and DEM are available at http://dx.doi.org/10.5066/F7RX9954.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161093","usgsCitation":"Snyder, A.G., Lacy, J.R., Stevens, A.W., and Carlson, E.M., 2016, Bathymetric survey and digital elevation model of Little Holland Tract, Sacramento-San Joaquin Delta, California: U.S. Geological Survey Open-File Report 2016‒1093, 14 p., https://dx.doi.org/10.3133/ofr20161093. ","productDescription":"iv, 14 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071752","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":323417,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1093/ofr20161093.pdf","text":"Report","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1093"},{"id":323416,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1093/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.69349670410158,\n 38.27632714009116\n ],\n [\n -121.69349670410158,\n 38.34556060133404\n ],\n [\n -121.64148330688475,\n 38.34556060133404\n ],\n [\n -121.64148330688475,\n 38.27632714009116\n ],\n [\n -121.69349670410158,\n 38.27632714009116\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
The purpose of this project was to develop a technique to use environmental DNA (eDNA) to distinguish between redds made by Chinook salmon (Oncorhynchus tshawytscha) and redds made by Coho salmon (O. kisutch) and to distinguish utilized redds from test/abandoned redds or scours that have the appearance of redds. The project had two phases:
Phase 1. Develop, test, and optimize a molecular assay for detecting and identifying Coho salmon DNA and differentiating it from Chinook salmon DNA.
Phase 2. Demonstrate the efficacy of the technique.
The Sandy River is a large tributary of the Columbia River. The Sandy River meets the Columbia River approximately 23 km upstream of Portland, Oregon. The Sandy River Basin provides overlapping spawning habitat for both Chinook and Coho salmon.
Samples provided by Portland Water Bureau for analysis were collected from the Bull Run River, Sixes Creek, Still Creek, Arrah Wanna Side Channel, and Side Channel 18.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161091","collaboration":"Prepared in cooperation with Portland Water Bureau","usgsCitation":"Pilliod, D.S., and Laramie, M.B., 2016, Salmon redd identification using environmental DNA (eDNA): U.S. Geological Survey Open-File Report 2016–1091, 25 p., https://dx.doi.org/10.3133/ofr20161091.","productDescription":"iv, 25 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064586","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":323430,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1091/coverthb3.jpg"},{"id":323387,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1091/ofr20161091.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1091"}],"country":"United States","state":"Oregon","otherGeospatial":"Sandy River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.28744506835938,\n 45.298075138707965\n ],\n [\n -122.28744506835938,\n 45.481317798141255\n ],\n [\n -121.84112548828125,\n 45.481317798141255\n ],\n [\n -121.84112548828125,\n 45.298075138707965\n ],\n [\n -122.28744506835938,\n 45.298075138707965\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
The Delaware River Basin Streamflow Estimator Tool (DRB-SET) is a tool for the simulation of streamflow at a daily time step for an ungaged stream location in the Delaware River Basin. DRB-SET was developed by the U.S. Geological Survey (USGS) and funded through WaterSMART as part of the National Water Census, a USGS research program on national water availability and use that develops new water accounting tools and assesses water availability at the regional and national scales. DRB-SET relates probability exceedances at a gaged location to those at an ungaged stream location. Once the ungaged stream location has been identified by the user, an appropriate streamgage is automatically selected in DRB-SET using streamflow correlation (map correlation method). Alternately, the user can manually select a different streamgage or use the closest streamgage. A report file is generated documenting the reference streamgage and ungaged stream location information, basin characteristics, any warnings, baseline (minimally altered) and altered (affected by regulation, diversion, mining, or other anthropogenic activities) daily mean streamflow, and the mean and median streamflow. The estimated daily flows for the ungaged stream location can be easily exported as a text file that can be used as input into a statistical software package to determine additional streamflow statistics, such as flow duration exceedance or streamflow frequency statistics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151192","usgsCitation":"Stuckey, M.H., and Ulrich, J.E., 2016, User’s Guide for the Delaware River Basin Streamflow Estimator Tool (DRB-SET): U.S. Geological Survey Open-File Report 2015–1192, 6 p., https://dx.doi.org/10.3133/ofr20151192.","productDescription":"iv, 6 p.","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069187","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":322015,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20155157","text":"Estimation of Daily Mean Streamflow for Ungaged Stream Locations in the Delaware River Basin, Water Years 1960–2010","description":"OFR 2015-1192"},{"id":322012,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1192/coverthb.jpg"},{"id":322016,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://www.usgs.gov/software/delaware-river-basin-streamflow-estimator-tool-drb-set","text":"Delaware River Basin Streamflow Estimator Tool (DRB-SET)","linkFileType":{"id":5,"text":"html"},"description":"OFR 2015-1192"},{"id":322013,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1192/ofr20151192.pdf","text":"Report","size":"1.76 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1192"}],"contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
http://pa.water.usgs.gov/
The U.S. Geological Survey has completed an assessment of the potential geologic carbon dioxide storage resources in the onshore areas of the United States. To provide geological context and input data sources for the resources numbers, framework documents are being prepared for all areas that were investigated as part of the national assessment. This report, chapter M, is the geologic framework document for the Uinta and Piceance, San Juan, Paradox, Raton, Eastern Great, and Black Mesa Basins, and subbasins therein of Arizona, Colorado, Idaho, Nevada, New Mexico, and Utah. In addition to a summary of the geology and petroleum resources of studied basins, the individual storage assessment units (SAUs) within the basins are described and explanations for their selection are presented. Although appendixes in the national assessment publications include the input values used to calculate the available storage resource, this framework document provides only the context and source of the input values selected by the assessment geologists. Spatial-data files of the boundaries for the SAUs, and the well-penetration density of known well bores that penetrate the SAU seal, are available for download with the release of this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121024M","usgsCitation":"Merrill, M.D., Drake, R.M., II, Buursink, M.L., Craddock, W.H., East, J.A., Slucher, E.R., Warwick, P.D., Brennan, S.T., Blondes, M.S., Freeman, P.A., Cahan, S.M., DeVera, C.A., and Lohr, C.D., 2016, Geologic framework for the national assessment of carbon dioxide storage resources—Southern Rocky Mountain Basins, chap. M of Warwick, P.D., and Corum, M.D., eds., Geologic framework for the national assessment of carbon dioxide storage resources: U.S. Geological Survey Open-File Report 2012–1024–M, 59 p., at https://dx.doi.org/10.3133/ofr20121024M.","productDescription":"Report: viii, 60 p.; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-056759","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":322007,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20121024","text":"Geologic Framework for the National Assessment of Carbon Dioxide Storage Resources","linkHelpText":"- (Main Report)"},{"id":322003,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2012/1024/m/coverthb.jpg"},{"id":322005,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2012/1024/m/downloads/ofr2012-1024m_storage-assessment-units.zip","text":"Storage Assessment Units","size":"478 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2012-1024m"},{"id":322004,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1024/m/ofr20121024m.pdf","text":"Report","size":"79.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2012-1024m"},{"id":322006,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2012/1024/m/downloads/ofr2012-1024m_well-density.zip","text":"Well Density","size":"753 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2012-1024m"}],"country":"United States","state":"Arizona, Colorado, Idaho, Nevada, New Mexico, Utah","otherGeospatial":"Uinta Basin, Piceance Basin, San Juan Basin, Paradox Basin, Raton Basin, Eastern Great Basin, Black Mesa Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.59765625,\n 33.358061612778876\n ],\n [\n -117.59765625,\n 44.96479793033104\n ],\n [\n -103.18359375,\n 44.96479793033104\n ],\n [\n -103.18359375,\n 33.358061612778876\n ],\n [\n -117.59765625,\n 33.358061612778876\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Energy Resources Program
12201 Sunrise Valley Drive
913 National Center
Reston, VA 20192
Email: gd-energyprogram@usgs.gov
http://energy.usgs.gov/GeneralInfo/
AbouttheEnergyProgram.aspx
The Tree Cover Mapping (TCM) tool was developed by scientists at the U.S. Geological Survey Earth Resources Observation and Science Center to allow a user to quickly map tree cover density over large areas using visual interpretation of high resolution imagery within a geographic information system interface. The TCM tool uses a systematic sample grid to produce maps of tree cover. The TCM tool allows the user to define sampling parameters to estimate tree cover within each sample unit. This mapping method generated the first on-farm tree cover maps of vast regions of Niger and Burkina Faso. The approach contributes to implementing integrated landscape management to scale up re-greening and restore degraded land in the drylands of Africa. The TCM tool is easy to operate, practical, and can be adapted to many other applications such as crop mapping, settlements mapping, or other features. This user manual provides step-by-step instructions for installing and using the tool, and creating tree cover maps. Familiarity with ArcMap tools and concepts is helpful for using the tool.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161067","usgsCitation":"Cotillon, Suzanne, and Mathis, Melissa, 2016, Tree cover mapping tool—documentation and user manual (ver. 1.0, March 2016): U.S. Geological Survey Open-File Report 2016–1067, 11 p., https://dx.doi.org/10.3133/ofr20161067.","productDescription":"v, 11 p.","startPage":"1","endPage":"11","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073965","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":321947,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1067/coverthb.jpg"},{"id":321948,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1067/ofr20161067.pdf","text":"Report","size":"5.20 MB","description":"OFR 2016–1067"},{"id":344363,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://edcintl.cr.usgs.gov/downloads/sciweb1/shared/wafrica/downloads/tools/TreeCoverMapping10.x_Addins.zip","text":"Software Tool Download","description":"Software Tool Download"}],"contact":"Director
Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The U.S. Geological Survey provided technical support to the Agency for Toxic Substances and Disease Registry for site selection and sample collection and analysis in a 2012 investigation of groundwater quality from 29 private domestic water-supply wells in the vicinity of petroleum production in southwestern Indiana. Petroleum hydrocarbons, oil and grease, aromatic volatile organic compounds, methane concentrations greater than 8,800 micrograms per liter, chloride concentrations greater than 250 milligrams per liter, and gross alpha radioactivity greater than 15 picocuries per liter were reported in the analysis of groundwater samples from 11 wells.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161081","usgsCitation":"Risch, M.R., and Silcox, C.A., 2016, Groundwater quality from private domestic water-supply wells in the vicinity of petroleum production in southwestern Indiana: U.S. Geological Survey Open-File Report 2016–1081, 29 p., https://dx.doi.org/10.3133/ofr20161081.","productDescription":"Report: v, 29 p.; Appendix tables","startPage":"1","endPage":"29","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-040076","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":322060,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1081/ofr20161081.pdf","text":"Report","size":"791 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1081"},{"id":322061,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1081/ofr20161081_appendixtables.pdf","text":"Appendix Tables","description":"OFR 2016–1081 Appendix Tables"},{"id":322059,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1081/coverthb.jpg"}],"country":"United States","state":"Indiana","otherGeospatial":"Mt. Vernon Consolidated Oilfield","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88,\n 38\n ],\n [\n -88,\n 37.83\n ],\n [\n -87.8,\n 37.83\n ],\n [\n -87.8,\n 38\n ],\n [\n -88,\n 38\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278–1996
The GIS Flood Tool (GFT) was developed by the U.S. Geological Survey with support from the U.S. Agency for International Development’s Office of U.S. Foreign Disaster Assistance to provide a means for production of reconnaissance-level flood inundation mapping for data-sparse and resource-limited areas of the world. The GFT has also attracted interest as a tool for rapid assessment flood inundation mapping for the Flood Inundation Mapping Program of the U.S. Geological Survey. The GFT can fill an important gap for communities that lack flood inundation mapping by providing a first-estimate of inundation zones, pending availability of resources to complete an engineering study. The tool can also help identify priority areas for application of scarce flood inundation mapping resources. The technical basis of the GFT is an application of the Manning equation for steady flow in an open channel, operating on specially processed digital elevation data. The GFT is implemented as a software extension in ArcGIS. Output maps from the GFT were validated at 11 sites with inundation maps produced previously by the Flood Inundation Mapping Program using standard one-dimensional hydraulic modeling techniques. In 80 percent of the cases, the GFT inundation patterns matched 75 percent or more of the one-dimensional hydraulic model inundation patterns. Lower rates of pattern agreement were seen at sites with low relief and subtle surface water divides. Although the GFT is simple to use, it should be applied with the oversight or review of a qualified hydraulic engineer who understands the simplifying assumptions of the approach.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161038","collaboration":"Prepared in cooperation with the U.S. Agency for International Development, Office of U.S. Foreign Disaster Assistance (USAID/OFDA)","usgsCitation":"Verdin, James; Verdin, Kristine; Mathis, Melissa; Magadzire, Tamuka; Kabuchanga, Eric; Woodbury, Mark; and Gadain, Hussein, 2016, A software tool for rapid flood inundation mapping: U.S. Geological Survey Open-File Report 2016–1038, 26 p., https://dx.doi.org/10.3133/ofr20161038.","productDescription":"vi, 26 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055868","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":322105,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1038/ofr20161038.pdf","text":"Report","size":"16.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1038"},{"id":322104,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1038/coverthb.jpg"}],"contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, South Dakota 57198
The magnitude 4.0 earthquake that occurred on October 16, 2012, near Hollis Center and Waterboro in southwestern Maine surprised and startled local residents but caused only minor damage. A two-person U.S. Geological Survey (USGS) team was sent to Maine to conduct an intensity survey and document the damage. The only damage we observed was the failure of a chimney and plaster cracks in two buildings in East and North Waterboro, 6 kilometers (km) west of the epicenter. We photographed the damage and interviewed residents to determine the intensity distribution in the epicentral area. The damage and shaking reports are consistent with a maximum Modified Mercalli Intensity (MMI) of 5–6 for an area 1–8 km west of the epicenter, slightly higher than the maximum Community Decimal Intensity (CDI) of 5 determined by the USGS “Did You Feel It?” Web site. The area of strong shaking in East Waterboro corresponds to updip rupture on a fault plane that dips steeply east.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161071","usgsCitation":"Radakovich, A.L., Ferguson, A.J., and Boatwright, John, 2016, Field survey of earthquake effects from the magnitude 4.0 southern Maine earthquake of October 16, 2012: U.S. Geological Survey Open-File Report 2016–1071, 17 p., https://dx.doi.org/10.3133/ofr20161071. ","productDescription":"iv, 17 p.","startPage":"1","endPage":"17","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-046067","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":322068,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1071/ofr20161071.pdf","text":"Report","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1071"},{"id":322067,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1071/coverthb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Rhode Island, Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76,\n 41\n ],\n [\n -76,\n 46\n ],\n [\n -68.5,\n 46\n ],\n [\n -68.5,\n 41\n ],\n [\n -76,\n 41\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
http://earthquake.usgs.gov/
Mapping in the Morena Reservoir 7.5-minute quadrangle began in 1980, when the Hauser Wilderness Area, which straddles the Morena Reservoir and Barrett Lake quadrangles, was mapped for the U.S. Forest Service. Mapping was completed in 1993–1994. The Morena Reservoir quadrangle contains part of a regional-scale Late Jurassic(?) to Early Cretaceous tectonic suture that coincides with the western limit of Jurassic metagranites in this part of the Peninsular Ranges batholith (PRB). This suture, and a nearly coincident map unit consisting of metamorphosed Cretaceous and Jurassic back-arc basinal volcanic and sedimentary rocks (unit KJvs), mark the boundary between western, predominantly metavolcanic rocks, and eastern, mainly metasedimentary, rocks. The suture is intruded and truncated by the western margin of middle to Late Cretaceous Granite Mountain and La Posta plutons of the eastern zone of the batholith.
","publisher":"U. S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr9550","usgsCitation":"Todd, V.R., 2016, Geologic map of the Morena Reservoir 7.5-minute quadrangle, San Diego County, California: U.S. Geological Survey Open-File Report 95–50, 12 p., scale 1:24,000, https://dx.doi.org/10.3133/ofr9550.","productDescription":"Pamphlet: iii, 12 p.; 1 Plate: 32.74 x 30.79 inches; Metadata; Read Me; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":399099,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_104275.htm"},{"id":321428,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/1995/0050/ofr95-50_MorenaRes_metadata.txt","text":"Morena Reservoir metadata","linkFileType":{"id":2,"text":"txt"},"description":"OFR 95-50 Metadata TXT"},{"id":321427,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/1995/0050/ofr95-50_MorenaRes_metadata.htm","text":"Morena Reservoir metadata","linkFileType":{"id":5,"text":"html"},"description":"OFR 95-50 Metadata HTML"},{"id":321426,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/of/1995/0050/ofr95-50_MorenaRes_README.txt","text":"Morena Reservoir read me","linkFileType":{"id":2,"text":"txt"},"description":"OFR 95-50 Read Me"},{"id":321425,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/1995/0050/ofr95-50_MorenaRes_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 95-50 Pamphlet"},{"id":321424,"rank":2,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/1995/0050/ofr95-50_MorenaRes_plate.pdf","text":"Morena Reservoir plate","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 95-50 Plate"},{"id":321429,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/1995/0050/ofr95-50_DATABASE.zip","text":"Morena Reservoir database","linkFileType":{"id":6,"text":"zip"},"description":"OFR 95-50 Database"},{"id":321423,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/1995/0050/coverthb2.jpg"}],"country":"United States","state":"California","county":"San Diego County","otherGeospatial":"Morena Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.625,\n 32.625\n ],\n [\n -116.5,\n 32.625\n ],\n [\n -116.5,\n 32.75\n ],\n [\n -116.625,\n 32.75\n ],\n [\n -116.625,\n 32.625\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Tucson
U.S. Geological Survey
520 North Park Avenue
Tucson, AZ 85719
http://geomaps.wr.usgs.gov/
The U.S. Department of Interior’s Bureau of Reclamation, Lower Colorado Region (Reclamation) is preparing an environmental impact statement (EIS) for the Navajo Generating Station-Kayenta Mine Complex Project (NGS-KMC Project). The proposed project involves various Federal approvals that would facilitate continued operation of the Navajo Generating Station (NGS) from December 23, 2019 through 2044, and continued operation of the Kayenta Mine and support facilities (collectively called the Kayenta Mine Complex, or KMC) to supply coal to the NGS for this operational period. The EIS will consider several project alternatives that are likely to produce different effects on the Navajo (N) aquifer; the N aquifer is the principal water resource in the Black Mesa area used by the Navajo Nation, Hopi Tribe, and Peabody Western Coal Company (PWCC).
The N aquifer is composed of three hydraulically connected formations—the Navajo Sandstone, the Kayenta Formation, and the Lukachukai Member of the Wingate Sandstone—that function as a single aquifer. The N aquifer is confined under most of Black Mesa, and the overlying stratigraphy limits recharge to this part of the aquifer. The N aquifer is unconfined in areas surrounding Black Mesa, and most recharge occurs where the Navajo Sandstone is exposed in the area near Shonto, Arizona. Overlying the N aquifer is the D aquifer, which includes the Dakota Sandstone, Morrison Formation, Entrada Sandstone, and Carmel Formation. The aquifer is named for the Dakota Sandstone, which is the primary water-bearing unit.
The NGS is located near Page, Arizona on the Navajo Nation. The KMC, which delivers coal to NGS by way of a dedicated electric railroad, is located approximately 83 miles southeast of NGS (about 125 miles northeast of Flagstaff, Arizona). The Kayenta Mine permit area is located on about 44,073 acres of land leased within the boundaries of the Hopi and Navajo Indian Reservations. KMC has been conducting mining and reclamation operations within the Kayenta Mine permit boundary since 1973.
The KMC part of the proposed project requires approval by the Office of Surface Mining (OSM) of a significant revision of the mine’s permit to operate in accordance with the Surface Mine Control and Reclamation Act (Public Law 95-87, 91 Stat. 445 [30 U.S.C. 1201 et seq.]). The revision will identify coal resource areas that may be used to continue extracting coal at the present rate of approximately 8.2 million tons per year. The Kayenta Mine Complex uses water pumped from the D and N aquifers beneath PWCC’s leasehold to support mining and reclamation activities. Prior to 2006, water from the PWCC well field also was used to transport coal by way of a coal-slurry pipeline to the now-closed Mohave Generating Station. Water usage at the leasehold was approximately 4,100 acre-feet per year (acre-ft/yr) during the period the pipeline was in use, and declined to an average 1,255 acre-ft/yr from 2006 to 2011. The Probable Hydrologic Consequences (PHC) section of the mining and reclamation permit must be modified to project the consequences of extended water use by the mine for the duration of the KMC part of the project, including a post-mining reclamation period.
Since 1971, the U.S. Geological Survey (USGS) has conducted the Black Mesa Monitoring Program, which consists of monitoring water levels and water quality in the N aquifer, compiling information on water use by PWCC and tribal communities, maintaining several stream-gaging stations, measuring discharge at selected springs, conducting special studies, and reporting findings. These data are useful in evaluating the effects on the N aquifer from PWCC and community pumping, and the effects of variable precipitation.
The EIS will assess the impacts of continued pumping on the N aquifer, including changes in storage, water quality, and effects on spring and baseflow discharge, by proposed mining through 2044, and during the reclamation process to 2057.
Several groundwater models exist for the area and Reclamation concluded it would conduct a peer review of the groundwater flow model that will be used to assess the direct, reasonably foreseeable indirect, and cumulative effects of future groundwater withdrawals on the D and N aquifers in the Black Mesa area. Reclamation made this determination because of the level of controversy around the effects of continued water use and the comments received from the 2014 draft EIS scoping meetings. Reclamation requested assistance from the USGS in evaluating existing groundwater flow models of the Black Mesa Basin that can be used to predict the effects of different project alternatives on the D and N aquifers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161088","productDescription":"vi, 23 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076168","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":321807,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1088/ofr20161088.pdf","text":"Report","size":"3.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1088"},{"id":321806,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1088/coverthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Black Mesa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.4453125,\n 35.545635932499415\n ],\n [\n -111.4453125,\n 36.84446074079564\n ],\n [\n -109.6490478515625,\n 36.84446074079564\n ],\n [\n -109.6490478515625,\n 35.545635932499415\n ],\n [\n -111.4453125,\n 35.545635932499415\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
http://az.water.usgs.gov/
Between 2007 and 2008, seven Earthscope Plate Boundary Observatory (PBO) boreholes ranging in depth from about 200 to 800 feet deep were drilled in and adjacent to the Yellowstone caldera in Yellowstone National Park, for the purpose of installing volcano monitoring instrumentation. Five of the seven boreholes were equipped with strainmeters, downhole seismometers, and tiltmeters. Data collected during drilling included field observations of drill cuttings, stratigraphy within the boreholes, water temperature, and water and drill cuttings samples from selected depths.
\nSix of the seven boreholes encountered rhyolite lavas and tuffs. The rhyolite lavas compose the Canyon flow, the Gardner River flow, the Gibbon River flow, the Hayden Valley flow, the Nez Perce Creek flow, and the West Thumb flow. Boreholes also penetrated a vertical sequence through the Lava Creek Tuff and the Tuff of Bluff Point. In addition, one borehole drilled through a Swan Lake Flat Basalt sequence and terminated in a rhyolite lava flow.
\nAfter drilling the seven PBO boreholes, cuttings were examined and selected for preparation of grain mounts, thin sections, and geochemical analysis. Major ions and trace elements (including rare earth elements) of selected cuttings were determined by x-ray fluorescence (XRF) and inductively coupled plasma-mass spectrometry (ICP-MS); the ICP-MS provided more precise trace-element analysis than XRF. A preliminary interpretation of the results of geochemical analyses generally shows a correlation between borehole cuttings and previously mapped geology. The geochemical data and borehole stratigraphy presented in this report provide a foundation for future petrologic, geochemical, and geophysical studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161028","collaboration":"Prepared in cooperation with the National Park Service, Yellowstone National Park, and Earthscope Plate Boundary Observatory","usgsCitation":"Jaworowski, C., Susong, D., Heasler, H., Mencin, D., Johnson, W., Conrey, R., and Von Stauffenberg, J., 2016,\nGeologic and geochemical results from boreholes drilled in Yellowstone National Park, Wyoming, 2007 and 2008:\nU.S. Geological Survey Open-File Report 2016-1028, 39 p. https://dx.doi.org/10.3133/ofr20161028","productDescription":"Report: viii, 39 p.; 2 Appendixes","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064084","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":321191,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1028/ofr20161028.pdf","text":"Report","size":"4.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1028"},{"id":321192,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1028/ofr20161028_appendix01.xlsx","text":"Appendix 1","size":"74 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1028 Appendix 1"},{"id":321193,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1028/ofr20161028_appendix02.xlsx","text":"Appendix 2","size":"35 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1028 Appendix 2"},{"id":321190,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1028/coverthb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.93994140625,\n 44.402391829093915\n ],\n [\n -110.93994140625,\n 44.93758500391091\n ],\n [\n -110.0830078125,\n 44.93758500391091\n ],\n [\n -110.0830078125,\n 44.402391829093915\n ],\n [\n -110.93994140625,\n 44.402391829093915\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Utah Water Science Center
U.S. Geological Survey
2329 Orton Circle
Salt Lake City, Utah 84119-2047
http://ut.water.usgs.gov
Solar power represents an important and rapidly expanding component of the renewable energy portfolio of the United States (Lovich and Ennen, 2011; Hernandez and others, 2014). Understanding the impacts of renewable energy development on wildlife is a priority for the U.S. Fish and Wildlife Service (FWS) in compliance with Department of Interior Order No. 3285 (U.S. Department of the Interior, 2009) to “develop best management practices for renewable energy and transmission projects on the public lands to ensure the most environmentally responsible development and delivery of renewable energy.” Recent studies examining effects of renewable energy development on mortality of migratory birds have primarily focused on wind energy (California Energy Commission and California Department of Fish and Game, 2007), and in 2012 the FWS published guidance for addressing wildlife conservation concerns at all stages of land-based wind energy development (U.S. Fish and Wildlife Service, 2012). As yet, no similar guidelines exist for solar development, and no published studies have directly addressed the methodology needed to accurately estimate mortality of birds and bats at solar facilities. In the absence of such guidelines, ad hoc methodologies applied to solar energy projects may lead to estimates of wildlife mortality rates that are insufficiently accurate and precise to meaningfully inform conversations regarding unintended consequences of this energy source and management decisions to mitigate impacts. Although significant advances in monitoring protocols for wind facilities have been made in recent years, there remains a need to provide consistent guidance and study design to quantify mortality of bats, and resident and migrating birds at solar power facilities (Walston and others, 2015).
In this document, we suggest methods for mortality monitoring at solar facilities that are based on current methods used at wind power facilities but adapted for the unique conditions encountered at solar facilities. In particular, unlike at wind-power facilities, the unimpeded access to almost all areas within the facilities, the typically flat terrain, and general absence of thick vegetation allow distance-sampling techniques (Buckland and others, 2001, 2004) to be exploited to advantage at industrial solar sites. These protocols build on the work of Nicolai and others (2011), and as our understanding and techniques for monitoring improve, the methods may be further modified to incorporate improvements in the future. We present case studies based on monitoring methods currently implemented at different utility-scale solar facilities to illustrate how distance-sampling techniques may improve overall detectability without substantially increasing costs. Every facility is unique, and the protocols presented may be adapted based on specific monitoring objectives and conditions at each site.
We provide guidance for designing monitoring programs whose objective it is to estimate the total number of bird and bat fatalities occurring at a facility over an extended period of time. We address spatial variation in causes of mortality, as well as potential sources of imperfect detection, for example, animals falling in or moving to unsearched areas, carcasses removed by predators, and carcasses missed by searchers. We suggest methods to estimate and account for each source of imperfect detection. This document focuses on monitoring design only and does not discuss approaches for estimating mortality from collected data. The development of statistically sound estimators relevant to the solar context is a current topic of research, although there are already strong foundations for estimation with distance-sampling methods in similar open, arid environments (Anderson and others, 2001; Freilich and others, 2005). Nonetheless, if protocols described in this document are followed, the resulting data will be adequate and sufficient for estimating mortality using newly formulated estimators.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161087","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Huso, Manuela, Dietsch, Thomas, and Nicolai, Chris, 2016, Mortality monitoring design for utility-scale solar power facilities: U.S. Geological Survey Open-File Report 2016-1087, 44 p., https://dx.doi.org/10.3133/ofr20161087.","productDescription":"vi, 44 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073911","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":321633,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1087/ofr20161087.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1087 Report PDF"},{"id":321632,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1087/coverthb.jpg"}],"contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
Efforts to improve fish passage have resulted in the replacement of six culverts in Crystal Springs Creek in Portland, Oregon. Two more culverts are scheduled to be replaced at Glenwood Street and Bybee Boulevard (Glenwood/Bybee project) in 2016. Recently acquired data have allowed for a more comprehensive understanding of the hydrology of the creek and the topography of the watershed. To evaluate the impact of the culvert replacements and recent hydrologic data, a Hydrologic Engineering Center-River Analysis System hydraulic model was developed to estimate water-surface elevations during high-flow events. Longitudinal surface-water profiles were modeled to evaluate current conditions and future conditions using the design plans for the culverts to be installed in 2016. Additional profiles were created to compare with the results from the most recent flood model approved by the Federal Emergency Management Agency for Crystal Springs Creek and to evaluate model sensitivity.
Model simulation results show that water-surface elevations during high-flow events will be lower than estimates from previous models, primarily due to lower estimates of streamflow associated with the 0.01 and 0.002 annual exceedance probability (AEP) events. Additionally, recent culvert replacements have resulted in less ponding behind crossings. Similarly, model simulation results show that the proposed replacement culverts at Glenwood Street and Bybee Boulevard will result in lower water-surface elevations during high-flow events upstream of the proposed project. Wider culverts will allow more water to pass through crossings, resulting in slightly higher water-surface elevations downstream of the project during high-flows than water-surface elevations that would occur under current conditions. For the 0.01 AEP event, the water-surface elevations downstream of the Glenwood/Bybee project will be an average of 0.05 ft and a maximum of 0.07 ft higher than current conditions. Similarly, for the 0.002 AEP event, the water-surface elevations will be an average of 0.04 ft and a maximum of 0.19 ft higher than current conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161079","collaboration":"Prepared in cooperation with the City of Portland Bureau of Environmental Services","usgsCitation":"Stonewall, Adam, and Hess, Glen, 2016, Evaluation of flood inundation in Crystal Springs Creek, Portland, Oregon: U.S. Geological Survey Open-File Report 2016-1079, 33 p., https://dx.doi.org/10.3133/ofr20161079.","productDescription":"Report: iv, 33 p.; Plate: 24.00 x 36.00 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052885","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":321611,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1079/ofr20161079.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1079 Report PDF"},{"id":321612,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2016/1079/ofr20161079_plate1.pdf","text":"Plate 1","size":"9.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1079 Plate 1 PDF"},{"id":321610,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1079/coverthb.jpg"}],"country":"United States","state":"Oregon","city":"Portland","otherGeospatial":"Crystal Springs Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.62,\n 45.45\n ],\n [\n -122.62,\n 45.5\n ],\n [\n -122.65,\n 45.5\n ],\n [\n -122.65,\n 45.45\n ],\n [\n -122.62,\n 45.45\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
During 2015, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, collected groundwater samples from 31 wells at or near the Idaho Nuclear Technology and Engineering Center (INTEC) at the Idaho National Laboratory for purgeable organic compounds (POCs). The samples were collected and analyzed for the purpose of evaluating whether purge water from wells located inside an areal polygon established downgradient of the INTEC must be treated as a Resource Conservation and Recovery Act listed waste.
POC concentrations in water samples from 29 of 31 wells completed in the eastern Snake River Plain aquifer were greater than their detection limit, determined from detection and quantitation calculation software, for at least one to four POCs. Of the 29 wells with concentrations greater than their detection limits, only 20 had concentrations greater than the laboratory reporting limit as calculated with detection and quantitation calculation software. None of the concentrations exceeded any maximum contaminant levels established for public drinking water supplies. Most commonly detected compounds were 1,1,1-trichoroethane, 1,1-dichloroethene, and trichloroethene.
","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161083","collaboration":"DOE/ID-22238Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
Topock Marsh is a large wetland adjacent to the Colorado River and the main feature of Havasu National Wildlife Refuge (Havasu NWR) in southern Arizona. In 2010, the U.S. Fish and Wildlife Service (FWS) and Bureau of Reclamation began a project to improve water management capabilities at Topock Marsh and protect habitats and species. Initial construction required a drawdown, which caused below-average inflows and water depths in 2010–11. U.S. Geological Survey Fort Collins Science Center (FORT) scientists collected an assemblage of biotic, abiotic, and hydrologic data from Topock Marsh during the drawdown and immediately after, thus obtaining valuable information needed by FWS.
Building upon that work, FORT developed a decision support system (DSS) to better understand ecosystem health and function of Topock Marsh under various hydrologic conditions. The DSS was developed using a spatially explicit geographic information system package of historical data, habitat indices, and analytical tools to synthesize outputs for hydrologic time periods. Deliverables include high-resolution orthorectified imagery of Topock Marsh; a DSS tool that can be used by Havasu NWR to compare habitat availability associated with three hydrologic scenarios (dry, average, wet years); and this final report which details study results. This project, therefore, has addressed critical FWS management questions by integrating ecologic and hydrologic information into a DSS framework. This DSS will assist refuge management to make better informed decisions about refuge operations and better understand the ecological results of those decisions by providing tools to identify the effects of water operations on species-specific habitat and ecological processes. While this approach was developed to help FWS use the best available science to determine more effective water management strategies at Havasu NWR, technologies used in this study could be applied elsewhere within the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161065","collaboration":"In cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Holmquist-Johnson, Chris; Hanson, Leanne; Daniels, Joan; Talbert, Colin; and Haegele, Jeanette, 2016, Development of a decision support tool for water and resource management using biotic, abiotic, and hydrological assessments of Topock Marsh, Arizona: U.S. Geological Survey Open-File Report 2016–1065, 121 p., https://dx.doi.org/10.3133/ofr20161065.","productDescription":"viii, 121 p.","numberOfPages":"130","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070577","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":321529,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1065/ofr20161065.pdf","text":"Report","size":"55.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1065"},{"id":321528,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1065/coverthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Topock Marsh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.57572937011719,\n 34.75233231513255\n ],\n [\n -114.57572937011719,\n 34.85015678001124\n ],\n [\n -114.46826934814453,\n 34.85015678001124\n ],\n [\n -114.46826934814453,\n 34.75233231513255\n ],\n [\n -114.57572937011719,\n 34.75233231513255\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, USGS Fort Collins Science Center
2150 Centre Ave., Bldg. C
Box 25046, MS-939
Fort Collins, CO 80526-8118
The Airborne Lidar Processing System (ALPS) analyzes Experimental Advanced Airborne Research Lidar (EAARL) data—digitized laser-return waveforms, position, and attitude data—to derive point clouds of target surfaces. A full-waveform airborne lidar system, the EAARL seamlessly and simultaneously collects mixed environment data, including submerged, sub-aerial bare earth, and vegetation-covered topographies.
ALPS uses three waveform target-detection algorithms to determine target positions within a given waveform: centroid analysis, leading edge detection, and bottom detection using water-column backscatter modeling. The centroid analysis algorithm detects opaque hard surfaces. The leading edge algorithm detects topography beneath vegetation and shallow, submerged topography. The bottom detection algorithm uses water-column backscatter modeling for deeper submerged topography in turbid water.
The report describes slant range calculations and explains how ALPS uses laser range and orientation measurements to project measurement points into the Universal Transverse Mercator coordinate system. Parameters used for coordinate transformations in ALPS are described, as are Interactive Data Language-based methods for gridding EAARL point cloud data to derive digital elevation models. Noise reduction in point clouds through use of a random consensus filter is explained, and detailed pseudocode, mathematical equations, and Yorick source code accompany the report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161046","usgsCitation":"Nagle, David B., and Wright, C. Wayne, 2016, Algorithms used in the Airborne Lidar Processing System (ALPS):\nU.S. Geological Survey Open-File Report, 2016–1046, 45 p., https://dx.doi.org/10.3133/ofr20161046.","productDescription":"x, 45 p.","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063528","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":321007,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1046/ofr20161046.pdf","text":"Report","size":"1.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1046"},{"id":321006,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1046/coverthb.jpg"}],"contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
http://coastal.er.usgs.gov/
Successful adaptive management hinges largely upon integrating new and improved sources of information as they become available. As a timely example of this tenet, we updated a management decision support tool that was previously developed for greater sage-grouse (Centrocercus urophasianus, hereinafter referred to as “sage-grouse”) populations in Nevada and California. Specifically, recently developed spatially explicit habitat maps derived from empirical data played a key role in the conservation of this species facing listing under the Endangered Species Act. This report provides an updated process for mapping relative habitat suitability and management categories for sage-grouse in Nevada and northeastern California (Coates and others, 2014, 2016). These updates include: (1) adding radio and GPS telemetry locations from sage-grouse monitored at multiple sites during 2014 to the original location dataset beginning in 1998; (2) integrating output from high resolution maps (1–2 m2) of sagebrush and pinyon-juniper cover as covariates in resource selection models; (3) modifying the spatial extent of the analyses to match newly available vegetation layers; (4) explicit modeling of relative habitat suitability during three seasons (spring, summer, winter) that corresponded to critical life history periods for sage-grouse (breeding, brood-rearing, over-wintering); (5) accounting for differences in habitat availability between more mesic sagebrush steppe communities in the northern part of the study area and drier Great Basin sagebrush in more southerly regions by categorizing continuous region-wide surfaces of habitat suitability index (HSI) with independent locations falling within two hydrological zones; (6) integrating the three seasonal maps into a composite map of annual relative habitat suitability; (7) deriving updated land management categories based on previously determined cut-points for intersections of habitat suitability and an updated index of sage-grouse abundance and space-use (AUI); and (8) masking urban footprints and major roadways out of the final map products.
Seasonal habitat maps were generated based on model-averaged resource selection functions (RSF) derived for 10 project areas (813 sage-grouse; 14,085 locations) during the spring season, 10 during the summer season (591 sage-grouse, 11,743 locations), and 7 during the winter season (288 sage-grouse, 4,862 locations). RSF surfaces were transformed to HSIs and averaged in a GIS framework for every pixel for each season. Validation analyses of categorized HSI surfaces using a suite of independent datasets resulted in an agreement of 93–97 percent for habitat versus non-habitat on an annual basis. Spring and summer maps validated similarly well at 94–97 percent, while winter maps validated slightly less accurately at 87–93 percent.
We then provide an updated example of how space use models can be integrated with habitat models to help inform conservation planning. We used updated lek count data to calculate a composite abundance and space use index (AUI) that comprised the combination of probabilistic breeding density with a non-linear probability of occurrence relative to distance to nearest lek. The AUI was then classified into two categories of use (high and low-to-no) and intersected with the HSI categories to create potential management prioritization scenarios based on information about sage-grouse occupancy coupled with habitat suitability. Compared to Coates and others (2014, 2016), the amount of area classified as habitat across the region increased by 6.5 percent (approximately 1,700,000 acres). For management categories, core increased by 7.2 percent (approximately 865,000 acres), priority increased by 9.6 percent (approximately 855,000 acres), and general increased by 9.2 percent (approximately 768,000 acres), while non-habitat decreased (that is, classified non-habitat occurring outside of areas of concentrated use) by 11.9 percent (approximately 2,500,000 acres). Importantly, seasonal and annual maps represent habitat for all age and sex classes of sage-grouse (that is, sample sizes of marked grouse were insufficient to only construct models for reproductive females). This revised sage-grouse habitat mapping product helps improve adaptive application of conservation planning tools based on intersections of spatially explicit habitat suitability, abundance, and space use indices.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161080","collaboration":"Prepared in cooperation with the State of Nevada Sagebrush Ecosystem Program, Bureau of Land Management, Nevada Department of Wildlife, California Department of Fish and Wildlife, and Idaho State University","usgsCitation":"Coates, P.S., Casazza, M.L., Brussee B.E., Ricca, M.A., Gustafson, K.B., Sanchez-Chopitea, E., Mauch, K., Niell, L., Gardner, S., Espinosa, S., and Delehanty, D.J., 2016, Spatially explicit modeling of annual and seasonal habitat for greater sage-grouse (Centrocercus urophasianus) in Nevada and Northeastern California—An updated decision-support tool for management: U.S. Geological Survey Open-File Report 2016-1080, 160 p., https://dx.doi.org/10.3133/ofr20161080.","productDescription":"Report: viii, 160 p.; Dataset","numberOfPages":"172","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072897","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":322138,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://dx.doi.org/10.5066/F7CC0XRV","text":"USGS data release - Spatially Explicit Modeling of Annual and Seasonal Habitat for Greater Sage-Grouse (Centrocercus urophasianus) in Nevada and Northeastern California - an Updated Decision-Support Tool for Management"},{"id":321471,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1080/coverthb.jpg"},{"id":321472,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1080/ofr20161080.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1080 Report PDF"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.87158203125,\n 37.50972584293751\n ],\n [\n -120.87158203125,\n 41.96765920367816\n ],\n [\n -114.06005859375,\n 41.96765920367816\n ],\n [\n -114.06005859375,\n 37.50972584293751\n ],\n [\n -120.87158203125,\n 37.50972584293751\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
http://werc.usgs.gov/
The U.S. Geological Survey (USGS) has developed a dynamic food-web simulation model to provide decision support for Bureau of Reclamation (Reclamation) river restoration projects in the Methow River, Washington. This modeling effort was done to contribute to Reasonable and Prudent Alternative actions 56 and 57of the 2014 Federal Columbia River Power System Biological Opinion (FCRPS BO), which calls for exploration of modeling as a means to help evaluate Endangered Species Act (ESA)-listed fish response to river restoration efforts. In the Methow River, these species of concern include Upper Columbia River (UCR) spring Chinook salmon (Oncorhynchus tshawytscha) and UCR summer steelhead (Oncorhynchus mykiss). Additionally, the Independent Scientific Advisory Board (ISAB) for the Columbia River has identified the need for modeling (Independent Scientific Advisory Board, 2011a)—including models that incorporate food-web dynamics (Independent Scientific Advisory Board, 2011b)—to better understand how restoration and management strategies might enhance salmon and steelhead populations.
\nDynamic food-web models, even relatively simple ones, can be valuable tools for exploring responses to river restoration. Although these models have rarely been applied to rivers and streams (but see Mcintire and Colby, 1978; Power and others, 1995), they are commonly used for management decisions in terrestrial and ocean ecosystems (Christensen and Pauly, 1993; Evans and others, 2013). One of the main strengths of these models is that they are rooted in the fundamental laws of thermodynamics (that is, mass balance). Moreover, these models can be easily adapted to different contexts by adding or subtracting different species from the web and by mechanistically linking the dynamics of web members to local environmental conditions, such as water temperature, stream discharge, and channel hydraulics (Power and others, 1995; Doyle, 2006). Alternative management actions can then be evaluated by changing these environmental conditions to simulate potential outcomes following restoration.
\nIn this report, we outline the structure of a stream food-web model constructed to explore how alternative river restoration strategies may affect stream fish populations. We have termed this model the “Aquatic Trophic Productivity model” (ATP). We present the model structure, followed by three case study applications of the model to segments of the Methow River watershed in northern Washington. For two case studies (middle Methow River and lower Twisp River floodplain), we ran a series of simulations to explore how food-web dynamics respond to four distinctly different, but applied, strategies in the Methow River watershed: (1) reconnection of floodplain aquatic habitats, (2) riparian vegetation planting, (3) nutrient augmentation (that is, salmon carcass addition), and (4) enhancement of habitat suitability for fish. For the third case study, we conducted simulations to explore the potential fish and food-web response to habitat improvements conducted in 2012 at the Whitefish Island Side Channel, located in the middle Methow River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161075","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Benjamin, J.R., and Bellmore, J.R., 2016, Aquatic trophic productivity model: A decision support model for river restoration planning in the Methow River, Washington: U.S. Geological Survey Open-File Report 2016‒1075, 85 p., https://dx.doi.org/10.3133/ofr20161075.","productDescription":"vi, 85 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071770","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":321408,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1075/coverthb.jpg"},{"id":321409,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1075/ofr20161075.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1075 Report PDF"}],"country":"United States","state":"Washington","otherGeospatial":"Methow River","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
During summer 2014, lake level, streamflow, and water temperature in and around Crystal Springs Lake in Portland, Oregon, were measured by the U.S. Geological Survey and the City of Portland Bureau of Environmental Services to better understand the effect of the lake on Crystal Springs Creek and Johnson Creek downstream. Johnson Creek is listed as an impaired water body for temperature by the Oregon Department of Environmental Quality (ODEQ), as required by section 303(d) of the Clean Water Act. A temperature total maximum daily load applies to all streams in the Johnson Creek watershed, including Crystal Springs Creek. Summer water temperatures downstream of Crystal Springs Lake and the Golf Pond regularly exceed the ODEQ numeric criterion of 64.4 °F (18.0 °C) for salmonid rearing and migration. To better understand temperature contributions of this system, the U.S. Geological Survey developed two-dimensional hydrodynamic water temperature models of Crystal Springs Lake and the Golf Pond. Model grids were developed to closely resemble the bathymetry of the lake and pond using data from a 2014 survey. The calibrated models simulated surface water elevations to within 0.06 foot (0.02 meter) and outflow water temperature to within 1.08 °F (0.60 °C). Streamflow, water temperature, and lake elevation data collected during summer 2014 supplied the boundary and reference conditions for the model. Measured discrepancies between outflow and inflow from the lake, assumed to be mostly from unknown and diffuse springs under the lake, accounted for about 46 percent of the total inflow to the lake.
\nModel simulations (scenarios) were run with lower water surface elevations in Crystal Springs Lake and increased shading to the lake to assess the relative effect the lake and pond characteristics have on water temperature. The Golf Pond was unaltered in all scenarios. The models estimated that lower lake elevations would result in cooler water downstream of the Golf Pond and shorter residence times in the lake. Increased shading to the lake would also provide substantial cooling. Most management scenarios resulted in a decrease in 7-day average of daily maximum values by about 2.0– 4.7 °F (1.1 –2.6 °C) for outflow from Crystal Springs Lake during the period of interest. Outflows from the Golf Pond showed a net temperature reduction of 0.5–2.7 °F (0.3–1.5 °C) compared to measured values in 2014 because of solar heating and downstream warming in the Golf Pond resulting from mixing with inflow from Reed Lake.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161076","collaboration":"Prepared in cooperation with City of Portland Bureau of Environmental Services","usgsCitation":"Buccola, N.L., and Stonewall, A.J., 2016, Development of a CE-QUAL-W2 temperature model for Crystal Springs Lake, Portland, Oregon: U.S. Geological Survey Open-File Report 2016‒1076, 26 p.,\nhttps://dx.doi.org/10.3133/ofr20161076.","productDescription":"Report: vi, 26 p.; Tables 1-9","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060388","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":321392,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1076/ofr20161076_tables1-9.xlsx","text":"Tables 1-9","size":"63 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1076 Tables 1-9"},{"id":321390,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1076/coverthb.jpg"},{"id":321391,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1076/ofr20161076.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1076"}],"country":"United States","state":"Oregon","city":"Portland","otherGeospatial":"Crystal Springs Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.63982295989989,\n 45.47522429601816\n ],\n [\n -122.63982295989989,\n 45.48085140521857\n ],\n [\n -122.63482332229613,\n 45.48085140521857\n ],\n [\n -122.63482332229613,\n 45.47522429601816\n ],\n [\n -122.63982295989989,\n 45.47522429601816\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
The coral reef in Faga‘alu Bay, Tutuila, American Samoa, has suffered numerous natural and anthropogenic stresses. Areas once dominated by live coral are now mostly rubble surfaces covered with turf or macroalgae. In an effort to improve the health and resilience of the coral reef system, the U.S. Coral Reef Task Force selected Faga‘alu Bay as a priority study area. To support these efforts, the U.S. Geological Survey mapped nearly 1 km2 of seafloor to depths of about 60 m. Unconsolidated sediment (predominantly sand) constitutes slightly greater than 50 percent of the seafloor in the mapped area; reef and other hardbottom potentially available for coral recruitment constitute nearly 50 percent of the mapped area. Of this potentially available hardbottom, only slightly greater than 37 percent is covered with at least 10 percent coral, which is fairly evenly distributed between the reef flat, fore reef, and offshore bank/shelf.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161077","usgsCitation":"Cochran, S.A., Gibbs, A.E., D’Antonio, N.L., and Storlazzi, C.D., 2016, Benthic habitat map of U.S. Coral Reef Task Force Faga‘alu Bay priority study area, Tutuila, American Samoa: U.S. Geological Survey Open-File Report 2016–1077, 32 p., https://dx.doi.org/10.3133/ofr20161077.","productDescription":"Report: v, 32 p.; Metadata; Spatial Data","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072636","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":321386,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1077/coverthb2.jpg"},{"id":321350,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1077/ofr20161077.pdf","text":"Report","size":"16.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1077"},{"id":321366,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2016/1077/ofr20161077_metadata.html","text":"Metadata","size":"65 KB","linkFileType":{"id":5,"text":"html"},"description":"OFR 2016-1077 Metadata"},{"id":321367,"rank":2,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2016/1077/ofr20161077_gis_data.zip","text":"Polygon shapefile of benthic habitats and associated files","size":"256 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1077 GIS data"}],"country":"United States","state":"American Samoa","otherGeospatial":"Faga'alu Bay, Tutuila","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -170.69046020507812,\n -14.277026769167454\n ],\n [\n -170.76547622680664,\n -14.332417680244378\n ],\n [\n -170.74419021606442,\n -14.367674440539975\n ],\n [\n -170.69578170776367,\n -14.326097485980599\n ],\n [\n -170.66900253295898,\n -14.288006232490893\n ],\n [\n -170.69046020507812,\n -14.277026769167454\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
The original National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL) was extensively modified to increase the spatial sampling density and to improve performance in water ranging from 3 to 44 meters (m). The new (EAARL-B) sensor features a higher spatial density that was achieved by optically splitting each laser pulse into three pulses spatially separated by 1.6 m along the flight track and 2.0 m across the flight track, on the water surface when flown at a nominal altitude of 300 m (984 feet). The sample spacing can be optionally increased to 1.0 m across the flight track. Improved depth capability was achieved by increasing the total peak laser power by a factor of 10 and by designing a new “deep-water” receiver, which is optimized to exclusively receive refracted and scattered light from deeper water (15–44 m).
\nTwo different clear-water flight missions were conducted over the U.S. Navy's South Florida Testing Facility (SFTF) to determine the EAARL-B calibration coefficients. The SFTF is an established lidar calibration range located in the coastal waters southeast of Fort Lauderdale, Florida. We used 23 selected polygons at 23 distinct depths to compare a reference dataset from this site to determine EAARL-B calibration constants over the depth range of 6.5 to 34 m.
\nWe also conducted a near-simultaneous single-beam jet-ski-based sonar survey of selected transects ranging from 1 to 33 m depth in the same area. The near-concurrent jet ski data were used to evaluate the EAARL-B performance over the depth range from 0.9 to 10 m. The more timely jet ski data were necessary because the primary reference dataset was 9 years old, and areas shallower than 6.5 m are dominated by shifting sand. We determined the jet ski data were not useful as a calibration reference in water deeper than 10 m due to large uncertainty in the vertical measurement introduced by the lack of any sensor orientation data, that is, for pitch, roll, and heading to correct the measured slant range to a vertical measurement.
\nThe resulting calibrated EAARL-B data were then analyzed and compared with the original reference dataset, the jet-ski-based dataset from the same Fort Lauderdale site, as well as the depth-accuracy requirements of the International Hydrographic Organization (IHO). We do not claim to meet all of the IHO requirements and standards. The IHO minimum depth-accuracy requirements were used as a reference only and we do not address the other IHO requirements such as “ Full Seafloor Search”. Our results show good agreement between the calibrated EAARL-B data and all reference datasets, with results that are within the 95 percent depth accuracy of the IHO Order 1 (a and b) depth-accuracy requirements.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161048","usgsCitation":"Wright, C.W., Kranenburg, C.J., Troche, R.J., Mitchell, R.W., and, Nagle, D.B., 2016, Depth calibration of the experimental advanced airborne research lidar, EAARL-B: U.S. Geological Survey Open-File Report 2016–1048, 23 p., https://dx.doi.org/10.3133/ofr20161048.","productDescription":"Report: vi, 22 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061552","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":320937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1048/coverthb.jpg"},{"id":320951,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://dx.doi.org/10.5066/F79S1P4S","text":"Data Release"},{"id":320938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1048/ofr20161048.pdf","text":"Report","size":"1.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1048"}],"contact":"Director, St. Petersburg Coastal and Marine Science Center
600 4th Street South
St. Petersburg, FL 33701
(727) 502-8000
http://coastal.er.usgs.gov/
Industrial practices at the Naval Industrial Reserve Ordnance Plant, in Fridley, Minnesota, caused soil and groundwater contamination. Some volatile organic compounds from the plant might have discharged to the Mississippi River, forced by the natural hydraulic gradient in the surficial aquifer system. The U.S. Environmental Protection Agency included the Naval Industrial Reserve Ordnance Plant on the Superfund National Priorities List in 1989.
\nThis report describes a preliminary characterization of trichloroethene transport in the surficial and Cambrian-Ordovician aquifer systems at the Naval Industrial Reserve Ordnance Plant. The characterization first involved simulation of 2001 conditions using a model, followed by an application of this 2001 simulator to 2011 conditions.
\nThe U.S. Geological Survey, in cooperation with the U.S. Department of the Navy, used a steady-state, uniform-density groundwater flow model to simulate measured potentiometric heads in aquifer systems on August 20, 2001, and a single-phase, conservative, non-reactive, miscible transport model to simulate trichloroethene concentrations in aquifer systems measured in 2001. The U.S. Department of the Navy furnished trichloroethene source areas and trichloroethene source area concentrations to the U.S. Geological Survey for this model simulation. Furnished delineations were postulated and informed by data collected from 1995 to 2011. The groundwater flow simulation of August 20, 2001, was superior to the trichloroethene transport simulation at replicating measurements; simulated potentiometric heads matched 90 percent of measured potentiometric heads on August 20, within 2 feet at selected locations whereas simulated trichloroethene concentration contours of 3, 10, 100, 1000, and 10,000 micrograms per liter (µg/L) correctly bounded 52 percent of measured concentrations in 2001 at selected locations. The degree to which the simulated trichloroethene plume does not match trichloroethene measurements in the surficial aquifer system during the 2001 simulation may suggest that furnished trichloroethene source areas and trichloroethene source area concentrations did not accurately represent all trichloroethene sources in the hydrogeologic system.
\nDuring the model simulation of 2001, trichloroethene discharged to the Mississippi River. A simulated 900-foot-long zone of benthic trichloroethene discharge flux existed in the shallow flow zone, across which simulated trichloroethene discharged from the surficial aquifer system to the Mississippi River at simulated trichloroethene concentrations that ranged from 3 µg/L to more than 100 µg/L. The Mississippi River was not sampled for volatile organic compounds in Fridley, Minn., from 1999 to 2016 (the publication of this report). Trichloroethene concentrations were measured in wells close to the Mississippi River in the surficial aquifer system on the downgradient side of the Naval Industrial Reserve Ordnance Plant groundwater flow field; for example, at well MS–43 in the shallow flow zone of the surficial aquifer system 280 feet east of the Mississippi River between December 1999 and August 2012, trichloroethene concentrations ranged from 130 to 220 µg/L. The 220-µg/L maximum concentration was reached in March 2003 and October 2006. The August 2012 concentration was 140 µg/L.
\nThe August 20, 2001, groundwater flow model simulator and the 2001 trichloroethene transport simulator were applied to a groundwater extraction and treatment system that existed in 2011. Furnished trichloroethene source areas and concentrations in the 2001 simulator were replaced with different, furnished, hypothetical source areas and concentrations. Forcing in 2001 was replaced with forcing in 2011. No trichloroethene concentrations greater than 3 µg/L were simulated as discharging to the Mississippi River during applications of the 2001 simulator to the 2011 groundwater extraction and treatment system. These applications were not intended to represent historical conditions. Differences between furnished and actual trichloroethene sources may explain differences between measurements and simulation results for the 2001 trichloroethene transport simulator. Causes of differences between furnished and actual trichloroethene sources may cause differences between hypothetical application results and the performance of the actual U.S. Department of the Navy groundwater extraction and treatment system at the Naval Industrial Reserve Ordnance Plant. Other limitations may also cause differences between application results and performance.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161066","collaboration":"Prepared in cooperation with the U.S. Department of the Navy, Naval Facilities Engineering Command","usgsCitation":"King, J.N., and Davis, J.H., 2016, Preliminary investigation of groundwater flow and trichloroethene transport in the surficial aquifer system, Naval Industrial Reserve Ordnance Plant, Fridley, Minnesota: U.S. Geological Survey Open File Report 2016–1066, 120 p., https://dx.doi.org/10.3133/ofr20161066.","productDescription":"Report: x, 120 p.; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-039553","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":321042,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://dx.doi.org/10.5066/F798853M","text":"Data Release","linkFileType":{"id":5,"text":"html"},"description":"OFR 2016-1066"},{"id":321040,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1066/coverthb.jpg"},{"id":321041,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1066/ofr20161066.pdf","text":"Report","size":"12,1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1066"}],"country":"United States","state":"Minnesota","city":"Fridley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.38172912597656,\n 45.09582203415993\n ],\n [\n -93.34877014160155,\n 45.03228854011639\n ],\n [\n -93.27735900878906,\n 45.02986219868277\n ],\n [\n -92.96905517578125,\n 45.180584858570136\n ],\n [\n -93.043212890625,\n 45.25652199219273\n ],\n [\n -93.38172912597656,\n 45.09582203415993\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
(763) 783-3100
http://mn.water.usgs.gov/