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 limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar 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 Offshore of Santa Cruz map area is located in central California, on the Pacific Coast about 98 km south of San Francisco. The city of Santa Cruz (population, about 63,000), the largest incorporated city in the map area and the county seat of Santa Cruz County, lies on uplifted marine terraces between the shoreline and the northwest-trending Santa Cruz Mountains, part of California’s Coast Ranges. All of California’s State Waters in the map area is part of the Monterey Bay National Marine Sanctuary.
The map area is cut by an offshore section of the San Gregorio Fault Zone, and it lies about 20 kilometers southwest of the San Andreas Fault Zone. Regional folding and uplift along the coast has been attributed to a westward bend in the San Andreas Fault Zone and to right-lateral movement along the San Gregorio Fault Zone. Most of the coastal zone is characterized by low, rocky cliffs and sparse, small pocket beaches backed by low, terraced hills. Point Santa Cruz, which forms the north edge of Monterey Bay, provides protection for the beaches in the easternmost part of the map area by sheltering them from the predominantly northwesterly waves.
The shelf in the map area is underlain by variable amounts (0 to 25 m) of upper Quaternary shelf, estuarine, and fluvial sediments deposited as sea level fluctuated in the late Pleistocene. The inner shelf is characterized by bedrock outcrops that have local thin sediment cover, the result of regional uplift, high wave energy, and limited sediment supply. The midshelf occupies part of an extensive, shore-parallel mud belt. The thickest sediment deposits, inferred to consist mainly of lowstand nearshore deposits, are found in the southeastern and northwestern parts of the map area.
Coastal sediment transport in the map area is characterized by northwest-to-southeast littoral transport of sediment that is derived mainly from ephemeral streams in the Santa Cruz Mountains and also from local coastal-bluff erosion. During the last approximately 300 years, as much as 18 million cubic yards (14 million cubic meters) of sand-sized sediment has been eroded from the area between Año Nuevo Island and Point Año Nuevo and transported south; this mass of eroded sand is now enriching beaches in the map area. Sediment transport is within the Santa Cruz littoral cell, which terminates in the submarine Monterey Canyon.
Benthic species observed in the Offshore of Santa Cruz map area are natives of the cold-temperate biogeographic zone that is called either the “Oregonian province” or the “northern California ecoregion.” This biogeographic province is maintained by the long-term stability of the southward-flowing California Current, the eastern limb of the North Pacific subtropical gyre that flows from southern British Columbia to Baja California. At its midpoint off central California, the California Current transports subarctic surface (0–500 m deep) waters southward, about 150 to 1,300 km from shore. Seasonal northwesterly winds that are, in part, responsible for the California Current, generate coastal upwelling. The south end of the Oregonian province is at Point Conception (about 300 km south of the map area), although its associated phylogeographic group of marine fauna may extend beyond to the area offshore of Los Angeles in southern California. The ocean off of central California has experienced a warming over the last 50 years that is driving an ecosystem shift away from the productive subarctic regime towards a depopulated subtropical environment.
Biological productivity resulting from coastal upwelling supports populations of Sooty Shearwater, Western Gull, Common Murre, Cassin’s Auklet, and many other less populous bird species. In addition, an observable recovery of Humpback and Blue Whales has occurred in the area; both species are dependent on coastal upwelling to provide nutrients. The large extent of exposed inner shelf bedrock supports large forests of “bull kelp,” which is well adapted for high-wave-energy environments. The kelp beds are the northernmost known habitat for the population of southern sea otters. Common fish species found in the kelp beds and rocky reefs include lingcod and various species of rockfish and greenling.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161024","usgsCitation":"Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., Sliter, R.W., Maier, K.L., and Krigsman, L.M. (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State Waters Map Series — Offshore of Santa Cruz, California: U.S. Geological Survey Open-File Report 2016–1024, pamphlet 40 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20161024.","productDescription":"Pamphlet: iv, 40 p.; 10 Sheets: 60.0 x 36.0 inches or smaller; Data Catalog; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-058743","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438627,"rank":21,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TM785G","text":"USGS data release","linkHelpText":"California State Waters Map Series Data Catalog--Offshore of Santa Cruz, California"},{"id":318983,"rank":19,"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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Gary Greene, and Mercedes D. Erdey"},{"id":318968,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1024/ofr20161024_sheet6.pdf","text":"Sheet 6","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1024 Sheet 6 PDF","linkHelpText":"Ground-Truth Studies, Offshore of Santa Cruz Map Area, California By Nadine E. Golden, Guy R. Cochrane, and Lisa M. Krigsman"},{"id":318967,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1024/ofr20161024_sheet5.pdf","text":"Sheet 5","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1024 Sheet 5 PDF","linkHelpText":"Seafloor Character, Offshore of Santa Cruz Map Area, California By Mercedes D. Erdey and Guy R. Cochrane"},{"id":318966,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1024/ofr20161024_sheet4.pdf","text":"Sheet 4","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1024 Sheet 4 PDF","linkHelpText":"Data Integration and Visualization, Offshore of Santa Cruz Map Area, California By Peter Dartnell"},{"id":318965,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1024/ofr20161024_sheet3.pdf","text":"Sheet 3","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1024 Sheet 3 PDF","linkHelpText":"Acoustic Backscatter, Offshore of Santa Cruz Map Area, California By Peter Dartnell, Andrew C. Ritchie, and David P. Finlayson"},{"id":318975,"rank":11,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1024/ofr20161024_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1024 Pamphlet"},{"id":318977,"rank":13,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2016/1024/ofr20161024_metadata.html"},{"id":318970,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1024/ofr20161024_sheet8.pdf","text":"Sheet 8","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1024 Sheet 8 PDF","linkHelpText":"Seismic-Reflection Profiles, Offshore of Santa Cruz Map Area, California by Samuel Y. Johnson, Stephen R. Hartwell, and Ray W. Sliter"},{"id":399098,"rank":20,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_104092.htm"},{"id":318976,"rank":12,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1024/coverthb.jpg"},{"id":318964,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1024/ofr20161024_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1024 Sheet 2 PDF","linkHelpText":"Shaded-Relief Bathymetry, Offshore of Santa Cruz Map Area, California By Peter Dartnell, Andrew C. Ritchie, and David P. Finlayson"},{"id":318963,"rank":1,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1024/ofr20161024_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1024 Sheet 1 PDF","linkHelpText":"Colored Shaded-Relief Bathymetry, Offshore of Santa Cruz Map Area, California By Peter Dartnell, Andrew C. Ritchie, and David P. Finlayson"},{"id":318979,"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":318972,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1024/ofr20161024_sheet10.pdf","text":"Sheet 10","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1024 Sheet 10 PDF","linkHelpText":"Offshore and Onshore Geology and Geomorphology, Offshore of Santa Cruz Map Area, California By Samuel Y. Johnson, Stephen R. Hartwell, and Clifton W. Davenport"},{"id":318980,"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."}],"country":"United States","state":"California","city":"Santa Cruz","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.1997,\n 36.8425\n ],\n [\n -122.0333,\n 36.8425\n ],\n [\n -122.0333,\n 37.0033\n ],\n [\n -122.1997,\n 37.0033\n ],\n [\n -122.1997,\n 36.8425\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/
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 California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar bathymetric data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), 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.
\nThe Offshore of Aptos map area is located on the Pacific Coast, on the north side of Monterey Bay, about 105 km southeast of San Francisco. The largest incorporated city in the map area, Capitola, and numerous unincorporated towns including Aptos, lie on uplifted marine terraces between the shoreline, and the northwest-trending Santa Cruz Mountains, part of California’s Coast Ranges. The map area includes the northernmost part of Santa Cruz Harbor, and Moss Landing Harbor is located about 10 km south of the map area. The offshore part of the map area is entirely within California’s State Waters and is also part of the Monterey Bay National Marine Sanctuary. In the southern part of the map area, the Soquel Canyon State Marine Conservation Area extends eastward from the limit of California’s State Waters across Soquel Canyon.
\nThe Offshore of Aptos map area is on the western margin of North American Plate—the only continental margin in the world delineated largely by transform faults. The San Andreas Fault Zone cuts through the Santa Cruz Mountains just 3.5 km northeast of the map area. The San Gregorio Fault Zone, another major plate-boundary structure, cuts through Monterey Canyon about 13 km southwest of the map area. Ongoing deformation associated with and between these major fault zones has uplifted the Santa Cruz Mountains and formed well-developed sets of marine terraces that characterize almost the entire coastal zone of the map area.
\nThe offshore part of the map area consists of relatively flat and shallow continental shelf which is underlain by variable amounts (0 to 30 m) of upper Quaternary shelf, estuarine, and fluvial sediments deposited as sea level fluctuated in the late Pleistocene. Along the southern edge of the map area, the shelf is incised by the head of Soquel Canyon, a northeast-trending tributary to the west-trending Monterey Canyon. During the last sea-level lowstand (the Last Glacial Maximum [LGM], about 21,000 years ago) Soquel Creek flowed through a paleochannel across the emergent shelf into the head of Soquel Canyon. This canyon was disconnected from its onshore watershed during the post-LGM sea-level rise of about 125 m; the abandoned paleochannel was subsequently filled with marine sediment. Coastal sediment in the Offshore of Aptos map area is supplied by coastal watersheds and bluff erosion. Sediment transport in this part of the Santa Cruz littoral cell is primarily from the northwest to the southeast and terminates in the submarine Monterey Canyon. Longshore drift is impeded by jetties at Santa Cruz Harbor, resulting in high beach erosion rates east of the harbor. Sediment dredged from the harbor mouth (estimated 300,000 yds3/yr) is currently being used to nourish beaches directly to the east. Farther downcoast, the rapidly eroding beach at Capitola was stabilized by construction of an about 75-m-long groin.
\nThis part of central California is exposed to large North Pacific swells from the northwest throughout the year. North Pacific swell heights range from 2 to 10 meters, with larger swells occurring from October to May. During El Niño-Southern Oscillation (ENSO) events, winter storms track farther south than they do in normal (non-ENSO) years, thereby impacting the map area more frequently and with waves of larger heights. Bedrock exposed in coastal cliffs is relatively erosion-resistant, and significant erosional events primarily are restricted to storm-wave activity that also erodes the overlying unconsolidated marine-terrace sediments.
\nThe Offshore of Aptos map area lies within the cold-temperate biogeographic zone that is called either the “Oregonian” province or the “northern California ecoregion.” This biogeographic province is maintained by the long-term stability of the southward-flowing California Current, the eastern limb of the North Pacific subtropical gyre that flows from southern British Columbia to Baja California. At its midpoint off central California, the California Current transports subarctic surface (0–500 m deep) waters southward, about 150 to 1,300 km from shore. Seasonal northwesterly winds that are, in part, responsible for the California Current, generate coastal upwelling. The south end of the Oregonian province is at Point Conception (about 310 km southeast of the map area), although its associated phylogeographic group of marine fauna may extend beyond to the area offshore of Los Angeles in southern California. The ocean off of central California has experienced a warming over the last 50 years that is driving an ecosystem shift away from the productive subarctic regime towards a depopulated subtropical environment.
\nSeafloor habitats in the Offshore of Aptos map area lie within the “Shelf” Megahabitat class and include patchy rocky habitats, gravel-rich scour depressions, minor bedrock habitat, and predominantly sandy inner shelf. Sandy shelf habitats grade offshore to mud-dominated habitats on the midshelf in deeper water. Biological productivity resulting from coastal upwelling supports populations of Sooty Shearwater, Western Gull, Common Murre, Cassin’s Auklet, and many other less populous bird species. In addition, an observable recovery of Humpback and Blue Whales has occurred in the area; both species are dependent on coastal upwelling to provide nutrients. California sea lions and Pacific harbor seals are abundant in the map area. Common bottlenose dolphins are often observed very close to shore and in the surf zone. The large extent of exposed inner shelf bedrock supports large forests of “bull kelp,” which is well adapted for high-wave-energy environments. The kelp beds are the northernmost known habitat for the population of southern sea otters. Common fish species found in the kelp beds and rocky reefs include blue rockfish, black rockfish, olive rockfish, kelp rockfish, gopher rockfish, black-and-yellow rockfish, painted greenling, kelp greenling, and lingcod.
\n","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20161025","usgsCitation":"Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, R.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, R.W., Finlayson, D.P., and Krigsman, L.M. (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State Waters Map Series — Offshore of Aptos, California: U.S. Geological Survey Open-File Report 2016–1025, pamphlet 43 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20161025.","productDescription":"Pamphlet: iv, 43 p.; 10 Sheets: 55.0 x 36.0 inches or smaller; Data Catalog; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059274","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438628,"rank":21,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7K35RQB","text":"USGS data release","linkHelpText":"California State Waters Map Series Data Catalog--Offshore of Aptos, California"},{"id":318989,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20151191","text":"Open-File Report 2015–1191,","linkHelpText":"California State Waters Map Series—Offshore of Scott Creek, California, by Guy R. Cochrane and others."},{"id":399015,"rank":20,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_104093.htm"},{"id":318984,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1025/coverthb.jpg"},{"id":318985,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1025/ofr20161025_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1025 Pamphlet PDF"},{"id":318986,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2016/1025/ofr20161025_metadata.html"},{"id":318987,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://dx.doi.org/10.5066/F7K35RQB","text":"Data Catalog","linkFileType":{"id":5,"text":"html"},"linkHelpText":"The GIS data layers for this map are accessible from “Data Catalog—Offshore of Aptos, California,” which is part of California State Waters Map Series Data Catalog. 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Cochrane and others."},{"id":318991,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/sim3306","text":"Scientific Investigations Map 3306,","linkHelpText":"California State Waters Map Series—Offshore of San Gregorio, California, by Guy R. Cochrane and others."},{"id":318992,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/ofr20141214","text":"Open-File Report 2014–1214,","linkHelpText":"California State Waters Map Series—Offshore of Half Moon Bay, California, by Guy R. Cochrane and others."},{"id":318993,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1025/ofr20161025_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1025 Sheet 1 PDF","linkHelpText":"Colored Shaded-Relief Bathymetry, Offshore of Aptos Map Area, California By Peter Dartnell, Andrew C. Ritchie, David P. Finlayson, and Rikk G. Kvitek"},{"id":318994,"rank":11,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1025/ofr20161025_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1025 Sheet 2 PDF","linkHelpText":"Shaded-Relief Bathymetry, Offshore of Aptos Map Area, California By Peter Dartnell, Andrew C. Ritchie, David P. Finlayson, and Rikk G. Kvitek"},{"id":318995,"rank":12,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1025/ofr20161025_sheet3.pdf","text":"Sheet 3","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1025 Sheet 3 PDF","linkHelpText":"Acoustic Backscatter, Offshore of Aptos Map Area, California By Peter Dartnell, Andrew C. Ritchie, David P. Finlayson, and Rikk G. Kvitek"},{"id":318996,"rank":13,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1025/ofr20161025_sheet4.pdf","text":"Sheet 4","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1025 Sheet 4 PDF","linkHelpText":"Data Integration and Visualization, Offshore of Aptos Map Area, California By Peter Dartnell"},{"id":318997,"rank":14,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1025/ofr20161025_sheet5.pdf","text":"Sheet 5","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1025 Sheet 5 PDF","linkHelpText":"Seafloor Character, Offshore of Aptos Map Area, California By Mercedes D. Erdey and Guy R. Cochrane"},{"id":318998,"rank":15,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1025/ofr20161025_sheet6.pdf","text":"Sheet 6","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1025 Sheet 6 PDF","linkHelpText":"Ground-Truth Studies, Offshore of Aptos Map Area, California By Nadine E. Golden, Guy R. 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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/
This report describes two software tools that, when used as front ends for the three-dimensional backward Monte Carlo atmospheric-radiative-transfer model (RTM) McArtim, facilitate the generation of lookup tables of volcanic-plume optical-transmittance characteristics in the ultraviolet/visible-spectral region. In particular, the differential optical depth and derivatives thereof (that is, weighting functions), with regard to a change in SO2 column density or aerosol optical thickness, can be simulated for a specific measurement geometry and a representative range of plume conditions. These tables are required for the retrieval of SO2 column density in volcanic plumes, using the simulated radiative-transfer/differential optical-absorption spectroscopic (SRT-DOAS) approach outlined by Kern and others (2012). This report, together with the software tools published online, is intended to make this sophisticated SRT-DOAS technique available to volcanologists and gas geochemists in an operational environment, without the need for an indepth treatment of the underlying principles or the low-level interface of the RTM McArtim.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161045","usgsCitation":"Kern, Christoph, 2016, An interface for simulating radiative transfer in and around volcanic plumes with the Monte Carlo radiative transfer model McArtim: U.S. Geological Survey Open-File Report 2016–1045, 18 p., https://dx.doi.org/10.3133/ofr20161045.","productDescription":"iv, 18 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-046306","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":319193,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1045/coverthb.jpg"},{"id":319194,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1045/ofr20161045.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1045"}],"contact":"Contact CVO
Volcano Science Center, Cascades Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court, Building 10, Suite 100
Vancouver, WA 98683-9589
http://vulcan.wr.usgs.gov/
The Comprehensive Sturgeon Research Project is a multiyear, multiagency collaborative research framework developed to provide information to support pallid sturgeon recovery and Missouri River management decisions. The project strategy integrates field and laboratory studies of sturgeon reproductive ecology, early life history, habitat requirements, and physiology. The project scope of work is developed annually with collaborating research partners and in cooperation with the U.S. Army Corps of Engineers, Missouri River Recovery Program–Integrated Science Program. The project research consists of several interdependent and complementary tasks that involve multiple disciplines.
The project research tasks in the 2014 scope of work emphasized understanding of reproductive migrations and spawning of adult pallid sturgeon and hatch and drift of larvae. These tasks were addressed in three hydrologically and geomorphologically distinct parts of the Missouri River Basin: the Lower Missouri River downstream from Gavins Point Dam, the Upper Missouri River downstream from Fort Peck Dam and downstream reaches of the Milk River, and the Lower Yellowstone River. The project research is designed to inform management decisions related to channel re-engineering, flow modification, and pallid sturgeon population augmentation on the Missouri River and throughout the range of the species. Research and progress made through this project are reported to the U.S. Army Corps of Engineers annually. This annual report details the research effort and progress made by the Comprehensive Sturgeon Research Project during 2014.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161013","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Missouri River Recovery—Integrated Science Program","usgsCitation":"DeLonay, A.J., Chojnacki, K.A., Jacobson, R.B., Braaten, P.J., Buhl, K.J., Elliott, C.M., Erwin, S.O., Faulkner, J.D.A., Candrl, J.S., Fuller, D.B., Backes, K.M., Haddix, T.M., Rugg, M.L., Wesolek, C.J., Eder, B.L., and Mestl, G.E., 2016,\nEcological requirements for pallid sturgeon reproduction and recruitment in the Missouri River—Annual report 2014: U.S. Geological Survey Open-File Report 2016–1013, 131 p., https://dx.doi.org/10.3133/ofr20161013.","productDescription":"xv, 131 p.","numberOfPages":"152","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065464","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":318883,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1013/coverthb.jpg"},{"id":318884,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1013/ofr20161013.pdf","text":"Report","size":"24.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1013"}],"country":"United States","state":"Missouri, Montana, Nebraska","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.57812499999999,\n 47.956823800497475\n ],\n [\n -107.57812499999999,\n 48.629278127969414\n ],\n [\n -104.029541015625,\n 48.629278127969414\n ],\n [\n -104.029541015625,\n 47.956823800497475\n ],\n [\n -107.57812499999999,\n 47.956823800497475\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.84423828125,\n 41.054501963290505\n ],\n [\n -97.84423828125,\n 42.956422511073335\n ],\n [\n -95.78979492187499,\n 42.956422511073335\n ],\n [\n -95.78979492187499,\n 41.054501963290505\n ],\n [\n -97.84423828125,\n 41.054501963290505\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.08441162109374,\n 38.52668162061619\n ],\n [\n -93.08441162109374,\n 39.3024245604149\n ],\n [\n -91.67816162109375,\n 39.3024245604149\n ],\n [\n -91.67816162109375,\n 38.52668162061619\n ],\n [\n -93.08441162109374,\n 38.52668162061619\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201
Evidence indicates that competition with newly established barred owls (Strix varia) is causing rapid declines in populations of northern spotted owls (Strix occidentalis caurina), and that the longterm persistence of spotted owls may be in question without additional management intervention. A pilot study in California showed that lethal removal of barred owls in combination with habitat conservation may be able to slow or even reverse population declines of spotted owls at local scales, but it remains unknown whether similar results can be obtained in larger areas with different forest conditions and where barred owls are more abundant. In 2015, we implemented a before-after-controlimpact (BACI) experimental design on two study areas in Oregon and Washington with at least 20 years of pre-treatment demographic data on spotted owls to determine if removal of barred owls can improve population trends of spatially associated spotted owls. Here we provide an overview of our research accomplishments and preliminary results in Oregon and Washington in 2015.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161041","usgsCitation":"Wiens, J.D., Dugger, K.M., Lewicki, K.E., and Simon, D.C., 2016, Effects of experimental removal of barred owls on population demography of northern spotted owls in Washington and Oregon—2015 progress report: U.S. Geological Survey Open-File Report 2016-1041, 16 p., https://dx.doi.org/10.3133/ofr20161041.","productDescription":"iv, 16 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-072911","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":318862,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1041/ofr20161041.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1041"},{"id":318861,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1041/coverthb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.31054687499999,\n 49.023461463214126\n ],\n [\n -117.04833984375001,\n 49.023461463214126\n ],\n [\n -117.02636718749999,\n 46.31658418182218\n ],\n [\n -116.91650390625,\n 46.164614496897094\n ],\n [\n -116.89453125,\n 46.07323062540838\n ],\n [\n -117.02636718749999,\n 45.9511496866914\n ],\n [\n -116.71874999999999,\n 45.82879925192134\n ],\n [\n -116.49902343749999,\n 45.72152152227954\n ],\n [\n -116.52099609375,\n 45.537136680398596\n ],\n [\n -116.65283203124999,\n 45.30580259943578\n ],\n [\n -116.69677734375,\n 45.1510532655634\n ],\n [\n -116.8505859375,\n 44.98034238084973\n ],\n [\n -116.8505859375,\n 44.91813929958515\n ],\n [\n -117.04833984375001,\n 44.68427737181225\n ],\n [\n -117.158203125,\n 44.55916341529184\n ],\n [\n -117.20214843749999,\n 44.38669150215206\n ],\n [\n -117.158203125,\n 44.26093725039923\n ],\n [\n -116.91650390625,\n 44.213709909702054\n ],\n [\n -116.806640625,\n 44.071800467511565\n ],\n [\n -116.93847656250001,\n 43.929549935614595\n ],\n [\n -117.04833984375001,\n 43.73935207915473\n ],\n [\n -117.04833984375001,\n 41.96765920367816\n ],\n [\n -124.25537109375,\n 41.96765920367816\n ],\n [\n -124.45312499999999,\n 42.19596877629178\n ],\n [\n -124.49707031249999,\n 42.42345651793833\n ],\n [\n -124.43115234375,\n 42.569264372193864\n ],\n [\n -124.51904296875,\n 42.68243539838623\n ],\n [\n -124.60693359374999,\n 42.81152174509788\n ],\n [\n -124.43115234375,\n 43.229195113965005\n ],\n [\n -124.51904296875,\n 43.34116005412307\n ],\n [\n -124.29931640625,\n 43.40504748787035\n ],\n [\n -124.21142578125,\n 43.73935207915473\n ],\n [\n -124.21142578125,\n 44.402391829093915\n ],\n [\n -124.12353515624999,\n 44.762336674810996\n ],\n [\n -124.01367187499999,\n 45.19752230305685\n ],\n [\n -123.99169921875,\n 45.61403741135093\n ],\n [\n -124.01367187499999,\n 45.9511496866914\n ],\n [\n -123.99169921875,\n 46.13417004624326\n ],\n [\n -124.1455078125,\n 46.240651955001695\n ],\n [\n -124.16748046874999,\n 46.66451741754235\n ],\n [\n -124.21142578125,\n 46.93526088057719\n ],\n [\n -124.25537109375,\n 47.234489635299184\n ],\n [\n -124.43115234375,\n 47.39834920035926\n ],\n [\n -124.47509765625,\n 47.635783590864854\n ],\n [\n -124.73876953125,\n 47.945786463687185\n ],\n [\n -124.73876953125,\n 48.268569112964336\n ],\n [\n -124.73876953125,\n 48.516604348867475\n ],\n [\n -124.34326171874999,\n 48.45835188280866\n ],\n [\n -123.94775390625,\n 48.268569112964336\n ],\n [\n -123.59619140625001,\n 48.25394114463431\n ],\n [\n -123.33251953125,\n 48.25394114463431\n ],\n [\n -123.1787109375,\n 48.4146186174932\n ],\n [\n -123.31054687499999,\n 48.69096039092549\n ],\n [\n -123.06884765625,\n 48.76343113791796\n ],\n [\n -123.11279296875001,\n 48.850258199721495\n ],\n [\n -123.31054687499999,\n 49.023461463214126\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
U.S. Geological Survey National Oil and Gas Assessments (NOGA) of Albian aged clastic reservoirs in the U.S. Gulf Coast region indicate a relatively low prospectivity for undiscovered hydrocarbon resources due to high levels of past production and exploration. Evaluation of two assessment units (AUs), (1) the Albian Clastic AU 50490125, and (2) the Updip Albian Clastic AU 50490126, were based on a geologic model incorporating consideration of source rock, thermal maturity, migration, events timing, depositional environments, reservoir rock characteristics, and production analyses built on well and field-level production histories. The Albian Clastic AU is a mature conventional hydrocarbon prospect with undiscovered accumulations probably restricted to small faulted and salt-associated structural traps that could be revealed using high resolution subsurface imaging and from targeting structures at increased drilling depths that were unproductive at shallower intervals. Mean undiscovered accumulation volumes from the probabilistic assessment are 37 million barrels of oil (MMBO), 152 billion cubic feet of gas (BCFG), and 4 million barrels of natural gas liquids (MMBNGL). Limited exploration of the Updip Albian Clastic AU reflects a paucity of hydrocarbon discoveries updip of the periphery fault zones in the northern Gulf Coastal region. Restricted migration across fault zones is a major factor behind the small discovered fields and estimation of undiscovered resources in the AU. Mean undiscovered accumulation volumes from the probabilistic assessment are 1 MMBO and 5 BCFG for the Updip Albian Clastic AU.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161026","usgsCitation":"Merrill, M.D., 2016, Geologic assessment of undiscovered oil and gas resources in the Albian clastic and updip Albian clastic assessment units, U.S. Gulf Coast region: U.S. Geological Survey Open-File Report 2016–1026, 31 p., https://dx.doi.org/10.3133/ofr20161026.","productDescription":"Report: v, 27; Appendixes 1-2","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-038743","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":318712,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1026//ofr20161026.pdf","text":"Report","size":"2.90 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1026"},{"id":318714,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1026/ofr20161026_appendix2.pdf","text":"Appendix 2 - Basic Input Data for the Updip Albian Clastic Assessment Unit","size":"32.3 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1026"},{"id":318713,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1026/ofr20161026_appendix1.pdf","text":"Appendix 1 - Basic Input Data for the Albian Clastic Assessment Unit","size":"32.4 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1026"},{"id":318711,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1026/coverthb.jpg"}],"country":"United States","otherGeospatial":"Gulf Coast Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.71630859375,\n 24.307053283225915\n ],\n [\n -80.39794921875,\n 24.746831298412058\n ],\n [\n -80.04638671875,\n 25.50278454875533\n ],\n [\n -80.04638671875,\n 27.0982539061379\n 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U.S. Geological Survey
12201 Sunrise Valley Drive
MS 956 National Center
Reston, VA 20192
http://energy.usgs.gov/
http://energy.usgs.gov/GeneralInfo/
ScienceCenters/Eastern.aspx
Understanding the distribution of coal-bearing geologic units in Antarctica provides information that can be used in sedimentary, geomorphological, paleontological, and climatological studies. This report is a digital compilation of information on Antarctica’s coal-bearing geologic units found in the literature. It is intended to be used in small-scale spatial geographic information system (GIS) investigations and as a visual aid in the discussion of Antarctica’s coal resources or in other coal-based geologic investigations. Instead of using spatially insignificant point markers to represent large coal-bearing areas, this dataset uses polygons to represent actual coal-bearing lithologic units. Specific locations of coal deposits confirmed from the literature are provided in the attribution for the coal-bearing unit polygons. Coal-sample-location data were used to confirm some reported coal-bearing geology. The age and extent of the coal deposits indicated in the literature were checked against geologic maps ranging from local scale at 1:50,000 to Antarctic continental scale at 1:5,000,000; if satisfactory, the map boundaries were used to generate the polygons for the coal-bearing localities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161031","usgsCitation":"Merrill, M.D., 2016, GIS representation of coal-bearing areas in Antarctica: U.S. Geological Survey Open-File Report 2016–1031, \n3 p., https://dx.doi.org/10.3133/ofr20161031.","productDescription":"Report: iii, 3 p.; Zipped Shapefiles; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-063245","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":318710,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/of/2016/1031/ofr20161031.zip","text":"Zipped Shapefiles and metadata","size":"1.10 MB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 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U.S. Geological Survey
Mail Stop 956
12201 Sunrise Valley Drive
Reston, VA 20192
http://energy.usgs.gov/
The production and accessibility of geospatial information including Earth observation is changing greatly both technically and in terms of human participation. Advances in technology have changed the way that geospatial data are produced and accessed, resulting in more efficient processes and greater accessibility than ever before. Improved technology has also created opportunities for increased participation in the gathering and interpretation of data through crowdsourcing and citizen science efforts. Increased accessibility has resulted in greater participation in the use of data as prices for Government-produced data have fallen and barriers to access have been reduced.
\nThe increase in participation in the production and in the use of data, defined as data democracy for this workshop, are having great impacts on economics and more generally on society.
\nThere is also a strong drive by governments around the world, as shown by the G8 Declaration in June 2013, to make public sector information and scientific data more widely accessible. These are respectively termed “open data” and “open research data.”
\nThis report summarizes discussion at the Workshop on Assessing the Impact and Value of Open Geospatial Information held at George Washington University in Washington, D.C. in October 2014. Workshop participants examined the consequences of expanding data democracy with a focus on its socioeconomic impacts. Evaluations were presented of state-of-the-art methods to assess these socioeconomic impacts, which included position papers and remarks by discussants. The workshop included discussions about the following topics: (1) increased and expanded information sources; (2) societal impacts, including approaches to economics assessments; (3) constraints to open access, including the demands for return on investment, specifications of intellectual property rights, and privacy issues; and (4) learning from the experiences of other data-rich domains, such as environmental management, internet businesses, health, and transportation.
\nThe workshop was a working meeting with strong participant engagement, leading to recommendations for action. The meeting included five topic-driven sessions and keynote presentations. Precirculated position papers for each panel session facilitated preparation and remarks by discussants. After the position papers are updated following the discussants’ remarks, it is planned to submit them for publication.
\nThe workshop included 68 participants coming from international organizations, the U.S. public and private sectors, nongovernmental organizations, and academia. Participants included policy makers and analysts, financial analysts, economists, information scientists, geospatial practitioners, and other discipline experts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161036","collaboration":"Prepared in cooperation with the Socioeconomic Benefits Community","usgsCitation":"Pearlman, Francoise, Pearlman, Jay, Bernknopf, Richard, Coote, Andrew, Craglia, Massimo, Friedl, Lawrence, Gallo, Jason, Hertzfeld, Henry, Jolly, Claire, Macauley, Molly, Shapiro, Carl, and Smart, Alan, 2016, Assessing the socioeconomic impact and value of open geospatial information: U.S. Geological Survey Open-File Report 2016–1036, 36 p., https://dx.doi.org/10.3133/ofr20161036.","productDescription":"vi, 36 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":318802,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1036/coverthb.jpg"},{"id":318803,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1036/ofr20161036.pdf","text":"Report","size":"5.36 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1036"}],"otherGeospatial":"Global","contact":"U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
http://www.usgs.gov
Four commercially available ultraviolet nitrate spectrophotometric sensors were evaluated by the U.S. Geological Survey Hydrologic Instrumentation Facility (HIF) to determine the effects of suspended sediment concentration (SSC) and colored dissolved organic matter (CDOM) on sensor accuracy. The evaluated sensors were: the Hach NITRATAX plus sc (5-millimeters (mm) path length), Hach NITRATAX plus sc (2 mm), S::CAN Spectro::lyser (5 mm), and the Satlantic SUNA V2 (5 mm). A National Institute of Standards and Technology-traceable nitrate-free sediment standard was purchased and used to create the turbid environment, and an easily made filtered tea solution was used for the CDOM test. All four sensors performed well in the test that evaluated the effect of suspended sediment on accuracy. The Hach 5 mm, Hach 2 mm, and the SUNA V2 met their respective manufacturer accuracy specifications up to concentrations of 4,500 milligrams per liter (mg/L) SSC. The S::CAN failed to meet its accuracy specifications when the SSC concentrations exceeded 4,000 mg/L. Test results from the effect of CDOM on accuracy indicated a significant skewing of data from all four sensors and showed an artificial elevation of measured nitrate to varying amounts. Of the four sensors tested, the Satlantic SUNA V2’s accuracy was affected the least in the CDOM test. The nitrate concentration measured by the SUNA V2 was approximately 24 percent higher than the actual concentration when estimated total organic carbon values exceeded 44 mg/L. Measured nitrate concentration falsely increased 49 percent when measured by the Hach 5 mm, and 75 percent when measured by the Hach 2 mm. The S::CAN’s reported nitrate concentration increased 96 percent. Path length plays an important role in the sensor’s ability to compensate measurements for matrix interferences, but does not solely determine how well a sensor can handle all interferences. The sensor’s proprietary algorithms also play a key role in matrix interference compensation. The sensors’ ability to compensate for CDOM varied significantly during the tests, even among the three with 5-mm path lengths. Results of this evaluation suggest that the proprietary algorithms of the nitrate analyzers are more effective compensating for suspended sediment, and less effective compensating for CDOM (color) when sensor path length remains constant.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161014","usgsCitation":"Snazelle, T.T., 2016, The effect of suspended sediment and color on ultraviolet spectrophotometric nitrate sensors: U.S. Geological Survey Open-File Report, 2016−1014, 10 p., https://dx.doi.org/10.3133/ofr20161014.","productDescription":"Report: v,10 p.; Tables: 2-4","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064543","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":318658,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1014/ofr20161014.pdf","text":"Report","size":"1.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1014"},{"id":318676,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1014/table/ofr20161014_table4.xlsx","text":"Table 4 - Nitrate measurements by four ultraviolet sensors in water with a 5-mg-NL concentration with varying concentrations ofChief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
http://water.usgs.gov/hif/
An increase of groundwater withdrawals from the surficial aquifer system on Jekyll Island, Georgia, prompted an investigation of hydrologic conditions and water quality by the U.S. Geological Survey during October 2012 through December 2013. The study demonstrated the importance of rainfall as the island’s main source of recharge to maintain freshwater resources by replenishing the water table from the effects of hydrologic stresses, primarily evapotranspiration and pumping. Groundwater-flow directions, recharge, and water quality of the water-table zone on the island were investigated by installing 26 shallow wells and three pond staff gages to monitor groundwater levels and water quality in the water-table zone. Climatic data from Brunswick, Georgia, were used to calculate potential maximum recharge to the water-table zone on Jekyll Island. A weather station located on the island provided only precipitation data. Additional meteorological data from the island would enhance potential evapotranspiration estimates for recharge calculations.
\nGroundwater levels and specific-conductance measurements showed the dependence of freshwater resources on rainfall to recharge the water-table zone of the surficial aquifer system and to influence groundwater flow on Jekyll Island. The unseasonably dry conditions during November 2012 to April 2013 induced saline water infiltration to the water-table zone from the marshland separating the Jekyll River from the island. A strong correlation (R2 = 0.97) of specific conductance to chloride concentration in water samples from wells installed in the water-table zone provided support for the determination of seasonal directions of groundwater flow by confirming salinity changes in the water-table zone. Unseasonably wet conditions during the late spring to August caused groundwater-flow reversals in some areas. The high dependence of the water-table zone in the surficial aquifer system on precipitation to replenish the aquifer with freshwater underscored the importance of monitoring groundwater levels, water quality, and water use to identify aquifer-discharge conditions that have the potential to promote seawater encroachment and degrade freshwater resources on Jekyll Island.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161017","collaboration":"Prepared in cooperation with the Jekyll Island Authority","usgsCitation":"Gordon, D.W., and Torak, L.J., 2016, Hydrologic conditions, recharge, and baseline water quality of the surficial aquifer system at Jekyll Island, Georgia, 2012–13: U.S. Geological Survey Open-File Report 2016–1017, 34 p., https://dx.doi.org/10.3133/ofr20161017.","productDescription":"Report: viii, 34 p.; Appendixes: 1-3","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-055404","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":318637,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1017/coverthb.jpg"},{"id":318641,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1017/ofr20161017_appendix3.xlsx","text":"Appendix 3. Groundwater-Level Measurements Made onDirector, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
In a U.S. Geological Survey (USGS) study, recovery-factor estimates were calculated by using a publicly available reservoir simulator (CO2 Prophet) to estimate how much oil might be recovered with the application of a miscible carbon dioxide (CO2) enhanced oil recovery (EOR) method to technically screened oil reservoirs located in onshore and State offshore areas in the conterminous United States. A recovery factor represents the percentage of an oil reservoir’s original oil in place estimated to be recoverable by the application of a miscible CO2-EOR method. The USGS estimates were calculated for 2,018 clastic and 1,681 carbonate candidate reservoirs in the “Significant Oil and Gas Fields of the United States Database” prepared by Nehring Associates, Inc. (2012).
\nThis report presents distributions of estimated recovery factors organized by plays in seven U.S. regions. The distributional parameters for plays containing at least three candidate reservoirs are presented in tables, and parameters for plays containing at least six candidate reservoirs are presented in boxplots. Over all the reservoirs evaluated, 90 percent of the recovery-factor estimates for clastic reservoirs fell within the range from 8.7 to 16.2 percent, and the median value of the distribution was 9.5 percent. Similarly, 90 percent of the recovery-factor estimates for carbonate reservoirs were within the range from 11.8 to 27.5 percent, and the median value of the distribution was 13.6 percent. Both distributions were right skewed.
\nThe retention factor is the percentage of injected CO2 that is naturally retained in the reservoir. Retention factors were also estimated in this study. For clastic reservoirs, 90 percent of the estimated retention factors were between 21.7 and 32.1 percent, and for carbonate reservoirs, 90 percent were between 23.7 and 38.2 percent. The respective median values were 22.9 for clastic reservoirs and 26.1 for carbonate reservoirs. Both distributions were right skewed. The recovery and retention factors that were calculated are consistent with the corresponding factors reported in the literature.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151239","usgsCitation":"Attanasi, E.D., and Freeman, P.A., 2016, Play-level distributions of estimates of recovery factors for a miscible carbon dioxide enhanced oil recovery method used in oil reservoirs in the conterminous United States: U.S. Geological Survey Open-File Report 2015–1239, 36 p., https://dx.doi.org/10.3133/ofr20151239.","productDescription":"vii, 36 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-067608","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":318493,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1239/ofr20151239.pdf","text":"Report","size":"2.13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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\"}}]}\n","contact":"Eastern Energy Resources Science Center
U.S. Geological Survey
MS 956 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
http://energy.usgs.gov/GeneralInfo/
ScienceCenters/Eastern.aspx
The Navajo (N) aquifer is an extensive aquifer and the primary source of groundwater in the 5,400-square-mile Black Mesa area in northeastern Arizona. Availability of water is an important issue in northeastern Arizona because of continued water requirements for industrial and municipal use by a growing population and because of low precipitation in the arid climate of the Black Mesa area. Precipitation in the area typically is between 6 and 14 inches per year.
The U.S. Geological Survey water-monitoring program in the Black Mesa area began in 1971 and provides information about the long-term effects of groundwater withdrawals from the N aquifer for industrial and municipal uses. This report presents results of data collected as part of the monitoring program in the Black Mesa area from January 2012 to September 2013. The monitoring program includes measurements of (1) groundwater withdrawals, (2) groundwater levels, (3) spring discharge, (4) surface-water discharge, and (5) groundwater chemistry.
In calendar year 2012, total groundwater withdrawals were 4,010 acre-ft, industrial withdrawals were 1,370 acre-ft, and municipal withdrawals were 2,640 acre-ft. Total withdrawals during 2012 were about 45 percent less than total withdrawals in 2005 because of Peabody Western Coal Company’s discontinued use of water to transport coal in a coal slurry pipeline. From 2011 to 2012 total withdrawals decreased by 10 percent; industrial withdrawals decreased by approximately 1 percent, and total municipal withdrawals decreased by 15 percent.
From 2012 to 2013, annually measured water levels in the Black Mesa area declined in 6 of 16 wells that were available for comparison in the unconfined areas of the N aquifer, and the median change was 0.8 feet. Water levels declined in 5 of 16 wells measured in the confined area of the aquifer. The median change for the confined area of the aquifer was 0.3 feet. From the prestress period (prior to 1965) to 2013, the median water-level change for 34 wells in both the confined and unconfined areas was -13.5 feet; the median water-level changes were -0.8 feet for 16 wells measured in the unconfined areas and -51.0 feet for 16 wells measured in the confined area.
Spring flow was measured at four springs in 2013; Burro, Unnamed Spring near Dennehotso, Moenkopi School, and Pasture Canyon Springs. Flow fluctuated during the period of record for Burro and Unnamed Springs near Dennehotso, but a decreasing trend was apparent at Moenkopi School Spring and Pasture Canyon Spring. Discharge at Burro Spring has remained relatively constant since it was first measured in the 1980s and discharge at Unnamed Spring near Dennehotso has fluctuated for the period of record at each spring. Trend analysis for discharge at Moenkopi School and Pasture Canyon Springs showed a decreasing trend.
Continuous records of surface-water discharge in the Black Mesa area were collected from streamflow-gaging stations at the following sites: Moenkopi Wash at Moenkopi 09401260 (1976 to 2013), Dinnebito Wash near Sand Springs 09401110 (1993 to 2013), Polacca Wash near Second Mesa 09400568 (1994 to 2013), and Pasture Canyon Springs 09401265 (2004 to 2013). Median winter flows (November through February) from these sites for each water year were used as an index of the amount of groundwater discharge. For the period of record of each streamflow-gaging station, the median winter flows have generally remained constant, which suggests no change in groundwater discharge.
In 2013, water samples collected from 12 wells and 4 springs in the Black Mesa area were analyzed for selected chemical constituents, and the results were compared with previous analyses. Concentrations of dissolved solids, chloride, and sulfate have varied at all 12 wells for the period of record, but neither increasing nor decreasing trends over time were found. Dissolved solids, chloride, and sulfate concentrations increased at Moenkopi School Spring during the more than 13 years of record at that site. Concentrations of dissolved solids, chloride, and sulfate at Pasture Canyon Spring have not varied significantly since the early 1980s. Concentrations of dissolved solids, chloride, and sulfate at Burro Spring and Unnamed Spring near Dennehotso have varied for the period of record with no increasing or decreasing trend in the data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151221","collaboration":"Prepared in cooperation with the Bureau of Indian Affairs and the Arizona Department of Water Resources","usgsCitation":"Macy, J.P., and Truini, Margot, 2016, Groundwater, surface-water, and water-chemistry data, Black Mesa area, northeastern Arizona—2012–2013: U.S. Geological Survey Open-File Report 2015–1221, 43 p., https://dx.doi.org/10.3133/ofr20151221.","productDescription":"vi, 43 p.","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2012-01-01","ipdsId":"IP-059312","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":318423,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1221/coverthb.jpg"},{"id":318424,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1221/ofr20151221.pdf","text":"Report","size":"5.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1221 PDF"}],"country":"United States","state":"Arizona","otherGeospatial":"Black Mesa Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.3,\n 35.3\n ],\n [\n -111.3,\n 37\n ],\n [\n -109.3,\n 37\n ],\n [\n -109.3,\n 35.3\n ],\n [\n -111.3,\n 35.3\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/
We describe high-resolution gravity and seismic refraction surveys acquired to determine the thickness of valley-fill deposits and to delineate geologic structures that might influence groundwater flow beneath the Smoke Tree Wash area in Joshua Tree National Park. These surveys identified a sedimentary basin that is fault-controlled. A profile across the Smoke Tree Wash fault zone reveals low gravity values and seismic velocities that coincide with a mapped strand of the Smoke Tree Wash fault. Modeling of the gravity data reveals a basin about 2–2.5 km long and 1 km wide that is roughly centered on this mapped strand, and bounded by inferred faults. According to the gravity model the deepest part of the basin is about 270 m, but this area coincides with low velocities that are not characteristic of typical basement complex rocks. Most likely, the density contrast assumed in the inversion is too high or the uncharacteristically low velocities represent highly fractured or weathered basement rocks, or both. A longer seismic profile extending onto basement outcrops would help differentiate which scenario is more accurate. The seismic velocities also determine the depth to water table along the profile to be about 40–60 m, consistent with water levels measured in water wells near the northern end of the profile.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161027","usgsCitation":"Langenheim, V.E., Rymer, M.J., Catchings, R.D., Goldman, M.R., Watt, J.T., Powell, R.E., and Matti, J.C., 2016, High-resolution gravity and seismic-refraction surveys of the Smoke Tree Wash Area, Joshua Tree National Park, California: U.S. Geological Survey Open-File Report 2016–1027, 15 p., https://dx.doi.org/10.3133/ofr20161027.","productDescription":"Report: iii, 15 p.; Dataset; Metadata; Read Me","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070548","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":318441,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/of/2016/1027/ofr20161027_readme.txt","size":"4 KB","linkFileType":{"id":2,"text":"txt"}},{"id":318440,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2016/1027/ofr20161027_metadata.txt","size":"10 KB","linkFileType":{"id":2,"text":"txt"}},{"id":318439,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1027/ofr20161027.pdf","text":"Report","size":"700 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1027 Report PDF"},{"id":318438,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1027/coverthb.jpg"},{"id":318442,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/of/2016/1027/ofr20161027_iso_all.txt","text":"Gravity Data","size":"11 KB","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"California","otherGeospatial":"Joshua Tree National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.8745,\n 33.7498\n ],\n [\n -115.8745,\n 33.8402\n ],\n [\n -115.7667,\n 33.8402\n ],\n [\n -115.7667,\n 33.7498\n ],\n [\n -115.8745,\n 33.7498\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"GMEG staff, Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
http://geomaps.wr.usgs.gov/gmeg/
Agassiz’s desert tortoise, Gopherus agassizii, was considered a single species for 150 years after its discovery by James Cooper (1861), with a geographic range extending from southeastern California, southern Nevada, and southwestern Utah southward into northern Sinaloa, Mexico (Murphy and others, 2011). What was once G. agassizii is now recognized as a complex composed of three sister species, G. agassizii, G. morafkai, and G. evgoodei (Murphy and others, 2011; Edwards and others, 2016) (fig. 1). The geographic range of Agassiz’s Desert Tortoise (G. agassizii) is now limited to north and west of the Colorado River (Murphy and others, 2011), with the exception of a small population in northwestern Arizona (Edwards and others, 2015). This annotated bibliography is based on peer-reviewed journal articles published between January 1991 and December 2015 on Agassiz’s Desert Tortoise, with the geographic range as defined by Murphy and others (2011). Studies pertaining to other species of Gopherus (e.g., G. morafkai), were included only when associated with G. agassizii. In addition to articles pertaining directly to desert tortoises, we compiled articles concerning threats to desert tortoises and the habitats they occupy. Similarly, we only included studies that encompass other habitat types when they were directly compared with habitats of G. agassizii.
\nAgassiz’s Desert Tortoise (hereinafter called desert tortoise) is a state- and federally-listed threatened species (U.S. Fish and Wildlife Service, 1990; California Department of Fish and Game, 2015). The first population federally listed as threatened occurred on the Beaver Dam Slope, Utah (U.S. Fish and Wildlife Service, 1980). In 1990, the entire geographic range north and west of the Colorado River was federally listed as threatened (U.S. Fish and Wildlife Service, 1990), with the exception being a small population in northwestern Arizona. The purpose of this annotated bibliography is to support recovery efforts for the species, because populations have continued to decline in spite of designation of critical habitat and publication of a recovery plan (U.S. Fish and Wildlife Service, 1994). For example, between 2005 and 2014, populations in critical habitats declined about 50% (U.S. Fish and Wildlife Service, 2015).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161023","usgsCitation":"Berry, K.H., Lyren, L.M., Mack, J.S., Brand, L.A., and Wood, D.A., 2016, Desert tortoise annotated bibliography, 1991–2015: U.S. Geological Survey Open-File Report 2016-1023, 312 p., https://dx.doi.org/10.3133/ofr20161023.","productDescription":"iv, 312 p.","numberOfPages":"320","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071164","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":318474,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1023/ofr20161023.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1023"},{"id":318473,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1023/coverthb.jpg"}],"contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
http://www.werc.usgs.gov/
Lake Spokane, locally referred to as Long Lake, is a 24-mile-long section of the Spokane River impounded by Long Lake Dam that has, in recent decades, experienced water-quality problems associated with eutrophication. Consumption of oxygen by the decomposition of aquatic plants that have proliferated because of high nutrient concentrations has led to seasonally low dissolved oxygen concentrations in the lake. Of nitrogen and phosphorus, the two primary nutrients necessary for aquatic vegetation growth, phosphorus was previously identified as the limiting nutrient that regulates the growth of aquatic plants and, thus, dissolved oxygen concentrations in Lake Spokane. Phosphorus is delivered to Lake Spokane from municipal and industrial point-source inputs to the Spokane River upstream of Lake Spokane, but is also conveyed by groundwater and surface water from nonpoint-sources including septic tanks, agricultural fields, and wildlife. In response, the Washington State Department of Ecology listed Lake Spokane on the 303(d) list of impaired water bodies for low dissolved oxygen concentrations and developed a Total Maximum Daily Load for phosphorus in 1992, which was revised in 2010 because of continuing algal blooms and water-quality concerns.
This report evaluates the concentrations of phosphorus and nitrogen in shallow groundwater discharging to Lake Spokane to determine if a difference exists between nutrient concentrations in groundwater discharging to the lake downgradient of residential development with on-site septic systems and downgradient of undeveloped land without on-site septic systems. Elevated nitrogen isotope values (δ15N) within the roots of aquatic vegetation were used as an indicator of septic-system derived nitrogen. δ15N values were measured in August and September 2014 downgradient of residential development near the lakeshore, of residential development on 300-ft-high terraces above the lake, and of undeveloped land in the eastern (upper) and central (lower) parts of Lake Spokane. Significantly lower δ15N values were measured within aquatic vegetation downgradient of undeveloped land in eastern Lake Spokane relative to both near-shore and terrace residential development land uses. Conversely, significantly higher δ15N values were measured downgradient of undeveloped land in central Lake Spokane relative to the two developed land uses. These results guided the location of subsequent groundwater sampling in March and April 2015 from 30 shallow piezometers driven into the near-shore area of Lake Spokane. Nitrate plus nitrite concentrations in groundwater discharging to Lake Spokane downgradient of undeveloped areas were significantly lower than those measured downgradient of both near-shore and terrace residential development. Orthophosphate concentrations in groundwater were not significantly different with respect to upgradient land use.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161029","collaboration":"Prepared in cooperation with the Washington State Department of Ecology","usgsCitation":"Gendaszek, A.S., Cox, S.E., and Spanjer, A.R., 2016, Preliminary characterization of nitrogen and phosphorus in groundwater discharging to Lake Spokane, northeastern Washington, using stable nitrogen isotopes: U.S. Geological Survey Open-File Report 2016-1029, 22 p., https://dx.doi.org/10.3133/ofr20161029.","productDescription":"vi, 22 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068545","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":318436,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1029/ofr20161029.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1029 PDF"},{"id":318435,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1029/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Lake Spokane","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.83935546874999,\n 47.77694420640404\n ],\n [\n -117.83935546874999,\n 47.897930761804936\n ],\n [\n -117.53002166748047,\n 47.897930761804936\n ],\n [\n -117.53002166748047,\n 47.77694420640404\n ],\n [\n -117.83935546874999,\n 47.77694420640404\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
The Landscape Fire and Resource Management Planning Tools (LANDFIRE) 2010 data release provides updated and enhanced vegetation, fuel, and fire regime layers consistently across the United States. The data represent landscape conditions from approximately 2010 and are the latest release in a series of planned updates to maintain currency of LANDFIRE data products. Enhancements to the data products included refinement of urban areas by incorporating the National Land Cover Database 2006 land cover product, refinement of agricultural lands by integrating the National Agriculture Statistics Service 2011 cropland data layer, and improved wetlands delineations using the National Land Cover Database 2006 land cover and the U.S. Fish and Wildlife Service National Wetlands Inventory data. Disturbance layers were generated for years 2008 through 2010 using remotely sensed imagery, polygons representing disturbance events submitted by local organizations, and fire mapping program data such as the Monitoring Trends in Burn Severity perimeters produced by the U.S. Geological Survey and the U.S. Forest Service. Existing vegetation data were updated to account for transitions in disturbed areas and to account for vegetation growth and succession in undisturbed areas. Surface and canopy fuel data were computed from the updated vegetation type, cover, and height and occasionally from potential vegetation. Historical fire frequency and succession classes were also updated. Revised topographic layers were created based on updated elevation data from the National Elevation Dataset. The LANDFIRE program also released a new Web site offering updated content, enhanced usability, and more efficient navigation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161010","usgsCitation":"Nelson, K.J., Long, D.G., and Connot, J.A., 2016, LANDFIRE 2010—Updates to the national dataset to support improved fire and natural resource management: U.S. Geological Survey Open-File Report, 2016–1010, 48 p, https://dx.doi.org/10.3133/ofr20161010. ","productDescription":"x, 48 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063923","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":318398,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1010/ofr20161010.pdf","text":"Report","size":"3.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1010"},{"id":318397,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1010/coverthb.jpg"}],"contact":"Director, U.S. Geological Survey
Earth Resources Observation and Science (EROS) Center
47914 252nd Street
Sioux Falls, SD 57198-0001
The Altoona Water Authority (AWA) obtains all of its water supply from headwater streams that drain western Blair County, an area underlain in part by black shale of the Marcellus Formation. Development of the shale-gas reservoirs will require new access roads, stream crossing, drill-pad construction, and pipeline installation, activities that have the potential to alter existing stream channel morphology, increase runoff and sediment supply, alter streamwater chemistry, and affect aquatic habitat. The U.S. Geological Survey, in cooperation with Altoona Water Authority and Blair County Conservation District, investigated the water quality of 12 headwater streams and biotic health of 10 headwater streams.
\nChannel morphology was characterized at 10 of 12 stream sites using 500-foot (minimum) longitudinal profiles, four cross-sections each, and pebble counts. Channel slopes ranged from 0.008 in Poplar Run near Newry to 0.045 in Mill Run. In general, streams draining watersheds of 5 square miles or less and at higher elevation had the steepest slopes. On the basis of the median particle size, determined during pebble counts, the streambed substrate can be characterized as cobble (Mill Run, Bells Gap Run, Tipton Run, and Sink Run), a mix of gravel and cobble (South Poplar Run, Dry Gap Run, Glenwhite Run, Sugar Run, Blair Gap Run), and gravel (Poplar Run, Newry).
\nDaily mean values of gage height were determined, and continuous (30-minute interval) data consisting of specific conductance and water temperature were collected, at four sites; each site showed typical seasonal fluctuations and the effects of precipitation.
\nStreamflow affected discrete water-quality. Dissolved oxygen always increased with increased streamflow. Most cations (including barium and strontium), along with pH, specific conductance, and total dissolved solids, decreased with greater streamflow, reflecting the dilution effect of moderately acidic surface runoff and precipitation on groundwater discharge (base flow) into the stream channels. Concentrations of trace elements varied by constituent and streamflow.
\nOn the basis of the results of water-quality analyses for the selected constituents, the water quality in 9 of the 12 streams can be considered fair or attaining with no measured constituent exceeding a U.S. Environmental Protection Agency maximum or secondary contaminant level. Abandoned mine drainage (AMD) affects Glenwhite Run, Blair Gap Run, and Sugar Run. For Sugar Run, the AMD is reflected in the elevated iron concentration (greater than 300 micrograms per liter). Manganese concentrations greater than 50 micrograms per liter were measured in Glenwhite Run, Sugar Run, and Blair Gap Run.
\nA mixing curve based upon chloride/bromide ratios for two end points—precipitation and deicing salts—indicate that deicing salt is migrating to the streams. A similar curve representative of late-emerging flowback water from Marcellus gas wells indicated that the surface-water samples had not been influenced by such brines.
\nOn the basis of the concentration of major ions, the streams in the study area generally had mixed cation and anion compositions. Calcium is the dominant cation in one stream. Carbonate and bicarbonate are the dominant anions for two streams, and sulfate is dominant in three streams. The remaining six streams do not have a dominant ion.
\nBiotic health was characterized at 10 of 12 stream sites; the two sites excluded were established late in the study period (May 2013) for refinement of water quality in the headwaters of Poplar Run and the location of Marcellus Formation gas wells. On the basis of the Maryland Index of Biotic Integrity (MdIBI) for fish assemblages, 8 of 10 streams can be considered in fair health. Tipton Run had the highest MdIBI score (3.75) and the greatest number of native species. South Poplar Run had the lowest MdIBI score (1.75); pollution tolerant blacknose dace was dominant. On the basis of the Pennsylvania Department of Environmental Protection macroinvertebrate index of biotic integrity, 9 of 10 streams were characterized as attaining, with scores as high as 88.9 at Tipton Run. Only Sugar Run was characterized as impaired, with a score of 40.4.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151173","collaboration":"Prepared in cooperation with the Altoona Water Authority and the Blair County Conservation District","usgsCitation":"Low, D.J., Brightbill, R.A., Eggleston, H.L., and Chaplin, J.J., 2016, Physical, chemical, and biological characteristics of selected headwater streams along the Allegheny Front, Blair County, Pennsylvania, July 2011–September 2013: U.S. Geological Survey Open-File Report 2015–1173, 66 p., https://dx.doi.org/10.3133/ofr20151173.","productDescription":"Report: viii, 66 p.; Appendixes 1-3","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059743","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":314565,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1173/ofr20151173.pdf","text":"Report","size":"3.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1173"},{"id":314564,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1173/coverthb.jpg"},{"id":314566,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1173/ofr20151173_appendix1-surfacewaterquality.xlsx","text":"Appendix 1 - Surface Water Quality","size":"145 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2015-1173"},{"id":314567,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1173/ofr20151173_appendix2-fishassemblages.xlsx","text":"Appendix 2 - Fish Assemblages","size":"92.6 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2015-1173"},{"id":314568,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1173/ofr20151173_appendix3-ibiscore.xlsx","text":"Appendix 3 - Index of Biotic Integrity","size":"21.1 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2015-1173"}],"country":"United States","state":"Pennsylvania","county":"Blair County","otherGeospatial":"Allegheny Front","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.35861206054688,\n 40.73581157695217\n ],\n [\n -78.21578979492188,\n 40.677513627085034\n ],\n [\n -78.45474243164062,\n 40.24913603826261\n ],\n [\n -78.62777709960938,\n 40.32665496008367\n ],\n [\n -78.35861206054688,\n 40.73581157695217\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
http://pa.water.usgs.gov/
Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. By recognizing the spatial differences in the capacities and potentials of ecosystems, ecoregions stratify the environment by its probable response to disturbance (Bryce and others, 1999). These general purpose regions are critical for structuring and implementing ecosystem management strategies across Federal agencies, State agencies, and nongovernment organizations that are responsible for different types of resources in the same geographical areas (Omernik and others, 2000).
The approach used to compile this map is based on the premise that ecological regions are hierarchical and can be identified through the analysis of the spatial patterns and the composition of biotic and abiotic phenomena that affect or reflect differences in ecosystem quality and integrity (Wiken, 1986; Omernik, 1987, 1995). These phenomena include geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another regardless of the hierarchical level. A Roman numeral hierarchical scheme has been adopted for different levels of ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997, map revised 2006). At level III, the continental United States contains 105 ecoregions and the conterminous United States has 85 ecoregions (U.S. Environmental Protection Agency, 2013). Level IV, depicted here for California, is a further refinement of level III ecoregions. Explanations of the methods used to define these ecoregions are given in Omernik (1995), Omernik and others (2000), and Omernik and Griffith (2014).
California has great ecological and biological diversity. The State contains offshore islands and coastal lowlands, large alluvial valleys, forested mountain ranges, deserts, and various aquatic habitats. There are 13 level III ecoregions and 177 level IV ecoregions in California and most continue into ecologically similar parts of adjacent States of the United States or Mexico (Bryce and others, 2003; Thorson and others, 2003; Griffith and others, 2014).
The California ecoregion map was compiled at a scale of 1:250,000. It revises and subdivides an earlier national ecoregion map that was originally compiled at a smaller scale (Omernik, 1987; U.S. Environmental Protection Agency, 2013). This poster is the result of a collaborative project primarily between U.S. Environmental Protection Agency (USEPA) Region IX, USEPA National Health and Environmental Effects Research Laboratory (Corvallis, Oregon), California Department of Fish and Wildlife (DFW), U.S. Department of Agriculture (USDA)–Natural Resources Conservation Service (NRCS), U.S. Department of the Interior–Geological Survey (USGS), and other State of California agencies and universities.
The project is associated with interagency efforts to develop a common framework of ecological regions (McMahon and others, 2001). Reaching that objective requires recognition of the differences in the conceptual approaches and mapping methodologies applied to develop the most common ecoregion-type frameworks, including those developed by the USDA–Forest Service (Bailey and others, 1994; Miles and Goudy, 1997; Cleland and others, 2007), the USEPA (Omernik 1987, 1995), and the NRCS (U.S. Department of Agriculture–Soil Conservation Service, 1981; U.S. Department of Agriculture–Natural Resources Conservation Service, 2006). As each of these frameworks is further refined, their differences are becoming less discernible. Regional collaborative projects such as this one in California, where some agreement has been reached among multiple resource-management agencies, are a step toward attaining consensus and consistency in ecoregion frameworks for the entire nation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161021","collaboration":"Prepared in collaboration with U.S. Environmental Protection Agency, Region IX, Regional Applied Research Effort (RARE) program.","usgsCitation":"Griffith, G.E., Omernik, J.M., Smith, D.W., Cook, T.D.,\nTallyn, E., Moseley, K., and Johnson, C.B., 2016, Ecoregions of California (poster):\nU.S. Geological Survey Open-File Report 2016–1021, with map, scale 1:1,100,000,\nhttps://dx.doi.org/10.3133/ofr20161021.","productDescription":"2 Sheets: 36.00 x 47.00 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057004","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":318343,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1021/ofr20161021_sheet1.pdf","text":"Sheet 1 - Map","size":"21 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\"}}]}","contact":"Western Geographic Science Center
U.S. Geological Survey
345 Middlefield Road, MS 531
Menlo Park, CA 94025
http://geography.wr.usgs.gov/
Heavy rainfall occurred across South Carolina during October 1–5, 2015, as a result of an upper atmospheric low-pressure system that funneled tropical moisture from Hurricane Joaquin into the State. The storm caused major flooding in the central and coastal parts of South Carolina. Almost 27 inches of rain fell near Mount Pleasant in Charleston County during this period. U.S. Geological Survey (USGS) streamgages recorded peaks of record at 17 locations, and 15 other locations had peaks that ranked in the top 5 for the period of record. During the October 2015 flood event, USGS personnel made about 140 streamflow measurements at 86 locations to verify, update, or extend existing rating curves (which are used to compute streamflow from monitored river stage). Immediately after the storm event, USGS personnel documented 602 high-water marks, noting the location and height of the water above land surface. Later in October, 50 additional high-water marks were documented near bridges for South Carolina Department of Transportation. Using a subset of these high-water marks, 20 flood-inundation maps of 12 communities were created. Digital datasets of the inundation area, modeling boundary, and water depth rasters are all available for download.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161019","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Musser, J.W., Watson, K.M., Painter, J.A., and Gotvald, A.J., 2016, Flood-inundation maps of selected areas affected by the flood of October 2015 in central and coastal South Carolina: U.S. Geological Survey Open-File Report 2016–1019, 81 p., https://dx.doi.org/10.3133/ofr20161019.","productDescription":"Report: v, 81 p.; Raw Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072657","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":318176,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1019/ofr20161019.pdf","text":"Report","size":"47.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1019"},{"id":318175,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1019/coverthb.jpg"},{"id":318184,"rank":3,"type":{"id":19,"text":"Raw Data"},"url":"https://water.usgs.gov/floods/events/2015/Joaquin/data_ofr20161019","text":"USGS Flood Information (Data Download)"}],"country":"United States","state":"South Carolina","otherGeospatial":"Salkehatchie River Basin, Savannah River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.541259765625,\n 33.86129311351553\n ],\n [\n -78.64013671875,\n 33.76088200086917\n ],\n [\n -78.94775390625,\n 33.61461929233378\n ],\n [\n -79.1015625,\n 33.348884792201694\n ],\n [\n -79.1455078125,\n 33.22030778968541\n ],\n [\n -79.34326171875,\n 32.99945000822837\n ],\n [\n -79.530029296875,\n 32.96258644191747\n ],\n [\n -79.60693359375,\n 32.85190345738802\n ],\n [\n -79.815673828125,\n 32.74108223150125\n ],\n [\n -80.057373046875,\n 32.55607364492029\n ],\n [\n -80.2880859375,\n 32.491230287947594\n ],\n [\n -80.386962890625,\n 32.41706632846282\n ],\n [\n -80.474853515625,\n 32.287132632616384\n ],\n [\n -80.628662109375,\n 32.175612478499346\n ],\n [\n -80.7275390625,\n 32.06395559466043\n ],\n [\n -80.85937499999999,\n 31.942839972853083\n ],\n [\n -80.936279296875,\n 31.99875937194732\n ],\n [\n -81.123046875,\n 32.12910537866886\n ],\n [\n -81.14501953125,\n 32.25926542645936\n ],\n [\n -81.14501953125,\n 32.36140331527543\n ],\n [\n -81.2548828125,\n 32.44488496716713\n ],\n [\n -81.298828125,\n 32.537551746769\n ],\n [\n -81.375732421875,\n 32.58384932565662\n ],\n [\n -81.4306640625,\n 32.685619853722\n ],\n [\n -81.474609375,\n 32.879587173066305\n ],\n [\n -81.507568359375,\n 33.00866349457558\n ],\n [\n -81.58447265624999,\n 33.073130945006625\n ],\n [\n -81.71630859375,\n 33.146750228776455\n ],\n [\n -81.815185546875,\n 33.23868752757414\n ],\n [\n -81.88110351562499,\n 33.32134852669881\n ],\n [\n -81.990966796875,\n 33.37641235124676\n ],\n [\n -81.947021484375,\n 33.458942753687644\n ],\n [\n -82.078857421875,\n 33.568861182555544\n ],\n [\n -82.166748046875,\n 33.642062504753675\n ],\n [\n -82.19970703125,\n 33.715201644740844\n ],\n [\n -82.28759765625,\n 33.80653802509606\n ],\n [\n -82.430419921875,\n 33.897777013859475\n ],\n [\n -82.55126953124999,\n 34.00713506435885\n ],\n [\n -82.496337890625,\n 34.17999758688084\n ],\n [\n -82.254638671875,\n 34.75966612466248\n ],\n [\n -81.947021484375,\n 35.11990857099681\n ],\n [\n -81.837158203125,\n 35.191766965947394\n ],\n [\n -81.39770507812499,\n 35.16482750605027\n ],\n [\n -81.046142578125,\n 35.146862906756304\n ],\n [\n -81.024169921875,\n 35.074964853989556\n ],\n [\n -80.91430664062499,\n 35.110921809704756\n ],\n [\n -80.771484375,\n 34.95799531086792\n ],\n [\n -80.782470703125,\n 34.84987503195418\n ],\n [\n -80.5517578125,\n 34.831841149828676\n ],\n [\n -80.255126953125,\n 34.804782919572425\n ],\n [\n -79.716796875,\n 34.82282272723702\n ],\n [\n -78.541259765625,\n 33.86129311351553\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
This report contains reduced 40Ar/39Ar geochronological data from 63 hydrothermal white mica samples separated from orogenic gold-rich quartz veins in the Laramide Caborca orogenic gold belt (COGB) of northwestern Sonora, Mexico. The main objective of this report is to present the sample locations, 40Ar/39Ar experimental methodology, and 40Ar/39Ar isotopic data. We include age spectra and inverse-isotope correlation diagrams for all white mica samples. The age spectra are separated into three groups based on the type of age used for geologic interpretation, including plateau ages (group 1), isochron ages (group 2), and average or single-step heating ages (group 3). The resulting age spectra are used to help establish the age of mineralization for the COGB.
\nThe COGB is approximately 600 kilometers long and 60 to 80 km wide, trends northwest, and extends from west-central Sonora to southern Arizona and California. The COGB contains mineralized gold-rich quartz veins that contain free gold associated with white mica (sericite), carbonate minerals (calcite and ankerite), and sulfides such as pyrite and galena. Limited geochronologic studies exist for parts of the COGB, and previous work was concentrated in mining districts. These previous studies recorded mineralization ages of approximately 70 to 40 Ma. Therefore, some workers proposed that the orogenic gold mineralization in the region occurred during a single pulse that was associated with the Laramide Orogeny that took place during the Cretaceous to early Eocene in the western margin of North America. However, the geochronologic dataset was quite limited, making any regional interpretations tenuous. Accordingly, one of the objectives of this geochronology study was to get a better representative sampling of the COGB in order to obtain a more complete record of the mineralization history. The 63 samples presented in this work are broadly distributed throughout the area of the COGB and allow us to better test the hypothesis that mineralization occurred in a single pulse.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161008","usgsCitation":"Izaguirre, Aldo, Kunk, M.J., Iriondo, Alexander, McAleer, Ryan, Caballero-Martínez, J.A, and Espinosa Arámburu, Enrique, 2016, The Laramide Caborca orogenic gold belt of northwestern Sonora, Mexico; white mica 40Ar/39Ar geochronology from gold-rich quartz veins: U.S. Geological Survey Open-File Report 2016–1008, 30 p., https://dx.doi.org/10.3133/ofr20161008.","productDescription":"Report: iv, 30 p.; 4 Tables","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069619","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":316618,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1008/ofr20161008_table4.xls","text":"Table 4 - 40Ar/39Ar step-heating data and average or single step ages determined from white micas of gold-rich quartz veins","size":"165 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1008","linkHelpText":"of the Caborca orogenic gold belt (COGB), northwestern Sonora, Mexico"},{"id":316609,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1008/coverthb.jpg"},{"id":316610,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1008/ofr20161008.pdf","text":"Report","size":"1.68 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1008"},{"id":316615,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1008/ofr20161008_table1.xls","text":"Table 1 - Summary of 63 40Ar/39Ar ages determined from white micas of gold-rich quartz veins","size":"718 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1008","linkHelpText":"of the Caborca orogenic gold belt (COGB), northwestern Sonora, Mexico"},{"id":316616,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1008/ofr20161008_table2.xls","text":"Table 2 - 40Ar/39Ar step-heating data and plateau ages determined from white micas of gold-rich quartz veins","size":"106 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1008","linkHelpText":"of the Caborca orogenic gold belt (COGB), northwestern Sonora, Mexico"},{"id":316617,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1008/ofr20161008_table3.xls","text":"Table 3 - 40Ar/39Ar step-heating data and isochron ages determined from white micas of gold-rich quartz veins","size":"95 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1008","linkHelpText":"of the Caborca orogenic gold belt (COGB), northwestern Sonora, Mexico."}],"country":"Mexico, United States","state":"Arizona, California, Sonora","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.82910156249999,\n 34.125447565116126\n ],\n [\n -114.36767578124999,\n 34.052659421375964\n ],\n [\n -113.48876953125,\n 33.687781758439364\n ],\n [\n -112.236328125,\n 32.41706632846282\n ],\n [\n -111.70898437499999,\n 31.653381399664\n ],\n [\n -111.3134765625,\n 31.071755902820108\n ],\n [\n -110.32470703125,\n 30.259067203213018\n ],\n [\n -110.12695312499999,\n 29.76437737516313\n ],\n [\n -110.01708984374999,\n 28.94086176940554\n ],\n [\n -109.97314453125,\n 28.478348692223165\n ],\n [\n -109.97314453125,\n 28.09136628140692\n ],\n [\n -110.19287109375,\n 27.877928333679495\n ],\n [\n -110.654296875,\n 28.05259082333986\n ],\n [\n -110.9619140625,\n 28.130127737874005\n ],\n [\n -111.533203125,\n 28.536274512989916\n ],\n [\n -112.06054687499999,\n 28.863918426224537\n ],\n [\n -112.54394531249999,\n 29.49698759653577\n ],\n [\n -113.09326171875,\n 30.486550842588485\n ],\n [\n -113.7744140625,\n 31.16580958786196\n ],\n [\n -114.60937499999999,\n 31.50362930577303\n ],\n [\n -115.224609375,\n 32.39851580247402\n ],\n [\n -115.3564453125,\n 33.90689555128866\n ],\n [\n -114.82910156249999,\n 34.125447565116126\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate Science Center
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12201 Sunrise Valley Drive
Reston, VA 20192
http://geology.er.usgs.gov/egpsc
The model presented in this report is a spreadsheet-based model using Visual Basic for Applications within Microsoft Excel (http://dx.doi.org/10.5066/F7057D0Z) prepared in cooperation with the U.S. Army Corps of Engineers and U.S. Fish and Wildlife Service. It uses the same model structure and, initially, parameters as used by Wildhaber and others (2015) for pallid sturgeon. The difference between the model structure used for this report and that used by Wildhaber and others (2015) is that variance is not partitioned. For the model of this report, all variance is applied at the iteration and time-step levels of the model. Wildhaber and others (2015) partition variance into parameter variance (uncertainty about the value of a parameter itself) applied at the iteration level and temporal variance (uncertainty caused by random environmental fluctuations with time) applied at the time-step level. They included implicit individual variance (uncertainty caused by differences between individuals) within the time-step level.
The interface developed for the model of this report is designed to allow the user the flexibility to change population model structure and parameter values and uncertainty separately for every component of the model. This flexibility makes the modeling tool potentially applicable to any fish species; however, the flexibility inherent in this modeling tool makes it possible for the user to obtain spurious outputs. The value and reliability of the model outputs are only as good as the model inputs. Using this modeling tool with improper or inaccurate parameter values, or for species for which the structure of the model is inappropriate, could lead to untenable management decisions. By facilitating fish population modeling, this modeling tool allows the user to evaluate a range of management options and implications. The goal of this modeling tool is to be a user-friendly modeling tool for developing fish population models useful to natural resource managers to inform their decision-making processes; however, as with all population models, caution is needed, and a full understanding of the limitations of a model and the veracity of user-supplied parameters should always be considered when using such model output in the management of any species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161009","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers and U.S. Fish and Wildlife Service","usgsCitation":"Moran, E.H., Wildhaber, M.L., Green, N.S., and Albers, J.L., 2016, Visual basic, Excel-based fish population modeling tool—The pallid sturgeon example: U.S. Geological Survey Open-File Report 2016–1009, 20 p., https://dx.doi.org/10.3133/ofr20161009.","productDescription":"vi, 20 p.","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066994","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":316871,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1009/coverthb.jpg"},{"id":316872,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1009/ofr20161009.pdf","text":"Report","size":"17.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1009"},{"id":316917,"rank":3,"type":{"id":4,"text":"Application Site"},"url":"https://dx.doi.org/10.5066/F7057D0Z","text":"http://dx.doi.org/10.5066/F7057D0Z","description":"Microsoft Visual Basic for Applications"}],"contact":"Director, Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201-8709
Scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center conducted a seasonal collection of surficial sediments from Chincoteague Bay and Tom's Cove, between Assateague Island and the Delmarva Peninsula in late March/early April 2014 and October 2014. The sampling efforts were part of a larger U.S. Geological Survey study to assess the effects of storm events on sediment distribution in back-barrier environments of the United States. By sampling during the spring and fall, a more complete understanding of seasonal variability in the area can help determine baseline conditions. The objective of this study was to characterize the sediments of Chincoteague Bay in order to create baseline conditions to incorporate with the hydrodynamic and sediment transport models used to evaluate pre- and post-storm change and compare with future field measurements.
\nThis report is an archive for sedimentological data derived from the surface sediment of Chincoteague Bay. Data are available for the spring (March/April 2014) and fall (October 2014) samples collected. Downloadable data are provided as Excel spreadsheets and as JPEG files. Additional files include ArcGIS shapefiles of the sampling sites, detailed results of sediment grain-size analyses, and formal Federal Geographic Data Committee metadata (data downloads).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151219","usgsCitation":"Ellis, A.M., Marot, M.E., Wheaton, C.J., Bernier, J.C., and Smith, C.G., 2015, A seasonal comparison of surface sediment characteristics in Chincoteague Bay, Maryland and Virginia, USA: U.S. Geological Survey Open-File Report 2015-1219, https://dx.doi.org/10.3133/ofr20151219.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065701","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":315341,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1219","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2015-1219"},{"id":316535,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chincoteague Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.19317626953125,\n 38.28778081436419\n ],\n [\n -75.50628662109375,\n 37.88677656291023\n ],\n [\n -75.3717041015625,\n 37.83364941345968\n ],\n [\n -75.17532348632812,\n 38.09241741843045\n ],\n [\n -75.09292602539062,\n 38.272688535980976\n ],\n [\n -75.19317626953125,\n 38.28778081436419\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
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Surface-water supplies are important sources of drinking water for residents in the Triangle area of North Carolina, which is located within the upper Cape Fear and Neuse River Basins. Since 1988, the U.S. Geological Survey and a consortium of local governments have tracked water-quality conditions and trends in several of the area’s water-supply lakes and streams. This report summarizes data collected through this cooperative effort, known as the Triangle Area Water Supply Monitoring Project, during October 2009 through September 2010 (water year 2010) and October 2010 through September 2011 (water year 2011). Major findings for this data-collection effort include
\nDirector, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
The Integrated Landscape Modeling (ILM) partnership is an effort by the U.S. Geological Survey (USGS) and U.S. Department of Agriculture (USDA) to identify, evaluate, and develop models to quantify services derived from ecosystems, with a focus on wetland ecosystems and conservation effects. The ILM partnership uses the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) modeling platform to facilitate regional quantifications of ecosystem services under various scenarios of land-cover change that are representative of differing conservation program and practice implementation scenarios. To date, the ILM InVEST partnership has resulted in capabilities to quantify carbon stores, amphibian habitat, plant-community diversity, and pollination services. Work to include waterfowl and grassland bird habitat quality is in progress. Initial InVEST modeling has been focused on the Prairie Pothole Region (PPR) of the United States; future efforts might encompass other regions as data availability and knowledge increase as to how functions affecting ecosystem services differ among regions.
The ILM partnership is also developing the capability for field-scale process-based modeling of depressional wetland ecosystems using the Agricultural Policy/Environmental Extender (APEX) model. Progress was made towards the development of techniques to use the APEX model for closed-basin depressional wetlands of the PPR, in addition to the open systems that the model was originally designed to simulate. The ILM partnership has matured to the stage where effects of conservation programs and practices on multiple ecosystem services can now be simulated in selected areas. Future work might include the continued development of modeling capabilities, as well as development and evaluation of differing conservation program and practice scenarios of interest to partner agencies including the USDA’s Farm Service Agency (FSA) and Natural Resources Conservation Service (NRCS). When combined, the ecosystem services modeling capabilities of InVEST and the process-based abilities of the APEX model should provide complementary information needed to meet USDA and the Department of the Interior information needs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161006","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service and Farm Service Agency","usgsCitation":"Mushet, D.M., and Scherff, E.J., 2016, The integrated landscape modeling partnership—Current status and future directions (ver. 1.1, December 2016): U.S. Geological Survey Open-File Report 2016–1006, 59 p., https://dx.doi.org/10.3133/ofr20161006.","productDescription":"72 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070297","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":314982,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1006/coverthb1.1.jpg"},{"id":332701,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2016/1006/version_history.txt"},{"id":314983,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1006/ofr20161006.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1006"}],"country":"United States","state":"Iowa, Minnesota, Nebraska, North Dakota, South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.82080078125,\n 48.99463598353408\n ],\n [\n -105.13916015625,\n 48.90805939965008\n ],\n [\n -104.83154296875,\n 48.44377831058805\n ],\n [\n -104.4140625,\n 47.945786463687185\n ],\n [\n -103.18359375,\n 47.87214396888731\n ],\n [\n -102.39257812499999,\n 47.502358951968596\n ],\n [\n -101.29394531249999,\n 47.010225655683485\n ],\n [\n -101.0302734375,\n 46.66451741754235\n ],\n [\n -100.96435546875,\n 45.87471224890479\n ],\n [\n -100.70068359374999,\n 45.27488643704894\n ],\n [\n -100.8544921875,\n 44.4808302785626\n ],\n [\n -100.30517578125,\n 43.929549935614595\n ],\n [\n -98.89892578125,\n 43.03677585761058\n ],\n [\n -97.22900390625,\n 42.84375132629021\n ],\n [\n -95.07568359375,\n 42.04929263868686\n ],\n [\n -93.955078125,\n 41.590796851056005\n ],\n [\n -93.05419921875,\n 41.57436130598913\n ],\n [\n -92.4169921875,\n 41.77131167976407\n ],\n [\n -92.35107421874999,\n 42.391008609205045\n ],\n [\n -92.74658203125,\n 43.34116005412307\n ],\n [\n -93.31787109374999,\n 43.929549935614595\n ],\n [\n -93.88916015625,\n 44.2294565683017\n ],\n [\n -94.68017578125,\n 45.413876460821086\n ],\n [\n -94.9658203125,\n 46.84516443029279\n ],\n [\n -96.6357421875,\n 48.472921272487824\n ],\n [\n -98.0859375,\n 48.951366470947725\n ],\n [\n -103.82080078125,\n 48.99463598353408\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted January 28, 2016; Version 1.1: December 30, 2016","contact":"Director, USGS Northern Prairie Wildlife Research Center
8711 37th Street Southeast
Jamestown, North Dakota 58401
A multidimensional model of geographic features has been developed and implemented with data from The National Map of the U.S. Geological Survey. The model, programmed in C++ and implemented as a feature library, was tested with data from the National Hydrography Dataset demonstrating the capability to handle changes in feature attributes, such as increases in chlorine concentration in a stream, and feature geometry, such as the changing shoreline of barrier islands over time. Data can be entered directly, from a comma separated file, or features with attributes and relationships can be automatically populated in the model from data in the Spatial Data Transfer Standard format.
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1400 Independence Road
Rolla, MO 65401