A shapefile of 311 undersea features from all major oceans and seas has been created as an aid for retrieving georeferenced information resources. Geospatial information systems with the capability to search user-defined, polygonal geographic areas will be able to utilize this shapefile or secondary products derived from it, such as linked data based on well-known text representations of the individual polygons within the shapefile. Version 1.1 of this report also includes a linked data representation of 299 of these features and their spatial extents.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141040","usgsCitation":"Hartwell, S., Wingfield, D.K., Allwardt, A., Lightsom, F.L., and Wong, F.L., 2018, Polygons of global undersea features for geographic searches (Version 1.1: June 2018; Version 1.0: March 2014): U.S. Geological Survey Open-File Report 2014-1040, HTML, https://doi.org/10.3133/ofr20141040.","productDescription":"HTML","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053850","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":284379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141040.jpg"},{"id":284377,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1040/","text":"Index page","linkFileType":{"id":5,"text":"html"},"description":"OFR 2014-1040"},{"id":354598,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2014/1040/versionHist.txt","size":"1.75 KB","linkFileType":{"id":2,"text":"txt"}},{"id":284378,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1040/ofr2014-1040-title_page.html","text":"Report (HTML)"}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,-90.0 ], [ -180.0,90.0 ], [ 180.0,90.0 ], [ 180.0,-90.0 ], [ -180.0,-90.0 ] ] ] } } ] }","edition":"Version 1.1: June 2018; Version 1.0: March 2014","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
The U.S. Geological Survey currently (2020) publishes information on concentrations and loads of water-quality constituents at 110 sites across the United States as part of the U.S. Geological Survey National Water Quality Network (NWQN). This report details historical and updated methods for computing water-quality loads at NWQN sites. The primary updates to historical load estimation methods include (1) an adaptation to methods for computing loads to the Gulf of Mexico; (2) the inclusion of loads and trends computed using the Weighted Regressions on Time, Discharge, and Season (WRTDS) and Weighted Regressions on Time, Discharge, and Season with Kalman filtering (WRTDS–K) methods; and (3) the inclusion of loads computed using continuous water-quality data. Loads computed using WRTDS and WRTDS–K and continuous water-quality data are provided along with those computed using historical methods. Various aspects of method updates are evaluated in this report to help users of water-quality loading data determine which estimation methods best suit their particular application.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171120","usgsCitation":"Lee, C.J., Murphy, J.C., Crawford, C.G., and Deacon, J.R, 2017, Methods for computing water-quality loads at sites in the U.S. Geological Survey National Water Quality Network (ver. 1.3, August 2021): U.S. Geological Survey Open-File Report 2017–1120, 20 p., https://doi.org/10.3133/ofr20171120.","productDescription":"Report: vii, 20 p.; Version History","onlineOnly":"Y","ipdsId":"IP-086966","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":438099,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93DHTRJ","text":"USGS data release","linkHelpText":"Nutrient and pesticide data collected from the USGS National Water Quality Network and previous networks, 1950-2022"},{"id":438098,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P948Z0VZ","text":"USGS data release","linkHelpText":"Nutrient and pesticide data collected from the USGS National Water Quality Network and previous networks, 1950-2021"},{"id":388566,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2017/1120/versionHist.txt","text":"Version History","size":"9.89 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2017–1120 Version History"},{"id":388565,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1120/ofr20171120.pdf","text":"Report","size":"14.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1120"},{"id":347239,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1120/coverthb4.jpg"}],"edition":"Version 1.3: August 2021; Version 1.2: November 2020; Version 1.1: January 2020; Version 1.0: October 2017","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
The Washington West 30’ × 60’ quadrangle covers an area of approximately 4,884 square kilometers (1,343 square miles) in and west of the Washington, D.C., metropolitan area. The eastern part of the area is highly urbanized, and more rural areas to the west are rapidly being developed. The area lies entirely within the Chesapeake Bay drainage basin and mostly within the Potomac River watershed. It contains part of the Nation's main north-south transportation corridor east of the Blue Ridge Mountains, consisting of Interstate Highway 95, U.S. Highway 1, and railroads, as well as parts of the Capital Beltway and Interstate Highway 66. Extensive Federal land holdings in addition to those in Washington, D.C., include the Marine Corps Development and Education Command at Quantico, Fort Belvoir, Vint Hill Farms Station, the Naval Ordnance Station at Indian Head, the Chesapeake and Ohio Canal National Historic Park, Great Falls Park, and Manassas National Battlefield Park. The quadrangle contains most of Washington, D.C.; part or all of Arlington, Culpeper, Fairfax, Fauquier, Loudoun, Prince William, Rappahannock, and Stafford Counties in northern Virginia; and parts of Charles, Montgomery, and Prince Georges Counties in Maryland.
The Washington West quadrangle spans four geologic provinces. From west to east these provinces are the Blue Ridge province, the early Mesozoic Culpeper basin, the Piedmont province, and the Coastal Plain province. There is some overlap in ages of rocks in the Blue Ridge and Piedmont provinces. The Blue Ridge province, which occupies the western part of the quadrangle, contains metamorphic and igneous rocks of Mesoproterozoic to Early Cambrian age. Mesoproterozoic (Grenville-age) rocks are mostly granitic gneisses, although older metaigneous rocks are found as xenoliths. Small areas of Neoproterozoic metasedimentary rocks nonconformably overlie Mesoproterozoic rocks. Neoproterozoic granitic rocks of the Robertson River Igneous Suite intruded the Mesoproterozoic rocks. The Mesoproterozoic rocks are nonconformably overlain by Neoproterozoic metasedimentary rocks of the Fauquier and Lynchburg Groups, which in turn are overlain by metabasalt of the Catoctin Formation. The Catoctin Formation is overlain by Lower Cambrian clastic metasedimentary rocks of the Chilhowee Group. The Piedmont province is exposed in the east-central part of the map area, between overlapping sedimentary units of the Culpeper basin on the west and those of the Coastal Plain province on the east. In this area, the Piedmont province contains Neoproterozoic and lower Paleozoic metamorphosed sedimentary, volcanic, and plutonic rocks. Allochthonous mélange complexes on the western side of the Piedmont are bordered on the east by metavolcanic and metasedimentary rocks of the Chopawamsic Formation, which has been interpreted as part of volcanic arc. The mélange complexes are unconformably overlain by metasedimentary rocks of the Popes Head Formation. The Silurian and Ordovician Quantico Formation is the youngest metasedimentary unit in this part of the Piedmont. Igneous rocks include the Garrisonville Mafic Complex, transported ultramafic and mafic inclusions in mélanges, monzogranite of the Dale City pluton, and Ordovician tonalitic and granitic plutons. Jurassic diabase dikes are the youngest intrusions. The fault boundary between rocks of the Blue Ridge and Piedmont provinces is concealed beneath the Culpeper basin in this area but is exposed farther south. Early Mesozoic rocks of the Culpeper basin unconformably overlie those of the Piedmont and Blue Ridge provinces in the central part of the quadrangle. The north-northeast-trending extensional basin contains Upper Triassic to Lower Jurassic nonmarine sedimentary rocks. Lower Jurassic sedimentary strata are interbedded with basalt flows, and both Upper Triassic and Lower Jurassic strata are intruded by diabase of Early Jurassic age. The Bull Run Mountain fault, a major Mesozoic normal fault characterized by down-to-the-east displacement, separates rocks of the Culpeper basin from those of the Blue Ridge province on the west. On the east, the contact between rocks of the Culpeper basin and those of the Piedmont province is an unconformity, which has been locally disrupted by normal faults. Sediments of the Coastal Plain province unconformably overlie rocks of the Piedmont province along the Fall Zone and occupy the eastern part of the quadrangle. Lower Cretaceous deposits of the Potomac Formation consist of fluvial-deltaic gravels, sands, silts, and clays. Discontinuous fluvial and estuarine terrace deposits of Pleistocene and middle- to late-Tertiary age flank the modern Potomac River valley unconformable capping these Cretaceous strata and the crystalline basement where the Cretaceous has been removed by erosion. East of the Potomac River, the Potomac Formation is onlapped and unconformably overlain by a westward thinning wedge of marine sedimentary deposits of Late Cretaceous and early- and late-Tertiary age. Basement rooted Coastal Plain faults of Tertiary to Quaternary age occur along the Fall Zone and this part of the inner Coastal Plain. These Coastal Plain faults have geomorphic expression that appear to influence river drainage patterns.
The geologic map of the Washington West quadrangle is intended to serve as a foundation for applying geologic information to problems involving land use decisions, groundwater availability and quality, earth resources such as natural aggregate for construction, assessment of natural hazards, and engineering and environmental studies for waste disposal sites and construction projects. This 1:100,000-scale map is mainly based on more detailed geologic mapping at a scale of 1:24,000.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171142","usgsCitation":"Lyttle, P.T., Aleinikoff, J.N., Burton, W.C., Crider, E.A., Jr., Drake, A.A., Jr., Froelich, A.J., Horton, J.W., Jr., Kasselas, Gregorios, Mixon, R.B., McCartan, Lucy, Nelson, A.E., Newell, W.L., Pavlides, Louis, Powars, D.S., Southworth, C.S., and Weems, R.E., 2017, Geologic map of the Washington West 30’ × 60’ quadrangle, Maryland, Virginia, and Washington D.C.: U.S. Geological Survey Open-File Report 2017–1142, 1 sheet, scale 1:100,000, https://doi.org/10.3133/ofr20171142.","productDescription":"Map: 55.30 x 60.78 inches; Database; Database Metadata; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052801","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":350265,"rank":6,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142_washington-west-geologic-map-database.zip","text":"Database","size":"102 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Washington West Geologic Map Database"},{"id":350266,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142_washingtonwestVADCMD-ArcGIS-10.0.mxd","size":"438 KB mxd","linkHelpText":"- Washington West: Maryland, Virginia, and Washington, D.C. (ArcGIS 10.0)"},{"id":350263,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142_washington-west-base-map.zip","text":"Base Map","size":"50.4 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Washington West Base Map Files"},{"id":350262,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142_washington-west-geologic-shapefiles.zip","text":"Shapefiles","size":"9.08 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Washington West Geologic Shapefiles"},{"id":350260,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1142/coverthb.jpg"},{"id":350261,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142.pdf","text":"Report","size":"35.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1142"},{"id":350264,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142_washington-west-geologic-database-metadata.zip","text":"Database Metadata","linkHelpText":"- Washington West Geologic Database Metadata"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Washington, D.C.","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78,\n 38.5\n ],\n [\n -77,\n 38.5\n ],\n [\n -77,\n 39\n ],\n [\n -78,\n 39\n ],\n [\n -78,\n 38.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
926A National Center
Reston, VA 20192
In support of earthquake hazard studies and ground motion simulations in the Pacific Northwest, three-dimensional P- and S-wave velocity (VP and VS, respectively) models incorporating the Cascadia subduction zone were previously developed for the region encompassed from about 40.2°N. to 50°N. latitude, and from about 122°W. to 129°W. longitude. This report describes updates to the Cascadia velocity property volumes of model version 1.3 (V1.3), herein called model version 1.6 (V1.6). As in model V1.3, the updated V1.6 model volume includes depths from 0 kilometers (mean sea level) to 60 kilometers, and it is intended to be a reference for researchers who have used, or are planning to use, this model in their Earth science investigations. To this end, it is intended that the VP and VS property volumes of model V1.6 will be considered a template for a community velocity model of the Cascadia region as additional results become available. With the recent and ongoing development of the National Crustal Model, we envision any future versions of this model will be directly integrated with that effort.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171152","collaboration":"Earthquake Hazards Ground Motion Investigations","usgsCitation":"Stephenson, W.J., Reitman, N.G., and Angster, S.J., 2017, P- and S-wave velocity models incorporating the Cascadia subduction zone for 3D earthquake ground motion simulations, version 1.6—Update for Open-File Report 2007–1348 (ver. 1.1, Sept. 10, 2019): U.S. Geological Survey Open-File Report 2017–1152, 17 p., https://doi.org/10.3133/ofr20171152. [Supersedes USGS Open-File Report 2007–1348.]","productDescription":"Report: vi, 17 p.; Read Me; Data Release","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-088666","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":350108,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NS0SWM","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data for P- and S-wave Seismic Velocity Models Incorporating the Cascadia Subduction Zone for 3D Earthquake Ground Motion simulations-Update for Open-File Report 2007-1348"},{"id":350107,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/of/2017/1152/Readme.txt","text":"Read Me","size":"3.82 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2017–1152 Read Me"},{"id":350105,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1152/coverthb2.jpg"},{"id":350106,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1152/ofr20171152.pdf","text":"Report","size":"9.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1152"},{"id":367615,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2017/1152/versionHist.txt","text":"Version History","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2017–1152 Version History"}],"country":"Canada, United States","state":"Oregon, Vancouver, Washington","otherGeospatial":"Cascadia Subduction Zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -128.583984375,\n 40.36328834091583\n ],\n [\n -121.61865234375,\n 40.36328834091583\n ],\n [\n -121.61865234375,\n 49.92293545449574\n ],\n [\n -128.583984375,\n 49.92293545449574\n ],\n [\n -128.583984375,\n 40.36328834091583\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: December 20, 2017; Version 1.1: September 11, 2019","contact":"Center Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046 Mail Stop 966
Denver, CO 80225
Generating an informative display of groundwater withdrawals can sometimes be difficult because the symbols for closely spaced wells can overlap. An alternative method for displaying groundwater withdrawals is to generate a “footprint” of the withdrawals. WellFootprint version 1.0 implements the Footprint algorithm with two optional variations that can speed up the footprint calculation. ModelMuse has been modified in order to generate the input for WellFootprint and to read and graphically display the output from WellFootprint.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171137","usgsCitation":"Winston, R.B., and Goode, D.J., 2017, Visualization of groundwater withdrawals: U.S. Geological Survey Open-File Report 2017–1137, 8 p., https://doi.org/10.3133/ofr20171137.","productDescription":"Report: vi, 8 p.; Application Site","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-089907","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":438124,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70C4TQ8","text":"USGS data release","linkHelpText":"WellFootprint Software Release"},{"id":350110,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1137/ofr20171137.pdf","text":"Report","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1137"},{"id":350113,"rank":3,"type":{"id":4,"text":"Application Site"},"url":"https://doi.org/10.5066/F70C4TQ8","linkHelpText":"- WellFootprint source code and examples: U.S. Geological Survey software release"},{"id":350109,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1137/coverthb.jpg"}],"contact":"Director, Integrated Modeling and Prediction Division
U.S. Geological Survey
MS 415 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
We worked with managers in two focal areas to plan for the uncertain future by integrating quantitative climate change scenarios and simulation modeling into scenario planning exercises.
In our central North Dakota focal area, centered on Knife River Indian Villages National Historic Site, managers are concerned about how changes in flood severity and growing conditions for native and invasive plants may affect archaeological resources and cultural landscapes associated with the Knife and Missouri Rivers. Climate projections and hydrological modeling based on those projections indicate plausible changes in spring and summer soil moisture ranging from a 7 percent decrease to a 13 percent increase and maximum winter snowpack (important for spring flooding) changes ranging from a 13 percent decrease to a 47 percent increase. Facilitated discussions among managers and scientists exploring the implications of these different climate scenarios for resource management revealed potential conflicts between protecting archeological sites and fostering riparian cottonwood forests. The discussions also indicated the need to prioritize archeological sites for excavation or protection and culturally important plant species for intensive management attention.
In our southwestern South Dakota focal area, centered on Badlands National Park, managers are concerned about how changing climate will affect vegetation production, wildlife populations, and erosion of fossils, archeological artifacts, and roads. Climate scenarios explored by managers and scientists in this focal area ranged from a 13 percent decrease to a 33 percent increase in spring precipitation, which is critical to plant growth in the northern Great Plains region, and a slight decrease to a near doubling of intense rain events. Facilitated discussions in this focal area concluded that greater effort should be put into preparing for emergency protection, excavation, and preservation of exposed fossils or artifacts and revealed substantial opportunities for different agencies to learn from each other and cooperate on common management goals. Follow up quantitative simulation modeling of grassland dynamics helped quantify the degree of change expected in vegetation production under the wide range of climate scenarios and suggested that (a) low grazing rates could be adversely affecting vegetation composition in the national park and (b) understanding of the management practices needed to maintain desired vegetation conditions is incomplete.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171129","usgsCitation":"Symstad, A.J., Miller, B.W., Friedman, J.M., Fisichelli, N.A., Ray, A.J., Rowland, Erika, and Schuurman, G.W., 2017, Model-based scenario planning to inform climate change adaptation in the Northern Great Plains—Final report: U.S. Geological Survey Open-File Report 2017–1129, 22 p., https://doi.org/10.3133/ofr20171129.","productDescription":"Report: vii, 22 p.; Data Release","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-089059","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":348794,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1129/coverthb.jpg"},{"id":348795,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1129/ofr20171129.pdf","text":"Report","size":"2.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1129"},{"id":348796,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7T1524X","text":"USGS data release","linkHelpText":"State-and-transition simulation model of rangeland vegetation in southwest South Dakota (1969–2050)"}],"country":"United States","state":"Montana, Nebraska, North Dakota, South Dakota, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114,\n 41\n ],\n [\n -97,\n 41\n ],\n [\n -97,\n 49\n ],\n [\n -114,\n 49\n ],\n [\n -114,\n 41\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, North Dakota 58401
Sequoia Scientific’s LISST-ABS is an acoustic backscatter sensor designed to measure suspended-sediment concentration at a point source. Three LISST-ABS were evaluated at the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF). Serial numbers 6010, 6039, and 6058 were assessed for accuracy in solutions with varying particle-size distributions and for the effect of temperature on sensor accuracy. Certified sediment samples composed of different ranges of particle size were purchased from Powder Technology Inc. These sediment samples were 30–80-micron (µm) Arizona Test Dust; less than 22-µm ISO 12103-1, A1 Ultrafine Test Dust; and 149-µm MIL-STD 810E Silica Dust. The sensor was able to accurately measure suspended-sediment concentration when calibrated with sediment of the same particle-size distribution as the measured. Overall testing demonstrated that sensors calibrated with finer sized sediments overdetect sediment concentrations with coarser sized sediments, and sensors calibrated with coarser sized sediments do not detect increases in sediment concentrations from small and fine sediments. These test results are not unexpected for an acoustic-backscatter device and stress the need for using accurate site-specific particle-size distributions during sensor calibration. When calibrated for ultrafine dust with a less than 22-µm particle size (silt) and with the Arizona Test Dust with a 30–80-µm range, the data from sensor 6039 were biased high when fractions of the coarser (149-µm) Silica Dust were added. Data from sensor 6058 showed similar results with an elevated response to coarser material when calibrated with a finer particle-size distribution and a lack of detection when subjected to finer particle-size sediment. Sensor 6010 was also tested for the effect of dissimilar particle size during the calibration and showed little effect. Subsequent testing revealed problems with this sensor, including an inadequate temperature compensation, making this data questionable. The sensor was replaced by Sequoia Scientific with serial number 6039. Results from the extended temperature testing showed proper temperature compensation for sensor 6039, and results from the dissimilar calibration/testing particle-size distribution closely corroborated the results from sensor 6058.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171154","usgsCitation":"Snazelle, T.T., 2017, Laboratory evaluation of the Sequoia Scientific LISST-ABS acoustic backscatter sediment sensor: U.S. Geological Survey Open-File Report 2017–1154, 21 p., https://doi.org/10.3133/ofr20171154.","productDescription":"Report: vii, 21 p.; Data; Metadata","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-083385","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":350020,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1154/ofr20171154.pdf","text":"Report","size":"921 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1154"},{"id":350021,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://www.sciencebase.gov/catalog/item/59ba9376e4b091459a563ba7","text":"Data and Metadata","linkHelpText":"HIF evaluation of LISST-ABS"},{"id":350019,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1154/coverthb.jpg"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
The U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility evaluated three Hydrolab HL4 multiparameter water-quality sondes by OTT Hydromet. The sondes were equipped with temperature, conductivity, pH, dissolved oxygen (DO), and turbidity sensors. The sensors were evaluated for compliance with the USGS National Field Manual for the Collection of Water-Quality Data (NFM) criteria for continuous water-quality monitors and to verify the validity of the manufacturer’s technical specifications. The conductivity sensors were evaluated for the accuracy of the specific conductance (SC) values (conductance at 25 degrees Celsius [oC]), that were calculated by using the vendor default method, Hydrolab Fresh. The HL4’s communication protocols and operating temperature range along with accuracy of the water-quality sensors were tested in a controlled laboratory setting May 1–19, 2016. To evaluate the sonde’s performance in a surface-water field application, an HL4 equipped with temperature, conductivity, pH, DO, and turbidity sensors was deployed June 20–July 22, 2016, at USGS water-monitoring site 02492620, Pearl River at National Space Technology Laboratories (NSTL) Station, Mississippi, located near Bay Saint Louis, Mississippi, and compared to the adjacent well-maintained EXO2 site sonde.
The three HL4 sondes met the USGS temperature testing criteria and the manufacturer’s technical specifications for temperature based upon the median room temperature difference between the measured and standard temperatures, but two of the three sondes exceeded the allowable difference criteria at the temperature extremes of approximately 5 and 40 ºC. Two sondes met the USGS criteria for SC. One of the sondes failed the criteria for SC when evaluated in a 100,000-microsiemens-per-centimeter (μS/cm) standard at room temperature, and also failed in a 10,000-μS/cm standard at 5, 15, and 40 ºC. All three sondes met the USGS criteria for pH and DO at room temperature, but one sonde exceeded the allowable difference criteria when tested in pH 5.00 buffer and at 40 ºC. The USGS criteria and the technical specifications for turbidity were met by one sonde in standards ranging from 10 to 3,000 nephelometric turbidity units (NTU). A second sonde met the USGS criteria and the technical specifications except in the 3,000-NTU standard, and the third sonde exceeded the USGS calibration criteria in the 10- and 20-NTU standards and the technical specifications in the 20-NTU standard.
Results of the field test showed acceptable performance and revealed that differences in data sample processing between sonde manufacturers may result in variances between the reported measurements when comparing one sonde to another. These variances in data would be more pronounced in dynamic site conditions. The lack of a wiper or other sensor-cleaning device on the DO sensor could prove problematic, and could limit the use of the HL4 to profiling applications or at sites with limited biofouling.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171153","usgsCitation":"Snazelle, T.T., 2017, Evaluation of the Hydrolab HL4 water-quality sonde and sensors: U.S. Geological Survey Open-File Report 2017–1153, 20 p., https://doi.org/10.3133/ofr20171153.","productDescription":"Report: v, 20 p.; Data; Metadata","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072173","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":350018,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://www.sciencebase.gov/catalog/item/59b94eaae4b091459a54d8f9","text":"Data and Metadata ","linkHelpText":"Evaluation of Hydrolab HL4 Water-Quality Sondes and Sensors"},{"id":350016,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1153/coverthb.jpg"},{"id":350017,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1153/ofr20171153.pdf","text":"Report","size":"602 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1153"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
In previous tests of the effectiveness of four common fish screen materials for excluding lamprey ammocoetes, we determined that woven wire (WW) allowed substantially more entrainment than perforated plate (PP), profile bar (PB), or Intralox (IL) material. These tests were simplistic because they used small vertically-oriented screens positioned perpendicular to the flow without a bypass or a sweeping velocity (SV). In the subsequent test discussed in this report, we exposed ammocoetes to much larger (2.5-m-wide) screen panels with flows up to 10 ft3 /s, a SV component, and a simulated bypass channel. The addition of a SV modestly improved protection of lamprey ammocoetes for all materials tested. A SV of 35 cm/s with an approach velocity (AV) of 12 cm/s, was able to provide protection for fish about 5–15 mm smaller than the protection provided by an AV of 12 cm/s without a SV component. The best-performing screen panels (PP, IL, and PB) provided nearly complete protection from entrainment for fish greater than 50-mm toal length, but the larger openings in the WW material only protected fish greater than 100-mm total length. Decreasing the AV and SV by 50 percent expanded the size range of protected lampreys by about 10–15 mm for those exposed to IL and WW screens, and it decreased the protective ability of PP screens by about 10 mm. Much of the improvement for IL and WW screens under the reduced flow conditions resulted from an increase in the number of lampreys swimming away from the screen. Fish of all sizes became impinged (that is, stuck on the screen surface for more than 1 s) on the screens, with the rate of impingement highest on PP (39– 72 percent) and lowest on WW (7–22 percent). Although impingements were common, injuries were rare, and 24-h post-test survival was greater than 99 percent. Our results refined the level of protection provided by these screen materials when both an AV and SV are present and confirmed our earlier recommendation that WW screens be replaced with more effective materials. Future work should focus on determining the risks associated with other screen types (for example, rotary drum screens, horizontal flat plate screens) and exploring the effectiveness of higher SV:AV ratios, because it may help expand the range of sizes protected by the best performing materials.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171163","usgsCitation":"Mesa, M.G., Liedtke, T.L., Weiland, L.K., and Christiansen, H.E., 2017, Effectiveness of common fish screen materials for protecting lamprey ammocoetes—Influence of sweeping velocities and decreasing flows: U.S. Geological Survey Open-File Report 2017-1163, 19 p., https://doi.org/10.3133/ofr20171163.","productDescription":"iv, 19 p.","numberOfPages":"28","ipdsId":"IP-092482","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":350014,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1163/ofr20171163.pdf","text":"Report","size":"836 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1163"},{"id":350013,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1163/coverthb.jpg"}],"contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
The U.S. Geological Survey evaluated the interaction of groundwater and surface water in the central part of Sevier County, Tennessee, from October 2015 through October 2016. Stream base flow was surveyed in December 2015 and in July and October 2016 to evaluate losing and gaining stream reaches along three streams in the area. During a July 2016 synoptic survey, groundwater levels were measured in wells screened in the Cambrian-Ordovician aquifer to define the potentiometric surface in the area. The middle and lower reaches of the Little Pigeon River and the middle reaches of Middle Creek and the West Prong Little Pigeon River were gaining streams at base-flow conditions. The lower segments of the West Prong Little Pigeon River and Middle Creek were losing reaches under base-flow conditions, with substantial flow losses in the West Prong Little Pigeon River and complete subsurface diversion of flow in Middle Creek through a series of sinkholes that developed in the streambed and adjacent flood plain beginning in 2010. The potentiometric surface of the Cambrian-Ordovician aquifer showed depressed water levels in the area where loss of flow occurred in the lower reaches of West Prong Little Pigeon River and Middle Creek. Continuous dewatering activities at a rock quarry located in this area appear to have lowered groundwater levels by as much as 180 feet, which likely is the cause of flow losses observed in the two streams, and a contributing factor to the development of sinkholes at Middle Creek near Collier Drive.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171147","collaboration":"Prepared in cooperation with the City of Sevierville and Tennessee Department of Environment and Conservation","usgsCitation":"Carmichael, J.K., and Johnson, G.C., 2017, Groundwater/surface-water interaction in central Sevier County, Tennessee, October 2015–2016: U.S. Geological Survey Open-File Report 2017–1147, 22 p., https://doi.org/10.3133/ofr20171147.","productDescription":"v, 22 p.","numberOfPages":"32","onlineOnly":"N","ipdsId":"IP-086182","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":349937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1147/coverthb.jpg"},{"id":349938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1147/ofr20171147.pdf","text":"Report","size":"2.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1147"}],"country":"United States","state":"Tennessee","county":"Sevier County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.60664367675781,\n 35.74261114799056\n ],\n [\n -83.38485717773438,\n 35.74261114799056\n ],\n [\n -83.38485717773438,\n 35.88126165890356\n ],\n [\n -83.60664367675781,\n 35.88126165890356\n ],\n [\n -83.60664367675781,\n 35.74261114799056\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center—Tennessee
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Concentrations of particulate organic carbon (POC) and dissolved organic carbon (DOC), which together comprise total organic carbon, were measured in this reconnaissance study at sampling sites in the Upper Klamath River, Lost River, and Klamath Straits Drain in 2013–16. Optical absorbance and fluorescence properties of dissolved organic matter (DOM), which contains DOC, also were analyzed. Parallel factor analysis was used to decompose the optical fluorescence data into five key components for all samples. Principal component analysis (PCA) was used to investigate differences in DOM source and processing among sites.
At all sites in this study, average DOC concentrations were higher than average POC concentrations. The highest DOC concentrations were at sites in the Klamath Straits Drain and at Pump Plant D. Evaluation of optical properties indicated that Klamath Straits Drain DOM had a refractory, terrestrial source, likely extracted from the interaction of this water with wetland peats and irrigated soils. Pump Plant D DOM exhibited more labile characteristics, which could, for instance, indicate contributions from algal or microbial exudates. The samples from Klamath River also had more microbial or algal derived material, as indicated by PCA analysis of the optical properties. Most sites, except Pump Plant D, showed a linear relation between fluorescent dissolved organic matter (fDOM) and DOC concentration, indicating these measurements are highly correlated (R2=0.84), and thus a continuous fDOM probe could be used to estimate DOC loads from these sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171160","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Goldman, J.H., and Sullivan, A.B., 2017, Characteristics of dissolved organic matter in the Upper Klamath River, Lost River, and Klamath Straits Drain, Oregon and California: U.S. Geological Survey Open File Report 2017-1160, 21 p., https://doi.org/10.3133/ofr20171160.","productDescription":"Report: iv, 21 p.; Data Release","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-088888","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":349912,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1160/coverthb.jpg"},{"id":349913,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1160/ofr20171160.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1160"},{"id":349914,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71Z42V4","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data from an analysis of dissolved organic matter in the Upper Klamath River, Lost River, and Klamath Straits Drain, Oregon and California, 2013–16"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Lost River, Klamath Straits Drain, Upper Klamath River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.05261230468751,\n 41.77131167976407\n ],\n [\n -121.0308837890625,\n 41.77131167976407\n ],\n [\n -121.0308837890625,\n 42.44980808481614\n ],\n [\n -122.05261230468751,\n 42.44980808481614\n ],\n [\n -122.05261230468751,\n 41.77131167976407\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
The deep sea is a rich environment composed of diverse habitat types. While deep-sea coral habitats have been discovered within each ocean basin, knowledge about the ecology of these habitats and associated inhabitants continues to grow. This report presents information and results from the Lophelia II project that examined deep-sea coral habitats in the Gulf of Mexico. The Lophelia II project focused on Lophelia pertusa habitats along the continental slope, at depths ranging from 300 to 1,000 meters. The chapters are authored by several scientists from the U.S. Geological Survey, National Oceanic and Atmospheric Administration, University of North Carolina Wilmington, and Florida State University who examined the community ecology (from microbes to fishes), deep-sea coral age, growth, and reproduction, and population connectivity of deep-sea corals and inhabitants. Data from these studies are presented in the chapters and appendixes of the report as well as in journal publications. This study was conducted by the Ecosystems Mission Area of the U.S. Geological Survey to meet information needs identified by the Bureau of Ocean Energy Management.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171139","collaboration":"Prepared in collaboration with the Bureau of Ocean Energy Management and the National Oceanic and Atmospheric Administration","usgsCitation":"Demopoulos, A.W.J., Ross, S.W., Kellogg, C.A., Morrison, C.L., Nizinski, M., Prouty, N.G., Bourque, J.R., Galkiewicz, J.P., Gray, M.A., Springmann, M.J., Coykendall, D.K., Miller, A., Rhode, M., Quattrini, A., Ames, C.L., Brooke, S., McClain-Counts, J., Roark, E.B., Buster, N.A., Phillips, R.M., and Frometa, J., 2017, Deepwater Program: Lophelia II, continuing ecological research on deep-sea corals and deep-reef habitats in the Gulf of Mexico: U.S. Geological Survey Open-File Report 2017–1139, 269 p., https://doi.org/10.3133/ofr20171139.","productDescription":"xviii, 269 p.","numberOfPages":"287","onlineOnly":"Y","ipdsId":"IP-057758","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":349831,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1139/coverthb2.jpg"},{"id":349832,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1139/ofr20171139.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1139"}],"country":"United States","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.48193359375,\n 24\n ],\n [\n -74.81689453125,\n 24\n ],\n [\n -74.81689453125,\n 35\n ],\n [\n -96.48193359375,\n 35\n ],\n [\n -96.48193359375,\n 24\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71st St.
Gainesville, FL 32653
The mission of the National Strong-Motion Project is to provide measurements of how the ground and built environment behave during earthquake shaking to the earthquake engineering community, the scientific community, emergency managers, public agencies, industry, media, and other users for the following purposes:
Director,
Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road
Mail Stop 977
Menlo Park, CA 94025
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 16 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 2013 to December 2015. The monitoring program includes measurements of (1) groundwater withdrawals (pumping), (2) groundwater levels, (3) spring discharge, (4) surface-water discharge, and (5) groundwater chemistry.
In 2013, total groundwater withdrawals were 3,980 acre-feet (ft), in 2014 total withdrawals were 4,170 acre-ft, and in 2015 total withdrawals were 3,970 acre-ft. From 2013 to 2015 total withdrawals varied by less than 5 percent.
From 2014 to 2015, annually measured water levels in the Black Mesa area declined in 9 of 15 wells that were available for comparison in the unconfined areas of the N aquifer, and the median change was -0.1 feet. Water levels declined in 3 of 16 wells measured in the confined area of the aquifer. The median change for the confined area of the aquifer was 0.6 feet. From the prestress period (prior to 1965) to 2015, the median water-level change for 34 wells in both the confined and unconfined areas was -13.2 feet; the median water-level changes were -1.7 feet for 16 wells measured in the unconfined areas and -42.3 feet for 18 wells measured in the confined area.
Spring flow was measured at four springs in 2014. Flow fluctuated during the period of record for Burro Spring and Unnamed Spring near Dennehotso, but a decreasing trend was statistically significant (p<0.05) 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. Trend analysis for discharge at Moenkopi and Pasture Canyon Springs yielded a slope significantly different (p<0.05) from zero.
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 2015), Dinnebito Wash near Sand Springs 09401110 (1993 to 2015), Polacca Wash near Second Mesa 09400568 (1994 to 2015), and Pasture Canyon Springs 09401265 (2004 to 2015). Median winter flows (November through February) of each water year were used as an index of the amount of groundwater discharge at the above-named sites. 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 2014, water samples collected from four springs in the Black Mesa area were analyzed for selected chemical constituents, and the results were compared with previous analyses. Dissolved solids, chloride, and sulfate concentrations increased at Moenkopi School Spring during the more than 25 years of record at that site. Concentrations of dissolved solids, chloride, and sulfate at Pasture Canyon Spring have not varied significantly (p>0.05) since the early 1980s, and there is no increasing or decreasing trend in those data. Concentrations of dissolved solids, chloride, and sulfate at Burro Spring and Unnamed Spring near Dennehotso have varied for the period of record, but there is no increasing or decreasing statistical trend in the data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171127","collaboration":"Prepared in cooperation with the Navajo Nation and the Arizona Department of Water Resources","usgsCitation":"Macy, J.P., and Mason, J.P., 2017, Groundwater, surface-water, and water-chemistry data, Black Mesa area, northeastern Arizona—2013–2015: U.S. Geological Survey Open-File Report 2017–1127, 49 p., https://doi.org/10.3133/ofr20171127.","productDescription":"v., 49 p.","numberOfPages":"58","onlineOnly":"Y","ipdsId":"IP-083213","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":349866,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1127/coverthb.jpg"},{"id":349867,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1127/ofr20171127.pdf","text":"Report","size":"2.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1127"}],"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 -111.5,\n 35.5\n ],\n [\n -109.5,\n 35.5\n ],\n [\n -109.5,\n 37\n ],\n [\n -111.5,\n 37\n ],\n [\n -111.5,\n 35.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
In almost all past inversions of large-earthquake ground motions for rupture behavior, the goal of the inversion is to find the “best fitting” rupture model that predicts ground motions which optimize some function of the difference between predicted and observed ground motions. This type of inversion was pioneered in the linear-inverse sense by Olson and Apsel (1982), who minimized the square of the difference between observed and simulated motions (“least squares”) while simultaneously minimizing the rupture-model norm (by setting the null-space component of the rupture model to zero), and has been extended in many ways, one of which is the use of nonlinear inversion schemes such as simulated annealing algorithms that optimize some other misfit function. For example, the simulated annealing algorithm of Piatanesi and others (2007) finds the rupture model that minimizes a “cost” function which combines a least-squares and a waveform-correlation measure of misfit.
All such inversions that look for a unique “best” model have at least three problems. (1) They have removed the null-space component of the rupture model—that is, an infinite family of rupture models that all fit the data equally well have been narrowed down to a single model. Some property of interest in the rupture model might have been discarded in this winnowing process. (2) Smoothing constraints are commonly used to yield a unique “best” model, in which case spatially rough rupture models will have been discarded, even if they provide a good fit to the data. (3) No estimate of confidence in the resulting rupture models can be given because the effects of unknown errors in the Green’s functions (“theory errors”) have not been assessed. In inversion for rupture behavior, these theory errors are generally larger than the data errors caused by ground noise and instrumental limitations, and so overfitting of the data is probably ubiquitous for such inversions.
Recently, attention has turned to the inclusion of theory errors in the inversion process. Yagi and Fukahata (2011) made an important contribution by presenting a method to estimate the uncertainties in predicted large-earthquake ground motions due to uncertainties in the Green’s functions. Here we derive their result and compare it with the results of other recent studies that look at theory errors in a Bayesian inversion context particularly those by Bodin and others (2012), Duputel and others (2012), Dettmer and others (2014), and Minson and others (2014).
Notably, in all these studies, the estimates of theory error were obtained from theoretical considerations alone; none of the investigators actually measured Green’s function errors. Large earthquakes typically have aftershocks, which, if their rupture surfaces are physically small enough, can be considered point evaluations of the real Green’s functions of the Earth. Here we simulate smallaftershock ground motions with (erroneous) theoretical Green’s functions. Taking differences between aftershock ground motions and simulated motions to be the “theory error,” we derive a statistical model of the sources of discrepancies between the theoretical and real Green’s functions. We use this model with an extended frequency-domain version of the time-domain theory of Yagi and Fukahata (2011) to determine the expected variance 2 τ caused by Green’s function error in ground motions from a larger (nonpoint) earthquake that we seek to model.
We also differ from the above-mentioned Bayesian inversions in our handling of the nonuniqueness problem of seismic inversion. We follow the philosophy of Segall and Du (1993), who, instead of looking for a best-fitting model, looked for slip models that answered specific questions about the earthquakes they studied. In their Bayesian inversions, they inductively derived a posterior probability-density function (PDF) for every model parameter. We instead seek to find two extremal rupture models whose ground motions fit the data within the error bounds given by 2 τ , as quantified by using a chi-squared test described below. So, we can ask questions such as, “What are the rupture models with the highest and lowest average rupture speed consistent with the theory errors?” Having found those models, we can then say with confidence that the true rupture speed is somewhere between those values. Although the Bayesian approach gives a complete solution to the inverse problem, it is computationally demanding: Minson and others (2014) needed 1010 forward kinematic simulations to derive their posterior probability distribution. In our approach, only about107 simulations are needed. Moreover, in practical application, only a small set of rupture models may be needed to answer the relevant questions—for example, determining the maximum likelihood solution (achievable through standard inversion techniques) and the two rupture models bounding some property of interest.
The specific property that we wish to investigate is the correlation between various rupturemodel parameters, such as peak slip velocity and rupture velocity, in models of real earthquakes. In some simulations of ground motions for hypothetical large earthquakes, such as those by Aagaard and others (2010) and the Southern California Earthquake Center Broadband Simulation Platform (Graves and Pitarka, 2015), rupture speed is assumed to correlate locally with peak slip, although there is evidence that rupture speed should correlate better with peak slip speed, owing to its dependence on local stress drop. We may be able to determine ways to modify Piatanesi and others’s (2007) inversion’s “cost” function to find rupture models with either high or low degrees of correlation between pairs of rupture parameters. We propose a cost function designed to find these two extremal models.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171151","usgsCitation":"Spudich, P., Cirella, A., Scognamiglio, L., and Tinti, E., 2017, Analysis of the variability in ground-motion synthesis and inversion: U.S. Geological Survey Open-File Report 2017–1151, 39 p., https://doi.org/10.3133/ofr20171151.","productDescription":"iv, 39 p.","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-087954","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":349837,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1151/ofr20171151_.pdf","text":"Report","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1151"},{"id":349836,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1151/coverthb.jpg"}],"contact":"Director,
Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road
Mail Stop 977
Menlo Park, CA 94025
Cobalt (Co) is a potentially critical mineral. The vast majority of cobalt is a byproduct of copper and (or) nickel production. Cobalt is increasingly used in magnets and rechargeable batteries. More than 50 percent of primary cobalt production is from the Central African Copperbelt. The Central African Copperbelt is the only sedimentary rock-hosted stratiform copper district that contains significant cobalt. Its presence may indicate significant mafic-ultramafic rocks in the local basement. The balance of primary cobalt production is from magmatic nickel-copper and nickel laterite deposits. Cobalt is present in several carbonate-hosted lead-zinc and copper districts. It is also variably present in Besshi-type volcanogenic massive sulfide and siliciclastic sedimentary rock-hosted deposits in back arc and rift environments associated with mafic-ultramafic rocks. Metasedimentary cobalt-copper-gold deposits (such as Blackbird, Idaho), iron oxide-copper-gold deposits, and the five-element vein deposits (such as Cobalt, Ontario) contain different amounts of cobalt. None of these deposit types show direct links to mafic-ultramafic rocks; the deposits may result from crustal-scale hydrothermal systems capable of leaching and transporting cobalt from great depths. Hydrothermal deposits associated with ultramafic rocks, typified by the Bou Azzer district of Morocco, represent another type of primary cobalt deposit.
In the United States, exploration for cobalt deposits may focus on magmatic nickel-copper deposits in the Archean and Proterozoic rocks of the Midwest and the east coast (Pennsylvania) and younger mafic rocks in southeastern and southern Alaska; also, possibly basement rocks in southeastern Missouri. Other potential exploration targets include—
Office of the Associate Director for Energy and Minerals
U.S. Geological Survey
12201 Sunrise Valley Drive
MS 102
Reston, VA 20192
Mattamuskeet National Wildlife Refuge (MNWR) offers a mix of open water, marsh, forest, and cropland habitats on 20,307 hectares in coastal North Carolina. In 1934, Federal legislation (Executive Order 6924) established MNWR to benefit wintering waterfowl and other migratory bird species. On an annual basis, the refuge staff decide how to manage 14 impoundments to benefit not only waterfowl during the nonbreeding season, but also shorebirds during fall and spring migration. In making these decisions, the challenge is to select a portfolio, or collection, of management actions for the impoundments that optimizes use by the three groups of birds while respecting budget constraints. In this study, a decision support tool was developed for these annual management decisions.
Within the decision framework, there are three different management objectives: shorebird-use days during fall and spring migrations, and waterfowl-use days during the nonbreeding season. Sixteen potential management actions were identified for impoundments; each action represents a combination of hydroperiod and vegetation manipulation. Example hydroperiods include semi-permanent and seasonal drawdowns, and vegetation manipulations include mechanical-chemical treatment, burning, disking, and no action. Expert elicitation was used to build a Bayesian Belief Network (BBN) model that predicts shorebird- and waterfowl-use days for each potential management action. The BBN was parameterized for a representative impoundment, MI-9, and predictions were re-scaled for this impoundment to predict outcomes at other impoundments on the basis of size. Parameter estimates in the BBN model can be updated using observations from ongoing monitoring that is part of the Integrated Waterbird Management and Monitoring (IWMM) program.
The optimal portfolio of management actions depends on the importance, that is, weights, assigned to the three objectives, as well as the budget. Five scenarios with a variety of objective weights and budgets were developed. Given the large number of possible portfolios (1614), a heuristic genetic algorithm was used to identify a management action portfolio that maximized use-day objectives while respecting budget constraints. The genetic algorithm identified a portfolio of management actions for each of the five scenarios, enabling refuge staff to explore the sensitivity of their management decisions to objective weights and budget constraints.
The decision framework developed here provides a transparent, defensible, and testable foundation for decision making at MNWR. The BBN model explicitly structures and parameterizes a mental model previously used by an expert to assign management actions to the impoundments. With ongoing IWMM monitoring, predictions from the model can be tested, and model parameters updated, to reflect empirical observations. This framework is intended to be a living document that can be updated to reflect changes in the decision context (for example, new objectives or constraints, or new models to compete with the current BBN model). Rather than a mandate to refuge staff, this framework is intended to be a decision support tool; tool outputs can become part of the deliberations of refuge staff when making difficult management decisions for multiple objectives.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171052","usgsCitation":"Tavernia, B.G., Stanton, J.D., and Lyons, J.E., 2017, Integrated wetland management for waterfowl and shorebirds at Mattamuskeet National Wildlife Refuge, North Carolina: U.S. Geological Survey Open-File Report 2017–1052, 43 p., https://doi.org/10.3133/ofr20171052.","productDescription":"vii, 43 p.","numberOfPages":"55","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074603","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":348384,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1052/coverthb.jpg"},{"id":348385,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1052/ofr20171052.pdf","text":"Report","size":"9.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1052"}],"country":"United States","state":"North Carolina","otherGeospatial":"Mattamuskeet National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.36459350585938,\n 35.42262976362149\n ],\n [\n -76.03363037109374,\n 35.42262976362149\n ],\n [\n -76.03363037109374,\n 35.59031875398378\n ],\n [\n -76.36459350585938,\n 35.59031875398378\n ],\n [\n -76.36459350585938,\n 35.42262976362149\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road, Ste 4039
Laurel, MD 20708
Managers at the U.S. Fish and Wildlife Service Crystal River National Wildlife Refuge (CRNWR) desire to update their management plan regarding the operation of select springs including Three Sisters Springs. They wish to refine existing parameters used to predict the presence of federally threatened Trichechus manatus latirostris (Florida manatee) in the springs and thereby improve their manatee management options. The U.S. Geological Survey Sirenia Project has been tracking manatees in the CRNWR area since 2006 with floating Global Positioning System (GPS) satellite-monitored telemetry tags. Analyzing movements of these tagged manatees will provide valuable insight into their habitat use patterns.
A total of 136 GPS telemetry bouts were available for this project, representing 730,009 locations generated from 40 manatees tagged in the Gulf of Mexico north of Tampa, Florida. Dates from October through March were included to correspond to the times that cold ambient temperatures were expected, thus requiring a need for manatee thermoregulation and a physiologic need for warm water. Water level (tide) and water temperatures were obtained for the study from Salt River, Crystal River mouth, Bagley Cove, Kings Bay mouth, and Magnolia Spring. Polygons were drawn to subdivide the manatee locations into areas around the most-used springs (Three Sisters/Idiots Delight, House/Hunter/Jurassic, Magnolia and King), Kings Bay, Crystal/Salt Rivers and the Gulf of Mexico.
Manatees were found in the Crystal or Salt Rivers or in the Gulf of Mexico when ambient temperatures were warmer (>20 °C), while they were found in or near the springs (especially Three Sisters Springs) at colder ambient water temperatures. There was a trend of manatees entering springs early in the morning and leaving in the afternoon. There was a strong association of manatee movements in and out of the Three Sisters/Idiots Delight polygon with tide cycles: manatees were more likely to enter the Three Sisters/Idiots Delight polygon on an incoming tide, and leave the polygon on an outgoing tide. Both movement directions were associated with midtide. Future analysis will incorporate human activity and a finer spatial scale, including movements between Three Sisters Springs and Idiots Delight and nearby canals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171146","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Slone, D.H., Butler, S.M., Reid, J.P., and Haase, C.G., 2017, Timing of warm water refuge use in Crystal River National Wildlife Refuge by manatees—Results and insights from Global Positioning System telemetry data: U.S. Geological Survey Open-File Report 2017–1146, 17 p., https://doi.org/10.3133/ofr20171146.","productDescription":"Report: v, 17 p.; Data Release","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091745","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":349180,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1146/ofr20171146.pdf","text":"Report","size":"1.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1146"},{"id":349181,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78P5ZGR","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water temperature in Three Sisters Springs, and water temperature and level in Magnolia Spring: Winter 2014–15"},{"id":349179,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1146/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Crystal River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.850,\n 28.830\n ],\n [\n -82.570,\n 28.830\n ],\n [\n -82.570,\n 28.955\n ],\n [\n -82.850,\n 28.955\n ],\n [\n -82.850,\n 28.830\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71 Street
Gainesville, FL 32653
Red tides (blooms of the harmful alga Karenia brevis) are one of the major sources of mortality for the Florida manatee (Trichechus manatus latirostris), especially in southwest Florida. It has been hypothesized that the frequency and severity of red tides may increase in the future because of global climate change and other factors. To improve our ecological forecast for the effects of red tides on manatee population dynamics and long-term persistence, we conducted a formal expert judgment process to estimate probability distributions for the frequency and relative magnitude of red-tide-related manatee mortality (RTMM) events over a 100-year time horizon in three of the four regions recognized as manatee management units in Florida. This information was used to update a population viability analysis for the Florida manatee (the Core Biological Model). We convened a panel of 12 experts in manatee biology or red-tide ecology; the panel met to frame, conduct, and discuss the elicitation. Each expert provided a best estimate and plausible low and high values (bounding a confidence level of 80 percent) for each parameter in each of three regions (Northwest, Southwest, and Atlantic) of the subspecies’ range (excluding the Upper St. Johns River region) for two time periods (0−40 and 41−100 years from present). We fitted probability distributions for each parameter, time period, and expert by using these three elicited values. We aggregated the parameter estimates elicited from individual experts and fitted a parametric distribution to the aggregated results.
Across regions, the experts expected the future frequency of RTMM events to be higher than historical levels, which is consistent with the hypothesis that global climate change (among other factors) may increase the frequency of red-tide blooms. The experts articulated considerable uncertainty, however, about the future frequency of RTMM events. The historical frequency of moderate and intense RTMM (combined) in the Southwest region was 0.35 (80-percent confidence interval [CI]: 0.21−0.52), whereas the forecast probability was 0.48 (80-percent CI: 0.30−0.64) over a 40-year projected time horizon. Moderate and intense RTMM events are expected to continue to be most frequent in the Southwest region, to increase in mean frequency in the Northwest region (historical frequency of moderate and intense RTMM events [combined] in the Northwest region was 0, whereas the forecast probability was 0.12 [80-percent CI: 0.02−0.39] over a 40-year projected time horizon) and in the Atlantic region (historical frequency of moderate and intense RTMM events [combined] in the Atlantic region was 0.05 [80-percent CI: 0.005–0.18], whereas the forecast probability was 0.11 [80-percent CI: 0.03−0.25] over a 40-year projected time horizon), and to remain absent from the Upper St. Johns River region.
The impact of red-tide blooms on manatee mortality has been measured for the Southwest region but not for the Northwest and Atlantic regions, where such events have been rare. The expert panel predicted that the median magnitude of RTMM events in the Atlantic and Northwest regions will be much smaller than that in the Southwest; given the large uncertainties, however, they acknowledged the possibility that these events could be larger in their mortality impacts than in the Southwest region.
By its nature, forecasting requires expert judgment because it is impossible to have empirical evidence about the future. The large uncertainties in parameter estimates over a 100-year timeframe are to be expected and may also indicate that the training provided to panelists successfully minimized one common pitfall of expert judgment, that of overconfidence. This study has provided useful and needed inputs to the Florida manatee population viability analysis associated with an important and recurrent source of mortality from harmful algal blooms.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171132","collaboration":"Prepared in cooperation with the Florida Fish and Wildlife Conservation Commission","usgsCitation":"Martin, Julien, Runge, M.C., Flewelling, L.J., Deutsch, C.J., and Landsberg, J.H., 2017, An expert elicitation process to project the frequency and magnitude of Florida manatee mortality events caused by red tide (Karenia brevis): U.S. Geological Survey Open-File Report 2017–1132, 17 p., https://doi.org/10.3133/ofr20171132.","productDescription":"Report: vi, 17 p.; Data Release","numberOfPages":"28","ipdsId":"IP-084079","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":348904,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1132/ofr20171132.pdf","text":"Report","size":"725 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1132"},{"id":348905,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78P5XQG","text":"USGS data release","description":"USGS Data Release","linkHelpText":"An expert elicitation process to project the frequency and magnitude of Florida manatee mortality events caused by red tide (Karenia brevis)"},{"id":348903,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1132/coverthb.jpg"}],"contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71St Street
Gainesville, FL 32653
Most extant giant gartersnake (Thamnophis gigas) populations persist in an agro-ecosystem dominated by rice, which serves as a surrogate to the expansive marshes lost to flood control projects and development of the Great Central Valley of California. Knowledge of how giant gartersnakes use the rice agricultural landscape, including how they respond to fallowing, idling, or crop rotations, would greatly benefit conservation of giant gartersnakes by informing more snake-friendly land and water management practices. We studied adult giant gartersnakes at 11 sites in the rice-growing regions of the Sacramento Valley during an extended drought in California to evaluate their response to differences in water availability at the site and individual levels. Although our study indicated that giant gartersnakes make little use of rice fields themselves, and avoid cultivated rice relative to its availability on the landscape, rice is a crucial component of the modern landscape for giant gartersnakes. Giant gartersnakes are strongly associated with the canals that supply water to and drain water from rice fields; these canals provide much more stable habitat than rice fields because they maintain water longer and support marsh-like conditions for most of the giant gartersnake active season. Nonetheless, our results suggest that maintaining canals without neighboring rice fields would be detrimental to giant gartersnake populations, with decreases in giant gartersnake survival rates associated with less rice production in the surrounding landscape. Increased productivity of prey populations, dispersion of potential predators across a larger landscape, and a more secure water supply are just some of the mechanisms by which rice fields might benefit giant gartersnakes in adjacent canals. Results indicate that identifying how rice benefits giant gartersnakes in canals and the extent to which the rice agro-ecosystem could provide these benefits when rice is fallowed would inform the use of water for other purposes without harm to giant gartersnakes. Our study also suggests that without such understanding, maintaining rice and associated canals in the Sacramento Valley is critical for the sustainability of giant gartersnake populations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171141","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Reyes, G.A., Halstead, B.J., Rose, J.P., Ersan, J.S.M., Jordan, A.C., Essert, A.M., Fouts, K.J., Fulton, A.M., Gustafson, K.B., Wack, R.F., Wylie, G.D., and Casazza, M.L., 2017, Behavioral response of giant gartersnakes (Thamnophis gigas) to the relative availability of aquatic habitat on the landscape: U.S. Geological Survey Open-File Report 2017-1141, 134 p., https://doi.org/10.3133/ofr20171141.","productDescription":"vi, 134 p.","numberOfPages":"144","onlineOnly":"Y","ipdsId":"IP-086237","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":348951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1141/coverthb.jpg"},{"id":348952,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1141/ofr20171141.pdf","text":"Report","size":"9.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1141"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.42340087890624,\n 38.62116234642254\n ],\n [\n -121.36596679687499,\n 38.62116234642254\n ],\n [\n -121.36596679687499,\n 39.605688178320804\n ],\n [\n -122.42340087890624,\n 39.605688178320804\n ],\n [\n -122.42340087890624,\n 38.62116234642254\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive
East Sacramento, California 95819
The U.S. Geological Survey (USGS), in cooperation with the Virginia Department of Environmental Quality (DEQ), reviewed a previously compiled set of linear regression models to assess their utility in defining the response of the aquatic biological community to streamflow depletion.
As part of the 2012 Virginia Healthy Watersheds Initiative (HWI) study conducted by Tetra Tech, Inc., for the U.S. Environmental Protection Agency (EPA) and Virginia DEQ, a database with computed values of 72 hydrologic metrics, or indicators of hydrologic alteration (IHA), 37 fish metrics, and 64 benthic invertebrate metrics was compiled and quality assured. Hydrologic alteration was represented by simulation of streamflow record for a pre-water-withdrawal condition (baseline) without dams or developed land, compared to the simulated recent-flow condition (2008 withdrawal simulation) including dams and altered landscape to calculate a percent alteration of flow. Biological samples representing the existing populations represent a range of alteration in the biological community today.
For this study, all 72 IHA metrics, which included more than 7,272 linear regression models, were considered. This extensive dataset provided the opportunity for hypothesis testing and prioritization of flow-ecology relations that have the potential to explain the effect(s) of hydrologic alteration on biological metrics in Virginia streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171088","collaboration":"Prepared in cooperation with the Virginia Department of Environmental Quality","usgsCitation":"Rapp, J.L., and Reilly, P.A., 2017, Virginia flow-ecology modeling results—An initial assessment of flow reduction effects on aquatic biota: U.S. Geological Survey Open-File Report 2017–1088, 68 p., https://doi.org/10.3133/ofr20171088.","productDescription":"68 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-086496","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":438149,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZW1J42","text":"USGS data release","linkHelpText":"Fish and Benthic Macroinvertebrate Flow-Ecology Regression Summary Statistics for 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\"}}]}","contact":"Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond VA 23228
The May 18, 1980, eruption of Mount St. Helens produced a 2.5-cubic-kilometer debris avalanche that dammed South Fork Castle Creek, causing Castle Lake to form behind a 20-meter-tall blockage. Risk of a catastrophic breach of the newly impounded lake led to outlet channel stabilization work, aggressive monitoring programs, mapping efforts, and blockage stability studies. Despite relatively large uncertainty, early mapping efforts adequately supported several lake breakout models, but have limited applicability to current lake monitoring and hazard assessment. Here, we present the results of a bathymetric survey conducted in August 2012 with the purpose of (1) verifying previous volume estimates, (2) computing an area/capacity table, and (3) producing a bathymetric map. Our survey found seasonal lake volume ranges between 21.0 and 22.6 million cubic meters with a fundamental vertical accuracy representing 0.88 million cubic meters. Lake surface area ranges between 1.13 and 1.16 square kilometers. Relationships developed by our results allow the computation of lake volume from near real-time lake elevation measurements or from remotely sensed imagery.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171145","usgsCitation":"Mosbrucker, A.R., and Spicer, K.R., 2017, Bathymetric map and area/capacity table for Castle Lake, Washington: U.S. Geological Survey Open-File Report 2017–1145, 22 p., https://doi.org/10.3133/ofr20171145.","productDescription":"iv, 22 p.","numberOfPages":"27","onlineOnly":"Y","ipdsId":"IP-058706","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":348849,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1145/ofr20171145.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1145"},{"id":348848,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1145/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Castle Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.30100631713866,\n 46.231271774559936\n ],\n [\n -122.25088119506836,\n 46.231271774559936\n ],\n [\n -122.25088119506836,\n 46.2668841963711\n ],\n [\n -122.30100631713866,\n 46.2668841963711\n ],\n [\n -122.30100631713866,\n 46.231271774559936\n ]\n ]\n ]\n }\n }\n ]\n}","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
Two Eureka Manta2 3.5 water-quality multiprobe sondes by Eureka Water Probes were tested at the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF) against known standards over the sonde operating temperatures to verify the manufacturer’s stated accuracy specifications for pH, specific conductance (SC) at 25 degrees Celsius (°C), dissolved oxygen (DO), and turbidity. The Manta2 sondes were evaluated for compliance with the USGS National Field Manual for the Collection of Water-Quality Data (NFM) criteria for continuous water-quality monitors, and for compliance with the manufacturer’s technical specifications. The Manta2 was also evaluated for its compliance to Serial Digital Interface at 1200 baud (SDI-12) version 1.3.
The Manta2 met the NFM recommendations and manufacturer’s accuracy specifications for DO and turbidity at all values tested. The Manta2 pH sensors met the NFM recommendations and manufacturer’s accuracy specification for nominal pH values of 10 and lower. One of the two sensors was out of compliance by 1.2 units for pH 11.16 at 15 °C and by 0.25 unit for pH 10.78 at 40 °C. The Manta2 sensors were within the NFM recommendations for SC, except at 100 microsiemens (μS/cm) at 40 °C, where the SC sensor exceeded the test standard value by as much as 25 percent. One of two sensors was within manufacturer’s accuracy specifications at 25 °C for all the tested SC values, while the other SC sensor was outside the manufacturer’s accuracy specifications at 100 μS/cm, exceeding the test standard value by 9 percent. One of two sensors was outside the manufacturer’s accuracy specifications at 10,000 μS/cm at 15°C, exceeding the test standard value by 3 percent. One Manta2 passed SDI-12 compliance testing with a NR Systems SDI-12 Verifier. One Manta2 was field tested for 6 weeks at USGS station 02492620, National Space Technology Laboratories (NSTL) Station, Mississippi, on the Pearl River and showed overall good agreement with a well-maintained Hydrolab Datasonde 5X site sonde for water temperature, pH, and DO. Differences in SC values between the Manta2 and the site sonde were most likely due to differences in the deployment depth of the sondes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171118","usgsCitation":"Tillman, E.F., 2017, Evaluation of the Eureka Manta2 Water-Quality Multiprobe Sonde: U.S. Geological Survey Open-File Report 2017–1118, 37 p., https://doi.org/10.3133/ofr20171118. ","productDescription":"vi, 37 p.","numberOfPages":"43","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076099","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":347738,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1118/coverthb.jpg"},{"id":347739,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1118/ofr20171118.pdf","text":"Report","size":"1.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1118"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
The Columbia River, in Washington and Oregon, and Coos Bay, in Oregon, are economically important shipping channels that are inhabited by several fishes protected under the Endangered Species Act (ESA). Maintenance of shipping channels involves dredge operations to maintain sufficient in-channel depths to allow large ships to navigate the waterways safely. Fishes entrained by dredge equipment often die or experience delayed mortality. Other potential negative effects of dredging include increased turbidity, reductions in prey resources, and the release of harmful contaminants from the dredged sediments. One species of concern is the ESA-listed green sturgeon (Acipenser medirostris; Southern Distinct Population Segment). In this study, we used acoustic telemetry to identify habitat use, arrival and departure timing, and the extent of upstream migration of green sturgeon in the Columbia River and Coos Bay to help inform dredge operations to minimize potential take of green sturgeon. Autonomous acoustic receivers were deployed in Coos Bay from the mouth to river kilometer (rkm) 21.6 from October 2009 through October 2010. In the Columbia River Estuary, receivers were deployed between the mouth and rkm 37.8 from April to November in 2010 and 2011. A total of 29 subadult and adult green sturgeon were tagged with temperature and pressure sensor tags and released during the study, primarily in Willapa Bay and Grays Harbor, Washington, and the Klamath River, Oregon. Green sturgeon detected during the study but released by other researchers also were included in the study.
The number of tagged green sturgeon detected in the two estuaries differed markedly. In Coos Bay, only one green sturgeon was detected for about 2 hours near the estuary mouth. In the Columbia River Estuary, 9 green sturgeon were detected in 2010 and 10 fish were detected in 2011. Green sturgeon entered the Columbia River from May through October during both years, with the greatest numbers of fish being present in August and September. One green sturgeon was detected at the uppermost receiver station (rkm 37.8), but overall, the number of fish detected upriver decreased rapidly with distance from the estuary mouth. Residence times of fish that were only detected in the lower 4.8 rkm generally were less than 24 hours, but fish detected farther upriver had a median residence time greater than 10 days. Green sturgeon were widely dispersed among channel and non-channel habitats in the lower estuary in 2010. In 2011, the fish were more concentrated near the estuary mouth. The intensity of use, measured as the total number of fish detections at each station, generally was greatest from Point Ellice (rkm 20.1) to Rice Island (rkm 33.0) in channel and shallow shoal areas, and lowest at the stations west of Point Ellice with the exception of the area near the entrance to the Ilwaco Channel.
Sensor tag data indicated that the deeper South and North Channel habitats (bottom depth ≥10 m) were used, as were the more shallow sandy shoal, shoreline, and bay habitats (bottom depth <10 m). Median fish depths among fish and receiver locations ranged from 2.5 to 28.2 m below water surface (bws) and water temperatures ranged from 9.1 to 22.0 °C during late May through mid-October. In the deeper channel habitat, near the Ilwaco Channel, fish inhabited water with median temperatures ranging from 11.4 to 16.7 °C, whereas east of Point Ellice, predominantly in shallow non-channel habitats, fish inhabited water with median temperatures ranging from about 17.0 to 21.0 °C.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171144","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Hansel, H.C., Romine, J.G., and Perry, R.W., 2017, Acoustic tag detections of green sturgeon in the Columbia River and Coos Bay estuaries, Washington and Oregon, 2010–11: U.S. Geological Survey Open-File Report 2017-1144, 30 p., https://doi.org/10.3133/ofr20171144.","productDescription":"vi, 30 p.","onlineOnly":"Y","ipdsId":"IP-088817","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":348413,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1144/ofr20171144.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1144"},{"id":348412,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1144/coverthb.jpg"}],"country":"United States","state":"Oregon","city":"Astoria","otherGeospatial":"Coos Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.36283111572264,\n 43.33067209551502\n ],\n [\n -124.12696838378908,\n 43.33067209551502\n ],\n [\n -124.12696838378908,\n 43.476591264232674\n ],\n [\n -124.36283111572264,\n 43.476591264232674\n ],\n [\n -124.36283111572264,\n 43.33067209551502\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.09263610839842,\n 46.14416148780093\n ],\n [\n -123.61129760742186,\n 46.14416148780093\n ],\n [\n -123.61129760742186,\n 46.32559414426375\n ],\n [\n -124.09263610839842,\n 46.32559414426375\n ],\n [\n -124.09263610839842,\n 46.14416148780093\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
The demonstration of clear linkages between planning, funding, outcomes, and performance management has created unique challenges for U.S. Federal science programs. An approach is presented here that characterizes science program strategic objectives by one of five “activity types”: (1) knowledge discovery, (2) knowledge development and delivery, (3) science support, (4) inventory and monitoring, and (5) knowledge synthesis and assessment. The activity types relate to performance measurement tools for tracking outcomes of research funded under the objective. The result is a multi-time scale, integrated performance measure that tracks individual performance metrics synthetically while also measuring progress toward long-term outcomes. Tracking performance on individual metrics provides explicit linkages to root causes of potentially suboptimal performance and captures both internal and external program drivers, such as customer relations and science support for managers. Functionally connecting strategic planning objectives with performance measurement tools is a practical approach for publicly funded science agencies that links planning, outcomes, and performance management—an enterprise that has created unique challenges for public-sector research and development programs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171143","usgsCitation":"Whalen, K.G., 2017, A concept for performance management for Federal science programs: U.S. Geological Survey Open-File Report 2017-1143, 16 p., https://doi.org/10.3133/ofr20171143.","productDescription":"iv, 16 p.","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-090006","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348313,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1143/coverthb.jpg"},{"id":348314,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1143/ofr20171143.pdf","text":"Report","size":"490 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1143"}],"contact":"Western Region Unit Supervisor
Cooperative Fish and Wildlife Research Unit Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 303
Reston, Virginia 20192