During the summer 2015, the U.S. Geological Survey collected geologic and geotechnical data for two sites on coastal bluffs along the eastern shore of Puget Sound, Washington. The U.S. Geological Survey also installed hydrologic instrumentation at the sites and collected specimens for laboratory testing. The two sites are located on City of Mukilteo open-space land and are about 0.6 kilometers apart. The bluffs at each site are approximately 42 meters high, and rise steeply from the shoreline with 32–35° slopes. The more northerly of the two sites occupies an active landslide and is mostly unvegetated. The other site is forested, and although stable during the preparation of this report, shows evidence of historical and potential landslide activity. The slopes of the bluffs at both sites are mantled by a thin, nonuniform colluvium underlain by clay-rich glacial deposits and tills of the Whidbey Formation or Double Bluff Drift. Till consisting of sand, gravel, and cobbles caps the bluffs and rests on finer grained glacial deposits of sand, silt, and clay. These types of different glacial deposits are dense, vertically fractured, and generally have low permeability, but field observations indicate that locally the deposits are sufficiently permeable to allow lateral flow of water along fractures and subhorizontal boundaries between deposits of different texture. Laboratory tests indicate that many of the deposits are highly plastic, with low hydraulic conductivity, and moderate shear strength. Steep slopes combined with the strength and hydraulic characteristics of the deposits leave the bluffs prone to slope instability, particularly during the wet season when infiltrating rainfall changes moisture content, pore-water pressure, and effective stress within the hillslope. The instrumentation was designed to primarily observe rainfall variability and hydrologic changes in the subsurface that can affect stability of the bluffs, and also to compare the hydrologic response between areas where previous landslides have disturbed vegetation and areas where the bluff is apparently more stable and well vegetated.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20161082","collaboration":"Prepared as part of a Technical Assistance Agreement with Sound Transit","usgsCitation":"Mirus, B.B., Smith, J.B., Stark, Benjamin, Lewis, York, Michel, Abigail, and Baum, R.L., 2016, Assessing landslide potential on coastal bluffs near Mukilteo, Washington—Geologic site characterization for hydrologic monitoring: U.S. Geological Survey Open-File Report 2016–1082, 28 p., https://dx.doi.org/10.3133/ofr20161082.","productDescription":"Report: vi, 34 p. HTML Document: Data Release","startPage":"1","endPage":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-075317","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":438597,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H13033","text":"USGS data release","linkHelpText":"Lab tests for specimens from Mukilteo, WA, 2016"},{"id":324697,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1082/ofr20161082.pdf","text":"Report","size":"28.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1082"},{"id":324696,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1082/coverthb.jpg"},{"id":324698,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7H13033","text":"Laboratory Testing Results: Material strength and hydraulic properties for specimens collected from coastal bluffs near Mukilteo, Washington","description":"OFR 2016-1082 Data"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.66098022460939,\n 48.448333001219005\n ],\n [\n -122.68157958984375,\n 48.448333001219005\n ],\n [\n -122.68844604492186,\n 48.43193420325806\n ],\n [\n -122.67608642578126,\n 48.4164415885222\n ],\n [\n -122.67333984374999,\n 48.37632112598019\n ],\n [\n -122.77084350585938,\n 48.26034139584532\n ],\n [\n -122.80517578125,\n 48.17158081783164\n ],\n [\n -122.91778564453125,\n 48.09275716032736\n ],\n [\n -122.90679931640624,\n 47.7476346002088\n ],\n [\n -122.90267944335938,\n 47.6441113460123\n ],\n [\n -122.80517578125,\n 47.646886969413\n ],\n [\n -122.75024414062499,\n 47.666312203609145\n ],\n [\n -122.67745971679688,\n 47.585789182379905\n ],\n [\n -122.56759643554689,\n 47.304378285521565\n ],\n [\n -122.46734619140625,\n 47.280160670764744\n ],\n [\n -122.39730834960938,\n 47.26711582310954\n ],\n [\n -122.29980468749999,\n 47.352780247239586\n ],\n [\n -122.3272705078125,\n 47.525547335516556\n ],\n [\n -122.30804443359375,\n 47.78363463526376\n ],\n [\n -122.20642089843749,\n 47.989002568678686\n ],\n [\n -122.1844482421875,\n 48.060643120324514\n ],\n [\n -122.38632202148438,\n 48.31882083063846\n ],\n [\n -122.66098022460939,\n 48.448333001219005\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS 966
Denver, CO 80225-0046
Wildfire can significantly alter the hydrologic response of a watershed to the extent that even modest rainstorms can generate dangerous flash floods and debris flows. To reduce public exposure to hazard, the U.S. Geological Survey produces post-fire debris-flow hazard assessments for select fires in the western United States. We use publicly available geospatial data describing basin morphology, burn severity, soil properties, and rainfall characteristics to estimate the statistical likelihood that debris flows will occur in response to a storm of a given rainfall intensity. Using an empirical database and refined geospatial analysis methods, we defined new equations for the prediction of debris-flow likelihood using logistic regression methods. We showed that the new logistic regression model outperformed previous models used to predict debris-flow likelihood.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161106","usgsCitation":"Staley, D.M., Negri, J.A., Kean, J.W., Laber, J.M., Tillery, A.C., and Youberg, A.M., 2016, Updated logistic regression equations for the calculation of post-fire debris-flow likelihood in the western United States: U.S. Geological Survey Open-File Report 2016–1106, 13 p., https://dx.doi.org/ofr20161106.","productDescription":"Report: iv, 13 p.; Appendix 1","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076051","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":324673,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1106/ofr20161106.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1106 Report"},{"id":324672,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1106/coverthb.jpg"},{"id":324675,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1106/ofr20161106_appx-1.xlsx","text":"Appendix 1","size":"268 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1106 Appendix 1"}],"contact":"Center Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS 966
Denver, CO 80225-0046
Mercury (Hg) analyses were conducted on samples of sport fish and water collected from selected sampling sites in Brownlee Reservoir and the Boise and Snake Rivers to meet National Pollution Discharge and Elimination System (NPDES) permit requirements for the City of Boise, Idaho, between 2013 and 2015. City of Boise personnel collected water samples from six sites between October and November 2013 and 2015, with one site sampled in 2014. Total Hg concentrations in unfiltered water samples ranged from 0.48 to 8.8 nanograms per liter (ng/L), with the highest value in Brownlee Reservoir in 2013. All Hg concentrations in water samples were less than the U.S. Environmental Protection Agency (USEPA) Hg chronic aquatic life criterion of 12 ng/L.
The USEPA recommended a water-quality criterion of 0.30 milligrams per kilogram (mg/kg) methylmercury (MeHg) expressed as a fish-tissue residue value (wet-weight MeHg in fish tissue). The Idaho Department of Environmental Quality adopted the USEPA’s fish-tissue criterion and established a reasonable potential to exceed (RPTE) threshold 20 percent lower than the criterion or greater than 0.24 mg/kg Hg based on an average concentration of 10 fish from a receiving waterbody. NPDES permitted discharge to waters with fish having Hg concentrations exceeding 0.24 mg/kg are said to have a reasonable potential to exceed the water-quality criterion and thus are subject to additional permit obligations, such as requirements for increased monitoring and the development of a Hg minimization plan. The Idaho Fish Consumption Advisory Program (IFCAP) issues fish advisories to protect general and sensitive populations of fish consumers and has developed an action level of 0.22 mg/kg Hg in fish tissue. Fish consumption advisories are water body- and species-specific and are used to advise allowable fish consumption from specific water bodies. The geometric mean Hg concentration of 10 fish of a single species collected from a single water body (lake or stream) in Idaho is compared to the action level to determine if a fish consumption advisory should be issued.
The U.S. Geological Survey collected and analyzed individual fillets of mountain whitefish (Prosopium williamsoni), rainbow trout (Oncorhynchus mykiss), smallmouth bass (Micropterus dolomieu), and channel catfish (Ictalurus punctatus) for Hg. The 2013 average Hg concentration for small mouth bass (0.32 mg/kg) collected at Brownlee Reservoir and for channel catfish (0.33 mg/kg) collected at the Boise River mouth, exceeded the Idaho water quality criterion (>0.3 mg/kg), the Hg RPTE threshold (>0.24 mg/kg), and the IFCAP action level (>0.22 mg/kg). Average Hg concentrations in fish collected in 2014 or 2015 did not exceed evaluation criteria for any of the species assessed.
Selenium (Se) analysis was conducted on one composite fish tissue sample per site to assess general concentrations and to provide information for future risk assessments. Composite concentrations of Se in fish tissue collected between 2013 and 2015 ranged from 0.07 and 0.49 mg/kg wet weight with the highest concentration collected from smallmouth bass from the Snake River near Murphy, and the lowest from mountain whitefish from the Boise River at Eckert Road.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161098","collaboration":"Prepared in cooperation with the City of Boise, Idaho","usgsCitation":"Williams, M.L., and MacCoy, D.E., 2016, Mercury concentrations in water and mercury and selenium concentrations in fish from Brownlee Reservoir and selected sites in the Boise and Snake Rivers, Idaho and Oregon, 2013–15: U.S. Geological Survey Open-File Report 2016–1098, 29 p., https://dx.doi.org/10.3133/ofr20161098.","productDescription":"iv, 38p.","startPage":"1","endPage":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070289","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":324695,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1098/ofr20161098.pdf","text":"Report","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1098"},{"id":324694,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1098/coverthb.jpg"}],"country":"United States","state":"Idaho","city":"Boise","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.6912841796875,\n 43.07089421067248\n ],\n [\n -116.6912841796875,\n 44.004669106432225\n ],\n [\n -115.58990478515625,\n 44.004669106432225\n ],\n [\n -115.58990478515625,\n 43.07089421067248\n ],\n [\n -116.6912841796875,\n 43.07089421067248\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
The jaguar is the largest Neotropical felid and the only extant representative of the genus Panthera in the Americas. In recorded history, the jaguars range has extended from the Southern United States, throughout Mexico, to Central and South America, and they occupy a wide variety of habitats. A previous jaguar genetic study found high historical levels of gene flow among jaguar populations over broad areas but did not include any samples of jaguar from the States of Arizona, United States, or Sonora, Mexico. Arizona and Sonora have been part of the historical distribution of jaguars; however, poaching and habitat fragmentation have limited their distribution until they were declared extinct in the United States and endangered in Sonora. Therefore, a need was apparent to have this northernmost (Arizona/Sonora) jaguar population included in an overall jaguar molecular taxonomy and genetic diversity analyses. In this study, we used molecular genetic markers to examine diversity and taxonomy for jaguars in the Northwestern Jaguar Recovery Unit (NJRU; Sonora, Sinaloa, and Jalisco, Mexico; and southern Arizona and New Mexico, United States) relative to jaguars in other parts of the jaguar range (Central and South America). The objectives of this study were to:
Leader, Arizona Cooperative Fish and Wildlife Research Unit
U.S. Geological Survey
325 Biosciences East
Tucson, Arizona 85721
http://www.coopunits.org/Arizona/
Bacteria related to the intestinal tract of humans and other warm-blooded animals have been detected in fresh and saline surface waters used for recreational purposes in coastal areas of Horry County, South Carolina, since the early 2000s. Specifically, concentrations of the facultative anaerobic organism, Enterococcus, have been observed to exceed the single-sample regulatory limit of 104 colony forming units per 100 milliliters of water. Water bodies characterized by these concentrations are identified on the 303(d) list for impaired water in South Carolina; moreover, because current analytical methods used to monitor Enterococcus concentrations take up to 1 day for results to become available, water-quality advisories are not reflective of the actual health risk.
\nTo determine if Enterococcus concentrations in surface water could be assessed in a more rapid manner, an investigation was completed between 2003 and 2004 in the study area of coastal Horry County, South Carolina. The study was designed to assess the relation between Enterococcus concentrations and turbidity, which, unlike Enterococcus concentrations, can be measured continuously by using a multiparameter water-quality sensor and results reported in real time. In 2003, three water-quality data collection stations that included a multiparameter water-quality sensor that measured turbidity were located in three representative surface-water basins in coastal Horry County, South Carolina. All these locations had previous reports of high Enterococcus concentrations. At each station, the water-quality sensor was placed in the water column and continuously measured turbidity, pH, specific conductivity, dissolved oxygen, and temperature. Each water-quality data collection station also monitored instantaneous precipitation and wind speed and direction. Surface-water samples were collected at each station during events characterized by no precipitation and by some recorded precipitation using manual and automatic methods, and analyzed for Enterococcus concentrations. A comparison of Enterococcus concentrations in surface-water samples collected simultaneously using both methods indicated a positive relation, although the average percent relative difference between the methods was 46 percent.
\nDuring a period of no precipitation in February 2004, no relation between turbidity and Enterococcus concentrations was observed for surface-water samples collected at the water-quality data collection station located in the channel that drains a freshwater swamp. In contrast, during periods of precipitation in March and August 2004 at this location, a positive relation was observed between turbidity and Enterococcus concentrations in surface-water samples; that is, water samples characterized by higher turbidity also contained higher Enterococcus concentrations. At the water-quality data collection station located in a channel that drains to the surf zone of the Atlantic Ocean, no relation was observed between turbidity and Enterococcus concentrations during periods of either no precipitation (July 2004) or precipitation (August 2004). At this location, the turbidity was inversely related to relative tide height, high turbidity was observed during low tide when freshwater flowed seaward, and low turbidity was observed during high tide when saline seawater flowed landward.
\nThe positive relation observed between turbidity and Enterococcus concentrations in surface water at the water-quality data collection station located in the channel that drains a freshwater swamp may be attributed to bacterial survival in the abundant channel bed sediments that characterized this more naturalized area. Surface-water bed sediments collected near each water-quality data collection station and the surf zone were incubated in static microcosms in the laboratory and analyzed for Enterococcus concentrations over time. Enterococcus concentrations continued to persist in bed sediments collected in the channel that drains the swamp even after almost 4 months of incubation. Conversely, enterococci were not observed to persist in bed sediments characterized by high specific conductance. Although it is currently (2016) unknown whether this persistence of enterococci demonstrates growth or viability, the data indicate that enterococci can exist in channel bed-sediment environments outside of a host for a long time. This observation confirms previous reports that challenge the use of Enterococcus concentrations as an indicator of the recent introduction of fecal-related material and the associated acute risk to other pathogens.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20161015","collaboration":"Prepared in cooperation with Horry County Stormwater Management ","usgsCitation":"Landmeyer, J.E., and Garigen, T.J., 2016, Relation between Enterococcus concentrations and turbidity in fresh and saline recreational waters, coastal Horry County, South Carolina, 2003–04: U.S. Geological Survey Open-File Report 2016–1015, 21 p., https://dx.doi.org/10.3133/ofr20161015.","productDescription":"Report: viii, 21 p., Appendixes: Tables 1-1, 1-2, 1-3","startPage":"1","endPage":"21","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064657","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":324066,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1015/ofr20161015.pdf","text":"Report","size":"12.3 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South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive, Suite 500
Norcross, GA 30093
(678) 924–6700
https://www.usgs.gov/water/southatlantic/
The endangered Cape Sable seaside sparrow (Ammodramus maritimus mirabilis) is endemic to south Florida and a key indicator species of marl prairie, a highly diverse freshwater community in the Florida Everglades. Maintenance and creation of suitable habitat is seen as the most important pathway to the persistence of the six existing sparrow subpopulations; however, major uncertainties remain in how to increase suitable habitat within and surrounding these subpopulations, which are vulnerable to environmental stochasticity. Currently, consistently suitable conditions for the Cape Sable seaside sparrow are only present in two of these subpopulations (B and E). The water management scenarios evaluated herein were intended to lower water levels and improve habitat conditions in subpopulation A and D, raise water levels to improve habitat conditions in subpopulations C and F, and minimize impacts to subpopulations B and E. Our objective in this analysis was to compare these scenarios utilizing a set of metrics (short- to long-time scales) that relate habitat suitability to hydrologic conditions. Although hydrologic outputs are similar across scenarios in subpopulation A, scenario R2H reaches the hydroperiod and depth suitability targets more than the other scenarios relative to ECB, while minimizing negative consequences to subpopulation E. However, although R2H hydroperiods are longer than those for ECB during the wet season in subpopulations C and F, depths during the breeding season are predicted to decrease in suitability (less than -50 cm) relative to existing conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161107","usgsCitation":"Beerens, J.M., Romañach, S.S., and McKelvy, Mark. 2016, Evaluating water management scenarios to support habitat management for the Cape Sable seaside sparrow: U.S. Geological Survey Open-File Report 2016-1107, 62 p., https://dx.doi.org/10.3133/ofr20161107.","productDescription":"x, 52 p.","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076424","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":324233,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1107/ofr20161107.pdf","text":"Report","size":"5.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1107"},{"id":324232,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1107/coverthb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.84814453125,\n 25.110471486223346\n ],\n [\n -81.84814453125,\n 26.23430203240673\n ],\n [\n -80.079345703125,\n 26.23430203240673\n ],\n [\n -80.079345703125,\n 25.110471486223346\n ],\n [\n -81.84814453125,\n 25.110471486223346\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,
https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc
","tableOfContents":"The software program, QRev applies common and consistent computational algorithms combined with automated filtering and quality assessment of the data to improve the quality and efficiency of streamflow measurements and helps ensure that U.S. Geological Survey streamflow measurements are consistent, accurate, and independent of the manufacturer of the instrument used to make the measurement. Software from different manufacturers uses different algorithms for various aspects of the data processing and discharge computation. The algorithms used by QRev to filter data, interpolate data, and compute discharge are documented and compared to the algorithms used in the manufacturers’ software. QRev applies consistent algorithms and creates a data structure that is independent of the data source. QRev saves an extensible markup language (XML) file that can be imported into databases or electronic field notes software. This report is the technical manual for version 2.8 of QRev.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161068","usgsCitation":"Mueller, D.S., 2016, QRev—Software for computation and quality assurance of acoustic Doppler current profiler moving-boat streamflow measurements—Technical manual for version 2.8: U.S. Geological Survey Open-File Report, 2016–1068, 79 p., https://dx.doi.org/10.3133/ofr20161068.","productDescription":"vi, 79 p.","numberOfPages":"87","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073115","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":324040,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/ofr20161052","text":"Open-File Report 2016–1052 - ","linkHelpText":"QRev—Software for computation and quality assurance of acoustic Doppler current profiler moving-boat streamflow measurements—User’s manual for version 2.8"},{"id":324033,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1068/ofr20161068.pdf","text":"Report","size":"3.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1068"},{"id":324032,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1068/coverthb.jpg"}],"contact":"Chief, USGS Office of Surface Water
415 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
(703) 648-5301
Or visit the Office of Surface Water Web site at: http://water.usgs.gov/osw/
","tableOfContents":"Resource managers rely on abundance or density metrics derived from beach seine surveys to make vital decisions that affect fish population dynamics and assemblage structure. However, abundance and density metrics may be biased by imperfect capture and lack of geographic closure during sampling. Currently, there is considerable uncertainty about the capture efficiency of juvenile Chinook salmon (Oncorhynchus tshawytscha) by beach seines. Heterogeneity in capture can occur through unrealistic assumptions of closure and from variation in the probability of capture caused by environmental conditions. We evaluated the assumptions of closure and the influence of environmental conditions on capture efficiency and abundance estimates of Chinook salmon from beach seining within the Sacramento–San Joaquin Delta and the San Francisco Bay. Beach seine capture efficiency was measured using a stratified random sampling design combined with open and closed replicate depletion sampling. A total of 56 samples were collected during the spring of 2014. To assess variability in capture probability and the absolute abundance of juvenile Chinook salmon, beach seine capture efficiency data were fitted to the paired depletion design using modified N-mixture models. These models allowed us to explicitly test the closure assumption and estimate environmental effects on the probability of capture. We determined that our updated method allowing for lack of closure between depletion samples drastically outperformed traditional data analysis that assumes closure among replicate samples. The best-fit model (lowest-valued Akaike Information Criterion model) included the probability of fish being available for capture (relaxed closure assumption), capture probability modeled as a function of water velocity and percent coverage of fine sediment, and abundance modeled as a function of sample area, temperature, and water velocity. Given that beach seining is a ubiquitous sampling technique for many species, our improved sampling design and analysis could provide significant improvements in density and abundance estimation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161099","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Perry, R.W., Kirsch, J.E., and Hendrix, A.N., 2016, Estimating juvenile Chinook salmon (Oncorhynchus tshawytscha) abundance from beach seine data collected in the Sacramento–San Joaquin Delta and San Francisco Bay, California: U.S. Geological Survey Open-File Report 2016–1099, 21 p., https://dx.doi.org/10.3133/ofr20161099.","productDescription":"iv, 21 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074132","costCenters":[{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":323938,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1099/coverthb.jpg"},{"id":323939,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1099/ofr20161099.pdf","text":"Report","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1099"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin Delta, San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.5579833984375,\n 37.31338308990806\n ],\n [\n -122.5579833984375,\n 39.21523130910493\n ],\n [\n -121.1077880859375,\n 39.21523130910493\n ],\n [\n -121.1077880859375,\n 37.31338308990806\n ],\n [\n -122.5579833984375,\n 37.31338308990806\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
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http://wfrc.usgs.gov/
From May 2011 to August 2014, the U.S. Geological Survey (USGS) collected gravity data at more than 2,300 stations and physical property measurements on more than 640 rock samples from outcrops in the eastern Mojave Desert, California and Nevada. Gravity, magnetic, and physical-property data are used to study and locate regional crustal structures as an aid to understanding the geologic framework related to mineral resources of the eastern Mojave Desert.
The eastern Mojave Desert is host to a world-class rare earth element carbonatite deposit located at Mountain Pass, California. Carbonatites are typically defined as magmatic rocks with high modal abundances of primary carbonate minerals >50 weight percent and elevated abundances of rare earth elements (REEs) (Nelson and others, 1988; Woolley and Kempe, 1989). The “Sulphide Queen” carbonatite ore deposit is a composite, tabular body made up of sills and dikes of REE-bearing sovites and beforsites that occurs just south of the Clark Mountain Range along a north-northwest trending fault-bounded block that extends along the northeast edge of the Mescal Range and northwestern extent of Ivanpah Mountains. This early to middle Proterozoic block is composed of a 1.7 Ga metamorphic complex of gneiss and schist that underwent widespread metamorphism and associated plutonism during the Ivanpah orogeny (Miller and others, 2007). Subsequently, these rocks were intruded by a series of granitoids, which included the 1.4 Ga (DeWitt and others, 1987) ultrapotassic alkaline suite of intrusions that are spatially and temporally associated with hundreds of dikes, outcrops, and a carbonatite ore body. The relative age sequence of this intrusive suite of alkaline rocks from oldest to youngest includes shonkinite, mesosyenite, syenite, quartz syenite, potassic granite, carbonatite, and late shonkinite dikes (Olson and others, 1954; Wooden and Miller, 1990; Haxel, 2005; Miller and others, 2007).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161070","usgsCitation":"Denton, K.M., and Ponce, D.A., 2018, Gravity and magnetic studies of the eastern Mojave Desert, California and Nevada (ver 1.1, August 2018): U.S. Geological Survey Open-File Report 2016-1070, 20 p., https://doi.org/10.3133/ofr20161070.","productDescription":"Report: iv, 20 p.; 3 Tables; Metadata; version history","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-05-01","ipdsId":"IP-064300","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":323913,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1070/ofr20161070_table01_gravity_data_v1.1.xlsx","text":"Table 1 version 1.1","size":"472 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1070 Table 1 ver. 1.1"},{"id":323914,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1070/ofr20161070_table02_rock_property_data.xlsx","text":"Table 2","size":"128 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1070 Table 2"},{"id":323915,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1070/ofr20161070_table03_rock_modifier_data.xlsx","text":"Table 3","size":"20 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1070 Table 3"},{"id":323910,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1070/coverthb_.jpg"},{"id":323911,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1070/ofr20161070_v1.1.pdf","text":"Report","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1070"},{"id":323912,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2016/1070/ofr20161070_metadata.txt","size":"3 KB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2016-1070 Metadata"},{"id":356639,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2016/1070/versionHist.txt"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.5,\n 35.0\n ],\n [\n -115.5,\n 35.5\n ],\n [\n -115.0,\n 35.5\n ],\n [\n -115.0,\n 35.0\n ],\n [\n -115.5,\n 35.0\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"ver. 1.1: August 2018; ver. 1: June 2016","contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Tucson
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ENRB Bldg, 520 N. Park Ave, Rm 355
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Flooding occurred in the central and southeastern United States during December 2015 and January 2016. The flooding was the result of more than 20 inches of rain falling in a 19 day period from December 12 to December 31, 2015. U.S. Geological Survey streamgages recorded 23 peaks of record during the subsequent flooding, with a total of 172 streamgages recording peaks that ranked in the top 5 all time for the period of record.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161092","usgsCitation":"Holmes, R.R., Jr., Watson, K.M., and Harris, T.E., 2016, Preliminary peak stage and streamflow data at selected U.S. Geological Survey streamgages for flooding in the central and southeastern United States during December 2015 and January 2016: U.S. Geological Survey Open-File Report 2016–1092, 27 p., https://dx.doi.org/10.3133/ofr20161092.","productDescription":"iv, 28 p.","startPage":"1","endPage":"28","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074393","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":323762,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1092/ofr20161092.pdf","text":"Report","size":"38.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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States\"}}]}","contact":"Chief, Office of Surface Water
U.S. Geological Survey
415 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Or visit the Office of Surface Water Web site at:
http://water.usgs.gov/osw/
Ulaanbaatar, the capital city of Mongolia (fig. 1), is dependent on groundwater for its municipal and industrial water supply. The population of Mongolia is about 3 million people, with about one-half the population residing in or near Ulaanbaatar (World Population Review, 2016). Groundwater is drawn from a network of shallow wells in an alluvial aquifer along the Tuul River. Evidence indicates that current water use may not be sustainable from existing water sources, especially when factoring the projected water demand from a rapidly growing urban population (Ministry of Environment and Green Development, 2013). In response, the Government of Mongolia Ministry of Environment, Green Development, and Tourism (MEGDT) and the Freshwater Institute, Mongolia, requested technical assistance on groundwater modeling through the U.S. Army Corps of Engineers (USACE) to the U.S. Geological Survey (USGS). Scientists from the USGS and USACE provided two workshops in 2015 to Mongolian hydrology experts on basic principles of groundwater modeling using the USGS groundwater modeling program MODFLOW-2005 (Harbaugh, 2005). The purpose of the workshops was to bring together representatives from the Government of Mongolia, local universities, technical experts, and other key stakeholders to build in-country capacity in hydrogeology and groundwater modeling.
A preliminary steady-state groundwater-flow model was developed as part of the workshops to demonstrate groundwater modeling techniques to simulate groundwater conditions in alluvial deposits along the Tuul River in the vicinity of Ulaanbaatar. ModelMuse (Winston, 2009) was used as the graphical user interface for MODFLOW for training purposes during the workshops. Basic and advanced groundwater modeling concepts included in the workshops were groundwater principles; estimating hydraulic properties; developing model grids, data sets, and MODFLOW input files; and viewing and evaluating MODFLOW output files. A key to success was developing in-country technical capacity and partnerships with the Mongolian University of Science and Technology; Freshwater Institute, Mongolia, a non-profit organization; United Nations Educational, Scientific and Cultural Organization (UNESCO); the Government of Mongolia; and the USACE.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161096","collaboration":"Prepared in cooperation with U.S. Army Corps of Engineers; U.S. Pacific Command; United Nations Educational, Scientific and Cultural Organization (UNESCO) and International Center for Integrated Water Resources Management under the auspices of UNESCO; Government of Mongolia Ministry of Environment, Green Development, and Tourism; and Freshwater Institute, Mongolia","usgsCitation":"Valder, J.F., Carter, J.M., Anderson, M.T., Davis, K.W., Haynes M.A., and Dechinlhundev, Dorjsuren, 2016, Building groundwater modeling capacity in Mongolia: U.S. Geological Survey Open-File Report 2016–1096, 1 sheet, https://dx.doi.org/10.3133/ofr20161096.","productDescription":"Sheet: 60.00 x 36.00 inches","numberOfPages":"1","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-075136","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":323764,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1096/ofr20161096.pdf","text":"Report","size":"8.91 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1096"},{"id":323763,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1096/coverthb.jpg"}],"country":"Mongolia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[87.75126,49.2972],[88.80557,49.47052],[90.71367,50.33181],[92.23471,50.80217],[93.10422,50.49529],[94.14757,50.48054],[94.81595,50.01343],[95.81403,49.97747],[97.25973,49.72606],[98.23176,50.4224],[97.82574,51.011],[98.86149,52.04737],[99.98173,51.63401],[100.88948,51.51686],[102.06522,51.25992],[102.25591,50.51056],[103.67655,50.08997],[104.62155,50.27533],[105.88659,50.40602],[106.8888,50.2743],[107.86818,49.79371],[108.47517,49.28255],[109.40245,49.29296],[110.66201,49.13013],[111.58123,49.37797],[112.89774,49.54357],[114.36246,50.2483],[114.96211,50.14025],[115.4857,49.80518],[116.6788,49.88853],[116.1918,49.1346],[115.48528,48.13538],[115.74284,47.72654],[116.30895,47.85341],[117.29551,47.69771],[118.06414,48.06673],[118.86657,47.74706],[119.77282,47.04806],[119.66327,46.69268],[118.87433,46.80541],[117.4217,46.67273],[116.71787,46.3882],[115.9851,45.72724],[114.46033,45.33982],[113.46391,44.80889],[112.43606,45.01165],[111.87331,45.10208],[111.34838,44.45744],[111.66774,44.07318],[111.82959,43.74312],[111.12968,43.40683],[110.4121,42.87123],[109.2436,42.51945],[107.74477,42.48152],[106.12932,42.13433],[104.96499,41.59741],[104.52228,41.90835],[103.31228,41.90747],[101.83304,42.51487],[100.84587,42.6638],[99.51582,42.52469],[97.45176,42.74889],[96.3494,42.72564],[95.76245,43.31945],[95.30688,44.24133],[94.68893,44.35233],[93.48073,44.97547],[92.13389,45.11508],[90.94554,45.28607],[90.58577,45.71972],[90.97081,46.88815],[90.28083,47.69355],[88.8543,48.06908],[88.01383,48.59946],[87.75126,49.2972]]]},\"properties\":{\"name\":\"Mongolia\"}}]}","contact":"Director, South Dakota Water Science Center
U.S. Geological Survey
1608 Mountain View Road
Rapid City, South Dakota 57702
Or visit the South Dakota Water Science Center Web site at:
http://sd.water.usgs.gov/
The primary goal of the Trinity River Restoration Program is to rehabilitate the fisheries on the dam-controlled Trinity River. However, maintaining and enhancing other wildlife populations through the restoration initiative is also a key objective. Foothill yellow-legged frogs (Rana boylii) and western pond turtles (Actinemys marmorata) have been identified as important herpetological species on which to focus monitoring efforts due to their status as California state-listed species of concern and potential listing on the U.S. Endangered Species List. We developed and implemented a monitoring strategy for these species specific to the Trinity River with the objectives of establishing baseline values for probabilities of site occupancy, colonization, and local extinction; identifying site characteristics that correlate with the probability of extinction; and estimating overall trends in abundance. Our 3-year study suggests that foothill yellow-legged frogs declined in the probability of site occupancy. Conversely, our results suggest that western pond turtles increased in both abundance and the probability of site occupancy. The short length of our study period makes it difficult to draw firm conclusions, but these results provide much-needed baseline data. Further monitoring and directed studies are required to assess how habitat changes and management decisions relate to the status and trend of these species over the long term.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161089","collaboration":"Prepared in cooperation with the Trinity River Restoration Program","usgsCitation":"Snover, M.L., and Adams, M.J., 2016, Herpetological monitoring and assessment on the Trinity River, Trinity County, California—Final report: U.S. Geological Survey Open-File Report 2016-1089, 93 p., https://dx.doi.org/10.3133/ofr20161089.","productDescription":"vi, 93 p.","numberOfPages":"103","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070527","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":323596,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1089/ofr20161089.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
Predation of endangered Lost River suckers (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) during larval egress to Upper Klamath Lake from the Williamson River is poorly understood but may be an important factor limiting recruitment into adult spawning populations. Native and non-native piscivores are abundant in nursery wetland habitat, but larval predation has not been directly studied for all species. Larvae lack hard body structures and digest rapidly in predator digestive systems. Therefore, traditional visual methods for diet analysis may fail to identify the extent of predation on larvae. The goals of this study were to (1) use quantitative polymerase chain reaction (qPCR) and single nucleotide polymorphism (SNP) assays developed for Lost River and shortnose suckers to assay predator stomach contents for sucker DNA, and (2) to assess our ability to use this technique to study predation. Predators were captured opportunistically during larval sucker egress. Concurrent feeding trials indicate that most predators—yellow perch (Perca flaverscens), fathead minnow (Pimephales promelas), blue chub (Gila coerulea), Klamath tui chub (Siphatales bicolor bicolor), Klamath Lake sculpin (Cottus princeps), slender sculpin (Cottus tenuis)—preyed on sucker larvae in the laboratory. However, sucker DNA was not detected in fathead minnow stomachs. Of the stomachs screened from fish captured in the Williamson River Delta, 15.6 percent of yellow perch contained sucker DNA. This study has demonstrated that the application of qPCR and SNP assays is effective for studying predation on larval suckers. We suggest that techniques associated with dissection or detection of sucker DNA from fathead minnow stomachs need improvement.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161094","usgsCitation":"Hereford, D.M., Ostberg, C.O., and Burdick, S.M., 2016, Predation on larval suckers in the Williamson River Delta revealed by molecular genetic assays—A pilot study: U.S. Geological Survey Open-File Report 2016-1094, 16 p., https://dx.doi.org/10.3133/ofr20161094.","productDescription":"iv, 16 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074834","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":323556,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1094/coverthb.jpg"},{"id":323557,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1094/ofr20161094.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1094"}],"country":"United States","state":"Oregon","otherGeospatial":"Williamson River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.95922851562501,\n 42.484504292781125\n ],\n [\n -121.95922851562501,\n 42.5171568649003\n ],\n [\n -121.91493988037108,\n 42.5171568649003\n ],\n [\n -121.91493988037108,\n 42.484504292781125\n ],\n [\n -121.95922851562501,\n 42.484504292781125\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/
In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath bathymetry data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow subsurface geology.
The Monterey Canyon and Vicinity map area lies within Monterey Bay in central California. Monterey Bay is one of the largest embayments along the west coast of the United States, spanning 36 km from its northern to southern tips (in Santa Cruz and Monterey, respectively) and 20 km along its central axis. Not only does it contain one of the broadest sections of continental shelf along California’s coast, it also contains Monterey Canyon, one of the largest and deepest submarine canyons in the world. Note that the California’s State Waters limit extends farther offshore between Santa Cruz and Monterey so that it encompasses all of Monterey Bay.
The coastal area within the map area is lightly populated. The community of Moss Landing (population, 204) hosts the largest commercial fishing fleet in Monterey Bay in its harbor. The map area also includes parts of the cities of Marina (population, about 20,000) and Castroville (population, about 6,500). Fertile lowlands of the Salinas River and Pajaro River valleys largely occupy the inland part of the map area, and land use is primarily agricultural.
The offshore part of the map area lies completely within the Monterey Bay National Marine Sanctuary. The map area also includes Portuguese Ledge and Soquel Canyon State Marine Conservation Areas. Designated conservation and (or) recreation areas in the onshore part of the map area include Salinas River National Wildlife Refuge, Elkhorn Slough State Marine Conservation Area, Elkhorn Slough State Marine Reserve, Moss Landing Wildlife Area, Zmudowski and Salinas River State Beaches, and Marina Dunes Preserve.
Monterey Bay, a geologically complex area within a tectonically active continental margin, lies between two major, converging strike-slip faults. The northwest-striking San Andreas Fault lies about 34 km east of Monterey Bay; this section of the fault ruptured in both the 1989 M6.9 Loma Prieta earthquake and the 1906 M7.8 great California earthquake. The northwest-striking San Gregorio Fault crosses Monterey Canyon west of Monterey Bay. Between these two regional faults, strain is accommodated by the northwest-striking Monterey Bay Fault Zone. Deformation associated with these major regional faults and related structures has resulted in uplift of the Santa Cruz Mountains, as well as the granitic highlands of the Monterey peninsula.
Monterey Canyon begins in the nearshore area directly offshore of Moss Landing and Elkhorn Slough, and it can be traced for more than 400 km seaward, out to water depths of more than 4,000 m. Within the map area, the canyon can be traced for about 42 km to a water depth of about 1,520 m. The head of the canyon consists of three branches that begin about 150 m offshore of Moss Landing Harbor. At 500 m offshore, the canyon is already 70 m deep and 750 m wide. Large sand waves, which have heights from 1 to 3 m and wavelengths of about 50 m, are present along the channel axis in the upper 4 km of the canyon.
Soquel Canyon is the most prominent tributary of Monterey Canyon within the map area. The head of Soquel Canyon is isolated from coastal watersheds and, thus, is considered inactive as a conduit for coarse sediment transport.
North and south of Monterey and Soquel Canyons, the relatively flat continental shelf contains only a few rocky outcrop exposures. Bedrock is covered largely by sediment derived from the Salinas and Pajaro Rivers. North of Monterey Canyon, the broad and flat continental shelf dips gently seaward, to water depths of about 95 m. To the south, the shelf also dips slightly, to water depths of as much as 150 m along the canyon edge.
In the map area, Monterey Canyon splits the Santa Cruz littoral cell (north of the canyon) and the southern Monterey littoral cell (south of the canyon). It is estimated that about 400,000 m3/yr of sand on average enters Monterey Canyon from both of these littoral cells.
In the Santa Cruz littoral cell, sand generally travels east and south. Sand is supplied through sea cliff erosion, as well as from the San Lorenzo River, the Pajaro River, and several other smaller coastal watersheds. About 152,911 m3/yr of sand is dredged from the entrance channel of the Santa Cruz Small Craft Harbor north of the map area and then placed on beaches to the east (downdrift) of it. This sand feeds the beaches in the southeastern reach of the Santa Cruz littoral cell and (or) is eventually trapped and lost by Monterey Canyon.
The southern Monterey Bay littoral cell in the map area consists of two subcells. From the head of Monterey Canyon to the Salinas River, littoral drift is dominantly to the north; sand entering the ocean from the Salinas River either is deposited offshore or travels north in the littoral zone, nourishing the beaches until it is transported down Monterey Canyon. From south of the Salinas River to the southern extent of the map area, coastal sediment is moved mainly to the south; dune erosion is the only significant source of sand in this subcell.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161072","usgsCitation":"Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., Endris, C.A., and Krigsman, L.M. (P. Dartnell and S.A. Cochran, eds.), 2016, California State Waters Map Series — Monterey Canyon and Vicinity, California: U.S. Geological Survey Open-File Report 2016–1072, 48 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20161072.","productDescription":"Pamphlet: iv, 48 p.; 10 Sheets: 72.75 x 36.00 inches or smaller; Data Catalog; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059488","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438614,"rank":22,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7XD0ZQ4","text":"USGS data release","linkHelpText":"California State Waters Map Series Data Catalog--Monterey Canyon and Vicinity, California"},{"id":321805,"rank":20,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20161025","text":"Open-File Report 2016–1025","linkHelpText":"California State Waters Map Series—Offshore of Aptos, California, by Guy R. 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Each GIS data file is listed with a brief description, a small image, and links to the metadata files and the downloadable data files."},{"id":321796,"rank":11,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_sheet9.pdf","text":"Sheet 9","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1072 Sheet 9 PDF","linkHelpText":"Local (Monterey Canyon and Vicinity Map Area) and Regional (Offshore from Pigeon Point to Southern Monterey Bay) Shallow-Subsurface Geology and Structure, California By Katherine L. Maier, Samuel Y. Johnson, Stephen R. Hartwell, Janet T. Watt, and Ray W. Sliter"},{"id":321794,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_sheet7.pdf","text":"Sheet 7","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1072 Sheet 7 PDF","linkHelpText":"Potential Marine Benthic Habitats, Monterey Canyon and Vicinity Map Area, California By Bryan E. Dieter, Charles A. Endris, H. Gary Greene, and Mercedes D. Erdey"},{"id":321792,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_sheet5.pdf","text":"Sheet 5","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1072 Sheet 5 PDF","linkHelpText":"Seafloor Character, Monterey Canyon and Vicinity Map Area, California By Mercedes D. Erdey and Guy R. Cochrane"},{"id":321791,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_sheet4.pdf","text":"Sheet 4","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1072 Sheet 4 PDF","linkHelpText":"Data Integration and Visualization, Monterey Canyon and Vicinity Map Area, California By Peter Dartnell"},{"id":321790,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_sheet3.pdf","text":"Sheet 3","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1072 Sheet 3 PDF","linkHelpText":"Acoustic Backscatter, Monterey Canyon and Vicinity Map Area, California By Peter Dartnell, Andrew C. Ritchie, David P. Finlayson, and Rikk G. 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Kvitek"},{"id":399103,"rank":21,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_104300.htm"},{"id":321799,"rank":14,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_metadata.html"},{"id":321797,"rank":12,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2016/1072/ofr20161072_sheet10.pdf","text":"Sheet 10","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1072 Sheet 10 PDF","linkHelpText":"Offshore and Onshore Geology and Geomorphology, Monterey Canyon and Vicinity Map Area, California By Katherine L. Maier, Stephen R. Hartwell, Samuel Y. Johnson, Clifton W. Davenport, and H. 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Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2016-06-10","noUsgsAuthors":false,"publicationDate":"2016-06-10","publicationStatus":"PW","scienceBaseUri":"575bd6a0e4b04f417c275edb","contributors":{"editors":[{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":630600,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cochran, Susan A. 0000-0002-2442-8787 scochran@usgs.gov","orcid":"https://orcid.org/0000-0002-2442-8787","contributorId":2062,"corporation":false,"usgs":true,"family":"Cochran","given":"Susan A.","email":"scochran@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science 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Because of the jaguar’s (Panthera onca) endangered status under the Endangered Species Act (ESA) of 1973 throughout its range (from Arizona in the north to Argentina in the south), jaguar individuals and populations are monitored to varying degrees throughout their range. Knowledge gained from monitoring jaguars is helpful for wildlife managers who are responsible for conserving this species. The University of Arizona (UA) has conducted a multiyear surveying and monitoring effort for jaguars and ocelots in southern Arizona and New Mexico. The purpose of this work was to establish an effective surveying and monitoring system for jaguars along the United States-Mexico border. Surveying and monitoring in this study focused on the United States side of the border, but the methods could also be used in Mexico. The intent was to develop and implement a surveying and monitoring system that would provide the greatest probability of recording jaguar presence in, and passage through, the border area.
\nThis project established and implemented a noninvasive system for detecting and monitoring jaguars. The study area incorporates most of the mountainous areas north of the United States-Mexico international border and south of Interstate 10, from the Baboquivari Mountains in Arizona to the Animas Mountains in New Mexico. We used two primary methods to detect exact jaguar locations: paired motion-sensor trail cameras, and genetic testing of large carnivore scat collected in the field. We emphasize that this project used entirely noninvasive methods and no jaguars were captured, radiocollared, baited, or harassed in any way. Scat sample collection occurred during the entire field part of the study, but was intensified with the use of a trained scat detection dog following the first jaguar photo detection event (photo detection event was October 2012, scat detection dog began working January 2013). We also collected weather, vegetation, and geographic information system (GIS) data to analyze in conjunction with photo and video data. The results of this study are intended to aid and inform future management and conservation practices for jaguars and ocelots in this region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161095","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Culver, Melanie, 2016, Jaguar surveying and monitoring in the United States (ver. 1.1, November 2016): U.S. Geological Survey Open-File Report 2016–1095, 228 p., https://dx.doi.org/10.3133/ofr20161095.","productDescription":"228 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-075400","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323458,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1095/ofr20161095.pdf","text":"Report","size":"18.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1095"},{"id":323457,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1095/coverthb.jpg"},{"id":330879,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2016/1095/versionHist.txt","size":"708 bytes","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2016-1095 Version History"}],"country":"United States","state":"Arizona, California, New Mexico, Texas","otherGeospatial":"United States - Mexico Border","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.3779296875,\n 33.50475906922606\n ],\n [\n -104.9853515625,\n 32.32427558887655\n ],\n [\n -97.3388671875,\n 27.644606381943326\n ],\n [\n -97.3828125,\n 24.806681353851964\n ],\n [\n -102.26074218749999,\n 27.955591004642553\n ],\n [\n -106.74316406249999,\n 30.29701788337205\n ],\n [\n -117.158203125,\n 31.203404950917395\n ],\n [\n -117.3779296875,\n 33.50475906922606\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Leader, Arizona Cooperative Fish and Wildlife Research Unit
U.S. Geological Survey
325 Biosciences East
Tucson, Arizona 85721
http://www.coopunits.org/Arizona/
The U.S. Geological Survey conducted a bathymetric survey in Little Holland Tract, a flooded agricultural tract, in the northern Sacramento-San Joaquin Delta (the “Delta”) during the summer of 2015. The new bathymetric data were combined with existing data to generate a digital elevation model (DEM) at 1-meter resolution. Little Holland Tract (LHT) was historically diked off for agricultural uses and has been tidally inundated since an accidental levee breach in 1983. Shallow tidal regions such as LHT have the potential to improve habitat quality in the Delta. The DEM of LHT was developed to support ongoing studies of habitat quality in the area and to provide a baseline for evaluating future geomorphic change. The new data comprise 138,407 linear meters of real-time-kinematic (RTK) Global Positioning System (GPS) elevation data, including both bathymetric data collected from personal watercraft and topographic elevations collected on foot at low tide. A benchmark (LHT15_b1) was established for geodetic control of the survey. Data quality was evaluated both by comparing results among surveying platforms, which showed systematic offsets of 1.6 centimeters (cm) or less, and by error propagation, which yielded a mean vertical uncertainty of 6.7 cm. Based on the DEM and time-series measurements of water depth, the mean tidal prism of LHT was determined to be 2,826,000 cubic meters. The bathymetric data and DEM are available at http://dx.doi.org/10.5066/F7RX9954.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161093","usgsCitation":"Snyder, A.G., Lacy, J.R., Stevens, A.W., and Carlson, E.M., 2016, Bathymetric survey and digital elevation model of Little Holland Tract, Sacramento-San Joaquin Delta, California: U.S. Geological Survey Open-File Report 2016‒1093, 14 p., https://dx.doi.org/10.3133/ofr20161093. ","productDescription":"iv, 14 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071752","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":323417,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1093/ofr20161093.pdf","text":"Report","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1093"},{"id":323416,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1093/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.69349670410158,\n 38.27632714009116\n ],\n [\n -121.69349670410158,\n 38.34556060133404\n ],\n [\n -121.64148330688475,\n 38.34556060133404\n ],\n [\n -121.64148330688475,\n 38.27632714009116\n ],\n [\n -121.69349670410158,\n 38.27632714009116\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
The purpose of this project was to develop a technique to use environmental DNA (eDNA) to distinguish between redds made by Chinook salmon (Oncorhynchus tshawytscha) and redds made by Coho salmon (O. kisutch) and to distinguish utilized redds from test/abandoned redds or scours that have the appearance of redds. The project had two phases:
Phase 1. Develop, test, and optimize a molecular assay for detecting and identifying Coho salmon DNA and differentiating it from Chinook salmon DNA.
Phase 2. Demonstrate the efficacy of the technique.
The Sandy River is a large tributary of the Columbia River. The Sandy River meets the Columbia River approximately 23 km upstream of Portland, Oregon. The Sandy River Basin provides overlapping spawning habitat for both Chinook and Coho salmon.
Samples provided by Portland Water Bureau for analysis were collected from the Bull Run River, Sixes Creek, Still Creek, Arrah Wanna Side Channel, and Side Channel 18.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161091","collaboration":"Prepared in cooperation with Portland Water Bureau","usgsCitation":"Pilliod, D.S., and Laramie, M.B., 2016, Salmon redd identification using environmental DNA (eDNA): U.S. Geological Survey Open-File Report 2016–1091, 25 p., https://dx.doi.org/10.3133/ofr20161091.","productDescription":"iv, 25 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064586","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":323430,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1091/coverthb3.jpg"},{"id":323387,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1091/ofr20161091.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1091"}],"country":"United States","state":"Oregon","otherGeospatial":"Sandy River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.28744506835938,\n 45.298075138707965\n ],\n [\n -122.28744506835938,\n 45.481317798141255\n ],\n [\n -121.84112548828125,\n 45.481317798141255\n ],\n [\n -121.84112548828125,\n 45.298075138707965\n ],\n [\n -122.28744506835938,\n 45.298075138707965\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
The Delaware River Basin Streamflow Estimator Tool (DRB-SET) is a tool for the simulation of streamflow at a daily time step for an ungaged stream location in the Delaware River Basin. DRB-SET was developed by the U.S. Geological Survey (USGS) and funded through WaterSMART as part of the National Water Census, a USGS research program on national water availability and use that develops new water accounting tools and assesses water availability at the regional and national scales. DRB-SET relates probability exceedances at a gaged location to those at an ungaged stream location. Once the ungaged stream location has been identified by the user, an appropriate streamgage is automatically selected in DRB-SET using streamflow correlation (map correlation method). Alternately, the user can manually select a different streamgage or use the closest streamgage. A report file is generated documenting the reference streamgage and ungaged stream location information, basin characteristics, any warnings, baseline (minimally altered) and altered (affected by regulation, diversion, mining, or other anthropogenic activities) daily mean streamflow, and the mean and median streamflow. The estimated daily flows for the ungaged stream location can be easily exported as a text file that can be used as input into a statistical software package to determine additional streamflow statistics, such as flow duration exceedance or streamflow frequency statistics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151192","usgsCitation":"Stuckey, M.H., and Ulrich, J.E., 2016, User’s Guide for the Delaware River Basin Streamflow Estimator Tool (DRB-SET): U.S. Geological Survey Open-File Report 2015–1192, 6 p., https://dx.doi.org/10.3133/ofr20151192.","productDescription":"iv, 6 p.","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069187","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":322015,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20155157","text":"Estimation of Daily Mean Streamflow for Ungaged Stream Locations in the Delaware River Basin, Water Years 1960–2010","description":"OFR 2015-1192"},{"id":322012,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1192/coverthb.jpg"},{"id":322016,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://www.usgs.gov/software/delaware-river-basin-streamflow-estimator-tool-drb-set","text":"Delaware River Basin Streamflow Estimator Tool (DRB-SET)","linkFileType":{"id":5,"text":"html"},"description":"OFR 2015-1192"},{"id":322013,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1192/ofr20151192.pdf","text":"Report","size":"1.76 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1192"}],"contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
http://pa.water.usgs.gov/
The U.S. Geological Survey has completed an assessment of the potential geologic carbon dioxide storage resources in the onshore areas of the United States. To provide geological context and input data sources for the resources numbers, framework documents are being prepared for all areas that were investigated as part of the national assessment. This report, chapter M, is the geologic framework document for the Uinta and Piceance, San Juan, Paradox, Raton, Eastern Great, and Black Mesa Basins, and subbasins therein of Arizona, Colorado, Idaho, Nevada, New Mexico, and Utah. In addition to a summary of the geology and petroleum resources of studied basins, the individual storage assessment units (SAUs) within the basins are described and explanations for their selection are presented. Although appendixes in the national assessment publications include the input values used to calculate the available storage resource, this framework document provides only the context and source of the input values selected by the assessment geologists. Spatial-data files of the boundaries for the SAUs, and the well-penetration density of known well bores that penetrate the SAU seal, are available for download with the release of this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121024M","usgsCitation":"Merrill, M.D., Drake, R.M., II, Buursink, M.L., Craddock, W.H., East, J.A., Slucher, E.R., Warwick, P.D., Brennan, S.T., Blondes, M.S., Freeman, P.A., Cahan, S.M., DeVera, C.A., and Lohr, C.D., 2016, Geologic framework for the national assessment of carbon dioxide storage resources—Southern Rocky Mountain Basins, chap. M of Warwick, P.D., and Corum, M.D., eds., Geologic framework for the national assessment of carbon dioxide storage resources: U.S. Geological Survey Open-File Report 2012–1024–M, 59 p., at https://dx.doi.org/10.3133/ofr20121024M.","productDescription":"Report: viii, 60 p.; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-056759","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":322007,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20121024","text":"Geologic Framework for the National Assessment of Carbon Dioxide Storage Resources","linkHelpText":"- (Main Report)"},{"id":322003,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2012/1024/m/coverthb.jpg"},{"id":322005,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2012/1024/m/downloads/ofr2012-1024m_storage-assessment-units.zip","text":"Storage Assessment Units","size":"478 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2012-1024m"},{"id":322004,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1024/m/ofr20121024m.pdf","text":"Report","size":"79.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2012-1024m"},{"id":322006,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2012/1024/m/downloads/ofr2012-1024m_well-density.zip","text":"Well Density","size":"753 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2012-1024m"}],"country":"United States","state":"Arizona, Colorado, Idaho, Nevada, New Mexico, Utah","otherGeospatial":"Uinta Basin, Piceance Basin, San Juan Basin, Paradox Basin, Raton Basin, Eastern Great Basin, Black Mesa Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.59765625,\n 33.358061612778876\n ],\n [\n -117.59765625,\n 44.96479793033104\n ],\n [\n -103.18359375,\n 44.96479793033104\n ],\n [\n -103.18359375,\n 33.358061612778876\n ],\n [\n -117.59765625,\n 33.358061612778876\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Energy Resources Program
12201 Sunrise Valley Drive
913 National Center
Reston, VA 20192
Email: gd-energyprogram@usgs.gov
http://energy.usgs.gov/GeneralInfo/
AbouttheEnergyProgram.aspx
The GIS Flood Tool (GFT) was developed by the U.S. Geological Survey with support from the U.S. Agency for International Development’s Office of U.S. Foreign Disaster Assistance to provide a means for production of reconnaissance-level flood inundation mapping for data-sparse and resource-limited areas of the world. The GFT has also attracted interest as a tool for rapid assessment flood inundation mapping for the Flood Inundation Mapping Program of the U.S. Geological Survey. The GFT can fill an important gap for communities that lack flood inundation mapping by providing a first-estimate of inundation zones, pending availability of resources to complete an engineering study. The tool can also help identify priority areas for application of scarce flood inundation mapping resources. The technical basis of the GFT is an application of the Manning equation for steady flow in an open channel, operating on specially processed digital elevation data. The GFT is implemented as a software extension in ArcGIS. Output maps from the GFT were validated at 11 sites with inundation maps produced previously by the Flood Inundation Mapping Program using standard one-dimensional hydraulic modeling techniques. In 80 percent of the cases, the GFT inundation patterns matched 75 percent or more of the one-dimensional hydraulic model inundation patterns. Lower rates of pattern agreement were seen at sites with low relief and subtle surface water divides. Although the GFT is simple to use, it should be applied with the oversight or review of a qualified hydraulic engineer who understands the simplifying assumptions of the approach.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161038","collaboration":"Prepared in cooperation with the U.S. Agency for International Development, Office of U.S. Foreign Disaster Assistance (USAID/OFDA)","usgsCitation":"Verdin, James; Verdin, Kristine; Mathis, Melissa; Magadzire, Tamuka; Kabuchanga, Eric; Woodbury, Mark; and Gadain, Hussein, 2016, A software tool for rapid flood inundation mapping: U.S. Geological Survey Open-File Report 2016–1038, 26 p., https://dx.doi.org/10.3133/ofr20161038.","productDescription":"vi, 26 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055868","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":322105,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1038/ofr20161038.pdf","text":"Report","size":"16.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1038"},{"id":322104,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1038/coverthb.jpg"}],"contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, South Dakota 57198
The U.S. Geological Survey provided technical support to the Agency for Toxic Substances and Disease Registry for site selection and sample collection and analysis in a 2012 investigation of groundwater quality from 29 private domestic water-supply wells in the vicinity of petroleum production in southwestern Indiana. Petroleum hydrocarbons, oil and grease, aromatic volatile organic compounds, methane concentrations greater than 8,800 micrograms per liter, chloride concentrations greater than 250 milligrams per liter, and gross alpha radioactivity greater than 15 picocuries per liter were reported in the analysis of groundwater samples from 11 wells.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161081","usgsCitation":"Risch, M.R., and Silcox, C.A., 2016, Groundwater quality from private domestic water-supply wells in the vicinity of petroleum production in southwestern Indiana: U.S. Geological Survey Open-File Report 2016–1081, 29 p., https://dx.doi.org/10.3133/ofr20161081.","productDescription":"Report: v, 29 p.; Appendix tables","startPage":"1","endPage":"29","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-040076","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":322060,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1081/ofr20161081.pdf","text":"Report","size":"791 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1081"},{"id":322061,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1081/ofr20161081_appendixtables.pdf","text":"Appendix Tables","description":"OFR 2016–1081 Appendix Tables"},{"id":322059,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1081/coverthb.jpg"}],"country":"United States","state":"Indiana","otherGeospatial":"Mt. Vernon Consolidated Oilfield","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88,\n 38\n ],\n [\n -88,\n 37.83\n ],\n [\n -87.8,\n 37.83\n ],\n [\n -87.8,\n 38\n ],\n [\n -88,\n 38\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278–1996
The Tree Cover Mapping (TCM) tool was developed by scientists at the U.S. Geological Survey Earth Resources Observation and Science Center to allow a user to quickly map tree cover density over large areas using visual interpretation of high resolution imagery within a geographic information system interface. The TCM tool uses a systematic sample grid to produce maps of tree cover. The TCM tool allows the user to define sampling parameters to estimate tree cover within each sample unit. This mapping method generated the first on-farm tree cover maps of vast regions of Niger and Burkina Faso. The approach contributes to implementing integrated landscape management to scale up re-greening and restore degraded land in the drylands of Africa. The TCM tool is easy to operate, practical, and can be adapted to many other applications such as crop mapping, settlements mapping, or other features. This user manual provides step-by-step instructions for installing and using the tool, and creating tree cover maps. Familiarity with ArcMap tools and concepts is helpful for using the tool.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161067","usgsCitation":"Cotillon, Suzanne, and Mathis, Melissa, 2016, Tree cover mapping tool—documentation and user manual (ver. 1.0, March 2016): U.S. Geological Survey Open-File Report 2016–1067, 11 p., https://dx.doi.org/10.3133/ofr20161067.","productDescription":"v, 11 p.","startPage":"1","endPage":"11","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073965","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":321947,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1067/coverthb.jpg"},{"id":321948,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1067/ofr20161067.pdf","text":"Report","size":"5.20 MB","description":"OFR 2016–1067"},{"id":344363,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://edcintl.cr.usgs.gov/downloads/sciweb1/shared/wafrica/downloads/tools/TreeCoverMapping10.x_Addins.zip","text":"Software Tool Download","description":"Software Tool Download"}],"contact":"Director
Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The magnitude 4.0 earthquake that occurred on October 16, 2012, near Hollis Center and Waterboro in southwestern Maine surprised and startled local residents but caused only minor damage. A two-person U.S. Geological Survey (USGS) team was sent to Maine to conduct an intensity survey and document the damage. The only damage we observed was the failure of a chimney and plaster cracks in two buildings in East and North Waterboro, 6 kilometers (km) west of the epicenter. We photographed the damage and interviewed residents to determine the intensity distribution in the epicentral area. The damage and shaking reports are consistent with a maximum Modified Mercalli Intensity (MMI) of 5–6 for an area 1–8 km west of the epicenter, slightly higher than the maximum Community Decimal Intensity (CDI) of 5 determined by the USGS “Did You Feel It?” Web site. The area of strong shaking in East Waterboro corresponds to updip rupture on a fault plane that dips steeply east.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161071","usgsCitation":"Radakovich, A.L., Ferguson, A.J., and Boatwright, John, 2016, Field survey of earthquake effects from the magnitude 4.0 southern Maine earthquake of October 16, 2012: U.S. Geological Survey Open-File Report 2016–1071, 17 p., https://dx.doi.org/10.3133/ofr20161071. ","productDescription":"iv, 17 p.","startPage":"1","endPage":"17","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-046067","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":322068,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1071/ofr20161071.pdf","text":"Report","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1071"},{"id":322067,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1071/coverthb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Rhode Island, Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76,\n 41\n ],\n [\n -76,\n 46\n ],\n [\n -68.5,\n 46\n ],\n [\n -68.5,\n 41\n ],\n [\n -76,\n 41\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
http://earthquake.usgs.gov/
Mapping in the Morena Reservoir 7.5-minute quadrangle began in 1980, when the Hauser Wilderness Area, which straddles the Morena Reservoir and Barrett Lake quadrangles, was mapped for the U.S. Forest Service. Mapping was completed in 1993–1994. The Morena Reservoir quadrangle contains part of a regional-scale Late Jurassic(?) to Early Cretaceous tectonic suture that coincides with the western limit of Jurassic metagranites in this part of the Peninsular Ranges batholith (PRB). This suture, and a nearly coincident map unit consisting of metamorphosed Cretaceous and Jurassic back-arc basinal volcanic and sedimentary rocks (unit KJvs), mark the boundary between western, predominantly metavolcanic rocks, and eastern, mainly metasedimentary, rocks. The suture is intruded and truncated by the western margin of middle to Late Cretaceous Granite Mountain and La Posta plutons of the eastern zone of the batholith.
","publisher":"U. S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr9550","usgsCitation":"Todd, V.R., 2016, Geologic map of the Morena Reservoir 7.5-minute quadrangle, San Diego County, California: U.S. Geological Survey Open-File Report 95–50, 12 p., scale 1:24,000, https://dx.doi.org/10.3133/ofr9550.","productDescription":"Pamphlet: iii, 12 p.; 1 Plate: 32.74 x 30.79 inches; Metadata; Read Me; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":399099,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_104275.htm"},{"id":321428,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/1995/0050/ofr95-50_MorenaRes_metadata.txt","text":"Morena Reservoir metadata","linkFileType":{"id":2,"text":"txt"},"description":"OFR 95-50 Metadata TXT"},{"id":321427,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/1995/0050/ofr95-50_MorenaRes_metadata.htm","text":"Morena Reservoir metadata","linkFileType":{"id":5,"text":"html"},"description":"OFR 95-50 Metadata HTML"},{"id":321426,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/of/1995/0050/ofr95-50_MorenaRes_README.txt","text":"Morena Reservoir read me","linkFileType":{"id":2,"text":"txt"},"description":"OFR 95-50 Read Me"},{"id":321425,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/1995/0050/ofr95-50_MorenaRes_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 95-50 Pamphlet"},{"id":321424,"rank":2,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/1995/0050/ofr95-50_MorenaRes_plate.pdf","text":"Morena Reservoir plate","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 95-50 Plate"},{"id":321429,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/1995/0050/ofr95-50_DATABASE.zip","text":"Morena Reservoir database","linkFileType":{"id":6,"text":"zip"},"description":"OFR 95-50 Database"},{"id":321423,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/1995/0050/coverthb2.jpg"}],"country":"United States","state":"California","county":"San Diego County","otherGeospatial":"Morena Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.625,\n 32.625\n ],\n [\n -116.5,\n 32.625\n ],\n [\n -116.5,\n 32.75\n ],\n [\n -116.625,\n 32.75\n ],\n [\n -116.625,\n 32.625\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Tucson
U.S. Geological Survey
520 North Park Avenue
Tucson, AZ 85719
http://geomaps.wr.usgs.gov/
Between 2007 and 2008, seven Earthscope Plate Boundary Observatory (PBO) boreholes ranging in depth from about 200 to 800 feet deep were drilled in and adjacent to the Yellowstone caldera in Yellowstone National Park, for the purpose of installing volcano monitoring instrumentation. Five of the seven boreholes were equipped with strainmeters, downhole seismometers, and tiltmeters. Data collected during drilling included field observations of drill cuttings, stratigraphy within the boreholes, water temperature, and water and drill cuttings samples from selected depths.
\nSix of the seven boreholes encountered rhyolite lavas and tuffs. The rhyolite lavas compose the Canyon flow, the Gardner River flow, the Gibbon River flow, the Hayden Valley flow, the Nez Perce Creek flow, and the West Thumb flow. Boreholes also penetrated a vertical sequence through the Lava Creek Tuff and the Tuff of Bluff Point. In addition, one borehole drilled through a Swan Lake Flat Basalt sequence and terminated in a rhyolite lava flow.
\nAfter drilling the seven PBO boreholes, cuttings were examined and selected for preparation of grain mounts, thin sections, and geochemical analysis. Major ions and trace elements (including rare earth elements) of selected cuttings were determined by x-ray fluorescence (XRF) and inductively coupled plasma-mass spectrometry (ICP-MS); the ICP-MS provided more precise trace-element analysis than XRF. A preliminary interpretation of the results of geochemical analyses generally shows a correlation between borehole cuttings and previously mapped geology. The geochemical data and borehole stratigraphy presented in this report provide a foundation for future petrologic, geochemical, and geophysical studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161028","collaboration":"Prepared in cooperation with the National Park Service, Yellowstone National Park, and Earthscope Plate Boundary Observatory","usgsCitation":"Jaworowski, C., Susong, D., Heasler, H., Mencin, D., Johnson, W., Conrey, R., and Von Stauffenberg, J., 2016,\nGeologic and geochemical results from boreholes drilled in Yellowstone National Park, Wyoming, 2007 and 2008:\nU.S. Geological Survey Open-File Report 2016-1028, 39 p. https://dx.doi.org/10.3133/ofr20161028","productDescription":"Report: viii, 39 p.; 2 Appendixes","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064084","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":321191,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1028/ofr20161028.pdf","text":"Report","size":"4.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1028"},{"id":321192,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1028/ofr20161028_appendix01.xlsx","text":"Appendix 1","size":"74 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1028 Appendix 1"},{"id":321193,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1028/ofr20161028_appendix02.xlsx","text":"Appendix 2","size":"35 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1028 Appendix 2"},{"id":321190,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1028/coverthb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.93994140625,\n 44.402391829093915\n ],\n [\n -110.93994140625,\n 44.93758500391091\n ],\n [\n -110.0830078125,\n 44.93758500391091\n ],\n [\n -110.0830078125,\n 44.402391829093915\n ],\n [\n -110.93994140625,\n 44.402391829093915\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Utah Water Science Center
U.S. Geological Survey
2329 Orton Circle
Salt Lake City, Utah 84119-2047
http://ut.water.usgs.gov