Sandstone-hosted deposits mined primarily for their uranium content also have been a source of vanadium and modest amounts of copper. Processing of these ores has also recovered small amounts of molybdenum, rhenium, rare earth elements, scandium, and selenium. These deposits share a generally common origin, but variations in the source of metals, composition of ore-forming solutions, and geologic history result in complex variability in deposit composition. This heterogeneity is evident regionally within the same host rock, as well as within districts. Future recovery of elements associated with uranium in these deposits will be strongly dependent on mining and ore-processing methods.
","largerWorkTitle":"Rare earth and critical elements in ore deposits","language":"English","publisher":"Society of Economic Geologists","usgsCitation":"Breit, G.N., 2016, Resource potential for commodities in addition to Uranium in sandstone-hosted deposits, chap. 13 of Rare earth and critical elements in ore deposits: Reviews in Economic Geology, p. 323-338.","productDescription":"16 p.","startPage":"323","endPage":"338","ipdsId":"IP-057031","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":349564,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fc65e4b06e28e9c23e19","contributors":{"authors":[{"text":"Breit, George N. 0000-0003-2188-6798 gbreit@usgs.gov","orcid":"https://orcid.org/0000-0003-2188-6798","contributorId":1480,"corporation":false,"usgs":true,"family":"Breit","given":"George","email":"gbreit@usgs.gov","middleInitial":"N.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":719258,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70191678,"text":"70191678 - 2016 - A simple rubric for Stratigraphic Fidelity (β) of paleoenvironmental time series","interactions":[],"lastModifiedDate":"2017-10-25T12:42:00","indexId":"70191678","displayToPublicDate":"2016-12-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3481,"text":"Stratigraphy","active":true,"publicationSubtype":{"id":10}},"title":"A simple rubric for Stratigraphic Fidelity (β) of paleoenvironmental time series","docAbstract":"The Pliocene, specifically the late Pliocene, has been a focus of paleoclimate research formore than 25 years. Synoptic regional\nand global reconstructions along with high-resolution time-series have produced nuanced conceptual models of paleoenvironmental\nconditions and enhanced our understanding of climate variability and climate sensitivity from the Late Pliocene, the most\nrecent interval of global warmth similar to what is projected for the end of the 21st century. These data are used as a source of boundary\nconditions for climate models as well as ameans of verification of global climate model experiments. In this note, we introduce a measure\nof stratigraphic fidelity, ß, used to characterize the chronology and achievable resolution of an ever-growing library of Pliocene\npaleoenvironmental time-series. The ß index serves as an aid to end-users by allowing selection of time-series that meet the stratigraphic\nrequirements of a particular study.","language":"English","publisher":"MicroPress","usgsCitation":"Dowsett, H.J., Robinson, M.M., and Foley, K.M., 2016, A simple rubric for Stratigraphic Fidelity (β) of paleoenvironmental time series: Stratigraphy, v. 13, no. 4, p. 303-305.","productDescription":"3 p.","startPage":"303","endPage":"305","ipdsId":"IP-086569","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":347351,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346751,"type":{"id":15,"text":"Index Page"},"url":"https://www.micropress.org/microaccess/stratigraphy/issue-329"}],"volume":"13","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f1a2a6e4b0220bbd9d9f67","contributors":{"authors":[{"text":"Dowsett, Harry J. 0000-0003-1983-7524 hdowsett@usgs.gov","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":949,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry","email":"hdowsett@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":713039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Marci M. 0000-0002-9200-4097 mmrobinson@usgs.gov","orcid":"https://orcid.org/0000-0002-9200-4097","contributorId":2082,"corporation":false,"usgs":true,"family":"Robinson","given":"Marci","email":"mmrobinson@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":713040,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foley, Kevin M. 0000-0003-1013-462X kfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-1013-462X","contributorId":2543,"corporation":false,"usgs":true,"family":"Foley","given":"Kevin","email":"kfoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":713041,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194342,"text":"70194342 - 2016 - Modeling ancient land use and resilient forests in the Jemez Mountains","interactions":[],"lastModifiedDate":"2017-11-28T11:06:20","indexId":"70194342","displayToPublicDate":"2016-12-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5568,"text":"Archaeology Southwest Magazine","active":true,"publicationSubtype":{"id":10}},"title":"Modeling ancient land use and resilient forests in the Jemez Mountains","docAbstract":"No abstract available.
","language":"English","publisher":"Archaeology Southwest","usgsCitation":"Loehman, R.A., 2016, Modeling ancient land use and resilient forests in the Jemez Mountains: Archaeology Southwest Magazine, v. 30, no. 4.","ipdsId":"IP-077246","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":349428,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":349301,"type":{"id":15,"text":"Index Page"},"url":"https://www.archaeologysouthwest.org/product/asw30-4/"}],"volume":"30","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fc65e4b06e28e9c23e12","contributors":{"authors":[{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":723378,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70187206,"text":"70187206 - 2016 - Establishing links between streamflow and ecological integrity in the Sudbury River (Northeastern U.S.)","interactions":[],"lastModifiedDate":"2017-04-27T09:59:13","indexId":"70187206","displayToPublicDate":"2016-12-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"122-2016","title":"Establishing links between streamflow and ecological integrity in the Sudbury River (Northeastern U.S.)","docAbstract":"With increased pressure from a growing human population, managers are challenged to understand how novel disturbances (e.g., climate change, increased water withdrawals, urbanization) may affect natural resources. The Sudbury River is a National Wild and Scenic River located in suburban Boston, Massachusetts (Northeastern US) with myriad impairments (e.g., mainstem impoundments, withdrawals, and urbanization) that is under increasing pressure from hydrologic alteration. We sampled fish, mussel, and macroinvertebrate assemblages in the Sudbury River and used species traits to investigate potential effects of past and future flow alteration on biota. Analysis of 33 years of stream gage data indicates continued hydrologic alteration of the Sudbury River, likely related to increased urbanization and water withdrawals over that time. These changes include a roughly 200% increase in rise rates of flows, an approximate 65% decrease in 1-day minimum flows, and a trend towards increasing high flow pulse counts. Biotic sampling in summer of 2014 demonstrated that the Sudbury River is now dominated by generalist species. Of five mussel species sampled, all are generalists in their habitat requirements. Though one mussel species of special concern was sampled, the most abundant species collected were the widespread Eastern elliptio (58%) and Eastern lampmussel (40%). We used the target fish community (TFC) model to assess the degree to which the fish assemblage deviated from that expected for a river with similar zoogeographic and physical features. Overall, the current community has a 22.7% similarity to the TFC. Of the four fluvial specialist species present in the TFC, only fallfish was sampled in our study. While the TFC showed that the historical assemblage was likely dominated by fluvial specialist and fluvial dependent species, the current assemblage is overwhelmingly dominated by macrohabitat generalists (90.6% of fishes sampled). These results are consistent with other studies that show shifts in assemblages from fluvial specialists to habitat generalists with hydrologic alteration. If the current trends continue, it is likely that biotic assemblages will experience increasing pressure from hydrologic alteration. While hydrologic alteration is likely impacting biotic assemblages in the Sudbury River, other factors such as high temperatures, low dissolved oxygen, high nutrients, low availability of high-quality habitat, and poor habitat connectivity may also be negatively impacting biotic assemblages. Comparisons to other rivers and a complete longitudinal habitat survey could help to identify availability of unique habitats and representativeness of this study. While this study suggests impacts of flow on biota, future studies with quantitative, habitat-specific sampling during different flow levels could help to directly identify links between hydrologic alteration and biotic impairment in the Sudbury River.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Roy, A.H., Jane, S.F., Hazelton, P.D., Richards, T.A., Finn, J.T., and Randhir, T.O., 2016, Establishing links between streamflow and ecological integrity in the Sudbury River (Northeastern U.S.): Cooperator Science Series 122-2016, vi, 78 p.","productDescription":"vi, 78 p.","ipdsId":"IP-065793","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340464,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalmedia.fws.gov/cdm/singleitem/collection/document/id/2152/rec/19"}],"country":"United States","state":"Massachussetts","otherGeospatial":"Sudbury River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.63497924804688,\n 42.13998671872691\n ],\n [\n -71.17767333984375,\n 42.13998671872691\n ],\n [\n -71.17767333984375,\n 42.5530802889558\n ],\n [\n -71.63497924804688,\n 42.5530802889558\n ],\n [\n -71.63497924804688,\n 42.13998671872691\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5901b1bae4b0c2e071a99b96","contributors":{"authors":[{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jane, Stephen F.","contributorId":191442,"corporation":false,"usgs":false,"family":"Jane","given":"Stephen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":693056,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hazelton, Peter D.","contributorId":171765,"corporation":false,"usgs":false,"family":"Hazelton","given":"Peter","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":693057,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richards, Todd A.","contributorId":52266,"corporation":false,"usgs":true,"family":"Richards","given":"Todd","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":693058,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Finn, John T.","contributorId":43398,"corporation":false,"usgs":false,"family":"Finn","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":16720,"text":"Department of Environmental Conservation, University of Massachusetts, Amherst, MA 01003-9485, USA","active":true,"usgs":false}],"preferred":false,"id":693059,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Randhir, Timothy O.","contributorId":191443,"corporation":false,"usgs":false,"family":"Randhir","given":"Timothy","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":693060,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70189528,"text":"70189528 - 2016 - Seismic‐hazard forecast for 2016 including induced and natural earthquakes in the central and eastern United States","interactions":[],"lastModifiedDate":"2017-07-14T13:23:24","indexId":"70189528","displayToPublicDate":"2016-12-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Seismic‐hazard forecast for 2016 including induced and natural earthquakes in the central and eastern United States","docAbstract":"The U.S. Geological Survey (USGS) has produced a one‐year (2016) probabilistic seismic‐hazard assessment for the central and eastern United States (CEUS) that includes contributions from both induced and natural earthquakes that are constructed with probabilistic methods using alternative data and inputs. This hazard assessment builds on our 2016 final model (Petersen et al., 2016) by adding sensitivity studies, illustrating hazard in new ways, incorporating new population data, and discussing potential improvements. The model considers short‐term seismic activity rates (primarily 2014–2015) and assumes that the activity rates will remain stationary over short time intervals. The final model considers different ways of categorizing induced and natural earthquakes by incorporating two equally weighted earthquake rate submodels that are composed of alternative earthquake inputs for catalog duration, smoothing parameters, maximum magnitudes, and ground‐motion models. These alternatives represent uncertainties on how we calculate earthquake occurrence and the diversity of opinion within the science community. In this article, we also test sensitivity to the minimum moment magnitude between M 4 and M 4.7 and the choice of applying a declustered catalog with b=1.0 rather than the full catalog with b=1.3. We incorporate two earthquake rate submodels: in the informed submodel we classify earthquakes as induced or natural, and in the adaptive submodel we do not differentiate. The alternative submodel hazard maps both depict high hazard and these are combined in the final model. Results depict several ground‐shaking measures as well as intensity and include maps showing a high‐hazard level (1% probability of exceedance in 1 year or greater). Ground motions reach 0.6g horizontal peak ground acceleration (PGA) in north‐central Oklahoma and southern Kansas, and about 0.2g PGA in the Raton basin of Colorado and New Mexico, in central Arkansas, and in north‐central Texas near Dallas–Fort Worth. The chance of having levels of ground motions corresponding to modified Mercalli intensity (MMI) VI or greater earthquake shaking is 2%–12% per year in north‐central Oklahoma and southern Kansas and New Madrid similar to the chance of damage at sites in high‐hazard portions of California caused by natural earthquakes. Hazard is also significant in the Raton basin of Colorado/New Mexico; north‐central Arkansas; Dallas–Fort Worth, Texas; and in a few other areas. Hazard probabilities are much lower (by about half or more) for exceeding MMI VII or VIII. Hazard is 3‐ to 10‐fold higher near some areas of active‐induced earthquakes than in the 2014 USGS National Seismic Hazard Model (NSHM), which did not consider induced earthquakes. This study in conjunction with the LandScan TM Database (2013) indicates that about 8 million people live in areas of active injection wells that have a greater than 1% chance of experiencing damaging ground shaking (MMI≥VI) in 2016. The final model has high uncertainty, and engineers, regulators, and industry should use these assessments cautiously to make informed decisions on mitigating the potential effects of induced and natural earthquakes.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220160072","usgsCitation":"Petersen, M.D., Mueller, C., Moschetti, M.P., Hoover, S.M., Llenos, A.L., Ellsworth, W.L., Michael, A.J., Rubinstein, J.L., McGarr, A.F., and Rukstales, K.S., 2016, Seismic‐hazard forecast for 2016 including induced and natural earthquakes in the central and eastern United States: Seismological Research Letters, v. 87, no. 6, p. 1327-1341, https://doi.org/10.1785/0220160072.","productDescription":"15 p. 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mcgarr@usgs.gov","orcid":"https://orcid.org/0000-0001-9769-4093","contributorId":3178,"corporation":false,"usgs":true,"family":"McGarr","given":"Arthur","email":"mcgarr@usgs.gov","middleInitial":"F.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705061,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rukstales, Kenneth S. 0000-0003-2818-078X rukstales@usgs.gov","orcid":"https://orcid.org/0000-0003-2818-078X","contributorId":775,"corporation":false,"usgs":true,"family":"Rukstales","given":"Kenneth","email":"rukstales@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705062,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70173826,"text":"70173826 - 2016 - Improving our understanding of hydraulic-electrical relations: A case study of the surficial aquifer in Emirate Abu Dhabi","interactions":[],"lastModifiedDate":"2017-11-08T17:24:55","indexId":"70173826","displayToPublicDate":"2016-12-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"title":"Improving our understanding of hydraulic-electrical relations: A case study of the surficial aquifer in Emirate Abu Dhabi","docAbstract":"Transmissivity is a bulk hydraulic property that can be correlated with bulk electrical properties of an aquifer. In aquifers that are electrically-resistive relative to adjacent layers in a horizontally stratified sequence, transmissivity has been shown to correlate with bulk transverse resistance. Conversely, in aquifers that are electrically-conductive relative to adjacent layers, transmissivity has been shown to correlate with bulk longitudinal conductance. In both cases, previous investigations have relied on small datasets (on average less than eight observations) that have yielded coefficients of determination (R2) that are typically in the range of 0.6 to 0.7 to substantiate these relations. Compared to previous investigations, this paper explores hydraulic-electrical relations using a much larger dataset. Geophysical data collected from 26 boreholes in Emirate Abu Dhabi, United Arab Emirates, are used to correlate transmissivity modeled from neutron porosity logs to the bulk electrical properties of the surficial aquifer that are computed from deep-induction logs. Transmissivity is found to be highly correlated with longitudinal conductance. An R2 value of 0.853 is obtained when electrical effects caused by variations in pore-fluid salinity are taken into consideration.
","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Symposium on the Application of Geophysics to Engineering and Environmental Problems 2016","conferenceTitle":"Symposium on the Application of Geophysics to Engineering and Environmental Problems","conferenceDate":"March 20-24, 2016","conferenceLocation":"Denver, CO","language":"English","publisher":"Society of Exploration Geophysicists and Environment and Engineering Geophysical Society","doi":"10.4133/SAGEEP.29-060","issn":"1554-8015","usgsCitation":"Ikard, S., and Kress, W.H., 2016, Improving our understanding of hydraulic-electrical relations: A case study of the surficial aquifer in Emirate Abu Dhabi, in Symposium on the Application of Geophysics to Engineering and Environmental Problems 2016, Denver, CO, March 20-24, 2016, p. 340-353, https://doi.org/10.4133/SAGEEP.29-060.","productDescription":"14 p.","startPage":"340","endPage":"353","ipdsId":"IP-070679","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":348522,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425bde4b0dc0b45b453d0","contributors":{"authors":[{"text":"Ikard, Scott 0000-0002-8304-4935 sikard@usgs.gov","orcid":"https://orcid.org/0000-0002-8304-4935","contributorId":171751,"corporation":false,"usgs":true,"family":"Ikard","given":"Scott","email":"sikard@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":638521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kress, Wade H. 0000-0002-6833-028X wkress@usgs.gov","orcid":"https://orcid.org/0000-0002-6833-028X","contributorId":1576,"corporation":false,"usgs":true,"family":"Kress","given":"Wade","email":"wkress@usgs.gov","middleInitial":"H.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":638522,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198161,"text":"70198161 - 2016 - Building damage survey and microtremor measurements for the source region of the 2015 Gorkha, Nepal, earthquake","interactions":[],"lastModifiedDate":"2018-07-18T09:55:53","indexId":"70198161","displayToPublicDate":"2016-12-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1430,"text":"Earth, Planets and Space","active":true,"publicationSubtype":{"id":10}},"title":"Building damage survey and microtremor measurements for the source region of the 2015 Gorkha, Nepal, earthquake","docAbstract":"We performed a damage survey of buildings and carried out microtremor observations in the source region of the 2015 Gorkha earthquake. Our survey area spans the Kathmandu valley and areas to the east and north of the valley. Damage of buildings in the Kathmandu valley was localized, and the percentage of the totally collapsed buildings was less than 5 %. East of the Kathmandu valley, especially in Sindhupalchok district, damage of buildings was more severe. In the center of Chautara and Bahrabise, towns in Sindhupalchok district, the percentage of the totally collapsed houses exceeded 40 %. North of the Kathmandu valley, the damage was moderate, and 20–30 % of the buildings were totally collapsed in Dhunche. Based on the past studies and our microtremor observations near the strong motion station, the H/V spectrum in Kathmandu has a peak at around 0.3 Hz, which reflects the velocity contrast of the deep sedimentary basin. The H/V spectra in Bahrabise, Chautara, and Dhunche do not show clear peaks, which suggests that the sites have stiff soil conditions. Therefore, the more severe damage outside the Kathmandu valley compared with the relatively light damage levels in the valley is probably due to the source characteristics of the earthquake and/or the seismic performance of buildings, rather than the local site conditions.","language":"English","publisher":"Springer","doi":"10.1186/s40623-016-0483-4","usgsCitation":"Yamada, M., Hayashida, T., Mori, J., and Mooney, W., 2016, Building damage survey and microtremor measurements for the source region of the 2015 Gorkha, Nepal, earthquake: Earth, Planets and Space, e117; 8 p., https://doi.org/10.1186/s40623-016-0483-4.","productDescription":"e117; 8 p.","ipdsId":"IP-070252","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":470301,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40623-016-0483-4","text":"Publisher Index Page"},{"id":355765,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Nepal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 84.0179443359375,\n 27.36201054924028\n ],\n [\n 85.484619140625,\n 27.36201054924028\n ],\n [\n 85.484619140625,\n 28.73394733840369\n ],\n [\n 84.0179443359375,\n 28.73394733840369\n ],\n [\n 84.0179443359375,\n 27.36201054924028\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-13","publicationStatus":"PW","scienceBaseUri":"5b6fc7d7e4b0f5d57878ebf1","contributors":{"authors":[{"text":"Yamada, Masumi","contributorId":206385,"corporation":false,"usgs":false,"family":"Yamada","given":"Masumi","email":"","affiliations":[{"id":37321,"text":"University of Kyoto","active":true,"usgs":false}],"preferred":false,"id":740312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayashida, Takumi","contributorId":206386,"corporation":false,"usgs":false,"family":"Hayashida","given":"Takumi","email":"","affiliations":[{"id":34873,"text":"Building Research Institute, Tsukuba, Japan","active":true,"usgs":false}],"preferred":false,"id":740313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mori, James","contributorId":206387,"corporation":false,"usgs":false,"family":"Mori","given":"James","affiliations":[{"id":37321,"text":"University of Kyoto","active":true,"usgs":false}],"preferred":false,"id":740314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mooney, Walter 0000-0002-5310-3631","orcid":"https://orcid.org/0000-0002-5310-3631","contributorId":206384,"corporation":false,"usgs":true,"family":"Mooney","given":"Walter","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":740311,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196911,"text":"70196911 - 2016 - Leveraging constraints and biotelemetry data to pinpoint repetitively used spatial features","interactions":[],"lastModifiedDate":"2018-05-10T15:01:49","indexId":"70196911","displayToPublicDate":"2016-12-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Leveraging constraints and biotelemetry data to pinpoint repetitively used spatial features","docAbstract":"Satellite telemetry devices collect valuable information concerning the sites visited by animals, including the location of central places like dens, nests, rookeries, or haul‐outs. Existing methods for estimating the location of central places from telemetry data require user‐specified thresholds and ignore common nuances like measurement error. We present a fully model‐based approach for locating central places from telemetry data that accounts for multiple sources of uncertainty and uses all of the available locational data. Our general framework consists of an observation model to account for large telemetry measurement error and animal movement, and a highly flexible mixture model specified using a Dirichlet process to identify the location of central places. We also quantify temporal patterns in central place use by incorporating ancillary behavioral data into the model; however, our framework is also suitable when no such behavioral data exist. We apply the model to a simulated data set as proof of concept. We then illustrate our framework by analyzing an Argos satellite telemetry data set on harbor seals (Phoca vitulina) in the Gulf of Alaska, a species that exhibits fidelity to terrestrial haul‐out sites.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.1618","usgsCitation":"Brost, B.M., Hooten, M., and Small, R.J., 2016, Leveraging constraints and biotelemetry data to pinpoint repetitively used spatial features: Ecology, v. 98, no. 1, p. 12-20, https://doi.org/10.1002/ecy.1618.","productDescription":"9 p.","startPage":"12","endPage":"20","ipdsId":"IP-074247","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":354064,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kodiak Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.796875,\n 56.022948079627454\n ],\n [\n -142.6904296875,\n 56.022948079627454\n ],\n [\n -142.6904296875,\n 62.75472592723178\n ],\n [\n -156.796875,\n 62.75472592723178\n ],\n [\n -156.796875,\n 56.022948079627454\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"98","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-09","publicationStatus":"PW","scienceBaseUri":"5afee922e4b0da30c1bfc527","contributors":{"authors":[{"text":"Brost, Brian M.","contributorId":171484,"corporation":false,"usgs":false,"family":"Brost","given":"Brian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":735048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":734981,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Small, Robert J.","contributorId":171486,"corporation":false,"usgs":false,"family":"Small","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":735049,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211549,"text":"70211549 - 2016 - Thermal mapping of a pahoehoe lava flow, Kilauea Volcano","interactions":[],"lastModifiedDate":"2020-07-30T15:01:51.901725","indexId":"70211549","displayToPublicDate":"2016-12-30T09:56:32","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Thermal mapping of a pahoehoe lava flow, Kilauea Volcano","docAbstract":"Pāhoehoe lava flows are a major component of Hawaiian eruptive activity, and an important part of basaltic volcanism worldwide. In recent years, pāhoehoe lava has destroyed homes and threatened parts of Hawai‘i with inundation and disruption. In this study, we use oblique helicopter-borne thermal images to create high spatial resolution (~1 m) georeferenced thermal maps of the active pāhoehoe flow on Kīlauea Volcano’s East Rift Zone. Thermal maps were created on 27 days during 2014–2016 in the course of operational monitoring, encompassing a phase of activity that threatened the town of Pāhoa. Our results illustrate and reinforce how pāhoehoe flows are multicomponent systems consisting of the vent, master tube, distributary tubes and surface breakouts. The thermal maps accurately depict the distribution and character of pāhoehoe breakouts through time, and also delineate the subsurface lava tube. Surface breakouts were distributed widely across the pāhoehoe flow, with significant portions concurrently active well upslope of the flow front, often concentrated in clusters of activity that evolved through time. Gradual changes to surface breakout distribution and migration relate to intrinsic processes in the flow, including the slow evolution of the distributary tube system. Abrupt disruptions to this system, and the creation of new breakouts (and associated hazards), were triggered by extrinsic forcing—namely fluctuations in lava supply rate at the vent which disrupted the master lava tube. Although the total area of a pāhoehoe flow has been suggested to relate to effusion rate, our results show that changes in the proportion of expansion vs. overplating can complicate this relationship. By modifying existing techniques, we estimate time-averaged discharge rates for the flow during 2014–2016 generally in the range of 1–2 m3 s-1 (mean: 1.3±0.4 m3 s-1) – less than half of Kīlauea’s typical eruption rate on the East Rift Zone and suggestive of a weak eruptive regime during 2014–2016. We caution, however, that this discharge rate approach requires further independent corroboration. The thermal maps provide the first synoptic characterization of pāhoehoe flow activity at high spatial resolution, essential both for operational hazard assessment and fundamental understanding of pāhoehoe behavior.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2016.12.007","usgsCitation":"Patrick, M.R., Orr, T.R., Fisher, G.B., Trusdell, F., and Kauahikaua, J.P., 2016, Thermal mapping of a pahoehoe lava flow, Kilauea Volcano: Journal of Volcanology and Geothermal Research, v. 332, p. 71-87, https://doi.org/10.1016/j.jvolgeores.2016.12.007.","productDescription":"17 p.","startPage":"71","endPage":"87","ipdsId":"IP-076230","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":376891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.3102874755859,\n 19.38759093442151\n ],\n [\n -155.2333831787109,\n 19.38759093442151\n ],\n [\n -155.2333831787109,\n 19.444579339485816\n ],\n [\n -155.3102874755859,\n 19.444579339485816\n ],\n [\n -155.3102874755859,\n 19.38759093442151\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"332","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":794589,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orr, Tim R. 0000-0003-1157-7588 torr@usgs.gov","orcid":"https://orcid.org/0000-0003-1157-7588","contributorId":149803,"corporation":false,"usgs":true,"family":"Orr","given":"Tim","email":"torr@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":794590,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Gary B. 0000-0001-8777-0216 gtfisher@usgs.gov","orcid":"https://orcid.org/0000-0001-8777-0216","contributorId":215627,"corporation":false,"usgs":true,"family":"Fisher","given":"Gary","email":"gtfisher@usgs.gov","middleInitial":"B.","affiliations":[{"id":36171,"text":"National Civil Applications Center","active":true,"usgs":true}],"preferred":true,"id":794591,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Trusdell, Frank A. 0000-0002-0681-0528 trusdell@usgs.gov","orcid":"https://orcid.org/0000-0002-0681-0528","contributorId":754,"corporation":false,"usgs":true,"family":"Trusdell","given":"Frank A.","email":"trusdell@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":794592,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kauahikaua, James P. 0000-0003-3777-503X jimk@usgs.gov","orcid":"https://orcid.org/0000-0003-3777-503X","contributorId":2146,"corporation":false,"usgs":true,"family":"Kauahikaua","given":"James","email":"jimk@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":794593,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70179488,"text":"70179488 - 2016 - Applying downscaled Global Climate Model data to a groundwater model of the Suwannee River Basin, Florida, USA","interactions":[],"lastModifiedDate":"2017-02-08T14:32:46","indexId":"70179488","displayToPublicDate":"2016-12-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":725,"text":"American Journal of Climate Change","active":true,"publicationSubtype":{"id":10}},"title":"Applying downscaled Global Climate Model data to a groundwater model of the Suwannee River Basin, Florida, USA","docAbstract":"The application of Global Climate Model (GCM) output to a hydrologic model allows for comparisons between simulated recent and future conditions and provides insight into the dynamics of hydrology as it may be affected by climate change. A previously developed numerical model of the Suwannee River Basin, Florida, USA, was modified and calibrated to represent transient conditions. A simulation of recent conditions was developed for the 372-month period 1970-2000 and was compared with a simulation of future conditions for a similar-length period 2039-2069, which uses downscaled GCM data. The MODFLOW groundwater-simulation code was used in both of these simulations, and two different MODFLOW boundary condition “packages” (River and Streamflow-Routing Packages) were used to represent interactions between surface-water and groundwater features.\nThe hydrologic fluxes between the atmosphere and landscape for the simulation of future conditions were developed from dynamically downscaled precipitation and evapotranspiration (ET) data generated by the Community Climate System Model (CCSM). The downscaled precipitation data were interpolated for the Suwannee River model grid, and the downscaled ET data were used to develop potential ET and were interpolated to the grid. The fu¬ture period has higher simulated rainfall (10.8 percent) and ET (4.5 percent) than the recent period.\nThe higher future rainfall causes simulated groundwater levels to rise in areas where they are deep and have little ET in either the recent or future case. However, in areas where groundwater levels were originally near the surface, the greater future ET causes groundwater levels to become lower despite the higher projected rainfall. The general implication is that unsaturated zone depth could be more spatially uniform in the future and vegetation that requires a range of conditions (substantially wetter or drier than aver¬age) could be detrimentally affected. This vegetation would include wetland species, especially in areas inland from the coast.","language":"English","publisher":"Scientific Research Publishing","doi":"10.4236/ajcc.2016.54037","usgsCitation":"Swain, E.D., and Davis, J., 2016, Applying downscaled Global Climate Model data to a groundwater model of the Suwannee River Basin, Florida, USA: American Journal of Climate Change, v. 5, p. 526-557, https://doi.org/10.4236/ajcc.2016.54037.","productDescription":"32 p.","startPage":"526","endPage":"557","ipdsId":"IP-060930","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":470307,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4236/ajcc.2016.54037","text":"Publisher Index Page"},{"id":332908,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":335050,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7CV4FVR","text":"MODFLOW datasets for simulations of groundwater flow with downscaled global climate model data for the Suwannee River Basin, Florida"}],"country":"United States","state":"Florida","otherGeospatial":"Suwannee River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.276123046875,\n 29.046565622728846\n ],\n [\n -84.276123046875,\n 30.642638258763263\n ],\n [\n -82.73803710937499,\n 30.642638258763263\n ],\n [\n -82.73803710937499,\n 29.046565622728846\n ],\n [\n -84.276123046875,\n 29.046565622728846\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"586e1820e4b0f5ce109fcad9","contributors":{"authors":[{"text":"Swain, Eric D. 0000-0001-7168-708X edswain@usgs.gov","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":1538,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","email":"edswain@usgs.gov","middleInitial":"D.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":657443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, J. Hal","contributorId":53832,"corporation":false,"usgs":true,"family":"Davis","given":"J. Hal","affiliations":[],"preferred":false,"id":657444,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70179454,"text":"70179454 - 2016 - Ciscoes (Coregonus, subgenus Leucichthys) of the Laurentian Great Lakes and Lake Nipigon","interactions":[],"lastModifiedDate":"2017-08-15T12:53:11","indexId":"70179454","displayToPublicDate":"2016-12-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Ciscoes (Coregonus, subgenus Leucichthys) of the Laurentian Great Lakes and Lake Nipigon","docAbstract":"This study of the ciscoes (Coregonus, subgenus Leucichthys) of the Great Lakes and Lake Nipigon represents a furtherance through 2015 of field research initiated by Walter Koelz in 1917 and continued by Stanford Smith in the mid-1900s—a period spanning nearly a century. Like Koelz’s study, this work contains information on taxonomy, geographical distribution, ecology, and status of species (here considered forms). Of the seven currently recognized forms (C. artedi, C. hoyi, C. johannae, C. kiyi, C. nigripinnis, C. reighardi, and C. zenithicus) described by Koelz as major in his 1929 monograph, two (C. johannae and C. reighardi) are extinct. In addition, C. alpenae, described by Koelz but subsequently synonymized with C. zenithicus, although extinct, is recognized as valid making a total of eight major forms. Six of these forms, all but C. artedi and C. hoyi, have been lost from Lake Michigan, and seven have been lost from Lake Huron, leaving in Lake Huron only C. artedi and an introgressed deepwater form that we term a hybrid swarm. C. artedi appears, like its sister form C. alpenae, to have been lost from Lake Erie. Only C. artedi remains extant in Lake Ontario, its three sister forms (C. hoyi, C. kiyi, and C. reighardi) having disappeared long ago.
Lakes Superior and Nipigon have retained their original species flocks consisting of four forms each: C. artedi, C. hoyi, and C. zenithicus in both lakes; C. kiyi in Lake Superior; and C. nigripinnis in Lake Nipigon. Morphological deviations from the morphotypes described by Koelz have been modest in contemporary samples. Overall, C. kiyi and C. artedi were the most morphologically stable forms while C. hoyi, C. nigripinnis, and C. zenithicus were the least stable. Although contemporary populations of C. artedi from Lakes Michigan and Huron are highly diverged from the morphotypes described by Koelz, the contemporary samples were of undescribed deep-bodied forms unlikely to have been sampled by Koelz because of their association with bays. Of the two intact species flocks, Lake Nipigon’s was much less stable morphologically than Lake Superior’s even though Lake Nipigon is far less disturbed. Two priorities for research are determining the role of developmental plasticity in morphological divergence, especially within C. zenithicus of Lake Superior, and the basis for morphological divergence in C. artedi.
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applications","interactions":[],"lastModifiedDate":"2017-01-03T13:49:49","indexId":"70179457","displayToPublicDate":"2016-12-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3230,"text":"Rangelands","active":true,"publicationSubtype":{"id":10}},"title":"Generalizing ecological site concepts of the Colorado Plateau for landscape-level applications","docAbstract":"Elevation data derived from light detection and ranging present challenges for hydrologic modeling as the elevation surface includes bridge decks and elevated road features overlaying culvert drainage structures. In reality, water is carried through these structures; however, in the elevation surface these features impede modeled overland surface flow. Thus, a hydrologically-enforced elevation surface is needed for hydrodynamic modeling. In the Delaware River Basin, hydrologic-enforcement techniques were used to modify elevations to simulate how constructed drainage structures allow overland surface flow. By calculating residuals between unfilled and filled elevation surfaces, artificially pooled depressions that formed upstream of constructed drainage structure features were defined, and elevation values were adjusted by generating transects at the location of the drainage structures. An assessment of each hydrologically-enforced drainage structure was conducted using field-surveyed culvert and bridge coordinates obtained from numerous public agencies, but it was discovered the disparate drainage structure datasets were not comprehensive enough to assess all remotely located depressions in need of hydrologic-enforcement. Alternatively, orthoimagery was interpreted to define drainage structures near each depression, and these locations were used as reference points for a quantitative hydrologic-enforcement assessment. The orthoimagery-interpreted reference points resulted in a larger corresponding sample size than the assessment between hydrologic-enforced transects and field-surveyed data. This assessment demonstrates the viability of rules-based hydrologic-enforcement that is needed to achieve hydrologic connectivity, which is valuable for hydrodynamic models in sensitive coastal regions. Hydrologic-enforced elevation data are also essential for merging with topographic/bathymetric elevation data that extend over vulnerable urbanized areas and dynamic coastal regions.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/SI76-009","usgsCitation":"Poppenga, S.K., and Worstell, B.B., 2016, Hydrologic connectivity: Quantitative assessments of hydrologic-enforced drainage structures in an elevation model: Journal of Coastal Research, v. Special Issue 76, p. 90-106, https://doi.org/10.2112/SI76-009.","productDescription":"17 p.","startPage":"90","endPage":"106","ipdsId":"IP-059049","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":470306,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.2112/SI76-009","text":"External Repository"},{"id":332787,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"Special Issue 76","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"586cc690e4b0f5ce109fa943","contributors":{"authors":[{"text":"Poppenga, Sandra K. 0000-0002-2846-6836 spoppenga@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-6836","contributorId":3327,"corporation":false,"usgs":true,"family":"Poppenga","given":"Sandra","email":"spoppenga@usgs.gov","middleInitial":"K.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":657389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Worstell, Bruce B. 0000-0001-8927-3336 worstell@usgs.gov","orcid":"https://orcid.org/0000-0001-8927-3336","contributorId":1815,"corporation":false,"usgs":true,"family":"Worstell","given":"Bruce","email":"worstell@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":657390,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70179489,"text":"70179489 - 2016 - Topobathymetric elevation model development using a new methodology: Coastal National Elevation Database","interactions":[],"lastModifiedDate":"2017-01-17T19:02:11","indexId":"70179489","displayToPublicDate":"2016-12-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Topobathymetric elevation model development using a new methodology: Coastal National Elevation Database","docAbstract":"During the coming decades, coastlines will respond to widely predicted sea-level rise, storm surge, and coastalinundation flooding from disastrous events. Because physical processes in coastal environments are controlled by the geomorphology of over-the-land topography and underwater bathymetry, many applications of geospatial data in coastal environments require detailed knowledge of the near-shore topography and bathymetry. In this paper, an updated methodology used by the U.S. Geological Survey Coastal National Elevation Database (CoNED) Applications Project is presented for developing coastal topobathymetric elevation models (TBDEMs) from multiple topographic data sources with adjacent intertidal topobathymetric and offshore bathymetric sources to generate\r\nseamlessly integrated TBDEMs. This repeatable, updatable, and logically consistent methodology assimilates topographic data (land elevation) and bathymetry (water depth) into a seamless coastal elevation model. Within the overarching framework, vertical datum transformations are standardized in a workflow that interweaves spatially consistent interpolation (gridding) techniques with a land/water boundary mask delineation approach. Output gridded raster TBDEMs are stacked into a file storage system of mosaic datasets within an Esri ArcGIS geodatabase for\r\nefficient updating while maintaining current and updated spatially referenced metadata. Topobathymetric data provide a required seamless elevation product for several science application studies, such as shoreline delineation, coastal inundation mapping, sediment-transport, sea-level rise, storm surge models, and tsunami impact assessment. These detailed coastal elevation data are critical to depict regions prone to climate change impacts and are essential to planners and managers responsible for mitigating the associated risks and costs to both human communities and ecosystems. The CoNED methodology approach has been used to construct integrated TBDEM models in Mobile Bay, the northern Gulf of Mexico, San Francisco Bay, the Hurricane Sandy region, and southern California.","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/SI76-008","usgsCitation":"Danielson, J.J., Poppenga, S.K., Brock, J., Evans, G.A., Tyler, D.J., Gesch, D.B., Thatcher, C.A., and Barras, J., 2016, Topobathymetric elevation model development using a new methodology: Coastal National Elevation Database: Journal of Coastal Research, v. Special Issue 76, p. 75-89, https://doi.org/10.2112/SI76-008.","productDescription":"15 p.","startPage":"75","endPage":"89","ipdsId":"IP-067362","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":470304,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.2112/SI76-008","text":"External Repository"},{"id":438478,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N4WLC8","text":"USGS data release","linkHelpText":"Southeast Texas Pilot National Topography Model (NTM), 1933 to 2021"},{"id":438477,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R8UZU6","text":"USGS data release","linkHelpText":"Topobathymetric Model of Puʻuhonua o Hōnaunau National Historical Park, 2011 to 2019"},{"id":438476,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J11VV6","text":"USGS data release","linkHelpText":"Topobathymetric Model of the Coastal Georgia, 1851 to 2020"},{"id":438475,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MPA8K0","text":"USGS data release","linkHelpText":"Topobathymetric Model of the Coastal Carolinas, 1851 to 2020"},{"id":438474,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q3VAY8","text":"USGS data release","linkHelpText":"Pilot Topobathymetric Terrain Model of the Kootenai River near Bonners Ferry, Idaho, 2009 - 2019"},{"id":438473,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KZ3LCV","text":"USGS data release","linkHelpText":"Topobathymetric Model of Northern California, 1986 to 2019"},{"id":438472,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GB3PC8","text":"USGS data release","linkHelpText":"Topobathymetric Model of the Strait of Juan de Fuca, 1891 to 2016"},{"id":438471,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UZIYI8","text":"USGS data release","linkHelpText":"Topobathymetric Model for the Southern Coast of California and the Channel Islands, 1930 to 2014"},{"id":438470,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7736Q34","text":"USGS data release","linkHelpText":"Topobathymetric Model for the Central Coast of California, 1929 to 2017"},{"id":332803,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"Special Issue 76","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"586cc68fe4b0f5ce109fa941","contributors":{"authors":[{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":657445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poppenga, Sandra K. 0000-0002-2846-6836 spoppenga@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-6836","contributorId":3327,"corporation":false,"usgs":true,"family":"Poppenga","given":"Sandra","email":"spoppenga@usgs.gov","middleInitial":"K.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":657447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":657446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Evans, Gayla A. 0000-0001-5072-4232 gevans@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-4232","contributorId":3125,"corporation":false,"usgs":true,"family":"Evans","given":"Gayla","email":"gevans@usgs.gov","middleInitial":"A.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":657448,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tyler, Dean J. 0000-0002-1542-7539 dtyler@usgs.gov","orcid":"https://orcid.org/0000-0002-1542-7539","contributorId":177897,"corporation":false,"usgs":true,"family":"Tyler","given":"Dean","email":"dtyler@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":657449,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":657450,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thatcher, Cindy A. 0000-0003-0331-071X thatcherc@usgs.gov","orcid":"https://orcid.org/0000-0003-0331-071X","contributorId":2868,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy","email":"thatcherc@usgs.gov","middleInitial":"A.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":657451,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Barras, John 0000-0002-4207-2972 jbarras@usgs.gov","orcid":"https://orcid.org/0000-0002-4207-2972","contributorId":177812,"corporation":false,"usgs":true,"family":"Barras","given":"John","email":"jbarras@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":657452,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70179347,"text":"70179347 - 2016 - Comment on “The reduction of friction in long-runout landslides as an emergent phenomenon” by Brandon C. Johnson et al.","interactions":[],"lastModifiedDate":"2016-12-29T12:26:10","indexId":"70179347","displayToPublicDate":"2016-12-29T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Comment on “The reduction of friction in long-runout landslides as an emergent phenomenon” by Brandon C. Johnson et al.","docAbstract":"Results from a highly idealized, 2-D computational model indicate that dynamic normal-stress rarefactions might cause friction reduction in long-runout landslides, but the physical relevance of the idealized dynamics has not been confirmed by experimental tests. More importantly, the model results provide no evidence that refutes alternative hypotheses about friction reduction mechanisms. One alternative hypothesis, which is strongly supported by field evidence, experimental data, and the predictions of a well-constrained computational model, involves development of high pore fluid pressures in deforming landslide material or overridden bed material. However, no scientific basis exists for concluding that a universal mechanism is responsible for friction reduction in all long-runout landslides.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2016JF003979","usgsCitation":"Iverson, R.M., 2016, Comment on “The reduction of friction in long-runout landslides as an emergent phenomenon” by Brandon C. Johnson et al.: Journal of Geophysical Research F: Earth Surface, v. 121, no. 11, p. 2238-2242, https://doi.org/10.1002/2016JF003979.","productDescription":"5 p.","startPage":"2238","endPage":"2242","ipdsId":"IP-076543","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":332636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-22","publicationStatus":"PW","scienceBaseUri":"58662f0fe4b0cd2dabe7c4a7","contributors":{"authors":[{"text":"Iverson, Richard M. 0000-0002-7369-3819 riverson@usgs.gov","orcid":"https://orcid.org/0000-0002-7369-3819","contributorId":536,"corporation":false,"usgs":true,"family":"Iverson","given":"Richard","email":"riverson@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":656871,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70179337,"text":"70179337 - 2016 - Debris flow runup on vertical barriers and adverse slopes","interactions":[],"lastModifiedDate":"2017-01-19T13:48:39","indexId":"70179337","displayToPublicDate":"2016-12-29T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Debris flow runup on vertical barriers and adverse slopes","docAbstract":"Runup of debris flows against obstacles in their paths is a complex process that involves profound flow deceleration and redirection. We investigate the dynamics and predictability of runup by comparing results from large-scale laboratory experiments, four simple analytical models, and a depth-integrated numerical model (D-Claw). The experiments and numerical simulations reveal the important influence of unsteady, multidimensional flow on runup, and the analytical models highlight key aspects of the underlying physics. Runup against a vertical barrier normal to the flow path is dominated by rapid development of a shock, or jump in flow height, associated with abrupt deceleration of the flow front. By contrast, runup on sloping obstacles is initially dominated by a smooth flux of mass and momentum from the flow body to the flow front, which precedes shock development and commonly increases the runup height. D-Claw simulations that account for the emergence of shocks show that predicted runup heights vary systematically with the adverse slope angle and also with the Froude number and degree of liquefaction (or effective basal friction) of incoming flows. They additionally clarify the strengths and limitations of simplified analytical models. Numerical simulations based on a priori knowledge of the evolving dynamics of incoming flows yield quite accurate runup predictions. Less predictive accuracy is attained in ab initio simulations that compute runup based solely on knowledge of static debris properties in a distant debris flow source area. Nevertheless, the paucity of inputs required in ab initio simulations enhances their prospective value in runup forecasting.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2016JF003933","usgsCitation":"Iverson, R.M., George, D.L., and Logan, M., 2016, Debris flow runup on vertical barriers and adverse slopes: Journal of Geophysical Research F: Earth Surface, v. 121, no. 12, p. 2333-2357, https://doi.org/10.1002/2016JF003933.","productDescription":"25 p.","startPage":"2333","endPage":"2357","ipdsId":"IP-075299","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":470310,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016jf003933","text":"Publisher Index Page"},{"id":438480,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JH3JB0","text":"USGS data release","linkHelpText":"Data from debris-flow run-up experiments conducted in June, 1994, and May, 1997, at the USGS Debris-flow Flume, HJ Andrews Experimental Forest, Blue River, Oregon"},{"id":332623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-13","publicationStatus":"PW","scienceBaseUri":"58662f11e4b0cd2dabe7c4ab","contributors":{"authors":[{"text":"Iverson, Richard M. 0000-0002-7369-3819 riverson@usgs.gov","orcid":"https://orcid.org/0000-0002-7369-3819","contributorId":536,"corporation":false,"usgs":true,"family":"Iverson","given":"Richard","email":"riverson@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":656848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, David L. 0000-0002-5726-0255 dgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-5726-0255","contributorId":3120,"corporation":false,"usgs":true,"family":"George","given":"David","email":"dgeorge@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":656849,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Logan, Matthew 0000-0002-3558-2405 mlogan@usgs.gov","orcid":"https://orcid.org/0000-0002-3558-2405","contributorId":638,"corporation":false,"usgs":true,"family":"Logan","given":"Matthew","email":"mlogan@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":656850,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70179338,"text":"70179338 - 2016 - Discussion of “The relation between dilatancy, effective stress and dispersive pressure in granular avalanches” by P. Bartelt and O. Buser (DOI: 10.1007/s11440-016-0463-7)","interactions":[],"lastModifiedDate":"2016-12-29T11:24:38","indexId":"70179338","displayToPublicDate":"2016-12-29T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5247,"text":"Acta Geotechnica","onlineIssn":"1861-1133","printIssn":"1861-1125","active":true,"publicationSubtype":{"id":10}},"title":"Discussion of “The relation between dilatancy, effective stress and dispersive pressure in granular avalanches” by P. Bartelt and O. Buser (DOI: 10.1007/s11440-016-0463-7)","docAbstract":"A paper recently published by Bartelt and Buser (hereafter identified as “the authors”) aims to clarify relationships between granular dilatancy and dispersive pressure and to question the effective stress principle and its application to shallow granular avalanches (Bartelt and Buser in Act Geotech 11:549–557, 2). The paper also criticizes our own recent work, which utilizes the concepts of evolving dilatancy and effective stress to model the initiation and dynamics of water-saturated landslides and debris flows. Here we first explain why we largely agree with the authors’ views of dilatancy and dispersive pressure as they apply to depth-integrated granular avalanche models, and why we disagree with their views of effective stress and pore-fluid pressure. We conclude by explaining why the authors’ characterization of our recently developed D-Claw model is inaccurate.
","language":"English","publisher":"Springer","publisherLocation":"Berlin","doi":"10.1007/s11440-016-0502-4","usgsCitation":"Iverson, R.M., and George, D.L., 2016, Discussion of “The relation between dilatancy, effective stress and dispersive pressure in granular avalanches” by P. Bartelt and O. Buser (DOI: 10.1007/s11440-016-0463-7): Acta Geotechnica, v. 11, no. 6, p. 1465-1468, https://doi.org/10.1007/s11440-016-0502-4.","productDescription":"4 p.","startPage":"1465","endPage":"1468","ipdsId":"IP-077983","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":332624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-17","publicationStatus":"PW","scienceBaseUri":"58662f10e4b0cd2dabe7c4a9","contributors":{"authors":[{"text":"Iverson, Richard M. 0000-0002-7369-3819 riverson@usgs.gov","orcid":"https://orcid.org/0000-0002-7369-3819","contributorId":536,"corporation":false,"usgs":true,"family":"Iverson","given":"Richard","email":"riverson@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":656851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, David L. 0000-0002-5726-0255 dgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-5726-0255","contributorId":3120,"corporation":false,"usgs":true,"family":"George","given":"David","email":"dgeorge@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":656852,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70179348,"text":"70179348 - 2016 - Modelling landslide liquefaction, mobility bifurcation and the dynamics of the 2014 Oso disaster","interactions":[],"lastModifiedDate":"2016-12-29T12:24:19","indexId":"70179348","displayToPublicDate":"2016-12-29T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1825,"text":"Geotechnique","active":true,"publicationSubtype":{"id":10}},"title":"Modelling landslide liquefaction, mobility bifurcation and the dynamics of the 2014 Oso disaster","docAbstract":"Some landslides move slowly or intermittently downslope, but others liquefy during the early stages of motion, leading to runaway acceleration and high-speed runout across low-relief terrain. Mechanisms responsible for this disparate behaviour are represented in a two-phase, depth-integrated, landslide dynamics model that melds principles from soil mechanics, granular mechanics and fluid mechanics. The model assumes that gradually increasing pore-water pressure causes slope failure to nucleate at the weakest point on a basal slip surface in a statically balanced mass. Failure then spreads to adjacent regions as a result of momentum exchange. Liquefaction is contingent on pore-pressure feedback that depends on the initial soil state. The importance of this feedback is illustrated by using the model to study the dynamics of a disastrous landslide that occurred near Oso, Washington, USA, on 22 March 2014. Alternative simulations of the event reveal the pronounced effects of a landslide mobility bifurcation that occurs if the initial void ratio of water-saturated soil equals the lithostatic, critical-state void ratio. They also show that the tendency for bifurcation increases as the soil permeability decreases. The bifurcation implies that it can be difficult to discriminate conditions that favour slow landsliding from those that favour liquefaction and long runout.
","language":"English","publisher":"Institution of Civil Engineers","publisherLocation":"London","doi":"10.1680/jgeot.15.LM.004","usgsCitation":"Iverson, R.M., and George, D.L., 2016, Modelling landslide liquefaction, mobility bifurcation and the dynamics of the 2014 Oso disaster: Geotechnique, v. 66, no. 3, p. 175-187, https://doi.org/10.1680/jgeot.15.LM.004.","productDescription":"13 p.","startPage":"175","endPage":"187","ipdsId":"IP-063350","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":332634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","city":"Oso","volume":"66","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58662f0ee4b0cd2dabe7c4a5","contributors":{"authors":[{"text":"Iverson, Richard M. 0000-0002-7369-3819 riverson@usgs.gov","orcid":"https://orcid.org/0000-0002-7369-3819","contributorId":536,"corporation":false,"usgs":true,"family":"Iverson","given":"Richard","email":"riverson@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":656872,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, David L. 0000-0002-5726-0255 dgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-5726-0255","contributorId":3120,"corporation":false,"usgs":true,"family":"George","given":"David","email":"dgeorge@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":656873,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70178049,"text":"fs20163088 - 2016 - The 3D elevation program - Precision agriculture and other farm practices","interactions":[],"lastModifiedDate":"2018-02-15T16:10:39","indexId":"fs20163088","displayToPublicDate":"2016-12-27T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3088","title":"The 3D elevation program - Precision agriculture and other farm practices","docAbstract":"A founding motto of the Natural Resources Conservation Service (NRCS), originally the Soil Conservation Service (SCS), explains that “If we take care of the land, it will take care of us.” Digital elevation models (DEMs; see fig. 1) are derived from light detection and ranging (lidar) data and can be processed to derive values such as slope angle, aspect, and topographic curvature. These three measurements are the principal parameters of the NRCS LidarEnhanced Soil Survey (LESS) model, which improves the precision of soil surveys, by more accurately displaying the slopes and soils patterns, while increasing the objectivity and science in line placement. As combined resources, DEMs, LESS model outputs, and similar derived datasets are essential for conserving soil, wetlands, and other natural resources managed and overseen by the NRCS and other Federal and State agencies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163088","usgsCitation":"Sugarbaker, L.J., and Carswell, W.J., Jr., 2016, The 3D Elevation Program—Precision agriculture and other farm practices: U.S. Geological Survey Fact Sheet 2016–3088, 2 p., https://dx.doi.org/10.3133/fs20163088.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-072256","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":332363,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3088/coverthb.jpg"},{"id":332364,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3088/fs20163088.pdf","text":"Report","size":"409 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3088"}],"contact":"Director, National Geospatial Program
U.S. Geological Survey
12201 Sunrise Valley Drive
MS 511 National Center
Reston, VA 20192
Email: 3DEP@usgs.gov
http://www.usgs.gov/ngpo/
http://nationalmap.gov/3DEP/
1.Recently, estimators have been developed to estimate occupancy probabilities when false-positive detections occur during presence-absence surveys. Some of these estimators combine different types of survey data to improve estimates of occupancy. With these estimators, there is a tradeoff between the number of sample units surveyed, and the number and type of surveys at each sample unit. Guidance on efficient design of studies when false positives occur is unavailable.
2.For a range of scenarios, I identified survey designs that minimized the mean square error of the estimate of occupancy. I considered an approach that uses one survey method and two observation states and an approach that uses two survey methods. For each approach, I used numerical methods to identify optimal survey designs when model assumptions were met and parameter values were correctly anticipated, when parameter values were not correctly anticipated, and when the assumption of no unmodelled detection heterogeneity was violated.
3.Under the approach with two observation states, false positive detections increased the number of recommended surveys, relative to standard occupancy models. If parameter values could not be anticipated, pessimism about detection probabilities avoided poor designs. Detection heterogeneity could require more or fewer repeat surveys, depending on parameter values. If model assumptions were met, the approach with two survey methods was inefficient. However, with poor anticipation of parameter values, with detection heterogeneity, or with removal sampling schemes, combining two survey methods could improve estimates of occupancy.
4.Ignoring false positives can yield biased parameter estimates, yet false positives greatly complicate the design of occupancy studies. Specific guidance for major types of false-positive occupancy models, and for two assumption violations common in field data, can conserve survey resources. This guidance can be used to design efficient monitoring programs and studies of species occurrence, species distribution, or habitat selection, when false positives occur during surveys.
","language":"English","doi":"10.1111/2041-210X.12617","usgsCitation":"Clement, M., 2016, Designing occupancy studies when false-positive detections occur: Methods in Ecology and Evolution, v. 7, no. 12, p. 1529-1547, https://doi.org/10.1111/2041-210X.12617.","productDescription":"19 p.","startPage":"1529","endPage":"1547","ipdsId":"IP-073228","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470312,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.12617","text":"Publisher Index Page"},{"id":332545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":332511,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1111/2041-210X.12617/abstract"}],"volume":"7","issue":"12","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-18","publicationStatus":"PW","scienceBaseUri":"58638bd3e4b0cd2dabe7beac","contributors":{"authors":[{"text":"Clement, Matthew mclement@usgs.gov","contributorId":138815,"corporation":false,"usgs":true,"family":"Clement","given":"Matthew","email":"mclement@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":656555,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70179254,"text":"ofr20161211 - 2016 - Development of a study design and implementation plan to estimate juvenile salmon survival in Lookout Point Reservoir and other reservoirs of the Willamette Project, western Oregon","interactions":[],"lastModifiedDate":"2017-01-02T09:56:52","indexId":"ofr20161211","displayToPublicDate":"2016-12-23T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1211","title":"Development of a study design and implementation plan to estimate juvenile salmon survival in Lookout Point Reservoir and other reservoirs of the Willamette Project, western Oregon","docAbstract":"Survival estimates for juvenile salmon and steelhead fry in reservoirs impounded by high head dams are coveted data by resource managers. However, this information is difficult to obtain because these fish are too small for tagging using conventional methods such as passive-integrated transponders or radio or acoustic transmitters. We developed a study design and implementation plan to conduct a pilot evaluation that would assess the performance of two models for estimating fry survival in a field setting. The first model is a staggered-release recovery model that was described by Skalski and others (2009) and Skalski (2016). The second model is a parentage-based tagging N-mixture model that was developed and described in this document. Both models are conceptually and statistically sound, but neither has been evaluated in the field. In this document we provide an overview of a proposed study for 2017 in Lookout Point Reservoir, Oregon, that will evaluate survival of Chinook salmon fry using both models. This approach will allow us to test each model and compare survival estimates, to determine model performance and better understand these study designs using field-collected data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161211","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers and the Oregon Department of Fish and Wildlife","usgsCitation":"Kock, T.J., Perry, R.W., Monzyk, F.R., Pope, A.C., and Plumb, J.M., 2016, Development of a study design and implementation plan to estimate juvenile salmon survival in Lookout Point Reservoir and other reservoirs of the Willamette Project, western Oregon: U.S. Geological Survey Open-File Report 2016–1211, 25 p., https://doi.org/10.3133/ofr20161211.","productDescription":"iv, 25 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-079919","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":332514,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1211/coverthb.jpg"},{"id":332515,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1211/ofr20161211.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1211 Report PDF"}],"country":"United States","state":"Oregon","otherGeospatial":"Dexter Dam, Dexter Reservoir, Lookout Point Reservoir, Lookout Point Dam, Middle Fork Willamette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.89718627929688,\n 43.91768033000405\n ],\n [\n -122.81410217285155,\n 43.98589821991874\n ],\n [\n -122.64244079589842,\n 43.929055415997134\n ],\n [\n -122.5140380859375,\n 43.82808744469062\n ],\n [\n -122.63626098632812,\n 43.77059798257491\n ],\n [\n -122.75711059570312,\n 43.854830911225235\n ],\n [\n -122.89718627929688,\n 43.91768033000405\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/
Suspended-sediment and total phosphorus loads were computed for two sites in the Upper Klamath Basin on the Wood and Williamson Rivers, the two main tributaries to Upper Klamath Lake. High temporal resolution turbidity and acoustic backscatter data were used to develop surrogate regression models to compute instantaneous concentrations and loads on these rivers. Regression models for the Williamson River site showed strong correlations of turbidity with total phosphorus and suspended-sediment concentrations (adjusted coefficients of determination [Adj R2]=0.73 and 0.95, respectively). Regression models for the Wood River site had relatively poor, although statistically significant, relations of turbidity with total phosphorus, and turbidity and acoustic backscatter with suspended sediment concentration, with high prediction uncertainty. Total phosphorus loads for the partial 2014 water year (excluding October and November 2013) were 39 and 28 metric tons for the Williamson and Wood Rivers, respectively. These values are within the low range of phosphorus loads computed for these rivers from prior studies using water-quality data collected by the Klamath Tribes. The 2014 partial year total phosphorus loads on the Williamson and Wood Rivers are assumed to be biased low because of the absence of data from the first 2 months of water year 2014, and the drought conditions that were prevalent during that water year. Therefore, total phosphorus and suspended-sediment loads in this report should be considered as representative of a low-water year for the two study sites. Comparing loads from the Williamson and Wood River monitoring sites for November 2013–September 2014 shows that the Williamson and Sprague Rivers combined, as measured at the Williamson River site, contributed substantially more suspended sediment to Upper Klamath Lake than the Wood River, with 4,360 and 1,450 metric tons measured, respectively.
Surrogate techniques have proven useful at the two study sites, particularly in using turbidity to compute suspended-sediment concentrations in the Williamson River. This proof-of-concept effort for computing total phosphorus concentrations using turbidity at the Williamson and Wood River sites also has shown that with additional samples over a wide range of flow regimes, high-temporal-resolution total phosphorus loads can be estimated on a daily, monthly, and annual basis, along with uncertainties for total phosphorus and suspended-sediment concentrations computed using regression models. Sediment-corrected backscatter at the Wood River has potential for estimating suspended-sediment loads from the Wood River Valley as well, with additional analysis of the variable streamflow measured at that site. Suspended-sediment and total phosphorus loads with a high level of temporal resolution will be useful to water managers, restoration practitioners, and scientists in the Upper Klamath Basin working toward the common goal of decreasing nutrient and sediment loads in Upper Klamath Lake.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165167","collaboration":"Prepared in cooperation with the Bureau of Reclamation and the Klamath Tribes","usgsCitation":"Schenk, L.N., Anderson, C.W., Diaz, Paul, and Stewart, M.A., 2016, Evaluating external nutrient and suspended-sediment loads to Upper Klamath Lake, Oregon, using surrogate regressions with real-time turbidity and acoustic backscatter data: U.S. Geological Survey Scientific Investigations Report 2016–5167, 46 p., https://doi.org/10.3133/sir20165167.","productDescription":"vii, 46 p.","numberOfPages":"58","onlineOnly":"Y","ipdsId":"IP-075160","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":332500,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5167/sir20165167.pdf","text":"Report","size":"6.5","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5167 Report PDF"},{"id":332499,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5167/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.3,\n 42.0\n ],\n [\n -122.3,\n 43.3\n ],\n [\n -120.4,\n 43.3\n ],\n [\n -120.4,\n 42.0\n ],\n [\n -122.3,\n 42.0\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov