{"pageNumber":"1073","pageRowStart":"26800","pageSize":"25","recordCount":184743,"records":[{"id":70179646,"text":"70179646 - 2016 - DOM composition and transformation in boreal forest soils: The effects of temperature and organic-horizon decomposition state","interactions":[],"lastModifiedDate":"2017-01-10T11:13:30","indexId":"70179646","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"DOM composition and transformation in boreal forest soils: The effects of temperature and organic-horizon decomposition state","docAbstract":"<p><span>The boreal region stores large amounts of organic carbon (C) in organic-soil horizons, which are vulnerable to destabilization via warming and disturbance. Decomposition of soil organic matter (SOM) contributes to the production and turnover of dissolved organic matter (DOM). While temperature is a primary control on rates of SOM and DOM cycling, little is known about temperature effects on DOM composition in soil leachate. Here we conducted a 30 day incubation to examine the effects of temperature (20 versus 5°C) and SOM decomposition state (moss versus fibric versus amorphous horizons) on DOM composition in organic soils of interior Alaska. We characterized DOM using bulk dissolved organic C (DOC) concentration, chemical fractionation, optical properties, and ultrahigh-resolution mass spectrometry. We observed an increase in DOC concentration and DOM aromaticity in the 20°C treatment compared to the 5°C treatment. Leachate from fibric horizons had higher DOC concentration than shallow moss or deep amorphous horizons. We also observed chemical shifts in DOM leachate over time, including increases in hydrophobic organic acids, polyphenols, and condensed aromatics and decreases in low-molecular weight hydrophilic compounds and aliphatics. We compared ultrahigh-resolution mass spectrometry and optical data and observed strong correlations between polyphenols, condensed aromatics, SUVA</span><sub>254</sub><span>, and humic-like fluorescence intensities. These findings suggest that biolabile DOM was preferentially mineralized, and the magnitude of this transformation was determined by kinetics (i.e., temperature) and substrate quality (i.e., soil horizon). With future warming, our findings indicate that organic soils may release higher concentrations of aromatic DOM to aquatic ecosystems.</span></p>","language":"English","publisher":"AGU Publications","doi":"10.1002/2016JG003431","usgsCitation":"O’Donnell, J.A., Aiken, G.R., Butler, K.D., Guillemette, F., Podgorski, D.C., and Spencer, R., 2016, DOM composition and transformation in boreal forest soils: The effects of temperature and organic-horizon decomposition state: Journal of Geophysical Research: Biogeosciences, v. 121, no. 10, p. 2727-2744, https://doi.org/10.1002/2016JG003431.","productDescription":"18 p.","startPage":"2727","endPage":"2744","ipdsId":"IP-077855","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470533,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016jg003431","text":"Publisher Index Page"},{"id":333013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-29","publicationStatus":"PW","scienceBaseUri":"58760116e4b04eac8e0746e1","contributors":{"authors":[{"text":"O’Donnell, Jonathan A.","contributorId":178151,"corporation":false,"usgs":false,"family":"O’Donnell","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":658042,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":658041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Butler, Kenna D. kebutler@usgs.gov","contributorId":3283,"corporation":false,"usgs":true,"family":"Butler","given":"Kenna","email":"kebutler@usgs.gov","middleInitial":"D.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":658043,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guillemette, Francois","contributorId":178152,"corporation":false,"usgs":false,"family":"Guillemette","given":"Francois","affiliations":[],"preferred":false,"id":658044,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Podgorski, David C.","contributorId":178153,"corporation":false,"usgs":false,"family":"Podgorski","given":"David","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":658045,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spencer, Robert G. M.","contributorId":139731,"corporation":false,"usgs":false,"family":"Spencer","given":"Robert G. M.","affiliations":[{"id":12894,"text":"Department of Land, Air, and Water Resources, University of California, One Shields Avenue, Davis, CA, 95616, USA","active":true,"usgs":false}],"preferred":false,"id":658046,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70175071,"text":"70175071 - 2016 - Hydrothermal frictional strengths of rock and mineral samples relevant to the creeping section of the San Andreas Fault","interactions":[],"lastModifiedDate":"2016-10-04T16:17:40","indexId":"70175071","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2468,"text":"Journal of Structural Geology","active":true,"publicationSubtype":{"id":10}},"title":"Hydrothermal frictional strengths of rock and mineral samples relevant to the creeping section of the San Andreas Fault","docAbstract":"<p><span>We compare frictional strengths in the temperature range 25–250&nbsp;°C of fault gouge from SAFOD (CDZ and SDZ) with quartzofeldspathic wall rocks typical of the central creeping section of the San Andreas Fault (Great Valley sequence and Franciscan Complex). The Great Valley and Franciscan samples have coefficients of friction, μ &gt; 0.35&nbsp;at all experimental conditions. Strength is unchanged between 25° and 150&nbsp;°C, but μ increases at higher temperatures, exceeding 0.50&nbsp;at 250&nbsp;°C. Both samples are velocity strengthening at room temperature but show velocity-weakening behavior beginning at 150&nbsp;°C and stick-slip motion at 250&nbsp;°C. These rocks, therefore, have the potential for unstable seismic slip at depth. The CDZ gouge, with a high saponite content, is weak (μ&nbsp;=&nbsp;0.09–0.17) and velocity strengthening in all experiments, and μ decreases at temperatures above 150&nbsp;°C. Behavior of the SDZ is intermediate between the CDZ and wall rocks: μ &lt; 0.2 and does not vary with temperature. Although saponite is probably not stable at depths greater than ∼3&nbsp;km, substitution of the frictionally similar minerals talc and Mg-rich chlorite for saponite at higher temperatures could potentially extend the range of low strength and stable slip down to the base of the seismogenic zone.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jsg.2016.06.005","usgsCitation":"Moore, D.E., Lockner, D.A., and Hickman, S.H., 2016, Hydrothermal frictional strengths of rock and mineral samples relevant to the creeping section of the San Andreas Fault: Journal of Structural Geology, v. 89, p. 153-167, https://doi.org/10.1016/j.jsg.2016.06.005.","productDescription":"15 p.","startPage":"153","endPage":"167","ipdsId":"IP-071748","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":329297,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.16796875,\n              35.5\n            ],\n            [\n              -122.16796875,\n              37\n            ],\n            [\n              -120,\n              37\n            ],\n            [\n              -120,\n              35.5\n            ],\n            [\n              -122.16796875,\n              35.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"89","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7c63ae4b0bc0bec09c834","contributors":{"authors":[{"text":"Moore, Diane E. 0000-0002-8641-1075 dmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-8641-1075","contributorId":2704,"corporation":false,"usgs":true,"family":"Moore","given":"Diane","email":"dmoore@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":643768,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lockner, David A. 0000-0001-8630-6833 dlockner@usgs.gov","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":567,"corporation":false,"usgs":true,"family":"Lockner","given":"David","email":"dlockner@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":643769,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hickman, Stephen H. 0000-0003-2075-9615 hickman@usgs.gov","orcid":"https://orcid.org/0000-0003-2075-9615","contributorId":2705,"corporation":false,"usgs":true,"family":"Hickman","given":"Stephen","email":"hickman@usgs.gov","middleInitial":"H.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":643770,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192733,"text":"70192733 - 2016 - Consequences of changes in vegetation and snow cover for climate feedbacks in Alaska and northwest Canada","interactions":[],"lastModifiedDate":"2017-11-08T13:14:53","indexId":"70192733","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Consequences of changes in vegetation and snow cover for climate feedbacks in Alaska and northwest Canada","docAbstract":"<p><span>Changes in vegetation and snow cover may lead to feedbacks to climate through changes in surface albedo and energy fluxes between the land and atmosphere. In addition to these biogeophysical feedbacks, biogeochemical feedbacks associated with changes in carbon (C) storage in the vegetation and soils may also influence climate. Here, using a transient biogeographic model (ALFRESCO) and an ecosystem model (DOS-TEM), we quantified the biogeophysical feedbacks due to changes in vegetation and snow cover across continuous permafrost to non-permafrost ecosystems in Alaska and northwest Canada. We also computed the changes in carbon storage in this region to provide a general assessment of the direction of the biogeochemical feedback. We considered four ecoregions, or Landscape Conservations Cooperatives (LCCs; including the Arctic, North Pacific, Western Alaska, and Northwest Boreal). We examined the 90 year period from 2010 to 2099 using one future emission scenario (A1B), under outputs from two general circulation models (MPI-ECHAM5 and CCCMA-CGCM3.1). We found that changes in snow cover duration, including both the timing of snowmelt in the spring and snow return in the fall, provided the dominant positive biogeophysical feedback to climate across all LCCs, and was greater for the ECHAM (+3.1 W m</span><sup>−2</sup><span><span>&nbsp;</span>decade</span><sup>−1</sup><span>regionally) compared to the CCCMA (+1.3 W m</span><sup>−2</sup><span><span>&nbsp;</span>decade</span><sup>−1</sup><span><span>&nbsp;</span>regionally) scenario due to an increase in loss of snow cover in the ECHAM scenario. The greatest overall negative feedback to climate from changes in vegetation cover was due to fire in spruce forests in the Northwest Boreal LCC and fire in shrub tundra in the Western LCC (−0.2 to −0.3 W m</span><sup>−2</sup><span><span>&nbsp;</span>decade</span><sup>−1</sup><span>). With the larger positive feedbacks associated with reductions in snow cover compared to the smaller negative feedbacks associated with shifts in vegetation, the feedback to climate warming was positive (total feedback of +2.7 W m</span><sup>−2</sup><span>decade regionally in the ECHAM scenario compared to +0.76 W m</span><sup>−2</sup><span><span>&nbsp;</span>decade regionally in the CCCMA scenario). Overall, increases in C storage in the vegetation and soils across the study region would act as a negative feedback to climate. By exploring these feedbacks to climate, we can reach a more integrated understanding of the manner in which climate change may impact interactions between high-latitude ecosystems and the global climate system.</span></p>","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/11/10/105003","usgsCitation":"Euskirchen, E., Bennett, A.P., Breen, A.L., Genet, H., Lindgren, M.A., Kurkowski, T., McGuire, A.D., and Rupp, T., 2016, Consequences of changes in vegetation and snow cover for climate feedbacks in Alaska and northwest Canada: Environmental Research Letters, v. 11, p. 1-19, https://doi.org/10.1088/1748-9326/11/10/105003.","productDescription":"Article 105003; 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-075009","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470523,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/11/10/105003","text":"Publisher Index Page"},{"id":348455,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -179.560546875,\n              50.958426723359935\n            ],\n            [\n              -125.20019531249999,\n              50.958426723359935\n            ],\n            [\n              -125.20019531249999,\n              71.38514208411495\n            ],\n            [\n              -179.560546875,\n              71.38514208411495\n            ],\n            [\n              -179.560546875,\n              50.958426723359935\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-03","publicationStatus":"PW","scienceBaseUri":"5a0425bee4b0dc0b45b453e7","contributors":{"authors":[{"text":"Euskirchen, Eugénie S.","contributorId":83378,"corporation":false,"usgs":false,"family":"Euskirchen","given":"Eugénie S.","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":721167,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bennett, A. P.","contributorId":200154,"corporation":false,"usgs":false,"family":"Bennett","given":"A.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":721168,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breen, Amy L.","contributorId":81396,"corporation":false,"usgs":true,"family":"Breen","given":"Amy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":721169,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Genet, Helene","contributorId":95370,"corporation":false,"usgs":true,"family":"Genet","given":"Helene","affiliations":[],"preferred":false,"id":721170,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindgren, Michael A.","contributorId":33237,"corporation":false,"usgs":true,"family":"Lindgren","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":721171,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kurkowski, Tom","contributorId":198681,"corporation":false,"usgs":false,"family":"Kurkowski","given":"Tom","affiliations":[],"preferred":false,"id":721172,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":716792,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rupp, T. Scott","contributorId":21395,"corporation":false,"usgs":true,"family":"Rupp","given":"T. Scott","affiliations":[],"preferred":false,"id":721173,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70191893,"text":"70191893 - 2016 - How well are you teaching one of the most important biological concepts for humankind? A call to action","interactions":[],"lastModifiedDate":"2017-10-26T14:18:01","indexId":"70191893","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5534,"text":"The American Biology Teacher","active":true,"publicationSubtype":{"id":10}},"title":"How well are you teaching one of the most important biological concepts for humankind? A call to action","docAbstract":"<p id=\"p-1\">We represent several generations of biology educators – with teaching experiences beginning in the 1940s and continuing to the present, from elementary school to graduate-level programs. We find the vast array of subjects that biology teachers can now cover both thrilling and mind-boggling. Depending on the grade level, units exist that focus on neurobiology, forensics, DNA analysis, biotechnology, marine biology, and a host of other topics.</p><p id=\"p-2\">Although science teachers cover a potpourri of advanced topics, we must ask ourselves – no matter our biology-teaching responsibilities – how well we are teaching<span>&nbsp;</span><i>carrying capacity</i>, one of the most fundamental biological concepts for our society, knowledge of which becomes more important every day. As biology teachers, most of you know that carrying capacity is defined as the maximum population an environment can sustain, given the amounts of food, habitat, and other resources available. Every environment – from your goldfish bowl to the local forest to planet Earth – can only sustain a set number (weight) of a particular species, based on available resources and space. Currently, most science classes teach …</p>","language":"English","publisher":"National Association of Biology Teachers","doi":"10.1525/abt.2016.78.8.623","usgsCitation":"Bonar, S.A., Fife, D.A., and Bonar, J.S., 2016, How well are you teaching one of the most important biological concepts for humankind? A call to action: The American Biology Teacher, v. 78, no. 8, p. 623-623, https://doi.org/10.1525/abt.2016.78.8.623.","productDescription":"1 p.","startPage":"623","endPage":"623","ipdsId":"IP-066233","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":347488,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","issue":"8","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07e9c5e4b09af898c8cc4f","contributors":{"authors":[{"text":"Bonar, Scott A. 0000-0003-3532-4067 sbonar@usgs.gov","orcid":"https://orcid.org/0000-0003-3532-4067","contributorId":3712,"corporation":false,"usgs":true,"family":"Bonar","given":"Scott","email":"sbonar@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":713551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fife, Deanna A.","contributorId":198571,"corporation":false,"usgs":false,"family":"Fife","given":"Deanna","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":716426,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bonar, John S.","contributorId":198572,"corporation":false,"usgs":false,"family":"Bonar","given":"John","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":716427,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70187250,"text":"70187250 - 2016 - Long-term deer exclusion has complex effects on a suburban forest understory","interactions":[],"lastModifiedDate":"2017-04-28T11:38:30","indexId":"70187250","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3297,"text":"Rhodora","active":true,"publicationSubtype":{"id":10}},"title":"Long-term deer exclusion has complex effects on a suburban forest understory","docAbstract":"<p><span>Herbivory by deer is one of the leading biotic disturbances on forest understories (i.e., herbs, small shrubs, and small tree seedlings). A large body of research has reported declines in height, abundance, and reproductive capacity of forbs and woody plants coupled with increases in abundance of graminoids, ferns, and exotic species due to deer herbivory. Less clear is the extent to which (and the direction in which) deer alter herbaceous layer diversity, where much of the plant diversity in a forest occurs. We examined the effect of 15 y of deer exclusion on the understory of a suburban hardwood forest in Connecticut exposed to decades of intensive herbivory by white-tailed deer (</span><i><i>Odocoileus virginianus</i></i><span>). We compared species richness (at subplot and plot scale), individual species and life form group abundance (% cover), and community composition between grazed and exclosure plots, as well as between mesic and wet soil blocks. Forb cover was more than twice as abundant in exclosure as in grazed plots, whereas sedge (</span><i><i>Carex</i></i><span> spp.) cover was 28 times more abundant, and exotic species cover generally higher in grazed than in exclosure plots. Native and exotic species richness were both higher in grazed than exclosure plots at the subplot scale, and native herbaceous richness was higher in grazed plots at both spatial scales. In contrast, native shrub richness increased with deer exclusion at the plot scale. Our results suggest that deer exclusion had contrasting effects on species richness, depending on plant life form, but that overall richness of both exotic and native plants declined with deer exclusion. In addition, site heterogeneity remained an important driver of vegetation dynamics even in the midst of high deer densities.</span></p>","language":"English","publisher":"The New England Botanical Club, Inc.","doi":"10.3119/15-35","usgsCitation":"Faison, E.K., Foster, D., and DeStefano, S., 2016, Long-term deer exclusion has complex effects on a suburban forest understory: Rhodora, v. 118, no. 976, p. 382-402, https://doi.org/10.3119/15-35.","productDescription":"21 p.","startPage":"382","endPage":"402","ipdsId":"IP-072271","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"118","issue":"976","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"590454a3e4b022cee40dc22e","contributors":{"authors":[{"text":"Faison, Edward K.","contributorId":191559,"corporation":false,"usgs":false,"family":"Faison","given":"Edward","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":693468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foster, David R.","contributorId":149881,"corporation":false,"usgs":false,"family":"Foster","given":"David R.","affiliations":[{"id":16810,"text":"Harvard Univ.","active":true,"usgs":false}],"preferred":false,"id":693469,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeStefano, Stephen 0000-0003-2472-8373 destef@usgs.gov","orcid":"https://orcid.org/0000-0003-2472-8373","contributorId":166706,"corporation":false,"usgs":true,"family":"DeStefano","given":"Stephen","email":"destef@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":693108,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70184980,"text":"70184980 - 2016 - Fragmented patterns of flood change across the United States","interactions":[],"lastModifiedDate":"2017-03-14T15:38:22","indexId":"70184980","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Fragmented patterns of flood change across the United States","docAbstract":"<p><span>Trends in the peak magnitude, frequency, duration, and volume of frequent floods (floods occurring at an average of two events per year relative to a base period) across the United States show large changes; however, few trends are found to be statistically significant. The multidimensional behavior of flood change across the United States can be described by four distinct groups, with streamgages experiencing (1) minimal change, (2) increasing frequency, (3) decreasing frequency, or (4) increases in all flood properties. Yet group membership shows only weak geographic cohesion. Lack of geographic cohesion is further demonstrated by weak correlations between the temporal patterns of flood change and large-scale climate indices. These findings reveal a complex, fragmented pattern of flood change that, therefore, clouds the ability to make meaningful generalizations about flood change across the United States.</span></p>","language":"English","publisher":"AGU Publications","doi":"10.1002/2016GL070590","usgsCitation":"Archfield, S.A., Hirsch, R.M., Viglione, A., and Blöschl, G., 2016, Fragmented patterns of flood change across the United States: Geophysical Research Letters, v. 43, no. 19, p. 10232-10239, https://doi.org/10.1002/2016GL070590.","productDescription":"8 p.","startPage":"10232","endPage":"10239","ipdsId":"IP-079542","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":470526,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl070590","text":"Publisher Index Page"},{"id":337538,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"43","issue":"19","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-09","publicationStatus":"PW","scienceBaseUri":"58c90125e4b0849ce97abcd7","contributors":{"authors":[{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":683811,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":683812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Viglione, A.","contributorId":189084,"corporation":false,"usgs":false,"family":"Viglione","given":"A.","affiliations":[],"preferred":false,"id":683813,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blöschl, G.","contributorId":189085,"corporation":false,"usgs":false,"family":"Blöschl","given":"G.","affiliations":[],"preferred":false,"id":683814,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70178430,"text":"70178430 - 2016 - Geology, selected geophysics, and hydrogeology of the White River and parts of the Great Salt Lake Desert regional groundwater flow systems, Utah and Nevada","interactions":[],"lastModifiedDate":"2017-04-19T11:49:02","indexId":"70178430","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Geology, selected geophysics, and hydrogeology of the White River and parts of the Great Salt Lake Desert regional groundwater flow systems, Utah and Nevada","docAbstract":"The east-central Great Basin near the Utah-Nevada border contains two great \ngroundwater flow systems.  The first, the White River regional groundwater \nflow system, consists of a string of hydraulically connected hydrographic basins \nin Nevada spanning about 270 miles from north to south.  The northernmost \nbasin is Long Valley and the southernmost basin is the Black Mountain area, a \nvalley bordering the Colorado River.  The general regional groundwater flow \ndirection is north to south. The second flow system, the Great Salt Lake Desert \nregional groundwater flow system, consists of hydrographic basins that straddle\nthe Utah-Nevada border, with a length of about 150 miles from north to south.  \nThe general regional groundwater flow direction is from south to north towards \nthe Great Salt Lake Desert.\n\nFor 15 years with support from the Southern Nevada Water Authority (SNWA), \nhydrologists, geologists, and geophysicists studied the basin connections and \nthe groundwater resources in these and adjacent flow systems over an area of \nabout 25,000 square miles. A major first part of the SNWA study was \nconstructing a 3-dimensional digital hydrogeologic framework based on \ngeologic maps and cross sections at 1:250,000 scale. This framework \ndocuments the presence of three major aquifers: (1) Paleozoic carbonate \nrocks, (2) Eocene to Miocene volcanic rocks, and (3) Miocene to Holocene \nbasin-fill sediments, as well as confining units that constrain flow. We \ninterpret that movement of most groundwater through and across basins is by \nfracture-dominated flow along faults/fractures, yet in most places flow is \nprevented or retarded across faults, so mapping structures gives a first \napproximation to conduits and barriers to flow.\n\nThe most important structures by far are high-angle normal faults of the \nbasin-range episode of east-west extensional deformation. This event \nbegan at about 20 Ma, although most deformation and the formation of the \npresent topography took place between 10 Ma and present.  This topography \nconsists of north-trending basins (mostly grabens) that alternate with north-\ntrending ranges (mostly horsts); erosion of the ranges filled the basins with \nclastic alluvial basin-fill deposits.\n\nGeophysics provides data on the third dimension (cross sections) of the \nhydrogeologic framework.  Audiomagnetotelluric profiles and gravity \ninversion located faults and enabled us to estimate thicknesses of basin-fill \ndeposits. To this framework, hydrologic studies addressed precipitation, \nsurface water, and springs, as well as groundwater levels, volumes, \ngeochemistry, water budgets, and monitoring. At nearly the same time as \nour study, the Utah Geological Survey (UGS) and U.S. Geological Survey \n(USGS) addressed the same issues in many of the same areas, and publication \nof the efforts by all three agencies reveals a surprising similarity of conclusions, \nwith some critical exceptions, which therefore demonstrates the great value of \nmany scientists independently studying the same complex scientific problem. \nThe differences in conclusions include directions and volumes of some ground-\nwater flow paths, such as one proposed by the USGS of unlikely groundwater \nflow from Steptoe Valley to southern Snake Valley, and another proposed by the \nUGS of unlikely significant groundwater recharge flow from the Snake Range to \nthe Fish Springs complex.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Resources and Geo- logy of Utah's West Desert","language":"English","publisher":"Utah Geologic Association","usgsCitation":"Rowley, P.D., Dixon, G.L., Watrus, J.M., Burns, A.G., Mankinen, E.A., McKee, E.H., Pari, K.T., Ekren, E.B., and Patrick, W.G., 2016, Geology, selected geophysics, and hydrogeology of the White River and parts of the Great Salt Lake Desert regional groundwater flow systems, Utah and Nevada, chap. <i>of</i> Resources and Geo- logy of Utah's West Desert, v. 45, p. 167-200.","productDescription":"34 p. 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mckee@usgs.gov","contributorId":3728,"corporation":false,"usgs":true,"family":"McKee","given":"Edwin","email":"mckee@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":673665,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pari, Keith T.","contributorId":184155,"corporation":false,"usgs":false,"family":"Pari","given":"Keith","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":673666,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ekren, E. Bartlett","contributorId":47644,"corporation":false,"usgs":true,"family":"Ekren","given":"E.","email":"","middleInitial":"Bartlett","affiliations":[],"preferred":false,"id":673667,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Patrick, William G.","contributorId":184151,"corporation":false,"usgs":false,"family":"Patrick","given":"William","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":673668,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70189238,"text":"70189238 - 2016 - Inter-comparison of three-dimensional models of volcanic plumes","interactions":[],"lastModifiedDate":"2017-07-06T13:11:53","indexId":"70189238","displayToPublicDate":"2016-10-01T00:00:00","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":"Inter-comparison of three-dimensional models of volcanic plumes","docAbstract":"<p><span>We performed an inter-comparison study of three-dimensional models of volcanic plumes. A set of common volcanological input parameters and meteorological conditions were provided for two kinds of eruptions, representing a weak and a strong eruption column. From the different models, we compared the maximum plume height, neutral buoyancy level (where plume density equals that of the atmosphere), and level of maximum radial spreading of the umbrella cloud. We also compared the vertical profiles of eruption column properties, integrated across cross-sections of the plume (integral variables). Although the models use different numerical procedures and treatments of subgrid turbulence and particle dynamics, the inter-comparison shows qualitatively consistent results. In the weak plume case (mass eruption rate 1.5</span><span>&nbsp;</span><span>×</span><span>&nbsp;</span><span>10</span><sup>6</sup><span>&nbsp;</span><span>kg</span><span>&nbsp;</span><span>s</span><sup>−&nbsp;1</sup><span>), the vertical profiles of plume properties (e.g., vertical velocity, temperature) are similar among models, especially in the buoyant plume region. Variability among the simulated maximum heights is ~</span><span>&nbsp;</span><span>20%, whereas neutral buoyancy level and level of maximum radial spreading vary by ~</span><span>&nbsp;</span><span>10%. Time-averaging of the three-dimensional (3D) flow fields indicates an effective entrainment coefficient around 0.1 in the buoyant plume region, with much lower values in the jet region, which is consistent with findings of small-scale laboratory experiments. On the other hand, the strong plume case (mass eruption rate 1.5</span><span>&nbsp;</span><span>×</span><span>&nbsp;</span><span>10</span><sup>9</sup><span>&nbsp;</span><span>kg</span><span>&nbsp;</span><span>s</span><sup>−&nbsp;1</sup><span>) shows greater variability in the vertical plume profiles predicted by the different models. Our analysis suggests that the unstable flow dynamics in the strong plume enhances differences in the formulation and numerical solution of the models. This is especially evident in the overshooting top of the plume, which extends a significant portion (~</span><span>&nbsp;</span><span>1/8) of the maximum plume height. Nonetheless, overall variability in the spreading level and neutral buoyancy level is ~</span><span>&nbsp;</span><span>20%, whereas that of maximum height is ~</span><span>&nbsp;</span><span>10%. This inter-comparison study has highlighted the different capabilities of 3D volcanic plume models, and identified key features of weak and strong plumes, including the roles of jet stability, entrainment efficiency, and particle non-equilibrium, which deserve future investigation in field, laboratory, and numerical studies.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2016.06.011","usgsCitation":"Suzuki, Y., Costa, A., Cerminara, M., Esposti Ongaro, T., Herzog, M., Van Eaton, A.R., and Denby, L., 2016, Inter-comparison of three-dimensional models of volcanic plumes: Journal of Volcanology and Geothermal Research, v. 326, p. 26-42, https://doi.org/10.1016/j.jvolgeores.2016.06.011.","productDescription":"17 p.","startPage":"26","endPage":"42","ipdsId":"IP-071593","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":470540,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.17863/cam.1638","text":"External Repository"},{"id":343414,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"326","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595f4c3ee4b0d1f9f057e345","contributors":{"authors":[{"text":"Suzuki, Yujiro","contributorId":194289,"corporation":false,"usgs":false,"family":"Suzuki","given":"Yujiro","email":"","affiliations":[],"preferred":false,"id":703662,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Costa, Antonio","contributorId":194290,"corporation":false,"usgs":false,"family":"Costa","given":"Antonio","email":"","affiliations":[{"id":27088,"text":"Istituto Nazionale di Geofisica e Vulcanologia (INGV)","active":true,"usgs":false}],"preferred":false,"id":703663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cerminara, Matteo","contributorId":194291,"corporation":false,"usgs":false,"family":"Cerminara","given":"Matteo","email":"","affiliations":[],"preferred":false,"id":703664,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esposti Ongaro, Tomaso","contributorId":194292,"corporation":false,"usgs":false,"family":"Esposti Ongaro","given":"Tomaso","email":"","affiliations":[],"preferred":false,"id":703665,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herzog, Michael","contributorId":194293,"corporation":false,"usgs":false,"family":"Herzog","given":"Michael","email":"","affiliations":[],"preferred":false,"id":703666,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Van Eaton, Alexa R. 0000-0001-6646-4594 avaneaton@usgs.gov","orcid":"https://orcid.org/0000-0001-6646-4594","contributorId":184079,"corporation":false,"usgs":true,"family":"Van Eaton","given":"Alexa","email":"avaneaton@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":703661,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Denby, Leif","contributorId":194294,"corporation":false,"usgs":false,"family":"Denby","given":"Leif","email":"","affiliations":[],"preferred":false,"id":703667,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70178310,"text":"70178310 - 2016 - Regional land subsidence caused by the compaction of susceptible aquifer systems accompanying groundwater extraction","interactions":[],"lastModifiedDate":"2019-09-06T11:17:58","indexId":"70178310","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Regional land subsidence caused by the compaction of susceptible aquifer systems accompanying groundwater extraction","docAbstract":"Land subsidence includes both gentle downwarping and sudden sinking of\nsegments of the land surface. Major anthropogenic causes of land subsidence\nare extraction of fluids including water, oil, and gas. Measurement and detec-\ntion of land subsidence include both ground-based and remotely sensed air-\nborne and space-based methods. Methods for measurement of subsidence at\npoints include differential leveling, global positioning system surveys, and\nextensometers. Satellite-borne differential interferometric synthetic aperture\nradar and airborne LiDAR techniques can detect land-surface movement over\nwide areas of interest. Aquifer-system compaction and subsidence owing to\ngroundwater extraction typically occurs in areas of unconsolidated alluvial or\nbasin-fill aquifer systems comprising aquifers and aquitards. Approaches to\nanalyzing and modeling deformation of aquifer systems follow from the basic\nrelations  between  head,  stress,  compressibility,  and  groundwater  flow.\nAnalysis and simulation of aquifer-system compaction have been addressed\nprimarily using either an approach based on conventional groundwater flow\ntheory or an approach based on linear poroelasticity theory. Both approaches\nrely on the principle of effective stress outlined by Karl Terzaghi in 1925. In\nthe approach based on conventional groundwater flow theory, an aquitard\ndrainage model explains the compaction of fine grained material using the\nprinciple of effective stress and theory of hydrodynamic lag. Packages for the\nwidely-used MODFLOW groundwater model are available to simulate aqui-\nfer-system  compaction  and  land  subsidence  using  the  aquitard-drainage\napproach. Poroelasticity theory describes the more fully coupled processes of\ngroundwater flow and three-dimensional deformation of aquifer systems.\nThe general theory accounts for compressible fluid, porous matrix and solid\ngrains. Simulation codes using the poroelastic theory include some commer-\ncial software products and a few research codes.","largerWorkTitle":"Handbook of applied hydrology","language":"English","publisher":"McGraw-Hill Education","isbn":"9780071835091","usgsCitation":"Galloway, D.L., and Leake, S.A., 2016, Regional land subsidence caused by the compaction of susceptible aquifer systems accompanying groundwater extraction, chap. <i>of</i> Handbook of applied hydrology, p. 56.1-56.11.","productDescription":"11 p.","startPage":"56.1","endPage":"56.11","ipdsId":"IP-066741","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":337768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"2nd","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58cba41ae4b0849ce97dc744","contributors":{"editors":[{"text":"Singh, Vijay P.","contributorId":176741,"corporation":false,"usgs":false,"family":"Singh","given":"Vijay","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":684832,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Galloway, Devin L. 0000-0003-0904-5355 dlgallow@usgs.gov","orcid":"https://orcid.org/0000-0003-0904-5355","contributorId":679,"corporation":false,"usgs":true,"family":"Galloway","given":"Devin","email":"dlgallow@usgs.gov","middleInitial":"L.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":653592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leake, Stanley A. 0000-0003-3568-2542 saleake@usgs.gov","orcid":"https://orcid.org/0000-0003-3568-2542","contributorId":1846,"corporation":false,"usgs":true,"family":"Leake","given":"Stanley","email":"saleake@usgs.gov","middleInitial":"A.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":653593,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70187241,"text":"70187241 - 2016 - Development of habitat suitability indices for the Candy Darter, with cross-scale validation across representative populations","interactions":[],"lastModifiedDate":"2017-04-28T14:00:09","indexId":"70187241","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Development of habitat suitability indices for the Candy Darter, with cross-scale validation across representative populations","docAbstract":"<p><span>Understanding relationships between habitat associations for individuals and habitat factors that limit populations is a primary challenge for managers of stream fishes. Although habitat use by individuals can provide insight into the adaptive significance of selected microhabitats, not all habitat parameters will be significant at the population level, particularly when distributional patterns partially result from habitat degradation. We used underwater observation to quantify microhabitat selection by an imperiled stream fish, the Candy Darter </span><i>Etheostoma osburni</i><span>, in two streams with robust populations. We developed multiple-variable and multiple-life-stage habitat suitability indices (HSIs) from microhabitat selection patterns and used them to assess the suitability of available habitat in streams where Candy Darter populations were extirpated, localized, or robust. Next, we used a comparative framework to examine relationships among (1) habitat availability across streams, (2) projected habitat suitability of each stream, and (3) a rank for the likely long-term viability (robustness) of the population inhabiting each stream. Habitat selection was characterized by ontogenetic shifts from the low-velocity, slightly embedded areas used by age-0 Candy Darters to the swift, shallow areas with little fine sediment and complex substrate, which were used by adults. Overall, HSIs were strongly correlated with population rank. However, we observed weak or inverse relationships between predicted individual habitat suitability and population robustness for multiple life stages and variables. The results demonstrated that microhabitat selection by individuals does not always reflect population robustness, particularly when based on a single life stage or season, which highlights the risk of generalizing habitat selection that is observed during nonstressful periods or for noncritical resources. These findings suggest that stream fish managers may need to be cautious when implementing conservation measures based solely on observations of habitat selection by individuals and that detailed study at the individual and population levels may be necessary to identify habitat that limits populations.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2016.1217929","usgsCitation":"Dunn, C.G., and Angermeier, P.L., 2016, Development of habitat suitability indices for the Candy Darter, with cross-scale validation across representative populations: Transactions of the American Fisheries Society, v. 145, no. 6, p. 1266-1281, https://doi.org/10.1080/00028487.2016.1217929.","productDescription":"16 p.","startPage":"1266","endPage":"1281","ipdsId":"IP-075181","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470544,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Development_of_Habitat_Suitability_Indices_for_the_Candy_Darter_with_Cross-Scale_Validation_across_Representative_Populations/4001256","text":"External Repository"},{"id":340627,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"145","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-07","publicationStatus":"PW","scienceBaseUri":"590454a3e4b022cee40dc230","contributors":{"authors":[{"text":"Dunn, Corey G.","contributorId":191569,"corporation":false,"usgs":false,"family":"Dunn","given":"Corey","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":693502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693093,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70178043,"text":"70178043 - 2016 - Simulation modeling to explore the effects of length-based harvest regulations for <i>Ictalurus</i> fisheries","interactions":[],"lastModifiedDate":"2016-11-01T12:54:35","indexId":"70178043","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Simulation modeling to explore the effects of length-based harvest regulations for <i>Ictalurus</i> fisheries","docAbstract":"<p><span>Management of Blue Catfish </span><i>Ictalurus furcatus</i><span> and Channel Catfish </span><i>I. punctatus</i><span> for trophy production has recently become more common. Typically, trophy management is attempted with length-based regulations that allow for the moderate harvest of small fish but restrict the harvest of larger fish. However, the specific regulations used vary considerably across populations, and no modeling efforts have evaluated their effectiveness. We used simulation modeling to compare total yield, trophy biomass (</span><i>B<sub>trophy</sub></i><span>), and sustainability (spawning potential ratio [SPR] &gt; 0.30) of Blue Catfish and Channel Catfish populations under three scenarios: (1) current regulation (typically a length-based trophy regulation), (2) the best-performing minimum length regulation (MLR</span><i><sub>best</sub></i><span>), and (3) the best-performing length-based trophy catfish regulation (LTR</span><i><sub>best</sub></i><span>; “best performing” was defined as the regulation that maximized yield, </span><i>B<sub>trophy</sub></i><span>, and sustainability). The </span><i>B<sub>trophy</sub></i><span> produced did not differ among the three scenarios. For each fishery, the MLR</span><i><sub>best</sub></i><span> and LTR</span><i><sub>best</sub></i><span> produced greater yield (&gt;22% more) than the current regulation and maintained sustainability at higher finite exploitation rates (&gt;0.30) than the current regulation. The MLR</span><i><sub>best</sub></i><span> and LTR</span><i><sub>best</sub></i><span> produced similar yields and SPRs for Channel Catfish and similar yields for Blue Catfish; however, the MLR</span><i><sub>best</sub></i><span> for Blue Catfish produced more resilient fisheries (higher SPR) than the LTR</span><i><sub>best</sub></i><span>. Overall, the variation in yield, </span><i>B<sub>trophy</sub></i><span>, and SPR among populations was greater than the variation among regulations applied to any given population, suggesting that population-specific regulations may be preferable to regulations applied to geographic regions. We conclude that LTRs are useful for improving catfish yield and maintaining sustainability without overly restricting harvest but are not effective at increasing the </span><i>B<sub>trophy</sub></i><span> of catfish.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02755947.2016.1204391","usgsCitation":"Stewart, D., Long, J.M., and Shoup, D.E., 2016, Simulation modeling to explore the effects of length-based harvest regulations for <i>Ictalurus</i> fisheries: North American Journal of Fisheries Management, v. 36, no. 5, p. 1190-1204, https://doi.org/10.1080/02755947.2016.1204391.","productDescription":"15 p.","startPage":"1190","endPage":"1204","ipdsId":"IP-068502","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":330607,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"5","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-13","publicationStatus":"PW","scienceBaseUri":"5819a9c2e4b0bb36a4c91015","contributors":{"authors":[{"text":"Stewart, David R.","contributorId":141323,"corporation":false,"usgs":false,"family":"Stewart","given":"David R.","affiliations":[],"preferred":false,"id":652624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":652588,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shoup, Daniel E.","contributorId":141325,"corporation":false,"usgs":false,"family":"Shoup","given":"Daniel","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":652625,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70185023,"text":"70185023 - 2016 - Circumpolar distribution and carbon storage of thermokarst landscapes","interactions":[],"lastModifiedDate":"2017-03-14T13:44:37","indexId":"70185023","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Circumpolar distribution and carbon storage of thermokarst landscapes","docAbstract":"<p><span>Thermokarst is the process whereby the thawing of ice-rich permafrost ground causes land subsidence, resulting in development of distinctive landforms. Accelerated thermokarst due to climate change will damage infrastructure, but also impact hydrology, ecology and biogeochemistry. Here, we present a circumpolar assessment of the distribution of thermokarst landscapes, defined as landscapes comprised of current thermokarst landforms and areas susceptible to future thermokarst development. At 3.6 × 10</span><sup>6</sup><span> km</span><sup>2</sup><span>, thermokarst landscapes are estimated to cover </span><span class=\"stix\">∼</span><span>20% of the northern permafrost region, with approximately equal contributions from three landscape types where characteristic wetland, lake and hillslope thermokarst landforms occur. We estimate that approximately half of the below-ground organic carbon within the study region is stored in thermokarst landscapes. Our results highlight the importance of explicitly considering thermokarst when assessing impacts of climate change, including future landscape greenhouse gas emissions, and provide a means for assessing such impacts at the circumpolar scale.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/ncomms13043","usgsCitation":"Olefeldt, D., Goswami, S., Grosse, G., Hayes, D., Hugelius, G., Kuhry, P., McGuire, A.D., Romanovsky, V., Sannel, A.B., Schuur, E., and Turetsky, M., 2016, Circumpolar distribution and carbon storage of thermokarst landscapes: Nature Communications, v. 7, p. 1-11, https://doi.org/10.1038/ncomms13043.","productDescription":"Article number 13043; 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-069482","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470527,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/ncomms13043","text":"Publisher Index Page"},{"id":337514,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-11","publicationStatus":"PW","scienceBaseUri":"58c90125e4b0849ce97abcd3","contributors":{"authors":[{"text":"Olefeldt, David","contributorId":169408,"corporation":false,"usgs":false,"family":"Olefeldt","given":"David","affiliations":[{"id":32365,"text":"Department of Renewable Resources, University of Alberta","active":true,"usgs":false}],"preferred":false,"id":684239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goswami, S.","contributorId":189252,"corporation":false,"usgs":false,"family":"Goswami","given":"S.","email":"","affiliations":[],"preferred":false,"id":684240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grosse, G.","contributorId":82140,"corporation":false,"usgs":true,"family":"Grosse","given":"G.","affiliations":[],"preferred":false,"id":684241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayes, D.","contributorId":15275,"corporation":false,"usgs":true,"family":"Hayes","given":"D.","email":"","affiliations":[],"preferred":false,"id":684242,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hugelius, G.","contributorId":27338,"corporation":false,"usgs":true,"family":"Hugelius","given":"G.","affiliations":[],"preferred":false,"id":684243,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kuhry, P.","contributorId":57277,"corporation":false,"usgs":false,"family":"Kuhry","given":"P.","affiliations":[],"preferred":false,"id":684244,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":683987,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Romanovsky, V.E.","contributorId":54721,"corporation":false,"usgs":true,"family":"Romanovsky","given":"V.E.","email":"","affiliations":[],"preferred":false,"id":684245,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sannel, A. B. K.","contributorId":38450,"corporation":false,"usgs":false,"family":"Sannel","given":"A.","email":"","middleInitial":"B. K.","affiliations":[],"preferred":false,"id":684246,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Schuur, E.A.G.","contributorId":106679,"corporation":false,"usgs":true,"family":"Schuur","given":"E.A.G.","affiliations":[],"preferred":false,"id":684247,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Turetsky, M.R.","contributorId":107470,"corporation":false,"usgs":true,"family":"Turetsky","given":"M.R.","email":"","affiliations":[],"preferred":false,"id":684248,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70193668,"text":"70193668 - 2016 - Combining landscape variables and species traits can improve the utility of climate change vulnerability assessments","interactions":[],"lastModifiedDate":"2017-11-13T14:18:21","indexId":"70193668","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Combining landscape variables and species traits can improve the utility of climate change vulnerability assessments","docAbstract":"<p><span>Conservation organizations worldwide are investing in climate change vulnerability assessments. Most vulnerability assessment methods focus on either landscape features or species traits that can affect a species vulnerability to climate change. However, landscape features and species traits likely interact to affect vulnerability. We compare a landscape-based assessment, a trait-based assessment, and an assessment that combines landscape variables and species traits for 113 species of birds, herpetofauna</span><span>, and mammals in the northeastern United States. Our aim is to better understand which species traits and landscape variables have the largest influence on assessment results and which types of vulnerability assessments are most useful for different objectives. Species traits were most important for determining which species will be most vulnerable to climate change. The sensitivity of species to dispersal barriers and the species average natal dispersal distance were the most important traits. Landscape features were most important for determining where species will be most vulnerable because species were most vulnerable in areas where multiple landscape features combined to increase vulnerability, regardless of species traits. The interaction between landscape variables and species traits was important when determining how to reduce climate change vulnerability. For example, an assessment that combines information on landscape connectivity, climate change velocity, and natal dispersal distance suggests that increasing landscape connectivity may not reduce the vulnerability of many species. Assessments that include landscape features and species traits will likely be most useful in guiding conservation under climate change.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2016.07.030","usgsCitation":"Nadeau, C.P., and Fuller, A.K., 2016, Combining landscape variables and species traits can improve the utility of climate change vulnerability assessments: Biological Conservation, v. 202, p. 30-38, https://doi.org/10.1016/j.biocon.2016.07.030.","productDescription":"9 p.","startPage":"30","endPage":"38","ipdsId":"IP-060118","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348712,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.70556640625,\n              37.996162679728116\n            ],\n            [\n              -66.70898437499999,\n              37.996162679728116\n            ],\n            [\n              -66.70898437499999,\n              47.68018294648414\n            ],\n            [\n              -80.70556640625,\n              47.68018294648414\n            ],\n            [\n              -80.70556640625,\n              37.996162679728116\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"202","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fcb7e4b06e28e9c24166","contributors":{"authors":[{"text":"Nadeau, Christopher P.","contributorId":105956,"corporation":false,"usgs":true,"family":"Nadeau","given":"Christopher","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":721844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719842,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70194549,"text":"70194549 - 2016 - Climate change and indigenous peoples: A synthesis of current impacts and experiences","interactions":[],"lastModifiedDate":"2017-12-15T11:06:35","indexId":"70194549","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":32,"text":"General Technical Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"PNW-GTR-944","title":"Climate change and indigenous peoples: A synthesis of current impacts and experiences","docAbstract":"<p>A growing body of literature examines the vulnerability, risk, resilience, and adaptation of indigenous peoples to climate change. This synthesis of literature brings together research pertaining to the impacts of climate change on sovereignty, culture, health, and economies that are currently being experienced by Alaska Native and American Indian tribes and other indigenous communities in the United States. The knowledge and science of how climate change impacts are affecting indigenous peoples contributes to the development of policies, plans, and programs for adapting to climate change and reducing greenhouse gas emissions. This report defines and describes the key frameworks that inform indigenous understandings of climate change impacts and pathways for adaptation and mitigation, namely, tribal sovereignty and self-determination, culture and cultural identity, and indigenous community health indicators. It also provides a comprehensive synthesis of climate knowledge, science, and strategies that indigenous communities are exploring, as well as an understanding of the gaps in research on these issues. This literature synthesis is intended to make a contribution to future efforts such as the 4th National Climate Assessment, while serving as a resource for future research, tribal and agency climate initiatives, and policy development. </p>","language":"English","publisher":"U.S. Department of Agriculture, Forest Service","usgsCitation":"Norton-Smith, K., Lynn, K., Chief, K., Cozetto, K., Donatuto, J., Hiza, M., Kruger, L., Maldonado, J., Viles, C., and Whyte, K., 2016, Climate change and indigenous peoples: A synthesis of current impacts and experiences: General Technical Report PNW-GTR-944, 136 p.","productDescription":"136 p.","ipdsId":"IP-077840","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":350029,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":349669,"type":{"id":15,"text":"Index Page"},"url":"https://www.fs.fed.us/pnw/pubs/pnw_gtr944.pdf"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fcb7e4b06e28e9c2415d","contributors":{"authors":[{"text":"Norton-Smith, Kathryn","contributorId":201144,"corporation":false,"usgs":false,"family":"Norton-Smith","given":"Kathryn","email":"","affiliations":[],"preferred":false,"id":724430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lynn, Kathy","contributorId":201145,"corporation":false,"usgs":false,"family":"Lynn","given":"Kathy","email":"","affiliations":[],"preferred":false,"id":724431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chief, Karletta","contributorId":147055,"corporation":false,"usgs":false,"family":"Chief","given":"Karletta","email":"","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":724432,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cozetto, Karen","contributorId":147057,"corporation":false,"usgs":false,"family":"Cozetto","given":"Karen","email":"","affiliations":[{"id":6709,"text":"University of Colorado, Denver","active":true,"usgs":false}],"preferred":false,"id":724433,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Donatuto, Jamie","contributorId":201146,"corporation":false,"usgs":false,"family":"Donatuto","given":"Jamie","email":"","affiliations":[],"preferred":false,"id":724434,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hiza, Margaret 0000-0003-2851-2502 mhiza@usgs.gov","orcid":"https://orcid.org/0000-0003-2851-2502","contributorId":198449,"corporation":false,"usgs":true,"family":"Hiza","given":"Margaret","email":"mhiza@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":724429,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kruger, Linda","contributorId":168546,"corporation":false,"usgs":false,"family":"Kruger","given":"Linda","email":"","affiliations":[{"id":6679,"text":"US Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":724435,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Maldonado, Julie","contributorId":168542,"corporation":false,"usgs":false,"family":"Maldonado","given":"Julie","email":"","affiliations":[{"id":25327,"text":"Livelihoods Knowledge Network, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":724436,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Viles, Carson","contributorId":201147,"corporation":false,"usgs":false,"family":"Viles","given":"Carson","email":"","affiliations":[],"preferred":false,"id":724437,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Whyte, Kyle P.","contributorId":168548,"corporation":false,"usgs":false,"family":"Whyte","given":"Kyle P.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":724438,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70175670,"text":"ofr20161124 - 2016 - Laboratory evaluation of the Design Analysis Associates DAA H-3613i radar water-level sensor—Results of  temperature, distance, and SDI-12 tests","interactions":[],"lastModifiedDate":"2016-10-03T11:42:46","indexId":"ofr20161124","displayToPublicDate":"2016-09-30T16:30:00","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":"2016-1124","title":"Laboratory evaluation of the Design Analysis Associates DAA H-3613i radar water-level sensor—Results of  temperature, distance, and SDI-12 tests","docAbstract":"<p>The Design Analysis Associates (DAA) DAA H-3613i radar water-level sensor (DAA H-3613i), manufactured by Xylem Incorporated, was evaluated by the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF) for conformance to manufacturer’s accuracy specifications for measuring a distance throughout the sensor’s operating temperature range, for measuring distances from 3 to 15 feet at ambient temperatures, and for compliance with the SDI-12 serial-to-digital interface at 1200-baud communication standard. The DAA H-3613i is a noncontact water-level sensor that uses pulsed radar to measure the distance between the radar and the water surface from 0.75 to 131 feet over a temperature range of −40 to 60 degrees Celsius (°C). Manufacturer accuracy specifications that were evaluated, the test procedures that followed, and the results obtained are described in this report. The sensor’s accuracy specification of ± 0.01 feet (± 3 millimeters) meets USGS requirements for a primary water-stage sensor used in the operation of a streamgage. The sensor met the manufacturer’s stated accuracy specifications for water-level measurements during temperature testing at a distance of 8 feet from the target over its temperature-compensated operating range of −40 to 60 °C, except at 60 °C. At 60 °C, about half the measurements exceeded the manufacturer’s accuracy specification by not more than 0.005 feet.The sensor met the manufacturer’s stated accuracy specifications for water-level measurements during distance-accuracy testing at the tested distances from 3 to 15 feet above the water surface at the HIF.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161124","usgsCitation":"Carnley, M.V., 2016, Laboratory evaluation of the Design Analysis Associates DAA H-3613i radar water-level sensor—Results of temperature, distance, and SDI-12 tests: U.S. Geological Survey Open-File Report 2016–1124, 7 p., https://dx.doi.org/10.3133/ofr20161124. ","productDescription":"iii, 7 p.","numberOfPages":"16","onlineOnly":"Y","ipdsId":"IP-071442","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":329212,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1124/coverthb.jpg"},{"id":329213,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1124/ofr20161124.pdf","text":"Report","size":"2.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1124"}],"contact":"<p>Hydrologic Instrumentation Facility<br> U.S. Geological Survey<br> Building 2101<br> Stennis Space Center, MS 39529<br> <a href=\"http://water.usgs.gov/hif/\" data-mce-href=\"http://water.usgs.gov/hif/\">http://water.usgs.gov/hif/</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Description of the Design Analysis Associates DAA H-3613i Radar Water-Level Sensor</li><li>Methods</li><li>Results</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-09-30","noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"57f7c63be4b0bc0bec09c836","contributors":{"authors":[{"text":"Carnley, Mark V. mcarnley@usgs.gov","contributorId":2723,"corporation":false,"usgs":true,"family":"Carnley","given":"Mark","email":"mcarnley@usgs.gov","middleInitial":"V.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":645990,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70176610,"text":"ofr20161170 - 2016 - Preliminary geologic mapping of Cretaceous and Tertiary formations in the eastern part of the Little Snake River coal field, Carbon County, Wyoming","interactions":[],"lastModifiedDate":"2016-09-30T14:14:25","indexId":"ofr20161170","displayToPublicDate":"2016-09-30T13:00:00","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":"2016-1170","title":"Preliminary geologic mapping of Cretaceous and Tertiary formations in the eastern part of the Little Snake River coal field, Carbon County, Wyoming","docAbstract":"<p>In the 1970s and 1980s, C.S. Venable Barclay conducted geologic mapping of areas primarily underlain by Cretaceous coals in the eastern part of the Little Snake River coal field (LSR) in Carbon County, southwest Wyoming. With some exceptions, most of the mapping data were never published. Subsequently, after his retirement from the U.S. Geological Survey (USGS), his field maps and field notebooks were archived in the USGS Field Records. Due to a pending USGS coal assessment of the Little Snake River coal field area and planned geological mapping to be conducted by the Wyoming State Geological Survey, Barclay’s mapping data needed to be published to support these efforts. Subsequently, geologic maps were scanned and georeferenced into a geographic information system, and project and field notes were scanned into Portable Document Format (PDF) files. Data for seventeen 7½-minute quadrangles are presented in this report. This publication is solely intended to compile the mapping data as it was last worked on by Barclay and provides no interpretation or modification of his work.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161170","usgsCitation":"Haacke, J.E., Barclay, C.S.V., and Hettinger, R.D., 2016, Preliminary geologic mapping of Cretaceous and Tertiary formations in the eastern part of the Little Snake River coal field, Carbon County, Wyoming: U.S. Geological Survey Open-File Report 2016–1170, 9 p., https://dx.doi.org/10.3133/ofr20161170.","productDescription":"Report: iii, 9 p.; Field Notes; Metadata; Read Me; Spatial Data","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-070800","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":329139,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2016/1170/ofr20161170_Field Notes.zip","text":"Field Notes","size":"444 MB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1170 Field Notes"},{"id":329143,"rank":6,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/of/2016/1170/ofr20161170_Readme.txt","text":"Read Me","size":"8.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2016-1170 Read Me"},{"id":329138,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1170/ofr20161170.pdf","text":"Report","size":"7.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1170"},{"id":329137,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1170/coverthb.jpg"},{"id":329142,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2016/1170/ofr20161170_Metadata.zip","text":"Metadata","size":"32.0 kB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1170 Metadata"},{"id":329141,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2016/1170/ofr20161170_GIS.zip","text":"Spatial Data","size":"2.45 GB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1170 Spatial Data"}],"country":"United States","state":"Wyoming","county":"Carbon County","otherGeospatial":"Little Snake River Coal Field","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-106.0749,42.4325],[-106.0747,42.4179],[-106.0745,42.4038],[-106.0747,42.3748],[-106.0756,42.3189],[-106.076,42.3039],[-106.0752,42.2893],[-106.0756,42.2748],[-106.0753,42.2612],[-106.0734,42.1735],[-106.0738,42.1135],[-106.0744,41.9581],[-106.0748,41.9436],[-106.0746,41.9291],[-106.075,41.915],[-106.0741,41.9005],[-106.0739,41.8859],[-106.0743,41.8714],[-106.0747,41.8569],[-106.0745,41.8423],[-106.0743,41.8278],[-106.0735,41.8119],[-106.0745,41.7974],[-106.0747,41.7683],[-106.0745,41.7538],[-106.0728,41.6593],[-106.072,41.6407],[-106.0718,41.6257],[-106.071,41.5676],[-106.0708,41.3951],[-106.0977,41.3955],[-106.1155,41.3953],[-106.3243,41.3936],[-106.3251,41.2851],[-106.3241,41.2252],[-106.3237,41.2162],[-106.3233,41.1785],[-106.3227,41.1036],[-106.3227,41.075],[-106.3223,41.0446],[-106.3215,41.001],[-106.3257,41.0023],[-106.3263,41.0025],[-106.3318,41.0025],[-106.3519,41.0025],[-106.3793,41.0026],[-106.4481,41.0035],[-106.456,41.0035],[-106.4864,41.0033],[-106.5436,41.0038],[-106.5723,41.0038],[-106.582,41.0037],[-106.5911,41.0035],[-106.8639,41.0041],[-107.0021,41.0044],[-107.0259,41.0043],[-107.1355,41.0037],[-107.2299,41.0035],[-107.306,41.0034],[-107.3181,41.0035],[-107.3437,41.0033],[-107.3674,41.0032],[-107.3948,41.003],[-107.4137,41.0029],[-107.4575,41.0027],[-107.4947,41.0026],[-107.5093,41.0026],[-107.5136,41.0026],[-107.5288,41.0026],[-107.6049,41.0028],[-107.6767,41.0028],[-107.7078,41.0028],[-107.7845,41.0028],[-107.8131,41.0028],[-107.8206,41.0028],[-107.8326,41.0028],[-107.8391,41.0028],[-107.8521,41.0029],[-107.8801,41.0029],[-107.888,41.0029],[-107.9154,41.0029],[-107.9176,41.2244],[-107.9168,41.3996],[-107.9308,41.3996],[-107.9308,41.4123],[-107.9314,41.4272],[-107.9314,41.4418],[-107.932,41.4567],[-107.9326,41.4713],[-107.9326,41.4862],[-107.9326,41.5017],[-107.9326,41.5162],[-107.9319,41.5312],[-107.9319,41.5457],[-107.9319,41.5607],[-107.9319,41.572],[-107.9319,41.587],[-107.9319,41.6015],[-107.9318,41.6161],[-107.9318,41.631],[-107.9318,41.6456],[-107.9318,41.6592],[-107.9128,41.6592],[-107.8931,41.6592],[-107.874,41.6591],[-107.8544,41.6591],[-107.8353,41.6591],[-107.8169,41.6591],[-107.7991,41.659],[-107.78,41.659],[-107.7604,41.659],[-107.7407,41.659],[-107.721,41.6589],[-107.702,41.6589],[-107.6799,41.6588],[-107.6608,41.6588],[-107.6418,41.6582],[-107.6221,41.6582],[-107.6037,41.6581],[-107.5858,41.6581],[-107.5668,41.658],[-107.5477,41.6575],[-107.5287,41.6574],[-107.509,41.6574],[-107.5004,41.6573],[-107.501,41.6691],[-107.5008,41.6837],[-107.5007,41.6986],[-107.5013,41.7132],[-107.5012,41.7277],[-107.5011,41.74],[-107.501,41.7549],[-107.5009,41.7695],[-107.5007,41.7849],[-107.5,41.7994],[-107.4999,41.814],[-107.4998,41.8285],[-107.4997,41.8435],[-107.4996,41.858],[-107.4995,41.873],[-107.4994,41.8871],[-107.4999,41.9021],[-107.4998,41.9148],[-107.4997,41.9275],[-107.5002,41.942],[-107.5001,41.957],[-107.5,41.9715],[-107.5005,41.9861],[-107.5005,41.9992],[-107.5003,42.0147],[-107.5002,42.0288],[-107.5001,42.0437],[-107.5,42.0583],[-107.4999,42.0737],[-107.4998,42.0878],[-107.5221,42.0883],[-107.5196,42.1742],[-107.5195,42.1887],[-107.521,42.2459],[-107.5209,42.2596],[-107.5208,42.2741],[-107.5209,42.3473],[-107.5208,42.3618],[-107.5206,42.3904],[-107.5211,42.4054],[-107.5209,42.4336],[-107.4426,42.4342],[-107.4234,42.4341],[-107.4041,42.4345],[-107.3873,42.4344],[-107.3457,42.4346],[-107.3084,42.4349],[-107.2885,42.4343],[-107.1916,42.4347],[-107.173,42.4346],[-107.0934,42.4345],[-107.0742,42.4343],[-106.9704,42.4331],[-106.9574,42.433],[-106.9455,42.4334],[-106.9412,42.4333],[-106.9387,42.4333],[-106.8747,42.4323],[-106.8642,42.4322],[-106.8492,42.4321],[-106.8362,42.4324],[-106.8219,42.4328],[-106.7958,42.4325],[-106.7834,42.4324],[-106.738,42.4324],[-106.7169,42.4322],[-106.7076,42.4317],[-106.6864,42.4315],[-106.6187,42.4312],[-106.6088,42.4311],[-106.6007,42.4315],[-106.592,42.4314],[-106.5336,42.4312],[-106.5137,42.431],[-106.4814,42.4306],[-106.474,42.4305],[-106.4435,42.4306],[-106.4323,42.4305],[-106.3658,42.431],[-106.3546,42.4309],[-106.3434,42.4312],[-106.3235,42.4314],[-106.2651,42.4315],[-106.2471,42.4317],[-106.239,42.4321],[-106.1464,42.4326],[-106.1265,42.4328],[-106.1228,42.4323],[-106.1054,42.4325],[-106.0749,42.4325]]]},\"properties\":{\"name\":\"Carbon\",\"state\":\"WY\"}}]}","contact":"<p>Center Director, USGS Central Energy Resources Science Center<br>Box 25046, Mail Stop 939<br>Denver, CO 80225</p><p><a href=\"http://energy.usgs.gov/\" data-mce-href=\"http://energy.usgs.gov/\">http://energy.usgs.gov/</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Overview of Barclay Studies</li><li>The Little Snake River Coal Field Map Data</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2016-09-30","noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"57f7c63be4b0bc0bec09c838","contributors":{"authors":[{"text":"Haacke, Jon E.","contributorId":86054,"corporation":false,"usgs":true,"family":"Haacke","given":"Jon E.","affiliations":[],"preferred":false,"id":649803,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barclay, C. S. Venable","contributorId":174821,"corporation":false,"usgs":false,"family":"Barclay","given":"C.","email":"","middleInitial":"S. Venable","affiliations":[{"id":27516,"text":"USGS Retired, deceased","active":true,"usgs":false}],"preferred":false,"id":649804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hettinger, Robert D.","contributorId":102486,"corporation":false,"usgs":true,"family":"Hettinger","given":"Robert","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":649805,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70176082,"text":"fs20163065 - 2016 - Assessing potential scour using the South Carolina bridge-scour envelope curves","interactions":[],"lastModifiedDate":"2016-10-11T09:48:07","indexId":"fs20163065","displayToPublicDate":"2016-09-30T10:30:00","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":"2016-3065","title":"Assessing potential scour using the South Carolina bridge-scour envelope curves","docAbstract":"<h1>Summary</h1><p>Bridge-scour equations presented in the Federal Highway Administration Hydraulic Engineering Circular No. 18 reflect the current state-of-the practice for predicting scour at bridges. Although these laboratory-derived equations provide an important resource for assessing scour potential, there is a measure of uncertainty when applying these equations to field conditions. The uncertainty and limitations have been acknowledged by laboratory researchers and confirmed in field investigations.</p><p>Because of the uncertainty associated with bridge-scour equations, HEC-18 recommends that engineers evaluate the computed scour depths obtained from the equations and modify the resulting data if they appear unreasonable. Perhaps the best way to evaluate the reasonableness of predicted scour is to compare it to field measurements of historic scour. Historic field data show scour depths resulting from high flows and provide a reference for evaluating predicted scour. It is rare, however, that such data are available at or near a site of interest, making the evaluation of predicted scour as compared to field data difficult if not impossible. Realizing the value of historic scour measurements, the U.S. Geological Survey (USGS), in cooperation with the South Carolina Department of Transportation (SCDOT), conducted a series of three field investigations to collect historic scour data with the goal of understanding regional trends of scour at riverine bridges in South Carolina.</p><p>Historic scour measurements, including measurements of clear-water abutment, contraction, and pier scour, as well as live-bed contraction and pier scour, were made at more than 200 bridges. These field investigations provided valuable insights into regional scour trends and yielded regional bridge-scour envelope curves that can be used as supplementary tools for assessing all components of scour at riverine bridges in South Carolina.</p><p>The application and limitations of these envelope curves were documented in four reports. Because each report addresses different components of bridge scour, it was recognized that there was a need to develop an integrated procedure for applying the envelope curves to help assess scour potential at riverine bridges in South Carolina. The result of that effort is detailed in Benedict and others (2016) and summarized in this fact sheet.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163065","collaboration":"Prepared in cooperation with the South Carolina Department of Transportation","usgsCitation":"Benedict, S.T., Feaster, T.D., and Caldwell, A.W., 2016, Assessing potential scour using the South Carolina bridge-scour envelope curves: U.S. Geological Survey Fact Sheet 2016-3065, 2 p., https://dx.doi.org/10.3133/fs20163065.","productDescription":"2 p. ","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076488","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":329018,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3065/coverthb.jpg"},{"id":329019,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3065/fs20163065.pdf","text":"Report","size":"1.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3065"},{"id":329022,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20165121","text":"Scientific Investigations Report 2016–5121","linkHelpText":"- The South Carolina Bridge-Scour Envelope Curves"}],"country":"United States","state":"South Carolina 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Carolina\",\"nation\":\"USA  \"}}]}","contact":"<p><a href=\"mailto:dc_sc@usgs.gov\" data-mce-href=\"mailto:dc_sc@usgs.gov\">Director</a>, South Atlantic Water Science Center<br> U.S. Geological Survey<br> 720 Gracern Road, Suite 129<br> Columbia, SC 29210<br> <a href=\"http://sc.water.usgs.gov/\" data-mce-href=\"http://sc.water.usgs.gov/\">http://sc.water.usgs.gov/</a></p>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-09-30","noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"57f7c63be4b0bc0bec09c83c","contributors":{"authors":[{"text":"Benedict, Stephen T. benedict@usgs.gov","contributorId":3198,"corporation":false,"usgs":true,"family":"Benedict","given":"Stephen T.","email":"benedict@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":649728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Feaster, Toby D. 0000-0002-5626-5011 tfeaster@usgs.gov","orcid":"https://orcid.org/0000-0002-5626-5011","contributorId":174044,"corporation":false,"usgs":true,"family":"Feaster","given":"Toby D.","email":"tfeaster@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":647036,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell, Andral W. 0000-0003-1269-5463 acaldwel@usgs.gov","orcid":"https://orcid.org/0000-0003-1269-5463","contributorId":138690,"corporation":false,"usgs":true,"family":"Caldwell","given":"Andral W.","email":"acaldwel@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":647037,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70176670,"text":"ofr20161172 - 2016 - Feasibility study of earthquake early warning (EEW) in Hawaii","interactions":[],"lastModifiedDate":"2016-10-03T11:40:00","indexId":"ofr20161172","displayToPublicDate":"2016-09-30T00:00:00","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":"2016-1172","title":"Feasibility study of earthquake early warning (EEW) in Hawaii","docAbstract":"<p>The effects of earthquake shaking on the population and infrastructure across the State of Hawaii could be catastrophic, and the high seismic hazard in the region emphasizes the likelihood of such an event. Earthquake early warning (EEW) has the potential to give several seconds of warning before strong shaking starts, and thus reduce loss of life and damage to property. The two approaches to EEW are (1) a network approach (such as ShakeAlert or ElarmS) where the regional seismic network is used to detect the earthquake and distribute the alarm and (2) a local approach where a critical facility has a single seismometer (or small array) and a warning system on the premises.</p><p>The network approach, also referred to here as ShakeAlert or ElarmS, uses the closest stations within a regional seismic network to detect and characterize an earthquake. Most parameters used for a network approach require observations on multiple stations (typically 3 or 4), which slows down the alarm time slightly, but the alarms are generally more reliable than with single-station EEW approaches. The network approach also benefits from having stations closer to the source of any potentially damaging earthquake, so that alarms can be sent ahead to anyone who subscribes to receive the notification. Thus, a fully implemented ShakeAlert system can provide seconds of warning for both critical facilities and general populations ahead of damaging earthquake shaking.</p><p>The cost to implement and maintain a fully operational ShakeAlert system is high compared to a local approach or single-station solution, but the benefits of a ShakeAlert system would be felt statewide—the warning times for strong shaking are potentially longer for most sources at most locations.</p><p>The local approach, referred to herein as “single station,” uses measurements from a single seismometer to assess whether strong earthquake shaking can be expected. Because of the reliance on a single station, false alarms are more common than when using a regional network of seismometers. Given the current network, a single-station approach provides more warning for damaging earthquakes that occur close to the station, but it would have limited benefit compared to a fully implemented ShakeAlert system. For Honolulu, for example, the single-station approach provides an advantage over ShakeAlert only for earthquakes that occur in a narrow zone extending northeast and southwest of O‘ahu. Instrumentation and alarms associated with the single-station approach are typically maintained&nbsp;and assessed within the target facility, and thus no outside connectivity is required. A single-station approach, then, is unlikely to help broader populations beyond the individuals at the target facility, but they have the benefit of being commercially available for relatively little cost. </p><p>The USGS Hawaiian Volcano Observatory (HVO) is the Advanced National Seismic System (ANSS) regional seismic network responsible for locating and characterizing earthquakes across the State of Hawaii. During 2014 and 2015, HVO tested a network-based EEW algorithm within the current seismic network in order to assess the suitability for building a full EEW system. Using the current seismic instrumentation and processing setup at HVO, it is possible for a network approach to release an alarm a little more than 3 seconds after the earthquake is recorded on the fourth seismometer. Presently, earthquakes having M≥3 detected with the ElarmS algorithm have an average location error of approximately 4.5 km and an average magnitude error of -0.3 compared to the reviewed catalog locations from the HVO. Additional stations and upgrades to existing seismic stations would serve to improve solution precision and warning times and additional staffing would be required to provide support for a robust, network-based EEW system. </p><p>For a critical facility on the Island of Hawaiʻi, such as the telescopes atop Mauna Kea, one phased approach to mitigate losses could be to immediately install a single station system to establish some level of warning. Subsequently, supporting the implementation of a full network-based EEW system on the Island of Hawaiʻi would provide additional benefit in the form of improved warning times once the system is fully installed and operational, which may take several years. </p><p>Distributed populations across the Hawaiian Islands, including those outside the major cities and far from the likely earthquake source areas, would likely only benefit from a network approach such as ShakeAlert to provide warnings of strong shaking. </p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161172","usgsCitation":"Thelen, W.A., Hotovec-Ellis, A.J., Bodin, P., 2016, Feasibility study of earthquake early warning (EEW) in Hawaii: U.S. Geological Survey Open-File Report 2016–1172, 33 p., https://dx.doi.org/10.3133/ofr20161172.","productDescription":"iii, 30 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 \"}}]}","contact":"<p><a href=\"http://hvo.wr.usgs.gov/observatory/contactHVO.html\" target=\"blank\" data-mce-href=\"http://hvo.wr.usgs.gov/observatory/contactHVO.html\">Contact HVO</a><br>Volcano Science Center, Hawaiian Volcano Observatory<br>U.S. Geological Survey<br>P.O. Box 51, 1 Crater Rim Road<br>Hawaiʻi Volcanoes National Park, HI 96718-0051<br> <a href=\"http://hvo.wr.usgs.gov/\" target=\"blank\" data-mce-href=\"http://hvo.wr.usgs.gov/\">http://hvo.wr.usgs.gov/</a></p>","tableOfContents":"<ul><li>Executive Summary<br></li><li>Introduction<br></li><li>Current State of the Seismic Network<br></li><li>Theoretical Performance of ElarmS and a Single Station Within the Current Network<br></li><li>Steps Toward Full EEW Implementation<br></li><li>ElarmS Compared to a Single-Station Approach<br></li><li>Summary<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2016-09-30","noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"57f7c63be4b0bc0bec09c840","contributors":{"authors":[{"text":"Thelen, Weston A. 0000-0003-2534-5577 wthelen@usgs.gov","orcid":"https://orcid.org/0000-0003-2534-5577","contributorId":4126,"corporation":false,"usgs":true,"family":"Thelen","given":"Weston","email":"wthelen@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":649851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hotovec-Ellis, Alicia J.","contributorId":81023,"corporation":false,"usgs":true,"family":"Hotovec-Ellis","given":"Alicia","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":649852,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bodin, Paul","contributorId":104142,"corporation":false,"usgs":true,"family":"Bodin","given":"Paul","affiliations":[],"preferred":false,"id":649853,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70175349,"text":"ofr20161127 - 2016 - Geologic structure of the Yucaipa area inferred from gravity data, San Bernardino and Riverside Counties, California","interactions":[],"lastModifiedDate":"2016-10-03T11:36:18","indexId":"ofr20161127","displayToPublicDate":"2016-09-30T00:00:00","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":"2016-1127","title":"Geologic structure of the Yucaipa area inferred from gravity data, San Bernardino and Riverside Counties, California","docAbstract":"<p class=\"p1\">In the spring of 2009, the U.S. Geological Survey, in cooperation with the San Bernardino Valley Municipal Water District, began working on a gravity survey in the Yucaipa area to explore the three-dimensional shape of the sedimentary fill (alluvial deposits) and the surface of the underlying crystalline basement rocks. As water use has increased in pace with rapid urbanization, water managers have need for better information about the subsurface geometry and the boundaries of groundwater subbasins in the Yucaipa area. The large density contrast between alluvial deposits and the crystalline basement complex permits using modeling of gravity data to estimate the thickness of alluvial deposits. The bottom of the alluvial deposits is considered to be the top of crystalline basement rocks. The gravity data, integrated with geologic information from surface outcrops and 51 subsurface borings (15 of which penetrated basement rock), indicated a complex basin configuration where steep slopes coincide with mapped faults―such as the Crafton Hills Fault and the eastern section of the Banning Fault―and concealed ridges separate hydrologically defined subbasins.</p><p class=\"p2\">Gravity measurements and well logs were the primary data sets used to define the thickness and structure of the groundwater basin. Gravity measurements were collected at 256 new locations along profiles that totaled approximately 104.6 km (65 mi) in length; these data supplemented previously collected gravity measurements. Gravity data were reduced to isostatic anomalies and separated into an anomaly field representing the valley fill. The ‘valley-fill-deposits gravity anomaly’ was converted to thickness by using an assumed, depth-varying density contrast between the alluvial deposits and the underlying bedrock.</p><p class=\"p3\">To help visualize the basin geometry, an animation of the elevation of the top of the basement-rocks was prepared. The animation “flies over” the Yucaipa groundwater basin, viewing the land surface, geology, faults, and ridges and valleys of the shaded-relief elevation of the top of the basement complex.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161127","collaboration":"Prepared in cooperation with the San Bernardino Valley Municipal Water District","usgsCitation":"Mendez, G.O., Langenheim, V.E., Morita, Andrew, and Danskin, W.R., 2016, Geologic structure of the Yucaipa area inferred from gravity data, San Bernardino and Riverside Counties, California: U.S. Geological Survey Open-File Report 2016–1127, 22 p., https://dx.doi.org/10.3133/ofr20161127.","productDescription":"Report: vii, 23 p.; Video Animation","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077241","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":329070,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1127/ofr20161127.pdf","text":"Report","size":"34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1127"},{"id":329071,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2016/1127/ofr20161127_gravity.mp4","text":"Video animation","size":"47.3 MB mp4","description":"OFR 2016-1127 Video Animation","linkHelpText":"Land surface, geology, faults, wells, and elevation of the basement rocks in the Yucaipa area, California."},{"id":329069,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1127/coverthb.jpg"}],"country":"United States","state":"California","county":"San Bernardino County, Riverside County","otherGeospatial":"Yucaipa Area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.15888977050781,\n              33.96842016198477\n            ],\n            [\n              -117.15888977050781,\n              34.08962997133382\n            ],\n            [\n              -116.97212219238281,\n              34.08962997133382\n            ],\n            [\n              -116.97212219238281,\n              33.96842016198477\n            ],\n            [\n              -117.15888977050781,\n              33.96842016198477\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>, California Water Science Center<br> U.S. Geological Survey<br> 6000 J Street, Placer Hall<br> Sacramento, CA 95819<br> <a href=\"http://ca.water.usgs.gov\" target=\"blank\" data-mce-href=\"http://ca.water.usgs.gov\">http://ca.water.usgs.gov</a></p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Purpose and Scope<br></li><li>Geology<br></li><li>Geologic Units<br></li><li>Data Sets<br></li><li>Depth-to-Basement Profiles<br></li><li>Limitations<br></li><li>Results<br></li><li>Animation of Alluvial Thickness Model<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2016-09-30","noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"57f7c63be4b0bc0bec09c842","contributors":{"authors":[{"text":"Mendez, Gregory O. 0000-0002-9955-3726 gomendez@usgs.gov","orcid":"https://orcid.org/0000-0002-9955-3726","contributorId":1489,"corporation":false,"usgs":true,"family":"Mendez","given":"Gregory","email":"gomendez@usgs.gov","middleInitial":"O.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":644830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Langenheim, Victoria E. 0000-0003-2170-5213 zulanger@usgs.gov","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":1526,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria E.","email":"zulanger@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":644831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morita, Andrew 0000-0002-8120-996X","orcid":"https://orcid.org/0000-0002-8120-996X","contributorId":52292,"corporation":false,"usgs":true,"family":"Morita","given":"Andrew","affiliations":[],"preferred":false,"id":644832,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Danskin, Wesley R. 0000-0001-8672-5501 wdanskin@usgs.gov","orcid":"https://orcid.org/0000-0001-8672-5501","contributorId":1034,"corporation":false,"usgs":true,"family":"Danskin","given":"Wesley","email":"wdanskin@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":644833,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70176696,"text":"ofr20161175 - 2016 - Benthic processes affecting contaminant transport in Upper Klamath Lake, Oregon","interactions":[],"lastModifiedDate":"2016-10-12T09:45:28","indexId":"ofr20161175","displayToPublicDate":"2016-09-30T00:00:00","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":"2016-1175","title":"Benthic processes affecting contaminant transport in Upper Klamath Lake, Oregon","docAbstract":"<h1>Executive Summary</h1><p>Multiple sampling trips during calendar years 2013 through 2015 were coordinated to provide measurements of interdependent benthic processes that potentially affect contaminant transport in Upper Klamath Lake (UKL), Oregon. The measurements were motivated by recognition that such internal processes (for example, solute benthic flux, bioturbation and solute efflux by benthic invertebrates, and physical groundwater-surface water interactions) were not integrated into existing management models for UKL. Up until 2013, all of the benthic-flux studies generally had been limited spatially to a number of sites in the northern part of UKL and limited temporally to 2–3 samplings per year. All of the benthic invertebrate studies also had been limited to the northern part of the lake; however, intensive temporal (weekly) studies had previously been completed independent of benthic-flux studies. Therefore, knowledge of both the spatial and temporal variability in benthic flux and benthic invertebrate distributions for the entire lake was lacking. To address these limitations, we completed a lakewide spatial study during 2013 and a coordinated temporal study with weekly sampling of benthic flux and benthic invertebrates during 2014. Field design of the spatially focused study in 2013 involved 21 sites sampled three times as the summer cyanobacterial bloom developed (that is, <span class=\"aBn\" data-term=\"goog_1023710937\"><span class=\"aQJ\">May 23</span></span>, <span class=\"aBn\" data-term=\"goog_1023710938\"><span class=\"aQJ\">June 13</span></span>, and July 3, 2013). Results of the 27-week, temporally focused study of one site in 2014 were summarized and partitioned into three periods (referred to herein as pre-bloom, bloom and post-bloom periods), each period involving 9 weeks of profiler deployments, water column and benthic sampling. Partitioning of the pre-bloom, bloom, and post-bloom periods were based on water-column chlorophyll concentrations and involved the following date intervals, respectively: <span class=\"aBn\" data-term=\"goog_1023710939\"><span class=\"aQJ\">April 15 through June 10</span></span>, <span class=\"aBn\" data-term=\"goog_1023710940\"><span class=\"aQJ\">June 17 through August 13</span></span>, and August 20 through October 16, 2014.&nbsp;</p><p>To examine dissolved-solute (0.2-micrometer [μm] filtered) benthic flux, sets of nonmetallic pore-water profilers (U.S. Patent 8,051,727 B1) were deployed. In 2013, the deployment of profilers at 21 UKL sites occurred at the beginning of the annual cyanobacterial bloom of <i>Aphanizomenon flos–aquae </i>(AFA), in the middle of the bloom period, and at the peak of the bloom. Coordinated benthic invertebrate collections also were made. Based on results from 2013, weekly deployments of profilers and collection of benthic invertebrate samples from late spring to early autumn were used to estimate temporal trends in solute flux and benthic invertebrate densities. Estimates of nutrient efflux by benthic invertebrates were determined in the spring and autumn from 2011 through 2013 and three times (spring, summer, and autumn) in 2015. This work extends UKL studies that began in 2006 to quantify the importance of benthic solute sources in the lake. In 2015, piezometers and thermistor sets were deployed to quantify potential groundwater exchange with the lake water column.&nbsp;</p><p>Analysis of the 2013 soluble reactive phosphorus (SRP) benthic flux indicated no effect of location (lake region), habitat, or sampling period, and the average lakewide flux values were consistent with earlier studies that had been confined to the northern region of UKL and adjacent wetlands. The 2014 study therefore focused on estimating temporal trends at a site within Ball Bay. During both 2013 and 2014 field studies, fluxes of macronutrients (soluble reactive phosphorus (SRP) and ammonia) and micronutrients (iron [Fe] and manganese [Mn]) were consistently positive and increased prior to the initial AFA bloom, varied or lagged with water-column chlorophyll during the summer bloom period, then decreased after the cyanobacterial blooms, only to rebound toward pre-bloom conditions in the final weeks of sampling. These four solutes exhibited benthic loads greater than maximum riverine loads estimated during the spring and early summers of 2013 and 2014. However, consistently detectable concentrations for all four solutes provide no evidence that they consistently serve as the limiting nutrient for primary production in the lake. In contrast to the four solutes (SRP, ammonia, Fe, and Mn), benthic fluxes of dissolved arsenic (As) were both negative and positive (that is, the lakebed currently serves as both a source and a sink for dissolved As, depending on season). In a further contrast with SRP, ammonia, dissolved Fe, and Mn, dissolved-As riverine loads to UKL were of similar magnitude to benthic loads. A negative relationship between dissolved-As flux and water-column As over the 2014 temporal study provides a potential advantage for the management of water-quality in contrast to solutes, like SRP or ammonia, with consistently positive flux.&nbsp;</p><p>The mean total benthic invertebrate density during 2013 was 12,610 individuals per square meter (n=63). Although benthic invertebrate density did not change over the study period, it was higher in littoral habitats than open-lake or trench habitats and higher in the northern region compared to the central or southern regions of UKL. Mean total benthic invertebrate density during 2014 was 19,726 individuals m<span>−2 </span>(n=27). Density during the pre-bloom and bloom periods of April 15 to August 13, 2014 (the first two thirds of the 2014 sampling period), were similar to 2013. However, benthic invertebrate density more than doubled during the latter one-third of the study, that is, the post-bloom period between August 20 to October 16, 2014. Oligochaeta, Chironomidae and Hirudinea represented well over 90 percent of the benthic fauna; Oligochaeta were twice as abundant as Chironomidae or Hirudinea, the latter two of which were similar in density.&nbsp;</p><p>Benthic invertebrates may enhance dissolved-nutrient (or toxicant) transport across the sediment-water interface by (1) modifying diffusion-layer thicknesses and permeability through bioturbation, (2) enhancing advective flow across the interface through bioirrigation, and (3) excreting or expelling dissolved or particulate solutes directly into the overlying water column (Boudreau and Jorgensen, 2001). We evaluated SRP efflux via excretion for approximately 15 different major taxa in UKL. Once these measures were scaled, it was evident that benthic invertebrates potentially contribute approximately 1.5 times the amount of SRP to the water column of Upper Klamath Lake as diffusive SRP flux alone, measured in profiler deployments.&nbsp;</p><p>Sets of piezometers and temperature loggers were deployed in UKL to obtain estimates of vertical advective solute flux. The pressure transducer installations, within the piezometers, did not perform as designed, rendering the head gradient data unreliable. However, in terms of future research, this field work did demonstrate the feasibility of collecting vertical gradient data with piezometer deployments. Advective flux estimates herein are based solely on heat-flow modeling based on temperature data from four lake sites, without use of transducer data. Given the magnitudes (both positive or negative) of the heat-transfer fluxes for SRP, relative to diffusive-flux and macroinvertebrate efflux measurements (all positive but spanning the same orders of magnitude), further examination of solute advective flux is recommended as a potential transport process to integrate into existing water-quality (for example, Total Maximum Daily Load [TMDL]) models.&nbsp;</p><p>As a complement to the biogeochemical focus of this study, initial analyses of suspended-particle (floc) characteristics and settling velocities from the water column were derived near the surface and lakebed at two UKL sites. To better understand changing particle characteristics during the AFA-bloom period, suspended particles were examined in 2015 using a LabSFLOC (LF), which is a Laboratory Spectral Flocculation Characteristics version of an In-Situ Settling Velocity instrument (INSSEV-LF). Particle characteristics and settling velocities were analyzed from the water column near the surface (sample <i>dp_10</i>) and lakebed (sample <i>dp_90</i>) at two lake sites (open-lake site ML and littoral site LS01). The term “floc” refers herein to suspended particles that may aggregate or disaggregate to change in size, composition, and settling velocity.&nbsp;</p><p>During pre-bloom (May) conditions, where maximum suspended particulate matter concentration (SPMC) was 140 milligrams per liter (mg&nbsp;<span class=\"nowrap\">L<sup>−1</sup></span>) was now observed at site LS01 in close proximity to the bed, where D<span><sub>mean</sub> </span>peaked at 305 μm, and the corresponding Ws<span><sub>mean</sub> </span>was 3.9 millimeters per second (mm s<sup>−1</sup>). The high near-bed SPMC (828 mg L<sup>−1</sup>) experienced during post-bloom October 2015 at LS01 formed a benthic nepheloid layer (BNL) above the lake’s bed. Numerous low density, fast settling macrofloc-sized organic aggregates (D &gt;160 μm) were observed (some up to 1 mm in size) near bed at LS01 both during the bloom and post-bloom conditions; many of these flocs displayed fibrous organic structures. In terms of mass settling fluxes, the post-bloom BNL produced a total MSF of 4,139 milligrams per square meter per second (mg m<span><sup>−2</sup> </span>s<sup>−1</sup>) (92.1 percent of MSF credited to the macrofloc-sized organic aggregates/cyanobacterial colonies); that was nearly three times the corresponding near-bed settling flux observed during the July 2015 bloom and 360 times greater than the pre-bloom conditions from May 2015 (98.8 percent and 14 percent of MSF credited to the macrofloc-sized fractions for those respective months). Such changes in the near-bed settling flux demonstrate the highly significant seasonal effects that the AFA bloom has on the floc depositional fluxes in UKL and highlights the importance of seasonal monitoring of these conditions in order to correctly parameterize the wide range in depositional characteristics and floc properties measured throughout UKL.&nbsp;</p><p>Collectively, floc populations observed within UKL demonstrated a wide range in settling velocity (Ws) for a given particle size, D. Similarly, a given settling velocity was not associated with a specific particle size. This variability in particle characteristics and properties indicates the influence of varying floc effective density and its effect on mass and mass settling fluxes (MSF). The use of instruments, such as the INSSEV-LF, enables measuring the variability of settling velocity and its relation to particle density and size.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161175","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Kuwabara, J.S., Topping, B.R., Carter, J.L., Carlson, R.A., Parchaso, F., Fend, S.V., Stauffer-Olsen, N., Manning, A.J., Land, J.M., 2016, Benthic processes affecting contaminant transport in Upper Klamath Lake, Oregon (ver. 1.1, October 2016): U.S. Geological Survey Open-File Report 2016–1175, 103 p., https://dx.doi.org/10.3133/ofr20161175. ","productDescription":"Report: viii, 103 p.; 2 Tables","numberOfPages":"115","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":329222,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1175/coverthb.jpg"},{"id":329223,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1175/ofr20161175.pdf","text":"Report","size":"4.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1175"},{"id":329224,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1175/ofr20161175_table4.xlsx","text":"Table 4","size":"96 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1175 Table 4"},{"id":329425,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2016/1175/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2016-1175 Version History"},{"id":329424,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1175/ofr20161175_table19.xlsx","text":"Table 19","size":"18 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1175 Table 19"}],"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              -122.09793090820311,\n              42.231567925608616\n            ],\n            [\n              -122.09793090820311,\n              42.70464124398721\n            ],\n            [\n              -121.79992675781249,\n              42.70464124398721\n            ],\n            [\n              -121.79992675781249,\n              42.231567925608616\n            ],\n            [\n              -122.09793090820311,\n              42.231567925608616\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.0: Originally posted September 30, 2016; Version 1.1: October 11, 2016","contact":"<p><a href=\"http://water.usgs.gov/nrp/index-scientists.html\" target=\"_blank\" data-mce-href=\"http://water.usgs.gov/nrp/index-scientists.html\">NRP staff</a>&nbsp;<br>Water Resources National Research Program&nbsp;<br>U.S. Geological Survey&nbsp;<br>345 Middlefield Road, MS-435&nbsp;<br>Menlo Park, CA 94025&nbsp;<br><a href=\"http://water.usgs.gov/nrp/\" target=\"_blank\" data-mce-href=\"http://water.usgs.gov/nrp/\">National Research Program</a></p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>Results and Discussion</li><li>Methods</li><li>References Cited</li><li>Tables</li></ul>","publishedDate":"2016-09-30","revisedDate":"2016-10-11","noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"57f7c63be4b0bc0bec09c83e","contributors":{"authors":[{"text":"Kuwabara, James S. 0000-0003-2502-1601 kuwabara@usgs.gov","orcid":"https://orcid.org/0000-0003-2502-1601","contributorId":3374,"corporation":false,"usgs":true,"family":"Kuwabara","given":"James","email":"kuwabara@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":649913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Topping, Brent R. 0000-0002-7887-4221 btopping@usgs.gov","orcid":"https://orcid.org/0000-0002-7887-4221","contributorId":1484,"corporation":false,"usgs":true,"family":"Topping","given":"Brent","email":"btopping@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":649914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carter, James L. 0000-0002-0104-9776 jlcarter@usgs.gov","orcid":"https://orcid.org/0000-0002-0104-9776","contributorId":3278,"corporation":false,"usgs":true,"family":"Carter","given":"James","email":"jlcarter@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":649915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carlson, Rick A","contributorId":120306,"corporation":false,"usgs":true,"family":"Carlson","given":"Rick A","affiliations":[],"preferred":false,"id":649916,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parchaso, Francis 0000-0002-9471-7787 parchaso@usgs.gov","orcid":"https://orcid.org/0000-0002-9471-7787","contributorId":150620,"corporation":false,"usgs":true,"family":"Parchaso","given":"Francis","email":"parchaso@usgs.gov","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":649917,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fend, Steven V. 0000-0002-4638-6602 svfend@usgs.gov","orcid":"https://orcid.org/0000-0002-4638-6602","contributorId":3591,"corporation":false,"usgs":true,"family":"Fend","given":"Steven","email":"svfend@usgs.gov","middleInitial":"V.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":649918,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stauffer-Olsen, Natalie","contributorId":175078,"corporation":false,"usgs":true,"family":"Stauffer-Olsen","given":"Natalie","affiliations":[],"preferred":false,"id":649919,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Manning, Andrew J.","contributorId":175079,"corporation":false,"usgs":false,"family":"Manning","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":649920,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Land, Jennie M.","contributorId":175080,"corporation":false,"usgs":true,"family":"Land","given":"Jennie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":649921,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70176920,"text":"70176920 - 2016 - Characterizing changes in streamflow and sediment supply in the Sacramento River Basin, California, using hydrological simulation program—FORTRAN (HSPF)","interactions":[],"lastModifiedDate":"2017-10-30T09:43:05","indexId":"70176920","displayToPublicDate":"2016-09-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing changes in streamflow and sediment supply in the Sacramento River Basin, California, using hydrological simulation program—FORTRAN (HSPF)","docAbstract":"<p><span>A daily watershed model of the Sacramento River Basin of northern California was developed to simulate streamflow and suspended sediment transport to the San Francisco Bay-Delta. To compensate for sparse data, a unique combination of model inputs was developed, including meteorological variables, potential evapotranspiration, and parameters defining hydraulic geometry. A slight decreasing trend of sediment loads and concentrations was statistically significant in the lowest 50% of flows, supporting the observed historical sediment decline. Historical changes in climate, including seasonality and decline of snowpack, contribute to changes in streamflow, and are a significant component describing the mechanisms responsible for the decline in sediment. Several wet and dry hypothetical climate change scenarios with temperature changes of 1.5 °C and 4.5 °C were applied to the base historical conditions to assess the model sensitivity of streamflow and sediment to changes in climate. Of the scenarios evaluated, sediment discharge for the Sacramento River Basin increased the most with increased storm magnitude and frequency and decreased the most with increases in air temperature, regardless of changes in precipitation. The model will be used to develop projections of potential hydrologic and sediment trends to the Bay-Delta in response to potential future climate scenarios, which will help assess the hydrological and ecological health of the Bay-Delta into the next century.</span></p>","language":"English","publisher":"Molecular Diversity Preservation International","publisherLocation":"Basel, Switzerland","doi":"10.3390/w8100432","usgsCitation":"Stern, M.A., Flint, L.E., Minear, J.T., Flint, A.L., and Wright, S., 2016, Characterizing changes in streamflow and sediment supply in the Sacramento River Basin, California, using hydrological simulation program—FORTRAN (HSPF): Water, v. 8, no. 10, https://doi.org/10.3390/w8100432.","startPage":"432","numberOfPages":"21","ipdsId":"IP-073991","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":462073,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w8100432","text":"Publisher Index Page"},{"id":329512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.5,\n              38.25\n            ],\n            [\n              -123.5,\n              41\n            ],\n            [\n              -121,\n              41\n            ],\n            [\n              -121,\n              38.25\n            ],\n            [\n              -123.5,\n              38.25\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","issue":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"57ffdefee4b0824b2d179cf4","contributors":{"authors":[{"text":"Stern, Michelle A. 0000-0003-3030-7065 mstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3030-7065","contributorId":4244,"corporation":false,"usgs":true,"family":"Stern","given":"Michelle","email":"mstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":650712,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":650713,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Minear, Justin Toby jminear@usgs.gov","contributorId":3736,"corporation":false,"usgs":true,"family":"Minear","given":"Justin","email":"jminear@usgs.gov","middleInitial":"Toby","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":650714,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":650715,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":650716,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70156288,"text":"tm6A53 - 2016 - MT3D-USGS version 1: A U.S. Geological Survey release of MT3DMS updated with new and expanded transport capabilities for use with MODFLOW","interactions":[],"lastModifiedDate":"2016-10-03T11:14:03","indexId":"tm6A53","displayToPublicDate":"2016-09-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-A53","title":"MT3D-USGS version 1: A U.S. Geological Survey release of MT3DMS updated with new and expanded transport capabilities for use with MODFLOW","docAbstract":"<p class=\"p1\">MT3D-USGS, a U.S. Geological Survey updated release of the groundwater solute transport code MT3DMS, includes new transport modeling capabilities to accommodate flow terms calculated by MODFLOW packages that were previously unsupported by MT3DMS and to provide greater flexibility in the simulation of solute transport and reactive solute transport. Unsaturated-zone transport and transport within streams and lakes, including solute exchange with connected groundwater, are among the new capabilities included in the MT3D-USGS code. MT3D-USGS also includes the capability to route a solute through dry cells that may occur in the Newton-Raphson formulation of MODFLOW (that is, MODFLOW-NWT). New chemical reaction Package options include the ability to simulate inter-species reactions and parent-daughter chain reactions. A new pump-and-treat recirculation package enables the simulation of dynamic recirculation with or without treatment for combinations of wells that are represented in the flow model, mimicking the above-ground treatment of extracted water. A reformulation of the treatment of transient mass storage improves conservation of mass and yields solutions for better agreement with analytical benchmarks. Several additional features of MT3D-USGS are (1) the separate specification of the partitioning coefficient (<i>K</i><sub><i>d</i></sub>) within mobile and immobile domains; (2) the capability to assign prescribed concentrations to the top-most active layer; (3) the change in mass storage owing to the change in water volume now appears as its own budget item in the global mass balance summary; (4) the ability to ignore cross-dispersion terms; (5) the definition of Hydrocarbon Spill-Source Package (HSS) mass loading zones using regular and irregular polygons, in addition to the currently supported circular zones; and (6) the ability to specify an absolute minimum thickness rather than the default percent minimum thickness in dry-cell circumstances.</p><p class=\"p2\">Benchmark problems that implement the new features and packages test the accuracy of new code through comparison to analytical benchmarks, as well as to solutions from other published codes. The input file structure for MT3D-USGS adheres to MT3DMS conventions for backward compatibility: the new capabilities and packages described herein are readily invoked by adding three-letter package name acronyms to the name file or by setting input flags as needed. Memory is managed in MT3D-USGS using FORTRAN modules in order to simplify code development and expansion.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Ground water in Book 6: <i>Modeling techniques</i>","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A53","collaboration":"Prepared in collaboration with S.S. Papadopulos & Associates, Inc.","usgsCitation":"Bedekar, Vivek, Morway, E.D., Langevin, C.D., and Tonkin, Matt, 2016, MT3D-USGS version 1: A U.S. Geological Survey release of MT3DMS updated with new and expanded transport capabilities for use with MODFLOW:\nU.S. Geological Survey Techniques and Methods 6-A53, 69 p., https://dx.doi.org/10.3133/tm6A53.","productDescription":"Report: x, 69 p.; Application Site","numberOfPages":"84","onlineOnly":"Y","ipdsId":"IP-053896","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":329190,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/a53/coverthb.jpg"},{"id":329191,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/a53/tm06a53.pdf","text":"Report","size":"4.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 6-A53"},{"id":329192,"rank":3,"type":{"id":4,"text":"Application Site"},"url":"https://dx.doi.org/10.5066/F75T3HKD","text":"MT3D-USGS Version 1","description":"TM 6-A53 MT3D-USGS Version 1"}],"publicComments":"Ground Water Resources Program\nThis report is Chapter 53 of Section A: Ground water in Book 6: <i>Modeling techniques</i>.","contact":"<p>Office of Groundwater<br> U.S. Geological Survey<br> Mail Stop 411<br> 12201 Sunrise Valley Drive<br> Reston, VA 20192<br> <a href=\"http://water.usgs.gov/ogw/\" target=\"_blank\" data-mce-href=\"http://water.usgs.gov/ogw/\">http://water.usgs.gov/ogw/</a></p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Mathematical Model and Formulations in MT3D-USGS<br></li><li>Modifications to the Existing MT3DMS Program and Packages<br></li><li>New Transport Packages Developed for MT3D-USGS<br></li><li>Benchmark Problems and Application Examples<br></li><li>Summary<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2016-09-30","noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"57f7c63be4b0bc0bec09c844","contributors":{"authors":[{"text":"Bedekar, Vivek","contributorId":80985,"corporation":false,"usgs":true,"family":"Bedekar","given":"Vivek","email":"","affiliations":[],"preferred":false,"id":568521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morway, Eric D.","contributorId":72276,"corporation":false,"usgs":true,"family":"Morway","given":"Eric D.","affiliations":[],"preferred":false,"id":568520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langevin, Christian D. 0000-0001-5610-9759 langevin@usgs.gov","orcid":"https://orcid.org/0000-0001-5610-9759","contributorId":1030,"corporation":false,"usgs":true,"family":"Langevin","given":"Christian","email":"langevin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":568522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tonkin, Matthew J.","contributorId":26376,"corporation":false,"usgs":true,"family":"Tonkin","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":568523,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70174219,"text":"sir20165094 - 2016 - Using inferential sensors for quality control of Everglades Depth Estimation Network water-level data","interactions":[],"lastModifiedDate":"2016-09-29T10:11:07","indexId":"sir20165094","displayToPublicDate":"2016-09-29T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5094","title":"Using inferential sensors for quality control of Everglades Depth Estimation Network water-level data","docAbstract":"<p>The Everglades Depth Estimation Network (EDEN), with over 240 real-time gaging stations, provides hydrologic data for freshwater and tidal areas of the Everglades. These data are used to generate daily water-level and water-depth maps of the Everglades that are used to assess biotic responses to hydrologic change resulting from the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. The generation of EDEN daily water-level and water-depth maps is dependent on high quality real-time data from water-level stations. Real-time data are automatically checked for outliers by assigning minimum and maximum thresholds for each station. Small errors in the real-time data, such as gradual drift of malfunctioning pressure transducers, are more difficult to immediately identify with visual inspection of time-series plots and may only be identified during on-site inspections of the stations. Correcting these small errors in the data often is time consuming and water-level data may not be finalized for several months. To provide daily water-level and water-depth maps on a near real-time basis, EDEN needed an automated process to identify errors in water-level data and to provide estimates for missing or erroneous water-level data.</p><p>The Automated Data Assurance and Management (ADAM) software uses inferential sensor technology often used in industrial applications. Rather than installing a redundant sensor to measure a process, such as an additional water-level station, inferential sensors, or virtual sensors, were developed for each station that make accurate estimates of the process measured by the hard sensor (water-level gaging station). The inferential sensors in the ADAM software are empirical models that use inputs from one or more proximal stations. The advantage of ADAM is that it provides a redundant signal to the sensor in the field without the environmental threats associated with field conditions at stations (flood or hurricane, for example). In the event that a station does malfunction, ADAM provides an accurate estimate for the period of missing data. The ADAM software also is used in the quality assurance and quality control of the data. The virtual signals are compared to the real-time data, and if the difference between the two signals exceeds a certain tolerance, corrective action to the data and (or) the gaging station can be taken. The ADAM software is automated so that, each morning, the real-time EDEN data are compared to the inferential sensor signals and digital reports highlighting potential erroneous real-time data are generated for appropriate support personnel. The development and application of inferential sensors is easily transferable to other real-time hydrologic monitoring networks.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165094","collaboration":"Greater Everglades Priority Ecosystems Science","usgsCitation":"Petkewich, M.D., Daamen, R.C., Roehl, E.A., and Conrads, P.A., 2016, Using inferential sensors for quality control of Everglades Depth Estimation Network water-level data: U.S. Geological Survey Scientific Investigations Report 2016–5094, 25 p., https://dx.doi.org/10.3133/sir20165094.","productDescription":"v, 25 p.","onlineOnly":"Y","ipdsId":"IP-066447","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":329015,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20161116","text":"Open-File Report 2016–1116","description":"Open-File Report 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Assurance and Management (ADAM) Software</li><li>ADAM Software Architecture&nbsp;</li><li>Using ADAM Software to Process Everglades Depth Estimation Network Data&nbsp;</li><li>Summary&nbsp;</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-09-29","noUsgsAuthors":false,"publicationDate":"2016-09-29","publicationStatus":"PW","scienceBaseUri":"57ed3e3ee4b090825011d493","contributors":{"authors":[{"text":"Petkewich, Matthew D. 0000-0002-5749-6356 mdpetkew@usgs.gov","orcid":"https://orcid.org/0000-0002-5749-6356","contributorId":982,"corporation":false,"usgs":true,"family":"Petkewich","given":"Matthew","email":"mdpetkew@usgs.gov","middleInitial":"D.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641330,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daamen, Ruby C.","contributorId":105391,"corporation":false,"usgs":true,"family":"Daamen","given":"Ruby","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":641333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roehl, Edwin A.","contributorId":89242,"corporation":false,"usgs":true,"family":"Roehl","given":"Edwin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":641332,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":641331,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70174889,"text":"ofr20161116 - 2016 - User’s manual for the Automated Data Assurance and Management application developed for quality control of Everglades Depth Estimation Network water-level data","interactions":[],"lastModifiedDate":"2016-09-29T10:05:26","indexId":"ofr20161116","displayToPublicDate":"2016-09-29T10:00:00","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":"2016-1116","title":"User’s manual for the Automated Data Assurance and Management application developed for quality control of Everglades Depth Estimation Network water-level data","docAbstract":"<p>The generation of Everglades Depth Estimation Network (EDEN) daily water-level and water-depth maps is dependent on high quality real-time data from over 240 water-level stations. To increase the accuracy of the daily water-surface maps, the Automated Data Assurance and Management (ADAM) tool was created by the U.S. Geological Survey as part of Greater Everglades Priority Ecosystems Science. The ADAM tool is used to provide accurate quality-assurance review of the real-time data from the EDEN network and allows estimation or replacement of missing or erroneous data. This user’s manual describes how to install and operate the ADAM software. File structure and operation of the ADAM software is explained using examples.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161116","collaboration":"Greater Everglades Priority Ecosystems Science","usgsCitation":"Petkewich, M.D., Daamen, R.C., Roehl, E.A., and Conrads, P.A., 2016, User’s manual for the Automated Data Assurance and Management application developed for quality control of Everglades Depth Estimation Network water-level data: U.S. Geological Survey Open-File Report 2016–1116, 28 p., https://dx.doi.org/10.3133/ofr20161116.","productDescription":"Report: vi, 28 p.; Companion File","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-076311","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":329016,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20165094","text":"Scientific Investigations Report 2016–5094","description":"Scientific Investigations Report 2016–5094","linkHelpText":"- Using Inferential Sensors for Quality Control of Everglades Depth Estimation Network Water-Level Data"},{"id":328990,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1116/ofr20161116.pdf","text":"Report","size":"13.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1116"},{"id":328989,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1116/coverthb.jpg"},{"id":329002,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2016/1116/downloads","text":"Executable files for Automated Data Assurance and Management application","description":"OFR 2016-1116"}],"contact":"<p><a href=\"mailto:dc_sc@usgs.gov\" data-mce-href=\"mailto:dc_sc@usgs.gov\">Director</a>, South Atlantic Water Science Center<br> U.S. Geological Survey<br> Stephenson Center, Suite 129<br> Gracern Road<br> Columbia, SC 29210<br> <a href=\"https://www2.usgs.gov/water/southatlantic/\" data-mce-href=\"https://www2.usgs.gov/water/southatlantic/\">https://www2.usgs.gov/water/southatlantic</a></p>","tableOfContents":"<ul><li>Abstract&nbsp;</li><li>Introduction</li><li>Application Files&nbsp;</li><li>Installation, System Requirements, and Removal</li><li>Application Overview</li><li>Operation&nbsp;</li><li>Application Input File Format</li><li>Application User Worksheets</li><li>ADAMDB Table Structure</li><li>Summary</li><li>Reference Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-09-29","noUsgsAuthors":false,"publicationDate":"2016-09-29","publicationStatus":"PW","scienceBaseUri":"57ed2bdae4b090825011d41a","contributors":{"authors":[{"text":"Petkewich, Matthew D. 0000-0002-5749-6356 mdpetkew@usgs.gov","orcid":"https://orcid.org/0000-0002-5749-6356","contributorId":982,"corporation":false,"usgs":true,"family":"Petkewich","given":"Matthew","email":"mdpetkew@usgs.gov","middleInitial":"D.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daamen, Ruby C.","contributorId":105391,"corporation":false,"usgs":true,"family":"Daamen","given":"Ruby","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":643009,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roehl, Edwin A.","contributorId":89242,"corporation":false,"usgs":true,"family":"Roehl","given":"Edwin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":643010,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":643011,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70176548,"text":"fs20163073 - 2016 - 2011 Souris River flood—Will it happen again?","interactions":[],"lastModifiedDate":"2017-10-12T19:51:53","indexId":"fs20163073","displayToPublicDate":"2016-09-29T00:00:00","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":"2016-3073","title":"2011 Souris River flood—Will it happen again?","docAbstract":"<p>The Souris River Basin is a 61,000 square kilometer basin in the provinces of Saskatchewan and Manitoba and the state of North Dakota. Record setting rains in May and June of 2011 led to record flooding with peak annual streamflow values (762 cubic meters per second [m<sup>3</sup>/s]) more than twice that of any previously recorded peak streamflow and more than five times the estimated 100 year postregulation streamflow (142 m<sup>3</sup>/s) at the U.S. Geological Survey (USGS) streamflow-gaging station above Minot, North Dakota. Upstream from Minot, N. Dak., the Souris River is regulated by three reservoirs in Saskatchewan (Rafferty, Boundary, and Alameda) and Lake Darling in North Dakota. During the 2011 flood, the city of Minot, N. Dak., experienced devastating damages with more than 4,000 homes flooded and 11,000 evacuated. As a result, the Souris River Basin Task Force recommended the U.S. Geological Survey (in cooperation with the North Dakota State Water Commission) develop a model for estimating the probabilities of future flooding and drought. The model that was developed took on four parts: (1) looking at past climate, (2) predicting future climate, (3) developing a streamflow model in response to certain climatic variables, and (4) combining future climate estimates with the streamflow model to predict future streamflow events. By taking into consideration historical climate record and trends in basin response to various climatic conditions, it was determined flood risk will remain high in the Souris River Basin until the wet climate state ends.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163073","collaboration":"Prepared in cooperation with the North Dakota State Water Commission","usgsCitation":"Nustad, R.A., Kolars, K.A., Vecchia, A.V., and Ryberg, K.R., 2016, 2011 Souris River flood—Will it happen again?: U.S. Geological Survey Fact Sheet 2016–3073, 4 p., https://dx.doi.org/10.3133/fs20163073.","productDescription":"4 p.","startPage":"1","endPage":"4","numberOfPages":"4","onlineOnly":"Y","ipdsId":"IP-078012","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":328874,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3073/fs20163073.pdf","text":"Fact Sheet","size":"994 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016–3073"},{"id":328873,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3073/coverthb.jpg"}],"country":"Canada, United States","otherGeospatial":"Souris River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -94.81201171875,\n              48.545705491847464\n            ],\n            [\n              -95.03173828125,\n              49.53946900793534\n            ],\n            [\n              -95.73486328124999,\n              50.387507803003146\n            ],\n            [\n        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       51.2206474303833\n            ],\n            [\n              -108.896484375,\n              49.85215166776998\n            ],\n            [\n              -109.0283203125,\n              48.83579746243093\n            ],\n            [\n              -108.5009765625,\n              47.916342040161155\n            ],\n            [\n              -107.22656249999999,\n              46.22545288226939\n            ],\n            [\n              -105.27099609375,\n              44.88701247981298\n            ],\n            [\n              -103.55712890625,\n              44.66865287227321\n            ],\n            [\n              -102.7880859375,\n              44.26093725039923\n            ],\n            [\n              -101.53564453124999,\n              43.91372326852401\n            ],\n            [\n              -99.90966796875,\n              43.99281450048989\n            ],\n            [\n              -97.66845703124999,\n              44.653024159812\n            ],\n            [\n              -96.767578125,\n              45.44471679159555\n            ],\n            [\n              -96.064453125,\n              46.210249600187225\n            ],\n            [\n              -95.51513671875,\n              47.42808726171425\n            ],\n            [\n              -94.81201171875,\n              48.545705491847464\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, North Dakota Water Science Center<br>U.S. Geological Survey<br>821 East Interstate Ave.<br>Bismarck, North Dakota 58503</p><p><a href=\"http://nd.water.usgs.gov/\" data-mce-href=\"http://nd.water.usgs.gov/\">http://nd.water.usgs.gov/</a></p>","tableOfContents":"<ul><li>Introduction<br></li><li>Looking at Past Climate<br></li><li>Predicting Future Climate<br></li><li>Streamflow Model<br></li><li>Will it Flood Again?<br></li><li>References Cited<br></li><li>Further Information<br></li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-09-29","noUsgsAuthors":false,"publicationDate":"2016-09-29","publicationStatus":"PW","scienceBaseUri":"57ed3e42e4b090825011d495","contributors":{"authors":[{"text":"Nustad, Rochelle A. 0000-0002-4713-5944 ranustad@usgs.gov","orcid":"https://orcid.org/0000-0002-4713-5944","contributorId":1811,"corporation":false,"usgs":true,"family":"Nustad","given":"Rochelle","email":"ranustad@usgs.gov","middleInitial":"A.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":649176,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolars, Kelsey A. kkolars@usgs.gov","contributorId":167117,"corporation":false,"usgs":true,"family":"Kolars","given":"Kelsey A.","email":"kkolars@usgs.gov","affiliations":[],"preferred":false,"id":649177,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vecchia, Aldo V. 0000-0002-2661-4401","orcid":"https://orcid.org/0000-0002-2661-4401","contributorId":41810,"corporation":false,"usgs":true,"family":"Vecchia","given":"Aldo","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":649591,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":649592,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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