Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low-quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision-making framework will result in better-informed, more robust decisions.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.1520","usgsCitation":"Zajac, Z., Stith, B., Bowling, A.C., Langtimm, C.A., and Swain, E.D., 2015, Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation: Ecology and Evolution, v. 5, no. 13, p. 2503-2517, https://doi.org/10.1002/ece3.1520.","productDescription":"15 p.","startPage":"2503","endPage":"2517","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053424","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":471925,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1520","text":"Publisher Index Page"},{"id":306252,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.36474609375,\n 25.090573819461\n ],\n [\n -81.36474609375,\n 25.84439325019514\n ],\n [\n -80.8154296875,\n 25.84439325019514\n ],\n [\n -80.8154296875,\n 25.090573819461\n ],\n [\n -81.36474609375,\n 25.090573819461\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","issue":"13","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55b9eb1ee4b05b91f6398b37","chorus":{"doi":"10.1002/ece3.1520","url":"http://dx.doi.org/10.1002/ece3.1520","publisher":"Wiley-Blackwell","authors":"Zajac Zuzanna, Stith Bradley, Bowling Andrea C., Langtimm Catherine A., Swain Eric D.","journalName":"Ecology and Evolution","publicationDate":"6/1/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Zajac, Zuzanna","contributorId":145637,"corporation":false,"usgs":false,"family":"Zajac","given":"Zuzanna","email":"","affiliations":[{"id":16181,"text":"University of Florida, Department of Agriculture and Biological Engineering","active":true,"usgs":false}],"preferred":false,"id":564855,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stith, Bradley bstith@usgs.gov","contributorId":3596,"corporation":false,"usgs":true,"family":"Stith","given":"Bradley","email":"bstith@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":564856,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowling, Andrea C.","contributorId":43615,"corporation":false,"usgs":true,"family":"Bowling","given":"Andrea","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":564857,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Langtimm, Catherine A. 0000-0001-8499-5743 clangtimm@usgs.gov","orcid":"https://orcid.org/0000-0001-8499-5743","contributorId":3045,"corporation":false,"usgs":true,"family":"Langtimm","given":"Catherine","email":"clangtimm@usgs.gov","middleInitial":"A.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":564854,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swain, Eric D. 0000-0001-7168-708X edswain@usgs.gov","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":1538,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","email":"edswain@usgs.gov","middleInitial":"D.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":564858,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155300,"text":"sir20155109 - 2015 - Water-quality conditions and suspended-sediment transport in the Wilson and Trask Rivers, northwestern Oregon, water years 2012–14","interactions":[],"lastModifiedDate":"2019-12-30T14:33:12","indexId":"sir20155109","displayToPublicDate":"2015-07-28T20:45:00","publicationYear":"2015","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":"2015-5109","title":"Water-quality conditions and suspended-sediment transport in the Wilson and Trask Rivers, northwestern Oregon, water years 2012–14","docAbstract":"In October 2011, the U.S. Geological Survey began investigating and monitoring water-quality conditions and suspended-sediment transport in the Wilson and Trask Rivers, northwestern Oregon. Water temperature, specific conductance, turbidity, and dissolved oxygen were measured every 15–30 minutes in both streams using real-time instream water-quality monitors. In conjunction with the monitoring effort, suspended-sediment samples were collected and analyzed to model the amount of suspended sediment being transported by each river. Over the course of the 3-year study, which ended in September 2014, nearly 600,000 tons (t) of suspended-sediment material entered Tillamook Bay from these two tributaries.
\nEach year of the study, the Wilson River transported between 80,300 and 240,000 t of suspended sediment, while the Trask River contributed between 28,200 and 69,900 t. The suspended-sediment loads observed during the study were relatively small because streamflow conditions were routinely lower than normal between October 2011 and September 2014. Only one storm had a recurrence interval between a 2- and 5-year event. Every other storm produced streamflows equivalent to what would be classified as a 1- or 2-year event. Because most sediment moves during high flows, the lack of heavy rainfall and elevated streamflows muted any high sediment loads.
\nAlong with assessing suspended-sediment transport, the U.S. Geological Survey also monitored instream water quality. This monitoring was used to track instream conditions and relate them to water temperature, dissolved oxygen, and sedimentation issues for the Wilson and Trask Rivers. Stream temperatures in the Wilson and Trask Rivers exceeded the temperature standard for cold-water habitat. Water temperatures at both streams exceeded the standard for more than 30 percent of the year, as stream temperatures increased above the seasonal 13 degrees Celsius (°C) (seasonal core cold-water habitat) and 16 °C (salmon and steelhead [Oncorhynchus mykiss] spawning) thresholds. Conversely, dissolved oxygen concentrations rarely decreased to less than the absolute water-quality criterion of 8 milligrams per liter for cold-water streams.
\nResults from this study will provide resource managers insight into the seasonality of water-quality conditions and the extent of suspended-sediment transport in the Wilson and Trask Rivers. The data are useful for establishing a baseline and for maintaining best-use land management practices and possibly for aiding in prioritization of restoration actions for both rivers and their respective watersheds.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155109","collaboration":"Prepared in cooperation with the Tillamook Estuaries Partnership","usgsCitation":"Sobieszczyk, Steven, Bragg, H.M., and Uhrich, M.A., 2015, Water-quality conditions and suspended-sediment transport in the Wilson and Trask Rivers, northwestern Oregon, water years 2012–14: U.S. Geological Survey Scientific Investigations Report 2015-5109, 32 p., https://dx.doi.org/10.3133/sir20155109.","productDescription":"vi, 32 p.","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2011-10-01","temporalEnd":"2014-09-30","ipdsId":"IP-064609","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":306219,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5109/sir20155109.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5109"},{"id":306220,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5109/coverthmb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Trask River, Wilson River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.77746582031249,\n 45.325116643332684\n ],\n [\n -123.56597900390626,\n 45.325116643332684\n ],\n [\n -123.56597900390626,\n 45.4947963896697\n ],\n [\n -123.77746582031249,\n 45.4947963896697\n ],\n [\n -123.77746582031249,\n 45.325116643332684\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
Anthropogenic disturbances resulting from human land use affect forest landscapes over a range of spatial and temporal scales, with diverse influences on vegetation patterns and dynamics. These processes fall within the scope of the coupled human and natural systems (CHANS) concept, which has emerged as an important framework for understanding the reciprocal interactions and feedbacks that connect human activities and ecosystem responses. Spatial simulation modeling of forest landscape change is an important technique for exploring the dynamics of CHANS over large areas and long time periods. Landscape models for simulating interactions between human activities and forest landscape dynamics can be grouped into two main categories. Forest landscape models (FLMs) focus on landscapes where forests are the dominant land cover and simulate succession and natural disturbances along with forest management activities. In contrast, land change models (LCMs) simulate mosaics of different land cover and land use classes that include forests in addition to other land uses such as developed areas and agricultural lands. There are also several examples of coupled models that combine elements of FLMs and LCMs. These integrated models are particularly useful for simulating human–natural interactions in landscapes where human settlement and agriculture are expanding into forested areas. Despite important differences in spatial scale and disciplinary scope, FLMs and LCMs have many commonalities in conceptual design and technical implementation that can facilitate continued integration. The ultimate goal will be to implement forest landscape disturbance modeling in a CHANS framework that recognizes the contextual effects of regional land use and other human activities on the forest ecosystem while capturing the reciprocal influences of forests and their disturbances on the broader land use mosaic.
","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-19809-5_9","usgsCitation":"Wimberly, M., Sohl, T.L., Liu, Z., and Lamsal, A., 2015, Simulating forest landscape disturbances as coupled human and natural systems, p. 233-261, https://doi.org/10.1007/978-3-319-19809-5_9.","productDescription":"29 p.","startPage":"233","endPage":"261","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054503","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":320465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":319384,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1007/978-3-319-19809-5_9"}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-28","publicationStatus":"PW","scienceBaseUri":"571dee2ce4b071321fe56425","contributors":{"authors":[{"text":"Wimberly, Michael","contributorId":51654,"corporation":false,"usgs":true,"family":"Wimberly","given":"Michael","affiliations":[],"preferred":false,"id":623841,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sohl, Terry L. 0000-0002-9771-4231 sohl@usgs.gov","orcid":"https://orcid.org/0000-0002-9771-4231","contributorId":648,"corporation":false,"usgs":true,"family":"Sohl","given":"Terry","email":"sohl@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":623840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Zhihua","contributorId":105228,"corporation":false,"usgs":true,"family":"Liu","given":"Zhihua","email":"","affiliations":[],"preferred":false,"id":623842,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lamsal, Aashis","contributorId":37255,"corporation":false,"usgs":true,"family":"Lamsal","given":"Aashis","email":"","affiliations":[],"preferred":false,"id":623843,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160786,"text":"70160786 - 2015 - Application of a putative alarm cue hastens the arrival of invasive sea lamprey (Petromyzon marinus) at a trapping location","interactions":[],"lastModifiedDate":"2017-08-15T12:44:42","indexId":"70160786","displayToPublicDate":"2015-07-28T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Application of a putative alarm cue hastens the arrival of invasive sea lamprey (Petromyzon marinus) at a trapping location","docAbstract":"The sea lamprey Petromyzon marinus is an invasive pest in the Laurentian Great Lakes basin, threatening the persistence of important commercial and recreational fisheries. There is substantial interest in developing effective trapping practices via the application of behavior-modifying semiochemicals (odors). Here we report on the effectiveness of utilizing repellent and attractant odors in a push–pull configuration, commonly employed to tackle invertebrate pests, to improve trapping efficacy at permanent barriers to sea lamprey migration. When a half-stream channel was activated by a naturally derived repellent odor (a putative alarm cue), we found that sea lamprey located a trap entrance significantly faster than when no odor was present as a result of their redistribution within the stream. The presence of a partial sex pheromone, acting as an attractant within the trap, was not found to further decrease the time to when sea lamprey located a trap entrance relative to when the alarm cue alone was applied. Neither the application of alarm cue singly nor alarm cue and partial sex pheromone in combination was found to improve the numbers of sea lamprey captured in the trap versus when no odor was present — likely because nominal capture rate during control trials was unusually high during the study period. Behavioural guidance using these odors has the potential to both improve control of invasive non-native sea lamprey in the Great Lakes as well as improving the efficiency of fish passage devices used in the restoration of threatened lamprey species elsewhere.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2014-0535","usgsCitation":"Hume, J.B., Meckley, T., Johnson, N., Luhring, T.M., Siefkes, M.J., and Wagner, C.M., 2015, Application of a putative alarm cue hastens the arrival of invasive sea lamprey (Petromyzon marinus) at a trapping location: Canadian Journal of Fisheries and Aquatic Sciences, v. 72, no. 12, p. 1799-1806, https://doi.org/10.1139/cjfas-2014-0535.","productDescription":"8 p.","startPage":"1799","endPage":"1806","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065703","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":313143,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Carp Lake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.82947349548338,\n 45.74925869886274\n ],\n [\n -84.82870101928711,\n 45.749019127824525\n ],\n [\n -84.82910871505737,\n 45.748090780339176\n ],\n [\n -84.82970952987671,\n 45.74620409110211\n ],\n [\n -84.8294949531555,\n 45.74578481816729\n ],\n [\n -84.82865810394287,\n 45.7453505678793\n ],\n [\n -84.8277997970581,\n 45.7454553872236\n ],\n [\n -84.8267912864685,\n 45.74539549047953\n ],\n [\n -84.82696294784546,\n 45.74490133988872\n ],\n [\n -84.82904434204102,\n 45.74490133988872\n ],\n [\n -84.83022451400757,\n 45.74572492177667\n ],\n [\n -84.83063220977783,\n 45.74674315167684\n ],\n [\n -84.8302674293518,\n 45.747701468734114\n ],\n [\n -84.82945203781128,\n 45.74874960917743\n ],\n [\n -84.82979536056519,\n 45.74904907426054\n ],\n [\n -84.82947349548338,\n 45.74925869886274\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"72","issue":"12","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56865fbee4b0e7594ee74cb4","contributors":{"authors":[{"text":"Hume, John B.","contributorId":150987,"corporation":false,"usgs":false,"family":"Hume","given":"John","email":"","middleInitial":"B.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":583898,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meckley, Trevor D.","contributorId":67417,"corporation":false,"usgs":true,"family":"Meckley","given":"Trevor D.","affiliations":[],"preferred":false,"id":583899,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":150983,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583897,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Luhring, Thomas M","contributorId":150988,"corporation":false,"usgs":false,"family":"Luhring","given":"Thomas","email":"","middleInitial":"M","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":583900,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Siefkes, Michael J","contributorId":150989,"corporation":false,"usgs":false,"family":"Siefkes","given":"Michael","email":"","middleInitial":"J","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":583901,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wagner, C. Michael","contributorId":145442,"corporation":false,"usgs":false,"family":"Wagner","given":"C.","email":"","middleInitial":"Michael","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":583902,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70157270,"text":"70157270 - 2015 - Approaches to modeling landscape-scale drought-induced forest mortality","interactions":[],"lastModifiedDate":"2017-11-22T16:17:17","indexId":"70157270","displayToPublicDate":"2015-07-28T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Approaches to modeling landscape-scale drought-induced forest mortality","docAbstract":"Drought stress is an important cause of tree mortality in forests, and drought-induced disturbance events are projected to become more common in the future due to climate change. Landscape Disturbance and Succession Models (LDSM) are becoming widely used to project climate change impacts on forests, including potential interactions with natural and anthropogenic disturbances, and to explore the efficacy of alternative management actions to mitigate negative consequences of global changes on forests and ecosystem services. Recent studies incorporating drought-mortality effects into LDSMs have projected significant potential changes in forest composition and carbon storage, largely due to differential impacts of drought on tree species and interactions with other disturbance agents. In this chapter, we review how drought affects forest ecosystems and the different ways drought effects have been modeled (both spatially and aspatially) in the past. Building on those efforts, we describe several approaches to modeling drought effects in LDSMs, discuss advantages and shortcomings of each, and include two case studies for illustration. The first approach features the use of empirically derived relationships between measures of drought and the loss of tree biomass to drought-induced mortality. The second uses deterministic rules of species mortality for given drought events to project changes in species composition and forest distribution. A third approach is more mechanistic, simulating growth reductions and death caused by water stress. Because modeling of drought effects in LDSMs is still in its infancy, and because drought is expected to play an increasingly important role in forest health, further development of modeling drought-forest dynamics is urgently needed.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Simulation modeling of forest landscape disturbances","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-19809-5","usgsCitation":"Gustafson, E., and Shinneman, D.J., 2015, Approaches to modeling landscape-scale drought-induced forest mortality, chap. of Simulation modeling of forest landscape disturbances, p. 45-71, https://doi.org/10.1007/978-3-319-19809-5.","productDescription":"27 p. ","startPage":"45","endPage":"71","ipdsId":"IP-053550","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":328262,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57cfe8ade4b04836416a0d1f","contributors":{"authors":[{"text":"Gustafson, Eric J.","contributorId":70196,"corporation":false,"usgs":true,"family":"Gustafson","given":"Eric J.","affiliations":[],"preferred":false,"id":572521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":572520,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70137282,"text":"ds890 - 2015 - Lithostratigraphic, borehole-geophysical, hydrogeologic, and hydrochemical data from the East Bay Plain, Alameda County, California","interactions":[],"lastModifiedDate":"2015-07-27T09:48:06","indexId":"ds890","displayToPublicDate":"2015-07-24T16:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"890","title":"Lithostratigraphic, borehole-geophysical, hydrogeologic, and hydrochemical data from the East Bay Plain, Alameda County, California","docAbstract":"The U.S. Geological Survey, in cooperation with the East Bay Municipal Utility District, carried out an investigation of aquifer-system deformation associated with groundwater-level changes at the Bayside Groundwater Project near the modern San Francisco Bay shore in San Lorenzo, California. As a part of the Bayside Groundwater Project, East Bay Municipal Utility District proposed an aquifer storage and recovery program for 1 million gallons of water per day. The potential for aquifer-system compaction and expansion, and related subsidence, uplift, or both, resulting from aquifer storage and recovery activities were investigated and monitored in the Bayside Groundwater Project. In addition, baseline analysis of groundwater and substrata properties were performed to assess the potential effect of such activities. Chemical and physical data, obtained from the subsurface at four sites on the east side of San Francisco Bay in the San Lorenzo and San Leandro areas of the East Bay Plain, Alameda County, California, were collected during the study. The results of the study were provided to the East Bay Municipal Utility District and other agencies to evaluate the chemical and mechanical responses of aquifers underlying the East Bay Plain to the future injection and recovery of imported water from the Sierra Nevada of California.
\nAmong 4 sites, 14 piezometers and 2 extensometers were installed in 6 boreholes, which ranged in depth from 460 to 1,040 feet. The lithology of drill cuttings, collected at 5- or 10-foot intervals, was described for grain size and any other noticeable features, such as wood or shell fragments. Borehole geophysical logging was performed at each site in the deepest borehole, immediately following drilling.
\nDrill-core samples, totaling 284 feet, were collected at the Bayside site. The drill-core sediment was subsampled to determine pore-water chemistry, vertical hydraulic conductivity, and physical and mechanical properties at different depths. Depositional environment and age were determined by luminescence geochronology and fossil identification. The elemental composition of the drill-core sediments was determined by inductively coupled plasma mass spectroscopy and instrumental neutron activation by abbreviated count analysis. Mineral composition was determined by X-ray diffraction and scanning electron microscopy analysis.
\nGroundwater samples were collected from all 14 piezometers as part of either the USGS Groundwater Ambient Monitoring and Assessment or the USGS National Water Quality Assessment program for water-quality analyses. Sample analytes included nutrients, major and minor ions, trace elements, isotopic ratios of hydrogen and oxygen in water, carbon-14, and tritium.
\nWater-level and aquifer-system-compaction measurements, which indicated diurnal and seasonal fluctuations, were made at the Bayside Groundwater Project site. Slug tests were performed at the Bayside piezometers and nine pre-existing wells to estimate hydraulic conductivity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds890","collaboration":"Prepared in cooperation with the East Bay Municipal Utility District","usgsCitation":"Sneed, M., Orlando, P., Borchers, J.W., Everett, R., Solt, M., McGann, M., Lowers, H., and Mahan, S., 2015, Lithostratigraphic, borehole-geophysical, hydrogeologic, and hydrochemical data from the East Bay Plain, Alameda County, California: U.S. Geological Survey Data Series 890, viii, 56 p., https://doi.org/10.3133/ds890.","productDescription":"viii, 56 p.","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-012259","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":305938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0890/ds890.pdf","text":"Report","size":"6.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 890"},{"id":305937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0890/coverthb.jpg"}],"country":"United States","state":"California","county":"Alameda County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.20916748046876,\n 37.62945956107554\n ],\n [\n -122.20916748046876,\n 37.70772645289049\n ],\n [\n -122.0416259765625,\n 37.70772645289049\n ],\n [\n -122.0416259765625,\n 37.62945956107554\n ],\n [\n -122.20916748046876,\n 37.62945956107554\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, U.S. Geological Survey
\nCalifornia Water Science Center
\n6000 J Street, Placer Hall
\nSacramento, CA 95829
","tableOfContents":"The Alaska Peninsula is composed of the late Paleozoic to Quaternary sedimentary, igneous, and minor metamorphic rocks that record the history of a number of magmatic arcs. These magmatic arcs include an unnamed Late Triassic(?) and Early Jurassic island arc, the early Cenozoic Meshik arc, and the late Cenozoic Aleutian arc. Also found on the Alaska Peninsula is one of the most complete nonmetamorphosed, fossiliferous, marine Jurassic sedimentary sections known. As much as 8,500 m of section of Mesozoic sedimentary rocks record the growth and erosion of the Early Jurassic island arc.
\nA thinner, but still thick (as much as 5,400 m), sequence of Tertiary sedimentary rocks that are predominantly continental overlies the Mesozoic section. A brief regression in early Tertiary time on the Alaska Peninsula and granodiorite plutonism in the Shumagin, Semidi, and Sanak Islands was followed by deposition of fluvial and minor marine clastic strata. This was followed by deposition of transgressive marine clastic strata and initiation of the Meshik arc, shown by an areally extensive outpouring of volcanic and volcaniclastic rocks and debris between late Eocene and earliest Miocene time. Late Miocene time was marked by another brief transgression and northwest- to southeast-directed compression, followed by renewed volcanism and plutonism which initiated the modern Aleutian magmatic arc.
\nExtensive glacial and glaciomarine deposits of late Pleistocene age create an extensive lowland physiographic province on the northwest side of the Alaska Peninsula and join isolated mountain masses to the Alaska Peninsula on the southwest. Multiple active volcanoes and volcanic peaks dominate the skyline of the Alaska Peninsula and represent the continuation of magmatic activity that has formed the Aleutian arc since late Miocene time.
\nThe Alaska Peninsula has had a long and involved history since Paleozoic time. We propose that the Paleozoic and Mesozoic rocks that constitute much of the Alaska Peninsula be called the Alaska Peninsula terrane. Using the concept of subterranes, we divide the terrane into two distinct but tectonically related subterranes: the Chignik and Iliamna subterranes, which share a limited common geologic history. The Iliamna subterrane has served at most times as a source area for the Chignik subterrane; however, some rock units are in common across the subterranes. The Iliamna and Chignik subterranes are in part separated by the Bruin Bay fault system. The Iliamna subterrane is composed of moderately deformed early Mesozoic marine sedimentary and volcanic rocks and schist, gneiss, and marble of Paleozoic(?) and Mesozoic age, and plutonic rocks of the Alaska-Aleutian Range batholith. Characteristic of the Chignik subterrane are little-deformed, shallow-marine to continental clastic sedimentary rocks ranging in age from Permian to latest Cretaceous. However, deep-marine, volcaniclastic, and calcareous rocks form important components of the older rocks in the subterrane.
\nThe two subterranes of the Alaska Peninsula terrane are characterized by radically different structural and metamorphic styles. The nonplutonic rocks of the Iliamna subterrane are characterized by metamorphism up to amphibolite-facies grade and intense folding. In the Chignik subterrane, the structural style is dominated by large, open, en echelon anticlinal structures, normal faulting, and thrust and high-angle reverse faults that have minor displacement in a northwest to southeast direction. In the Outer Shumagin and Sanak Islands, rocks assigned to the Chugach terrane are characterized structurally by tight, generally northeast-trending folds. Dips in these rocks tend to be steep, rarely less than 35°, and overturned beds are locally common.
\nThe boundaries separating the Alaska Peninsula terrane from other terranes are commonly indistinct or poorly defined. A few boundaries have been defined at major faults, although the extensions of these faults are speculative through some areas. The west side of the Alaska Peninsula terrane is overlapped by Tertiary sedimentary and volcanic rocks and Quaternary deposits.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/b1969B","usgsCitation":"Wilson, F.H., Detterman, R.L., and DuBois, G.D., 2015, Geologic framework of the Alaska Peninsula, southwest Alaska, and the Alaska Peninsula terrane (Legacy Report): U.S. Geological Survey Bulletin 1969, Report: iii, 34 p.; 2 Plates: 57 x 44 inches and 31.5 x 32.77 inches; Digital Data, https://doi.org/10.3133/b1969B.","productDescription":"Report: iii, 34 p.; 2 Plates: 57 x 44 inches and 31.5 x 32.77 inches; Digital Data","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":305966,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/b1969b.gif"},{"id":305962,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/bul/1969b/pdf/bul1969b_report.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":305963,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/bul/1969b/pdf/bul1969b_plate1.pdf","text":"Plate 1","size":"22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Plate 1"},{"id":305961,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/bul/1969b/"},{"id":305964,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/bul/1969b/pdf/bul1969b_plate2.pdf","text":"Plate 2","size":"200 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Plate 2"},{"id":305965,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/1999/0317/","text":"Digital Data","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Digital data for the Geologic Framework of the Alaska Peninsula, Southwest Alaska, and the Alaska Peninsula Terrane is available in USGS Open-File Report 99-317"}],"country":"United States","state":"Alaska","otherGeospatial":"Alaska Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -157.6318359375,\n 59.01794033995246\n ],\n [\n -153.193359375,\n 58.99531118795094\n ],\n [\n -154.7314453125,\n 57.77451753559619\n ],\n [\n -157.412109375,\n 56.24334992410525\n ],\n [\n -158.9501953125,\n 54.77534585936447\n ],\n [\n -162.94921875,\n 54.13669645687002\n ],\n [\n -163.9599609375,\n 54.13669645687002\n ],\n [\n -164.70703125,\n 55.00282580979323\n ],\n [\n -162.59765625,\n 55.92458580482951\n ],\n [\n -160.400390625,\n 56.511017504952136\n ],\n [\n -158.7744140625,\n 57.32652122521709\n ],\n [\n -157.85156249999997,\n 58.147518599073585\n ],\n [\n -157.6318359375,\n 59.01794033995246\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Legacy Report","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7eee1e4b0bc0bec09ed82","contributors":{"authors":[{"text":"Wilson, Frederic H. 0000-0003-1761-6437 fwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1761-6437","contributorId":67174,"corporation":false,"usgs":true,"family":"Wilson","given":"Frederic","email":"fwilson@usgs.gov","middleInitial":"H.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":565689,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Detterman, Robert L.","contributorId":71526,"corporation":false,"usgs":true,"family":"Detterman","given":"Robert","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":565690,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DuBois, Gregory D.","contributorId":6824,"corporation":false,"usgs":true,"family":"DuBois","given":"Gregory","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":565691,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70148549,"text":"sir20155081 - 2015 - Updated numerical model with uncertainty assessment of 1950-56 drought conditions on brackish-water movement within the Edwards aquifer, San Antonio, Texas","interactions":[],"lastModifiedDate":"2017-08-16T07:19:36","indexId":"sir20155081","displayToPublicDate":"2015-07-24T09:30:00","publicationYear":"2015","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":"2015-5081","title":"Updated numerical model with uncertainty assessment of 1950-56 drought conditions on brackish-water movement within the Edwards aquifer, San Antonio, Texas","docAbstract":"In 2010, the U.S. Geological Survey, in cooperation with the San Antonio Water System, began a study to assess the brackish-water movement within the Edwards aquifer (more specifically the potential for brackish-water encroachment into wells near the interface between the freshwater and brackish-water transition zones, referred to in this report as the transition-zone interface) and effects on spring discharge at Comal and San Marcos Springs under drought conditions using a numerical model. The quantitative targets of this study are to predict the effects of higher-than-average groundwater withdrawals from wells and drought-of-record rainfall conditions of 1950–56 on (1) dissolved-solids concentration changes at production wells near the transition-zone interface, (2) total spring discharge at Comal and San Marcos Springs, and (3) the groundwater head (head) at Bexar County index well J-17. The predictions of interest, and the parameters implemented into the model, were evaluated to quantify their uncertainty so the results of the predictions could be presented in terms of a 95-percent credible interval.
\nThe model area covers the San Antonio and Barton Springs segments of the Edwards aquifer; the history-matching effort was focused on the San Antonio segment. A previously developed diffuse-flow model of the Edwards aquifer, which forms the basis for the model in this assessment, is primarily based on a conceptualization in which flow in the aquifer is predominately through a network of numerous small fractures and openings. Primary updates to this model include an extension of the active area downdip, a conversion to an 8-layer SEAWAT variable-density flow and transport model to simulate dissolved-solids concentration effects on water density, history matching to 1999–2009 conditions, and parameter estimation in a highly parameterized context using automated methods in PEST (a model-independent Parameter ESTimation code).
\nIn addition to the best-fit parameter values derived from history matching, the uncertainty of model parameters was also estimated by using linear uncertainty analysis. Comparison of “prior” (before history matching) and “posterior” (after history matching) variances of parameters indicate that the information within the observation dataset used for history matching informs many parameters. The concentration threshold parameters were well-informed by the observation dataset as their posterior distributions were much narrower than their prior distributions. The transition-zone scaling parameters of hydraulic conductivity, effective porosity, and specific storage were all informed by the observation dataset, as evidenced by the difference between the prior and posterior variances. Saline-zone scaling parameters, alternatively, were not informed by the observation dataset for effective porosity and specific storage. Resulting posterior drier-month, wetter-month, and annual recharge multiplier parameter variances are important to understanding how well recharge is estimated and implemented within the model. The shifts of the posterior distributions left and right indicate that there were zones where less or more water was needed in the model. The widths of the distributions were not decreased substantially, indicating that many of the best-fit recharge parameters are not statistically different from the initial values specified in the history-matching effort. Recharge from rainfall is the driving force behind groundwater flow and heads in the aquifer; therefore, an increase in understanding of this process would benefit model development by potentially decreasing the uncertainty of this parameter. The history-matching effort was most helpful in informing the parameters in the model that control discharge at springs, namely, the spring orifice (drain) altitude and drain conductance parameters for each spring.
\nThe uncertainty assessment of the predictive model (a hypothetical recurrence of 1950–56 drought conditions and higher-than-average groundwater withdrawals from wells) provided insights into the potential effects of these conditions on dissolved-solids concentration changes at production wells near the transition-zone interface, discharges at Comal and San Marcos Springs, and heads at Bexar County index well J-17. Results at the 25 production wells near the transition-zone interface indicate that the uncertainty of model input parameters based on expert knowledge yielded an upper bound of the 95-percent credible interval of dissolved-solids concentrations that exceeds the secondary drinking water standards of 1,000 milligrams per liter (mg/L) of the Texas Commission on Environmental Quality (TCEQ) for many wells. However, the history-matching process provided key information to inform prediction-sensitive model parameters and therefore, contributed to a substantial decrease of the upper bound of the 95-percent credible interval to below the secondary drinking water standards. Reductions in dissolved-solids concentration changes were on the order of 400 mg/L to 1,300 mg/L. The reduction in uncertainty in regards to this prediction implies that this prediction of dissolved-solids concentration change can be made with some certainty using this current model and that those parameters that control this prediction are informed by the observation dataset. Even though predictive uncertainty was reduced for this prediction, dissolved-solids concentration changes were still greater than zero, indicating a minimal increase in concentration at these 25 production wells during the 7-year simulation period is likely. However, this minimal concentration increase indicates a small potential for movement of the brackish-water transition zone near these wells during the 7-year simulation period of drought-ofrecord (1950–56) rainfall conditions with higher-than-average groundwater withdrawals by wells.
\nPredictive results of total spring discharge during the 7-year period, as well as head predictions at Bexar County index well J-17, were much different than the dissolved-solids concentration change results at the production wells. These upper bounds are an order of magnitude larger than the actual prediction which implies that (1) the predictions of total spring discharge at Comal and San Marcos Springs and head at Bexar County index well J-17 made with this model are not reliable, and (2) parameters that control these predictions are not informed well by the observation dataset during historymatching, even though the history-matching process yielded parameters to reproduce spring discharges and heads at these locations during the history-matching period. Furthermore, because spring discharges at these two springs and heads at Bexar County index well J-17 represent more of a cumulative effect of upstream conditions over a larger distance (and longer time), many more parameters (with their own uncertainties) are potentially controlling these predictions than the prediction of dissolved-solids concentration change at the prediction wells, and therefore contributing to a large posterior uncertainty.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155081","collaboration":"Prepared in cooperation with the San Antonio Water System","usgsCitation":"Brakefield, L., White, J., Houston, N.A., and Thomas, J.V., 2015, Updated numerical model with uncertainty assessment of 1950-56 drought conditions on brackish-water movement within the Edwards aquifer, San Antonio, Texas: U.S. Geological Survey Scientific Investigations Report 2015-5081, viii, 54 p., https://doi.org/10.3133/sir20155081.","productDescription":"viii, 54 p.","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056599","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":305941,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5081/sir2015-5081.pdf","text":"Report","size":"6.32 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":305942,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5081/coverthb.jpg"}],"country":"United States","state":"Texas","city":"San Antonio","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.1181640625,\n 29.477861195816843\n ],\n [\n -98.173828125,\n 30.486550842588485\n ],\n [\n -97.9541015625,\n 30.562260950499414\n ],\n [\n -97.37182617187499,\n 29.44916482692468\n ],\n [\n -100.338134765625,\n 28.36240173523821\n ],\n [\n -101.063232421875,\n 29.430029404571762\n ],\n [\n -101.1181640625,\n 29.477861195816843\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a5b8e0e4b0ebae89b78a9e","contributors":{"authors":[{"text":"Brakefield, Linzy K. lbrake@usgs.gov","contributorId":145899,"corporation":false,"usgs":true,"family":"Brakefield","given":"Linzy K.","email":"lbrake@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":565606,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Jeremy T. jwhite@usgs.gov","contributorId":3930,"corporation":false,"usgs":true,"family":"White","given":"Jeremy T.","email":"jwhite@usgs.gov","affiliations":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"preferred":false,"id":565607,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Houston, Natalie A. 0000-0002-6071-4545 nhouston@usgs.gov","orcid":"https://orcid.org/0000-0002-6071-4545","contributorId":1682,"corporation":false,"usgs":true,"family":"Houston","given":"Natalie","email":"nhouston@usgs.gov","middleInitial":"A.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":565608,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thomas, Jonathan V. 0000-0003-0903-9713 jvthomas@usgs.gov","orcid":"https://orcid.org/0000-0003-0903-9713","contributorId":2194,"corporation":false,"usgs":true,"family":"Thomas","given":"Jonathan","email":"jvthomas@usgs.gov","middleInitial":"V.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":565609,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70148719,"text":"sim3336 - 2015 - Delineation of marsh types from Corpus Christi Bay, Texas, to Perdido Bay, Alabama, in 2010","interactions":[],"lastModifiedDate":"2015-07-24T09:00:02","indexId":"sim3336","displayToPublicDate":"2015-07-23T07:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3336","title":"Delineation of marsh types from Corpus Christi Bay, Texas, to Perdido Bay, Alabama, in 2010","docAbstract":"Coastal zone managers and researchers often require detailed information regarding emergent marsh vegetation types (that is, fresh, intermediate, brackish, and saline) for modeling habitat capacities and needs of marsh dependent taxa (such as waterfowl and alligator). Detailed information on the extent and distribution of emergent marsh vegetation types throughout the northern Gulf of Mexico coast has been historically unavailable. In response, the U.S. Geological Survey, in collaboration with the Gulf Coast Joint Venture, the University of Louisiana at Lafayette, Ducks Unlimited, Inc., and the Texas A&M University-Kingsville, produced a classification of emergent marsh vegetation types from Corpus Christi Bay, Texas, to Perdido Bay, Alabama.
\nThis study incorporates about 9,800 ground reference locations collected via helicopter surveys in coastal wetland areas. Decision-tree analyses were used to classify emergent marsh vegetation types by using ground reference data from helicopter vegetation surveys and independent variables such as multitemporal satellite-based multispectral imagery from 2009 to 2011, bare-earth digital elevation models based on airborne light detection and ranging (lidar), alternative contemporary land cover classifications, and other spatially explicit variables. Image objects were created from 2010 National Agriculture Imagery Program color-infrared aerial photography. The final classification is a 10-meter raster dataset that was produced by using a majority filter to classify image objects according to the marsh vegetation type covering the majority of each image object. The classification is dated 2010 because the year is both the midpoint of the classified multitemporal satellite-based imagery (2009–11) and the date of the high-resolution airborne imagery that was used to develop image objects. The seamless classification produced through this work can be used to help develop and refine conservation efforts for priority natural resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3336","collaboration":"Prepared in collaboration with the Gulf Coast Joint Venture, the University of Louisiana at Lafayette, Ducks Unlimited, Inc., and Texas A&M University-Kingsville","usgsCitation":"Enwright, N.M., Hartley, S.B., Couvillion, B.R., Brasher, M.G., Visser, J.M., Mitchell, M.K., Ballard, B.M., Parr, M.W., and Wilson, B.C., 2015, Delineation of marsh types from Corpus Christi Bay, Texas, to Perdido Bay, Alabama, in 2010: U.S. Geological Survey Scientific Investigations Map 3336, 1 sheet, scale 1:750,000, https://dx.doi.org/10.3133/sim3336.","productDescription":"Map: 52 x 38 inches; ReadMe; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064404","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":305863,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3336/coverthb.jpg"},{"id":305865,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3336/SIM_3336_Spatial_Data.zip","text":"Spatial Data"},{"id":305864,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3336/sim3336.pdf","text":"Map","size":"2.76 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3336"},{"id":305911,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3336/readME.txt","text":"ReadMe","size":"1.19 kB","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"Alabama, Louisiana, Mississippi, Texas","otherGeospatial":"Corpus Christi Bay, Perdido Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.80029296875,\n 26.941659545381516\n ],\n [\n -97.80029296875,\n 31.31610138349565\n ],\n [\n -87.34130859375,\n 31.31610138349565\n ],\n [\n -87.34130859375,\n 26.941659545381516\n ],\n [\n -97.80029296875,\n 26.941659545381516\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, National Wetlands Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506
http://www.nwrc.usgs.gov/
Surrogate measurements of suspended-sediment concentration (SSC) are increasingly used to provide continuous, high-resolution, and demonstrably accurate data at a reasonable cost. Densimetric data, calculated from the difference between two in situ pressure measurements, exploit variations in real-time streamflow densities to infer SSCs. Unlike other suspendedsediment surrogate technologies based on bulk or digital optics, laser, or hydroacoustics, the accuracy of SSC data estimated using the pressure-difference (also referred to as densimetric) surrogate technology theoretically improves with increasing SCCs. Coupled with streamflow data, continuous suspended-sediment discharges can be calculated using SSC data estimated in real-time using the densimetric technology.
The densimetric technology was evaluated at the Rio Puerco in New Mexico, a stream where SSC values regularly range from 10,000-200,000 milligrams per liter (mg/L) and have exceeded 500,000 mg/L. The constant-flow dual-orifice bubbler measures pressure using two precision pressure-transducer sensors at vertically aligned fixed locations in a water column. Water density is calculated from the temperature-compensated differential pressure and SSCs are inferred from the density data.
A linear regression model comparing density values to field-measured SSC values yielded an R² of 0.74. Although the application of the densimetric surrogate is likely limited to fluvial systems with SSCs larger than about 10,000 mg/L, based on this and previous studies, the densimetric technology fills a void for monitoring streams with high SSCs.
","conferenceTitle":"10th Federal Interagency Sedimentation Conference / 5th Federal Interagency Hydrologic Modeling Conference","conferenceDate":"April 19-23, 2015","conferenceLocation":"Reno, NV","language":"English","usgsCitation":"Brown, J.E., Gray, J.R., and Hornewer, N.J., 2015, In situ densimetric measurements as a surrogate for suspended-sediment concentrations in the Rio Puerco, New Mexico, 10th Federal Interagency Sedimentation Conference / 5th Federal Interagency Hydrologic Modeling Conference, Reno, NV, April 19-23, 2015, 12 p.","productDescription":"12 p.","ipdsId":"IP-062739","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":340963,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Rio Puerco","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.95965576171875,\n 34.39331222316112\n ],\n [\n -106.81182861328125,\n 34.39331222316112\n ],\n [\n -106.81182861328125,\n 36.11125252076156\n ],\n [\n -108.95965576171875,\n 36.11125252076156\n ],\n [\n -108.95965576171875,\n 34.39331222316112\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591183b5e4b0e541a03c1a60","contributors":{"authors":[{"text":"Brown, Jeb E. 0000-0001-7671-2379 jebbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-7671-2379","contributorId":4357,"corporation":false,"usgs":true,"family":"Brown","given":"Jeb","email":"jebbrown@usgs.gov","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":563972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gray, John R. 0000-0002-8817-3701 jrgray@usgs.gov","orcid":"https://orcid.org/0000-0002-8817-3701","contributorId":1158,"corporation":false,"usgs":true,"family":"Gray","given":"John","email":"jrgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true}],"preferred":true,"id":563973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hornewer, Nancy J. njhornew@usgs.gov","contributorId":910,"corporation":false,"usgs":true,"family":"Hornewer","given":"Nancy","email":"njhornew@usgs.gov","middleInitial":"J.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":563974,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70154961,"text":"70154961 - 2015 - Influence of hydrologic modifications on Fraxinus pennsylvanica in the Mississippi River Alluvial Valley, USA","interactions":[],"lastModifiedDate":"2015-09-28T11:01:38","indexId":"70154961","displayToPublicDate":"2015-07-22T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1170,"text":"Canadian Journal of Forest Research","active":true,"publicationSubtype":{"id":10}},"title":"Influence of hydrologic modifications on Fraxinus pennsylvanica in the Mississippi River Alluvial Valley, USA","docAbstract":"We used tree-ring analysis to examine radial growth response of a common, moderately flood-tolerant species (<i>Fraxinus pennsylvanica</i> Marshall) to hydrologic and climatic variability for > 40 years before and after hydrologic modifications affecting two forest stands in the Mississippi River Alluvial Valley (USA): a stand without levees below dams and a stand within a ring levee. At the stand without levees below dams, spring flood stages decreased and overall growth increased after dam construction, which we attribute to a reduction in flood stress. At the stand within a ring levee, growth responded to the elimination of overbank flooding by shifting from being positively correlated with river stage to not being correlated with river stage. In general, growth in swales was positively correlated with river stage and Palmer Drought Severity Index (an index of soil moisture) for longer periods than flats. Growth decreased after levee construction, but swales were less impacted than flats likely because of differences in elevation and soils provide higher soil moisture. Results of this study indicate that broad-scale hydrologic processes differ in their effects on the flood regime, and the effects on growth of moderately flood-tolerant species such as <i>F. pennsylvanica</i> can be mediated by local-scale factors such as topographic position, which affects soil moisture.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfr-2015-0138","usgsCitation":"Gee, H.K., King, S.L., and Keim, R., 2015, Influence of hydrologic modifications on Fraxinus pennsylvanica in the Mississippi River Alluvial Valley, USA: Canadian Journal of Forest Research, v. 45, no. 10, p. 1397-1406, https://doi.org/10.1139/cjfr-2015-0138.","productDescription":"10 p.","startPage":"1397","endPage":"1406","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050730","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":305884,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Bayou Cocodrie National Wildlife Refuge, White River National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.834716796875,\n 31.31610138349565\n ],\n [\n -91.834716796875,\n 31.73050322928437\n ],\n [\n -91.38153076171875,\n 31.73050322928437\n ],\n [\n -91.38153076171875,\n 31.31610138349565\n ],\n [\n -91.834716796875,\n 31.31610138349565\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.56005859375,\n 33.568861182555565\n ],\n [\n -91.56005859375,\n 34.298068350990846\n ],\n [\n -90.8349609375,\n 34.298068350990846\n ],\n [\n -90.8349609375,\n 33.568861182555565\n ],\n [\n -91.56005859375,\n 33.568861182555565\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"10","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55b0b0a2e4b09a3b01b53070","contributors":{"authors":[{"text":"Gee, Hugo K.W.","contributorId":140925,"corporation":false,"usgs":false,"family":"Gee","given":"Hugo","email":"","middleInitial":"K.W.","affiliations":[],"preferred":false,"id":565293,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":564412,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keim, Richard F.","contributorId":21858,"corporation":false,"usgs":true,"family":"Keim","given":"Richard F.","affiliations":[],"preferred":false,"id":565294,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70155946,"text":"70155946 - 2015 - Constraining the heat flux between Enceladus’ tiger stripes: numerical modeling of funiscular plains formation","interactions":[],"lastModifiedDate":"2015-08-13T13:08:12","indexId":"70155946","displayToPublicDate":"2015-07-22T03:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Constraining the heat flux between Enceladus’ tiger stripes: numerical modeling of funiscular plains formation","docAbstract":"The Cassini spacecraft’s Composite Infrared Spectrometer (CIRS) has observed at least 5 GW of thermal emission at Enceladus’ south pole. The vast majority of this emission is localized on the four long, parallel, evenly-spaced fractures dubbed tiger stripes. However, the thermal emission from regions between the tiger stripes has not been determined. These spatially localized regions have a unique morphology consisting of short-wavelength (∼1 km) ridges and troughs with topographic amplitudes of ∼100 m, and a generally ropy appearance that has led to them being referred to as “funiscular terrain.” Previous analysis pursued the hypothesis that the funiscular terrain formed via thin-skinned folding, analogous to that occurring on a pahoehoe flow top (Barr, A.C., Preuss, L.J. [2010]. Icarus 208, 499–503). Here we use finite element modeling of lithospheric shortening to further explore this hypothesis. Our best-case simulations reproduce funiscular-like morphologies, although our simulated fold wavelengths after 10% shortening are 30% longer than those observed. Reproducing short-wavelength folds requires high effective surface temperatures (∼185 K), an ice lithosphere (or high-viscosity layer) with a low thermal conductivity (one-half to one-third that of intact ice or lower), and very high heat fluxes (perhaps as great as 400 mW m−2). These conditions are driven by the requirement that the high-viscosity layer remain extremely thin (≲200 m). Whereas the required conditions are extreme, they can be met if a layer of fine grained plume material 1–10 m thick, or a highly fractured ice layer >50 m thick insulates the surface, and the lithosphere is fractured throughout as well. The source of the necessary heat flux (a factor of two greater than previous estimates) is less obvious. We also present evidence for an unusual color/spectral character of the ropy terrain, possibly related to its unique surface texture. Our simulations demonstrate that producing the funiscular ridges via folding remains plausible, but the relatively extreme conditions required to do so leaves their origin open to further investigation. The high heat fluxes required to produce the terrain by folding, which equate to an endogenic blackbody temperature near 50 K, should be observable by future nighttime CIRS observations, if funiscular deformation is occurring today.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2015.07.016","usgsCitation":"Bland, M.T., McKinnon, W., and Schenk, P., 2015, Constraining the heat flux between Enceladus’ tiger stripes: numerical modeling of funiscular plains formation: Icarus, v. 260, p. 232-245, https://doi.org/10.1016/j.icarus.2015.07.016.","productDescription":"14 p.","startPage":"232","endPage":"245","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064330","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":306655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Enceladus","volume":"260","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55cdbfaee4b08400b1fe13e0","contributors":{"authors":[{"text":"Bland, Michael T. 0000-0001-5543-1519 mbland@usgs.gov","orcid":"https://orcid.org/0000-0001-5543-1519","contributorId":146287,"corporation":false,"usgs":true,"family":"Bland","given":"Michael","email":"mbland@usgs.gov","middleInitial":"T.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":567309,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKinnon, William B.","contributorId":146288,"corporation":false,"usgs":false,"family":"McKinnon","given":"William B.","affiliations":[{"id":16661,"text":"Washington University in Saint Louis","active":true,"usgs":false}],"preferred":false,"id":567310,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schenk, Paul M.","contributorId":66946,"corporation":false,"usgs":false,"family":"Schenk","given":"Paul M.","affiliations":[{"id":12445,"text":"Lunar and Planetary Institute","active":true,"usgs":false}],"preferred":false,"id":567311,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70173510,"text":"70173510 - 2015 - Designing a monitoring program to estimate estuarine survival of anadromous salmon smolts: simulating the effect of sample design on inference","interactions":[],"lastModifiedDate":"2016-06-09T15:14:18","indexId":"70173510","displayToPublicDate":"2015-07-21T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Designing a monitoring program to estimate estuarine survival of anadromous salmon smolts: simulating the effect of sample design on inference","docAbstract":"A number of researchers have attempted to estimate salmonid smolt survival during outmigration through an estuary. However, it is currently unclear how the design of such studies influences the accuracy and precision of survival estimates. In this simulation study we consider four patterns of smolt survival probability in the estuary, and test the performance of several different sampling strategies for estimating estuarine survival assuming perfect detection. The four survival probability patterns each incorporate a systematic component (constant, linearly increasing, increasing and then decreasing, and two pulses) and a random component to reflect daily fluctuations in survival probability. Generally, spreading sampling effort (tagging) across the season resulted in more accurate estimates of survival. All sampling designs in this simulation tended to under-estimate the variation in the survival estimates because seasonal and daily variation in survival probability are not incorporated in the estimation procedure. This under-estimation results in poorer performance of estimates from larger samples. Thus, tagging more fish may not result in better estimates of survival if important components of variation are not accounted for. The results of our simulation incorporate survival probabilities and run distribution data from previous studies to help illustrate the tradeoffs among sampling strategies in terms of the number of tags needed and distribution of tagging effort. This information will assist researchers in developing improved monitoring programs and encourage discussion regarding issues that should be addressed prior to implementation of any telemetry-based monitoring plan. We believe implementation of an effective estuary survival monitoring program will strengthen the robustness of life cycle models used in recovery plans by providing missing data on where and how much mortality occurs in the riverine and estuarine portions of smolt migration. These data could result in better informed management decisions and assist in guidance for more effective estuarine restoration projects.
","language":"English","publisher":"PLOS one","doi":"10.1371/journal.pone.0132912","usgsCitation":"Romer, J.D., Gitelman, A.I., Clements, S., and Schreck, C.B., 2015, Designing a monitoring program to estimate estuarine survival of anadromous salmon smolts: simulating the effect of sample design on inference: PLoS ONE, 11 p., https://doi.org/10.1371/journal.pone.0132912.","productDescription":"11 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066437","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471935,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0132912","text":"Publisher Index Page"},{"id":323413,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-21","publicationStatus":"PW","scienceBaseUri":"575a9330e4b04f417c275131","contributors":{"authors":[{"text":"Romer, Jeremy D.","contributorId":171684,"corporation":false,"usgs":false,"family":"Romer","given":"Jeremy","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":638299,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gitelman, Alix I.","contributorId":168402,"corporation":false,"usgs":false,"family":"Gitelman","given":"Alix","email":"","middleInitial":"I.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":638300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clements, Shaun","contributorId":171685,"corporation":false,"usgs":false,"family":"Clements","given":"Shaun","email":"","affiliations":[],"preferred":false,"id":638301,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schreck, Carl B. 0000-0001-8347-1139 carl.schreck@usgs.gov","orcid":"https://orcid.org/0000-0001-8347-1139","contributorId":878,"corporation":false,"usgs":true,"family":"Schreck","given":"Carl","email":"carl.schreck@usgs.gov","middleInitial":"B.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":637222,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70147240,"text":"sir20155064 - 2015 - Flood-Inundation maps for the Hohokus Brook in Waldwick Borough, Ho-Ho-Kus Borough, and the Village of Ridgewood, New Jersey, 2014","interactions":[],"lastModifiedDate":"2015-07-20T10:37:04","indexId":"sir20155064","displayToPublicDate":"2015-07-20T11:15:00","publicationYear":"2015","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":"2015-5064","title":"Flood-Inundation maps for the Hohokus Brook in Waldwick Borough, Ho-Ho-Kus Borough, and the Village of Ridgewood, New Jersey, 2014","docAbstract":"Digital flood-inundation maps for a 6-mile reach of the Hohokus Brook in New Jersey from White's Lake Dam in Waldwick Borough, through Ho-Ho-Kus Borough to Grove Street in the Village of Ridgewood were created by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection. The flood inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Hohokus Brook at Ho-Ho-Kus, New Jersey (station number 01391000). Stage data at this streamgage may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/nwis/uv?site_no=01391000 or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http://water.weather.gov/ahps2/hydrograph.php?gage=hohn4&wfo=okx.
\nFlood profiles were simulated for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated using the most current stage-discharge relation at the Hohokus Brook at Ho-Ho-Kus, New Jersey, streamgage (station number 01391000). The hydraulic model was then used to compute 12 water-surface profiles for flood stages at 0.5-foot (ft) intervals referenced to the streamgage datum and ranging from 2.5 ft, the NWS “action stage” or near bankfull, to 8.0 ft, which exceeds the stage that corresponds to the maximum recorded peak flow (7.32 ft) and is the extent of the current stage-discharge relation for the streamgage. The simulated water-surface profiles were then combined with a geographic information system 3-meter (9.84 ft) digital elevation model [derived from light detection and ranging (lidar) data] to delineate the area flooded at each water level.
\nThe availability of these maps along with information on the Internet regarding current stage from the USGS streamgage will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155064","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Watson, K.M., and Niemoczynski, M.J., 2015, Flood-Inundation maps for the Hohokus Brook in Waldwick Borough, Ho-Ho-Kus Borough, and the Village of Ridgewood, New Jersey, 2014: U.S. Geological Survey Scientific Investigations Report 2015–5064, 12 p., https://dx.doi.org/10.3133/sir20155064.","productDescription":"v, 12 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053102","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":305705,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5064/coverthb.jpg"},{"id":305706,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5064/sir20155064.pdf","text":"Report","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5064"},{"id":305707,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2015/5064/downloads/depth_raster/","text":"Depth_Raster","size":"112 MB","description":"XML, ovr, adf, and Other Files"},{"id":305708,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2015/5064/downloads/KML/","text":"KML","size":"116 KB","description":"KMZ"},{"id":305709,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2015/5064/downloads/readme.txt","text":"Readme","size":"9.72 KB","linkFileType":{"id":2,"text":"txt"},"description":"Readme"},{"id":305710,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2015/5064/downloads/water_surface_final/","text":"Water Data","size":"1.43 MB","linkFileType":{"id":4,"text":"shapefile"},"description":"Water Surface"}],"country":"United States","state":"New Jersey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.09042358398438,\n 40.86627605595889\n ],\n [\n -74.09042358398438,\n 40.914550362677204\n ],\n [\n -74.01592254638672,\n 40.914550362677204\n ],\n [\n -74.01592254638672,\n 40.86627605595889\n ],\n [\n -74.09042358398438,\n 40.86627605595889\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
http://nj.usgs.gov/
","tableOfContents":"
In August of 2013, the U.S. Geological Survey conducted a geophysical survey offshore of Petit Bois Island, Mississippi. This effort was part of the U.S. Geological Survey Gulf of Mexico Science Coordination partnership with the U.S. Army Corps of Engineers to assist the Mississippi Coastal Improvements Program and the Northern Gulf of Mexico Ecosystem Change and Hazards Susceptibility Project, by mapping the shallow geologic stratigraphic framework of the Mississippi Barrier Island Complex.
\nThis geophysical survey will provide additional data necessary for scientists to define, interpret, and provide baseline bathymetry and seafloor habitat for this area, and to aid scientists in predicting future geomorphological changes of the islands with respect to climate change, storm impact, and sea-level rise. Furthermore, these data will provide information for barrier island restoration, particularly in Camille Cut, and protection for the historical Fort Massachusetts on Ship Island, Mississippi.
\nThe geophysical data were collected during one cruise (USGS Field Activity Numbers 13CCT04) aboard the Research Vessel Tommy Munro offshore along the gulf side of Petit Bois Island, Gulf Islands National Seashore, Mississippi. Data were acquired with the following equipment: a Systems Engineering and Assessment, Ltd., SWATHplus interferometric sonar (468 kilohertz (kHz)), an EdgeTech 424 (4-24 kHz), an EdgeTech 525i chirp subbottom profiling system, and a Klein 3900 sidescan sonar system.
\nThis report serves as an archive of the processed interferometric swath bathymetry and sidescan sonar data. Geographic information system data products include an interpolated digital elevation model, an acoustic backscatter mosaic, trackline maps, and point data files. Additional files include error analysis maps, Field Activity Collection System logs, and formal Federal Geographic Data Committee metadata.
\nNOTE: These data are scientific in nature and are not to be used for navigation. Any use of trade names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds917","usgsCitation":"DeWitt, N.T., Flocks, J.G., Kindinger, J.L., Bernier, J., Kelso, K.W., Wiese, D.S., Finlayson, D.P., and Pfeiffer, W.R., 2015, Archive of Sidescan Sonar and Swath Bathymetry Data Collected During USGS Cruise 13CCT04 Offshore of Petit Bois Island, Gulf Islands National Seashore, Mississippi, August 2013: U.S. Geological Survey Data Series 917, HTML Document, https://doi.org/10.3133/ds917.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-058072","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science 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-88.50517272949219,\n 30.217690185142587\n ],\n [\n -88.51066589355469,\n 30.217393512825158\n ],\n [\n -88.50980758666992,\n 30.21353669128429\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7eee2e4b0bc0bec09ed8a","contributors":{"authors":[{"text":"DeWitt, Nancy T. 0000-0002-2419-4087 ndewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-2419-4087","contributorId":4095,"corporation":false,"usgs":true,"family":"DeWitt","given":"Nancy","email":"ndewitt@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":539459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flocks, James G. 0000-0002-6177-7433 jflocks@usgs.gov","orcid":"https://orcid.org/0000-0002-6177-7433","contributorId":816,"corporation":false,"usgs":true,"family":"Flocks","given":"James","email":"jflocks@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":539460,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kindinger, Jack L. jkindinger@usgs.gov","contributorId":815,"corporation":false,"usgs":true,"family":"Kindinger","given":"Jack","email":"jkindinger@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":539461,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bernier, Julie 0000-0002-9918-5353 jbernier@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-5353","contributorId":3549,"corporation":false,"usgs":true,"family":"Bernier","given":"Julie","email":"jbernier@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":539462,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelso, Kyle W. 0000-0003-0615-242X kkelso@usgs.gov","orcid":"https://orcid.org/0000-0003-0615-242X","contributorId":4307,"corporation":false,"usgs":true,"family":"Kelso","given":"Kyle","email":"kkelso@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":539463,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wiese, Dana S. dwiese@usgs.gov","contributorId":2476,"corporation":false,"usgs":true,"family":"Wiese","given":"Dana","email":"dwiese@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":539464,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Finlayson, David P. dfinlayson@usgs.gov","contributorId":1381,"corporation":false,"usgs":true,"family":"Finlayson","given":"David","email":"dfinlayson@usgs.gov","middleInitial":"P.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":539465,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pfeiffer, William R. wpfeiffer@usgs.gov","contributorId":3725,"corporation":false,"usgs":true,"family":"Pfeiffer","given":"William","email":"wpfeiffer@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":539466,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70156716,"text":"70156716 - 2015 - Topography and climate are more important drivers of long-term, post-fire vegetation assembly than time-since-fire in the Sonoran Desert, US","interactions":[],"lastModifiedDate":"2015-10-19T12:30:29","indexId":"70156716","displayToPublicDate":"2015-07-18T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2490,"text":"Journal of Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Topography and climate are more important drivers of long-term, post-fire vegetation assembly than time-since-fire in the Sonoran Desert, US","docAbstract":"Questions
\nDo abiotic environmental filters or time-since-fire (TSF) explain more variability in post-fire vegetation assembly? Do these influences vary between vegetation structure and composition, and across spatial scales?
\nLocation
\nSonoran Desert of southwestern Arizona, US.
\nMethods
\nWe measured perennial vegetation in a chronosequence of 13 fires (8-33 yr TSF) spanning a broad regional gradient. The relative influence of environmental filters (topography and climate) and TSF were compared as predictors of long-term, post-fire vegetation assembly. Analyses considered different measures of vegetation structure (cover, height and density) and scales of community organization (species composition, structure and landscape).
\nResults
\nSpecies and growth form composition did not exhibit directional responses with increasing TSF, but sorted along abiotic gradients. Differences in vegetation cover and height between burned and unburned control areas were attributed primarily to gradients of topography and climate. In contrast, vegetation density initially increased in burned areas but declined to pre-burn levels with increasing TSF. The strongest predictors of landscape-scale recovery of vegetation cover, height and density were elevation, post-fire precipitation and average annual precipitation, respectively. Recovery of vegetation height was positively correlated with precipitation in the first year following fire, suggesting that abiotic conditions of the immediate post-fire environment may drive long-term variability in vegetation structure.
\nConclusions
\nWe find substantial evidence that environmental filters, rather than TSF, drive the majority of variability in long-term, post-fire vegetation assembly within the Sonoran Desert. Careful consideration of spatial variability in abiotic conditions may benefit post-fire vegetation modelling, as well as fire management and restoration strategies.
","language":"English","publisher":"International Association for Vegetation Science","publisherLocation":"Uppsala, Sweden","doi":"10.1111/jvs.12324","usgsCitation":"Shryock, D.F., Esque, T., and Chen, F.C., 2015, Topography and climate are more important drivers of long-term, post-fire vegetation assembly than time-since-fire in the Sonoran Desert, US: Journal of Vegetation Science, v. 26, no. 6, p. 1134-1147, https://doi.org/10.1111/jvs.12324.","productDescription":"14 p.","startPage":"1134","endPage":"1147","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062961","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":307830,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"6","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-18","publicationStatus":"PW","scienceBaseUri":"560bb70ee4b058f706e53f40","chorus":{"doi":"10.1111/jvs.12324","url":"http://dx.doi.org/10.1111/jvs.12324","publisher":"Wiley-Blackwell","authors":"Shryock Daniel F., Esque Todd C., Chen Felicia C.","journalName":"Journal of Vegetation Science","publicationDate":"7/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Shryock, Daniel F. dshryock@usgs.gov","contributorId":5139,"corporation":false,"usgs":true,"family":"Shryock","given":"Daniel","email":"dshryock@usgs.gov","middleInitial":"F.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":570229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esque, Todd C. tesque@usgs.gov","contributorId":145679,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":570228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chen, Felicia C. 0000-0002-7408-5946 fchen@usgs.gov","orcid":"https://orcid.org/0000-0002-7408-5946","contributorId":140025,"corporation":false,"usgs":true,"family":"Chen","given":"Felicia","email":"fchen@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":570230,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70155511,"text":"70155511 - 2015 - Pore-pressure sensitivities to dynamic strains: observations in active tectonic regions","interactions":[],"lastModifiedDate":"2015-09-28T11:12:18","indexId":"70155511","displayToPublicDate":"2015-07-17T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Pore-pressure sensitivities to dynamic strains: observations in active tectonic regions","docAbstract":"Triggered seismicity arising from dynamic stresses is often explained by the Mohr-Coulomb failure criterion, where elevated pore pressures reduce the effective strength of faults in fluid-saturated rock. The seismic response of a fluid-rock system naturally depends on its hydro-mechanical properties, but accurately assessing how pore-fluid pressure responds to applied stress over large scales in situ remains a challenging task; hence, spatial variations in response are not well understood, especially around active faults. Here I analyze previously unutilized records of dynamic strain and pore-pressure from regional and teleseismic earthquakes at Plate Boundary Observatory (PBO) stations from 2006 through 2012 to investigate variations in response along the Pacific/North American tectonic plate boundary. I find robust scaling-response coefficients between excess pore pressure and dynamic strain at each station that are spatially correlated: around the San Andreas and San Jacinto fault systems, the response is lowest in regions of the crust undergoing the highest rates of secular shear strain. PBO stations in the Parkfield instrument cluster are at comparable distances to the San Andreas fault (SAF), and spatial variations there follow patterns in dextral creep rates along the fault, with the highest response in the actively creeping section, which is consistent with a narrowing zone of strain accumulation seen in geodetic velocity profiles. At stations in the San Juan Bautista (SJB) and Anza instrument clusters, the response depends non-linearly on the inverse fault-perpendicular distance, with the response decreasing towards the fault; the SJB cluster is at the northern transition from creeping-to-locked behavior along the SAF, where creep rates are at moderate to low levels, and the Anza cluster is around the San Jacinto fault, where to date there have been no statistically significant creep rates observed at the surface. These results suggest that the strength of the pore pressure response in fluid-saturated rock near active faults is controlled by shear strain accumulation associated with tectonic loading, which implies a strong feedback between fault strength and permeability: dynamic triggering susceptibilities may vary in space and also in time.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Richmond, VA","doi":"10.1002/2015JB012201","usgsCitation":"Barbour, A., 2015, Pore-pressure sensitivities to dynamic strains: observations in active tectonic regions: Journal of Geophysical Research B: Solid Earth, v. 120, no. 8, p. 5863-5883, https://doi.org/10.1002/2015JB012201.","productDescription":"21 p.","startPage":"5863","endPage":"5883","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062248","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":471937,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb012201","text":"Publisher Index Page"},{"id":306526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-18","publicationStatus":"PW","scienceBaseUri":"55c9cb37e4b08400b1fdb720","contributors":{"authors":[{"text":"Barbour, Andrew J. 0000-0002-6890-2452 abarbour@usgs.gov","orcid":"https://orcid.org/0000-0002-6890-2452","contributorId":140443,"corporation":false,"usgs":true,"family":"Barbour","given":"Andrew J.","email":"abarbour@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":565621,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70148547,"text":"sir20155083 - 2015 - Simulation of groundwater flow and chloride transport in the “1,200-foot” sand with scenarios to mitigate saltwater migration in the “2,000-foot” sand in the Baton Rouge area, Louisiana","interactions":[],"lastModifiedDate":"2015-09-17T09:38:10","indexId":"sir20155083","displayToPublicDate":"2015-07-16T14:30:00","publicationYear":"2015","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":"2015-5083","title":"Simulation of groundwater flow and chloride transport in the “1,200-foot” sand with scenarios to mitigate saltwater migration in the “2,000-foot” sand in the Baton Rouge area, Louisiana","docAbstract":"Groundwater withdrawals have caused saltwater to encroach into freshwater-bearing aquifers beneath Baton Rouge, Louisiana. The 10 aquifers beneath the Baton Rouge area, which includes East and West Baton Rouge Parishes, Pointe Coupee Parish, and East and West Feliciana Parishes, provided about 184.3 million gallons per day (Mgal/d) for public supply and industrial use in 2012. Groundwater withdrawals from the “1,200-foot” sand in East Baton Rouge Parish have caused water-level drawdown as large as 177 feet (ft) north of the Baton Rouge Fault and limited saltwater encroachment from south of the fault. The recently developed groundwater model for simulating transport in the “2,000-foot” sand was rediscretized to also enable transport simulation within the “1,200-foot” sand and was updated with groundwater withdrawal data through 2012. The model was recalibrated to water-level observation data through 2012 with the parameter-estimation code PEST and calibrated to observed chloride concentrations at observation wells within the “1,200-foot” sand and “2,000-foot” sand. The model is designed to evaluate strategies to control saltwater migration, including changes in the distribution of groundwater withdrawals and installation of scavenger wells to intercept saltwater before it reaches existing production wells.
\nSeven hypothetical scenarios predict the effects of different groundwater withdrawal options on groundwater levels and the transport of chloride within the “1,200-foot” sand and the “2,000-foot” sand during 2015–2112. The predicted water levels and concentrations for all scenarios are depicted in maps for the years 2047 and 2112. The first scenario is a base case for comparison to the six other scenarios and simulates continuation of 2012 reported groundwater withdrawals through 2112 (100 years). The second scenario that simulates increased withdrawals from industrial wells in the “1,200-foot” sand predicts that water levels will be 12–25 ft lower by 2047 and that there will be a negligible difference in chloride concentrations within the “1,200-foot” sand. The five other scenarios simulate the effects of various withdrawal schemes on water levels and chloride concentrations within the “2,000-foot” sand. Amongst these five other scenarios, three of the scenarios simulate only various withdrawal reductions, whereas the two others also incorporate withdrawals from a scavenger well that is designed to extract salty water from the base of the “2,000-foot” sand. Two alternative pumping rates (2.5 Mgal/d and 1.25 Mgal/d) are simulated in each of the scavenger-well scenarios. For the “2,000-foot” sand scenarios, comparison of the predicted effects of the scenarios is facilitated by graphs of predicted chloride concentrations through time at selected observation wells, plots of salt mass in the aquifer through time, and a summary of the predicted plume area and average concentration. In all scenarios, water levels essentially equilibrate by 2047, after 30 years of simulated constant withdrawal rates. Although predicted water-level recovery within the “2,000-foot” sand is greatest for the scenario with the greatest reduction in groundwater withdrawal from that aquifer, the scavenger-well scenarios are most effective in mitigating the future extent and concentration of the chloride plume. The simulated scavenger-well withdrawal rate has more influence on the plume area and concentration than do differences among the scenarios in industrial and public-supply withdrawal rates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155083","collaboration":"Prepared in cooperation with the Capital Area Groundwater Conservation Commission; the Louisiana Department of Transportation and Development, Public Works and Water Resources Division; and the City of Baton Rouge and Parish of East Baton Rouge","usgsCitation":"Heywood, C.E., Lovelace, J.K., and Griffith, J.M., 2015, Simulation of groundwater flow and chloride transport in the “1,200-foot” sand with scenarios to mitigate saltwater migration in the “2,000-foot” sand in the Baton Rouge area, Louisiana (ver. 1.1, September 2015): U.S. Geological Survey Scientific Investigations Report 2015–5083, 69 p.,\nhttps://dx.doi.org/10.3133/sir20155083.","productDescription":"xi, 69 p.","numberOfPages":"85","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060614","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":308118,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2015/5083/versionHist.txt","text":"Version History","size":"1 kB","linkFileType":{"id":2,"text":"txt"}},{"id":305784,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5083/coverthb.jpg"},{"id":305785,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5083/sir20155083.pdf","text":"Report","size":"17.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5083 ver1.1"}],"country":"United States","state":"Louisiana, Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.318115234375,\n 30.372875188118016\n ],\n [\n -92.318115234375,\n 31.44741029142872\n ],\n [\n -90.52734374999999,\n 31.44741029142872\n ],\n [\n -90.52734374999999,\n 30.372875188118016\n ],\n [\n -92.318115234375,\n 30.372875188118016\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted July 16, 2015; Version 1.1: September 14, 2015","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
3535 S. Sherwood Forest Blvd., Suite 120
Baton Rouge, LA 70816
http://la.water.usgs.gov/
Morphodynamic data assimilation blends observations with model predictions and comes in many forms, including linear regression, Kalman filter, brute-force parameter estimation, variational assimilation, and Bayesian analysis. Importantly, data assimilation can be used to identify sources of prediction errors that lead to improved fundamental understanding. Overall, models incorporating data assimilation yield better information to the people who must make decisions impacting safety and wellbeing in coastal regions that experience hazards due to storms, sea-level rise, and erosion. We present examples of data assimilation associated with morphologic change. We conclude that enough morphodynamic predictive capability is available now to be useful to people, and that we will increase our understanding and the level of detail of our predictions through assimilation of observations and numerical-statistical models.
","conferenceTitle":"Coastal Sediments 2015","conferenceDate":"May 11-15, 2015","conferenceLocation":"San Diego, CA","language":"English","publisher":"World Scientific Publishing Company","doi":"10.1142/9789814689977_0244","usgsCitation":"Plant, N.G., and Long, J.W., 2015, Morphodynamic data assimilation used to understand changing coasts, Coastal Sediments 2015, San Diego, CA, May 11-15, 2015, https://doi.org/10.1142/9789814689977_0244.","ipdsId":"IP-063044","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":342088,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-15","publicationStatus":"PW","scienceBaseUri":"59366dabe4b0f6c2d0d7d636","contributors":{"authors":[{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":547977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Joseph W. 0000-0003-2912-1992 jwlong@usgs.gov","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":3303,"corporation":false,"usgs":true,"family":"Long","given":"Joseph","email":"jwlong@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":547978,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70190039,"text":"70190039 - 2015 - A long-term earthquake rate model for the central and eastern United States from smoothed seismicity","interactions":[],"lastModifiedDate":"2017-08-06T16:15:26","indexId":"70190039","displayToPublicDate":"2015-07-16T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"A long-term earthquake rate model for the central and eastern United States from smoothed seismicity","docAbstract":"I present a long-term earthquake rate model for the central and eastern United States from adaptive smoothed seismicity. By employing pseudoprospective likelihood testing (L-test), I examined the effects of fixed and adaptive smoothing methods and the effects of catalog duration and composition on the ability of the models to forecast the spatial distribution of recent earthquakes. To stabilize the adaptive smoothing method for regions of low seismicity, I introduced minor modifications to the way that the adaptive smoothing distances are calculated. Across all smoothed seismicity models, the use of adaptive smoothing and the use of earthquakes from the recent part of the catalog optimizes the likelihood for tests with M≥2.7 and M≥4.0 earthquake catalogs. The smoothed seismicity models optimized by likelihood testing with M≥2.7 catalogs also produce the highest likelihood values for M≥4.0 likelihood testing, thus substantiating the hypothesis that the locations of moderate-size earthquakes can be forecast by the locations of smaller earthquakes. The likelihood test does not, however, maximize the fraction of earthquakes that are better forecast than a seismicity rate model with uniform rates in all cells. In this regard, fixed smoothing models perform better than adaptive smoothing models. The preferred model of this study is the adaptive smoothed seismicity model, based on its ability to maximize the joint likelihood of predicting the locations of recent small-to-moderate-size earthquakes across eastern North America. The preferred rate model delineates 12 regions where the annual rate of M≥5 earthquakes exceeds 2×10−3. Although these seismic regions have been previously recognized, the preferred forecasts are more spatially concentrated than the rates from fixed smoothed seismicity models, with rate increases of up to a factor of 10 near clusters of high seismic activity.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120140370","usgsCitation":"Moschetti, M.P., 2015, A long-term earthquake rate model for the central and eastern United States from smoothed seismicity: Bulletin of the Seismological Society of America, v. 6, no. 105, p. 2928-2941, https://doi.org/10.1785/0120140370.","productDescription":"14 p.","startPage":"2928","endPage":"2941","ipdsId":"IP-065608","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":344605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"105","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-10","publicationStatus":"PW","scienceBaseUri":"59882a95e4b05ba66e9ffddc","contributors":{"authors":[{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":707282,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70190124,"text":"70190124 - 2015 - Coevolution of bed surface patchiness and channel morphology: 1. Mechanisms of forced patch formation","interactions":[],"lastModifiedDate":"2017-08-12T08:27:05","indexId":"70190124","displayToPublicDate":"2015-07-16T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Coevolution of bed surface patchiness and channel morphology: 1. Mechanisms of forced patch formation","docAbstract":"Riverbeds frequently display a spatial structure where the sediment mixture composing the channel bed has been sorted into discrete patches of similar grain size. Even though patches are a fundamental feature in gravel bed rivers, we have little understanding of how patches form, evolve, and interact. Here we present a two-dimensional morphodynamic model that is used to examine in greater detail the mechanisms responsible for the development of forced bed surface patches and the coevolution of bed morphology and bed surface patchiness. The model computes the depth-averaged channel hydrodynamics, mixed-grain-size sediment transport, and bed evolution by coupling the river morphodynamic model Flow and Sediment Transport with Morphological Evolution of Channels (FaSTMECH) with a transport relation for gravel mixtures and the mixed-grain-size Exner equation using the active layer assumption. To test the model, we use it to simulate a flume experiment in which the bed developed a sequence of alternate bars and temporally and spatially persistent forced patches with a general pattern of coarse bar tops and fine pools. Cross-stream sediment flux causes sediment to be exported off of bars and imported into pools at a rate that balances downstream gradients in the streamwise sediment transport rate, allowing quasi-steady bar-pool topography to persist. The relative importance of lateral gravitational forces on the cross-stream component of sediment transport is a primary control on the amplitude of the bars. Because boundary shear stress declines as flow shoals over the bars, the lateral sediment transport is increasingly size selective and leads to the development of coarse bar tops and fine pools.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014JF003428","usgsCitation":"Nelson, P.A., McDonald, R.R., Nelson, J.M., and Dietrich, W.E., 2015, Coevolution of bed surface patchiness and channel morphology: 1. Mechanisms of forced patch formation: Journal of Geophysical Research F: Earth Surface, v. 120, no. 9, p. 1687-1707, https://doi.org/10.1002/2014JF003428.","productDescription":"21 p.","startPage":"1687","endPage":"1707","ipdsId":"IP-065143","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471938,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014jf003428","text":"Publisher Index Page"},{"id":344778,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-07","publicationStatus":"PW","scienceBaseUri":"59901399e4b09fa1cb17892b","contributors":{"authors":[{"text":"Nelson, Peter A.","contributorId":195598,"corporation":false,"usgs":false,"family":"Nelson","given":"Peter","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":707579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McDonald, Richard R. 0000-0002-0703-0638 rmcd@usgs.gov","orcid":"https://orcid.org/0000-0002-0703-0638","contributorId":2428,"corporation":false,"usgs":true,"family":"McDonald","given":"Richard","email":"rmcd@usgs.gov","middleInitial":"R.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":707578,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":707580,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dietrich, William E.","contributorId":195599,"corporation":false,"usgs":false,"family":"Dietrich","given":"William","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":707581,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188564,"text":"70188564 - 2015 - Can low-resolution airborne laser scanning data be used to model stream rating curves?","interactions":[],"lastModifiedDate":"2017-06-15T13:23:12","indexId":"70188564","displayToPublicDate":"2015-07-16T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Can low-resolution airborne laser scanning data be used to model stream rating curves?","docAbstract":"This pilot study explores the potential of using low-resolution (0.2 points/m2) airborne laser scanning (ALS)-derived elevation data to model stream rating curves. Rating curves, which allow the functional translation of stream water depth into discharge, making them integral to water resource monitoring efforts, were modeled using a physics-based approach that captures basic geometric measurements to establish flow resistance due to implicit channel roughness. We tested synthetically thinned high-resolution (more than 2 points/m2) ALS data as a proxy for low-resolution data at a point density equivalent to that obtained within most national-scale ALS strategies. Our results show that the errors incurred due to the effect of low-resolution versus high-resolution ALS data were less than those due to flow measurement and empirical rating curve fitting uncertainties. As such, although there likely are scale and technical limitations to consider, it is theoretically possible to generate rating curves in a river network from ALS data of the resolution anticipated within national-scale ALS schemes (at least for rivers with relatively simple geometries). This is promising, since generating rating curves from ALS scans would greatly enhance our ability to monitor streamflow by simplifying the overall effort required.
","language":"English","publisher":"MDPI","doi":"10.3390/w7041324","usgsCitation":"Lyon, S., Nathanson, M., Lam, N., Dahlke, H., Rutzinger, M., Kean, J.W., and Laudon, H., 2015, Can low-resolution airborne laser scanning data be used to model stream rating curves?: Water, v. 7, no. 4, p. 1324-1339, https://doi.org/10.3390/w7041324.","productDescription":"16 p.","startPage":"1324","endPage":"1339","ipdsId":"IP-063479","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471940,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w7041324","text":"Publisher Index Page"},{"id":342554,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Sweden","otherGeospatial":"Krycklan catchment","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 19.566650390625,\n 63.83340220990062\n ],\n [\n 20.6927490234375,\n 63.83340220990062\n ],\n [\n 20.6927490234375,\n 64.36724945936612\n ],\n [\n 19.566650390625,\n 64.36724945936612\n ],\n [\n 19.566650390625,\n 63.83340220990062\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-24","publicationStatus":"PW","scienceBaseUri":"59439c95e4b062508e31a9ce","contributors":{"authors":[{"text":"Lyon, Steve","contributorId":192971,"corporation":false,"usgs":false,"family":"Lyon","given":"Steve","affiliations":[],"preferred":false,"id":698353,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nathanson, Marcus","contributorId":192972,"corporation":false,"usgs":false,"family":"Nathanson","given":"Marcus","email":"","affiliations":[],"preferred":false,"id":698354,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lam, Norris","contributorId":192973,"corporation":false,"usgs":false,"family":"Lam","given":"Norris","email":"","affiliations":[],"preferred":false,"id":698355,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dahlke, Helen","contributorId":192974,"corporation":false,"usgs":false,"family":"Dahlke","given":"Helen","email":"","affiliations":[],"preferred":false,"id":698356,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rutzinger, Martin","contributorId":192975,"corporation":false,"usgs":false,"family":"Rutzinger","given":"Martin","email":"","affiliations":[],"preferred":false,"id":698357,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":698358,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Laudon, Hjalmar","contributorId":192976,"corporation":false,"usgs":false,"family":"Laudon","given":"Hjalmar","email":"","affiliations":[],"preferred":false,"id":698359,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70190035,"text":"70190035 - 2015 - Aftershock collapse vulnerability assessment of reinforced concrete frame structures","interactions":[],"lastModifiedDate":"2017-08-06T16:23:16","indexId":"70190035","displayToPublicDate":"2015-07-16T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1434,"text":"Earthquake Engineering and Structural Dynamics","active":true,"publicationSubtype":{"id":10}},"title":"Aftershock collapse vulnerability assessment of reinforced concrete frame structures","docAbstract":"In a seismically active region, structures may be subjected to multiple earthquakes, due to mainshock–aftershock phenomena or other sequences, leaving no time for repair or retrofit between the events. This study quantifies the aftershock vulnerability of four modern ductile reinforced concrete (RC) framed buildings in California by conducting incremental dynamic analysis of nonlinear MDOF analytical models. Based on the nonlinear dynamic analysis results, collapse and damage fragility curves are generated for intact and damaged buildings. If the building is not severely damaged in the mainshock, its collapse capacity is unaffected in the aftershock. However, if the building is extensively damaged in the mainshock, there is a significant reduction in its collapse capacity in the aftershock. For example, if an RC frame experiences 4% or more interstory drift in the mainshock, the median capacity to resist aftershock shaking is reduced by about 40%. The study also evaluates the effectiveness of different measures of physical damage observed in the mainshock-damaged buildings for predicting the reduction in collapse capacity of the damaged building in subsequent aftershocks. These physical damage indicators for the building are chosen such that they quantify the qualitative red tagging (unsafe for occupation) criteria employed in post-earthquake evaluation of RC frames. The results indicated that damage indicators related to the drift experienced by the damaged building best predicted the reduced aftershock collapse capacities for these ductile structures.
","language":"English","publisher":"International Association for Earthquake Engineering","doi":"10.1002/eqe.2478","usgsCitation":"Raghunandan, M., Liel, A.B., and Luco, N., 2015, Aftershock collapse vulnerability assessment of reinforced concrete frame structures: Earthquake Engineering and Structural Dynamics, v. 44, no. 3, p. 419-439, https://doi.org/10.1002/eqe.2478.","productDescription":"21 p.","startPage":"419","endPage":"439","ipdsId":"IP-060643","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":344607,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-04","publicationStatus":"PW","scienceBaseUri":"59882a96e4b05ba66e9ffdde","contributors":{"authors":[{"text":"Raghunandan, Meera","contributorId":184157,"corporation":false,"usgs":false,"family":"Raghunandan","given":"Meera","email":"","affiliations":[],"preferred":false,"id":707266,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liel, Abbie B.","contributorId":184158,"corporation":false,"usgs":false,"family":"Liel","given":"Abbie","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":707267,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":707265,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188815,"text":"70188815 - 2015 - Himalayan gneiss dome formation in the middle crust and exhumation by normal faulting: New geochronology of Gianbul dome, northwestern India","interactions":[],"lastModifiedDate":"2017-06-26T09:40:13","indexId":"70188815","displayToPublicDate":"2015-07-16T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Himalayan gneiss dome formation in the middle crust and exhumation by normal faulting: New geochronology of Gianbul dome, northwestern India","docAbstract":"A general lack of consensus about the origin of Himalayan gneiss domes hinders accurate thermomechanical modeling of the orogen. To test whether doming resulted from tectonic contraction (e.g., thrust duplex formation, antiformal bending above a thrust ramp, etc.), channel flow, or via the buoyant rise of anatectic melts, this study investigates the depth and timing of doming processes for Gianbul dome in the western Himalaya. The dome is composed of Greater Himalayan Sequence migmatite, Paleozoic orthogneiss, and metasedimentary rock cut by multiple generations of leucogranite dikes. These rocks record a major penetrative D2 deformational event characterized by a domed foliation and associated NE-SW–trending stretching lineation, and they are flanked by the top-down-to-the-SW (normal-sense) Khanjar shear zone and the top-down-to-the-NE (normal sense) Zanskar shear zone (the western equivalent of the South Tibetan detachment system). Monazite U/Th-Pb geochronology records (1) Paleozoic emplacement of the Kade orthogneiss and associated granite dikes; (2) prograde Barrovian metamorphism from 37 to 33 Ma; (3) doming driven by upper-crustal extension and positive buoyancy of decompression melts between 26 and 22 Ma; and (4) the injection of anatectic melts into the upper levels of the dome—neutralizing the effects of melt buoyancy and potentially adding strength to the host rock—by ca. 22.6 Ma on the southwestern flank and ca. 21 Ma on the northeastern flank. As shown by a northeastward decrease in 40Ar/39Ar muscovite dates from 22.4 to 20.2 Ma, ductile normal-sense displacement within the Zanskar shear zone ended by ca. 22 Ma, after which the Gianbul dome was exhumed as part of a rigid footwall block below the brittle Zanskar normal fault, tilting an estimated 5°–10°SW into its present orientation.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B31005.1","usgsCitation":"Horton, F., Lee, J., Hacker, B., Bowman-Kamaha’o, M., and Cosca, M.A., 2015, Himalayan gneiss dome formation in the middle crust and exhumation by normal faulting: New geochronology of Gianbul dome, northwestern India: Geological Society of America Bulletin, v. 127, no. 1-2, p. 162-180, https://doi.org/10.1130/B31005.1.","productDescription":"19 p.","startPage":"162","endPage":"180","ipdsId":"IP-056131","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":342852,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India","otherGeospatial":"Gianbul dome","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 74,\n 30.25\n ],\n [\n 79,\n 30.25\n ],\n [\n 79,\n 36.33333\n ],\n [\n 74,\n 36.33333\n ],\n [\n 74,\n 30.25\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"127","issue":"1-2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-07-16","publicationStatus":"PW","scienceBaseUri":"59521d21e4b062508e3c368d","contributors":{"authors":[{"text":"Horton, Forrest","contributorId":193436,"corporation":false,"usgs":false,"family":"Horton","given":"Forrest","email":"","affiliations":[],"preferred":false,"id":700468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Jeffrey","contributorId":193437,"corporation":false,"usgs":false,"family":"Lee","given":"Jeffrey","email":"","affiliations":[],"preferred":false,"id":700469,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hacker, Bradley","contributorId":193438,"corporation":false,"usgs":false,"family":"Hacker","given":"Bradley","affiliations":[],"preferred":false,"id":700470,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bowman-Kamaha’o, Meilani","contributorId":193439,"corporation":false,"usgs":false,"family":"Bowman-Kamaha’o","given":"Meilani","email":"","affiliations":[],"preferred":false,"id":700471,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cosca, Michael A. 0000-0002-0600-7663 mcosca@usgs.gov","orcid":"https://orcid.org/0000-0002-0600-7663","contributorId":1000,"corporation":false,"usgs":true,"family":"Cosca","given":"Michael","email":"mcosca@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":700472,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188817,"text":"70188817 - 2015 - The emergence of volcanic oceanic islands on a slow-moving plate: The example of Madeira Island, NE Atlantic","interactions":[],"lastModifiedDate":"2017-06-26T12:33:04","indexId":"70188817","displayToPublicDate":"2015-07-16T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"The emergence of volcanic oceanic islands on a slow-moving plate: The example of Madeira Island, NE Atlantic","docAbstract":"The transition from seamount to oceanic island typically involves surtseyan volcanism. However, the geological record at many islands in the NE Atlantic—all located within the slow-moving Nubian plate—does not exhibit evidence for an emergent surtseyan phase but rather an erosive unconformity between the submarine basement and the overlying subaerial shield sequences. This suggests that the transition between seamount and island may frequently occur by a relative fall of sea level through uplift, eustatic changes, or a combination of both, and may not involve summit volcanism. In this study, we explore the consequences for island evolutionary models using Madeira Island (Portugal) as a case study. We have examined the geologic record at Madeira using a combination of detailed fieldwork, biostratigraphy, and 40Ar/39Ar geochronology in order to document the mode, timing, and duration of edifice emergence above sea level. Our study confirms that Madeira's subaerial shield volcano was built upon the eroded remains of an uplifted seamount, with shallow marine sediments found between the two eruptive sequences and presently located at 320–430 m above sea level. This study reveals that Madeira emerged around 7.0–5.6 Ma essentially through an uplift process and before volcanic activity resumed to form the subaerial shield volcano. Basal intrusions are a likely uplift mechanism, and their emplacement is possibly enhanced by the slow motion of the Nubian plate relative to the source of partial melting. Alternating uplift and subsidence episodes suggest that island edifice growth may be governed by competing dominantly volcanic and dominantly intrusive processes.
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