Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of mud, sand, and gravel since 1927, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams, initiated in September 2011, induced massive increases in river sediment supply and provided an unprecedented opportunity to examine the geomorphic response of a coastal delta to these increases. Detailed measurements of beach topography and nearshore bathymetry show that ~ 2.5 million m3 of sediment was deposited during the first two years of dam removal, which is ~ 100 times greater than deposition rates measured prior to dam removal. The majority of the deposit was located in the intertidal and shallow subtidal region immediately offshore of the river mouth and was composed of sand and gravel. Additional areas of deposition include a secondary sandy deposit to the east of the river mouth and a muddy deposit west of the mouth. A comparison with fluvial sediment fluxes suggests that ~ 70% of the sand and gravel and ~ 6% of the mud supplied by the river was found in the survey area (within about 2 km of the mouth). A hydrodynamic and sediment transport model, validated with in-situ measurements, shows that tidal currents interacting with the larger relict submarine delta help disperse fine sediment large distances east and west of the river mouth. The model also suggests that waves and currents erode the primary deposit located near the river mouth and transport sandy sediment eastward to form the secondary deposit. Though most of the substrate of the larger relict submarine delta was unchanged during the first two years of dam removal, portions of the seafloor close to the river mouth became finer, modifying habitats for biological communities. These results show that river restoration, like natural changes in river sediment supply, can result in rapid and substantial coastal geomorphological responses.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2015.01.002","usgsCitation":"Gelfenbaum, G.R., Stevens, A.W., Miller, I.M., Warrick, J., Ogston, A.S., and Eidam, E., 2015, Large-scale dam removal on the Elwha River, Washington, USA: coastal geomorphic change: Geomorphology, v. 246, no. 1, p. 649-668, https://doi.org/10.1016/j.geomorph.2015.01.002.","productDescription":"20 p.","startPage":"649","endPage":"668","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058068","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":472272,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2015.01.002","text":"Publisher Index Page"},{"id":298024,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.74519348144531,\n 47.95636395852882\n ],\n [\n -123.74519348144531,\n 48.24936904607431\n ],\n [\n -123.3380126953125,\n 48.24936904607431\n ],\n [\n -123.3380126953125,\n 47.95636395852882\n ],\n [\n -123.74519348144531,\n 47.95636395852882\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"246","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54e5b7ede4b02d776a669ea3","chorus":{"doi":"10.1016/j.geomorph.2015.01.002","url":"http://dx.doi.org/10.1016/j.geomorph.2015.01.002","publisher":"Elsevier BV","authors":"Gelfenbaum Guy, Stevens Andrew W., Miller Ian, Warrick Jonathan A., Ogston Andrea S., Eidam Emily","journalName":"Geomorphology","publicationDate":"10/2015","publiclyAccessibleDate":"8/15/2016"},"contributors":{"authors":[{"text":"Gelfenbaum, Guy R. 0000-0003-1291-6107 ggelfenbaum@usgs.gov","orcid":"https://orcid.org/0000-0003-1291-6107","contributorId":742,"corporation":false,"usgs":true,"family":"Gelfenbaum","given":"Guy","email":"ggelfenbaum@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":540757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stevens, Andrew W. astevens@usgs.gov","contributorId":3199,"corporation":false,"usgs":true,"family":"Stevens","given":"Andrew","email":"astevens@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":540758,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Ian M. 0000-0002-3289-6337","orcid":"https://orcid.org/0000-0002-3289-6337","contributorId":41951,"corporation":false,"usgs":false,"family":"Miller","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":540759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warrick, Jonathan A. jwarrick@usgs.gov","contributorId":1904,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan A.","email":"jwarrick@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":540760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ogston, Andrea S.","contributorId":12119,"corporation":false,"usgs":true,"family":"Ogston","given":"Andrea","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":540761,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eidam, Emily","contributorId":139311,"corporation":false,"usgs":false,"family":"Eidam","given":"Emily","email":"","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":540762,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70137314,"text":"sir20155003 - 2015 - Water-quality characteristics and trends for selected wells possibly influenced by wastewater disposal at the Idaho National Laboratory, Idaho, 1981-2012","interactions":[],"lastModifiedDate":"2015-02-20T13:52:28","indexId":"sir20155003","displayToPublicDate":"2015-02-18T09:45:00","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":"2015-5003","title":"Water-quality characteristics and trends for selected wells possibly influenced by wastewater disposal at the Idaho National Laboratory, Idaho, 1981-2012","docAbstract":"The U.S. Geological Survey, in cooperation with the U.S. Department of Energy, analyzed water-quality data collected from 64 aquifer wells and 35 perched groundwater wells at the Idaho National Laboratory (INL) from 1981 through 2012. The wells selected for the study were wells that possibly were affected by wastewater disposal at the INL. The data analyzed included tritium, strontium-90, major cations, anions, nutrients, trace elements, total organic carbon, and volatile organic compounds. The analyses were performed to examine water-quality trends that might influence future management decisions about the number of wells to sample at the INL and the type of constituents to monitor.
\nThe data were processed using custom computer scripts developed in the R programming language. Summary statistics were calculated for the datasets. Water-quality trends were determined using a parametric survival regression model to fit the observed data, including left-censored, interval-censored, and uncensored data. The null hypothesis of the trend test was that no relation existed between time and concentration; the alternate hypothesis was that time and concentration were related through the regression equation. A significance level of 0.05 was selected to determine if the trend was statistically significant.
\nTrend test results for tritium and strontium-90 concentrations in aquifer wells indicated that nearly all wells had decreasing or no trends. Similarly, trends in perched groundwater wells were mostly decreasing or no trends; trends were increasing in two perched groundwater wells near the Advanced Test Reactor Complex. Decreasing trends generally are attributed to lack of recent wastewater disposal and radioactive decay.
\nTrend test results for chloride, sodium, sulfate, nitrite plus nitrate (as nitrogen), chromium, trace elements, and total organic carbon concentrations in aquifer wells indicated that most wells had either decreasing or no trends. The decreasing trends in these constituents are attributed to decrease in disposal of these constituents, as well as discontinued use of the old percolation ponds south of the Idaho Nuclear Technology and Engineering Center (INTEC) and redirection of wastewater to the new percolation ponds 2 miles southwest of the INTEC in 2002.
\nChloride (along with sodium, sulfate, and some nitrate) concentrations in wells south of the INTEC may be influenced by episodic recharge from the Big Lost River. These constituent concentrations decrease during wetter periods when there is probably more recharge from the Big Lost River and increase during dry periods, when there is less recharge.
\nSome wells downgradient of the Central Facilities Area and near the southern boundary of the INL showed increasing trends in sodium concentration, whereas there was no trend in chloride. The increasing trend for sodium could be due to the long term influence of wastewater disposal from upgradient facilities and the lack of trend for chloride could be because chloride is more mobile than sodium and more dispersed in the aquifer system.
\nVolatile organic compound concentration trends were analyzed for nine aquifer wells. Trend test results indicated an increasing trend for carbon tetrachloride for the Radioactive Waste Management Complex Production Well for the period 1987–2012; however, trend analyses of data collected since 2005 show no statistically significant trend indicating that engineering practices designed to reduce movement of volatile organic compounds to the aquifer may be having a positive effect on the aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155003","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Davis, L.C., Bartholomay, R.C., Fisher, J.C., and Maimer, N.V., 2015, Water-quality characteristics and trends for selected wells possibly influenced by wastewater disposal at the Idaho National Laboratory, Idaho, 1981-2012: U.S. Geological Survey Scientific Investigations Report 2015-5003, Report: viii, 105 p.; Appendixes A-E, https://doi.org/10.3133/sir20155003.","productDescription":"Report: viii, 105 p.; Appendixes A-E","numberOfPages":"118","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1981-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-053069","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":298022,"rank":8,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155003.jpg"},{"id":298016,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5003/pdf/sir2015-5003.pdf","text":"Report","size":"7.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298020,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5003/pdf/sir2015-5003_appendixd.pdf","text":"Appendix D","size":"36.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix D"},{"id":298004,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5003/"},{"id":298021,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5003/pdf/sir2015-5003_appendixe.pdf","text":"Appendix E","size":"2.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix E"},{"id":298017,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5003/pdf/sir2015-5003_appendixa.pdf","text":"Appendix A","size":"237 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix A"},{"id":298018,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5003/pdf/sir2015-5003_appendixb.pdf","text":"Appendix B","size":"22.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix B"},{"id":298019,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5003/pdf/sir2015-5003_appendixc.pdf","text":"Appendix C","size":"12.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix C"}],"projection":"Universal Transverse Mercator projection, Zone 12","datum":"North American Datum of 1927","country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.71536254882812,\n 43.37910133500264\n ],\n [\n -113.71536254882812,\n 44.03429525903969\n ],\n [\n -112.4835205078125,\n 44.03429525903969\n ],\n [\n -112.4835205078125,\n 43.37910133500264\n ],\n [\n -113.71536254882812,\n 43.37910133500264\n ]\n ]\n ]\n }\n }\n ]\n}","publicComments":"DOE/ID-22233","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54e5b7f2e4b02d776a669ead","contributors":{"authors":[{"text":"Davis, Linda C. lcdavis@usgs.gov","contributorId":2539,"corporation":false,"usgs":true,"family":"Davis","given":"Linda","email":"lcdavis@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540721,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartholomay, Roy C. 0000-0002-4809-9287 rcbarth@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-9287","contributorId":1131,"corporation":false,"usgs":true,"family":"Bartholomay","given":"Roy","email":"rcbarth@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540720,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Jason C. 0000-0001-9032-8912 jfisher@usgs.gov","orcid":"https://orcid.org/0000-0001-9032-8912","contributorId":2523,"corporation":false,"usgs":true,"family":"Fisher","given":"Jason","email":"jfisher@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540722,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maimer, Neil V. 0000-0003-3047-3282 nmaimer@usgs.gov","orcid":"https://orcid.org/0000-0003-3047-3282","contributorId":5659,"corporation":false,"usgs":true,"family":"Maimer","given":"Neil","email":"nmaimer@usgs.gov","middleInitial":"V.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540723,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70133102,"text":"ds898 - 2015 - Basement domain map of the conterminous United States and Alaska","interactions":[],"lastModifiedDate":"2016-06-29T13:36:05","indexId":"ds898","displayToPublicDate":"2015-02-18T09:15:00","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":"898","title":"Basement domain map of the conterminous United States and Alaska","docAbstract":"The basement-domain map is a compilation of basement domains in the conterminous United States and Alaska designed to be used at 1:5,000,000-scale, particularly as a base layer for national-scale mineral resource assessments. Seventy-seven basement domains are represented as eighty-three polygons on the map. The domains are based on interpretations of basement composition, origin, and architecture and developed from a variety of sources. Analysis of previously published basement, lithotectonic, and terrane maps as well as models of planetary development were used to formulate the concept of basement and the methodology of defining domains that spanned the ages of Archean to present but formed through different processes. The preliminary compilations for the study areas utilized these maps, national-scale gravity and aeromagnetic data, published and limited new age and isotopic data, limited new field investigations, and conventional geologic maps. Citation of the relevant source data for compilations and the source and types of original interpretation, as derived from different types of data, are provided in supporting descriptive text and tables.
\nThe tectonic settings for crustal types represented in the basement domains are subdivided into constituent geologic environments and the types of primary metals endowments and deposits in them are documented. The compositions, architecture, and original metals endowments are potentially important to assessments of primary mineral deposits and to the residence and recycling of metals in the crust of the United States portion of the North American continent. The databases can be configured to demonstrate the construction of the United States through time, to identify specific types of crust, or to identify domains potentially containing metal endowments of specific genetic types or endowed with specific metals. The databases can also be configured to illustrate other purposes chosen by users.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds898","usgsCitation":"Lund, K., Box, S.E., Holm-Denoma, C.S., San Juan, C.A., Blakely, R.J., Saltus, R.W., Anderson, E.D., and DeWitt, E., 2015, Basement domain map of the conterminous United States and Alaska: U.S. Geological Survey Data Series 898, Report: iv, 41 p.; Downloads Directory, https://doi.org/10.3133/ds898.","productDescription":"Report: iv, 41 p.; Downloads Directory","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053924","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":298007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds898.jpg"},{"id":298005,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0898/pdf/ds898.pdf","text":"Report","size":"11.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298006,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0898/downloads/","text":"Downloads Directory","linkHelpText":"Contains: geospatial database. 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edewitt@usgs.gov","contributorId":725,"corporation":false,"usgs":true,"family":"DeWitt","given":"Ed","email":"edewitt@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":540710,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70144681,"text":"70144681 - 2015 - The 21 May 2014 Mw 5.9 Bay of Bengal earthquake: macroseismic data suggest a high‐stress‐drop event","interactions":[],"lastModifiedDate":"2015-03-31T10:56:24","indexId":"70144681","displayToPublicDate":"2015-02-18T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"The 21 May 2014 Mw 5.9 Bay of Bengal earthquake: macroseismic data suggest a high‐stress‐drop event","docAbstract":"A modest but noteworthy Mw 5.9 earthquake occurred in the Bay of Bengal beneath the central Bengal fan at 21:51 Indian Standard Time (16:21 UTC) on 21 May 2014. Centered over 300 km from the eastern coastline of India (Fig. 1), it caused modest damage by virtue of its location and magnitude. However, shaking was very widely felt in parts of eastern India where earthquakes are uncommon. Media outlets reported as many as four fatalities. Although most deaths were blamed on heart attacks, the death of one woman was attributed by different sources to either a roof collapse or a stampede (see Table S1, available in the electronic supplement to this article). Across the state of Odisha, as many as 250 people were injured (see Table S1), most after jumping from balconies or terraces. Light damage was reported from a number of towns on coastal deltaic sediments, including collapsed walls and damage to pukka and thatched dwellings. Shaking was felt well inland into east‐central India and was perceptible in multistoried buildings as far as Chennai, Delhi, and Jaipur at distances of ≈1600 km (Table 1).
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220140155","usgsCitation":"Martin, S., and Hough, S.E., 2015, The 21 May 2014 Mw 5.9 Bay of Bengal earthquake: macroseismic data suggest a high‐stress‐drop event: Seismological Research Letters, v. 86, no. 2A, p. 369-377, https://doi.org/10.1785/0220140155.","productDescription":"9 p.","startPage":"369","endPage":"377","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058318","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":472274,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1785/0220140155","text":"External Repository"},{"id":299197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Bay of Bengal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 79.8486328125,\n 10.401377554543553\n ],\n [\n 79.8486328125,\n 11.652236404115413\n ],\n [\n 80.4638671875,\n 13.410994034321702\n ],\n [\n 80.1123046875,\n 15.496032414238634\n ],\n [\n 82.2216796875,\n 16.341225619207496\n ],\n [\n 82.529296875,\n 17.014767530557833\n ],\n [\n 85.341796875,\n 19.394067895396628\n ],\n [\n 86.748046875,\n 20.262197124246534\n ],\n [\n 87.1875,\n 20.797201434307\n ],\n [\n 87.451171875,\n 21.4121622297254\n ],\n [\n 89.56054687499999,\n 21.616579336740603\n ],\n [\n 91.0546875,\n 21.90227796666864\n ],\n [\n 91.49414062499999,\n 22.024545601240337\n ],\n [\n 93.42773437499999,\n 19.228176737766262\n ],\n [\n 93.2958984375,\n 18.47960905583197\n ],\n [\n 93.8671875,\n 18.271086109608877\n ],\n [\n 94.39453125,\n 17.43451055152291\n ],\n [\n 94.1748046875,\n 16.003575733881327\n ],\n [\n 92.8564453125,\n 13.025965926333539\n ],\n [\n 92.28515625,\n 10.14193168613103\n ],\n [\n 93.4716796875,\n 7.013667927566642\n ],\n [\n 92.2412109375,\n 5.79089681287197\n ],\n [\n 88.0224609375,\n 4.959615024698026\n ],\n [\n 83.1005859375,\n 5.266007882805511\n ],\n [\n 82.0458984375,\n 7.318881730366756\n ],\n [\n 79.8486328125,\n 10.401377554543553\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"86","issue":"2A","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-18","publicationStatus":"PW","scienceBaseUri":"551bc52ee4b0323842783a59","contributors":{"authors":[{"text":"Martin, Stacey","contributorId":35165,"corporation":false,"usgs":false,"family":"Martin","given":"Stacey","affiliations":[{"id":5110,"text":"Earth Observatory of Singapore, Nanyang Technological University","active":true,"usgs":false}],"preferred":false,"id":543768,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":543767,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70142050,"text":"70142050 - 2015 - Using motion-sensor camera technology to infer seasonal activity and thermal niche of the desert tortoise (Gopherus agassizii)","interactions":[],"lastModifiedDate":"2015-03-09T11:06:02","indexId":"70142050","displayToPublicDate":"2015-02-17T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2476,"text":"Journal of Thermal Biology","active":true,"publicationSubtype":{"id":10}},"title":"Using motion-sensor camera technology to infer seasonal activity and thermal niche of the desert tortoise (Gopherus agassizii)","docAbstract":"Understanding the relationships between environmental variables and wildlife activity is an important part of effective management. The desert tortoise (Gopherus agassizii), an imperiled species of arid environments in the southwest US, may have increasingly restricted windows for activity due to current warming trends. In summer 2013, we deployed 48 motion sensor cameras at the entrances of tortoise burrows to investigate the effects of temperature, sex, and day of the year on the activity of desert tortoises. Using generalized estimating equations, we found that the relative probability of activity was associated with temperature (linear and quadratic), sex, and day of the year. Sex effects showed that male tortoises are generally more active than female tortoises. Temperature had a quadratic effect, indicating that tortoise activity was heightened at a range of temperatures. In addition, we found significant support for interactions between sex and day of the year, and sex and temperature as predictors of the probability of activity. Using our models, we were able to estimate air temperatures and times (days and hours) that were associated with maximum activity during the study. Because tortoise activity is constrained by environmental conditions such as temperature, it is increasingly vital to conduct studies on how tortoises vary their activity throughout the Sonoran Desert to better understand the effects of a changing climate.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jtherbio.2015.02.009","usgsCitation":"Agha, M., Augustine, B., Lovich, J.E., Delaney, D.F., Sinervo, B., Murphy, M.O., Ennen, J., Briggs, J.R., Cooper, R.J., and Price, S.J., 2015, Using motion-sensor camera technology to infer seasonal activity and thermal niche of the desert tortoise (Gopherus agassizii): Journal of Thermal Biology, v. 49-50, p. 119-126, https://doi.org/10.1016/j.jtherbio.2015.02.009.","productDescription":"8 p.","startPage":"119","endPage":"126","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059750","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":298177,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Riverside County","city":"Palm Springs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n 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KY 40546, USA. mason.murphy@uky.edu","active":true,"usgs":false}],"preferred":false,"id":541584,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ennen, Joshua R.","contributorId":60368,"corporation":false,"usgs":false,"family":"Ennen","given":"Joshua R.","affiliations":[{"id":13216,"text":"Tennessee Aquarium Conservation Institute","active":true,"usgs":false}],"preferred":false,"id":541585,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Briggs, Jessica R.","contributorId":139510,"corporation":false,"usgs":false,"family":"Briggs","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":12783,"text":"Warner College of Natural Resources, Colorado State University, Fort Collins, CO 80523, USA","active":true,"usgs":false}],"preferred":false,"id":541588,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cooper, Robert J.","contributorId":99245,"corporation":false,"usgs":false,"family":"Cooper","given":"Robert","email":"","middleInitial":"J.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":541586,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Price, Steven J. 0000-0002-2388-0579","orcid":"https://orcid.org/0000-0002-2388-0579","contributorId":57738,"corporation":false,"usgs":false,"family":"Price","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":541587,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70133125,"text":"tm6B7 - 2015 - PRMS-IV, the precipitation-runoff modeling system, version 4","interactions":[],"lastModifiedDate":"2015-02-19T14:27:24","indexId":"tm6B7","displayToPublicDate":"2015-02-16T08:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-B7","title":"PRMS-IV, the precipitation-runoff modeling system, version 4","docAbstract":"Computer models that simulate the hydrologic cycle at a watershed scale facilitate assessment of variability in climate, biota, geology, and human activities on water availability and flow. This report describes an updated version of the Precipitation-Runoff Modeling System. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of various combinations of climate and land use on streamflow and general watershed hydrology. Several new model components were developed, and all existing components were updated, to enhance performance and supportability. This report describes the history, application, concepts, organization, and mathematical formulation of the Precipitation-Runoff Modeling System and its model components. This updated version provides improvements in (1) system flexibility for integrated science, (2) verification of conservation of water during simulation, (3) methods for spatial distribution of climate boundary conditions, and (4) methods for simulation of soil-water flow and storage.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Surface water in Book 6 Modeling Techniques","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6B7","usgsCitation":"Markstrom, S., Regan, R.S., Hay, L.E., Viger, R., Webb, R.M., Payn, R.A., and LaFontaine, J., 2015, PRMS-IV, the precipitation-runoff modeling system, version 4: U.S. Geological Survey Techniques and Methods 6-B7, vii, 158 p., https://doi.org/10.3133/tm6B7.","productDescription":"vii, 158 p.","numberOfPages":"169","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-045397","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":438724,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LVUWDC","text":"USGS data release","linkHelpText":"Precipitation Runoff Modeling System (PRMS) version 5.2.1"},{"id":438723,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HJ5TKZ","text":"USGS data release","linkHelpText":"Precipitation Runoff Modeling System (PRMS) version 5.2.0"},{"id":438722,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EMVKHC","text":"USGS data release","linkHelpText":"Precipitation Runoff Modeling System (PRMS) version 5.1.0"},{"id":438721,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X17IC9","text":"USGS data release","linkHelpText":"GSFLOW: Coupled Groundwater and Surface-Water Flow Model, version 2.1.0"},{"id":438720,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91FBZOB","text":"USGS data release","linkHelpText":"PRMS version 5.0.0: Precipitation-Runoff Modeling System"},{"id":298054,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm6b7.jpg"},{"id":297968,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/6b7/"},{"id":297988,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/6b7/pdf/tm6-b7.pdf","text":"Report","size":"6.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"publicComments":"This report is Chapter 7 of Section B: Surface Water in Book 6 Modeling Techniques.","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54e71739e4b02d776a66a016","contributors":{"authors":[{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":1986,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven L.","email":"markstro@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":540583,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Regan, R. Steve 0000-0003-4803-8596 rsregan@usgs.gov","orcid":"https://orcid.org/0000-0003-4803-8596","contributorId":2633,"corporation":false,"usgs":true,"family":"Regan","given":"R.","email":"rsregan@usgs.gov","middleInitial":"Steve","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":540585,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":540582,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":1204,"corporation":false,"usgs":true,"family":"Viger","given":"Roland J.","email":"rviger@usgs.gov","affiliations":[],"preferred":false,"id":540586,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Webb, Richard M. 0000-0001-9531-2207 rmwebb@usgs.gov","orcid":"https://orcid.org/0000-0001-9531-2207","contributorId":1570,"corporation":false,"usgs":true,"family":"Webb","given":"Richard","email":"rmwebb@usgs.gov","middleInitial":"M.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":540584,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Payn, Robert A.","contributorId":127363,"corporation":false,"usgs":false,"family":"Payn","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":6765,"text":"Montana State University, Department of Land Resources and Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":540587,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"LaFontaine, Jacob H.","contributorId":127364,"corporation":false,"usgs":false,"family":"LaFontaine","given":"Jacob H.","affiliations":[{"id":6672,"text":"former: USGS Southwest Biological Science Center, Colorado Plateau Research Station, Flagstaff, AZ. Current address: TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":false,"id":540588,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70143925,"text":"70143925 - 2015 - Quantification of colloidal and aqueous element transfer in soils: The dual-phase mass balance model","interactions":[],"lastModifiedDate":"2015-03-24T09:47:20","indexId":"70143925","displayToPublicDate":"2015-02-15T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Quantification of colloidal and aqueous element transfer in soils: The dual-phase mass balance model","docAbstract":"Mass balance models have become standard tools for characterizing element gains and losses and volumetric change during weathering and soil development. However, they rely on the assumption of complete immobility for an index element such as Ti or Zr. Here we describe a dual-phase mass balance model that eliminates the need for an assumption of immobility and in the process quantifies the contribution of aqueous versus colloidal element transfer. In the model, the high field strength elements Ti and Zr are assumed to be mobile only as suspended solids (colloids) and can therefore be used to distinguish elemental redistribution via colloids from redistribution via dissolved aqueous solutes. Calculations are based upon element concentrations in soil, parent material, and colloids dispersed from soil in the laboratory. We illustrate the utility of this model using a catena in South Africa. Traditional mass balance models systematically distort elemental gains and losses and changes in soil volume in this catena due to significant redistribution of Zr-bearing colloids. Applying the dual-phase model accounts for this colloidal redistribution and we find that the process accounts for a substantial portion of the major element (e.g., Al, Fe and Si) loss from eluvial soil. In addition, we find that in illuvial soils along this catena, gains of colloidal material significantly offset aqueous elemental loss. In other settings, processes such as accumulation of exogenous dust can mimic the geochemical effects of colloid redistribution and we suggest strategies for distinguishing between the two. The movement of clays and colloidal material is a major process in weathering and pedogenesis; the mass balance model presented here is a tool for quantifying effects of that process over time scales of soil development.
","language":"English","publisher":"Geochemical Society","publisherLocation":"New York, NY","doi":"10.1016/j.gca.2014.12.008","usgsCitation":"Bern, C., Thompson, A., and Chadwick, O.A., 2015, Quantification of colloidal and aqueous element transfer in soils: The dual-phase mass balance model: Geochimica et Cosmochimica Acta, v. 151, p. 1-18, https://doi.org/10.1016/j.gca.2014.12.008.","productDescription":"18 p.","startPage":"1","endPage":"18","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053366","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":472276,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.escholarship.org/uc/item/4801646x","text":"External Repository"},{"id":298894,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"151","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55128ab2e4b02e76d75bd61c","contributors":{"authors":[{"text":"Bern, Carleton R. cbern@usgs.gov","contributorId":139818,"corporation":false,"usgs":true,"family":"Bern","given":"Carleton R.","email":"cbern@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":543113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Aaron","contributorId":139820,"corporation":false,"usgs":false,"family":"Thompson","given":"Aaron","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":543114,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chadwick, Oliver A.","contributorId":88244,"corporation":false,"usgs":false,"family":"Chadwick","given":"Oliver","email":"","middleInitial":"A.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":543115,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70135359,"text":"ofr20141252 - 2015 - Evaluating coastal landscape response to sea-level rise in the northeastern United States: approach and methods","interactions":[],"lastModifiedDate":"2017-03-29T13:32:26","indexId":"ofr20141252","displayToPublicDate":"2015-02-13T17:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1252","title":"Evaluating coastal landscape response to sea-level rise in the northeastern United States: approach and methods","docAbstract":"The U.S. Geological Survey is examining effects of future sea-level rise on the coastal landscape from Maine to Virginia by producing spatially explicit, probabilistic predictions using sea-level projections, vertical land movement rates (due to isostacy), elevation data, and land-cover data. Sea-level-rise scenarios used as model inputs are generated by using multiple sources of information, including Coupled Model Intercomparison Project Phase 5 models following representative concentration pathways 4.5 and 8.5 in the Intergovernmental Panel on Climate Change Fifth Assessment Report. A Bayesian network is used to develop a predictive coastal response model that integrates the sea-level, elevation, and land-cover data with assigned probabilities that account for interactions with coastal geomorphology as well as the corresponding ecological and societal systems it supports. The effects of sea-level rise are presented as (1) level of landscape submergence and (2) coastal response type characterized as either static (that is, inundation) or dynamic (that is, landform or landscape change). Results are produced at a spatial scale of 30 meters for four decades (the 2020s, 2030s, 2050s, and 2080s). The probabilistic predictions can be applied to landscape management decisions based on sea-level-rise effects as well as on assessments of the prediction uncertainty and need for improved data or fundamental understanding. This report describes the methods used to produce predictions, including information on input datasets; the modeling approach; model outputs; data-quality-control procedures; and information on how to access the data and metadata online.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141252","usgsCitation":"Lentz, E.E., Stippa, S.R., Thieler, E.R., Plant, N.G., Gesch, D.B., and Horton, R.M., 2015, Evaluating coastal landscape response to sea-level rise in the northeastern United States—Approach and methods (ver. 2.0, December 2015): U.S. Geological Survey Open-File Report 2014–1252, 26 p., https://dx.doi.org/10.3133/ofr20141252.","productDescription":"Report: vi, 26 p.; Dataset; Project Web Page","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-058567","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438725,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73J3B0B","text":"USGS data release","linkHelpText":"Coastal Landscape Response to Sea-Level Rise Assessment for the Northeastern United States Data Release"},{"id":297982,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1252/"},{"id":297983,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1252/pdf/ofr2014-1252.pdf","size":"4.23 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297985,"rank":5,"type":{"id":18,"text":"Project Site"},"url":"https://woodshole.er.usgs.gov/project-pages/coastal_response/","text":"Coastal Landscape Response Project","linkFileType":{"id":5,"text":"html"}},{"id":297986,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2014/1252/images/coverthb.jpg"},{"id":297984,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://woodshole.er.usgs.gov/project-pages/coastal_response/data.html","text":"Landscape change predictions for the 2020s, 2030s, 2050s, and 2080s","linkFileType":{"id":5,"text":"html"}},{"id":312642,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2014/1252/versionHist.txt"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.19238281249999,\n 45.19752230305685\n ],\n [\n -69.23583984375,\n 44.69989765840318\n ],\n [\n -71.34521484375,\n 43.59630591596548\n ],\n [\n -71.69677734375,\n 41.96765920367816\n ],\n [\n -74.72900390625,\n 41.21172151054787\n ],\n [\n -77.6953125,\n 38.993572058209466\n ],\n [\n -77.49755859375,\n 36.54494944148322\n ],\n [\n -75.89355468749999,\n 36.56260003738548\n ],\n [\n -71.7626953125,\n 40.88029480552824\n ],\n [\n -69.80712890625,\n 41.11246878918086\n ],\n [\n -69.67529296875,\n 42.09822241118974\n ],\n [\n -70.24658203125,\n 42.779275360241904\n ],\n [\n -68.8623046875,\n 43.77109381775651\n ],\n [\n -66.796875,\n 44.715513732021336\n ],\n [\n -67.19238281249999,\n 45.19752230305685\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted February 13, 2015; Version 2.0: December 21, 2015","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
(508) 548-8700
http://woodshole.er.usgs.gov
Groundwater-level altitudes in 10 confined aquifers of the New Jersey Coastal Plain were measured and evaluated to provide an overview of regional groundwater conditions during fall 2008. Water levels were measured in more than 900 wells in New Jersey, eastern Pennsylvania, and northern Delaware and potentiometric surface maps prepared for the confined Cohansey aquifer of Cape May County, the Rio Grande water-bearing zone, the Atlantic City 800-foot sand, the Piney Point, Vincentown, and the Wenonah-Mount Laurel aquifers, the Englishtown aquifer system, and the Upper, Middle, and Lower aquifers of the Potomac-Raritan-Magothy aquifer system. In 2008, the highest water-level altitudes were observed in the Vincentown aquifer (median, 78 ft) and the lowest in the Atlantic City 800-foot sand (median, -45 ft). Persistent, regionally extensive cones of depression were present within the potentiometric surfaces of the Englishtown aquifer system in east-central New Jersey, the Wenonah-Mount Laurel aquifer in east-central and southern New Jersey, the Upper, Middle, and Lower Potomac-Raritan-Magothy aquifers in southern New Jersey, and the Atlantic City 800-foot sand in the southeastern part of the State. Cones of depression in the potentiometric surfaces of the Upper Potomac-Raritan-Magothy and the Piney Point aquifers in east-central and southwestern New Jersey had broadened and deepened since 2003.
\nDeclining water levels in many of New Jersey’s confined Coastal Plain aquifers intensified during the late 1970s and early 1980s, prompting the designation of two water-supply Critical Areas by the New Jersey Department of Environmental Protection; Critical Areas 1 and 2 continued to be of concern. To address that concern, water-level changes were assessed in nearly 800 wells measured during the fall of 2003 and 2008, and potentiometric-surface difference maps for each aquifer were constructed and evaluated. In addition, water-level trends were calculated for 77 wells for the periods 2003–8 and 1998–2008 and for 73 wells for the period 1978–2008.
\nFrom 2003 to 2008 small to moderate water-level changes were observed in many Coastal Plain aquifers in New Jersey, but in places, groundwater levels continued to decline substantially as a result of pumping. Groundwater levels in the Atlantic City 800-foot sand were lower in 2008 than in 2003; declines were greatest near pumping centers in eastern Atlantic County. Changes were less pronounced in Cape May County where water levels were, on average, 1 to 3 feet (ft) lower than those during the previous study (2003), except near Rio Grande where a localized cone of depression had formed as a result of increased withdrawals. Large and widespread declines occurred in the Piney Point aquifer in Cumberland County where water levels in and around the city of Bridgeton had fallen in excess of 100 ft since 2003, and by 30 ft to more than 60 ft in surrounding areas. Groundwater levels in the Wenonah-Mount Laurel aquifer and Englishtown aquifer system continued to recover in east-central New Jersey; however, groundwater levels in the Wenonah-Mount Laurel aquifer throughout the southern part of the State continued to decline.
\nIn the Upper Potomac-Raritan-Magothy aquifer, groundwater levels were substantially lower than in 2003 in parts of northern Ocean County but were stable in the area adjacent to Raritan Bay (Critical Area 1), and water levels continued to recover in southern New Jersey. In the Middle Potomac-Raritan-Magothy aquifer, water levels rose near Raritan Bay in Middlesex County; however, modest declines were recorded in interior areas of Monmouth and Ocean Counties. Groundwater levels in both the Middle and Lower Potomac-Raritan-Magothy aquifers were stable or rising within the regional cone of depression in Critical Area 2; beyond the critical area in southern New Jersey, however, water levels were slightly lower than in 2003.
\nAnalyses of long-term water-level changes indicate that from 1978 to 2008 downward trends occurred at 20 wells (27 percent), upward trends at 27 wells (37 percent), and trends at 26 wells (36 percent) were insubstantial. Sustained, long-term declines were observed most often at wells within the Atlantic City 800-foot sand and at wells in the Piney Point aquifer in southern New Jersey, in which rates of decline were as great as 1.4 feet/year. Upward water-level trends were observed frequently at wells screened in the Englishtown aquifer system and the Wenonah-Mount Laurel aquifer in Critical Area 1 in east-central New Jersey, and in the Potomac-Raritan-Magothy aquifer system in parts of Critical Area 1 and throughout most of Critical Area 2 in southern New Jersey. Annual rates of upward change were as great as 3.9 and 5.6 ft/yr in the Englishtown aquifer system and Wenonah-Mount Laurel aquifer, respectively. Among the units of the Potomac-Raritan-Magothy aquifer system, annual rates of recovery were greatest in the Lower aquifer.
\nFrom 1998 to 2008, downward water-level trends were observed at 22 wells (29 percent), upward trends were observed at 21 wells (27 percent), and insubstantial trends at 34 wells (44 percent). Downward trends were detected most often at wells open to the Piney Point aquifer and the Atlantic City 800-foot sand. Upward water-level trends were most frequent in wells open to the Englishtown aquifer system in Critical Area 1 and in wells within the Potomac-Raritan-Magothy aquifer system in southern New Jersey.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135232","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"DePaul, V.T., and Rosman, R., 2015, Water-level conditions in the confined aquifers of the New Jersey Coastal Plain, 2008: U.S. Geological Survey Scientific Investigations Report 2013-5232, Report: vii, 107 p.; 9 Plates: 34 inches x 44 inches or smaller, https://doi.org/10.3133/sir20135232.","productDescription":"Report: vii, 107 p.; 9 Plates: 34 inches x 44 inches or smaller","numberOfPages":"118","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-049629","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":297942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135232.jpg"},{"id":297934,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5232/pdf/sir2013-5232-plate2.pdf","text":"Plate 2","size":"4.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Plate 2","linkHelpText":"Potentiometric surface of the Atlantic City 800-foot sand, 2008"},{"id":297932,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5232/pdf/sir2013-5232.pdf","text":"Report","size":"10.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297931,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5232/"},{"id":297933,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5232/pdf/sir2013-5232-plate1.pdf","text":"Plate 1","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Plate 1","linkHelpText":"Potentiometric surface of the Cohansey aquifer and the Rio Grande water-bearing zone, 2008"},{"id":297936,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5232/pdf/sir2013-5232-plate4.pdf","text":"Plate 4","size":"3.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Plate 4","linkHelpText":"Potentiometric surface of the Vincentown aquifer, 2008"},{"id":297935,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5232/pdf/sir2013-5232-plate3.pdf","text":"Plate 3","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Plate 3","linkHelpText":"Potentiometric surface of the Piney Point aquifer, 2008"},{"id":297937,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5232/pdf/sir2013-5232-plate5.pdf","text":"Plate 5","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Plate 5","linkHelpText":"Potentiometric surface of the Wenonah-Mount Laurel aquifer, 2008"},{"id":297938,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5232/pdf/sir2013-5232-plate6.pdf","text":"Plate 6","size":"4.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Plate 6","linkHelpText":"Potentiometric surface of the Englishtown aquifer system, 2008"},{"id":297939,"rank":9,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5232/pdf/sir2013-5232-plate7.pdf","text":"Plate 7","size":"4.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Plate 7","linkHelpText":"Potentiometric surface of the Upper Potomac-Raritan-Magothy aquifer, 2008"},{"id":297940,"rank":10,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5232/pdf/sir2013-5232-plate8.pdf","text":"Plate 8","size":"4.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Plate 8","linkHelpText":"Potentiometric surface of the Middle and undifferentiated Potomac-Raritan-Magothy aquifer, 2008"},{"id":297941,"rank":11,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5232/pdf/sir2013-5232-plate9.pdf","text":"Plate 9","size":"3.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Plate 9","linkHelpText":"Potentiometric surface of the Lower Potomac-Raritan-Magothy aquifer, 2008"}],"country":"United States","state":"New Jersey","otherGeospatial":"Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.65185546874999,\n 38.950865400919994\n ],\n [\n -75.65185546874999,\n 40.44694705960048\n ],\n [\n -73.916015625,\n 40.44694705960048\n ],\n [\n -73.916015625,\n 38.950865400919994\n ],\n [\n -75.65185546874999,\n 38.950865400919994\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54ddceaae4b08de9379b3934","contributors":{"authors":[{"text":"DePaul, Vincent T. 0000-0002-7977-5217 vdepaul@usgs.gov","orcid":"https://orcid.org/0000-0002-7977-5217","contributorId":2778,"corporation":false,"usgs":true,"family":"DePaul","given":"Vincent","email":"vdepaul@usgs.gov","middleInitial":"T.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":518431,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosman, Robert 0000-0001-5042-1872 rrosman@usgs.gov","orcid":"https://orcid.org/0000-0001-5042-1872","contributorId":2846,"corporation":false,"usgs":true,"family":"Rosman","given":"Robert","email":"rrosman@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":518432,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70188571,"text":"70188571 - 2015 - Predicting locations of post-fire debris-flow erosionin the San Gabriel Mountains of southern California","interactions":[],"lastModifiedDate":"2017-06-15T14:59:07","indexId":"70188571","displayToPublicDate":"2015-02-12T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Predicting locations of post-fire debris-flow erosionin the San Gabriel Mountains of southern California","docAbstract":"Timely hazard assessments are needed to assess post-fire debris flows that may\nimpact communities located within and adjacent to recently burned areas. Implementing\nexisting models for debris-flow probability and magnitude can be time-consuming because\nthe geographic extent for applying the models is manually defined. In this study, a model is\npresented for predicting locations of post-fire debris-flow erosion. This model is further\ncalibrated to identify the geographic extent for applying post-fire hazard assessment\nmodels. Aerial photographs were used to map locations of post-fire debris-flow erosion and\ndeposition in the San Gabriel Mountains. Terrain, burn severity, and soil characteristics\nexpected to influence debris-flow erosion and deposition were calculated for each mapped\nlocation using 10-m resolution DEMs, GIS data for burn severity, and soil surveys.\nMultiple logistic regression was used to develop a model that predicts the probability of\nerosion as a function of channel slope, planform curvature, and the length of the longest\nupstream flow path. The model was validated using an independent database of mapped\nlocations of debris-flow erosion and deposition and found to make accurate and precise\npredictions. The model was further calibrated by identifying the average percentage of the\ndrainage network classified as erosion for mapped locations where debris flows transitioned\nfrom eroding to depositing material. The calibrated model provides critical information\nfor consistent and timely application of post-fire debris-flow hazard assessment\nmodels and the ability to identify locations of post-fire debris-flow erosion.","language":"English","publisher":"Springer","doi":"10.1007/s11069-015-1656-3","usgsCitation":"Gartner, J.E., Santi, P., and Cannon, S.H., 2015, Predicting locations of post-fire debris-flow erosionin the San Gabriel Mountains of southern California: Natural Hazards, v. 77, no. 2, p. 1305-1321, https://doi.org/10.1007/s11069-015-1656-3.","productDescription":"17 p. 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We developed a rule-based, piecewise regression-tree model trained on 99 points that used three data-sets – latitude, elevation, and start of season time based on remote sensing input data – to estimate cheatgrass beginning of spring growth (BOSG) in the northern Great Basin. The model was then applied to map the location and timing of cheatgrass spring growth for the entire area. The model was strong (R2 = 0.85) and predicted an average cheatgrass BOSG across the study area of 29 March–4 April. Of early cheatgrass BOSG areas, 65% occurred at elevations below 1452 m. The highest proportion of cheatgrass BOSG occurred between mid-April and late May. Predicted cheatgrass BOSG in this study matched well with previous Great Basin cheatgrass green-up studies.
","language":"English","publisher":"Taylor & Francis","publisherLocation":"Abingdon, UK","doi":"10.1080/17538947.2013.860196","usgsCitation":"Boyte, S.P., Wylie, B.K., Major, D.J., and Brown, J.F., 2015, The integration of geophysical and enhanced Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index data into a rule-based, piecewise regression-tree model to estimate cheatgrass beginning of spring growth: International Journal of Digital Earth, v. 8, no. 2, p. 116-130, https://doi.org/10.1080/17538947.2013.860196.","productDescription":"15 p.","startPage":"116","endPage":"130","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037330","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472279,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/17538947.2013.860196","text":"Publisher Index Page"},{"id":297921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.84033203125,\n 40.12849105685408\n ],\n [\n -120.66284179687499,\n 39.21523130910491\n ],\n [\n -122.03613281249999,\n 44.5278427984555\n ],\n [\n -114.686279296875,\n 45.398449976304086\n ],\n [\n -113.84033203125,\n 40.12849105685408\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2013-11-28","publicationStatus":"PW","scienceBaseUri":"54dd2abfe4b08de9379b31d2","contributors":{"authors":[{"text":"Boyte, Stephen P. 0000-0002-5462-3225 sboyte@usgs.gov","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":3463,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen","email":"sboyte@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":540443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":540450,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Major, Donald J.","contributorId":83405,"corporation":false,"usgs":false,"family":"Major","given":"Donald","email":"","middleInitial":"J.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":540451,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":3241,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":540452,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70140950,"text":"70140950 - 2015 - Mapping and monitoring cheatgrass dieoff in rangelands of the Northern Great Basin, USA","interactions":[],"lastModifiedDate":"2017-01-18T10:05:49","indexId":"70140950","displayToPublicDate":"2015-02-11T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Mapping and monitoring cheatgrass dieoff in rangelands of the Northern Great Basin, USA","docAbstract":"Understanding cheatgrass (Bromus tectorum) dynamics in the Northern Great Basin rangelands, USA, is necessary to effectively manage the region’s lands. This study’s goal was to map and monitor cheatgrass performance to identify where and when cheatgrass dieoff occurred in the Northern Great Basin and to discover how this phenomenon was affected by climatic, topographic, and edaphic variables. We also examined how fire affected cheatgrass performance. Land managers and scientists are concerned by cheatgrass dieoff because it can increase land degradation, and its causes and effects are not fully known. To better understand the scope of cheatgrass dieoff, we developed multiple ecological models that integrated remote sensing data with geophysical and biophysical data. The models’ R2 ranged from 0.71 to 0.88, and their root mean squared errors (RMSEs) ranged from 3.07 to 6.95. Validation of dieoff data showed that 41% of pixels within independently developed dieoff polygons were accurately classified as dieoff, whereas 2% of pixels outside of dieoff polygons were classified as dieoff. Site potential, a long-term spatial average of cheatgrass cover, dominated the development of the cheatgrass performance model. Fire negatively affected cheatgrass performance 1 year postfire, but by the second year postfire performance exceeded prefire levels. The landscape-scale monitoring study presented in this paper helps increase knowledge about recent rangeland dynamics, including where cheatgrass dieoffs occurred and how cheatgrass responded to fire. This knowledge can help direct further investigation and/or guide land management activities that can capitalize on, or mitigate the effects of, cheatgrass dieoff.
","language":"English","publisher":"Society for Range Management","doi":"10.1016/j.rama.2014.12.005","usgsCitation":"Boyte, S.P., Wylie, B.K., and Major, D.J., 2015, Mapping and monitoring cheatgrass dieoff in rangelands of the Northern Great Basin, USA: Rangeland Ecology and Management, v. 68, no. 1, p. 18-28, https://doi.org/10.1016/j.rama.2014.12.005.","productDescription":"11 p.","startPage":"18","endPage":"28","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053587","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":297920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northern Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.22314453124999,\n 40.1452892956766\n ],\n [\n -121.22314453124999,\n 44.85586880735725\n ],\n [\n -110.85205078124999,\n 44.85586880735725\n ],\n [\n -110.85205078124999,\n 40.1452892956766\n ],\n [\n -121.22314453124999,\n 40.1452892956766\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"68","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a94e4b08de9379b3112","contributors":{"authors":[{"text":"Boyte, Stephen P. 0000-0002-5462-3225 sboyte@usgs.gov","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":3463,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen","email":"sboyte@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":540447,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","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":540448,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Major, Donald J.","contributorId":83405,"corporation":false,"usgs":false,"family":"Major","given":"Donald","email":"","middleInitial":"J.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":540449,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70141321,"text":"70141321 - 2015 - Detrital zircon U-Pb reconnaissance of the Franciscan subduction complex in northwestern California","interactions":[],"lastModifiedDate":"2015-02-23T11:17:16","indexId":"70141321","displayToPublicDate":"2015-02-11T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2020,"text":"International Geology Review","active":true,"publicationSubtype":{"id":10}},"title":"Detrital zircon U-Pb reconnaissance of the Franciscan subduction complex in northwestern California","docAbstract":"In northwestern California, the Franciscan subduction complex has been subdivided into seven major tectonostratigraphic units. We report U-Pb ages of ≈2400 detrital zircon grains from 26 sandstone samples from 5 of these units. Here, we tabulate each unit's interpreted predominant sediment source areas and depositional age range, ordered from the oldest to the youngest unit. (1) Yolla Bolly terrane: nearby Sierra Nevada batholith (SNB); ca. 118 to 98 Ma. Rare fossils had indicated that this unit was mostly 151-137 Ma, but it is mostly much younger. (2) Central Belt: SND; ca. 103 too 53 Ma (but poorly constrained), again mostly younger than previously thought. (3) Yager terrane: distant Idaho batholith (IB); ca. 52 to 50 Ma. Much of the Yager's detritus was shed during major core complex extension and erosion in Idaho that started 53 Ma. An eocene Princeton River-Princeton submarine canyon system transported this detritus to the Great Valley forearc basin and thence to the Franciscan trench. (4) Coastal terrane: mostly IB, ±SNB, ±nearby Cascade arc, ±Nevada Cenozoic ignimbrite belt; 52 to <32 Ma. (5) King Range terrane: dominated by IB and SNB zircons; parts 16-14 Ma based on microfossils. Overall, some Franciscan units are younger than previously thought, making them more compatible with models for the growth of subduction complexes by positive accretion. From ca. 118 to 70 Ma, Franciscan sediments were sourced mainly from the nearby Sierra Nevada region and were isolated from southwestern US and Mexican sources. From 53 to 49 Ma, the Franciscan was sourced from both Idaho and the Sierra Nevada. By 37-32 Ma, input from Idaho had ceased. The influx from Idaho probably reflects major tectonism in Idaho, Oregon, and Washington, plus development of a through-going Princeton River to California, rather than radical changes in the subduction system at the Franciscan trench itself.
","language":"English","publisher":"American Geological Institute","publisherLocation":"Silver Spring, MD","doi":"10.1080/00206814.2015.1008060","collaboration":"Stanford University, UC Santa Cruz","usgsCitation":"Dimitru, T., Ernst, W.G., Hourigan, J.K., and McLaughlin, R.J., 2015, Detrital zircon U-Pb reconnaissance of the Franciscan subduction complex in northwestern California: International Geology Review, p. 1-35, https://doi.org/10.1080/00206814.2015.1008060.","productDescription":"35 p.","startPage":"1","endPage":"35","numberOfPages":"35","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060941","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":472280,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Detrital_zircon_U_8211_Pb_reconnaissance_of_the_Franciscan_subduction_complex_in_northwestern_California/1305626","text":"External Repository"},{"id":298107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.71679687499999,\n 38.25543637637947\n ],\n [\n -124.71679687499999,\n 41.96765920367816\n ],\n [\n -121.17919921875001,\n 41.96765920367816\n ],\n [\n -121.17919921875001,\n 38.25543637637947\n ],\n [\n -124.71679687499999,\n 38.25543637637947\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-11","publicationStatus":"PW","scienceBaseUri":"54ec5d3ee4b02d776a67daa0","contributors":{"authors":[{"text":"Dimitru, Trevor","contributorId":139288,"corporation":false,"usgs":false,"family":"Dimitru","given":"Trevor","email":"","affiliations":[{"id":6705,"text":"Stanford Synchrotron Radiation Lightsource, Menlo Park CA","active":true,"usgs":false}],"preferred":false,"id":540670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ernst, W. Gary","contributorId":139289,"corporation":false,"usgs":false,"family":"Ernst","given":"W.","email":"","middleInitial":"Gary","affiliations":[{"id":6705,"text":"Stanford Synchrotron Radiation Lightsource, Menlo Park CA","active":true,"usgs":false}],"preferred":false,"id":540671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hourigan, Jeremy K.","contributorId":99023,"corporation":false,"usgs":true,"family":"Hourigan","given":"Jeremy","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":540672,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McLaughlin, Robert J. 0000-0002-4390-2288 rjmcl@usgs.gov","orcid":"https://orcid.org/0000-0002-4390-2288","contributorId":1428,"corporation":false,"usgs":true,"family":"McLaughlin","given":"Robert","email":"rjmcl@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":540669,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70140628,"text":"ofr20151028 - 2015 - Strike-parallel and strike-normal coordinate system around geometrically complicated rupture traces: use by NGA-West2 and further improvements","interactions":[],"lastModifiedDate":"2015-02-11T09:20:44","indexId":"ofr20151028","displayToPublicDate":"2015-02-11T09:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1028","title":"Strike-parallel and strike-normal coordinate system around geometrically complicated rupture traces: use by NGA-West2 and further improvements","docAbstract":"We present a two-dimensional system of generalized coordinates for use with geometrically complex fault ruptures that are neither straight nor continuous. The coordinates are a generalization of the conventional strike-normal and strike-parallel coordinates of a single straight fault. The presented conventions and formulations are applicable to a single curved trace, as well as multiple traces representing the rupture of branching faults or noncontiguous faults. An early application of our generalized system is in the second round of the Next Generation of Ground-Motion Attenuation Model project for the Western United States (NGA-West2), where they were used in the characterization of the hanging-wall effects. We further improve the NGA-West2 strike-parallel formulation for multiple rupture traces with a more intuitive definition of the nominal strike direction. We also derive an analytical expression for the gradient of the generalized strike-normal coordinate. The direction of this gradient may be used as the strike-normal direction in the study of polarization effects on ground motions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151028","usgsCitation":"Spudich, P.A., and Chiou, B., 2015, Strike-parallel and strike-normal coordinate system around geometrically complicated rupture traces: use by NGA-West2 and further improvements: U.S. Geological Survey Open-File Report 2015-1028, iv, 20 p., https://doi.org/10.3133/ofr20151028.","productDescription":"iv, 20 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-062882","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":297908,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151028.PNG"},{"id":297903,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1028/"},{"id":297907,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1028/pdf/ofr2015-1028.pdf","text":"Report","size":"938 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ab9e4b08de9379b31ad","contributors":{"authors":[{"text":"Spudich, Paul A. 0000-0002-9484-4997 spudich@usgs.gov","orcid":"https://orcid.org/0000-0002-9484-4997","contributorId":2372,"corporation":false,"usgs":true,"family":"Spudich","given":"Paul","email":"spudich@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":540396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chiou, Brian","contributorId":139219,"corporation":false,"usgs":false,"family":"Chiou","given":"Brian","affiliations":[],"preferred":false,"id":540412,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70225727,"text":"70225727 - 2015 - Simulation of acceleration field of the Lushan earthquake (Ms7.0, April 20, 2013, China)","interactions":[],"lastModifiedDate":"2021-11-05T11:49:49.750359","indexId":"70225727","displayToPublicDate":"2015-02-11T06:45:27","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1517,"text":"Engineering Geology","active":true,"publicationSubtype":{"id":10}},"title":"Simulation of acceleration field of the Lushan earthquake (Ms7.0, April 20, 2013, China)","docAbstract":"The acceleration field of the Lushan earthquake (Ms7.0, April 20, 2013, China) is simulated using a new modified version of the stochastic finite-fault method (EXSIM) based on a dynamic corner frequency approach. To incorporate the effect of heterogeneous slip distribution on the variation of source spectrum, we adopt an empirical source spectral model and derive the corresponding dynamic parameters, which vary with the cumulative seismic moment of the ruptured area.
The new modified method is validated by: 1) comparison of the simulation results with those obtained from the EXSIM method using near-fault ground motion data of the 1994 Northridge earthquake; 2) comparison of simulated PGA contour map inferred from synthetic time histories at 315 grid locations with the observed PGA shakemap for the 2013 Lushan earthquake; 3) comparison of simulated PGA with those predicted by ground-motion prediction equations (GMPEs); and 4) comparison of simulated time histories with observed acceleration records at six strong motion stations during the mainshock of the Lushan earthquake, in which local site response is considered in the simulation. These comparisons confirm the validity of the new simulation procedure for purposes of regional strong ground motion estimation. Limitations of the procedure in modeling the phasing of different arrivals in the seismic signal and near-surface response of geologic deposits are discussed.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.enggeo.2015.02.003","usgsCitation":"Guoxin, W., Yang, D., and Borcherdt, R.D., 2015, Simulation of acceleration field of the Lushan earthquake (Ms7.0, April 20, 2013, China): Engineering Geology, v. 189, p. 84-97, https://doi.org/10.1016/j.enggeo.2015.02.003.","productDescription":"14 p.","startPage":"84","endPage":"97","ipdsId":"IP-052934","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":391420,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Lushan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 113.31298828125,\n 28.478348692223165\n ],\n [\n 118.7841796875,\n 28.478348692223165\n ],\n [\n 118.7841796875,\n 32.2313896627376\n ],\n [\n 113.31298828125,\n 32.2313896627376\n ],\n [\n 113.31298828125,\n 28.478348692223165\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"189","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Guoxin, Wang","contributorId":268328,"corporation":false,"usgs":false,"family":"Guoxin","given":"Wang","email":"","affiliations":[],"preferred":false,"id":826420,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Ding","contributorId":268329,"corporation":false,"usgs":false,"family":"Yang","given":"Ding","email":"","affiliations":[],"preferred":false,"id":826421,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Borcherdt, Roger D. 0000-0002-8668-0849","orcid":"https://orcid.org/0000-0002-8668-0849","contributorId":257482,"corporation":false,"usgs":true,"family":"Borcherdt","given":"Roger","email":"","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":826422,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70140627,"text":"70140627 - 2015 - Repeated landscape-scale treatments following fire suppress a non-native annual grass and promote recovery of native perennial vegetation","interactions":[],"lastModifiedDate":"2015-05-18T11:07:49","indexId":"70140627","displayToPublicDate":"2015-02-10T14:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Repeated landscape-scale treatments following fire suppress a non-native annual grass and promote recovery of native perennial vegetation","docAbstract":"Invasive non-native species pose a large threat to restoration efforts following large-scale disturbances. Bromus tectorum (cheatgrass) is a non-native annual grass in the western U.S. that both spreads quickly following fire and accelerates the fire cycle. Herbicide and seeding applications are common restoration practices to break the positive fire-invasion feedback loop and recover native perennial species, but their interactive effects have infrequently been tested at the landscape-scale and repeated in time to encourage long-lasting effects. We determined the efficacy of repeated post-fire application of the herbicide imazapic and seeding treatments to suppressBromus abundance and promote perennial vegetation recovery. We found that the selective herbicide reduced Bromus cover by ~30 % and density by >50 % across our study sites, but had a strong initial negative effect on seeded species. The most effective treatment to promote perennial seeded species cover was seeding them alone followed by herbicide application 3 years later when the seeded species had established. The efficacy of the treatments was strongly influenced by water availability, as precipitation positively affected the density and cover of Bromus; soil texture and aspect secondarily influenced Bromus abundance and seeded species cover by modifying water retention in this semi-arid region. Warmer temperatures positively affected the non-native annual grass in the cool-season, but negatively affected seeded perennial species in the warm-season, suggesting an important role of seasonality in a region projected to experience large increases in warming in the future. Our results highlight the importance of environmental interactions and repeated treatments in influencing restoration outcomes at the landscape-scale.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-015-0847-x","usgsCitation":"Munson, S.M., Long, A.L., Decker, C.E., Johnson, K.A., Walsh, K., and Miller, M.E., 2015, Repeated landscape-scale treatments following fire suppress a non-native annual grass and promote recovery of native perennial vegetation: Biological Invasions, v. 17, no. 6, p. 1915-1926, https://doi.org/10.1007/s10530-015-0847-x.","productDescription":"12 p.","startPage":"1915","endPage":"1926","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058692","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":297901,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Zion National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.26629638671875,\n 37.084762325442966\n ],\n [\n -113.26629638671875,\n 37.54893261064109\n ],\n [\n -112.78976440429688,\n 37.54893261064109\n ],\n [\n -112.78976440429688,\n 37.084762325442966\n ],\n [\n -113.26629638671875,\n 37.084762325442966\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-05","publicationStatus":"PW","scienceBaseUri":"54dd2aa9e4b08de9379b3170","contributors":{"authors":[{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":540261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, A. Lexine along@usgs.gov","contributorId":139181,"corporation":false,"usgs":true,"family":"Long","given":"A.","email":"along@usgs.gov","middleInitial":"Lexine","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":540262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Decker, Cheryl E.","contributorId":86051,"corporation":false,"usgs":false,"family":"Decker","given":"Cheryl","email":"","middleInitial":"E.","affiliations":[{"id":6959,"text":"National Park Service Southeast Utah Group","active":true,"usgs":false}],"preferred":false,"id":540263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Katie A.","contributorId":139182,"corporation":false,"usgs":false,"family":"Johnson","given":"Katie","email":"","middleInitial":"A.","affiliations":[{"id":12684,"text":"National Park Service, Lassen Volcanic National Park, Mineral, CA, 96063, USA","active":true,"usgs":false}],"preferred":false,"id":540264,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walsh, Kathleen","contributorId":139183,"corporation":false,"usgs":false,"family":"Walsh","given":"Kathleen","email":"","affiliations":[{"id":12685,"text":"National Park Service, Zion National Park, Springdale, UT, 84767, USA","active":true,"usgs":false}],"preferred":false,"id":540265,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Mark E.","contributorId":91580,"corporation":false,"usgs":false,"family":"Miller","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":6959,"text":"National Park Service Southeast Utah Group","active":true,"usgs":false}],"preferred":false,"id":540266,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70142047,"text":"70142047 - 2015 - Model-based interpretation of sediment concentration and vertical flux measurements in a shallow estuarine environment","interactions":[],"lastModifiedDate":"2015-03-09T11:10:42","indexId":"70142047","displayToPublicDate":"2015-02-10T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Model-based interpretation of sediment concentration and vertical flux measurements in a shallow estuarine environment","docAbstract":"A one-dimensional numerical model describing tidally varying vertical mixing and settling was used to interpret sediment concentrations and vertical fluxes observed in the shoals of South San Francisco Bay by two acoustic Doppler velocimeters (ADVs) at elevations of 0.36 m and 0.72 m above bed. Measured sediment concentrations changed by up to 100 g m−3 over the semidiurnal tidal cycle. These dynamics were dominated by local resuspension and settling. Multiple particle class models suggested the existence of a class with fast settling velocities (ws of 9.0 × 10−4 m s−1 in spring and 5.8 × 10−4 m s−1 in fall) and a slowly settling particle fraction (ws of <1 × 10−7 m s−1 in spring and 1.4 × 10−5 m s−1 in fall). Modeled concentrations of slowly settling particles at 0.36 m were as high as 20 g m−3 during fall and varied with the spring-neap cycle while fine sediment concentrations in spring were constant around 5 g m−3. Analysis of in situ water column floc size distributions suggested that floc properties in the lower part of the water column were most likely governed by particle-size distribution on the bed and not by coagulation, validating our multiple particle size approach. A comparison of different sediment bed models with respect to model performance, sensitivity, and identifiability suggested that the use of a sediment erosion model linear in bottom shear stress τb (E = M (τb − τc)) was the most appropriate choice to describe the field observations when the critical shear stress τc and the proportionality factor M were kept constant.
","language":"English","publisher":"Wiley","doi":"10.1002/lno.10047","usgsCitation":"Brand, A., Lacy, J.R., Gladding, S., Holleman, R., and Stacey, M., 2015, Model-based interpretation of sediment concentration and vertical flux measurements in a shallow estuarine environment: Limnology and Oceanography, v. 60, no. 2, p. 463-481, https://doi.org/10.1002/lno.10047.","productDescription":"19 p.","startPage":"463","endPage":"481","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-030148","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":472281,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.dora.lib4ri.ch/eawag/islandora/object/eawag%3A8063","text":"External Repository"},{"id":298178,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"South San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.40554809570311,\n 37.42307124980106\n ],\n [\n -122.40554809570311,\n 37.69849090879089\n ],\n [\n -121.92008972167969,\n 37.69849090879089\n ],\n [\n -121.92008972167969,\n 37.42307124980106\n ],\n [\n -122.40554809570311,\n 37.42307124980106\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"60","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-10","publicationStatus":"PW","scienceBaseUri":"54f19544e4b02419550ceae8","contributors":{"authors":[{"text":"Brand, Andreas","contributorId":32415,"corporation":false,"usgs":false,"family":"Brand","given":"Andreas","email":"","affiliations":[{"id":12775,"text":"Department of Surface Waters – Research and Management, Swiss Federal Institute of Aquatic Science and Technology (Eawag), Kastanienbaum, Switzerland","active":true,"usgs":false}],"preferred":false,"id":541568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lacy, Jessica R. 0000-0002-2797-6172 jlacy@usgs.gov","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":3158,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"jlacy@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":541567,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gladding, Steve","contributorId":54481,"corporation":false,"usgs":false,"family":"Gladding","given":"Steve","email":"","affiliations":[{"id":12776,"text":"Department of Civil and Environmental Engineering, University of California, Berkeley, California, USA","active":true,"usgs":false}],"preferred":false,"id":541571,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holleman, Rusty","contributorId":139500,"corporation":false,"usgs":false,"family":"Holleman","given":"Rusty","affiliations":[{"id":12776,"text":"Department of Civil and Environmental Engineering, University of California, Berkeley, California, USA","active":true,"usgs":false}],"preferred":false,"id":541570,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stacey, Mark T.","contributorId":94531,"corporation":false,"usgs":false,"family":"Stacey","given":"Mark T.","affiliations":[{"id":12776,"text":"Department of Civil and Environmental Engineering, University of California, Berkeley, California, USA","active":true,"usgs":false}],"preferred":false,"id":541569,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70099102,"text":"sir20145007 - 2015 - Geomorphic, flood, and groundwater-flow characteristics of Bayfield Peninsula streams, Wisconsin, and implications for brook-trout habitat","interactions":[],"lastModifiedDate":"2015-02-09T16:17:27","indexId":"sir20145007","displayToPublicDate":"2015-02-09T16:15:00","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":"2014-5007","title":"Geomorphic, flood, and groundwater-flow characteristics of Bayfield Peninsula streams, Wisconsin, and implications for brook-trout habitat","docAbstract":"In 2002–03, the U.S. Geological Survey conducted a study of the geomorphic, flood, and groundwater-flow characteristics of five Bayfield Peninsula streams, Wisconsin (Cranberry River, Bark River, Raspberry River, Sioux River, and Whittlesey Creek) to determine the physical limitations for brook-trout habitat. The goals of the study were threefold: (1) to describe geomorphic characteristics and processes, (2) to determine how land-cover characteristics affect flood peaks, and (3) to determine how regional groundwater flow patterns affect base flow.
\nThe geomorphic characterization consisted of analyses of historical aerial photographs and General Land Office Survey notes, observations from helicopter video footage, surveys of valley cross sections, and coring. Sources of sediment were identified from the helicopter video and field surveys, and past erosion-control techniques were evaluated. Geomorphic processes, such as runoff sediment erosion, transport, and deposition, are driven by channel location within the drainage network, texture of glacial deposits, and proximity to postglacial lake shorelines; these processes have historically increased because of decreases in upland forest cover and channel roughness. Sources of sediment for all studied streams mainly came from bank, terrace, or bluff erosion along main stem reaches and along feeder tributaries that bisect main-stem entrenched valley sides. Bluff, terrace, and bank erosion were the major sources of sediment to Whittlesey Creek and the Sioux River. No active bluff erosion was observed on the Cranberry River or the Bark River but anecdotal information suggests that landslides occasionally happen on the Cranberry River. For the Bark River, sources of sediment were somewhat evenly divided among road crossings (bridges, culverts, and unimproved forest lanes), terrace erosion, bank erosion, and incision along upper main stems and feeder channels along valley sides. Evaluation of past erosion-control techniques indicated that bluffs were stabilized by a combination of artificial hardening and bioengineering of the bluff base and reducing mass wasting of the tops of the bluffs.
\nFlood hydrographs for the Cranberry River were simulated for four land-cover scenarios—late 20th century (1992–93), presettlement (before 1870), peak agriculture (1928), and developed (25 percent urban). Results were compared to previous simulations of flood peaks for Whittlesey Creek and for North Fish Creek (southern adjacent basin to Whittlesey Creek). Even though most uplands are presently forested, flood peaks simulated for 1992–93 were 1.5 to 2 times larger than presettlement flood peaks. The increased flood peaks caused (1) increased incision along upper main stems and tributaries that bisect entrenched valley sides, (2) bluff and terrace erosion along reaches with entrenched valleys, (3) overbank deposition and bar formation in middle and lower main stems, and (4) aggradation in mouth areas.
\nA base-flow survey was conducted and a groundwater-flow model was developed for the Bayfield Peninsula to delineate groundwater contributing areas. A deep aquifer system, which includes thick deposits of sand and the upper part of the bedrock, is recharged through the permeable sands in the center of the peninsula. Base flow is unevenly distributed among the Bayfield streams and depends on the amount of channel incision and the proximity of the channels to the recharge area and coarse outwash deposits. Groundwater contributing areas for the five streams do not coincide with surface-water-contributing areas. About 89 percent of total recharge to the deep aquifer system discharges to Bayfield streams; the remaining 11 percent directly discharges to Lake Superior. Historical land-cover changes have had negligible effects on groundwater-flow from the deep aquifer system.
\nAvailable brook-trout habitat is dependent on the locations of groundwater upwellings, the sizes of flood peaks, and sediment loads. Management practices that focus on reducing or slowing runoff from upland areas and increasing channel roughness have potential to reduce flood peaks, erosion, and sedimentation and improve brook-trout habitat in all Bayfield Peninsula streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145007","collaboration":"In cooperation with the Wisconsin Department of Natural Resources","usgsCitation":"Fitzpatrick, F.A., Peppler, M.C., Saad, D.A., Pratt, D.M., and Lenz, B.N., 2015, Geomorphic, flood, and groundwater-flow characteristics of Bayfield Peninsula streams, Wisconsin, and implications for brook-trout habitat: U.S. Geological Survey Scientific Investigations Report 2014-5007, vii, 79 p., https://doi.org/10.3133/sir20145007.","productDescription":"vii, 79 p.","numberOfPages":"92","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051103","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":297884,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145007.jpg"},{"id":297883,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5007/pdf/sir2014-5007.pdf","text":"Report","size":"23.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297882,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5007/"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Bayfield Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.29638671875,\n 46.30140615437332\n ],\n [\n -91.29638671875,\n 47.07012182383309\n ],\n [\n -89.93408203124999,\n 47.07012182383309\n ],\n [\n -89.93408203124999,\n 46.30140615437332\n ],\n [\n -91.29638671875,\n 46.30140615437332\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a82e4b08de9379b30b3","contributors":{"authors":[{"text":"Fitzpatrick, Faith A. fafitzpa@usgs.gov","contributorId":1182,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith","email":"fafitzpa@usgs.gov","middleInitial":"A.","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":518619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peppler, Marie C. 0000-0002-1120-9673 mpeppler@usgs.gov","orcid":"https://orcid.org/0000-0002-1120-9673","contributorId":825,"corporation":false,"usgs":true,"family":"Peppler","given":"Marie","email":"mpeppler@usgs.gov","middleInitial":"C.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":518618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saad, David A. dasaad@usgs.gov","contributorId":121,"corporation":false,"usgs":true,"family":"Saad","given":"David","email":"dasaad@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":518617,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pratt, Dennis M.","contributorId":7673,"corporation":false,"usgs":true,"family":"Pratt","given":"Dennis","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":518620,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lenz, Bernard N.","contributorId":85170,"corporation":false,"usgs":true,"family":"Lenz","given":"Bernard","email":"","middleInitial":"N.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":518621,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70140587,"text":"fs20143098 - 2015 - Climate change: evaluating your local and regional water resources","interactions":[],"lastModifiedDate":"2015-02-09T14:43:33","indexId":"fs20143098","displayToPublicDate":"2015-02-09T14:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3098","title":"Climate change: evaluating your local and regional water resources","docAbstract":"The BCM is a fine-scale hydrologic model that uses detailed maps of soils, geology, topography, and transient monthly or daily maps of potential evapotranspiration, air temperature, and precipitation to generate maps of recharge, runoff, snow pack, actual evapotranspiration, and climatic water deficit. With these comprehensive environmental inputs and experienced scientific analysis, the BCM provides resource managers with important hydrologic and ecologic understanding of a landscape or basin at hillslope to regional scales. The model is calibrated using historical climate and streamflow data over the range of geologic materials specific to an area. Once calibrated, the model is used to translate climate-change data into hydrologic responses for a defined landscape, to provide managers an understanding of potential ecological risks and threats to water supplies and managed hydrologic systems. Although limited to estimates of unimpaired hydrologic conditions, estimates of impaired conditions, such as agricultural demand, diversions, or reservoir outflows can be incorporated into the calibration of the model to expand its utility. Additionally, the model can be linked to other models, such as groundwater-flow models (that is, MODFLOW) or the integrated hydrologic model (MF-FMP), to provide information about subsurface hydrologic processes. The model can be applied at a relatively small scale, but also can be applied to large-scale national and international river basins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143098","usgsCitation":"Flint, L.E., Flint, A.L., and Thorne, J.H., 2015, Climate change: evaluating your local and regional water resources: U.S. Geological Survey Fact Sheet 2014-3098, 6 p., https://doi.org/10.3133/fs20143098.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-045835","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":297878,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143098.JPG"},{"id":297877,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3098/pdf/fs2014-3098.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297875,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3098/"}],"publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a5ee4b08de9379b301c","contributors":{"authors":[{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540209,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thorne, James H.","contributorId":139144,"corporation":false,"usgs":false,"family":"Thorne","given":"James","email":"","middleInitial":"H.","affiliations":[{"id":12659,"text":"U C Davis","active":true,"usgs":false}],"preferred":false,"id":540210,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70134473,"text":"sir20145220 - 2015 - Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961-2010","interactions":[],"lastModifiedDate":"2015-02-06T12:59:44","indexId":"sir20145220","displayToPublicDate":"2015-02-06T13:45:00","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":"2014-5220","title":"Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961-2010","docAbstract":"The lakes, rivers, and streams of New York State provide an essential water resource for the State. The information provided by time series hydrologic data is essential to understanding ways to promote healthy instream ecology and to strengthen the scientific basis for sound water management decision making in New York. The U.S. Geological Survey, in cooperation with The Nature Conservancy and the New York State Energy Research and Development Authority, has developed the New York Streamflow Estimation Tool to estimate a daily mean hydrograph for the period from October 1, 1960, to September 30, 2010, at ungaged locations across the State. The New York Streamflow Estimation Tool produces a complete estimated daily mean time series from which daily flow statistics can be estimated. In addition, the New York Streamflow Estimation Tool provides a means for quantitative flow assessments at ungaged locations that can be used to address the objectives of the Clean Water Act—to restore and maintain the chemical, physical, and biological integrity of the Nation’s waters.
\nThe New York Streamflow Estimation Tool uses data from the U.S. Geological Survey streamflow network for selected streamgages in New York (excluding Long Island) and surrounding States with shared hydrologic boundaries, and physical and climate basin characteristics to estimate the natural unaltered streamflow at ungaged stream locations. The unaltered streamflow is representative of flows that are minimally altered by regulation, diversion, or mining, and other anthropogenic activities. With the streamflow network data, flow-duration exceedance probability equations were developed to estimate unaltered streamflow exceedance probabilities at an ungaged location using a methodology that equates streamflow as a percentile from a flow-duration curve for a particular day at a hydrologically similar reference streamgage with streamflow as a percentile from the flow-duration curve for the same day at an ungaged location. The reference streamgage is selected using map correlation, a geostatistical method in which variogram models are developed that correlate streamflow at one streamgage with streamflows at all other locations in the study area. Regression equations used to predict 17 flow-duration exceedance probabilities were developed to estimate the flow-duration curves at ungaged locations for New York using geographic information system-derived basin characteristics.
\nA graphical user interface, with an integrated spreadsheet summary report, has been developed to estimate and display the daily mean streamflows and statistics and to evaluate different water management or water withdrawal scenarios with the estimated monthly data. This package of regression equations, U.S. Geological Survey streamgage data, and spreadsheet application produces an interactive tool to estimate an unaltered daily streamflow hydrograph and streamflow statistics at ungaged sites in New York. Among other uses, the New York Streamflow Estimation Tool can assist water managers with permitting water withdrawals, implementing habitat protection, estimating contaminant loads, or determining the potential affect from chemical spills.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145220","collaboration":"Prepared in cooperation with The Nature Conservancy and the New York State Energy Research and Development Authority","usgsCitation":"Gazoorian, C.L., 2015, Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961-2010: U.S. Geological Survey Scientific Investigations Report 2014-5220, Report: viii, 29 p.; Readme; 5 Appendixes; NYSET application, https://doi.org/10.3133/sir20145220.","productDescription":"Report: viii, 29 p.; Readme; 5 Appendixes; NYSET application","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1960-10-01","temporalEnd":"2010-09-30","ipdsId":"IP-055442","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":297799,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145220.jpg"},{"id":297792,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5220/"},{"id":297793,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5220/pdf/sir2014-5220.pdf"},{"id":297794,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/sir2014-5220_readme.pdf","text":"Readme Appendix 1-5","size":"58 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":297795,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/sir2014-5220_app1-4.pdf","text":"Appendix 1-4 PDF","size":"308 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":297796,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/sir2014-5220_app1-4.xlsx","text":"Appendix 1-4 XLS","size":"75 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297797,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5220/attachments/SIR2014-5220_app5.pdf","text":"Appendix 5","size":"696 kB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"User’s Guide for the New York Streamflow Estimation Tool (NYSET) version 1.0"},{"id":297798,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://ny.water.usgs.gov/projects/nyset/","text":"NYSET application","linkFileType":{"id":5,"text":"html"}}],"scale":"200000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"New York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.771728515625,\n 42.27730877423709\n ],\n [\n -79.7607421875,\n 42.00032514831621\n ],\n [\n -75.35522460937499,\n 42.00032514831621\n ],\n [\n -75.003662109375,\n 41.46742831254425\n ],\n [\n -73.773193359375,\n 40.863679665481676\n ],\n [\n -73.487548828125,\n 41.054501963290505\n ],\n [\n -73.2568359375,\n 42.779275360241904\n ],\n [\n -73.223876953125,\n 45.01141864227728\n ],\n [\n -75.003662109375,\n 45.034714778688624\n ],\n [\n -76.5966796875,\n 44.166444664458595\n ],\n [\n -76.201171875,\n 43.58834891179792\n ],\n [\n -79.068603515625,\n 43.29320031385282\n ],\n [\n -79.771728515625,\n 42.27730877423709\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a74e4b08de9379b3070","contributors":{"authors":[{"text":"Gazoorian, Christopher L. 0000-0002-5408-6212 cgazoori@usgs.gov","orcid":"https://orcid.org/0000-0002-5408-6212","contributorId":2929,"corporation":false,"usgs":true,"family":"Gazoorian","given":"Christopher","email":"cgazoori@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":525962,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70138830,"text":"ofr20151012 - 2015 - Simulations of a hypothetical temperature control structure at Detroit Dam on the North Santiam River, northwestern Oregon","interactions":[],"lastModifiedDate":"2015-02-06T13:46:26","indexId":"ofr20151012","displayToPublicDate":"2015-02-06T13:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1012","title":"Simulations of a hypothetical temperature control structure at Detroit Dam on the North Santiam River, northwestern Oregon","docAbstract":"Water temperature models of Detroit Lake, Big Cliff Lake, and the North Santiam River in northwestern Oregon were used to assess the potential for a hypothetical structure with variable intake elevations and an internal connection to power turbines at Detroit Dam (scenario SlidingWeir) to release more natural, pre-dam temperatures year round. This hypothetical structure improved outflow temperature control from Detroit Dam while meeting minimum dry-season release rates and lake levels specified by the rule curve specified for Detroit Lake.
\nA water temperature target based on long-term, without-dams temperature estimates was developed and used to guide the Detroit Lake model to blend releases from the user-defined outlets at Detroit Dam. Simulations that included warm surface water releases during the spring and summer, and cool, deep hypolimnetic water releases later during autumn typically met the temperature target. Immediately downstream of Detroit Dam, these simulations resulted in temperatures within the range of the without-dams temperature estimates for most of the year until about November. The minimum release rates of flow imposed at Detroit Dam during late summer and early autumn exceeded unregulated, without-dams flow estimates. This higher flow led to temperatures near the low end of the without-dams temperature range 46.3 river miles downstream at Greens Bridge from July to September; the high flows released from Detroit Dam were less susceptible to downstream warming than the low unregulated flows. Simulations that blended warm and cool water from different outlets at Detroit Dam resulted in less daily temperature variation compared to the without-dams scenarios as far downstream as Greens Bridge.
\nEstimated egg-emergence days for endangered Upper Willamette River Chinook salmon (Oncorhynchus tshawytscha) and Upper Willamette River winter steelhead (Oncorhynchus mykiss) were assessed for all scenarios. Estimated spring Chinook fry emergence under SlidingWeir scenarios was 9 days later immediately downstream of Big Cliff Dam, and 4 days later at Greens Bridge compared with existing structural scenarios at Detroit Dam. Despite the inclusion of a hypothetical sliding weir at Detroit Dam, temperatures exceeded without-dams temperatures during November and December. These late-autumn exceedances likely represent the residual thermal effect of Detroit Lake operated to meet minimum dry-season release rates (supporting instream habitat and irrigation requirements) and lake levels specified by the current (2014) operating rules (supporting recreation and flood mitigation).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151012","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Buccola, N.L., Stonewall, A.J., and Rounds, S.A., 2015, Simulations of a hypothetical temperature control structure at Detroit Dam on the North Santiam River, northwestern Oregon: U.S. Geological Survey Open-File Report 2015-1012, vi, 30 p., https://doi.org/10.3133/ofr20151012.","productDescription":"vi, 30 p.","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057390","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":297807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151012.JPG"},{"id":297805,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1012/"},{"id":297806,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1012/pdf/ofr2015-1012.pdf","text":"Report","size":"4.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"projection":"Universal Transverse Mercator projection, Zone 10","datum":"North American Datum of 1927","country":"United States","state":"Oregon","otherGeospatial":"Big Cliff Lake, Detroit Lake, North Santiam River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.20068359374999,\n 44.469071224701096\n ],\n [\n -123.20068359374999,\n 44.912304304581525\n ],\n [\n -121.77246093750001,\n 44.912304304581525\n ],\n [\n -121.77246093750001,\n 44.469071224701096\n ],\n [\n -123.20068359374999,\n 44.469071224701096\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ab4e4b08de9379b3194","contributors":{"authors":[{"text":"Buccola, Norman L. nbuccola@usgs.gov","contributorId":139094,"corporation":false,"usgs":true,"family":"Buccola","given":"Norman","email":"nbuccola@usgs.gov","middleInitial":"L.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stonewall, Adam J. 0000-0002-3277-8736 stonewal@usgs.gov","orcid":"https://orcid.org/0000-0002-3277-8736","contributorId":138801,"corporation":false,"usgs":true,"family":"Stonewall","given":"Adam","email":"stonewal@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":540000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540001,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70140180,"text":"ofr20151027 - 2015 - Improved algorithms in the CE-QUAL-W2 water-quality model for blending dam releases to meet downstream water-temperature targets","interactions":[],"lastModifiedDate":"2015-02-06T12:51:55","indexId":"ofr20151027","displayToPublicDate":"2015-02-06T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1027","title":"Improved algorithms in the CE-QUAL-W2 water-quality model for blending dam releases to meet downstream water-temperature targets","docAbstract":"Water-quality models allow water resource professionals to examine conditions under an almost unlimited variety of potential future scenarios. The two-dimensional (longitudinal, vertical) water-quality model CE-QUAL-W2, version 3.7, was enhanced and augmented with new features to help dam operators and managers explore and optimize potential solutions for temperature management downstream of thermally stratified reservoirs. Such temperature management often is accomplished by blending releases from multiple dam outlets that access water of different temperatures at different depths. The modified blending algorithm in version 3.7 of CE-QUAL-W2 allows the user to specify a time-series of target release temperatures, designate from 2 to 10 floating or fixed-elevation outlets for blending, impose minimum and maximum head and flow constraints for any blended outlet, and set priority designations for each outlet that allow the model to choose which outlets to use and how to balance releases among them. The modified model was tested with a variety of examples and against a previously calibrated model of Detroit Lake on the North Santiam River in northwestern Oregon, and the results compared well. These updates to the blending algorithms will allow more complicated dam-operation scenarios to be evaluated somewhat automatically with the model, with decreased need for multiple model runs or preprocessing of model inputs to fully characterize the operational constraints.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151027","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Rounds, S.A., and Buccola, N., 2015, Improved algorithms in the CE-QUAL-W2 water-quality model for blending dam releases to meet downstream water-temperature targets: U.S. Geological Survey Open-File Report 2015-1027, Report: vi, 36 p.; Examples; Model Source, https://doi.org/10.3133/ofr20151027.","productDescription":"Report: vi, 36 p.; Examples; Model Source","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057372","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":297791,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151027.JPG"},{"id":297788,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1027/pdf/ofr2015-1027.pdf","text":"Report","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297787,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1027/"},{"id":297789,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1027/downloads/ofr2015-1027_code_changes_examples.zip","text":"Examples","size":"17.2 MB","description":"Examples"},{"id":297790,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1027/downloads/ofr2015-1027_code_changes_model_source.zip","text":"Model Source","size":"2.7 MB","description":"Model Source"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a88e4b08de9379b30da","contributors":{"authors":[{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buccola, Norman L. nbuccola@usgs.gov","contributorId":138859,"corporation":false,"usgs":true,"family":"Buccola","given":"Norman L.","email":"nbuccola@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539981,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70137743,"text":"sir20155004 - 2015 - Climate change and prairie pothole wetlands: mitigating water-level and hydroperiod effects through upland management","interactions":[],"lastModifiedDate":"2018-01-05T10:15:53","indexId":"sir20155004","displayToPublicDate":"2015-02-06T11:15:00","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":"2015-5004","title":"Climate change and prairie pothole wetlands: mitigating water-level and hydroperiod effects through upland management","docAbstract":"Prairie pothole wetlands offer crucial habitat for North America’s waterfowl populations. The wetlands also support an abundance of other species and provide ecological services valued by society. The hydrology of prairie pothole wetlands is dependent on atmospheric interactions. Therefore, changes to the region’s climate can have profound effects on wetland hydrology. The relevant literature related to climate change and upland management effects on prairie pothole wetland water levels and hydroperiods was reviewed. Climate change is widely expected to affect water levels and hydroperiods of prairie pothole wetlands, as well as the biota and ecological services that the wetlands support. In general, hydrologic model projections that incorporate future climate change scenarios forecast lower water levels in prairie pothole wetlands and longer periods spent in a dry condition, despite potential increases in precipitation. However, the extreme natural variability in climate and hydrology of prairie pothole wetlands necessitates caution when interpreting model results. Recent changes in weather patterns throughout much of the Prairie Pothole Region have been in increased precipitation that results in increased water inputs to wetlands above losses associated with warmer temperatures. However, observed precipitation increases are within the range of natural climate variability and therefore, may not persist. Identifying management techniques with the potential to affect water inputs to prairie pothole wetlands would provide increased options for managers when dealing with the uncertainties associated with a changing climate. Several grassland management techniques (for example, grazing and burning) have the potential to affect water levels and hydroperiods of prairie pothole by affecting infiltration, evapotranspiration, and snow deposition.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155004","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and North Dakota State University","usgsCitation":"Renton, D., Mushet, D.M., and DeKeyser, E., 2015, Climate change and prairie pothole wetlands: mitigating water-level and hydroperiod effects through upland management: U.S. Geological Survey Scientific Investigations Report 2015-5004, 32 p., https://doi.org/10.3133/sir20155004.","productDescription":"32 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059680","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":297781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155004.jpg"},{"id":297779,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5004/"},{"id":297780,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5004/pdf/sir2015-5004.pdf","text":"Report","size":"3.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"Canada, United States","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.9169921875,\n 54.03358633521085\n ],\n [\n -114.82910156249999,\n 48.1367666796927\n ],\n [\n -102.4365234375,\n 46.619261036171515\n ],\n [\n -98.8330078125,\n 43.32517767999296\n ],\n [\n -95.00976562499999,\n 41.541477666790286\n ],\n [\n -91.8896484375,\n 41.50857729743935\n ],\n [\n -92.021484375,\n 45.644768217751924\n ],\n [\n -96.3720703125,\n 50.65294336725709\n ],\n [\n -101.77734374999999,\n 52.802761415419674\n ],\n [\n -114.9169921875,\n 54.03358633521085\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a5ee4b08de9379b301a","contributors":{"authors":[{"text":"Renton, David A. drenton@usgs.gov","contributorId":138600,"corporation":false,"usgs":true,"family":"Renton","given":"David A.","email":"drenton@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":539966,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":539965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeKeyser, Edward S.","contributorId":138601,"corporation":false,"usgs":false,"family":"DeKeyser","given":"Edward S.","affiliations":[{"id":12459,"text":"NDSU","active":true,"usgs":false}],"preferred":false,"id":539967,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70140268,"text":"70140268 - 2015 - Long-term plant responses to climate are moderated by biophysical attributes in a North American desert","interactions":[],"lastModifiedDate":"2017-11-27T08:44:57","indexId":"70140268","displayToPublicDate":"2015-02-06T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Long-term plant responses to climate are moderated by biophysical attributes in a North American desert","docAbstract":"A regional, two-dimensional, steady-state groundwater-flow model was developed to simulate the groundwater-flow system and groundwater/surface-water interactions within the Menominee Indian Reservation. The model was developed by the U.S. Geological Survey (USGS), in cooperation with the Menominee Indian Tribe of Wisconsin, to contribute to the fundamental understanding of the region’s hydrogeology. The objectives of the regional model were to improve understanding of the groundwater-flow system, including groundwater/surface-water interactions, and to develop a tool suitable for evaluating the effects of potential regional water-management programs. The computer code GFLOW was used because of the ease with which the model can simulate groundwater/surface-water interactions, provide a framework for simulating regional groundwater-flow systems, and be refined in a stepwise fashion to incorporate new data and simulate groundwater-flow patterns at multiple scales. Simulations made with the regional model reproduce groundwater levels and stream base flows representative of recent conditions (1970–2013) and illustrate groundwater-flow patterns with maps of (1) the simulated water table and groundwater-flow directions, (2) probabilistic areas contributing recharge to high-capacity pumped wells, and (3) estimation of the extent of infiltrated wastewater from treatment lagoons.
\nThe groundwater-flow model described in this report simulates the major hydrogeologic features of the modeled area, including surficial unconsolidated aquifers, groundwater/surface-water interactions, and groundwater withdrawals from existing high-capacity production wells. Areas contributing recharge to pumped high-capacity wells on the Menominee Indian Reservation were delineated by tracking simulated water particles from the water table to wells in combination with Monte Carlo techniques, and maps of the probability of capture for each well nest were produced. Groundwater-agebased areas contributing recharge to wells were simulated by using the calibrated set of parameters and porosity values adjusted to account for bias in simulated saturated thickness. Simulations were performed for current (2013) pumping rates. The simulations show a range in sensitivity of the simulated areas contributing recharge to wells given the parameters evaluated through the Monte Carlo analysis. The areas contributing recharge to supply wells for the villages of Zoar and Neopit are long and narrow, with a sharp gradation from high to low probability of capture. The areas contributing recharge to supply wells for Middle Village and the village of Keshena exhibit a sharp gradation from high to low probability over a relatively small area between the well and a local groundwater mound. The highest probability areas contributing recharge to the supply wells for the Villages of Onekewat and Redwing are in the immediate vicinity of the wells. These wells also have an extensive area with low probability for capturing water that is likely due to a locally low hydraulic gradient and the large degree of uncertainty associated with the lakebed resistance parameters that control interaction between groundwater and local lakes. Additional field investigations and associated local model refinements would facilitate further reductions in uncertainty associated with simulated areas contributing recharge to the wells.
\nThe likely extent of the Neopit wastewater plume was simulated by using the groundwater-flow model and Monte Carlo techniques to evaluate the sensitivity of predictive simulations to a range of model parameter values. Wastewater infiltrated from the currently operating lagoons flows predominantly south toward Tourtillotte Creek. Some of the infiltrated wastewater is simulated as having a low probability of flowing beneath Tourtillotte Creek to the nearby West Branch Wolf River. Results for the probable extent of the wastewater plume are considered to be qualitative because the method only considers advective flow and does not account for processes affecting contaminant transport in porous media. Therefore, results for the probable extent of the wastewater plume are sensitive to the number of particles used to represent flow from the lagoon and the resolution of a synthetic grid used for the analysis. Nonetheless, it is expected that the qualitative results may be of use for identifying potential downgradient areas of concern that can then be evaluated using the quantitative “area contributing recharge to wells” method or traditional contaminant-transport simulations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145237","collaboration":"In cooperation with the Menominee Indian Tribe of Wisconsin","usgsCitation":"Juckem, P.F., and Dunning, C., 2015, Simulation of the regional groundwater-flow system of the Menominee Indian Reservation, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2014-5237, Report: vi, 40 p.; 1 Appendix, https://doi.org/10.3133/sir20145237.","productDescription":"Report: vi, 40 p.; 1 Appendix","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051827","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":297772,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145237.jpg"},{"id":297770,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5237/pdf/sir2014-5237.pdf","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297771,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5237/appendix/sir2014-5237_appendix1.xlsx","text":"Appendix 1","size":"43 kB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"Data from auger surveys near the Villages of Neopit, Zoar, and Keshena."},{"id":297768,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5237/"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Menominee Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.98376464843749,\n 45.11133093583214\n ],\n [\n -88.98239135742188,\n 44.94633342311665\n ],\n [\n -88.73794555664062,\n 44.94438944516438\n ],\n [\n -88.7310791015625,\n 44.85100108620397\n ],\n [\n -88.47152709960938,\n 44.8490538825394\n ],\n [\n -88.472900390625,\n 45.11326925230233\n ],\n [\n -88.98376464843749,\n 45.11133093583214\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ab4e4b08de9379b3192","contributors":{"authors":[{"text":"Juckem, Paul F. 0000-0002-3613-1761 pfjuckem@usgs.gov","orcid":"https://orcid.org/0000-0002-3613-1761","contributorId":1905,"corporation":false,"usgs":true,"family":"Juckem","given":"Paul","email":"pfjuckem@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539963,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunning, Charles P. cdunning@usgs.gov","contributorId":892,"corporation":false,"usgs":true,"family":"Dunning","given":"Charles P.","email":"cdunning@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539964,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}