It is asserted that reduction or elimination of hatchery stocking will increase natural‐origin salmon Oncorhynchus spp. and steelhead O. mykiss production. We conducted an analysis of steelhead population census data (1958–2017) to determine whether elimination of summer steelhead stocking in the upper Clackamas River in 1998 increased the productivity of natural‐origin winter steelhead. A Bayesian state–space stock–recruitment model was fitted to the adult steelhead data set, and productivity was estimated as a function of hatchery‐origin spawner abundance as well as other environmental factors. When used as a predictive variable in our model, the abundance of hatchery summer steelhead spawners (1972–2001) did not have a negative effect on winter steelhead recruitment. However, spill at North Fork Dam (the gateway to the upper Clackamas River basin) and the Pacific Decadal Oscillation (an index of ocean conditions) were both negatively associated with winter steelhead recruitment. Moreover, winter steelhead abundance in the upper Clackamas River basin failed to rebound to abundances observed in years prior to the hatchery program, and fluctuations in winter steelhead abundance were correlated with those of other regional winter steelhead stocks. Our assessment underscores the need for studies that (1) directly quantify the effects of hatchery fish on the production of natural‐origin salmon and steelhead, (2) empirically test published theories about mechanisms of hatchery fish impacts on natural‐origin populations, and (3) document population responses to major changes in hatchery programs.
","language":"English","publisher":"American Fisheries Society ","doi":"10.1002/tafs.10140","usgsCitation":"Courter, I.I., Wyatt, G.J., Perry, R., Plumb, J., Carpenter, F.M., Ackerman, N.K., Lessard, R.B., and Galbreath, P., 2018, A natural‐origin steelhead population's response to exclusion of hatchery fish: Transactions of the American Fisheries Society, v. 148, no. 2, p. 339-351, https://doi.org/10.1002/tafs.10140.","productDescription":"13 p.","startPage":"339","endPage":"351","ipdsId":"IP-098370","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":468181,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10140","text":"Publisher Index Page"},{"id":363055,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":" Clackamas River ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.73376464843749,\n 45.0657615477031\n ],\n [\n -121.73263549804688,\n 45.0657615477031\n ],\n [\n -121.73263549804688,\n 45.45724086262233\n ],\n [\n -122.73376464843749,\n 45.45724086262233\n ],\n [\n -122.73376464843749,\n 45.0657615477031\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"148","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Courter, Ian I","contributorId":214903,"corporation":false,"usgs":false,"family":"Courter","given":"Ian","email":"","middleInitial":"I","affiliations":[{"id":39134,"text":"Mount Hood Environmental, P.O. Box 744, Boring, Oregon 97009","active":true,"usgs":false}],"preferred":false,"id":761132,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wyatt, Garth J","contributorId":214904,"corporation":false,"usgs":false,"family":"Wyatt","given":"Garth","email":"","middleInitial":"J","affiliations":[{"id":39135,"text":"Portland General Electric, 33831 Faraday Rd., Estacada, Oregon 97023","active":true,"usgs":false}],"preferred":false,"id":761133,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perry, Russell 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":214905,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":761134,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plumb, John 0000-0003-4255-1612 jplumb@usgs.gov","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":214906,"corporation":false,"usgs":true,"family":"Plumb","given":"John","email":"jplumb@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":761135,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carpenter, Forrest M","contributorId":214907,"corporation":false,"usgs":false,"family":"Carpenter","given":"Forrest","email":"","middleInitial":"M","affiliations":[{"id":39134,"text":"Mount Hood Environmental, P.O. Box 744, Boring, Oregon 97009","active":true,"usgs":false}],"preferred":false,"id":761136,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ackerman, Nicklaus K","contributorId":214552,"corporation":false,"usgs":false,"family":"Ackerman","given":"Nicklaus","email":"","middleInitial":"K","affiliations":[{"id":39068,"text":"Portland General Electric, Estacada, OR","active":true,"usgs":false}],"preferred":false,"id":761137,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lessard, Robert B","contributorId":214908,"corporation":false,"usgs":false,"family":"Lessard","given":"Robert","email":"","middleInitial":"B","affiliations":[{"id":39136,"text":"Columbia River Intertribal Fish Commission, 700 NE Multnomah St., Portland, Oregon 97232","active":true,"usgs":false}],"preferred":false,"id":761138,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Galbreath, Peter F","contributorId":214909,"corporation":false,"usgs":false,"family":"Galbreath","given":"Peter F","affiliations":[{"id":39136,"text":"Columbia River Intertribal Fish Commission, 700 NE Multnomah St., Portland, Oregon 97232","active":true,"usgs":false}],"preferred":false,"id":761139,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70201105,"text":"sir20185162 - 2018 - Simulation of groundwater storage changes in the Quincy Basin, Washington","interactions":[],"lastModifiedDate":"2018-12-19T15:47:47","indexId":"sir20185162","displayToPublicDate":"2018-12-18T15:30:10","publicationYear":"2018","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":"2018-5162","displayTitle":"Simulation of Groundwater Storage Changes in the Quincy Basin, Washington","title":"Simulation of groundwater storage changes in the Quincy Basin, Washington","docAbstract":"The Miocene Columbia River Basalt Group and younger sedimentary deposits of lacustrine, fluvial, eolian, and cataclysmic-flood origins compose the aquifer system of the Quincy Basin in eastern Washington. Irrigation return flow and canal leakage from the Columbia Basin Project have caused groundwater levels to rise substantially in some areas. Water resource managers are considering extraction of additional stored groundwater to supply increasing demand. To help address these concerns, the transient groundwater model of the Quincy Basin documented in this report was developed to quantify the changes in groundwater flow and storage.
The model based on the U.S. Geological Survey modular three-dimensional finite-difference numerical code MODFLOW uses a 1-kilometer finite-difference grid and is constrained by logs from 698 wells in the study area. Five model layers represent two sedimentary hydrogeologic units and underlying basalt formations. Head-dependent flux boundaries represent the Columbia River and other streams, lakes and reservoirs, underflow to and (or) from adjacent areas, and discharge to agricultural drains and springs. Specified flux boundaries represent recharge from precipitation and anthropogenic sources, including irrigation return flow and leakage from water-distribution canals and discharge through groundwater withdrawal wells. Transient conditions were simulated from 1920 to 2013 using annual stress periods. The model was calibrated with the parameter-estimation code PEST to a total of 4,064 water levels measured in 710 wells. Increased recharge since predevelopment resulted in an 11.5 million acre-feet increase in storage in the Quincy Groundwater Management Subarea of the Quincy Basin.
Four groundwater-management scenarios were formulated with input from project stakeholders and were simulated using the calibrated model to provide representative examples of how the model could be used to evaluate the effect on groundwater levels as a result of potential changes in recharge, groundwater withdrawals, or increased flow in Crab Creek. Decreased recharge and increased groundwater withdrawals both resulted in declines in groundwater levels over 2013 conditions, whereas increasing the flow in Crab Creek resulted in increased groundwater levels over 2013 conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185162","collaboration":"Prepared in cooperation with the Washington State Department of Ecology and the Bureau of Reclamation","usgsCitation":"Frans, L.M., Kahle, S.C., Tecca, A.E., and Olsen, T.D., 2018, Simulation of groundwater storage changes in the Quincy Basin, Washington: U.S. Geological Survey Scientific Investigations Report 2018-5162, 63 p., https://doi.org/10.3133/sir20185162.","productDescription":"Report: viii, 63 p.; Model archive","onlineOnly":"Y","ipdsId":"IP-098440","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":437647,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MCIR8M","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used to simulate groundwater storage changes in the Quincy Basin, Washington"},{"id":360527,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5162/coverthb.jpg"},{"id":360528,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5162/sir20185162.pdf","text":"Report","size":"17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5162"},{"id":360529,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://doi.org/10.5066/P9MCIR8M","text":"USGS model archive —","description":"USGS Model Archive","linkHelpText":"MODFLOW-NWT model used in Simulation of Groundwater Storage Changes in the Quincy Basin, Washington"}],"country":"United States","state":"Washington","otherGeospatial":"Quincy Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.13275146484374,\n 46.61548796222358\n ],\n [\n -118.52874755859376,\n 46.61548796222358\n ],\n [\n -118.52874755859376,\n 47.615421267605434\n ],\n [\n -120.13275146484374,\n 47.615421267605434\n ],\n [\n -120.13275146484374,\n 46.61548796222358\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Animals co‐occurring in a region (sympatry) may use the same habitat (syntopy) within that region. A central aim in ecology is determining what factors drive species distributions (i.e., abiotic conditions, dispersal limitations, and/or biotic interactions). Assessing the degree of biotic interactions can be difficult for species with wide ranges at sea. This study investigated the spatial ecology of two sea turtle species that forage on benthic invertebrates in neritic GoM waters: Kemp's ridleys (Lepidochelys kempii) and loggerheads (Caretta caretta). We used satellite tracking and modeled behavioral modes, then calculated individual home ranges, compared foraging areas, and determined extent of co‐occurrence. Using six environmental variables and principal component analysis, we assessed similarity of chosen foraging sites. We predicted foraging location (eco‐region) based on species, nesting site, and turtle size. For 127 turtles (64 Kemp's ridleys, 63 loggerheads) tracked from 1989 to 2013, foraging home ranges were nine to ten times larger for Kemp's ridleys than for loggerheads. Species intersected off all U.S. coasts and the Yucatán Peninsula, but co‐occurrence areas were small compared to species' distributions. Kemp's ridley foraging home ranges were concentrated in the northern GoM, whereas those for loggerheads were concentrated in the eastern GoM. The two species were different in all habitat variables compared (latitude, longitude, distance to shore, net primary production, mean sea surface temperature, and bathymetry). Nesting site was the single dominant variable that dictated foraging ecoregion. Although Kemp's ridleys and loggerheads may compete for resources, the separation in foraging areas, significant differences in environmental conditions, and importance of nesting location on ecoregion selection (i.e., dispersal ability) indicate that adult females of these species do not interact greatly during foraging and that dispersal and environmental factors more strongly determine their distributions. These species show sympatry in this region but evidence for syntopy was rare.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4691","usgsCitation":"Hart, K., Iverson, A., Fujisaki, I., Lamont, M.M., Bucklin, D.N., and Shaver, D.J., 2018, Sympatry or syntopy? Investigating drivers of distribution and co‐occurrence for two imperiled sea turtle species in Gulf of Mexico neritic waters: Ecology and Evolution, v. 8, no. 24, p. 12656-12669, https://doi.org/10.1002/ece3.4691.","productDescription":"14 p.","startPage":"12656","endPage":"12669","ipdsId":"IP-091384","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468182,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4691","text":"Publisher Index Page"},{"id":360480,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99,\n 18\n ],\n [\n -81,\n 18\n ],\n [\n -81,\n 32\n ],\n [\n -99,\n 32\n ],\n [\n -99,\n 18\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"24","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-26","publicationStatus":"PW","scienceBaseUri":"5c1a1530e4b0708288c23514","contributors":{"authors":[{"text":"Hart, Kristen M. 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":209782,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":754495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iverson, Autumn R. 0000-0002-8353-6745","orcid":"https://orcid.org/0000-0002-8353-6745","contributorId":173555,"corporation":false,"usgs":false,"family":"Iverson","given":"Autumn R.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":754496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fujisaki, Ikuko","contributorId":38359,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","affiliations":[],"preferred":false,"id":754497,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lamont, Margaret M. 0000-0001-7520-6669 mlamont@usgs.gov","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":4525,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","email":"mlamont@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":754498,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bucklin, David N.","contributorId":175273,"corporation":false,"usgs":false,"family":"Bucklin","given":"David","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":754499,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shaver, Donna J.","contributorId":191186,"corporation":false,"usgs":false,"family":"Shaver","given":"Donna","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":754500,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70201248,"text":"fs20183078 - 2018 - Comparing groundwater quality in public-supply and shallow aquifers in the Monterey Bay and Salinas Valley Basins, California","interactions":[],"lastModifiedDate":"2018-12-18T16:15:02","indexId":"fs20183078","displayToPublicDate":"2018-12-18T13:46:42","publicationYear":"2018","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":"2018-3078","displayTitle":"Comparing Groundwater Quality in Public-Supply and Shallow Aquifers in the Monterey Bay and Salinas Valley Basins, California","title":"Comparing groundwater quality in public-supply and shallow aquifers in the Monterey Bay and Salinas Valley Basins, California","docAbstract":"Groundwater provides more than 40 percent of California’s drinking water. To protect this vital resource, the State of California created the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The Priority Basin Project of the GAMA Program (GAMA-PBP) provides a comprehensive assessment of the State’s groundwater quality and increases public access to groundwater-quality information.
Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The Yankee Fork of the Salmon River is one of the larger watersheds in the upper Salmon River subbasin of central Idaho. Mining activities since the late 19th century, specifically placer mining and associated dredging from 1940 to 1953, have left the fluvial system in a highly altered and unnatural state. To improve aquatic and terrestrial habitat in the Yankee Fork, the Bureau of Reclamation and other stakeholders collaborated on the Dredge Tailings Restoration Project and Yankee Fork Rehabilitation Project. In conjunction with these rehabilitation efforts, the U.S. Geological Survey monitored suspended-sediment transport and discharge between 2012 and 2015 at three sites in the lower reaches of the Yankee Fork. Pseudo-hydrographs were developed for the Bonanza and Confluence sites using data from the streamgage site as a surrogate. Results showed a good fit between measured and calculated discharge with R2 values of 0.96 for the Bonanza site and 0.98 for the Confluence site. Both regressions have high hypothesis test statistics (t>23) and low probability values (p<0.0001), indicating a strong linear correlation. Suspended-sediment samples collected mostly during snowmelt runoff showed a positive correlation with stream discharge. Hysteresis in the sample results indicates a supply-limited suspended-sediment transport regime. Percent sand by weight of suspended-sediment samples identified a possible discharge threshold for sand suspension at about 400 cubic feet per second (ft3/s) at the Bonanza site and about 1,000 ft3/s at the Confluence and Gage sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181189","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Johnsen, J.W., 2018, Sediment transport monitoring of the Yankee Fork of the Salmon River near Stanley, Idaho, 2012–15: U.S. Geological Survey Open-File Report 2018-1189, 17 p., https://doi.org/10.3133/ofr20181189.","productDescription":"iv, 17 p.","onlineOnly":"Y","ipdsId":"IP-090600","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":360434,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1189/coverthb.jpg"},{"id":360435,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1189/ofr20181189.pdf","text":"Report","size":"12.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1189"}],"country":"United States","state":"Idaho","city":"Stanley","otherGeospatial":"Salmon River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.4892,\n 43.5222\n ],\n [\n -114.2392,\n 43.5222\n ],\n [\n -114.2392,\n 44.7725\n ],\n [\n -115.4892,\n 44.7725\n ],\n [\n -115.4892,\n 43.5222\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
Researchers from the U.S. Geological Survey (USGS) conducted a long-term coastal morphologic-change study at Fire Island, New York, prior to and after Hurricane Sandy impacted the area in October 2012. The Fire Island Coastal Change project objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related effects, post-storm beach response, and recovery. In April 2016, scientists from the USGS St. Petersburg Coastal and Marine Science Center conducted sediment sampling and geophysical surveys on Fire Island to characterize and quantify spatial variability in the subaerial geology with the goal of subsequently integrating onshore geology with other surf zone and nearshore datasets.
This report, along with the accompanying USGS data release, serves as an archive of sediment data from 14 vibracores collected on April 10 and 11, 2016 (USGS Field Activity Number 2016–322–FA), along 6 transects that extend from the upper to lower subaerial shoreface at Fire Island. Sedimentologic and stratigraphic metrics (for example, sediment texture or unit thicknesses) derived from these data can be used to assess spatial and temporal trends and may aid in understanding beach evolution. Data products include sample location tables, descriptive core logs, core photographs, results of sediment grain-size analyses, and geographic information system data files with accompanying formal Federal Geographic Data Committee metadata.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1100","usgsCitation":"Buster, N.A., Bernier, J.C., Brenner, O.T., Kelso, K.W., Tuten, T.M., and Miselis, J.L., 2018, Sediment data from vibracores collected in 2016 from Fire Island, New York: U.S. Geological Survey Data Series 1100, https://doi.org/10.3133/ds1100.","productDescription":"HTML Document; Data Release","ipdsId":"IP-099448","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":437649,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91P1T88","text":"USGS data release","linkHelpText":"Sediment Data From Vibracores and Sand Augers Collected in 2021 and 2022 From Fire Island, New York"},{"id":359473,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1100/coverthb.jpg"},{"id":359475,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FN15GX","text":"USGS data release","description":"USGS data release"},{"id":359474,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1100/","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"DS 1100"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.32069396972655,\n 40.60926110386811\n ],\n [\n -72.74871826171875,\n 40.60926110386811\n ],\n [\n -72.74871826171875,\n 40.77534183237267\n ],\n [\n -73.32069396972655,\n 40.77534183237267\n ],\n [\n -73.32069396972655,\n 40.60926110386811\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
Influenza A viruses (IAVs) are maintained in wild waterbirds and have the potential to infect a broad range of species, including wild mammals. The Arctic Coastal Plain of Alaska supports a diverse suite of species, including waterfowl that are common hosts of IAVs. Mammals co-occur with geese and other migratory waterbirds during the summer breeding season, providing a plausible mechanism for interclass transmission of IAVs. To estimate IAV seroprevalence and identify the subtypes to which geese, loons, Arctic foxes (Vulpes lagopus), caribou (Rangifer tarandus), and polar bears (Ursus maritimus) are potentially exposed, we used a blocking enzyme-linked immunosorbent assay (bELISA) and a hemagglutination inhibition (HI) assay to screen for antibodies to IAVs in samples collected during spring and summer of 2012–16. Apparent IAV seroprevalence using the bELISA was 50.7% in geese (range by species: 46.1–52.8%), 9.2% in loons, (range by species: 3.4–20.0%), and 0.4% in Arctic foxes. We found no evidence for exposure to IAVs in polar bears or caribou by either assay. Among geese, we estimated detection probability from replicate bELISA analyses to be 0.92 and also found good concordance (>85%) between results from bELISA and HI assays, which identified antibodies reactive to H1, H6, and H9 subtype IAVs. In contrast, the HI assay detected antibodies in only one of seven loon samples that were positive by bELISA; that sample had low titers to both H4 and H5 IAV subtypes. Our results provide evidence that a relatively high proportion of waterbirds breeding on the Arctic Coastal Plain are exposed to IAVs, although it is unknown whether such exposure occurs locally or on staging or wintering grounds. In contrast, seroprevalence of IAVs in concomitant mammals is apparently low.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2018-05-128","usgsCitation":"Van Hemert, C.R., Spivey, T.J., Uher-Koch, B.D., Atwood, T.C., Sinnett, D.R., Meixell, B.W., Hupp, J.W., Jiang, K., Adams, L., Gustine, D.D., Ramey, A.M., and Wan, X., 2018, Survey of Arctic Alaskan wildlife for influenza A antibodies: Limited evidence for exposure of mammals: Journal of Wildlife Diseases, v. 55, no. 2, p. 387-398, https://doi.org/10.7589/2018-05-128.","productDescription":"12 p.","startPage":"387","endPage":"398","ipdsId":"IP-097920","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":437650,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FPXQTP","text":"USGS data release","linkHelpText":"Serological Data on Influenza A from Birds and Mammals on the Arctic Coastal Plain of Northern Alaska, 2011-2017"},{"id":360442,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -160,\n 69\n ],\n [\n -149.5,\n 69\n ],\n [\n -149.5,\n 71.5\n ],\n [\n -160,\n 71.5\n ],\n [\n -160,\n 69\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c1a1531e4b0708288c23520","contributors":{"authors":[{"text":"Van Hemert, Caroline R. 0000-0002-6858-7165 cvanhemert@usgs.gov","orcid":"https://orcid.org/0000-0002-6858-7165","contributorId":3592,"corporation":false,"usgs":true,"family":"Van 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bmeixell@usgs.gov","orcid":"https://orcid.org/0000-0002-6738-0349","contributorId":138716,"corporation":false,"usgs":true,"family":"Meixell","given":"Brandt","email":"bmeixell@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":754483,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hupp, Jerry W. 0000-0002-6439-3910 jhupp@usgs.gov","orcid":"https://orcid.org/0000-0002-6439-3910","contributorId":127803,"corporation":false,"usgs":true,"family":"Hupp","given":"Jerry","email":"jhupp@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":754484,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jiang, Kaijun","contributorId":211603,"corporation":false,"usgs":false,"family":"Jiang","given":"Kaijun","email":"","affiliations":[],"preferred":false,"id":754485,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Adams, Layne G. 0000-0001-6212-2896 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2896","contributorId":2776,"corporation":false,"usgs":true,"family":"Adams","given":"Layne G.","email":"ladams@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":754486,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gustine, David D. 0000-0003-1087-1937","orcid":"https://orcid.org/0000-0003-1087-1937","contributorId":201734,"corporation":false,"usgs":false,"family":"Gustine","given":"David","email":"","middleInitial":"D.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":754487,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":754488,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wan, Xiu-Feng","contributorId":173959,"corporation":false,"usgs":false,"family":"Wan","given":"Xiu-Feng","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":754489,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70201673,"text":"70201673 - 2018 - Storm surge propagation and flooding in small tidal rivers during events of mixed coastal and fluvial influence","interactions":[],"lastModifiedDate":"2018-12-20T15:36:37","indexId":"70201673","displayToPublicDate":"2018-12-17T15:36:30","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Storm surge propagation and flooding in small tidal rivers during events of mixed coastal and fluvial influence","docAbstract":"The highly urbanized estuary of San Francisco Bay is an excellent example of a location susceptible to flooding from both coastal and fluvial influences. As part of developing a forecast model that integrates fluvial and oceanic drivers, a case study of the Napa River and its interactions with the San Francisco Bay was performed. For this application we utilize Delft3D-FM, a hydrodynamic model that computes conservation of mass and momentum on a flexible mesh grid, to calculate water levels that account for tidal forcing, storm surge generated by wind and pressure fields, and river flows. We simulated storms with realistic atmospheric pressure, river discharge, and tidal forcing to represent a realistic joint fluvial and coastal storm event. Storm conditions were applied to both a realistic field-scale Napa river drainage as well as an idealized geometry. With these scenarios, we determine how the extent, level, and duration of flooding is dependent on these atmospheric and hydrologic parameters. Unsurprisingly, the model indicates that maximal water levels will occur in a tidal river when high tides, storm surge, and large fluvial discharge events are coincident. Model results also show that large tidal amplitudes diminish storm surge propagation upstream and that phasing between peak fluvial discharges and high tide is important for predicting when and where the highest water levels will occur. The interactions between tides, river discharge, and storm surge are not simple, indicating the need for more integrated flood forecasting models in the future.
","language":"English","publisher":"MDPI","doi":"10.3390/jmse6040158","usgsCitation":"Herdman, L.M., Erikson, L.H., and Barnard, P., 2018, Storm surge propagation and flooding in small tidal rivers during events of mixed coastal and fluvial influence: Journal of Marine Science and Engineering, v. 6, no. 4, p. 1-26, https://doi.org/10.3390/jmse6040158.","productDescription":"Article 158; 26 p.","startPage":"1","endPage":"26","ipdsId":"IP-100898","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468183,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse6040158","text":"Publisher Index Page"},{"id":360648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay, Napa River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.5,\n 36.5\n ],\n [\n -121,\n 36.5\n ],\n [\n -121,\n 39\n ],\n [\n -124.5,\n 39\n ],\n [\n -124.5,\n 36.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-17","publicationStatus":"PW","scienceBaseUri":"5c1cb860e4b0708288c83827","contributors":{"authors":[{"text":"Herdman, Liv M. 0000-0002-5444-6441 lherdman@usgs.gov","orcid":"https://orcid.org/0000-0002-5444-6441","contributorId":149964,"corporation":false,"usgs":true,"family":"Herdman","given":"Liv","email":"lherdman@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":754831,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":754833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":754832,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202371,"text":"70202371 - 2018 - Regeneration and expansion of Quercus tomentella (island oak) groves on Santa Rosa Island","interactions":[],"lastModifiedDate":"2019-02-26T15:06:57","indexId":"70202371","displayToPublicDate":"2018-12-17T15:06:50","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Regeneration and expansion of Quercus tomentella (island oak) groves on Santa Rosa Island","title":"Regeneration and expansion of Quercus tomentella (island oak) groves on Santa Rosa Island","docAbstract":"Quercus tomentella (island oak) is an endemic species that plays a key functional role in Channel Island ecosystems. Growing in groves on highland ridges, Q. tomentella captures fog and increases water inputs, stabilizes soils, and provides habitat for flora and fauna. This cloud forest system has been impacted by a long history of ranching, and restoration efforts are underway that include erosion control, leaf litter capture, fog capture, and reforestation. To inform retoration efforts, we explored tree regeneration and the potential for Q. tomentella grove expansion on Santa Rosa Island. We delineated current and historic groves at Black Mountain by comparing stand maps from 1989 and aerial photographs from 1994 and 2015. We evaluated regeneration in the outlying areas by recording the location, diameter at breast height, number of trunks, height class, percent crown mortality, nurse plant species (if present), and reproductive status for all 4355 outlying seedlings, saplings, and mature trees. We defined outliers as individuals that were 15 m outside of the canopy of island oak groves. There are 14 groves at Black Mountain, and grove size expanded by an average of 36.9% (SD 18.5%) between 1994 and 2015. Nurse plants correlated positively with outlier tree height and reduced percent crown mortality. This effect is potentially due to increased fog drip from nurse plant species such as Quercus pacifica (island scrub oak), Heteromeles arbutifolia (toyon), and Baccharis pilularis (coyote brush). These results indicate that Q. tomentella is regenerating and that nurse plants can serve as catalysts for ecosystem restoration.
","language":"English","publisher":"Monte L. Bean Life Science Museum (Brigham Young University)","doi":"10.3398/064.078.0415","usgsCitation":"Woolsey, J., Hanna, C., McEachern, K., Anderson, S., and Hartman, B.D., 2018, Regeneration and expansion of Quercus tomentella (island oak) groves on Santa Rosa Island: Western North American Naturalist, v. 78, no. 4, p. 758-767, https://doi.org/10.3398/064.078.0415.","productDescription":"10 p.","startPage":"758","endPage":"767","ipdsId":"IP-087991","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":361561,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Rosa Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.25497436523436,\n 33.88922749934704\n ],\n [\n -119.96315002441408,\n 33.88922749934704\n ],\n [\n -119.96315002441408,\n 34.048108084909835\n ],\n [\n -120.25497436523436,\n 34.048108084909835\n ],\n [\n -120.25497436523436,\n 33.88922749934704\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Woolsey, Jay","contributorId":213580,"corporation":false,"usgs":false,"family":"Woolsey","given":"Jay","email":"","affiliations":[{"id":38803,"text":"CSU Channel Islands","active":true,"usgs":false}],"preferred":false,"id":758056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanna, Cause","contributorId":69035,"corporation":false,"usgs":false,"family":"Hanna","given":"Cause","affiliations":[{"id":13013,"text":"Department of Environmental Science, Policy and Management, University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":758057,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McEachern, Kathryn 0000-0003-2631-8247 kathryn_mceachern@usgs.gov","orcid":"https://orcid.org/0000-0003-2631-8247","contributorId":146324,"corporation":false,"usgs":true,"family":"McEachern","given":"Kathryn","email":"kathryn_mceachern@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":758055,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Sean","contributorId":213581,"corporation":false,"usgs":false,"family":"Anderson","given":"Sean","affiliations":[{"id":38803,"text":"CSU Channel Islands","active":true,"usgs":false}],"preferred":false,"id":758058,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartman, Brett D.","contributorId":213582,"corporation":false,"usgs":false,"family":"Hartman","given":"Brett","email":"","middleInitial":"D.","affiliations":[{"id":38803,"text":"CSU Channel Islands","active":true,"usgs":false}],"preferred":false,"id":758059,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70200497,"text":"ofr20181169 - 2018 - User guide for the Massachusetts Sustainable-Yield Estimator (MA SYE—version 2.0) computer program","interactions":[],"lastModifiedDate":"2018-12-17T13:26:20","indexId":"ofr20181169","displayToPublicDate":"2018-12-17T11:00:00","publicationYear":"2018","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":"2018-1169","displayTitle":"User Guide for the Massachusetts Sustainable-Yield Estimator (MA SYE—Version 2.0) Computer Program","title":"User guide for the Massachusetts Sustainable-Yield Estimator (MA SYE—version 2.0) computer program","docAbstract":"This report is a user guide for the Massachusetts Sustainable-Yield Estimator (MA SYE) computer program (version 2.0). The MA SYE was developed by the U.S. Geological Survey in cooperation with the Massachusetts Department of Environmental Protection to provide a planning-level decision-support tool designed to help decision makers estimate daily mean streamflows and selected streamflow statistics to assess sustainable water use at ungaged sites in Massachusetts. The MA SYE provides estimates of unaltered streamflow (which is assumed to occur in the absence of any water withdrawals or wastewater discharges and with minimal human development), net streamflow alterations caused by water use, water-use-adjusted streamflow, streamflow yields (estimated unaltered streamflow minus user-defined flow targets), and estimates of the accuracy and uncertainty of estimated unaltered streamflow. The MA SYE uses basin characteristics and water-use volumes (water withdrawals and wastewater-return flows) obtained from the U.S. Geological Survey online StreamStats application to estimate the unaltered and water-use-adjusted streamflows. The MA SYE is a database application with a graphical user interface developed by using Visual Basic for Applications with the 32-bit version of Microsoft Access. The graphical user interface is designed include full documentation for users: an introductory instruction form and onscreen help within each interactive form, including explanation buttons, context-sensitive help buttons, and tool-tip and status-bar messages.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181169","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Granato, G.E., and Levin, S.B., 2018, User guide for the Massachusetts Sustainable-Yield Estimator (MA SYE—version 2.0) computer program: U.S. Geological Survey Open-File Report 2018–1169, 7 p., https://doi.org/10.3133/ofr20181169.\n\n","productDescription":"Report: vi, 7 p.; Software release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-098957","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":358596,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95VX5AX","text":"USGS software release","description":"USGS software release","linkHelpText":"Massachusetts Sustainable-Yield Estimator (MASYE) application software (version 2.0) 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
The Massachusetts Sustainable-Yield Estimator is a decision support tool that provides estimates of daily unaltered streamflow, water-use-adjusted streamflow, and water availability for ungaged, user-defined basins in Massachusetts. Daily streamflow at the ungaged site is estimated for unaltered (no water use) and water-use scenarios. The procedure for estimating streamflow was developed previously and has been implemented with minor changes and updated water-use data in version 2.0 of the Massachusetts Sustainable-Yield Estimator. Unaltered streamflow at selected exceedance probabilities is estimated by previously published regression equations. Streamflow is interpolated between the regressed quantiles to produce a continuous flow duration curve. A daily streamflow time series is produced for the ungaged site by relating the estimated flow duration curve at the ungaged site to a flow duration curve at a gaged reference site and then transferring the dates from the reference site to the ungaged site.
Minor refinements were made to the previously published methods to estimate unaltered and water-use-adjusted streamflow, including a procedure to enforce the monotonic structure of the regression-based unaltered flow quantiles, improvements to the interpolation method used for computing the estimated flow duration curve, and updates to the methods used to compute time-lagged stream alterations from groundwater pumping or discharges. Additionally, a procedure was developed to estimate prediction intervals for daily and monthly unregulated streamflow time series at an ungaged site.
The Massachusetts Sustainable-Yield Estimator computes water-use-adjusted streamflow using water-use data provided by the Massachusetts Department of Environmental Protection. Available water-use data included monthly withdrawal and wastewater discharge volumes from 2010 to 2014 for surface-water and groundwater sources. Water-use-adjusted streamflow represents the potential effect of current water use on natural streamflow in the basin over the range of historical hydrologic conditions. Georeferenced water withdrawal and discharge volumes were incorporated into the Massachusetts StreamStats web application for use in version 2.0 of the Massachusetts Sustainable-Yield Estimator. To compute water-use-adjusted streamflow, mean daily withdrawals and discharges within a user-defined basin are subtracted and added to the unaltered time series, respectively. Surface-water volumes are applied directly to the equation. Time-lagged streamflow alterations from groundwater withdrawal or wastewater discharge sources are estimated by using a response-coefficient method developed from results of previously published, calibrated groundwater models in Massachusetts.
The Massachusetts Sustainable-Yield Estimator was updated to version 2.0 to improve software stability and usability. The version 2.0 software application was developed in Microsoft Access with a graphical user interface. All geoprocessing steps, including basin delineation and compilation of basin characteristics and water use within the basin, were completed in the Massachusetts StreamStats web application and exported for use by the Massachusetts Sustainable-Yield Estimator version 2.0.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185146","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Levin, S.B., and Granato, G.E., 2018, Methods used to estimate daily streamflow and water availability in the Massachusetts Sustainable-Yield Estimator version 2.0: U.S. Geological Survey Scientific Investigations Report 2018–5146, 16 p., https://doi.org/10.3133/sir20185146.","productDescription":"Report: vi, 16 p.; Software release","ipdsId":"IP-087736","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":360268,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5146/coverthb.jpg"},{"id":360271,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95VX5AX ","text":"USGS software release","description":"USGS software 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Occupancy models provide a reliable method of estimating species distributions while accounting for imperfect detectability. The cost of accounting for false absences is that detection and nondetection surveys typically require repeated visits to a site or multiple-observer techniques. More efficient methods of collecting data to estimate detection probabilities would allow additional sites to be surveyed for the same amount of effort, which would support more precise estimation of covariate effects to improve inference about underlying ecological processes. Time-to-detection surveys allow the estimation of detection probability based on a single site visit by one observer, and therefore might be an efficient technique for herpetological occupancy studies. We evaluated the use of time-to-detection surveys to estimate the occupancy of pond-breeding amphibians at Point Reyes National Seashore, California, USA, including variables that affected detection rates and the probability of occurrence. We found that detection times were short enough, and occupancy was high enough, to estimate reliably the probability of occurrence of three pond-breeding amphibians at Point Reyes National Seashore, and that survey and site conditions had species-specific effects on detection rates. In particular, pond characteristics affected detection times of all commonly detected species. Probability of occurrence of Sierran Treefrogs (Hyliola sierra) and Rough-Skinned Newts (Taricha granulosa) was negatively related to the detection of fish and pond area. Time-to-detection surveys can provide an efficient method for estimating detection probabilities and accounting for false absences in occupancy studies of reptiles and amphibians.
","language":"English","publisher":"The Society for the Study of Amphibians and Reptiles","doi":"10.1670/18-049","usgsCitation":"Halstead, B., Kleeman, P.M., and Rose, J.P., 2018, Time-to-detection occupancy modeling: An efficient method for analyzing the occurrence of amphibians and reptiles: Journal of Herpetology, v. 52, no. 4, p. 415-424, https://doi.org/10.1670/18-049.","productDescription":"10 p.; Data Release","startPage":"415","endPage":"424","ipdsId":"IP-098079","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":437651,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A9LA1O","text":"USGS data release","linkHelpText":"Time to detection data for Point Reyes pond-breeding amphibians, 2017"},{"id":360358,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Point Reyes National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.03451538085939,\n 37.92578434712101\n ],\n [\n -122.68913269042967,\n 37.92578434712101\n ],\n [\n -122.68913269042967,\n 38.24842651622814\n ],\n [\n -123.03451538085939,\n 38.24842651622814\n ],\n [\n -123.03451538085939,\n 37.92578434712101\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c18c423e4b006c4f856acce","contributors":{"authors":[{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":754352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":754353,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":754354,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198668,"text":"sir20185109 - 2018 - The Puʻu ʻŌʻō eruption of Kīlauea Volcano, Hawai‘i—Episode 21 through early episode 48, June 1984–April 1987","interactions":[],"lastModifiedDate":"2018-12-17T16:03:44","indexId":"sir20185109","displayToPublicDate":"2018-12-17T09:17:00","publicationYear":"2018","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":"2018-5109","displayTitle":"The Pu‘u ‘Ō‘ō Eruption of Kīlauea Volcano, Hawai‘i—Episode 21 Through Early Episode 48, June 1984–April 1987","title":"The Puʻu ʻŌʻō eruption of Kīlauea Volcano, Hawai‘i—Episode 21 through early episode 48, June 1984–April 1987","docAbstract":"The Pu‘u ‘Ō‘ō eruption from the middle East Rift Zone of Kīlauea Volcano began in January 1983 with intermittent activity along several fissures. By June 1983, the eruption had localized at the Pu‘u ‘Ō‘ō vent and the activity settled into an increasingly regular pattern of brief eruptive episodes characterized by high lava fountains. The first 18 months of the eruption (episodes 1–20) are chronicled in previous publications.
In the two years following episode 20, Pu‘u ‘Ō‘ō produced another 27 high-fountaining episodes. Episodes 21–47 lasted an average of 12.9 hours and were separated by inter-episode periods averaging 26.5 days. The lava fountains, which reached as high as 510 meters (m), fed lava flows (mostly channelized ʻaʻā) that brought the total area covered by the eruption to 40 square kilometers (km2) by the end of episode 47. Flow thickness measurements obtained for episodes 21–40 averaged 3.4 m; lava volumes for episodes 21–47 averaged 8.0×106 m3 per episode (including the 16-day fissure outbreak of episode 35).
The Pu‘u ‘Ō‘ō cone—a composite of pyroclastic material and lava flows—reached its maximum height of 255 m above the pre-eruption surface during episode 43 and maintained that height through episode 47. Short-lived eruptive fissures and vents at or near the base of the Pu‘u ‘Ō‘ō cone accompanied episodes 21, 25, 29, 35, 39, and 44. Episode 35 was unusual in that a fissure on the uprift flank of the cone erupted early in the episode, and then reactivated and extended 2.5 km uprift after the high fountaining was over and erupted for the next 16 days.
The volcano was primed for the 48th episode of high fountaining on July 18, 1986, when the conduit beneath Pu‘u ‘Ō‘ō ruptured again and magma erupted through new fissures at the base of the cone on both its uprift and downrift sides. These fissures were active for only 21 hours, but a third fissure, which opened 3 km downrift from Pu‘u ‘Ō‘ō on July 20, persisted and evolved into a single vent, later named Kupaianaha. Kupaianaha erupted almost continuously for the next 5.5 years (the main part of episode 48). The onset of episode 48 marked the end of episodic high fountaining and the transition to nearly continuous effusion. A lava lake developed over the Kupaianaha vent, and overflows from the lake built a broad, low shield that reached a relatively stable height of 45 m by November 1986.
After weeks of continuous eruption, the main lava channel leading from the lake gradually roofed over, forming a lava tube. By November 1986, the tube had extended from the lake to the ocean, 12 km southeast, closing the coastal highway. Tube-fed flows overran 28 houses in the coastal communities of Kapa‘ahu and Kalapana over the next month.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185109","usgsCitation":"Orr, T.R., Ulrich, G.E., Heliker, C., DeSmither, L.G., and Hoffmann, J.P., 2018, The Pu‘u ‘Ō‘ō eruption of Kīlauea Volcano, Hawai‘i—Episode 21 through early episode 48, June 1984–April 1987: U.S. Geological Survey Scientific Investigations Report 2018–5109, 107 p., https://doi.org/10.3133/sir20185109.","productDescription":"x, 107 p.","onlineOnly":"Y","ipdsId":"IP-087464","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":360340,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5109/sir20185109.pdf","text":"Report ","size":"50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientific Investigations Report 2018–5109"},{"id":360339,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5109/coverthb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.30685424804688,\n 19.250218840825706\n ],\n [\n -154.9504852294922,\n 19.250218840825706\n ],\n [\n -154.9504852294922,\n 19.44652177370614\n ],\n [\n -155.30685424804688,\n 19.44652177370614\n ],\n [\n -155.30685424804688,\n 19.250218840825706\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact,
Hawaiian Volcano Observatory
U.S. Geological Survey
P.O. Box 51
Hawaiʻi Volcanoes National Park, HI 96718-0051
Retrieving accurate volcanic sulfur dioxide (SO2) gas emission rates is important for a variety of purposes. It is an indicator of shallow subsurface magma, and thus may signal impending eruption or unrest. SO2 emission rates are significant for accurately assessing climate impact, and providing context for assessing environmental, agricultural, and human health effects during volcanic eruptions. The U.S. Geological Survey Hawaiian Volcano Observatory uses an array of ten fixed, upward-looking ultraviolet spectrometer systems to measure SO2 emission rates at 10-s sample intervals from the Kīlauea summit. We present Kīlauea SO2 emission rates from the volcano’s summit and middle East Rift Zone during 2014–2017 and discuss the major sources of error for these measurements. Due to the wide range of SO2 emissions encountered at the summit vent, we used a variable wavelength spectral analysis range to accurately quantify both high and low SO2 column densities. We compare measured emission rates from the fixed spectrometer array to independent road and helicopter-based traverse measurements and evaluate the magnitudes and sources of uncertainties for each method. To address the challenge of obtaining accurate plume speed measurements, we examine ground-based wind-speed, plume speed tracking via spectrometer, and SO2 camera derived plume speeds. Our analysis shows that: (1) the summit array column densities calculated using a dual fit window, are within -6 to +22% of results obtained with a variety of other conventional and experimental retrieval methods; (2) emission rates calculated from the summit array located ∼3 km downwind provide the best, practical estimate of summit SO2 release under normal trade wind conditions; (3) ground-based anemometer wind speeds are 22% less than plume speeds determined by cross-correlation of plume features; (4) our best estimate of average Kīlauea SO2 release for 2014–2017 is 5100 t/d, which is comparable to the space-based OMI emissions of 5518 t/d; and (5) short-term variability of SO2 emissions reflects Kīlauea lava lake dynamics.
The reintroduction of extirpated salmonids to historically occupied areas is becoming increasingly common as a conservation and recovery strategy. Often, reintroductions are implemented after the factors that originally led to species extirpation have been reduced, eliminated, or mitigated. For anadromous Oncorhynchus spp. (Pacific salmon) and O. mykiss (steelhead), addressing barriers to migration, which have been a primary factor in the decline and extirpation of many populations, has been an integral component of recovery efforts. Mitigation has included barrier removal, developing fish passage opportunities, and (or) actively trapping and hauling juvenile and adult anadromous salmonids around barriers.
With any reintroduction, there are a number of concerns regarding the ecological impact of the reintroduction efforts. Three of the main tenets to consider when assessing reintroductions are (1) the potential benefits if reintroduction is successful, (2) the biological risk through interactions of reintroduced strains with existing populations, and (3) the factors potentially limiting a successful reintroduction. This report focuses on information and data to address the second and third factors as they apply to the upper Lewis River in Washington.
The upper Lewis River historically contained wild populations of O. tshawytscha (Chinook salmon), O. kisutch (coho salmon), and steelhead. These populations were extirpated after completion of hydropower facilities on Lake Merwin in 1932, Yale Lake in 1953, and Swift Reservoir in 1958, which prevented fish from migrating to and from ocean environments. However, recent licenses issued by the Federal Energy Regulatory Commission require the installation and operation of an upstream fish passage facility at Lake Merwin and a downstream fish passage facility at Swift Reservoir. The licenses were developed in consultation with the National Marine Fisheries Service and the U.S. Fish and Wildlife Service. The overarching goal of this fish reintroduction project is to establish viable, self-sustaining, naturally reproducing, harvestable populations of spring Chinook salmon, winter steelhead, and coho salmon at levels higher than minimum viable populations.
This report uses a combination of field data and existing information to address six key objectives related to the reintroduction in order to inform decisions about passage at the Yale Lake and Lake Merwin hydropower projects. The objectives are (1) a review of information relevant to anadromous fish reintroduction and full fish passage; (2) a habitat assessment of tributaries to Swift Reservoir, Yale Lake, and Lake Merwin; (3) a field study to assess adult potential for spawning success; (4) an assessment of juvenile production and outmigration success; (5) a Lake Merwin predator impact study; and (6) a set of studies assessing interactions between anadromous and resident fish.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181190","collaboration":"Prepared in cooperation with PacifiCorp","usgsCitation":"Al-Chokhachy, R., Clark, C.L., Sorel, M.H., and Beauchamp, D.A., 2018, Development of new information to inform fish passage decisions at the Yale and Merwin hydro projects on the Lewis River, Washington—Final report, 2018: U.S. Geological Survey Open-File Report 2018–1190, 206 p., https://doi.org/10.3133/ofr20181190.","productDescription":"xv, 206 p.","onlineOnly":"Y","ipdsId":"IP-078496","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":360226,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1190/coverthb.jpg"},{"id":360227,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1190/ofr20181190.pdf","text":"Report","size":"12.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1190"}],"country":"United States","state":"Washington","otherGeospatial":"Lewis River","contact":"Director, Northern Rocky Mountain Science Center
U.S. Geological Survey
2327 University Way, Suite 2
Bozeman, MT 59715
We present an exploratory study examining the use of airborne remote-sensing observations to detect ecological responses to elevated CO2emissions from active volcanic systems. To evaluate these ecosystem responses, existing spectroscopic, thermal, and lidar data acquired over forest ecosystems on Mammoth Mountain volcano, California, were exploited, along with in situ measurements of persistent volcanic soil CO2fluxes. The elevated CO2 response was used to statistically model ecosystem structure, composition, and function, evaluated via data products including biomass, plant foliar traits and vegetation indices, and evapotranspiration (ET). Using regression ensemble models, we found that soil CO2 flux was a significant predictor for ecological variables, including canopy greenness (normalized vegetation difference index, NDVI), canopy nitrogen, ET, and biomass. With increasing CO2, we found a decrease in ET and an increase in canopy nitrogen, both consistent with theory, suggesting more water- and nutrient-use-efficient canopies. However, we also observed a decrease in NDVI with increasing CO2 (a mean NDVI of 0.27 at 200 g m−2 d−1 CO2 reduced to a mean NDVI of 0.10 at 800 g m−2 d−1 CO2). This is inconsistent with theory though consistent with increased efficiency of fewer leaves. We found a decrease in above-ground biomass with increasing CO2, also inconsistent with theory, but we did also find a decrease in biomass variance, pointing to a long-term homogenization of structure with elevated CO2. Additionally, the relationships between ecological variables changed with elevated CO2, suggesting a shift in coupling/decoupling among ecosystem structure, composition, and function synergies. For example, ET and biomass were significantly correlated for areas without elevated CO2 flux but decoupled with elevated CO2 flux. This study demonstrates that (a) volcanic systems show great potential as a means to study the properties of ecosystems and their responses to elevated CO2 emissions and (b) these ecosystem responses are measurable using a suite of airborne remotely sensed data.
","language":"English","publisher":"European Biogeosciences Union","doi":"10.5194/bg-15-7403-2018","usgsCitation":"Cawse-Nicholson, K., Fisher, J.B., Famiglietti, C.A., Braverman, A., Schwandner, F.M., Lewicki, J.L., Townsend, P.A., Schimel, D.S., Pavlick, R., Bormann, K., Ferraz, A., Kang, E.L., Ma, P., Bogue, R.R., Youmans, T., and Pieri, D.C., 2018, Ecosystem responses to elevated CO2 using airborne remote sensing at Mammoth Mountain, California: Biogeosciences, v. 15, p. 7403-7418, https://doi.org/10.5194/bg-15-7403-2018.","productDescription":"16 p.","startPage":"7403","endPage":"7418","ipdsId":"IP-094903","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468185,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-15-7403-2018","text":"Publisher Index Page"},{"id":360330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mammoth Mountain","volume":"15","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-14","publicationStatus":"PW","scienceBaseUri":"5c14cfb4e4b006c4f8545d1c","contributors":{"authors":[{"text":"Cawse-Nicholson, Kerry","contributorId":211502,"corporation":false,"usgs":false,"family":"Cawse-Nicholson","given":"Kerry","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisher, Joshua B.","contributorId":211503,"corporation":false,"usgs":false,"family":"Fisher","given":"Joshua","email":"","middleInitial":"B.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Famiglietti, Caroline A.","contributorId":211504,"corporation":false,"usgs":false,"family":"Famiglietti","given":"Caroline","email":"","middleInitial":"A.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754300,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Braverman, Amy","contributorId":211505,"corporation":false,"usgs":false,"family":"Braverman","given":"Amy","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754301,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schwandner, Florian M.","contributorId":211506,"corporation":false,"usgs":false,"family":"Schwandner","given":"Florian","email":"","middleInitial":"M.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754302,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":754297,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Townsend, Philip A.","contributorId":211507,"corporation":false,"usgs":false,"family":"Townsend","given":"Philip","email":"","middleInitial":"A.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":754303,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schimel, David S.","contributorId":211508,"corporation":false,"usgs":false,"family":"Schimel","given":"David","email":"","middleInitial":"S.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754304,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pavlick, Ryan","contributorId":211509,"corporation":false,"usgs":false,"family":"Pavlick","given":"Ryan","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754305,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bormann, Kathryn J.","contributorId":211510,"corporation":false,"usgs":false,"family":"Bormann","given":"Kathryn J.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754306,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ferraz, Antonio","contributorId":211511,"corporation":false,"usgs":false,"family":"Ferraz","given":"Antonio","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754307,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kang, Emily L.","contributorId":211512,"corporation":false,"usgs":false,"family":"Kang","given":"Emily","email":"","middleInitial":"L.","affiliations":[{"id":38260,"text":"University of Cincinnnati","active":true,"usgs":false}],"preferred":false,"id":754308,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ma, Pulong","contributorId":211513,"corporation":false,"usgs":false,"family":"Ma","given":"Pulong","email":"","affiliations":[{"id":38260,"text":"University of Cincinnnati","active":true,"usgs":false}],"preferred":false,"id":754309,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Bogue, Robert R.","contributorId":211528,"corporation":false,"usgs":false,"family":"Bogue","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754334,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Youmans, Thomas","contributorId":211529,"corporation":false,"usgs":false,"family":"Youmans","given":"Thomas","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754335,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Pieri, David C.","contributorId":211514,"corporation":false,"usgs":false,"family":"Pieri","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754310,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70201189,"text":"ofr20131024D - 2018 - Lithostratigraphic framework in boreholes from Goldstone Lake and Nelson Lake Basins, Fort Irwin, California","interactions":[{"subject":{"id":70201189,"text":"ofr20131024D - 2018 - Lithostratigraphic framework in boreholes from Goldstone Lake and Nelson Lake Basins, Fort Irwin, California","indexId":"ofr20131024D","publicationYear":"2018","noYear":false,"chapter":"D","title":"Lithostratigraphic framework in boreholes from Goldstone Lake and Nelson Lake Basins, Fort Irwin, California"},"predicate":"IS_PART_OF","object":{"id":70201192,"text":"ofr20131024 - 2014 - Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","indexId":"ofr20131024","publicationYear":"2014","noYear":false,"title":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California"},"id":1}],"isPartOf":{"id":70201192,"text":"ofr20131024 - 2014 - Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","indexId":"ofr20131024","publicationYear":"2014","noYear":false,"title":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California"},"lastModifiedDate":"2024-06-26T15:40:52.511787","indexId":"ofr20131024D","displayToPublicDate":"2018-12-14T12:31:47","publicationYear":"2018","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":"2013-1024","chapter":"D","title":"Lithostratigraphic framework in boreholes from Goldstone Lake and Nelson Lake Basins, Fort Irwin, California","docAbstract":"In 2011 and 2012, the sedimentary basins in the Fort Irwin National Training Center, California, were evaluated for groundwater resources using a variety of techniques, including drilling of boreholes. This study summarizes lithostratigraphic features and deposits in 8 of 10 boreholes drilled in 2 basins located in the western part of Fort Irwin. The western part of Fort Irwin straddles the eastern edge of the Miocene Eagle Crags volcanic field; therefore, many of the rocks penetrated in the boreholes are primary volcanic deposits (lava flow, pyroclastic flow, and fallout tephra deposits) and tuffaceous or lithic-rich sedimentary rocks (siltstone to cobble conglomerates) deposited in alluvial, fluvial, lacustrine, and possibly groundwater discharge environments. Boreholes were drilled with mud-rotary techniques that result in cuttings samples, and only two to four cores ranging in length from 3 to 5 feet (ft) were collected in each borehole.
Correlation of lithostratigraphic features to borehole geophysical logs (especially gamma and resistivity) helps to establish properties of the rock and enables identification of depositional sequences of similar rock types. Lithostratigraphic features and resistivity in boreholes compare reasonably well to nearby time-domain electromagnetic sounding (resistivity) model results.
There is no direct age control on the rocks penetrated in the boreholes. The abundance of tuffaceous material as primary or slightly redeposited matrix is used to identify rocks deposited during the activity of the Eagle Crags volcanic field in the Miocene. In contrast, sedimentary rocks composed of detrital and epiclastic grains (only a few of which are tuffaceous rocks as clasts) are inferred to have been deposited during the Quaternary or Pliocene(?). The lithostratigraphic-based estimates of relative age indicate the typical thickness of the Quaternary or Pliocene(?) deposits is 70–170 ft, and that several water-bearing horizons are probable in the Miocene(?) section.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131024D","usgsCitation":"Buesch, D.C., 2018, Lithostratigraphic framework in boreholes from Goldstone Lake and Nelson Lake Basins, Fort Irwin, California, chap. D of Buesch, D.C., ed., Geology and geophysics applied to groundwater hydrology at Fort Irwin, California: U.S. Geological Survey Open-file Report 2013–1024–D, 133 p., https://doi.org/10.3133/ofr20131024D.","productDescription":"vi, 133 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079918","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":362164,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2013/1024/d/ofr20131024d_table2.1.xls","text":"Table 2.1","size":"56 KB xls","description":"OFR 2013-1024 Chapter D Table 2.1"},{"id":360342,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1024/d/ofr20131024d.pdf","text":"Report","size":"8.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2013-1024 Chapter D"},{"id":360343,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2013/1024/d/coverthb.jpg"}],"country":"United States","state":"California","county":"San Bernardino County","city":"Fort Irwin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117,\n 35\n ],\n [\n -116,\n 35\n ],\n [\n -116,\n 35.67\n ],\n [\n -117,\n 35.67\n ],\n [\n -117,\n 35\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
One important component of continental-scale hydrologic modeling is quantifying the level of uncertainty in long-term hydrologic simulations and providing a range of possible simulated streamflow and/or runoff values for gaged and ungaged locations. In this paper, uncertainty was quantified for simulated streamflow and runoff generated from a monthly water balance model (MWBM) at 1575 streamgages and 109,951 hydrologic response units (HRUs), which span the conterminous United States (CONUS). A stochastic-approach, which incorporated the properties of modeled streamflow residuals back into the simulated model output, was used to create time series of upper and lower uncertainty intervals (UIs) around the simulated monthly time series. This approach was applied to an existing hydrologic regionalization implementation. Metrics used to evaluate the UIs across the CONUS (the coverage ratio, average width index, and interval skill score) indicated that on average the UIs were reliable, skillful, and sharp in being able to both contain measured streamflow observations and reduce estimates of uncertainty based on expected model predictions. These uncertainty evaluation metrics can complement each other in characterizing model skill and uncertainty over large-scale domains.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.advwatres.2018.10.005","usgsCitation":"Bock, A.R., Farmer, W.H., and Hay, L., 2018, Quantifying uncertainty in simulated streamflow and runoff from a continental-scale monthly water balance model: Advances in Water Resources, v. 122, p. 166-175, https://doi.org/10.1016/j.advwatres.2018.10.005.","productDescription":"10 p.","startPage":"166","endPage":"175","ipdsId":"IP-094722","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":360293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"122","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c14cfb5e4b006c4f8545d26","contributors":{"authors":[{"text":"Bock, Andrew R. 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":4580,"corporation":false,"usgs":true,"family":"Bock","given":"Andrew","email":"abock@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":754251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farmer, William H. 0000-0002-2865-2196 wfarmer@usgs.gov","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":4374,"corporation":false,"usgs":true,"family":"Farmer","given":"William","email":"wfarmer@usgs.gov","middleInitial":"H.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":754253,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hay, Lauren E. 0000-0003-3763-4595","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":211478,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":754252,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199284,"text":"ofr20131024C - 2018 - Cenozoic geology of Fort Irwin and vicinity, California","interactions":[{"subject":{"id":70199284,"text":"ofr20131024C - 2018 - Cenozoic geology of Fort Irwin and vicinity, California","indexId":"ofr20131024C","publicationYear":"2018","noYear":false,"chapter":"C","displayTitle":"Cenozoic Geology of Fort Irwin and Vicinity, California","title":"Cenozoic geology of Fort Irwin and vicinity, California"},"predicate":"IS_PART_OF","object":{"id":70201192,"text":"ofr20131024 - 2014 - Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","indexId":"ofr20131024","publicationYear":"2014","noYear":false,"title":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California"},"id":1}],"isPartOf":{"id":70201192,"text":"ofr20131024 - 2014 - Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","indexId":"ofr20131024","publicationYear":"2014","noYear":false,"title":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California"},"lastModifiedDate":"2019-03-18T18:19:25","indexId":"ofr20131024C","displayToPublicDate":"2018-12-14T10:31:31","publicationYear":"2018","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":"2013-1024","chapter":"C","displayTitle":"Cenozoic Geology of Fort Irwin and Vicinity, California","title":"Cenozoic geology of Fort Irwin and vicinity, California","docAbstract":"The geology of the Fort Irwin National Training Center in the north-central Mojave Desert, California, provides insights into the hydrology and water resources of the area. The Fort Irwin area is underlain by rocks ranging in age from Proterozoic to Quaternary that have been deformed by faults as young as Quaternary. Pre-Tertiary sedimentary, igneous, and metamorphic bedrock and Miocene volcanic and sedimentary rocks are exposed in the mountains and ridges, between which are basins containing Quaternary to Pliocene deposits. During the Miocene, in the western part of Fort Irwin, development of the Eagle Crags volcanic field resulted in a complex assemblage of lava flows, pyroclastic flow and fallout tephra deposits, and volcaniclastic sedimentary rocks that were deposited in alluvial, fluvial, and locally lacustrine environments; in the eastern part of Fort Irwin, epiclastic sedimentary rocks and minor tuffaceous rocks were deposited in alluvial, fluvial, and locally lacustrine environments. In the Pliocene and Quaternary, sandstone and conglomerate were deposited in alluvial and fluvial environments, and locally fine-grained materials were deposited in lacustrine, eolian, playa, and groundwater discharge environments. The Fort Irwin area is transected by Neogene to Holocene northwest- and east-striking (and fewer northeast-striking) strike-slip, normal, and locally thrust faults. Structural blocks between faults are broadly warped, and locally rocks adjacent to the faults are folded and sheared. Many of these faults influenced the formation or modification of basins, especially after about 11 million years, when the Eastern California Shear Zone developed in this area. The three-dimensional geologic framework produced by the late Cenozoic stratigraphic and structural history is represented by the continuity or spatial limitations of lithostratigraphic and correlative hydrogeologic properties. The continuity or limitations of rocks and properties influence how water moved (and moves) through the hydrogeologic system.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131024C","collaboration":"Prepared in cooperation with the U.S. Army, Fort Irwin National Training Center","usgsCitation":"Buesch, D.C., Miller, D.M., and Menges, C.M., 2018, Cenozoic geology of Fort Irwin and vicinity, California, chap. C of Buesch, D.C., ed., Geology and geophysics applied to groundwater hydrology at Fort Irwin, California: U.S. Geological Survey Open-File Report 2013–1024–C, 39 p., https://doi.org/10.3133/ofr20131024C.","productDescription":"Report: iv, 39 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-079524","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":359938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1024/c/ofr20131024c.pdf","text":"Report","size":"7.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2013-1024"},{"id":359937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2013/1024/c/coverthb.jpg"}],"country":"United States","state":"California","county":"San Bernardino County","city":"Fort Irwin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117,\n 35\n ],\n [\n -116,\n 35\n ],\n [\n -116,\n 35.67\n ],\n [\n -117,\n 35.67\n ],\n [\n -117,\n 35\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
The Southern Great Plains Rapid Ecoregional Assessment was conducted in partnership with the Bureau of Land Management (BLM) and the Great Plains Landscape Conservation Cooperative. The overall goal of the Rapid Ecoregional Assessments (REAs) is to compile and synthesize regional datasets to facilitate evaluation of the cumulative effects of change agents on priority ecological communities and species. In particular, the REAs identify and map the distribution of communities and wildlife habitats at broad spatial extents and provide assessments of ecological conditions. The REAs also identify where and to what degree ecological resources are currently at risk from change agents, such as development, fire, invasive species, and climate change. The REAs can help managers identify and prioritize potential areas for conservation or restoration, assess cumulative effects as required by the National Environmental Policy Act, and inform landscape-level planning and management decisions for multiple uses of public lands.
Management questions form the basis for the REA framework and were developed in conjunction with the BLM and other stakeholders. Conservation elements are communities and species that are of regional management concern. Core management questions relate to the key ecological attributes and change agents associated with each conservation element. Integrated management questions synthesize the results of the primary core management questions into overall landscape-level ranks for each conservation element.
The ecological communities evaluated as conservation elements are shortgrass, mixed-grass, and sand prairies; all grasslands; riparian and nonplaya wetlands; playa wetlands and saline lakes; and prairie streams and rivers. Species and species assemblages evaluated are the freshwater mussel assemblage, Arkansas River shiner (Notropis girardi), ferruginous hawk (Buteo regalis), lesser prairie chicken (Tympanuchus pallidicinctus), snowy plover (Charadrius nivosus), mountain plover (Charadrius montanus), long-billed curlew (Numenius americanus), interior least tern (Sternula antillarum athalassos), burrowing owl (Athene cunicularia), black-tailed prairie dog (Cynomys ludovicianus), bat assemblage, swift fox (Vulpes velox), and mule deer (Odocoileus hemionus).
The Southern Great Plains REA is summarized in a series of three reports and associated datasets. The pre-assessment report (available online at https://doi.org/10.3133/ofr20151003) summarizes the process used by the REA stakeholders to select management questions, conservation elements, and change agents. It also provides background information for each conservation element. Volume I of the Southern Great Plains REA report addresses the ecological communities (available online at https://doi.org/10.3133/ofr20171100). Volume II (this volume) addresses the species and species assemblages. All source and derived datasets used to produce the maps and graphs for REAs are available online at the BLM Landscape Approach Data Portal (https://landscape.blm.gov/geoportal/catalog/REAs/REAs.page).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181109","collaboration":"Prepared in cooperation with the Bureau of Land Management and the Great Plains Landscape Conservation Cooperative","usgsCitation":"Reese, G.C., Carr, N.B., and Burris, L.E., 2018, Southern Great Plains Rapid Ecoregional Assessment—Volume II. Species and assemblages (ver. 1.1, December 2018): U.S. Geological Survey Open-File Report 2018–1109, 134 p., https://doi.org/10.3133/ofr20181109.","productDescription":"xiii, 134 p.","onlineOnly":"Y","ipdsId":"IP-094978","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":360274,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2018/1109/versionHist.txt","text":"Version History","size":"4.00 KB","linkFileType":{"id":2,"text":"txt"},"description":"Version History"},{"id":359623,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20171100 ","text":"Open-File Report 2017-1100—","linkHelpText":"Southern Great Plains Rapid Ecoregional assessment—Volume I. Ecological communities"},{"id":359620,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1109/coverthb2.jpg"},{"id":359621,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1109/ofr20181109.pdf","text":"Report","size":"9.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1109"},{"id":359622,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20151003","text":"Open-File Report 2015–1003—","linkHelpText":"Southern Great Plains Rapid Ecoregional Assessment—Pre-Assessment Report"}],"country":"United States","state":"Colorado, Kansas, Nebraska, New Mexico, Oklahoma, Texas, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.14990234375,\n 30.939924331023445\n ],\n [\n -96.2841796875,\n 30.939924331023445\n ],\n [\n -96.2841796875,\n 43.08493742707592\n ],\n [\n -106.14990234375,\n 43.08493742707592\n ],\n [\n -106.14990234375,\n 30.939924331023445\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: December 2018; Version 1.0: November 2018","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
The U.S. Geological Survey has created a hydrogeologic framework for Quaternary sediments in glaciated areas of the conterminous United States that categorizes, maps, and characterizes the glacial sediments at and beneath the land surface. The hydrogeologic framework divides the glaciated United States into 17 distinct hydrogeologic terranes using a geologic approach based on previous mapping, and was characterized using the Glacial Environments and Surficial Sediments geodatabase compiled from the Quaternary Atlas of the United States map series, the Surficial Materials Map of the United States, and several Integrated Geologic Map Databases for the United States; a groundwater use database compiled from public-supply, water-well data; and a lithologic database compiled from State-managed well records and geologic logs. This framework is to be used to assess the occurrence and characteristics of confined and unconfined glacial aquifers, their distribution and extent, and their potential intrinsic susceptibility and vulnerability.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1090","usgsCitation":"Haj, A.E., Soller, D.R., Reddy, J.E., Kauffman, L.J., Yager, R.M., and Buchwald, C.A., 2018, Hydrogeologic framework for characterization and occurrence of confined and unconfined aquifers in quaternary sediments in the glaciated conterminous United States—A digital map compilation and database: U.S. Geological Survey Data Series 1090, 31 p., https://doi.org/10.3133/ds1090.\n\n","productDescription":"Report: vi, 31 p.; Interactive Maps; Data Releases","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081250","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":359730,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/sir20185091","text":"Scientific Investigations Report 2018-5091","linkHelpText":"- Characterization and occurrence of confined and unconfined aquifers in Quaternary sediments in the glaciated conterminous United States"},{"id":359725,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1090/coverthb.jpg"},{"id":359729,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HH6J8X","text":"USGS data release","description":"USGS data release","linkHelpText":"Digital products from a hydrogeologic framework for Quaternary sediments within the glaciated conterminous United States "},{"id":359726,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1090/ds1090.pdf","text":"Report","size":"11.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1090"},{"id":359727,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/1090/ds1090_index.html","linkFileType":{"id":5,"text":"html"},"linkHelpText":"- Index page for oversized, interactive Leaflet maps"},{"id":359728,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71R6PQG","text":"USGS data release","description":"USGS data release","linkHelpText":"Databases used to develop a hydrogeologic framework for Quaternary sediments in the glaciated conterminous United States"}],"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 -124.969069883,\n 35.090811167\n ],\n [\n -65.343237884,\n 35.090811167\n ],\n [\n -65.343237884,\n 50.932504994\n ],\n [\n -124.969069883,\n 50.932504994\n ],\n [\n -124.969069883,\n 35.090811167\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street
Iowa City, IA 52240
This report is a user guide for the Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE) computer program (version 1.0). The CT SSWUE was developed by the U.S. Geological Survey in cooperation with the Connecticut Department of Energy and Environmental Protection to provide a planning-level decision-support tool designed to help decision makers estimate daily mean streamflows and selected streamflow statistics to assess sustainable water use at ungaged sites in Connecticut. The CT SSWUE provides estimates of unaltered streamflow (which is assumed to occur in the absence of any water withdrawals or wastewater discharges and with minimal human development), net streamflow alterations caused by water use, water-use-adjusted streamflow, streamflow yields (estimated unaltered streamflow minus user-defined flow targets), and estimates of the accuracy and uncertainty of estimated unaltered streamflow. The CT SSWUE uses basin characteristics and water-use volumes (water withdrawals and wastewater-return flows) obtained from the U.S. Geological Survey online StreamStats application to estimate the unaltered and water-use-adjusted streamflows. The CT SSWUE is a database application with a graphical user interface developed by using Visual Basic for Applications with the 32-bit version of Microsoft Access. The graphical user interface is designed to include full documentation for users: an introductory instruction form and onscreen help within each interactive form, including explanation buttons, context-sensitive help buttons, and tool-tip and status-bar messages.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181163","collaboration":"Prepared in cooperation with the Connecticut Department of Energy and Environmental Protection","usgsCitation":"Granato, G.E., and Levin, S.B., 2018, User guide for the Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE—version 1.0) computer program: U.S. Geological Survey Open-File Report 2018–1163, 7 p., https://doi.org/10.3133/ofr20181163.","productDescription":"vi, 7 p.","ipdsId":"IP-098955","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":360048,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V6ARUS","text":"USGS data release","description":"USGS data release","linkHelpText":"Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE) Application Software "},{"id":360046,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1163/ofr20181163.pdf","text":"Report","size":"360 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1163"},{"id":360045,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1163/coverthb.jpg"},{"id":360047,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20185135","text":"Scientific Investigations Report 2018–5135","linkHelpText":"- The Connecticut Streamflow and Sustainable Water Use Estimator: A Decision-Support Tool To Estimate Water Availability at Ungaged Stream Locations in Connecticut"}],"contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Freshwater streams in Connecticut are subject to many competing demands, including public water supply; agricultural, commercial, and industrial water use; and ecosystem and habitat needs. In recent years, drought has further stressed Connecticut’s water resources. To sustainably allocate and manage water resources among these competing uses, Federal, State, and local water-resource managers require data and modeling tools to estimate the water availability at a variety of temporal and spatial scales for planning purposes. The Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE), developed by the U.S. Geological Survey in cooperation with the Connecticut Department of Energy and Environmental Protection, is a decision-support tool for estimating daily unaltered streamflow and sustainable water use at ungaged sites in Connecticut.
The CT SSWUE estimates unaltered daily mean streamflow and water-use-adjusted streamflow for the period from October 1, 1960, to September 30, 2015, and the monthly sustainable net withdrawal at ungaged sites in Connecticut. Unaltered streamflow is the estimated daily mean streamflow in a drainage basin in the absence of any water withdrawals or wastewater discharges and with minimal human development. Sustainable net withdrawal is the maximum net withdrawal (withdrawal minus wastewater discharges) that can be drawn from a basin without critically depleting the water available through natural streamflow patterns. Sustainable net withdrawal is defined for this study as the difference between the unaltered daily mean streamflow and a user-defined target minimum streamflow.
Weighted least squares and Tobit regression techniques were used to develop equations for estimating streamflow at ungaged sites at 19 streamflow quantiles with exceedance probabilities ranging from 0.005 to 99.995 percent. Regressions were based on streamflow quantiles and basin characteristics from 36 reference streamgages in and around Connecticut. Four basin characteristics—drainage area, mean of the soil permeability, mean of the average annual precipitation, and ratio of the length of streams that overlay sand and gravel deposits to the total length of streams in the basin—are used as explanatory variables in the equations. At an ungaged site, interpolation between the streamflow quantiles estimated from the regression equations produces a continuous flow-duration curve. A time series of daily mean streamflow at an ungaged site is then estimated by assuming that for each day, the streamflow quantile occurs on the same date at both a reference streamgage and the ungaged site.
In a remove-one cross validation, estimated unaltered daily mean streamflow agreed well with observed values at reference streamgages, with a few exceptions. Nash Sutcliffe efficiency ranged from −0.43 to 0.97 with a median value of 0.88. The normalized root-mean-square error ranged from 16.6 to 120.4 percent with a median value of 34.5 percent.
An empirical method for estimating 95-percent prediction intervals for unaltered daily and monthly mean streamflow was developed and tested by using the cross-validation data. Prediction intervals for unaltered daily mean streamflow at the cross-validation reference streamgages performed well in most cases. Gaged streamflow values from the cross-validation data fell within the prediction intervals a median 96.6 percent of the time for daily mean time series and 93.9 percent of the time for monthly mean time series.
The CT SSWUE computes water-use-adjusted streamflow using spatially referenced water-use information provided by the Connecticut Department of Energy and Environmental Protection. Available water-use information included permitted and registered water withdrawals and permitted wastewater discharges during 1998 to 2015 for the Thames River Basin and central coastal drainage basins. Water-use information was incorporated into the U.S. Geological Survey StreamStats web application for Connecticut and can be used for computing water-use-adjusted streamflow and sustainable net withdrawal at selected points of interest. Altered daily streamflow is computed by applying average daily withdrawals and wastewater discharges to the water balance equation. Average daily surface water withdrawals and wastewater discharges are applied directly to the daily water balance equation. Time-lagged alterations on streamflow from groundwater withdrawals or wastewater discharges are estimated by using a response-coefficient method developed from results of previously published, calibrated groundwater models.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185135","collaboration":"Prepared in cooperation with the Connecticut Department of Energy and Environmental Protection","usgsCitation":"Levin, S.B., Olson, S.A., Nielsen, M.G., and Granato, G.E., 2018, The Connecticut Streamflow and Sustainable Water Use Estimator—A decision-support tool to estimate water availability at ungaged stream locations in Connecticut: U.S. Geological Survey Scientific Investigations Report 2018–5135, 34 p., https://doi.org/10.3133/sir20185135.","productDescription":"Report: vii, 34 p.; Table; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-087738","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":360020,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5135/sir20185135.pdf","text":"Report","size":"8.92 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Context
Habitat complexity in rivers is linked to dynamic fluvial conditions acting at various spatial scales. On regulated rivers in the western United States, tributaries are regions of high energy and disturbance, providing important resource inputs for riparian ecosystems.
Objectives
This study investigated spatial patterns and extents of tributary influence on riparian habitat complexity in the near channel zone along regulated reaches of the Colorado (> 200 km) and Dolores Rivers (~ 300 km) in the western United States. Because tributary confluences are regions of increased dynamism, we hypothesized that: (1) geomorphic and land cover complexity would be greatest close to tributary junctions and decrease with distance from tributaries; and (2) patterns in complexity would vary across different sized spatial units.
Methods
Using a combination of remote sensing and spatial analysis, we classified fluvial features and land cover classes to investigate patterns longitudinally at 10-, 25-, and 100-m spatial units in the near channel zone of two regulated rivers.
Results
Using change point analysis and randomization tests, we detected shifts in riparian habitat complexity closer to tributary junctions. Patterns varied across 10-, 25-, and 100-m spatial units in the near channel zone, with significance (p ≤ 0.05) recorded for 10- and 25-m spatial units.
Conclusions
Tributary junctions deliver critical resource inputs on regulated systems, providing for increased geomorphic and land cover diversity upstream and downstream of tributaries. We found that patterns of response were non-linear and discontinuous, varying across spatial units and potentially influenced by the degree of mainstem flow regulation.
Karst subterranean estuaries (KSEs) extend into carbonate platforms along 12% of all coastlines. A recent study has shown that microbial methane (CH4) consumption is an important component of the carbon cycle and food web dynamics within flooded caves that permeate KSEs. In this study, we obtained high‐resolution (~2.5‐day) temporal records of dissolved methane concentrations and its stable isotopic content (δ13C) to evaluate how regional meteorology and hydrology control methane dynamics in KSEs. Our records show that less methane was present in the anoxic fresh water during the wet season (4,361 ± 89 nM) than during the dry season (5,949 ± 132 nM), suggesting that the wet season hydrologic regime enhances mixing of methane and other constituents into the underlying brackish water. The δ13C of the methane (−38.1 ± 1.7‰) in the brackish water was consistently more 13C‐enriched than fresh water methane (−65.4 ± 0.4‰), implying persistent methane oxidation in the cave. Using a hydrologically based mass balance model, we calculate that methane consumption in the KSE was 21–28 mg CH4·m−2·year−1 during the 6‐month dry period, which equates to ~1.4 t of methane consumed within the 102‐ to 138‐km2 catchment basin for the cave. Unless wet season methane consumption is much greater, the magnitude of methane oxidized within KSEs is not likely to affect the global methane budget. However, our estimates constrain the contribution of a critical resource for this widely distributed subterranean ecosystem.
","language":"English","publisher":"AGU","doi":"10.1029/2018GB006026","usgsCitation":"Brankovits, D., Pohlman, J.W., Ganju, N., Iliffe, T., Lowell, N., Roth, E., Sylva, S., Emmert, J., and Lapham, L.L., 2018, Hydrologic controls of methane dynamics in karst subterranean estuaries: Global Biogeochemical Cycles, v. 32, no. 12, p. 1759-1775, https://doi.org/10.1029/2018GB006026.","productDescription":"17 p.","startPage":"1759","endPage":"1775","ipdsId":"IP-102700","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468186,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018gb006026","text":"Publisher Index Page"},{"id":360248,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"12","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-07","publicationStatus":"PW","scienceBaseUri":"5c137dd2e4b006c4f8514874","contributors":{"authors":[{"text":"Brankovits, David 0000-0002-0863-5698","orcid":"https://orcid.org/0000-0002-0863-5698","contributorId":210617,"corporation":false,"usgs":true,"family":"Brankovits","given":"David","email":"","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":753870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pohlman, John W. 0000-0002-3563-4586 jpohlman@usgs.gov","orcid":"https://orcid.org/0000-0002-3563-4586","contributorId":145771,"corporation":false,"usgs":true,"family":"Pohlman","given":"John","email":"jpohlman@usgs.gov","middleInitial":"W.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":753871,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":753872,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iliffe, T.M.","contributorId":201287,"corporation":false,"usgs":false,"family":"Iliffe","given":"T.M.","email":"","affiliations":[],"preferred":false,"id":753873,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowell, N.","contributorId":211383,"corporation":false,"usgs":false,"family":"Lowell","given":"N.","email":"","affiliations":[{"id":38240,"text":"Lowell Instruments","active":true,"usgs":false}],"preferred":false,"id":753874,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roth, E.","contributorId":90499,"corporation":false,"usgs":true,"family":"Roth","given":"E.","affiliations":[],"preferred":false,"id":753875,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sylva, S.P.","contributorId":211384,"corporation":false,"usgs":false,"family":"Sylva","given":"S.P.","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":753876,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Emmert, J.A.","contributorId":211385,"corporation":false,"usgs":false,"family":"Emmert","given":"J.A.","email":"","affiliations":[{"id":38241,"text":"Moody Gardens Aquarium","active":true,"usgs":false}],"preferred":false,"id":753877,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lapham, L. L.","contributorId":140085,"corporation":false,"usgs":false,"family":"Lapham","given":"L.","email":"","middleInitial":"L.","affiliations":[{"id":13383,"text":"University of Maryland Center for Environmental Science, Chesapeake Biological Laboratory, 6 Solomons, Maryland 20688","active":true,"usgs":false}],"preferred":false,"id":753878,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ]}