Multichannel electrical resistivity (ER) measurements were conducted at two contrasting coastal sites in Hawaii to obtain new information on the spatial scales and dynamics of the fresh water–seawater interface and rates of coastal groundwater exchange. At Kiholo Bay (located on the dry, Kona side of the Big Island) and at a site in Maunalua Bay (Oahu), there is an evidence for abundant submarine groundwater discharge (SGD). However, the hydrologic and geologic controls on coastal groundwater discharge are likely to be different at these two sites. While at Kiholo Bay SGD is predominantly through lava tubes, at the Maunalua Bay site exchange occurs mostly through nearshore submarine springs. In order to calculate SGD fluxes, it is important to understand the spatial and temporal scales of coastal groundwater exchange. From ER time series data, subsurface salinity distributions were calculated using site-specific formation factors. A salinity mass balance box model was then used to calculate rates of point source (i.e., spatially discreet) and total fresh water discharge. From these data, mean SGD rates were calculated for Kiholo Bay (∼9,200 m3/d) and for the Maunalua Bay site (∼5,900 m3/d). While such results are on the same order of magnitude to geochemical tracer-derived SGD rates, the ER SGD rates provide enhanced details of coastal groundwater exchange that can enable a more cohesive whole watershed perspective.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2011JC007509","usgsCitation":"Dimova, N.T., Swarzenski, P.W., Dulaiova, H., and Glenn, C.R., 2012, Utilizing multichannel electrical resistivity methods to examine the dynamics of the fresh water–seawater interface in two Hawaiian groundwater systems: Journal of Geophysical Research C: Oceans, v. 117, no. C2, C02012; 12 p., https://doi.org/10.1029/2011JC007509.","productDescription":"C02012; 12 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-032654","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":474583,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011jc007509","text":"Publisher Index Page"},{"id":272289,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Big Island, Kiholo Bay, Oahu, Wailupe Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.9,\n 19.83\n ],\n [\n -155.9,\n 19.88\n ],\n [\n -155.95,\n 19.88\n ],\n [\n -155.95,\n 19.83\n ],\n [\n -155.9,\n 19.83\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -157.8,\n 21.25\n ],\n [\n -157.8,\n 21.3\n ],\n [\n -157.75,\n 21.3\n ],\n [\n -157.75,\n 21.25\n ],\n [\n -157.8,\n 21.25\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"117","issue":"C2","noUsgsAuthors":false,"publicationDate":"2012-02-07","publicationStatus":"PW","scienceBaseUri":"51955851e4b0a933d82c4cd7","contributors":{"authors":[{"text":"Dimova, Natasha T.","contributorId":50769,"corporation":false,"usgs":true,"family":"Dimova","given":"Natasha","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":472529,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":472526,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dulaiova, Henrieta","contributorId":46635,"corporation":false,"usgs":true,"family":"Dulaiova","given":"Henrieta","affiliations":[],"preferred":false,"id":472528,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glenn, Craig R.","contributorId":10850,"corporation":false,"usgs":true,"family":"Glenn","given":"Craig","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":472527,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193188,"text":"70193188 - 2012 - Using assemblage data in ecological indicators: A comparison and evaluation of commonly available statistical tools","interactions":[],"lastModifiedDate":"2017-12-01T09:59:57","indexId":"70193188","displayToPublicDate":"2012-02-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Using assemblage data in ecological indicators: A comparison and evaluation of commonly available statistical tools","docAbstract":"Ecological indicators are science-based tools used to assess how human activities have impacted environmental resources. For monitoring and environmental assessment, existing species assemblage data can be used to make these comparisons through time or across sites. An impediment to using assemblage data, however, is that these data are complex and need to be simplified in an ecologically meaningful way. Because multivariate statistics are mathematical relationships, statistical groupings may not make ecological sense and will not have utility as indicators. Our goal was to define a process to select defensible and ecologically interpretable statistical simplifications of assemblage data in which researchers and managers can have confidence. For this, we chose a suite of statistical methods, compared the groupings that resulted from these analyses, identified convergence among groupings, then we interpreted the groupings using species and ecological guilds. When we tested this approach using a statewide stream fish dataset, not all statistical methods worked equally well. For our dataset, logistic regression (Log), detrended correspondence analysis (DCA), cluster analysis (CL), and non-metric multidimensional scaling (NMDS) provided consistent, simplified output. Specifically, the Log, DCA, CL-1, and NMDS-1 groupings were ≥60% similar to each other, overlapped with the fluvial-specialist ecological guild, and contained a common subset of species. Groupings based on number of species (e.g., Log, DCA, CL and NMDS) outperformed groupings based on abundance [e.g., principal components analysis (PCA) and Poisson regression]. Although the specific methods that worked on our test dataset have generality, here we are advocating a process (e.g., identifying convergent groupings with redundant species composition that are ecologically interpretable) rather than the automatic use of any single statistical tool. We summarize this process in step-by-step guidance for the future use of these commonly available ecological and statistical methods in preparing assemblage data for use in ecological indicators.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2011.06.009","usgsCitation":"Smith, J.M., and Mather, M.E., 2012, Using assemblage data in ecological indicators: A comparison and evaluation of commonly available statistical tools: Ecological Indicators, v. 13, no. 1, p. 253-262, https://doi.org/10.1016/j.ecolind.2011.06.009.","productDescription":"10 p.","startPage":"253","endPage":"262","ipdsId":"IP-008536","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":349610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a61059fe4b06e28e9c2556b","contributors":{"authors":[{"text":"Smith, Joseph M.","contributorId":106712,"corporation":false,"usgs":false,"family":"Smith","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":17855,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA","active":true,"usgs":false},{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":724247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mather, Martha E. 0000-0003-3027-0215 mather@usgs.gov","orcid":"https://orcid.org/0000-0003-3027-0215","contributorId":2580,"corporation":false,"usgs":true,"family":"Mather","given":"Martha","email":"mather@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":718143,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70156894,"text":"70156894 - 2012 - Long-term creep rates on the Hayward Fault: Evidence for controls on the size and frequency of large earthquakes","interactions":[],"lastModifiedDate":"2022-11-07T17:40:56.947812","indexId":"70156894","displayToPublicDate":"2012-02-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Long-term creep rates on the Hayward Fault: Evidence for controls on the size and frequency of large earthquakes","docAbstract":"The Hayward fault (HF) in California exhibits large (Mw 6.5–7.1) earthquakes with short recurrence times (161±65 yr), probably kept short by a 26%–78% aseismic release rate (including postseismic). Its interseismic release rate varies locally over time, as we infer from many decades of surface creep data. Earliest estimates of creep rate, primarily from infrequent surveys of offset cultural features, revealed distinct spatial variation in rates along the fault, but no detectable temporal variation. Since the 1989 Mw 6.9 Loma Prieta earthquake (LPE), monitoring on 32 alinement arrays and 5 creepmeters has greatly improved the spatial and temporal resolution of creep rate. We now identify significant temporal variations, mostly associated with local and regional earthquakes. The largest rate change was a 6‐yr cessation of creep along a 5‐km length near the south end of the HF, attributed to a regional stress drop from the LPE, ending in 1996 with a 2‐cm creep event. North of there near Union City starting in 1991, rates apparently increased by 25% above pre‐LPE levels on a 16‐km‐long reach of the fault. Near Oakland in 2007 an Mw 4.2 earthquake initiated a 1–2 cm creep event extending 10–15 km along the fault. Using new better‐constrained long‐term creep rates, we updated earlier estimates of depth to locking along the HF. The locking depths outline a single, ∼50‐km‐long locked or retarded patch with the potential for an Mw∼6.8 event equaling the 1868 HF earthquake. We propose that this inferred patch regulates the size and frequency of large earthquakes on HF.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120110033","usgsCitation":"Lienkaemper, J.J., McFarland, F.S., Simpson, R.W., Bilham, R.G., Ponce, D.A., Boatwright, J., and Caskey, S., 2012, Long-term creep rates on the Hayward Fault: Evidence for controls on the size and frequency of large earthquakes: Bulletin of the Seismological Society of America, v. 102, no. 1, p. 31-41, https://doi.org/10.1785/0120110033.","productDescription":"11 p.","startPage":"31","endPage":"41","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-027196","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":307782,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Hayward Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.38123406534956,\n 38.00934151742379\n ],\n [\n -122.32149985140742,\n 37.926931149563714\n ],\n [\n -122.25536554311417,\n 37.83600445938727\n ],\n [\n -122.14016384479675,\n 37.721344572141575\n ],\n [\n -121.90549371859511,\n 37.51180141349239\n ],\n [\n -121.83935941030182,\n 37.57607899882744\n ],\n [\n -122.06976280693638,\n 37.812412552098394\n ],\n [\n -122.18069777568618,\n 37.93870972218559\n ],\n [\n -122.35350032316217,\n 38.03959147739795\n ],\n [\n -122.38123406534956,\n 38.00934151742379\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"102","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-02-15","publicationStatus":"PW","scienceBaseUri":"55e6cc35e4b05561fa20a01b","contributors":{"authors":[{"text":"Lienkaemper, James J. 0000-0002-7578-7042 jlienk@usgs.gov","orcid":"https://orcid.org/0000-0002-7578-7042","contributorId":1941,"corporation":false,"usgs":true,"family":"Lienkaemper","given":"James","email":"jlienk@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":571018,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McFarland, Forrest S.","contributorId":32104,"corporation":false,"usgs":true,"family":"McFarland","given":"Forrest","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":571019,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simpson, Robert W. simpson@usgs.gov","contributorId":1053,"corporation":false,"usgs":true,"family":"Simpson","given":"Robert","email":"simpson@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":571020,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bilham, Roger G. 0000-0002-5547-4102","orcid":"https://orcid.org/0000-0002-5547-4102","contributorId":48200,"corporation":false,"usgs":true,"family":"Bilham","given":"Roger","email":"","middleInitial":"G.","affiliations":[],"preferred":true,"id":571021,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ponce, David A. 0000-0003-4785-7354 ponce@usgs.gov","orcid":"https://orcid.org/0000-0003-4785-7354","contributorId":1049,"corporation":false,"usgs":true,"family":"Ponce","given":"David","email":"ponce@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":571022,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boatwright, John 0000-0002-6931-5241 boat@usgs.gov","orcid":"https://orcid.org/0000-0002-6931-5241","contributorId":1938,"corporation":false,"usgs":true,"family":"Boatwright","given":"John","email":"boat@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":571023,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Caskey, S. John","contributorId":21483,"corporation":false,"usgs":true,"family":"Caskey","given":"S. John","affiliations":[],"preferred":false,"id":571024,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70007246,"text":"sir20115207 - 2012 - Survey of hydrologic models and hydrologic data needs for tracking flow in the Rio Grande, north-central New Mexico, 2010","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"sir20115207","displayToPublicDate":"2012-01-31T00:00:00","publicationYear":"2012","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":"2011-5207","title":"Survey of hydrologic models and hydrologic data needs for tracking flow in the Rio Grande, north-central New Mexico, 2010","docAbstract":"The six Middle Rio Grande Pueblos have prior and paramount rights to deliveries of water from the Rio Grande for their use. When the pueblos or the Bureau of Indian Affairs Designated Engineer identifies a need for additional flow on the Rio Grande, the Designated Engineer is tasked with deciding the timing and amount of releases of prior and paramount water from storage at El Vado Reservoir to meet the needs of the pueblos. Over the last three decades, numerous models have been developed by Federal, State, and local agencies in New Mexico to simulate, understand, and (or) manage flows in the Middle Rio Grande upstream from Elephant Butte Reservoir. In 2008, the Coalition of Six Middle Rio Grande Basin Pueblos entered into a cooperative agreement with the U.S. Geological Survey to conduct a comprehensive survey of these hydrologic models and their capacity to quantify and track various components of flow. The survey of hydrologic models provided in this report will help water-resource managers at the pueblos, as well as the Designated Engineer, make informed water-resource-management decisions that affect the prior and paramount water use. Analysis of 4 publicly available surface-water models and 13 publicly available groundwater models shows that, although elements from many models can be helpful in tracking flow in the Rio Grande, numerous data gaps and modeling needs indicate that accurate, consistent, and timely tracking of flow on the Rio Grande could be improved. Deficient or poorly constrained hydrologic variables are sources of uncertainty in hydrologic models that can be reduced with the acquisition of more refined data. Data gaps need to be filled to allow hydrologic models to be run on a real-time basis and thus ensure predictable water deliveries to meet needs for irrigation, domestic, stock, and other water uses. Timeliness of flow-data reporting is necessary to facilitate real-time model simulation, but even daily data are sometimes difficult to obtain because the data come from multiple sources. Each surface-water model produces results that could be helpful in quantifying the flow of the Rio Grande, specifically by helping to track water as it moves down the channel of the Rio Grande and by improving the understanding of river hydraulics for the specified reaches. The ability of each surface-water model to track flow on the Rio Grande varies according to the purpose for which each model was designed. The purpose of Upper Rio Grande Water Operations Model (URGWOM) - to simulate water storage and delivery operations in the Rio Grande - is more applicable to tracking flow on the Rio Grande than are any of the other surface-water models surveyed. Specifically, the strengths of URGWOM in relation to modeling flow are the details and attention given to the accounting of Rio Grande flow and San Juan-Chama flow at a daily time step. The most significant difficulty in using any of the surveyed surface-water models for the purpose of predicting the need for requested water releases is that none of the surface-water models surveyed consider water accounting on a real-time basis. Groundwater models that provide detailed simulations of shallow groundwater flow in the vicinity of the Rio Grande can provide large-scale estimates of flow between the Rio Grande and shallow aquifers, which can be an important component of the Rio Grande water budget as a whole. The groundwater models surveyed for this report cannot, however, be expected to provide simulations of flow at time scales of less than the simulated time step (1 month to 1 year in most cases). Of those of the currently used groundwater models, the purpose of model 13 - to simulate the shallow riparian groundwater environment - is the most appropriate for examining local-scale surface-water/groundwater interactions. The basin-scale models, however, are also important in understanding the large-scale water balances between the aquifers and the surface water. In the case of the Upper and Middle Rio Grande Valley, models 6, 10, and 12 are the most accurate and current groundwater models available.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115207","collaboration":"Prepared in cooperation with the Coalition of Six Middle Rio Grande Basin Pueblos","usgsCitation":"Tillery, A., and Eggleston, J.R., 2012, Survey of hydrologic models and hydrologic data needs for tracking flow in the Rio Grande, north-central New Mexico, 2010: U.S. Geological Survey Scientific Investigations Report 2011-5207, vii, 39 p., https://doi.org/10.3133/sir20115207.","productDescription":"vii, 39 p.","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":116455,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5207.gif"},{"id":115750,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5207/","linkFileType":{"id":5,"text":"html"}}],"scale":"24000","projection":"Universal Transverse Mercator, zone 13","datum":"North American Datum of 1988","country":"United States","state":"Colorado;New Mexico","otherGeospatial":"Rio Grande Basin;Elephant Butte Reservoir","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -105,33 ], [ -105,39 ], [ -109,39 ], [ -109,33 ], [ -105,33 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505ba295e4b08c986b31f7e8","contributors":{"authors":[{"text":"Tillery, Anne","contributorId":16120,"corporation":false,"usgs":true,"family":"Tillery","given":"Anne","affiliations":[],"preferred":false,"id":356177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eggleston, Jack R.","contributorId":20011,"corporation":false,"usgs":true,"family":"Eggleston","given":"Jack","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":356178,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70007105,"text":"70007105 - 2012 - A caveat regarding diatom-inferred nitrogen concentrations in oligotrophic lakes","interactions":[],"lastModifiedDate":"2021-01-04T18:07:50.71384","indexId":"70007105","displayToPublicDate":"2012-01-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2411,"text":"Journal of Paleolimnology","active":true,"publicationSubtype":{"id":10}},"title":"A caveat regarding diatom-inferred nitrogen concentrations in oligotrophic lakes","docAbstract":"Atmospheric deposition of reactive nitrogen (Nr) has enriched oligotrophic lakes with nitrogen (N) in many regions of the world and elicited dramatic changes in diatom community structure. The lakewater concentrations of nitrate that cause these community changes remain unclear, raising interest in the development of diatom-based transfer functions to infer nitrate. We developed a diatom calibration set using surface sediment samples from 46 high-elevation lakes across the Rocky Mountains of the western US, a region spanning an N deposition gradient from very low to moderate levels (<1 to 3.2 kg Nr ha−1 year−1 in wet deposition). Out of the fourteen measured environmental variables for these 46 lakes, ordination analysis identified that nitrate, specific conductance, total phosphorus, and hypolimnetic water temperature were related to diatom distributions. A transfer function was developed for nitrate and applied to a sedimentary diatom profile from Heart Lake in the central Rockies. The model coefficient of determination (bootstrapping validation) of 0.61 suggested potential for diatom-inferred reconstructions of lakewater nitrate concentrations over time, but a comparison of observed versus diatom-inferred nitrate values revealed the poor performance of this model at low nitrate concentrations. Resource physiology experiments revealed that nitrogen requirements of two key taxa were opposite to nitrate optima defined in the transfer function. Our data set reveals two underlying ecological constraints that impede the development of nitrate transfer functions in oligotrophic lakes: (1) even in lakes with nitrate concentrations below quantification (<1 μg L−1), diatom assemblages were already dominated by species indicative of moderate N enrichment; (2) N-limited oligotrophic lakes switch to P limitation after receiving only modest inputs of reactive N, shifting the controls on diatom species changes along the length of the nitrate gradient. These constraints suggest that quantitative inferences of nitrate from diatom assemblages will likely require experimental approaches.
","language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10933-011-9576-z","usgsCitation":"Arnett, H.A., Saros, J.E., and Mast, M.A., 2012, A caveat regarding diatom-inferred nitrogen concentrations in oligotrophic lakes: Journal of Paleolimnology, v. 47, no. 2, p. 277-291, https://doi.org/10.1007/s10933-011-9576-z.","productDescription":"15 p.","startPage":"277","endPage":"291","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":204684,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Idaho, Montana, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.02636718749999,\n 37.17782559332976\n ],\n [\n -102.41455078125,\n 37.17782559332976\n ],\n [\n -102.41455078125,\n 48.980216985374994\n ],\n [\n -117.02636718749999,\n 48.980216985374994\n ],\n [\n -117.02636718749999,\n 37.17782559332976\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-01-10","publicationStatus":"PW","scienceBaseUri":"5059e33ce4b0c8380cd45ecc","contributors":{"authors":[{"text":"Arnett, Heather A.","contributorId":74141,"corporation":false,"usgs":true,"family":"Arnett","given":"Heather","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":355826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saros, Jasmine E.","contributorId":29958,"corporation":false,"usgs":true,"family":"Saros","given":"Jasmine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":355825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mast, M. Alisa 0000-0001-6253-8162 mamast@usgs.gov","orcid":"https://orcid.org/0000-0001-6253-8162","contributorId":827,"corporation":false,"usgs":true,"family":"Mast","given":"M.","email":"mamast@usgs.gov","middleInitial":"Alisa","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":355824,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70007241,"text":"mineral2012 - 2012 - Mineral Commodity Summaries 2012","interactions":[],"lastModifiedDate":"2013-02-04T10:57:03","indexId":"mineral2012","displayToPublicDate":"2012-01-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":323,"text":"Mineral Commodity Summaries","code":"MCS","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012","title":"Mineral Commodity Summaries 2012","docAbstract":"Each chapter of the 2012 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production and resources. The MCS is the earliest comprehensive source of 2011 mineral production data for the world. More than 90 individual minerals and materials are covered by 2-page synopses.
\nFor mineral commodities for which there is a Government stockpile, detailed information concerning the stockpile status is included in the two-page synopsis.
\nAbbreviations and units of measure, and definitions of selected terms used in the report, are in Appendix A and Appendix B, respectively. \"Appendix C—Reserves and Resources\" includes \"Part A—Resource/Reserve Classification for Minerals\" and \"Part B—Sources of Reserves Data.\" A directory of USGS minerals information country specialists and their responsibilities is Appendix D.
\nThe USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the MCS 2012 are welcomed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/mineral2012","isbn":"9781411333499","usgsCitation":"Mineral Commodity Summaries 2012; 2012; MINERAL; 2012; ","productDescription":"191 p.; Appendixes; Individual Commodity Data Sheets; Available Online, Printed, and on CD-ROM","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":115736,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://minerals.usgs.gov/minerals/pubs/mcs/","linkFileType":{"id":5,"text":"html"}},{"id":204589,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/mineral_2012.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a574fe4b0c8380cd6dbc7"} ,{"id":70007247,"text":"70007247 - 2012 - Ocean-atmosphere dynamics during Hurricane Ida and Nor'Ida: An application of the coupled ocean-;atmosphere–wave–sediment transport (COAWST) modeling system","interactions":[],"lastModifiedDate":"2017-04-06T15:04:03","indexId":"70007247","displayToPublicDate":"2012-01-27T09:39:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2925,"text":"Ocean Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Ocean-atmosphere dynamics during Hurricane Ida and Nor'Ida: An application of the coupled ocean-;atmosphere–wave–sediment transport (COAWST) modeling system","docAbstract":"The coupled ocean–atmosphere–wave–sediment transport (COAWST) modeling system was used to investigate atmosphere–ocean–wave interactions in November 2009 during Hurricane Ida and its subsequent evolution to Nor'Ida, which was one of the most costly storm systems of the past two decades. One interesting aspect of this event is that it included two unique atmospheric extreme conditions, a hurricane and a nor'easter storm, which developed in regions with different oceanographic characteristics. Our modeled results were compared with several data sources, including GOES satellite infrared data, JASON-1 and JASON-2 altimeter data, CODAR measurements, and wave and tidal information from the National Data Buoy Center (NDBC) and the National Tidal Database. By performing a series of numerical runs, we were able to isolate the effect of the interaction terms between the atmosphere (modeled with Weather Research and Forecasting, the WRF model), the ocean (modeled with Regional Ocean Modeling System (ROMS)), and the wave propagation and generation model (modeled with Simulating Waves Nearshore (SWAN)). Special attention was given to the role of the ocean surface roughness. Three different ocean roughness closure models were analyzed: DGHQ (which is based on wave age), TY2001 (which is based on wave steepness), and OOST (which considers both the effects of wave age and steepness). Including the ocean roughness in the atmospheric module improved the wind intensity estimation and therefore also the wind waves, surface currents, and storm surge amplitude. For example, during the passage of Hurricane Ida through the Gulf of Mexico, the wind speeds were reduced due to wave-induced ocean roughness, resulting in better agreement with the measured winds. During Nor'Ida, including the wave-induced surface roughness changed the form and dimension of the main low pressure cell, affecting the intensity and direction of the winds. The combined wave age- and wave steepness-based parameterization (OOST) provided the best results for wind and wave growth prediction. However, the best agreement between the measured (CODAR) and computed surface currents and storm surge values was obtained with the wave steepness-based roughness parameterization (TY2001), although the differences obtained with respect to DGHQ were not significant. The influence of sea surface temperature (SST) fields on the atmospheric boundary layer dynamics was examined; in particular, we evaluated how the SST affects wind wave generation, surface currents and storm surges. The integrated hydrograph and integrated wave height, parameters that are highly correlated with the storm damage potential, were found to be highly sensitive to the ocean surface roughness parameterization.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ocean Modelling","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.ocemod.2011.12.008","usgsCitation":"Olabarrieta, M., Warner, J., Armstrong, B., Zambon, J.B., and He, R., 2012, Ocean-atmosphere dynamics during Hurricane Ida and Nor'Ida: An application of the coupled ocean-;atmosphere–wave–sediment transport (COAWST) modeling system: Ocean Modelling, v. 43-44, p. 112-137, https://doi.org/10.1016/j.ocemod.2011.12.008.","productDescription":"26 p.","startPage":"112","endPage":"137","numberOfPages":"25","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":474584,"rank":101,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/5124","text":"External Repository"},{"id":204581,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":115753,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1016/j.ocemod.2011.12.008","linkFileType":{"id":5,"text":"html"}}],"volume":"43-44","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a6c98e4b0c8380cd74ce7","contributors":{"authors":[{"text":"Olabarrieta, Maitane 0000-0002-7619-7992 molabarrieta@usgs.gov","orcid":"https://orcid.org/0000-0002-7619-7992","contributorId":81631,"corporation":false,"usgs":true,"family":"Olabarrieta","given":"Maitane","email":"molabarrieta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":356183,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":356179,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Armstrong, Brandy N. barmstrong@usgs.gov","contributorId":5897,"corporation":false,"usgs":true,"family":"Armstrong","given":"Brandy N.","email":"barmstrong@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":356180,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zambon, Joseph B.","contributorId":8222,"corporation":false,"usgs":true,"family":"Zambon","given":"Joseph","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":356181,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"He, Ruoying","contributorId":68029,"corporation":false,"usgs":true,"family":"He","given":"Ruoying","affiliations":[],"preferred":false,"id":356182,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70007235,"text":"gip137 - 2012 - GloVis","interactions":[],"lastModifiedDate":"2012-02-02T00:15:56","indexId":"gip137","displayToPublicDate":"2012-01-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"137","title":"GloVis","docAbstract":"The Global Visualization Viewer (GloVis) trifold provides basic information for online access to a subset of satellite and aerial photography collections from the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center archive. The GloVis (http://glovis.usgs.gov/) browser-based utility allows users to search and download National Aerial Photography Program (NAPP), National High Altitude Photography (NHAP), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Earth Observing-1 (EO-1), Global Land Survey, Moderate Resolution Imaging Spectroradiometer (MODIS), and TerraLook data. Minimum computer system requirements and customer service contact information also are included in the brochure.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip137","usgsCitation":"Houska, T., and Johnson, A., 2012, GloVis: U.S. Geological Survey General Information Product 137, 2 p., https://doi.org/10.3133/gip137.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":116454,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/gip_137.jpg"},{"id":115721,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/gip/137/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a292ee4b0c8380cd5a71d","contributors":{"authors":[{"text":"Houska, Treva R. 0000-0002-4358-6131","orcid":"https://orcid.org/0000-0002-4358-6131","contributorId":45460,"corporation":false,"usgs":true,"family":"Houska","given":"Treva R.","affiliations":[],"preferred":false,"id":356155,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, A.P.","contributorId":22495,"corporation":false,"usgs":true,"family":"Johnson","given":"A.P.","email":"","affiliations":[],"preferred":false,"id":356154,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70007223,"text":"sim3190 - 2012 - Description and validation of an automated methodology for mapping mineralogy, vegetation, and hydrothermal alteration type from ASTER satellite imagery with examples from the San Juan Mountains, Colorado","interactions":[],"lastModifiedDate":"2012-02-10T00:12:01","indexId":"sim3190","displayToPublicDate":"2012-01-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3190","title":"Description and validation of an automated methodology for mapping mineralogy, vegetation, and hydrothermal alteration type from ASTER satellite imagery with examples from the San Juan Mountains, Colorado","docAbstract":"The efficacy of airborne spectroscopic, or \"hyperspectral,\" remote sensing for geoenvironmental watershed evaluations and deposit-scale mapping of exposed mineral deposits has been demonstrated. However, the acquisition, processing, and analysis of such airborne data at regional and national scales can be time and cost prohibitive. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor carried by the NASA Earth Observing System Terra satellite was designed for mineral mapping and the acquired data can be efficiently used to generate uniform mineral maps over very large areas. Multispectral remote sensing data acquired by the ASTER sensor were analyzed to identify and map minerals, mineral groups, hydrothermal alteration types, and vegetation groups in the western San Juan Mountains, Colorado, including the Silverton and Lake City calderas. This mapping was performed in support of multidisciplinary studies involving the predictive modeling of surface water geochemistry at watershed and regional scales. Detailed maps of minerals, vegetation groups, and water were produced from an ASTER scene using spectroscopic, expert system-based analysis techniques which have been previously described. New methodologies are presented for the modeling of hydrothermal alteration type based on the Boolean combination of the detailed mineral maps, and for the entirely automated mapping of alteration types, mineral groups, and green vegetation. Results of these methodologies are compared with the more detailed maps and with previously published mineral mapping results derived from analysis of high-resolution spectroscopic data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor. Such comparisons are also presented for other mineralized and (or) altered areas including the Goldfield and Cuprite mining districts, Nevada and the central Marysvale volcanic field, Wah Wah Mountains, and San Francisco Mountains, Utah. The automated mineral group mapping products described in this study are ideal for application to mineral resource and mineral-environmental assessments at regional and national scales.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3190","usgsCitation":"Rockwell, B.W., 2012, Description and validation of an automated methodology for mapping mineralogy, vegetation, and hydrothermal alteration type from ASTER satellite imagery with examples from the San Juan Mountains, Colorado: U.S. Geological Survey Scientific Investigations Map 3190, Pamphlet: v, 35 p. ;5 Sheets; Sheet 1: 32 inches x 39 inches; Sheet 2: 32 inches x 39 inches; Sheet 3: 32 inches x 39 inches; Sheet 4: 32 inches x 39 inches; Sheet 5: 32 inches x 39 inches; Metadata; Additional Data, https://doi.org/10.3133/sim3190.","productDescription":"Pamphlet: v, 35 p. ;5 Sheets; Sheet 1: 32 inches x 39 inches; Sheet 2: 32 inches x 39 inches; Sheet 3: 32 inches x 39 inches; Sheet 4: 32 inches x 39 inches; Sheet 5: 32 inches x 39 inches; Metadata; Additional Data","numberOfPages":"35","additionalOnlineFiles":"Y","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":116450,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3190.png"},{"id":115712,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3190/","linkFileType":{"id":5,"text":"html"}}],"scale":"100000","country":"United States","state":"Colorado","otherGeospatial":"San Juan Mountains","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -108,37.46666666666667 ], [ -108,38.083333333333336 ], [ -107.15,38.083333333333336 ], [ -107.15,37.46666666666667 ], [ -108,37.46666666666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059feeee4b0c8380cd4efbb","contributors":{"authors":[{"text":"Rockwell, Barnaby W. 0000-0002-9549-0617 barnabyr@usgs.gov","orcid":"https://orcid.org/0000-0002-9549-0617","contributorId":2195,"corporation":false,"usgs":true,"family":"Rockwell","given":"Barnaby","email":"barnabyr@usgs.gov","middleInitial":"W.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":356135,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70007228,"text":"ds657 - 2012 - Selected water-quality data from the Cedar River and Cedar Rapids well fields, Cedar Rapids, Iowa, 2006-10","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"ds657","displayToPublicDate":"2012-01-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"657","title":"Selected water-quality data from the Cedar River and Cedar Rapids well fields, Cedar Rapids, Iowa, 2006-10","docAbstract":"The Cedar River alluvial aquifer is the primary source of municipal water in the Cedar Rapids, Iowa area. Municipal wells are completed in the alluvial aquifer approximately 40 to 80 feet below land surface. The City of Cedar Rapids and the U.S. Geological Survey have been conducting a cooperative study of the groundwater-flow system and water quality of the aquifer since 1992. Cooperative reports between the City of Cedar Rapids and the U.S. Geological Survey have documented hydrologic and water-quality data, geochemistry, and groundwater models. Water-quality samples were collected for studies involving well field monitoring, trends, source-water protection, groundwater geochemistry, surface-water-groundwater interaction, and pesticides in groundwater and surface water. Water-quality analyses were conducted for major ions (boron, bromide, calcium, chloride, fluoride, iron, magnesium, manganese, potassium, silica, sodium, and sulfate), nutrients (ammonia as nitrogen, nitrite as nitrogen, nitrite plus nitrate as nitrogen, and orthophosphate as phosphorus), dissolved organic carbon, and selected pesticides including two degradates of the herbicide atrazine. Physical characteristics (alkalinity, dissolved oxygen, pH, specific conductance and water temperature) were measured in the field and recorded for each water sample collected. This report presents the results of routine water-quality data-collection activities from January 2006 through December 2010. Methods of data collection, quality-assurance, and water-quality analyses are presented. Data include the results of water-quality analyses from quarterly sampling from monitoring wells, municipal wells, and the Cedar River.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds657","collaboration":"Prepared in cooperation with the City of Cedar Rapids","usgsCitation":"Littin, G.R., 2012, Selected water-quality data from the Cedar River and Cedar Rapids well fields, Cedar Rapids, Iowa, 2006-10: U.S. Geological Survey Data Series 657, vi, 32 p., https://doi.org/10.3133/ds657.","productDescription":"vi, 32 p.","onlineOnly":"Y","temporalStart":"2006-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":116449,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_657.jpg"},{"id":115710,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/657/","linkFileType":{"id":5,"text":"html"}}],"scale":"1000000","projection":"Universal Transverse Mercator projection, Zone 15","datum":"North American Datum of 1983","country":"United States","state":"Iowa","county":"Linn","city":"Cedar Rapids","otherGeospatial":"Cedar River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91.75,41.96666666666667 ], [ -91.75,42.03333333333333 ], [ -91.66666666666667,42.03333333333333 ], [ -91.66666666666667,41.96666666666667 ], [ -91.75,41.96666666666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b8cc3e4b08c986b3180ef","contributors":{"authors":[{"text":"Littin, Gregory R. grlittin@usgs.gov","contributorId":1732,"corporation":false,"usgs":true,"family":"Littin","given":"Gregory","email":"grlittin@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":356146,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70007227,"text":"ds660 - 2012 - Construction diagrams, geophysical logs, and lithologic descriptions for boreholes USGS 103, 105, 108, 131, 135, NRF-15, and NRF-16, Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"ds660","displayToPublicDate":"2012-01-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"660","title":"Construction diagrams, geophysical logs, and lithologic descriptions for boreholes USGS 103, 105, 108, 131, 135, NRF-15, and NRF-16, Idaho National Laboratory, Idaho","docAbstract":"This report, prepared in cooperation with the U.S. Department of Energy, summarizes construction, geophysical, and lithologic data collected from about 4,509 feet of core from seven boreholes deepened or drilled by the U.S. Geological Survey (USGS), Idaho National Laboratory (INL) Project Office, from 2006 to 2009 at the INL. USGS 103, 105, 108, and 131 were deepened and cored from 759 to 1,307 feet, 800 to 1,409 feet, 760 to 1,218 feet, and 808 to 1,239 feet, respectively. Boreholes USGS 135, NRF-15, and NRF-16 were drilled and continuously cored from land surface to 1,198, 759, and 425 feet, respectively. Cores were photographed and digitally logged by using commercially available software. Borehole descriptions summarize location, completion date, and amount and type of core recovered.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds660","collaboration":"Prepared in cooperation with the U.S. Department of Energy, DOE/ID-22217","usgsCitation":"Hodges, M., Orr, S.M., Potter, K.E., and LeMaitre, T., 2012, Construction diagrams, geophysical logs, and lithologic descriptions for boreholes USGS 103, 105, 108, 131, 135, NRF-15, and NRF-16, Idaho National Laboratory, Idaho: U.S. Geological Survey Data Series 660, vi, 33 p.; Appendices; Downloadable Appendices A-G, https://doi.org/10.3133/ds660.","productDescription":"vi, 33 p.; Appendices; Downloadable Appendices A-G","temporalStart":"2006-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":116448,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_660.jpg"},{"id":115709,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/660/","linkFileType":{"id":5,"text":"html"}}],"scale":"24000","projection":"Universal Transverse Mercator projection, Zone 12","datum":"Datum is North American Datum of 1927","country":"United States","state":"Idaho","otherGeospatial":"Eastern Snake River Plain;Idaho National Laboratory","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.5,43.25 ], [ -113.5,44 ], [ -112.5,44 ], [ -112.5,43.25 ], [ -113.5,43.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059fa17e4b0c8380cd4d926","contributors":{"authors":[{"text":"Hodges, Mary K.V.","contributorId":66848,"corporation":false,"usgs":true,"family":"Hodges","given":"Mary K.V.","affiliations":[],"preferred":false,"id":356144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orr, Stephanie M.","contributorId":22089,"corporation":false,"usgs":true,"family":"Orr","given":"Stephanie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":356142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Potter, Katherine E.","contributorId":76886,"corporation":false,"usgs":true,"family":"Potter","given":"Katherine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":356145,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LeMaitre, Tynan","contributorId":51455,"corporation":false,"usgs":true,"family":"LeMaitre","given":"Tynan","email":"","affiliations":[],"preferred":false,"id":356143,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70007222,"text":"sir20125005 - 2012 - A comparison of consumptive-use estimates derived from the simplified surface energy balance approach and indirect reporting methods","interactions":[],"lastModifiedDate":"2017-03-29T14:26:09","indexId":"sir20125005","displayToPublicDate":"2012-01-26T00:00:00","publicationYear":"2012","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":"2012-5005","title":"A comparison of consumptive-use estimates derived from the simplified surface energy balance approach and indirect reporting methods","docAbstract":"Recent advances in remote-sensing technology and Simplified Surface Energy Balance (SSEB) methods can provide accurate and repeatable estimates of evapotranspiration (ET) when used with satellite observations of irrigated lands. Estimates of ET are generally considered equivalent to consumptive use (CU) because they represent the part of applied irrigation water that is evaporated, transpired, or otherwise not available for immediate reuse. The U.S. Geological Survey compared ET estimates from SSEB methods to CU data collected for 1995 using indirect methods as part of the National Water Use Information Program (NWUIP). Ten-year (2000-2009) average ET estimates from SSEB methods were derived using Moderate Resolution Imaging Spectroradiometer (MODIS) 1-kilometer satellite land surface temperature and gridded weather datasets from the Global Data Assimilation System (GDAS). County-level CU estimates for 1995 were assembled and referenced to 1-kilometer grid cells to synchronize with the SSEB ET estimates. Both datasets were seasonally and spatially weighted to represent the irrigation season (June-September) and those lands that were identified in the county as irrigated. A strong relation (R2 greater than 0.7) was determined between NWUIP CU and SSEB ET data. Regionally, the relation is stronger in arid western states than in humid eastern states, and positive and negative biases are both present at state-level comparisons. SSEB ET estimates can play a major role in monitoring and updating county-based CU estimates by providing a quick and cost-effective method to detect major year-to-year changes at county levels, as well as providing a means to disaggregate county-based ET estimates to sub-county levels. More research is needed to identify the causes for differences in state-based relations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125005","collaboration":"Groundwater Resources Program","usgsCitation":"Maupin, M.A., Senay, G., Kenny, J., and Savoca, M.E., 2012, A comparison of consumptive-use estimates derived from the simplified surface energy balance approach and indirect reporting methods: U.S. Geological Survey Scientific Investigations Report 2012-5005, iv, 8 p., https://doi.org/10.3133/sir20125005.","productDescription":"iv, 8 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":116452,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5005.jpg"},{"id":115711,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5005/","linkFileType":{"id":5,"text":"html"}},{"id":338663,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5005/pdf/sir20125005.pdf"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e359e4b0c8380cd45fa9","contributors":{"authors":[{"text":"Maupin, Molly A. 0000-0002-2695-5505 mamaupin@usgs.gov","orcid":"https://orcid.org/0000-0002-2695-5505","contributorId":951,"corporation":false,"usgs":true,"family":"Maupin","given":"Molly","email":"mamaupin@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356131,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":66808,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel B.","affiliations":[],"preferred":false,"id":356133,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kenny, Joan F.","contributorId":69132,"corporation":false,"usgs":true,"family":"Kenny","given":"Joan F.","affiliations":[],"preferred":false,"id":356134,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Savoca, Mark E. mesavoca@usgs.gov","contributorId":1961,"corporation":false,"usgs":true,"family":"Savoca","given":"Mark","email":"mesavoca@usgs.gov","middleInitial":"E.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356132,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70005180,"text":"70005180 - 2012 - Using existing data to estimate aquifer properties, Great Lakes Region, USA","interactions":[],"lastModifiedDate":"2012-06-14T01:01:39","indexId":"70005180","displayToPublicDate":"2012-01-24T09:55:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Using existing data to estimate aquifer properties, Great Lakes Region, USA","docAbstract":"To determine specific storage and porosity, areally limited and time-consuming aquifer tests are frequently done. Hydrogeologic studies often do not have the resources to collect such data and rely on existing data sources for aquifer properties. An alternative tool for determining these aquifer properties is the analysis of earth tides. The objective of this study was to determine whether existing water-level and barometric-pressure data could be used to determine aquifer properties, such as porosity and specific storage, on a regional scale. In this study, national databases from the Great Lakes Region were queried for continuous records of groundwater-level and barometric-pressure data. Records from 37 selected wells were then analyzed for barometric efficiency and earth-tide responses. Specific-storage (Ss) and porosity values were determined, and the quality of the results were assessed with a measure of the \"goodness of fit\" (percent variance) of reconstruction of the response. Records from wells completed in several aquifer systems were analyzed with varying degrees of success. Aquifer Ss values ranging from 5.9 x 10-8 to 3.8 x 10-6/m were derived, with percent variance of reconstruction ranging from 1% to 78%. Comparisons with aquifer and laboratory testing of Ss and porosity are favorable if the percent variance of reconstruction is above about 30%. Although the earth-tide-analysis method is not suitable for every situation, the Ss and porosity of aquifers can, in many places, be estimated with existing water-level and barometric-pressure data or with data that are relatively inexpensive to collect.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ground Water","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"National Ground Water Assocation","publisherLocation":"Westerville, OH","doi":"10.1111/j.1745-6584.2011.00848.x","usgsCitation":"Darner, R.A., and Sheets, R., 2012, Using existing data to estimate aquifer properties, Great Lakes Region, USA: Ground Water, v. 50, no. 3, https://doi.org/10.1111/j.1745-6584.2011.00848.x.","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":257571,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257554,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1745-6584.2011.00848.x","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Great Lakes","volume":"50","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-07-28","publicationStatus":"PW","scienceBaseUri":"505bc04be4b08c986b32a03c","contributors":{"authors":[{"text":"Darner, Robert A. 0000-0003-1333-8265 radarner@usgs.gov","orcid":"https://orcid.org/0000-0003-1333-8265","contributorId":1972,"corporation":false,"usgs":true,"family":"Darner","given":"Robert","email":"radarner@usgs.gov","middleInitial":"A.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":352051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheets, Rodney A. rasheets@usgs.gov","contributorId":1848,"corporation":false,"usgs":true,"family":"Sheets","given":"Rodney A.","email":"rasheets@usgs.gov","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":352050,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70007181,"text":"ofr20111312 - 2012 - Preliminary investigations of the winter ecology of Long-billed Curlews in coastal Texas","interactions":[],"lastModifiedDate":"2012-02-10T00:12:01","indexId":"ofr20111312","displayToPublicDate":"2012-01-23T11:26:00","publicationYear":"2012","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":"2011-1312","title":"Preliminary investigations of the winter ecology of Long-billed Curlews in coastal Texas","docAbstract":"Since the early 1900s, the distribution of the Long-billed Curlew (Numenius americanus) has contracted dramatically in the eastern one-half of its historic range. The species has been designated as a \"Bird of Conservation Concern\" and focal species by the U.S. Fish and Wildlife Service, a species of concern by several states, and a \"Highly Imperiled\" species in the U.S. Shorebird Conservation Plan. The uncertain outlook for this species has contributed to a plethora of research on Long-billed Curlews, most of which have focused on breeding and nesting ecology of the species. Gaps remain in information about factors affecting population dynamics on the winter grounds and the linkages between Long-billed Curlew populations on the breeding range, migration routes, and winter range. To begin filling those gaps, a pilot study was done to evaluate (1) curlew use of nocturnal roost sites, (2) use of public outreach to locate curlews and contribute to preliminary assessment of foraging habitat use, (3) six different methods to capture curlews, and (4) movements by curlews on wintering areas. The study area includes the lower Texas coast, which harbors the eastern-most dense populations of Long-billed Curlews in North America.
\nUse of historical winter roost sites was not observed; however, there was documented limited use (up to 150 curlews) of several new roost sites, some of which were used on an intermittent or erratic basis. Reports elicited from the public indicated Long-billed Curlews wintering in coastal Texas often forage in open, grass-covered lots of partially developed residential areas, golf courses, and public parks within urban and suburban zones. Curlews were reported to use these sites in developed areas as far as 100 kilometers inland. Other reports indicated Long-billed Curlews foraging in farm fields, shallow coastal marsh, and on the beaches of Gulf of Mexico barrier islands.
\nThe effectiveness of six techniques for capture of Long-billed Curlews was evaluated in the study. Seven curlews were captured and banded with four of six methods attempted. At least one curlew each was captured with (1) noose ropes, (2) baited bow net, (3) Coda Netgun, and (4) whoosh net; no curlews were caught with a cast net or Super Talon netgun. The Coda Netgun proved to be the most effective methodology examined. Captured birds (7) were weighed, measured, and banded. Body masses (mean = 518 grams) were low compared to data previously published on body mass of Long-billed Curlews. There were 22 observations recorded of banded curlews. Resightings confirmed that birds were not harmed during capture. All of the 22 resightings occurred within two kilometers of the banding locations, suggesting that birds remained near their chosen foraging areas.
\nResults from this 1-year pilot study yielded an intriguing combination of findings that warrant further investigation. Observations include reduced numbers of roosting birds along the Texas coast during dry conditions, highly dynamic use of nocturnal roost sites, use of widely divergent habitat types for foraging, low body mass of most captured birds, and apparent fidelity to general feeding areas. Future investigations of this eastern winter population of curlews would benefit from larger sample sizes and monitoring of individual birds.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111312","usgsCitation":"Woodin, M.C., Skoruppa, M.K., Edwardson, J.W., and Austin, J., 2012, Preliminary investigations of the winter ecology of Long-billed Curlews in coastal Texas: U.S. Geological Survey Open-File Report 2011-1312, vi, 17 p., https://doi.org/10.3133/ofr20111312.","productDescription":"vi, 17 p.","onlineOnly":"Y","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":116373,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1312.jpg"},{"id":115679,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1312/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Texas","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -99.5,26.666666666666668 ], [ -99.5,29 ], [ -95.16666666666667,29 ], [ -95.16666666666667,26.666666666666668 ], [ -99.5,26.666666666666668 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a8856e4b0c8380cd7d865","contributors":{"authors":[{"text":"Woodin, Marc C.","contributorId":56316,"corporation":false,"usgs":true,"family":"Woodin","given":"Marc","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":356027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skoruppa, Mary Kay","contributorId":24872,"corporation":false,"usgs":true,"family":"Skoruppa","given":"Mary","email":"","middleInitial":"Kay","affiliations":[],"preferred":false,"id":356025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwardson, Jeremy W.","contributorId":22091,"corporation":false,"usgs":true,"family":"Edwardson","given":"Jeremy","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":356024,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Austin, Jane E.","contributorId":43094,"corporation":false,"usgs":true,"family":"Austin","given":"Jane E.","affiliations":[],"preferred":false,"id":356026,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70007190,"text":"ofr20111261 - 2012 - Shallow coal exploration drill-hole data--Alabama, Georgia, Kentucky, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, and Texas","interactions":[],"lastModifiedDate":"2019-06-06T08:05:56","indexId":"ofr20111261","displayToPublicDate":"2012-01-23T00:00:00","publicationYear":"2012","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":"2011-1261","title":"Shallow coal exploration drill-hole data--Alabama, Georgia, Kentucky, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, and Texas","docAbstract":"Coal exploration drill-hole data from over 24,000 wells in 10 States are discussed by State in the chapters of this report, and the data are provided in an accompanying spreadsheet. The drill holes were drilled between 1962 and 1984 by Phillips Coal Company, a division of Phillips Petroleum Company (Phillips). The data were donated to the U.S. Geological Survey (USGS) in 2001 by the North American Coal Corporation, which purchased the Phillips assets as part of a larger dataset. Under the terms of the agreement with North American Coal Corporation, the data were deemed proprietary until February 2011, a period of 10 years after the donation (Appendix of Chapter A). Now that the required period of confidentiality has passed, the data have been digitized from tabulated data files to create unified and spatially consistent coal exploration drill-hole maps and reports for the States of Alabama, Georgia, Kentucky, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, and Texas. The data are made publicly available by this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111261","usgsCitation":"Valentine, B.J., and Dennen, K., 2012, Shallow coal exploration drill-hole data--Alabama, Georgia, Kentucky, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, and Texas: U.S. Geological Survey Open-File Report 2011-1261, Report: 104 p., 12 Appendixes, https://doi.org/10.3133/ofr20111261.","productDescription":"Report: 104 p., 12 Appendixes","numberOfPages":"104","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[],"links":[{"id":116372,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1261.gif"},{"id":115683,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1261/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alabama; Georgia; Kentucky; Louisiana; Mississippi; Missouri; North Carolina; South Carolina; Tennessee; Texas","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-81.677535,36.588117],[-75.867044,36.550754],[-75.533012,35.787377],[-75.960069,36.495025],[-75.791637,36.082267],[-76.132005,36.287773],[-76.191715,36.107197],[-76.447812,36.192514],[-76.298733,36.1012],[-76.575936,36.006167],[-76.721445,36.147838],[-76.675462,36.266882],[-76.744436,36.212725],[-76.608052,35.936668],[-76.014685,35.960361],[-76.046813,35.717935],[-75.86042,35.978262],[-75.713502,35.693993],[-76.165392,35.328659],[-76.499251,35.381492],[-76.586349,35.508957],[-76.476706,35.511707],[-76.634468,35.510332],[-76.580187,35.387113],[-77.023912,35.514802],[-76.472273,35.294936],[-76.801426,34.964369],[-76.958465,35.047647],[-76.762931,34.920374],[-76.463468,35.076411],[-76.332044,34.970917],[-76.524712,34.681964],[-76.673619,34.71491],[-76.523303,34.652271],[-76.093349,35.048705],[-76.524199,34.615416],[-76.990262,34.669623],[-77.556943,34.417218],[-77.956881,33.87779],[-78.383964,33.901946],[-78.862931,33.705654],[-79.359961,33.006672],[-79.55756,33.021269],[-80.905378,32.051943],[-80.841913,32.002643],[-81.065255,31.877095],[-81.254218,31.55594],[-81.17831,31.52241],[-81.276862,31.254734],[-81.490586,30.984952],[-81.408484,30.977718],[-81.461065,30.753684],[-82.004973,30.791744],[-82.116385,30.367335],[-82.227254,30.561041],[-84.836324,30.710709],[-84.997628,30.971186],[-85.145835,31.000695],[-87.598928,30.997457],[-87.615367,30.837031],[-87.39643,30.617734],[-87.558097,30.274437],[-88.014572,30.222366],[-87.766626,30.262353],[-88.008396,30.684956],[-88.191542,30.317002],[-89.315067,30.375408],[-89.461275,30.174745],[-89.854533,30.007821],[-89.711158,29.879287],[-89.418465,30.049747],[-89.231178,29.925484],[-89.42421,29.697638],[-89.598068,29.74757],[-89.487915,29.630405],[-89.681092,29.534487],[-89.02185,29.218162],[-89.09126,29.066931],[-89.383814,28.947434],[-89.447472,29.178576],[-89.782149,29.311132],[-89.832898,29.463536],[-90.01251,29.462775],[-90.097678,29.26199],[-90.019772,29.231903],[-90.174273,29.105301],[-90.343293,29.057062],[-90.311523,29.256374],[-90.495299,29.287277],[-90.811473,29.03658],[-91.278792,29.247776],[-91.258226,29.446954],[-91.854677,29.807436],[-92.134347,29.669516],[-91.719102,29.565568],[-91.848665,29.484144],[-93.267456,29.778113],[-94.056506,29.671163],[-94.731047,29.369141],[-94.532348,29.5178],[-94.767246,29.525523],[-94.724616,29.774766],[-94.965963,29.70033],[-94.894234,29.338],[-95.16525,29.113566],[-94.73132,29.338066],[-94.803695,29.279237],[-96.341617,28.417334],[-95.983106,28.641942],[-96.221784,28.580364],[-96.287942,28.683164],[-96.473694,28.57324],[-96.664534,28.696904],[-96.481836,28.407844],[-96.790235,28.383926],[-96.898123,28.152881],[-97.21535,28.076575],[-97.040618,28.028708],[-97.183455,27.833231],[-97.354614,27.849572],[-97.296598,27.613947],[-97.399398,27.344735],[-97.640111,27.270943],[-97.485149,27.250841],[-97.552325,26.867633],[-97.145567,25.971132],[-97.36542,25.849826],[-99.110855,26.426278],[-99.452316,27.062669],[-99.556812,27.614336],[-99.841708,27.766464],[-100.280518,28.267969],[-100.785521,29.228137],[-101.441059,29.753451],[-102.341033,29.869305],[-102.698347,29.695591],[-103.107811,29.013812],[-103.427754,29.042334],[-104.46652,29.609296],[-104.924796,30.604832],[-106.158218,31.438885],[-106.623933,31.925335],[-103.088698,32.000453],[-103.041924,36.500439],[-100.003762,36.499699],[-100.000381,34.560509],[-99.630905,34.376007],[-99.381011,34.456936],[-99.192104,34.216694],[-98.504182,34.072371],[-98.138979,34.141805],[-97.905467,33.863531],[-97.688023,33.986607],[-97.372941,33.819454],[-97.226522,33.914642],[-97.126102,33.716941],[-96.922114,33.959579],[-96.36959,33.716809],[-95.230491,33.960764],[-94.413155,33.569368],[-94.100107,33.572568],[-94.043036,33.079485],[-93.814553,33.019372],[-91.166073,33.004106],[-91.057621,33.445341],[-91.210275,33.433796],[-91.086758,33.95827],[-90.874541,34.072041],[-90.93268,34.214824],[-90.580677,34.410554],[-90.483969,34.877176],[-90.250095,34.90732],[-90.09061,35.118287],[-90.112504,35.410153],[-89.923161,35.514428],[-89.915491,35.754917],[-89.714565,35.963034],[-90.368718,35.995812],[-90.075934,36.281485],[-90.157136,36.484317],[-94.617919,36.499414],[-94.605734,39.122204],[-95.082714,39.516712],[-94.876344,39.806894],[-95.382957,40.027112],[-95.731179,40.525436],[-95.64184,40.584234],[-91.696359,40.588148],[-91.452458,40.375501],[-91.510322,40.127994],[-91.369953,39.745042],[-90.721593,39.23273],[-90.653164,38.916141],[-90.113327,38.849306],[-90.367013,38.250054],[-89.952499,37.883218],[-89.516685,37.692762],[-89.438275,37.161287],[-89.185491,36.973518],[-89.00592,37.221198],[-88.490276,37.067836],[-88.450127,37.411717],[-88.062568,37.513563],[-88.158374,37.639948],[-87.865558,37.915056],[-87.672397,37.829127],[-87.380247,37.935596],[-87.14195,37.816176],[-86.794985,37.988982],[-86.604624,37.858272],[-86.431749,38.126121],[-86.271802,38.137874],[-86.048458,37.959369],[-85.823764,38.280569],[-85.425787,38.52873],[-85.456978,38.689135],[-84.835672,38.784289],[-84.87805,39.030819],[-84.754449,39.146658],[-84.449793,39.117754],[-84.222059,38.813753],[-83.68552,38.63189],[-83.156926,38.620547],[-82.879492,38.751476],[-82.844306,38.590862],[-82.610458,38.471457],[-82.619429,38.169027],[-82.474635,37.905902],[-81.982479,37.541807],[-83.128813,36.757864],[-83.625013,36.625183],[-81.677535,36.588117]]],[[[-88.865067,29.752714],[-88.940346,29.657234],[-88.86972,30.043798],[-88.865067,29.752714]]],[[[-75.753765,35.199612],[-75.523952,35.318198],[-75.533512,35.773577],[-75.52592,35.233839],[-75.982812,35.081513],[-75.753765,35.199612]]],[[[-97.240849,26.411504],[-97.383531,26.875521],[-97.366771,27.333276],[-96.946988,28.026522],[-96.403206,28.371475],[-96.929053,27.99044],[-97.276091,27.472145],[-97.370731,26.909706],[-97.161471,26.088705],[-97.240849,26.411504]]]]},\"properties\":{\"name\":\"Alabama\",\"nation\":\"USA \"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b8e19e4b08c986b318724","contributors":{"authors":[{"text":"Valentine, Brett J. 0000-0002-8678-2431 bvalentine@usgs.gov","orcid":"https://orcid.org/0000-0002-8678-2431","contributorId":3846,"corporation":false,"usgs":true,"family":"Valentine","given":"Brett","email":"bvalentine@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":356034,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dennen, Kristin O.","contributorId":61437,"corporation":false,"usgs":true,"family":"Dennen","given":"Kristin O.","affiliations":[],"preferred":false,"id":356035,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70007169,"text":"ofr20111306 - 2012 - User's guide for mapIMG 3--Map image re-projection software package","interactions":[],"lastModifiedDate":"2012-02-02T00:16:02","indexId":"ofr20111306","displayToPublicDate":"2012-01-20T00:00:00","publicationYear":"2012","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":"2011-1306","title":"User's guide for mapIMG 3--Map image re-projection software package","docAbstract":"Version 0.0 (1995), Dan Steinwand, U.S. Geological Survey (USGS)/Earth Resources Observation Systems (EROS) Data Center (EDC)--Version 0.0 was a command line version for UNIX that required four arguments: the input metadata, the output metadata, the input data file, and the output destination path. Version 1.0 (2003), Stephen Posch and Michael P. Finn, USGS/Mid-Continent Mapping Center (MCMC--Version 1.0 added a GUI interface that was built using the Qt library for cross platform development. Version 1.01 (2004), Jason Trent and Michael P. Finn, USGS/MCMC--Version 1.01 suggested bounds for the parameters of each projection. Support was added for larger input files, storage of the last used input and output folders, and for TIFF/ GeoTIFF input images. Version 2.0 (2005), Robert Buehler, Jason Trent, and Michael P. Finn, USGS/National Geospatial Technical Operations Center (NGTOC)--Version 2.0 added Resampling Methods (Mean, Mode, Min, Max, and Sum), updated the GUI design, and added the viewer/pre-viewer. The metadata style was changed to XML and was switched to a new naming convention. Version 3.0 (2009), David Mattli and Michael P. Finn, USGS/Center of Excellence for Geospatial Information Science (CEGIS)--Version 3.0 brings optimized resampling methods, an updated GUI, support for less than global datasets, UTM support and the whole codebase was ported to Qt4.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111306","usgsCitation":"Finn, M.P., and Mattli, D.M., 2012, User's guide for mapIMG 3--Map image re-projection software package: U.S. Geological Survey Open-File Report 2011-1306, iv, 12 p., https://doi.org/10.3133/ofr20111306.","productDescription":"iv, 12 p.","startPage":"i","endPage":"12","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"links":[{"id":116445,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1306.jpg"},{"id":115659,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1306/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bbfdae4b08c986b329dd1","contributors":{"authors":[{"text":"Finn, Michael P. 0000-0003-0415-2194 mfinn@usgs.gov","orcid":"https://orcid.org/0000-0003-0415-2194","contributorId":2657,"corporation":false,"usgs":true,"family":"Finn","given":"Michael","email":"mfinn@usgs.gov","middleInitial":"P.","affiliations":[{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":356015,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mattli, David M. dmattli@usgs.gov","contributorId":5606,"corporation":false,"usgs":true,"family":"Mattli","given":"David","email":"dmattli@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":356016,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70007142,"text":"70007142 - 2012 - Integrating scales of seagrass monitoring to meet conservation needs","interactions":[],"lastModifiedDate":"2020-12-30T18:03:46.117277","indexId":"70007142","displayToPublicDate":"2012-01-19T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Integrating scales of seagrass monitoring to meet conservation needs","docAbstract":"We evaluated a hierarchical framework for seagrass monitoring in two estuaries in the northeastern USA: Little Pleasant Bay, Massachusetts, and Great South Bay/Moriches Bay, New York. This approach includes three tiers of monitoring that are integrated across spatial scales and sampling intensities. We identified monitoring attributes for determining attainment of conservation objectives to protect seagrass ecosystems from estuarine nutrient enrichment. Existing mapping programs provided large-scale information on seagrass distribution and bed sizes (tier 1 monitoring). We supplemented this with bay-wide, quadrat-based assessments of seagrass percent cover and canopy height at permanent sampling stations following a spatially distributed random design (tier 2 monitoring). Resampling simulations showed that four observations per station were sufficient to minimize bias in estimating mean percent cover on a bay-wide scale, and sample sizes of 55 stations in a 624-ha system and 198 stations in a 9,220-ha system were sufficient to detect absolute temporal increases in seagrass abundance from 25% to 49% cover and from 4% to 12% cover, respectively. We made high-resolution measurements of seagrass condition (percent cover, canopy height, total and reproductive shoot density, biomass, and seagrass depth limit) at a representative index site in each system (tier 3 monitoring). Tier 3 data helped explain system-wide changes. Our results suggest tiered monitoring as an efficient and feasible way to detect and predict changes in seagrass systems relative to multi-scale conservation objectives.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-011-9410-x","usgsCitation":"Neckles, H.A., Kopp, B.S., Peterson, B.J., and Pooler, P.S., 2012, Integrating scales of seagrass monitoring to meet conservation needs: Estuaries and Coasts, v. 35, no. 1, p. 23-46, https://doi.org/10.1007/s12237-011-9410-x.","productDescription":"24 p.","startPage":"23","endPage":"46","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":381760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.301513671875,\n 41.74672584176937\n ],\n [\n -69.89501953125,\n 41.74672584176937\n ],\n [\n -69.89501953125,\n 42.12267315117256\n ],\n [\n -70.301513671875,\n 42.12267315117256\n ],\n [\n -70.301513671875,\n 41.74672584176937\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-05-10","publicationStatus":"PW","scienceBaseUri":"505a3c82e4b0c8380cd62dc8","contributors":{"authors":[{"text":"Neckles, Hilary A. 0000-0002-5662-2314 hneckles@usgs.gov","orcid":"https://orcid.org/0000-0002-5662-2314","contributorId":3821,"corporation":false,"usgs":true,"family":"Neckles","given":"Hilary","email":"hneckles@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":355927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kopp, Blaine S.","contributorId":99648,"corporation":false,"usgs":true,"family":"Kopp","given":"Blaine","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":355930,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, Bradley J.","contributorId":84502,"corporation":false,"usgs":true,"family":"Peterson","given":"Bradley","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":355929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pooler, Penelope S.","contributorId":51018,"corporation":false,"usgs":true,"family":"Pooler","given":"Penelope","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":355928,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70156821,"text":"70156821 - 2012 - Fluid geochemistry of Yucca Mountain and vicinity","interactions":[],"lastModifiedDate":"2015-08-28T16:03:13","indexId":"70156821","displayToPublicDate":"2012-01-19T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Fluid geochemistry of Yucca Mountain and vicinity","docAbstract":"Yucca Mountain, a site in southwest Nevada, has been proposed for a deep underground radioactive waste repository. An extensive database of geochemical and isotopic characteristics has been established for pore waters and gases from the unsaturated zone, perched water, and saturated zone waters in the Yucca Mountain area. The development of this database has been driven by diverse needs of the Yucca Mountain Project, especially those aspects of the project involving process modeling and performance assessment. Water and gas chemistries influence the sorption behavior of radionuclides and the solubility of the radionuclide compounds that form. The chemistry of waters that may infiltrate the proposed repository will be determined in part by that of water present in the unsaturated zone above the proposed repository horizon, whereas pore-water compositions beneath the repository horizon will influence the sorption behavior of the radionuclides transported toward the water table. However, more relevant to the discussion in this chapter, development and testing of conceptual flow and transport models for the Yucca Mountain hydrologic system are strengthened through the incorporation of natural environmental tracer data into the process. Chemical and isotopic data are used to establish bounds on key hydrologic parameters and to provide corroborative evidence for model assumptions and predictions. Examples of specific issues addressed by these data include spatial and temporal variability in net fluxes, the role of faults in controlling flow paths, fracture-matrix interactions, the age and origin of perched water, and the distribution of water traveltimes.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Hydrology and geochemistry of Yucca Mountain and vicinity, Southern Nevada and California","language":"English","publisher":"Geological Society of America","doi":"10.1130/2012.1209(04)","usgsCitation":"Marshall, B.D., Moscati, R.J., and Patterson, G.L., 2012, Fluid geochemistry of Yucca Mountain and vicinity, chap. of Hydrology and geochemistry of Yucca Mountain and vicinity, Southern Nevada and California, p. 143-218, https://doi.org/10.1130/2012.1209(04).","productDescription":"76 p.","startPage":"143","endPage":"218","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":307694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Yucca Mountain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.79702758789061,\n 36.6959520787169\n ],\n [\n -116.79702758789061,\n 37.12857106113289\n ],\n [\n -116.09527587890624,\n 37.12857106113289\n ],\n [\n -116.09527587890624,\n 36.6959520787169\n ],\n [\n -116.79702758789061,\n 36.6959520787169\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f545e4b0bc0bec0a152b","contributors":{"editors":[{"text":"Stuckless, John S. 0000-0002-7536-0444 jstuckless@usgs.gov","orcid":"https://orcid.org/0000-0002-7536-0444","contributorId":4974,"corporation":false,"usgs":true,"family":"Stuckless","given":"John","email":"jstuckless@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":570695,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Marshall, Brian D. 0000-0002-8093-0093 bdmarsha@usgs.gov","orcid":"https://orcid.org/0000-0002-8093-0093","contributorId":520,"corporation":false,"usgs":true,"family":"Marshall","given":"Brian","email":"bdmarsha@usgs.gov","middleInitial":"D.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":570692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moscati, Richard J. 0000-0002-0818-4401 rmoscati@usgs.gov","orcid":"https://orcid.org/0000-0002-0818-4401","contributorId":2462,"corporation":false,"usgs":true,"family":"Moscati","given":"Richard","email":"rmoscati@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":570693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Patterson, Gary L. glpatter@usgs.gov","contributorId":519,"corporation":false,"usgs":true,"family":"Patterson","given":"Gary","email":"glpatter@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":570694,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70007152,"text":"sir20115208 - 2012 - Wastewater indicator compounds in wastewater effluent, surface water, and bed sediment in the St. Croix National Scenic Riverway and implications for water resources and aquatic biota, Minnesota and Wisconsin, 2007-08","interactions":[],"lastModifiedDate":"2012-03-08T17:16:42","indexId":"sir20115208","displayToPublicDate":"2012-01-19T00:00:00","publicationYear":"2012","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":"2011-5208","title":"Wastewater indicator compounds in wastewater effluent, surface water, and bed sediment in the St. Croix National Scenic Riverway and implications for water resources and aquatic biota, Minnesota and Wisconsin, 2007-08","docAbstract":"The U.S. Geological Survey and the National Park Service cooperated on a study to determine the occurrence of wastewater indicator compounds including nutrients; organic wastewater compounds (OWCs), such as compounds used in plastic components, surfactant metabolites, antimicrobials, fragrances, and fire retardants; and pharmaceuticals in the St. Croix National Scenic Riverway in Minnesota and Wisconsin. Samples of treated wastewater effluent from two wastewater-treatment plants (WWTPs), located in St. Croix Falls, Wisc. (SCF-WWTP) and Taylors Falls, Minn. (TF-WWTP), were collected from 2007 to 2008. During this time, surface-water and bed-sediment samples from the St. Croix River below Sunrise River near Sunrise, Minn., upstream from the two WWTPs (Sunrise site), and from the St. Croix River above Rock Island near Franconia, Minn., downstream from the WWTPs (Franconia site), also were collected. The Franconia site was selected because of the two large WWTP discharge points and the presence of mussel beds in this area of the St. Croix River.\nA variety of OWCs and pharmaceuticals were detected in wastewater effluent from both WWTPs. Compounds detected varied between the two WWTPs and varied over time from samples collected at each site. The concentration and numbers of OWCs detected were greater in the wastewater effluent samples from SCF-WWTP (38 OWCs and 7 pharmaceuticals detected) than from TF-WWTP (20 OWCs and 3 pharmaceuticals detected). Four endocrine active compounds, compounds known to affect the endocrine systems of fish-4-nonylphenol, 4-nonylphenol diethoxylate, acetyl hexamethyl tetrahydronaphthalene, and hexahydrohexamethyl cyclopentabenzopyran-also were detected in effluent samples from both WWTPs. Concentrations of phosphate flame retardants were greater in effluent from SCF-WWTP than from TF-WWTP with the concentration of tris(2-butoxyethyl) phosphate greater than 200 micrograms per liter.\nSeven OWCs, including one endocrine active compound, and two pharmaceuticals were detected in surface-water samples from the Sunrise site. Twelve OWCs and three pharmaceuticals were detected in surface-water samples from the Franconia site. Eighteen OWCs were detected in bed-sediment samples from the Sunrise site, whereas 21 OWCs were detected in bed-sediment samples from the Franconia site. Eight pharmaceuticals were detected in bed-sediment samples from both sites.\nThe results of this study indicate that aquatic biota in the St. Croix River are exposed to a wide variety of organic contaminants that originate from diverse sources including WWTP effluent. The data on wastewater indicator compounds indicate that exposures are temporally and spatially variable and that OWCs may accumulate in bed sediment. These results also indicate that OWCs in water and bed sediment increase downstream from discharges of wastewater effluent to the St. Croix River; however, the presence of OWCs in surface water and bed sediment at the Sunrise site indicates that potential sources of compounds, such as WWTPs or other sources, are upstream from the Taylors Falls-St. Croix Falls area.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115208","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Tomasek, A., Lee, K., and Hansen, D.S., 2012, Wastewater indicator compounds in wastewater effluent, surface water, and bed sediment in the St. Croix National Scenic Riverway and implications for water resources and aquatic biota, Minnesota and Wisconsin, 2007-08: U.S. Geological Survey Scientific Investigations Report 2011-5208, viii, 34 p.; Appendices; Tables; Figures, https://doi.org/10.3133/sir20115208.","productDescription":"viii, 34 p.; Appendices; Tables; Figures","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2007-01-01","temporalEnd":"2008-12-31","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":116444,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5208.jpg"},{"id":112506,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5208/","linkFileType":{"id":5,"text":"html"}}],"state":"Minnesota;Wisconsin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -93.75,44.5 ], [ -93.75,46.75 ], [ -91,46.75 ], [ -91,44.5 ], [ -93.75,44.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bc3fbe4b08c986b32b440","contributors":{"authors":[{"text":"Tomasek, Abigail A.","contributorId":6187,"corporation":false,"usgs":true,"family":"Tomasek","given":"Abigail A.","affiliations":[],"preferred":false,"id":355949,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Kathy 0000-0002-7683-1367 klee@usgs.gov","orcid":"https://orcid.org/0000-0002-7683-1367","contributorId":2538,"corporation":false,"usgs":true,"family":"Lee","given":"Kathy","email":"klee@usgs.gov","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":355948,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Donald S. dshansen@usgs.gov","contributorId":455,"corporation":false,"usgs":true,"family":"Hansen","given":"Donald","email":"dshansen@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":355947,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70007183,"text":"ds663 - 2012 - Steroidal hormones and other endocrine active compounds in shallow groundwater in nonagricultural areas of Minnesota—Study design, methods, and data, 2009–10","interactions":[],"lastModifiedDate":"2012-03-08T17:16:42","indexId":"ds663","displayToPublicDate":"2012-01-18T12:18:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"663","title":"Steroidal hormones and other endocrine active compounds in shallow groundwater in nonagricultural areas of Minnesota—Study design, methods, and data, 2009–10","docAbstract":"The U.S. Geological Survey, in cooperation with the Minnesota Pollution Control Agency, completed a study on the occurrence of steroidal hormones and other endocrine active compounds in shallow groundwater in nonagricultural areas of Minnesota during 2009–10. This report describes the study design and methods, and presents the data collected on steroidal hormones and other related compounds. Environmental and quality-control samples were collected from 40 wells as part of this study. Samples were analyzed by the U.S. Geological Survey National Water Quality Laboratory for 16 steroidal hormones and 4 other related compounds, of which all but 2 compounds are endocrine active compounds. Most of the water samples did not contain detectable concentrations of any of the 20 compounds analyzed. Water samples from three wells had detectable concentrations of one or more compounds. Bisphenol A was detected in samples from three wells, and trans-diethylstilbestrol was detected in one of the samples in which bisphenol A also was detected.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds663","collaboration":"Prepared in cooperation with the Minnesota Pollution Control Agency","usgsCitation":"Erickson, M., 2012, Steroidal hormones and other endocrine active compounds in shallow groundwater in nonagricultural areas of Minnesota—Study design, methods, and data, 2009–10: U.S. Geological Survey Data Series 663, vi, 9 p.; Downloads Directory, https://doi.org/10.3133/ds663.","productDescription":"vi, 9 p.; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2009-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":116368,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_663.jpg"},{"id":115681,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/663/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Minnesota","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.25,43 ], [ -97.25,50 ], [ -89,50 ], [ -89,43 ], [ -97.25,43 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b983ae4b08c986b31befc","contributors":{"authors":[{"text":"Erickson, Melinda L. 0000-0002-1117-2866 merickso@usgs.gov","orcid":"https://orcid.org/0000-0002-1117-2866","contributorId":3671,"corporation":false,"usgs":true,"family":"Erickson","given":"Melinda L.","email":"merickso@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356030,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70007182,"text":"sir20115224 - 2012 - Base flow (1966-2009) and streamflow gain and loss (2010) of the Brazos River from the New Mexico-Texas State line to Waco, Texas","interactions":[],"lastModifiedDate":"2016-08-08T09:26:15","indexId":"sir20115224","displayToPublicDate":"2012-01-18T11:48:00","publicationYear":"2012","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":"2011-5224","title":"Base flow (1966-2009) and streamflow gain and loss (2010) of the Brazos River from the New Mexico-Texas State line to Waco, Texas","docAbstract":"During 2010–11, the U.S. Geological Survey (USGS), in cooperation with the Texas Water Development Board, used hydrograph separation to quantify historical base flow at 11 USGS streamflow-gaging stations between water years 1966–2009 and streamflow gains and losses from two sets of synoptic measurements of streamflow and specific conductance (the first in June 2010, followed by another set in October 2010) in the upper Brazos River Basin from the New Mexico–Texas State line to Waco, Texas. The following subbasins compose the study area: Salt Fork Brazos River Basin, Double Mountain Fork Brazos River Basin, Clear Fork Brazos River Basin, North Bosque River Basin, and the Brazos River Basin (main stem) (including its tributaries). Base-flow analysis was done using historical streamflow data from 11 USGS streamflow-gaging stations in the upper Brazos River Basin to compute yearly base-flow indexes (base flow divided by total streamflow) for each station. The base-flow index was used to indicate the fraction of flow consisting of base flow on an annual basis for the period of record evaluated at each streamflow-gaging station. At nine stations there were long-term streamflow data from water years 1966–2009 (October 1965 through September 2009); at two stations slightly shorter periods of record (water years 1967–2009 and 1969–2009) were available. The median base-flow indexes were 0.16 and 0.15 at USGS streamflow-gaging stations 08082000 Salt Fork Brazos River near Aspermont, Tex., and 08080500 Double Mountain Fork Brazos River near Aspermont, Tex., respectively. The amount of the total streamflow consisting of base flow was larger at sites in the Clear Fork Brazos River Basin compared to sites in the Salt Fork Brazos River Basin or Double Mountain Fork Brazos River Basin; at USGS streamflow-gaging stations 08084000 Clear Fork Brazos River at Nugent, Tex., and at 08085500 Clear Fork Brazos River at Fort Griffin, Tex., the median base-flow indexes were 0.28 and 0.23, respectively. The largest median base-flow index for any station was 0.35 at USGS streamflow-gaging station 08091500 Paluxy River at Glen Rose, Tex. The second largest base-flow index was 0.30 at USGS streamflow-gaging station 08095000 North Bosque River near Clifton, Tex. Median base-flow indexes on the main stem of the Brazos River upstream from Possum Kingdom Lake were 0.22 at USGS streamflow-gaging station 08082500 Brazos River at Seymour, Tex., and 0.24 at USGS streamflow-gaging station 08088000 Brazos River near South Bend, Tex. The base-flow indexes for stations between Possum Kingdom Lake and Lake Granbury were 0.19 and 0.27 at USGS streamflow-gaging stations 08089000 Brazos River near Palo Pinto, Tex., and 08090800 Brazos River near Dennis, Tex., respectively. A median base-flow index of 0.19 was also measured at USGS streamflow-gaging station 08091000 Brazos River near Glen Rose, Tex., located between Lake Granbury and Lake Whitney. A Mann-Kendall trend analysis test was performed on annual base-flow index values from each of the 11 streamflow records that were analyzed. Upward trends in base-flow index values indicating increasing flows during the study period were found for USGS streamflow-gaging stations 08080500 Double Mountain Fork Brazos River near Aspermont, Tex., 08089000 Brazos River near Palo Pinto, Tex., and 08090800 Brazos River near Dennis, Tex. Flows at these three streamflow-gaging stations are regulated by reservoir releases, and additional analyses are needed before these streamflow trends can be characterized as indicative of changes in base flow over time.
\nStreamflow was measured at 66 sites from June 6–9, 2010, and at 68 sites from October 16–19, 2010, to identify reaches in the upper Brazos River Basin that were gaining or losing streamflow. Gaining reaches were identified in each of the five subbasins. The gaining reach in the Salt Fork Brazos River Basin began at USGS streamflow-gaging station 08080940 Salt Fork Brazos River at State Highway 208 near Clairemont, Tex. (site SF–6), upstream from where Duck Creek flows into the Salt Fork Brazos River and continued downstream past USGS streamflow-gaging station 08082000 Salt Fork Brazos River near Aspermont, Tex. (site SF–9), to the outlet of the basin. In the Double Mountain Fork Brazos River Basin, a gaining reach from near Post, Tex., downstream to the outlet of the basin was identified. Two gaining reaches were identified in the Clear Fork Brazos River Basin—one from near Roby, Tex., downstream to near Noodle, Tex., and second from Hawley, Tex., downstream to Nugent, Tex. Most of the North Bosque River was characterized as gaining streamflow. Streamflow gains were identified in the main stem of the Brazos River from where the Brazos River main stem forms at the confluence of the Salt Fork Brazos River and Double Mountain Fork Brazos River near Knox City, Tex., downstream to near Seymour, Tex.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115224","collaboration":"Prepared in cooperation with the Texas Water Development Board","usgsCitation":"Baldys, S., and Schalla, F.E., 2012, Base flow (1966-2009) and streamflow gain and loss (2010) of the Brazos River from the New Mexico-Texas State line to Waco, Texas (Version 1.0: Originally posted January 23, 2012; Version 1.1: June 27, 2016): U.S. Geological Survey Scientific Investigations Report 2011-5224, viii, 53 p., https://doi.org/10.3133/sir20115224.","productDescription":"viii, 53 p.","numberOfPages":"65","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1965-10-01","temporalEnd":"2010-10-31","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":116374,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20115224.png"},{"id":115680,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5224/","linkFileType":{"id":5,"text":"html"}},{"id":325026,"rank":101,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5224/report/SIR2011-5224.pdf"},{"id":325027,"rank":102,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2011/5224/versionHist.txt"}],"country":"United States","state":"New Mexico, Texas","otherGeospatial":"Brazos River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -103.75,31.25 ], [ -103.75,34.666666666666664 ], [ -97.16666666666667,34.666666666666664 ], [ -97.16666666666667,31.25 ], [ -103.75,31.25 ] ] ] } } ] }","edition":"Version 1.0: Originally posted January 23, 2012; Version 1.1: June 27, 2016","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059efc7e4b0c8380cd4a450","contributors":{"authors":[{"text":"Baldys, Stanley sbaldys@usgs.gov","contributorId":3366,"corporation":false,"usgs":true,"family":"Baldys","given":"Stanley","email":"sbaldys@usgs.gov","affiliations":[],"preferred":true,"id":356028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schalla, Frank E.","contributorId":71449,"corporation":false,"usgs":true,"family":"Schalla","given":"Frank","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":356029,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70007140,"text":"fs20123006 - 2012 - Monitoring floods and fires during the summer of 2011--The value of the Landsat satellite 40-year archives","interactions":[],"lastModifiedDate":"2012-02-02T00:16:01","indexId":"fs20123006","displayToPublicDate":"2012-01-18T00:00:00","publicationYear":"2012","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":"2012-3006","title":"Monitoring floods and fires during the summer of 2011--The value of the Landsat satellite 40-year archives","docAbstract":"The summer of 2011 proved to be a season of extreme events. Heavy snowfall in the western mountains and excessive spring rains caused flooding along the Missouri and Mississippi Rivers; whereas extended dry conditions enabled fires to rage out of control from Alaska and Canada, south to Texas, Arizona, New Mexico, Georgia, and Mexico. The Landsat archive holds nearly 40 years of continuous global earth observation data. Landsat data are used by emergency responders to monitor change and damage caused by natural and man-made disasters. Decision makers rely on Landsat as they create plans for future environmental concerns.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123006","collaboration":"N","usgsCitation":"Owen, L., 2012, Monitoring floods and fires during the summer of 2011--The value of the Landsat satellite 40-year archives: U.S. Geological Survey Fact Sheet 2012-3006, 2 p., https://doi.org/10.3133/fs20123006.","productDescription":"2 p.","startPage":"1","endPage":"2","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":116443,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3006.jpg"},{"id":112504,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3006/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"North America","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5da7e4b0c8380cd704ec","contributors":{"authors":[{"text":"Owen, Linda 0000-0002-1734-5406 jonescheit@usgs.gov","orcid":"https://orcid.org/0000-0002-1734-5406","contributorId":478,"corporation":false,"usgs":true,"family":"Owen","given":"Linda","email":"jonescheit@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":355920,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}