In 2001, the National Water-Quality Assessment (NAWQA) Program of the U.S. Geological Survey initiated a series of studies on the transport of anthropogenic and natural contaminants (TANC) to public-supply wells (PSWs). The main goal of the TANC project was to better understand the source, transport, and receptor factors that control contaminant movement to PSWs in representative aquifers of the United States. Regional- and local-scale study areas were selected from within existing NAWQA study units, including the south-central Texas Edwards aquifer. The local-scale TANC study area, nested within the regional-scale NAWQA study area, is representative of the regional Edwards aquifer. The PSW selected for study is within a well field of six production wells. Although a single PSW was initially selected, because of constraints of well-field operation, samples were collected from different wells within the well field for different components of the study. Data collected from all of the well-field wells were considered comparable because of similar well construction, hydrogeology, and geochemistry. An additional 38 PSWs (mostly completed in the confined part of the aquifer) were sampled throughout the regional aquifer to characterize water quality. Two monitoring well clusters, with wells completed at different depths, were installed to the east and west of the well field (the Zarzamora and Timberhill monitoring well clusters, respectively). One of the monitoring wells was completed in the overburden to evaluate potential hydrologic connectivity with the Edwards aquifer. Geophysical and flowmeter logs were collected from one of the well-field PSWs to determine zones of contribution to the wellbore. These contributing zones, associated with different hydrogeologic units, were used to select monitoring well completion depths and groundwater sample collection depths for depth-dependent sampling. Depth-dependent samples were collected from the PSW from three different depths and under three different pumping conditions. Additionally, selected monitoring wells and one of the well-field PSWs were sampled several times in response to a rainfall and recharge event to assess short-term (event-scale) temporal variations in water quality. For comparison purposes, groundwater samples were categorized as being from regional aquifer PSWs, from the well field (wellhead samples), from the monitoring wells (excluding the overburden well), from the overburden well, from the PSW depth-dependent sampling, and from temporal sampling. Groundwater samples were analyzed for inorganic, organic, isotopic, and age-dating tracers to characterize geochemical conditions in the aquifer and provide understanding of the mechanisms of mobilization and movement of selected constituents from source areas to a PSW. Sources, tracers, and conditions used to assess water quality and processes affecting the PSW and the aquifer system included (1) carbonate host rock composition; (2) physicochemical constituents; (3) major and trace element concentrations; (4) saturation indices with respect to minerals in aquifer rocks; (5) elemental ratios, such as magnesium to calcium ratios, that are indicative of water-rock interaction processes; (6) oxidation-reduction conditions; (7) nutrient concentrations, in particular nitrate concentrations; (8) the isotopic composition of nitrate, which can point to specific nitrate sources; (9) strontium isotopes; (10) stable isotopes of hydrogen and oxygen; (11) organic contaminant concentrations, including pesticides and volatile organic compounds; (12) age tracers, apparent-age distribution, and dissolved gas data used in age interpretations; (13) depth-dependent water chemistry collected from the PSW under different pumping conditions to assess zones of contribution; and (14) temporal variability in groundwater composition from the PSW and selected monitoring wells in response to an aquifer recharge event. Geochemical results indicate that the well-field and monitoring well samples were largely representative of groundwater in the regional confined aquifer. Constituents of concern in the Edwards aquifer for the long-term sustainability of the groundwater resource include the nutrient nitrate and anthropogenic organic contaminants. Nitrate concentrations (as nitrogen) for regional aquifer PSWs had a median value of 1.9 milligrams per liter, which is similar to previously reported values for the regional aquifer. Nitrate-isotope compositions for groundwater samples collected from the well-field PSWs and monitoring wells had a narrow range, with values indicative of natural soil organic values. A comparison with historical nitrate-isotope values, however, suggests that a component of nitrate in groundwater from biogenic sources might have increased over the last 30 years. Several organic contaminants (the pesticide atrazine, its degradate deethylatrazine, trichloromethane (chloroform; a drinking-water disinfection byproduct), and the solvent tetrachloroethene (PCE)) were widely distributed throughout the regional aquifer and in the local-scale TANC study area at low concentrations (less than 1 microgram per liter). Higher concentrations of PCE were detected in samples from the well-field PSWs and Zarzamora monitoring wells relative to the regional aquifer PSWs. The urban environment is a likely source of contaminants to the aquifer, and these results indicate that one or more local urban sources might be supplying PCE to the Zarzamora monitoring wells and the well-field wells. Samples from the well field also had high concentrations of chloroform relative to the monitoring wells and regional aquifer PSWs. For samples from the regional aquifer PSWs, the most frequently detected organic contaminants generally decreased in concentration with increasing well depth. Deeper wells might intercept longer regional flow paths with higher fractions of older water or water recharged in rural recharge areas in the western part of the aquifer that have been less affected by anthropogenic contaminants. A scenario of hypothetical contaminant loading was evaluated by using results from groundwater-flow-model particle tracking to assess the response of the aquifer to potential contamination. Results indicate that the aquifer responds quickly (less than 1 year to several years) to contaminant loading; however, it takes a relatively long time (decades) for concentrations to reach peak values. The aquifer also responds quickly (less than 1 year to several years) to the removal of contaminant loading; however, it also takes a relatively long time (decades) to reach near background concentrations. Interpretation of geochemical age tracers in this well-mixed karst system was complicated by contamination of a majority of measured tracers and complexities of extensive mixing. Age-tracer results generally indicated that groundwater samples were composed of young, recently recharged water with piston-flow model ages ranging from less than 1 to 41 years, with a median of 17 years. Although a piston-flow model is typically not valid for karst aquifers, the model ages provide a basis for comparing relative ages of different samples and a reference point for more complex hydrogeologic models for apparent-age interpretations. Young groundwater ages are consistent with particle-tracking results from hydrogeologic modeling for the local-scale TANC study area. Age-tracer results compared poorly with other geochemical indicators of groundwater residence time and anthropogenic effects on water quality, indicating that hydrogeologic conceptual models used in groundwater age interpretations might not adequately account for mixing in this karst system. Groundwater samples collected from the well field under a variety of pumping conditions were relatively homogeneous and well mixed for numerous geochemical constituents (with the notable exception of age tracers). Groundwater contributions to the PSW were dominated by well-mixed, relatively homogeneous groundwater, typical of the regional confined aquifer. Zones of preferential flow were determined for the PSW, but groundwater samples from different stratigraphic units were not geochemically distinct. Variations in chemical constituents in response to a rainfall and aquifer recharge event occurred but were relatively minor in the PSW and monitoring wells. This observation is consistent with the hypothesis that the response to individual recharge events in the confined aquifer, unless intersecting conduit flow paths, might be attenuated by mixing processes along regional flow paths. Results of this study are consistent with the existing conceptual understanding of aquifer processes in this karst system and are useful for water-resource development and management practices.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115146","collaboration":"U.S. Geological Survey National Water-Quality Assessment Program","usgsCitation":"Musgrove, M., Fahlquist, L., Stanton, G.P., Houston, N.A., and Lindgren, R.J., 2011, Hydrogeology, chemical characteristics, and water sources and pathways in the zone of contribution of a public-supply well in San Antonio, Texas: U.S. Geological Survey Scientific Investigations Report 2011-5146, xii, 90 p.; Tables, https://doi.org/10.3133/sir20115146.","productDescription":"xii, 90 p.; Tables","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":116557,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5146.png"},{"id":101793,"rank":700,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5146/"}],"country":"United States","state":"Texas","city":"San Antonio","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -101,28.75 ], [ -101,30.75 ], [ -97.25,30.75 ], [ -97.25,28.75 ], [ -101,28.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a2de4b07f02db61492f","contributors":{"authors":[{"text":"Musgrove, MaryLynn","contributorId":34878,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","affiliations":[],"preferred":false,"id":353502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fahlquist, Lynne","contributorId":8810,"corporation":false,"usgs":true,"family":"Fahlquist","given":"Lynne","affiliations":[],"preferred":false,"id":353501,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stanton, Gregory P. 0000-0001-8622-0933 gstanton@usgs.gov","orcid":"https://orcid.org/0000-0001-8622-0933","contributorId":1583,"corporation":false,"usgs":true,"family":"Stanton","given":"Gregory","email":"gstanton@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":353498,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Houston, Natalie A. 0000-0002-6071-4545 nhouston@usgs.gov","orcid":"https://orcid.org/0000-0002-6071-4545","contributorId":1682,"corporation":false,"usgs":true,"family":"Houston","given":"Natalie","email":"nhouston@usgs.gov","middleInitial":"A.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353500,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindgren, Richard J. lindgren@usgs.gov","contributorId":1667,"corporation":false,"usgs":true,"family":"Lindgren","given":"Richard","email":"lindgren@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":353499,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70005002,"text":"70005002 - 2011 - Quantifying differences in the impact of variable chemistry on equilibrium uranium(VI) adsorption properties of aquifer sediments","interactions":[],"lastModifiedDate":"2020-01-11T10:58:03","indexId":"70005002","displayToPublicDate":"2011-11-09T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying differences in the impact of variable chemistry on equilibrium uranium(VI) adsorption properties of aquifer sediments","docAbstract":"Uranium adsorption-desorption on sediment samples collected from the Hanford 300-Area, Richland, WA varied extensively over a range of field-relevant chemical conditions, complicating assessment of possible differences in equilibrium adsorption properties. Adsorption equilibrium was achieved in 500-1000 h although dissolved uranium concentrations increased over thousands of hours owing to changes in aqueous chemical composition driven by sediment-water reactions. A nonelectrostatic surface complexation reaction, >SOH + UO22+ + 2CO32- = >SOUO2(CO3HCO3)2-, provided the best fit to experimental data for each sediment sample resulting in a range of conditional equilibrium constants (logKc) from 21.49 to 21.76. Potential differences in uranium adsorption properties could be assessed in plots based on the generalized mass-action expressions yielding linear trends displaced vertically by differences in logKc values. Using this approach, logKc values for seven sediment samples were not significantly different. However, a significant difference in adsorption properties between one sediment sample and the fines (<0.063 mm) of another could be demonstrated despite the fines requiring a different reaction stoichiometry. Estimates of logKc uncertainty were improved by capturing all data points within experimental errors. The mass-action expression plots demonstrate that applying models outside the range of conditions used in model calibration greatly increases potential errors.","language":"English","publisher":"ACS Publications","doi":"10.1021/es202677v","usgsCitation":"Stoliker, D., Kent, D.B., and Zachara, J.M., 2011, Quantifying differences in the impact of variable chemistry on equilibrium uranium(VI) adsorption properties of aquifer sediments: Environmental Science & Technology, v. 45, no. 20, p. 8733-8740, https://doi.org/10.1021/es202677v.","productDescription":"8 p.","startPage":"8733","endPage":"8740","costCenters":[{"id":148,"text":"Branch of Regional Research-Western Region","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":474902,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/es202677v","text":"Publisher Index 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Chemical Society (ACS)","authors":"Stoliker Deborah L., Kent Douglas B., Zachara John M.","journalName":"Environmental Science & Technology","publicationDate":"10/15/2011","auditedOn":"3/4/2016","publiclyAccessibleDate":"9/16/2011"},"contributors":{"authors":[{"text":"Stoliker, Deborah L. dlstoliker@usgs.gov","contributorId":2954,"corporation":false,"usgs":true,"family":"Stoliker","given":"Deborah L.","email":"dlstoliker@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":351810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kent, Douglas B. 0000-0003-3758-8322 dbkent@usgs.gov","orcid":"https://orcid.org/0000-0003-3758-8322","contributorId":1871,"corporation":false,"usgs":true,"family":"Kent","given":"Douglas","email":"dbkent@usgs.gov","middleInitial":"B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":351809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zachara, John M.","contributorId":7421,"corporation":false,"usgs":true,"family":"Zachara","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":351811,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70005803,"text":"70005803 - 2011 - Constraints on the long‐period moment‐dip tradeoff for the Tohoku earthquake","interactions":[],"lastModifiedDate":"2021-02-25T21:28:35.322581","indexId":"70005803","displayToPublicDate":"2011-11-09T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Constraints on the long‐period moment‐dip tradeoff for the Tohoku earthquake","docAbstract":"Since the work of Kanamori and Given (1981), it has been recognized that shallow, pure dip‐slip earthquakes excite long‐period surface waves such that it is difficult to independently constrain the moment (M0) and the dip (δ) of the source mechanism, with only the product M0 sin(2δ) being well constrained. Because of this, it is often assumed that the primary discrepancies between the moments of shallow, thrust earthquakes are due to this moment‐dip tradeoff. In this work, we quantify how severe this moment‐dip tradeoff is depending on the depth of the earthquake, the station distribution, the closeness of the mechanism to pure dip‐slip, and the quality of the data. We find that both long‐period Rayleigh and Love wave modes have moment‐dip resolving power even for shallow events, especially when stations are close to certain azimuths with respect to mechanism strike and when source depth is well determined. We apply these results to USGS W phase inversions of the recent M9.0 Tohoku, Japan earthquake and estimate the likely uncertainties in dip and moment associated with the moment‐ dip tradeoff. After discussing some of the important sources of moment and dip error, we suggest two methods for potentially improving this uncertainty.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1029/2011GL049129","usgsCitation":"Tsai, V., Hayes, G., and Duputel, Z., 2011, Constraints on the long‐period moment‐dip tradeoff for the Tohoku earthquake: Geophysical Research Letters, v. 38, no. 7, L00G17, 6 p., https://doi.org/10.1029/2011GL049129.","productDescription":"L00G17, 6 p.","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":474898,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011gl049129","text":"Publisher Index Page"},{"id":204442,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan","state":"Tohoku","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 139.295654296875,\n 36.83566824724438\n ],\n [\n 142.108154296875,\n 36.83566824724438\n ],\n [\n 142.108154296875,\n 41.590796851056005\n ],\n [\n 139.295654296875,\n 41.590796851056005\n ],\n [\n 139.295654296875,\n 36.83566824724438\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","issue":"7","noUsgsAuthors":false,"publicationDate":"2011-10-25","publicationStatus":"PW","scienceBaseUri":"4f4e4afde4b07f02db697068","contributors":{"authors":[{"text":"Tsai, Victor C. 0000-0003-1809-6672","orcid":"https://orcid.org/0000-0003-1809-6672","contributorId":87675,"corporation":false,"usgs":true,"family":"Tsai","given":"Victor C.","affiliations":[],"preferred":false,"id":353268,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayes, Gavin P. 0000-0003-3323-0112","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":6157,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":353266,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duputel, Zacharie","contributorId":20462,"corporation":false,"usgs":true,"family":"Duputel","given":"Zacharie","email":"","affiliations":[],"preferred":false,"id":353267,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70003910,"text":"70003910 - 2011 - Quantifying the fire regime distributions for severity in Yosemite National Park, California, USA","interactions":[],"lastModifiedDate":"2021-04-28T16:06:16.44102","indexId":"70003910","displayToPublicDate":"2011-11-09T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the fire regime distributions for severity in Yosemite National Park, California, USA","docAbstract":"This paper quantifies current fire severity distributions for 19 different fire-regime types in Yosemite National Park, California, USA. Landsat Thematic Mapper remote sensing data are used to map burn severity for 99 fires (cumulatively over 97 000 ha) that burned in Yosemite over a 20-year period. These maps are used to quantify the frequency distributions of fire severity by fire-regime type. A classification is created for the resultant distributions and they are discussed within the context of four vegetation zones: the foothill shrub and woodland zone; the lower montane forest zone; the upper montane forest zone and the subalpine forest zone. The severity distributions can form a building block from which to discuss current fire regimes across the Sierra Nevada in California. This work establishes a framework for comparing the effects of current fires on our landscapes with our notions of how fires historically burned, and how current fire severity distributions differ from our desired future conditions. As this process is refined, a new set of information will be available to researchers and land managers to help understand how fire regimes have changed from the past and how we might attempt to manage them in the future.
","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WF09060","usgsCitation":"Thode, A., van Wagtendonk, J., Miller, D.J., and Quinn, J.F., 2011, Quantifying the fire regime distributions for severity in Yosemite National Park, California, USA: International Journal of Wildland Fire, v. 20, no. 2, p. 223-239, https://doi.org/10.1071/WF09060.","productDescription":"17 p.","startPage":"223","endPage":"239","numberOfPages":"17","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":204490,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.06134033203125,\n 37.477037796698056\n ],\n [\n -119.11102294921875,\n 37.477037796698056\n ],\n [\n -119.11102294921875,\n 38.156156969924915\n ],\n [\n -120.06134033203125,\n 38.156156969924915\n ],\n [\n -120.06134033203125,\n 37.477037796698056\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4adce4b07f02db6862f8","contributors":{"authors":[{"text":"Thode, Andrea E.","contributorId":31896,"corporation":false,"usgs":false,"family":"Thode","given":"Andrea E.","affiliations":[],"preferred":false,"id":349427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Wagtendonk, Jan W. 0000-0002-0788-2654","orcid":"https://orcid.org/0000-0002-0788-2654","contributorId":98269,"corporation":false,"usgs":true,"family":"van Wagtendonk","given":"Jan W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":349429,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, D. Jay","contributorId":67644,"corporation":false,"usgs":false,"family":"Miller","given":"D.","email":"","middleInitial":"Jay","affiliations":[],"preferred":false,"id":349428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quinn, James F.","contributorId":101379,"corporation":false,"usgs":false,"family":"Quinn","given":"James","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":349430,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70005917,"text":"sir20115163 - 2011 - New U.S. Geological Survey method for the assessment of reserve growth","interactions":[],"lastModifiedDate":"2018-07-31T10:21:05","indexId":"sir20115163","displayToPublicDate":"2011-11-08T00:00:00","publicationYear":"2011","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":"2011-5163","title":"New U.S. Geological Survey method for the assessment of reserve growth","docAbstract":"Reserve growth is defined as the estimated increases in quantities of crude oil, natural gas, and natural gas liquids that have the potential to be added to remaining reserves in discovered accumulations through extension, revision, improved recovery efficiency, and additions of new pools or reservoirs. A new U.S. Geological Survey method was developed to assess the reserve-growth potential of technically recoverable crude oil and natural gas to be added to reserves under proven technology currently in practice within the trend or play, or which reasonably can be extrapolated from geologically similar trends or plays. This method currently is in use to assess potential additions to reserves in discovered fields of the United States. The new approach involves (1) individual analysis of selected large accumulations that contribute most to reserve growth, and (2) conventional statistical modeling of reserve growth in remaining accumulations. This report will focus on the individual accumulation analysis.\r\nIn the past, the U.S. Geological Survey estimated reserve growth by statistical methods using historical recoverable-quantity data. Those statistical methods were based on growth rates averaged by the number of years since accumulation discovery. Accumulations in mature petroleum provinces with volumetrically significant reserve growth, however, bias statistical models of the data; therefore, accumulations with significant reserve growth are best analyzed separately from those with less significant reserve growth. Large (greater than 500 million barrels) and older (with respect to year of discovery) oil accumulations increase in size at greater rates late in their development history in contrast to more recently discovered accumulations that achieve most growth early in their development history. Such differences greatly affect the statistical methods commonly used to forecast reserve growth.\r\nThe individual accumulation-analysis method involves estimating the in-place petroleum quantity and its uncertainty, as well as the estimated (forecasted) recoverability and its respective uncertainty. These variables are assigned probabilistic distributions and are combined statistically to provide probabilistic estimates of ultimate recoverable quantities. Cumulative production and remaining reserves are then subtracted from the estimated ultimate recoverable quantities to provide potential reserve growth. In practice, results of the two methods are aggregated to various scales, the highest of which includes an entire country or the world total. The aggregated results are reported along with the statistically appropriate uncertainties.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115163","usgsCitation":"Klett, T., Attanasi, E.D., Charpentier, R., Cook, T.A., Freeman, P., Gautier, D.L., Le, P., Ryder, R., Schenk, C.J., Tennyson, M., and Verma, M., 2011, New U.S. Geological Survey method for the assessment of reserve growth: U.S. Geological Survey Scientific Investigations Report 2011-5163, iv, 8 p., https://doi.org/10.3133/sir20115163.","productDescription":"iv, 8 p.","onlineOnly":"Y","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":116490,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5163.png"},{"id":101699,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5163/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afee4b07f02db6975a8","contributors":{"authors":[{"text":"Klett, Timothy R. 0000-0001-9779-1168 tklett@usgs.gov","orcid":"https://orcid.org/0000-0001-9779-1168","contributorId":709,"corporation":false,"usgs":true,"family":"Klett","given":"Timothy R.","email":"tklett@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":353453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Attanasi, Emil D. 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":193092,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil","email":"attanasi@usgs.gov","middleInitial":"D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":353459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Charpentier, Ronald R. charpentier@usgs.gov","contributorId":934,"corporation":false,"usgs":true,"family":"Charpentier","given":"Ronald R.","email":"charpentier@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":353455,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cook, Troy A.","contributorId":52519,"corporation":false,"usgs":true,"family":"Cook","given":"Troy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":353462,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Freeman, Philip A. 0000-0002-0863-7431 pfreeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":193093,"corporation":false,"usgs":true,"family":"Freeman","given":"Philip A.","email":"pfreeman@usgs.gov","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":353461,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gautier, Donald L. gautier@usgs.gov","contributorId":1310,"corporation":false,"usgs":true,"family":"Gautier","given":"Donald","email":"gautier@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":353457,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Le, Phuong A. 0000-0003-2477-509X ple@usgs.gov","orcid":"https://orcid.org/0000-0003-2477-509X","contributorId":2151,"corporation":false,"usgs":true,"family":"Le","given":"Phuong A.","email":"ple@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":353460,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ryder, Robert T.","contributorId":77918,"corporation":false,"usgs":true,"family":"Ryder","given":"Robert T.","affiliations":[],"preferred":false,"id":353463,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schenk, Christopher J. 0000-0002-0248-7305 schenk@usgs.gov","orcid":"https://orcid.org/0000-0002-0248-7305","contributorId":826,"corporation":false,"usgs":true,"family":"Schenk","given":"Christopher","email":"schenk@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":353454,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Tennyson, Marilyn E. 0000-0002-5166-2421 tennyson@usgs.gov","orcid":"https://orcid.org/0000-0002-5166-2421","contributorId":1433,"corporation":false,"usgs":true,"family":"Tennyson","given":"Marilyn E.","email":"tennyson@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":353458,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Verma, Mahendra K. mverma@usgs.gov","contributorId":1027,"corporation":false,"usgs":true,"family":"Verma","given":"Mahendra K.","email":"mverma@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":353456,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70005918,"text":"ofr20111208 - 2011 - Monitoring coastal inundation with Synthetic Aperture Radar satellite data","interactions":[],"lastModifiedDate":"2012-02-02T00:15:56","indexId":"ofr20111208","displayToPublicDate":"2011-11-08T00:00:00","publicationYear":"2011","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":"2011-1208","title":"Monitoring coastal inundation with Synthetic Aperture Radar satellite data","docAbstract":"Maps representing the presence and absence of surface inundation in the Louisiana coastal zone were created from available satellite scenes acquired by the Japanese Aerospace Exploration Agency's Advanced Land Observing Satellite and by the European Space Agency's Envisat from late 2006 through summer 2009. Detection of aboveground surface flooding relied on the well-documented and distinct signature of decreased backscatter in Synthetic Aperture Radar (SAR), which is indicative of inundated marsh in the Gulf of Mexico. Even though decreases in backscatter were distinctive, the multiplicity of possible interactions between changing flood depths and canopy height yielded complex SAR-based representations of the marshes.\nValidated by comparison to inland water levels, success of inundation mapping was primarily related to the operational frequencies of the SAR used to perform the mapping. Success of mapping was based on frequency of correspondence between satellite- and ground-based data. Overall, the most successful mapping (83 percent correspondence) was derived from Phased Array type L-band SAR (PALSAR), while mapping derived from C-band Advanced SAR (ASAR) was less successful (≤61 percent correspondence). Exceptions to the low performance of ASAR-based mapping (defined as >76 percent correspondence) occurred when water levels were well below or above ground, occurring over spatially extensive portions of the ASAR scene.\nWhen mapping day-to-day coastal inundation extents, results indicate that SAR systems operating at C-band frequencies are not as effective as those operating at L-band frequencies; however, multiple factors not related to frequency also reduced the effectiveness of C-Band in detecting subcanopy inundation. C-band has performed and continues to perform exceedingly well in applications for response to dramatic events and when strategic collections are available; however, L-band seems to be more suitable for day-to-day mapping of coastal inundation.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111208","collaboration":"Prepared in cooperation with the National Aeronautics and Space Administration","usgsCitation":"Suzuoki, Y., Rangoonwala, A., and Ramsey, E., 2011, Monitoring coastal inundation with Synthetic Aperture Radar satellite data: U.S. Geological Survey Open-File Report 2011-1208, vi, 45 p., https://doi.org/10.3133/ofr20111208.","productDescription":"vi, 45 p.","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":116489,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1208.gif"},{"id":101700,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1208/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a4de4b07f02db6273e2","contributors":{"authors":[{"text":"Suzuoki, Yukihiro","contributorId":25283,"corporation":false,"usgs":true,"family":"Suzuoki","given":"Yukihiro","email":"","affiliations":[],"preferred":false,"id":353465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rangoonwala, Amina 0000-0002-0556-0598 rangoonwalaa@usgs.gov","orcid":"https://orcid.org/0000-0002-0556-0598","contributorId":3455,"corporation":false,"usgs":true,"family":"Rangoonwala","given":"Amina","email":"rangoonwalaa@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":353464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramsey, Elijah W. III 0000-0002-4518-5796","orcid":"https://orcid.org/0000-0002-4518-5796","contributorId":72769,"corporation":false,"usgs":true,"family":"Ramsey","given":"Elijah W.","suffix":"III","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":353466,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70005886,"text":"ofr20111267 - 2011 - Assessment of Hyporheic Zone, Flood-Plain, Soil-Gas, Soil, and Surface-Water Contamination at the McCoys Creek Chemical Training Area, Fort Gordon, Georgia, 2009-2010","interactions":[],"lastModifiedDate":"2016-12-08T14:53:31","indexId":"ofr20111267","displayToPublicDate":"2011-11-07T00:00:00","publicationYear":"2011","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":"2011-1267","title":"Assessment of Hyporheic Zone, Flood-Plain, Soil-Gas, Soil, and Surface-Water Contamination at the McCoys Creek Chemical Training Area, Fort Gordon, Georgia, 2009-2010","docAbstract":"The U.S. Geological Survey, in cooperation with the U.S. Department of the Army Environmental and Natural Resources Management Office of the U.S. Army Signal Center and Fort Gordon, Georgia, assessed the hyporheic zone, flood plain, soil gas, soil, and surface water for contaminants at the McCoys Creek Chemical Training Area (MCTA) at Fort Gordon, from October 2009 to September 2010. The assessment included the detection of organic contaminants in the hyporheic zone, flood plain, soil gas, and surface water. In addition, the organic contaminant assessment included the analysis of organic compounds classified as explosives and chemical agents in selected areas. Inorganic contaminants were assessed in soil and surface-water samples. The assessment was conducted to provide environmental contamination data to the U.S. Army at Fort Gordon pursuant to requirements of the Resource Conservation and Recovery Act Part B Hazardous Waste Permit process. Ten passive samplers were deployed in the hyporheic zone and flood plain, and total petroleum hydrocarbons (TPH) and octane were detected above the method detection level in every sampler. Other organic compounds detected above the method detection level in the hyporheic zone and flood-plain samplers were trichloroethylene, and cis- and trans- 1, 2-dichloroethylene. One trip blank detected TPH below the method detection level but above the nondetection level. The concentrations of TPH in the samplers were many times greater than the concentrations detected in the blank; therefore, all other TPH concentrations detected are considered to represent environmental conditions. Seventy-one soil-gas samplers were deployed in a grid pattern across the MCTA. Three trip blanks and three method blanks were used and not deployed, and TPH was detected above the method detection level in two trip blanks and one method blank. Detection of TPH was observed at all 71 samplers, but because TPH was detected in the trip and method blanks, TPH was censored and, therefore, only 7 of the 71 samplers were reported as detecting TPH. In addition, benzene, toluene, ethylbenzene, and total xylene were detected above the method detection level in 22 samplers. Other compounds detected above the method detection level included naphthalene, octane, undecane, tridecane, 1,2,4-trimethylbenzene, trichloroethylene, perchloroethylene, chloroform, and 1,4-dichlorobenzene. Subsequent to the soil-gas survey, five locations with elevated contaminant mass were selected and a passive sampler was deployed at those locations to detect the presence of organic compounds classified as explosives or chemical agents. No explosives or chemical agents were detected above the method detection level, but some compounds were detected below the method detection level but above the nondetection level. Dimethyl disulfide, benzothiazole, chloroacetophenones, and para-chlorophenyl methyl sulfide were all detected below the method detection level but above the nondetection level. The compounds 2,4-dinitrotoluene, and para-chlorophenyl methyl sulfone were detected in samplers but also were detected in trip blanks and are not considered as present in the MCTA. The same five locations that were selected for sampling of explosives and chemical agents were selected for soil sampling. Metal concentrations in composite soil samples collected at five locations from land surface to a depth of 6 inches did not exceed the U.S. Environmental Protection Agency Regional Screening Levels for Industrial Soil. Concentrations in some compounds were higher than the South Carolina Department of Health and Environmental Control background levels for nearby South Carolina, including aluminum, arsenic, barium, beryllium, chromium, copper, iron, lead, manganese, nickel, and potassium. A surface-water sample was collected from McCoys Creek and analyzed for volatile organic compounds, semivolatile organic compounds, and inorganic compounds (metals). No volatile organic compounds and (or) semivolatile organic compounds were detected at levels above the maximum contaminant level of the U.S. Environmental Protection Agency (USEPA) National Primary Drinking Water Standard, and no inorganic compounds exceeded the maximum contaminant level of the USEPA National Primary Drinking Water Standard or the Georgia In-Stream Water-Quality Standard. Iron was the only inorganic compound detected in the surface-water sample (578 micrograms per liter) that exceeded the USEPA National Secondary Drinking Water Standard of 300 micrograms per liter.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111267","collaboration":"Prepared in cooperation with the U.S. Department of the Army Environmental and Natural Resources Management Office of the U.S. Army Signal Center and Fort Gordon","usgsCitation":"Guimaraes, W.B., Falls, W.F., Caldwell, A.W., Ratliff, W.H., Wellborn, J.B., and Landmeyer, J., 2011, Assessment of Hyporheic Zone, Flood-Plain, Soil-Gas, Soil, and Surface-Water Contamination at the McCoys Creek Chemical Training Area, Fort Gordon, Georgia, 2009-2010: U.S. Geological Survey Open-File Report 2011-1267, v, 14 p.; Tables, https://doi.org/10.3133/ofr20111267.","productDescription":"v, 14 p.; Tables","temporalStart":"2009-10-01","temporalEnd":"2010-09-30","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":116534,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1267.jpg"},{"id":94687,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1267/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Georgia","city":"Augusta","otherGeospatial":"Coastal Plain Physiographic Province, Fort Gordon, Mccoys Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.42355346679688,\n 33.247301699949205\n ],\n [\n -82.42355346679688,\n 33.54940663754663\n ],\n [\n -82.01774597167969,\n 33.54940663754663\n ],\n [\n -82.01774597167969,\n 33.247301699949205\n ],\n [\n -82.42355346679688,\n 33.247301699949205\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4abbe4b07f02db672931","contributors":{"authors":[{"text":"Guimaraes, Wladmir B. wbguimar@usgs.gov","contributorId":3818,"corporation":false,"usgs":true,"family":"Guimaraes","given":"Wladmir","email":"wbguimar@usgs.gov","middleInitial":"B.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353439,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falls, W. Fred 0000-0003-2928-9795 wffalls@usgs.gov","orcid":"https://orcid.org/0000-0003-2928-9795","contributorId":107754,"corporation":false,"usgs":true,"family":"Falls","given":"W.","email":"wffalls@usgs.gov","middleInitial":"Fred","affiliations":[],"preferred":false,"id":353442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell, Andral W. 0000-0003-1269-5463 acaldwel@usgs.gov","orcid":"https://orcid.org/0000-0003-1269-5463","contributorId":3228,"corporation":false,"usgs":true,"family":"Caldwell","given":"Andral","email":"acaldwel@usgs.gov","middleInitial":"W.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ratliff, W. Hagan","contributorId":60347,"corporation":false,"usgs":true,"family":"Ratliff","given":"W.","email":"","middleInitial":"Hagan","affiliations":[],"preferred":false,"id":353441,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wellborn, John B.","contributorId":24822,"corporation":false,"usgs":true,"family":"Wellborn","given":"John","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":353440,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Landmeyer, James 0000-0002-5640-3816 jlandmey@usgs.gov","orcid":"https://orcid.org/0000-0002-5640-3816","contributorId":3257,"corporation":false,"usgs":true,"family":"Landmeyer","given":"James","email":"jlandmey@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353438,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70005899,"text":"fs20113087 - 2011 - Water resources of Bossier Parish","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"fs20113087","displayToPublicDate":"2011-11-07T00:00:00","publicationYear":"2011","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":"2011-3087","title":"Water resources of Bossier Parish","docAbstract":"In 2005, about 15.8 million gallons per day (Mgal/d) of water were withdrawn in Bossier Parish, Louisiana, including 4.12 Mgal/d from groundwater sources and about 11.7 Mgal/d from surface-water sources. Public-supply use accounted for about 78 percent (12.4 Mgal/d) of the total water withdrawn. Other categories of use included industry, rural domestic, livestock, rice irrigation, general irrigation, and aquaculture. Based on water-use data collected at 5-year intervals from 1960 to 2005, water withdrawals in the parish increased from 4.96 to 15.8 Mgal/d. This fact sheet summarizes basic information on the water resources of Bossier Parish, La. Information on groundwater and surface-water availability, quality, development, use, and trends is based on previously published reports listed in the Selected References section.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20113087","collaboration":"In cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Prakken, L., and Griffith, J.M., 2011, Water resources of Bossier Parish: U.S. Geological Survey Fact Sheet 2011-3087, 6 p., https://doi.org/10.3133/fs20113087.","productDescription":"6 p.","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":116536,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2011_3087.gif"},{"id":94689,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2011/3087/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Bossier Parish;Red River Alluvial Aquifer;Upland Terrace Aquifer;Sparta Aquifer;Carrizo-wilcox Aquifer;Red River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94,32 ], [ -94,33 ], [ -93.33333333333333,33 ], [ -93.33333333333333,32 ], [ -94,32 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a0ce4b07f02db5fc981","contributors":{"authors":[{"text":"Prakken, Lawrence B.","contributorId":73978,"corporation":false,"usgs":true,"family":"Prakken","given":"Lawrence B.","affiliations":[],"preferred":false,"id":353449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffith, Jason M. 0000-0002-8942-0380 jmgriff@usgs.gov","orcid":"https://orcid.org/0000-0002-8942-0380","contributorId":2923,"corporation":false,"usgs":true,"family":"Griffith","given":"Jason","email":"jmgriff@usgs.gov","middleInitial":"M.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353448,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70005898,"text":"fs20113088 - 2011 - Water resources of Webster Parish","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"fs20113088","displayToPublicDate":"2011-11-07T00:00:00","publicationYear":"2011","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":"2011-3088","title":"Water resources of Webster Parish","docAbstract":"In 2005, about 9.52 million gallons per day (Mgal/d) of water were withdrawn in Webster Parish, Louisiana (fig. 1), including about 9.33 Mgal/d from groundwater sources and 0.19 Mgal/d from surface-water sources1 (table 1). Publicsupply use accounted for about 70 percent of the total water withdrawn. Other categories of use included industrial, rural domestic, livestock, general irrigation, and aquaculture (table 2). Water-use data collected at 5-year intervals from 1960 to 2005 indicate water withdrawals in Webster Parish decreased substantially from 1970 to 1980; surface-water withdrawals for industrial use decreased from about 37 to 0 Mgal/d because of a paper mill closure in 1979. From 1980 to 2000, total water withdrawals in the parish ranged from 7 to 8 Mgal/d (fig. 2). This fact sheet summarizes basic information on the water resources of Webster Parish, La. Information on groundwater and surface-water availability, quality, development, use, and trends is based on previously published reports listed in the Selected References section.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20113088","collaboration":"In cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Prakken, L., and Griffith, J.M., 2011, Water resources of Webster Parish: U.S. Geological Survey Fact Sheet 2011-3088, 6 p., https://doi.org/10.3133/fs20113088.","productDescription":"6 p.","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":116535,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2011_3088.gif"},{"id":94688,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2011/3088/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Webster Parish;Upland Terrace Aquifer;Sparta Aquifer;Carrizo-wilcox Aquifer","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -93.58333333333333,32.25 ], [ -93.58333333333333,33 ], [ -93.16666666666667,33 ], [ -93.16666666666667,32.25 ], [ -93.58333333333333,32.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49f4e4b07f02db5f06ec","contributors":{"authors":[{"text":"Prakken, Lawrence B.","contributorId":73978,"corporation":false,"usgs":true,"family":"Prakken","given":"Lawrence B.","affiliations":[],"preferred":false,"id":353447,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffith, Jason M. 0000-0002-8942-0380 jmgriff@usgs.gov","orcid":"https://orcid.org/0000-0002-8942-0380","contributorId":2923,"corporation":false,"usgs":true,"family":"Griffith","given":"Jason","email":"jmgriff@usgs.gov","middleInitial":"M.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353446,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70003702,"text":"70003702 - 2011 - Prediction and assimilation of surf-zone processes using a Bayesian network: Part I: Forward models","interactions":[],"lastModifiedDate":"2021-01-07T20:07:40.784844","indexId":"70003702","displayToPublicDate":"2011-11-04T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Prediction and assimilation of surf-zone processes using a Bayesian network: Part I: Forward models","docAbstract":"Prediction of coastal processes, including waves, currents, and sediment transport, can be obtained from a variety of detailed geophysical-process models with many simulations showing significant skill. This capability supports a wide range of research and applied efforts that can benefit from accurate numerical predictions. However, the predictions are only as accurate as the data used to drive the models and, given the large temporal and spatial variability of the surf zone, inaccuracies in data are unavoidable such that useful predictions require corresponding estimates of uncertainty. We demonstrate how a Bayesian-network model can be used to provide accurate predictions of wave-height evolution in the surf zone given very sparse and/or inaccurate boundary-condition data. The approach is based on a formal treatment of a data-assimilation problem that takes advantage of significant reduction of the dimensionality of the model system. We demonstrate that predictions of a detailed geophysical model of the wave evolution are reproduced accurately using a Bayesian approach. In this surf-zone application, forward prediction skill was 83%, and uncertainties in the model inputs were accurately transferred to uncertainty in output variables. We also demonstrate that if modeling uncertainties were not conveyed to the Bayesian network (i.e., perfect data or model were assumed), then overly optimistic prediction uncertainties were computed. More consistent predictions and uncertainties were obtained by including model-parameter errors as a source of input uncertainty. Improved predictions (skill of 90%) were achieved because the Bayesian network simultaneously estimated optimal parameters while predicting wave heights.","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.coastaleng.2010.09.003","usgsCitation":"Plant, N.G., and Holland, K.T., 2011, Prediction and assimilation of surf-zone processes using a Bayesian network: Part I: Forward models: Coastal Engineering, v. 58, no. 1, p. 119-130, https://doi.org/10.1016/j.coastaleng.2010.09.003.","productDescription":"12 p.","startPage":"119","endPage":"130","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":204217,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67e7e4","contributors":{"authors":[{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":348413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holland, K. Todd","contributorId":68748,"corporation":false,"usgs":true,"family":"Holland","given":"K.","email":"","middleInitial":"Todd","affiliations":[],"preferred":false,"id":348414,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70003802,"text":"70003802 - 2011 - Prediction and assimilation of surf-zone processes using a Bayesian network: Part II: Inverse models","interactions":[],"lastModifiedDate":"2021-01-07T20:06:01.681955","indexId":"70003802","displayToPublicDate":"2011-11-04T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Prediction and assimilation of surf-zone processes using a Bayesian network: Part II: Inverse models","docAbstract":"A Bayesian network model has been developed to simulate a relatively simple problem of wave propagation in the surf zone (detailed in Part I). Here, we demonstrate that this Bayesian model can provide both inverse modeling and data-assimilation solutions for predicting offshore wave heights and depth estimates given limited wave-height and depth information from an onshore location. The inverse method is extended to allow data assimilation using observational inputs that are not compatible with deterministic solutions of the problem. These inputs include sand bar positions (instead of bathymetry) and estimates of the intensity of wave breaking (instead of wave-height observations). Our results indicate that wave breaking information is essential to reduce prediction errors. In many practical situations, this information could be provided from a shore-based observer or from remote-sensing systems. We show that various combinations of the assimilated inputs significantly reduce the uncertainty in the estimates of water depths and wave heights in the model domain. Application of the Bayesian network model to new field data demonstrated significant predictive skill (R2 = 0.7) for the inverse estimate of a month-long time series of offshore wave heights. The Bayesian inverse results include uncertainty estimates that were shown to be most accurate when given uncertainty in the inputs (e.g., depth and tuning parameters). Furthermore, the inverse modeling was extended to directly estimate tuning parameters associated with the underlying wave-process model. The inverse estimates of the model parameters not only showed an offshore wave height dependence consistent with results of previous studies but the uncertainty estimates of the tuning parameters also explain previously reported variations in the model parameters.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.coastaleng.2010.11.002","usgsCitation":"Plant, N.G., and Holland, K.T., 2011, Prediction and assimilation of surf-zone processes using a Bayesian network: Part II: Inverse models: Coastal Engineering, v. 58, no. 3, p. 256-266, https://doi.org/10.1016/j.coastaleng.2010.11.002.","productDescription":"11 p.","startPage":"256","endPage":"266","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":204256,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67e7da","contributors":{"authors":[{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":348949,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holland, K. Todd","contributorId":68748,"corporation":false,"usgs":true,"family":"Holland","given":"K.","email":"","middleInitial":"Todd","affiliations":[],"preferred":false,"id":348950,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70005276,"text":"70005276 - 2011 - Probability of detecting perchlorate under natural conditions in deep groundwater in California and the Southwestern United States","interactions":[],"lastModifiedDate":"2021-02-23T15:52:40.639899","indexId":"70005276","displayToPublicDate":"2011-11-04T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Probability of detecting perchlorate under natural conditions in deep groundwater in California and the Southwestern United States","docAbstract":"We use data from 1626 groundwater samples collected in California, primarily from public drinking water supply wells, to investigate the distribution of perchlorate in deep groundwater under natural conditions. The wells were sampled for the California Groundwater Ambient Monitoring and Assessment Priority Basin Project. We develop a logistic regression model for predicting probabilities of detecting perchlorate at concentrations greater than multiple threshold concentrations as a function of climate (represented by an aridity index) and potential anthropogenic contributions of perchlorate (quantified as an anthropogenic score, AS). AS is a composite categorical variable including terms for nitrate, pesticides, and volatile organic compounds. Incorporating water-quality parameters in AS permits identification of perturbation of natural occurrence patterns by flushing of natural perchlorate salts from unsaturated zones by irrigation recharge as well as addition of perchlorate from industrial and agricultural sources. The data and model results indicate low concentrations (0.1-0.5 μg/L) of perchlorate occur under natural conditions in groundwater across a wide range of climates, beyond the arid to semiarid climates in which they mostly have been previously reported. The probability of detecting perchlorate at concentrations greater than 0.1 μg/L under natural conditions ranges from 50-70% in semiarid to arid regions of California and the Southwestern United States to 5-15% in the wettest regions sampled (the Northern California coast). The probability of concentrations above 1 μg/L under natural conditions is low (generally <3%).","language":"English","publisher":"American Chemical Society Publications","publisherLocation":"Washington, D.C.","doi":"10.1021/es103103p","usgsCitation":"Fram, M.S., and Belitz, K., 2011, Probability of detecting perchlorate under natural conditions in deep groundwater in California and the Southwestern United States: Environmental Science & Technology, v. 45, no. 4, p. 1271-1277, https://doi.org/10.1021/es103103p.","productDescription":"7 p.","startPage":"1271","endPage":"1277","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":204538,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"45","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-01-19","publicationStatus":"PW","scienceBaseUri":"4f4e4ae4e4b07f02db689f37","contributors":{"authors":[{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":352198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":352197,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70004975,"text":"70004975 - 2011 - Potential use of weather radar to study movements of wintering waterfowl","interactions":[],"lastModifiedDate":"2012-02-02T00:15:58","indexId":"70004975","displayToPublicDate":"2011-11-02T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Potential use of weather radar to study movements of wintering waterfowl","docAbstract":"To protect and restore wintering waterfowl habitat, managers require knowledge of routine wintering waterfowl movements and habitat use. During preliminary screening of Doppler weather radar data we observed biological movements consistent with routine foraging flights of wintering waterfowl known to occur near Lacassine National Wildlife Refuge (NWR), Louisiana. During the winters of 2004–2005 and 2005–2006, we conducted field surveys to identify the source of the radar echoes emanating from Lacassine NWR. We compared field data to weather radar reflectivity data. Spatial and temporal patterns consistent with foraging flight movements appeared in weather radar data on all dates of field surveys. Dabbling ducks were the dominant taxa flying within the radar beam during the foraging flight period. Using linear regression, we found a positive log-linear relationship between average radar reflectivity (Z) and number of birds detected over the study area (P < 0.001, r2 = 0.62, n = 40). Ground observations and the statistically significant relationship between radar data and field data confirm that Doppler weather radar recorded the foraging flights of dabbling ducks. Weather radars may be effective tools for wintering waterfowl management because they provide broad-scale views of both diurnal and nocturnal movements. In addition, an extensive data archive enables the study of wintering waterfowl response to habitat loss, agricultural practices, wetland restoration, and other research questions that require multiple years of data.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Wildlife Society","publisherLocation":"Bethesda, MD","doi":"10.1002/jwmg.173","usgsCitation":"Randall, L.A., Diehl, R.H., Wilson, B.C., Barrow, W., and Jeske, C.W., 2011, Potential use of weather radar to study movements of wintering waterfowl: Journal of Wildlife Management, v. 75, no. 6, p. 1324-1329, https://doi.org/10.1002/jwmg.173.","productDescription":"6 p.","startPage":"1324","endPage":"1329","numberOfPages":"5","temporalStart":"2004-12-21","temporalEnd":"2006-03-21","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":204247,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":24459,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1002/jwmg.173","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Lacassine National Wildlife Refuge","volume":"75","issue":"6","noUsgsAuthors":false,"publicationDate":"2011-07-13","publicationStatus":"PW","scienceBaseUri":"4f4e4b23e4b07f02db6ae1b3","contributors":{"authors":[{"text":"Randall, Lori A. 0000-0003-0100-994X randalll@usgs.gov","orcid":"https://orcid.org/0000-0003-0100-994X","contributorId":2678,"corporation":false,"usgs":true,"family":"Randall","given":"Lori","email":"randalll@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":351747,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diehl, Robert H. 0000-0001-9141-1734 rhdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9141-1734","contributorId":3396,"corporation":false,"usgs":true,"family":"Diehl","given":"Robert","email":"rhdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":351749,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Barry C.","contributorId":12968,"corporation":false,"usgs":true,"family":"Wilson","given":"Barry","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":351750,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barrow, Wylie C. 0000-0003-4671-2823 barroww@usgs.gov","orcid":"https://orcid.org/0000-0003-4671-2823","contributorId":1988,"corporation":false,"usgs":true,"family":"Barrow","given":"Wylie C.","email":"barroww@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":351746,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jeske, Clinton W. jeskec@usgs.gov","contributorId":2982,"corporation":false,"usgs":true,"family":"Jeske","given":"Clinton","email":"jeskec@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":true,"id":351748,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70005853,"text":"70005853 - 2011 - Population genetic structure and conservation genetics of threatened Okaloosa darters (Etheostoma okaloosae)","interactions":[],"lastModifiedDate":"2021-01-07T20:23:27.48686","indexId":"70005853","displayToPublicDate":"2011-11-02T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Population genetic structure and conservation genetics of threatened Okaloosa darters (Etheostoma okaloosae)","title":"Population genetic structure and conservation genetics of threatened Okaloosa darters (Etheostoma okaloosae)","docAbstract":"Imperiled Okaloosa darters (Etheostoma okaloosae) are small, benthic fish limited to six streams that flow into three bayous of Choctawhatchee Bay in northwest Florida, USA. We analyzed the complete mitochondrial cytochrome b gene and 10 nuclear microsatellite loci for 255 and 273 Okaloosa darters, respectively. Bayesian clustering analyses and AMOVA reflect congruent population genetic structure in both mitochondrial and microsatellite DNA. This structure reveals historical isolation of Okaloosa darter streams nested within bayous. Most of the six streams appear to have exchanged migrants though they remain genetically distinct. The U.S. Fish and Wildlife Service recently reclassified Okaloosa darters from endangered to threatened status. Our genetic data support the reclassification of Okaloosa darter Evolutionary Significant Units (ESUs) in the larger Tom’s, Turkey, and Rocky creeks from endangered to threatened status. However, the three smaller drainages (Mill, Swift, and Turkey Bolton creeks) remain at risk due to their small population sizes and anthropogenic pressures on remaining habitat. Natural resource managers now have the evolutionary information to guide recovery actions within and among drainages throughout the range of the Okaloosa darter.
","language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10592-011-0201-5","usgsCitation":"Austin, J.D., Jelks, H.L., Tate, B., Johnson, A.R., and Jordan, F., 2011, Population genetic structure and conservation genetics of threatened Okaloosa darters (Etheostoma okaloosae): Conservation Genetics, v. 12, no. 4, p. 981-989, https://doi.org/10.1007/s10592-011-0201-5.","productDescription":"9 p.","startPage":"981","endPage":"989","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":204203,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Choctawhatchee Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.66427612304688,\n 30.336139145258013\n ],\n [\n -86.02706909179688,\n 30.336139145258013\n ],\n [\n -86.02706909179688,\n 30.524413269923986\n ],\n [\n -86.66427612304688,\n 30.524413269923986\n ],\n [\n -86.66427612304688,\n 30.336139145258013\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-04-02","publicationStatus":"PW","scienceBaseUri":"4f4e4ad6e4b07f02db683f28","contributors":{"authors":[{"text":"Austin, James D.","contributorId":57584,"corporation":false,"usgs":true,"family":"Austin","given":"James","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":353383,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jelks, Howard L. 0000-0002-0672-6297 hjelks@usgs.gov","orcid":"https://orcid.org/0000-0002-0672-6297","contributorId":2962,"corporation":false,"usgs":true,"family":"Jelks","given":"Howard","email":"hjelks@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":353380,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tate, Bill","contributorId":36669,"corporation":false,"usgs":true,"family":"Tate","given":"Bill","email":"","affiliations":[],"preferred":false,"id":353381,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Aria R.","contributorId":44662,"corporation":false,"usgs":true,"family":"Johnson","given":"Aria","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":353382,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jordan, Frank","contributorId":103405,"corporation":false,"usgs":true,"family":"Jordan","given":"Frank","affiliations":[],"preferred":false,"id":353384,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70005883,"text":"sir20115186 - 2011 - Water-quality requirements, tolerances, and preferences of pallid sturgeon Scaphirhynchus albus in the lower Missouri River","interactions":[],"lastModifiedDate":"2021-08-24T16:33:39.927859","indexId":"sir20115186","displayToPublicDate":"2011-11-02T00:00:00","publicationYear":"2011","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":"2011-5186","displayTitle":"Water-quality requirements, tolerances, and preferences of pallid sturgeon (Scaphirhynchus albus) in the lower Missouri River","title":"Water-quality requirements, tolerances, and preferences of pallid sturgeon Scaphirhynchus albus in the lower Missouri River","docAbstract":"Although numerous studies have been completed on pallid sturgeon populations and behavior, few have addressed the potential for water-quality characteristics to limit recruitment and population success of pallid sturgeon. Literature on sturgeon and water-quality data indicates recruitment of pallid sturgeon may be limited by several water-quality characteristics of the lower Missouri River including: High summer water temperatures in excess of 30 degrees Celsius, which likely are stressful to pallid sturgeon,\nTurbidities that are more than an order of magnitude less than the unaltered Missouri River and may no longer provide adequate cover for egg, larval, and young pallid sturgeon or for older pallid sturgeon attempting to capture prey, Dissolved oxygen that decreases to concentrations less than 2 milligrams per liter during some river rises in the late spring and summer, Food webs altered by increased light availability and hypereutrophic conditions caused by or enhanced by impoundment, bank stabilization, nonnative species, and decreased allocthanous material from the basin, Bioaccumulative contaminants, including polychlorinated biphenyls, chlordane, dichlorodiphenyltrichloroethane (DDT) and its metabolites, mercury, and synergistic contaminant cocktails that are particularly damaging to long-lived fish, and Other contaminants such as agricultural chemicals (particularly atrazine) and organic wastewater compounds that can disrupt endocrine systems of fish and limit reproduction at extremely low concentrations.\nAdditional research could be used to characterize and quantify the requirements, tolerance, and preferences of pallid sturgeon to these water-quality characteristics, especially during the egg and larval life stages. Enhancements to existing water-sampling programs are needed to quantify the exposure of pallid sturgeon to many of these water-quality stressors.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115186","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Blevins, D.W., 2011, Water-quality requirements, tolerances, and preferences of pallid sturgeon Scaphirhynchus albus in the lower Missouri River: U.S. Geological Survey Scientific Investigations Report 2011-5186, iv, 20 p., https://doi.org/10.3133/sir20115186.","productDescription":"iv, 20 p.","startPage":"i","endPage":"20","numberOfPages":"24","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":116485,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5186.jpg"},{"id":94611,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5186/","linkFileType":{"id":5,"text":"html"}}],"scale":"2000000","projection":"Albers Equal-area Conic","country":"United States","otherGeospatial":"Missouri River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120,35 ], [ -120,55 ], [ -80,55 ], [ -80,35 ], [ -120,35 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a09e4b07f02db5fab60","contributors":{"authors":[{"text":"Blevins, Dale W. dblevins@usgs.gov","contributorId":2729,"corporation":false,"usgs":true,"family":"Blevins","given":"Dale","email":"dblevins@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":true,"id":353436,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70047199,"text":"70047199 - 2011 - Simultaneous speciation of arsenic, selenium, and chromium: species, stability, sample preservation, and analysis of ash and soil leachates","interactions":[],"lastModifiedDate":"2013-07-25T10:05:56","indexId":"70047199","displayToPublicDate":"2011-11-01T09:55:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":764,"text":"Analytical and Bioanalytical Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Simultaneous speciation of arsenic, selenium, and chromium: species, stability, sample preservation, and analysis of ash and soil leachates","docAbstract":"An analytical method using high-performance liquid chromatography separation with inductively coupled plasma mass spectrometry (ICP-MS) detection previously developed for the determination of Cr(III) and Cr(VI) has been adapted to allow the determination of As(III), As(V), Se(IV), Se(VI), Cr(III), and Cr(VI) under the same chromatographic conditions. Using this method, all six inorganic species can be determined in less than 3 min. A dynamic reaction cell (DRC)-ICP-MS system was used to detect the species eluted from the chromatographic column in order to reduce interferences. A variety of reaction cell gases and conditions may be utilized with the DRC-ICP-MS, and final selection of conditions is determined by data quality objectives. Results indicated all starting standards, reagents, and sample vials should be thoroughly tested for contamination. Tests on species stability indicated that refrigeration at 10° C was preferential to freezing for most species, particularly when all species were present, and that sample solutions and extracts should be analyzed as soon as possible to eliminate species instability and interconversion effects. A variety of environmental and geological samples, including waters and deionized water [leachates] and simulated biological leachates from soils and wildfire ashes have been analyzed using this method. Analytical spikes performed on each sample were used to evaluate data quality. Speciation analyses were conducted on deionized water leachates and simulated lung fluid leachates of ash and soils impacted by wildfires. These results show that, for leachates containing high levels of total Cr, the majority of the chromium was present in the hexavalent Cr(VI) form. In general, total and hexavalent chromium levels for samples taken from burned residential areas were higher than those obtained from non-residential forested areas. Arsenic, when found, was generally in the more oxidized As(V) form. Selenium (IV) and (VI) were present, but typically at low levels.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Analytical and Bioanalytical Chemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s00216-011-5275-x","usgsCitation":"Wolf, R.E., Morman, S.A., Hageman, P.L., Hoefen, T.M., and Plumlee, G.S., 2011, Simultaneous speciation of arsenic, selenium, and chromium: species, stability, sample preservation, and analysis of ash and soil leachates: Analytical and Bioanalytical Chemistry, v. 9, no. 401, p. 2733-2745, https://doi.org/10.1007/s00216-011-5275-x.","productDescription":"13 p.","startPage":"2733","endPage":"2745","numberOfPages":"13","ipdsId":"IP-029824","costCenters":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"links":[{"id":275374,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275357,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00216-011-5275-x"},{"id":275358,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/article/10.1007%2Fs00216-011-5275-x#page-1"}],"volume":"9","issue":"401","noUsgsAuthors":false,"publicationDate":"2011-08-12","publicationStatus":"PW","scienceBaseUri":"51f25423e4b0279fe2e1c02a","contributors":{"authors":[{"text":"Wolf, Ruth E. rwolf@usgs.gov","contributorId":903,"corporation":false,"usgs":true,"family":"Wolf","given":"Ruth","email":"rwolf@usgs.gov","middleInitial":"E.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":481332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morman, Suzette A. 0000-0002-2532-1033 smorman@usgs.gov","orcid":"https://orcid.org/0000-0002-2532-1033","contributorId":996,"corporation":false,"usgs":true,"family":"Morman","given":"Suzette","email":"smorman@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":481334,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hageman, Philip L. 0000-0002-3440-2150 phageman@usgs.gov","orcid":"https://orcid.org/0000-0002-3440-2150","contributorId":811,"corporation":false,"usgs":true,"family":"Hageman","given":"Philip","email":"phageman@usgs.gov","middleInitial":"L.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":481331,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoefen, Todd M. 0000-0002-3083-5987 thoefen@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5987","contributorId":403,"corporation":false,"usgs":true,"family":"Hoefen","given":"Todd","email":"thoefen@usgs.gov","middleInitial":"M.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":481330,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Plumlee, Geoffrey S. 0000-0002-9607-5626 gplumlee@usgs.gov","orcid":"https://orcid.org/0000-0002-9607-5626","contributorId":960,"corporation":false,"usgs":true,"family":"Plumlee","given":"Geoffrey","email":"gplumlee@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":481333,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70047286,"text":"70047286 - 2011 - Estimating eruption temperature from thermal emission spectra of lava fountain activity in the Erta'Ale (Ethiopia) volcano lava lake: Implications for observing Io's volcanoes","interactions":[],"lastModifiedDate":"2018-11-13T13:59:15","indexId":"70047286","displayToPublicDate":"2011-11-01T08:55:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Estimating eruption temperature from thermal emission spectra of lava fountain activity in the Erta'Ale (Ethiopia) volcano lava lake: Implications for observing Io's volcanoes","docAbstract":"We have analysed high-spatial-resolution and high-temporal-resolution temperature measurements of the active lava lake at Erta'Ale volcano, Ethiopia, to derive requirements for measuring eruption temperatures at Io's volcanoes. Lava lakes are particularly attractive targets because they are persistent in activity and large, often with ongoing lava fountain activity that exposes lava at near-eruption temperature. Using infrared thermography, we find that extracting useful temperature estimates from remote-sensing data requires (a) high spatial resolution to isolate lava fountains from adjacent cooler lava and (b) rapid acquisition of multi-color data. Because existing spacecraft data of Io's volcanoes do not meet these criteria, it is particularly important to design future instruments so that they will be able to collect such data. Near-simultaneous data at more than two relatively short wavelengths (shorter than 1 μm) are needed to constrain eruption temperatures. Resolving parts of the lava lake or fountains that are near the eruption temperature is also essential, and we provide a rough estimate of the required image scale.","language":"English","publisher":"Wiley","doi":"10.1029/2011GL049418","usgsCitation":"Davies, A., Keszthelyi, L., and McEwen, A.S., 2011, Estimating eruption temperature from thermal emission spectra of lava fountain activity in the Erta'Ale (Ethiopia) volcano lava lake: Implications for observing Io's volcanoes: Geophysical Research Letters, v. 38, no. 21, 5 p., https://doi.org/10.1029/2011GL049418.","productDescription":"5 p.","numberOfPages":"5","ipdsId":"IP-049705","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":275551,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ethiopia","otherGeospatial":"Erta'ale Volcano","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 40.660017,13.601647 ], [ 40.660017,13.607983 ], [ 40.666017,13.607983 ], [ 40.666017,13.601647 ], [ 40.660017,13.601647 ] ] ] } } ] }","volume":"38","issue":"21","noUsgsAuthors":false,"publicationDate":"2011-11-11","publicationStatus":"PW","scienceBaseUri":"51f8e061e4b0cecbe8fa986e","contributors":{"authors":[{"text":"Davies, Ashley G.","contributorId":36827,"corporation":false,"usgs":true,"family":"Davies","given":"Ashley G.","affiliations":[],"preferred":false,"id":481616,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keszthelyi, Laszlo P. 0000-0003-1879-4331 laz@usgs.gov","orcid":"https://orcid.org/0000-0003-1879-4331","contributorId":52802,"corporation":false,"usgs":true,"family":"Keszthelyi","given":"Laszlo P.","email":"laz@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":481617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McEwen, Alfred S.","contributorId":61657,"corporation":false,"usgs":false,"family":"McEwen","given":"Alfred","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":481618,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70005872,"text":"fs20113133 - 2011 - A promising tool for subsurface permafrost mapping-An application of airborne geophysics from the Yukon River Basin, Alaska","interactions":[],"lastModifiedDate":"2012-02-10T00:12:00","indexId":"fs20113133","displayToPublicDate":"2011-11-01T00:00:00","publicationYear":"2011","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":"2011-3133","title":"A promising tool for subsurface permafrost mapping-An application of airborne geophysics from the Yukon River Basin, Alaska","docAbstract":"Permafrost is a predominant physical feature of the Earth's Arctic and Subarctic clines and a major consideration encompassing ecosystem structure to infrastructure engineering and placement. Perennially frozen ground is estimated to cover about 85 percent of the state of Alaska where northern reaches are underlain with continuous permafrost and parts of interior Alaska are underlain by areas of discontinuous and (or) sporadic permafrost (fig. 1). The region of Interior Alaska, where permafrost is scattered among unfrozen ground, is a complex mosaic of terrains and habitats. Such diversity creates arrays of lakes and surface-water and groundwater patterns that continental populations of migratory waterfowl and internationally significant fisheries have adapted to over time. A road or pipeline might pass over frozen and unfrozen ground, affecting the types of materials and engineering approaches needed to sustain the infrastructure.\nEffective mapping of discontinuous permafrost at scales meaningful ecologically and (or) from an engineering perspective has been a long-standing challenge. Using techniques such as borehole logging for site-specific assessments or botanical techniques that can suggest underlying permafrost distributions can be labor intensive and difficult to accomplish at the scale and remoteness of much of Alaska.\nThe climate is changing in the Arctic and Subarctic regions. The warming observed throughout much of Alaska could create widespread changes in permafrost. How the warming of the permafrost affects near-surface processes, ecosystems, and community infrastructure and ecosystems is not clear. A better understanding of the dynamic distribution and physical properties of permafrost, from continuous to discontinuous, will provide knowledge of how the permafrost environment may change in the future and help inform engineering and natural resource response strategies.\nHere we discuss an application of an airborne remote sensing methodology for mapping and shade imaging permafrost characteristics at various scales. This work provides the first look into three-dimensional distribution of permafrost in the areas around Fort Yukon and is a demonstration of the application of airborne electromagnetic (AEM) to permafrost mapping. Such an approach is attractive, particularly in Arctic and Subarctic studies, where ground access is difficult and ecosystems are fragile.\nIn June 2010, the U.S. Geological Survey (USGS) conducted an AEM survey near Fort Yukon, Alaska. The primary focus of this survey was to map the distribution of permafrost in selected areas in order to supply information for the development of groundwater models of the Yukon River Basin. However, the methodologies have more far-reaching ecological and engineering applications. Approximately 1,800 line kilometers were acquired in a combination of typical block style surveying in the immediate area of Fort Yukon and in long reconnaissance lines over a broader area. The widely spaced lines were flown to cross the modern Yukon River in \"X\" like patterns with intersections at features that have been previously studied (fig. 2).\nAEM is used to gather data on the electrical resistivity of materials in the subsurface below the flight path of the helicopter, which are then analyzed to interpret the subsurface lithology and the location and extent of permafrost. For this survey, the electrical resistivity was imaged to depths on the order of 50-100 meters. Images from the survey can be qualitatively compared with known permafrost features and suggest new permafrost features. Electrical properties of earth materials are affected by lithology as well as temperature and the presence of ice; frozen materials become substantially more resistive. This allows for the identification of permafrost from the resistivity image (Abraham and others, 2011).\nIn the area of Fort Yukon, the AEM survey shows elevated resistivities extending to depth, likely indicative of thick permafrost. This depth corresponds well to observations from a borehole drilled in the area in the late 1990s, which detected permafrost to a depth of about 100 meters (Clark and others, 2009). In contrast to the area of Fort Yukon, the Yukon River and its floodplain are not associated with deep resistive sediments, suggesting a lack of deep permafrost, at least within the depth range of the AEM mapping (fig. 3).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20113133","usgsCitation":"Abraham, J.E., 2011, A promising tool for subsurface permafrost mapping-An application of airborne geophysics from the Yukon River Basin, Alaska: U.S. Geological Survey Fact Sheet 2011-3133, 4 p., https://doi.org/10.3133/fs20113133.","productDescription":"4 p.","costCenters":[{"id":542,"text":"Regional Executive for Alaska","active":false,"usgs":true}],"links":[{"id":116304,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2011_3133.png"},{"id":94600,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2011/3133/","linkFileType":{"id":5,"text":"html"}}],"state":"Alaska","otherGeospatial":"Yukon River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -149.5,66 ], [ -149.5,67.5 ], [ -143,67.5 ], [ -143,66 ], [ -149.5,66 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b1be4b07f02db6a8d0d","contributors":{"authors":[{"text":"Abraham, Jared E.","contributorId":73739,"corporation":false,"usgs":true,"family":"Abraham","given":"Jared","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":353426,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70189061,"text":"70189061 - 2011 - The Moon Mineralogy Mapper (M3) imaging spectrometer for lunar science: Instrument description, calibration, on‐orbit measurements, science data calibration and on‐orbit validation","interactions":[],"lastModifiedDate":"2021-03-17T13:35:12.656446","indexId":"70189061","displayToPublicDate":"2011-10-31T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The Moon Mineralogy Mapper (M3) imaging spectrometer for lunar science: Instrument description, calibration, on‐orbit measurements, science data calibration and on‐orbit validation","title":"The Moon Mineralogy Mapper (M3) imaging spectrometer for lunar science: Instrument description, calibration, on‐orbit measurements, science data calibration and on‐orbit validation","docAbstract":"The NASA Discovery Moon Mineralogy Mapper imaging spectrometer was selected to pursue a wide range of science objectives requiring measurement of composition at fine spatial scales over the full lunar surface. To pursue these objectives, a broad spectral range imaging spectrometer with high uniformity and high signal-to-noise ratio capable of measuring compositionally diagnostic spectral absorption features from a wide variety of known and possible lunar materials was required. For this purpose the Moon Mineralogy Mapper imaging spectrometer was designed and developed that measures the spectral range from 430 to 3000 nm with 10 nm spectral sampling through a 24 degree field of view with 0.7 milliradian spatial sampling. The instrument has a signal-to-noise ratio of greater than 400 for the specified equatorial reference radiance and greater than 100 for the polar reference radiance. The spectral cross-track uniformity is >90% and spectral instantaneous field-of-view uniformity is >90%. The Moon Mineralogy Mapper was launched on Chandrayaan-1 on the 22nd of October. On the 18th of November 2008 the Moon Mineralogy Mapper was turned on and collected a first light data set within 24 h. During this early checkout period and throughout the mission the spacecraft thermal environment and orbital parameters varied more than expected and placed operational and data quality constraints on the measurements. On the 29th of August 2009, spacecraft communication was lost. Over the course of the flight mission 1542 downlinked data sets were acquired that provide coverage of more than 95% of the lunar surface. An end-to-end science data calibration system was developed and all measurements have been passed through this system and delivered to the Planetary Data System (PDS.NASA.GOV). An extensive effort has been undertaken by the science team to validate the Moon Mineralogy Mapper science measurements in the context of the mission objectives. A focused spectral, radiometric, spatial, and uniformity validation effort has been pursued with selected data sets including an Earth-view data set. With this effort an initial validation of the on-orbit performance of the imaging spectrometer has been achieved, including validation of the cross-track spectral uniformity and spectral instantaneous field of view uniformity. The Moon Mineralogy Mapper is the first imaging spectrometer to measure a data set of this kind at the Moon. These calibrated science measurements are being used to address the full set of science goals and objectives for this mission.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2011JE003797","usgsCitation":"C. Pieters, Mouroulis, P., M. Eastwood, Boardman, J., Green, R., Glavich, T., Isaacson, P., Clark, R., Annadurai, M., Chatterjee, A., Barr, D., Besse, S., Cate, D., Cheek, L., Combe, J., Dhingra, D., Essandoh, V., Geier, S., Goswami, J., Green, R., Haemmerle, V., Head, J., Hovland, L., Hyman, S., Klima, R., Koch, T., Kramer, G., Kumar, A., Lee, K., Lundeen, S., Malaret, E., McCord, T., McLaughlin, S., Mustard, J., Nettles, J., Petro, N., Plourde, K., Racho, C., Rodriguez, J., Runyon, C., Sellar, G., Smith, C., Sobel, H., Staid, M., Sunshine, J., Taylor, L., Thaisen, K., Tompkins, S., Tseng, H., Vane, G., Varanasi, P., White, M., and Wilson, D., 2011, The Moon Mineralogy Mapper (M3) imaging spectrometer for lunar science: Instrument description, calibration, on‐orbit measurements, science data calibration and on‐orbit validation: Journal of Geophysical Research E: Planets, v. 116, no. E10, p. 1-31, https://doi.org/10.1029/2011JE003797.","productDescription":"31 p.","startPage":"1","endPage":"31","ipdsId":"IP-029080","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":474907,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011je003797","text":"Publisher Index Page"},{"id":343213,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Moon","volume":"116","issue":"E10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2011-10-29","publicationStatus":"PW","scienceBaseUri":"59576339e4b0d1f9f051b55c","contributors":{"authors":[{"text":"C. Pieters","contributorId":193947,"corporation":false,"usgs":false,"family":"C. Pieters","affiliations":[],"preferred":false,"id":702694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mouroulis, P.","contributorId":193949,"corporation":false,"usgs":false,"family":"Mouroulis","given":"P.","email":"","affiliations":[],"preferred":false,"id":702697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"M. Eastwood","contributorId":193948,"corporation":false,"usgs":false,"family":"M. Eastwood","affiliations":[],"preferred":false,"id":702696,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boardman, J.","contributorId":193902,"corporation":false,"usgs":false,"family":"Boardman","given":"J.","email":"","affiliations":[],"preferred":false,"id":702695,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Green, R.O.","contributorId":27249,"corporation":false,"usgs":true,"family":"Green","given":"R.O.","email":"","affiliations":[],"preferred":false,"id":703001,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Glavich, T.","contributorId":23000,"corporation":false,"usgs":true,"family":"Glavich","given":"T.","email":"","affiliations":[],"preferred":false,"id":703002,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Isaacson, P.","contributorId":45549,"corporation":false,"usgs":true,"family":"Isaacson","given":"P.","email":"","affiliations":[],"preferred":false,"id":703003,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Chatterjee, A.","contributorId":33156,"corporation":false,"usgs":true,"family":"Chatterjee","given":"A.","email":"","affiliations":[],"preferred":false,"id":703008,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Clark, R.","contributorId":100780,"corporation":false,"usgs":true,"family":"Clark","given":"R.","affiliations":[],"preferred":false,"id":703009,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Barr, D.","contributorId":100177,"corporation":false,"usgs":true,"family":"Barr","given":"D.","affiliations":[],"preferred":false,"id":703006,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Annadurai, M.","contributorId":13467,"corporation":false,"usgs":true,"family":"Annadurai","given":"M.","email":"","affiliations":[],"preferred":false,"id":703004,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Besse, S.","contributorId":79330,"corporation":false,"usgs":true,"family":"Besse","given":"S.","email":"","affiliations":[],"preferred":false,"id":703005,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Cate, D.","contributorId":99410,"corporation":false,"usgs":true,"family":"Cate","given":"D.","email":"","affiliations":[],"preferred":false,"id":703007,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Cheek, L.","contributorId":20189,"corporation":false,"usgs":true,"family":"Cheek","given":"L.","email":"","affiliations":[],"preferred":false,"id":703010,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Combe, 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J.N.","contributorId":41677,"corporation":false,"usgs":true,"family":"Goswami","given":"J.N.","email":"","affiliations":[],"preferred":false,"id":703015,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Green, R.","contributorId":88858,"corporation":false,"usgs":true,"family":"Green","given":"R.","affiliations":[],"preferred":false,"id":703016,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Haemmerle, V.","contributorId":44778,"corporation":false,"usgs":true,"family":"Haemmerle","given":"V.","email":"","affiliations":[],"preferred":false,"id":703017,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Head, J.","contributorId":6595,"corporation":false,"usgs":true,"family":"Head","given":"J.","email":"","affiliations":[],"preferred":false,"id":703018,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Hovland, 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G.","contributorId":32378,"corporation":false,"usgs":true,"family":"Kramer","given":"G.","email":"","affiliations":[],"preferred":false,"id":703023,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Kumar, A.S.K.","contributorId":76585,"corporation":false,"usgs":true,"family":"Kumar","given":"A.S.K.","email":"","affiliations":[],"preferred":false,"id":703024,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Lee, K. 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The report describes the methods used to develop the geospatial data, which was primarily derived from the National Watershed Boundary Dataset. The geospatial data contains polygon shapefiles of basin boundaries for 33 NASQAN and 5 NMN streamflow and water-quality monitoring stations. In addition, 30 polygon shapefiles of the closed and noncontributing basins contained within the NASQAN or NMN boundaries are included. Also included is a point shapefile of the NASQAN and NMN monitoring stations and associated basin and station attributes. Geospatial data for basin delineations, associated closed and noncontributing basins, and monitoring station locations are available at http://water.usgs.gov/GIS/metadata/usgswrd/XML/ds641_nasqan_wbd12.xml.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds641","usgsCitation":"Baker, N.T., 2011, National Stream Quality Accounting Network and National Monitoring Network Basin Boundary Geospatial Dataset, 2008–13: U.S. Geological Survey Data Series 641, iv, 16 p.; Link to Metadata, https://doi.org/10.3133/ds641.","productDescription":"iv, 16 p.; Link to Metadata","startPage":"i","endPage":"16","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2008-01-01","temporalEnd":"2013-12-31","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":116366,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_641.gif"},{"id":94577,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/641/","linkFileType":{"id":5,"text":"html"}},{"id":273223,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/ds641_nasqan_wbd12.xml"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b01e4b07f02db6987d8","contributors":{"authors":[{"text":"Baker, Nancy T. 0000-0002-7979-5744 ntbaker@usgs.gov","orcid":"https://orcid.org/0000-0002-7979-5744","contributorId":1955,"corporation":false,"usgs":true,"family":"Baker","given":"Nancy","email":"ntbaker@usgs.gov","middleInitial":"T.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353423,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70005844,"text":"sir20105057 - 2011 - Development of flood-inundation maps for the West Branch Susquehanna River near the Borough of Jersey Shore, Lycoming County, Pennsylvania","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"sir20105057","displayToPublicDate":"2011-10-28T00:00:00","publicationYear":"2011","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":"2010-5057","title":"Development of flood-inundation maps for the West Branch Susquehanna River near the Borough of Jersey Shore, Lycoming County, Pennsylvania","docAbstract":"Streamflow data, water-surface-elevation profiles derived from a Hydrologic Engineering Center River Analysis System hydraulic model, and geographical information system digital elevation models were used to develop a set of 18 flood-inundation maps for an approximately 5-mile reach of the West Branch Susquehanna River near the Borough of Jersey Shore, Pa. The inundation maps were created by the U.S. Geological Survey in cooperation with the Susquehanna River Basin Commission and Lycoming County as part of an ongoing effort by the National Oceanic and Atmospheric Administration's National Weather Service to focus on continued improvements to the flood forecasting and warning abilities in the Susquehanna River Basin and to modernize flood-forecasting methodologies. The maps, ranging from 23.0 to 40.0 feet in 1-foot increments, correspond to river stage at the U.S. Geological Survey streamgage 01549760 at Jersey Shore. The electronic files used to develop the maps were provided to the National Weather Service for incorporation into their Advanced Hydrologic Prediction Service website. The maps are displayed on this website, which serves as a web-based floodwarning system, and can be used to identify areas of predicted flood inundation associated with forecasted flood-peak stages. 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