In August 2007, the U.S. Geological Survey, in cooperation with the San Antonio Water System, did a hydrogeologic and geophysical investigation to characterize the hydrostratigraphy (hydrostratigraphic zones) and also the hydrogeologic features (karst features such as sinkholes and caves) of the Edwards aquifer in a 16-square-kilometer area of northeastern Bexar County, Texas, undergoing urban development. Existing hydrostratigraphic information, enhanced by local-scale geologic mapping in the area, and surface geophysics were used to associate ranges of electrical resistivities obtained from capacitively coupled (CC) resistivity surveys, frequency-domain electromagnetic (FDEM) surveys, time-domain electromagnetic (TDEM) soundings, and two-dimensional direct-current (2D-DC) resistivity surveys with each of seven hydrostratigraphic zones (equivalent to members of the Kainer and Person Formations) of the Edwards aquifer. The principal finding of this investigation is the relation between electrical resistivity and the contacts between the hydrostratigraphic zones of the Edwards aquifer and the underlying Trinity aquifer in the area. In general, the TDEM data indicate a two-layer model in which an electrical conductor underlies an electrical resistor, which is consistent with the Trinity aquifer (conductor) underlying the Edwards aquifer (resistor). TDEM data also show the plane of Bat Cave fault, a well-known fault in the area, to be associated with a local, nearly vertical zone of low resistivity that provides evidence, although not definitive, for Bat Cave fault functioning as a flow barrier, at least locally. In general, the CC resistivity, FDEM survey, and 2D-DC resistivity survey data show a sharp electrical contrast from north to south, changing from high resistivity to low resistivity across Bat Cave fault as well as possible karst features in the study area. Interpreted karst features that show relatively low resistivity within a relatively high-resistivity area likely are attributable to clay or soil filling a sinkhole. In general, faults are inferred where lithologic incongruity indicates possible displacement. Along most inferred faults, displacement was not sufficient to place different members of the Kainer or Person Formations (hydrostratigraphic zones) adjacent across the inferred fault plane. In general, the Kainer Formation (hydrostratigraphic zones V through VIII) has a higher resistivity than the Person Formation (hydrostratigraphic zones II through IV). Although resistivity variations from the CC resistivity, FDEM, and 2D-DC resistivity surveys, with mapping information, were sufficient to allow surface mapping of the lateral extent of hydrostratigraphic zones in places, resistivity variations from TDEM data were not sufficient to allow vertical delineation of hydrostratigraphic zones; however, the Edwards aquifer-Trinity aquifer contact could be identified from the TDEM data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20085181","collaboration":"Prepared in cooperation with the San Antonio Water System","usgsCitation":"Shah, S., Smith, B.D., Clark, A.K., and Payne, J., 2008, An Integrated Hydrogeologic and Geophysical Investigation to Characterize the Hydrostratigraphy of the Edwards Aquifer in an Area of Northeastern Bexar County, Texas (Version 1.0): U.S. Geological Survey Scientific Investigations Report 2008-5181, Report: vi, 26 p.; Plate: 24 x 18 inches; Data Files, https://doi.org/10.3133/sir20085181.","productDescription":"Report: vi, 26 p.; Plate: 24 x 18 inches; Data Files","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2007-08-01","temporalEnd":"2007-08-31","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":124763,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2008_5181.jpg"},{"id":12108,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2008/5181/","linkFileType":{"id":5,"text":"html"}},{"id":327655,"rank":101,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2008/5181/pdf/sir2008-5181.pdf","size":"8.59 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":327656,"rank":102,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2008/5181/pdf/sir2008-5181-pl1.pdf","size":"26.7 MB","linkFileType":{"id":1,"text":"pdf"}}],"projection":"Universal Transverse Mercator","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -98.43416666666667,29.634166666666665 ], [ -98.43416666666667,29.683333333333334 ], [ -98.36666666666666,29.683333333333334 ], [ -98.36666666666666,29.634166666666665 ], [ -98.43416666666667,29.634166666666665 ] ] ] } } ] }","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4adce4b07f02db6864d4","contributors":{"authors":[{"text":"Shah, Sachin D.","contributorId":60174,"corporation":false,"usgs":true,"family":"Shah","given":"Sachin D.","affiliations":[],"preferred":false,"id":301100,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Bruce D. 0000-0002-1643-2997 bsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-1643-2997","contributorId":845,"corporation":false,"usgs":true,"family":"Smith","given":"Bruce","email":"bsmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":301097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Allan K. 0000-0003-0099-1521 akclark@usgs.gov","orcid":"https://orcid.org/0000-0003-0099-1521","contributorId":1279,"corporation":false,"usgs":true,"family":"Clark","given":"Allan","email":"akclark@usgs.gov","middleInitial":"K.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":301099,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Payne, Jason 0000-0003-4294-7924 jdpayne@usgs.gov","orcid":"https://orcid.org/0000-0003-4294-7924","contributorId":1062,"corporation":false,"usgs":true,"family":"Payne","given":"Jason ","email":"jdpayne@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":301098,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207217,"text":"70207217 - 2008 - Uncertainty and sensitivity issues in process-based models of carbon and nitrogen cycles in terrestrial ecosystems","interactions":[],"lastModifiedDate":"2022-05-18T16:34:21.455034","indexId":"70207217","displayToPublicDate":"2008-12-12T12:03:11","publicationYear":"2008","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"18","title":"Uncertainty and sensitivity issues in process-based models of carbon and nitrogen cycles in terrestrial ecosystems","docAbstract":"Many process-based models of carbon (C) and nitrogen (N) cycles have been developed for northern forest ecosystems. These models are widely used to evaluate the long-term decisions in forest management dealing with effects like particulate pollution, productivity and climate change. Regarding climate change, one of the key questions that have sensitive political implications is whether northern forests will sequester atmospheric C or not. Whilst many process-based models have been tested for accuracy by evaluating or validating against observed data, few have dealt with the complexity of the incorporated procedures to estimate uncertainties associated with model predictions or the sensitivity of these predictions to input factors in a systematic, inter-model comparison fashion. In general, models differ in their underlying attempts to match natural complexities with assumed or imposed model structure and process formulations to estimate model parameters, to gather data and to address issues on scope, scale and natural variations. Uncertainties may originate from model structure, estimation of model parameters, data input, representation of natural variation and scaling exercises. Model structure relates to the mathematical representation of the processes modelled and the type of state variables that a model contains. The modelling of partitioning among above- and below-ground C and N pools and the interdependence among these pools remain a major source of uncertainty in model structure and error propagation. For example, most soil C models use at least three state variables to represent the different types of soil organic matter (SOM). This approach results in creating three artificial SOM pools, assuming that each one contains C compounds with the same turnover rate. In reality, SOM consists of many different types of C compounds with widely different turnover rates. Uncertainty in data and parameter estimates are closely linked. Data uncertainties are associated with high variations in estimating forest biomass, productivity and soil organic matter and their estimates may be incomplete for model initialisation, calibration, validation and sensitivity analysis of generalised predictor models. The scale at which a model is being used also affects the level of uncertainty, as the errors in the prediction of the C and N dynamics differ from site to landscape levels and across climatic regions. If the spatial or temporal scale of a model application is changed, additional uncertainty arises from neglecting natural variability in system variables in time and space. Uncertainty issues are also intimately related to model validation and sensitivity analysis. The estimation of uncertainties is needed to inform decision processes in order to detect the possible corridor of development. Uncertainty in this context is an essential measure of quality for stakeholder and decision makers.
Current uncertainty in quantifying the global carbon budget remains a major contributing source of uncertainty in reliably projecting future climate change. Furthermore, quantifying the global carbon budget and characterising uncertainties have emerged as critical to a successful implementation of the United Nations Framework Convention on Climate Change and its Kyoto Protocol. Beyond fundamental quantification, attribution of the processes responsible for the so-called ‘residual terrestrial uptake’ is important to the carbon cycle communities' ability to simulate the future response of the terrestrial biosphere to climate change and intentional sequestration activities. The objective of this chapter is to describe the approaches to model-data fusion enabling continued advances in quantifying carbon cycling and the terrestrial mechanisms at work. The major impediments to advances in this field include accounting for climate variability and uncertainties in model outcomes. One proposed solution to overcome these obstacles is the use of data from the FLUXNET network to characterise the relative strength of climate impact on plant productivity and respiration. Other solutions involve the use of atmospheric CO2 concentration measurements for model validation and the use of remote sensing data.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Developments in integrated environmental assessment","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","publisherLocation":"Oxford","doi":"10.1016/S1574-101X(08)00619-4","usgsCitation":"Alexandrov, G., Chan, D., Chen, M., Gurney, K., Higuchi, K., Ito, A., Jones, C., Komarov, A., Mabuchi, K., Matross, D., Veroustraete, F., and Verstreten, W., 2008, Model-data fusion in studies of the terrestrial carbon sink, chap. 19 of Developments in integrated environmental assessment, v. 3, p. 329-344, https://doi.org/10.1016/S1574-101X(08)00619-4.","productDescription":"16 p.","startPage":"329","endPage":"344","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":370211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Jakeman, A.J.","contributorId":12639,"corporation":false,"usgs":true,"family":"Jakeman","given":"A.J.","email":"","affiliations":[],"preferred":false,"id":777304,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Voinov, A.A.","contributorId":113598,"corporation":false,"usgs":true,"family":"Voinov","given":"A.A.","affiliations":[],"preferred":false,"id":777305,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Rizzoli, A.E.","contributorId":113184,"corporation":false,"usgs":true,"family":"Rizzoli","given":"A.E.","email":"","affiliations":[],"preferred":false,"id":777306,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Chen, S. H.","contributorId":221190,"corporation":false,"usgs":false,"family":"Chen","given":"S.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":777307,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Alexandrov, G.A.","contributorId":221173,"corporation":false,"usgs":false,"family":"Alexandrov","given":"G.A.","email":"","affiliations":[],"preferred":false,"id":777292,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chan, D.","contributorId":221174,"corporation":false,"usgs":false,"family":"Chan","given":"D.","email":"","affiliations":[],"preferred":false,"id":777293,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chen, M.","contributorId":73417,"corporation":false,"usgs":true,"family":"Chen","given":"M.","email":"","affiliations":[],"preferred":false,"id":777294,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gurney, K.","contributorId":24174,"corporation":false,"usgs":true,"family":"Gurney","given":"K.","affiliations":[],"preferred":false,"id":777295,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Higuchi, K","contributorId":221175,"corporation":false,"usgs":false,"family":"Higuchi","given":"K","email":"","affiliations":[],"preferred":false,"id":777296,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ito, A","contributorId":221176,"corporation":false,"usgs":false,"family":"Ito","given":"A","email":"","affiliations":[],"preferred":false,"id":777297,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, C.D.","contributorId":221177,"corporation":false,"usgs":false,"family":"Jones","given":"C.D.","email":"","affiliations":[],"preferred":false,"id":777298,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Komarov, A","contributorId":221178,"corporation":false,"usgs":false,"family":"Komarov","given":"A","email":"","affiliations":[],"preferred":false,"id":777299,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mabuchi, K","contributorId":221179,"corporation":false,"usgs":false,"family":"Mabuchi","given":"K","email":"","affiliations":[],"preferred":false,"id":777300,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Matross, D.M.","contributorId":221180,"corporation":false,"usgs":false,"family":"Matross","given":"D.M.","email":"","affiliations":[],"preferred":false,"id":777301,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Veroustraete, F","contributorId":221181,"corporation":false,"usgs":false,"family":"Veroustraete","given":"F","email":"","affiliations":[],"preferred":false,"id":777302,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Verstreten, W.W.","contributorId":221189,"corporation":false,"usgs":false,"family":"Verstreten","given":"W.W.","email":"","affiliations":[],"preferred":false,"id":777303,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":97117,"text":"sir20085172 - 2008 - Geoinformatics 2008 - Data to Knowledge","interactions":[],"lastModifiedDate":"2012-02-02T00:14:28","indexId":"sir20085172","displayToPublicDate":"2008-12-04T00:00:00","publicationYear":"2008","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":"2008-5172","title":"Geoinformatics 2008 - Data to Knowledge","docAbstract":"Geoinformatics is the term used to describe a variety of efforts to promote collaboration between the computer sciences and the geosciences to solve complex scientific questions. It refers to the distributed, integrated digital information system and working environment that provides innovative means for the study of the Earth systems, as well as other planets, through use of advanced information technologies. Geoinformatics activities range from major research and development efforts creating new technologies to provide high-quality, sustained production-level services for data discovery, integration and analysis, to small, discipline-specific efforts that develop earth science data collections and data analysis tools serving the needs of individual communities. The ultimate vision of Geoinformatics is a highly interconnected data system populated with high quality, freely available data, as well as, a robust set of software for analysis, visualization, and modeling. This volume is a collection of extended abstracts for oral papers presented at the Geoinformatics 2008 conference, June 11 and 13, 2008, in Potsdam, Germany.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20085172","isbn":"9781411322790","usgsCitation":"Brady, S.R., Sinha, A.K., and Gundersen, L.C., 2008, Geoinformatics 2008 - Data to Knowledge: U.S. Geological Survey Scientific Investigations Report 2008-5172, vi, 76 p., https://doi.org/10.3133/sir20085172.","productDescription":"vi, 76 p.","temporalStart":"2008-06-11","temporalEnd":"2008-06-13","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":12099,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2008/5172/","linkFileType":{"id":5,"text":"html"}},{"id":195072,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b1ae4b07f02db6a8728","contributors":{"authors":[{"text":"Brady, Shailaja R. srbrady@usgs.gov","contributorId":1762,"corporation":false,"usgs":true,"family":"Brady","given":"Shailaja","email":"srbrady@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":301083,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sinha, A. Krishna","contributorId":32998,"corporation":false,"usgs":true,"family":"Sinha","given":"A.","email":"","middleInitial":"Krishna","affiliations":[],"preferred":false,"id":301084,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gundersen, Linda C. lgundersen@usgs.gov","contributorId":238,"corporation":false,"usgs":true,"family":"Gundersen","given":"Linda","email":"lgundersen@usgs.gov","middleInitial":"C.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":301082,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":97119,"text":"ofr20081186 - 2008 - Watershed Regressions for Pesticides (WARP) for Predicting Annual Maximum and Annual Maximum Moving-Average Concentrations of Atrazine in Streams","interactions":[],"lastModifiedDate":"2012-03-08T17:16:31","indexId":"ofr20081186","displayToPublicDate":"2008-12-04T00:00:00","publicationYear":"2008","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":"2008-1186","title":"Watershed Regressions for Pesticides (WARP) for Predicting Annual Maximum and Annual Maximum Moving-Average Concentrations of Atrazine in Streams","docAbstract":"Regression models were developed for predicting annual maximum and selected annual maximum moving-average concentrations of atrazine in streams using the Watershed Regressions for Pesticides (WARP) methodology developed by the National Water-Quality Assessment Program (NAWQA) of the U.S. Geological Survey (USGS). The current effort builds on the original WARP models, which were based on the annual mean and selected percentiles of the annual frequency distribution of atrazine concentrations. Estimates of annual maximum and annual maximum moving-average concentrations for selected durations are needed to characterize the levels of atrazine and other pesticides for comparison to specific water-quality benchmarks for evaluation of potential concerns regarding human health or aquatic life.\r\n\r\nSeparate regression models were derived for the annual maximum and annual maximum 21-day, 60-day, and 90-day moving-average concentrations. Development of the regression models used the same explanatory variables, transformations, model development data, model validation data, and regression methods as those used in the original development of WARP. The models accounted for 72 to 75 percent of the variability in the concentration statistics among the 112 sampling sites used for model development. Predicted concentration statistics from the four models were within a factor of 10 of the observed concentration statistics for most of the model development and validation sites.\r\n\r\nOverall, performance of the models for the development and validation sites supports the application of the WARP models for predicting annual maximum and selected annual maximum moving-average atrazine concentration in streams and provides a framework to interpret the predictions in terms of uncertainty. For streams with inadequate direct measurements of atrazine concentrations, the WARP model predictions for the annual maximum and the annual maximum moving-average atrazine concentrations can be used to characterize the probable levels of atrazine for comparison to specific water-quality benchmarks. Sites with a high probability of exceeding a benchmark for human health or aquatic life can be prioritized for monitoring.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20081186","usgsCitation":"Stone, W.W., Gilliom, R.J., and Crawford, C.G., 2008, Watershed Regressions for Pesticides (WARP) for Predicting Annual Maximum and Annual Maximum Moving-Average Concentrations of Atrazine in Streams: U.S. Geological Survey Open-File Report 2008-1186, viii, 19 p., https://doi.org/10.3133/ofr20081186.","productDescription":"viii, 19 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":195945,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":12101,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2008/1186/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ad7e4b07f02db68460e","contributors":{"authors":[{"text":"Stone, Wesley W. 0000-0003-0239-2063 wwstone@usgs.gov","orcid":"https://orcid.org/0000-0003-0239-2063","contributorId":1496,"corporation":false,"usgs":true,"family":"Stone","given":"Wesley","email":"wwstone@usgs.gov","middleInitial":"W.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":301088,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gilliom, Robert J. rgilliom@usgs.gov","contributorId":488,"corporation":false,"usgs":true,"family":"Gilliom","given":"Robert","email":"rgilliom@usgs.gov","middleInitial":"J.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":301086,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crawford, Charles G. 0000-0003-1653-7841 cgcrawfo@usgs.gov","orcid":"https://orcid.org/0000-0003-1653-7841","contributorId":1064,"corporation":false,"usgs":true,"family":"Crawford","given":"Charles","email":"cgcrawfo@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":301087,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":97116,"text":"sir20085098 - 2008 - Digital surfaces and thicknesses of selected hydrogeologic units within the Mississippi Embayment Regional Aquifer Study (MERAS)","interactions":[],"lastModifiedDate":"2025-07-17T13:12:17.055626","indexId":"sir20085098","displayToPublicDate":"2008-12-04T00:00:00","publicationYear":"2008","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":"2008-5098","displayTitle":"Digital Surfaces and Thicknesses of Selected Hydrogeologic Units within the Mississippi Embayment Regional Aquifer Study (MERAS)","title":"Digital surfaces and thicknesses of selected hydrogeologic units within the Mississippi Embayment Regional Aquifer Study (MERAS)","docAbstract":"Digital surfaces of selected Tertiary and younger age hydrogeologic units within the Mississippi embayment aquifer system were created using more than 2,600 geophysical logs for an area that covers approximately 70,000 square miles and encompasses parts of eight states. The digital surfaces were developed to define and display the hydrogeologic framework for the Mississippi Embayment Regional Aquifer Study (MERAS). The digital surfaces also provide a foundation of the selected hydrogeologic units for development of a steady-state and transient regional ground-water flow model of the Mississippi embayment aquifer system from the top of the Midway confining unit upwards to land surface. The ground-water flow model is under development as part of the U.S. Geological Survey Ground-Water Resources Program.\r\n\r\nUsing a Geographic Information System, nine digital surfaces of the tops of selected hydrogeologic units were created using the Australian National University Digital Elevation Model method as an interpolation scheme. Thickness maps also were constructed using the Geographic Information System by calculating the difference between the altitude of the interpreted base of an overlying unit and the altitude of the interpreted top of an underlying unit. In general, the highest hydrogeologic unit altitudes are located along the eastern edge of the study area in the outcrop, and the lowest altitudes, in general, are located along the southern edge of the study area along the axis of the embayment. The Mississippi River Valley alluvial aquifer and the lower Claiborne aquifer are the thinnest aquifers of importance in the study area; the thickest aquifer of importance is the middle Claiborne aquifer.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20085098","usgsCitation":"Hart, R.M., Clark, B.R., and Bolyard, S., 2008, Digital surfaces and thicknesses of selected hydrogeologic units within the Mississippi Embayment Regional Aquifer Study (MERAS) (Version 1.0): U.S. Geological Survey Scientific Investigations Report 2008-5098, Report: iv, 34 p.; Downloads Directory; Data Release, https://doi.org/10.3133/sir20085098.","productDescription":"Report: iv, 34 p.; Downloads Directory; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":327,"text":"Groundwater Resources Program","active":false,"usgs":true}],"links":[{"id":195080,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":492368,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1VRSZLE","text":"USGS data release","description":"USGS data release","linkHelpText":"Digital surfaces and extents of selected hydrogeologic units within the Mississippi embayment aquifer system"},{"id":12098,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2008/5098/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Mississippi Embayment Regional Aquifer","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.5,30 ], [ -94.5,38 ], [ -86,38 ], [ -86,30 ], [ -94.5,30 ] ] ] } } ] }","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b32e4b07f02db6b45fb","contributors":{"authors":[{"text":"Hart, Rheannon M. 0000-0003-4657-5945 rmhart@usgs.gov","orcid":"https://orcid.org/0000-0003-4657-5945","contributorId":5516,"corporation":false,"usgs":true,"family":"Hart","given":"Rheannon","email":"rmhart@usgs.gov","middleInitial":"M.","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":301080,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Brian R. 0000-0001-6611-3807 brclark@usgs.gov","orcid":"https://orcid.org/0000-0001-6611-3807","contributorId":1502,"corporation":false,"usgs":true,"family":"Clark","given":"Brian","email":"brclark@usgs.gov","middleInitial":"R.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":301079,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bolyard, Susan E.","contributorId":47321,"corporation":false,"usgs":true,"family":"Bolyard","given":"Susan E.","affiliations":[],"preferred":false,"id":301081,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70032522,"text":"70032522 - 2008 - Heat as a tracer to determine streambed water exchanges","interactions":[],"lastModifiedDate":"2022-08-31T16:40:35.740385","indexId":"70032522","displayToPublicDate":"2008-12-02T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Heat as a tracer to determine streambed water exchanges","docAbstract":"This work reviews the use of heat as a tracer of shallow groundwater movement and describes current temperature-based approaches for estimating streambed water exchanges. Four common hydrologic conditions in stream channels are graphically depicted with the expected underlying streambed thermal responses, and techniques are discussed for installing and monitoring temperature and stage equipment for a range of hydrological environments. These techniques are divided into direct-measurement techniques in streams and streambeds, groundwater techniques relying on traditional observation wells, and remote sensing and other large-scale advanced temperature-acquisition techniques. A review of relevant literature suggests researchers often graphically visualize temperature data to enhance conceptual models of heat and water flow in the near-stream environment and to determine site-specific approaches of data analysis. Common visualizations of stream and streambed temperature patterns include thermographs, temperature envelopes, and one-, two-, and three-dimensional temperature contour plots. Heat and water transport governing equations are presented for the case of transport in streambeds, followed by methods of streambed data analysis, including simple heat-pulse arrival time and heat-loss procedures, analytical and time series solutions, and heat and water transport simulation models. A series of applications of these methods are presented for a variety of stream settings ranging from arid to continental climates. Progressive successes to quantify both streambed fluxes and the spatial extent of streambeds indicate heat-tracing tools help define the streambed as a spatially distinct field (analogous to soil science), rather than simply the lower boundary in stream research or an amorphous zone beneath the stream channel.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2008WR006996","usgsCitation":"Constantz, J., 2008, Heat as a tracer to determine streambed water exchanges: Water Resources Research, v. 46, no. 4, W00D10, 20 p., https://doi.org/10.1029/2008WR006996.","productDescription":"W00D10, 20 p.","costCenters":[],"links":[{"id":476579,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2008wr006996","text":"Publisher Index Page"},{"id":241481,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"4","noUsgsAuthors":false,"publicationDate":"2008-12-02","publicationStatus":"PW","scienceBaseUri":"505a2fe5e4b0c8380cd5d1ab","contributors":{"authors":[{"text":"Constantz, Jim","contributorId":66338,"corporation":false,"usgs":true,"family":"Constantz","given":"Jim","affiliations":[],"preferred":false,"id":436625,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70209631,"text":"70209631 - 2008 - Stratigraphic models for deep-water sedimentary systems","interactions":[],"lastModifiedDate":"2020-04-16T16:38:51.742153","indexId":"70209631","displayToPublicDate":"2008-12-01T09:53:14","publicationYear":"2008","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Stratigraphic models for deep-water sedimentary systems","docAbstract":"Stratigraphic models predict sedimentary architecture. Prediction requires understanding systems across a sufficient range of scales. To be predictive a model must address the interaction of multiple process-response relationships. For deep-water systems these processes include (1) subaqueous flow initiation and transformation, (2) linkages between channel, levee and lobe processes, and (3) shelf-to-basin profile evolution. Thickness, lithology and the geomorphic hierarchy of sedimentary bodies are responses that can be used to define phases in deep-water episodes recording both external (allogenic) and internal (autogenic) controls.
Shelf-to-basin studies of the Middle Permian Brushy Canyon Formation demonstrate that the more complete basinal record correlates to an incomplete shelf record; this incongruity impacts recognition of allogenic forcing. Preserving the signature of external controls, internal changes in local gradient and topography also impact the deep-water record requiring complete basin analysis. Independent but nested autogenic and allogenic stratigraphic models address these challenges and predict patterns of deep-water sedimentation.
Tectonics and climate modulate sediment supply and sea level, which are considered the principal allogenic controls on deep-water sedimentation as described by the phases of the AIGR (Adjustment-Initiation-Growth-Retreat) model. The complete AIGR cycle commences with the Adjustment (A) phase, which defines the initial profile gradient and topography. The Initiation (I), Growth (G), and Retreat (R) phases describe variations in sedimentary response.
Autogenic controls on deep-water sedimentation include (1) lateral offset and compensational stacking of lobes, (2) channel migration, switching and avulsion, and (3) longitudinal translation of the channel-lobe transition zone. The BCFS (Build-Cut-Fill-Spill) model describes autogenic controls on local gradient and confinement based on a hierarchy of channel-fill, channel-flank, and lobe sedimentary bodies, which vary in proportion and arrangement in each phase.
The sedimentation phases of the AIGR and BCFS models describe the systematic increase and decrease in sedimentation energy recorded in hierarchical stratigraphy. When linked to gradient, the models form the axes of a sedimentary system energy matrix (SSEM) for sedimentary architecture. The BCFS model for submarine channels is embedded within the AIGR basin model and, together they facilitate the correlation of a hierarchy of internally and externally generated stratigraphic cycles.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Answering the challenges of production from deep-water reservoirs: Analogues and case histories to aid a new generatio","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"SEPM Society for Sedimentary Geology","doi":"10.5724/gcs.08.28.0077","usgsCitation":"Gardner, M.H., Borer, J.M., Romans, B.W., Baptista, N., Kling, E.K., Hanggoro, D., Melick, J.J., Wagerle, R.M., Dechesne, M., Carr, M.M., Amerman, R., and Atan, S., 2008, Stratigraphic models for deep-water sedimentary systems, chap. of Answering the challenges of production from deep-water reservoirs: Analogues and case histories to aid a new generatio, p. 77-175, https://doi.org/10.5724/gcs.08.28.0077.","productDescription":"99 p.","startPage":"77","endPage":"175","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":374059,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gardner, Michael H.","contributorId":224186,"corporation":false,"usgs":false,"family":"Gardner","given":"Michael","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":787279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Borer, James M.","contributorId":224187,"corporation":false,"usgs":false,"family":"Borer","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":787280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romans, Brian W.","contributorId":40426,"corporation":false,"usgs":true,"family":"Romans","given":"Brian","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":787281,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baptista, Noelia","contributorId":224188,"corporation":false,"usgs":false,"family":"Baptista","given":"Noelia","email":"","affiliations":[],"preferred":false,"id":787282,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kling, Erik K.","contributorId":224189,"corporation":false,"usgs":false,"family":"Kling","given":"Erik","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":787283,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hanggoro, Diah","contributorId":224190,"corporation":false,"usgs":false,"family":"Hanggoro","given":"Diah","email":"","affiliations":[],"preferred":false,"id":787284,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Melick, Jesse J.","contributorId":224191,"corporation":false,"usgs":false,"family":"Melick","given":"Jesse","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":787285,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wagerle, Roger M.","contributorId":224192,"corporation":false,"usgs":false,"family":"Wagerle","given":"Roger","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":787286,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Dechesne, Marieke 0000-0002-4468-7495 mdechesne@usgs.gov","orcid":"https://orcid.org/0000-0002-4468-7495","contributorId":5036,"corporation":false,"usgs":true,"family":"Dechesne","given":"Marieke","email":"mdechesne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":787287,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Carr, Mary M.","contributorId":224193,"corporation":false,"usgs":false,"family":"Carr","given":"Mary","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":787288,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Amerman, Robert","contributorId":224195,"corporation":false,"usgs":false,"family":"Amerman","given":"Robert","email":"","affiliations":[],"preferred":false,"id":787289,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Atan, Safian","contributorId":224194,"corporation":false,"usgs":false,"family":"Atan","given":"Safian","email":"","affiliations":[],"preferred":false,"id":787290,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70179365,"text":"70179365 - 2008 - Survival and migration behavior of juvenile salmonids at McNary Dam, 2006","interactions":[],"lastModifiedDate":"2016-12-29T13:52:06","indexId":"70179365","displayToPublicDate":"2008-12-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Survival and migration behavior of juvenile salmonids at McNary Dam, 2006","docAbstract":"During 2006, we used acoustic telemetry and a route-specific survival model (RSSM, Skalski et al. 2002) to estimate behavior, passage, and survival of juvenile salmonids during two different spill operations and diel periods at McNary Dam. An evaluation of 12-h versus 24-h spill was proposed for the spring migration period at McNary Dam. However, high river discharge did not allow for the 12-h spill treatment, and thus, resource managers decided on testing two 24-h spill treatments having two distinct spill patterns. The first treatment, the “Fish Passage Plan” (FPP) treatment emphasized spill on the north end (bays 1-3) of the spillway and generally higher discharge through the north powerhouse. The second treatment, the “Test Spill” (TS) treatment emphasized spill on the south end (bays 18-20) of the spillway and relatively less discharge through the north powerhouse. During the summer, two dam operations were evaluated: 1) 24-h spill at 60% of total river discharge, and 2) 24-h spill at 40% of total river discharge. Both the Fish Passage Plan treatment in spring and the 40% spill treatment in summer had the more distinct pattern in powerhouse operations over the 24-h diel cycle, with generally higher powerhouse discharge and lower spill discharge during daytime hours (about 0600 to 1800 hours) compared to the alternative spill treatment.
","language":"English","publisher":"U. S. Army Corps of Engineers","usgsCitation":"U. S. Army Corps of Engineers, 2008, Survival and migration behavior of juvenile salmonids at McNary Dam, 2006, xx., 129 p.","productDescription":"xx., 129 p.","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":332645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"McNary dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.30740356445311,\n 45.94924003378791\n ],\n [\n -119.24697875976562,\n 45.95592353109714\n ],\n [\n -119.15771484375,\n 45.93969078234\n ],\n [\n -119.15496826171875,\n 45.915810457254395\n ],\n [\n -119.28268432617188,\n 45.917721261594224\n ],\n [\n -119.37469482421875,\n 45.909122123907295\n ],\n [\n -119.4049072265625,\n 45.90625544858718\n ],\n [\n -119.40628051757812,\n 45.93396044192156\n ],\n [\n -119.30740356445311,\n 45.94924003378791\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58662f15e4b0cd2dabe7c4bf"} ,{"id":70156754,"text":"70156754 - 2008 - The Importance of Uncertainty and Sensitivity Analysis in Process-based Models of Carbon and Nitrogen Cycling in Terrestrial Ecosystems with Particular Emphasis on Forest Ecosystems — Selected Papers from a Workshop Organized by the International Society for Ecological Modelling (ISEM) at the Third Biennal Meeting of the International Environmental Modelling and Software Society (IEMSS) in Burlington, Vermont, USA, August 9-13, 2006","interactions":[],"lastModifiedDate":"2015-08-27T12:40:04","indexId":"70156754","displayToPublicDate":"2008-12-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"The Importance of Uncertainty and Sensitivity Analysis in Process-based Models of Carbon and Nitrogen Cycling in Terrestrial Ecosystems with Particular Emphasis on Forest Ecosystems — Selected Papers from a Workshop Organized by the International Society for Ecological Modelling (ISEM) at the Third Biennal Meeting of the International Environmental Modelling and Software Society (IEMSS) in Burlington, Vermont, USA, August 9-13, 2006","docAbstract":"Many process-based models of carbon (C) and nitrogen (N) cycles have been developed for terrestrial ecosystems, including forest ecosystems. They address many basic issues of ecosystems structure and functioning, such as the role of internal feedback in ecosystem dynamics. The critical factor in these phenomena is scale, as these processes operate at scales from the minute (e.g. particulate pollution impacts on trees and other organisms) to the global (e.g. climate change). Research efforts remain important to improve the capability of such models to better represent the dynamics of terrestrial ecosystems, including the C, nutrient, (e.g. N) and water cycles. Existing models are sufficiently well advanced to help decision makers develop sustainable management policies and planning of terrestrial ecosystems, as they make realistic predictions when used appropriately. However, decision makers must be aware of their limitations by having the opportunity to evaluate the uncertainty associated with process-based models (Smith and Heath, 2001 and Allen et al., 2004). The variation in scale of issues currently being addressed by modelling efforts makes the evaluation of uncertainty a daunting task.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2008.07.010","usgsCitation":"Larocque, G.R., Bhatti, J.S., Liu, J., Ascough, J.C., and Gordon, A.M., 2008, The Importance of Uncertainty and Sensitivity Analysis in Process-based Models of Carbon and Nitrogen Cycling in Terrestrial Ecosystems with Particular Emphasis on Forest Ecosystems — Selected Papers from a Workshop Organized by the International Society for Ecological Modelling (ISEM) at the Third Biennal Meeting of the International Environmental Modelling and Software Society (IEMSS) in Burlington, Vermont, USA, August 9-13, 2006: Ecological Modelling, v. 219, no. 3-4, p. 261-263, https://doi.org/10.1016/j.ecolmodel.2008.07.010.","productDescription":"3 p.","startPage":"261","endPage":"263","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":307623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"219","issue":"3-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55e034c3e4b0f42e3d040e4c","contributors":{"authors":[{"text":"Larocque, Guy R.","contributorId":68139,"corporation":false,"usgs":true,"family":"Larocque","given":"Guy","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":570371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bhatti, Jagtar S.","contributorId":12720,"corporation":false,"usgs":true,"family":"Bhatti","given":"Jagtar","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":570372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Jinxun 0000-0003-0561-8988 jxliu@usgs.gov","orcid":"https://orcid.org/0000-0003-0561-8988","contributorId":3414,"corporation":false,"usgs":true,"family":"Liu","given":"Jinxun","email":"jxliu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":570373,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ascough, James C. II","contributorId":68678,"corporation":false,"usgs":true,"family":"Ascough","given":"James","suffix":"II","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":570374,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gordon, Andrew M.","contributorId":9093,"corporation":false,"usgs":true,"family":"Gordon","given":"Andrew","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":570375,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70156104,"text":"70156104 - 2008 - Coast salish and U.S. Geological Survey: Tribal journey water quality project","interactions":[],"lastModifiedDate":"2016-09-09T14:51:56","indexId":"70156104","displayToPublicDate":"2008-12-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Coast salish and U.S. Geological Survey: Tribal journey water quality project","docAbstract":"The ancestral waters of the Coast Salish People, the Salish Sea, comprise a large inland sea contained within both United States (Puget Sound) and Canadian (Georgia Strait) territory. The Salish Sea is home to more than 220 species of fish, 29 species of marine mammals, more than 40 species of commercial and recreationally harvested invertebrates, and numerous resident and migratory bird species (Washington Sea Grant Program, 2000). Unfortunately, at least 60 of these marine based species are listed as threatened, endangered or of concern (Fraser and others, 2006), many of which sustained Coast Salish for millennia and are of essential cultural importance.\nThe cumulative impacts of human activities and climate change are deteriorating coastal ecosystems and accelerating the loss of ecologically and culturally important marine resources. Watershed modifications, coastal development and industrial activities are altering river and tidal flow, sediment transport, and nutrient delivery all across the region, leading to the break down of ecosystem functions and decreasing biodiversity, thus changing the face of the Salish Sea. A cooperative trans-boundary partnership between the U.S. Environmental Protection Agency (USEPA) and the Government of Canada has identified Salish Sea indicators of health. Several of these indicators have been noted as having degrading quality including urbanization and forest change, river, stream, and lake quality, marine species at risk, toxics in harbor seals, and marine water quality conditions (USEPA, 2008). The functioning of the Salish Sea ecosystem is increasingly threatened by ever more frequent observations and expanding zones of anoxia. The complexities of monitoring, protecting, and restoring such a large and diverse geographical area are exacerbated by a political border.\nThe Coast Salish Peoples and U.S. Geological Survey (USGS) have commenced on a partnership to examine water quality throughout the Georgia Straits and Puget Sound, blending tradition and science, in response to this deterioration of coastal environments and loss of essential habitats and marine resources of cultural and ecological importance throughout the ancestral waters of the Salish Sea. This report describes the Coast Salish Tribal Journey Water Quality Project, its inception, the results of the 2008 Tribal Journey project, lessons learned, and recommendations for future directions.","language":"English","publisher":"U.S Geological Survey ","usgsCitation":"Akin, S.K., Grossman, E., Lekanof, D., and O’Hara, C.J., 2008, Coast salish and U.S. Geological Survey: Tribal journey water quality project, 58 p. .","productDescription":"58 p. 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The first 30 feet of relief above mean sea level are displayed as brightly colored 5-foot elevation bands, which highlight low-elevation areas at a coarse spatial resolution. Standard USGS National Elevation Dataset (NED) 1 arc-second (nominally 30-meter) digital elevation model (DEM) data are the basis for the map, which is designed to be used at a broad scale and for informational purposes only. \r\n\r\nThe NED data were derived from the original 1:24,000-scale USGS topographic map bare-earth contours, which were converted into gridded quadrangle-based DEM tiles at a constant post spacing (grid cell size) of either 30 meters (data before the mid-1990s data) or 10 meters (mid-1990s and later data). These individual-quadrangle DEMs were then converted to spherical coordinates (latitude/longitude decimal degrees) and edge-matched to ensure seamlessness. Approximately one-half of the area shown on this map has DEM source data at a 30-meter resolution, with the remaining half consisting of 10-meter contour-derived DEM data or higher-resolution LIDAR data.\r\n\r\nAreas below sea level typically are surrounded by levees or some other type of flood-control structures.\r\n\r\nState and county boundary, hydrography, city, and road layers were modified from USGS National Atlas data downloaded in 2003. The NED data were downloaded in 2005.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sim3048","usgsCitation":"Kosovich, J.J., 2008, Gulf of Mexico region — Highlighting low-lying areas derived from USGS Digital Elevation Data (Version 1.0): U.S. Geological Survey Scientific Investigations Map 3048, 1 Plate: 56 x 34 inches; Downloads Directory, https://doi.org/10.3133/sim3048.","productDescription":"1 Plate: 56 x 34 inches; Downloads Directory","additionalOnlineFiles":"Y","costCenters":[{"id":176,"text":"Central Region Geospatial Information Office","active":false,"usgs":true}],"links":[{"id":195141,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":12080,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3048/","linkFileType":{"id":5,"text":"html"}},{"id":394795,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_96746.htm"}],"scale":"1350000","projection":"Albers Conic Equal Area","country":"United States","state":"Alabama, Florida, Louisiana, Mississippi, Texas","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.9594,\n 23.8147\n ],\n [\n -79.2531,\n 23.8147\n ],\n [\n -79.2531,\n 32.4628\n ],\n [\n -99.9594,\n 32.4628\n ],\n [\n -99.9594,\n 23.8147\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a81e4b07f02db64a1e2","contributors":{"authors":[{"text":"Kosovich, John J. 0000-0002-3795-4436 jjkosovich@usgs.gov","orcid":"https://orcid.org/0000-0002-3795-4436","contributorId":1470,"corporation":false,"usgs":true,"family":"Kosovich","given":"John","email":"jjkosovich@usgs.gov","middleInitial":"J.","affiliations":[{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true},{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":301039,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":97098,"text":"sim3047 - 2008 - State of Florida 1:24,000- and 1:100,000-scale quadrangle index map - Highlighting low-lying areas derived from USGS Digital Elevation Models","interactions":[],"lastModifiedDate":"2017-03-29T11:03:54","indexId":"sim3047","displayToPublicDate":"2008-11-27T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3047","title":"State of Florida 1:24,000- and 1:100,000-scale quadrangle index map - Highlighting low-lying areas derived from USGS Digital Elevation Models","docAbstract":"In support of U.S. Geological Survey (USGS) disaster preparedness efforts, this map depicts 1:24,000- and 1:100,000-scale quadrangle footprints over a color shaded relief representation of the State of Florida. The first 30 feet of relief above mean sea level are displayed as brightly colored 5-foot elevation bands, which highlight low-elevation areas at a coarse spatial resolution. Standard USGS National Elevation Dataset (NED) 1 arc-second (nominally 30-meter) digital elevation model (DEM) data are the basis for the map, which is designed to be used at a broad scale and for informational purposes only.\r\n\r\nThe NED source data for this map consists of a mixture of 30-meter- and 10-meter-resolution DEMs. The NED data were derived from the original 1:24,000-scale USGS topographic map bare-earth contours, which were converted into gridded quadrangle-based DEM tiles at a constant post spacing (grid cell size) of either 30 meters (data before the mid-1990s) or 10 meters (mid-1990s and later data). These individual-quadrangle DEMs were then converted to spherical coordinates (latitude/longitude decimal degrees) and edge-matched to ensure seamlessness. \r\n\r\nFigure 1 shows a similar representation for the entire U.S. Gulf Coast, using coarsened 30-meter NED data. Areas below sea level typically are surrounded by levees or some other type of flood-control structures.\r\n\r\nState and county boundary, hydrography, city, and road layers were modified from USGS National Atlas data downloaded in 2003. Quadrangle names, dated April, 2006, were obtained from the Federal Geographic Names Information System. The NED data were downloaded in 2004.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sim3047","usgsCitation":"Kosovich, J.J., 2008, State of Florida 1:24,000- and 1:100,000-scale quadrangle index map - Highlighting low-lying areas derived from USGS Digital Elevation Models (Version 1.0): U.S. Geological Survey Scientific Investigations Map 3047, Map Sheet: 39 x 38 inches; Downloads Directory, https://doi.org/10.3133/sim3047.","productDescription":"Map Sheet: 39 x 38 inches; Downloads Directory","additionalOnlineFiles":"Y","costCenters":[{"id":176,"text":"Central Region Geospatial Information Office","active":false,"usgs":true}],"links":[{"id":194987,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":12079,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3047/","linkFileType":{"id":5,"text":"html"}}],"scale":"1000000","projection":"Universal Transverse Mercator","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88,24 ], [ -88,31.25 ], [ -80,31.25 ], [ -80,24 ], [ -88,24 ] ] ] } } ] }","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49e0e4b07f02db5e3fd7","contributors":{"authors":[{"text":"Kosovich, John J. 0000-0002-3795-4436 jjkosovich@usgs.gov","orcid":"https://orcid.org/0000-0002-3795-4436","contributorId":1470,"corporation":false,"usgs":true,"family":"Kosovich","given":"John","email":"jjkosovich@usgs.gov","middleInitial":"J.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true}],"preferred":true,"id":301038,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":97100,"text":"sim3049 - 2008 - State of Louisiana - Highlighting low-lying areas derived from USGS Digital Elevation Data","interactions":[],"lastModifiedDate":"2017-03-29T11:01:42","indexId":"sim3049","displayToPublicDate":"2008-11-27T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3049","title":"State of Louisiana - Highlighting low-lying areas derived from USGS Digital Elevation Data","docAbstract":"In support of U.S. Geological Survey (USGS) disaster preparedness efforts, this map depicts a color shaded relief representation highlighting the State of Louisiana and depicts the surrounding areas using muted elevation colors. The first 30 feet of relief above mean sea level are displayed as brightly colored 5-foot elevation bands, which highlight low-elevation areas at a coarse spatial resolution. Areas below sea level typically are surrounded by levees or some other type of flood-control structures. Standard USGS National Elevation Dataset (NED) 1 arc-second (nominally 30-meter) digital elevation model (DEM) data are the basis for the map, which is designed to be used at a broad scale and for informational purposes only.\r\n\r\nThe NED data are a mixture of data and were derived from the original 1:24,000-scale USGS topographic map bare-earth contours, which were converted into gridded quadrangle-based DEM tiles at a constant post spacing (grid cell size) of either 30 meters (data before the mid-1990s) or 10 meters (mid-1990s and later data). These individual-quadrangle DEMs were then converted to spherical coordinates (latitude/longitude decimal degrees) and edge-matched to ensure seamlessness. Approximately one-half of the area shown on this map has DEM source data at a 30-meter resolution, with the remaining half consisting of mostly 10-meter contour-derived DEM data and some small areas of higher-resolution LIght Detection And Ranging (LIDAR) data along parts of the coastline.\r\n\r\nAreas below sea level typically are surrounded by levees or some other type of flood-control structures.\r\n\r\nState and parish boundary, hydrography, city, and road layers were modified from USGS National Atlas data downloaded in 2003. The NED data were downloaded in 2007.","language":"English","publisher":"U.S Geological Survey","doi":"10.3133/sim3049","usgsCitation":"Kosovich, J.J., 2008, State of Louisiana - Highlighting low-lying areas derived from USGS Digital Elevation Data (Version 1.0): U.S. Geological Survey Scientific Investigations Map 3049, Map Sheet: 40 x 33 inches; Downloads Directory, https://doi.org/10.3133/sim3049.","productDescription":"Map Sheet: 40 x 33 inches; Downloads Directory","additionalOnlineFiles":"Y","costCenters":[{"id":176,"text":"Central Region Geospatial Information Office","active":false,"usgs":true}],"links":[{"id":12081,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3049/","linkFileType":{"id":5,"text":"html"}},{"id":195042,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"scale":"700000","projection":"Albers Conic Equal Area","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.25,28.916666666666668 ], [ -94.25,33.083333333333336 ], [ -88.5,33.083333333333336 ], [ -88.5,28.916666666666668 ], [ -94.25,28.916666666666668 ] ] ] } } ] }","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4adbe4b07f02db685a84","contributors":{"authors":[{"text":"Kosovich, John J. 0000-0002-3795-4436 jjkosovich@usgs.gov","orcid":"https://orcid.org/0000-0002-3795-4436","contributorId":1470,"corporation":false,"usgs":true,"family":"Kosovich","given":"John","email":"jjkosovich@usgs.gov","middleInitial":"J.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true}],"preferred":true,"id":301040,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":97101,"text":"sim3050 - 2008 - State of Texas - Highlighting low-lying areas derived from USGS Digital Elevation Data","interactions":[],"lastModifiedDate":"2017-03-29T11:00:50","indexId":"sim3050","displayToPublicDate":"2008-11-27T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3050","title":"State of Texas - Highlighting low-lying areas derived from USGS Digital Elevation Data","docAbstract":"In support of U.S. Geological Survey (USGS) disaster preparedness efforts, this map depicts a color shaded relief representation of Texas and a grayscale relief of the surrounding areas. The first 30 feet of relief above mean sea level are displayed as brightly colored 5-foot elevation bands, which highlight low-elevation areas at a coarse spatial resolution. Standard USGS National Elevation Dataset (NED) 1 arc-second (nominally 30-meter) digital elevation model (DEM) data are the basis for the map, which is designed to be used at a broad scale and for informational purposes only.\r\n\r\nThe NED data were derived from the original 1:24,000-scale USGS topographic map bare-earth contours, which were converted into gridded quadrangle-based DEM tiles at a constant post spacing (grid cell size) of either 30 meters (data before the mid-1990s) or 10 meters (mid-1990s and later data). These individual-quadrangle DEMs were then converted to spherical coordinates (latitude/longitude decimal degrees) and edge-matched to ensure seamlessness. The NED source data for this map consists of a mixture of 30-meter- and 10-meter-resolution DEMs.\r\n\r\nState and county boundary, hydrography, city, and road layers were modified from USGS National Atlas data downloaded in 2003. The NED data were downloaded in 2002. Shaded relief over Mexico was obtained from the USGS National Atlas.\r\n","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sim3050","usgsCitation":"Kosovich, J.J., 2008, State of Texas - Highlighting low-lying areas derived from USGS Digital Elevation Data (Version 1.0): U.S. Geological Survey Scientific Investigations Map 3050, Map Sheet: 39 x 35 inches; Downloads Directory, https://doi.org/10.3133/sim3050.","productDescription":"Map Sheet: 39 x 35 inches; Downloads Directory","additionalOnlineFiles":"Y","costCenters":[{"id":176,"text":"Central Region Geospatial Information Office","active":false,"usgs":true}],"links":[{"id":195552,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":12082,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3050/","linkFileType":{"id":5,"text":"html"}}],"scale":"700000","projection":"Albers Conic Equal Area","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -107.5,25.5 ], [ -107.5,36.5 ], [ -92.75,36.5 ], [ -92.75,25.5 ], [ -107.5,25.5 ] ] ] } } ] }","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4adbe4b07f02db685a87","contributors":{"authors":[{"text":"Kosovich, John J. 0000-0002-3795-4436 jjkosovich@usgs.gov","orcid":"https://orcid.org/0000-0002-3795-4436","contributorId":1470,"corporation":false,"usgs":true,"family":"Kosovich","given":"John","email":"jjkosovich@usgs.gov","middleInitial":"J.","affiliations":[{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true},{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":301041,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":97103,"text":"ds382 - 2008 - Radionuclide Data and Calculations and Loss-On-Ignition, X-Ray Fluorescence, and ICP-AES Data from Cores in Catchments of the Animas River, Colorado","interactions":[],"lastModifiedDate":"2012-02-02T00:15:05","indexId":"ds382","displayToPublicDate":"2008-11-27T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"382","title":"Radionuclide Data and Calculations and Loss-On-Ignition, X-Ray Fluorescence, and ICP-AES Data from Cores in Catchments of the Animas River, Colorado","docAbstract":"The U.S. Departments of Agriculture and Interior Abandoned Mine Lands (AML) Initiative is focused on the evaluation of the effect of past mining practices on the water quality and the riparian and aquatic habitats of impacted stream reaches downstream from historical mining districts located primarily on Federal lands. This problem is manifest in the eleven western states (west of longitude 102 degrees) where the majority of hardrock mines that had past production are located on Federal lands. In areas of temperate climate and moderate to heavy precipitation, the effects of rapid chemical and physical weathering of sulfides exposed on mine-waste dumps and acidic drainage from mines have resulted in elevated metal concentrations in the stream water and stream-bed sediment. The result of these mineral weathering processes has an unquantified impact on the quality of the water and the aquatic and riparian habitats that may limit their recreational resource value. One of the confounding factors in these studies is the determination of the component of metals derived from hydrothermally altered but unmined portions of these drainage basins. \r\n\r\nSeveral watersheds have been studied to evaluate the effects of acid mine drainage and acid rock drainage on the near-surface environment. The Animas River watershed in southwestern Colorado contains a large number of past-producing metal mines that have affected the watershed. Beginning in October 1996, the U.S. Geological Survey (USGS) began a collaborative study of these effects under the USGS-AML Initiative. In this report, we present the radionuclide and geochemical analytical results of sediment coring during 1997-1999 from two cores from oxbow lakes 0.5 mi. upstream from the 32nd Street Bridge near Durango, Colo., and from three cores from beaver ponds within the Mineral Creek drainage basin near Silverton, Colo.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/ds382","usgsCitation":"Church, S.E., Rice, C.A., and Marot, M.E., 2008, Radionuclide Data and Calculations and Loss-On-Ignition, X-Ray Fluorescence, and ICP-AES Data from Cores in Catchments of the Animas River, Colorado (Version 1.0): U.S. Geological Survey Data Series 382, Report: iv, 20 p.; Tables, https://doi.org/10.3133/ds382.","productDescription":"Report: iv, 20 p.; Tables","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":169,"text":"Central Mineral Resources Team","active":false,"usgs":true}],"links":[{"id":198371,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":12084,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/382/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a80e4b07f02db649af7","contributors":{"authors":[{"text":"Church, Stan E. schurch@usgs.gov","contributorId":803,"corporation":false,"usgs":true,"family":"Church","given":"Stan","email":"schurch@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":false,"id":301043,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rice, Cyndi A.","contributorId":31080,"corporation":false,"usgs":true,"family":"Rice","given":"Cyndi","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":301045,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marot, Marci E. 0000-0003-0504-315X mmarot@usgs.gov","orcid":"https://orcid.org/0000-0003-0504-315X","contributorId":2078,"corporation":false,"usgs":true,"family":"Marot","given":"Marci","email":"mmarot@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":301044,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":97105,"text":"ofr20081331 - 2008 - The U.S. Geological Survey Modular Ground-Water Model - PCGN: A Preconditioned Conjugate Gradient Solver with Improved Nonlinear Control","interactions":[],"lastModifiedDate":"2012-02-02T00:14:28","indexId":"ofr20081331","displayToPublicDate":"2008-11-27T00:00:00","publicationYear":"2008","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":"2008-1331","title":"The U.S. Geological Survey Modular Ground-Water Model - PCGN: A Preconditioned Conjugate Gradient Solver with Improved Nonlinear Control","docAbstract":"The preconditioned conjugate gradient with improved nonlinear control (PCGN) package provides addi-tional means by which the solution of nonlinear ground-water flow problems can be controlled as compared to existing solver packages for MODFLOW. Picard iteration is used to solve nonlinear ground-water flow equations by iteratively solving a linear approximation of the nonlinear equations. The linear solution is provided by means of the preconditioned conjugate gradient algorithm where preconditioning is provided by the modi-fied incomplete Cholesky algorithm. The incomplete Cholesky scheme incorporates two levels of fill, 0 and 1, in which the pivots can be modified so that the row sums of the preconditioning matrix and the original matrix are approximately equal. A relaxation factor is used to implement the modified pivots, which determines the degree of modification allowed. The effects of fill level and degree of pivot modification are briefly explored by means of a synthetic, heterogeneous finite-difference matrix; results are reported in the final section of this report. The preconditioned conjugate gradient method is coupled with Picard iteration so as to efficiently solve the nonlinear equations associated with many ground-water flow problems. The description of this coupling of the linear solver with Picard iteration is a primary concern of this document.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/ofr20081331","usgsCitation":"Naff, R.L., and Banta, E., 2008, The U.S. Geological Survey Modular Ground-Water Model - PCGN: A Preconditioned Conjugate Gradient Solver with Improved Nonlinear Control (Version 1.0): U.S. Geological Survey Open-File Report 2008-1331, vi, 35 p., https://doi.org/10.3133/ofr20081331.","productDescription":"vi, 35 p.","onlineOnly":"Y","costCenters":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true}],"links":[{"id":195071,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":12086,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2008/1331/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4abce4b07f02db67321b","contributors":{"authors":[{"text":"Naff, Richard L.","contributorId":79867,"corporation":false,"usgs":true,"family":"Naff","given":"Richard","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":301050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Banta, Edward R.","contributorId":49820,"corporation":false,"usgs":true,"family":"Banta","given":"Edward R.","affiliations":[],"preferred":false,"id":301049,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":97112,"text":"sir20085196 - 2008 - Comparison of the modified Biot-Gassmann theory and the Kuster-Toksöz theory in predicting elastic velocities of sediments","interactions":[],"lastModifiedDate":"2018-08-28T15:54:39","indexId":"sir20085196","displayToPublicDate":"2008-11-27T00:00:00","publicationYear":"2008","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":"2008-5196","title":"Comparison of the modified Biot-Gassmann theory and the Kuster-Toksöz theory in predicting elastic velocities of sediments","docAbstract":"Elastic velocities of water-saturated sandstones depend primarily on porosity, effective pressure, and the degree of consolidation. If the dry-frame moduli are known, from either measurements or theoretical calculations, the effect of pore water on velocities can be modeled using the Gassmann theory. Kuster and Toksoz developed a theory based on wave-scattering theory for a variety of inclusion shapes, which provides a means for calculating dry- or wet-frame moduli. In the Kuster-Toksoz theory, elastic wave velocities through different sediments can be predicted by using different aspect ratios of the sediment's pore space. Elastic velocities increase as the pore aspect ratio increases (larger pore aspect ratio describes a more spherical pore). On the basis of the velocity ratio, which is assumed to be a function of (1-0)n, and the Biot-Gassmann theory, Lee developed a semi-empirical equation for predicting elastic velocities, which is referred to as the modified Biot-Gassmann theory of Lee. In this formulation, the exponent n, which depends on the effective pressure and the degree of consolidation, controls elastic velocities; as n increases, elastic velocities decrease. Computationally, the role of exponent n in the modified Biot-Gassmann theory by Lee is similar to the role of pore aspect ratios in the Kuster-Toksoz theory. For consolidated sediments, either theory predicts accurate velocities. However, for unconsolidated sediments, the modified Biot-Gassmann theory by Lee performs better than the Kuster-Toksoz theory, particularly in predicting S-wave velocities.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20085196","usgsCitation":"Lee, M.W., 2008, Comparison of the modified Biot-Gassmann theory and the Kuster-Toksöz theory in predicting elastic velocities of sediments (Version 1.0): U.S. Geological Survey Scientific Investigations Report 2008-5196, iv, 14 p., https://doi.org/10.3133/sir20085196.","productDescription":"iv, 14 p.","onlineOnly":"Y","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":125655,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2008_5196.jpg"},{"id":356873,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2008/5196/pdf/SIR08-5196_508.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":12094,"rank":100,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2008/5196/","text":"Index Page","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b24e4b07f02db6ae656","contributors":{"authors":[{"text":"Lee, Myung W. mlee@usgs.gov","contributorId":779,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","email":"mlee@usgs.gov","middleInitial":"W.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":301073,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":97094,"text":"ofr20081340 - 2008 - Incorporation of Fine-Grained Sediment Erodibility Measurements into Sediment Transport Modeling, Capitol Lake, Washington","interactions":[],"lastModifiedDate":"2012-02-10T00:11:55","indexId":"ofr20081340","displayToPublicDate":"2008-11-20T00:00:00","publicationYear":"2008","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":"2008-1340","title":"Incorporation of Fine-Grained Sediment Erodibility Measurements into Sediment Transport Modeling, Capitol Lake, Washington","docAbstract":"Capitol Lake was created in 1951 with the construction of a concrete dam and control gate that prevented salt-water intrusion into the newly formed lake and regulated flow of the Deschutes River into southern Puget Sound. Physical processes associated with the former tidally dominated estuary were altered, and the dam structure itself likely caused an increase in retention of sediment flowing into the lake from the Deschutes River. Several efforts to manage sediment accumulation in the lake, including dredging and the construction of sediment traps upriver, failed to stop the lake from filling with sediment. The Deschutes Estuary Feasibility Study (DEFS) was carried out to evaluate the possibility of removing the dam and restoring estuarine processes as an alternative ongoing lake management. \r\n\r\nAn important component of DEFS was the creation of a hydrodynamic and sediment transport model of the restored Deschutes Estuary. Results from model simulations indicated that estuarine processes would be restored under each of four restoration alternatives, and that over time, the restored estuary would have morphological features similar to the predam estuary. The model also predicted that after dam-removal, a large portion of the sediment eroded from the lake bottom would be deposited near the Port of Olympia and a marina located in lower Budd Inlet seaward of the present dam. The volume of sediment transported downstream was a critical piece of information that managers needed to estimate the total cost of the proposed restoration project. However, the ability of the model to predict the magnitude of sediment transport in general and, in particular, the volume of sediment deposition in the port and marina was limited by a lack of information on the erodibility of fine-grained sediments in Capitol Lake. \r\n\r\nCores at several sites throughout Capitol Lake were collected between October 31 and November 1, 2007. The erodibility of sediments in the cores was later determined in the lab with Sedflume, an apparatus for measuring sediment erosion-parameters. In this report, we present results of the characterization of fine-grained sediment erodibility within Capitol Lake. The erodibility data were incorporated into the previously developed hydrodynamic and sediment transport model. Model simulations using the measured erodibility parameters were conducted to provide more robust estimates of the overall magnitudes and spatial patterns of sediment transport resulting from restoration of the Deschutes Estuary.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/ofr20081340","usgsCitation":"Stevens, A., Gelfenbaum, G., Elias, E., and Jones, C., 2008, Incorporation of Fine-Grained Sediment Erodibility Measurements into Sediment Transport Modeling, Capitol Lake, Washington: U.S. Geological Survey Open-File Report 2008-1340, vi, 72 p., https://doi.org/10.3133/ofr20081340.","productDescription":"vi, 72 p.","onlineOnly":"Y","temporalStart":"2007-10-31","temporalEnd":"2007-11-01","costCenters":[{"id":645,"text":"Western Coastal and Marine Geology","active":false,"usgs":true}],"links":[{"id":195906,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":12075,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2008/1340/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123,47 ], [ -123,47.15 ], [ -122.8,47.15 ], [ -122.8,47 ], [ -123,47 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac8e4b07f02db67c0e0","contributors":{"authors":[{"text":"Stevens, Andrew W.","contributorId":89093,"corporation":false,"usgs":true,"family":"Stevens","given":"Andrew W.","affiliations":[],"preferred":false,"id":301029,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gelfenbaum, Guy","contributorId":79844,"corporation":false,"usgs":true,"family":"Gelfenbaum","given":"Guy","affiliations":[],"preferred":false,"id":301028,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elias, Edwin","contributorId":50615,"corporation":false,"usgs":true,"family":"Elias","given":"Edwin","affiliations":[],"preferred":false,"id":301027,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Craig","contributorId":104173,"corporation":false,"usgs":true,"family":"Jones","given":"Craig","affiliations":[],"preferred":false,"id":301030,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":97095,"text":"sir20085207 - 2008 - Simulated effects of ground-water withdrawals and artificial recharge on discharge to streams, springs, and riparian vegetation in the Sierra Vista Subwatershed of the Upper San Pedro Basin, southeastern Arizona","interactions":[],"lastModifiedDate":"2014-04-24T13:26:41","indexId":"sir20085207","displayToPublicDate":"2008-11-20T00:00:00","publicationYear":"2008","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":"2008-5207","title":"Simulated effects of ground-water withdrawals and artificial recharge on discharge to streams, springs, and riparian vegetation in the Sierra Vista Subwatershed of the Upper San Pedro Basin, southeastern Arizona","docAbstract":"In the context of ground-water resources, “capture” or “streamflow depletion” refers to withdrawal-induced changes in inflow to or outflow from an aquifer. These concepts are helpful in understanding the effects of long-term development of ground-water resources. For the Upper San Pedro Basin in Arizona, USA and Sonora, Mexico, a recently developed ground-water flow model is available to help quantify capture of water from the river and riparian system. A common method of analysis is to compute curves of capture and aquifer-storage change for a range of time at select points of interest. This study, however, presents results of a method to show spatial distributions of total change in inflow and outflow from withdrawal or injection for select times of interest. The mapped areal distributions show the effect of a single well in terms of the ratio of the change in boundary flow rate to rate of withdrawal or injection by the well. To the extent that the system responds linearly to ground-water withdrawal or injection, fractional responses in the mapped distributions can be used to quantify response for any withdrawal or injection rate. Capture distributions calculated using the Upper San Pedro model include response to (1) withdrawal in the lower basin-fill aquifer for times of 10 and 50 years following the initiation of pumping from predevelopment conditions and (2) artificial recharge to the water table in the area underlain by the lower basin-fill aquifer after 10 and 50 years. The mapped distributions show that response to withdrawals and injections is greatest near the river/riparian system. Presence of clay layers in the vertical interval between withdrawal locations and the river/riparian system, however, can delay the response.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20085207","collaboration":"Prepared in cooperation with the Upper San Pedro Partnership","usgsCitation":"Leake, S.A., Pool, D.R., and Leenhouts, J.M., 2008, Simulated effects of ground-water withdrawals and artificial recharge on discharge to streams, springs, and riparian vegetation in the Sierra Vista Subwatershed of the Upper San Pedro Basin, southeastern Arizona (Version 1.0 November 18, 2008; Version 1.1 April 2014): U.S. Geological Survey Scientific Investigations Report 2008-5207, iv, 15 p., https://doi.org/10.3133/sir20085207.","productDescription":"iv, 15 p.","numberOfPages":"22","onlineOnly":"Y","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":195907,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20085207.jpg"},{"id":12076,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2008/5207/","linkFileType":{"id":5,"text":"html"}},{"id":286532,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2008/5207/sir2008-5207.pdf"}],"projection":"Universal Transverse Mercator projection","country":"Mexico;United States","state":"Arizona;Sonora","otherGeospatial":"Upper San Pedro Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -110.6,30.9 ], [ -110.6,31.9 ], [ -109.0,31.9 ], [ -109.0,30.9 ], [ -110.6,30.9 ] ] ] } } ] }","edition":"Version 1.0 November 18, 2008; Version 1.1 April 2014","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4adee4b07f02db687297","contributors":{"authors":[{"text":"Leake, Stanley A. 0000-0003-3568-2542 saleake@usgs.gov","orcid":"https://orcid.org/0000-0003-3568-2542","contributorId":1846,"corporation":false,"usgs":true,"family":"Leake","given":"Stanley","email":"saleake@usgs.gov","middleInitial":"A.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":301033,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pool, Donald R. drpool@usgs.gov","contributorId":1121,"corporation":false,"usgs":true,"family":"Pool","given":"Donald","email":"drpool@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":301032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leenhouts, James M. 0000-0001-5171-9240 leenhout@usgs.gov","orcid":"https://orcid.org/0000-0001-5171-9240","contributorId":225,"corporation":false,"usgs":true,"family":"Leenhouts","given":"James","email":"leenhout@usgs.gov","middleInitial":"M.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":301031,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70236296,"text":"70236296 - 2008 - Boreal soil carbon dynamics under a changing climate: A model inversion approach","interactions":[],"lastModifiedDate":"2022-08-31T16:55:13.288911","indexId":"70236296","displayToPublicDate":"2008-11-15T11:49:39","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7359,"text":"Journal of Geophysical Research Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Boreal soil carbon dynamics under a changing climate: A model inversion approach","docAbstract":"Several fundamental but important factors controlling the feedback of boreal organic carbon (OC) to climate change were examined using a mechanistic model of soil OC dynamics, including the combined effects of temperature and moisture on the decomposition of OC and the factors controlling carbon quality and decomposition with depth. To estimate decomposition rates and evaluate their variations with depth, the model was inverted using a global optimization algorithm. Three sites with different drainage conditions that represent a broad diversity of boreal black spruce ecosystems were modeled. The comparison among the models with different depth patterns of decomposition rates (i.e., constant, linear, and exponential decrease) revealed that the model with constant inherent decomposition rates through the soil profile was able to fit the observed data in the most efficient way. There were also lower turnover times in the wettest site compared to the drier site even after accounting for moisture and temperature differences. Taken together, these results indicate that decomposition (especially for the wetter site) was not accurately represented with standard moisture and temperature controls and that other important protection mechanisms (e.g., limitation of O2, redox conditions, and permafrost) rather than low inherent decomposition rates are responsible for the recalcitrance of deep OC. The simulation results also showed that most of the soil CO2 efflux is generated from subsurface layers of OC because of the large OC stocks and optimal moisture conditions, suggesting that these deeper soil OC stocks are likely to be critically important to the future carbon dynamics.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2008JG000723","usgsCitation":"Fan, Z., Neff, J.C., Harden, J.W., and Wickland, K.P., 2008, Boreal soil carbon dynamics under a changing climate: A model inversion approach: Journal of Geophysical Research Biogeosciences, v. 113, no. G4, G04016, 13 p., https://doi.org/10.1029/2008JG000723.","productDescription":"G04016, 13 p.","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":476587,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2008jg000723","text":"Publisher Index Page"},{"id":406008,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"113","issue":"G4","noUsgsAuthors":false,"publicationDate":"2008-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Fan, Zhaosheng","contributorId":83410,"corporation":false,"usgs":true,"family":"Fan","given":"Zhaosheng","affiliations":[],"preferred":false,"id":850503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neff, Jason C.","contributorId":34813,"corporation":false,"usgs":true,"family":"Neff","given":"Jason","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":850504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harden, Jennifer W. 0000-0002-6570-8259 jharden@usgs.gov","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":1971,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","email":"jharden@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":850505,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wickland, Kimberly P. 0000-0002-6400-0590 kpwick@usgs.gov","orcid":"https://orcid.org/0000-0002-6400-0590","contributorId":1835,"corporation":false,"usgs":true,"family":"Wickland","given":"Kimberly","email":"kpwick@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":850506,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":97091,"text":"ofr20081345 - 2008 - Release of Hexavalent Chromium by Ash and Soils in Wildfire-Impacted Areas","interactions":[],"lastModifiedDate":"2012-02-10T00:11:55","indexId":"ofr20081345","displayToPublicDate":"2008-11-15T00:00:00","publicationYear":"2008","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":"2008-1345","title":"Release of Hexavalent Chromium by Ash and Soils in Wildfire-Impacted Areas","docAbstract":"The highly oxidizing environment of a wildfire has the potential to convert any chromium present in the soil or in residential or industrial debris to its more toxic form, hexavalent chromium, a known carcinogen. In addition, the highly basic conditions resulting from the combustion of wood and wood products could result in the stabilization of any aqueous hexavalent chromium formed.\r\n\r\nSamples were collected from the October 2007 wildfires in Southern California and subjected to an array of test procedures to evaluate the potential effects of fire-impacted soils and ashes on human and environmental health. Soil and ash samples were leached using de-ionized water to simulate conditions resulting from rainfall on fire-impacted areas. The resulting leachates were of high pH (10-13) and many, particularly those of ash from burned residential areas, contained elevated total chromium as much as 33 micrograms per liter. Samples were also leached using a near-neutral pH simulated lung fluid to model potential chemical interactions of inhaled particles with fluids lining the respiratory tract.\r\n\r\nHigh Performance Liquid Chromatography coupled to Inductively Coupled Plasma Mass Spectrometry was used to separate and detect individual species (for example, Cr+3, Cr+6, As+3, As+5, Se+4, and Se+6). These procedures were used to determine the form of the chromium present in the de-ionized water and simulated lung fluid leachates.\r\n\r\nThe results show that in the de-ionized water leachate, all of the chromium present is in the form of Cr+6, and the resulting high pH tends to stabilize Cr+6 from reduction to Cr+3. Analysis of the simulated lung fluid leachates indicates that the predominant form of chromium present in the near-neutral pH of lung fluid would be Cr+6, which is of concern due to the high possibility of inhalation of the small ash and soil particulates, particularly by fire or restoration crews.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/ofr20081345","usgsCitation":"Wolf, R.E., Morman, S.A., Plumlee, G.S., Hageman, P.L., and Adams, M., 2008, Release of Hexavalent Chromium by Ash and Soils in Wildfire-Impacted Areas (Version 1.0): U.S. Geological Survey Open-File Report 2008-1345, 22 p., https://doi.org/10.3133/ofr20081345.","productDescription":"22 p.","onlineOnly":"Y","temporalStart":"2007-10-01","temporalEnd":"2007-10-31","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":195852,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":12068,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2008/1345/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.5,32 ], [ -119.5,35 ], [ -116,35 ], [ -116,32 ], [ -119.5,32 ] ] ] } } ] }","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac8e4b07f02db67c10a","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":301018,"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":301020,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":301019,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":301017,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adams, Monique madams@usgs.gov","contributorId":1231,"corporation":false,"usgs":true,"family":"Adams","given":"Monique","email":"madams@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":301021,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":97078,"text":"sir20085175 - 2008 - Assessing gas-hydrate prospects on the North Slope of Alaska—Theoretical considerations","interactions":[],"lastModifiedDate":"2018-08-28T15:55:39","indexId":"sir20085175","displayToPublicDate":"2008-11-08T00:00:00","publicationYear":"2008","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":"2008-5175","title":"Assessing gas-hydrate prospects on the North Slope of Alaska—Theoretical considerations","docAbstract":"Gas-hydrate resource assessment on the Alaska North Slope using 3-D and 2-D seismic data involved six important steps: (1) determining the top and base of the gas-hydrate stability zone, (2) 'tying' well log information to seismic data through synthetic seismograms, (3) differentiating ice from gas hydrate in the permafrost interval, (4) developing an acoustic model for the reservoir and seal, (5) developing a method to estimate gas-hydrate saturation and thickness from seismic attributes, and (6) assessing the potential gas-hydrate prospects from seismic data based on potential migration pathways, source, reservoir quality, and other relevant geological information. This report describes the first five steps in detail using well logs and provides theoretical backgrounds for resource assessments carried out by the U.S. Geological Survey.\r\n\r\nMeasured and predicted P-wave velocities enabled us to tie synthetic seismograms to the seismic data. The calculated gas-hydrate stability zone from subsurface wellbore temperature data enabled us to focus our effort on the most promising depth intervals in the seismic data. A typical reservoir in this area is characterized by the P-wave velocity of 1.88 km/s, porosity of 42 percent, and clay volume content of 5 percent, whereas seal sediments encasing the reservoir are characterized by the P-wave velocity of 2.2 km/s, porosity of 32 percent, and clay volume content of 20 percent. Because the impedance of a reservoir without gas hydrate is less than that of the seal, a complex amplitude variation with respect to gas-hydrate saturation is predicted, namely polarity change, amplitude blanking, and high seismic amplitude (a bright spot). This amplitude variation with gas-hydrate saturation is the physical basis for the method used to quantify the resource potential of gas hydrates in this assessment.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20085175","usgsCitation":"Lee, M.W., Collett, T.S., and Agena, W.F., 2008, Assessing gas-hydrate prospects on the North Slope of Alaska—Theoretical considerations (Version 1.0): U.S. Geological Survey Scientific Investigations Report 2008-5175, iv, 28 p., https://doi.org/10.3133/sir20085175.","productDescription":"iv, 28 p.","onlineOnly":"Y","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":126874,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2008_5175.jpg"},{"id":356874,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2008/5175/pdf/SIR08-5175_508.pdf","text":"Report","size":"5.9 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":12055,"rank":100,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2008/5175/","text":"Index Page","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4abbe4b07f02db672ad1","contributors":{"authors":[{"text":"Lee, Myung W. mlee@usgs.gov","contributorId":779,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","email":"mlee@usgs.gov","middleInitial":"W.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":300973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":300974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Agena, Warren F. wagena@usgs.gov","contributorId":3181,"corporation":false,"usgs":true,"family":"Agena","given":"Warren","email":"wagena@usgs.gov","middleInitial":"F.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":300975,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":97077,"text":"sir20085194 - 2008 - Hydrologic Analysis and Two-Dimensional Simulation of Flow at State Highway 17 crossing the Gasconade River near Waynesville, Missouri","interactions":[],"lastModifiedDate":"2012-03-08T17:16:28","indexId":"sir20085194","displayToPublicDate":"2008-11-08T00:00:00","publicationYear":"2008","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":"2008-5194","title":"Hydrologic Analysis and Two-Dimensional Simulation of Flow at State Highway 17 crossing the Gasconade River near Waynesville, Missouri","docAbstract":"In cooperation with the Missouri Department of Transportation, the U.S. Geological Survey determined hydrologic and hydraulic parameters for the Gasconade River at the site of a proposed bridge replacement and highway realignment of State Highway 17 near Waynesville, Missouri. Information from a discontinued streamflow-gaging station on the Gasconade River near Waynesville was used to determine streamflow statistics for analysis of the 25-, 50-, 100-, and 500-year floods at the site. Analysis of the streamflow-gaging stations on the Gasconade River upstream and downstream from Waynesville indicate that flood peaks attenuate between the upstream gaging station near Hazelgreen and the Waynesville gaging station, such that the peak discharge observed on the Gasconade River near Waynesville will be equal to or only slightly greater (7 percent or less) than that observed near Hazelgreen.\r\n\r\nA flood event occurred on the Gasconade River in March 2008, and a flood measurement was obtained near the peak at State Highway 17. The elevation of high-water marks from that event indicated it was the highest measured flood on record with a measured discharge of 95,400 cubic feet per second, and a water-surface elevation of 766.18 feet near the location of the Waynesville gaging station. The measurements obtained for the March flood resulted in a shift of the original stage-discharge relation for the Waynesville gaging station, and the streamflow statistics were modified based on the new data.\r\n\r\nA two-dimensional hydrodynamic flow model was used to simulate flow conditions on the Gasconade River in the vicinity of State Highway 17. A model was developed that represents existing (2008) conditions on State Highway 17 (the 'model of existing conditions'), and was calibrated to the floods of March 20, 2008, December 4, 1982, and April 14, 1945. Modifications were made to the model of existing conditions to create a model that represents conditions along the same reach of the Gasconade River with preliminary proposed replacement bridges and realignment of State Highway 17 (the 'model of proposed conditions'). The models of existing and proposed conditions were used to simulate the 25-, 50-, 100-, and 500-year recurrence floods, as well as the March 20, 2008 flood.\r\n\r\nResults from the model of proposed conditions show that the proposed replacement structures and realignment of State Highway 17 will result in additional backwater upstream from State Highway 17 ranging from approximately 0.18 foot for the 25-year flood to 0.32 foot for the 500-year flood. Velocity magnitudes in the proposed overflow structures were greater than in the existing structures [by as much as 4.9 feet per second in the left (west) overflow structure for the 500-year flood], and shallow, high-velocity flow occurs at the upstream edges of the abutments of the proposed overflow structures in the 100- and 500-year floods where flow overtops parts of the existing road embankment that will be left in place in the proposed scenario. Velocity magnitude in the main channel of the model of proposed conditions increased by a maximum of 1.2 feet per second over the model of existing conditions, with the maximum occurring approximately 1,500 feet downstream from existing main channel structure J-802.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/sir20085194","collaboration":"Prepared in cooperation with the Missouri Department of Transportation","usgsCitation":"Huizinga, R.J., 2008, Hydrologic Analysis and Two-Dimensional Simulation of Flow at State Highway 17 crossing the Gasconade River near Waynesville, Missouri (Version 1.0): U.S. Geological Survey Scientific Investigations Report 2008-5194, viii, 42 p., https://doi.org/10.3133/sir20085194.","productDescription":"viii, 42 p.","temporalStart":"2008-03-20","temporalEnd":"2008-03-20","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":195062,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":12054,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2008/5194/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.28333333333333,37.81666666666667 ], [ -92.28333333333333,37.9 ], [ -92.18333333333334,37.9 ], [ -92.18333333333334,37.81666666666667 ], [ -92.28333333333333,37.81666666666667 ] ] ] } } ] }","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b15e4b07f02db6a4939","contributors":{"authors":[{"text":"Huizinga, Richard J. 0000-0002-2940-2324 huizinga@usgs.gov","orcid":"https://orcid.org/0000-0002-2940-2324","contributorId":2089,"corporation":false,"usgs":true,"family":"Huizinga","given":"Richard","email":"huizinga@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":300972,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}