Statistical models of nitrate occurrence in the glacial aquifer system of the northern United States, developed by the U.S. Geological Survey, use observed relations between nitrate concentrations and sets of explanatory variables—representing well-construction, environmental, and source characteristics— to predict the probability that nitrate, as nitrogen, will exceed a threshold concentration. However, the models do not explicitly account for the processes that control the transport of nitrogen from surface sources to a pumped well and use area-weighted mean spatial variables computed from within a circular buffer around the well as a simplified source-area conceptualization. The use of models that explicitly represent physical-transport processes can inform and, potentially, improve these statistical models. Specifically, groundwater-flow models simulate advective transport—predominant in many surficial aquifers— and can contribute to the refinement of the statistical models by (1) providing for improved, physically based representations of a source area to a well, and (2) allowing for more detailed estimates of environmental variables.
\nA source area to a well, known as a contributing recharge area, represents the area at the water table that contributes recharge to a pumped well; a well pumped at a volumetric rate equal to the amount of recharge through a circular buffer will result in a contributing recharge area that is the same size as the buffer but has a shape that is a function of the hydrologic setting. These volume-equivalent contributing recharge areas will approximate circular buffers in areas of relatively flat hydraulic gradients, such as near groundwater divides, but in areas with steep hydraulic gradients will be elongated in the upgradient direction and agree less with the corresponding circular buffers.
\nThe degree to which process-model-estimated contributing recharge areas, which simulate advective transport and therefore account for local hydrologic settings, would inform and improve the development of statistical models can be implicitly estimated by evaluating the differences between explanatory variables estimated from the contributing recharge areas and the circular buffers used to develop existing statistical models. The larger the difference in estimated variables, the more likely that statistical models would be changed, and presumably improved, if explanatory variables estimated from contributing recharge areas were used in model development. Comparing model predictions from the two sets of estimated variables would further quantify—albeit implicitly—how an improved, physically based estimate of explanatory variables would be reflected in model predictions. Differences between the two sets of estimated explanatory variables and resultant model predictions vary spatially; greater differences are associated with areas of steep hydraulic gradients. A direct comparison, however, would require the development of a separate set of statistical models using explanatory variables from contributing recharge areas.
\nArea-weighted means of three environmental variables—silt content, alfisol content, and depth to water from the U.S. Department of Agriculture State Soil Geographic (STATSGO) data—and one nitrogen-source variable (fertilizer-application rate from county data mapped to Enhanced National Land Cover Data 1992 (NLCDe 92) agricultural land use) can vary substantially between circular buffers and volume-equivalent contributing recharge areas and among contributing recharge areas for different sets of well variables. The differences in estimated explanatory variables are a function of the same factors affecting the contributing recharge areas as well as the spatial resolution and local distribution of the underlying spatial data. As a result, differences in estimated variables between circular buffers and contributing recharge areas are complex and site specific as evidenced by differences in estimated variables for circular buffers and contributing recharge areas of existing public-supply and network wells in the Great Miami River Basin. Large differences in areaweighted mean environmental variables are observed at the basin scale, determined by using the network of uniformly spaced hypothetical wells; the differences have a spatial pattern that generally is similar to spatial patterns in the underlying STATSGO data. Generally, the largest differences were observed for area-weighted nitrogen-application rate from county and national land-use data; the basin-scale differences ranged from -1,600 (indicating a larger value from within the volume-equivalent contributing recharge area) to 1,900 kilograms per year (kg/yr); the range in the underlying spatial data was from 0 to 2,200 kg/yr. Silt content, alfisol content, and nitrogen-application rate are defined by the underlying spatial data and are external to the groundwater system; however, depth to water is an environmental variable that can be estimated in more detail and, presumably, in a more physically based manner using a groundwater-flow model than using the spatial data. Model-calculated depths to water within circular buffers in the Great Miami River Basin differed substantially from values derived from the spatial data and had a much larger range.
\nDifferences in estimates of area-weighted spatial variables result in corresponding differences in predictions of nitrate occurrence in the aquifer. In addition to the factors affecting contributing recharge areas and estimated explanatory variables, differences in predictions also are a function of the specific set of explanatory variables used and the fitted slope coefficients in a given model. For models that predicted the probability of exceeding 1 and 4 milligrams per liter as nitrogen (mg/L as N), predicted probabilities using variables estimated from circular buffers and contributing recharge areas generally were correlated but differed significantly at the local and basin scale. The scale and distribution of prediction differences can be explained by the underlying differences in the estimated variables and the relative weight of the variables in the statistical models. Differences in predictions of exceeding 1 mg/L as N, which only includes environmental variables, generally correlated with the underlying differences in STATSGO data, whereas differences in exceeding 4 mg/L as N were more spatially extensive because that model included environmental and nitrogen-source variables. Using depths to water from within circular buffers derived from the spatial data and depths to water within the circular buffers calculated from the groundwater-flow model, restricted to the same range, resulted in large differences in predicted probabilities. The differences in estimated explanatory variables between contributing recharge areas and circular buffers indicate incorporation of physically based contributing recharge area likely would result in a different set of explanatory variables and an improved set of statistical models.
\nThe use of a groundwater-flow model to improve representations of source areas or to provide more-detailed estimates of specific explanatory variables includes a number of limitations and technical considerations. An assumption in these analyses is that (1) there is a state of mass balance between recharge and pumping, and (2) transport to a pumped well is under a steady state flow field. Comparison of volumeequivalent contributing recharge areas under steady-state and transient transport conditions at a location in the southeastern part of the basin shows the steady-state contributing recharge area is a reasonable approximation of the transient contributing recharge area after between 10 and 20 years of pumping. The first assumption is a more important consideration for this analysis. A gradient effect refers to a condition where simulated pumping from a well is less than recharge through the corresponding contributing recharge area. This generally takes place in areas with steep hydraulic gradients, such as near discharge locations, and can be mitigated using a finer model discretization. A boundary effect refers to a condition where recharge through the contributing recharge area is less than pumping. This indicates other sources of water to the simulated well and could reflect a real hydrologic process. In the Great Miami River Basin, large gradient and boundary effects—defined as the balance between pumping and recharge being less than half—occurred in 5 and 14 percent of the basin, respectively. The agreement between circular buffers and volume-equivalent contributing recharge areas, differences in estimated variables, and the effect on statisticalmodel predictions between the population of wells with a balance between pumping and recharge within 10 percent and the population of all wells were similar. This indicated process-model limitations did not affect the overall findings in the Great Miami River Basin; however, this would be model specific, and prudent use of a process model needs to entail a limitations analysis and, if necessary, alterations to the model.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125001","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Walter, D.A., and Starn, J.J., 2013, The use of process models to inform and improve statistical models of nitrate occurrence, Great Miami River Basin, southwestern Ohio: U.S. Geological Survey Scientific Investigations Report 2012-5001, x, 75 p., https://doi.org/10.3133/sir20125001.","productDescription":"x, 75 p.","numberOfPages":"90","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":377,"text":"Massachusetts-Rhode Island Water Science Center","active":false,"usgs":true}],"links":[{"id":272823,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125001.jpg"},{"id":272821,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5001/"},{"id":272822,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5001/pdf/sir2012-5001_report_508.pdf"}],"country":"United States","state":"Ohio","otherGeospatial":"Great Miami River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.82,38.4 ], [ -84.82,42.0 ], [ -80.52,42.0 ], [ -80.52,38.4 ], [ -84.82,38.4 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a4805fe4b064a995b7a0d0","contributors":{"authors":[{"text":"Walter, Donald A. 0000-0003-0879-4477 dawalter@usgs.gov","orcid":"https://orcid.org/0000-0003-0879-4477","contributorId":1101,"corporation":false,"usgs":true,"family":"Walter","given":"Donald","email":"dawalter@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478948,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Starn, J. Jeffrey","contributorId":101617,"corporation":false,"usgs":true,"family":"Starn","given":"J.","email":"","middleInitial":"Jeffrey","affiliations":[],"preferred":false,"id":478949,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046136,"text":"sim3252 - 2013 - Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado","interactions":[],"lastModifiedDate":"2013-05-28T14:30:22","indexId":"sim3252","displayToPublicDate":"2013-05-28T00:00:00","publicationYear":"2013","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":"3252","title":"Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado","docAbstract":"Multispectral satellite data acquired by the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) and Landsat 7 Enhanced Thematic Mapper Plus (TM) sensors are being used to populate an online Geographic Information System (GIS) of the spatial occurrence of mineral groups and green vegetation across the western conterminous United States and Alaska. These geospatial data are supporting U.S. Geological Survey national-scale mineral deposit database development and other mineral resource and geoenvironmental research as a means of characterizing mineral exposures related to mined and unmined hydrothermally altered rocks and mine waste.\n\nThis report introduces a new methodology for the automated analysis of Landsat TM data that has been applied to more than 180 scenes covering the western United States. A map of mineral groups and green vegetation produced using this new methodology that covers the western San Juan Mountains, Colorado, and the Four Corners Region is presented. The map is provided as a layered GeoPDF and in GIS-ready digital format. TM data analysis results from other well-studied and mineralogically characterized areas with strong hydrothermal alteration and (or) supergene weathering of near-surface sulfide minerals are also shown and compared with results derived from ASTER data analysis.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3252","usgsCitation":"Rockwell, B.W., 2013, Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado: U.S. Geological Survey Scientific Investigations Map 3252, iv, 25 p.; Map: 1 Sheet: 36 x 40 inches; Downloads Directory, https://doi.org/10.3133/sim3252.","productDescription":"iv, 25 p.; Map: 1 Sheet: 36 x 40 inches; Downloads Directory","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":272912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3252.gif"},{"id":272908,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3252/"},{"id":272909,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3252/downloads/pdfs/SIM3252_pamphlet.pdf"},{"id":272910,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3252/downloads/pdfs/SIM3252_map.pdf"},{"id":272911,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3252/downloads/"}],"country":"United States","state":"Colorado","otherGeospatial":"San Juan Mountains","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0,37.0 ], [ -109.0,41.0 ], [ -102.0,41.0 ], [ -102.0,37.0 ], [ -109.0,37.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a5c3e2e4b0605bc571ef5a","contributors":{"authors":[{"text":"Rockwell, Barnaby W. 0000-0002-9549-0617 barnabyr@usgs.gov","orcid":"https://orcid.org/0000-0002-9549-0617","contributorId":2195,"corporation":false,"usgs":true,"family":"Rockwell","given":"Barnaby","email":"barnabyr@usgs.gov","middleInitial":"W.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":479002,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70046129,"text":"ofr20131081 - 2013 - Final report for sea-level rise response modeling for San Francisco Bay estuary tidal marshes","interactions":[],"lastModifiedDate":"2017-10-30T12:19:43","indexId":"ofr20131081","displayToPublicDate":"2013-05-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1081","title":"Final report for sea-level rise response modeling for San Francisco Bay estuary tidal marshes","docAbstract":"The International Panel on Climate Change has identified coastal ecosystems as areas that will be disproportionally affected by climate change. Current sea-level rise projections range widely with 0.57 to 1.9 meters increase in mea sea level by 2100. The expected accelerated rate of sea-level rise through the 21st century will put many coastal ecosystems at risk, especially those in topographically low-gradient areas.\n\nWe assessed marsh accretion and plant community state changes through 2100 at 12 tidal salt marshes around San Francisco Bay estuary with a sea-level rise response model. Detailed ground elevation, vegetation, and water level data were collected at all sites between 2008 and 2011 and used as model inputs. Sediment cores (taken by Callaway and others, 2012) at four sites around San Francisco Bay estuary were used to estimate accretion rates. A modification of the Callaway and others (1996) model, the Wetland Accretion Rate Model for Ecosystem Resilience (WARMER), was utilized to run sea-level rise response models for all sites. With a mean sea level rise of 1.24 m by 2100, WARMER projected that the vast majority, 95.8 percent (1,942 hectares), of marsh area in our study will lose marsh plant communities by 2100 and to transition to a relative elevation range consistent with mudflat habitat. Three marshes were projected to maintain marsh vegetation to 2100, but they only composed 4.2 percent (85 hectares) of the total marsh area surveyed.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131081","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service","usgsCitation":"Takekawa, J.Y., Thorne, K.M., Buffington, K., Spragens, K., Swanson, K., Drexler, J., Schoellhamer, D., Overton, C.T., and Casazza, M.L., 2013, Final report for sea-level rise response modeling for San Francisco Bay estuary tidal marshes: U.S. Geological Survey Open-File Report 2013-1081, x, 161 p., https://doi.org/10.3133/ofr20131081.","productDescription":"x, 161 p.","numberOfPages":"171","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":272882,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131081.jpg"},{"id":272881,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1081/pdf/ofr20131081.pdf"},{"id":272880,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1081/"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.498478,37.447658 ], [ -122.498478,37.964872 ], [ -122.041878,37.964872 ], [ -122.041878,37.447658 ], [ -122.498478,37.447658 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a5c3e3e4b0605bc571ef5e","contributors":{"authors":[{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":478976,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thorne, Karen M. 0000-0002-1381-0657 kthorne@usgs.gov","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":4191,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen","email":"kthorne@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":478979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buffington, Kevin J. 0000-0001-9741-1241 kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":478980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spragens, Kyle A.","contributorId":98452,"corporation":false,"usgs":true,"family":"Spragens","given":"Kyle A.","affiliations":[],"preferred":false,"id":478983,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swanson, Kathleen M.","contributorId":11289,"corporation":false,"usgs":true,"family":"Swanson","given":"Kathleen M.","affiliations":[],"preferred":false,"id":478982,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drexler, Judith Z. 0000-0002-0127-3866","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":8941,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith Z.","affiliations":[],"preferred":false,"id":478981,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478975,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":478978,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":478977,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70046132,"text":"fs20133024 - 2013 - A conceptual hydrogeologic model for the hydrogeologic framework, geochemistry, and groundwater-flow system of the Edwards-Trinity and related aquifers in the Pecos County region, Texas","interactions":[],"lastModifiedDate":"2016-08-05T14:01:32","indexId":"fs20133024","displayToPublicDate":"2013-05-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3024","title":"A conceptual hydrogeologic model for the hydrogeologic framework, geochemistry, and groundwater-flow system of the Edwards-Trinity and related aquifers in the Pecos County region, Texas","docAbstract":"The Edwards-Trinity aquifer is a vital groundwater resource for agricultural, industrial, and municipal uses in the Trans-Pecos region of west Texas. A conceptual model of the hydrogeologic framework, geochemistry, and groundwater-flow system in the 4,700 square-mile study area was developed by the U.S. Geological Survey (USGS) in cooperation with the Middle Pecos Groundwater Conservation District, Pecos County, City of Fort Stockton, Brewster County, and Pecos County Water Control and Improvement District No. 1. The model was developed to gain a better understanding of the groundwater system and to establish a scientific foundation for resource-management decisions. Data and information were collected or obtained from various sources to develop the model. Lithologic information obtained from well reports and geophysical data were used to describe the hydrostratigraphy and structural features of the groundwater system, and aquifer-test data were used to estimate aquifer hydraulic properties. Groundwater-quality data were used to evaluate groundwater-flow paths, water and rock interaction, aquifer interaction, and the mixing of water from different sources. Groundwater-level data also were used to evaluate aquifer interaction as well as to develop a potentiometric-surface map, delineate regional groundwater divides, and describe regional groundwater-flow paths.
\nSeveral previous studies have been done to compile or collect physical and chemical data, describe the hydrogeologic processes, and develop conceptual and numerical groundwater-flow models of the Edwards-Trinity aquifer in the Trans-Pecos region. Documented methods were used to compile and collect groundwater, surface-water, geochemical, geophysical, and geologic information that subsequently were used to develop this conceptual model.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133024","collaboration":"Prepared in cooperation with the Middle Pecos Groundwater Conservation District, Pecos County, City of Fort Stockton, Brewster County, and Pecos County Water Control and Improvement District No. 1","usgsCitation":"Thomas, J.V., Stanton, G.P., Bumgarner, J.R., Pearson, D., Teeple, A., Houston, N.A., Payne, J., and Musgrove, M., 2013, A conceptual hydrogeologic model for the hydrogeologic framework, geochemistry, and groundwater-flow system of the Edwards-Trinity and related aquifers in the Pecos County region, Texas: U.S. Geological Survey Fact Sheet 2013-3024, 6 p., https://doi.org/10.3133/fs20133024.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":272903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133024.gif"},{"id":272902,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3024/pdf/fs2013-3024.pdf"},{"id":272901,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3024/"}],"projection":"Albers Equal Area","datum":"North American Datum of 1983","country":"United States","state":"Texas","county":"Pecos County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104,30.08 ], [ -104,31.30 ], [ -102,31.30 ], [ -102,30.08 ], [ -104,30.08 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a5c3d2e4b0605bc571ef52","contributors":{"authors":[{"text":"Thomas, Jonathan V. 0000-0003-0903-9713 jvthomas@usgs.gov","orcid":"https://orcid.org/0000-0003-0903-9713","contributorId":2194,"corporation":false,"usgs":true,"family":"Thomas","given":"Jonathan","email":"jvthomas@usgs.gov","middleInitial":"V.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478993,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanton, Gregory P. 0000-0001-8622-0933 gstanton@usgs.gov","orcid":"https://orcid.org/0000-0001-8622-0933","contributorId":1583,"corporation":false,"usgs":true,"family":"Stanton","given":"Gregory","email":"gstanton@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":478991,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bumgarner, Johnathan R. jbumgarner@usgs.gov","contributorId":5378,"corporation":false,"usgs":true,"family":"Bumgarner","given":"Johnathan","email":"jbumgarner@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":478994,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearson, Daniel K.","contributorId":52014,"corporation":false,"usgs":true,"family":"Pearson","given":"Daniel K.","affiliations":[],"preferred":false,"id":478996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Teeple, Andrew 0000-0003-1781-8354 apteeple@usgs.gov","orcid":"https://orcid.org/0000-0003-1781-8354","contributorId":1399,"corporation":false,"usgs":true,"family":"Teeple","given":"Andrew ","email":"apteeple@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":478990,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Houston, Natalie A. 0000-0002-6071-4545 nhouston@usgs.gov","orcid":"https://orcid.org/0000-0002-6071-4545","contributorId":1682,"corporation":false,"usgs":true,"family":"Houston","given":"Natalie","email":"nhouston@usgs.gov","middleInitial":"A.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478992,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":478989,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Musgrove, MaryLynn","contributorId":34878,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","affiliations":[],"preferred":false,"id":478995,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70046134,"text":"70046134 - 2013 - Marsh wrens as bioindicators of mercury in wetlands of Great Salt Lake: do blood and feathers reflect site-specific exposure risk to bird reproduction?","interactions":[],"lastModifiedDate":"2017-07-01T17:25:38","indexId":"70046134","displayToPublicDate":"2013-05-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Marsh wrens as bioindicators of mercury in wetlands of Great Salt Lake: do blood and feathers reflect site-specific exposure risk to bird reproduction?","docAbstract":"Nonlethal sampling of bird blood and feathers are among the more common ways of estimating the risk of mercury exposure to songbird reproduction. The implicit assumption is that mercury concentrations in blood or feathers of individuals captured in a given area are correlated with mercury concentrations in eggs from the same area. Yet, this assumption is rarely tested. We evaluated mercury concentrations in blood, feathers, and eggs of marsh wrens in wetlands of Great Salt Lake, Utah, and, at two spatial scales, specifically tested the assumption that mercury concentrations in blood and feather samples from birds captured in a defined area were predictive of mercury concentrations in eggs collected in the same area. Mercury concentrations in blood were not correlated with mercury concentrations in eggs collected within the same wetland unit, and were poorly correlated with mercury concentrations in eggs collected at the smaller home range spatial scale of analysis. Moreover, mercury exposure risk, as estimated via tissue concentrations, differed among wetland units depending upon whether blood or egg mercury concentrations were sampled. Mercury concentrations in feathers also were uncorrelated with mercury concentrations in eggs, and were poorly correlated with mercury concentrations in blood. These results demonstrate the potential for contrasting management actions that may be implemented based solely on the specific avian tissue that is sampled, and highlight the importance of developing avian tissues as biomonitoring tools for assessing local risk of mercury exposure to bird reproduction.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Science and Technology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ACS Publications","doi":"10.1021/es400910x","usgsCitation":"Hartman, C., Ackerman, J., Herring, G., Isanhart, J., and Herzog, M., 2013, Marsh wrens as bioindicators of mercury in wetlands of Great Salt Lake: do blood and feathers reflect site-specific exposure risk to bird reproduction?: Environmental Science & Technology, v. 47, no. 12, p. 6597-6605, https://doi.org/10.1021/es400910x.","productDescription":"9 p.","startPage":"6597","endPage":"6605","ipdsId":"IP-037566","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":272923,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es400910x"},{"id":272925,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.1395,40.6046 ], [ -113.1395,41.7094 ], [ -111.8671,41.7094 ], [ -111.8671,40.6046 ], [ -113.1395,40.6046 ] ] ] } } ] }","volume":"47","issue":"12","noUsgsAuthors":false,"publicationDate":"2013-05-21","publicationStatus":"PW","scienceBaseUri":"51a5c3e5e4b0605bc571ef6a","contributors":{"authors":[{"text":"Hartman, C. 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Like the Alaska Geochemical Database (AGDB, http://pubs.usgs.gov/ds/637/) before it, the AGDB2 was created and designed to compile and integrate geochemical data from Alaska in order to facilitate geologic mapping, petrologic studies, mineral resource assessments, definition of geochemical baseline values and statistics, environmental impact assessments, and studies in medical geology. This relational database, created from the Alaska Geochemical Database (AGDB) that was released in 2011, serves as a data archive in support of present and future Alaskan geologic and geochemical projects, and contains data tables in several different formats describing historical and new quantitative and qualitative geochemical analyses. The analytical results were determined by 85 laboratory and field analytical methods on 264,095 rock, sediment, soil, mineral and heavy-mineral concentrate samples. Most samples were collected by U.S. Geological Survey personnel and analyzed in U.S. Geological Survey laboratories or, under contracts, in commercial analytical laboratories. These data represent analyses of samples collected as part of various U.S. Geological Survey programs and projects from 1962 through 2009. In addition, mineralogical data from 18,138 nonmagnetic heavy-mineral concentrate samples are included in this database. The AGDB2 includes historical geochemical data originally archived in the U.S. Geological Survey Rock Analysis Storage System (RASS) database, used from the mid-1960s through the late 1980s and the U.S. Geological Survey PLUTO database used from the mid-1970s through the mid-1990s. All of these data are currently maintained in the National Geochemical Database (NGDB). Retrievals from the NGDB were used to generate most of the AGDB data set. These data were checked for accuracy regarding sample location, sample media type, and analytical methods used. This arduous process of reviewing, verifying and, where necessary, editing all U.S. Geological Survey geochemical data resulted in a significantly improved Alaska geochemical dataset. USGS data that were not previously in the NGDB because the data predate the earliest U.S. Geological Survey geochemical databases, or were once excluded for programmatic reasons, are included here in the AGDB2 and will be added to the NGDB. The AGDB2 data provided here are the most accurate and complete to date, and should be useful for a wide variety of geochemical studies. The AGDB2 data provided in the linked database may be updated or changed periodically.
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future","interactions":[],"lastModifiedDate":"2013-05-30T08:16:29","indexId":"70045974","displayToPublicDate":"2013-05-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":773,"text":"Animal Biotelemetry","active":true,"publicationSubtype":{"id":10}},"title":"Tracking animals in freshwater with electronic tags: past, present and future","docAbstract":"Considerable technical developments over the past half century have enabled widespread application of electronic tags to the study of animals in the wild, including in freshwater environments. We review the constraints associated with freshwater telemetry and biologging and the technical developments relevant to their use. Technical constraints for tracking animals are often influenced by the characteristics of the animals being studied and the environment they inhabit. Collectively, they influence which and how technologies can be used and their relative effectiveness. Although radio telemetry has historically been the most commonly used technology in freshwater, passive integrated transponder (PIT) technology, acoustic telemetry and biologgers are becoming more popular. Most telemetry studies have focused on fish, although an increasing number have focused on other taxa, such as turtles, crustaceans and molluscs. Key technical developments for freshwater systems include: miniaturization of tags for tracking small-size life stages and species, fixed stations and coded tags for tracking large samples of animals over long distances and large temporal scales, inexpensive PIT systems that enable mass tagging to yield population- and community-level relevant sample sizes, incorporation of sensors into electronic tags, validation of tag attachment procedures with a focus on maintaining animal welfare, incorporation of different techniques (for example, genetics, stable isotopes) and peripheral technologies (for example, geographic information systems, hydroacoustics), development of novel analytical techniques, and extensive international collaboration. Innovations are still needed in tag miniaturization, data analysis and visualization, and in tracking animals over larger spatial scales (for example, pelagic areas of lakes) and in challenging environments (for example, large dynamic floodplain systems, under ice). There seems to be a particular need for adapting various global positioning system and satellite tagging approaches to freshwater. Electronic tagging provides a mechanism to collect detailed information from imperilled animals and species that have no direct economic value. Current and future advances will continue to improve our knowledge of the natural history of aquatic animals and ecological processes in freshwater ecosystems while facilitating evidence-based resource management and conservation.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Animal Biotelemetry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1186/2050-3385-1-5","usgsCitation":"Cooke, S., Midwood, J.D., Thiem, J.D., Klimley, P., Lucas, M.C., Thorstad, E.B., Eiler, J., Holbrook, C., and Ebner, B.C., 2013, Tracking animals in freshwater with electronic tags: past, present and future: Animal Biotelemetry, v. 1, no. 5, 19 p., https://doi.org/10.1186/2050-3385-1-5.","productDescription":"19 p.","ipdsId":"IP-044813","costCenters":[{"id":332,"text":"Hammond Bay Biological Station","active":false,"usgs":true}],"links":[{"id":473812,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/2050-3385-1-5","text":"Publisher Index Page"},{"id":272997,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1186/2050-3385-1-5"},{"id":272998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"1","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a874ece4b082d85d5ed90e","contributors":{"authors":[{"text":"Cooke, Steven J.","contributorId":56132,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":36574,"text":"Carleton University, Ottawa, Ontario","active":true,"usgs":false}],"preferred":false,"id":478625,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Midwood, Jonathan D.","contributorId":74659,"corporation":false,"usgs":true,"family":"Midwood","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":478627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thiem, Jason D.","contributorId":75421,"corporation":false,"usgs":true,"family":"Thiem","given":"Jason","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":478628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klimley, Peter","contributorId":62507,"corporation":false,"usgs":true,"family":"Klimley","given":"Peter","email":"","affiliations":[],"preferred":false,"id":478626,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lucas, Martyn C.","contributorId":18725,"corporation":false,"usgs":true,"family":"Lucas","given":"Martyn","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":478623,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thorstad, Eva B.","contributorId":95367,"corporation":false,"usgs":true,"family":"Thorstad","given":"Eva","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":478630,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eiler, John","contributorId":34025,"corporation":false,"usgs":true,"family":"Eiler","given":"John","affiliations":[],"preferred":false,"id":478624,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Holbrook, Chris","contributorId":94194,"corporation":false,"usgs":true,"family":"Holbrook","given":"Chris","email":"","affiliations":[],"preferred":false,"id":478629,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ebner, Brendan C.","contributorId":9556,"corporation":false,"usgs":true,"family":"Ebner","given":"Brendan","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":478622,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70046089,"text":"70046089 - 2013 - Geomorphic characterization of the U.S. Atlantic continental margin","interactions":[],"lastModifiedDate":"2017-11-18T10:18:28","indexId":"70046089","displayToPublicDate":"2013-05-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphic characterization of the U.S. Atlantic continental margin","docAbstract":"The increasing volume of multibeam bathymetry data collected along continental margins is providing new opportunities to study the feedbacks between sedimentary and oceanographic processes and seafloor morphology. Attempts to develop simple guidelines that describe the relationships between form and process often overlook the importance of inherited physiography in slope depositional systems. Here, we use multibeam bathymetry data and seismic reflection profiles spanning the U.S. Atlantic outer continental shelf, slope and rise from Cape Hatteras to New England to quantify the broad-scale, across-margin morphological variation. Morphometric analyses suggest the margin can be divided into four basic categories that roughly align with Quaternary sedimentary provinces. Within each category, Quaternary sedimentary processes exerted heavy modification of submarine canyons, landslide complexes and the broad-scale morphology of the continental rise, but they appear to have preserved much of the pre-Quaternary, across-margin shape of the continental slope. Without detailed constraints on the substrate structure, first-order morphological categorization the U.S. Atlantic margin does not provide a reliable framework for predicting relationships between form and process.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2012.12.008","usgsCitation":"Brothers, D., ten Brink, U., Andrews, B., and Chaytor, J., 2013, Geomorphic characterization of the U.S. Atlantic continental margin: Marine Geology, v. 338, p. 46-63, https://doi.org/10.1016/j.margeo.2012.12.008.","productDescription":"18 p.","startPage":"46","endPage":"63","ipdsId":"IP-044529","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":473814,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/6124","text":"External Repository"},{"id":272777,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272776,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.margeo.2012.12.008"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.0,29.0 ], [ -80.0,45.0 ], [ -60.0,45.0 ], [ -60.0,29.0 ], [ -80.0,29.0 ] ] ] } } ] }","volume":"338","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a07dd7e4b0e4245580365c","chorus":{"doi":"10.1016/j.margeo.2012.12.008","url":"http://dx.doi.org/10.1016/j.margeo.2012.12.008","publisher":"Elsevier BV","authors":"Brothers Daniel S., ten Brink Uri S., Andrews Brian D., Chaytor Jason D.","journalName":"Marine Geology","publicationDate":"4/2013","auditedOn":"11/1/2014"},"contributors":{"authors":[{"text":"Brothers, Daniel S.","contributorId":72686,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel S.","affiliations":[],"preferred":false,"id":478881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"ten Brink, Uri S. 0000-0001-6858-3001 utenbrink@usgs.gov","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":127560,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri S.","email":"utenbrink@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":478882,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Andrews, Brian D.","contributorId":54180,"corporation":false,"usgs":true,"family":"Andrews","given":"Brian D.","affiliations":[],"preferred":false,"id":478880,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chaytor, Jason D.","contributorId":88637,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason D.","affiliations":[],"preferred":false,"id":478883,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70046090,"text":"ofr20131082 - 2013 - Implications of flume slope on discharge estimates from 0.762-meter H flumes used in edge-of-field monitoring","interactions":[],"lastModifiedDate":"2013-05-24T09:46:18","indexId":"ofr20131082","displayToPublicDate":"2013-05-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1082","title":"Implications of flume slope on discharge estimates from 0.762-meter H flumes used in edge-of-field monitoring","docAbstract":"The effects of longitudinal slope on the estimation of discharge in a 0.762-meter (m) (depth at flume entrance) H flume were tested under controlled conditions with slopes from −8 to +8 percent and discharges from 1.2 to 323 liters per second. Compared to the stage-discharge rating for a longitudinal flume slope of zero, computed discharges were negatively biased (maximum −31 percent) when the flume was sloped downward from the front (entrance) to the back (exit), and positively biased (maximum 44 percent) when the flume was sloped upward. Biases increased with greater flume slopes and with lower discharges. A linear empirical relation was developed to compute a corrected reference stage for a 0.762-m H flume using measured stage and flume slope. The reference stage was then used to determine a corrected discharge from the stage-discharge rating. A dimensionally homogeneous correction equation also was developed, which could theoretically be used for all standard H-flume sizes. Use of the corrected discharge computation method for a sloped H flume was determined to have errors ranging from −2.2 to 4.6 percent compared to the H-flume measured discharge at a level position. These results emphasize the importance of the measurement of and the correction for flume slope during an edge-of-field study if the most accurate discharge estimates are desired.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131082","collaboration":"Prepared in cooperation with the University of Wisconsin–Madison Discovery Farms program and the University of Wisconsin–Platteville Pioneer Farm program","usgsCitation":"Komiskey, M.J., Stuntebeck, T.D., Cox, A.L., and Frame, D.R., 2013, Implications of flume slope on discharge estimates from 0.762-meter H flumes used in edge-of-field monitoring: U.S. Geological Survey Open-File Report 2013-1082, iv, 11 p., https://doi.org/10.3133/ofr20131082.","productDescription":"iv, 11 p.","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":272774,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131082.jpg"},{"id":272772,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1082/"},{"id":272773,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1082/pdf/ofr2013-1082_web.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a07dd7e4b0e42455803668","contributors":{"authors":[{"text":"Komiskey, Matthew J. 0000-0003-2962-6974 mjkomisk@usgs.gov","orcid":"https://orcid.org/0000-0003-2962-6974","contributorId":1776,"corporation":false,"usgs":true,"family":"Komiskey","given":"Matthew","email":"mjkomisk@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478885,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stuntebeck, Todd D. 0000-0002-8405-7295 tdstunte@usgs.gov","orcid":"https://orcid.org/0000-0002-8405-7295","contributorId":902,"corporation":false,"usgs":true,"family":"Stuntebeck","given":"Todd","email":"tdstunte@usgs.gov","middleInitial":"D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cox, Amanda L.","contributorId":35220,"corporation":false,"usgs":true,"family":"Cox","given":"Amanda","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":478886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frame, Dennis R.","contributorId":77282,"corporation":false,"usgs":true,"family":"Frame","given":"Dennis","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":478887,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70046100,"text":"70046100 - 2013 - Holocene faulting in the Bellingham forearc basin: Upper-plate deformation at the northern end of the Cascadia subduction zone","interactions":[],"lastModifiedDate":"2023-06-05T15:23:19.416847","indexId":"70046100","displayToPublicDate":"2013-05-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Holocene faulting in the Bellingham forearc basin: Upper-plate deformation at the northern end of the Cascadia subduction zone","docAbstract":"The northern Cascadia forearc takes up most of the strain transmitted northward via the Oregon Coast block from the northward-migrating Sierra Nevada block. The north-south contractional strain in the forearc manifests in upper-plate faults active during the Holocene, the northern-most components of which are faults within the Bellingham Basin. The Bellingham Basin is the northern of four basins of the actively deforming northern Cascadia forearc. A set of Holocene faults, Drayton Harbor, Birch Bay, and Sandy Point faults, occur within the Bellingham Basin and can be traced from onshore to offshore using a combination of aeromagnetic lineaments, paleoseismic investigations and scarps identified using LiDAR imagery. With the recognition of such Holocene faults, the northernmost margin of the actively deforming Cascadia forearc extends 60 km north of the previously recognized limit of Holocene forearc deformation. Although to date no Holocene faults are recognized at the northern boundary of the Bellingham Basin, which is 15 km north of the international border, there is no compelling tectonic reason to expect that Holocene faults are limited to south of the international border.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2011JB008816","usgsCitation":"Kelsey, H.M., Sherrod, B.L., Blakely, R.J., and Haugerud, R.A., 2013, Holocene faulting in the Bellingham forearc basin: Upper-plate deformation at the northern end of the Cascadia subduction zone: Journal of Geophysical Research B: Solid Earth, v. 117, no. B3, B03409; 26 p., https://doi.org/10.1029/2011JB008816.","productDescription":"B03409; 26 p.","ipdsId":"IP-035190","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":473816,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011jb008816","text":"Publisher Index Page"},{"id":272808,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Bellingham Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.79,45.54 ], [ -124.79,49.0 ], [ -116.92,49.0 ], [ -116.92,45.54 ], [ -124.79,45.54 ] ] ] } } ] }","volume":"117","issue":"B3","noUsgsAuthors":false,"publicationDate":"2012-03-30","publicationStatus":"PW","scienceBaseUri":"51a07dd7e4b0e42455803664","contributors":{"authors":[{"text":"Kelsey, Harvey M.","contributorId":101713,"corporation":false,"usgs":true,"family":"Kelsey","given":"Harvey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":478915,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sherrod, Brian L.","contributorId":16874,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":478914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blakely, Richard J. 0000-0003-1701-5236 blakely@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-5236","contributorId":1540,"corporation":false,"usgs":true,"family":"Blakely","given":"Richard","email":"blakely@usgs.gov","middleInitial":"J.","affiliations":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":478912,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haugerud, Ralph A. 0000-0001-7302-4351 rhaugerud@usgs.gov","orcid":"https://orcid.org/0000-0001-7302-4351","contributorId":2691,"corporation":false,"usgs":true,"family":"Haugerud","given":"Ralph","email":"rhaugerud@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":478913,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}