{"pageNumber":"654","pageRowStart":"16325","pageSize":"25","recordCount":40804,"records":[{"id":70046016,"text":"sir20135038 - 2013 - Investigation of the structure and lithology of bedrock concealed by basin fill, using ground-based magnetic-field-profile data acquired in the San Rafael Basin, southeastern Arizona","interactions":[],"lastModifiedDate":"2023-06-05T15:24:39.969302","indexId":"sir20135038","displayToPublicDate":"2013-05-18T00:00:00","publicationYear":"2013","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":"2013-5038","title":"Investigation of the structure and lithology of bedrock concealed by basin fill, using ground-based magnetic-field-profile data acquired in the San Rafael Basin, southeastern Arizona","docAbstract":"Data on the Earth’s total-intensity magnetic field acquired near ground level and at measurement intervals as small as 1 m include information on the spatial distribution of nearsurface magnetic dipoles that in many cases are unique to a specific lithology. Such spatial information is expressed in the texture (physical appearance or characteristics) of the data at scales of hundreds of meters to kilometers. These magnetic textures are characterized by several descriptive statistics, their power spectrum, and their multifractal spectrum. On the basis of a graphical comparison and textural characterization, ground-based magnetic-field profile data can be used to estimate bedrock lithology concealed by as much as 100 m of basin fill in some cases, information that is especially important in assessing and exploring for concealed mineral deposits. I demonstrate that multifractal spectra of ground-based magnetic-field-profile data can be used to differentiate exposed lithologies and that the shape and position of the multifractal spectrum of the ground-based magnetic-field-profile of concealed lithologies can be matched to the upward-continued multifractal spectrum of an exposed lithology to help distinguish the concealed lithology.\n\nIn addition, ground-based magnetic-field-profile data also detect minute differences in the magnetic susceptibility of rocks over small horizontal and vertical distances and so can be used for precise modeling of bedrock geometry and structure, even when that bedrock is concealed by 100 m or more of nonmagnetic basin fill. Such data contain valuable geologic information on the bedrock concealed by basin fill that may not be so visible in aeromagnetic data, including areas of hydrothermal alteration, faults, and other bedrock structures. Interpretation of these data in the San Rafael Basin, southeastern Arizona, has yielded results for estimating concealed lithologies, concealed structural geology, and a concealed potential mineral-resource target.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135038","usgsCitation":"Bultman, M.W., 2013, Investigation of the structure and lithology of bedrock concealed by basin fill, using ground-based magnetic-field-profile data acquired in the San Rafael Basin, southeastern Arizona: U.S. Geological Survey Scientific Investigations Report 2013-5038, iv, 26 p., https://doi.org/10.3133/sir20135038.","productDescription":"iv, 26 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":272359,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135038.png"},{"id":272358,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5038/sir2013-5038.pdf"},{"id":272357,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5038/"}],"country":"United States","state":"Arizona","otherGeospatial":"San Rafael Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.82,31.33 ], [ -114.82,37.0 ], [ -109.0,37.0 ], [ -109.0,31.33 ], [ -114.82,31.33 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51989519e4b0eb382b44ac53","contributors":{"authors":[{"text":"Bultman, Mark W. 0000-0001-8352-101X mbultman@usgs.gov","orcid":"https://orcid.org/0000-0001-8352-101X","contributorId":3348,"corporation":false,"usgs":true,"family":"Bultman","given":"Mark","email":"mbultman@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":478698,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70046018,"text":"ds694 - 2013 - Bathymetric surveys of the Kootenai River near Bonners Ferry, Idaho, water year 2011","interactions":[],"lastModifiedDate":"2013-06-04T13:25:34","indexId":"ds694","displayToPublicDate":"2013-05-18T00:00:00","publicationYear":"2013","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":"694","title":"Bathymetric surveys of the Kootenai River near Bonners Ferry, Idaho, water year 2011","docAbstract":"In 2009, the Kootenai Tribe of Idaho released and implemented the Kootenai River Habitat Restoration Master Plan. This plan aimed to restore, enhance, and maintain the Kootenai River habitat and landscape to support and sustain habitat conditions for aquatic species and animal populations. In support of these restoration efforts, the U.S. Geological Survey, in cooperation with the Kootenai Tribe of Idaho, conducted high-resolution multibeam echosounder bathymetric surveys in May, June, and July 2011, as a baseline bathymetric monitoring survey on the Kootenai River near Bonners Ferry, Idaho. Three channel patterns or reaches exist in the study area—braided, meander, and a transitional zone connecting the braided and meander reaches. Bathymetric data were collected at three study areas in 2011 to provide: (1) surveys in unmapped portions of the meander reach; (2) monitoring of the presence and extent of sand along planned lines within a section of the meander reach; and (3) monitoring aggradation and degradation of the channel bed at specific cross sections within the braided reach and transitional zone. The bathymetric data will be used to update and verify flow models, calibrate and verify sediment transport modeling efforts, and aid in the biological assessment in support of the Kootenai River Habitat Restoration Master Plan. The data and planned lines for each study reach were produced in ASCII XYZ format supported by most geospatial software.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds694","collaboration":"Prepared in cooperation with the Kootenai Tribe of Idaho","usgsCitation":"Fosness, R.L., 2013, Bathymetric surveys of the Kootenai River near Bonners Ferry, Idaho, water year 2011: U.S. Geological Survey Data Series 694, iv, 26 p.; 6 Appendixes; 3 Metadata, https://doi.org/10.3133/ds694.","productDescription":"iv, 26 p.; 6 Appendixes; 3 Metadata","numberOfPages":"34","additionalOnlineFiles":"Y","temporalStart":"2010-10-01","temporalEnd":"2011-09-30","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":272377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds694.jpg"},{"id":272368,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/694/data/ds694_appendixA.xlsx"},{"id":272366,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/694/"},{"id":272367,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/694/pdf/ds694.pdf"},{"id":272369,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/694/data/ds694_appendixB.xlsx"},{"id":272370,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/694/data/ds694_appendixC.xlsx"},{"id":272371,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/694/data/ds694_appendixD.xlsx"},{"id":272372,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/694/data/ds694_appendixE.xlsx"},{"id":272373,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/694/data/ds694_appendixF.xlsx"},{"id":272374,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/lookup/getspatial?ds694_meander_reach_2011"},{"id":272375,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/lookup/getspatial?ds694_substrate_enhancement_2011"},{"id":272376,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/lookup/getspatial?ds694_braided_reach_2011"}],"country":"United States","state":"Idaho","otherGeospatial":"Kootenai River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.2,42.0 ], [ -117.2,49.0 ], [ -111.0,49.0 ], [ -111.0,42.0 ], [ -117.2,42.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"519894dbe4b0eb382b44ac4b","contributors":{"authors":[{"text":"Fosness, Ryan L. 0000-0003-4089-2704 rfosness@usgs.gov","orcid":"https://orcid.org/0000-0003-4089-2704","contributorId":2703,"corporation":false,"usgs":true,"family":"Fosness","given":"Ryan","email":"rfosness@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478706,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70046010,"text":"70046010 - 2013 - A global standard for monitoring coastal wetland vulnerability to accelerated sea-level rise","interactions":[],"lastModifiedDate":"2013-05-18T17:08:43","indexId":"70046010","displayToPublicDate":"2013-05-18T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"A global standard for monitoring coastal wetland vulnerability to accelerated sea-level rise","docAbstract":"Sea-level rise threatens coastal salt-marshes and mangrove forests around the world, and a key determinant of coastal wetland vulnerability is whether its surface elevation can keep pace with rising sea level. Globally, a large data gap exists because wetland surface and shallow subsurface processes remain unaccounted for by traditional vulnerability assessments using tide gauges. Moreover, those processes vary substantially across wetlands, so modelling platforms require relevant local data. The low-cost, simple, high-precision rod surface-elevation table–marker horizon (RSET-MH) method fills this critical data gap, can be paired with spatial data sets and modelling and is financially and technically accessible to every country with coastal wetlands. Yet, RSET deployment has been limited to a few regions and purposes. A coordinated expansion of monitoring efforts, including development of regional networks that could support data sharing and collaboration, is crucial to adequately inform coastal climate change adaptation policy at several scales.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Nature Climate Change","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Nature Publishing Group","doi":"10.1038/nclimate1756","usgsCitation":"Webb, E.L., Friess, D., Krauss, K.W., Cahoon, D.R., Guntenspergen, G.R., and Phelps, J., 2013, A global standard for monitoring coastal wetland vulnerability to accelerated sea-level rise: Nature Climate Change, v. 3, no. 5, p. 458-465, https://doi.org/10.1038/nclimate1756.","productDescription":"8 p.","startPage":"458","endPage":"465","ipdsId":"IP-031590","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":473822,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1038/nclimate1756","text":"External Repository"},{"id":272378,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272355,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1038/nclimate1756"}],"volume":"3","issue":"5","noUsgsAuthors":false,"publicationDate":"2013-04-25","publicationStatus":"PW","scienceBaseUri":"519894d3e4b0eb382b44ac43","contributors":{"authors":[{"text":"Webb, Edward L.","contributorId":22083,"corporation":false,"usgs":true,"family":"Webb","given":"Edward","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":478685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Friess, Daniel A.","contributorId":35454,"corporation":false,"usgs":false,"family":"Friess","given":"Daniel A.","affiliations":[{"id":25407,"text":"Department of Geography, National University of Singapore","active":true,"usgs":false}],"preferred":false,"id":478686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":478682,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cahoon, Donald R. 0000-0002-2591-5667 dcahoon@usgs.gov","orcid":"https://orcid.org/0000-0002-2591-5667","contributorId":3791,"corporation":false,"usgs":true,"family":"Cahoon","given":"Donald","email":"dcahoon@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":478684,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":478683,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Phelps, Jacob","contributorId":85862,"corporation":false,"usgs":true,"family":"Phelps","given":"Jacob","email":"","affiliations":[],"preferred":false,"id":478687,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70045993,"text":"ofr20131049 - 2013 - Multiscale sagebrush rangeland habitat modeling in the Gunnison Basin of Colorado","interactions":[],"lastModifiedDate":"2018-03-08T13:01:51","indexId":"ofr20131049","displayToPublicDate":"2013-05-17T00:00:00","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":"2013-1049","title":"Multiscale sagebrush rangeland habitat modeling in the Gunnison Basin of Colorado","docAbstract":"North American sagebrush-steppe ecosystems have decreased by about 50 percent since European settlement. As a result, sagebrush-steppe dependent species, such as the Gunnison sage-grouse, have experienced drastic range contractions and population declines. Coordinated ecosystem-wide research, integrated with monitoring and management activities, is needed to help maintain existing sagebrush habitats; however, products that accurately model and map sagebrush habitats in detail over the Gunnison Basin in Colorado are still unavailable. The goal of this project is to provide a rigorous large-area sagebrush habitat classification and inventory with statistically validated products and estimates of precision across the Gunnison Basin. This research employs a combination of methods, including (1) modeling sagebrush rangeland as a series of independent objective components that can be combined and customized by any user at multiple spatial scales; (2) collecting ground measured plot data on 2.4-meter QuickBird satellite imagery in the same season the imagery is acquired; (3) modeling of ground measured data on 2.4-meter imagery to maximize subsequent extrapolation; (4) acquiring multiple seasons (spring, summer, and fall) of Landsat Thematic Mapper imagery (30-meter) for optimal modeling; (5) using regression tree classification technology that optimizes data mining of multiple image dates, ratios, and bands with ancillary data to extrapolate ground training data to coarser resolution Landsat Thematic Mapper; and 6) employing accuracy assessment of model predictions to enable users to understand their dependencies. Results include the prediction of four primary components including percent bare ground, percent herbaceous, percent shrub, and percent litter, and four secondary components including percent sagebrush (Artemisia spp.), percent big sagebrush (Artemisia tridentata), percent Wyoming sagebrush (Artemisia tridentata wyomingensis), and shrub height (centimeters). Results were validated with an independent accuracy assessment, with root mean square error values ranging from 3.5 (percent big sagebrush) to 10.8 (percent bare ground) at the QuickBird scale, and from 4.5 (percent Wyoming sagebrush) to 12.4 (percent herbaceous) at the full Landsat scale. These results offer significant improvement in sagebrush ecosystem quantification across the Gunnison Basin, and also provide maximum flexibility to users to employ for a wide variety of applications. Further refinement of these remote sensing component predictions in the future will be most likely achieved by focusing on more extensive ground plot sampling, employing new high and moderate-resolution satellite sensors that offer additional spectral bands for vegetation discrimination, and capturing more dates of satellite imagery to better represent phenological variation.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131049","usgsCitation":"Homer, C.G., Aldridge, C.L., Meyer, D., and Schell, S., 2013, Multiscale sagebrush rangeland habitat modeling in the Gunnison Basin of Colorado: U.S. Geological Survey Open-File Report 2013-1049, iv, 12 p., https://doi.org/10.3133/ofr20131049.","productDescription":"iv, 12 p.","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-041635","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":272338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131049.gif"},{"id":272336,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1049/"},{"id":272337,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1049/of13-1049.pdf"}],"country":"United States","state":"Colorado","otherGeospatial":"Gunnison Basin","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":"51974367e4b09a9cb58d5ede","contributors":{"authors":[{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":478661,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":478658,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meyer, Debra K. 0000-0002-8841-697X","orcid":"https://orcid.org/0000-0002-8841-697X","contributorId":72282,"corporation":false,"usgs":true,"family":"Meyer","given":"Debra K.","affiliations":[],"preferred":false,"id":478660,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schell, Spencer J.","contributorId":50432,"corporation":false,"usgs":true,"family":"Schell","given":"Spencer J.","affiliations":[],"preferred":false,"id":478659,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70045986,"text":"fs20133019 - 2013 - The U.S. Geological Survey Climate Geo Data Portal: an integrated broker for climate and geospatial data","interactions":[],"lastModifiedDate":"2013-05-16T14:50:13","indexId":"fs20133019","displayToPublicDate":"2013-05-16T00:00:00","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":"2013-3019","title":"The U.S. Geological Survey Climate Geo Data Portal: an integrated broker for climate and geospatial data","docAbstract":"The increasing availability of downscaled climate projections and other data products that summarize or predict climate conditions, is making climate data use more common in research and management. Scientists and decisionmakers often need to construct ensembles and compare climate hindcasts and future projections for particular spatial areas. These tasks generally require an investigator to procure all datasets of interest en masse, integrate the various data formats and representations into commonly accessible and comparable formats, and then extract the subsets of the datasets that are actually of interest. This process can be challenging and time intensive due to data-transfer, -storage, and(or) -processing limits, or unfamiliarity with methods of accessing climate data. Data management for modeling and assessing the impacts of future climate conditions is also becoming increasingly expensive due to the size of the datasets. The Climate Geo Data Portal (http://cida.usgs.gov/climate/gdp/) addresses these limitations, making access to numerous climate datasets for particular areas of interest a simple and efficient task.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133019","usgsCitation":"Blodgett, D.L., 2013, The U.S. Geological Survey Climate Geo Data Portal: an integrated broker for climate and geospatial data: U.S. Geological Survey Fact Sheet 2013-3019, 2 p., https://doi.org/10.3133/fs20133019.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"links":[{"id":272335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133019.jpg"},{"id":272333,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3019/"},{"id":272334,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3019/pdf/FS_2013-3019_508.pdf"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51955816e4b0a933d82c4c91","contributors":{"authors":[{"text":"Blodgett, David L. 0000-0001-9489-1710 dblodgett@usgs.gov","orcid":"https://orcid.org/0000-0001-9489-1710","contributorId":3868,"corporation":false,"usgs":true,"family":"Blodgett","given":"David","email":"dblodgett@usgs.gov","middleInitial":"L.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478652,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70045978,"text":"sir20135095 - 2013 - Evaluation of the potential for hysteresis in index-velocity ratings for the Chicago Sanitary and Ship Canal near Lemont, Illinois","interactions":[],"lastModifiedDate":"2013-05-16T11:01:06","indexId":"sir20135095","displayToPublicDate":"2013-05-16T00:00:00","publicationYear":"2013","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":"2013-5095","title":"Evaluation of the potential for hysteresis in index-velocity ratings for the Chicago Sanitary and Ship Canal near Lemont, Illinois","docAbstract":"The U.S. Geological Survey (USGS) is responsible for monitoring flows in the Chicago Sanitary and Ship Canal (CSSC) near Lemont, Illinois, as a part of the Lake Michigan Diversion Accounting overseen by the U.S. Army Corps of Engineers, Chicago District. Lake Michigan Diversion Accounting is mandated by a U.S. Supreme Court decree in order to monitor, and limit, the State of Illinois’ annual diversion of Great Lakes water through the manmade CSSC. Every 5 years, a technical review committee consisting of practicing engineers and academics reviews USGS streamgaging practices in the CSSC near Lemont, Illinois. The sixth technical review committee expressed concern that the index-velocity rating—the method used to estimate mean cross-sectional velocity from a measured index velocity—may be subject to hysteresis at this site because of the unique, unsteady hydraulics of the canal. Hysteresis in index-velocity ratings can occur at sites where the flow distribution in the channel varies significantly between the rising and falling limbs of the hydrograph for the same discharge. Presently, hysteresis in index-velocity ratings has been documented only in tidally affected sites. This report investigates whether hysteresis can occur at this nontidal site, and the conditions under which it is likely to occur, by using both a theoretical approach and a three-dimensional hydrodynamic model. The theoretical analysis investigated the conditions required for hysteresis in the index-velocity rating, and the modeling analysis focused on the effect of the timing of the inflows from the CSSC and the Cal-Sag Channel on the potential for hysteresis and whether highly resolved simulations of actual high-flow events show any evidence of hysteresis.   Based on both a theoretical analysis using observed historical data and an analysis using a three-dimensional hydrodynamic model, there is no conclusive evidence for the existence of hysteresis in the index-velocity rating at the USGS streamgage on the CSSC near Lemont, Illinois. Although the theoretical analysis indicated the possibility of hysteresis at this site, the hydrodynamic conditions required to generate hysteresis are not present at this site based on historical data. Ongoing streamgaging practices at this site will use the information in this report and include periodic assessment of the index-velocity rating for any signs of hysteresis that might result from future changes to the operation of this manmade canal.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135095","collaboration":"Prepared in cooperation with the Chicago District of the U.S. Army Corps of Engineers","usgsCitation":"Jackson, P., Sinha, S., Dutta, S., Johnson, K.K., Duncker, J.J., and Garcia, M., 2013, Evaluation of the potential for hysteresis in index-velocity ratings for the Chicago Sanitary and Ship Canal near Lemont, Illinois: U.S. Geological Survey Scientific Investigations Report 2013-5095, vi, 35 p., https://doi.org/10.3133/sir20135095.","productDescription":"vi, 35 p.","numberOfPages":"43","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":272307,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135095.jpg"},{"id":272305,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5095/"},{"id":272306,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5095/pdf/sir2013-5095.pdf"}],"country":"United States","state":"Illinois","city":"Chicago","otherGeospatial":"Sanitary And Ship Canal","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.25,41.46 ], [ -88.25,42.25 ], [ -87.5,42.25 ], [ -87.5,41.46 ], [ -88.25,41.46 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51955815e4b0a933d82c4c85","contributors":{"authors":[{"text":"Jackson, P. Ryan","contributorId":68571,"corporation":false,"usgs":true,"family":"Jackson","given":"P. Ryan","affiliations":[],"preferred":false,"id":478634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sinha, Sumit","contributorId":18656,"corporation":false,"usgs":true,"family":"Sinha","given":"Sumit","email":"","affiliations":[],"preferred":false,"id":478633,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dutta, Som","contributorId":105200,"corporation":false,"usgs":true,"family":"Dutta","given":"Som","email":"","affiliations":[],"preferred":false,"id":478636,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Kevin K. 0000-0003-2703-5994 johnsonk@usgs.gov","orcid":"https://orcid.org/0000-0003-2703-5994","contributorId":4220,"corporation":false,"usgs":true,"family":"Johnson","given":"Kevin","email":"johnsonk@usgs.gov","middleInitial":"K.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478631,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duncker, James J. 0000-0001-5464-7991 jduncker@usgs.gov","orcid":"https://orcid.org/0000-0001-5464-7991","contributorId":4316,"corporation":false,"usgs":true,"family":"Duncker","given":"James","email":"jduncker@usgs.gov","middleInitial":"J.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478632,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Garcia, Marcelo H.","contributorId":74236,"corporation":false,"usgs":false,"family":"Garcia","given":"Marcelo H.","affiliations":[{"id":33106,"text":"University of Illinois at Urbana Champaign","active":true,"usgs":false}],"preferred":false,"id":478635,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70045984,"text":"sir20135066 - 2013 - Estimating irrigation water use in the humid eastern United States","interactions":[],"lastModifiedDate":"2013-05-16T13:41:25","indexId":"sir20135066","displayToPublicDate":"2013-05-16T00:00:00","publicationYear":"2013","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":"2013-5066","title":"Estimating irrigation water use in the humid eastern United States","docAbstract":"Accurate accounting of irrigation water use is an important part of the U.S. Geological Survey National Water-Use Information Program and the WaterSMART initiative to help maintain sustainable water resources in the Nation. Irrigation water use in the humid eastern United States is not well characterized because of inadequate reporting and wide variability associated with climate, soils, crops, and farming practices. To better understand irrigation water use in the eastern United States, two types of predictive models were developed and compared by using metered irrigation water-use data for corn, cotton, peanut, and soybean crops in Georgia and turf farms in Rhode Island. Reliable metered irrigation data were limited to these areas.  The first predictive model that was developed uses logistic regression to predict the occurrence of irrigation on the basis of antecedent climate conditions. Logistic regression equations were developed for corn, cotton, peanut, and soybean crops by using weekly irrigation water-use data from 36 metered sites in Georgia in 2009 and 2010 and turf farms in Rhode Island from 2000 to 2004. For the weeks when irrigation was predicted to take place, the irrigation water-use volume was estimated by multiplying the average metered irrigation application rate by the irrigated acreage for a given crop.  The second predictive model that was developed is a crop-water-demand model that uses a daily soil water balance to estimate the water needs of a crop on a given day based on climate, soil, and plant properties. Crop-water-demand models were developed independently of reported irrigation water-use practices and relied on knowledge of plant properties that are available in the literature. Both modeling approaches require accurate accounting of irrigated area and crop type to estimate total irrigation water use.  Water-use estimates from both modeling methods were compared to the metered irrigation data from Rhode Island and Georgia that were used to develop the models as well as two independent validation datasets from Georgia and Virginia that were not used in model development. Irrigation water-use estimates from the logistic regression method more closely matched mean reported irrigation rates than estimates from the crop-water-demand model when compared to the irrigation data used to develop the equations. The root mean squared errors (RMSEs) for the logistic regression estimates of mean annual irrigation ranged from 0.3 to 2.0 inches (in.) for the five crop types; RMSEs for the crop-water-demand models ranged from 1.4 to 3.9 in. However, when the models were applied and compared to the independent validation datasets from southwest Georgia from 2010, and from Virginia from 1999 to 2007, the crop-water-demand model estimates were as good as or better at predicting the mean irrigation volume than the logistic regression models for most crop types. RMSEs for logistic regression estimates of mean annual irrigation ranged from 1.0 to 7.0 in. for validation data from Georgia and from 1.8 to 4.9 in. for validation data from Virginia; RMSEs for crop-water-demand model estimates ranged from 2.1 to 5.8 in. for Georgia data and from 2.0 to 3.9 in. for Virginia data. In general, regression-based models performed better in areas that had quality daily or weekly irrigation data from which the regression equations were developed; however, the regression models were less reliable than the crop-water-demand models when applied outside the area for which they were developed. In most eastern coastal states that do not have quality irrigation data, the crop-water-demand model can be used more reliably.  The development of predictive models of irrigation water use in this study was hindered by a lack of quality irrigation data. Many mid-Atlantic and New England states do not require irrigation water use to be reported. A survey of irrigation data from 14 eastern coastal states from Maine to Georgia indicated that, with the exception of the data in Georgia, irrigation data in the states that do require reporting commonly did not contain requisite ancillary information such as irrigated area or crop type, lacked precision, or were at an aggregated temporal scale making them unsuitable for use in the development of predictive models. Confidence in the reliability of either modeling method is affected by uncertainty in the reported data from which the models were developed or validated. Only through additional collection of quality data and further study can the accuracy and uncertainty of irrigation water-use estimates be improved in the humid eastern United States.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135066","collaboration":"Prepared in cooperation with the WaterSMART Initiative","usgsCitation":"Levin, S.B., and Zarriello, P.J., 2013, Estimating irrigation water use in the humid eastern United States: U.S. Geological Survey Scientific Investigations Report 2013-5066, viii, 34 p., https://doi.org/10.3133/sir20135066.","productDescription":"viii, 34 p.","numberOfPages":"44","onlineOnly":"N","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":272329,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135066.gif"},{"id":272328,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5066/pdf/sir2013-5066_report_508.pdf"},{"id":272327,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5066/"}],"country":"United States","otherGeospatial":"Eastern United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -85,30 ], [ -85,33.08 ], [ -81,33.08 ], [ -81,30 ], [ -85,30 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51955815e4b0a933d82c4c81","contributors":{"authors":[{"text":"Levin, Sara B. 0000-0002-2448-3129 slevin@usgs.gov","orcid":"https://orcid.org/0000-0002-2448-3129","contributorId":1870,"corporation":false,"usgs":true,"family":"Levin","given":"Sara","email":"slevin@usgs.gov","middleInitial":"B.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zarriello, Phillip J. 0000-0001-9598-9904 pzarriel@usgs.gov","orcid":"https://orcid.org/0000-0001-9598-9904","contributorId":1868,"corporation":false,"usgs":true,"family":"Zarriello","given":"Phillip","email":"pzarriel@usgs.gov","middleInitial":"J.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478645,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70045329,"text":"70045329 - 2013 - Using diets to reveal overlap and egg predation among benthivorous fishes in Lake Michigan","interactions":[],"lastModifiedDate":"2013-05-16T10:12:56","indexId":"70045329","displayToPublicDate":"2013-05-15T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Using diets to reveal overlap and egg predation among benthivorous fishes in Lake Michigan","docAbstract":"Ecological stability in the Laurentian Great Lakes has been altered by nonindigenous species, such as the Round Goby Neogobius melanostomus and dreissenid mussels, and by declines in native amphipods Diporeia spp. We evaluated whether these changes could influence diet overlap between three benthivorous fishes (Slimy Sculpin Cottus cognatus, Deepwater Sculpin Myoxocephalus thompsonii, and Round Goby) and whether predation on eggs of native species was occurring. We examined diets of fish collected at depths of 69–128 m in Lake Michigan offshore of Frankfort and Muskegon, Michigan, and Two Rivers and Sturgeon Bay, Wisconsin, during January–May 2009 and 2010. Important prey (by dry weight proportion and by percent frequency of occurrence) for Slimy Sculpin were Mysis (0.34; 45%), Diporeia (0.16; 34%), and Limnocalanus macrurus (0.22; 68%); important prey for Deepwater Sculpin were Mysis (0.74; 92%) and Diporeia (0.16; 54%). Round Goby consumed mainly bivalves (i.e., dreissenids: 0.68; 95%) and Mysis (0.15; 37%). The two sculpin species consumed the eggs of Bloaters Coregonus hoyi (Slimy Sculpin: 0.04, 11%; Deepwater Sculpin: 0.02, 7%) and the eggs of Deepwater Sculpin (Slimy Sculpin: 0.03, 13%; Deepwater Sculpin: 0.05, 16%) during February–May at all sites. Round Goby also consumed eggs of these species but at lower levels (≤0.01; <1%). Diet overlap was identified between sculpin species at Frankfort and Sturgeon Bay, suggesting possible interspecific competition, but their diets did not overlap at Two Rivers; diet overlap was never observed between Round Goby and either sculpin species. Given that (1) diet overlap varied by site and (2) diet proportions varied spatially more than temporally, benthivores appear to be exhibiting localized responses to recent ecological changes. Overall, these results reveal that egg predation and interspecific competition could be important interactions to consider in future examinations of the population dynamics of these species or in ecosystem models that forecast how fisheries will respond to possible perturbations or management scenarios.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Transactions of the American Fisheries Society","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2012.756431","usgsCitation":"Mychek-Londer, J., Bunnell, D., Stott, W., Diana, J., French, J.R., and Chriscinske, M., 2013, Using diets to reveal overlap and egg predation among benthivorous fishes in Lake Michigan: Transactions of the American Fisheries Society, v. 142, no. 2, p. 492-504, https://doi.org/10.1080/00028487.2012.756431.","productDescription":"13 p.","startPage":"492","endPage":"504","ipdsId":"IP-042610","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":473823,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/00028487.2012.756431","text":"Publisher Index Page"},{"id":272302,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/00028487.2012.756431"},{"id":272303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Lake Michigan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -90,0.0011111111111111111 ], [ -90,0.0011111111111111111 ], [ -84,0.0011111111111111111 ], [ -84,0.0011111111111111111 ], [ -90,0.0011111111111111111 ] ] ] } } ] }","volume":"142","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-02-19","publicationStatus":"PW","scienceBaseUri":"51955817e4b0a933d82c4c99","contributors":{"authors":[{"text":"Mychek-Londer, Justin G.","contributorId":64138,"corporation":false,"usgs":true,"family":"Mychek-Londer","given":"Justin G.","affiliations":[],"preferred":false,"id":477234,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David B.","contributorId":14360,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","affiliations":[],"preferred":false,"id":477232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stott, Wendylee","contributorId":8058,"corporation":false,"usgs":true,"family":"Stott","given":"Wendylee","affiliations":[],"preferred":false,"id":477231,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diana, James S.","contributorId":52137,"corporation":false,"usgs":true,"family":"Diana","given":"James S.","affiliations":[],"preferred":false,"id":477233,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"French, John R. P. III","contributorId":107635,"corporation":false,"usgs":true,"family":"French","given":"John","suffix":"III","email":"","middleInitial":"R. P.","affiliations":[],"preferred":false,"id":477236,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chriscinske, Margret","contributorId":78683,"corporation":false,"usgs":true,"family":"Chriscinske","given":"Margret","affiliations":[],"preferred":false,"id":477235,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70043361,"text":"70043361 - 2013 - Estimating irrigation water demand using an improved method and optimizing reservoir operation for water supply and hydropower generation: a case study of the Xinfengjiang reservoir in southern China","interactions":[],"lastModifiedDate":"2013-05-14T09:17:57","indexId":"70043361","displayToPublicDate":"2013-05-14T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":680,"text":"Agricultural Water Management","active":true,"publicationSubtype":{"id":10}},"title":"Estimating irrigation water demand using an improved method and optimizing reservoir operation for water supply and hydropower generation: a case study of the Xinfengjiang reservoir in southern China","docAbstract":"The ever-increasing demand for water due to growth of population and socioeconomic development in the past several decades has posed a worldwide threat to water supply security and to the environmental health of rivers. This study aims to derive reservoir operating rules through establishing a multi-objective optimization model for the Xinfengjiang (XFJ) reservoir in the East River Basin in southern China to minimize water supply deficit and maximize hydropower generation. Additionally, to enhance the estimation of irrigation water demand from the downstream agricultural area of the XFJ reservoir, a conventional method for calculating crop water demand is improved using hydrological model simulation results. Although the optimal reservoir operating rules are derived for the XFJ reservoir with three priority scenarios (water supply only, hydropower generation only, and equal priority), the river environmental health is set as the basic demand no matter which scenario is adopted. The results show that the new rules derived under the three scenarios can improve the reservoir operation for both water supply and hydropower generation when comparing to the historical performance. Moreover, these alternative reservoir operating policies provide the flexibility for the reservoir authority to choose the most appropriate one. Although changing the current operating rules may influence its hydropower-oriented functions, the new rules can be significant to cope with the increasingly prominent water shortage and degradation in the aquatic environment. Overall, our results and methods (improved estimation of irrigation water demand and formulation of the reservoir optimization model) can be useful for local watershed managers and valuable for other researchers worldwide.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Agricultural Water Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.agwat.2012.10.016","usgsCitation":"Wu, Y., and Chen, J., 2013, Estimating irrigation water demand using an improved method and optimizing reservoir operation for water supply and hydropower generation: a case study of the Xinfengjiang reservoir in southern China: Agricultural Water Management, v. 116, p. 110-121, https://doi.org/10.1016/j.agwat.2012.10.016.","productDescription":"12 p.","startPage":"110","endPage":"121","ipdsId":"IP-041608","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":272201,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272200,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.agwat.2012.10.016"}],"country":"China","otherGeospatial":"Xinfengjiang Reservoir","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 114.3728,23.7144 ], [ 114.3728,24.1164 ], [ 114.7686,24.1164 ], [ 114.7686,23.7144 ], [ 114.3728,23.7144 ] ] ] } } ] }","volume":"116","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd5804e4b0b290850f7d16","contributors":{"authors":[{"text":"Wu, Yiping ywu@usgs.gov","contributorId":987,"corporation":false,"usgs":true,"family":"Wu","given":"Yiping","email":"ywu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":473461,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Ji","contributorId":101960,"corporation":false,"usgs":true,"family":"Chen","given":"Ji","email":"","affiliations":[],"preferred":false,"id":473462,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70045946,"text":"70045946 - 2013 - Optimizing stream water mercury sampling for calculation of fish bioaccumulation factors","interactions":[],"lastModifiedDate":"2013-06-17T09:35:00","indexId":"70045946","displayToPublicDate":"2013-05-14T00:00:00","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":"Optimizing stream water mercury sampling for calculation of fish bioaccumulation factors","docAbstract":"Mercury (Hg) bioaccumulation factors (BAFs) for game fishes are widely employed for monitoring, assessment, and regulatory purposes. Mercury BAFs are calculated as the fish Hg concentration (Hg<sub>fish</sub>) divided by the water Hg concentration (Hg<sub>water</sub>) and, consequently, are sensitive to sampling and analysis artifacts for fish and water. We evaluated the influence of water sample timing, filtration, and mercury species on the modeled relation between game fish and water mercury concentrations across 11 streams and rivers in five states in order to identify optimum Hg<sub>water</sub> sampling approaches. Each model included fish trophic position, to account for a wide range of species collected among sites, and flow-weighted Hg<sub>water</sub> estimates. Models were evaluated for parsimony, using Akaike’s Information Criterion. Better models included filtered water methylmercury (FMeHg) or unfiltered water methylmercury (UMeHg), whereas filtered total mercury did not meet parsimony requirements. Models including mean annual FMeHg were superior to those with mean FMeHg calculated over shorter time periods throughout the year. FMeHg models including metrics of high concentrations (80th percentile and above) observed during the year performed better, in general. These higher concentrations occurred most often during the growing season at all sites. Streamflow was significantly related to the probability of achieving higher concentrations during the growing season at six sites, but the direction of influence varied among sites. These findings indicate that streamwater Hg collection can be optimized by evaluating site-specific FMeHg - UMeHg relations, intra-annual temporal variation in their concentrations, and streamflow-Hg dynamics.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Science and Technology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Chemical Society","doi":"10.1021/es303758e","usgsCitation":"Riva-Murray, K., Bradley, P.M., Journey, C.A., Brigham, M.E., Scudder Eikenberry, B.C., Knightes, C., and Button, D.T., 2013, Optimizing stream water mercury sampling for calculation of fish bioaccumulation factors: Environmental Science & Technology, v. 47, no. 11, p. 5904-5912, https://doi.org/10.1021/es303758e.","productDescription":"9 p.","startPage":"5904","endPage":"5912","ipdsId":"IP-041712","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":473826,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/es303758e","text":"Publisher Index Page"},{"id":272251,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273767,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es303758e"}],"volume":"47","issue":"11","noUsgsAuthors":false,"publicationDate":"2013-05-13","publicationStatus":"PW","scienceBaseUri":"51c02ff3e4b0ee1529ed3d38","chorus":{"doi":"10.1021/es303758e","url":"http://dx.doi.org/10.1021/es303758e","publisher":"American Chemical Society (ACS)","authors":"Riva-Murray Karen, Bradley Paul M., Scudder Eikenberry Barbara C., Knightes Christopher D., Journey Celeste A., Brigham Mark E., Button Daniel T.","journalName":"Environmental Science & Technology","publicationDate":"6/4/2013","auditedOn":"3/4/2016","publiclyAccessibleDate":"1/1/1999"},"contributors":{"authors":[{"text":"Riva-Murray, Karen","contributorId":85650,"corporation":false,"usgs":true,"family":"Riva-Murray","given":"Karen","affiliations":[],"preferred":false,"id":478589,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":478586,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brigham, Mark E. 0000-0001-7412-6800 mbrigham@usgs.gov","orcid":"https://orcid.org/0000-0001-7412-6800","contributorId":1840,"corporation":false,"usgs":true,"family":"Brigham","given":"Mark","email":"mbrigham@usgs.gov","middleInitial":"E.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478584,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scudder Eikenberry, Barbara C.","contributorId":63771,"corporation":false,"usgs":true,"family":"Scudder Eikenberry","given":"Barbara","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":478588,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knightes, Christopher","contributorId":52476,"corporation":false,"usgs":true,"family":"Knightes","given":"Christopher","affiliations":[],"preferred":false,"id":478587,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Button, Daniel T. 0000-0002-7479-884X dtbutton@usgs.gov","orcid":"https://orcid.org/0000-0002-7479-884X","contributorId":2084,"corporation":false,"usgs":true,"family":"Button","given":"Daniel","email":"dtbutton@usgs.gov","middleInitial":"T.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478585,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70043750,"text":"70043750 - 2013 - Evapotranspiration and water balance of an anthropogenic coastal desert wetland: responses to fire, inflows and salinities","interactions":[],"lastModifiedDate":"2013-10-23T10:05:21","indexId":"70043750","displayToPublicDate":"2013-05-14T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Evapotranspiration and water balance of an anthropogenic coastal desert wetland: responses to fire, inflows and salinities","docAbstract":"Evapotranspiration (ET) and other water balance components were estimated for Cienega de Santa Clara, an anthropogenic brackish wetland in the delta of the Colorado River in Mexico. The marsh is in the Biosphere Reserve of the Upper Gulf of California and Delta of the Colorado River, and supports a high abundance and diversity of wildlife. Over 95% of its water supply originates as agricultural drain water from the USA, sent for disposal in Mexico. This study was conducted from 2009 to 2011, before, during and after a trial run of the Yuma Desalting Plant in the USA, which will divert water from the wetland and replace it with brine from the desalting operation. The goal was to estimate the main components in the water budget to be used in creating management scenarios for this marsh. We used a remote sensing algorithm to estimate ET from meteorological data and Enhanced Vegetation Index values from the Moderate Resolution Imaging Spectrometer (MODIS) sensors on the Terra satellite. ET estimates from the MODIS method were then compared to results from a mass balance of water and salt inflows and outflows over the study period. By both methods, mean annual ET estimates ranged from 2.6 to 3.0 mm d<sup>−1</sup>, or 50 to 60% of reference ET (ET<sub>o</sub>). Water entered at a mean salinity of 2.6 g L<sup>−1</sup> TDS and mean salinity in the wetland was 3.73 g L<sup>−1</sup> TDS over the 33 month study period. Over an annual cycle, 54% of inflows supported ET while the rest exited the marsh as outflows; however, in winter when ET was low, up to 90% of the inflows exited the marsh. An analysis of ET estimates over the years 2000–2011 showed that annual ET was proportional to the volume of inflows, but was also markedly stimulated by fires. Spring fires in 2006 and 2011 burned off accumulated thatch, resulting in vigorous growth of new leaves and a 30% increase in peak summer ET compared to non-fire years. Following fires, peak summer ET estimates were equal to ET<sub>o</sub>, while in non-fire years peak ET was equal to only one-half to two-thirds of ET<sub>o</sub>. Over annual cycles, estimated ET was always lower than ET<sub>o</sub>, because T. domingensis is dormant in winter and shades the water surface, reducing direct evaporation. Thus, ET of a Typha marsh is likely to be less than an open water surface under most conditions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2012.06.043","usgsCitation":"Glenn, E.P., Mexicano, L., Garcia-Hernandez, J., Nagler, P.L., Gomez-Sapiens, M.M., Tang, D., Lomeli, M.A., Ramírez-Hernández, J., and Zamora-Arroyo, F., 2013, Evapotranspiration and water balance of an anthropogenic coastal desert wetland: responses to fire, inflows and salinities: Ecological Engineering, v. 59, p. 176-184, https://doi.org/10.1016/j.ecoleng.2012.06.043.","productDescription":"9 p.","startPage":"176","endPage":"184","ipdsId":"IP-038206","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":272224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272223,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecoleng.2012.06.043"}],"volume":"59","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5268efe3e4b0584cbe916856","contributors":{"authors":[{"text":"Glenn, Edward P.","contributorId":19289,"corporation":false,"usgs":true,"family":"Glenn","given":"Edward","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":474201,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mexicano, Lourdes","contributorId":91773,"corporation":false,"usgs":true,"family":"Mexicano","given":"Lourdes","email":"","affiliations":[],"preferred":false,"id":474207,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garcia-Hernandez, Jaqueline","contributorId":37627,"corporation":false,"usgs":true,"family":"Garcia-Hernandez","given":"Jaqueline","email":"","affiliations":[],"preferred":false,"id":474203,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":474199,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gomez-Sapiens, Martha M.","contributorId":58172,"corporation":false,"usgs":true,"family":"Gomez-Sapiens","given":"Martha","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":474204,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tang, Dawei","contributorId":17515,"corporation":false,"usgs":true,"family":"Tang","given":"Dawei","email":"","affiliations":[],"preferred":false,"id":474200,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lomeli, Marcelo A.","contributorId":60523,"corporation":false,"usgs":true,"family":"Lomeli","given":"Marcelo","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":474205,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ramírez-Hernández, Jorge","contributorId":24264,"corporation":false,"usgs":true,"family":"Ramírez-Hernández","given":"Jorge","affiliations":[],"preferred":false,"id":474202,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zamora-Arroyo, Francisco","contributorId":75834,"corporation":false,"usgs":true,"family":"Zamora-Arroyo","given":"Francisco","email":"","affiliations":[],"preferred":false,"id":474206,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70045677,"text":"70045677 - 2013 - Evaluation of a new model of aeolian transport in the presence of vegetation","interactions":[],"lastModifiedDate":"2013-05-14T11:05:21","indexId":"70045677","displayToPublicDate":"2013-05-14T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of a new model of aeolian transport in the presence of vegetation","docAbstract":"Aeolian transport is an important characteristic of many arid and semiarid regions worldwide that affects dust emission and ecosystem processes. The purpose of this paper is to evaluate a recent model of aeolian transport in the presence of vegetation. This approach differs from previous models by accounting for how vegetation affects the distribution of shear velocity on the surface rather than merely calculating the average effect of vegetation on surface shear velocity or simply using empirical relationships. Vegetation, soil, and meteorological data at 65 field sites with measurements of horizontal aeolian flux were collected from the Western United States. Measured fluxes were tested against modeled values to evaluate model performance, to obtain a set of optimum model parameters, and to estimate the uncertainty in these parameters. The same field data were used to model horizontal aeolian flux using three other schemes. Our results show that the model can predict horizontal aeolian flux with an approximate relative error of 2.1 and that further empirical corrections can reduce the approximate relative error to 1.0. The level of error is within what would be expected given uncertainties in threshold shear velocity and wind speed at our sites. The model outperforms the alternative schemes both in terms of approximate relative error and the number of sites at which threshold shear velocity was exceeded. These results lend support to an understanding of the physics of aeolian transport in which (1) vegetation's impact on transport is dependent upon the distribution of vegetation rather than merely its average lateral cover and (2) vegetation impacts surface shear stress locally by depressing it in the immediate lee of plants rather than by changing the bulk surface's threshold shear velocity. Our results also suggest that threshold shear velocity is exceeded more than might be estimated by single measurements of threshold shear stress and roughness length commonly associated with vegetated surfaces, highlighting the variation of threshold shear velocity with space and time in real landscapes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research F: Earth Surface","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"AGU","doi":"10.1002/jgrf.20040","usgsCitation":"Li, J., Okin, G.S., Herrick, J.E., Belnap, J., Miller, M.E., Vest, K., and Draut, A.E., 2013, Evaluation of a new model of aeolian transport in the presence of vegetation: Journal of Geophysical Research F: Earth Surface, v. 118, no. 1, p. 288-306, https://doi.org/10.1002/jgrf.20040.","productDescription":"9 p.","startPage":"288","endPage":"306","ipdsId":"IP-025701","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":473829,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jgrf.20040","text":"Publisher Index Page"},{"id":272217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272215,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrf.20040"}],"volume":"118","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-03-26","publicationStatus":"PW","scienceBaseUri":"53cd584ee4b0b290850f802d","chorus":{"doi":"10.1002/jgrf.20040","url":"http://dx.doi.org/10.1002/jgrf.20040","publisher":"Wiley-Blackwell","authors":"Li Junran, Okin Gregory S., Herrick Jeffrey E., Belnap Jayne, Miller Mark E., Vest Kimberly, Draut Amy E.","journalName":"Journal of Geophysical Research: Earth Surface","publicationDate":"3/2013","auditedOn":"3/7/2016"},"contributors":{"authors":[{"text":"Li, Junran","contributorId":23418,"corporation":false,"usgs":true,"family":"Li","given":"Junran","affiliations":[],"preferred":false,"id":478037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Okin, Gregory S.","contributorId":50025,"corporation":false,"usgs":true,"family":"Okin","given":"Gregory","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":478039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herrick, Jeffrey E.","contributorId":26054,"corporation":false,"usgs":false,"family":"Herrick","given":"Jeffrey","email":"","middleInitial":"E.","affiliations":[{"id":12627,"text":"USDA-ARS Jornada Experimental Range, New Mexico State University, Las Cruces, NM 88003-8003, USA","active":true,"usgs":false}],"preferred":false,"id":478038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":478036,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, Mark E.","contributorId":91580,"corporation":false,"usgs":false,"family":"Miller","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":6959,"text":"National Park Service Southeast Utah Group","active":true,"usgs":false}],"preferred":false,"id":478041,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vest, Kimberly","contributorId":83818,"corporation":false,"usgs":true,"family":"Vest","given":"Kimberly","email":"","affiliations":[],"preferred":false,"id":478040,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Draut, Amy E.","contributorId":92215,"corporation":false,"usgs":true,"family":"Draut","given":"Amy","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":478042,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70045945,"text":"70045945 - 2013 - Regional patterns and proximal causes of the recent snowpack decline in the Rocky Mountains, U.S.","interactions":[],"lastModifiedDate":"2013-06-17T09:28:15","indexId":"70045945","displayToPublicDate":"2013-05-14T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Regional patterns and proximal causes of the recent snowpack decline in the Rocky Mountains, U.S.","docAbstract":"We used a first-order, monthly snow model and observations to disentangle seasonal influences on 20th century,regional snowpack anomalies in the Rocky Mountains of western North America, where interannual variations in cool-season (November–March) temperatures are broadly synchronous, but precipitation is typically antiphased north to south and uncorrelated with temperature. Over the previous eight centuries, regional snowpack variability exhibits strong, decadally persistent north-south (N-S) antiphasing of snowpack anomalies. Contrary to the normal regional antiphasing, two intervals of spatially synchronized snow deficits were identified. Snow deficits shown during the 1930s were synchronized north-south by low cool-season precipitation, with spring warming (February–March) since the 1980s driving the majority of the recent synchronous snow declines, especially across the low to middle elevations. Spring warming strongly influenced low snowpacks in the north after 1958, but not in the south until after 1980. The post-1980, synchronous snow decline reduced snow cover at low to middle elevations by ~20% and partly explains earlier and reduced streamflow and both longer and more active fire seasons. Climatologies of Rocky Mountain snowpack are shown to be seasonally and regionally complex, with Pacific decadal variability positively reinforcing the anthropogenic warming trend.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"AGU","doi":"10.1002/grl.50424","usgsCitation":"Pederson, G.T., Betancourt, J.L., and McCabe, G., 2013, Regional patterns and proximal causes of the recent snowpack decline in the Rocky Mountains, U.S.: Geophysical Research Letters, v. 40, no. 9, p. 1811-1816, https://doi.org/10.1002/grl.50424.","productDescription":"6 p.","startPage":"1811","endPage":"1816","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":272195,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272194,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/grl.50424"}],"country":"United States","otherGeospatial":"Rocky Mountains","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -127.5,29.1 ], [ -127.5,49.0 ], [ -102.4,49.0 ], [ -102.4,29.1 ], [ -127.5,29.1 ] ] ] } } ] }","volume":"40","issue":"9","noUsgsAuthors":false,"publicationDate":"2013-05-12","publicationStatus":"PW","scienceBaseUri":"51c02ff5e4b0ee1529ed3d49","contributors":{"authors":[{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":478581,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Betancourt, Julio L. 0000-0002-7165-0743 jlbetanc@usgs.gov","orcid":"https://orcid.org/0000-0002-7165-0743","contributorId":3376,"corporation":false,"usgs":true,"family":"Betancourt","given":"Julio","email":"jlbetanc@usgs.gov","middleInitial":"L.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":478582,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":1453,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":478580,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70045131,"text":"70045131 - 2013 - Field measurement of basal forces generated by erosive debris flows","interactions":[],"lastModifiedDate":"2013-07-29T09:25:19","indexId":"70045131","displayToPublicDate":"2013-05-14T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Field measurement of basal forces generated by erosive debris flows","docAbstract":"It has been proposed that debris flows cut bedrock valleys in steeplands worldwide, but field measurements needed to constrain mechanistic models of this process remain sparse due to the difficulty of instrumenting natural flows. Here we present and analyze measurements made using an automated sensor network, erosion bolts, and a 15.24 cm by 15.24 cm force plate installed in the bedrock channel floor of a steep catchment. These measurements allow us to quantify the distribution of basal forces from natural debris‒flow events that incised bedrock. Over the 4 year monitoring period, 11 debris‒flow events scoured the bedrock channel floor. No clear water flows were observed. Measurements of erosion bolts at the beginning and end of the study indicated that the bedrock channel floor was lowered by 36 to 64 mm. The basal force during these erosive debris‒flow events had a large‒magnitude (up to 21 kN, which was approximately 50 times larger than the concurrent time‒averaged mean force), high‒frequency (greater than 1 Hz) fluctuating component. We interpret these fluctuations as flow particles impacting the bed. The resulting variability in force magnitude increased linearly with the time‒averaged mean basal force. Probability density functions of basal normal forces were consistent with a generalized Pareto distribution, rather than the exponential distribution that is commonly found in experimental and simulated monodispersed granular flows and which has a lower probability of large forces. When the bed sediment thickness covering the force plate was greater than ~ 20 times the median bed sediment grain size, no significant fluctuations about the time‒averaged mean force were measured, indicating that a thin layer of sediment (~ 5 cm in the monitored cases) can effectively shield the subjacent bed from erosive impacts. Coarse‒grained granular surges and water‒rich, intersurge flow had very similar basal force distributions despite differences in appearance and bulk‒flow density. These results demonstrate that debris flows can have strong control on rates of steepland evolution and contribute to a foundation needed for modeling debris‒flow incision stochastically.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research F: Earth Surface","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/jgrf.20041","usgsCitation":"McCoy, S., Tucker, G., Kean, J., and Coe, J.A., 2013, Field measurement of basal forces generated by erosive debris flows: Journal of Geophysical Research F: Earth Surface, v. 118, no. 2, p. 589-602, https://doi.org/10.1002/jgrf.20041.","productDescription":"14 p.","startPage":"589","endPage":"602","ipdsId":"IP-041443","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":473825,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jgrf.20041","text":"Publisher Index Page"},{"id":272278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272277,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrf.20041"}],"volume":"118","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-05-14","publicationStatus":"PW","scienceBaseUri":"51f78ee6e4b02e26443a9378","contributors":{"authors":[{"text":"McCoy, S.W.","contributorId":74608,"corporation":false,"usgs":true,"family":"McCoy","given":"S.W.","affiliations":[],"preferred":false,"id":476904,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, G.E.","contributorId":102992,"corporation":false,"usgs":true,"family":"Tucker","given":"G.E.","affiliations":[],"preferred":false,"id":476905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kean, J. W. 0000-0003-3089-0369","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":71679,"corporation":false,"usgs":true,"family":"Kean","given":"J. W.","affiliations":[],"preferred":false,"id":476903,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coe, J. A.","contributorId":8867,"corporation":false,"usgs":true,"family":"Coe","given":"J.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":476902,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70042353,"text":"70042353 - 2013 - Evaporative losses from soils covered by physical and different types of biological soil crusts","interactions":[],"lastModifiedDate":"2013-05-14T11:23:03","indexId":"70042353","displayToPublicDate":"2013-05-14T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Evaporative losses from soils covered by physical and different types of biological soil crusts","docAbstract":"Evaporation of soil moisture is one of the most important processes affecting water availability in semiarid ecosystems. Biological soil crusts, which are widely distributed ground cover in these ecosystems, play a recognized role on water processes. Where they roughen surfaces, water residence time and thus infiltration can be greatly enhanced, whereas their ability to clog soil pores or cap the soil surface when wetted can greatly decrease infiltration rate, thus affecting evaporative losses. In this work, we compared evaporation in soils covered by physical crusts, biological crusts in different developmental stages and in the soils underlying the different biological crust types. Our results show that during the time of the highest evaporation (Day 1), there was no difference among any of the crust types or the soils underlying them. On Day 2, when soil moisture was moderately low (11%), evaporation was slightly higher in well-developed biological soil crusts than in physical or poorly developed biological soil crusts. However, crust removal did not cause significant changes in evaporation compared with the respective soil crust type. These results suggest that the small differences we observed in evaporation among crust types could be caused by differences in the properties of the soil underneath the biological crusts. At low soil moisture (<6%), there was no difference in evaporation among crust types or the underlying soils. Water loss for the complete evaporative cycle (from saturation to dry soil) was similar in both crusted and scraped soils. Therefore, we conclude that for the specific crust and soil types tested, the presence or the type of biological soil crust did not greatly modify evaporation with respect to physical crusts or scraped soils.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Hydrological Processes","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/hyp.8421","usgsCitation":"Chamizo, S., Canton, Y., Domingo, F., and Belnap, J., 2013, Evaporative losses from soils covered by physical and different types of biological soil crusts: Hydrological Processes, v. 27, no. 3, p. 324-332, https://doi.org/10.1002/hyp.8421.","productDescription":"9 p.","startPage":"324","endPage":"332","ipdsId":"IP-029706","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":473824,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/hyp.8421","text":"External Repository"},{"id":272222,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272221,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/hyp.8421"}],"volume":"27","issue":"3","noUsgsAuthors":false,"publicationDate":"2012-03-19","publicationStatus":"PW","scienceBaseUri":"53cd588ae4b0b290850f828e","contributors":{"authors":[{"text":"Chamizo, S.","contributorId":49260,"corporation":false,"usgs":true,"family":"Chamizo","given":"S.","affiliations":[],"preferred":false,"id":471367,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Canton, Y.","contributorId":99868,"corporation":false,"usgs":true,"family":"Canton","given":"Y.","email":"","affiliations":[],"preferred":false,"id":471369,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Domingo, F.","contributorId":91776,"corporation":false,"usgs":true,"family":"Domingo","given":"F.","email":"","affiliations":[],"preferred":false,"id":471368,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belnap, J. 0000-0001-7471-2279","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":23872,"corporation":false,"usgs":true,"family":"Belnap","given":"J.","affiliations":[],"preferred":false,"id":471366,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70045078,"text":"70045078 - 2013 - Estimating economic losses from earthquakes using an empirical approach","interactions":[],"lastModifiedDate":"2013-05-12T21:46:04","indexId":"70045078","displayToPublicDate":"2013-05-12T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Estimating economic losses from earthquakes using an empirical approach","docAbstract":"We extended the U.S. Geological Survey's Prompt Assessment of Global Earthquakes for Response (PAGER) empirical fatality estimation methodology proposed by Jaiswal et al. (2009) to rapidly estimate economic losses after significant earthquakes worldwide. The requisite model inputs are shaking intensity estimates made by the ShakeMap system, the spatial distribution of population available from the LandScan database, modern and historic country or sub-country population and Gross Domestic Product (GDP) data, and economic loss data from Munich Re's historical earthquakes catalog. We developed a strategy to approximately scale GDP-based economic exposure for historical and recent earthquakes in order to estimate economic losses. The process consists of using a country-specific multiplicative factor to accommodate the disparity between economic exposure and the annual per capita GDP, and it has proven successful in hindcast-ing past losses. Although loss, population, shaking estimates, and economic data used in the calibration process are uncertain, approximate ranges of losses can be estimated for the primary purpose of gauging the overall scope of the disaster and coordinating response. The proposed methodology is both indirect and approximate and is thus best suited as a rapid loss estimation model for applications like the PAGER system.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Earthquake Spectra","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"EERI","doi":"10.1193/1.4000104","usgsCitation":"Jaiswal, K., and Wald, D.J., 2013, Estimating economic losses from earthquakes using an empirical approach: Earthquake Spectra, v. 29, no. 1, p. 309-324, https://doi.org/10.1193/1.4000104.","productDescription":"16 p.","startPage":"309","endPage":"324","ipdsId":"IP-037500","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":272191,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272190,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1193/1.4000104"}],"volume":"29","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-02-01","publicationStatus":"PW","scienceBaseUri":"5190abcee4b05ebc8f7cc329","contributors":{"authors":[{"text":"Jaiswal, Kishor kjaiswal@usgs.gov","contributorId":861,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":false,"id":476745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":476744,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70045934,"text":"70045934 - 2013 - Simulating mechanisms for dispersal, production and stranding of small forage fish in temporary wetland habitats","interactions":[],"lastModifiedDate":"2013-05-11T23:50:49","indexId":"70045934","displayToPublicDate":"2013-05-11T00:00:00","publicationYear":"2013","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":"Simulating mechanisms for dispersal, production and stranding of small forage fish in temporary wetland habitats","docAbstract":"Movement strategies of small forage fish (<8 cm total length) between temporary and permanent wetland habitats affect their overall population growth and biomass concentrations, i.e., availability to predators. These fish are often the key energy link between primary producers and top predators, such as wading birds, which require high concentrations of stranded fish in accessible depths. Expansion and contraction of seasonal wetlands induce a sequential alternation between rapid biomass growth and concentration, creating the conditions for local stranding of small fish as they move in response to varying water levels. To better understand how landscape topography, hydrology, and fish behavior interact to create high densities of stranded fish, we first simulated population dynamics of small fish, within a dynamic food web, with different traits for movement strategy and growth rate, across an artificial, spatially explicit, heterogeneous, two-dimensional marsh slough landscape, using hydrologic variability as the driver for movement. Model output showed that fish with the highest tendency to invade newly flooded marsh areas built up the largest populations over long time periods with stable hydrologic patterns. A higher probability to become stranded had negative effects on long-term population size, and offset the contribution of that species to stranded biomass. The model was next applied to the topography of a 10 km × 10 km area of Everglades landscape. The details of the topography were highly important in channeling fish movements and creating spatiotemporal patterns of fish movement and stranding. This output provides data that can be compared in the future with observed locations of fish biomass concentrations, or such surrogates as phosphorus ‘hotspots’ in the marsh.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Modelling","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2012.11.001","usgsCitation":"Yurek, S., DeAngelis, D., Trexler, J.C., Jopp, F., and Donalson, D.D., 2013, Simulating mechanisms for dispersal, production and stranding of small forage fish in temporary wetland habitats: Ecological Modelling, v. 250, p. 391-401, https://doi.org/10.1016/j.ecolmodel.2012.11.001.","productDescription":"11 p.","startPage":"391","endPage":"401","ipdsId":"IP-038780","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":272189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272188,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolmodel.2012.11.001"}],"volume":"250","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518f5a51e4b05ebc8f7cc30a","contributors":{"authors":[{"text":"Yurek, Simeon 0000-0002-6209-7915 syurek@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-7915","contributorId":103167,"corporation":false,"usgs":true,"family":"Yurek","given":"Simeon","email":"syurek@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":478555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":88015,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald L.","affiliations":[],"preferred":false,"id":478554,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Trexler, Joel C.","contributorId":36267,"corporation":false,"usgs":false,"family":"Trexler","given":"Joel","email":"","middleInitial":"C.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":478551,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jopp, Fred","contributorId":62336,"corporation":false,"usgs":true,"family":"Jopp","given":"Fred","email":"","affiliations":[],"preferred":false,"id":478552,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Donalson, Douglas D.","contributorId":74660,"corporation":false,"usgs":true,"family":"Donalson","given":"Douglas","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":478553,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70045935,"text":"sir20135079 - 2013 - Groundwater depletion in the United States (1900−2008)","interactions":[],"lastModifiedDate":"2018-05-22T09:57:25","indexId":"sir20135079","displayToPublicDate":"2013-05-10T00:00:00","publicationYear":"2013","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":"2013-5079","title":"Groundwater depletion in the United States (1900−2008)","docAbstract":"A natural consequence of groundwater withdrawals is the removal of water from subsurface storage, but the overall rates and magnitude of groundwater depletion in the United States are not well characterized. This study evaluates long-term cumulative depletion volumes in 40 separate aquifers or areas and one land use category in the United States, bringing together information from the literature and from new analyses. Depletion is directly calculated using calibrated groundwater models, analytical approaches, or volumetric budget analyses for multiple aquifer systems. Estimated groundwater depletion in the United States during 1900–2008 totals approximately 1,000 cubic kilometers (km<sup>3</sup>). Furthermore, the rate of groundwater depletion has increased markedly since about 1950, with maximum rates occurring during the most recent period (2000–2008) when the depletion rate averaged almost 25 km<sup>3</sup> per year (compared to 9.2 km<sup>3</sup> per year averaged over the 1900–2008 timeframe).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135079","usgsCitation":"Konikow, L.F., 2013, Groundwater depletion in the United States (1900−2008): U.S. Geological Survey Scientific Investigations Report 2013-5079, viii, 65 p., https://doi.org/10.3133/sir20135079.","productDescription":"viii, 65 p.","numberOfPages":"75","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1900-01-01","temporalEnd":"2008-12-31","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":272180,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135079.gif"},{"id":272178,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5079/"},{"id":272179,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5079/SIR2013-5079.pdf"},{"id":354382,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/sir2013-5079_Groundwater_Depletion.xml"}],"country":"United States","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-66.28243,18.51476],[-65.7713,18.42668],[-65.591,18.22803],[-65.84716,17.97591],[-66.59993,17.98182],[-67.18416,17.94655],[-67.24243,18.37446],[-67.10068,18.5206],[-66.28243,18.51476]]],[[[-155.54211,19.08348],[-155.68817,18.91619],[-155.93665,19.05939],[-155.90806,19.33888],[-156.07347,19.70294],[-156.02368,19.81422],[-155.85008,19.97729],[-155.91907,20.17395],[-155.86108,20.26721],[-155.78505,20.2487],[-155.40214,20.07975],[-155.22452,19.99302],[-155.06226,19.8591],[-154.80741,19.50871],[-154.83147,19.45328],[-155.22217,19.23972],[-155.54211,19.08348]]],[[[-156.07926,20.64397],[-156.41445,20.57241],[-156.58673,20.783],[-156.70167,20.8643],[-156.71055,20.92676],[-156.61258,21.01249],[-156.25711,20.91745],[-155.99566,20.76404],[-156.07926,20.64397]]],[[[-156.75824,21.17684],[-156.78933,21.06873],[-157.32521,21.09777],[-157.25027,21.21958],[-156.75824,21.17684]]],[[[-157.65283,21.32217],[-157.70703,21.26442],[-157.7786,21.27729],[-158.12667,21.31244],[-158.2538,21.53919],[-158.29265,21.57912],[-158.0252,21.71696],[-157.94161,21.65272],[-157.65283,21.32217]]],[[[-159.34512,21.982],[-159.46372,21.88299],[-159.80051,22.06533],[-159.74877,22.1382],[-159.5962,22.23618],[-159.36569,22.21494],[-159.34512,21.982]]],[[[-94.81758,49.38905],[-94.64,48.84],[-94.32914,48.67074],[-93.63087,48.60926],[-92.61,48.45],[-91.64,48.14],[-90.83,48.27],[-89.6,48.01],[-89.27292,48.01981],[-88.37811,48.30292],[-87.43979,47.94],[-86.46199,47.55334],[-85.65236,47.22022],[-84.87608,46.90008],[-84.77924,46.6371],[-84.54375,46.53868],[-84.6049,46.4396],[-84.3367,46.40877],[-84.14212,46.51223],[-84.09185,46.27542],[-83.89077,46.11693],[-83.61613,46.11693],[-83.46955,45.99469],[-83.59285,45.81689],[-82.55092,45.34752],[-82.33776,44.44],[-82.13764,43.57109],[-82.43,42.98],[-82.9,42.43],[-83.12,42.08],[-83.142,41.97568],[-83.02981,41.8328],[-82.69009,41.67511],[-82.43928,41.67511],[-81.27775,42.20903],[-80.24745,42.3662],[-78.93936,42.86361],[-78.92,42.965],[-79.01,43.27],[-79.17167,43.46634],[-78.72028,43.62509],[-77.73789,43.62906],[-76.82003,43.62878],[-76.5,44.01846],[-76.375,44.09631],[-75.31821,44.81645],[-74.867,45.00048],[-73.34783,45.00738],[-71.50506,45.0082],[-71.405,45.255],[-71.08482,45.30524],[-70.66,45.46],[-70.305,45.915],[-69.99997,46.69307],[-69.23722,47.44778],[-68.905,47.185],[-68.23444,47.35486],[-67.79046,47.06636],[-67.79134,45.70281],[-67.13741,45.13753],[-66.96466,44.8097],[-68.03252,44.3252],[-69.06,43.98],[-70.11617,43.68405],[-70.64548,43.09024],[-70.81489,42.8653],[-70.825,42.335],[-70.495,41.805],[-70.08,41.78],[-70.185,42.145],[-69.88497,41.92283],[-69.96503,41.63717],[-70.64,41.475],[-71.12039,41.49445],[-71.86,41.32],[-72.295,41.27],[-72.87643,41.22065],[-73.71,40.9311],[-72.24126,41.11948],[-71.945,40.93],[-73.345,40.63],[-73.982,40.628],[-73.95232,40.75075],[-74.25671,40.47351],[-73.96244,40.42763],[-74.17838,39.70926],[-74.90604,38.93954],[-74.98041,39.1964],[-75.20002,39.24845],[-75.52805,39.4985],[-75.32,38.96],[-75.07183,38.78203],[-75.05673,38.40412],[-75.37747,38.01551],[-75.94023,37.21689],[-76.03127,37.2566],[-75.72205,37.93705],[-76.23287,38.31921],[-76.35,39.15],[-76.54272,38.71762],[-76.32933,38.08326],[-76.99,38.23999],[-76.30162,37.91794],[-76.25874,36.9664],[-75.9718,36.89726],[-75.86804,36.55125],[-75.72749,35.55074],[-76.36318,34.80854],[-77.39763,34.51201],[-78.05496,33.92547],[-78.55435,33.86133],[-79.06067,33.49395],[-79.20357,33.15839],[-80.30132,32.50935],[-80.86498,32.0333],[-81.33629,31.44049],[-81.49042,30.72999],[-81.31371,30.03552],[-80.98,29.18],[-80.53558,28.47213],[-80.53,28.04],[-80.05654,26.88],[-80.08801,26.20576],[-80.13156,25.81677],[-80.38103,25.20616],[-80.68,25.08],[-81.17213,25.20126],[-81.33,25.64],[-81.71,25.87],[-82.24,26.73],[-82.70515,27.49504],[-82.85526,27.88624],[-82.65,28.55],[-82.93,29.1],[-83.70959,29.93656],[-84.1,30.09],[-85.10882,29.63615],[-85.28784,29.68612],[-85.7731,30.15261],[-86.4,30.4],[-87.53036,30.27433],[-88.41782,30.3849],[-89.18049,30.31598],[-89.59383,30.15999],[-89.41373,29.89419],[-89.43,29.48864],[-89.21767,29.29108],[-89.40823,29.15961],[-89.77928,29.30714],[-90.15463,29.11743],[-90.88022,29.14854],[-91.62678,29.677],[-92.49906,29.5523],[-93.22637,29.78375],[-93.84842,29.71363],[-94.69,29.48],[-95.60026,28.73863],[-96.59404,28.30748],[-97.14,27.83],[-97.37,27.38],[-97.38,26.69],[-97.33,26.21],[-97.14,25.87],[-97.53,25.84],[-98.24,26.06],[-99.02,26.37],[-99.3,26.84],[-99.52,27.54],[-100.11,28.11],[-100.45584,28.69612],[-100.9576,29.38071],[-101.6624,29.7793],[-102.48,29.76],[-103.11,28.97],[-103.94,29.27],[-104.45697,29.57196],[-104.70575,30.12173],[-105.03737,30.64402],[-105.63159,31.08383],[-106.1429,31.39995],[-106.50759,31.75452],[-108.24,31.75485],[-108.24194,31.34222],[-109.035,31.34194],[-111.02361,31.33472],[-113.30498,32.03914],[-114.815,32.52528],[-114.72139,32.72083],[-115.99135,32.61239],[-117.12776,32.53534],[-117.29594,33.04622],[-117.944,33.62124],[-118.4106,33.74091],[-118.51989,34.02778],[-119.081,34.078],[-119.43884,34.34848],[-120.36778,34.44711],[-120.62286,34.60855],[-120.74433,35.15686],[-121.71457,36.16153],[-122.54747,37.55176],[-122.51201,37.78339],[-122.95319,38.11371],[-123.7272,38.95166],[-123.86517,39.76699],[-124.39807,40.3132],[-124.17886,41.14202],[-124.2137,41.99964],[-124.53284,42.76599],[-124.14214,43.70838],[-124.02053,44.6159],[-123.89893,45.52341],[-124.07963,46.86475],[-124.39567,47.72017],[-124.68721,48.18443],[-124.5661,48.37971],[-123.12,48.04],[-122.58736,47.096],[-122.34,47.36],[-122.5,48.18],[-122.84,49],[-120,49],[-117.03121,49],[-116.04818,49],[-113,49],[-110.05,49],[-107.05,49],[-104.04826,48.99986],[-100.65,49],[-97.22872,49.0007],[-95.15907,49],[-95.15609,49.38425],[-94.81758,49.38905]]],[[[-153.00631,57.11584],[-154.00509,56.73468],[-154.5164,56.99275],[-154.67099,57.4612],[-153.76278,57.81657],[-153.22873,57.96897],[-152.56479,57.90143],[-152.14115,57.59106],[-153.00631,57.11584]]],[[[-165.57916,59.90999],[-166.19277,59.75444],[-166.84834,59.94141],[-167.45528,60.21307],[-166.46779,60.38417],[-165.67443,60.29361],[-165.57916,59.90999]]],[[[-171.73166,63.78252],[-171.11443,63.59219],[-170.49111,63.69498],[-169.68251,63.43112],[-168.68944,63.29751],[-168.77194,63.1886],[-169.52944,62.97693],[-170.29056,63.19444],[-170.67139,63.37582],[-171.55306,63.31779],[-171.79111,63.40585],[-171.73166,63.78252]]],[[[-155.06779,71.14778],[-154.34417,70.69641],[-153.90001,70.88999],[-152.21001,70.82999],[-152.27,70.60001],[-150.73999,70.43002],[-149.72,70.53001],[-147.61336,70.21403],[-145.68999,70.12001],[-144.92001,69.98999],[-143.58945,70.15251],[-142.07251,69.85194],[-140.98599,69.712],[-140.9925,66.00003],[-140.99777,60.3064],[-140.013,60.27684],[-139.039,60.00001],[-138.34089,59.56211],[-137.4525,58.905],[-136.47972,59.46389],[-135.47583,59.78778],[-134.945,59.27056],[-134.27111,58.86111],[-133.35555,58.41029],[-132.73042,57.69289],[-131.70781,56.55212],[-130.00778,55.91583],[-129.97999,55.285],[-130.53611,54.80275],[-131.08582,55.17891],[-131.96721,55.49778],[-132.25001,56.37],[-133.53918,57.17889],[-134.07806,58.12307],[-135.03821,58.18771],[-136.62806,58.21221],[-137.80001,58.5],[-139.86779,59.53776],[-140.82527,59.72752],[-142.57444,60.08445],[-143.95888,59.99918],[-145.92556,60.45861],[-147.11437,60.88466],[-148.22431,60.67299],[-148.01807,59.97833],[-148.57082,59.91417],[-149.72786,59.70566],[-150.60824,59.36821],[-151.71639,59.15582],[-151.85943,59.74498],[-151.40972,60.7258],[-150.34694,61.03359],[-150.62111,61.28442],[-151.89584,60.7272],[-152.57833,60.06166],[-154.01917,59.35028],[-153.28751,58.86473],[-154.23249,58.14637],[-155.30749,57.72779],[-156.30833,57.42277],[-156.5561,56.97998],[-158.11722,56.46361],[-158.43332,55.99415],[-159.60333,55.56669],[-160.28972,55.64358],[-161.22305,55.36473],[-162.23777,55.02419],[-163.06945,54.68974],[-164.78557,54.40417],[-164.94223,54.57222],[-163.84834,55.03943],[-162.87,55.34804],[-161.80417,55.89499],[-160.5636,56.00805],[-160.07056,56.41806],[-158.68444,57.01668],[-158.4611,57.21692],[-157.72277,57.57],[-157.55027,58.32833],[-157.04167,58.91888],[-158.19473,58.6158],[-158.51722,58.78778],[-159.05861,58.42419],[-159.71167,58.93139],[-159.98129,58.57255],[-160.35527,59.07112],[-161.355,58.67084],[-161.96889,58.67166],[-162.05499,59.26693],[-161.87417,59.63362],[-162.51806,59.98972],[-163.81834,59.79806],[-164.66222,60.26748],[-165.34639,60.5075],[-165.35083,61.0739],[-166.12138,61.50002],[-165.73445,62.075],[-164.91918,62.63308],[-164.56251,63.14638],[-163.75333,63.21945],[-163.06722,63.05946],[-162.26056,63.54194],[-161.53445,63.45582],[-160.77251,63.76611],[-160.95834,64.2228],[-161.51807,64.40279],[-160.77778,64.7886],[-161.39193,64.77724],[-162.45305,64.55944],[-162.75779,64.33861],[-163.54639,64.55916],[-164.96083,64.44695],[-166.42529,64.68667],[-166.845,65.0889],[-168.11056,65.67],[-166.70527,66.08832],[-164.47471,66.57666],[-163.65251,66.57666],[-163.7886,66.07721],[-161.67777,66.11612],[-162.48971,66.73557],[-163.71972,67.11639],[-164.43099,67.61634],[-165.39029,68.04277],[-166.76444,68.35888],[-166.20471,68.88303],[-164.43081,68.91554],[-163.16861,69.37111],[-162.93057,69.85806],[-161.9089,70.33333],[-160.9348,70.44769],[-159.03918,70.89164],[-158.11972,70.82472],[-156.58082,71.35776],[-155.06779,71.14778]]]]},\"properties\":{\"name\":\"United States\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518e08f6e4b05ebc8f7cc2d6","contributors":{"authors":[{"text":"Konikow, Leonard F. 0000-0002-0940-3856 lkonikow@usgs.gov","orcid":"https://orcid.org/0000-0002-0940-3856","contributorId":158,"corporation":false,"usgs":true,"family":"Konikow","given":"Leonard","email":"lkonikow@usgs.gov","middleInitial":"F.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":478556,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70045932,"text":"ofr20121038 - 2013 - Tidal wetlands of the Yaquina and Alsea River estuaries, Oregon: Geographic Information Systems layer development and recommendations for National Wetlands Inventory revisions","interactions":[],"lastModifiedDate":"2016-05-04T14:44:24","indexId":"ofr20121038","displayToPublicDate":"2013-05-10T00:00:00","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":"2012-1038","title":"Tidal wetlands of the Yaquina and Alsea River estuaries, Oregon: Geographic Information Systems layer development and recommendations for National Wetlands Inventory revisions","docAbstract":"<p>Geographic Information Systems (GIS) layers of current, and likely former, tidal wetlands in two Oregon estuaries were generated by enhancing the 2010 National Wetlands Inventory (NWI) data with expert local field knowledge, Light Detection and Ranging-derived elevations, and 2009 aerial orthophotographs. Data were generated for two purposes: First, to enhance the NWI by recommending revised Cowardin classifications for certain NWI wetlands within the study area; and second, to generate GIS data for the 1999 Yaquina and Alsea River Basins Estuarine Wetland Site Prioritization study. Two sets of GIS products were generated: (1) enhanced NWI shapefiles; and (2) shapefiles of prioritization sites. The enhanced NWI shapefiles contain recommended changes to the Cowardin classification (system, subsystem, class, and/or modifiers) for 286 NWI polygons in the Yaquina estuary (1,133 acres) and 83 NWI polygons in the Alsea estuary (322 acres). These enhanced NWI shapefiles also identify likely former tidal wetlands that are classified as upland in the current NWI (64 NWI polygons totaling 441 acres in the Yaquina estuary; 16 NWI polygons totaling 51 acres in the Alsea estuary). The former tidal wetlands were identified to assist strategic planning for tidal wetland restoration. Cowardin classifications for the former tidal wetlands were not provided, because their current hydrology is complex owing to dikes, tide gates, and drainage ditches. The scope of this project did not include the field evaluation that would be needed to determine whether the former tidal wetlands are currently wetlands, and if so, determine their correct Cowardin classification. The prioritization site shapefiles contain 49 prioritization sites totaling 2,177 acres in the Yaquina estuary, and 39 prioritization sites totaling 1,045 acres in the Alsea estuary. The prioritization sites include current and former (for example, diked) tidal wetlands, and provide landscape units appropriate for basin-scale wetland restoration and conservation action planning. Several new prioritization sites (not included in the 1999 prioritization) were identified in each estuary, consisting of NWI polygons formerly classified as nontidal wetland or upland. The GIS products of this project improve the accuracy and utility of the NWI data, and provide useful tools for estuarine resource management.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121038","collaboration":"Prepared in cooperation with Green Point Consulting and the U.S. Environmental Protection Agency","usgsCitation":"Brophy, L.S., Reusser, D.A., and Janousek, C.N., 2013, Tidal wetlands of the Yaquina and Alsea River estuaries, Oregon: Geographic Information Systems layer development and recommendations for National Wetlands Inventory revisions: U.S. Geological Survey Open-File Report 2012-1038, vi, 60 p., https://doi.org/10.3133/ofr20121038.","productDescription":"vi, 60 p.","numberOfPages":"68","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":272177,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121038.gif"},{"id":272323,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1038/"},{"id":272176,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1038/pdf/ofr2012-1038.pdf","text":"Report","size":"18.86 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Oregon","otherGeospatial":"Yaquina And Alsea Estuaries","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.16,44.16 ], [ -124.16,44.5 ], [ -123.5,44.5 ], [ -123.5,44.16 ], [ -124.16,44.16 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518e08f7e4b05ebc8f7cc2de","contributors":{"authors":[{"text":"Brophy, Laura S.","contributorId":47266,"corporation":false,"usgs":false,"family":"Brophy","given":"Laura","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":478548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reusser, Deborah A. dreusser@usgs.gov","contributorId":2423,"corporation":false,"usgs":true,"family":"Reusser","given":"Deborah","email":"dreusser@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":547809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Janousek, Christopher N. 0000-0003-2124-6715","orcid":"https://orcid.org/0000-0003-2124-6715","contributorId":103951,"corporation":false,"usgs":false,"family":"Janousek","given":"Christopher","email":"","middleInitial":"N.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":478549,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70045937,"text":"ofr20131055 - 2013 - National assessment of geologic carbon dioxide storage resources: methodology implementation","interactions":[],"lastModifiedDate":"2013-10-30T13:32:59","indexId":"ofr20131055","displayToPublicDate":"2013-05-10T00:00:00","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":"2013-1055","title":"National assessment of geologic carbon dioxide storage resources: methodology implementation","docAbstract":"In response to the 2007 Energy Independence and Security Act, the U.S. Geological Survey (USGS) conducted a national assessment of potential geologic storage resources for carbon dioxide (CO2). Storage of CO2 in subsurface saline formations is one important method to reduce greenhouse gas emissions and curb global climate change. This report provides updates and implementation details of the assessment methodology of Brennan and others (2010, http://pubs.usgs.gov/of/2010/1127/) and describes the probabilistic model used to calculate potential storage resources in subsurface saline formations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131055","usgsCitation":"Blondes, M., Brennan, S.T., Merrill, M., Buursink, M.L., Warwick, P.D., Cahan, S.M., Corum, M., Cook, T.A., Craddock, W.H., DeVera, C.A., Drake, R.M., Drew, L.J., Freeman, P., Lohr, C., Olea, R., Roberts-Ashby, T., Slucher, E.R., and Varela, B., 2013, National assessment of geologic carbon dioxide storage resources: methodology implementation: U.S. Geological Survey Open-File Report 2013-1055, vii, 27 p., https://doi.org/10.3133/ofr20131055.","productDescription":"vii, 27 p.","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":272187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131055.gif"},{"id":272185,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1055/"},{"id":272186,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1055/OF13-1055.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518e08f7e4b05ebc8f7cc2da","contributors":{"authors":[{"text":"Blondes, Madalyn S. 0000-0003-0320-0107 mblondes@usgs.gov","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":3598,"corporation":false,"usgs":true,"family":"Blondes","given":"Madalyn S.","email":"mblondes@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":478570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brennan, Sean T. 0000-0002-7102-9359 sbrennan@usgs.gov","orcid":"https://orcid.org/0000-0002-7102-9359","contributorId":559,"corporation":false,"usgs":true,"family":"Brennan","given":"Sean","email":"sbrennan@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":478562,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merrill, Matthew D. 0000-0003-3766-847X","orcid":"https://orcid.org/0000-0003-3766-847X","contributorId":48256,"corporation":false,"usgs":true,"family":"Merrill","given":"Matthew D.","affiliations":[],"preferred":false,"id":478576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buursink, Marc L. 0000-0001-6491-386X mbuursink@usgs.gov","orcid":"https://orcid.org/0000-0001-6491-386X","contributorId":3362,"corporation":false,"usgs":true,"family":"Buursink","given":"Marc","email":"mbuursink@usgs.gov","middleInitial":"L.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":478568,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Warwick, Peter D. 0000-0002-3152-7783 pwarwick@usgs.gov","orcid":"https://orcid.org/0000-0002-3152-7783","contributorId":762,"corporation":false,"usgs":true,"family":"Warwick","given":"Peter","email":"pwarwick@usgs.gov","middleInitial":"D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":478563,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cahan, Steven M. 0000-0002-4776-3668 scahan@usgs.gov","orcid":"https://orcid.org/0000-0002-4776-3668","contributorId":4529,"corporation":false,"usgs":true,"family":"Cahan","given":"Steven","email":"scahan@usgs.gov","middleInitial":"M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":478574,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Corum, M.D. 0000-0002-9038-3935 mcorum@usgs.gov","orcid":"https://orcid.org/0000-0002-9038-3935","contributorId":2249,"corporation":false,"usgs":true,"family":"Corum","given":"M.D.","email":"mcorum@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":478565,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cook, Troy A.","contributorId":52519,"corporation":false,"usgs":true,"family":"Cook","given":"Troy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":478577,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Craddock, William H. 0000-0002-4181-4735 wcraddock@usgs.gov","orcid":"https://orcid.org/0000-0002-4181-4735","contributorId":3411,"corporation":false,"usgs":true,"family":"Craddock","given":"William","email":"wcraddock@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":478569,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"DeVera, Christina A. 0000-0002-4691-6108 cdevera@usgs.gov","orcid":"https://orcid.org/0000-0002-4691-6108","contributorId":3845,"corporation":false,"usgs":true,"family":"DeVera","given":"Christina","email":"cdevera@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":478571,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Drake, Ronald M. II 0000-0002-1770-4667 rmdrake@usgs.gov","orcid":"https://orcid.org/0000-0002-1770-4667","contributorId":1353,"corporation":false,"usgs":true,"family":"Drake","given":"Ronald","suffix":"II","email":"rmdrake@usgs.gov","middleInitial":"M.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":478564,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Drew, Lawrence J. ldrew@usgs.gov","contributorId":2635,"corporation":false,"usgs":true,"family":"Drew","given":"Lawrence","email":"ldrew@usgs.gov","middleInitial":"J.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":478566,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Freeman, P.A. 0000-0002-0863-7431 pfreeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":3154,"corporation":false,"usgs":true,"family":"Freeman","given":"P.A.","email":"pfreeman@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":478567,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Lohr, Celeste D. 0000-0001-6287-9047 clohr@usgs.gov","orcid":"https://orcid.org/0000-0001-6287-9047","contributorId":3866,"corporation":false,"usgs":true,"family":"Lohr","given":"Celeste D.","email":"clohr@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":478572,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":47873,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":478575,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Roberts-Ashby, Tina L. 0000-0003-2940-1740","orcid":"https://orcid.org/0000-0003-2940-1740","contributorId":62103,"corporation":false,"usgs":true,"family":"Roberts-Ashby","given":"Tina L.","affiliations":[],"preferred":false,"id":478578,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Slucher, Ernie R. 0000-0002-5865-5734 eslucher@usgs.gov","orcid":"https://orcid.org/0000-0002-5865-5734","contributorId":3966,"corporation":false,"usgs":true,"family":"Slucher","given":"Ernie","email":"eslucher@usgs.gov","middleInitial":"R.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":478573,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Varela, Brian A. 0000-0001-9849-6742","orcid":"https://orcid.org/0000-0001-9849-6742","contributorId":62495,"corporation":false,"usgs":true,"family":"Varela","given":"Brian A.","affiliations":[],"preferred":false,"id":478579,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70042766,"text":"70042766 - 2013 - Ecosystem services from keystone species: diversionary seeding and seed-caching desert rodents can enhance Indian ricegrass seedling establishment","interactions":[],"lastModifiedDate":"2013-05-09T09:16:39","indexId":"70042766","displayToPublicDate":"2013-05-09T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem services from keystone species: diversionary seeding and seed-caching desert rodents can enhance Indian ricegrass seedling establishment","docAbstract":"Seeds of Indian ricegrass (Achnatherum hymenoides), a native bunchgrass common to sandy soils on arid western rangelands, are naturally dispersed by seed-caching rodent species, particularly Dipodomys spp. (kangaroo rats). These animals cache large quantities of seeds when mature seeds are available on or beneath plants and recover most of their caches for consumption during the remainder of the year. Unrecovered seeds in caches account for the vast majority of Indian ricegrass seedling recruitment. We applied three different densities of white millet (Panicum miliaceum) seeds as “diversionary foods” to plots at three Great Basin study sites in an attempt to reduce rodents' over-winter cache recovery so that more Indian ricegrass seeds would remain in soil seedbanks and potentially establish new seedlings. One year after diversionary seed application, a moderate level of Indian ricegrass seedling recruitment occurred at two of our study sites in western Nevada, although there was no recruitment at the third site in eastern California. At both Nevada sites, the number of Indian ricegrass seedlings sampled along transects was significantly greater on all plots treated with diversionary seeds than on non-seeded control plots. However, the density of diversionary seeds applied to plots had a marginally non-significant effect on seedling recruitment, and it was not correlated with recruitment patterns among plots. Results suggest that application of a diversionary seed type that is preferred by seed-caching rodents provides a promising passive restoration strategy for target plant species that are dispersed by these rodents.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Restoration Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/j.1526-100X.2012.00895.x","usgsCitation":"Longland, W., and Ostoja, S.M., 2013, Ecosystem services from keystone species: diversionary seeding and seed-caching desert rodents can enhance Indian ricegrass seedling establishment: Restoration Ecology, v. 21, no. 2, p. 285-291, https://doi.org/10.1111/j.1526-100X.2012.00895.x.","productDescription":"7 p.","startPage":"285","endPage":"291","ipdsId":"IP-032558","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":272121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272120,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1526-100X.2012.00895.x"}],"country":"United States","state":"California;Nevada","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,32.53 ], [ -124.41,42.0 ], [ -114.0,42.0 ], [ -114.0,32.53 ], [ -124.41,32.53 ] ] ] } } ] }","volume":"21","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-07-06","publicationStatus":"PW","scienceBaseUri":"518cb759e4b05ebc8f7cc0dc","contributors":{"authors":[{"text":"Longland, William","contributorId":73899,"corporation":false,"usgs":true,"family":"Longland","given":"William","affiliations":[],"preferred":false,"id":472211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ostoja, Steven M. sostoja@usgs.gov","contributorId":3039,"corporation":false,"usgs":true,"family":"Ostoja","given":"Steven","email":"sostoja@usgs.gov","middleInitial":"M.","affiliations":[{"id":33665,"text":"USDA California Climate Hub, UC Davis","active":true,"usgs":false},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":472210,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70045856,"text":"70045856 - 2013 - Investigating the effects of point source and nonpoint source pollution on the water quality of the East River (Dongjiang) in South China","interactions":[],"lastModifiedDate":"2013-05-07T14:25:21","indexId":"70045856","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Investigating the effects of point source and nonpoint source pollution on the water quality of the East River (Dongjiang) in South China","docAbstract":"Understanding the physical processes of point source (PS) and nonpoint source (NPS) pollution is critical to evaluate river water quality and identify major pollutant sources in a watershed. In this study, we used the physically-based hydrological/water quality model, Soil and Water Assessment Tool, to investigate the influence of PS and NPS pollution on the water quality of the East River (Dongjiang in Chinese) in southern China. Our results indicate that NPS pollution was the dominant contribution (>94%) to nutrient loads except for mineral phosphorus (50%). A comprehensive Water Quality Index (WQI) computed using eight key water quality variables demonstrates that water quality is better upstream than downstream despite the higher level of ammonium nitrogen found in upstream waters. Also, the temporal (seasonal) and spatial distributions of nutrient loads clearly indicate the critical time period (from late dry season to early wet season) and pollution source areas within the basin (middle and downstream agricultural lands), which resource managers can use to accomplish substantial reduction of NPS pollutant loadings. Overall, this study helps our understanding of the relationship between human activities and pollutant loads and further contributes to decision support for local watershed managers to protect water quality in this region. In particular, the methods presented such as integrating WQI with watershed modeling and identifying the critical time period and pollutions source areas can be valuable for other researchers worldwide.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Indicators","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2013.04.002","usgsCitation":"Wu, Y., and Chen, J., 2013, Investigating the effects of point source and nonpoint source pollution on the water quality of the East River (Dongjiang) in South China: Ecological Indicators, v. 32, p. 294-304, https://doi.org/10.1016/j.ecolind.2013.04.002.","productDescription":"11 p.","startPage":"294","endPage":"304","ipdsId":"IP-044856","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":272033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272011,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolind.2013.04.002"}],"country":"China","otherGeospatial":"Dongjiang","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 73.5,18.2 ], [ 73.5,53.6 ], [ 134.8,53.6 ], [ 134.8,18.2 ], [ 73.5,18.2 ] ] ] } } ] }","volume":"32","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518a145be4b061e1bd53333f","contributors":{"authors":[{"text":"Wu, Yiping ywu@usgs.gov","contributorId":987,"corporation":false,"usgs":true,"family":"Wu","given":"Yiping","email":"ywu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":478440,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Ji","contributorId":101960,"corporation":false,"usgs":true,"family":"Chen","given":"Ji","email":"","affiliations":[],"preferred":false,"id":478441,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70042647,"text":"70042647 - 2013 - Practical guidance on characterizing availability in resource selection functions under a use-availability design","interactions":[],"lastModifiedDate":"2013-07-15T09:20:03","indexId":"70042647","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Practical guidance on characterizing availability in resource selection functions under a use-availability design","docAbstract":"Habitat selection is a fundamental aspect of animal ecology, the understanding of which is critical to management and conservation. Global positioning system data from animals allow fine-scale assessments of habitat selection and typically are analyzed in a use-availability framework, whereby animal locations are contrasted with random locations (the availability sample). Although most use-availability methods are in fact spatial point process models, they often are fit using logistic regression. This framework offers numerous methodological challenges, for which the literature provides little guidance. Specifically, the size and spatial extent of the availability sample influences coefficient estimates potentially causing interpretational bias. We examined the influence of availability on statistical inference through simulations and analysis of serially correlated mule deer GPS data. Bias in estimates arose from incorrectly assessing and sampling the spatial extent of availability. Spatial autocorrelation in covariates, which is common for landscape characteristics, exacerbated the error in availability sampling leading to increased bias. These results have strong implications for habitat selection analyses using GPS data, which are increasingly prevalent in the literature. We recommend researchers assess the sensitivity of their results to their availability sample and, where bias is likely, take care with interpretations and use cross validation to assess robustness.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","doi":"10.1890/12-1688.1","usgsCitation":"Northrup, J.M., Hooten, M., Anderson, C.R., and Wittemyer, G., 2013, Practical guidance on characterizing availability in resource selection functions under a use-availability design: Ecology, v. 94, no. 7, p. 1456-1463, https://doi.org/10.1890/12-1688.1.","productDescription":"8 p.","startPage":"1456","endPage":"1463","ipdsId":"IP-040982","costCenters":[{"id":189,"text":"Colorado Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":473839,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/12-1688.1","text":"Publisher Index Page"},{"id":271952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271946,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/12-1688.1"}],"volume":"94","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518a145de4b061e1bd53334b","contributors":{"authors":[{"text":"Northrup, Joseph M.","contributorId":101965,"corporation":false,"usgs":true,"family":"Northrup","given":"Joseph","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":471981,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":471978,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Charles R. Jr.","contributorId":75042,"corporation":false,"usgs":true,"family":"Anderson","given":"Charles","suffix":"Jr.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":471980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wittemyer, George","contributorId":25058,"corporation":false,"usgs":true,"family":"Wittemyer","given":"George","affiliations":[],"preferred":false,"id":471979,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70045859,"text":"70045859 - 2013 - Analyzing the water budget and hydrological characteristics and responses to land use in a monsoonal climate river basin in South China","interactions":[],"lastModifiedDate":"2013-06-17T09:24:06","indexId":"70045859","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Analyzing the water budget and hydrological characteristics and responses to land use in a monsoonal climate river basin in South China","docAbstract":"Hydrological models have been increasingly used by hydrologists and water resource managers to understand natural processes and human activities that affect watersheds. In this study, we use the physically based model, Soil and Water Assessment Tool (SWAT), to investigate the hydrological processes in the East River Basin in South China, a coastal area dominated by monsoonal climate. The SWAT model was calibrated using 8-year (1973–1980) record of the daily streamflow at the basin outlet (Boluo station), and then validated using data collected during the subsequent 8 years (1981–1988). Statistical evaluation shows that SWAT can consistently simulate the streamflow of the East River with monthly Nash–Sutcliffe efficiencies of 0.93 for calibration and 0.90 for validation at the Boluo station. We analyzed the model simulations with calibrated parameters, presented the spatiotemporal distribution of the key hydrological components, and quantified their responses to different land uses. Watershed managers can use the results of this study to understand hydrological features and evaluate water resources of the East River in terms of sustainable development and effective management.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s00267-013-0045-5","usgsCitation":"Wu, Y., and Chen, J., 2013, Analyzing the water budget and hydrological characteristics and responses to land use in a monsoonal climate river basin in South China: Environmental Management, v. 51, no. 6, p. 1174-1186, https://doi.org/10.1007/s00267-013-0045-5.","productDescription":"13 p.","startPage":"1174","endPage":"1186","ipdsId":"IP-042191","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":272031,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272012,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00267-013-0045-5"}],"country":"China","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 73.5,18.2 ], [ 73.5,53.6 ], [ 134.8,53.6 ], [ 134.8,18.2 ], [ 73.5,18.2 ] ] ] } } ] }","volume":"51","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-04-23","publicationStatus":"PW","scienceBaseUri":"518a1451e4b061e1bd533337","contributors":{"authors":[{"text":"Wu, Yiping ywu@usgs.gov","contributorId":987,"corporation":false,"usgs":true,"family":"Wu","given":"Yiping","email":"ywu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":478445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Ji","contributorId":101960,"corporation":false,"usgs":true,"family":"Chen","given":"Ji","email":"","affiliations":[],"preferred":false,"id":478446,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70045855,"text":"70045855 - 2013 - Parallelization of a hydrological model using the message passing interface","interactions":[],"lastModifiedDate":"2013-05-07T14:33:07","indexId":"70045855","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Parallelization of a hydrological model using the message passing interface","docAbstract":"With the increasing knowledge about the natural processes, hydrological models such as the Soil and Water Assessment Tool (SWAT) are becoming larger and more complex with increasing computation time. Additionally, other procedures such as model calibration, which may require thousands of model iterations, can increase running time and thus further reduce rapid modeling and analysis. Using the widely-applied SWAT as an example, this study demonstrates how to parallelize a serial hydrological model in a Windows® environment using a parallel programing technology—Message Passing Interface (MPI). With a case study, we derived the optimal values for the two parameters (the number of processes and the corresponding percentage of work to be distributed to the master process) of the parallel SWAT (P-SWAT) on an ordinary personal computer and a work station. Our study indicates that model execution time can be reduced by 42%–70% (or a speedup of 1.74–3.36) using multiple processes (two to five) with a proper task-distribution scheme (between the master and slave processes). Although the computation time cost becomes lower with an increasing number of processes (from two to five), this enhancement becomes less due to the accompanied increase in demand for message passing procedures between the master and all slave processes. Our case study demonstrates that the P-SWAT with a five-process run may reach the maximum speedup, and the performance can be quite stable (fairly independent of a project size). Overall, the P-SWAT can help reduce the computation time substantially for an individual model run, manual and automatic calibration procedures, and optimization of best management practices. In particular, the parallelization method we used and the scheme for deriving the optimal parameters in this study can be valuable and easily applied to other hydrological or environmental models.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Modelling and Software","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2013.02.002","usgsCitation":"Wu, Y., Li, T., Sun, L., and Chen, J., 2013, Parallelization of a hydrological model using the message passing interface: Environmental Modelling and Software, v. 43, p. 124-132, https://doi.org/10.1016/j.envsoft.2013.02.002.","productDescription":"9 p.","startPage":"124","endPage":"132","ipdsId":"IP-044027","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":272036,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272010,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.envsoft.2013.02.002"}],"volume":"43","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518a145de4b061e1bd533347","contributors":{"authors":[{"text":"Wu, Yiping ywu@usgs.gov","contributorId":987,"corporation":false,"usgs":true,"family":"Wu","given":"Yiping","email":"ywu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":478436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Tiejian","contributorId":25437,"corporation":false,"usgs":true,"family":"Li","given":"Tiejian","email":"","affiliations":[],"preferred":false,"id":478438,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sun, Liqun","contributorId":18249,"corporation":false,"usgs":true,"family":"Sun","given":"Liqun","email":"","affiliations":[],"preferred":false,"id":478437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Ji","contributorId":101960,"corporation":false,"usgs":true,"family":"Chen","given":"Ji","email":"","affiliations":[],"preferred":false,"id":478439,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
]}