In mined watersheds, water quality alters aquatic faunas, but few studies have focused on associations between stream habitat and crayfish distributions. We examined associations of water quality and physical habitat quality on presence/absence of six crayfish species in the upper Kanawha River drainage of southern West Virginia, USA, a region with a long history of surface and mountaintop removal mining of coal. Data supported an association of physical habitat quality with the presence of four species (Cambarus carinirostris, Cambarus robustus, Cambarus cf. sciotensis, and Orconectes sanbornii). Cambarus bartonii cavatus and the non-native Orconectes virilis were associated with lower quality physical habitat than that of the other four species. Relative to other species, C. b. cavatus was associated with the lowest conductivity values, whereas O. virilis was associated with the highest conductivity values. Secondary and tertiary burrowers were generally associated with relatively high-quality physical habitat. However, C. b. cavatus, a crayfish known to burrow extensively in headwater streams, was associated with the lowest quality physical habitat. Physical habitat quality was generally supported over stream conductivity as a variable influencing crayfish distributions. Our data demonstrate the importance of stream habitat quality when assessing crayfish assemblages within mined watersheds.
","language":"English","publisher":"Springer International Publishing","doi":"10.1007/s10750-014-2095-y","usgsCitation":"Welsh, S., and Loughman, Z.J., 2014, Physical habitat and water quality correlates of crayfish distributions in a mined watershed: Hydrobiologia, v. 745, no. 1, p. 85-96, https://doi.org/10.1007/s10750-014-2095-y.","productDescription":"12 p.","startPage":"85","endPage":"96","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059642","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323800,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Kanawha River drainage","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.49658203125,\n 38.436379603\n ],\n [\n -81.749267578125,\n 38.47079371120379\n ],\n [\n -81.968994140625,\n 38.33303882235456\n ],\n [\n -82.0458984375,\n 38.09998264736481\n ],\n [\n -81.837158203125,\n 37.84015683604134\n ],\n [\n -81.573486328125,\n 37.779398571318765\n ],\n [\n -81.265869140625,\n 37.71859032558816\n ],\n [\n -81.01318359375,\n 37.79676317682161\n ],\n [\n -80.804443359375,\n 38.09998264736481\n ],\n [\n -81.090087890625,\n 38.41055825094609\n ],\n [\n -81.32080078125,\n 38.436379603\n ],\n [\n -81.49658203125,\n 38.436379603\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"745","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-12","publicationStatus":"PW","scienceBaseUri":"5763cdb8e4b07657d19ba78d","contributors":{"authors":[{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":152088,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart A.","email":"swelsh@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":637100,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loughman, Zachary J.","contributorId":76157,"corporation":false,"usgs":false,"family":"Loughman","given":"Zachary","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":639418,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70128733,"text":"fs20143104 - 2014 - USGS investigations of water produced during hydrocarbon reservoir development","interactions":[],"lastModifiedDate":"2014-11-11T10:58:53","indexId":"fs20143104","displayToPublicDate":"2014-11-11T09:15:00","publicationYear":"2014","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":"2014-3104","title":"USGS investigations of water produced during hydrocarbon reservoir development","docAbstract":"Significant quantities of water are present in hydrocarbon reservoirs. When brought to the land surface during oil, gas, and coalbed methane production, the water—either naturally occurring or injected as a method to enhance production—is termed produced water. Produced water is currently managed through processes such as recycling, treatment and discharge, spreading on roads, evaporation or infiltration, and deep well injection. U.S. Geological Survey (USGS) scientists conduct research and publish data related to produced water, thus providing information and insight to scientists, decisionmakers, the energy industry, and the public. The information advances scientific knowledge, informs resource management decisions, and facilitates environmental protection. This fact sheet discusses integrated research being conducted by USGS scientists supported by programs in the Energy and Minerals and Environmental Health Mission Areas. The research products help inform decisions pertaining to understanding the nature and management of produced water in the United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143104","collaboration":"Integrated Research by the Energy and Minerals and the Environmental Health Mission Areas","usgsCitation":"Engle, M.A., Cozzarelli, I.M., and Smith, B.D., 2014, USGS investigations of water produced during hydrocarbon reservoir development: U.S. Geological Survey Fact Sheet 2014-3104, 4 p., https://doi.org/10.3133/fs20143104.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056678","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":295981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143104.jpg"},{"id":295979,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3104/"},{"id":295980,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3104/pdf/fs2014-3104.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5463251fe4b0ba83040c6a5d","contributors":{"authors":[{"text":"Engle, Mark A. 0000-0001-5258-7374 engle@usgs.gov","orcid":"https://orcid.org/0000-0001-5258-7374","contributorId":584,"corporation":false,"usgs":true,"family":"Engle","given":"Mark","email":"engle@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":519754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cozzarelli, Isabelle M. 0000-0002-5123-1007 icozzare@usgs.gov","orcid":"https://orcid.org/0000-0002-5123-1007","contributorId":1693,"corporation":false,"usgs":true,"family":"Cozzarelli","given":"Isabelle","email":"icozzare@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":519756,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Bruce D. 0000-0002-1643-2997 bsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-1643-2997","contributorId":845,"corporation":false,"usgs":true,"family":"Smith","given":"Bruce","email":"bsmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":519755,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70131571,"text":"ofr20141223 - 2014 - Effects of human disturbance on waterbird nesting and reproductive success at restoration pond SF2, south San Francisco Bay, California","interactions":[],"lastModifiedDate":"2017-07-01T17:19:10","indexId":"ofr20141223","displayToPublicDate":"2014-11-11T09:00:00","publicationYear":"2014","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":"2014-1223","title":"Effects of human disturbance on waterbird nesting and reproductive success at restoration pond SF2, south San Francisco Bay, California","docAbstract":"To offset for the loss of managed pond habitat during restoration of wetlands to tidal marsh, the South Bay Salt Pond (SBSP) Restoration Project is enhancing some of the remaining ponds by constructing islands for roosting and nesting waterbirds. Among these wetland habitats, the SBSP Restoration Project also is installing walking trails and viewing platforms in an effort to bring the public closer to nature. In winter of 2010–11, the SBSP Restoration Project constructed 30 islands in Pond SF2 and walking trails and viewing platforms around the edge of the pond. The restoration project partners acknowledged that human disturbance could detrimentally affect nesting and roosting waterbirds. Although optimal buffer distances and potential for human disturbance were unknown, islands in Pond SF2, nevertheless, were designed with built-in buffers of greater than 300 feet (91 meters) from a trail and 600 feet (182 meters) from a viewing platform in order to minimize potential human disturbances.
\nTo determine the effects that human disturbance may have on waterbirds nesting on these newly constructed islands in Pond SF2, we assessed the potential effects of human disturbance features (specifically, access trails, viewing platforms, internal pond berms, exterior levees, and highways) on breeding waterbirds in 2011 and 2012. We found no clear pattern of potential disturbance features on a group of reproductive factors, including nest survival, nest initiation date, and clutch size. Because all the islands were constructed greater than 90 meters from the nearest disturbance feature, Pond SF2 alone did not provide adequate variation in the distance of disturbance features to detect potential detrimental effects for islands closer to disturbance features in other areas of the SBSP Restoration Project. If there is a need for SBSP Restoration Project Management Team to understand how close islands can be built to disturbance features in the future, we suggest a more comprehensive study that includes multiple ponds, other than SF2, with islands at varying distances to disturbance features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141223","collaboration":"Prepared in cooperation with the South Bay Salt Pond Restoration Project","usgsCitation":"Ackerman, J., Herzog, M., and Hartman, C.A., 2014, Effects of human disturbance on waterbird nesting and reproductive success at restoration pond SF2, south San Francisco Bay, California: U.S. Geological Survey Open-File Report 2014-1223, iv, 16 p., https://doi.org/10.3133/ofr20141223.","productDescription":"iv, 16 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-060374","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":295973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141223.jpg"},{"id":295955,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1223/"},{"id":295972,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1223/pdf/ofr2014-1223.pdf"}],"country":"United States","state":"California","city":"San Francisco","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.40142822265625,\n 37.759858513184625\n ],\n [\n -122.23114013671875,\n 37.76420119453823\n ],\n [\n -121.92352294921874,\n 37.45523781879053\n ],\n [\n -122.01690673828124,\n 37.42252593456307\n ],\n [\n -122.39044189453124,\n 37.612055711412815\n ],\n [\n -122.40142822265625,\n 37.759858513184625\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5463251ae4b0ba83040c6a46","contributors":{"authors":[{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":524851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herzog, Mark P. mherzog@usgs.gov","contributorId":3965,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark P.","email":"mherzog@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":524852,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hartman, Christopher A. chartman@usgs.gov","contributorId":5242,"corporation":false,"usgs":true,"family":"Hartman","given":"Christopher","email":"chartman@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":524853,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70136276,"text":"70136276 - 2014 - Simulating 2,368 temperate lakes reveals weak coherence in stratification phenology","interactions":[],"lastModifiedDate":"2018-04-24T13:44:40","indexId":"70136276","displayToPublicDate":"2014-11-10T11:15:00","publicationYear":"2014","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 2,368 temperate lakes reveals weak coherence in stratification phenology","docAbstract":"Changes in water temperatures resulting from climate warming can alter the structure and function of aquatic ecosystems. Lake-specific physical characteristics may play a role in mediating individual lake responses to climate. Past mechanistic studies of lake-climate interactions have simulated generic lake classes at large spatial scales or performed detailed analyses of small numbers of real lakes. Understanding the diversity of lake responses to climate change across landscapes requires a hybrid approach that couples site-specific lake characteristics with broad-scale environmental drivers. This study provides a substantial advancement in lake ecosystem modeling by combining open-source tools with freely available continental-scale data to mechanistically model daily temperatures for 2,368 Wisconsin lakes over three decades (1979-2011). The model accurately predicted observed surface layer temperatures (RMSE: 1.74°C) and the presence/absence of stratification (81.1% agreement). Among-lake coherence was strong for surface temperatures and weak for the timing of stratification, suggesting individual lake characteristics mediate some - but not all - ecologically relevant lake responses to climate.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2014.07.029","usgsCitation":"Read, J.S., Winslow, L.A., Hansen, G.J., Van Den Hoek, J., Hanson, P.C., Bruce, L.C., and Markfort, C.D., 2014, Simulating 2,368 temperate lakes reveals weak coherence in stratification phenology: Ecological Modelling, v. 291, p. 142-150, https://doi.org/10.1016/j.ecolmodel.2014.07.029.","productDescription":"9 p.","startPage":"142","endPage":"150","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056409","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":472647,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2014.07.029","text":"Publisher Index Page"},{"id":296929,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":337361,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7028PN4","text":"Climate warming of Wisconsin lakes can be either amplified or suppressed by trends in water clarity"}],"volume":"291","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2c58e4b08de9379b373c","chorus":{"doi":"10.1016/j.ecolmodel.2014.07.029","url":"http://dx.doi.org/10.1016/j.ecolmodel.2014.07.029","publisher":"Elsevier BV","authors":"Read Jordan S., Winslow Luke A., Hansen Gretchen J.A., Van Den Hoek Jamon, Hanson Paul C., Bruce Louise C., Markfort Corey D.","journalName":"Ecological Modelling","publicationDate":"11/2014","auditedOn":"11/1/2014","publiclyAccessibleDate":"8/5/2014"},"contributors":{"authors":[{"text":"Read, Jordan S. 0000-0002-3888-6631 jread@usgs.gov","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":4453,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","email":"jread@usgs.gov","middleInitial":"S.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":537269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winslow, Luke A. 0000-0002-8602-5510 lwinslow@usgs.gov","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":5919,"corporation":false,"usgs":true,"family":"Winslow","given":"Luke","email":"lwinslow@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":false,"id":537270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Gretchen J. A.","contributorId":131099,"corporation":false,"usgs":false,"family":"Hansen","given":"Gretchen","email":"","middleInitial":"J. A.","affiliations":[{"id":7242,"text":"Wisconsin Department of Natural Resources, Madison, WI, USA","active":true,"usgs":false}],"preferred":false,"id":537271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Den Hoek, Jamon","contributorId":127555,"corporation":false,"usgs":false,"family":"Van Den Hoek","given":"Jamon","email":"","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":537272,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hanson, Paul C.","contributorId":35634,"corporation":false,"usgs":false,"family":"Hanson","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":537273,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bruce, Louise C.","contributorId":131100,"corporation":false,"usgs":false,"family":"Bruce","given":"Louise","email":"","middleInitial":"C.","affiliations":[{"id":7243,"text":"School of Earth & Environment, The University of Western Australia, Perth, Australia","active":true,"usgs":false}],"preferred":false,"id":537274,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Markfort, Corey D.","contributorId":131098,"corporation":false,"usgs":false,"family":"Markfort","given":"Corey","email":"","middleInitial":"D.","affiliations":[{"id":7241,"text":"IIHR-Hydroscience and Engineering, Department of Civil and Environmental Engineering, The University of Iowa","active":true,"usgs":false}],"preferred":false,"id":537275,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70131482,"text":"70131482 - 2014 - Practical limitations on the use of diurnal temperature signals to quantify groundwater upwelling","interactions":[],"lastModifiedDate":"2018-09-18T16:25:14","indexId":"70131482","displayToPublicDate":"2014-11-07T17:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Practical limitations on the use of diurnal temperature signals to quantify groundwater upwelling","docAbstract":"Groundwater upwelling to streams creates unique habitat by influencing stream water quality and temperature; upwelling zones also serve as vectors for contamination when groundwater is degraded. Temperature time series data acquired along vertical profiles in the streambed have been applied to simple analytical models to determine rates of vertical fluid flux. These models are based on the downward propagation characteristics (amplitude attenuation and phase-lag) of the surface diurnal signal. Despite the popularity of these models, there are few published characterizations of moderate-to-strong upwelling. We attribute this limitation to the thermodynamics of upwelling, under which the downward conductive signal transport from the streambed interface occurs opposite the upward advective fluid flux. Governing equations describing the advection–diffusion of heat within the streambed predict that under upwelling conditions, signal amplitude attenuation will increase, but, counterintuitively, phase-lag will decrease. Therefore the extinction (measurable) depth of the diurnal signal is very shallow, but phase lag is also short, yielding low signal to noise ratio and poor model sensitivity. Conversely, amplitude attenuation over similar sensor spacing is strong, yielding greater potential model sensitivity. Here we present streambed thermal time series over a range of moderate to strong upwelling sites in the Quashnet River, Cape Cod, Massachusetts. The predicted inverse relationship between phase-lag and rate of upwelling was observed in the field data over a range of conditions, but the observed phase-lags were consistently shorter than predicted. Analytical solutions for fluid flux based on signal amplitude attenuation return results consistent with numerical models and physical seepage meters, but the phase-lag analytical model results are generally unreasonable. Through numerical modeling we explore reasons why phase-lag may have been over-predicted by the analytical models, and develop guiding relations of diurnal temperature signal extinction depth based on stream diurnal signal amplitude, upwelling magnitude, and streambed thermal properties that will be useful in designing future experiments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2014.09.030","usgsCitation":"Briggs, M.A., Lautz, L.K., Buckley, S.F., and Lane, J.W., 2014, Practical limitations on the use of diurnal temperature signals to quantify groundwater upwelling: Journal of Hydrology, v. 519, no. B, p. 1739-1751, https://doi.org/10.1016/j.jhydrol.2014.09.030.","productDescription":"13 p.","startPage":"1739","endPage":"1751","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057864","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":295951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295952,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S0022169414007124"}],"volume":"519","issue":"B","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545ddf17e4b0ba8303f8b62a","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":521241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lautz, Laura K.","contributorId":124523,"corporation":false,"usgs":false,"family":"Lautz","given":"Laura","email":"","middleInitial":"K.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":521242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buckley, Sean F. sbuckley@usgs.gov","contributorId":3910,"corporation":false,"usgs":true,"family":"Buckley","given":"Sean","email":"sbuckley@usgs.gov","middleInitial":"F.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":521243,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lane, John W. Jr. jwlane@usgs.gov","contributorId":1738,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":false,"id":521244,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70131483,"text":"70131483 - 2014 - On the downscaling of actual evapotranspiration maps based on combination of MODIS and landsat-based actual evapotranspiration estimates","interactions":[],"lastModifiedDate":"2017-01-18T11:27:04","indexId":"70131483","displayToPublicDate":"2014-11-07T17:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"On the downscaling of actual evapotranspiration maps based on combination of MODIS and landsat-based actual evapotranspiration estimates","docAbstract":"Downscaling is one of the important ways of utilizing the combined benefits of the high temporal resolution of Moderate Resolution Imaging Spectroradiometer (MODIS) images and fine spatial resolution of Landsat images. We have evaluated the output regression with intercept method and developed the Linear with Zero Intercept (LinZI) method for downscaling MODIS-based monthly actual evapotranspiration (AET) maps to the Landsat-scale monthly AET maps for the Colorado River Basin for 2010. We used the 8-day MODIS land surface temperature product (MOD11A2) and 328 cloud-free Landsat images for computing AET maps and downscaling. The regression with intercept method does have limitations in downscaling if the slope and intercept are computed over a large area. A good agreement was obtained between downscaled monthly AET using the LinZI method and the eddy covariance measurements from seven flux sites within the Colorado River Basin. The mean bias ranged from −16 mm (underestimation) to 22 mm (overestimation) per month, and the coefficient of determination varied from 0.52 to 0.88. Some discrepancies between measured and downscaled monthly AET at two flux sites were found to be due to the prevailing flux footprint. A reasonable comparison was also obtained between downscaled monthly AET using LinZI method and the gridded FLUXNET dataset. The downscaled monthly AET nicely captured the temporal variation in sampled land cover classes. The proposed LinZI method can be used at finer temporal resolution (such as 8 days) with further evaluation. The proposed downscaling method will be very useful in advancing the application of remotely sensed images in water resources planning and management.
","language":"English","publisher":"MDPI","doi":"10.3390/rs61110483","usgsCitation":"Singh, R.K., Senay, G.B., Velpuri, N.M., Bohms, S., and Verdin, J.P., 2014, On the downscaling of actual evapotranspiration maps based on combination of MODIS and landsat-based actual evapotranspiration estimates: Remote Sensing, v. 6, no. 11, p. 10483-10509, https://doi.org/10.3390/rs61110483.","productDescription":"27 p.","startPage":"10483","endPage":"10509","numberOfPages":"27","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057248","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472650,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs61110483","text":"Publisher Index Page"},{"id":295950,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295953,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.mdpi.com/2072-4292/6/11/10483"}],"volume":"6","issue":"11","noUsgsAuthors":false,"publicationDate":"2014-10-30","publicationStatus":"PW","scienceBaseUri":"545ddf17e4b0ba8303f8b625","contributors":{"authors":[{"text":"Singh, Ramesh K. 0000-0002-8164-3483 rsingh@usgs.gov","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":3895,"corporation":false,"usgs":true,"family":"Singh","given":"Ramesh","email":"rsingh@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":521245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":521246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Velpuri, Naga Manohar 0000-0002-6370-1926 nvelpuri@usgs.gov","orcid":"https://orcid.org/0000-0002-6370-1926","contributorId":4441,"corporation":false,"usgs":true,"family":"Velpuri","given":"Naga","email":"nvelpuri@usgs.gov","middleInitial":"Manohar","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":521247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bohms, Stefanie 0000-0002-2979-4655 sbohms@usgs.gov","orcid":"https://orcid.org/0000-0002-2979-4655","contributorId":3148,"corporation":false,"usgs":true,"family":"Bohms","given":"Stefanie","email":"sbohms@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":521248,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Verdin, James P. 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":720,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":521249,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70128252,"text":"sir20145193 - 2014 - An initial abstraction and constant loss model, and methods for estimating unit hydrographs, peak streamflows, and flood volumes for urban basins in Missouri","interactions":[],"lastModifiedDate":"2014-11-07T13:13:55","indexId":"sir20145193","displayToPublicDate":"2014-11-07T11:00:00","publicationYear":"2014","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":"2014-5193","title":"An initial abstraction and constant loss model, and methods for estimating unit hydrographs, peak streamflows, and flood volumes for urban basins in Missouri","docAbstract":"Streamflow data, basin characteristics, and rainfall data from 39 streamflow-gaging stations for urban areas in and adjacent to Missouri were used by the U.S. Geological Survey in cooperation with the Metropolitan Sewer District of St. Louis to develop an initial abstraction and constant loss model (a time-distributed basin-loss model) and a gamma unit hydrograph (GUH) for urban areas in Missouri. Study-specific methods to determine peak streamflow and flood volume for a given rainfall event also were developed.
\n\n
Distinct basin characteristics were evaluated and selected for use on the basis of their theoretical relation to flow, results from previous studies, and the ability to reliably measure the basin characteristic using digital datasets and geographic information system (GIS) technology. The key basin characteristics determined or computed for each of the 39 basins upstream from the streamflow-gaging stations were drainage area, percent impervious area, main-channel slope based on the 10- and 85-percent length method, percentage of the basin area in storage (lakes, ponds, reservoirs, wetlands), the composite Natural Resources Conservation Service curve number estimated from a combination of the soil type data and land-use characteristics, and the streamflow variability index developed for the recently completed study of low-flow regression in Missouri.
\n\n
Characteristics of spatial and temporal rainfall distribution came from the next generation weather radar (NEXRAD) network. Procedures were developed for this study to convert the variable radar sweep rate into a 5-minute total rainfall hyetograph using data from the radar bin at the centroid of a given basin. Additional characteristics determined for each storm on the basin included the 5-day and 14-day antecedent rainfall, estimated from the mean of daily rainfall values from various rain gages in the area.
\n\n
The database of observed rainfall and runoff events for the 39 basins upstream from the streamflow-gaging stations was analyzed to compute the optimal storm-specific initial abstraction and constant loss values, as well as the time to peak, peak streamflow, and shape factor values of the GUH. The optimal storm-specific values were used to develop a regional regression equation for initial abstraction; conversely, the constant loss was estimated not by regression but from either a generalized or specific regional mean value. The optimal storm-specific values of GUH time to peak, GUH peak streamflow, and GUH shape factor were used to develop regression equations for the GUH.
\n\n
The regression equations for the GUH initially were tested alone, and then were combined with the appropriate regional regression equation for initial abstraction and both the generalized regional and specific regional mean constant loss values. For the GUH regression equations, the interquartile range was substantially smaller than the range spanned by the minimum and maximum values, which indicates most of the errors have much smaller variation, and the minimum and maximum values may be extreme outliers. The central tendency of the regressed errors for peak streamflow and runoff hydrograph volume were both approximately zero, which implies a generally unbiased estimation of these values. The mean and median of the regressed errors for time to peak streamflow were both small but greater than zero, which implies the GUH regression equations create a hydrograph that has a peak that is later in time than observed. Specifically, the regressed times indicate an offset of about 10 minutes, on average, from observed. The mean and median of the regressed errors for widths of the runoff hydrograph at 50 and 75 percent were less than zero, which implies the GUH tends to slightly underestimate these widths compared to the observed.
\n\n
The appropriate regional initial abstraction regression equation was combined with both the generalized and the specific regional mean constant loss values and the GUH regression equations. Both the generalized regional mean constant loss and specific regional mean constant loss forms of the basin-loss model worked equally well to model the observed runoff hydrograph based on the error analysis, and neither model seems to make a consistently better approximation. Both initial abstraction and constant loss models combined with the GUH regression equations were further validated using several storms available after the start of the project in early 2011 with similar but consistently higher error results. If these methods are used in an urban area in Missouri other than those examined in this study, advice to the user is given to consider using the generalized regional mean values. If these methods are used in an urban area that is a subbasin of one of the basins in this study, advice to the user is given to consider using the specific regional mean values.
\n\n
The rainfall-runoff pairs from the storm-specific GUH analysis were further analyzed against various basin and rainfall characteristics to develop equations to estimate the peak streamflow and flood volume based on a quantity of rainfall on the basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145193","collaboration":"Prepared in cooperation with the Metropolitan Sewer District of St. Louis","usgsCitation":"Huizinga, R.J., 2014, An initial abstraction and constant loss model, and methods for estimating unit hydrographs, peak streamflows, and flood volumes for urban basins in Missouri: U.S. Geological Survey Scientific Investigations Report 2014-5193, Report: x, 59 p.; Downloads Directory, https://doi.org/10.3133/sir20145193.","productDescription":"Report: x, 59 p.; Downloads Directory","numberOfPages":"74","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057930","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":295937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145193.jpg"},{"id":295934,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5193/"},{"id":295935,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5193/pdf/sir2014-5193.pdf"},{"id":295936,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5193/downloads/"}],"country":"United States","state":"Missouri","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545ddf16e4b0ba8303f8b61f","contributors":{"authors":[{"text":"Huizinga, Richard J. 0000-0002-2940-2324 huizinga@usgs.gov","orcid":"https://orcid.org/0000-0002-2940-2324","contributorId":2089,"corporation":false,"usgs":true,"family":"Huizinga","given":"Richard","email":"huizinga@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519683,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70118093,"text":"ds862 - 2014 - USGS Arctic Ocean Carbon Cruise 2012: Field Activity L-01-12-AR to collect carbon data in the Arctic Ocean, August-September 2012","interactions":[],"lastModifiedDate":"2014-11-07T13:27:04","indexId":"ds862","displayToPublicDate":"2014-11-06T16:30:00","publicationYear":"2014","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":"862","title":"USGS Arctic Ocean Carbon Cruise 2012: Field Activity L-01-12-AR to collect carbon data in the Arctic Ocean, August-September 2012","docAbstract":"From August 25 to September 27, 2012, the United States Coast Guard Cutter (USCGC) Healy was part of an Extended Continental Shelf Project to determine the limits of the extended continental shelf in the Arctic. On a non-interference basis, a USGS ocean acidification team participated on the cruise to collect baseline water data in the Arctic. The collection of data extended from coastal waters near Barrow, Alaska, to 83°2'N., -175°36'W., and southward back to coastal waters near Barrow and on to Dutch Harbor, Alaska. As a consequence, a number of hypotheses were tested and questions asked associated with ocean acidification, including:
\n\n
\n
During the cruise, underway continuous and discrete water samples were collected, and discrete water samples were collected at stations to document the carbonate chemistry of the Arctic waters and quantify the saturation state of seawater with respect to calcium carbonate. These data are critical for providing baseline information in areas where no data have existed prior and will also be used to test existing models and predict future trends.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds862","usgsCitation":"Robbins, L.L., Wynn, J., Knorr, P.O., Onac, B., Lisle, J.T., McMullen, K.Y., Yates, K.K., Byrne, R., and Liu, X., 2014, USGS Arctic Ocean Carbon Cruise 2012: Field Activity L-01-12-AR to collect carbon data in the Arctic Ocean, August-September 2012: U.S. Geological Survey Data Series 862, HTML Document, https://doi.org/10.3133/ds862.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2012-08-01","temporalEnd":"2012-09-30","ipdsId":"IP-051020","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":295933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds862.jpg"},{"id":295931,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0862/"},{"id":295932,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0862/ds862_abstract.html"}],"country":"United States","otherGeospatial":"Arctic Ocean","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8da2e4b0ba8303f703c0","contributors":{"authors":[{"text":"Robbins, Lisa L. 0000-0003-3681-1094 lrobbins@usgs.gov","orcid":"https://orcid.org/0000-0003-3681-1094","contributorId":422,"corporation":false,"usgs":true,"family":"Robbins","given":"Lisa","email":"lrobbins@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wynn, Jonathan","contributorId":9943,"corporation":false,"usgs":false,"family":"Wynn","given":"Jonathan","affiliations":[],"preferred":false,"id":524457,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knorr, Paul O. pknorr@usgs.gov","contributorId":3691,"corporation":false,"usgs":true,"family":"Knorr","given":"Paul","email":"pknorr@usgs.gov","middleInitial":"O.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":524458,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Onac, Bogdan","contributorId":127356,"corporation":false,"usgs":false,"family":"Onac","given":"Bogdan","affiliations":[],"preferred":false,"id":524459,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lisle, John T. 0000-0002-5447-2092 jlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-5447-2092","contributorId":2944,"corporation":false,"usgs":true,"family":"Lisle","given":"John","email":"jlisle@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":524460,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McMullen, Katherine Y. kmcmullen@usgs.gov","contributorId":2148,"corporation":false,"usgs":true,"family":"McMullen","given":"Katherine","email":"kmcmullen@usgs.gov","middleInitial":"Y.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":524461,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yates, Kimberly K. 0000-0001-8764-0358 kyates@usgs.gov","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":420,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","email":"kyates@usgs.gov","middleInitial":"K.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":524462,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Byrne, Robert H.","contributorId":83260,"corporation":false,"usgs":true,"family":"Byrne","given":"Robert H.","affiliations":[],"preferred":false,"id":524463,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Liu, Xuewu","contributorId":87676,"corporation":false,"usgs":true,"family":"Liu","given":"Xuewu","email":"","affiliations":[],"preferred":false,"id":524464,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70131570,"text":"ofr20141225 - 2014 - Ecological implications of Laurel Wilt infestation on Everglades Tree Islands, southern Florida","interactions":[],"lastModifiedDate":"2016-04-19T11:34:56","indexId":"ofr20141225","displayToPublicDate":"2014-11-06T09:30:00","publicationYear":"2014","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":"2014-1225","title":"Ecological implications of Laurel Wilt infestation on Everglades Tree Islands, southern Florida","docAbstract":"There is a long history of introduced pests attacking native forest trees in the United States (Liebhold and others, 1995; Aukema and others, 2010). Well-known examples include chestnut blight that decimated the American chestnut (Castanea dentata), an extremely important tree in the eastern United States, both as a food source for wildlife and humans and for the wood; Dutch elm disease that attacks native elms (Ulmus spp.), including those commonly planted as shade trees along city streets; and the balsam wooly adelgid (Adelges piceae), an insect that is destroying Fraser firs (Abies fraseri) in higher elevations of Great Smoky Mountains National Park. Laurel wilt, a fungal disease transmitted by the redbay ambrosia beetle (Xyleborus glabratus), is a 21st-century example of an introduced forest pest that attacks native tree species in the laurel family (Lauraceae) (Mayfield, 2007; Hulcr and Dunn, 2011).
The introduction of laurel wilt disease has been traced to the arrival of an Asian ambrosia beetle (Xyleborus glabratus) at Port Wentworth, Georgia, near Savannah, in 2002, apparently accidently introduced in wooden shipping material (Mayfield, 2007). Within the next 2 years, it was determined that the non-native wood-boring insect was the vector of an undescribed species of fungus, responsible for killing large numbers of red bay (Persea borbonia) trees in the surrounding area. Dispersing female redbay ambrosia beetles drill into live trees and create tunnels in the wood. They carry with them fungal spores in specialized organs called mycangia at the base of each mandible and sow the spores in the tunnels they excavate. The fungus, since named Raffaelea lauricola (Harrington and others, 2008), is the food source for adults and larvae. The introduction of Raffaelea lauricola causes the host plant to react in such a way as to block the vascular tissue, resulting in loss of water conduction, wilt, and death (Kendra and others, 2013).
Although first seen in red bay, laurel wilt disease also kills other native trees that are members of the laurel family, including swamp bay (Persea palustris), silk bay (Persea borbonia var. humilis), and sassafras (Sassafras albidum), as well as the economically important cultivated avocado (Persea americana) (Fraedrich and others, 2008). This paper is concerned primarily with swamp bay, an important component of Everglades tree islands.
The spread of the redbay ambrosia beetle and its fungal symbiont has been very rapid, exceeding model predictions (Koch and Smith, 2008); by 2011, laurel wilt disease was found from the southern coastal plain of North Carolina to southern peninsular Florida. The first redbay ambrosia beetle was trapped in Miami-Dade County in March 2010, and laurel wilt disease was discovered in swamp bays in February 2011 and in commercial avocado groves about a year later (Kendra and others, 2013). By 2013, laurel wilt disease was seen in swamp bays throughout the southern Everglades in Everglades National Park, Big Cypress National Preserve, and Water Conservation Areas (WCAs) 3A and 3B (Rodgers and others, 2014).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141225","usgsCitation":"Snyder, J.R., 2014, Ecological implications of Laurel Wilt infestation on Everglades Tree Islands, southern Florida: U.S. Geological Survey Open-File Report 2014-1225, iv, 18 p., https://doi.org/10.3133/ofr20141225.","productDescription":"iv, 18 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056042","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":295912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141225.JPG"},{"id":295892,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1225/"},{"id":295911,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1225/pdf/ofr2014-1225.pdf"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.19033813476562,\n 25.275745340949022\n ],\n [\n -81.17660522460938,\n 25.3241665257384\n ],\n [\n -81.16836547851562,\n 25.37753154832537\n ],\n [\n -81.18209838867188,\n 25.435833800555567\n ],\n [\n -81.21368408203125,\n 25.4866701822106\n ],\n [\n -81.2548828125,\n 25.553592617284565\n ],\n [\n -81.29608154296874,\n 25.615524531842528\n ],\n [\n -81.35101318359374,\n 25.66999808235069\n ],\n [\n -81.4031982421875,\n 25.740529092773226\n ],\n [\n -81.49795532226562,\n 25.798654774824335\n ],\n [\n -81.57211303710938,\n 25.84439325019514\n ],\n [\n -81.6448974609375,\n 25.88270106537761\n ],\n [\n -81.60369873046875,\n 25.916055815010868\n ],\n [\n -81.56112670898436,\n 25.91482062206972\n ],\n [\n -81.50894165039062,\n 25.949401131968656\n ],\n [\n -81.43615722656249,\n 25.944461680551118\n ],\n [\n -81.42105102539061,\n 25.94322678532246\n ],\n [\n -81.41555786132812,\n 25.899997297677864\n ],\n [\n -81.41143798828125,\n 25.86910939099931\n ],\n [\n -81.3812255859375,\n 25.856751966503136\n ],\n [\n -81.36749267578125,\n 25.903703303407667\n ],\n [\n -81.26724243164062,\n 25.904938612781873\n ],\n [\n -81.27410888671875,\n 25.849336891707605\n ],\n [\n -81.02828979492188,\n 25.693513062561056\n ],\n [\n -80.8538818359375,\n 25.695988053632746\n ],\n [\n -80.85525512695312,\n 25.849336891707605\n ],\n [\n -80.48309326171875,\n 25.855516152996614\n ],\n [\n -80.48583984375,\n 25.77392392167507\n ],\n [\n -80.49545288085938,\n 25.759082934951692\n ],\n [\n -80.49545288085938,\n 25.67866203603157\n ],\n [\n -80.51193237304688,\n 25.671235828577068\n ],\n [\n -80.518798828125,\n 25.65266828598998\n ],\n [\n -80.53115844726562,\n 25.65266828598998\n ],\n [\n -80.53253173828124,\n 25.642764414761196\n ],\n [\n -80.54763793945311,\n 25.63657407787705\n ],\n [\n -80.54763793945311,\n 25.618001141542337\n ],\n [\n -80.53939819335938,\n 25.608094394794268\n ],\n [\n -80.540771484375,\n 25.58703983205006\n ],\n [\n -80.56686401367188,\n 25.57341431679579\n ],\n [\n -80.5682373046875,\n 25.54244147012483\n ],\n [\n -80.57373046875,\n 25.512700007620513\n ],\n [\n -80.55999755859375,\n 25.50650294177565\n ],\n [\n -80.56549072265625,\n 25.47923205344432\n ],\n [\n -80.57510375976562,\n 25.47923205344432\n ],\n [\n -80.57510375976562,\n 25.469313832612475\n ],\n [\n -80.58883666992188,\n 25.46063471847754\n ],\n [\n -80.58746337890625,\n 25.42219111871144\n ],\n [\n -80.57510375976562,\n 25.42219111871144\n ],\n [\n -80.57373046875,\n 25.289404556494823\n ],\n [\n -80.43914794921875,\n 25.288162873186213\n ],\n [\n -80.43365478515625,\n 25.25960064916269\n ],\n [\n -80.42129516601562,\n 25.209911213827688\n ],\n [\n -80.3924560546875,\n 25.19002975536265\n ],\n [\n -80.41580200195312,\n 25.141555107671604\n ],\n [\n -80.45562744140625,\n 25.10301024053073\n ],\n [\n -80.47897338867188,\n 25.07440458233748\n ],\n [\n -80.52978515625,\n 25.0333500082522\n ],\n [\n -80.595703125,\n 24.98107885823501\n ],\n [\n -80.628662109375,\n 24.946219074360084\n ],\n [\n -80.70693969726562,\n 24.90263046793521\n ],\n [\n -80.76599121093749,\n 24.892665194900047\n ],\n [\n -81.0845947265625,\n 25.085598897064777\n ],\n [\n -81.13128662109375,\n 25.12787928859755\n ],\n [\n -81.1669921875,\n 25.157715464367914\n ],\n [\n -81.18209838867188,\n 25.19375777608886\n ],\n [\n -81.19445800781249,\n 25.236000699800467\n ],\n [\n -81.19033813476562,\n 25.275745340949022\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8d9de4b0ba8303f70373","contributors":{"authors":[{"text":"Snyder, James R. jim_snyder@usgs.gov","contributorId":2760,"corporation":false,"usgs":true,"family":"Snyder","given":"James","email":"jim_snyder@usgs.gov","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":524266,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70129339,"text":"sir20145203 - 2014 - Selenium in the upper Blackfoot River watershed, southeastern Idaho, 2001-12","interactions":[],"lastModifiedDate":"2015-08-11T09:02:02","indexId":"sir20145203","displayToPublicDate":"2014-11-06T09:15:00","publicationYear":"2014","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":"2014-5203","title":"Selenium in the upper Blackfoot River watershed, southeastern Idaho, 2001-12","docAbstract":"The upper Blackfoot River in southeastern Idaho receives runoff from 12 large phosphate mines. Waste shales that are removed to access the phosphate ore are highly enriched with selenium, resulting in elevated selenium in runoff from the mine waste dumps. In 2001, in cooperation with the Bureau of Land Management, the U.S. Geological Survey (USGS) began monitoring streamflow, selenium, and other water-quality parameters at a single location near the outlet of the upper Blackfoot River to the Blackfoot Reservoir. Water samples primarily were collected by a flow triggered, automated pump sampler, supplemented by manual point and equal-width integrated manual samples.
\n\n
The approach to monitoring concentrations and streamflow over time at a fixed location is ideal for evaluating temporal trends, but provides no information about the relative source contributions from the mine waste dumps draining into various tributaries. In 2001, the Idaho Department of Environmental Quality (IDEQ) began an annual, mid-May, synoptic survey of selenium concentrations and streamflow at 21 locations along the main stem Blackfoot River and its tributaries. Individually, neither the intensive USGS sampling at the outlet nor the IDEQ annual synoptic sampling provides a comprehensive view of selenium runoff in the Blackfoot River watershed. Together, the efforts are complementary; therefore, in this report, results are presented from both sampling efforts.
\n\n
The USGS collected time-series data from 2001 to 2012 at a fixed location, the Blackfoot River near the outlet of the reservoir, near Henry, Idaho (USGS streamgage 13063000). Dissolved selenium concentrations from 450 filtered samples collected at this site ranged from 0.5 to 11.4 micrograms per liter (μg/L). The State of Idaho chronic aquatic life criterion concentration of 5 μg/L was exceeded in 31 percent of the samples, with most exceedances occurring during May of each year. No exceedances of the selenium criterion were recorded in months other than April, May, or June. Concentrations of selenium in unfiltered and filtered samples were similar, and concentrations from samples collected by depth and width integrated methods were similar to those collected by grab (point) samples, indicating that the grab samples adequately represent selenium concentrations across the entire river cross section. In speciation analyses made during 2003 and 2004, the median percentage of total selenium as selenate was 81 percent, ranging from 17 to 98 percent, and the median percentage of total selenium as selenite was 19 percent, ranging from 2 to 83 percent of the total selenium. During the period of study, selenium concentrations had an upward trend during the lowflow season of August–October. Time trends were not obvious during other seasons. Selenium daily loads varied by more than a factor of 900 during the study period and ranged from 0.03 kilograms per day (kg/d) to more than 24 kg/d. Annual maximum daily loads of selenium varied over nearly a factor of 12, ranging from about 2 to 24 kg/d.
\n\n
For the annual spring synoptic samples collected by the IDEQ along the main stem Blackfoot River and major tributaries, selenium concentrations ranged from less than 2 to 870 μg/L in 176 samples. In most years, the synoptic sampling showed that the majority of the selenium loads passing the USGS streamgage at the outlet of the watershed could be attributed to a single tributary, East Mill Creek, which enters the Blackfoot River through Spring Creek. Selenium loads decreased by about half from East Mill Creek before reaching the Blackfoot River, suggesting that much selenium is at least temporarily removed from the water column by uptake by aquatic vegetation or by losses to sediment. Similar decreases in selenium loads occurred through the main stem Blackfoot River before reaching the outlet in low flow years, but not in high flow years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145203","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Mebane, C.A., Mladenka, G.C., Van Every, Lynn, Williams, M.L., Hardy, M.A., and Garbarino, J.R., 2014, Selenium in the upper Blackfoot River watershed, southeastern Idaho, 2001–12, with an appendix on selenium speciation analytical methods, by Garbarino, J.R. (ver.1.1, August 2015): U.S. Geological Survey Scientific Investigations Report 2014-5203, 34 p., plus appendixes, https://dx.doi.org/10.3133/sir20145203.","productDescription":"Report: vi, 34 p.; 5 Appendixes","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2001-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-048924","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":295905,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145203.jpg"},{"id":295899,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5203/pdf/sir2014-5203.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2014-5203 report"},{"id":295900,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5203/downloads/sir2014-5203_appendixa.kml","text":"Appendix A","size":"7 KB"},{"id":295901,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5203/downloads/sir2014-5203_appendixb.pdf","text":"Appendix B","size":"280 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":295902,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5203/downloads/sir2014-5203_appendixc.pdf","text":"Appendix C","size":"706 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":295895,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5203/"},{"id":295903,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5203/downloads/sir2014-5203_appendixd.xlsx","text":"Appendix D","size":"321 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":295904,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5203/downloads/sir2014-5203_appendixe.pdf","text":"Appendix E","size":"507 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":306562,"rank":9,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2014/5203/versionHist.pdf","linkFileType":{"id":1,"text":"pdf"}}],"scale":"100000","projection":"Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Idaho","otherGeospatial":"Blackfoot River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.544189453125,\n 42.49842801732158\n ],\n [\n -111.544189453125,\n 42.974511174899156\n ],\n [\n -111.0662841796875,\n 42.974511174899156\n ],\n [\n -111.0662841796875,\n 42.49842801732158\n ],\n [\n -111.544189453125,\n 42.49842801732158\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1: Originally posted November 5, 2014; Version 1.1: August 2015","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, designed and operates a series of monitoring stations on streams and springs throughout Missouri known as the Ambient Water-Quality Monitoring Network. During the 2013 water year (October 1, 2012, through September 30, 2013), data were collected at 79 stations—73 Ambient Water-Quality Monitoring Network stations, 4 alternate Ambient Water-Quality Monitoring Network stations, and 2 U.S. Geological Survey National Stream Quality Accounting Network stations. Dissolved oxygen, specific conductance, water temperature, suspended solids, suspended sediment, Escherichia coli bacteria, fecal coliform bacteria, dissolved nitrate plus nitrite as nitrogen, total phosphorus, dissolved and total recoverable lead and zinc, and select pesticide compound summaries are presented for 76 of these stations. The stations primarily have been classified into groups corresponding to the physiography of the State, primary land use, or unique station types. In addition, a summary of hydrologic conditions in the State including peak discharges, monthly mean discharges, and 7-day low flow is presented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds886","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Barr, M.N., and Schneider, R.E., 2014, Quality of surface water in Missouri, water year 2013: U.S. Geological Survey Data Series 886, iv, 21 p., https://doi.org/10.3133/ds886.","productDescription":"iv, 21 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2013-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-058570","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":295907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds886.jpg"},{"id":295894,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0886/"},{"id":295906,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0886/pdf/ds886.pdf"}],"country":"United States","state":"Missouri","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8da1e4b0ba8303f703a6","contributors":{"authors":[{"text":"Barr, Miya N. 0000-0002-9961-9190 mnbarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9961-9190","contributorId":3686,"corporation":false,"usgs":true,"family":"Barr","given":"Miya","email":"mnbarr@usgs.gov","middleInitial":"N.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":524274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schneider, Rachel E. rschneider@usgs.gov","contributorId":5786,"corporation":false,"usgs":true,"family":"Schneider","given":"Rachel","email":"rschneider@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":524275,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70126400,"text":"sir20145172 - 2014 - Groundwater levels in the Denver Basin bedrock aquifers of Douglas County, Colorado, 2011-2013","interactions":[],"lastModifiedDate":"2014-12-02T10:44:54","indexId":"sir20145172","displayToPublicDate":"2014-11-06T09:15:00","publicationYear":"2014","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":"2014-5172","title":"Groundwater levels in the Denver Basin bedrock aquifers of Douglas County, Colorado, 2011-2013","docAbstract":"More than 70 percent of the municipal water supply in the south Denver metropolitan area is provided by groundwater, and homeowners in rural areas depend solely on self-supplied groundwater for water supply. Increased groundwater withdrawal to meet the demand of the rapidly growing population is causing water levels to decline. The U.S. Geological Survey, in cooperation with the Rural Water Authority of Douglas County, began a study in 2011 to assess the groundwater resources of the Denver Basin aquifers within Douglas County, Colorado. The primary purpose of this study was to monitor changes in the groundwater levels of the bedrock aquifers of the Denver Basin within rural Douglas County. To better assess the water resources of the Denver Basin bedrock aquifers, a groundwater monitoring network was established in 2011. More than 500 manual and 213,900 automated water-level measurements collected from the 36 domestic-well network between April 2011 and June 2013 showed water-level declines in all aquifers.
\n\n
Manual and automated (time-series) water-level data collection from these sites between 2011 and 2013 showed water level declines in 36 wells. Over the 2-year monitoring period, average declines of approximately 0.4 foot per year were observed in the upper Dawson aquifer, declines of over 2.6 feet per year were observed in the lower Dawson aquifer, declines of about 3.2 feet per year were observed in the Denver aquifer, declines of about 1.9 feet per year were observed in the Arapahoe aquifer, and declines of about 9.9 feet per year were observed in the Laramie-Fox Hills aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145172","collaboration":"Prepared in cooperation with the Rural Water Authority of Douglas County","usgsCitation":"Everett, R., 2014, Groundwater levels in the Denver Basin bedrock aquifers of Douglas County, Colorado, 2011-2013: U.S. Geological Survey Scientific Investigations Report 2014-5172, viii, 45 p., https://doi.org/10.3133/sir20145172.","productDescription":"viii, 45 p.","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055778","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":295924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145172.jpg"},{"id":295918,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5172/"},{"id":295919,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5172/pdf/sir2014-5172.pdf"}],"country":"United States","state":"Colorado","county":"Douglas County","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8d9ee4b0ba8303f70385","contributors":{"authors":[{"text":"Everett, Rhett R. 0000-0001-7983-6270 reverett@usgs.gov","orcid":"https://orcid.org/0000-0001-7983-6270","contributorId":843,"corporation":false,"usgs":true,"family":"Everett","given":"Rhett R.","email":"reverett@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":524352,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70129724,"text":"fs20143109 - 2014 - Summary of estimated water use in the United States in 2010","interactions":[],"lastModifiedDate":"2014-11-04T22:48:07","indexId":"fs20143109","displayToPublicDate":"2014-11-05T08:00:00","publicationYear":"2014","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":"2014-3109","title":"Summary of estimated water use in the United States in 2010","docAbstract":"About 355,000 million gallons per day (Mgal/d) of water was withdrawn for use in the United States during 2010, a decline of 13 percent from 2005 and a substantial change from the level of about 400,000 Mgal/d reported from 1985 to 2005. Withdrawals for 2010 were lower than withdrawals estimated for 1970. Fresh surface-water withdrawals (230,000 Mgal/d) were almost 15 percent less than in 2005, and fresh groundwater withdrawals (76,000 Mgal/day) were about 4 percent less than in 2005. Saline surface-water withdrawals were 45,000 Mgal/d, or 24 percent less than in 2005, and saline groundwater withdrawals in 2010, mostly used for mining, were 3,290 Mgal/d.
\n\n
As in 2005, water withdrawals in four States—California, Texas, Idaho, and Florida—accounted for more than one-quarter of all fresh and saline water withdrawn in the United States in 2010. California accounted for 11 percent of the total withdrawals nationwide and 10 percent of the total freshwater withdrawals. More than 60 percent of California’s withdrawals were for irrigation, and 17 percent, almost exclusively saline water, was for thermoelectric power. In Texas, about 45 percent of withdrawals were for thermoelectric power, and 28 percent was for irrigation. Irrigation accounted for 81 percent of water withdrawn in Idaho, and thermoelectric power accounted for 61 percent of water withdrawn in Florida.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143109","usgsCitation":"Barber, N.L., 2014, Summary of estimated water use in the United States in 2010: U.S. Geological Survey Fact Sheet 2014-3109, 2 p., https://doi.org/10.3133/fs20143109.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060372","costCenters":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"links":[{"id":295889,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143109.jpg"},{"id":295873,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3109/"},{"id":295874,"rank":2,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/circ/1405"},{"id":295875,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3109/pdf/fs2014-3109.pdf"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545b3c1be4b009f8aec98d4e","contributors":{"authors":[{"text":"Barber, Nancy L. 0000-0002-2952-5017 nlbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-2952-5017","contributorId":3679,"corporation":false,"usgs":true,"family":"Barber","given":"Nancy","email":"nlbarber@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519919,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70127140,"text":"cir1405 - 2014 - Estimated use of water in the United States in 2010","interactions":[],"lastModifiedDate":"2026-04-29T17:14:25.123909","indexId":"cir1405","displayToPublicDate":"2014-11-05T08:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1405","title":"Estimated use of water in the United States in 2010","docAbstract":"Water use in the United States in 2010 was estimated to be about 355 billion gallons per day (Bgal/d), which was 13 percent less than in 2005. The 2010 estimates put total withdrawals at the lowest level since before 1970. Freshwater withdrawals were 306 Bgal/d, or 86 percent of total withdrawals, and saline-water withdrawals were 48.3 Bgal/d, or 14 percent of total withdrawals. Fresh surface-water withdrawals (230 Bgal/d) were almost 15 percent less than in 2005, and fresh groundwater withdrawals (76.0 Bgal/d) were about 4 percent less than in 2005. Saline surface-water withdrawals were 45.0 Bgal/d, or 24 percent less than in 2005. Updates to the 2005 saline groundwater withdrawals, mostly for thermoelectric power, reduced total saline groundwater withdrawals to 1.51 Bgal/d, down from the originally reported 3.02 Bgal/d. Total saline groundwater withdrawals in 2010 were 3.29 Bgal/d, mostly for mining use.
\n\n
Thermoelectric power and irrigation remained the two largest uses of water in 2010, and total withdrawals for both were notably less than in 2005. Withdrawals in 2010 for thermoelectric power were 20 percent less and withdrawals for irrigation were 9 percent less than in 2005. Similarly, other uses showed reductions compared to 2005, specifically public supply (–5 percent), self-supplied domestic (–3 percent), self-supplied industrial (–12 percent), and livestock (–7 percent). Only mining (39 percent) and aquaculture (7 percent) reported larger withdrawals in 2010 compared to 2005. Thermoelectric power, irrigation, and public-supply withdrawals accounted for 90 percent of total withdrawals in 2010.
\n\n
Withdrawals for thermoelectric power were 161 Bgal/d in 2010 and represented the lowest levels since before 1970. Surface-water withdrawals accounted for more than 99 percent of total thermoelectric-power withdrawals, and 73 percent of those surface-water withdrawals were from freshwater sources. Saline surface-water withdrawals for thermoelectric power accounted for 97 percent of total saline surface-water withdrawals for all uses. Thermoelectric-power withdrawals accounted for 45 percent of total withdrawals for all uses, and freshwater withdrawals for thermoelectric power accounted for 38 percent of the total freshwater withdrawals for all uses.
\n\n
Irrigation withdrawals were 115 Bgal/d in 2010 and represented the lowest levels since before 1965. Irrigation withdrawals, all freshwater, accounted for 38 percent of total freshwater withdrawals for all uses, or 61 percent of total freshwater withdrawals for all uses excluding thermoelectric power. Surface-water withdrawals (65.9 Bgal/d) accounted for 57 percent of the total irrigation withdrawals, or about 12 percent less than in 2005. Groundwater withdrawals were 49.5 Bgal/d in 2010, about 6 percent less than in 2005. About 62,400 thousand acres were irrigated in 2010, an increase from 2005 of about 950 thousand acres (1.5 percent). The number of acres irrigated using sprinkler and microirrigation systems continued to increase and accounted for 58 percent of the total irrigated lands in 2010.
\n\n
Public-supply withdrawals in 2010 were 42.0 Bgal/d, or 5 percent less than in 2005, and represented the first declines in public-supply withdrawals since the 5-year reporting began in 1950. Total population in the United States increased from 300.7 million people in 2005 to 313.0 million people in 2010, an increase of 4 percent. Public-supply withdrawals accounted for 14 percent of the total freshwater withdrawals for all uses and 22 percent of freshwater withdrawals for all uses excluding thermoelectric power. The number of people that received potable water from public-supply facilities in 2010 was 268 million, or about 86 percent of the total U.S. population. This percentage was unchanged from 2005. Self-supplied domestic withdrawals were 3.60 Bgal/d, or 3 percent less than in 2005. More than 98 percent of the self-supplied domestic withdrawals were from groundwater sources.
\n\n
Self-supplied industrial withdrawals were 15.9 Bgal/d in 2010, a 12 percent decline from 2005, and continued the downward trend since the peak of 47 Bgal/d in 1970. Total self-supplied industrial withdrawals were 4 percent of total withdrawals for all uses and 8 percent of total withdrawals for all uses excluding thermoelectric power. Most of the total self-supplied industrial withdrawals were from surface-water sources (82 percent), and nearly all (93 percent) of those surface-water withdrawals were from freshwater sources. Nearly all of the groundwater withdrawals for self-supplied industrial use (98 percent) were from freshwater sources.
\n\n
Total aquaculture withdrawals were 9.42 Bgal/d in 2010, or 7 percent more than in 2005, and surface water was the primary source (81 percent). Most of the surface-water withdrawals occurred at facilities that operated flowthrough raceways, which returned the water to the source directly after use. Aquaculture withdrawals accounted for 3 percent of the total withdrawals for all uses and 5 percent of the total withdrawals for all uses excluding thermoelectric.
\n\n
Total mining withdrawals in 2010 were 5.32 Bgal/d, or about 1 percent of total withdrawals from all uses and 3 percent of total withdrawals from all uses excluding thermoelectric. Mining withdrawals accounted for the largest percentage increase (39 percent) in water use between 2005 and 2010 among all the categories. Groundwater withdrawals accounted for 73 percent of the total mining withdrawals, and the majority of the groundwater was saline (71 percent). The majority (80 percent) of surface-water withdrawals for mining was freshwater.
\n\n
Livestock withdrawals in 2010 were 2.00 Bgal/d, or 7 percent less than in 2005. All livestock withdrawals were from freshwater sources, mostly from groundwater (60 percent). Livestock withdrawals accounted for about 1 percent of total freshwater withdrawals for all uses excluding thermoelectric power.
\n\n
In 2010, more than 50 percent of the total withdrawals in the United States were accounted for by 12 States. California accounted for about 11 percent of the total withdrawals and 10 percent of freshwater withdrawals in the United States, predominantly for irrigation. Texas accounted for about 7 percent of total withdrawals, predominantly for thermoelectric power, irrigation, and public supply. Florida accounted for 18 percent of the total saline-water withdrawals in the United States, mostly from surface-water sources for thermoelectric power. Oklahoma and Texas accounted for about 70 percent of the total saline groundwater withdrawals in the United States, mostly for mining.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1405","usgsCitation":"Maupin, M.A., Kenny, J.F., Hutson, S.S., Lovelace, J.K., Barber, N.L., and Linsey, K.S., 2014, Estimated use of water in the United States in 2010: U.S. Geological Survey Circular 1405, Report: iv, 56 p.; County-level data; Related work, https://doi.org/10.3133/cir1405.","productDescription":"iv, 56 p.","numberOfPages":"64","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057650","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":295877,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1405/pdf/circ1405.pdf"},{"id":295878,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/fs/2014/3109/"},{"id":503652,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_101047.htm","linkFileType":{"id":5,"text":"html"}},{"id":295888,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":295876,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/circ/1405/"},{"id":295879,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://water.usgs.gov/watuse/data/2010/"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545b3c19e4b009f8aec98d48","contributors":{"authors":[{"text":"Maupin, Molly A. 0000-0002-2695-5505 mamaupin@usgs.gov","orcid":"https://orcid.org/0000-0002-2695-5505","contributorId":951,"corporation":false,"usgs":true,"family":"Maupin","given":"Molly","email":"mamaupin@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kenny, Joan F. jkenny@usgs.gov","contributorId":3676,"corporation":false,"usgs":true,"family":"Kenny","given":"Joan","email":"jkenny@usgs.gov","middleInitial":"F.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":519596,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hutson, Susan S. sshutson@usgs.gov","contributorId":2040,"corporation":false,"usgs":true,"family":"Hutson","given":"Susan","email":"sshutson@usgs.gov","middleInitial":"S.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519595,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lovelace, John K. 0000-0002-8532-2599 jlovelac@usgs.gov","orcid":"https://orcid.org/0000-0002-8532-2599","contributorId":999,"corporation":false,"usgs":true,"family":"Lovelace","given":"John","email":"jlovelac@usgs.gov","middleInitial":"K.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519594,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barber, Nancy L. 0000-0002-2952-5017 nlbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-2952-5017","contributorId":3679,"corporation":false,"usgs":true,"family":"Barber","given":"Nancy","email":"nlbarber@usgs.gov","middleInitial":"L.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519598,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Linsey, Kristin S. 0000-0001-6492-7639 kslinsey@usgs.gov","orcid":"https://orcid.org/0000-0001-6492-7639","contributorId":3678,"corporation":false,"usgs":true,"family":"Linsey","given":"Kristin","email":"kslinsey@usgs.gov","middleInitial":"S.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519597,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70156257,"text":"70156257 - 2014 - Using ecological indicators and a decision support system for integrated ecological assessment at two national park units in the Mid-Atlantic region, U.S.A.","interactions":[],"lastModifiedDate":"2022-11-10T16:32:18.700862","indexId":"70156257","displayToPublicDate":"2014-11-05T00:00:00","publicationYear":"2014","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":"Using ecological indicators and a decision support system for integrated ecological assessment at two national park units in the Mid-Atlantic region, U.S.A.","docAbstract":"We implemented an integrated ecological assessment using a GIS-based decision support system model for Upper Delaware Scenic and Recreational River (UPDE) and Delaware Water Gap National Recreation Area (DEWA)—national park units with the mid-Atlantic region of the United States. Our assessment examined a variety of aquatic and terrestrial indicators of ecosystem components that reflect the parks’ conservation purpose and reference condition. Our assessment compared these indicators to ecological thresholds to determine the condition of park watersheds. Selected indicators included chemical and physical measures of water quality, biologic indicators of water quality, and landscape condition measures. For the chemical and physical measures of water quality, we used a water quality index and each of its nine components to assess the condition of water quality in each watershed. For biologic measures of water quality, we used the Ephemeroptera, Plecoptera, Trichoptera aquatic macroinvertebrate index and, secondarily, the Hilsenhoff aquatic macroinvertebrate index. Finally, for the landscape condition measures of our model, we used percent forest and percent impervious surface. Based on our overall assessment, UPDE and DEWA watersheds had an ecological assessment score of 0.433 on a −1 to 1 fuzzy logic scale. This score indicates that, in general, the natural resource condition within watersheds at these parks is healthy or ecologically unimpaired; however, we had only partial data for many of our indicators. Our model is iterative and new data may be incorporated as they become available. These natural parks are located within a rapidly urbanizing landscape—we recommend that natural resource managers remain vigilant to surrounding land uses that may adversely affect natural resources within the parks.
","language":"English","publisher":"Springer","doi":"10.1007/s00267-014-0391-y","usgsCitation":"Mahan, C.G., Young, J.A., Miller, B., and Saunders, M.C., 2014, Using ecological indicators and a decision support system for integrated ecological assessment at two national park units in the Mid-Atlantic region, U.S.A.: Environmental Management, v. 55, no. 2, p. 508-522, https://doi.org/10.1007/s00267-014-0391-y.","productDescription":"14 p.","startPage":"508","endPage":"522","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061210","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":472651,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00267-014-0391-y","text":"Publisher Index Page"},{"id":306857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware Water Gap National Recreation Area, Upper Delaware Scenic and Recreational River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.16363259831336,\n 41.00157864774306\n ],\n [\n -75.18360089268816,\n 40.93121492169374\n ],\n [\n -75.10372771518792,\n 40.93456727654237\n ],\n [\n -75.10150901581329,\n 40.96305542448701\n ],\n [\n -74.91957566706338,\n 41.065176406050654\n ],\n [\n -74.7931098026881,\n 41.170479402035426\n ],\n [\n -74.81085939768826,\n 41.20220428653266\n ],\n [\n -74.77314150831329,\n 41.26560793794221\n ],\n [\n -74.7687041095635,\n 41.2906187651337\n ],\n [\n -74.65333174206344,\n 41.342277434101675\n ],\n [\n -74.69548703018819,\n 41.37225400060595\n ],\n [\n -74.79089110331344,\n 41.33894585228984\n ],\n [\n -74.8618894833131,\n 41.31228706249345\n ],\n [\n -74.90626347081299,\n 41.25726886581319\n ],\n [\n -74.90404477143836,\n 41.21388852711442\n ],\n [\n -74.93066916393812,\n 41.17214951599155\n ],\n [\n -74.96838705331307,\n 41.15210533865738\n ],\n [\n -75.03051063581313,\n 41.105311752732376\n ],\n [\n -75.05935372768802,\n 41.056811790208826\n ],\n [\n -75.16363259831336,\n 41.00157864774306\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.31006585769143,\n 41.939183002612225\n ],\n [\n -75.28566016456683,\n 41.8384297630042\n ],\n [\n -75.19469349019188,\n 41.84173566734978\n ],\n [\n -75.12591380956687,\n 41.80205354376042\n ],\n [\n -75.12813250894152,\n 41.762346830362134\n ],\n [\n -75.09485201831683,\n 41.74413970315629\n ],\n [\n -75.08597722081676,\n 41.63976304239466\n ],\n [\n -75.10594551519156,\n 41.60659218093528\n ],\n [\n -75.03494713519191,\n 41.51694563301149\n ],\n [\n -74.99279184706664,\n 41.453786486136295\n ],\n [\n -74.93954306206668,\n 41.450460615191105\n ],\n [\n -74.921793467067,\n 41.42717474429995\n ],\n [\n -74.75317231456697,\n 41.39722349174036\n ],\n [\n -74.74207881769173,\n 41.3839073914761\n ],\n [\n -74.69770483019184,\n 41.39722349174036\n ],\n [\n -74.71545442519201,\n 41.442145191832054\n ],\n [\n -74.8042024001918,\n 41.46043771647152\n ],\n [\n -74.86410728331671,\n 41.46708826471874\n ],\n [\n -74.92401216644163,\n 41.51030020105466\n ],\n [\n -74.95507395769167,\n 41.513623002313324\n ],\n [\n -75.0194162395669,\n 41.60493318994418\n ],\n [\n -75.02163493894153,\n 41.772275813796995\n ],\n [\n -75.04604063206665,\n 41.82520443777676\n ],\n [\n -75.15919430019153,\n 41.89790990874036\n ],\n [\n -75.23019268019168,\n 41.89790990874036\n ],\n [\n -75.25681707269143,\n 41.9655837730665\n ],\n [\n -75.31006585769143,\n 41.939183002612225\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"55","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-05","publicationStatus":"PW","scienceBaseUri":"55d45736e4b0518e35469508","contributors":{"authors":[{"text":"Mahan, Carolyn G.","contributorId":146582,"corporation":false,"usgs":false,"family":"Mahan","given":"Carolyn","email":"","middleInitial":"G.","affiliations":[{"id":12754,"text":"Penn State University Altoona","active":true,"usgs":false}],"preferred":false,"id":568352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":568351,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Bruce","contributorId":146583,"corporation":false,"usgs":false,"family":"Miller","given":"Bruce","email":"","affiliations":[{"id":6945,"text":"private 3721 2nd Avenue, Salt Lake City","active":true,"usgs":false}],"preferred":false,"id":568353,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saunders, Michael C.","contributorId":146584,"corporation":false,"usgs":false,"family":"Saunders","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":16724,"text":"Penn Sate University","active":true,"usgs":false}],"preferred":false,"id":568354,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70122982,"text":"ds852 - 2014 - Digital topographic data based on lidar survey of Mount Shasta Volcano, California, July-September 2010","interactions":[],"lastModifiedDate":"2019-03-15T10:15:30","indexId":"ds852","displayToPublicDate":"2014-11-04T13:30:00","publicationYear":"2014","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":"852","title":"Digital topographic data based on lidar survey of Mount Shasta Volcano, California, July-September 2010","docAbstract":"The most voluminous of the Cascade volcanoes, northern California’s Mount Shasta, is a massive compound stratovolcano composed of at least four main edifices constructed over a period of at least 590,000 years. An ancestral Shasta volcano was destroyed by Earth’s largest known Quaternary subaerial debris avalanche, which filled Shasta Valley, northwest of the volcano. The Hotlum cone, forming the present summit, the Shastina lava dome complex, and the Black Butte lava dome on the southwest flank, were constructed during the early Holocene.
As part of the American Recovery and Reinvestment Act (ARRA) of 2009, the U.S. Geological Survey was awarded funding for high-precision airborne lidar (light detection and ranging) data collection at several volcanoes in the Cascade Range. Data collection was arranged by the Oregon Lidar Consortium, administered by the Oregon Department of Geology and Mineral Industries (DOGAMI). The Oregon Lidar Consortium contracted with Watershed Sciences, Inc., to collect 1,220 square km of high-precision airborne lidar data. These data provide a digital map of the ground surface beneath forest cover with horizontal resolution of 1 m (average of 1.82 ground laser returns per square meter) and estimated vertical accuracy of ±4 centimeters (1 sigma), and horizontal accuracies of ±1.5 centimeters. These data will contribute to monitoring and description of natural hazards, the study of regional geology and volcanic landforms, and analysis of landscape modification during and after the next volcanic eruption at Mount Shasta.
Survey Bounding Coordinates:
The U.S. Geological Survey, in cooperation with the New Mexico Environment Department, compiled data from various sources to develop a dataset that can be used to conduct an assessment of the total dissolved solids in surface water and groundwater of the Palomas, Mesilla, and Hueco Basins in New Mexico and Texas, from below Caballo Reservoir, N. Mex., to Fort Quitman, Tex. Data include continuous surface-water discharge records at various locations on the Rio Grande; surface-water-quality data for the Rio Grande collected at selected locations in the Palomas, Mesilla, and Hueco Basins; groundwater levels and groundwater-quality data collected from selected wells in the Palomas and Mesilla Basins; and data from several seepage investigations conducted on the Rio Grande and selected drains in the Mesilla Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds884","collaboration":"Prepared in cooperation with the New Mexico Environment Department","usgsCitation":"McKean, S., Matherne, A.M., and Thomas, N., 2014, Water quality, discharge, and groundwater levels in the Palomas, Mesilla, and Hueco Basins in New Mexico and Texas from below Caballo Reservoir, New Mexico, to Fort Quitman, Texas, 1889-2013: U.S. Geological Survey Data Series 884, Report: HTML Document; Downloads Directory, https://doi.org/10.3133/ds884.","productDescription":"Report: HTML Document; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1889-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-057294","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":295866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds884.png"},{"id":295851,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0884/"},{"id":295864,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0884/downloads/","text":"Downloads Directory"}],"projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"New Mexico, Texas","otherGeospatial":"Hueco Basin, Mesilla Basin, Palomas Basin","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459eaa4e4b009f8aec97025","contributors":{"authors":[{"text":"McKean, Sarah E.","contributorId":71894,"corporation":false,"usgs":true,"family":"McKean","given":"Sarah E.","affiliations":[],"preferred":false,"id":523263,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matherne, Anne Marie 0000-0002-5873-2226 matherne@usgs.gov","orcid":"https://orcid.org/0000-0002-5873-2226","contributorId":303,"corporation":false,"usgs":true,"family":"Matherne","given":"Anne","email":"matherne@usgs.gov","middleInitial":"Marie","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":523264,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Nicole nithomas@usgs.gov","contributorId":5649,"corporation":false,"usgs":true,"family":"Thomas","given":"Nicole","email":"nithomas@usgs.gov","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":523265,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70131499,"text":"70131499 - 2014 - Lake Michigan offshore ecosystem structure and food web changes from 1987 to 2008","interactions":[],"lastModifiedDate":"2014-11-04T12:50:31","indexId":"70131499","displayToPublicDate":"2014-11-04T13:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Lake Michigan offshore ecosystem structure and food web changes from 1987 to 2008","docAbstract":"Ecosystems undergo dynamic changes owing to species invasions, fisheries management decisions, landscape modifications, and nutrient inputs. At Lake Michigan, new invaders (e.g., dreissenid mussels (Dreissena spp.), spiny water flea (Bythotrephes longimanus), round goby (Neogobius melanostomus)) have proliferated and altered energy transfer pathways, while nutrient concentrations and stocking rates to support fisheries have changed. We developed an ecosystem model to describe food web structure in 1987 and ran simulations through 2008 to evaluate changes in biomass of functional groups, predator consumption, and effects of recently invading species. Keystone functional groups from 1987 were identified as Mysis, burbot (Lota lota), phytoplankton, alewife (Alosa pseudoharengus), nonpredatory cladocerans, and Chinook salmon (Oncorhynchus tshawytscha). Simulations predicted biomass reductions across all trophic levels and predicted biomasses fit observed trends for most functional groups. The effects of invasive species (e.g., dreissenid grazing) increased across simulation years, but were difficult to disentangle from other changes (e.g., declining offshore nutrient concentrations). In total, our model effectively represented recent changes to the Lake Michigan ecosystem and provides an ecosystem-based tool for exploring future resource management scenarios.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Canadian Journal of Fisheries and Aquatic Sciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"NRC Research Press","publisherLocation":"Ottawa, Canada","usgsCitation":"Rogers, M.W., Bunnell, D., Madenjian, C.P., and Warner, D.M., 2014, Lake Michigan offshore ecosystem structure and food web changes from 1987 to 2008: Canadian Journal of Fisheries and Aquatic Sciences, v. 71, no. 7, p. 1072-7086.","productDescription":"15 p.","startPage":"1072","endPage":"7086","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055220","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":295862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295769,"type":{"id":15,"text":"Index Page"},"url":"https://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2013-0514#.VFOBV_nF-8w"}],"country":"United States","otherGeospatial":"Lake Michigan","volume":"71","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459eaa1e4b009f8aec96fee","contributors":{"authors":[{"text":"Rogers, Mark W. 0000-0001-7205-5623 mwrogers@usgs.gov","orcid":"https://orcid.org/0000-0001-7205-5623","contributorId":4590,"corporation":false,"usgs":true,"family":"Rogers","given":"Mark","email":"mwrogers@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":521314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David B. 0000-0003-3521-7747 dbunnell@usgs.gov","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":3139,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":521315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":521316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warner, David M. 0000-0003-4939-5368 dmwarner@usgs.gov","orcid":"https://orcid.org/0000-0003-4939-5368","contributorId":2986,"corporation":false,"usgs":true,"family":"Warner","given":"David","email":"dmwarner@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":521317,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70125639,"text":"ds885 - 2014 - EAARL-B submerged topography: Barnegat Bay, New Jersey, pre-Hurricane Sandy, 2012","interactions":[],"lastModifiedDate":"2014-11-06T10:09:12","indexId":"ds885","displayToPublicDate":"2014-11-04T12:45:00","publicationYear":"2014","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":"885","title":"EAARL-B submerged topography: Barnegat Bay, New Jersey, pre-Hurricane Sandy, 2012","docAbstract":"These remotely sensed, geographically referenced elevation measurements of lidar-derived submerged topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida.
\n\n
This project provides highly detailed and accurate datasets for part of Barnegat Bay, New Jersey, acquired pre-Hurricane Sandy on October 18, 22, 23, and 26, 2012. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nm) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL-B sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, down-looking red-green-blue (RGB) and infrared (IR) digital cameras, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL-B platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys.
\n\n
Elevation measurements were collected over the survey area using the EAARL-B system. The resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed originally in a NASA-USGS collaboration. The exploration and processing of lidar data in an interactive or batch mode is supported using ALPS. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. The Airborne Lidar Processing System (ALPS) is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the \"bare earth\" under vegetation from a point cloud of last return elevations.
\n\n
For more information about similar projects, please visit the Lidar for Science and Resource Management Web site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds885","usgsCitation":"Wright, C.W., Troche, R.J., Klipp, E.S., Kranenburg, C., Fredericks, X., and Nagle, D.B., 2014, EAARL-B submerged topography: Barnegat Bay, New Jersey, pre-Hurricane Sandy, 2012: U.S. Geological Survey Data Series 885, Web Page, https://doi.org/10.3133/ds885.","productDescription":"Web Page","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-054940","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":295861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":295859,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0885/"},{"id":295860,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0885/home.html"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f032e4b0bc0bec09f5fe","contributors":{"authors":[{"text":"Wright, C. Wayne wwright@usgs.gov","contributorId":2973,"corporation":false,"usgs":true,"family":"Wright","given":"C.","email":"wwright@usgs.gov","middleInitial":"Wayne","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":519514,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Troche, Rodolfo J. rtroche@usgs.gov","contributorId":4304,"corporation":false,"usgs":true,"family":"Troche","given":"Rodolfo","email":"rtroche@usgs.gov","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519517,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klipp, Emily S. eklipp@usgs.gov","contributorId":2754,"corporation":false,"usgs":true,"family":"Klipp","given":"Emily","email":"eklipp@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519512,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kranenburg, Christine J. ckranenburg@usgs.gov","contributorId":3924,"corporation":false,"usgs":true,"family":"Kranenburg","given":"Christine J.","email":"ckranenburg@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":519516,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fredericks, Xan 0000-0001-7186-6555 afredericks@usgs.gov","orcid":"https://orcid.org/0000-0001-7186-6555","contributorId":2972,"corporation":false,"usgs":true,"family":"Fredericks","given":"Xan","email":"afredericks@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519513,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nagle, David B. 0000-0002-2306-6147 dnagle@usgs.gov","orcid":"https://orcid.org/0000-0002-2306-6147","contributorId":3380,"corporation":false,"usgs":true,"family":"Nagle","given":"David","email":"dnagle@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519515,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70128981,"text":"ds888 - 2014 - EAARL-B coastal topography: Fire Island, New York, pre-Hurricane Sandy, 2012: seamless (bare earth and submerged)","interactions":[],"lastModifiedDate":"2014-11-06T10:54:55","indexId":"ds888","displayToPublicDate":"2014-11-04T12:15:00","publicationYear":"2014","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":"888","title":"EAARL-B coastal topography: Fire Island, New York, pre-Hurricane Sandy, 2012: seamless (bare earth and submerged)","docAbstract":"These remotely sensed, geographically referenced elevation measurements of lidar-derived seamless (bare-earth and submerged) topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida.
\n\n
This project provides highly detailed and accurate datasets for part of Fire Island, New York, acquired pre-Hurricane Sandy on October 27, 2012. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nm) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL-B sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, down-looking red-green-blue (RGB) and infrared (IR) digital cameras, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL-B platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys.
\n\n
Elevation measurements were collected over the survey area using the EAARL-B system. The resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed originally in a NASA-USGS collaboration. The exploration and processing of lidar data in an interactive or batch mode is supported using ALPS. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. The Airborne Lidar Processing System (ALPS) is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the \"bare earth\" under vegetation from a point cloud of last return elevations.
\n\n
For more information about similar projects, please visit the Lidar for Science and Resource Management Web site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds888","usgsCitation":"Wright, C.W., Kranenburg, C., Klipp, E.S., Troche, R.J., Fredericks, X., Masessa, M.L., and Nagle, D.B., 2014, EAARL-B coastal topography: Fire Island, New York, pre-Hurricane Sandy, 2012: seamless (bare earth and submerged): U.S. Geological Survey Data Series 888, HTML Document, https://doi.org/10.3133/ds888.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056095","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":295858,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":295857,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0888/html/home.html"},{"id":295856,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0888/"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f032e4b0bc0bec09f600","contributors":{"authors":[{"text":"Wright, C. Wayne wwright@usgs.gov","contributorId":2973,"corporation":false,"usgs":true,"family":"Wright","given":"C.","email":"wwright@usgs.gov","middleInitial":"Wayne","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":519776,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kranenburg, Christine J. ckranenburg@usgs.gov","contributorId":3924,"corporation":false,"usgs":true,"family":"Kranenburg","given":"Christine J.","email":"ckranenburg@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":519778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klipp, Emily S. eklipp@usgs.gov","contributorId":2754,"corporation":false,"usgs":true,"family":"Klipp","given":"Emily","email":"eklipp@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Troche, Rodolfo J. rtroche@usgs.gov","contributorId":4304,"corporation":false,"usgs":true,"family":"Troche","given":"Rodolfo","email":"rtroche@usgs.gov","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519779,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fredericks, Xan 0000-0001-7186-6555 afredericks@usgs.gov","orcid":"https://orcid.org/0000-0001-7186-6555","contributorId":2972,"corporation":false,"usgs":true,"family":"Fredericks","given":"Xan","email":"afredericks@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519775,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Masessa, Melanie L. mmasessa@usgs.gov","contributorId":5903,"corporation":false,"usgs":true,"family":"Masessa","given":"Melanie","email":"mmasessa@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519780,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nagle, David B. 0000-0002-2306-6147 dnagle@usgs.gov","orcid":"https://orcid.org/0000-0002-2306-6147","contributorId":3380,"corporation":false,"usgs":true,"family":"Nagle","given":"David","email":"dnagle@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519777,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70124957,"text":"sir20145177 - 2014 - Estimation of regional flow-duration curves for Indiana and Illinois","interactions":[],"lastModifiedDate":"2026-04-02T14:14:01.303233","indexId":"sir20145177","displayToPublicDate":"2014-11-04T10:30:00","publicationYear":"2014","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":"2014-5177","displayTitle":"Estimation of Regional Flow-Duration Curves for Indiana and Illinois","title":"Estimation of regional flow-duration curves for Indiana and Illinois","docAbstract":"Flow-duration curves (FDCs) of daily streamflow are useful for many applications in water resources planning and management but must be estimated at ungaged sites. One common technique for estimating FDCs at ungaged sites in a given region is to use equations obtained by linear regression of FDC quantiles against multiple basin characteristics that can be computed by means of a geographic information system (GIS) computer program. In this study, such regional regression equations for estimating FDC quantiles were computed at the 0.1, 0.2, 0.5, 1, 2, 5, 10, 20, 25, 30, 40, 50, 60, 70, 75, 80, 90, 95, 98, 99, 99.5, 99.8, and 99.9-percent exceedance probabilities for rural, unregulated streams in Indiana and Illinois with temporally stationary records, using data through September 30, 2007. The approach used accounts for censored values below 0.01 cubic feet per second, which are observed at exceedance probabilities as low as 70 percent (that is, occurring at least 30 percent of the time). The basin characteristics used are suitable for computation by the USGS Web-based application, StreamStats, and are available for all U.S. Environmental Protection Agency (EPA) Region V states and the larger Great Lakes area, with some specific local exceptions. Indiana and Illinois were each divided into three regions, and a different set of equations for estimating FDC quantiles was computed for each region.
The error of estimation of the FDC quantiles, measured as the mean square residual in log space converted to a percentage of the quantile, varies somewhat among regions and varies strongly with exceedance probability, with a minimum error of 10 to 20 percent at an exceedance probability of 5 or 10 percent, but rises to 17 to 38 percent at the high-flow end of the FDCs (the 0.1-percent quantile) and 100 to 745 percent at the low-flow end. For comparison, errors of estimation also were computed for FDC quantiles estimated by linear regression on drainage area alone and by using the drainage-area ratio (DAR) method. Three criteria, the nearest basin centroid and two others termed “strict” and “broad”, were used to select index stations for the DAR method. The “strict” and “broad” criteria put conditions on the basin centroid distance and the range of their drainage-area ratios, and the errors were averaged for all index station pairs satisfying each criterion. The use of the simpler DAR method usually resulted in higher errors of estimation compared to the linear regression equations with multiple basin characteristics, except occasionally in the case of the DAR method with the strict index station selection criterion, a criterion that is rarely possible to satisfy in practice.
An example application of the estimated equations to one gaged and a few ungaged locations in a watershed in the study area is included to illustrate the steps required. These steps are the computation of the basin characteristics and, using those characteristics together with the estimated equations, the computation of the FDC quantiles and their uncertainties.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145177","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, Region V, and the Indiana Department of Environmental Management","usgsCitation":"Over, T.M., Riley, J.D., Marti, M.K., Sharpe, J.B., and Arvin, D., 2014, Estimation of regional flow-duration curves for Indiana and Illinois (ver. 2.0, April 2022): U.S. Geological Survey Scientific Investigations Report 2014–5177, 24 p. and additional downloads, tables 2–5, 8–13, and 18, https://doi.org/10.3133/sir20145177.","productDescription":"Report: v, 24 p.; Tables: 2-5, 8-13, and 18; Data Release","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053042","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":438739,"rank":26,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FM4VUZ","text":"USGS data release","linkHelpText":"Data for the Estimation of Regional Flow-Duration Curves for Indiana and Illinois (ver. 3.0, December 2021)"},{"id":398053,"rank":25,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table18.xlsx","text":"Table 18","size":"37.7 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398052,"rank":24,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table18.csv","text":"Table 18","size":"9.80 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398051,"rank":23,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table13.xlsx","text":"Table 13","size":"28.0 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398050,"rank":22,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table13.csv","text":"Table 13","size":"6.03 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398048,"rank":21,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table12.xlsx","text":"Table 12","size":"29.3 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398047,"rank":20,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table12.csv","text":"Table 12","size":"7.08 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398045,"rank":19,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table11.xlsx","text":"Table 11","size":"27.5 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398044,"rank":18,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table11.csv","text":"Table 11","size":"5.33 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398042,"rank":17,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table10.xlsx","text":"Table 10","size":"30.0 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398041,"rank":16,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table10.csv","text":"Table 10","size":"6.81 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398040,"rank":15,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table9.xlsx","text":"Table 9","size":"32.1 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398037,"rank":12,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table8.csv","text":"Table 8","size":"6.54 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398035,"rank":11,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table5.xlsx","text":"Table 5","size":"66.0 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398034,"rank":10,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table5.csv","text":"Table 5","size":"50.2 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398033,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table4.xlsx","text":"Table 4","size":"83.9 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398032,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table4.csv","text":"Table 4","size":"38.1 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398030,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table3.xlsx","text":"Table 3","size":"71.9 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398029,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table3.csv","text":"Table 3","size":"27.5 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398028,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table2.xlsx","text":"Table 2","size":"62.7 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398039,"rank":14,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table9.csv","text":"Table 9","size":"22.2 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398038,"rank":13,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table8.xlsx","text":"Table 8","size":"29.4 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":398027,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177_table2.csv","text":"Table 2","size":"25.1 kB","linkFileType":{"id":7,"text":"csv"}},{"id":398026,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2014/5177/versionHist.txt","text":"Version History","size":"1 kB","linkFileType":{"id":2,"text":"txt"}},{"id":398025,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5177/sir20145177.pdf","text":"Report","size":"1.63 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":398024,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2014/5177/coverthb2.jpg"},{"id":501940,"rank":27,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_101022.htm","linkFileType":{"id":5,"text":"html"}}],"projection":"Albers Equal-Area Conic projection","country":"United States","state":"Illinois, Indiana","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-89.366031,42.500274],[-88.786681,42.491983],[-88.115285,42.496219],[-87.800561,42.49192],[-87.79823,42.473054],[-87.80537,42.384721],[-87.820858,42.361584],[-87.830646,42.331368],[-87.834769,42.301522],[-87.828569,42.269922],[-87.812461,42.232278],[-87.800066,42.208024],[-87.741662,42.128227],[-87.712206,42.096455],[-87.682359,42.075729],[-87.671462,42.058334],[-87.668982,42.029142],[-87.630953,41.933132],[-87.624134,41.904574],[-87.611659,41.892216],[-87.616251,41.868933],[-87.60945,41.845233],[-87.600549,41.826833],[-87.580948,41.804334],[-87.576347,41.786034],[-87.560646,41.766034],[-87.542845,41.752135],[-87.530745,41.748235],[-87.524141,41.72399],[-87.524044,41.708335],[-87.520544,41.709935],[-87.505343,41.691535],[-87.470742,41.672835],[-87.463142,41.675535],[-87.446113,41.66934],[-87.43853,41.670679],[-87.432396,41.66053],[-87.438941,41.654335],[-87.42344,41.642835],[-87.365439,41.629536],[-87.324338,41.623036],[-87.261536,41.620336],[-87.187651,41.629653],[-87.160625,41.637266],[-87.160784,41.645385],[-87.125835,41.650302],[-87.120322,41.645701],[-87.027888,41.674661],[-86.93483,41.709638],[-86.90913,41.726938],[-86.824828,41.76024],[-84.805883,41.760216],[-84.802547,40.50181],[-84.814179,39.814212],[-84.820157,39.10548],[-84.831197,39.10192],[-84.860689,39.07814],[-84.888873,39.066376],[-84.897364,39.057378],[-84.889065,39.04082],[-84.870168,39.025551],[-84.83712,38.988059],[-84.829857,38.969385],[-84.83516,38.957961],[-84.877762,38.920357],[-84.877029,38.909016],[-84.867778,38.899133],[-84.812746,38.895132],[-84.785234,38.880439],[-84.785799,38.869496],[-84.791002,38.860572],[-84.823363,38.839196],[-84.829958,38.830632],[-84.827098,38.818634],[-84.813939,38.800209],[-84.812877,38.786087],[-84.828714,38.783208],[-84.887919,38.794652],[-84.941071,38.775627],[-84.990006,38.778383],[-85.100963,38.7268],[-85.13868,38.699168],[-85.172528,38.688082],[-85.190507,38.68795],[-85.213257,38.695446],[-85.226062,38.705456],[-85.246505,38.731821],[-85.275454,38.741172],[-85.306049,38.741649],[-85.363827,38.730477],[-85.410925,38.73708],[-85.434065,38.729455],[-85.452114,38.709348],[-85.456978,38.689135],[-85.455486,38.68209],[-85.438742,38.659319],[-85.437446,38.601724],[-85.415821,38.563558],[-85.4156,38.546341],[-85.423077,38.531581],[-85.472221,38.506279],[-85.482897,38.485701],[-85.498866,38.468242],[-85.536542,38.456083],[-85.587758,38.450495],[-85.607629,38.439295],[-85.620521,38.423105],[-85.632937,38.395666],[-85.638041,38.380338],[-85.638777,38.361443],[-85.653641,38.327108],[-85.683561,38.295469],[-85.744862,38.26717],[-85.761062,38.27257],[-85.765963,38.280469],[-85.780963,38.288469],[-85.816164,38.282969],[-85.829364,38.276769],[-85.845464,38.23027],[-85.894764,38.188469],[-85.908764,38.161169],[-85.906163,38.08617],[-85.915214,38.067664],[-85.925418,38.023456],[-85.951467,38.005608],[-86.009127,37.998529],[-86.029509,37.99264],[-86.035012,37.984814],[-86.033386,37.970382],[-86.038188,37.95935],[-86.045208,37.958258],[-86.053912,37.963571],[-86.064859,37.975618],[-86.075393,37.996948],[-86.095766,38.00893],[-86.12757,38.016011],[-86.16731,38.009879],[-86.178983,38.011308],[-86.220371,38.027922],[-86.233057,38.039305],[-86.261273,38.052721],[-86.273584,38.067443],[-86.27872,38.089303],[-86.271802,38.137874],[-86.287773,38.15805],[-86.317139,38.172907],[-86.347736,38.195363],[-86.360377,38.198796],[-86.373801,38.193352],[-86.378151,38.185845],[-86.377434,38.171379],[-86.37174,38.164183],[-86.325941,38.154317],[-86.321274,38.147418],[-86.323453,38.139032],[-86.335145,38.129242],[-86.379775,38.129274],[-86.401653,38.105396],[-86.431749,38.126121],[-86.449793,38.127223],[-86.463248,38.119278],[-86.466081,38.114437],[-86.463858,38.101177],[-86.434046,38.086763],[-86.430091,38.078638],[-86.432789,38.067171],[-86.452192,38.05049],[-86.51176,38.044448],[-86.521825,38.038327],[-86.524969,38.027879],[-86.525174,37.968228],[-86.520503,37.954438],[-86.50939,37.942492],[-86.50662,37.930719],[-86.534156,37.917007],[-86.586542,37.922285],[-86.599848,37.906754],[-86.598108,37.867382],[-86.609163,37.855408],[-86.638265,37.842718],[-86.652516,37.841636],[-86.661637,37.849714],[-86.661233,37.862761],[-86.644754,37.894806],[-86.647081,37.908621],[-86.680929,37.91501],[-86.716138,37.894073],[-86.73146,37.89434],[-86.75099,37.912893],[-86.765054,37.93251],[-86.794985,37.988982],[-86.820071,37.999392],[-86.85595,37.987292],[-86.902413,37.946161],[-86.919329,37.936664],[-86.969044,37.932858],[-87.010315,37.919668],[-87.033444,37.906593],[-87.045101,37.893775],[-87.043854,37.870796],[-87.067836,37.806065],[-87.090636,37.787808],[-87.111133,37.782512],[-87.129629,37.786608],[-87.14195,37.816176],[-87.162319,37.840159],[-87.20224,37.843791],[-87.220944,37.849134],[-87.302324,37.898445],[-87.344933,37.911164],[-87.380247,37.935596],[-87.418585,37.944763],[-87.450458,37.941451],[-87.501131,37.909162],[-87.511499,37.906426],[-87.559342,37.931146],[-87.57203,37.947466],[-87.577915,37.971542],[-87.589816,37.976042],[-87.601416,37.972542],[-87.606216,37.949642],[-87.625616,37.933442],[-87.628416,37.92145],[-87.620272,37.906922],[-87.591582,37.887194],[-87.588729,37.860984],[-87.615399,37.831974],[-87.645858,37.825899],[-87.672397,37.829127],[-87.679188,37.836321],[-87.681633,37.855917],[-87.66282,37.881449],[-87.665025,37.893514],[-87.67573,37.90193],[-87.684018,37.903498],[-87.717971,37.89257],[-87.740148,37.89465],[-87.76226,37.890906],[-87.7909,37.875714],[-87.830578,37.876516],[-87.841193,37.882325],[-87.844691,37.892048],[-87.857243,37.900649],[-87.87254,37.920999],[-87.883321,37.926238],[-87.898062,37.927514],[-87.904789,37.924892],[-87.936784,37.892587],[-87.940839,37.883338],[-87.936228,37.867937],[-87.910276,37.843416],[-87.903804,37.817762],[-87.90681,37.807624],[-87.932554,37.797672],[-87.944506,37.775256],[-87.95259,37.771742],[-87.96003,37.773223],[-87.976389,37.788004],[-87.997102,37.797672],[-88.015144,37.80193],[-88.02803,37.799224],[-88.035827,37.791917],[-88.042602,37.76712],[-88.059588,37.742608],[-88.122412,37.709685],[-88.159372,37.661847],[-88.156827,37.632801],[-88.142225,37.603737],[-88.139973,37.586451],[-88.13341,37.574273],[-88.105585,37.55618],[-88.088049,37.535124],[-88.069018,37.525297],[-88.061342,37.505327],[-88.064234,37.484548],[-88.067728,37.481593],[-88.072386,37.483563],[-88.087664,37.471059],[-88.135142,37.471626],[-88.188615,37.461896],[-88.281667,37.452596],[-88.312585,37.440591],[-88.333183,37.42721],[-88.348405,37.410726],[-88.365471,37.401663],[-88.39734,37.421644],[-88.413108,37.424468],[-88.456,37.408482],[-88.476592,37.386875],[-88.484462,37.345609],[-88.511497,37.298527],[-88.515939,37.284043],[-88.506942,37.266656],[-88.509328,37.26213],[-88.487277,37.244077],[-88.471753,37.220155],[-88.447764,37.203527],[-88.431488,37.160298],[-88.424403,37.152428],[-88.443538,37.109192],[-88.444605,37.098601],[-88.458948,37.073796],[-88.504437,37.065265],[-88.545403,37.070003],[-88.576718,37.085852],[-88.589207,37.099655],[-88.625889,37.119458],[-88.644872,37.122844],[-88.693983,37.141155],[-88.720224,37.140641],[-88.732105,37.143956],[-88.80572,37.188595],[-88.916934,37.224291],[-88.966831,37.229891],[-89.000968,37.224401],[-89.041263,37.202881],[-89.086526,37.165602],[-89.111189,37.119052],[-89.134931,37.103278],[-89.14132,37.093865],[-89.154504,37.088907],[-89.168087,37.074218],[-89.181369,37.046305],[-89.178975,37.020928],[-89.166447,37.003337],[-89.132685,36.9822],[-89.170008,36.970298],[-89.185491,36.973518],[-89.192097,36.979995],[-89.200793,37.016164],[-89.234053,37.037277],[-89.25493,37.072014],[-89.259936,37.064071],[-89.307726,37.069654],[-89.310819,37.057897],[-89.304752,37.047565],[-89.277715,37.03614],[-89.260003,37.023288],[-89.257608,37.015496],[-89.263527,37.00005],[-89.278628,36.98867],[-89.29213,36.992189],[-89.322982,37.01609],[-89.362397,37.030156],[-89.378277,37.039605],[-89.385434,37.05513],[-89.375712,37.080505],[-89.37871,37.094586],[-89.38805,37.107481],[-89.41173,37.122507],[-89.42558,37.138235],[-89.461862,37.199517],[-89.4675,37.221844],[-89.458246,37.247066],[-89.470525,37.253357],[-89.488728,37.251507],[-89.506773,37.268537],[-89.51834,37.285497],[-89.511842,37.310825],[-89.489005,37.333368],[-89.447556,37.340475],[-89.432836,37.347056],[-89.421054,37.387668],[-89.42594,37.407471],[-89.439769,37.4372],[-89.475525,37.471388],[-89.516447,37.535558],[-89.521925,37.560735],[-89.519808,37.582748],[-89.486062,37.580853],[-89.477548,37.585885],[-89.475932,37.592998],[-89.517718,37.641217],[-89.51204,37.680985],[-89.514255,37.689923],[-89.52573,37.698441],[-89.583316,37.713261],[-89.596566,37.732886],[-89.615586,37.74235],[-89.615933,37.748184],[-89.64953,37.745498],[-89.663352,37.750052],[-89.667993,37.759484],[-89.66038,37.786296],[-89.669644,37.799922],[-89.71748,37.825724],[-89.739873,37.84693],[-89.754104,37.846358],[-89.782035,37.855092],[-89.786369,37.851734],[-89.796087,37.859505],[-89.80036,37.868625],[-89.798041,37.879655],[-89.842649,37.905196],[-89.862949,37.896906],[-89.881475,37.879591],[-89.901832,37.869822],[-89.923185,37.870672],[-89.950594,37.881526],[-89.973642,37.917661],[-89.974918,37.926719],[-89.962273,37.934363],[-89.959646,37.940196],[-89.947429,37.940336],[-89.932467,37.947497],[-89.925389,37.95413],[-89.925085,37.960021],[-89.933797,37.959143],[-89.942099,37.970121],[-89.978919,37.962791],[-89.997103,37.963225],[-90.008353,37.970179],[-90.03241,37.995258],[-90.051357,38.003584],[-90.059367,38.015543],[-90.08826,38.015772],[-90.11052,38.026547],[-90.126194,38.040702],[-90.126396,38.054897],[-90.130788,38.062341],[-90.158533,38.074735],[-90.17222,38.069636],[-90.218708,38.094365],[-90.243116,38.112669],[-90.274928,38.157615],[-90.290765,38.170453],[-90.331554,38.18758],[-90.359559,38.224525],[-90.373929,38.281853],[-90.372519,38.323354],[-90.368219,38.340254],[-90.349743,38.377609],[-90.295316,38.426753],[-90.285215,38.443453],[-90.279215,38.472453],[-90.260314,38.528352],[-90.224212,38.575051],[-90.196011,38.594451],[-90.18451,38.611551],[-90.17801,38.63375],[-90.18111,38.65955],[-90.18641,38.67475],[-90.20921,38.70275],[-90.21201,38.71175],[-90.20991,38.72605],[-90.176309,38.754449],[-90.166409,38.772649],[-90.123107,38.798048],[-90.114707,38.815048],[-90.109407,38.843548],[-90.113327,38.849306],[-90.166409,38.876348],[-90.19761,38.887648],[-90.223041,38.907389],[-90.250248,38.919344],[-90.309454,38.92412],[-90.395816,38.960037],[-90.440078,38.967364],[-90.450792,38.967764],[-90.472122,38.958838],[-90.482419,38.94446],[-90.486974,38.925982],[-90.500117,38.910408],[-90.54403,38.87505],[-90.566557,38.868847],[-90.583388,38.86903],[-90.628485,38.891617],[-90.639917,38.908272],[-90.653164,38.916141],[-90.663372,38.928042],[-90.675949,38.96214],[-90.678193,38.991851],[-90.713629,39.053977],[-90.682744,39.088348],[-90.681086,39.10059],[-90.686051,39.117785],[-90.702923,39.138749],[-90.707902,39.15086],[-90.71048,39.176366],[-90.717404,39.197414],[-90.717113,39.213912],[-90.72996,39.255894],[-90.751599,39.265432],[-90.767648,39.280025],[-90.775673,39.292811],[-90.790675,39.302908],[-90.793461,39.309498],[-90.816851,39.320496],[-90.8475,39.345272],[-90.893777,39.367343],[-90.904862,39.379403],[-90.928745,39.387544],[-90.939025,39.402744],[-90.993789,39.422959],[-91.03827,39.448436],[-91.059439,39.46886],[-91.064305,39.494643],[-91.079769,39.507728],[-91.100307,39.538695],[-91.153628,39.548248],[-91.168419,39.564928],[-91.174232,39.591975],[-91.181936,39.602677],[-91.229317,39.620853],[-91.27614,39.665759],[-91.302485,39.679631],[-91.367753,39.729029],[-91.369953,39.745042],[-91.365125,39.758723],[-91.363444,39.792804],[-91.377971,39.811273],[-91.432919,39.840554],[-91.446385,39.870394],[-91.443513,39.893583],[-91.420878,39.914865],[-91.41936,39.927717],[-91.465315,39.983995],[-91.494878,40.036453],[-91.489606,40.057435],[-91.509245,40.121876],[-91.511749,40.147091],[-91.508324,40.156326],[-91.513079,40.178537],[-91.504477,40.198262],[-91.507269,40.209338],[-91.505828,40.238839],[-91.490524,40.259498],[-91.492727,40.278217],[-91.46214,40.342414],[-91.439342,40.366569],[-91.415695,40.381381],[-91.381958,40.387632],[-91.372921,40.399108],[-91.373721,40.417891],[-91.381769,40.442555],[-91.364915,40.484168],[-91.364211,40.500043],[-91.367876,40.510479],[-91.384531,40.530948],[-91.404125,40.539127],[-91.405241,40.554641],[-91.379752,40.57445],[-91.359873,40.601805],[-91.339719,40.613488],[-91.306524,40.626231],[-91.253074,40.637962],[-91.18698,40.637297],[-91.123928,40.669152],[-91.110927,40.703262],[-91.115735,40.725168],[-91.110424,40.745528],[-91.091703,40.779708],[-91.092256,40.792909],[-91.097649,40.805575],[-91.092993,40.821079],[-91.05643,40.848387],[-91.044653,40.868356],[-91.021562,40.884021],[-91.009536,40.900565],[-90.962916,40.924957],[-90.952233,40.954047],[-90.958142,40.979767],[-90.945949,41.006495],[-90.942253,41.034702],[-90.949383,41.07271],[-90.946259,41.094734],[-90.99496,41.160624],[-91.007586,41.166183],[-91.027214,41.163373],[-91.041536,41.166138],[-91.07298,41.207151],[-91.113648,41.241401],[-91.114186,41.250029],[-91.092034,41.286911],[-91.074841,41.305578],[-91.06652,41.365246],[-91.05158,41.385283],[-91.04589,41.414085],[-91.027787,41.423603],[-90.979815,41.434321],[-90.930016,41.421404],[-90.846558,41.455141],[-90.750142,41.449632],[-90.655839,41.462132],[-90.605937,41.494232],[-90.602137,41.506032],[-90.595237,41.511032],[-90.567236,41.517532],[-90.556235,41.524232],[-90.540935,41.526133],[-90.500633,41.518033],[-90.461432,41.523533],[-90.41283,41.565333],[-90.343228,41.587833],[-90.339528,41.598633],[-90.343452,41.646959],[-90.334525,41.679559],[-90.313435,41.698082],[-90.317668,41.72269],[-90.310708,41.742214],[-90.278633,41.767358],[-90.216889,41.795335],[-90.187969,41.803163],[-90.180954,41.809354],[-90.181901,41.843216],[-90.173006,41.857402],[-90.170041,41.876439],[-90.153584,41.906614],[-90.152659,41.933058],[-90.163847,41.944934],[-90.164135,41.956178],[-90.146225,41.981329],[-90.140061,42.003252],[-90.150916,42.02944],[-90.163446,42.040407],[-90.168358,42.075779],[-90.161504,42.098912],[-90.162895,42.116718],[-90.17097,42.125198],[-90.190452,42.125779],[-90.201404,42.130937],[-90.207421,42.149109],[-90.216107,42.15673],[-90.250129,42.171469],[-90.282173,42.178846],[-90.328273,42.201047],[-90.356964,42.205445],[-90.391108,42.225473],[-90.400653,42.239293],[-90.419326,42.254467],[-90.430884,42.27823],[-90.420454,42.305374],[-90.421047,42.316109],[-90.415937,42.322699],[-90.419027,42.328505],[-90.477279,42.383794],[-90.487154,42.385141],[-90.506829,42.398792],[-90.555018,42.416138],[-90.560439,42.432897],[-90.567968,42.440389],[-90.606328,42.451505],[-90.646727,42.471904],[-90.654027,42.478503],[-90.656527,42.489203],[-90.640927,42.508302],[-90.07367,42.508275],[-89.366031,42.500274]]]},\"properties\":{\"name\":\"Illinois\",\"nation\":\"USA \"}}]}","edition":"Version 1.0: October 29, 2014; Version 2.0: April 5, 2022","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
In order to better define the size of the thermal anomaly in the Raft River Valley, Idaho, the U.S. Geological Survey drilled a series of intermediate-depth (nominal 500-ft depth) wells in 1977 and 1978. This report presents geologic, geophysical, and temperature data for these drill holes, along with data for five wells drilled by the Idaho National Engineering Laboratory with U.S. Department of Energy Funding. Data previously reported for other drill holes are also included in order to make them available as digital files.
\n\n
For purposes of defining the thermal anomaly for the geothermal system, temperature gradients are calculated over long depth intervals on the basis of the appearance of reasonable linear segments on a temperature versus plot depth. Temperature versus depth data for some drill holes can be represented by a single gradient, whereas others require multiple gradients to match the data. Data for some drill holes clearly reflect vertical flows of water in the formation surrounding the drill holes, and water velocities are calculated for these drill holes. Within The Narrows area, temperature versus depth data show reversals at different depth in different drill holes. In the main thermal area, temperatures in intermediate-depth drill holes vary approximately linearly but with very high values of temperature gradient. Temperature gradients on a map of the area can be reasonable divided into a large area of regional gradients and smaller areas defining the thermal anomalies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141201","usgsCitation":"Nathenson, M., Urban, T.C., and Covington, H., 2014, Geologic and geophysical data for wells drilled at Raft River Valley, Cassia County, Idaho, in 1977-1978 and data for wells drilled previously: U.S. Geological Survey Open-File Report 2014-1201, Report: iv, 30 p.; 2 Appendixes, https://doi.org/10.3133/ofr20141201.","productDescription":"Report: iv, 30 p.; 2 Appendixes","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052136","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":295850,"rank":9,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141201.JPG"},{"id":295822,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1201/"},{"id":295844,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1201/pdf/ofr20141201_appendixA.pdf"},{"id":295843,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1201/pdf/ofr2014-1201.pdf"},{"id":295845,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1201/pdf/ofr20141201_appendixB.pdf"},{"id":295846,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1201/pdf/ofr20141201_appendixA_figs.pdf"},{"id":295847,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1201/downloads/ofr20141201_appendixA_tables.zip"},{"id":295848,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1201/pdf/ofr20141201_appendixB_figs.pdf"},{"id":295849,"rank":8,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1201/downloads/ofr20141201_appendixB_tables.zip"}],"country":"United States","state":"Idaho","county":"Cassia County","otherGeospatial":"Raft River Valley","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459eaa1e4b009f8aec96fe4","contributors":{"authors":[{"text":"Nathenson, Manuel 0000-0002-5216-984X mnathnsn@usgs.gov","orcid":"https://orcid.org/0000-0002-5216-984X","contributorId":1358,"corporation":false,"usgs":true,"family":"Nathenson","given":"Manuel","email":"mnathnsn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":522919,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Urban, Thomas C.","contributorId":53949,"corporation":false,"usgs":true,"family":"Urban","given":"Thomas","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":522920,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Covington, Harry R.","contributorId":101309,"corporation":false,"usgs":true,"family":"Covington","given":"Harry R.","affiliations":[],"preferred":false,"id":522921,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70127080,"text":"sir20145182 - 2014 - Simulation of hydrologic conditions and suspended-sediment loads in the San Antonio River Basin downstream from San Antonio, Texas, 2000-12","interactions":[],"lastModifiedDate":"2016-08-05T12:08:21","indexId":"sir20145182","displayToPublicDate":"2014-11-04T09:45:00","publicationYear":"2014","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":"2014-5182","title":"Simulation of hydrologic conditions and suspended-sediment loads in the San Antonio River Basin downstream from San Antonio, Texas, 2000-12","docAbstract":"Suspended sediment in rivers and streams can play an important role in ecological health of rivers and estuaries and consequently is an important issue for water-resource managers. To better understand suspended-sediment loads and transport in a watershed, the U.S. Geological Survey (USGS), in cooperation with the San Antonio River Authority, developed a Hydrological Simulation Program—FORTRAN model to simulate hydrologic conditions and suspended-sediment loads during 2000–12 for four watersheds, which comprise the overall study area in the San Antonio River Basin (hereinafter referred to as the “USGS–2014 model”). The study area consists of approximately 2,150 square miles encompassing parts of Bexar, Guadalupe, Wilson, Karnes, DeWitt, Goliad, Victoria, and Refugio Counties. The USGS–2014 model was calibrated for hydrology and suspended sediment for 2006–12. Overall, model-fit statistics and graphic evaluations from the calibration and testing periods provided multiple lines of evidence indicating that the USGS–2014 model simulations of hydrologic and suspended-sediment conditions were mostly “good” to “very good.” Model simulation results indicated that approximately 1,230 tons per day of suspended sediment exited the study area and were delivered to the Guadalupe River during 2006–12, of which approximately 62 percent originated upstream from the study area. Sample data and simulated model results indicate that most of the suspended-sediment load in the study area consisted of silt- and clay-sized particles (less than 0.0625 millimeters). The Cibolo Creek watershed was the largest contributor of suspended sediment from the study area. For the entire study area, open/developed land and cropland exhibited the highest simulated soil erosion rates; however, the largest contributions of sediment (by land-cover type) were pasture and forest/rangeland/shrubland, which together composed approximately 80 percent of the land cover of the study area and generated about 70 percent of the suspended-sediment load from the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145182","collaboration":"Prepared in cooperation with the San Antonio River Authority","usgsCitation":"Banta, J., and Ockerman, D.J., 2014, Simulation of hydrologic conditions and suspended-sediment loads in the San Antonio River Basin downstream from San Antonio, Texas, 2000-12: U.S. Geological Survey Scientific Investigations Report 2014-5182, v, 46 p., https://doi.org/10.3133/sir20145182.","productDescription":"v, 46 p.","numberOfPages":"56","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2000-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-056710","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":295842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145182.jpg"},{"id":295821,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5182/"},{"id":295841,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5182/pdf/sir2014-5182.pdf"}],"country":"United States","state":"Texas","city":"San Antonio","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459eaa3e4b009f8aec97016","contributors":{"authors":[{"text":"Banta, J. Ryan 0000-0002-2226-7270 jbanta@usgs.gov","orcid":"https://orcid.org/0000-0002-2226-7270","contributorId":4723,"corporation":false,"usgs":true,"family":"Banta","given":"J. Ryan","email":"jbanta@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":522917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ockerman, Darwin J. 0000-0003-1958-1688 ockerman@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-1688","contributorId":1579,"corporation":false,"usgs":true,"family":"Ockerman","given":"Darwin","email":"ockerman@usgs.gov","middleInitial":"J.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":522918,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70127784,"text":"ofr20141215 - 2014 - Water-quality characteristics indicative of wastewater in selected streams in the upper Neuse River Basin, Durham and Orange Counties, North Carolina, from 2004 to 2013","interactions":[],"lastModifiedDate":"2016-12-08T16:58:12","indexId":"ofr20141215","displayToPublicDate":"2014-11-04T09:45:00","publicationYear":"2014","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":"2014-1215","title":"Water-quality characteristics indicative of wastewater in selected streams in the upper Neuse River Basin, Durham and Orange Counties, North Carolina, from 2004 to 2013","docAbstract":"Data were collected during three time periods to assess the effects of wastewater treatment and disposal practices on the occurrence of selected contaminants indicative of wastewater in the upper Neuse River Basin, North Carolina. The first phase of data collection, December 2004 to June 2005, and the second phase, April to October 2008, addressed the effects of point and nonpoint sources of wastewater effluent on stream quality during baseflow conditions. Point-source effects were assessed by sampling a municipal wastewater treatment plant outfall and sites on the Eno River upstream and downstream from the outfall. Water-quality data suggest that the wastewater treatment plant effluent contributed to increases in concentrations of nitrogen and carbamazepine at the downstream site. Nonpoint source effects were assessed by sampling seven small streams that drained an undeveloped area and residential areas served by either centralized or onsite wastewater treatment systems. Samples were analyzed for inorganic constituents, including nutrients, ions, and metals; organic compounds considered indicative of wastewater contamination; antibiotics, optical brighteners, and fecal coliform bacteria. Hypothesized differences in water quality between the sites with primarily centralized and onsite wastewater treatment were not apparent, likely due to the relatively large heterogeneity of the sites within each category.
\n\n
During the third phase of data collection, May 2012 to January 2013, data were collected to address the suitability of optical brighteners as tracers of wastewater in small streams during streamflow recession. Samples were collected at five small streams following periods of rainfall and analyzed for optical brighteners, specific conductance nutrients, and selected hormones. Optical brighteners were absent in the undeveloped catchment but were present in the recession period after rainfall events in catchments with centralized though possibly leaky sewage treatment and areas with onsite treatment. Sand filter systems in areas with onsite treatment appear to change the effluent flow and retention characteristics such that optical brighteners were present both before and after rainfall events. Nitrate plus nitrite, as nitrogen concentrations in samples from this last study phase generally were larger than those collected during baseflow conditions in the previous phases of this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141215","collaboration":"North Carolina Department of Environment and Natural Resources, Division of Environmental Health; Durham County Health Department; City of Durham Stormwater Department; City of Raleigh, North Carolina","usgsCitation":"Ferrell, G.M., Yearout, M.S., Grimes, B.H., Graves, A.K., Fitzgerald, S., and Meyer, M.T., 2014, Water-quality characteristics indicative of wastewater in selected streams in the upper Neuse River Basin, Durham and Orange Counties, North Carolina, from 2004 to 2013: U.S. Geological Survey Open-File Report 2014-1215, Report: xi, 62 p.; 10 Appendixes; 2 Tables, https://doi.org/10.3133/ofr20141215.","productDescription":"Report: xi, 62 p.; 10 Appendixes; 2 Tables","numberOfPages":"77","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2004-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-052107","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":295840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141215.jpg"},{"id":295770,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1215/"},{"id":295825,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1215/pdf/ofr2014-1215.pdf"},{"id":295838,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1215/appendix/"},{"id":295839,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1215/table"}],"country":"United States","state":"North Carolina","county":"Durham County, Orange County","otherGeospatial":"Upper Neuse River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.4036865234375,\n 35.793310688351724\n ],\n [\n -79.4036865234375,\n 36.22876574685929\n ],\n [\n -78.63327026367188,\n 36.22876574685929\n ],\n [\n -78.63327026367188,\n 35.793310688351724\n ],\n [\n -79.4036865234375,\n 35.793310688351724\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459eaa4e4b009f8aec97030","contributors":{"authors":[{"text":"Ferrell, Gloria M. gferrell@usgs.gov","contributorId":1595,"corporation":false,"usgs":true,"family":"Ferrell","given":"Gloria","email":"gferrell@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":521319,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yearout, Matthew S.","contributorId":124564,"corporation":false,"usgs":false,"family":"Yearout","given":"Matthew","email":"","middleInitial":"S.","affiliations":[{"id":5039,"text":"Department of Environment, Land, and Infrastructure Engineering, Politecnico di Torino, Torino, Italy","active":true,"usgs":false}],"preferred":false,"id":521320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grimes, Barbara H.","contributorId":124565,"corporation":false,"usgs":false,"family":"Grimes","given":"Barbara","email":"","middleInitial":"H.","affiliations":[{"id":5039,"text":"Department of Environment, Land, and Infrastructure Engineering, Politecnico di Torino, Torino, Italy","active":true,"usgs":false}],"preferred":false,"id":521321,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graves, Alexandria K.","contributorId":124566,"corporation":false,"usgs":false,"family":"Graves","given":"Alexandria","email":"","middleInitial":"K.","affiliations":[{"id":5039,"text":"Department of Environment, Land, and Infrastructure Engineering, Politecnico di Torino, Torino, Italy","active":true,"usgs":false}],"preferred":false,"id":521322,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fitzgerald, Sharon A. safitzge@usgs.gov","contributorId":4532,"corporation":false,"usgs":true,"family":"Fitzgerald","given":"Sharon A.","email":"safitzge@usgs.gov","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":521318,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meyer, Michael T. 0000-0001-6006-7985 mmeyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6006-7985","contributorId":866,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael","email":"mmeyer@usgs.gov","middleInitial":"T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":521323,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70127487,"text":"ofr20141206 - 2014 - Low-head hydropower assessment of the Brazilian State of São Paulo","interactions":[],"lastModifiedDate":"2017-01-18T11:27:29","indexId":"ofr20141206","displayToPublicDate":"2014-11-04T09:30:00","publicationYear":"2014","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":"2014-1206","title":"Low-head hydropower assessment of the Brazilian State of São Paulo","docAbstract":"This study produced a comprehensive estimate of the magnitude of hydropower potential available in the streams that drain watersheds entirely within the State of São Paulo, Brazil. Because a large part of the contributing area is outside of São Paulo, the main stem of the Paraná River was excluded from the assessment. Potential head drops were calculated from the Digital Terrain Elevation Data,which has a 1-arc-second resolution (approximately 30-meter resolution at the equator). For the conditioning and validation of synthetic stream channels derived from the Digital Elevation Model datasets, hydrography data (in digital format) supplied by the São Paulo State Department of Energy and the Agência Nacional de Águas were used. Within the study area there were 1,424 rain gages and 123 streamgages with long-term data records. To estimate average yearly streamflow, a hydrologic regionalization system that divides the State into 21 homogeneous basins was used. Stream segments, upstream areas, and mean annual rainfall were estimated using geographic information systems techniques. The accuracy of the flows estimated with the regionalization models was validated. Overall, simulated streamflows were significantly correlated with the observed flows but with a consistent underestimation bias. When the annual mean flows from the regionalization models were adjusted upward by 10 percent, average streamflow estimation bias was reduced from -13 percent to -4 percent. The sum of all the validated stream reach mean annual hydropower potentials in the 21 basins is 7,000 megawatts (MW). Hydropower potential is mainly concentrated near the Serra do Mar mountain range and along the Tietê River. The power potential along the Tietê River is mainly at sites with medium and high potentials, sites where hydropower has already been harnessed. In addition to the annual mean hydropower estimates, potential hydropower estimates with flow rates with exceedance probabilities of 40 percent, 60 percent, and 90 percent were made.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141206","usgsCitation":"Artan, G.A., Cushing, W.M., Mathis, M.L., and Tieszen, L.L., 2014, Low-head hydropower assessment of the Brazilian State of São Paulo: U.S. Geological Survey Open-File Report 2014-1206, v, 15 p., https://doi.org/10.3133/ofr20141206.","productDescription":"v, 15 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051675","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":295835,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141206.jpg"},{"id":295834,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1206/pdf/ofr2014-1206.pdf","text":"Report","size":"11.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":295766,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1206/"}],"country":"Brazil","city":"São Paulo","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5459eaa2e4b009f8aec96ffe","contributors":{"authors":[{"text":"Artan, Guleid A. 0000-0001-8409-6182 gartan@usgs.gov","orcid":"https://orcid.org/0000-0001-8409-6182","contributorId":2938,"corporation":false,"usgs":true,"family":"Artan","given":"Guleid","email":"gartan@usgs.gov","middleInitial":"A.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":521219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cushing, W. Matthew 0000-0001-5209-6006 mcushing@usgs.gov","orcid":"https://orcid.org/0000-0001-5209-6006","contributorId":2980,"corporation":false,"usgs":true,"family":"Cushing","given":"W.","email":"mcushing@usgs.gov","middleInitial":"Matthew","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":521220,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mathis, Melissa L. 0000-0003-4967-4770 mlmathis@usgs.gov","orcid":"https://orcid.org/0000-0003-4967-4770","contributorId":5461,"corporation":false,"usgs":true,"family":"Mathis","given":"Melissa","email":"mlmathis@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":521221,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tieszen, Larry L. tieszen@usgs.gov","contributorId":2831,"corporation":false,"usgs":true,"family":"Tieszen","given":"Larry","email":"tieszen@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":521222,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}